diff --git a/.circleci/config.yml b/.circleci/config.yml
index 55fa9410845..dfc539fb80e 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -112,10 +112,10 @@ commands:
             node --version
             npm --version
   install_rust:
-    description: "Install pinned rustup (1.28.2) and Rust toolchain (1.97.1) with checksum verification. Adds ~/.cargo/bin to PATH. Run this before any `uv sync` or `uv build` of the workspace: the root package builds litellm-rust through maturin, and on an image without cargo maturin fetches an unpinned rustup and a floating toolchain by itself."
+    description: "Install pinned rustup (1.28.2) and Rust toolchain (1.98.0) with checksum verification. Adds ~/.cargo/bin to PATH. Run this before any `uv sync` or `uv build` of the workspace: the root package builds litellm-rust through maturin, and on an image without cargo maturin fetches an unpinned rustup and a floating toolchain by itself."
     steps:
       - run:
-          name: Install Rust (rustup 1.28.2, toolchain 1.97.1)
+          name: Install Rust (rustup 1.28.2, toolchain 1.98.0)
           command: |
             case "$(uname -m)" in
               x86_64)
@@ -135,7 +135,7 @@ commands:
               "https://static.rust-lang.org/rustup/archive/1.28.2/${RUSTUP_TRIPLE}/rustup-init"
             echo "${RUSTUP_SHA256}  /tmp/rustup-init" | sha256sum -c -
             chmod +x /tmp/rustup-init
-            /tmp/rustup-init -y --no-modify-path --profile minimal --default-toolchain 1.97.1
+            /tmp/rustup-init -y --no-modify-path --profile minimal --default-toolchain 1.98.0
             rm -f /tmp/rustup-init
             echo 'export PATH="$HOME/.cargo/bin:$PATH"' >> "$BASH_ENV"
             export PATH="$HOME/.cargo/bin:$PATH"
@@ -300,7 +300,7 @@ jobs:
             if ($rustupActual -ne $rustupExpected) {
               throw "rustup installer hash mismatch: expected $rustupExpected got $rustupActual"
             }
-            & $rustupInit -y --profile minimal --default-toolchain stable
+            & $rustupInit -y --profile minimal --default-toolchain 1.98.0
             if ($LASTEXITCODE -ne 0) {
               exit $LASTEXITCODE
             }
diff --git a/.github/actions/cache-cargo-build/action.yml b/.github/actions/cache-cargo-build/action.yml
index 36c6c790b84..c3b8ce22c68 100644
--- a/.github/actions/cache-cargo-build/action.yml
+++ b/.github/actions/cache-cargo-build/action.yml
@@ -4,17 +4,16 @@ description: >-
   so only the first job on a given Cargo.lock compiles the bridge from scratch.
 
   litellm builds through maturin, which compiles litellm-rust/crates/python-bridge
-  in release mode before it can produce a wheel. `uv sync` therefore pays a full
-  build in every job that installs the workspace: measured at 2m40s per unit shard
-  on 2026-08-21, more than the whole unit tier spends running tests. Nothing caught
-  it, because the uv cache holds wheels uv downloads rather than wheels it builds,
-  and a path dependency whose source moves every commit could never hit that cache
-  anyway. Cargo rebuilds only what changed when its target directory survives, so a
-  warm job pays for the bridge crate alone.
+  in the dev profile for editable installs. `uv sync` therefore pays a full build
+  in every job that installs the workspace. Nothing caught it, because the uv cache
+  holds wheels uv downloads rather than wheels it builds, and a path dependency
+  whose source moves every commit could never hit that cache anyway. Cargo rebuilds
+  only what changed when its target directory survives, so a warm job pays for the
+  bridge crate alone.
 
-  The key namespace is separate from test-rust.yml's. Both cache the same directory,
-  but that workflow fills it with debug and clippy artifacts, which a release build
-  cannot reuse, and a shared key would let whichever ran first deny the other a save.
+  The key namespace is separate from test-rust.yml's check and release caches. They
+  cache the same directory for different workloads, and a shared key would let
+  whichever ran first deny the others a save.
 
 runs:
   using: composite
@@ -26,6 +25,6 @@ runs:
           ~/.cargo/registry
           ~/.cargo/git
           litellm-rust/target
-        key: ${{ runner.os }}-cargo-release-${{ hashFiles('litellm-rust/Cargo.lock') }}
+        key: ${{ runner.os }}-maturin-dev-${{ hashFiles('litellm-rust/Cargo.lock') }}
         restore-keys: |
-          ${{ runner.os }}-cargo-release-
+          ${{ runner.os }}-maturin-dev-
diff --git a/.github/scripts/close_duplicate_issues.py b/.github/scripts/close_duplicate_issues.py
deleted file mode 100755
index ec522af4f88..00000000000
--- a/.github/scripts/close_duplicate_issues.py
+++ /dev/null
@@ -1,230 +0,0 @@
-#!/usr/bin/env python3
-"""
-Detect and close duplicate GitHub issues using title similarity.
-
-Modes:
-  --scan           Compare all open issues against each other (batch)
-  --issue-number N Check a single issue against older open issues
-
-Requires the `gh` CLI to be authenticated.
-"""
-
-import argparse
-import difflib
-import json
-import re
-import subprocess
-import sys
-
-
-def normalize_title(title: str) -> str:
-    """Strip common prefixes, lowercase, and collapse whitespace."""
-    title = re.sub(
-        r"^\[?(bug|feature request|enhancement|question|docs)[:\]]?\s*",
-        "",
-        title,
-        flags=re.IGNORECASE,
-    )
-    return " ".join(title.lower().split())
-
-
-def gh(*args: str) -> str:
-    """Run a gh CLI command and return stdout."""
-    result = subprocess.run(
-        ["gh", *args],
-        capture_output=True,
-        text=True,
-        check=True,
-    )
-    return result.stdout
-
-
-def fetch_open_issues(repo: str | None) -> list[dict]:
-    """Fetch all open issues (excluding PRs) via gh api --paginate."""
-    if repo:
-        endpoint = (
-            f"repos/{repo}/issues?state=open&per_page=100&sort=created&direction=asc"
-        )
-    else:
-        endpoint = "repos/{owner}/{repo}/issues?state=open&per_page=100&sort=created&direction=asc"
-    cmd = ["api", "--paginate", endpoint]
-
-    raw = gh(*cmd)
-    # gh --paginate concatenates JSON arrays, so we may get multiple arrays
-    issues = []
-    for line in raw.strip().splitlines():
-        line = line.strip()
-        if not line:
-            continue
-        parsed = json.loads(line)
-        if isinstance(parsed, list):
-            issues.extend(parsed)
-        else:
-            issues.append(parsed)
-
-    # Filter out pull requests (they also appear in the issues endpoint)
-    return [i for i in issues if "pull_request" not in i]
-
-
-def close_as_duplicate(
-    issue_number: int, duplicate_of: int, repo: str | None, dry_run: bool
-) -> None:
-    """Close an issue as duplicate of another, adding a comment and label."""
-    repo_args = ["--repo", repo] if repo else []
-
-    if dry_run:
-        print(
-            f"  [DRY RUN] Would close #{issue_number} as duplicate of #{duplicate_of}"
-        )
-        return
-
-    # Add comment
-    comment_body = (
-        f"Closing as duplicate of #{duplicate_of}.\n\n"
-        "If you believe this is not a duplicate, please reopen and add context "
-        "explaining how this differs."
-    )
-    gh("issue", "comment", str(issue_number), "--body", comment_body, *repo_args)
-
-    # Add label
-    gh("issue", "edit", str(issue_number), "--add-label", "duplicate", *repo_args)
-
-    # Close with not_planned reason
-    gh(
-        "api",
-        f"repos/{repo or '{owner}/{repo}'}/issues/{issue_number}",
-        "-X",
-        "PATCH",
-        "-f",
-        "state=closed",
-        "-f",
-        "state_reason=not_planned",
-    )
-
-    print(f"  Closed #{issue_number} as duplicate of #{duplicate_of}")
-
-
-def find_duplicate(
-    issue: dict, candidates: list[dict], threshold: float
-) -> dict | None:
-    """Return the first candidate whose normalized title is above threshold."""
-    norm = normalize_title(issue["title"])
-    for candidate in candidates:
-        if candidate["number"] == issue["number"]:
-            continue
-        cand_norm = normalize_title(candidate["title"])
-        ratio = difflib.SequenceMatcher(None, norm, cand_norm).ratio()
-        if ratio >= threshold:
-            return candidate
-    return None
-
-
-def scan_all(
-    issues: list[dict], threshold: float, repo: str | None, dry_run: bool
-) -> int:
-    """Compare every issue against all older issues. Returns count of duplicates found."""
-    # Sort oldest first
-    issues.sort(key=lambda i: i["number"])
-    closed_count = 0
-
-    for idx, issue in enumerate(issues):
-        older = issues[:idx]
-        if not older:
-            continue
-        dup = find_duplicate(issue, older, threshold)
-        if dup:
-            ratio = difflib.SequenceMatcher(
-                None,
-                normalize_title(issue["title"]),
-                normalize_title(dup["title"]),
-            ).ratio()
-            print(
-                f"#{issue['number']}: \"{issue['title']}\"\n"
-                f"  -> duplicate of #{dup['number']}: \"{dup['title']}\" "
-                f"({ratio:.0%} similar)"
-            )
-            close_as_duplicate(issue["number"], dup["number"], repo, dry_run)
-            closed_count += 1
-
-    return closed_count
-
-
-def check_single(
-    issue_number: int,
-    issues: list[dict],
-    threshold: float,
-    repo: str | None,
-    dry_run: bool,
-) -> bool:
-    """Check a single issue against all older open issues. Returns True if duplicate found."""
-    target = None
-    for i in issues:
-        if i["number"] == issue_number:
-            target = i
-            break
-
-    if target is None:
-        print(f"Issue #{issue_number} not found among open issues.")
-        return False
-
-    older = [i for i in issues if i["number"] < issue_number]
-    dup = find_duplicate(target, older, threshold)
-    if dup:
-        ratio = difflib.SequenceMatcher(
-            None,
-            normalize_title(target["title"]),
-            normalize_title(dup["title"]),
-        ).ratio()
-        print(
-            f"#{target['number']}: \"{target['title']}\"\n"
-            f"  -> duplicate of #{dup['number']}: \"{dup['title']}\" "
-            f"({ratio:.0%} similar)"
-        )
-        close_as_duplicate(issue_number, dup["number"], repo, dry_run)
-        return True
-
-    print(f"#{issue_number}: no duplicate found above threshold {threshold}")
-    return False
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser(
-        description="Detect and close duplicate GitHub issues"
-    )
-    mode = parser.add_mutually_exclusive_group(required=True)
-    mode.add_argument("--scan", action="store_true", help="Scan all open issues")
-    mode.add_argument("--issue-number", type=int, help="Check a single issue number")
-    parser.add_argument(
-        "--threshold", type=float, default=0.85, help="Similarity threshold (0-1)"
-    )
-    parser.add_argument(
-        "--close",
-        action="store_true",
-        help="Actually close duplicates (default is dry-run)",
-    )
-    parser.add_argument(
-        "--repo", type=str, help="Repository (owner/repo). Auto-detected if omitted."
-    )
-    args = parser.parse_args()
-
-    dry_run = not args.close
-
-    if dry_run:
-        print("=== DRY RUN MODE (pass --close to actually close issues) ===\n")
-
-    print("Fetching open issues...")
-    issues = fetch_open_issues(args.repo)
-    print(f"Found {len(issues)} open issues.\n")
-
-    if args.scan:
-        count = scan_all(issues, args.threshold, args.repo, dry_run)
-        print(f"\nTotal duplicates {'found' if dry_run else 'closed'}: {count}")
-    else:
-        found = check_single(
-            args.issue_number, issues, args.threshold, args.repo, dry_run
-        )
-        sys.exit(0 if found else 0)  # Always exit 0; finding no dup is not an error
-
-
-if __name__ == "__main__":
-    main()
diff --git a/.github/scripts/smoke_test_native_wheel.py b/.github/scripts/smoke_test_native_wheel.py
new file mode 100644
index 00000000000..577bb32fcf0
--- /dev/null
+++ b/.github/scripts/smoke_test_native_wheel.py
@@ -0,0 +1,68 @@
+from __future__ import annotations
+
+import subprocess
+import sys
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Final
+
+CHILD_SCRIPT: Final = """
+from importlib.util import module_from_spec, spec_from_file_location
+from pathlib import Path
+import sys
+
+native_path = Path(sys.argv[1])
+spec = spec_from_file_location("litellm.rust_bridge._native", native_path)
+if spec is None or spec.loader is None:
+    raise RuntimeError("cannot create native extension import specification")
+module = module_from_spec(spec)
+spec.loader.exec_module(module)
+
+before = module.gil_stats()
+if not isinstance(before.get("releases"), int):
+    raise AssertionError(f"unexpected gil_stats result: {before!r}")
+
+try:
+    module._panic_for_test()
+except BaseException as error:
+    if type(error).__name__ != "PanicException":
+        raise AssertionError(f"expected PanicException, got {type(error).__name__}") from error
+else:
+    raise AssertionError("Rust panic returned without raising")
+
+after = module.gil_stats()
+if not isinstance(after.get("releases"), int):
+    raise AssertionError(f"native module unusable after panic: {after!r}")
+"""
+
+
+def main() -> int:
+    if len(sys.argv) != 2:
+        sys.stderr.write(f"usage: {Path(sys.argv[0]).name} WHEEL\n")
+        return 2
+
+    wheel: Final = Path(sys.argv[1])
+    with tempfile.TemporaryDirectory() as temporary_directory, zipfile.ZipFile(wheel) as archive:
+        native_members: Final = tuple(
+            member
+            for member in archive.infolist()
+            if member.filename.startswith("litellm/rust_bridge/_native.") and member.filename.endswith(".so")
+        )
+        if len(native_members) != 1:
+            sys.stderr.write(f"expected one native extension, found {len(native_members)}\n")
+            return 1
+
+        native_path: Final = Path(temporary_directory) / Path(native_members[0].filename).name
+        native_path.write_bytes(archive.read(native_members[0]))
+        result: Final = subprocess.run((sys.executable, "-c", CHILD_SCRIPT, str(native_path)), check=False)
+
+    if result.returncode != 0:
+        sys.stderr.write(f"native wheel smoke test exited with status {result.returncode}\n")
+        return 1
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/.github/scripts/verify_linux_native_wheel.py b/.github/scripts/verify_linux_native_wheel.py
new file mode 100644
index 00000000000..899e2a211c0
--- /dev/null
+++ b/.github/scripts/verify_linux_native_wheel.py
@@ -0,0 +1,282 @@
+from __future__ import annotations
+
+import importlib.util
+import os
+import re
+import subprocess
+import sys
+import zipfile
+from collections.abc import Callable, Mapping, Sequence
+from itertools import product
+from pathlib import Path, PurePosixPath
+from types import MappingProxyType, ModuleType
+from typing import Final, Protocol
+
+EXPECTED_PYTHON_TAG: Final = "cp310"
+EXPECTED_ABI_TAG: Final = "abi3"
+EXPECTED_PLATFORM_TAG: Final = "linux_x86_64"
+
+
+class CommandRunner(Protocol):
+    def __call__(
+        self,
+        command: tuple[str, ...],
+        *,
+        check: bool,
+        capture_output: bool,
+        text: bool,
+    ) -> subprocess.CompletedProcess[str]: ...
+
+
+def _run_command(
+    command: tuple[str, ...],
+    *,
+    check: bool,
+    capture_output: bool,
+    text: bool,
+) -> subprocess.CompletedProcess[str]:
+    return subprocess.run(command, check=check, capture_output=capture_output, text=text)
+
+
+def _dist_info_directory(member: zipfile.ZipInfo) -> str | None:
+    parts: Final = PurePosixPath(member.filename).parts
+    if not parts or not parts[0].endswith(".dist-info"):
+        return None
+    return parts[0]
+
+
+def _wheel_metadata_tags(archive: zipfile.ZipFile, members: tuple[zipfile.ZipInfo, ...]) -> tuple[str, ...]:
+    if len(members) != 1:
+        return ()
+    lines: Final = archive.read(members[0]).splitlines()
+    return tuple(line.removeprefix(b"Tag:").strip().decode("ascii") for line in lines if line.startswith(b"Tag:"))
+
+
+def _load_native_module(native_path: Path) -> ModuleType | None:
+    module_spec: Final = importlib.util.spec_from_file_location("litellm.rust_bridge._native", native_path)
+    if module_spec is None or module_spec.loader is None:
+        return None
+    try:
+        native_module: Final = importlib.util.module_from_spec(module_spec)
+        module_spec.loader.exec_module(native_module)
+    except Exception as error:  # noqa: BLE001  # native module initialization can raise arbitrary exceptions
+        sys.stderr.write(f"native module load failed: {error}\n")
+        return None
+    return native_module
+
+
+def main(
+    argv: Sequence[str] | None = None,
+    environment: Mapping[str, str] | None = None,
+    load_native_module: Callable[[Path], ModuleType | None] = _load_native_module,
+    run_command: CommandRunner = _run_command,
+) -> int:
+    arguments: Final = tuple(sys.argv if argv is None else argv)
+    resolved_environment: Final = os.environ if environment is None else environment
+    if len(arguments) != 2:
+        sys.stderr.write(f"usage: {Path(arguments[0]).name} WHEEL\n")
+        return 2
+
+    wheel: Final = Path(arguments[1])
+    wheel_tags: Final = wheel.stem.rsplit("-", maxsplit=3)
+    if len(wheel_tags) != 4:
+        sys.stderr.write(f"cannot parse wheel tags from {wheel.name}\n")
+        return 1
+
+    wheel_identity: Final = wheel_tags[0].split("-")
+    if len(wheel_identity) != 2 or wheel_identity[0] != "litellm" or not wheel_identity[1]:
+        sys.stderr.write(f"unexpected wheel identity: {wheel_tags[0]}\n")
+        return 1
+
+    expected_dist_info_directory: Final = f"{wheel_tags[0]}.dist-info"
+    expected_dist_info_directories: Final = frozenset((expected_dist_info_directory,))
+    python_tag: Final = wheel_tags[1]
+    abi_tag: Final = wheel_tags[2]
+    platform_tag: Final = wheel_tags[3]
+    expanded_filename_tags: Final = frozenset(
+        "-".join(tag) for tag in product(python_tag.split("."), abi_tag.split("."), platform_tag.split("."))
+    )
+
+    with zipfile.ZipFile(wheel) as archive:
+        wheel_members: Final = archive.infolist()
+        dist_info_directories: Final = frozenset(
+            directory for member in wheel_members if (directory := _dist_info_directory(member)) is not None
+        )
+        required_dist_info_files: Final = ("METADATA", "RECORD", "WHEEL")
+        dist_info_file_counts: Final = MappingProxyType(
+            {
+                filename: sum(
+                    member.filename == f"{expected_dist_info_directory}/{filename}" for member in wheel_members
+                )
+                for filename in required_dist_info_files
+            }
+        )
+        wheel_metadata_members: Final = tuple(
+            member for member in wheel_members if member.filename == f"{expected_dist_info_directory}/WHEEL"
+        )
+        wheel_metadata_tags: Final = _wheel_metadata_tags(archive, wheel_metadata_members)
+        native_members: Final = tuple(
+            member
+            for member in wheel_members
+            if member.filename.startswith("litellm/rust_bridge/_native.") and member.filename.endswith(".so")
+        )
+        if len(native_members) != 1:
+            sys.stderr.write(f"expected one native extension, found {len(native_members)}\n")
+            return 1
+
+        unexpected_members: Final = tuple(
+            member.filename
+            for member in wheel_members
+            if member.filename.endswith((".pdb", ".dwp", ".rlib", ".rmeta", "Cargo.toml", "Cargo.lock"))
+            or any(part.endswith(".dSYM") for part in PurePosixPath(member.filename).parts)
+        )
+        native_member: Final = native_members[0]
+        uncompressed_wheel_size: Final = sum(member.file_size for member in wheel_members)
+        native_path: Final = wheel.parent / "native" / Path(native_member.filename).name
+        native_path.parent.mkdir(parents=True, exist_ok=True)
+        native_path.write_bytes(archive.read(native_member))
+
+    wheel_metadata_tags_match: Final = (
+        len(wheel_metadata_tags) == len(expanded_filename_tags)
+        and frozenset(wheel_metadata_tags) == expanded_filename_tags
+    )
+    commit_sha: Final = resolved_environment.get(
+        "RELEASE_WHEEL_COMMIT_SHA", resolved_environment.get("GITHUB_SHA", "unknown")
+    )
+    rustc_version: Final = run_command(
+        ("rustc", "--version"),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    pyproject: Final = (Path(__file__).parents[2] / "pyproject.toml").read_text()
+    maturin_match: Final = re.search(r'"maturin==([^";]+)', pyproject)
+    if maturin_match is None:
+        sys.stderr.write("build-system does not pin an exact Maturin version\n")
+        return 1
+
+    maturin_version: Final = maturin_match.group(1)
+    native_percentage: Final = native_member.file_size / uncompressed_wheel_size * 100
+    size_report: Final = "\n".join(
+        (
+            "## Native wheel build report",
+            "",
+            "| Build | Value |",
+            "| --- | --- |",
+            f"| Commit | `{commit_sha}` |",
+            f"| Platform | `{platform_tag}` |",
+            f"| Python ABI | `{python_tag}-{abi_tag}` |",
+            f"| Rust compiler | `{rustc_version}` |",
+            f"| Maturin | `{maturin_version}` |",
+            "| Cargo profile | `release` |",
+            "",
+            "| Artifact | Size |",
+            "| --- | ---: |",
+            f"| Compressed wheel | {wheel.stat().st_size / 1_000_000:.2f} MB |",
+            f"| Uncompressed wheel | {uncompressed_wheel_size / 1_000_000:.2f} MB |",
+            f"| Native extension | {native_member.file_size / 1_000_000:.2f} MB |",
+            f"| Native share | {native_percentage:.2f}% |",
+            "",
+        )
+    )
+    summary_path: Final = resolved_environment.get("GITHUB_STEP_SUMMARY")
+    if summary_path is None:
+        sys.stdout.write(size_report)
+    else:
+        Path(summary_path).write_text(size_report)
+
+    sections: Final = run_command(
+        ("readelf", "--sections", "--wide", str(native_path)),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    debug_sections: Final = tuple(section for section in (".debug_", ".zdebug_") if section in sections)
+    debug_sections_absent: Final = not debug_sections
+    static_symbol_table_absent: Final = ".symtab" not in sections
+
+    dynamic_symbols: Final = run_command(
+        ("readelf", "--dyn-syms", "--wide", str(native_path)),
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    extension_entry_point_present: Final = "PyInit__native" in dynamic_symbols
+    native_module: Final = load_native_module(native_path)
+    native_module_loads: Final = native_module is not None
+    panic_test_hook_absent: Final = native_module is not None and not hasattr(native_module, "_panic_for_test")
+    native_size_limit: Final = 20_000_000
+    native_size_within_limit: Final = native_member.file_size <= native_size_limit
+    validations: Final = (
+        (f"Python tag is {EXPECTED_PYTHON_TAG}", python_tag == EXPECTED_PYTHON_TAG),
+        (f"ABI tag is {EXPECTED_ABI_TAG}", abi_tag == EXPECTED_ABI_TAG),
+        (f"Platform tag is {EXPECTED_PLATFORM_TAG}", platform_tag == EXPECTED_PLATFORM_TAG),
+        ("Wheel dist-info directory matches the filename", dist_info_directories == expected_dist_info_directories),
+        (
+            "Required dist-info files are present exactly once",
+            all(count == 1 for count in dist_info_file_counts.values()),
+        ),
+        ("Wheel metadata tags match the filename", wheel_metadata_tags_match),
+        ("Debug sections are absent", debug_sections_absent),
+        ("Static symbol table is absent", static_symbol_table_absent),
+        ("Python extension entry point is present", extension_entry_point_present),
+        ("Native module loads", native_module_loads),
+        ("Production module omits the panic test hook", panic_test_hook_absent),
+        ("Native extension does not exceed 20 MB", native_size_within_limit),
+        ("Wheel contents are valid", not unexpected_members),
+    )
+
+    verified_report: Final = size_report + "\n".join(
+        ("", "| Validation | Expected | Result |", "| --- | --- | :---: |")
+        + tuple(f"| {label} | Yes | {'O' if passed else 'X'} |" for label, passed in validations)
+        + ("",)
+    )
+    if summary_path is not None:
+        Path(summary_path).write_text(verified_report)
+
+    invalid_dist_info_files: Final = any(count != 1 for count in dist_info_file_counts.values())
+    validation_errors: Final = tuple(
+        message
+        for failed, message in (
+            (bool(debug_sections), f"{native_member.filename} contains debug sections: {', '.join(debug_sections)}"),
+            (not static_symbol_table_absent, f"{native_member.filename} contains a static symbol table"),
+            (not extension_entry_point_present, "native extension does not export PyInit__native"),
+            (
+                python_tag != EXPECTED_PYTHON_TAG,
+                f"unexpected Python tag: expected {EXPECTED_PYTHON_TAG}, found {python_tag}",
+            ),
+            (abi_tag != EXPECTED_ABI_TAG, f"unexpected ABI tag: expected {EXPECTED_ABI_TAG}, found {abi_tag}"),
+            (
+                platform_tag != EXPECTED_PLATFORM_TAG,
+                f"unexpected platform tag: expected {EXPECTED_PLATFORM_TAG}, found {platform_tag}",
+            ),
+            (
+                dist_info_directories != expected_dist_info_directories,
+                f"unexpected dist-info directories: expected {expected_dist_info_directory}, "
+                f"found {', '.join(sorted(dist_info_directories))}",
+            ),
+            (invalid_dist_info_files, f"required dist-info file counts are invalid: {dist_info_file_counts}"),
+            (
+                not invalid_dist_info_files and not wheel_metadata_tags_match,
+                f"WHEEL tags do not match filename: expected {', '.join(sorted(expanded_filename_tags))}, "
+                f"found {', '.join(sorted(wheel_metadata_tags))}",
+            ),
+            (
+                native_module is not None and not panic_test_hook_absent,
+                "production native module exposes _panic_for_test",
+            ),
+            (
+                not native_size_within_limit,
+                f"native extension exceeds 20 MB: {native_member.file_size / 1_000_000:.2f} MB",
+            ),
+            (bool(unexpected_members), f"wheel contains unexpected build artifacts: {', '.join(unexpected_members)}"),
+        )
+        if failed
+    )
+    sys.stderr.write("".join(f"{message}\n" for message in validation_errors))
+
+    return 0 if all(passed for _, passed in validations) else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/.github/workflows/auto-close-duplicates.yml b/.github/workflows/auto-close-duplicates.yml
new file mode 100644
index 00000000000..d8256917805
--- /dev/null
+++ b/.github/workflows/auto-close-duplicates.yml
@@ -0,0 +1,69 @@
+name: Auto-close duplicate issues
+
+on:
+  schedule:
+    - cron: "0 9 * * *"
+  workflow_dispatch:
+    inputs:
+      dry_run:
+        description: Log which issues would close without closing anything
+        type: boolean
+        default: true
+      grace_period_days:
+        description: Days a duplicate notice must go unanswered before the close
+        type: number
+        default: 3
+  pull_request:
+    paths:
+      - .github/workflows/auto-close-duplicates.yml
+      - scripts/auto-close-duplicates.ts
+      - scripts/auto-close-duplicates.test.ts
+
+permissions: {}
+
+jobs:
+  test:
+    if: github.event_name == 'pull_request'
+    runs-on: ubuntu-latest
+    timeout-minutes: 5
+    permissions:
+      contents: read
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@0c5077e51419868618aeaa5fe8019c62421857d6 # v2.2.0
+        with:
+          bun-version: "1.4.0"
+
+      - name: Test the sweep
+        run: bun test scripts/auto-close-duplicates.test.ts
+
+  sweep:
+    if: github.event_name != 'pull_request' && github.repository == 'BerriAI/litellm'
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+    permissions:
+      contents: read
+      issues: write
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@0c5077e51419868618aeaa5fe8019c62421857d6 # v2.2.0
+        with:
+          # Exact version, never latest: the next step holds an issues: write token
+          bun-version: "1.4.0"
+
+      - name: Close unanswered duplicates, reopen ones the reporter answered
+        run: bun run scripts/auto-close-duplicates.ts
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          DRY_RUN: ${{ inputs.dry_run == true }}
+          GRACE_PERIOD_DAYS: ${{ inputs.grace_period_days }}
diff --git a/.github/workflows/check_duplicate_issues.yml b/.github/workflows/check_duplicate_issues.yml
index 78198b2c7bb..41ec43a1d9b 100644
--- a/.github/workflows/check_duplicate_issues.yml
+++ b/.github/workflows/check_duplicate_issues.yml
@@ -1,12 +1,19 @@
 name: Check Duplicate Issues
 
+# Flagging only. "Auto-close duplicate issues" closes a flagged issue 3 days later,
+# and only when its title is identical to an older open issue and nobody replied.
+# The HTML marker below is the handshake between the two, so keep it in the template.
+
 on:
   issues:
     types: [opened, edited]
 
+permissions: {}
+
 jobs:
   check-duplicate:
     runs-on: ubuntu-latest
+    timeout-minutes: 5
     permissions:
       issues: write
       contents: read
@@ -19,35 +26,12 @@ jobs:
           threshold: 0.6
           reaction: eyes
           comment: |
-            **⚠️ Potential duplicate detected**
+            <!-- litellm:potential-duplicate candidates={{#issues}}{{number}},{{/issues}} -->
+            **Potential duplicate detected**
 
-            This issue appears similar to existing issue(s):
+            This looks similar to:
             {{#issues}}
-            - [#{{number}}]({{html_url}}) - {{title}} ({{accuracy}}% similar)
+            - #{{number}} - {{title}}
             {{/issues}}
 
-            Please review the linked issue(s) to see if they address your concern. If this is not a duplicate, please provide additional context to help us understand the difference.
-
-      - name: Checkout close script
-        if: github.event.action == 'opened'
-        uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
-        with:
-          sparse-checkout: .github/scripts
-          persist-credentials: false
-
-      - name: Set up Python
-        if: github.event.action == 'opened'
-        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
-        with:
-          python-version: "3.12"
-
-      - name: Auto-close if high-confidence duplicate
-        if: github.event.action == 'opened'
-        env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          python3 .github/scripts/close_duplicate_issues.py \
-            --issue-number ${{ github.event.issue.number }} \
-            --repo ${{ github.repository }} \
-            --threshold 0.85 \
-            --close
+            If this is a duplicate, add a thumbs-up reaction to the existing issue and follow along there. When the title is identical to an older open issue, this issue closes automatically in 3 days unless someone responds. If it is not a duplicate, comment here or add a thumbs-down reaction to this comment and it stays open.
diff --git a/.github/workflows/image-scan.yml b/.github/workflows/image-scan.yml
index bb04563c1a8..206bb809e0c 100644
--- a/.github/workflows/image-scan.yml
+++ b/.github/workflows/image-scan.yml
@@ -80,7 +80,7 @@ jobs:
           LITELLM_IMAGE: litellm-image-scan:${{ github.sha }}
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py -v
+          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
       # Scans the whole shipped artifact: OS/apk plus every language package
       # baked into the image, including ones no lockfile declares (e.g. prisma's
@@ -124,7 +124,7 @@ jobs:
           LITELLM_IMAGE: litellm-runtime-scan:${{ github.sha }}
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py -v
+          python -m pytest tests/proxy_migration_tests/test_offline_image_migration.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
   migrations-image:
     name: migrations-image
@@ -185,7 +185,7 @@ jobs:
           LITELLM_COMPONENT_PORT: "4000"
         run: |
           python -m pip install "pytest==9.0.3"
-          python -m pytest tests/proxy_migration_tests/test_component_image_serves_offline.py -v
+          python -m pytest tests/proxy_migration_tests/test_component_image_serves_offline.py tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py -v
 
   ui-image:
     name: ui-image
diff --git a/.github/workflows/report-rust-release-wheel.yml b/.github/workflows/report-rust-release-wheel.yml
new file mode 100644
index 00000000000..1d93b56f77f
--- /dev/null
+++ b/.github/workflows/report-rust-release-wheel.yml
@@ -0,0 +1,130 @@
+name: Report LiteLLM Rust release wheel
+
+on: # zizmor: ignore[dangerous-triggers] reporter executes no PR code and consumes no PR artifacts or outputs
+  workflow_run:
+    workflows:
+      - LiteLLM Rust
+    types:
+      - completed
+
+permissions: {}
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.workflow_run.pull_requests[0].number || github.event.workflow_run.id }}
+  cancel-in-progress: false
+
+jobs:
+  report-release-wheel:
+    name: report release wheel
+    if: >-
+      github.event.workflow_run.event == 'pull_request' &&
+      github.event.workflow_run.path == '.github/workflows/test-rust.yml' &&
+      github.event.workflow_run.head_repository.full_name == github.repository &&
+      github.event.workflow_run.pull_requests[0].number != null
+    runs-on: ubuntu-latest
+    timeout-minutes: 5
+    permissions:
+      issues: write # PR comments use the issues API
+      pull-requests: read # Current-head validation rejects stale workflow runs
+
+    steps:
+      - name: Link release wheel report on PR
+        uses: actions/github-script@f28e40c7f34bde8b3046d885e986cb6290c5673b # v7.1.0
+        env:
+          COMMENT_MARKER: "<!-- litellm-release-wheel-size -->"
+        with:
+          script: |
+            const marker = process.env.COMMENT_MARKER;
+            const workflowRun = context.payload.workflow_run;
+            const allowedConclusions = new Set([
+              "action_required",
+              "cancelled",
+              "failure",
+              "neutral",
+              "skipped",
+              "stale",
+              "startup_failure",
+              "success",
+              "timed_out",
+            ]);
+            if (
+              !allowedConclusions.has(workflowRun.conclusion) ||
+              workflowRun.event !== "pull_request" ||
+              workflowRun.path !== ".github/workflows/test-rust.yml" ||
+              workflowRun.head_repository?.full_name !==
+                `${context.repo.owner}/${context.repo.repo}` ||
+              workflowRun.pull_requests?.length !== 1
+            ) {
+              throw new Error("unexpected source workflow");
+            }
+            const pullRequest = workflowRun.pull_requests[0];
+            const pullRequestNumber = pullRequest.number;
+            const headSha = workflowRun.head_sha;
+            const runId = workflowRun.id;
+            if (
+              !Number.isSafeInteger(pullRequestNumber) ||
+              pullRequestNumber <= 0 ||
+              !Number.isSafeInteger(runId) ||
+              runId <= 0 ||
+              !/^[0-9a-f]{40}$/.test(headSha) ||
+              pullRequest.head?.sha !== headSha
+            ) {
+              throw new Error("invalid source workflow metadata");
+            }
+            const runUrl =
+              `${context.serverUrl}/${context.repo.owner}/${context.repo.repo}` +
+              `/actions/runs/${runId}`;
+            const result =
+              workflowRun.conclusion === "success"
+                ? "successfully"
+                : `with \`${workflowRun.conclusion}\``;
+            const body = [
+              marker,
+              "## LiteLLM Rust workflow",
+              "",
+              `Workflow completed ${result} for \`${headSha}\``,
+              "",
+              `[View workflow run](${runUrl})`,
+            ].join("\n");
+            const comments = await github.paginate(github.rest.issues.listComments, {
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              issue_number: pullRequestNumber,
+              per_page: 100,
+            });
+            const existing = comments.find(
+              (comment) =>
+                comment.user?.login === "github-actions[bot]" &&
+                comment.body?.startsWith(marker),
+            );
+            const currentPullRequest = (
+              await github.rest.pulls.get({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                pull_number: pullRequestNumber,
+              })
+            ).data;
+            if (
+              currentPullRequest.state !== "open" ||
+              currentPullRequest.head.repo?.full_name !==
+                `${context.repo.owner}/${context.repo.repo}` ||
+              currentPullRequest.head.sha !== headSha
+            ) {
+              core.info("source workflow no longer matches the current pull request head");
+              return;
+            }
+            if (existing) {
+              await github.rest.issues.updateComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                comment_id: existing.id,
+                body,
+              });
+            } else {
+              await github.rest.issues.createComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                issue_number: pullRequestNumber,
+                body,
+              });
+            }
diff --git a/.github/workflows/test-redis-compat.yml b/.github/workflows/test-redis-compat.yml
new file mode 100644
index 00000000000..f29755a74b1
--- /dev/null
+++ b/.github/workflows/test-redis-compat.yml
@@ -0,0 +1,77 @@
+name: "Unit Tests: Redis Client Version Compatibility"
+
+on:
+  pull_request:
+    branches:
+      - main
+      - litellm_internal_staging
+      - litellm_oss_staging
+      - "litellm_**"
+    paths:
+      - "litellm/_redis.py"
+      - "litellm/_redis_credential_provider.py"
+      - "tests/test_litellm/test_redis.py"
+      - "tests/test_litellm/caching/test_redis_connection_pool.py"
+      - ".github/workflows/test-redis-compat.yml"
+      - "pyproject.toml"
+      - "uv.lock"
+
+permissions:
+  contents: read
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  redis-compat:
+    name: "redis-py ${{ matrix.redis-version }}"
+    runs-on: ubuntu-latest
+    timeout-minutes: 15
+
+    strategy:
+      fail-fast: false
+      matrix:
+        # 5.3.1 is the version pinned in uv.lock (redisvl caps it below 6); the
+        # newer legs prove the inspect.signature introspection in litellm/_redis.py
+        # keeps extracting kwargs on the redis-py releases people actually run now.
+        # Only the exact release 6.0.0 is skipped: rq (pulled by the proxy extra)
+        # specifies `redis != 6`, which excludes 6.0.0 alone, so 6.4.0 stands in
+        # for the 6.x line.
+        redis-version: ["5.3.1", "6.4.0", "7.4.1", "8.0.1"]
+
+    steps:
+      - uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Set up Python
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Set up uv
+        uses: ./.github/actions/setup-uv-with-retries
+        with:
+          version: "0.10.9"
+
+      - name: Install dependencies
+        run: |
+          .github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router
+
+      - name: Pin redis-py to the matrix version
+        env:
+          REDIS_VERSION: ${{ matrix.redis-version }}
+        run: |
+          uv pip install "redis==${REDIS_VERSION:?}"
+          uv run --no-sync python -c "import redis; assert redis.__version__ == '${REDIS_VERSION:?}', redis.__version__; print('redis-py', redis.__version__)"
+
+      - name: Run redis unit tests
+        run: |
+          uv run --no-sync pytest \
+            tests/test_litellm/test_redis.py \
+            tests/test_litellm/caching/test_redis_connection_pool.py \
+            --tb=short -vv \
+            --reruns 2 \
+            --reruns-delay 1 \
+            --durations=20
diff --git a/.github/workflows/test-rust.yml b/.github/workflows/test-rust.yml
index 21e1bcb90c6..1b71232bc2e 100644
--- a/.github/workflows/test-rust.yml
+++ b/.github/workflows/test-rust.yml
@@ -4,6 +4,12 @@ on:
   push:
     paths:
       - "litellm-rust/**"
+      - ".cargo/**"
+      - "pyproject.toml"
+      - "rust-toolchain.toml"
+      - ".github/scripts/smoke_test_native_wheel.py"
+      - ".github/scripts/verify_linux_native_wheel.py"
+      - "tests/test_litellm/rust_bridge/native_route_wheel_test.py"
       - ".github/workflows/test-rust.yml"
   pull_request:
     branches:
@@ -13,6 +19,12 @@ on:
       - "litellm_**"
     paths:
       - "litellm-rust/**"
+      - ".cargo/**"
+      - "pyproject.toml"
+      - "rust-toolchain.toml"
+      - ".github/scripts/smoke_test_native_wheel.py"
+      - ".github/scripts/verify_linux_native_wheel.py"
+      - "tests/test_litellm/rust_bridge/native_route_wheel_test.py"
       - ".github/workflows/test-rust.yml"
 
 permissions:
@@ -40,9 +52,7 @@ jobs:
           persist-credentials: false
 
       - name: Set up Rust
-        run: |
-          rustup toolchain install stable --profile minimal --component clippy,rustfmt
-          rustup default stable
+        run: rustup toolchain install
 
       - name: Cache Cargo registry and target
         uses: actions/cache@0057852bfaa89a56745cba8c7296529d2fc39830 # v4.3.0
@@ -51,7 +61,7 @@ jobs:
             ~/.cargo/registry
             ~/.cargo/git
             litellm-rust/target
-          key: ${{ runner.os }}-cargo-${{ hashFiles('litellm-rust/Cargo.lock') }}
+          key: ${{ runner.os }}-cargo-${{ hashFiles('rust-toolchain.toml', 'litellm-rust/Cargo.lock') }}
           restore-keys: |
             ${{ runner.os }}-cargo-
 
@@ -69,3 +79,50 @@ jobs:
 
       - name: Run core tests with Bedrock auth
         run: cargo test -p litellm-core --features bedrock-auth --locked
+
+  release-wheel:
+    name: release wheel
+    runs-on: ubuntu-latest
+    timeout-minutes: 20
+    permissions:
+      contents: read
+    env:
+      CARGO_TERM_COLOR: always
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0
+        with:
+          persist-credentials: false
+
+      - name: Set up Python
+        uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
+        with:
+          python-version: "3.12"
+
+      - name: Set up uv
+        uses: ./.github/actions/setup-uv-with-retries
+        with:
+          version: "0.10.9"
+
+      - name: Set up Rust
+        run: rustup toolchain install
+
+      - name: Build release wheel
+        run: uv build --wheel --out-dir dist
+
+      - name: Build panic contract wheel
+        run: >-
+          uv build --wheel --out-dir panic-dist
+          --config-setting "maturin.build-args=--features panic-test,extension-module"
+
+      - name: Smoke-test native panic unwinding
+        run: python .github/scripts/smoke_test_native_wheel.py panic-dist/*.whl
+
+      - name: Verify stripped native extension
+        env:
+          RELEASE_WHEEL_COMMIT_SHA: ${{ github.event.pull_request.head.sha || github.sha }}
+        run: python .github/scripts/verify_linux_native_wheel.py dist/*.whl
+
+      - name: Test native route wheel
+        run: python tests/test_litellm/rust_bridge/native_route_wheel_test.py dist/*.whl
diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml
index ed9d8800202..6da5fc07e80 100644
--- a/.github/workflows/test-unit.yml
+++ b/.github/workflows/test-unit.yml
@@ -96,6 +96,7 @@ jobs:
           - shard: misc
             artifact-name: misc
             test-path: >-
+              tests/sdk_function_trace
               tests/test_litellm/batches
               tests/test_litellm/secret_managers
               tests/test_litellm/a2a_protocol
@@ -103,6 +104,7 @@ jobs:
               tests/test_litellm/completion_extras
               tests/test_litellm/compression
               tests/test_litellm/containers
+              tests/test_litellm/endpoints
               tests/test_litellm/experimental_mcp_client
               tests/test_litellm/models
               tests/test_litellm/repositories
diff --git a/CLAUDE.md b/CLAUDE.md
index 930825aeb89..d9e9e8f1586 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -23,6 +23,8 @@ When adding new features, add meaningful tests. Don't add tests that don't check
 
 Same thing for bug fixes. The tests should make it so that this specific bug can never happen again without failing tests (i.e., regression)
 
+Never test structure of code only function of it
+
 `tests/test_litellm/` mirrors `litellm/` in a parallel path (see `tests/test_litellm/readme.md`). Name tests `test_<filename>.py`, but always match the existing test file in the directory you touch — many provider dirs use longer descriptive names (e.g. `test_anthropic_chat_transformation.py`) to avoid ambiguity across sibling folders. For bug fixes, extend the existing mapped test file rather than creating a new one. Only create a new test file for a new feature (provider, endpoint, or transformation module) that has no mapped test yet, following that directory's naming convention (or `test_<filename>.py` if you're the first test there). One focused regression test beats many shallow ones
 
 End-to-end tests belong in `tests/e2e/` and must follow the harness conventions documented in that directory's `CLAUDE.md`
diff --git a/Dockerfile b/Dockerfile
index 700b0d6525e..0a92aa9a68c 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,10 +1,10 @@
 # syntax=docker/dockerfile:1.7
 
 # Base image for building
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 
 # Runtime image
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 # Pinned by digest like the other base images; bump explicitly on Node upgrades.
 ARG UI_BUILD_IMAGE=node:24.19-alpine3.24@sha256:d32cdf619f63fe0471182d08996dd516c6275bb5fd31ae06e55a570bd9e1ad43
@@ -40,8 +40,8 @@ COPY --from=uvbin /uvx /usr/local/bin/uvx
 RUN apk add --no-cache \
     bash \
     gcc \
-    python3 \
-    python3-dev \
+    python-3.13 \
+    python-3.13-dev \
     rust \
     openssl \
     openssl-dev \
@@ -51,6 +51,7 @@ RUN apk add --no-cache \
 
 ENV UV_PROJECT_ENVIRONMENT=/app/.venv \
     UV_LINK_MODE=copy \
+    UV_PYTHON_DOWNLOADS=0 \
     PATH="/app/.venv/bin:${PATH}"
 
 # Copy dependency metadata first for layer caching
@@ -65,7 +66,8 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
-    --python python3
+    --extra bedrock-realtime \
+    --python python3.13
 
 # Copy full source tree
 COPY . .
@@ -86,7 +88,8 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
-    --python python3
+    --extra bedrock-realtime \
+    --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
     npm_config_cache=/root/.npm \
@@ -100,8 +103,14 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime
 
 USER root
 
+# The base image only configures Chainguard's authenticated apk repo, which
+# requires an enterprise subscription. Add the public Wolfi repo so `apk add`
+# also works for anyone installing extra packages into a running container.
+# https://github.com/BerriAI/litellm/issues/33518
+RUN echo "https://packages.wolfi.dev/os" >> /etc/apk/repositories
+
 # node (without npm) is required by the prisma CLI at runtime
-RUN apk add --no-cache bash openssl tzdata nodejs python3 libsndfile
+RUN apk add --no-cache bash openssl tzdata nodejs python-3.13 libsndfile
 
 WORKDIR /app
 ENV PATH="/app/.venv/bin:${PATH}" \
diff --git a/README.md b/README.md
index 68aaa09ec98..92757fcbbc1 100644
--- a/README.md
+++ b/README.md
@@ -354,6 +354,8 @@ curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
 | [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Pinstripes (`pinstripes`)](https://docs.litellm.ai/docs/providers/pinstripes) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Predibase (`predibase`)](https://docs.litellm.ai/docs/providers/predibase) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Qwen AI Platform (`qwen_ai_platform`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  | ✅ |
+| [QwenCloud (`qwencloud`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  | ✅ |
 | [Recraft (`recraft`)](https://docs.litellm.ai/docs/providers/recraft) |  |  |  |  | ✅ |  |  |  |  |  |
 | [Replicate (`replicate`)](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Sagemaker Chat (`sagemaker_chat`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
diff --git a/backend/Dockerfile b/backend/Dockerfile
index 4ca40944606..622fedcd70d 100644
--- a/backend/Dockerfile
+++ b/backend/Dockerfile
@@ -1,5 +1,5 @@
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 
 FROM $UV_IMAGE AS uvbin
@@ -16,7 +16,7 @@ COPY --from=uvbin /uv /uvx /usr/local/bin/
 # instead of nodeenv downloading one whose dynamic deps may not be in Wolfi
 # (e.g. Node 26.2.0 needs libatomic). Retry for transient apk.cgr.dev flakes.
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash gcc python3 python3-dev openssl openssl-dev libsndfile nodejs npm && break; \
+      apk add --no-cache bash gcc python-3.13 python-3.13-dev openssl openssl-dev libsndfile nodejs npm && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
@@ -46,7 +46,8 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra proxy-runtime \
         --extra extra_proxy \
         --extra semantic-router \
-        --python python3
+        --extra saml \
+        --python python3.13
 
 # Stage 2 — copy source and install the project + workspace members.
 COPY . .
@@ -57,7 +58,8 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra proxy-runtime \
         --extra extra_proxy \
         --extra semantic-router \
-        --python python3
+        --extra saml \
+        --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
     npm_config_cache=/root/.npm \
@@ -71,7 +73,7 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime
 USER root
 
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash openssl tzdata python3 libsndfile libatomic && break; \
+      apk add --no-cache bash openssl tzdata python-3.13 libsndfile libatomic && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index 83969d8dedf..aa2cb96a9f7 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -1,9 +1,9 @@
 {
   "reportAny": {
-    "limit": 17270
+    "limit": 14074
   },
   "reportArgumentType": {
-    "limit": 2538
+    "limit": 2215
   },
   "reportAssignmentType": {
     "limit": 319
@@ -18,13 +18,13 @@
     "limit": 40
   },
   "reportDeprecated": {
-    "limit": 212
+    "limit": 211
   },
   "reportDuplicateImport": {
     "limit": 19
   },
   "reportExplicitAny": {
-    "limit": 5485
+    "limit": 4125
   },
   "reportFunctionMemberAccess": {
     "limit": 7
@@ -42,7 +42,7 @@
     "limit": 12
   },
   "reportIndexIssue": {
-    "limit": 35
+    "limit": 25
   },
   "reportInvalidTypeForm": {
     "limit": 34
@@ -54,10 +54,10 @@
     "limit": 0
   },
   "reportMissingParameterType": {
-    "limit": 5658
+    "limit": 5601
   },
   "reportMissingTypeArgument": {
-    "limit": 15425
+    "limit": 15290
   },
   "reportMissingTypeStubs": {
     "limit": 40
@@ -72,7 +72,7 @@
     "limit": 0
   },
   "reportOptionalMemberAccess": {
-    "limit": 1055
+    "limit": 0
   },
   "reportOptionalOperand": {
     "limit": 0
@@ -90,40 +90,40 @@
     "limit": 8
   },
   "reportReturnType": {
-    "limit": 213
+    "limit": 181
   },
   "reportTypedDictNotRequiredAccess": {
-    "limit": 25
+    "limit": 24
   },
   "reportUndefinedVariable": {
     "limit": 0
   },
   "reportUnknownArgumentType": {
-    "limit": 44526
+    "limit": 44364
   },
   "reportUnknownLambdaType": {
     "limit": 109
   },
   "reportUnknownMemberType": {
-    "limit": 38721
+    "limit": 38332
   },
   "reportUnknownParameterType": {
-    "limit": 19778
+    "limit": 19625
   },
   "reportUnknownVariableType": {
-    "limit": 30290
+    "limit": 29861
   },
   "reportUnnecessaryCast": {
-    "limit": 117
+    "limit": 111
   },
   "reportUnnecessaryComparison": {
-    "limit": 697
+    "limit": 692
   },
   "reportUnnecessaryContains": {
     "limit": 5
   },
   "reportUnnecessaryIsInstance": {
-    "limit": 829
+    "limit": 826
   },
   "reportUntypedBaseClass": {
     "limit": 0
@@ -138,9 +138,9 @@
     "limit": 138
   },
   "reportUnusedImport": {
-    "limit": 543
+    "limit": 542
   },
   "reportUnusedVariable": {
-    "limit": 139
+    "limit": 137
   }
 }
diff --git a/docker/Dockerfile.database b/docker/Dockerfile.database
index f0d6d02fccf..e9ad2849bb2 100644
--- a/docker/Dockerfile.database
+++ b/docker/Dockerfile.database
@@ -1,10 +1,10 @@
 # syntax=docker/dockerfile:1.7
 
 # Base image for building
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 
 # Runtime image
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 # Pinned by digest like the other base images; bump explicitly on Node upgrades.
 ARG UI_BUILD_IMAGE=node:24.19-alpine3.24@sha256:d32cdf619f63fe0471182d08996dd516c6275bb5fd31ae06e55a570bd9e1ad43
@@ -39,8 +39,8 @@ COPY --from=uvbin /uvx /usr/local/bin/uvx
 RUN apk add --no-cache \
     bash \
     gcc \
-    python3 \
-    python3-dev \
+    python-3.13 \
+    python-3.13-dev \
     openssl \
     openssl-dev \
     nodejs \
@@ -49,6 +49,7 @@ RUN apk add --no-cache \
 
 ENV UV_PROJECT_ENVIRONMENT=/app/.venv \
     UV_LINK_MODE=copy \
+    UV_PYTHON_DOWNLOADS=0 \
     PATH="/app/.venv/bin:${PATH}"
 
 # Copy dependency metadata first for layer caching
@@ -63,7 +64,8 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
-    --python python3
+    --extra bedrock-realtime \
+    --python python3.13
 
 # Copy full source tree
 COPY . .
@@ -84,7 +86,8 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
-    --python python3
+    --extra bedrock-realtime \
+    --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
     npm_config_cache=/root/.npm \
@@ -98,7 +101,7 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime
 USER root
 
 # node (without npm) is required by the prisma CLI at runtime
-RUN apk add --no-cache bash openssl tzdata nodejs python3 libsndfile
+RUN apk add --no-cache bash openssl tzdata nodejs python-3.13 libsndfile
 
 WORKDIR /app
 ENV PATH="/app/.venv/bin:${PATH}" \
diff --git a/docker/Dockerfile.non_root b/docker/Dockerfile.non_root
index 4a5df6ecd69..edf20e8bbff 100644
--- a/docker/Dockerfile.non_root
+++ b/docker/Dockerfile.non_root
@@ -1,8 +1,8 @@
 # syntax=docker/dockerfile:1.7
 
 # Base images
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG PROXY_EXTRAS_SOURCE=published
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 # Pinned by digest like the other base images; bump explicitly on Node upgrades.
@@ -37,8 +37,8 @@ COPY --from=uvbin /uvx /usr/local/bin/uvx
 
 RUN for i in 1 2 3; do \
       apk add --no-cache \
-        python3 \
-        python3-dev \
+        python-3.13 \
+        python-3.13-dev \
         gcc \
         rust \
         bash \
@@ -52,6 +52,7 @@ RUN for i in 1 2 3; do \
 
 ENV UV_PROJECT_ENVIRONMENT=/app/.venv \
     UV_LINK_MODE=copy \
+    UV_PYTHON_DOWNLOADS=0 \
     PATH="/app/.venv/bin:${PATH}" \
     LITELLM_NON_ROOT=true \
     XDG_CACHE_HOME=/app/.cache
@@ -69,7 +70,8 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
-    --python python3
+    --extra bedrock-realtime \
+    --python python3.13
 
 # Copy full source tree
 COPY . .
@@ -96,7 +98,8 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
-        --python python3 \
+        --extra bedrock-realtime \
+        --python python3.13 \
         --no-sources-package litellm-proxy-extras; \
     else \
       uv sync --frozen --no-default-groups --no-editable \
@@ -105,7 +108,8 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
-        --python python3; \
+        --extra bedrock-realtime \
+        --python python3.13; \
     fi
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
@@ -124,7 +128,7 @@ RUN for i in 1 2 3; do \
       apk upgrade --no-cache && break || sleep 5; \
     done && \
     for i in 1 2 3; do \
-      apk add --no-cache python3 bash openssl tzdata libsndfile nodejs && break || sleep 5; \
+      apk add --no-cache python-3.13 bash openssl tzdata libsndfile nodejs && break || sleep 5; \
     done
 
 # Copy only what runtime needs. The application is installed inside the venv;
diff --git a/enterprise/litellm_enterprise/proxy/audit_logging_endpoints.py b/enterprise/litellm_enterprise/proxy/audit_logging_endpoints.py
index 8f4e999bb9d..b6f8bf2dc5b 100644
--- a/enterprise/litellm_enterprise/proxy/audit_logging_endpoints.py
+++ b/enterprise/litellm_enterprise/proxy/audit_logging_endpoints.py
@@ -7,7 +7,7 @@ GET - /audit/{id} - Get audit log by id
 GET - /audit - Get all audit logs
 """
 
-from typing import TYPE_CHECKING, Final, Optional
+from typing import TYPE_CHECKING, Final
 
 #### AUDIT LOGGING ####
 from fastapi import APIRouter, Depends, HTTPException, Query
@@ -58,33 +58,33 @@ async def get_audit_logs(
     page: int = Query(1, ge=1),
     page_size: int = Query(10, ge=1, le=100),
     # Filter parameters
-    changed_by: Optional[str] = Query(
+    changed_by: str | None = Query(
         None, description="Filter by user or system that performed the action"
     ),
-    changed_by_api_key: Optional[str] = Query(
+    changed_by_api_key: str | None = Query(
         None, description="Filter by API key hash that performed the action"
     ),
-    action: Optional[str] = Query(
+    action: str | None = Query(
         None, description="Filter by action type (create, update, delete)"
     ),
-    table_name: Optional[str] = Query(
+    table_name: str | None = Query(
         None, description="Filter by table name that was modified"
     ),
-    object_id: Optional[str] = Query(
+    object_id: str | None = Query(
         None, description="Filter by ID of the object that was modified"
     ),
-    start_date: Optional[str] = Query(None, description="Filter logs after this date"),
-    end_date: Optional[str] = Query(None, description="Filter logs before this date"),
-    object_team_id: Optional[str] = Query(
+    start_date: str | None = Query(None, description="Filter logs after this date"),
+    end_date: str | None = Query(None, description="Filter logs before this date"),
+    object_team_id: str | None = Query(
         None,
         description="Filter by team_id present in before_value or updated_values JSON (PostgreSQL only)",
     ),
-    object_key_hash: Optional[str] = Query(
+    object_key_hash: str | None = Query(
         None,
         description="Filter by token (key hash) present in before_value or updated_values JSON (PostgreSQL only)",
     ),
     # Sorting parameters
-    sort_by: Optional[str] = Query(
+    sort_by: str | None = Query(
         None,
         description="Column to sort by (e.g. 'updated_at', 'action', 'table_name')",
     ),
diff --git a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
index 3b09dc9272e..354a6ed2fd0 100644
--- a/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
+++ b/enterprise/litellm_enterprise/proxy/common_utils/check_batch_cost.py
@@ -5,7 +5,7 @@ Polls LiteLLM_ManagedObjectTable to check if the batch job is complete, and if t
 from dataclasses import replace as dataclasses_replace
 from datetime import datetime, timedelta, timezone
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Dict, Final, List, Literal, Optional, Tuple, cast
+from typing import TYPE_CHECKING, Final, List, Literal, Optional, Tuple, cast
 
 from litellm._logging import verbose_proxy_logger
 from litellm._uuid import uuid
@@ -87,7 +87,7 @@ class CheckBatchCost:
             return
         self.batch_processed_support_confirmed = True
 
-    async def _get_user_info(self, batch_id: str, user_id: Optional[str]) -> Dict[str, Any]:
+    async def _get_user_info(self, batch_id: str, user_id: Optional[str]) -> dict[str, str | None]:
         """
         Look up user email and key alias by user_id for enriching the S3 callback metadata.
         Returns a dict with user_api_key_user_email and user_api_key_alias (both may be None).
@@ -97,8 +97,10 @@ class CheckBatchCost:
         if not user_id:
             return {}
         try:
-            user_row = await self.prisma_client.db.litellm_usertable.find_unique(
-                where={"user_id": user_id}
+            user_row: prisma_models.LiteLLM_UserTable | None = (
+                await self.prisma_client.db.litellm_usertable.find_unique(
+                    where={"user_id": user_id}
+                )
             )
             if user_row is None:
                 return {}
@@ -115,8 +117,10 @@ class CheckBatchCost:
         if not api_key:
             return None
         try:
-            key_row = await self.prisma_client.db.litellm_verificationtoken.find_unique(
-                where={"token": api_key}
+            key_row: prisma_models.LiteLLM_VerificationToken | None = (
+                await self.prisma_client.db.litellm_verificationtoken.find_unique(
+                    where={"token": api_key}
+                )
             )
             return getattr(key_row, "key_alias", None) if key_row is not None else None
         except Exception as e:
@@ -128,8 +132,10 @@ class CheckBatchCost:
         if not team_id:
             return None
         try:
-            team_row = await self.prisma_client.db.litellm_teamtable.find_unique(
-                where={"team_id": team_id}
+            team_row: prisma_models.LiteLLM_TeamTable | None = (
+                await self.prisma_client.db.litellm_teamtable.find_unique(
+                    where={"team_id": team_id}
+                )
             )
             return getattr(team_row, "team_alias", None) if team_row is not None else None
         except Exception as e:
@@ -138,7 +144,7 @@ class CheckBatchCost:
 
     async def _build_creator_attribution_metadata(
         self, job: "LiteLLM_ManagedObjectTable", batch_id: str
-    ) -> Dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Rebuild the spend-tracking metadata for the key, team, and tags that created the
         batch so the batch-cost spend log is attributed the same way a non-batch request
@@ -152,7 +158,7 @@ class CheckBatchCost:
         team_id = getattr(job, "team_id", None)
         request_tags = getattr(job, "request_tags", None)
 
-        metadata: Dict[str, Any] = {
+        metadata: dict[str, object] = {
             "user_api_key_user_id": job.created_by,
             "user_api_key": api_key,
             "user_api_key_team_id": team_id,
diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
index 570b306d6df..5cfcf6129f0 100644
--- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
+++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py
@@ -182,6 +182,10 @@ class _ManagedObjectTableActions(Protocol):
     async def update_many(self, where: Mapping[str, object], data: Mapping[str, object]) -> int: ...
 
 
+class _SchedulerWithJobLookup(Protocol):
+    def get_job(self, job_id: str) -> object: ...
+
+
 class _CursorPageArgs(TypedDict, total=False):
     cursor: Mapping[str, str]
     skip: int
@@ -853,7 +857,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
                                 file_ids.append(file_id)
         return file_ids
 
-    def get_file_ids_from_responses_input(self, input: Union[str, List[Dict[str, Any]]]) -> List[str]:
+    def get_file_ids_from_responses_input(self, input: Union[str, List[Dict[str, object]]]) -> List[str]:
         """
         Gets file ids from responses API input.
 
@@ -878,7 +882,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
             # Check for direct input_file type
             if item.get("type") == "input_file":
                 file_id = item.get("file_id")
-                if file_id:
+                if isinstance(file_id, str) and file_id:
                     file_ids.append(file_id)
 
             # Check for input_file in content array
@@ -887,7 +891,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
                 for content_item in content:
                     if isinstance(content_item, dict) and content_item.get("type") == "input_file":
                         file_id = content_item.get("file_id")
-                        if file_id:
+                        if isinstance(file_id, str) and file_id:
                             file_ids.append(file_id)
 
         return file_ids
@@ -1227,7 +1231,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
 
                 # Handle both output_file_id and error_file_id
                 for file_attr in ["output_file_id", "error_file_id"]:
-                    file_id_value = getattr(response, file_attr, None)
+                    file_id_value: str | None = getattr(response, file_attr, None)
                     if file_id_value and model_id:
                         decoded_output_file_id = _is_base64_encoded_unified_file_id(file_id_value)
                         if decoded_output_file_id and "llm_output_file_id," in decoded_output_file_id:
@@ -1496,7 +1500,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
             import litellm.proxy.proxy_server as proxy_server_module
 
             # Check if the scheduler has the batch cost checking job registered
-            scheduler = getattr(proxy_server_module, "scheduler", None)
+            scheduler: Final[_SchedulerWithJobLookup | None] = getattr(proxy_server_module, "scheduler", None)
             if scheduler is None:
                 return False
 
@@ -1542,7 +1546,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
             )
         MAX_MATCHES_TO_RETURN = 10
 
-        batches = await self.prisma_client.db.litellm_managedobjecttable.find_many(
+        batches = await _managed_object_table(self.prisma_client).find_many(
             where={
                 "file_purpose": "batch",
                 "batch_processed": False,
@@ -1552,11 +1556,14 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints):
             order={"created_at": "desc"},
         )
 
-        referencing_batches = []
+        referencing_batches: Final[list[dict[str, object]]] = []
         for batch in batches:
             try:
                 # Parse the batch file_object to check for file references
-                batch_data = json.loads(batch.file_object) if isinstance(batch.file_object, str) else batch.file_object
+                decoded_file_object = _decode_json_blob(batch.file_object)
+                batch_data: Mapping[str, object] = (
+                    decoded_file_object if isinstance(decoded_file_object, Mapping) else {}
+                )
 
                 # Extract file IDs from batch
                 # Batches typically reference the unified file ID in input_file_id
diff --git a/enterprise/litellm_enterprise/proxy/management_endpoints/internal_user_endpoints.py b/enterprise/litellm_enterprise/proxy/management_endpoints/internal_user_endpoints.py
index 1d3268da9a0..190141470df 100644
--- a/enterprise/litellm_enterprise/proxy/management_endpoints/internal_user_endpoints.py
+++ b/enterprise/litellm_enterprise/proxy/management_endpoints/internal_user_endpoints.py
@@ -39,9 +39,9 @@ async def available_enterprise_users(
 
     if not premium_user:
         # check if SSO is enabled - show 5 user limit
-        from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+        from litellm.proxy.auth.auth_utils import has_user_setup_sso
 
-        if _has_user_setup_sso():
+        if has_user_setup_sso():
             premium_user_data = EnterpriseLicenseData(
                 max_users=5,
             )
diff --git a/enterprise/pyproject.toml b/enterprise/pyproject.toml
index cac98b69793..8360c0a077d 100644
--- a/enterprise/pyproject.toml
+++ b/enterprise/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "litellm-enterprise"
-version = "0.1.62"
+version = "0.1.63"
 description = "Package for LiteLLM Enterprise features"
 readme = "README.md"
 requires-python = ">=3.9"
@@ -26,7 +26,7 @@ required-version = ">=0.10.9"
 module-root = ""
 
 [tool.commitizen]
-version = "0.1.62"
+version = "0.1.63"
 version_files = [
     "pyproject.toml:^version",
     "../pyproject.toml:litellm-enterprise==",
diff --git a/gateway/Dockerfile b/gateway/Dockerfile
index 4a2e32e186e..308d70a6b26 100644
--- a/gateway/Dockerfile
+++ b/gateway/Dockerfile
@@ -1,5 +1,5 @@
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 
 FROM $UV_IMAGE AS uvbin
@@ -16,7 +16,7 @@ COPY --from=uvbin /uv /uvx /usr/local/bin/
 # instead of nodeenv downloading one whose dynamic deps may not be in Wolfi
 # (e.g. Node 26.2.0 needs libatomic). Retry for transient apk.cgr.dev flakes.
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash gcc python3 python3-dev openssl openssl-dev libsndfile nodejs npm && break; \
+      apk add --no-cache bash gcc python-3.13 python-3.13-dev openssl openssl-dev libsndfile nodejs npm && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
@@ -47,7 +47,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra extra_proxy \
         --extra semantic-router \
         --extra bedrock-realtime \
-        --python python3
+        --python python3.13
 
 # Stage 2 — copy source and install the project + workspace members.
 COPY . .
@@ -59,7 +59,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
         --extra extra_proxy \
         --extra semantic-router \
         --extra bedrock-realtime \
-        --python python3
+        --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
     npm_config_cache=/root/.npm \
@@ -73,7 +73,7 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime
 USER root
 
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash openssl tzdata python3 libsndfile libatomic && break; \
+      apk add --no-cache bash openssl tzdata python-3.13 libsndfile libatomic && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
diff --git a/gateway/routes/allowlist.py b/gateway/routes/allowlist.py
index 05baf98bbb5..92b73867e67 100644
--- a/gateway/routes/allowlist.py
+++ b/gateway/routes/allowlist.py
@@ -86,6 +86,7 @@ GATEWAY_PATH_PREFIXES: tuple[str, ...] = (
     "/comprehendmedical",
     "/cohere/",
     "/gemini/",
+    "/gigachat/",
     "/google/",
     "/vertex_ai/",
     "/vertex-ai/",
diff --git a/helm/litellm-helm/Chart.yaml b/helm/litellm-helm/Chart.yaml
index 3959d85edf3..a3cb388ffc6 100644
--- a/helm/litellm-helm/Chart.yaml
+++ b/helm/litellm-helm/Chart.yaml
@@ -18,7 +18,7 @@ type: application
 # This is the chart version. This version number should be incremented each time you make changes
 # to the chart and its templates, including the app version.
 # Versions are expected to follow Semantic Versioning (https://semver.org/)
-version: 1.1.2
+version: 1.1.3
 
 # This is the version number of the application being deployed. This version number should be
 # incremented each time you make changes to the application. Versions are not expected to
diff --git a/helm/litellm-helm/README.md b/helm/litellm-helm/README.md
index b242373de5d..bf4089404db 100644
--- a/helm/litellm-helm/README.md
+++ b/helm/litellm-helm/README.md
@@ -26,7 +26,7 @@ If `db.useStackgresOperator` is used (not yet implemented):
 | `replicaCount`              | The number of LiteLLM Proxy pods to be deployed                                                                                                                                                                                               | `1`                       |
 | `masterkeySecretName`       | The name of the Kubernetes Secret that contains the Master API Key for LiteLLM. If not specified, use the generated secret name.                                                                                                              | N/A                       |
 | `masterkeySecretKey`        | The key within the Kubernetes Secret that contains the Master API Key for LiteLLM. If not specified, use `masterkey` as the key.                                                                                                              | N/A                       |
-| `masterkey`                 | The Master API Key for LiteLLM. If not specified, a random key in the `sk-...` format is generated.                                                                                                                                           | N/A                       |
+| `masterkey`                 | The Master API Key for LiteLLM. If not specified, a random key in the `sk-...` format is generated on first install and reused on upgrades. | N/A                       |
 | `environmentSecrets`        | An optional array of Secret object names. The keys and values in these secrets will be presented to the LiteLLM proxy pod as environment variables. See below for an example Secret object.                                                   | `[]`                      |
 | `environmentConfigMaps`     | An optional array of ConfigMap object names. The keys and values in these configmaps will be presented to the LiteLLM proxy pod as environment variables. See below for an example Secret object.                                             | `[]`                      |
 | `image.repository`          | LiteLLM Proxy image repository                                                                                                                                                                                                                | `ghcr.io/berriai/litellm` |
@@ -212,6 +212,8 @@ service, the **Proxy Endpoint** should be set to `http://<RELEASE>-litellm:4000`
 The **Proxy Key** is the value specified for `masterkey` or, if a `masterkey`
 was not provided to the helm command line, the `masterkey` is a randomly
 generated string in the `sk-...` format stored in the `<RELEASE>-litellm-masterkey` Kubernetes Secret.
+The key is generated once on the first install; later `helm upgrade` runs reuse the
+value already in that Secret, so upgrading never rotates the master key.
 
 ```bash
 kubectl -n litellm get secret <RELEASE>-litellm-masterkey -o jsonpath="{.data.masterkey}"
diff --git a/helm/litellm-helm/templates/secret-masterkey.yaml b/helm/litellm-helm/templates/secret-masterkey.yaml
index 7c8560cc2cc..60ab4e74c6b 100644
--- a/helm/litellm-helm/templates/secret-masterkey.yaml
+++ b/helm/litellm-helm/templates/secret-masterkey.yaml
@@ -1,9 +1,11 @@
 {{- if not .Values.masterkeySecretName }}
-{{ $masterkey := (.Values.masterkey | default (printf "sk-%s" (randAlphaNum 18))) }}
+{{- $secretName := printf "%s-masterkey" (include "litellm.fullname" .) }}
+{{- $existing := lookup "v1" "Secret" .Release.Namespace $secretName }}
+{{- $masterkey := .Values.masterkey | default (dig "data" "masterkey" "" $existing | b64dec) | default (printf "sk-%s" (randAlphaNum 18)) }}
 apiVersion: v1
 kind: Secret
 metadata:
-  name: {{ include "litellm.fullname" . }}-masterkey
+  name: {{ $secretName }}
 data:
   masterkey: {{ $masterkey | b64enc }}
 type: Opaque
diff --git a/helm/litellm-helm/tests/hpa_tests.yaml b/helm/litellm-helm/tests/hpa_tests.yaml
index ec18c3591d3..cd062dd5971 100644
--- a/helm/litellm-helm/tests/hpa_tests.yaml
+++ b/helm/litellm-helm/tests/hpa_tests.yaml
@@ -1,4 +1,4 @@
-suite: "hpa with behavior"
+suite: "hpa"
 templates:
   - hpa.yaml
 tests:
@@ -23,14 +23,44 @@ tests:
       - equal: { path: spec.behavior.scaleUp.stabilizationWindowSeconds, value: 60 }
       - equal: { path: spec.behavior.scaleDown.stabilizationWindowSeconds, value: 90 }
 
----
-suite: "hpa without behavior"
-templates:
-  - hpa.yaml
-tests:
   - it: "does not render behavior when not set"
     set:
       autoscaling.enabled: true
     asserts:
       - isKind: { of: HorizontalPodAutoscaler }
       - isNull: { path: spec.behavior }
+
+  - it: "scales on cpu at the documented 60 percent by default"
+    set:
+      autoscaling.enabled: true
+    asserts:
+      - isKind: { of: HorizontalPodAutoscaler }
+      - equal: { path: "spec.metrics[0].resource.name", value: cpu }
+      - equal: { path: "spec.metrics[0].resource.target.type", value: Utilization }
+      - equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 60 }
+
+  - it: "does not scale on memory by default"
+    set:
+      autoscaling.enabled: true
+    asserts:
+      - lengthEqual: { path: spec.metrics, count: 1 }
+
+  - it: "honours an explicit cpu target override"
+    set:
+      autoscaling.enabled: true
+      autoscaling.targetCPUUtilizationPercentage: 75
+    asserts:
+      - equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 75 }
+
+  - it: "renders a memory metric only when a memory target is set"
+    set:
+      autoscaling.enabled: true
+      autoscaling.targetMemoryUtilizationPercentage: 80
+    asserts:
+      - lengthEqual: { path: spec.metrics, count: 2 }
+      - equal: { path: "spec.metrics[1].resource.name", value: memory }
+      - equal: { path: "spec.metrics[1].resource.target.averageUtilization", value: 80 }
+
+  - it: "renders no hpa when autoscaling is disabled"
+    asserts:
+      - hasDocuments: { count: 0 }
diff --git a/helm/litellm-helm/tests/masterkey-secret_tests.yaml b/helm/litellm-helm/tests/masterkey-secret_tests.yaml
index bbbade9d802..296f26755b8 100644
--- a/helm/litellm-helm/tests/masterkey-secret_tests.yaml
+++ b/helm/litellm-helm/tests/masterkey-secret_tests.yaml
@@ -15,6 +15,53 @@ tests:
           # Note: The masterkey is generated as "sk-<18-random-chars>" in plain text,
           # but stored as base64 encoded in Kubernetes secret (requirement).
           # "sk-" base64 encodes to "c2st", so we check for "^c2st" pattern.
+  - it: should reuse the master key already stored in the cluster instead of generating a new one on upgrade
+    template: secret-masterkey.yaml
+    set:
+      masterkeySecretName: ""
+    kubernetesProvider:
+      scheme:
+        "v1/Secret":
+          gvr:
+            version: "v1"
+            resource: "secrets"
+          namespaced: true
+      objects:
+        - kind: Secret
+          apiVersion: v1
+          metadata:
+            name: RELEASE-NAME-litellm-masterkey
+            namespace: NAMESPACE
+          data:
+            masterkey: c2stZXhpc3Rpbmcta2V5
+    asserts:
+      - equal:
+          path: data.masterkey
+          value: c2stZXhpc3Rpbmcta2V5
+  - it: should let an explicit masterkey value override the one already stored in the cluster
+    template: secret-masterkey.yaml
+    set:
+      masterkeySecretName: ""
+      masterkey: sk-explicit
+    kubernetesProvider:
+      scheme:
+        "v1/Secret":
+          gvr:
+            version: "v1"
+            resource: "secrets"
+          namespaced: true
+      objects:
+        - kind: Secret
+          apiVersion: v1
+          metadata:
+            name: RELEASE-NAME-litellm-masterkey
+            namespace: NAMESPACE
+          data:
+            masterkey: c2stZXhpc3Rpbmcta2V5
+    asserts:
+      - equal:
+          path: data.masterkey
+          value: c2stZXhwbGljaXQ=
   - it: should not create a secret if masterkeySecretName is set
     template: secret-masterkey.yaml
     set:
diff --git a/helm/litellm-helm/values.yaml b/helm/litellm-helm/values.yaml
index f8df98de102..637be2322e3 100644
--- a/helm/litellm-helm/values.yaml
+++ b/helm/litellm-helm/values.yaml
@@ -200,7 +200,16 @@ autoscaling:
   enabled: false
   minReplicas: 1
   maxReplicas: 100
-  targetCPUUtilizationPercentage: 80
+  # 60 is the documented recommendation. See "Recommended Machine Specifications"
+  # in https://docs.litellm.ai/docs/proxy/prod. A new replica clears the startupProbe
+  # above only after up to failureThreshold x periodSeconds = 300 seconds, so a target
+  # high enough to trip near saturation adds capacity minutes after it was needed.
+  targetCPUUtilizationPercentage: 60
+  # Deliberately left unset rather than given a value. The prisma query engine's
+  # resident memory is a high-water mark that ratchets to the pod's worst-ever write
+  # and is never returned, so a memory target reads the largest write a pod ever did
+  # rather than what it is doing now, and replicas ratchet up without scaling back in.
+  # Memory is a floor to provision under 'resources', not a signal to scale on.
   # targetMemoryUtilizationPercentage: 80
   # behavior: {}
 
diff --git a/helm/litellm/templates/backend/deployment.yaml b/helm/litellm/templates/backend/deployment.yaml
index 5c0431fc0bd..0db2f0b3d43 100644
--- a/helm/litellm/templates/backend/deployment.yaml
+++ b/helm/litellm/templates/backend/deployment.yaml
@@ -7,6 +7,10 @@ metadata:
     {{- include "litellm.commonLabels" . | nindent 4 }}
     app.kubernetes.io/component: backend
 spec:
+  {{- with .Values.backend.strategy }}
+  strategy:
+    {{- toYaml . | nindent 4 }}
+  {{- end }}
   selector:
     matchLabels:
       {{- include "litellm.backend.selectorLabels" . | nindent 6 }}
diff --git a/helm/litellm/templates/gateway/deployment.yaml b/helm/litellm/templates/gateway/deployment.yaml
index d5363d0096e..5030ba2c9dc 100644
--- a/helm/litellm/templates/gateway/deployment.yaml
+++ b/helm/litellm/templates/gateway/deployment.yaml
@@ -7,6 +7,10 @@ metadata:
     {{- include "litellm.commonLabels" . | nindent 4 }}
     app.kubernetes.io/component: gateway
 spec:
+  {{- with .Values.gateway.strategy }}
+  strategy:
+    {{- toYaml . | nindent 4 }}
+  {{- end }}
   selector:
     matchLabels:
       {{- include "litellm.gateway.selectorLabels" . | nindent 6 }}
diff --git a/helm/litellm/templates/migrations-job.yaml b/helm/litellm/templates/migrations-job.yaml
index 9cd8397f794..8d33081e72f 100644
--- a/helm/litellm/templates/migrations-job.yaml
+++ b/helm/litellm/templates/migrations-job.yaml
@@ -7,6 +7,8 @@
 #
 # Running this pre-upgrade closes the window where new application pods would
 # otherwise serve traffic against the previous release's unmigrated schema.
+# Argo CD users can swap the Helm hook for a PreSync hook through
+# `migrationJob.hooks`, which re-runs the Job on every sync.
 apiVersion: batch/v1
 kind: Job
 metadata:
@@ -14,10 +16,18 @@ metadata:
   labels:
     {{- include "litellm.commonLabels" . | nindent 4 }}
     app.kubernetes.io/component: migrations
+  {{- if or .Values.migrationJob.hooks.helm.enabled .Values.migrationJob.hooks.argocd.enabled }}
   annotations:
+    {{- if .Values.migrationJob.hooks.helm.enabled }}
     helm.sh/hook: pre-install,pre-upgrade
     helm.sh/hook-delete-policy: before-hook-creation
-    helm.sh/hook-weight: "0"
+    helm.sh/hook-weight: {{ .Values.migrationJob.hooks.helm.weight | default "0" | quote }}
+    {{- end }}
+    {{- if .Values.migrationJob.hooks.argocd.enabled }}
+    argocd.argoproj.io/hook: PreSync
+    argocd.argoproj.io/hook-delete-policy: BeforeHookCreation
+    {{- end }}
+  {{- end }}
 spec:
   backoffLimit: {{ .Values.migrationJob.backoffLimit }}
   ttlSecondsAfterFinished: {{ .Values.migrationJob.ttlSecondsAfterFinished }}
diff --git a/helm/litellm/templates/ui/deployment.yaml b/helm/litellm/templates/ui/deployment.yaml
index 91d6de39ea6..b992b347bad 100644
--- a/helm/litellm/templates/ui/deployment.yaml
+++ b/helm/litellm/templates/ui/deployment.yaml
@@ -7,6 +7,10 @@ metadata:
     {{- include "litellm.commonLabels" . | nindent 4 }}
     app.kubernetes.io/component: ui
 spec:
+  {{- with .Values.ui.strategy }}
+  strategy:
+    {{- toYaml . | nindent 4 }}
+  {{- end }}
   selector:
     matchLabels:
       {{- include "litellm.ui.selectorLabels" . | nindent 6 }}
diff --git a/helm/litellm/tests/migration_job_hooks_tests.yaml b/helm/litellm/tests/migration_job_hooks_tests.yaml
new file mode 100644
index 00000000000..650d2700429
--- /dev/null
+++ b/helm/litellm/tests/migration_job_hooks_tests.yaml
@@ -0,0 +1,63 @@
+suite: test migrations Job hook annotations
+templates:
+  - migrations-job.yaml
+values:
+  - ./values/required.yaml
+tests:
+  - it: runs as a Helm pre-install / pre-upgrade hook by default
+    asserts:
+      - equal:
+          path: metadata.annotations["helm.sh/hook"]
+          value: pre-install,pre-upgrade
+      - equal:
+          path: metadata.annotations["helm.sh/hook-delete-policy"]
+          value: before-hook-creation
+      - equal:
+          path: metadata.annotations["helm.sh/hook-weight"]
+          value: "0"
+      - notExists:
+          path: metadata.annotations["argocd.argoproj.io/hook"]
+
+  - it: adds the Argo CD PreSync hook when asked
+    set:
+      migrationJob.hooks.argocd.enabled: true
+    asserts:
+      - equal:
+          path: metadata.annotations["argocd.argoproj.io/hook"]
+          value: PreSync
+      - equal:
+          path: metadata.annotations["argocd.argoproj.io/hook-delete-policy"]
+          value: BeforeHookCreation
+
+  - it: drops the Helm hook so Argo CD owns the Job
+    set:
+      migrationJob.hooks.argocd.enabled: true
+      migrationJob.hooks.helm.enabled: false
+    asserts:
+      - equal:
+          path: metadata.annotations["argocd.argoproj.io/hook"]
+          value: PreSync
+      - notExists:
+          path: metadata.annotations["helm.sh/hook"]
+      - notExists:
+          path: metadata.annotations["helm.sh/hook-delete-policy"]
+      - notExists:
+          path: metadata.annotations["helm.sh/hook-weight"]
+
+  - it: renders an ordinary Job when both hooks are disabled
+    set:
+      migrationJob.hooks.helm.enabled: false
+    asserts:
+      - notExists:
+          path: metadata.annotations
+      - equal:
+          path: kind
+          value: Job
+
+  - it: honours a custom Helm hook weight
+    set:
+      migrationJob.hooks.helm.weight: "-5"
+    asserts:
+      - equal:
+          path: metadata.annotations["helm.sh/hook-weight"]
+          value: "-5"
diff --git a/helm/litellm/tests/rollout_strategy_tests.yaml b/helm/litellm/tests/rollout_strategy_tests.yaml
new file mode 100644
index 00000000000..b12e2073c7c
--- /dev/null
+++ b/helm/litellm/tests/rollout_strategy_tests.yaml
@@ -0,0 +1,66 @@
+suite: test rolling update strategy on the component deployments
+templates:
+  - gateway/deployment.yaml
+  - gateway/configmap.yaml
+  - backend/deployment.yaml
+  - ui/deployment.yaml
+values:
+  - ./values/required.yaml
+tests:
+  - it: leaves the strategy to Kubernetes defaults when unset
+    asserts:
+      - notExists:
+          path: spec.strategy
+
+  - it: renders the configured strategy on each deployment
+    set:
+      gateway.strategy:
+        type: RollingUpdate
+        rollingUpdate:
+          maxUnavailable: 0
+          maxSurge: 1
+      backend.strategy:
+        type: RollingUpdate
+        rollingUpdate:
+          maxUnavailable: "25%"
+          maxSurge: 2
+      ui.strategy:
+        type: Recreate
+    asserts:
+      - equal:
+          path: spec.strategy
+          value:
+            type: RollingUpdate
+            rollingUpdate:
+              maxUnavailable: 0
+              maxSurge: 1
+        template: gateway/deployment.yaml
+      - equal:
+          path: spec.strategy
+          value:
+            type: RollingUpdate
+            rollingUpdate:
+              maxUnavailable: 25%
+              maxSurge: 2
+        template: backend/deployment.yaml
+      - equal:
+          path: spec.strategy
+          value:
+            type: Recreate
+        template: ui/deployment.yaml
+
+  - it: keeps a component on the cluster default when only another one sets a strategy
+    set:
+      gateway.strategy:
+        type: Recreate
+    asserts:
+      - equal:
+          path: spec.strategy.type
+          value: Recreate
+        template: gateway/deployment.yaml
+      - notExists:
+          path: spec.strategy
+        template: backend/deployment.yaml
+      - notExists:
+          path: spec.strategy
+        template: ui/deployment.yaml
diff --git a/helm/litellm/values.yaml b/helm/litellm/values.yaml
index d0c80fd6f6f..378c3b7a618 100644
--- a/helm/litellm/values.yaml
+++ b/helm/litellm/values.yaml
@@ -75,6 +75,22 @@ serviceAccounts:
 # generate` — the migration engine doesn't need the generated client.
 migrationJob:
   enabled: true
+  # Which controller is responsible for running the Job.
+  #
+  # `helm.enabled` renders the Helm pre-install / pre-upgrade hook, so the Job
+  # runs whenever `helm upgrade` sees a change to apply. `argocd.enabled`
+  # renders an Argo CD PreSync hook instead, which runs the Job on every sync
+  # even when the rendered manifests are unchanged: the way to re-run
+  # migrations on demand from a GitOps pipeline. Turning the Helm hook off
+  # while the Argo CD hook is on leaves the Job out of Helm's own upgrade
+  # path, which is what Argo CD users want since Argo, not Helm, applies the
+  # manifests.
+  hooks:
+    helm:
+      enabled: true
+      weight: "0"
+    argocd:
+      enabled: false
   backoffLimit: 4
   ttlSecondsAfterFinished: 120
   # Wall-clock budget for the whole Job, shared across every `backoffLimit`
@@ -257,6 +273,15 @@ gateway:
     initialDelaySeconds: 5
     periodSeconds: 10
     timeoutSeconds: 10
+  # Rolling update tuning for the gateway Deployment. Empty by default, so
+  # Kubernetes applies its own RollingUpdate defaults (25% maxSurge /
+  # 25% maxUnavailable). Example, for a surge-only rollout behind a load
+  # balancer that must never lose capacity:
+  #   type: RollingUpdate
+  #   rollingUpdate:
+  #     maxUnavailable: 0
+  #     maxSurge: 1
+  strategy: {}
   # Optional startupProbe. Empty by default, so existing installs are unchanged
   # and liveness/readiness apply from container start. Set it to gate
   # liveness/readiness until a slow cold start finishes — a high failureThreshold
@@ -369,6 +394,8 @@ backend:
     initialDelaySeconds: 5
     periodSeconds: 10
     timeoutSeconds: 10
+  # Same shape as gateway.strategy.
+  strategy: {}
   # Optional startupProbe; same shape as gateway.startupProbe. Empty by default.
   startupProbe: {}
   hpa:
@@ -433,6 +460,8 @@ ui:
     httpGet: { path: /, port: http }
     initialDelaySeconds: 2
     periodSeconds: 10
+  # Same shape as gateway.strategy.
+  strategy: {}
   # Optional startupProbe; same shape as gateway.startupProbe. Empty by default.
   startupProbe: {}
   hpa:
diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831000000_shadow_eval_typed_targets/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831000000_shadow_eval_typed_targets/migration.sql
new file mode 100644
index 00000000000..b7dbe931dd2
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831000000_shadow_eval_typed_targets/migration.sql
@@ -0,0 +1,21 @@
+DO $$
+BEGIN
+    IF EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'LiteLLM_ShadowEvalJob' AND column_name = 'api_key_id'
+    ) THEN
+        ALTER TABLE "LiteLLM_ShadowEvalJob" RENAME COLUMN "api_key_id" TO "target_id";
+    END IF;
+END $$;
+
+ALTER TABLE "LiteLLM_ShadowEvalJob" ADD COLUMN IF NOT EXISTS "target_type" TEXT NOT NULL DEFAULT 'key';
+
+DROP INDEX IF EXISTS "LiteLLM_ShadowEvalJob_one_active_per_key_direction";
+
+CREATE UNIQUE INDEX IF NOT EXISTS "LiteLLM_ShadowEvalJob_one_active_per_target_direction"
+    ON "LiteLLM_ShadowEvalJob"("target_type", "target_id", "direction") WHERE "stopped_at" IS NULL;
+
+DROP INDEX IF EXISTS "LiteLLM_ShadowEvalJob_api_key_id_idx";
+
+CREATE INDEX IF NOT EXISTS "LiteLLM_ShadowEvalJob_target_type_target_id_idx"
+    ON "LiteLLM_ShadowEvalJob"("target_type", "target_id");
diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260901000000_shadow_eval_multi_router/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260901000000_shadow_eval_multi_router/migration.sql
new file mode 100644
index 00000000000..90b21205310
--- /dev/null
+++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260901000000_shadow_eval_multi_router/migration.sql
@@ -0,0 +1,3 @@
+ALTER TABLE "LiteLLM_ShadowEvalJob" ADD COLUMN IF NOT EXISTS "router_names" TEXT[] NOT NULL DEFAULT ARRAY[]::TEXT[];
+
+ALTER TABLE "LiteLLM_ShadowEvalAttempt" ADD COLUMN IF NOT EXISTS "router_name" TEXT;
diff --git a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
index f3b55fd4d96..2283814ab35 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
+++ b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py
@@ -14,9 +14,22 @@ then fails on a Node binary that was never written. Deleting a cache directory
 that exists without a Node binary is what turns a killed bootstrap back into a
 recoverable one.
 
-Both budgets are overridable so an operator can widen them without a release:
-``LITELLM_PRISMA_BOOTSTRAP_TIMEOUT`` for the toolchain install and
-``LITELLM_PRISMA_COMMAND_TIMEOUT`` for every individual Prisma command.
+``prisma migrate deploy`` is the other command whose runtime is not a
+constant: it grows with the number of pending migrations, so a fresh database
+that has to replay every migration this package ships overruns a per-command
+budget sized for the short bookkeeping commands, on a laptop as much as on a
+slow CI runner. The Python ``prisma`` wrapper spawns Node and the schema engine
+as separate children, so killing the wrapper on timeout leaves them running:
+the retry then contends with that orphan for Prisma's advisory lock and cannot
+finish any sooner. Migrate deploy therefore runs under its own budget.
+
+All three budgets are overridable so an operator can widen them without a
+release: ``LITELLM_PRISMA_BOOTSTRAP_TIMEOUT`` for the toolchain install,
+``LITELLM_PRISMA_MIGRATE_DEPLOY_TIMEOUT`` for ``prisma migrate deploy`` and
+``LITELLM_PRISMA_COMMAND_TIMEOUT`` for every other Prisma command. The
+per-command budget used to bound migrate deploy as well, so a deployment that
+raised it above the deploy default keeps that larger budget for deploy unless
+the deploy override says otherwise.
 """
 
 import math
@@ -36,10 +49,12 @@ except ImportError:
 
 PRISMA_COMMAND_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_COMMAND_TIMEOUT"
 PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_BOOTSTRAP_TIMEOUT"
+PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR = "LITELLM_PRISMA_MIGRATE_DEPLOY_TIMEOUT"
 NODEENV_CACHE_DIR_ENV_VAR = "PRISMA_NODEENV_CACHE_DIR"
 
 DEFAULT_PRISMA_COMMAND_TIMEOUT = 60.0
 DEFAULT_PRISMA_BOOTSTRAP_TIMEOUT = 600.0
+DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT = 600.0
 
 BOOTSTRAP_ARG = "--version"
 
@@ -88,6 +103,15 @@ def prisma_bootstrap_timeout() -> float:
     )
 
 
+def prisma_migrate_deploy_timeout() -> float:
+    """Seconds one ``prisma migrate deploy`` may run for, however many migrations are pending."""
+    if os.getenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR) is not None:
+        return _timeout_from_env(
+            PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT
+        )
+    return max(DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT, prisma_command_timeout())
+
+
 def nodeenv_cache_dir() -> Optional[Path]:
     """Where Prisma installs its private Node runtime, or None if unknowable."""
     override = os.getenv(NODEENV_CACHE_DIR_ENV_VAR)
diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
index 60223265211..7604ceadf7a 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
+++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
@@ -1529,14 +1529,16 @@ model LiteLLM_AutoRouterSession {
 model LiteLLM_ShadowEvalJob {
   id                String   @id @default(cuid())
   group_id          String   // legs of one job share this; the API's job id
-  api_key_id        String   // hashed virtual key whose traffic this leg shadows
-  router_name       String   // the auto-router under evaluation, in either direction
+  target_type       String   @default("key") // key | team | user
+  target_id         String   // hashed virtual key, team_id, or user_id whose traffic this leg shadows
+  router_name       String   // first (often only) auto-router under evaluation; router_names is the full set
+  router_names      String[] @default([]) // all routers this job runs as shadow arms; empty on legacy rows, whose set is (router_name)
   direction         String   @default("forward") // forward | reverse
   baseline_model    String?  // reverse only: the fixed model the router is judged against
   judge_model       String
   shadow_percentage Float
   max_turns         Int      // sample-count ceiling: the whole budget on pre-max_budget jobs, the error-loop valve otherwise
-  max_budget        Float?   // per-key USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
+  max_budget        Float?   // per-target USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
   created_at        DateTime @default(now())
   created_by        String?
   ends_at           DateTime
@@ -1544,7 +1546,7 @@ model LiteLLM_ShadowEvalJob {
   stopped_by        String?  // operator who stopped it early; null when it ended on its own
 
   @@index([group_id])
-  @@index([api_key_id])
+  @@index([target_type, target_id])
   @@index([created_at])
 }
 
@@ -1554,6 +1556,7 @@ model LiteLLM_ShadowEvalAttempt {
   job_id       String
   request_id   String   // the judged real request
   outcome      String   // real | shadow | tie | error
+  router_name  String?  // the arm this verdict scores; NULL on legacy rows, meaning the job's own router
   tier         String?  // router's tier for the prompt, when classified
   real_model   String?
   shadow_model String?
diff --git a/litellm-proxy-extras/litellm_proxy_extras/utils.py b/litellm-proxy-extras/litellm_proxy_extras/utils.py
index b2dc0a52c8f..d22484bc0e8 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/utils.py
+++ b/litellm-proxy-extras/litellm_proxy_extras/utils.py
@@ -15,8 +15,11 @@ from litellm_proxy_extras.replica_identity import (
     apply_replica_identity_full,
 )
 from litellm_proxy_extras.prisma_toolchain import (
+    PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
     ensure_prisma_toolchain,
     prisma_command_timeout,
+    prisma_migrate_deploy_timeout,
 )
 
 
@@ -40,6 +43,8 @@ def _get_prisma_env() -> dict:
 
 _MIGRATION_TS_RE = re.compile(r"^(\d{14})_")
 
+_MIGRATION_DEADLOCK_MARKER = "deadlock detected"
+
 _SPEND_LOGS_ALTER_RE = re.compile(r'^ALTER\s+TABLE\s+"LiteLLM_SpendLogs"\s', re.IGNORECASE)
 _SPEND_LOGS_ARTIFACT_DROP_RE = re.compile(
     r'^DROP\s+TABLE\s+"LiteLLM_SpendLogs_[^"]*"', re.IGNORECASE
@@ -262,6 +267,50 @@ class ProxyExtrasDBManager:
             env=prisma_env,
         )
 
+    @staticmethod
+    def _roll_back_migration_best_effort(migration_name: str) -> None:
+        """Mark a migration rolled back, tolerating a concurrent resolver
+        having already done it."""
+        try:
+            ProxyExtrasDBManager._roll_back_migration(migration_name)
+        except (subprocess.CalledProcessError, subprocess.TimeoutExpired):
+            pass
+
+    @staticmethod
+    def _failed_migration_logs(migration_name: str) -> Optional[str]:
+        """Return failed migration logs, or None if the ledger is unavailable."""
+        database_url = os.getenv("DATABASE_URL")
+        if not database_url:
+            return None
+
+        try:
+            import psycopg
+        except ImportError:
+            return None
+
+        cleaned_url = ProxyExtrasDBManager._strip_prisma_query_params(database_url)
+        ledger_table = psycopg.sql.SQL("{}.{}").format(
+            psycopg.sql.Identifier(
+                ProxyExtrasDBManager._prisma_schema_param(database_url) or "public"
+            ),
+            psycopg.sql.Identifier("_prisma_migrations"),
+        )
+        try:
+            with psycopg.connect(
+                cleaned_url, connect_timeout=10, autocommit=True
+            ) as conn:
+                row = conn.execute(
+                    psycopg.sql.SQL(
+                        "SELECT logs FROM {} "
+                        "WHERE migration_name = %s AND finished_at IS NULL "
+                        "AND rolled_back_at IS NULL"
+                    ).format(ledger_table),
+                    (migration_name,),
+                ).fetchone()
+        except (psycopg.OperationalError, psycopg.DatabaseError):
+            return None
+        return (row[0] or "") if row else ""
+
     @staticmethod
     def _resolve_specific_migration(migration_name: str):
         """Mark a specific migration as applied"""
@@ -512,6 +561,13 @@ class ProxyExtrasDBManager:
         try:
             import psycopg
         except ImportError:
+            logger.warning(
+                "psycopg is not installed; skipping the LiteLLM_SpendLogs "
+                "partition check. If this table is partitioned (see "
+                "db_scripts/partition_spend_logs.sql), schema reconciliation "
+                "will try to rewrite its primary key and fail. Install the "
+                "litellm[extra_proxy] extra, which now includes psycopg."
+            )
             return False
 
         cleaned_url = ProxyExtrasDBManager._strip_prisma_query_params(database_url)
@@ -651,7 +707,8 @@ class ProxyExtrasDBManager:
         v2 migration resolver (opt-in via --use_v2_migration_resolver).
 
         Runs `prisma migrate deploy` and handles standard recovery paths
-        (P3005 baseline, P3009/P3018 idempotent errors). Critically, it does
+        (P3005 baseline, P3009/P3018 idempotent errors, deadlocks against a
+        concurrent migrate deploy). Critically, it does
         NOT call `_resolve_all_migrations` — the diff-and-force recovery that
         caused schema thrashing when two LiteLLM versions contended for the
         same DB during rolling deploys.
@@ -691,12 +748,13 @@ class ProxyExtrasDBManager:
 
         original_dir = os.getcwd()
         os.chdir(migrations_dir)
+        deploy_timeout = prisma_migrate_deploy_timeout()
         try:
             for attempt in range(4):
                 try:
                     result = subprocess.run(
                         [_get_prisma_command(), "migrate", "deploy"],
-                        timeout=prisma_command_timeout(),
+                        timeout=deploy_timeout,
                         check=True,
                         capture_output=True,
                         text=True,
@@ -706,8 +764,12 @@ class ProxyExtrasDBManager:
                     return True
 
                 except subprocess.TimeoutExpired:
-                    logger.info(
-                        f"prisma migrate deploy attempt {attempt + 1} timed out, retrying"
+                    logger.warning(
+                        "prisma migrate deploy attempt %s timed out after %ss, retrying. "
+                        "Raise %s if this database needs longer to apply its pending migrations.",
+                        attempt + 1,
+                        deploy_timeout,
+                        PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
                     )
                     time.sleep(random.randrange(5, 15))
                     continue
@@ -757,6 +819,20 @@ class ProxyExtrasDBManager:
                                     f"Detail: {resolve_err}"
                                 ) from resolve_err
                             continue
+                        if migration_match:
+                            migration_name = migration_match.group(1)
+                            ledger_logs = ProxyExtrasDBManager._failed_migration_logs(migration_name)
+                            if ledger_logs is not None and (
+                                ledger_logs == "" or _MIGRATION_DEADLOCK_MARKER in ledger_logs
+                            ):
+                                logger.info(
+                                    "Migration %s failed in a concurrent migrate deploy "
+                                    "deadlock race, rolling its ledger row back and retrying",
+                                    migration_name,
+                                )
+                                ProxyExtrasDBManager._roll_back_migration_best_effort(migration_name)
+                                time.sleep(random.randrange(5, 15))
+                                continue
                         raise RuntimeError(
                             "Database migration failed and cannot be auto-recovered. "
                             f"Manual intervention required.\n\nPrisma error:\n{stderr}"
@@ -802,11 +878,42 @@ class ProxyExtrasDBManager:
                                 ) from resolve_err
                             continue
 
+                        if migration_match and _MIGRATION_DEADLOCK_MARKER in stderr:
+                            logger.info(
+                                "Migration %s deadlocked against a concurrent "
+                                "migrate deploy, rolling its ledger row back "
+                                "and retrying",
+                                migration_match.group(1),
+                            )
+                            ProxyExtrasDBManager._roll_back_migration_best_effort(
+                                migration_match.group(1)
+                            )
+                            time.sleep(random.randrange(5, 15))
+                            continue
+
                         raise RuntimeError(
                             "Database migration failed and cannot be auto-recovered. "
                             f"Manual intervention required.\n\nPrisma error:\n{stderr}"
                         ) from e
 
+                    if _MIGRATION_DEADLOCK_MARKER in stderr:
+                        logger.info(
+                            "prisma migrate deploy attempt %s deadlocked against "
+                            "a concurrent migrate deploy, retrying",
+                            attempt + 1,
+                        )
+                        time.sleep(random.randrange(5, 15))
+                        continue
+
+                    if "P1002" in stderr and "advisory lock" in stderr:
+                        logger.info(
+                            "prisma migrate deploy attempt %s timed out waiting for "
+                            "the advisory lock a concurrent migrate deploy holds, retrying",
+                            attempt + 1,
+                        )
+                        time.sleep(random.randrange(5, 15))
+                        continue
+
                     raise RuntimeError(
                         "Database migration failed and cannot be auto-recovered. "
                         f"Manual intervention required.\n\nPrisma error:\n{stderr}"
@@ -814,9 +921,10 @@ class ProxyExtrasDBManager:
 
             raise RuntimeError(
                 "Database migration failed after 4 attempts (retry loop "
-                "exhausted by timeouts or repeated idempotent-recovery "
-                "continues). Check database connectivity, load, and "
-                "_prisma_migrations ledger state."
+                "exhausted by timeouts, deadlock retries, or repeated "
+                "idempotent-recovery continues). Check database connectivity, "
+                "load, and _prisma_migrations ledger state, and raise "
+                f"{PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR} if the attempts timed out."
             )
         finally:
             os.chdir(original_dir)
@@ -901,7 +1009,7 @@ class ProxyExtrasDBManager:
                         # Set migrations directory for Prisma
                         result = subprocess.run(
                             [_get_prisma_command(), "migrate", "deploy"],
-                            timeout=prisma_command_timeout(),
+                            timeout=prisma_migrate_deploy_timeout(),
                             check=True,
                             capture_output=True,
                             text=True,
@@ -1119,7 +1227,11 @@ class ProxyExtrasDBManager:
                     )
                     return True
             except subprocess.TimeoutExpired:
-                logger.info(f"Attempt {attempt + 1} timed out")
+                logger.warning(
+                    "Attempt %s timed out. Raise %s if this database needs longer to apply its schema.",
+                    attempt + 1,
+                    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR if use_migrate else PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+                )
                 time.sleep(random.randrange(5, 15))
             except subprocess.CalledProcessError as e:
                 attempts_left = 3 - attempt
diff --git a/litellm-proxy-extras/pyproject.toml b/litellm-proxy-extras/pyproject.toml
index d5741d479bf..0944f99ad54 100644
--- a/litellm-proxy-extras/pyproject.toml
+++ b/litellm-proxy-extras/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "litellm-proxy-extras"
-version = "0.4.91"
+version = "0.4.92"
 description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
 readme = "README.md"
 requires-python = ">=3.9"
@@ -26,7 +26,7 @@ required-version = ">=0.10.9"
 module-root = ""
 
 [tool.commitizen]
-version = "0.4.91"
+version = "0.4.92"
 version_files = [
     "pyproject.toml:^version",
     "../pyproject.toml:litellm-proxy-extras==",
diff --git a/litellm-proxy-extras/tests/test_setup_database_fail_fast.py b/litellm-proxy-extras/tests/test_setup_database_fail_fast.py
index 8d66bf872de..406f07eb792 100644
--- a/litellm-proxy-extras/tests/test_setup_database_fail_fast.py
+++ b/litellm-proxy-extras/tests/test_setup_database_fail_fast.py
@@ -240,3 +240,223 @@ def test_v2_does_not_call_resolve_all_migrations(monkeypatch, tmp_path):
     ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
     assert ok is True
     assert resolve_called["n"] == 0, "v2 must not invoke the diff-and-force recovery"
+
+
+_DEADLOCK_P3018_STDERR = (
+    "Error: P3018\n"
+    "Migration name: 20260415120000_health_check_latest_per_model_index\n"
+    "Database error code: 40P01\n"
+    "deadlock detected"
+)
+
+
+def _stub_v2_env(monkeypatch, tmp_path):
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setattr(
+        ProxyExtrasDBManager, "_warn_if_db_ahead_of_head", lambda _: None
+    )
+    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
+    (tmp_path / "schema.prisma").write_text("// stub")
+    monkeypatch.setattr("time.sleep", lambda _: None)
+
+
+def _succeed_after(failures: int, stderr: str):
+    calls = {"n": 0}
+
+    class _OkResult:
+        stdout = "Applied migration.\n"
+        stderr = ""
+
+    def _run(*args, **kwargs):
+        if "deploy" not in args[0]:
+            return _OkResult()
+        calls["n"] += 1
+        if calls["n"] <= failures:
+            raise subprocess.CalledProcessError(
+                returncode=1, cmd=args[0], stderr=stderr, output=""
+            )
+        return _OkResult()
+
+    return _run
+
+
+def test_v2_p3018_deadlock_rolls_back_and_retries(monkeypatch, tmp_path):
+    """v2: losing the migrate deploy deadlock race against a concurrent
+    instance rolls the ledger row back and retries instead of dying."""
+    _stub_v2_env(monkeypatch, tmp_path)
+
+    rolled_back = []
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_roll_back_migration",
+        lambda name: rolled_back.append(name),
+    )
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_resolve_specific_migration",
+        lambda name: pytest.fail("a deadlocked migration must never be marked applied"),
+    )
+    monkeypatch.setattr("subprocess.run", _succeed_after(1, _DEADLOCK_P3018_STDERR))
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    assert ok is True
+    assert rolled_back == ["20260415120000_health_check_latest_per_model_index"]
+
+
+def test_v2_p3018_persistent_deadlock_exhausts_attempts(monkeypatch, tmp_path):
+    """v2: a deadlock on every attempt still fails after the retry budget."""
+    _stub_v2_env(monkeypatch, tmp_path)
+    monkeypatch.setattr(ProxyExtrasDBManager, "_roll_back_migration", lambda name: None)
+
+    with patch(
+        "subprocess.run",
+        side_effect=_fake_migrate_deploy_failure(1, _DEADLOCK_P3018_STDERR),
+    ):
+        with pytest.raises(RuntimeError, match="after 4 attempts"):
+            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+
+
+def test_v2_p3009_deadlocked_ledger_row_rolls_back_and_retries(monkeypatch, tmp_path):
+    """v2: the surviving instance sees the victim's failed ledger row as P3009.
+    When that row's logs show a deadlock, roll it back and retry."""
+    _stub_v2_env(monkeypatch, tmp_path)
+
+    stderr = (
+        "Error: P3009\n"
+        "migrate found failed migrations in the target database\n"
+        "The `20260415120000_health_check_latest_per_model_index` migration "
+        "started at 2026-09-01 18:46:13 UTC failed"
+    )
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_failed_migration_logs",
+        lambda name: "ERROR: deadlock detected\nDETAIL: Process 72 waits for ShareLock",
+    )
+    rolled_back = []
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_roll_back_migration",
+        lambda name: rolled_back.append(name),
+    )
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_resolve_specific_migration",
+        lambda name: pytest.fail("a deadlocked migration must never be marked applied"),
+    )
+    monkeypatch.setattr("subprocess.run", _succeed_after(1, stderr))
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    assert ok is True
+    assert rolled_back == ["20260415120000_health_check_latest_per_model_index"]
+
+
+def test_v2_p3009_empty_ledger_logs_rolls_back_and_retries(monkeypatch, tmp_path):
+    """v2: empty failed ledger logs mean a concurrent deploy moved it on."""
+    _stub_v2_env(monkeypatch, tmp_path)
+
+    stderr = (
+        "Error: P3009\n"
+        "migrate found failed migrations in the target database\n"
+        "The `20260415120000_health_check_latest_per_model_index` migration "
+        "started at 2026-09-01 18:46:13 UTC failed"
+    )
+    monkeypatch.setattr(ProxyExtrasDBManager, "_failed_migration_logs", lambda name: "")
+    rolled_back = []
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_roll_back_migration",
+        lambda name: rolled_back.append(name),
+    )
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_resolve_specific_migration",
+        lambda name: pytest.fail("a deadlocked migration must never be marked applied"),
+    )
+    monkeypatch.setattr("subprocess.run", _succeed_after(1, stderr))
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    assert ok is True
+    assert rolled_back == ["20260415120000_health_check_latest_per_model_index"]
+
+
+def test_v2_p3009_unreadable_ledger_still_raises(monkeypatch, tmp_path):
+    """v2: an unreadable ledger cannot establish that P3009 was a deadlock."""
+    _stub_v2_env(monkeypatch, tmp_path)
+
+    stderr = (
+        "Error: P3009\n"
+        "migrate found failed migrations in the target database\n"
+        "The `20260415120000_health_check_latest_per_model_index` migration "
+        "started at 2026-09-01 18:46:13 UTC failed"
+    )
+    monkeypatch.setattr(ProxyExtrasDBManager, "_failed_migration_logs", lambda name: None)
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_roll_back_migration",
+        lambda name: pytest.fail("an unreadable ledger must not trigger a retry"),
+    )
+    monkeypatch.setattr("subprocess.run", _succeed_after(1, stderr))
+
+    with pytest.raises(RuntimeError, match="cannot be auto-recovered"):
+        ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+
+
+def test_v2_p3009_non_deadlock_ledger_row_still_raises(monkeypatch, tmp_path):
+    """v2: a failed ledger row whose logs show a real SQL error stays fatal."""
+    _stub_v2_env(monkeypatch, tmp_path)
+
+    stderr = (
+        "Error: P3009\n"
+        "migrate found failed migrations in the target database\n"
+        "The `20260101000000_genuinely_broken` migration started at "
+        "2026-09-01 18:46:13 UTC failed"
+    )
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_failed_migration_logs",
+        lambda name: 'ERROR: syntax error at or near "BRKN"',
+    )
+
+    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
+        with pytest.raises(RuntimeError, match="cannot be auto-recovered"):
+            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+
+
+def test_v2_bare_deadlock_stderr_retries(monkeypatch, tmp_path):
+    """v2: a deadlock reported without a Prisma error code (the advisory-lock
+    waiter as victim) is retried, not fatal."""
+    _stub_v2_env(monkeypatch, tmp_path)
+    monkeypatch.setattr(
+        "subprocess.run", _succeed_after(1, "Database error: deadlock detected")
+    )
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    assert ok is True
+
+
+_P1002_ADVISORY_LOCK_STDERR = (
+    "Error: P1002\n\n"
+    "The database server at `127.0.0.1`:`45743` was reached but timed out.\n\n"
+    "Context: Timed out trying to acquire a postgres advisory lock "
+    "(SELECT pg_advisory_lock(72707369)). Elapsed: 10000ms."
+)
+
+
+def test_v2_advisory_lock_timeout_retries(monkeypatch, tmp_path):
+    """v2: the advisory-lock waiter that times out while a peer's retry holds
+    the lock retries instead of dying."""
+    _stub_v2_env(monkeypatch, tmp_path)
+    monkeypatch.setattr("subprocess.run", _succeed_after(2, _P1002_ADVISORY_LOCK_STDERR))
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    assert ok is True
+
+
+def test_v2_p1002_without_advisory_lock_context_still_raises(monkeypatch, tmp_path):
+    """v2: a plain P1002 (database unreachable) stays fatal."""
+    _stub_v2_env(monkeypatch, tmp_path)
+    stderr = "Error: P1002\n\nThe database server at `db`:`5432` was reached but timed out."
+    monkeypatch.setattr("subprocess.run", _succeed_after(1, stderr))
+
+    with pytest.raises(RuntimeError, match="cannot be auto-recovered"):
+        ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
diff --git a/litellm-rust/AGENTS.md b/litellm-rust/AGENTS.md
index 36a5ad5a8f4..b8b6291283d 100644
--- a/litellm-rust/AGENTS.md
+++ b/litellm-rust/AGENTS.md
@@ -1,6 +1,6 @@
 # AGENTS.md
 
-litellm-rust has exactly THREE crates. A crate is a LAYER, not a route. Routes (ocr, realtime, chat) and providers (mistral, openai) are MODULES inside the layers.
+litellm-rust has four crates. A crate is a layer or shared foundation, not a route. Routes (ocr, realtime, chat) and providers (mistral, openai) are modules inside the layers.
 
 ## Crates
 
@@ -8,9 +8,10 @@ litellm-rust has exactly THREE crates. A crate is a LAYER, not a route. Routes (
 |-------|------|
 | litellm-core | The LiteLLM SDK in Rust. One public entrypoint per top-level call (`messages::messages()`), owning types, transforms, provider resolution, auth, and the provider HTTP call. Call it, get a typed response. |
 | litellm-ai-gateway | The axum server (behind the `server` feature) plus the WebSocket hosts. Translates HTTP/WS to core entrypoints; owns no provider logic and no handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. Owns API registration, domain wiring, and Python exception mapping. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 ## Where a route lives
 
@@ -28,7 +29,7 @@ core/src/messages/
 
 Handlers never live in `ai-gateway`. `ocr`, `audio_transcription`, and `realtime` are still hosted there from before this rule; they move to `core` as they are touched.
 
-Adding a crate: default to a MODULE. New crate ONLY on a real trigger — separate artifact (binary/cdylib), proc-macro, shared foundation, or publishable standalone. A new provider or route is none of these.
+Adding a crate: default to a module. A new crate requires a real trigger: separate artifact (binary/cdylib), proc-macro, shared foundation, or publishable standalone. A new provider or route is none of these.
 
 Adding a crate fails crates/core/tests/workspace_crate_allowlist.rs until you update its allowlist and this file — intentional.
 
diff --git a/litellm-rust/CLAUDE.md b/litellm-rust/CLAUDE.md
index fe6ceedbb86..3dcf1853efc 100644
--- a/litellm-rust/CLAUDE.md
+++ b/litellm-rust/CLAUDE.md
@@ -21,12 +21,13 @@ variants of it. The test for a good abstraction is that adding the next provider
 is a few declarative lines, not a new file of duplicated flow. Only diverge from
 the base when behavior is genuinely different, and say so explicitly in the PR.
 
-## Crates (exactly three — see AGENTS.md)
+## Crates (see AGENTS.md)
 
 `litellm-core` **is** the LiteLLM SDK in Rust: it makes the LLM call.
 `litellm-ai-gateway` is an HTTP/WebSocket server in front of it, and
-`litellm-python-bridge` exposes it to the Python SDK. A crate is a **layer**, not
-a route — add modules, not crates.
+`litellm-python-bridge` exposes it to the Python SDK. `litellm-python-interop`
+holds domain-neutral PyO3 primitives shared by Python-facing Rust code. A crate
+is a layer or shared foundation, not a route; add modules, not crates.
 
 ## Core Boundary
 
@@ -175,7 +176,7 @@ cd litellm-rust
 cargo fmt --check
 # the ai-gateway binary + server code is behind the `server` feature
 cargo clippy -p litellm-ai-gateway --all-targets --features server -- -D warnings
-cargo clippy -p litellm-core -p litellm-python-bridge --all-targets -- -D warnings
+cargo clippy -p litellm-core -p litellm-python-interop -p litellm-python-bridge --all-targets -- -D warnings
 cargo test --workspace
 ```
 
diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock
index 4388e561026..b3dac5ca935 100644
--- a/litellm-rust/Cargo.lock
+++ b/litellm-rust/Cargo.lock
@@ -919,6 +919,12 @@ version = "0.3.33"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b231ed28831efb4a61a08580c4bc233ec56bc009f4cd8f52da2c3cb97df0c109"
 
+[[package]]
+name = "futures-timer"
+version = "3.0.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "af43fadb8a98512d547e37b4e92e0ced13e205c061b87b4623eff01d918d6968"
+
 [[package]]
 name = "futures-util"
 version = "0.3.33"
@@ -972,6 +978,12 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "glob"
+version = "0.3.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e4eba85ea1d0a966a983acd07deee566e67395d2d96b6fb39e62b5a833f1eb0b"
+
 [[package]]
 name = "h2"
 version = "0.3.27"
@@ -1380,6 +1392,12 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "lazy_static"
+version = "1.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
+
 [[package]]
 name = "libc"
 version = "0.2.186"
@@ -1404,6 +1422,7 @@ dependencies = [
  "tokio",
  "tokio-tungstenite",
  "tower",
+ "tracing",
 ]
 
 [[package]]
@@ -1423,6 +1442,7 @@ dependencies = [
  "sha2 0.10.9",
  "thiserror 2.0.19",
  "tokio",
+ "tracing",
 ]
 
 [[package]]
@@ -1430,14 +1450,29 @@ name = "litellm-python-bridge"
 version = "0.1.0"
 dependencies = [
  "criterion",
+ "futures-util",
  "litellm-ai-gateway",
  "litellm-core",
+ "litellm-python-interop",
  "pyo3",
  "pyo3-async-runtimes",
- "pythonize",
  "serde",
  "serde_json",
  "tokio",
+ "tokio-tungstenite",
+ "tracing",
+ "tracing-subscriber",
+]
+
+[[package]]
+name = "litellm-python-interop"
+version = "0.1.0"
+dependencies = [
+ "pyo3",
+ "pythonize",
+ "rstest",
+ "serde",
+ "serde_json",
 ]
 
 [[package]]
@@ -1627,6 +1662,15 @@ dependencies = [
  "zerocopy",
 ]
 
+[[package]]
+name = "proc-macro-crate"
+version = "3.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f"
+dependencies = [
+ "toml_edit",
+]
+
 [[package]]
 name = "proc-macro2"
 version = "1.0.107"
@@ -1638,9 +1682,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3"
-version = "0.29.0"
+version = "0.29.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "cd274650b21d4bfc26a0a47587962c1edb425f69287324355cd040c3ea66071c"
+checksum = "4688ddedf473e32662b9b067670129a8afb8c18e351482c70d62ba4a88171e8b"
 dependencies = [
  "libc",
  "once_cell",
@@ -1666,18 +1710,18 @@ dependencies = [
 
 [[package]]
 name = "pyo3-build-config"
-version = "0.29.0"
+version = "0.29.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "c5e2a7d2f0d013342f295c048ad19237add5154a55b1c5a254c0ec93d4109078"
+checksum = "f41027e41b4bd03f6e60f9f417fe24a6341a6bb744edd62b6f709f2a52ea30e9"
 dependencies = [
  "target-lexicon",
 ]
 
 [[package]]
 name = "pyo3-ffi"
-version = "0.29.0"
+version = "0.29.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "ca85c467da1bbc8d866eea5deff9cf29ea5f7785054a17da36e65bda9c05845b"
+checksum = "e591a95526fead067432c3b3a33fc74770b87b1e04e73671090d9c2055a2b327"
 dependencies = [
  "libc",
  "pyo3-build-config",
@@ -1685,9 +1729,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3-macros"
-version = "0.29.0"
+version = "0.29.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "9ac53762fd065daa3194dd09337a38bd793a188100fd1a9304c4ab312d901771"
+checksum = "73225868fc1cd84eef2c3c230ddb91273bf1de46aeb8a4248da76d32a0924a1c"
 dependencies = [
  "proc-macro2",
  "pyo3-macros-backend",
@@ -1697,9 +1741,9 @@ dependencies = [
 
 [[package]]
 name = "pyo3-macros-backend"
-version = "0.29.0"
+version = "0.29.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "4ca3a1557399783172dc5bf39cfca835157732532cba56b71d2292161e53b362"
+checksum = "571575aa3749fa6216757dd47d2a3e7ef360f329a40f0666a9fbd14889024952"
 dependencies = [
  "heck",
  "proc-macro2",
@@ -1899,6 +1943,12 @@ version = "0.8.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "d6f6ff9a378485b298a5286656da665ba74413d36db0979633275d2e708145d4"
 
+[[package]]
+name = "relative-path"
+version = "1.9.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ba39f3699c378cd8970968dcbff9c43159ea4cfbd88d43c00b22f2ef10a435d2"
+
 [[package]]
 name = "reqwest"
 version = "0.12.28"
@@ -1956,6 +2006,35 @@ dependencies = [
  "windows-sys 0.52.0",
 ]
 
+[[package]]
+name = "rstest"
+version = "0.26.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f5a3193c063baaa2a95a33f03035c8a72b83d97a54916055ba22d35ed3839d49"
+dependencies = [
+ "futures-timer",
+ "futures-util",
+ "rstest_macros",
+]
+
+[[package]]
+name = "rstest_macros"
+version = "0.26.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9c845311f0ff7951c5506121a9ad75aec44d083c31583b2ea5a30bcb0b0abba0"
+dependencies = [
+ "cfg-if",
+ "glob",
+ "proc-macro-crate",
+ "proc-macro2",
+ "quote",
+ "regex",
+ "relative-path",
+ "rustc_version",
+ "syn 2.0.119",
+ "unicode-ident",
+]
+
 [[package]]
 name = "rustc-hash"
 version = "2.1.3"
@@ -2210,6 +2289,15 @@ dependencies = [
  "digest 0.11.3",
 ]
 
+[[package]]
+name = "sharded-slab"
+version = "0.1.7"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f40ca3c46823713e0d4209592e8d6e826aa57e928f09752619fc696c499637f6"
+dependencies = [
+ "lazy_static",
+]
+
 [[package]]
 name = "shlex"
 version = "2.0.1"
@@ -2348,6 +2436,15 @@ dependencies = [
  "syn 3.0.0",
 ]
 
+[[package]]
+name = "thread_local"
+version = "1.1.10"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1ad99c4c6d32803332c548b1af0540b357b3f5fc0be8f6c6bfe8b2e6ae784070"
+dependencies = [
+ "cfg-if",
+]
+
 [[package]]
 name = "time"
 version = "0.3.53"
@@ -2488,6 +2585,36 @@ dependencies = [
  "tokio",
 ]
 
+[[package]]
+name = "toml_datetime"
+version = "1.1.1+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7"
+dependencies = [
+ "serde_core",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.25.13+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6975367e4d2ef766d86af01ffad14b622fecc8d4357a998fbc4deb6e9bacaf9b"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "toml_parser",
+ "winnow",
+]
+
+[[package]]
+name = "toml_parser"
+version = "1.1.3+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1d38ac1cf9b95face32296c0a3ede1fdc270627c9d9c02a7274dd6d960dc4d56"
+dependencies = [
+ "winnow",
+]
+
 [[package]]
 name = "tower"
 version = "0.5.3"
@@ -2566,6 +2693,17 @@ dependencies = [
  "once_cell",
 ]
 
+[[package]]
+name = "tracing-subscriber"
+version = "0.3.23"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "cb7f578e5945fb242538965c2d0b04418d38ec25c79d160cd279bf0731c8d319"
+dependencies = [
+ "sharded-slab",
+ "thread_local",
+ "tracing-core",
+]
+
 [[package]]
 name = "try-lock"
 version = "0.2.5"
@@ -2903,6 +3041,15 @@ version = "0.52.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
 
+[[package]]
+name = "winnow"
+version = "1.0.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "23b97319f7b8343df12cc98938e5c3eb436064524c8d2b4e30a1d3a36eecdf81"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "writeable"
 version = "0.6.3"
diff --git a/litellm-rust/Cargo.toml b/litellm-rust/Cargo.toml
index 481ea3f8f66..a13dd4c04b0 100644
--- a/litellm-rust/Cargo.toml
+++ b/litellm-rust/Cargo.toml
@@ -2,6 +2,7 @@
 members = [
     "crates/core",
     "crates/ai-gateway",
+    "crates/python-interop",
     "crates/python-bridge",
 ]
 resolver = "2"
@@ -13,14 +14,18 @@ license = "MIT"
 repository = "https://github.com/BerriAI/litellm"
 
 [workspace.dependencies]
+tracing = "0.1"
+tracing-subscriber = { version = "0.3", default-features = false, features = ["registry", "std"] }
 litellm-core = { path = "crates/core" }
 litellm-ai-gateway = { path = "crates/ai-gateway", default-features = false }
+litellm-python-interop = { path = "crates/python-interop" }
 axum = "0.7"
-pyo3 = "0.29.0"
+pyo3 = "0.29.2"
 pyo3-async-runtimes = { version = "0.29.0", features = ["tokio-runtime"] }
 pythonize = "0.29.0"
 rand = "0.8"
 reqwest = { version = "0.12", default-features = false, features = ["blocking", "json", "rustls-tls", "http2", "stream"] }
+rstest = "0.26.1"
 serde = { version = "1.0", features = ["derive"] }
 serde_json = "1.0"
 sha2 = "0.10"
@@ -30,3 +35,12 @@ tokio = { version = "1", features = ["rt-multi-thread", "macros", "time", "net"]
 tokio-tungstenite = { version = "0.24", default-features = false, features = ["connect", "rustls-tls-native-roots"] }
 futures-util = { version = "0.3", default-features = false, features = ["sink", "std"] }
 base64 = "0.22"
+
+[profile.release]
+opt-level = 3
+lto = "thin"
+codegen-units = 1
+panic = "unwind"
+debug = false
+incremental = false
+strip = "symbols"
diff --git a/litellm-rust/README.md b/litellm-rust/README.md
index bcccf93300b..a0d79c6f0a5 100644
--- a/litellm-rust/README.md
+++ b/litellm-rust/README.md
@@ -26,9 +26,10 @@ coverage and production evidence.
 |-------|------|
 | litellm-core | The SDK. Per-route entrypoints (`messages::messages()`), types, provider transforms (modules under `providers/`), provider resolution, auth, the provider HTTP call, and the router. |
 | litellm-ai-gateway | The axum server (behind the `server` feature) and WebSocket hosts. Translates HTTP/WS to core entrypoints; no provider handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. Owns API registration, domain wiring, and Python exception mapping. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 ## Layout
 
@@ -38,7 +39,8 @@ crates/
     src/messages/   mod.rs (entrypoint), types, transformation, prepare, handler, client
     src/providers/anthropic/messages/transformation.rs
   ai-gateway/     Axum server + WebSocket hosts; calls core entrypoints.
-  python-bridge/  PyO3 bridge for Python LiteLLM.
+  python-interop/ Domain-neutral PyO3 conversion and GIL primitives.
+  python-bridge/  PyO3 API adapter for Python LiteLLM.
 ```
 
 The folder shape follows the Python provider tree:
diff --git a/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md b/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
index a1860d8a9c9..4a689cb9579 100644
--- a/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
+++ b/litellm-rust/crates/CODING_STANDARDS/PROVIDER_CODING_STANDARDS.md
@@ -54,6 +54,6 @@ Rules for adding or changing an LLM provider/route in `litellm-rust`. `messages`
     cd litellm-rust
     cargo fmt --check
     cargo clippy -p litellm-ai-gateway --all-targets --features server -- -D warnings
-    cargo clippy -p litellm-core -p litellm-python-bridge --all-targets -- -D warnings
+    cargo clippy -p litellm-core -p litellm-python-interop -p litellm-python-bridge --all-targets -- -D warnings
     cargo test --workspace
     ```
diff --git a/litellm-rust/crates/ai-gateway/Cargo.toml b/litellm-rust/crates/ai-gateway/Cargo.toml
index 541beabe170..e3dbdf24ce6 100644
--- a/litellm-rust/crates/ai-gateway/Cargo.toml
+++ b/litellm-rust/crates/ai-gateway/Cargo.toml
@@ -14,6 +14,7 @@ path = "src/main.rs"
 required-features = ["server"]
 
 [dependencies]
+tracing.workspace = true
 litellm-core = { workspace = true, features = ["bedrock-auth"] }
 # reqwest (rustls + json) is used by io/ocr and ships realtime logs to the
 # Python proxy callbacks API.
diff --git a/litellm-rust/crates/ai-gateway/README.md b/litellm-rust/crates/ai-gateway/README.md
index 7a6c620ee84..5cbb47220be 100644
--- a/litellm-rust/crates/ai-gateway/README.md
+++ b/litellm-rust/crates/ai-gateway/README.md
@@ -6,15 +6,16 @@ dials OpenAI upstream, and splices the two sockets frame-by-frame.
 
 ## Crates
 
-`litellm-rust` is exactly three crates (a crate is a **layer**, not a route):
+`litellm-rust` has four crates. A crate is a layer or shared foundation, not a route:
 
 | Crate | Role |
 |-------|------|
 | litellm-core | The LiteLLM SDK in Rust — per-route entrypoints (`messages::messages()`) that resolve the provider, transform, and make the call; plus types, provider transforms, and the router. |
 | litellm-ai-gateway | The Axum server (behind the `server` feature) and WebSocket hosts. Translates HTTP/WS to core entrypoints; no provider handlers. |
-| litellm-python-bridge | PyO3 cdylib exposing Rust to the litellm Python SDK — marshals Python objects and calls core entrypoints. |
+| litellm-python-interop | Domain-neutral PyO3 foundation for GIL handling and typed Python/Serde conversion. |
+| litellm-python-bridge | PyO3 cdylib exposing LiteLLM Rust APIs to the Python SDK. |
 
-Dependency direction (acyclic): litellm-core ← litellm-ai-gateway ← litellm-python-bridge.
+Dependency direction is acyclic: `litellm-python-bridge` depends on the domain layers and `litellm-python-interop`; the interop foundation depends on no LiteLLM domain crate.
 
 - **Client endpoint:** `wss://<host>/v1/realtime?model=<model>` (WebSocket)
 - **Auth:** `Authorization: Bearer $LITELLM_MASTER_KEY` (fails closed if unset)
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs
deleted file mode 100644
index 270d5c2d97a..00000000000
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/common_utils.rs
+++ /dev/null
@@ -1,48 +0,0 @@
-use std::collections::BTreeMap;
-
-use litellm_core::CoreResult;
-use litellm_core::audio_transcription::transformation::AudioTranscriptionProviderConfig;
-use litellm_core::error::CoreError;
-use litellm_core::providers::bedrock::audio_transcription::BEDROCK_AUDIO_TRANSCRIPTION_CONFIG;
-use serde_json::{Map, Value};
-
-pub(super) fn audio_transcription_provider_config(
-    provider: &str,
-) -> Option<&'static dyn AudioTranscriptionProviderConfig> {
-    match provider {
-        "bedrock" => Some(&BEDROCK_AUDIO_TRANSCRIPTION_CONFIG),
-        _ => None,
-    }
-}
-
-pub(super) fn string_headers(
-    headers: Option<Map<String, Value>>,
-) -> CoreResult<BTreeMap<String, String>> {
-    headers
-        .unwrap_or_default()
-        .into_iter()
-        .map(|(key, value)| {
-            value
-                .as_str()
-                .map(|value| (key.clone(), value.to_string()))
-                .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
-                        "audio transcription extra_headers.{key} must be a string"
-                    ))
-                })
-        })
-        .collect()
-}
-
-pub(super) fn has_header(headers: &BTreeMap<String, String>, name: &str) -> bool {
-    headers.keys().any(|key| key.eq_ignore_ascii_case(name))
-}
-
-pub(super) fn truncate_error_body(body: &str) -> String {
-    let truncated: String = body.chars().take(256).collect();
-    if truncated.chars().count() == body.chars().count() {
-        truncated
-    } else {
-        format!("{truncated}... (truncated)")
-    }
-}
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs
deleted file mode 100644
index 33c13550f58..00000000000
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/handler.rs
+++ /dev/null
@@ -1,89 +0,0 @@
-use std::time::SystemTime;
-
-use litellm_core::CoreResult;
-use litellm_core::audio_transcription::transformation::AudioTranscriptionAuth;
-use litellm_core::error::CoreError;
-use litellm_core::providers::bedrock::audio_transcription::aws_auth_config;
-use litellm_core::providers::bedrock::aws_base::{resolve_credentials, sign_bedrock_post};
-use serde_json::Value;
-
-use super::common_utils::truncate_error_body;
-use super::types::ProviderAudioTranscriptionRequest;
-use crate::client::http_client;
-
-pub(crate) async fn execute_audio_transcription_provider_call(
-    request: ProviderAudioTranscriptionRequest,
-) -> CoreResult<Value> {
-    let body = serde_json::to_vec(&request.body).map_err(|error| {
-        CoreError::InvalidRequest(format!("invalid audio request body: {error}"))
-    })?;
-    let mut request_builder = http_client().post(&request.url).body(body.clone());
-    for (key, value) in &request.upstream_headers {
-        request_builder = request_builder.header(key, value);
-    }
-    if let Some(duration) = request.timeout {
-        request_builder = request_builder.timeout(duration);
-    }
-    let response = request_builder
-        .send()
-        .await
-        .map_err(|error| CoreError::Network(error.to_string()))?;
-    let status = response.status();
-    let text = response
-        .text()
-        .await
-        .map_err(|error| CoreError::Network(error.to_string()))?;
-    if !status.is_success() {
-        return Err(CoreError::Http {
-            status: status.as_u16(),
-            body: truncate_error_body(&text),
-        });
-    }
-    let response_json: Value = serde_json::from_str(&text).map_err(|error| {
-        CoreError::InvalidResponse(format!("invalid audio response JSON: {error}"))
-    })?;
-    Ok(request
-        .config
-        .transform_transcription_response(&request.model, response_json)?
-        .into_json())
-}
-
-pub(crate) async fn sign_request(
-    request: &ProviderAudioTranscriptionRequest,
-    optional_params: &serde_json::Map<String, Value>,
-) -> CoreResult<ProviderAudioTranscriptionRequest> {
-    let env_lookup = environment_lookup;
-    let auth = request
-        .config
-        .auth_strategy(&request.model, optional_params, &env_lookup)?;
-    let body = serde_json::to_vec(&request.body).map_err(|error| {
-        CoreError::InvalidRequest(format!("invalid audio request body: {error}"))
-    })?;
-    let mut headers = super::common_utils::string_headers(None)?;
-    headers.insert("Content-Type".to_string(), "application/json".to_string());
-    headers.extend(request.upstream_headers.iter().cloned());
-    match auth {
-        AudioTranscriptionAuth::Bearer => {}
-        AudioTranscriptionAuth::AwsSigV4 { region, .. } => {
-            let credentials =
-                resolve_credentials(aws_auth_config(optional_params, &env_lookup), &env_lookup)
-                    .await?;
-            headers.extend(sign_bedrock_post(
-                &request.url,
-                &body,
-                &headers,
-                &region,
-                &credentials,
-                SystemTime::now(),
-            )?);
-        }
-    }
-    Ok(ProviderAudioTranscriptionRequest {
-        upstream_headers: headers.into_iter().collect(),
-        ..request.clone()
-    })
-}
-
-pub(super) fn environment_lookup(key: &str) -> Option<String> {
-    std::env::var(key).ok()
-}
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
index 0c9faeda6e7..dbe2d3a325b 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/hooks.rs
@@ -1,15 +1,14 @@
+use litellm_core::audio_transcription::{
+    AudioTranscriptionRequest as CoreAudioTranscriptionRequest, ProviderAudioTranscriptionRequest,
+    prepare_audio_transcription_provider_call,
+};
+use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
+use litellm_core::error::Error;
+use serde_json::{Map, Value, json};
 use std::future::Future;
 use std::pin::Pin;
 
-use litellm_core::CoreResult;
-use litellm_core::audio_transcription::transformation::AudioTranscriptionAuth;
-use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
-use litellm_core::error::CoreError;
-use serde_json::{Map, Value, json};
-
-use super::common_utils::{audio_transcription_provider_config, has_header, string_headers};
-use super::handler::sign_request;
-use super::types::{PreparedAudioTranscriptionRequest, ProviderAudioTranscriptionRequest};
+use super::types::PreparedAudioTranscriptionRequest;
 use crate::integrations::custom_guardrail::{
     CustomGuardrailRunner, GuardrailContext, GuardrailError, GuardrailRequest,
 };
@@ -26,7 +25,7 @@ pub(crate) struct AudioTranscriptionLifecycleHooks {
     request_metadata: RequestMetadata,
 }
 
-type AudioFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type AudioFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 type AudioLogFuture<'a> = Pin<Box<dyn Future<Output = ()> + Send + 'a>>;
 
 impl AudioTranscriptionLifecycleHooks {
@@ -45,7 +44,7 @@ impl AudioTranscriptionLifecycleHooks {
     async fn run_pre_call_guardrails(
         &self,
         request: PreparedAudioTranscriptionRequest,
-    ) -> CoreResult<PreparedAudioTranscriptionRequest> {
+    ) -> Result<PreparedAudioTranscriptionRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -63,17 +62,17 @@ impl AudioTranscriptionLifecycleHooks {
             .await
             .map_err(guardrail_error_to_core_error)?;
         let Value::Object(mut data) = guardrail_request.data else {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "audio transcription pre_call guardrail must return an object".to_string(),
             ));
         };
         let audio = data.remove("audio").ok_or_else(|| {
-            CoreError::InvalidRequest("audio transcription guardrail removed audio".to_string())
+            Error::InvalidRequest("audio transcription guardrail removed audio".to_string())
         })?;
         let optional_params = match data.remove("optional_params") {
             Some(Value::Object(value)) => value,
             Some(_) => {
-                return Err(CoreError::InvalidRequest(
+                return Err(Error::InvalidRequest(
                     "audio transcription optional_params must be an object".to_string(),
                 ));
             }
@@ -89,53 +88,36 @@ impl AudioTranscriptionLifecycleHooks {
     async fn prepare_provider_request(
         &self,
         request: PreparedAudioTranscriptionRequest,
-    ) -> CoreResult<ProviderAudioTranscriptionRequest> {
-        let config = audio_transcription_provider_config(&request.custom_llm_provider)
-            .ok_or_else(|| CoreError::InvalidProvider(request.custom_llm_provider.clone()))?;
-        let env_lookup = super::handler::environment_lookup;
-        let headers = string_headers(request.extra_headers)?;
-        let url = config.complete_url(
-            request.api_base.as_deref(),
-            &request.model,
-            &request.optional_params,
-            &env_lookup,
-        )?;
-        let filtered_params = config.map_transcription_params(&request.optional_params);
-        let body = config.transform_transcription_request(
-            &request.model,
-            request.audio,
-            filtered_params,
-        )?;
-        let auth = config.auth_strategy(&request.model, &request.optional_params, &env_lookup)?;
-        let mut upstream_headers = headers.into_iter().collect::<Vec<_>>();
-        if matches!(auth, AudioTranscriptionAuth::Bearer)
-            && !has_header(
-                &upstream_headers
-                    .iter()
-                    .cloned()
-                    .collect::<std::collections::BTreeMap<_, _>>(),
-                "authorization",
-            )
-            && let Some(api_key) = request.api_key.as_deref()
-        {
-            upstream_headers.push(("Authorization".to_string(), format!("Bearer {api_key}")));
-        }
-        let provider_request = ProviderAudioTranscriptionRequest {
-            model: request.model,
-            config,
-            url,
-            body: body.body,
-            upstream_headers,
-            timeout: request.timeout,
-        };
-        let provider_request = self.run_during_call_guardrails(provider_request).await?;
-        sign_request(&provider_request, &request.optional_params).await
+    ) -> Result<ProviderAudioTranscriptionRequest, Error> {
+        let PreparedAudioTranscriptionRequest {
+            model,
+            custom_llm_provider,
+            audio,
+            api_key,
+            api_base,
+            extra_headers,
+            optional_params,
+            timeout,
+            ..
+        } = request;
+        let provider_request =
+            prepare_audio_transcription_provider_call(CoreAudioTranscriptionRequest {
+                model: &model,
+                audio,
+                api_key: api_key.as_deref(),
+                api_base: api_base.as_deref(),
+                custom_llm_provider: Some(&custom_llm_provider),
+                extra_headers,
+                optional_params,
+                timeout,
+            })?;
+        self.run_during_call_guardrails(provider_request).await
     }
 
     async fn run_during_call_guardrails(
         &self,
         request: ProviderAudioTranscriptionRequest,
-    ) -> CoreResult<ProviderAudioTranscriptionRequest> {
+    ) -> Result<ProviderAudioTranscriptionRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -144,23 +126,23 @@ impl AudioTranscriptionLifecycleHooks {
             .run_during_call(
                 &guardrail_context(&self.request_metadata),
                 GuardrailRequest::new(json!({
-                    "model": request.model,
-                    "custom_llm_provider": "bedrock",
-                    "url": request.url,
-                    "body": request.body,
+                    "model": request.model(),
+                    "custom_llm_provider": request.custom_llm_provider(),
+                    "url": request.url(),
+                    "body": request.body(),
                 })),
             )
             .await
             .map_err(guardrail_error_to_core_error)?;
         let Value::Object(mut data) = guardrail_request.data else {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "audio transcription during_call guardrail must return an object".to_string(),
             ));
         };
         let body = data.remove("body").ok_or_else(|| {
-            CoreError::InvalidRequest("audio transcription guardrail removed body".to_string())
+            Error::InvalidRequest("audio transcription guardrail removed body".to_string())
         })?;
-        Ok(ProviderAudioTranscriptionRequest { body, ..request })
+        Ok(request.with_body(body))
     }
 
     fn logging_payload(
@@ -241,7 +223,7 @@ impl CallLifecycleHooks<PreparedAudioTranscriptionRequest, ProviderAudioTranscri
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -281,22 +263,22 @@ fn guardrail_context(metadata: &RequestMetadata) -> GuardrailContext {
     }
 }
 
-fn guardrail_error_to_core_error(error: GuardrailError) -> CoreError {
-    CoreError::InvalidRequest(format!("{}: {}", error.kind, error.message))
+fn guardrail_error_to_core_error(error: GuardrailError) -> Error {
+    Error::InvalidRequest(format!("{}: {}", error.kind, error.message))
 }
 
-fn core_error_kind(error: &CoreError) -> &'static str {
+fn core_error_kind(error: &Error) -> &'static str {
     match error {
-        CoreError::Auth(_) => "AuthError",
-        CoreError::InvalidProvider(_) => "InvalidProvider",
-        CoreError::InvalidRequest(_) => "InvalidRequest",
-        CoreError::InvalidType { .. } => "InvalidType",
-        CoreError::MissingField(_) => "MissingField",
-        CoreError::Http { .. } => "HttpError",
-        CoreError::InvalidResponse(_) => "InvalidResponse",
-        CoreError::Network(_) => "NetworkError",
-        CoreError::Connect(_) => "ConnectError",
-        CoreError::Routing(_) => "RoutingError",
-        CoreError::Unsupported(_) => "UnsupportedRequest",
+        Error::Auth(_) => "AuthError",
+        Error::InvalidProvider(_) => "InvalidProvider",
+        Error::InvalidRequest(_) => "InvalidRequest",
+        Error::InvalidType { .. } => "InvalidType",
+        Error::MissingField(_) => "MissingField",
+        Error::Http { .. } => "HttpError",
+        Error::InvalidResponse(_) => "InvalidResponse",
+        Error::Network(_) => "NetworkError",
+        Error::Connect(_) => "ConnectError",
+        Error::Routing(_) => "RoutingError",
+        Error::Unsupported(_) => "UnsupportedRequest",
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
index 5d33d912c40..03d621b8414 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/mod.rs
@@ -1,19 +1,17 @@
-use litellm_core::CoreResult;
+use litellm_core::Error;
+use litellm_core::audio_transcription::execute_audio_transcription_provider_call;
 use litellm_core::call_lifecycle::CallLifecycle;
 use serde_json::Value;
 
-mod common_utils;
-mod handler;
 mod hooks;
 mod prepare;
 mod types;
 
 pub use types::AudioTranscriptionRequest;
 
-use handler::execute_audio_transcription_provider_call;
 use prepare::{PreparedAudioTranscriptionCall, prepare_audio_transcription_call};
 
-pub async fn audio_transcription(request: AudioTranscriptionRequest<'_>) -> CoreResult<Value> {
+pub async fn audio_transcription(request: AudioTranscriptionRequest<'_>) -> Result<Value, Error> {
     let PreparedAudioTranscriptionCall { request, hooks } =
         prepare_audio_transcription_call(request);
     CallLifecycle::default()
diff --git a/litellm-rust/crates/ai-gateway/src/audio_transcription/types.rs b/litellm-rust/crates/ai-gateway/src/audio_transcription/types.rs
index 9697aa98b0a..b470638264e 100644
--- a/litellm-rust/crates/ai-gateway/src/audio_transcription/types.rs
+++ b/litellm-rust/crates/ai-gateway/src/audio_transcription/types.rs
@@ -1,7 +1,6 @@
 use std::sync::Arc;
 use std::time::Duration;
 
-use litellm_core::audio_transcription::transformation::AudioTranscriptionProviderConfig;
 use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleRequest};
 use serde_json::{Map, Value};
 
@@ -46,13 +45,3 @@ impl CallLifecycleRequest for PreparedAudioTranscriptionRequest {
         )
     }
 }
-
-#[derive(Clone)]
-pub(crate) struct ProviderAudioTranscriptionRequest {
-    pub(crate) model: String,
-    pub(crate) config: &'static dyn AudioTranscriptionProviderConfig,
-    pub(crate) url: String,
-    pub(crate) body: Value,
-    pub(crate) upstream_headers: Vec<(String, String)>,
-    pub(crate) timeout: Option<Duration>,
-}
diff --git a/litellm-rust/crates/ai-gateway/src/io/realtime.rs b/litellm-rust/crates/ai-gateway/src/io/realtime.rs
index 845e7bf9527..662f7328982 100644
--- a/litellm-rust/crates/ai-gateway/src/io/realtime.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/realtime.rs
@@ -15,8 +15,7 @@ use std::time::Duration;
 
 use futures_util::stream::{SplitSink, SplitStream};
 use futures_util::{Sink, SinkExt, Stream, StreamExt};
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::realtime::transformation::RealtimeProviderConfig;
 use litellm_core::realtime::types::RealtimeEvent;
 use tokio::net::TcpStream;
@@ -48,7 +47,7 @@ pub(crate) type UpstreamRx = SplitStream<UpstreamWs>;
 /// Resolve the OpenAI API key from the explicit param or the environment.
 ///
 /// Blank/whitespace values are treated as absent (guard at resolution time).
-pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
+pub(crate) fn resolve_api_key(api_key: Option<&str>) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
@@ -58,7 +57,7 @@ pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
                 .ok()
                 .filter(|key| !key.trim().is_empty())
         })
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 /// Open the upstream WebSocket to OpenAI for `(model, api_key, api_base)`.
@@ -70,24 +69,24 @@ pub(crate) async fn dial_upstream(
     model: &str,
     api_key: &str,
     api_base: Option<&str>,
-) -> CoreResult<UpstreamWs> {
+) -> Result<UpstreamWs, Error> {
     let url = OPENAI_REALTIME_CONFIG.complete_url(api_base, model);
 
     let mut request = url
         .as_str()
         .into_client_request()
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     // GA realtime: only Authorization. The legacy OpenAI-Beta header triggers
     // beta_api_shape_disabled, so we do not send it.
     request.headers_mut().insert(
         AUTHORIZATION,
         HeaderValue::from_str(&format!("Bearer {api_key}"))
-            .map_err(|err| CoreError::Auth(err.to_string()))?,
+            .map_err(|err| Error::Auth(err.to_string()))?,
     );
 
     let (upstream, _response) = connect_async(request)
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     Ok(upstream)
 }
 
@@ -96,22 +95,22 @@ pub(crate) async fn dial_upstream(
 /// Used by the pool to pre-read OpenAI's unprompted `session.created`. Returns an
 /// error on a non-text frame, a closed socket, or undecodable JSON so the pool can
 /// discard a misbehaving socket rather than warm it.
-pub(crate) async fn read_event(upstream_rx: &mut UpstreamRx) -> CoreResult<RealtimeEvent> {
+pub(crate) async fn read_event(upstream_rx: &mut UpstreamRx) -> Result<RealtimeEvent, Error> {
     loop {
         let message = upstream_rx
             .next()
             .await
-            .ok_or_else(|| CoreError::Network("upstream closed before first event".to_string()))?
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .ok_or_else(|| Error::Network("upstream closed before first event".to_string()))?
+            .map_err(|err| Error::Network(err.to_string()))?;
         match message {
             Message::Text(text) => {
                 return serde_json::from_str(&text)
-                    .map_err(|err| CoreError::InvalidResponse(err.to_string()));
+                    .map_err(|err| Error::InvalidResponse(err.to_string()));
             }
             // Ignore protocol frames (ping/pong) while waiting for the first event.
             Message::Ping(_) | Message::Pong(_) => continue,
             Message::Close(_) => {
-                return Err(CoreError::Network(
+                return Err(Error::Network(
                     "upstream closed before first event".to_string(),
                 ));
             }
@@ -139,7 +138,7 @@ pub(crate) async fn splice<In, Out>(
     mut observe: impl FnMut(&RealtimeEvent) + Send,
     mut client_in: In,
     mut client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
@@ -154,7 +153,7 @@ where
             client_out
                 .send(outbound)
                 .await
-                .map_err(|err| CoreError::Network(err.to_string()))?;
+                .map_err(|err| Error::Network(err.to_string()))?;
         }
     }
 
@@ -175,26 +174,26 @@ where
                 // inflate its own spend log. Logging observes upstream events only.
                 for outbound in config.transform_realtime_request(&event, model)?.events {
                     let payload = serde_json::to_string(&outbound)
-                        .map_err(|err| CoreError::InvalidResponse(err.to_string()))?;
+                        .map_err(|err| Error::InvalidResponse(err.to_string()))?;
                     upstream_tx
                         .send(Message::Text(payload))
                         .await
-                        .map_err(|err| CoreError::Network(err.to_string()))?;
+                        .map_err(|err| Error::Network(err.to_string()))?;
                 }
             }
             // upstream -> client
             upstream_message = upstream_rx.next() => {
                 let Some(message) = upstream_message else { break }; // upstream closed
-                match message.map_err(|err| CoreError::Network(err.to_string()))? {
+                match message.map_err(|err| Error::Network(err.to_string()))? {
                     Message::Text(text) => {
                         let event: RealtimeEvent = serde_json::from_str(&text)
-                            .map_err(|err| CoreError::InvalidResponse(err.to_string()))?;
+                            .map_err(|err| Error::InvalidResponse(err.to_string()))?;
                         observe(&event);
                         for outbound in config.transform_realtime_response(&event, model)?.events {
                             client_out
                                 .send(outbound)
                                 .await
-                                .map_err(|err| CoreError::Network(err.to_string()))?;
+                                .map_err(|err| Error::Network(err.to_string()))?;
                         }
                     }
                     Message::Close(_) => break,
@@ -225,7 +224,7 @@ pub async fn realtime<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
@@ -258,7 +257,7 @@ pub async fn realtime_warm<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
diff --git a/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs b/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
index 4a1a3cd1166..49e9c459a88 100644
--- a/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/realtime_pool.rs
@@ -28,7 +28,7 @@ use std::sync::{Arc, Mutex};
 use std::time::{Duration, Instant};
 
 use futures_util::StreamExt;
-use litellm_core::CoreResult;
+use litellm_core::Error;
 use litellm_core::realtime::types::RealtimeEvent;
 
 use crate::io::realtime::{
@@ -438,7 +438,7 @@ impl RealtimePool {
 ///
 /// `key.api_key` is already resolved (non-blank). The first frame OpenAI sends
 /// unprompted is `session.created`; we buffer exactly that and read nothing more.
-async fn warm_one(key: &UpstreamKey) -> CoreResult<WarmConnection> {
+async fn warm_one(key: &UpstreamKey) -> Result<WarmConnection, Error> {
     let upstream: UpstreamWs =
         dial_upstream(&key.model, &key.api_key, key.api_base.as_deref()).await?;
     let (tx, mut rx) = upstream.split();
diff --git a/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs b/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
index 9b51019f4bc..0b01747b1a5 100644
--- a/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
+++ b/litellm-rust/crates/ai-gateway/src/io/responses_ws.rs
@@ -4,10 +4,10 @@ use std::time::Duration;
 
 use futures_util::stream::{SplitSink, SplitStream};
 use futures_util::{Sink, SinkExt, Stream, StreamExt};
+use litellm_core::Error;
 use litellm_core::providers::openai::responses::transformation::OPENAI_RESPONSES_WS_CONFIG;
 use litellm_core::responses::types::ResponsesWsEvent;
 use litellm_core::responses::websocket::ResponsesWebSocketProviderConfig;
-use litellm_core::{CoreError, CoreResult};
 use tokio::net::TcpStream;
 use tokio::sync::Mutex;
 use tokio_tungstenite::tungstenite::Message;
@@ -37,51 +37,49 @@ impl ResponsesWebSocketConnection {
         url: &str,
         headers: &HashMap<String, String>,
         timeout: Option<Duration>,
-    ) -> CoreResult<Self> {
+    ) -> Result<Self, Error> {
         let mut request = url
             .into_client_request()
-            .map_err(|error| CoreError::Network(error.to_string()))?;
+            .map_err(|error| Error::Network(error.to_string()))?;
         for (name, value) in headers {
             let header_name = name
                 .parse::<HeaderName>()
-                .map_err(|error| CoreError::InvalidRequest(error.to_string()))?;
+                .map_err(|error| Error::InvalidRequest(error.to_string()))?;
             let header_value = HeaderValue::from_str(value)
-                .map_err(|error| CoreError::InvalidRequest(error.to_string()))?;
+                .map_err(|error| Error::InvalidRequest(error.to_string()))?;
             request.headers_mut().insert(header_name, header_value);
         }
         let connect = connect_async(request);
         let result = match timeout {
             Some(timeout) => tokio::time::timeout(timeout, connect).await.map_err(|_| {
-                CoreError::Network("Responses WebSocket connection timed out".to_string())
+                Error::Network("Responses WebSocket connection timed out".to_string())
             })?,
             None => connect.await,
         };
         let (socket, _) = result.map_err(|error| match error {
-            tokio_tungstenite::tungstenite::Error::Http(response) => CoreError::Http {
+            tokio_tungstenite::tungstenite::Error::Http(response) => Error::Http {
                 status: response.status().as_u16(),
                 body: String::new(),
             },
-            other => CoreError::Network(other.to_string()),
+            other => Error::Network(other.to_string()),
         })?;
         Ok(Self {
             socket: Arc::new(Mutex::new(Some(socket))),
         })
     }
 
-    pub async fn send_text(&self, text: String) -> CoreResult<()> {
+    pub async fn send_text(&self, text: String) -> Result<(), Error> {
         let mut socket = self.socket.lock().await;
         let Some(socket) = socket.as_mut() else {
-            return Err(CoreError::Network(
-                "Responses WebSocket is closed".to_string(),
-            ));
+            return Err(Error::Network("Responses WebSocket is closed".to_string()));
         };
         socket
             .send(Message::Text(text))
             .await
-            .map_err(|error| CoreError::Network(error.to_string()))
+            .map_err(|error| Error::Network(error.to_string()))
     }
 
-    pub async fn recv_text(&self) -> CoreResult<Option<String>> {
+    pub async fn recv_text(&self) -> Result<Option<String>, Error> {
         let mut socket_guard = self.socket.lock().await;
         let Some(socket) = socket_guard.as_mut() else {
             return Ok(None);
@@ -90,27 +88,27 @@ impl ResponsesWebSocketConnection {
             Some(Ok(Message::Text(text))) => Ok(Some(text)),
             Some(Ok(Message::Binary(bytes))) => String::from_utf8(bytes.to_vec())
                 .map(Some)
-                .map_err(|error| CoreError::InvalidResponse(error.to_string())),
+                .map_err(|error| Error::InvalidResponse(error.to_string())),
             Some(Ok(Message::Close(_))) | None => Ok(None),
             Some(Ok(_)) => Ok(None),
-            Some(Err(error)) => Err(CoreError::Network(error.to_string())),
+            Some(Err(error)) => Err(Error::Network(error.to_string())),
         }
     }
 
-    pub async fn close(&self) -> CoreResult<()> {
+    pub async fn close(&self) -> Result<(), Error> {
         let mut socket = self.socket.lock().await;
         if let Some(socket) = socket.as_mut() {
             socket
                 .close(None)
                 .await
-                .map_err(|error| CoreError::Network(error.to_string()))?;
+                .map_err(|error| Error::Network(error.to_string()))?;
         }
         *socket = None;
         Ok(())
     }
 }
 
-pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
+pub(crate) fn resolve_api_key(api_key: Option<&str>) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|value| !value.is_empty())
@@ -120,38 +118,38 @@ pub(crate) fn resolve_api_key(api_key: Option<&str>) -> CoreResult<String> {
                 .ok()
                 .filter(|value| !value.trim().is_empty())
         })
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 async fn dial_upstream(
     model: &str,
     api_key: &str,
     api_base: Option<&str>,
-) -> CoreResult<ResponsesUpstreamWs> {
+) -> Result<ResponsesUpstreamWs, Error> {
     let url = OPENAI_RESPONSES_WS_CONFIG.complete_websocket_url(api_base, model);
     let mut request = url
         .as_str()
         .into_client_request()
-        .map_err(|error| CoreError::Network(error.to_string()))?;
+        .map_err(|error| Error::Network(error.to_string()))?;
     request.headers_mut().insert(
         AUTHORIZATION,
         HeaderValue::from_str(&format!("Bearer {api_key}"))
-            .map_err(|error| CoreError::Auth(error.to_string()))?,
+            .map_err(|error| Error::Auth(error.to_string()))?,
     );
     let result = tokio::time::timeout(
         Duration::from_secs(DEFAULT_RESPONSES_WS_CONNECT_TIMEOUT_SECS),
         connect_async(request),
     )
     .await
-    .map_err(|_| CoreError::Network("Responses WebSocket connection timed out".to_string()))?;
+    .map_err(|_| Error::Network("Responses WebSocket connection timed out".to_string()))?;
     result
         .map(|(socket, _)| socket)
         .map_err(|error| match error {
-            tokio_tungstenite::tungstenite::Error::Http(response) => CoreError::Http {
+            tokio_tungstenite::tungstenite::Error::Http(response) => Error::Http {
                 status: response.status().as_u16(),
                 body: String::new(),
             },
-            other => CoreError::Network(other.to_string()),
+            other => Error::Network(other.to_string()),
         })
 }
 
@@ -166,7 +164,7 @@ impl ResponsesWebSocketStreaming {
         observe: impl FnMut(&ResponsesWsEvent) + Send,
         client_in: In,
         client_out: Out,
-    ) -> CoreResult<()>
+    ) -> Result<(), Error>
     where
         In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
         Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -193,7 +191,7 @@ pub(crate) async fn splice<In, Out>(
     mut observe: impl FnMut(&ResponsesWsEvent) + Send,
     mut client_in: In,
     mut client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -210,18 +208,18 @@ where
                     .events
                 {
                     let payload = serde_json::to_string(&outbound)
-                        .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                        .map_err(|error| Error::InvalidResponse(error.to_string()))?;
                     upstream_tx.send(Message::Text(payload))
                         .await
-                        .map_err(|error| CoreError::Network(error.to_string()))?;
+                        .map_err(|error| Error::Network(error.to_string()))?;
                 }
             }
             message = upstream_rx.next() => {
                 let Some(message) = message else { break };
-                match message.map_err(|error| CoreError::Network(error.to_string()))? {
+                match message.map_err(|error| Error::Network(error.to_string()))? {
                     Message::Text(text) => {
                         let event = serde_json::from_str::<ResponsesWsEvent>(&text)
-                            .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                            .map_err(|error| Error::InvalidResponse(error.to_string()))?;
                         observe(&event);
                         for outbound in OPENAI_RESPONSES_WS_CONFIG
                             .transform_ws_response(&event, model)?
@@ -229,7 +227,7 @@ where
                         {
                             client_out.send(outbound)
                                 .await
-                                .map_err(|error| CoreError::Network(error.to_string()))?;
+                                .map_err(|error| Error::Network(error.to_string()))?;
                         }
                     }
                     Message::Close(_) => break,
@@ -252,7 +250,7 @@ pub async fn async_responses_websocket<In, Out>(
     mut observe: impl FnMut(&ResponsesWsEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -267,11 +265,11 @@ where
             .events
         {
             let payload = serde_json::to_string(&outbound)
-                .map_err(|error| CoreError::InvalidResponse(error.to_string()))?;
+                .map_err(|error| Error::InvalidResponse(error.to_string()))?;
             upstream_tx
                 .send(Message::Text(payload))
                 .await
-                .map_err(|error| CoreError::Network(error.to_string()))?;
+                .map_err(|error| Error::Network(error.to_string()))?;
         }
     }
     ResponsesWebSocketStreaming::bidirectional_forward(
@@ -296,7 +294,7 @@ pub async fn responses_ws<In, Out>(
     observe: impl FnMut(&ResponsesWsEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
@@ -514,7 +512,7 @@ mod tests {
         )
         .await
         .expect_err("status error");
-        assert!(matches!(error, CoreError::Http { status: 401, .. }));
+        assert!(matches!(error, Error::Http { status: 401, .. }));
         server.await.expect("server task");
     }
 
@@ -543,7 +541,7 @@ mod tests {
         )
         .await
         .expect_err("status error");
-        assert!(matches!(error, CoreError::Http { status: 500, .. }));
+        assert!(matches!(error, Error::Http { status: 500, .. }));
         server.await.expect("server task");
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs b/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
index 9bc2818b6e7..c1fb328893b 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/common_utils.rs
@@ -3,8 +3,7 @@ use std::time::{Duration, Instant};
 
 use base64::Engine;
 use base64::engine::general_purpose::STANDARD as BASE64_STANDARD;
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::ocr::transformation::OcrProviderConfig;
 use reqwest::Url;
 use serde_json::{Map, Value};
@@ -33,6 +32,7 @@ pub(super) fn truncate_error_body(body: &str) -> String {
     format!("{truncated}... (truncated)")
 }
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(super) fn ocr_provider_config(
     provider: &str,
     model: &str,
@@ -56,7 +56,7 @@ fn is_azure_document_intelligence_model(model: &str) -> bool {
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     extra_headers
         .unwrap_or_default()
         .into_iter()
@@ -65,7 +65,7 @@ pub(super) fn string_headers(
                 .as_str()
                 .map(|value| (key.clone(), value.to_string()))
                 .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
+                    Error::InvalidRequest(format!(
                         "OCR extra_headers.{key} must be a string, got {}",
                         litellm_core::error::json_type_name(&value)
                     ))
@@ -74,13 +74,7 @@ pub(super) fn string_headers(
         .collect()
 }
 
-pub(super) fn has_header(headers: &[(String, String)], name: &str) -> bool {
-    headers
-        .iter()
-        .any(|(key, _)| key.eq_ignore_ascii_case(name))
-}
-
-fn document_url_field(document: &Value) -> CoreResult<Option<(&str, &str)>> {
+fn document_url_field(document: &Value) -> Result<Option<(&str, &str)>, Error> {
     let Some(object) = document.as_object() else {
         return Ok(None);
     };
@@ -138,13 +132,13 @@ fn is_blocked_ip(ip: IpAddr) -> bool {
     }
 }
 
-fn blocked_url_error(url: &Url) -> CoreError {
-    CoreError::InvalidRequest(format!(
+fn blocked_url_error(url: &Url) -> Error {
+    Error::InvalidRequest(format!(
         "OCR document URL rejected by SSRF protection: {url}"
     ))
 }
 
-async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
+async fn validate_safe_fetch_url(url: &Url) -> Result<(), Error> {
     if !matches!(url.scheme(), "http" | "https") {
         return Err(blocked_url_error(url));
     }
@@ -162,7 +156,7 @@ async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
         .ok_or_else(|| blocked_url_error(url))?;
     let addresses = tokio::net::lookup_host((host, port))
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let mut saw_address = false;
     for address in addresses {
         saw_address = true;
@@ -176,25 +170,25 @@ async fn validate_safe_fetch_url(url: &Url) -> CoreResult<()> {
     Ok(())
 }
 
-fn redirect_location(response: &reqwest::Response, url: &Url) -> CoreResult<Url> {
+fn redirect_location(response: &reqwest::Response, url: &Url) -> Result<Url, Error> {
     let location = response
         .headers()
         .get(reqwest::header::LOCATION)
         .and_then(|value| value.to_str().ok())
         .ok_or_else(|| {
-            CoreError::InvalidResponse("OCR document redirect missing Location header".to_string())
+            Error::InvalidResponse("OCR document redirect missing Location header".to_string())
         })?;
     url.join(location)
-        .map_err(|err| CoreError::InvalidResponse(format!("invalid OCR document redirect: {err}")))
+        .map_err(|err| Error::InvalidResponse(format!("invalid OCR document redirect: {err}")))
 }
 
-async fn safe_get_document_url(url: &str) -> CoreResult<(Url, reqwest::Response)> {
+async fn safe_get_document_url(url: &str) -> Result<(Url, reqwest::Response), Error> {
     let client = reqwest::Client::builder()
         .redirect(reqwest::redirect::Policy::none())
         .build()
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let mut current_url = Url::parse(url)
-        .map_err(|err| CoreError::InvalidRequest(format!("invalid OCR document URL: {err}")))?;
+        .map_err(|err| Error::InvalidRequest(format!("invalid OCR document URL: {err}")))?;
 
     for _ in 0..MAX_SAFE_FETCH_REDIRECTS {
         validate_safe_fetch_url(&current_url).await?;
@@ -202,28 +196,28 @@ async fn safe_get_document_url(url: &str) -> CoreResult<(Url, reqwest::Response)
             .get(current_url.clone())
             .send()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         if !response.status().is_redirection() {
             return Ok((current_url, response));
         }
         current_url = redirect_location(&response, &current_url)?;
     }
 
-    Err(CoreError::InvalidRequest(
+    Err(Error::InvalidRequest(
         "Too many redirects while fetching OCR document URL".to_string(),
     ))
 }
 
-fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> CoreResult<()> {
+fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> Result<(), Error> {
     if max_bytes == 0 {
-        return Err(CoreError::InvalidRequest(format!(
+        return Err(Error::InvalidRequest(format!(
             "OCR document URL download is disabled (MAX_IMAGE_URL_DOWNLOAD_SIZE_MB=0). url={url}"
         )));
     }
     if content_length > max_bytes {
         let size_mb = content_length as f64 / (1024.0 * 1024.0);
         let max_size_mb = max_bytes as f64 / (1024.0 * 1024.0);
-        return Err(CoreError::InvalidRequest(format!(
+        return Err(Error::InvalidRequest(format!(
             "OCR document size ({size_mb:.2}MB) exceeds maximum allowed size ({max_size_mb:.2}MB). url={url}"
         )));
     }
@@ -233,7 +227,7 @@ fn enforce_download_size(content_length: u64, max_bytes: u64, url: &Url) -> Core
 async fn read_response_with_limit(
     mut response: reqwest::Response,
     url: &Url,
-) -> CoreResult<Vec<u8>> {
+) -> Result<Vec<u8>, Error> {
     let max_bytes = max_document_download_bytes();
     if let Some(content_length) = response.content_length() {
         enforce_download_size(content_length, max_bytes, url)?;
@@ -246,7 +240,7 @@ async fn read_response_with_limit(
     while let Some(chunk) = response
         .chunk()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?
+        .map_err(|err| Error::Network(err.to_string()))?
     {
         bytes_downloaded += chunk.len() as u64;
         enforce_download_size(bytes_downloaded, max_bytes, url)?;
@@ -255,7 +249,7 @@ async fn read_response_with_limit(
     Ok(bytes)
 }
 
-pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreResult<Value> {
+pub(super) async fn convert_document_url_to_data_uri(document: Value) -> Result<Value, Error> {
     let Some((field, url)) = document_url_field(&document)? else {
         return Ok(document);
     };
@@ -267,7 +261,7 @@ pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreRes
     let status = response.status();
     if !status.is_success() {
         let body = response.text().await.unwrap_or_default();
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&body),
         });
@@ -290,7 +284,7 @@ pub(super) async fn convert_document_url_to_data_uri(document: Value) -> CoreRes
     let mut transformed = document
         .as_object()
         .cloned()
-        .ok_or_else(|| CoreError::InvalidRequest("OCR document must be an object".to_string()))?;
+        .ok_or_else(|| Error::InvalidRequest("OCR document must be an object".to_string()))?;
     transformed.insert(field.to_string(), Value::String(data_uri));
     Ok(Value::Object(transformed))
 }
@@ -316,11 +310,11 @@ fn retry_after_secs(response: &reqwest::Response) -> u64 {
         .unwrap_or(2)
 }
 
-fn operation_status(response_json: &Value) -> CoreResult<&str> {
+fn operation_status(response_json: &Value) -> Result<&str, Error> {
     let status = response_json
         .get("status")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("status"))?;
+        .ok_or(Error::MissingField("status"))?;
     match status {
         "succeeded" => Ok("succeeded"),
         "running" | "notStarted" => Ok("running"),
@@ -330,11 +324,11 @@ fn operation_status(response_json: &Value) -> CoreResult<&str> {
                 .and_then(|error| error.get("message"))
                 .and_then(Value::as_str)
                 .unwrap_or("Unknown error");
-            Err(CoreError::InvalidResponse(format!(
+            Err(Error::InvalidResponse(format!(
                 "Azure Document Intelligence analysis failed: {message}"
             )))
         }
-        other => Err(CoreError::InvalidResponse(format!(
+        other => Err(Error::InvalidResponse(format!(
             "Unknown operation status: {other}"
         ))),
     }
@@ -345,9 +339,9 @@ pub(super) async fn poll_document_intelligence(
     original_url: &str,
     headers: &[(String, String)],
     timeout: Option<Duration>,
-) -> CoreResult<Value> {
+) -> Result<Value, Error> {
     if !same_origin(operation_url, original_url) {
-        return Err(CoreError::InvalidResponse(
+        return Err(Error::InvalidResponse(
             "Azure Document Intelligence: rejected cross-origin polling URL".to_string(),
         ));
     }
@@ -358,7 +352,7 @@ pub(super) async fn poll_document_intelligence(
     ));
     loop {
         if start.elapsed() > timeout {
-            return Err(CoreError::Network(format!(
+            return Err(Error::Network(format!(
                 "Azure Document Intelligence operation polling timed out after {} seconds",
                 timeout.as_secs()
             )));
@@ -373,21 +367,21 @@ pub(super) async fn poll_document_intelligence(
         let response = request_builder
             .send()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         let retry_after = retry_after_secs(&response);
         let status = response.status();
         let text = response
             .text()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
+            .map_err(|err| Error::Network(err.to_string()))?;
         if !status.is_success() {
-            return Err(CoreError::Http {
+            return Err(Error::Http {
                 status: status.as_u16(),
                 body: truncate_error_body(&text),
             });
         }
         let response_json: Value = serde_json::from_str(&text).map_err(|err| {
-            CoreError::InvalidResponse(format!("invalid Azure DI poll response JSON: {err}"))
+            Error::InvalidResponse(format!("invalid Azure DI poll response JSON: {err}"))
         })?;
         if operation_status(&response_json)? == "succeeded" {
             return Ok(response_json);
@@ -426,7 +420,7 @@ mod tests {
 
         assert!(matches!(
             error,
-            CoreError::InvalidRequest(message)
+            Error::InvalidRequest(message)
                 if message.contains("SSRF protection")
         ));
     }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/handler.rs b/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
index 1de34eb400e..856d9571201 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/handler.rs
@@ -1,13 +1,19 @@
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
+use litellm_core::http_utils::http_request;
 use litellm_core::ocr::transformation::OcrResponseHandling;
 use serde_json::Value;
 
 use super::common_utils::{poll_document_intelligence, truncate_error_body};
-use super::types::ProviderOcrRequest;
+use super::hooks::OcrLifecycleHooks;
+use super::types::PreparedOcrRequest;
 use crate::client::http_client;
 
-pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> CoreResult<Value> {
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub(crate) async fn execute_ocr_provider_call(
+    request: PreparedOcrRequest,
+    hooks: &OcrLifecycleHooks,
+) -> Result<Value, Error> {
+    let request = hooks.prepare_provider_request(request).await?;
     let mut request_builder = http_client().post(&request.url).json(&request.body);
     for (key, value) in &request.upstream_headers {
         request_builder = request_builder.header(key, value);
@@ -16,10 +22,9 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
         request_builder = request_builder.timeout(duration);
     }
 
-    let response = request_builder
-        .send()
+    let response = http_request(request_builder)
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     let status = response.status();
     if request.config.response_handling() == OcrResponseHandling::AzureDocumentIntelligencePoll
@@ -31,7 +36,7 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
             .and_then(|value| value.to_str().ok())
             .map(str::to_string)
             .ok_or_else(|| {
-                CoreError::InvalidResponse(
+                Error::InvalidResponse(
                     "Azure Document Intelligence returned 202 but no Operation-Location header found"
                         .to_string(),
                 )
@@ -52,17 +57,17 @@ pub(crate) async fn execute_ocr_provider_call(request: ProviderOcrRequest) -> Co
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
     let response_json: Value = serde_json::from_str(&text)
-        .map_err(|err| CoreError::InvalidResponse(format!("invalid OCR response JSON: {err}")))?;
+        .map_err(|err| Error::InvalidResponse(format!("invalid OCR response JSON: {err}")))?;
 
     Ok(request
         .config
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs b/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
index 95df566dc53..f8c4f8fe8c5 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/hooks.rs
@@ -1,15 +1,10 @@
+use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
+use litellm_core::error::Error;
+use serde_json::{Map, Value, json};
 use std::future::Future;
 use std::pin::Pin;
 
-use litellm_core::CoreResult;
-use litellm_core::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
-use litellm_core::error::CoreError;
-use litellm_core::ocr::transformation::OcrAuthStrategy;
-use serde_json::{Map, Value, json};
-
-use super::common_utils::{
-    convert_document_url_to_data_uri, has_header, ocr_provider_config, string_headers,
-};
+use super::common_utils::{convert_document_url_to_data_uri, string_headers};
 use super::types::{PreparedOcrRequest, ProviderOcrRequest};
 use crate::integrations::custom_guardrail::{
     CustomGuardrailRunner, GuardrailContext, GuardrailError, GuardrailRequest,
@@ -27,7 +22,7 @@ pub(crate) struct OcrLifecycleHooks {
     request_metadata: RequestMetadata,
 }
 
-type OcrFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type OcrFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 type OcrLogFuture<'a> = Pin<Box<dyn Future<Output = ()> + Send + 'a>>;
 
 impl OcrLifecycleHooks {
@@ -46,7 +41,7 @@ impl OcrLifecycleHooks {
     async fn run_pre_call_guardrails(
         &self,
         request: PreparedOcrRequest,
-    ) -> CoreResult<PreparedOcrRequest> {
+    ) -> Result<PreparedOcrRequest, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(request);
         }
@@ -64,6 +59,10 @@ impl OcrLifecycleHooks {
             .await
             .map_err(guardrail_error_to_core_error)?;
         let (document, optional_params) = parse_ocr_pre_call_guardrail_request(guardrail_request)?;
+        let optional_params = match &request.config {
+            Ok(config) => config.map_ocr_params(&optional_params),
+            Err(_) => optional_params,
+        };
         Ok(PreparedOcrRequest {
             document,
             optional_params,
@@ -71,25 +70,23 @@ impl OcrLifecycleHooks {
         })
     }
 
-    async fn prepare_provider_request(
+    pub(crate) async fn prepare_provider_request(
         &self,
         request: PreparedOcrRequest,
-    ) -> CoreResult<ProviderOcrRequest> {
-        let config = ocr_provider_config(&request.custom_llm_provider, &request.model)
-            .ok_or_else(|| CoreError::InvalidProvider(request.custom_llm_provider.clone()))?;
+    ) -> Result<ProviderOcrRequest, Error> {
+        let config = request.config?;
         let env_lookup = |key: &str| std::env::var(key).ok();
-        let headers = string_headers(request.extra_headers)?;
-        let auth_strategy = config.auth_strategy();
-        let api_key = (!has_header(&headers, auth_strategy.header_name()))
-            .then(|| config.resolve_api_key(request.api_key.as_deref(), &env_lookup))
-            .transpose()?;
+        let upstream_headers = config.validate_environment(
+            string_headers(request.extra_headers)?,
+            request.api_key.as_deref(),
+            &env_lookup,
+        )?;
         let url = config.complete_url(
             request.api_base.as_deref(),
             &request.model,
             &request.optional_params,
             &env_lookup,
         )?;
-        let filtered_params = config.map_ocr_params(&request.optional_params);
         let model = request.model.clone();
         let custom_llm_provider = request.custom_llm_provider.clone();
         let document = if config.requires_data_uri_document() {
@@ -98,9 +95,8 @@ impl OcrLifecycleHooks {
             request.document
         };
         let body = config
-            .transform_ocr_request(&request.model, document, filtered_params)?
+            .transform_ocr_request(&request.model, document, request.optional_params)?
             .data;
-        let upstream_headers = upstream_headers(&headers, auth_strategy, api_key.as_deref());
         let body = self
             .run_during_call_guardrails(&model, &custom_llm_provider, &url, body)
             .await?;
@@ -120,7 +116,7 @@ impl OcrLifecycleHooks {
         custom_llm_provider: &str,
         url: &str,
         body: Value,
-    ) -> CoreResult<Value> {
+    ) -> Result<Value, Error> {
         if self.guardrail_runner.is_empty() {
             return Ok(body);
         }
@@ -169,9 +165,9 @@ impl OcrLifecycleHooks {
     }
 }
 
-impl CallLifecycleHooks<PreparedOcrRequest, ProviderOcrRequest, Value> for OcrLifecycleHooks {
+impl CallLifecycleHooks<PreparedOcrRequest, PreparedOcrRequest, Value> for OcrLifecycleHooks {
     type PreCallFuture<'a> = OcrFuture<'a, PreparedOcrRequest>;
-    type DuringCallFuture<'a> = OcrFuture<'a, ProviderOcrRequest>;
+    type DuringCallFuture<'a> = OcrFuture<'a, PreparedOcrRequest>;
     type SuccessFuture<'a> = OcrLogFuture<'a>;
     type FailureFuture<'a> = OcrLogFuture<'a>;
 
@@ -188,7 +184,7 @@ impl CallLifecycleHooks<PreparedOcrRequest, ProviderOcrRequest, Value> for OcrLi
         _context: &'a CallLifecycleContext,
         request: PreparedOcrRequest,
     ) -> Self::DuringCallFuture<'a> {
-        Box::pin(async move { self.prepare_provider_request(request).await })
+        Box::pin(async move { Ok(request) })
     }
 
     fn async_log_success_event<'a>(
@@ -217,7 +213,7 @@ impl CallLifecycleHooks<PreparedOcrRequest, ProviderOcrRequest, Value> for OcrLi
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -249,21 +245,6 @@ impl CallLifecycleHooks<PreparedOcrRequest, ProviderOcrRequest, Value> for OcrLi
     }
 }
 
-fn upstream_headers(
-    headers: &[(String, String)],
-    auth_strategy: OcrAuthStrategy,
-    api_key: Option<&str>,
-) -> Vec<(String, String)> {
-    api_key
-        .map(|api_key| match auth_strategy {
-            OcrAuthStrategy::Bearer => ("Authorization".to_string(), format!("Bearer {api_key}")),
-            OcrAuthStrategy::Header(header_name) => (header_name.to_string(), api_key.to_string()),
-        })
-        .into_iter()
-        .chain(headers.iter().cloned())
-        .collect()
-}
-
 fn guardrail_context(metadata: &RequestMetadata) -> GuardrailContext {
     GuardrailContext {
         call_type: CallType::Ocr,
@@ -278,19 +259,19 @@ fn guardrail_context(metadata: &RequestMetadata) -> GuardrailContext {
 
 fn parse_ocr_pre_call_guardrail_request(
     request: GuardrailRequest,
-) -> CoreResult<(Value, Map<String, Value>)> {
+) -> Result<(Value, Map<String, Value>), Error> {
     let Value::Object(mut data) = request.data else {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "OCR pre_call guardrail must return an object".to_string(),
         ));
     };
     let document = data.remove("document").ok_or_else(|| {
-        CoreError::InvalidRequest("OCR pre_call guardrail removed document".to_string())
+        Error::InvalidRequest("OCR pre_call guardrail removed document".to_string())
     })?;
     let optional_params = match data.remove("optional_params") {
         Some(Value::Object(params)) => params,
         Some(_) => {
-            return Err(CoreError::InvalidRequest(
+            return Err(Error::InvalidRequest(
                 "OCR pre_call guardrail optional_params must be an object".to_string(),
             ));
         }
@@ -299,33 +280,32 @@ fn parse_ocr_pre_call_guardrail_request(
     Ok((document, optional_params))
 }
 
-fn parse_ocr_during_call_guardrail_request(request: GuardrailRequest) -> CoreResult<Value> {
+fn parse_ocr_during_call_guardrail_request(request: GuardrailRequest) -> Result<Value, Error> {
     let Value::Object(mut data) = request.data else {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "OCR during_call guardrail must return an object".to_string(),
         ));
     };
-    data.remove("body").ok_or_else(|| {
-        CoreError::InvalidRequest("OCR during_call guardrail removed body".to_string())
-    })
+    data.remove("body")
+        .ok_or_else(|| Error::InvalidRequest("OCR during_call guardrail removed body".to_string()))
 }
 
-fn guardrail_error_to_core_error(error: GuardrailError) -> CoreError {
-    CoreError::InvalidRequest(format!("{}: {}", error.kind, error.message))
+fn guardrail_error_to_core_error(error: GuardrailError) -> Error {
+    Error::InvalidRequest(format!("{}: {}", error.kind, error.message))
 }
 
-fn core_error_kind(error: &CoreError) -> &'static str {
+fn core_error_kind(error: &Error) -> &'static str {
     match error {
-        CoreError::Auth(_) => "AuthError",
-        CoreError::InvalidProvider(_) => "InvalidProvider",
-        CoreError::InvalidRequest(_) => "InvalidRequest",
-        CoreError::InvalidType { .. } => "InvalidType",
-        CoreError::MissingField(_) => "MissingField",
-        CoreError::Http { .. } => "HttpError",
-        CoreError::InvalidResponse(_) => "InvalidResponse",
-        CoreError::Network(_) => "NetworkError",
-        CoreError::Connect(_) => "ConnectError",
-        CoreError::Routing(_) => "RoutingError",
-        CoreError::Unsupported(_) => "UnsupportedRequest",
+        Error::Auth(_) => "AuthError",
+        Error::InvalidProvider(_) => "InvalidProvider",
+        Error::InvalidRequest(_) => "InvalidRequest",
+        Error::InvalidType { .. } => "InvalidType",
+        Error::MissingField(_) => "MissingField",
+        Error::Http { .. } => "HttpError",
+        Error::InvalidResponse(_) => "InvalidResponse",
+        Error::Network(_) => "NetworkError",
+        Error::Connect(_) => "ConnectError",
+        Error::Routing(_) => "RoutingError",
+        Error::Unsupported(_) => "UnsupportedRequest",
     }
 }
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/mod.rs b/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
index c4c13e2300c..d9230af1c59 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/mod.rs
@@ -1,4 +1,4 @@
-use litellm_core::CoreResult;
+use litellm_core::Error;
 use litellm_core::call_lifecycle::CallLifecycle;
 use serde_json::Value;
 
@@ -13,10 +13,13 @@ pub use types::OcrRequest;
 use handler::execute_ocr_provider_call;
 use prepare::{PreparedOcrCall, prepare_ocr_call};
 
-pub async fn ocr(request: OcrRequest<'_>) -> CoreResult<Value> {
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub async fn ocr(request: OcrRequest<'_>) -> Result<Value, Error> {
     let PreparedOcrCall { request, hooks } = prepare_ocr_call(request);
     CallLifecycle::default()
-        .run_request(request, &hooks, execute_ocr_provider_call)
+        .run_request(request, &hooks, |request| {
+            execute_ocr_provider_call(request, &hooks)
+        })
         .await
 }
 
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/prepare.rs b/litellm-rust/crates/ai-gateway/src/ocr/prepare.rs
index 6231393c889..fedacc62760 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/prepare.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/prepare.rs
@@ -3,6 +3,7 @@ use std::time::{SystemTime, UNIX_EPOCH};
 
 use litellm_core::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
 
+use super::common_utils::ocr_provider_config;
 use super::hooks::OcrLifecycleHooks;
 use super::types::{OcrRequest, PreparedOcrRequest};
 use crate::integrations::custom_guardrail::CustomGuardrailRunner;
@@ -13,6 +14,7 @@ pub(crate) struct PreparedOcrCall {
     pub(crate) hooks: OcrLifecycleHooks,
 }
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(crate) fn prepare_ocr_call(request: OcrRequest<'_>) -> PreparedOcrCall {
     let call_id = request
         .litellm_call_id
@@ -25,9 +27,25 @@ pub(crate) fn prepare_ocr_call(request: OcrRequest<'_>) -> PreparedOcrCall {
         });
     let model = provider_info.model.to_string();
     let custom_llm_provider = provider_info.custom_llm_provider.to_string();
+    let config = ocr_provider_config(&custom_llm_provider, &model)
+        .ok_or_else(|| litellm_core::Error::InvalidProvider(custom_llm_provider.clone()));
+    let optional_params = match &config {
+        Ok(config) => {
+            let supported = config.supported_ocr_params();
+            config.map_ocr_params(
+                &request
+                    .optional_params
+                    .into_iter()
+                    .filter(|(name, _)| supported.contains(&name.as_str()))
+                    .collect(),
+            )
+        }
+        Err(_) => request.optional_params,
+    };
 
     PreparedOcrCall {
         request: PreparedOcrRequest {
+            config,
             model,
             custom_llm_provider,
             litellm_call_id: call_id,
@@ -35,7 +53,7 @@ pub(crate) fn prepare_ocr_call(request: OcrRequest<'_>) -> PreparedOcrCall {
             api_key: request.api_key.map(str::to_string),
             api_base: request.api_base.map(str::to_string),
             extra_headers: request.extra_headers,
-            optional_params: request.optional_params,
+            optional_params,
             timeout: request.timeout,
         },
         hooks: OcrLifecycleHooks::new(
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/tests.rs b/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
index bb2a6b06501..85e4c408045 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/tests.rs
@@ -1,13 +1,14 @@
 use std::sync::{Arc, Mutex};
 use std::time::Duration;
 
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
+use litellm_core::http_utils::has_header;
 use litellm_core::ocr::transformation::OcrResponseHandling;
 use serde_json::{Map, Value, json};
 use tokio::io::{AsyncReadExt, AsyncWriteExt};
 use tokio::net::{TcpListener, TcpStream};
 
-use super::common_utils::{has_header, ocr_provider_config, string_headers, truncate_error_body};
+use super::common_utils::{ocr_provider_config, string_headers, truncate_error_body};
 use super::{OcrRequest, ocr};
 use crate::integrations::custom_guardrail::{
     CustomGuardrail, GuardrailContext, GuardrailDecision, GuardrailError, GuardrailEventHook,
@@ -395,7 +396,7 @@ async fn ocr_lifecycle_runs_failure_hook_on_provider_error() {
     .await
     .expect_err("provider error propagates");
 
-    assert!(matches!(err, CoreError::Http { status: 500, .. }));
+    assert!(matches!(err, Error::Http { status: 500, .. }));
     server.await.expect("server task completes");
     assert_eq!(
         logger.events(),
@@ -439,7 +440,7 @@ async fn ocr_lifecycle_pre_call_block_skips_provider_socket() {
     .await
     .expect_err("guardrail blocks request");
 
-    assert!(matches!(err, CoreError::InvalidRequest(_)));
+    assert!(matches!(err, Error::InvalidRequest(_)));
     assert_eq!(guardrail.events(), vec!["async_pre_call_hook"]);
     assert_eq!(
         logger.events(),
@@ -607,7 +608,7 @@ fn string_headers_rejects_non_string_values() {
     let err = string_headers(Some(headers)).expect_err("non-string header rejected");
     assert_eq!(
         err,
-        CoreError::InvalidRequest(
+        Error::InvalidRequest(
             "OCR extra_headers.x-retry-count must be a string, got number".to_string()
         )
     );
diff --git a/litellm-rust/crates/ai-gateway/src/ocr/types.rs b/litellm-rust/crates/ai-gateway/src/ocr/types.rs
index bde734a4dd1..95e551d79ca 100644
--- a/litellm-rust/crates/ai-gateway/src/ocr/types.rs
+++ b/litellm-rust/crates/ai-gateway/src/ocr/types.rs
@@ -25,6 +25,7 @@ pub struct OcrRequest<'a> {
 }
 
 pub(crate) struct PreparedOcrRequest {
+    pub(crate) config: Result<&'static dyn OcrProviderConfig, litellm_core::Error>,
     pub(crate) model: String,
     pub(crate) custom_llm_provider: String,
     pub(crate) litellm_call_id: String,
diff --git a/litellm-rust/crates/ai-gateway/src/python/config.rs b/litellm-rust/crates/ai-gateway/src/python/config.rs
index c028d3d6b51..d5a4dd69c8d 100644
--- a/litellm-rust/crates/ai-gateway/src/python/config.rs
+++ b/litellm-rust/crates/ai-gateway/src/python/config.rs
@@ -6,33 +6,31 @@
 //! (and recorded in [`crate::gil`]); the realtime hot path never touches Python.
 //!
 //! Compiled only under the `python-config` feature.
-
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::router::{Deployment, Router};
 use pyo3::prelude::*;
 
 use crate::gil;
 
 /// Load the router's `model_list` from `config_path` via the Python reader.
-pub fn load_router_from_config(config_path: &str) -> CoreResult<Router> {
+pub fn load_router_from_config(config_path: &str) -> Result<Router, Error> {
     gil::record_acquisition();
     Python::attach(|py| {
         let model_list = py
             .import("litellm.proxy.read_model_list")
             .and_then(|module| module.getattr("read_model_list"))
             .and_then(|reader| reader.call1((config_path,)))
-            .map_err(|err| CoreError::Routing(format!("read_model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("read_model_list failed: {err}")))?;
 
         let model_list_json: String = py
             .import("json")
             .and_then(|json| json.getattr("dumps"))
             .and_then(|dumps| dumps.call1((model_list,)))
             .and_then(|encoded| encoded.extract())
-            .map_err(|err| CoreError::Routing(format!("serializing model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("serializing model_list failed: {err}")))?;
 
         let deployments: Vec<Deployment> = serde_json::from_str(&model_list_json)
-            .map_err(|err| CoreError::Routing(format!("parsing model_list failed: {err}")))?;
+            .map_err(|err| Error::Routing(format!("parsing model_list failed: {err}")))?;
 
         Ok(Router::new(deployments))
     })
diff --git a/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs b/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
index 7e38d10c6ff..e9f8c477f36 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/messages/mod.rs
@@ -9,7 +9,7 @@ use axum::http::StatusCode;
 use axum::http::header::{CACHE_CONTROL, CONTENT_TYPE, HeaderMap, HeaderValue};
 use axum::response::{IntoResponse, Response};
 use axum::routing::post;
-use litellm_core::CoreError;
+use litellm_core::Error;
 use serde_json::{Map, Value};
 
 use crate::auth::RequireMasterKey;
@@ -46,7 +46,7 @@ fn stream_response(upstream: reqwest::Response) -> Result<Response, MessagesRout
     let mut response = Response::builder()
         .status(
             StatusCode::from_u16(upstream.status().as_u16()).map_err(|error| {
-                MessagesRouteError(CoreError::InvalidResponse(format!(
+                MessagesRouteError(Error::InvalidResponse(format!(
                     "invalid upstream response status: {error}"
                 )))
             })?,
@@ -58,13 +58,13 @@ fn stream_response(upstream: reqwest::Response) -> Result<Response, MessagesRout
     response
         .body(Body::from_stream(upstream.bytes_stream()))
         .map_err(|error| {
-            MessagesRouteError(CoreError::InvalidResponse(format!(
+            MessagesRouteError(Error::InvalidResponse(format!(
                 "failed to build streaming response: {error}"
             )))
         })
 }
 
-fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>, CoreError> {
+fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>, Error> {
     let forwarded = headers
         .iter()
         .filter(|(name, _)| {
@@ -74,19 +74,19 @@ fn forwarded_headers(headers: &HeaderMap) -> Result<Option<Map<String, Value>>,
         })
         .map(|(name, value)| {
             let value = value.to_str().map_err(|_| {
-                CoreError::InvalidRequest(format!("invalid value for header {}", name.as_str()))
+                Error::InvalidRequest(format!("invalid value for header {}", name.as_str()))
             })?;
             Ok((name.to_string(), Value::String(value.to_string())))
         })
-        .collect::<Result<Map<_, _>, CoreError>>()?;
+        .collect::<Result<Map<_, _>, Error>>()?;
     Ok((!forwarded.is_empty()).then_some(forwarded))
 }
 
 #[derive(Debug)]
-struct MessagesRouteError(CoreError);
+struct MessagesRouteError(Error);
 
-impl From<CoreError> for MessagesRouteError {
-    fn from(error: CoreError) -> Self {
+impl From<Error> for MessagesRouteError {
+    fn from(error: Error) -> Self {
         Self(error)
     }
 }
@@ -94,28 +94,28 @@ impl From<CoreError> for MessagesRouteError {
 impl IntoResponse for MessagesRouteError {
     fn into_response(self) -> Response {
         let (status, message) = match self.0 {
-            CoreError::InvalidRequest(message) => (StatusCode::BAD_REQUEST, message),
-            CoreError::InvalidProvider(_) | CoreError::Routing(_) => (
+            Error::InvalidRequest(message) => (StatusCode::BAD_REQUEST, message),
+            Error::InvalidProvider(_) | Error::Routing(_) => (
                 StatusCode::NOT_FOUND,
                 "no messages deployment is configured for this model".to_string(),
             ),
-            CoreError::Auth(_) => (
+            Error::Auth(_) => (
                 StatusCode::BAD_GATEWAY,
                 "messages provider authentication failed".to_string(),
             ),
-            CoreError::Http { .. }
-            | CoreError::Network(_)
-            | CoreError::Connect(_)
-            | CoreError::InvalidResponse(_)
-            | CoreError::InvalidType { .. }
-            | CoreError::MissingField(_) => (
+            Error::Http { .. }
+            | Error::Network(_)
+            | Error::Connect(_)
+            | Error::InvalidResponse(_)
+            | Error::InvalidType { .. }
+            | Error::MissingField(_) => (
                 StatusCode::BAD_GATEWAY,
                 "messages provider request failed".to_string(),
             ),
             // The gateway has no Python implementation to decline to, so a
             // request the core cannot serve is reported to the caller. The
             // reason is a fixed internal string, never provider content.
-            CoreError::Unsupported(reason) => (
+            Error::Unsupported(reason) => (
                 StatusCode::BAD_REQUEST,
                 format!("messages request is not supported: {reason}"),
             ),
diff --git a/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs b/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
index 5f4c5fe8de4..4fd29db05d6 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/messages/service.rs
@@ -1,10 +1,10 @@
 use std::sync::Arc;
 
+use litellm_core::Error;
 use litellm_core::constants::ANTHROPIC_MESSAGES_PROVIDER;
 use litellm_core::messages::types::MessagesRequest;
 use litellm_core::messages::{messages, messages_stream};
 use litellm_core::router::Router;
-use litellm_core::{CoreError, CoreResult};
 use serde_json::{Map, Value};
 
 pub(crate) enum MessagesResponse {
@@ -16,16 +16,16 @@ pub async fn run(
     router: &Arc<Router>,
     body: Value,
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<MessagesResponse> {
+) -> Result<MessagesResponse, Error> {
     let model = body
         .get("model")
         .and_then(Value::as_str)
         .map(str::trim)
         .filter(|model| !model.is_empty())
-        .ok_or_else(|| CoreError::InvalidRequest("messages body requires a model".to_string()))?;
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+        .ok_or_else(|| Error::InvalidRequest("messages body requires a model".to_string()))?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let provider_model = deployment.litellm_params.model.as_str();
     let upstream_model = provider_model
         .split_once('/')
@@ -37,7 +37,7 @@ pub async fn run(
     };
     let mut body = body;
     body.as_object_mut()
-        .ok_or_else(|| CoreError::InvalidRequest("messages body must be an object".to_string()))?
+        .ok_or_else(|| Error::InvalidRequest("messages body must be an object".to_string()))?
         .insert(
             "model".to_string(),
             Value::String(upstream_model.to_string()),
@@ -60,6 +60,6 @@ pub async fn run(
     serde_json::to_value(response)
         .map(MessagesResponse::Json)
         .map_err(|err| {
-            CoreError::InvalidResponse(format!("failed to serialize messages response: {err}"))
+            Error::InvalidResponse(format!("failed to serialize messages response: {err}"))
         })
 }
diff --git a/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs b/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
index 4ae8cfe7379..b8ee77c4269 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/realtime/service.rs
@@ -11,8 +11,7 @@ use std::time::Duration;
 
 use crate::io::realtime_pool::{RealtimePool, upstream_key};
 use futures_util::{Sink, Stream};
-use litellm_core::CoreResult;
-use litellm_core::error::CoreError;
+use litellm_core::error::Error;
 use litellm_core::realtime::types::RealtimeEvent;
 use litellm_core::router::Router;
 
@@ -29,15 +28,15 @@ pub async fn run<In, Out>(
     observe: impl FnMut(&RealtimeEvent) + Send,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = RealtimeEvent> + Unpin + Send,
     Out: Sink<RealtimeEvent> + Unpin + Send,
     <Out as Sink<RealtimeEvent>>::Error: std::fmt::Display,
 {
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let params = &deployment.litellm_params;
     // Strip a leading `openai/` so the OpenAI-only realtime fn gets the bare model.
     let provider_model = params
diff --git a/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs b/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
index 165c95695d3..e8f840c0c8e 100644
--- a/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
+++ b/litellm-rust/crates/ai-gateway/src/routes/responses/service.rs
@@ -2,13 +2,13 @@ use std::sync::Arc;
 use std::time::Duration;
 
 use futures_util::{Sink, Stream};
+use litellm_core::Error;
 use litellm_core::call_lifecycle::{CallLifecycle, CallLifecycleContext};
 use litellm_core::responses::instrumentation::{
     ResponsesWsCallbackPayload, ResponsesWsInstrumentation, ResponsesWsLogOutcome,
     ResponsesWsMetadata,
 };
 use litellm_core::responses::types::ResponsesWsEvent;
-use litellm_core::{CoreError, CoreResult};
 
 use crate::integrations::custom_logger::{
     CallbackTiming, CallbackValue, CustomLogger, CustomLoggerRunner, LoggingError, ModelCallDetails,
@@ -26,22 +26,22 @@ pub async fn run<In, Out>(
     metadata: RequestMetadata,
     client_in: In,
     client_out: Out,
-) -> CoreResult<()>
+) -> Result<(), Error>
 where
     In: Stream<Item = ResponsesWsEvent> + Unpin + Send,
     Out: Sink<ResponsesWsEvent> + Unpin + Send,
     Out::Error: std::fmt::Display,
 {
-    let deployment = router.get_available_deployment(model).ok_or_else(|| {
-        CoreError::Routing(format!("no deployment available for model '{model}'"))
-    })?;
+    let deployment = router
+        .get_available_deployment(model)
+        .ok_or_else(|| Error::Routing(format!("no deployment available for model '{model}'")))?;
     let params = &deployment.litellm_params;
     let provider_model = params
         .model
         .strip_prefix("openai/")
         .unwrap_or(&params.model);
     if params.model.contains('/') && !params.model.starts_with("openai/") {
-        return Err(CoreError::InvalidProvider(
+        return Err(Error::InvalidProvider(
             "Responses WebSocket route supports OpenAI deployments only".to_string(),
         ));
     }
diff --git a/litellm-rust/crates/core/Cargo.toml b/litellm-rust/crates/core/Cargo.toml
index ab8050734f2..389dbd49505 100644
--- a/litellm-rust/crates/core/Cargo.toml
+++ b/litellm-rust/crates/core/Cargo.toml
@@ -11,6 +11,7 @@ reqwest.workspace = true
 serde.workspace = true
 serde_json.workspace = true
 thiserror.workspace = true
+tracing.workspace = true
 sha2.workspace = true
 aws-config = { version = "1.9.0", default-features = false, features = ["rustls", "rt-tokio"], optional = true }
 aws-credential-types = { version = "1.3.0", features = ["hardcoded-credentials"], optional = true }
diff --git a/litellm-rust/crates/core/src/audio_transcription/client.rs b/litellm-rust/crates/core/src/audio_transcription/client.rs
new file mode 100644
index 00000000000..0e612628dc6
--- /dev/null
+++ b/litellm-rust/crates/core/src/audio_transcription/client.rs
@@ -0,0 +1,14 @@
+use std::sync::OnceLock;
+use std::time::Duration;
+
+use crate::constants::AUDIO_TRANSCRIPTION_TIMEOUT_SECS;
+
+pub(super) fn http_client() -> &'static reqwest::Client {
+    static CLIENT: OnceLock<reqwest::Client> = OnceLock::new();
+    CLIENT.get_or_init(|| {
+        reqwest::Client::builder()
+            .timeout(Duration::from_secs(AUDIO_TRANSCRIPTION_TIMEOUT_SECS))
+            .build()
+            .unwrap_or_else(|_| reqwest::Client::new())
+    })
+}
diff --git a/litellm-rust/crates/core/src/audio_transcription/handler.rs b/litellm-rust/crates/core/src/audio_transcription/handler.rs
new file mode 100644
index 00000000000..9a96b9d1140
--- /dev/null
+++ b/litellm-rust/crates/core/src/audio_transcription/handler.rs
@@ -0,0 +1,91 @@
+use serde_json::Value;
+
+use crate::error::Error;
+use crate::http_utils::{http_request, truncate_error_body};
+
+use super::client::http_client;
+use super::types::ProviderAudioTranscriptionRequest;
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub async fn execute_audio_transcription_provider_call(
+    request: ProviderAudioTranscriptionRequest,
+) -> Result<Value, Error> {
+    let body = serde_json::to_vec(&request.body)
+        .map_err(|error| Error::InvalidRequest(format!("invalid audio request body: {error}")))?;
+    let headers = signed_headers(&request, &body).await?;
+    let mut request_builder = http_client().post(&request.url).body(body);
+    for (key, value) in headers {
+        request_builder = request_builder.header(key, value);
+    }
+    if let Some(duration) = request.timeout {
+        request_builder = request_builder.timeout(duration);
+    }
+    let response = http_request(request_builder)
+        .await
+        .map_err(|error| Error::Network(error.to_string()))?;
+    let status = response.status();
+    let text = response
+        .text()
+        .await
+        .map_err(|error| Error::Network(error.to_string()))?;
+    if !status.is_success() {
+        return Err(Error::Http {
+            status: status.as_u16(),
+            body: truncate_error_body(&text),
+        });
+    }
+    let response_json = serde_json::from_str(&text)
+        .map_err(|error| Error::InvalidResponse(format!("invalid audio response JSON: {error}")))?;
+    Ok(request
+        .config
+        .transform_transcription_response(&request.model, response_json)?
+        .into_json())
+}
+
+#[cfg(feature = "bedrock-auth")]
+async fn signed_headers(
+    request: &ProviderAudioTranscriptionRequest,
+    body: &[u8],
+) -> Result<Vec<(String, String)>, Error> {
+    use std::collections::BTreeMap;
+    use std::time::SystemTime;
+
+    use crate::audio_transcription::transformation::AudioTranscriptionAuth;
+    use crate::providers::bedrock::audio_transcription::aws_auth_config;
+    use crate::providers::bedrock::aws_base::{resolve_credentials, sign_bedrock_post};
+
+    let AudioTranscriptionAuth::AwsSigV4 { region, .. } = &request.auth else {
+        return Ok(request.upstream_headers.clone());
+    };
+    let env_lookup = |key: &str| std::env::var(key).ok();
+    let credentials = resolve_credentials(
+        aws_auth_config(&request.optional_params, &env_lookup),
+        &env_lookup,
+    )
+    .await?;
+    let unsigned: BTreeMap<String, String> = request.upstream_headers.iter().cloned().collect();
+    let signature = sign_bedrock_post(
+        &request.url,
+        body,
+        &unsigned,
+        region,
+        &credentials,
+        SystemTime::now(),
+    )?;
+    Ok(unsigned.into_iter().chain(signature).collect())
+}
+
+#[cfg(not(feature = "bedrock-auth"))]
+async fn signed_headers(
+    request: &ProviderAudioTranscriptionRequest,
+    _body: &[u8],
+) -> Result<Vec<(String, String)>, Error> {
+    use crate::audio_transcription::transformation::AudioTranscriptionAuth;
+
+    match request.auth {
+        AudioTranscriptionAuth::AwsSigV4 { .. } => Err(Error::Unsupported(
+            "AWS SigV4 requires the bedrock-auth feature",
+        )),
+        AudioTranscriptionAuth::Bearer => Ok(request.upstream_headers.clone()),
+    }
+}
diff --git a/litellm-rust/crates/core/src/audio_transcription/mod.rs b/litellm-rust/crates/core/src/audio_transcription/mod.rs
index ec2fbb969a6..31b6de4b3e4 100644
--- a/litellm-rust/crates/core/src/audio_transcription/mod.rs
+++ b/litellm-rust/crates/core/src/audio_transcription/mod.rs
@@ -1,2 +1,21 @@
+use crate::Error;
+mod client;
+mod handler;
+mod prepare;
 pub mod transformation;
 pub mod types;
+
+use serde_json::Value;
+
+pub use handler::execute_audio_transcription_provider_call;
+pub use prepare::prepare_audio_transcription_provider_call;
+pub use types::{AudioTranscriptionRequest, ProviderAudioTranscriptionRequest};
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub async fn audio_transcription(request: AudioTranscriptionRequest<'_>) -> Result<Value, Error> {
+    execute_audio_transcription_provider_call(prepare_audio_transcription_provider_call(request)?)
+        .await
+}
+
+#[cfg(test)]
+mod tests;
diff --git a/litellm-rust/crates/core/src/audio_transcription/prepare.rs b/litellm-rust/crates/core/src/audio_transcription/prepare.rs
new file mode 100644
index 00000000000..bbef97341a9
--- /dev/null
+++ b/litellm-rust/crates/core/src/audio_transcription/prepare.rs
@@ -0,0 +1,74 @@
+use crate::error::Error;
+use crate::http_utils::{has_header, string_headers};
+#[cfg(feature = "bedrock-auth")]
+use crate::providers::bedrock::audio_transcription::BEDROCK_AUDIO_TRANSCRIPTION_CONFIG;
+use crate::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
+
+use super::transformation::{AudioTranscriptionAuth, AudioTranscriptionProviderConfig};
+use super::types::{AudioTranscriptionRequest, ProviderAudioTranscriptionRequest};
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+fn provider_config(provider: &str) -> Option<&'static dyn AudioTranscriptionProviderConfig> {
+    #[cfg(feature = "bedrock-auth")]
+    if provider == "bedrock" {
+        return Some(&BEDROCK_AUDIO_TRANSCRIPTION_CONFIG);
+    }
+    let _ = provider;
+    None
+}
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub fn prepare_audio_transcription_provider_call(
+    request: AudioTranscriptionRequest<'_>,
+) -> Result<ProviderAudioTranscriptionRequest, Error> {
+    let provider_info = get_custom_llm_provider(request.model, request.custom_llm_provider)
+        .or_else(|| {
+            request
+                .custom_llm_provider
+                .map(|provider| CustomLlmProvider {
+                    model: request.model,
+                    custom_llm_provider: provider,
+                })
+        })
+        .ok_or_else(|| {
+            Error::InvalidProvider(
+                "unable to resolve custom_llm_provider for audio transcription request".to_string(),
+            )
+        })?;
+    let model = provider_info.model.to_string();
+    let config = provider_config(provider_info.custom_llm_provider)
+        .ok_or_else(|| Error::InvalidProvider(provider_info.custom_llm_provider.to_string()))?;
+    let env_lookup = |key: &str| std::env::var(key).ok();
+    let mut headers = string_headers("audio transcription", request.extra_headers)?;
+    let auth = config.auth_strategy(&model, &request.optional_params, &env_lookup)?;
+    if matches!(auth, AudioTranscriptionAuth::Bearer)
+        && !has_header(&headers, "authorization")
+        && let Some(api_key) = request.api_key
+    {
+        headers.push(("Authorization".to_string(), format!("Bearer {api_key}")));
+    }
+    if !has_header(&headers, "content-type") {
+        headers.push(("Content-Type".to_string(), "application/json".to_string()));
+    }
+    let url = config.complete_url(
+        request.api_base,
+        &model,
+        &request.optional_params,
+        &env_lookup,
+    )?;
+    let filtered_params = config.map_transcription_params(&request.optional_params);
+    let transformed =
+        config.transform_transcription_request(&model, request.audio, filtered_params)?;
+    Ok(ProviderAudioTranscriptionRequest {
+        model,
+        custom_llm_provider: provider_info.custom_llm_provider.to_string(),
+        config,
+        url,
+        body: transformed.body,
+        upstream_headers: headers,
+        auth,
+        #[cfg(feature = "bedrock-auth")]
+        optional_params: request.optional_params,
+        timeout: request.timeout,
+    })
+}
diff --git a/litellm-rust/crates/core/src/audio_transcription/tests.rs b/litellm-rust/crates/core/src/audio_transcription/tests.rs
new file mode 100644
index 00000000000..263d63337b0
--- /dev/null
+++ b/litellm-rust/crates/core/src/audio_transcription/tests.rs
@@ -0,0 +1,50 @@
+use std::io::{Read, Write};
+use std::net::TcpListener;
+use std::thread;
+
+use serde_json::{Map, json};
+
+use super::audio_transcription;
+use super::types::AudioTranscriptionRequest;
+
+#[tokio::test]
+async fn bedrock_request_is_signed_and_contains_audio() {
+    let listener = TcpListener::bind("127.0.0.1:0").expect("listener");
+    let address = listener.local_addr().expect("address");
+    let server = thread::spawn(move || {
+        let (mut stream, _) = listener.accept().expect("connection");
+        let mut request = Vec::new();
+        let mut buffer = [0_u8; 16_384];
+        let count = stream.read(&mut buffer).expect("request");
+        request.extend_from_slice(&buffer[..count]);
+        let request = String::from_utf8_lossy(&request);
+        assert!(request.contains("POST /model/mistral.voxtral-mini-3b-2507/converse"));
+        assert!(request.contains("authorization: AWS4-HMAC-SHA256"));
+        assert!(request.contains("x-amz-date:"));
+        assert!(request.contains("\"bytes\":\"AQI=\""));
+        assert!(request.contains("Transcribe the audio. Respond with only the transcript."));
+        let response = b"HTTP/1.1 200 OK\r\nContent-Type: application/json\r\nContent-Length: 53\r\nConnection: close\r\n\r\n{\"output\":{\"message\":{\"content\":[{\"text\":\"hello\"}]}}}";
+        stream.write_all(response).expect("response");
+    });
+
+    let optional_params = Map::from_iter([
+        ("aws_access_key_id".to_string(), json!("access-key")),
+        ("aws_secret_access_key".to_string(), json!("secret-key")),
+        ("aws_region_name".to_string(), json!("us-east-1")),
+    ]);
+    let api_base = format!("http://{address}");
+    let response = audio_transcription(AudioTranscriptionRequest {
+        model: "mistral.voxtral-mini-3b-2507",
+        audio: json!({"data": "AQI=", "format": "wav", "filename": "audio.wav"}),
+        api_key: None,
+        api_base: Some(&api_base),
+        custom_llm_provider: Some("bedrock"),
+        extra_headers: None,
+        optional_params,
+        timeout: None,
+    })
+    .await
+    .expect("transcription");
+    assert_eq!(response, json!({"text": "hello"}));
+    server.join().expect("server");
+}
diff --git a/litellm-rust/crates/core/src/audio_transcription/transformation.rs b/litellm-rust/crates/core/src/audio_transcription/transformation.rs
index eab34c13843..aa9846427dc 100644
--- a/litellm-rust/crates/core/src/audio_transcription/transformation.rs
+++ b/litellm-rust/crates/core/src/audio_transcription/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::CoreResult;
-
 use super::types::{AudioTranscriptionRequestData, AudioTranscriptionResponseData};
 
 #[derive(Clone, Debug, PartialEq, Eq)]
@@ -16,6 +15,7 @@ pub enum AudioTranscriptionAuth {
 pub trait AudioTranscriptionProviderConfig: Sync {
     fn supported_transcription_params(&self) -> &'static [&'static str];
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn map_transcription_params(&self, params: &Map<String, Value>) -> Map<String, Value> {
         params
             .iter()
@@ -32,13 +32,13 @@ pub trait AudioTranscriptionProviderConfig: Sync {
         model: &str,
         audio: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<AudioTranscriptionRequestData>;
+    ) -> Result<AudioTranscriptionRequestData, Error>;
 
     fn transform_transcription_response(
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<AudioTranscriptionResponseData>;
+    ) -> Result<AudioTranscriptionResponseData, Error>;
 
     fn complete_url(
         &self,
@@ -46,12 +46,12 @@ pub trait AudioTranscriptionProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth_strategy(
         &self,
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<AudioTranscriptionAuth>;
+    ) -> Result<AudioTranscriptionAuth, Error>;
 }
diff --git a/litellm-rust/crates/core/src/audio_transcription/types.rs b/litellm-rust/crates/core/src/audio_transcription/types.rs
index 3a9e1ecd88c..559d7837027 100644
--- a/litellm-rust/crates/core/src/audio_transcription/types.rs
+++ b/litellm-rust/crates/core/src/audio_transcription/types.rs
@@ -1,5 +1,56 @@
+use std::time::Duration;
+
 use serde::{Deserialize, Serialize};
-use serde_json::Value;
+use serde_json::{Map, Value};
+
+use super::transformation::{AudioTranscriptionAuth, AudioTranscriptionProviderConfig};
+
+pub struct AudioTranscriptionRequest<'a> {
+    pub model: &'a str,
+    pub audio: Value,
+    pub api_key: Option<&'a str>,
+    pub api_base: Option<&'a str>,
+    pub custom_llm_provider: Option<&'a str>,
+    pub extra_headers: Option<Map<String, Value>>,
+    pub optional_params: Map<String, Value>,
+    pub timeout: Option<Duration>,
+}
+
+#[derive(Clone)]
+pub struct ProviderAudioTranscriptionRequest {
+    pub(super) model: String,
+    pub(super) custom_llm_provider: String,
+    pub(super) config: &'static dyn AudioTranscriptionProviderConfig,
+    pub(super) url: String,
+    pub(super) body: Value,
+    pub(super) upstream_headers: Vec<(String, String)>,
+    pub(super) auth: AudioTranscriptionAuth,
+    #[cfg(feature = "bedrock-auth")]
+    pub(super) optional_params: Map<String, Value>,
+    pub(super) timeout: Option<Duration>,
+}
+
+impl ProviderAudioTranscriptionRequest {
+    pub fn model(&self) -> &str {
+        &self.model
+    }
+
+    pub fn custom_llm_provider(&self) -> &str {
+        &self.custom_llm_provider
+    }
+
+    pub fn url(&self) -> &str {
+        &self.url
+    }
+
+    pub fn body(&self) -> &Value {
+        &self.body
+    }
+
+    pub fn with_body(self, body: Value) -> Self {
+        Self { body, ..self }
+    }
+}
 
 #[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
 pub struct AudioTranscriptionRequestData {
diff --git a/litellm-rust/crates/core/src/call_lifecycle/mod.rs b/litellm-rust/crates/core/src/call_lifecycle/mod.rs
index d9b68a1b726..637c156e192 100644
--- a/litellm-rust/crates/core/src/call_lifecycle/mod.rs
+++ b/litellm-rust/crates/core/src/call_lifecycle/mod.rs
@@ -1,7 +1,7 @@
 use std::future::Future;
 use std::time::{Instant, SystemTime, UNIX_EPOCH};
 
-use crate::{CoreError, CoreResult};
+use crate::Error;
 
 pub mod types;
 
@@ -11,14 +11,14 @@ pub use types::{
 };
 
 pub trait CallLifecycleHooks<InitialReq, ProviderReq, Resp>: Send + Sync {
-    type PreCallFuture<'a>: Future<Output = CoreResult<InitialReq>> + Send + 'a
+    type PreCallFuture<'a>: Future<Output = Result<InitialReq, Error>> + Send + 'a
     where
         Self: 'a,
         InitialReq: 'a,
         ProviderReq: 'a,
         Resp: 'a;
 
-    type DuringCallFuture<'a>: Future<Output = CoreResult<ProviderReq>> + Send + 'a
+    type DuringCallFuture<'a>: Future<Output = Result<ProviderReq, Error>> + Send + 'a
     where
         Self: 'a,
         InitialReq: 'a,
@@ -56,7 +56,7 @@ pub trait CallLifecycleHooks<InitialReq, ProviderReq, Resp>: Send + Sync {
     fn async_log_failure_event<'a>(
         &'a self,
         context: &'a CallLifecycleContext,
-        error: &'a CoreError,
+        error: &'a Error,
         timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a>;
 }
@@ -86,12 +86,12 @@ impl<'a> CallLifecycle<'a> {
         request: InitialReq,
         hooks: &Hooks,
         provider_call: ProviderCall,
-    ) -> CoreResult<Resp>
+    ) -> Result<Resp, Error>
     where
         InitialReq: CallLifecycleRequest,
         Hooks: CallLifecycleHooks<InitialReq, ProviderReq, Resp>,
         ProviderCall: FnOnce(ProviderReq) -> ProviderFuture,
-        ProviderFuture: Future<Output = CoreResult<Resp>>,
+        ProviderFuture: Future<Output = Result<Resp, Error>>,
     {
         let context = request.lifecycle_context();
         self.run(context, request, hooks, provider_call).await
@@ -103,11 +103,11 @@ impl<'a> CallLifecycle<'a> {
         request: InitialReq,
         hooks: &Hooks,
         provider_call: ProviderCall,
-    ) -> CoreResult<Resp>
+    ) -> Result<Resp, Error>
     where
         Hooks: CallLifecycleHooks<InitialReq, ProviderReq, Resp>,
         ProviderCall: FnOnce(ProviderReq) -> ProviderFuture,
-        ProviderFuture: Future<Output = CoreResult<Resp>>,
+        ProviderFuture: Future<Output = Result<Resp, Error>>,
     {
         let call_start = epoch_seconds();
         let mut phases = Vec::new();
@@ -166,7 +166,7 @@ impl<'a> CallLifecycle<'a> {
         &self,
         context: &CallLifecycleContext,
         hooks: &Hooks,
-        error: &CoreError,
+        error: &Error,
         call_start: f64,
         phases: &mut Vec<CallLifecyclePhaseTiming>,
     ) where
@@ -251,8 +251,8 @@ mod tests {
     }
 
     impl CallLifecycleHooks<String, String, String> for RecordingHooks {
-        type PreCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
-        type DuringCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
+        type PreCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
+        type DuringCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
         type SuccessFuture<'a> = BoxFuture<'a, ()>;
         type FailureFuture<'a> = BoxFuture<'a, ()>;
 
@@ -294,7 +294,7 @@ mod tests {
         fn async_log_failure_event<'a>(
             &'a self,
             _context: &'a CallLifecycleContext,
-            _error: &'a CoreError,
+            _error: &'a Error,
             _timing: &'a CallLifecycleTiming,
         ) -> Self::FailureFuture<'a> {
             Box::pin(async move {
@@ -304,8 +304,8 @@ mod tests {
     }
 
     impl CallLifecycleHooks<RecordingRequest, String, String> for RecordingHooks {
-        type PreCallFuture<'a> = BoxFuture<'a, CoreResult<RecordingRequest>>;
-        type DuringCallFuture<'a> = BoxFuture<'a, CoreResult<String>>;
+        type PreCallFuture<'a> = BoxFuture<'a, Result<RecordingRequest, Error>>;
+        type DuringCallFuture<'a> = BoxFuture<'a, Result<String, Error>>;
         type SuccessFuture<'a> = BoxFuture<'a, ()>;
         type FailureFuture<'a> = BoxFuture<'a, ()>;
 
@@ -345,7 +345,7 @@ mod tests {
         fn async_log_failure_event<'a>(
             &'a self,
             _context: &'a CallLifecycleContext,
-            _error: &'a CoreError,
+            _error: &'a Error,
             _timing: &'a CallLifecycleTiming,
         ) -> Self::FailureFuture<'a> {
             Box::pin(async move {
@@ -383,13 +383,13 @@ mod tests {
                 "request".to_string(),
                 &hooks,
                 |_request| async move {
-                    Err::<String, CoreError>(CoreError::Network("provider down".to_string()))
+                    Err::<String, Error>(Error::Network("provider down".to_string()))
                 },
             )
             .await
             .expect_err("call fails");
 
-        assert_eq!(error, CoreError::Network("provider down".to_string()));
+        assert_eq!(error, Error::Network("provider down".to_string()));
         assert_eq!(hooks.events(), vec!["pre_call", "during_call", "failure"]);
     }
 
diff --git a/litellm-rust/crates/core/src/chat_completions/common_utils.rs b/litellm-rust/crates/core/src/chat_completions/common_utils.rs
index 36eaf242a5a..69e5f175ad5 100644
--- a/litellm-rust/crates/core/src/chat_completions/common_utils.rs
+++ b/litellm-rust/crates/core/src/chat_completions/common_utils.rs
@@ -1,13 +1,13 @@
-use serde_json::{Map, Value};
-
-use crate::error::CoreResult;
+use crate::Error;
 use crate::http_utils::string_headers as shared_string_headers;
 use crate::providers::anthropic::chat_completions::transformation::ANTHROPIC_CHAT_COMPLETIONS_CONFIG;
+use serde_json::{Map, Value};
 
 use super::transformation::ChatCompletionsProviderConfig;
 
 const HEADER_CONTEXT: &str = "chat completions";
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(super) fn chat_completions_provider_config(
     provider: &str,
 ) -> Option<&'static dyn ChatCompletionsProviderConfig> {
@@ -23,6 +23,6 @@ pub(super) fn chat_completions_provider_config(
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     shared_string_headers(HEADER_CONTEXT, extra_headers)
 }
diff --git a/litellm-rust/crates/core/src/chat_completions/handler.rs b/litellm-rust/crates/core/src/chat_completions/handler.rs
index afc4529fd26..96d001e2892 100644
--- a/litellm-rust/crates/core/src/chat_completions/handler.rs
+++ b/litellm-rust/crates/core/src/chat_completions/handler.rs
@@ -1,19 +1,23 @@
 use serde_json::Value;
 
-use crate::error::{CoreError, CoreResult};
-use crate::http_utils::truncate_error_body;
+use crate::error::Error;
+use crate::http_utils::{http_request, truncate_error_body};
 
 use super::client::http_client;
+use super::prepare::prepare_provider_request;
 use super::transformation::ChatCompletionsAuth;
 use super::types::{
     ChatCompletionsResponse, ProviderChatCompletionsRequest, ProviderChatResponseData,
+    ResolvedChatCompletionsRequest,
 };
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(super) async fn execute_chat_completions_provider_call(
-    request: ProviderChatCompletionsRequest,
-) -> CoreResult<ChatCompletionsResponse> {
+    request: ResolvedChatCompletionsRequest<'_>,
+) -> Result<ChatCompletionsResponse, Error> {
+    let request = prepare_provider_request(request)?;
     let body = serde_json::to_vec(&request.body).map_err(|err| {
-        CoreError::InvalidRequest(format!(
+        Error::InvalidRequest(format!(
             "failed to serialize chat completions request: {err}"
         ))
     })?;
@@ -27,14 +31,14 @@ pub(super) async fn execute_chat_completions_provider_call(
         request_builder = request_builder.timeout(duration);
     }
 
-    let response = request_builder.send().await.map_err(|err| {
+    let response = http_request(request_builder).await.map_err(|err| {
         // Failing to establish the connection means the request never went out,
         // so the host can still serve it. Everything else here, a timeout
         // above all, may have reached the provider and been answered.
         if err.is_connect() || err.is_builder() {
-            CoreError::Connect(err.to_string())
+            Error::Connect(err.to_string())
         } else {
-            CoreError::Network(err.to_string())
+            Error::Network(err.to_string())
         }
     })?;
 
@@ -42,17 +46,17 @@ pub(super) async fn execute_chat_completions_provider_call(
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
     let body: Value = serde_json::from_str(&text).map_err(|err| {
-        CoreError::InvalidResponse(format!("invalid chat completions response JSON: {err}"))
+        Error::InvalidResponse(format!("invalid chat completions response JSON: {err}"))
     })?;
     request
         .config
@@ -69,10 +73,10 @@ pub(super) async fn execute_chat_completions_provider_call(
 /// second kind has already been billed, and a host that keeps a reference
 /// implementation must not retry those, so collapse them to one variant that
 /// can only mean the provider was already called.
-pub(super) fn as_response_error(err: CoreError) -> CoreError {
+pub(super) fn as_response_error(err: Error) -> Error {
     match err {
-        already @ (CoreError::InvalidResponse(_) | CoreError::Http { .. }) => already,
-        other => CoreError::InvalidResponse(other.to_string()),
+        already @ (Error::InvalidResponse(_) | Error::Http { .. }) => already,
+        other => Error::InvalidResponse(other.to_string()),
     }
 }
 
@@ -80,7 +84,7 @@ pub(super) fn as_response_error(err: CoreError) -> CoreError {
 pub(super) async fn signed_headers(
     request: &ProviderChatCompletionsRequest,
     body: &[u8],
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     use std::collections::BTreeMap;
     use std::time::SystemTime;
 
@@ -101,7 +105,7 @@ pub(super) async fn signed_headers(
         .iter()
         .any(|(name, _)| is_sigv4_computed_header(name))
     {
-        return Err(CoreError::Unsupported(
+        return Err(Error::Unsupported(
             "request forwards a header AWS SigV4 computes",
         ));
     }
@@ -137,9 +141,9 @@ pub(super) async fn signed_headers(
 pub(super) async fn signed_headers(
     request: &ProviderChatCompletionsRequest,
     _body: &[u8],
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     match &request.auth {
-        ChatCompletionsAuth::AwsSigV4 { .. } => Err(CoreError::Unsupported(
+        ChatCompletionsAuth::AwsSigV4 { .. } => Err(Error::Unsupported(
             "AWS SigV4 requires the bedrock-auth feature",
         )),
         _ => Ok(request.upstream_headers.clone()),
diff --git a/litellm-rust/crates/core/src/chat_completions/mod.rs b/litellm-rust/crates/core/src/chat_completions/mod.rs
index f30ac1a24bf..32dea17d202 100644
--- a/litellm-rust/crates/core/src/chat_completions/mod.rs
+++ b/litellm-rust/crates/core/src/chat_completions/mod.rs
@@ -6,6 +6,7 @@
 //! credentials, and it resolves the provider, translates the conversation,
 //! calls the provider, and returns a typed OpenAI-shaped response.
 
+use crate::Error;
 mod client;
 mod common_utils;
 pub mod conversation;
@@ -17,16 +18,15 @@ pub mod types;
 
 use serde_json::{Map, Value};
 
-use crate::error::CoreResult;
-
 use handler::execute_chat_completions_provider_call;
-use prepare::{parse_messages, prepare_chat_completions_call, resolve_provider_config};
+use prepare::{parse_messages, resolve_provider_config, resolve_request};
 use types::{ChatCompletionsRequest, ChatCompletionsResponse};
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub async fn chat_completions(
     request: ChatCompletionsRequest<'_>,
-) -> CoreResult<ChatCompletionsResponse> {
-    execute_chat_completions_provider_call(prepare_chat_completions_call(request)?).await
+) -> Result<ChatCompletionsResponse, Error> {
+    execute_chat_completions_provider_call(resolve_request(request)?).await
 }
 
 /// Whether the core would accept this request, without resolving credentials or
diff --git a/litellm-rust/crates/core/src/chat_completions/prepare.rs b/litellm-rust/crates/core/src/chat_completions/prepare.rs
index 1e1c8d1bafd..3be2ba21de4 100644
--- a/litellm-rust/crates/core/src/chat_completions/prepare.rs
+++ b/litellm-rust/crates/core/src/chat_completions/prepare.rs
@@ -1,17 +1,20 @@
 use serde_json::Value;
 
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::http_utils::has_header;
 use crate::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
 
 use super::common_utils::{chat_completions_provider_config, string_headers};
 use super::transformation::{ChatCompletionsAuth, ChatCompletionsProviderConfig};
-use super::types::{ChatCompletionsRequest, ChatMessage, ProviderChatCompletionsRequest};
+use super::types::{
+    ChatCompletionsRequest, ChatMessage, ProviderChatCompletionsRequest,
+    ResolvedChatCompletionsRequest,
+};
 
 pub(super) fn resolve_provider_config<'a>(
     model: &'a str,
     custom_llm_provider: Option<&'a str>,
-) -> CoreResult<(String, &'static dyn ChatCompletionsProviderConfig)> {
+) -> Result<(String, &'static dyn ChatCompletionsProviderConfig), Error> {
     let provider_info = get_custom_llm_provider(model, custom_llm_provider)
         .or_else(|| {
             custom_llm_provider.map(|provider| CustomLlmProvider {
@@ -20,41 +23,56 @@ pub(super) fn resolve_provider_config<'a>(
             })
         })
         .ok_or_else(|| {
-            CoreError::InvalidProvider(
+            Error::InvalidProvider(
                 "unable to resolve custom_llm_provider for chat completions request".to_string(),
             )
         })?;
     let config = chat_completions_provider_config(provider_info.custom_llm_provider)
-        .ok_or_else(|| CoreError::InvalidProvider(provider_info.custom_llm_provider.to_string()))?;
+        .ok_or_else(|| Error::InvalidProvider(provider_info.custom_llm_provider.to_string()))?;
     Ok((provider_info.model.to_string(), config))
 }
 
-pub(super) fn parse_messages(messages: Value) -> CoreResult<Vec<ChatMessage>> {
-    serde_json::from_value(messages).map_err(|err| {
-        CoreError::InvalidRequest(format!("invalid chat completions messages: {err}"))
-    })
+pub(super) fn parse_messages(messages: Value) -> Result<Vec<ChatMessage>, Error> {
+    serde_json::from_value(messages)
+        .map_err(|err| Error::InvalidRequest(format!("invalid chat completions messages: {err}")))
 }
 
-pub(super) fn prepare_chat_completions_call(
+pub(super) fn resolve_request(
     request: ChatCompletionsRequest<'_>,
-) -> CoreResult<ProviderChatCompletionsRequest> {
+) -> Result<ResolvedChatCompletionsRequest<'_>, Error> {
     let (model, config) = resolve_provider_config(request.model, request.custom_llm_provider)?;
-    let env_lookup = |key: &str| std::env::var(key).ok();
-
     let messages = parse_messages(request.messages)?;
     if messages.is_empty() {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "chat completions requires at least one message".to_string(),
         ));
     }
     if let Some(reason) = config.unsupported_reason(&messages, &request.optional_params) {
-        return Err(CoreError::Unsupported(reason.0));
+        return Err(Error::Unsupported(reason.0));
     }
+    Ok(ResolvedChatCompletionsRequest {
+        model,
+        config,
+        messages,
+        optional_params: request.optional_params,
+        api_key: request.api_key,
+        api_base: request.api_base,
+        extra_headers: request.extra_headers,
+        timeout: request.timeout,
+    })
+}
 
-    let mut headers = string_headers(request.extra_headers)?;
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+fn validate_environment(
+    request: &ResolvedChatCompletionsRequest<'_>,
+    model: &str,
+    config: &dyn ChatCompletionsProviderConfig,
+) -> Result<(Vec<(String, String)>, ChatCompletionsAuth), Error> {
+    let env_lookup = |key: &str| std::env::var(key).ok();
+    let mut headers = string_headers(request.extra_headers.clone())?;
     let auth = config.auth(
         request.api_key,
-        &model,
+        model,
         &request.optional_params,
         &env_lookup,
     )?;
@@ -95,7 +113,16 @@ pub(super) fn prepare_chat_completions_call(
             headers.push(((*name).to_string(), (*value).to_string()));
         }
     }
+    Ok((headers, auth))
+}
 
+pub(super) fn prepare_provider_request(
+    request: ResolvedChatCompletionsRequest<'_>,
+) -> Result<ProviderChatCompletionsRequest, Error> {
+    let (headers, auth) = validate_environment(&request, &request.model, request.config)?;
+    let model = request.model;
+    let config = request.config;
+    let env_lookup = |key: &str| std::env::var(key).ok();
     let url = config.complete_url(
         request.api_base,
         &model,
@@ -103,7 +130,7 @@ pub(super) fn prepare_chat_completions_call(
         &env_lookup,
     )?;
     let transformed =
-        config.transform_request(&model, messages, request.optional_params.clone())?;
+        config.transform_request(&model, request.messages, request.optional_params.clone())?;
 
     Ok(ProviderChatCompletionsRequest {
         model,
diff --git a/litellm-rust/crates/core/src/chat_completions/tests.rs b/litellm-rust/crates/core/src/chat_completions/tests.rs
index e2383723cb0..f8594dee447 100644
--- a/litellm-rust/crates/core/src/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/chat_completions/tests.rs
@@ -1,10 +1,16 @@
 use serde_json::{Map, Value, json};
 
-use crate::error::CoreError;
+use crate::error::Error;
 
-use super::prepare::prepare_chat_completions_call;
+use super::prepare::{prepare_provider_request, resolve_request};
 use super::transformation::ChatCompletionsAuth;
-use super::types::ChatCompletionsRequest;
+use super::types::{ChatCompletionsRequest, ProviderChatCompletionsRequest};
+
+fn prepare_chat_completions_call(
+    request: ChatCompletionsRequest<'_>,
+) -> Result<ProviderChatCompletionsRequest, Error> {
+    prepare_provider_request(resolve_request(request)?)
+}
 
 fn request<'a>(
     model: &'a str,
@@ -29,7 +35,7 @@ fn request<'a>(
 
 /// `ProviderChatCompletionsRequest` deliberately has no `Debug` (its headers
 /// carry resolved credentials), so unwrap the failure case by hand.
-fn decline(request: ChatCompletionsRequest<'_>) -> CoreError {
+fn decline(request: ChatCompletionsRequest<'_>) -> Error {
     match prepare_chat_completions_call(request) {
         Err(error) => error,
         Ok(prepared) => panic!("expected a decline, prepared a call to {}", prepared.url),
@@ -196,7 +202,7 @@ fn declines_an_unsupported_request_before_resolving_credentials() {
     call.api_key = None;
     // No api_key is set and no env is consulted: the gate must run first, so the
     // error is the decline rather than a missing-credential error.
-    assert_eq!(decline(call), CoreError::Unsupported("streaming"));
+    assert_eq!(decline(call), Error::Unsupported("streaming"));
 }
 
 #[test]
@@ -208,7 +214,7 @@ fn rejects_an_unknown_provider() {
             json!([{"role": "user", "content": "hi"}]),
             json!({}),
         )),
-        CoreError::InvalidProvider("openai".to_string())
+        Error::InvalidProvider("openai".to_string())
     );
 }
 
@@ -221,7 +227,7 @@ fn rejects_a_model_with_no_resolvable_provider() {
             json!([{"role": "user", "content": "hi"}]),
             json!({}),
         )),
-        CoreError::InvalidProvider(_)
+        Error::InvalidProvider(_)
     ));
 }
 
@@ -234,7 +240,7 @@ fn rejects_an_empty_or_malformed_message_list() {
             json!([]),
             json!({}),
         )),
-        CoreError::InvalidRequest("chat completions requires at least one message".to_string())
+        Error::InvalidRequest("chat completions requires at least one message".to_string())
     );
     assert!(matches!(
         decline(request(
@@ -243,7 +249,7 @@ fn rejects_an_empty_or_malformed_message_list() {
             json!("not a list"),
             json!({}),
         )),
-        CoreError::InvalidRequest(_)
+        Error::InvalidRequest(_)
     ));
 }
 
@@ -258,7 +264,7 @@ fn rejects_non_string_extra_headers() {
     call.extra_headers = Some(Map::from_iter([("x-trace".to_string(), json!(7))]));
     assert_eq!(
         decline(call),
-        CoreError::InvalidRequest(
+        Error::InvalidRequest(
             "chat completions extra_headers.x-trace must be a string, got number".to_string()
         )
     );
@@ -374,7 +380,7 @@ async fn a_forwarded_header_the_signer_computes_declines_to_python() {
             .await
             .expect_err("{forwarded} should decline instead of being signed");
         assert!(
-            matches!(error, CoreError::Unsupported(_)),
+            matches!(error, Error::Unsupported(_)),
             "{forwarded} declined as {error:?}, which the host would not fall back on"
         );
     }
@@ -727,7 +733,7 @@ mod round_trip {
         .expect_err("response cannot be normalized");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::InvalidResponse(_)),
+            matches!(err, Error::InvalidResponse(_)),
             "expected a post-send error, got {err:?}"
         );
     }
@@ -745,7 +751,7 @@ mod round_trip {
         .expect_err("response cannot be normalized");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::InvalidResponse(_)),
+            matches!(err, Error::InvalidResponse(_)),
             "expected a post-send error, got {err:?}"
         );
     }
@@ -763,7 +769,7 @@ mod round_trip {
         .expect_err("upstream rejects");
         handle.await.expect("server task");
         assert!(
-            matches!(err, CoreError::Http { status: 429, .. }),
+            matches!(err, Error::Http { status: 429, .. }),
             "expected a 429, got {err:?}"
         );
     }
@@ -787,7 +793,7 @@ mod round_trip {
         .await
         .expect_err("nothing is listening");
         assert!(
-            matches!(err, CoreError::Connect(_)),
+            matches!(err, Error::Connect(_)),
             "expected a pre-send connect failure, got {err:?}"
         );
     }
@@ -797,24 +803,24 @@ mod round_trip {
         use crate::chat_completions::handler::as_response_error;
 
         for original in [
-            CoreError::MissingField("usage"),
-            CoreError::Unsupported("non-text response content block"),
-            CoreError::InvalidRequest("whatever".to_string()),
-            CoreError::Auth("whatever".to_string()),
+            Error::MissingField("usage"),
+            Error::Unsupported("non-text response content block"),
+            Error::InvalidRequest("whatever".to_string()),
+            Error::Auth("whatever".to_string()),
         ] {
             let label = format!("{original:?}");
             assert!(
-                matches!(as_response_error(original), CoreError::InvalidResponse(_)),
+                matches!(as_response_error(original), Error::InvalidResponse(_)),
                 "{label} must not stay retryable once the provider has answered"
             );
         }
         // An upstream status is already unambiguous, so it survives intact.
         assert!(matches!(
-            as_response_error(CoreError::Http {
+            as_response_error(Error::Http {
                 status: 500,
                 body: "boom".to_string()
             }),
-            CoreError::Http { status: 500, .. }
+            Error::Http { status: 500, .. }
         ));
     }
 }
diff --git a/litellm-rust/crates/core/src/chat_completions/transformation.rs b/litellm-rust/crates/core/src/chat_completions/transformation.rs
index a30ce9dc77c..d7b9704c46c 100644
--- a/litellm-rust/crates/core/src/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/chat_completions/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::error::CoreResult;
-
 use super::types::{
     ChatCompletionsResponse, ChatMessage, ChatMessageContent, ProviderChatRequestData,
     ProviderChatResponseData,
@@ -39,7 +38,7 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth(
         &self,
@@ -47,7 +46,7 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth>;
+    ) -> Result<ChatCompletionsAuth, Error>;
 
     fn default_headers(&self) -> &'static [(&'static str, &'static str)] {
         &[("content-type", "application/json")]
@@ -63,9 +62,8 @@ pub trait ChatCompletionsProviderConfig: Sync {
         false
     }
 
-    /// Provider parameter names (post-mapping) the Rust path knows how to place
-    /// in the upstream body. Anything outside this set declines the request.
-    fn supported_params(&self) -> &'static [&'static str];
+    /// Supported OpenAI parameter names paired with their provider names.
+    fn supported_openai_params(&self) -> &'static [(&'static str, &'static str)];
 
     /// Parameters consumed as call configuration (credentials, endpoints)
     /// rather than placed in the body. Accepted, never serialized.
@@ -79,7 +77,7 @@ pub trait ChatCompletionsProviderConfig: Sync {
         optional_params: &Map<String, Value>,
     ) -> Option<Unsupported> {
         unsupported_param(
-            self.supported_params(),
+            self.supported_openai_params(),
             self.config_params(),
             optional_params,
         )
@@ -91,17 +89,17 @@ pub trait ChatCompletionsProviderConfig: Sync {
         model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData>;
+    ) -> Result<ProviderChatRequestData, Error>;
 
     fn transform_response(
         &self,
         model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse>;
+    ) -> Result<ChatCompletionsResponse, Error>;
 }
 
 pub fn unsupported_param(
-    supported: &'static [&'static str],
+    supported: &'static [(&'static str, &'static str)],
     config: &'static [&'static str],
     optional_params: &Map<String, Value>,
 ) -> Option<Unsupported> {
@@ -116,7 +114,9 @@ pub fn unsupported_param(
         .keys()
         .any(|key| {
             key != STREAM_PARAM
-                && !supported.contains(&key.as_str())
+                && !supported
+                    .iter()
+                    .any(|(_, provider_name)| *provider_name == key)
                 && !config.contains(&key.as_str())
         })
         .then_some(Unsupported("unrecognized request parameter"))
diff --git a/litellm-rust/crates/core/src/chat_completions/types.rs b/litellm-rust/crates/core/src/chat_completions/types.rs
index 35dd543a986..3238d09b6b5 100644
--- a/litellm-rust/crates/core/src/chat_completions/types.rs
+++ b/litellm-rust/crates/core/src/chat_completions/types.rs
@@ -22,6 +22,17 @@ pub struct ChatCompletionsRequest<'a> {
     pub timeout: Option<Duration>,
 }
 
+pub(super) struct ResolvedChatCompletionsRequest<'a> {
+    pub(super) model: String,
+    pub(super) config: &'static dyn ChatCompletionsProviderConfig,
+    pub(super) messages: Vec<ChatMessage>,
+    pub(super) optional_params: Map<String, Value>,
+    pub(super) api_key: Option<&'a str>,
+    pub(super) api_base: Option<&'a str>,
+    pub(super) extra_headers: Option<Map<String, Value>>,
+    pub(super) timeout: Option<Duration>,
+}
+
 pub(super) struct ProviderChatCompletionsRequest {
     pub(super) model: String,
     pub(super) config: &'static dyn ChatCompletionsProviderConfig,
diff --git a/litellm-rust/crates/core/src/constants.rs b/litellm-rust/crates/core/src/constants.rs
index e1ac0a4fc8f..a73961060eb 100644
--- a/litellm-rust/crates/core/src/constants.rs
+++ b/litellm-rust/crates/core/src/constants.rs
@@ -30,6 +30,8 @@ pub(crate) const CHAT_COMPLETIONS_TIMEOUT_SECS: u64 = 600;
 /// Connect timeout for chat completions provider calls, in seconds.
 pub(crate) const CHAT_COMPLETIONS_CONNECT_TIMEOUT_SECS: u64 = 10;
 
+pub(crate) const AUDIO_TRANSCRIPTION_TIMEOUT_SECS: u64 = 600;
+
 /// `object` field every non-streaming chat completion response carries.
 pub const CHAT_COMPLETION_OBJECT: &str = "chat.completion";
 
diff --git a/litellm-rust/crates/core/src/error.rs b/litellm-rust/crates/core/src/error.rs
index 739532f8cb5..db3fa2ec704 100644
--- a/litellm-rust/crates/core/src/error.rs
+++ b/litellm-rust/crates/core/src/error.rs
@@ -1,9 +1,7 @@
-use thiserror::Error;
+use thiserror::Error as ThisError;
 
-pub type CoreResult<T> = Result<T, CoreError>;
-
-#[derive(Debug, Error, PartialEq, Eq)]
-pub enum CoreError {
+#[derive(Debug, ThisError, PartialEq, Eq)]
+pub enum Error {
     #[error("expected {expected}, got {actual}")]
     InvalidType {
         expected: &'static str,
diff --git a/litellm-rust/crates/core/src/http_utils.rs b/litellm-rust/crates/core/src/http_utils.rs
index c541f50275b..3633130528d 100644
--- a/litellm-rust/crates/core/src/http_utils.rs
+++ b/litellm-rust/crates/core/src/http_utils.rs
@@ -3,7 +3,14 @@
 use serde_json::{Map, Value};
 
 use crate::constants::UPSTREAM_ERROR_BODY_MAX_CHARS;
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub async fn http_request(
+    request: reqwest::RequestBuilder,
+) -> Result<reqwest::Response, reqwest::Error> {
+    request.send().await
+}
 
 /// Bound an upstream error body before it crosses a host boundary, so provider
 /// bodies stay data-minimized.
@@ -18,7 +25,7 @@ pub fn truncate_error_body(body: &str) -> String {
 pub fn string_headers(
     context: &'static str,
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     extra_headers
         .unwrap_or_default()
         .into_iter()
@@ -27,7 +34,7 @@ pub fn string_headers(
                 .as_str()
                 .map(|value| (key.clone(), value.to_string()))
                 .ok_or_else(|| {
-                    CoreError::InvalidRequest(format!(
+                    Error::InvalidRequest(format!(
                         "{context} extra_headers.{key} must be a string, got {}",
                         json_type_name(&value)
                     ))
@@ -81,7 +88,7 @@ mod tests {
         let err = string_headers("chat completions", Some(headers)).expect_err("non-string value");
         assert_eq!(
             err,
-            CoreError::InvalidRequest(
+            Error::InvalidRequest(
                 "chat completions extra_headers.x-trace must be a string, got number".to_string()
             )
         );
diff --git a/litellm-rust/crates/core/src/lib.rs b/litellm-rust/crates/core/src/lib.rs
index dce4a425ea0..0e18d24e5d8 100644
--- a/litellm-rust/crates/core/src/lib.rs
+++ b/litellm-rust/crates/core/src/lib.rs
@@ -13,4 +13,4 @@ pub mod responses;
 pub mod router;
 pub mod routing_utils;
 
-pub use error::{CoreError, CoreResult};
+pub use error::Error;
diff --git a/litellm-rust/crates/core/src/messages/common_utils.rs b/litellm-rust/crates/core/src/messages/common_utils.rs
index a14dffbc1fe..8f0f6652fa4 100644
--- a/litellm-rust/crates/core/src/messages/common_utils.rs
+++ b/litellm-rust/crates/core/src/messages/common_utils.rs
@@ -1,9 +1,8 @@
-use serde_json::{Map, Value};
-
-use crate::error::CoreResult;
+use crate::Error;
 use crate::http_utils::string_headers as shared_string_headers;
 use crate::providers::anthropic::messages::transformation::ANTHROPIC_MESSAGES_CONFIG;
 use crate::providers::azure_ai::messages::transformation::AZURE_ANTHROPIC_MESSAGES_CONFIG;
+use serde_json::{Map, Value};
 
 use super::transformation::AnthropicMessagesProviderConfig;
 
@@ -11,6 +10,7 @@ pub(super) use crate::http_utils::{has_bearer_auth, has_header, truncate_error_b
 
 const HEADER_CONTEXT: &str = "messages";
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(super) fn messages_provider_config(
     provider: &str,
 ) -> Option<&'static dyn AnthropicMessagesProviderConfig> {
@@ -23,6 +23,6 @@ pub(super) fn messages_provider_config(
 
 pub(super) fn string_headers(
     extra_headers: Option<Map<String, Value>>,
-) -> CoreResult<Vec<(String, String)>> {
+) -> Result<Vec<(String, String)>, Error> {
     shared_string_headers(HEADER_CONTEXT, extra_headers)
 }
diff --git a/litellm-rust/crates/core/src/messages/handler.rs b/litellm-rust/crates/core/src/messages/handler.rs
index 1c895f66eba..61ff81bcdc8 100644
--- a/litellm-rust/crates/core/src/messages/handler.rs
+++ b/litellm-rust/crates/core/src/messages/handler.rs
@@ -1,13 +1,17 @@
 use crate::constants::ANTHROPIC_MESSAGES_PROVIDER;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
+use crate::http_utils::http_request;
 
 use super::client::http_client;
 use super::common_utils::truncate_error_body;
-use super::types::{AnthropicMessagesResponse, ProviderMessagesRequest};
+use super::prepare::prepare_provider_request;
+use super::types::{AnthropicMessagesResponse, MessagesRequest};
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub(super) async fn execute_messages_provider_call(
-    request: ProviderMessagesRequest,
-) -> CoreResult<AnthropicMessagesResponse> {
+    request: MessagesRequest<'_>,
+) -> Result<AnthropicMessagesResponse, Error> {
+    let request = prepare_provider_request(request)?;
     let mut request_builder = http_client().post(&request.url).json(&request.body);
     for (key, value) in &request.upstream_headers {
         request_builder = request_builder.header(key, value);
@@ -16,35 +20,34 @@ pub(super) async fn execute_messages_provider_call(
         request_builder = request_builder.timeout(duration);
     }
 
-    let response = request_builder
-        .send()
+    let response = http_request(request_builder)
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     let status = response.status();
     let text = response
         .text()
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
 
     if !status.is_success() {
-        return Err(CoreError::Http {
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
     }
 
-    let response = serde_json::from_str(&text).map_err(|err| {
-        CoreError::InvalidResponse(format!("invalid messages response JSON: {err}"))
-    })?;
+    let response = serde_json::from_str(&text)
+        .map_err(|err| Error::InvalidResponse(format!("invalid messages response JSON: {err}")))?;
     request.config.transform_response(&request.model, response)
 }
 
 pub(super) async fn execute_messages_provider_stream(
-    request: ProviderMessagesRequest,
-) -> CoreResult<reqwest::Response> {
+    request: MessagesRequest<'_>,
+) -> Result<reqwest::Response, Error> {
+    let request = prepare_provider_request(request)?;
     if request.provider != ANTHROPIC_MESSAGES_PROVIDER {
-        return Err(CoreError::InvalidRequest(
+        return Err(Error::InvalidRequest(
             "streaming messages is not supported for this provider".to_string(),
         ));
     }
@@ -57,17 +60,16 @@ pub(super) async fn execute_messages_provider_stream(
         request_builder = request_builder.timeout(duration);
     }
 
-    let response = request_builder
-        .send()
+    let response = http_request(request_builder)
         .await
-        .map_err(|err| CoreError::Network(err.to_string()))?;
+        .map_err(|err| Error::Network(err.to_string()))?;
     let status = response.status();
     if !status.is_success() {
         let text = response
             .text()
             .await
-            .map_err(|err| CoreError::Network(err.to_string()))?;
-        return Err(CoreError::Http {
+            .map_err(|err| Error::Network(err.to_string()))?;
+        return Err(Error::Http {
             status: status.as_u16(),
             body: truncate_error_body(&text),
         });
diff --git a/litellm-rust/crates/core/src/messages/mod.rs b/litellm-rust/crates/core/src/messages/mod.rs
index acb36d89daf..cfa8bda1104 100644
--- a/litellm-rust/crates/core/src/messages/mod.rs
+++ b/litellm-rust/crates/core/src/messages/mod.rs
@@ -7,6 +7,7 @@
 //! is the streaming variant; it hands the raw upstream response back so a host
 //! can splice the event stream to its own caller.
 
+use crate::Error;
 mod client;
 mod common_utils;
 mod handler;
@@ -14,18 +15,16 @@ mod prepare;
 pub mod transformation;
 pub mod types;
 
-use crate::error::CoreResult;
-
 use handler::{execute_messages_provider_call, execute_messages_provider_stream};
-use prepare::prepare_messages_call;
 use types::{AnthropicMessagesResponse, MessagesRequest};
 
-pub async fn messages(request: MessagesRequest<'_>) -> CoreResult<AnthropicMessagesResponse> {
-    execute_messages_provider_call(prepare_messages_call(request)?).await
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub async fn messages(request: MessagesRequest<'_>) -> Result<AnthropicMessagesResponse, Error> {
+    execute_messages_provider_call(request).await
 }
 
-pub async fn messages_stream(request: MessagesRequest<'_>) -> CoreResult<reqwest::Response> {
-    execute_messages_provider_stream(prepare_messages_call(request)?).await
+pub async fn messages_stream(request: MessagesRequest<'_>) -> Result<reqwest::Response, Error> {
+    execute_messages_provider_stream(request).await
 }
 
 #[cfg(test)]
diff --git a/litellm-rust/crates/core/src/messages/prepare.rs b/litellm-rust/crates/core/src/messages/prepare.rs
index 94b5b1eaed7..ec83d03f535 100644
--- a/litellm-rust/crates/core/src/messages/prepare.rs
+++ b/litellm-rust/crates/core/src/messages/prepare.rs
@@ -1,13 +1,14 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::routing_utils::provider::{CustomLlmProvider, get_custom_llm_provider};
 
 use super::common_utils::{has_bearer_auth, has_header, messages_provider_config, string_headers};
-use super::transformation::MessagesAuthStrategy;
+use super::transformation::{AnthropicMessagesProviderConfig, MessagesAuthStrategy};
 use super::types::{MessagesRequest, ProviderMessagesRequest};
+use serde_json::{Map, Value};
 
-pub(super) fn prepare_messages_call(
+pub(super) fn prepare_provider_request(
     request: MessagesRequest<'_>,
-) -> CoreResult<ProviderMessagesRequest> {
+) -> Result<ProviderMessagesRequest, Error> {
     let provider_info = get_custom_llm_provider(request.model, request.custom_llm_provider)
         .or_else(|| {
             request
@@ -18,7 +19,7 @@ pub(super) fn prepare_messages_call(
                 })
         })
         .ok_or_else(|| {
-            CoreError::InvalidProvider(
+            Error::InvalidProvider(
                 "unable to resolve custom_llm_provider for messages request".to_string(),
             )
         })?;
@@ -26,16 +27,49 @@ pub(super) fn prepare_messages_call(
     let provider = provider_info.custom_llm_provider;
 
     let config = messages_provider_config(provider)
-        .ok_or_else(|| CoreError::InvalidProvider(provider.to_string()))?;
+        .ok_or_else(|| Error::InvalidProvider(provider.to_string()))?;
     let env_lookup = |key: &str| std::env::var(key).ok();
 
-    let mut headers = string_headers(request.extra_headers)?;
+    let headers =
+        validate_environment(config, request.extra_headers, request.api_key, &env_lookup)?;
+
+    let typed_request = serde_json::from_value(request.body).map_err(|err| {
+        Error::InvalidRequest(format!("invalid Anthropic messages request: {err}"))
+    })?;
+    let transformed = config.transform_request(typed_request)?;
+    let body = serde_json::to_value(transformed).map_err(|err| {
+        Error::InvalidRequest(format!(
+            "failed to serialize Anthropic messages request: {err}"
+        ))
+    })?;
+
+    let url = config.complete_url(request.api_base, &model, &env_lookup)?;
+
+    Ok(ProviderMessagesRequest {
+        provider: provider.to_string(),
+        model,
+        config,
+        url,
+        body,
+        upstream_headers: headers,
+        timeout: request.timeout,
+    })
+}
+
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+fn validate_environment(
+    config: &dyn AnthropicMessagesProviderConfig,
+    extra_headers: Option<Map<String, Value>>,
+    api_key: Option<&str>,
+    env_lookup: &dyn Fn(&str) -> Option<String>,
+) -> Result<Vec<(String, String)>, Error> {
+    let mut headers = string_headers(extra_headers)?;
 
     let auth_strategy = config.auth_strategy();
     let already_authorized = has_header(&headers, auth_strategy.header_name())
         || (config.accepts_bearer_auth() && has_bearer_auth(&headers));
     if !already_authorized {
-        let api_key = config.resolve_api_key(request.api_key, &env_lookup)?;
+        let api_key = config.resolve_api_key(api_key, env_lookup)?;
         let auth_header = match auth_strategy {
             MessagesAuthStrategy::Bearer => {
                 ("authorization".to_string(), format!("Bearer {api_key}"))
@@ -51,24 +85,5 @@ pub(super) fn prepare_messages_call(
         }
     }
 
-    let url = config.complete_url(request.api_base, &model, &env_lookup)?;
-    let typed_request = serde_json::from_value(request.body).map_err(|err| {
-        CoreError::InvalidRequest(format!("invalid Anthropic messages request: {err}"))
-    })?;
-    let transformed = config.transform_request(typed_request)?;
-    let body = serde_json::to_value(transformed).map_err(|err| {
-        CoreError::InvalidRequest(format!(
-            "failed to serialize Anthropic messages request: {err}"
-        ))
-    })?;
-
-    Ok(ProviderMessagesRequest {
-        provider: provider.to_string(),
-        model,
-        config,
-        url,
-        body,
-        upstream_headers: headers,
-        timeout: request.timeout,
-    })
+    Ok(headers)
 }
diff --git a/litellm-rust/crates/core/src/messages/tests.rs b/litellm-rust/crates/core/src/messages/tests.rs
index 9fc1763683b..df9f7051011 100644
--- a/litellm-rust/crates/core/src/messages/tests.rs
+++ b/litellm-rust/crates/core/src/messages/tests.rs
@@ -4,7 +4,7 @@ use serde_json::{Map, Value, json};
 use tokio::io::{AsyncReadExt, AsyncWriteExt};
 use tokio::net::{TcpListener, TcpStream};
 
-use crate::error::CoreError;
+use crate::error::Error;
 
 use super::common_utils::{
     has_bearer_auth, has_header, messages_provider_config, string_headers, truncate_error_body,
@@ -77,7 +77,7 @@ fn truncate_error_body_caps_long_payloads() {
 fn string_headers_rejects_non_string_values() {
     let headers = json!({"x-count": 3}).as_object().unwrap().clone();
     let err = string_headers(Some(headers)).expect_err("non-string header rejected");
-    assert!(matches!(err, CoreError::InvalidRequest(_)));
+    assert!(matches!(err, Error::InvalidRequest(_)));
 }
 
 #[test]
@@ -341,7 +341,7 @@ async fn messages_requires_auth_when_no_key_and_no_header() {
     .await
     .expect_err("missing auth errors");
 
-    assert!(matches!(err, CoreError::Auth(_)));
+    assert!(matches!(err, Error::Auth(_)));
 }
 
 #[tokio::test]
@@ -420,7 +420,7 @@ async fn messages_maps_provider_error_status_to_http_error() {
     .await
     .expect_err("provider error propagates");
 
-    assert!(matches!(err, CoreError::Http { status: 401, .. }));
+    assert!(matches!(err, Error::Http { status: 401, .. }));
 }
 
 #[tokio::test]
@@ -437,5 +437,5 @@ async fn messages_rejects_unsupported_provider() {
     .await
     .expect_err("unsupported provider errors");
 
-    assert!(matches!(err, CoreError::InvalidProvider(provider) if provider == "openai"));
+    assert!(matches!(err, Error::InvalidProvider(provider) if provider == "openai"));
 }
diff --git a/litellm-rust/crates/core/src/messages/transformation.rs b/litellm-rust/crates/core/src/messages/transformation.rs
index b478e20d24b..a5904c085a0 100644
--- a/litellm-rust/crates/core/src/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/messages/transformation.rs
@@ -1,6 +1,5 @@
-use crate::error::CoreResult;
-
 use super::types::{AnthropicMessagesRequest, AnthropicMessagesResponse};
+use crate::Error;
 
 #[derive(Clone, Copy, Debug, PartialEq, Eq)]
 pub enum MessagesAuthStrategy {
@@ -23,13 +22,13 @@ pub trait AnthropicMessagesProviderConfig: Sync {
         api_base: Option<&str>,
         model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn resolve_api_key(
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn auth_strategy(&self) -> MessagesAuthStrategy {
         MessagesAuthStrategy::Header("x-api-key")
@@ -46,18 +45,20 @@ pub trait AnthropicMessagesProviderConfig: Sync {
         ]
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_request(
         &self,
         request: AnthropicMessagesRequest,
-    ) -> CoreResult<AnthropicMessagesRequest> {
+    ) -> Result<AnthropicMessagesRequest, Error> {
         Ok(request)
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_response(
         &self,
         _model: &str,
         response: AnthropicMessagesResponse,
-    ) -> CoreResult<AnthropicMessagesResponse> {
+    ) -> Result<AnthropicMessagesResponse, Error> {
         Ok(response)
     }
 }
diff --git a/litellm-rust/crates/core/src/ocr/transformation.rs b/litellm-rust/crates/core/src/ocr/transformation.rs
index cb3e735e533..ad484c8f968 100644
--- a/litellm-rust/crates/core/src/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/ocr/transformation.rs
@@ -1,7 +1,6 @@
+use crate::Error;
 use serde_json::{Map, Value};
 
-use crate::CoreResult;
-
 use super::types::{OcrRequestData, OcrResponseData};
 
 #[derive(Clone, Copy, Debug, PartialEq, Eq)]
@@ -28,6 +27,7 @@ pub enum OcrResponseHandling {
 pub trait OcrProviderConfig: Sync {
     fn supported_ocr_params(&self) -> &'static [&'static str];
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn map_ocr_params(&self, non_default_params: &Map<String, Value>) -> Map<String, Value> {
         let mut mapped_params = Map::new();
         for (param, value) in non_default_params {
@@ -43,13 +43,13 @@ pub trait OcrProviderConfig: Sync {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData>;
+    ) -> Result<OcrRequestData, Error>;
 
     fn transform_ocr_response(
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData>;
+    ) -> Result<OcrResponseData, Error>;
 
     fn complete_url(
         &self,
@@ -57,13 +57,32 @@ pub trait OcrProviderConfig: Sync {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
 
     fn resolve_api_key(
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String>;
+    ) -> Result<String, Error>;
+
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+    fn validate_environment(
+        &self,
+        headers: Vec<(String, String)>,
+        api_key: Option<&str>,
+        env_lookup: &dyn Fn(&str) -> Option<String>,
+    ) -> Result<Vec<(String, String)>, Error> {
+        let strategy = self.auth_strategy();
+        if crate::http_utils::has_header(&headers, strategy.header_name()) {
+            return Ok(headers);
+        }
+        let api_key = self.resolve_api_key(api_key, env_lookup)?;
+        let auth_header = match strategy {
+            OcrAuthStrategy::Bearer => ("Authorization".to_string(), format!("Bearer {api_key}")),
+            OcrAuthStrategy::Header(name) => (name.to_string(), api_key),
+        };
+        Ok(std::iter::once(auth_header).chain(headers).collect())
+    }
 
     fn auth_strategy(&self) -> OcrAuthStrategy {
         OcrAuthStrategy::Bearer
diff --git a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
index 4534ac0182c..b22de6c47de 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/tests.rs
@@ -1,4 +1,5 @@
 use super::*;
+use crate::Error;
 use serde_json::json;
 
 fn messages(value: Value) -> Vec<ChatMessage> {
@@ -19,7 +20,7 @@ fn transform(model: &str, msgs: Value, opts: Value) -> Value {
         .body
 }
 
-fn transform_response(body: Value) -> CoreResult<ChatCompletionsResponse> {
+fn transform_response(body: Value) -> Result<ChatCompletionsResponse, Error> {
     ANTHROPIC_CHAT_COMPLETIONS_CONFIG
         .transform_response("claude-sonnet-4-5", ProviderChatResponseData { body })
 }
@@ -390,29 +391,26 @@ fn declines_a_response_carrying_a_non_text_block() {
         "usage": {"input_tokens": 1, "output_tokens": 1}
     }))
     .expect_err("non-text block");
-    assert_eq!(
-        err,
-        CoreError::Unsupported("non-text response content block")
-    );
+    assert_eq!(err, Error::Unsupported("non-text response content block"));
 }
 
 #[test]
 fn errors_on_a_response_missing_required_fields() {
     assert_eq!(
         transform_response(json!("nope")).expect_err("not an object"),
-        CoreError::InvalidResponse("messages response is not an object".to_string())
+        Error::InvalidResponse("messages response is not an object".to_string())
     );
     assert_eq!(
         transform_response(json!({"model": "m", "usage": {}})).expect_err("no content"),
-        CoreError::MissingField("content")
+        Error::MissingField("content")
     );
     assert_eq!(
         transform_response(json!({"model": "m", "content": []})).expect_err("no usage"),
-        CoreError::MissingField("usage")
+        Error::MissingField("usage")
     );
     assert_eq!(
         transform_response(json!({"content": [], "usage": {}})).expect_err("no model"),
-        CoreError::MissingField("model")
+        Error::MissingField("model")
     );
 }
 
diff --git a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
index 3658642b539..a7d5a8ad0cf 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/chat_completions/transformation.rs
@@ -10,7 +10,7 @@ use crate::chat_completions::types::{
     ProviderChatRequestData, ProviderChatResponseData,
 };
 use crate::constants::ANTHROPIC_OAUTH_TOKEN_PREFIX;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::providers::anthropic::messages::transformation::{
     complete_anthropic_url, resolve_anthropic_api_key,
 };
@@ -27,7 +27,12 @@ use crate::chat_completions::response_utils::{finish_reason_for, unix_now, usage
 /// per-model gate inside `transform_request`, the function this route replaces.
 /// Forwarding it would send `top_k` to a model that removed sampling params and
 /// take a 400 after the call, where Python drops it and succeeds.
-const SUPPORTED_PARAMS: &[&str] = &["max_tokens", "temperature", "top_p", "stop_sequences"];
+const SUPPORTED_PARAMS: &[(&str, &str)] = &[
+    ("max_tokens", "max_tokens"),
+    ("temperature", "temperature"),
+    ("top_p", "top_p"),
+    ("stop", "stop_sequences"),
+];
 
 pub struct AnthropicChatCompletionsConfig;
 
@@ -74,7 +79,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_anthropic_url(api_base, env_lookup))
     }
 
@@ -84,7 +89,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth> {
+    ) -> Result<ChatCompletionsAuth, Error> {
         Ok(ChatCompletionsAuth::Header {
             name: "x-api-key",
             value: resolve_anthropic_api_key(api_key, env_lookup)?,
@@ -112,7 +117,8 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         })
     }
 
-    fn supported_params(&self) -> &'static [&'static str] {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+    fn supported_openai_params(&self) -> &'static [(&'static str, &'static str)] {
         SUPPORTED_PARAMS
     }
 
@@ -121,7 +127,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         messages: &[ChatMessage],
         optional_params: &Map<String, Value>,
     ) -> Option<Unsupported> {
-        unsupported_param(SUPPORTED_PARAMS, &[], optional_params)
+        unsupported_param(self.supported_openai_params(), &[], optional_params)
             .or_else(|| messages.iter().find_map(unsupported_message))
             // Anthropic rejects a request whose first turn is not a user turn.
             // Python only repairs that under `litellm.modify_params`, which the
@@ -132,30 +138,33 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
             })
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_request(
         &self,
         model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData> {
+    ) -> Result<ProviderChatRequestData, Error> {
         Ok(ProviderChatRequestData {
             body: anthropic_body(model, &build_conversation(&messages), optional_params),
         })
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_response(
         &self,
         _model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse> {
-        let body = response.body.as_object().ok_or_else(|| {
-            CoreError::InvalidResponse("messages response is not an object".into())
-        })?;
+    ) -> Result<ChatCompletionsResponse, Error> {
+        let body = response
+            .body
+            .as_object()
+            .ok_or_else(|| Error::InvalidResponse("messages response is not an object".into()))?;
 
         let content = body
             .get("content")
             .and_then(Value::as_array)
-            .ok_or(CoreError::MissingField("content"))?;
+            .ok_or(Error::MissingField("content"))?;
         // The route declines tool and thinking requests, so a non-text block
         // means the response carries something this path never asked for.
         // Decline rather than silently dropping it; the host falls back.
@@ -163,7 +172,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
             .iter()
             .any(|block| block.get("type").and_then(Value::as_str) != Some("text"))
         {
-            return Err(CoreError::Unsupported("non-text response content block"));
+            return Err(Error::Unsupported("non-text response content block"));
         }
         let text: String = content
             .iter()
@@ -173,7 +182,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
         let usage = body
             .get("usage")
             .and_then(Value::as_object)
-            .ok_or(CoreError::MissingField("usage"))?;
+            .ok_or(Error::MissingField("usage"))?;
         let field = |name: &str| usage.get(name).and_then(Value::as_u64).unwrap_or(0);
 
         Ok(ChatCompletionsResponse {
@@ -181,7 +190,7 @@ impl ChatCompletionsProviderConfig for AnthropicChatCompletionsConfig {
             model: body
                 .get("model")
                 .and_then(Value::as_str)
-                .ok_or(CoreError::MissingField("model"))?
+                .ok_or(Error::MissingField("model"))?
                 .to_string(),
             choices: vec![ChatCompletionsChoice {
                 index: 0,
diff --git a/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs b/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
index 829f2260d3c..f31b961e78a 100644
--- a/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/anthropic/messages/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::messages::transformation::{AnthropicMessagesProviderConfig, MessagesAuthStrategy};
 
 const ANTHROPIC_API_KEY_ENV: &str = "ANTHROPIC_API_KEY";
@@ -17,12 +17,12 @@ pub fn non_empty(value: Option<&str>) -> Option<&str> {
 pub fn resolve_anthropic_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(api_key)
         .map(str::to_string)
         .or_else(|| env_lookup(ANTHROPIC_API_KEY_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Anthropic API Key - Set `api_key` or the ANTHROPIC_API_KEY \
                  environment variable"
                     .to_string(),
@@ -47,12 +47,13 @@ pub fn complete_anthropic_url(
 }
 
 impl AnthropicMessagesProviderConfig for AnthropicMessagesConfig {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn complete_url(
         &self,
         api_base: Option<&str>,
         _model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_anthropic_url(api_base, env_lookup))
     }
 
@@ -60,7 +61,7 @@ impl AnthropicMessagesProviderConfig for AnthropicMessagesConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_anthropic_api_key(api_key, env_lookup)
     }
 
@@ -121,7 +122,7 @@ mod tests {
         );
         assert!(matches!(
             resolve_anthropic_api_key(None, &|_| None).expect_err("missing key"),
-            CoreError::Auth(_)
+            Error::Auth(_)
         ));
     }
 
diff --git a/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs b/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
index 7b958c77ba3..b8ca10461fb 100644
--- a/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/azure_ai/messages/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use crate::messages::transformation::{AnthropicMessagesProviderConfig, MessagesAuthStrategy};
 use crate::messages::types::{
     AnthropicMessage, AnthropicMessagesRequest, AnthropicMessagesResponse, ContentBlock,
@@ -28,12 +28,12 @@ pub const AZURE_ANTHROPIC_MESSAGES_CONFIG: AzureAnthropicMessagesConfig =
 pub fn resolve_azure_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(api_key)
         .map(str::to_string)
         .or_else(|| env_lookup(AZURE_API_KEY_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Azure API Key - Set `api_key` or the AZURE_API_KEY environment variable"
                     .to_string(),
             )
@@ -43,12 +43,12 @@ pub fn resolve_azure_api_key(
 pub fn complete_azure_anthropic_url(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let api_base = non_empty(api_base)
         .map(str::to_string)
         .or_else(|| env_lookup(AZURE_API_BASE_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Azure API Base - Set `api_base` or the AZURE_API_BASE environment variable. \
                  Expected format: https://<resource-name>.services.ai.azure.com/anthropic"
                     .to_string(),
@@ -142,12 +142,13 @@ fn fold_system_role_messages(request: AnthropicMessagesRequest) -> AnthropicMess
 }
 
 impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn complete_url(
         &self,
         api_base: Option<&str>,
         _model: &str,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_azure_anthropic_url(api_base, env_lookup)
     }
 
@@ -155,7 +156,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_azure_api_key(api_key, env_lookup)
     }
 
@@ -174,7 +175,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
     fn transform_request(
         &self,
         request: AnthropicMessagesRequest,
-    ) -> CoreResult<AnthropicMessagesRequest> {
+    ) -> Result<AnthropicMessagesRequest, Error> {
         let mut request = fold_system_role_messages(request);
         if let Some(system) = request.system.as_mut() {
             strip_scope_from_system(system);
@@ -190,7 +191,7 @@ impl AnthropicMessagesProviderConfig for AzureAnthropicMessagesConfig {
         &self,
         model: &str,
         response: AnthropicMessagesResponse,
-    ) -> CoreResult<AnthropicMessagesResponse> {
+    ) -> Result<AnthropicMessagesResponse, Error> {
         self.anthropic.transform_response(model, response)
     }
 }
@@ -268,7 +269,7 @@ mod tests {
             "https://env.services.ai.azure.com/anthropic/v1/messages"
         );
         let err = complete_azure_anthropic_url(Some("  "), &|_| None).expect_err("missing base");
-        assert!(matches!(err, CoreError::Auth(_)));
+        assert!(matches!(err, Error::Auth(_)));
     }
 
     #[test]
@@ -284,7 +285,7 @@ mod tests {
         );
         assert!(matches!(
             resolve_azure_api_key(None, &|_| None).expect_err("missing key"),
-            CoreError::Auth(_)
+            Error::Auth(_)
         ));
     }
 
diff --git a/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
index eabd15677cc..b26a7925e8a 100644
--- a/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/azure_ai/ocr/transformation.rs
@@ -1,6 +1,6 @@
 use std::collections::BTreeSet;
 
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::{OcrAuthStrategy, OcrProviderConfig, OcrResponseHandling};
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value, json};
@@ -32,17 +32,17 @@ fn resolve_value(
     env_name: &str,
     env_lookup: &dyn Fn(&str) -> Option<String>,
     missing_message: &str,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     non_empty(explicit)
         .map(str::to_string)
         .or_else(|| env_lookup(env_name).filter(|value| !value.trim().is_empty()))
-        .ok_or_else(|| CoreError::Auth(missing_message.to_string()))
+        .ok_or_else(|| Error::Auth(missing_message.to_string()))
 }
 
 pub fn resolve_azure_ai_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_key,
         AZURE_AI_API_KEY_ENV,
@@ -54,7 +54,7 @@ pub fn resolve_azure_ai_api_key(
 pub fn resolve_azure_ai_api_base(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_base,
         AZURE_AI_API_BASE_ENV,
@@ -66,7 +66,7 @@ pub fn resolve_azure_ai_api_base(
 pub fn complete_azure_ai_url(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let base = resolve_azure_ai_api_base(api_base, env_lookup)?;
     Ok(format!(
         "{}/providers/mistral/azure/ocr",
@@ -77,7 +77,7 @@ pub fn complete_azure_ai_url(
 pub fn resolve_document_intelligence_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_key,
         AZURE_DOCUMENT_INTELLIGENCE_API_KEY_ENV,
@@ -89,7 +89,7 @@ pub fn resolve_document_intelligence_api_key(
 pub fn resolve_document_intelligence_endpoint(
     api_base: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     resolve_value(
         api_base,
         AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT_ENV,
@@ -127,7 +127,7 @@ fn pages_token_is_valid(token: &str) -> bool {
     }
 }
 
-fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
+fn normalize_pages_param(pages: &Value) -> Result<Option<String>, Error> {
     match pages {
         Value::String(value) => {
             let normalized = value
@@ -138,7 +138,7 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
             if normalized.split(',').all(pages_token_is_valid) {
                 Ok(Some(normalized))
             } else {
-                Err(CoreError::InvalidRequest(format!(
+                Err(Error::InvalidRequest(format!(
                     "Invalid `pages` string for Azure Document Intelligence: {value:?}. Expected format like '1-3,5,7-9'."
                 )))
             }
@@ -152,7 +152,7 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
                 for value in values {
                     let page = value.as_i64().expect("checked is_i64");
                     if page < 0 {
-                        return Err(CoreError::InvalidRequest(
+                        return Err(Error::InvalidRequest(
                             "`pages` integers must be >= 0 (Mistral 0-based indices)".to_string(),
                         ));
                     }
@@ -176,16 +176,16 @@ fn normalize_pages_param(pages: &Value) -> CoreResult<Option<String>> {
                 if normalized.split(',').all(pages_token_is_valid) {
                     return Ok(Some(normalized));
                 }
-                return Err(CoreError::InvalidRequest(format!(
+                return Err(Error::InvalidRequest(format!(
                     "Invalid `pages` list for Azure Document Intelligence: {values:?}. Expected tokens like '1' or '3-5'."
                 )));
             }
-            Err(CoreError::InvalidRequest(
+            Err(Error::InvalidRequest(
                 "`pages` must be a list[int] (0-based, Mistral-style) or a string like '1-3,5,7-9'."
                     .to_string(),
             ))
         }
-        _ => Err(CoreError::InvalidRequest(
+        _ => Err(Error::InvalidRequest(
             "`pages` must be a list[int] (0-based, Mistral-style) or a string like '1-3,5,7-9'."
                 .to_string(),
         )),
@@ -197,7 +197,7 @@ pub fn complete_document_intelligence_url(
     model: &str,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let endpoint = resolve_document_intelligence_endpoint(api_base, env_lookup)?;
     let mut url = format!(
         "{}/documentintelligence/documentModels/{}:analyze?api-version={}",
@@ -216,20 +216,20 @@ pub fn complete_document_intelligence_url(
     Ok(url)
 }
 
-fn document_url_from_mistral_document(document: &Value) -> CoreResult<&str> {
-    let object = document.as_object().ok_or_else(|| CoreError::InvalidType {
+fn document_url_from_mistral_document(document: &Value) -> Result<&str, Error> {
+    let object = document.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(document),
     })?;
     let doc_type = object
         .get("type")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("document.type"))?;
+        .ok_or(Error::MissingField("document.type"))?;
     let field_name = match doc_type {
         "document_url" => "document_url",
         "image_url" => "image_url",
         other => {
-            return Err(CoreError::InvalidRequest(format!(
+            return Err(Error::InvalidRequest(format!(
                 "Invalid document type: {other}. Must be 'document_url' or 'image_url'"
             )));
         }
@@ -238,7 +238,7 @@ fn document_url_from_mistral_document(document: &Value) -> CoreResult<&str> {
         .get(field_name)
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField(field_name))
+        .ok_or(Error::MissingField(field_name))
 }
 
 fn extract_base64_from_data_uri(data_uri: &str) -> &str {
@@ -290,7 +290,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
     }
 
@@ -298,7 +298,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
     }
 
@@ -308,7 +308,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         _model: &str,
         _optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_azure_ai_url(api_base, env_lookup)
     }
 
@@ -316,7 +316,7 @@ impl OcrProviderConfig for AzureAiOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_azure_ai_api_key(api_key, env_lookup)
     }
 
@@ -335,7 +335,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         _model: &str,
         document: Value,
         _optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         let document_url = document_url_from_mistral_document(&document)?;
         let mut data = Map::new();
         if document_url.starts_with("data:") {
@@ -359,19 +359,19 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
         let status = response
             .get("status")
             .and_then(Value::as_str)
-            .ok_or(CoreError::MissingField("status"))?;
+            .ok_or(Error::MissingField("status"))?;
         if status != "succeeded" {
-            return Err(CoreError::InvalidResponse(format!(
+            return Err(Error::InvalidResponse(format!(
                 "Azure Document Intelligence analysis failed with status: {status}"
             )));
         }
@@ -414,7 +414,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_document_intelligence_url(api_base, model, optional_params, env_lookup)
     }
 
@@ -422,7 +422,7 @@ impl OcrProviderConfig for AzureDocumentIntelligenceOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_document_intelligence_api_key(api_key, env_lookup)
     }
 
diff --git a/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs b/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
index 5e885734182..9bf1f73a74d 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/audio_transcription.rs
@@ -6,7 +6,7 @@ use crate::audio_transcription::transformation::{
 use crate::audio_transcription::types::{
     AudioTranscriptionRequestData, AudioTranscriptionResponseData,
 };
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 
 pub use super::aws_base::{aws_auth_config, bedrock_model_id_and_region, resolve_bedrock_region};
 use super::constants::{BEDROCK_RUNTIME_ENDPOINT_TEMPLATE, BEDROCK_SERVICE};
@@ -18,8 +18,8 @@ pub static BEDROCK_AUDIO_TRANSCRIPTION_CONFIG: BedrockAudioTranscriptionConfig =
 
 pub struct BedrockAudioTranscriptionConfig;
 
-fn audio_fields(audio: Value) -> CoreResult<(String, String)> {
-    let object = audio.as_object().ok_or_else(|| CoreError::InvalidType {
+fn audio_fields(audio: Value) -> Result<(String, String), Error> {
+    let object = audio.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(&audio),
     })?;
@@ -27,13 +27,13 @@ fn audio_fields(audio: Value) -> CoreResult<(String, String)> {
         .get("data")
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField("audio.data"))?;
+        .ok_or(Error::MissingField("audio.data"))?;
     let format = object
         .get("format")
         .and_then(Value::as_str)
         .filter(|value| matches!(*value, "wav" | "mp3" | "flac" | "ogg"))
         .ok_or_else(|| {
-            CoreError::InvalidRequest("audio.format must be wav, mp3, flac, or ogg".to_string())
+            Error::InvalidRequest("audio.format must be wav, mp3, flac, or ogg".to_string())
         })?;
     Ok((data.to_string(), format.to_string()))
 }
@@ -46,16 +46,18 @@ fn optional_string<'a>(params: &'a Map<String, Value>, key: &str) -> Option<&'a
 }
 
 impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn supported_transcription_params(&self) -> &'static [&'static str] {
         SUPPORTED_PARAMS
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_transcription_request(
         &self,
         _model: &str,
         audio: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<AudioTranscriptionRequestData> {
+    ) -> Result<AudioTranscriptionRequestData, Error> {
         let (data, format) = audio_fields(audio)?;
         let mut instruction = "Transcribe the audio. Respond with only the transcript.".to_string();
         if let Some(language) = optional_string(&optional_params, "language") {
@@ -83,18 +85,19 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         })
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_transcription_response(
         &self,
         _model: &str,
         response_json: Value,
-    ) -> CoreResult<AudioTranscriptionResponseData> {
+    ) -> Result<AudioTranscriptionResponseData, Error> {
         let content = response_json
             .get("output")
             .and_then(|value| value.get("message"))
             .and_then(|value| value.get("content"))
             .and_then(Value::as_array)
             .ok_or_else(|| {
-                CoreError::InvalidResponse("Bedrock response has no output content".to_string())
+                Error::InvalidResponse("Bedrock response has no output content".to_string())
             })?;
         let mut text = String::new();
         for block in content {
@@ -111,7 +114,7 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         let (model_id, model_region) = bedrock_model_id_and_region(model);
         let region = resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup);
         let endpoint = optional_params
@@ -133,7 +136,7 @@ impl AudioTranscriptionProviderConfig for BedrockAudioTranscriptionConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<AudioTranscriptionAuth> {
+    ) -> Result<AudioTranscriptionAuth, Error> {
         let (_, model_region) = bedrock_model_id_and_region(model);
         Ok(AudioTranscriptionAuth::AwsSigV4 {
             region: resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup),
diff --git a/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs b/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
index b11639aa09b..e5e52bfce95 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/aws_base.rs
@@ -4,7 +4,7 @@ use std::time::Duration;
 use std::time::{SystemTime, UNIX_EPOCH};
 
 use crate::caching::in_memory_cache::InMemoryCache;
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 use aws_credential_types::Credentials;
 use aws_credential_types::provider::ProvideCredentials;
 use aws_sigv4::http_request::{
@@ -197,7 +197,7 @@ pub fn classify_auth(
 pub async fn resolve_credentials(
     config: AwsAuthConfig,
     env_lookup: &(dyn Fn(&str) -> Option<String> + Sync),
-) -> CoreResult<Credentials> {
+) -> Result<Credentials, Error> {
     let resolved = config.clone().with_environment(env_lookup);
     let flow = classify_auth(config, env_lookup);
     match flow {
@@ -244,9 +244,10 @@ pub async fn resolve_credentials(
             let provider = aws_config::profile::ProfileFileCredentialsProvider::builder()
                 .profile_name(name)
                 .build();
-            provider.provide_credentials().await.map_err(|error| {
-                CoreError::Auth(format!("AWS profile credentials failed: {error}"))
-            })
+            provider
+                .provide_credentials()
+                .await
+                .map_err(|error| Error::Auth(format!("AWS profile credentials failed: {error}")))
         }
         AwsAuthFlow::AssumeRole { role, session_name } => {
             if is_already_running_as_role(&role, &resolved).await? {
@@ -260,7 +261,7 @@ pub async fn resolve_credentials(
                         .build()
                         .await;
                 let credentials = provider.provide_credentials().await.map_err(|error| {
-                    CoreError::Auth(format!("AWS default credentials failed: {error}"))
+                    Error::Auth(format!("AWS default credentials failed: {error}"))
                 })?;
                 set_cached_credentials(
                     key,
@@ -301,7 +302,7 @@ pub async fn resolve_credentials(
             provider
                 .provide_credentials()
                 .await
-                .map_err(|error| CoreError::Auth(format!("AWS role credentials failed: {error}")))
+                .map_err(|error| Error::Auth(format!("AWS role credentials failed: {error}")))
         }
         AwsAuthFlow::WebIdentity {
             token,
@@ -325,13 +326,13 @@ pub async fn resolve_credentials(
                 .send()
                 .await
                 .map_err(|error| {
-                    CoreError::Auth(format!("AWS web identity credentials failed: {error}"))
+                    Error::Auth(format!("AWS web identity credentials failed: {error}"))
                 })?;
             let credentials = response.credentials().ok_or_else(|| {
-                CoreError::Auth("AWS web identity response had no credentials".to_string())
+                Error::Auth("AWS web identity response had no credentials".to_string())
             })?;
             let expiration = SystemTime::try_from(*credentials.expiration()).map_err(|error| {
-                CoreError::Auth(format!("AWS web identity expiration was invalid: {error}"))
+                Error::Auth(format!("AWS web identity expiration was invalid: {error}"))
             })?;
             Ok(Credentials::new(
                 credentials.access_key_id(),
@@ -350,9 +351,10 @@ pub async fn resolve_credentials(
                 aws_config::default_provider::credentials::DefaultCredentialsChain::builder()
                     .build()
                     .await;
-            let credentials = provider.provide_credentials().await.map_err(|error| {
-                CoreError::Auth(format!("AWS default credentials failed: {error}"))
-            })?;
+            let credentials = provider
+                .provide_credentials()
+                .await
+                .map_err(|error| Error::Auth(format!("AWS default credentials failed: {error}")))?;
             set_cached_credentials(
                 key,
                 credentials.clone(),
@@ -363,7 +365,7 @@ pub async fn resolve_credentials(
     }
 }
 
-async fn is_already_running_as_role(role: &str, config: &AwsAuthConfig) -> CoreResult<bool> {
+async fn is_already_running_as_role(role: &str, config: &AwsAuthConfig) -> Result<bool, Error> {
     if role_identity(role).is_none() {
         return Ok(false);
     }
@@ -437,7 +439,7 @@ pub fn sign_bedrock_post(
     region: &str,
     credentials: &Credentials,
     signing_time: SystemTime,
-) -> CoreResult<BTreeMap<String, String>> {
+) -> Result<BTreeMap<String, String>, Error> {
     let identity: Identity = credentials.clone().into();
     let params = v4::SigningParams::builder()
         .identity(&identity)
@@ -447,14 +449,14 @@ pub fn sign_bedrock_post(
         .settings(SigningSettings::default())
         .build()
         .map(SigningParams::from)
-        .map_err(|error| CoreError::Auth(format!("AWS signing parameters failed: {error}")))?;
+        .map_err(|error| Error::Auth(format!("AWS signing parameters failed: {error}")))?;
     let header_refs = headers
         .iter()
         .map(|(name, value)| (name.as_str(), value.as_str()));
     let request = SignableRequest::new("POST", url, header_refs, SignableBody::Bytes(body))
-        .map_err(|error| CoreError::Auth(format!("AWS signable request failed: {error}")))?;
+        .map_err(|error| Error::Auth(format!("AWS signable request failed: {error}")))?;
     let (instructions, _) = sign(request, &params)
-        .map_err(|error| CoreError::Auth(format!("AWS request signing failed: {error}")))?
+        .map_err(|error| Error::Auth(format!("AWS request signing failed: {error}")))?
         .into_parts();
     Ok(instructions
         .headers()
diff --git a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
index 4b75dcb8e9d..c86f061b9ca 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/tests.rs
@@ -1,4 +1,5 @@
 use super::*;
+use crate::Error;
 use serde_json::json;
 
 fn messages(value: Value) -> Vec<ChatMessage> {
@@ -23,7 +24,7 @@ fn transform(msgs: Value, opts: Value) -> Value {
         .body
 }
 
-fn transform_response(body: Value) -> CoreResult<ChatCompletionsResponse> {
+fn transform_response(body: Value) -> Result<ChatCompletionsResponse, Error> {
     BEDROCK_CHAT_COMPLETIONS_CONFIG.transform_response(
         "anthropic.claude-sonnet-4-5-v1:0",
         ProviderChatResponseData { body },
@@ -478,25 +479,22 @@ fn declines_a_response_carrying_a_tool_use_block() {
         "usage": {"inputTokens": 1, "outputTokens": 1}
     }))
     .expect_err("tool use block");
-    assert_eq!(
-        err,
-        CoreError::Unsupported("non-text response content block")
-    );
+    assert_eq!(err, Error::Unsupported("non-text response content block"));
 }
 
 #[test]
 fn errors_on_a_response_missing_required_fields() {
     assert_eq!(
         transform_response(json!("nope")).expect_err("not an object"),
-        CoreError::InvalidResponse("converse response is not an object".to_string())
+        Error::InvalidResponse("converse response is not an object".to_string())
     );
     assert_eq!(
         transform_response(json!({"usage": {}})).expect_err("no output"),
-        CoreError::MissingField("output.message.content")
+        Error::MissingField("output.message.content")
     );
     assert_eq!(
         transform_response(json!({"output": {"message": {"content": []}}})).expect_err("no usage"),
-        CoreError::MissingField("usage")
+        Error::MissingField("usage")
     );
 }
 
diff --git a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
index b107950748e..7be3d108d44 100644
--- a/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/bedrock/chat_completions/transformation.rs
@@ -11,7 +11,7 @@ use crate::chat_completions::types::{
     ChatCompletionsUsage, ChatMessage, ChatMessageContent, ProviderChatRequestData,
     ProviderChatResponseData,
 };
-use crate::error::{CoreError, CoreResult};
+use crate::error::Error;
 
 use super::super::aws_base::{bedrock_model_id_and_region, resolve_bedrock_region};
 use super::super::constants::{AWS_BEARER_TOKEN_BEDROCK, BEDROCK_RUNTIME_ENDPOINT_TEMPLATE};
@@ -23,11 +23,12 @@ use super::super::constants::{AWS_BEARER_TOKEN_BEDROCK, BEDROCK_RUNTIME_ENDPOINT
 /// `additionalModelRequestFields` for Anthropic base models and to
 /// `inferenceConfig` otherwise, and that branch reads the model catalog the
 /// core cannot see.
-const SUPPORTED_PARAMS: &[&str] = &["maxTokens", "temperature", "topP", "stopSequences"];
-
-/// Params that belong in `inferenceConfig`, in the order Python's
-/// `AmazonConverseConfig` declares them, so bodies compare cleanly.
-const INFERENCE_CONFIG_PARAMS: &[&str] = SUPPORTED_PARAMS;
+const SUPPORTED_PARAMS: &[(&str, &str)] = &[
+    ("max_tokens", "maxTokens"),
+    ("temperature", "temperature"),
+    ("top_p", "topP"),
+    ("stop", "stopSequences"),
+];
 
 const AWS_BEDROCK_RUNTIME_ENDPOINT: &str = "aws_bedrock_runtime_endpoint";
 
@@ -66,7 +67,7 @@ fn converse_body(conversation: &Conversation, params: &Map<String, Value>) -> Va
         })
         .collect();
 
-    let inference_config = Map::from_iter(INFERENCE_CONFIG_PARAMS.iter().filter_map(|name| {
+    let inference_config = Map::from_iter(SUPPORTED_PARAMS.iter().filter_map(|(_, name)| {
         params
             .get(*name)
             .map(|value| ((*name).to_string(), value.clone()))
@@ -110,7 +111,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         let (model_id, model_region) = bedrock_model_id_and_region(model);
         let region = resolve_bedrock_region(model_region.as_deref(), optional_params, env_lookup);
         let endpoint = optional_params
@@ -137,7 +138,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<ChatCompletionsAuth> {
+    ) -> Result<ChatCompletionsAuth, Error> {
         // Python reads `api_key` as the Bedrock bearer token and consults the
         // env only when the caller passed none, so a caller-supplied empty key
         // falls through to SigV4 without reaching for the environment. An
@@ -162,7 +163,8 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         &[("Content-Type", "application/json")]
     }
 
-    fn supported_params(&self) -> &'static [&'static str] {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+    fn supported_openai_params(&self) -> &'static [(&'static str, &'static str)] {
         SUPPORTED_PARAMS
     }
 
@@ -175,32 +177,36 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         messages: &[ChatMessage],
         optional_params: &Map<String, Value>,
     ) -> Option<Unsupported> {
-        unsupported_param(SUPPORTED_PARAMS, CONFIG_PARAMS, optional_params)
-            .or_else(|| messages.iter().find_map(unsupported_message))
-            // Python's Converse translation drops blank text blocks instead of
-            // substituting the placeholder the shared conversation builder
-            // applies, so decline blank text rather than diverge.
-            .or_else(|| {
-                messages
-                    .iter()
-                    .any(has_blank_text)
-                    .then_some(Unsupported("blank message text"))
-            })
-            // Converse has no assistant prefill: Python inserts a continue turn
-            // when a conversation opens or closes on an assistant message, and
-            // only under `litellm.modify_params`, which the core cannot see.
-            // Declining both ends also keeps the shared builder's final
-            // assistant right-strip (an Anthropic rule) unreachable here.
-            .or_else(|| {
-                let conversation = build_conversation(messages);
-                let ends_on_assistant = conversation
-                    .turns
-                    .last()
-                    .is_some_and(|turn| turn.role == TurnRole::Assistant);
-                (!conversation.opens_on_user_turn() || ends_on_assistant).then_some(Unsupported(
-                    "conversation does not run user turn to user turn",
-                ))
-            })
+        unsupported_param(
+            self.supported_openai_params(),
+            CONFIG_PARAMS,
+            optional_params,
+        )
+        .or_else(|| messages.iter().find_map(unsupported_message))
+        // Python's Converse translation drops blank text blocks instead of
+        // substituting the placeholder the shared conversation builder
+        // applies, so decline blank text rather than diverge.
+        .or_else(|| {
+            messages
+                .iter()
+                .any(has_blank_text)
+                .then_some(Unsupported("blank message text"))
+        })
+        // Converse has no assistant prefill: Python inserts a continue turn
+        // when a conversation opens or closes on an assistant message, and
+        // only under `litellm.modify_params`, which the core cannot see.
+        // Declining both ends also keeps the shared builder's final
+        // assistant right-strip (an Anthropic rule) unreachable here.
+        .or_else(|| {
+            let conversation = build_conversation(messages);
+            let ends_on_assistant = conversation
+                .turns
+                .last()
+                .is_some_and(|turn| turn.role == TurnRole::Assistant);
+            (!conversation.opens_on_user_turn() || ends_on_assistant).then_some(Unsupported(
+                "conversation does not run user turn to user turn",
+            ))
+        })
     }
 
     fn transform_request(
@@ -208,7 +214,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         _model: &str,
         messages: Vec<ChatMessage>,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<ProviderChatRequestData> {
+    ) -> Result<ProviderChatRequestData, Error> {
         Ok(ProviderChatRequestData {
             body: converse_body(&build_conversation(&messages), &optional_params),
         })
@@ -218,17 +224,18 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         &self,
         model: &str,
         response: ProviderChatResponseData,
-    ) -> CoreResult<ChatCompletionsResponse> {
-        let body = response.body.as_object().ok_or_else(|| {
-            CoreError::InvalidResponse("converse response is not an object".into())
-        })?;
+    ) -> Result<ChatCompletionsResponse, Error> {
+        let body = response
+            .body
+            .as_object()
+            .ok_or_else(|| Error::InvalidResponse("converse response is not an object".into()))?;
 
         let content = body
             .get("output")
             .and_then(|output| output.get("message"))
             .and_then(|message| message.get("content"))
             .and_then(Value::as_array)
-            .ok_or(CoreError::MissingField("output.message.content"))?;
+            .ok_or(Error::MissingField("output.message.content"))?;
         // The route declines tool requests, so anything other than a text block
         // is something this path never asked for. Decline; the host falls back.
         if content.iter().any(|block| {
@@ -236,7 +243,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
                 .as_object()
                 .is_none_or(|block| block.len() != 1 || !block.contains_key("text"))
         }) {
-            return Err(CoreError::Unsupported("non-text response content block"));
+            return Err(Error::Unsupported("non-text response content block"));
         }
         let text: String = content
             .iter()
@@ -246,7 +253,7 @@ impl ChatCompletionsProviderConfig for BedrockChatCompletionsConfig {
         let usage = body
             .get("usage")
             .and_then(Value::as_object)
-            .ok_or(CoreError::MissingField("usage"))?;
+            .ok_or(Error::MissingField("usage"))?;
         let field = |name: &str| usage.get(name).and_then(Value::as_u64).unwrap_or(0);
         let computed = usage_from_parts(
             field("inputTokens"),
diff --git a/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
index dc720cc4244..9648321d7ff 100644
--- a/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/mistral/ocr/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::OcrProviderConfig;
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value};
@@ -47,7 +47,7 @@ pub fn complete_url(api_base: Option<&str>) -> String {
 
 /// Resolve the Mistral API key from the explicit param or the environment.
 ///
-/// Blank/whitespace values are treated as absent. Returns `CoreError::Auth`
+/// Blank/whitespace values are treated as absent. Returns `Error::Auth`
 /// when no usable key is available.
 ///
 /// Note: the env fallback only reads the process environment. Secret-manager
@@ -56,13 +56,13 @@ pub fn complete_url(api_base: Option<&str>) -> String {
 pub fn resolve_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
         .map(str::to_string)
         .or_else(|| env_lookup(MISTRAL_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
-        .ok_or_else(|| CoreError::Auth(MISSING_KEY_MESSAGE.to_string()))
+        .ok_or_else(|| Error::Auth(MISSING_KEY_MESSAGE.to_string()))
 }
 
 pub struct MistralOcrConfig;
@@ -70,18 +70,20 @@ pub struct MistralOcrConfig;
 pub const MISTRAL_OCR_CONFIG: MistralOcrConfig = MistralOcrConfig;
 
 impl OcrProviderConfig for MistralOcrConfig {
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn supported_ocr_params(&self) -> &'static [&'static str] {
         SUPPORTED_OCR_PARAMS
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_ocr_request(
         &self,
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         if !document.is_object() {
-            return Err(CoreError::InvalidType {
+            return Err(Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&document),
             });
@@ -100,14 +102,15 @@ impl OcrProviderConfig for MistralOcrConfig {
         })
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn transform_ocr_response(
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response_object = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
@@ -134,13 +137,14 @@ impl OcrProviderConfig for MistralOcrConfig {
         })
     }
 
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
     fn complete_url(
         &self,
         api_base: Option<&str>,
         _model: &str,
         _optional_params: &Map<String, Value>,
         _env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         Ok(complete_url(api_base))
     }
 
@@ -148,11 +152,12 @@ impl OcrProviderConfig for MistralOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_api_key(api_key, env_lookup)
     }
 }
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub fn supported_ocr_params() -> &'static [&'static str] {
     MISTRAL_OCR_CONFIG.supported_ocr_params()
 }
@@ -161,15 +166,17 @@ pub fn map_ocr_params(non_default_params: &Map<String, Value>) -> Map<String, Va
     MISTRAL_OCR_CONFIG.map_ocr_params(non_default_params)
 }
 
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
 pub fn transform_ocr_request(
     model: &str,
     document: Value,
     optional_params: Map<String, Value>,
-) -> CoreResult<OcrRequestData> {
+) -> Result<OcrRequestData, Error> {
     MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
 }
 
-pub fn transform_ocr_response(model: &str, response_json: Value) -> CoreResult<OcrResponseData> {
+#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+pub fn transform_ocr_response(model: &str, response_json: Value) -> Result<OcrResponseData, Error> {
     MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
 }
 
@@ -250,7 +257,7 @@ mod tests {
 
         assert_eq!(
             err,
-            CoreError::InvalidType {
+            Error::InvalidType {
                 expected: "object",
                 actual: "string",
             }
@@ -307,6 +314,6 @@ mod tests {
     #[test]
     fn resolve_api_key_errors_when_absent() {
         let err = resolve_api_key(None, &|_| None).expect_err("missing key should error");
-        assert_eq!(err, CoreError::Auth(MISSING_KEY_MESSAGE.to_string()));
+        assert_eq!(err, Error::Auth(MISSING_KEY_MESSAGE.to_string()));
     }
 }
diff --git a/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs b/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
index b3f6b03b28a..f1985f81b7d 100644
--- a/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/openai/realtime/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::realtime::transformation::RealtimeProviderConfig;
 use crate::realtime::types::{RealtimeEvent, RealtimeTransformResult};
 
@@ -72,7 +72,7 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
         &self,
         event: &RealtimeEvent,
         _model: &str,
-    ) -> CoreResult<RealtimeTransformResult> {
+    ) -> Result<RealtimeTransformResult, Error> {
         Ok(RealtimeTransformResult::passthrough(event.clone()))
     }
 
@@ -80,7 +80,7 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
         &self,
         event: &RealtimeEvent,
         _model: &str,
-    ) -> CoreResult<RealtimeTransformResult> {
+    ) -> Result<RealtimeTransformResult, Error> {
         Ok(RealtimeTransformResult::passthrough(event.clone()))
     }
 }
@@ -88,14 +88,14 @@ impl RealtimeProviderConfig for OpenAiRealtimeConfig {
 pub fn transform_realtime_request(
     event: &RealtimeEvent,
     model: &str,
-) -> CoreResult<RealtimeTransformResult> {
+) -> Result<RealtimeTransformResult, Error> {
     OPENAI_REALTIME_CONFIG.transform_realtime_request(event, model)
 }
 
 pub fn transform_realtime_response(
     event: &RealtimeEvent,
     model: &str,
-) -> CoreResult<RealtimeTransformResult> {
+) -> Result<RealtimeTransformResult, Error> {
     OPENAI_REALTIME_CONFIG.transform_realtime_response(event, model)
 }
 
diff --git a/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs b/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
index e15197c468c..be86bb90311 100644
--- a/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/openai/responses/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsTransformResult};
 use crate::responses::websocket::{ResponsesWebSocketProviderConfig, enforce_model};
 
@@ -15,7 +15,7 @@ impl ResponsesWebSocketProviderConfig for OpenAIResponsesWsConfig {
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult> {
+    ) -> Result<ResponsesWsTransformResult, Error> {
         Ok(ResponsesWsTransformResult::passthrough(enforce_model(
             event, model,
         )))
@@ -25,7 +25,7 @@ impl ResponsesWebSocketProviderConfig for OpenAIResponsesWsConfig {
         &self,
         event: &ResponsesWsEvent,
         _model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult> {
+    ) -> Result<ResponsesWsTransformResult, Error> {
         Ok(ResponsesWsTransformResult::passthrough(event.clone()))
     }
 }
diff --git a/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs b/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
index 6300149c237..ee095447028 100644
--- a/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
+++ b/litellm-rust/crates/core/src/providers/vertex_ai/ocr/transformation.rs
@@ -1,4 +1,4 @@
-use crate::error::{CoreError, CoreResult, json_type_name};
+use crate::error::{Error, json_type_name};
 use crate::ocr::transformation::OcrProviderConfig;
 use crate::ocr::types::{OcrRequestData, OcrResponseData};
 use serde_json::{Map, Value, json};
@@ -43,7 +43,7 @@ pub fn is_deepseek_model(model: &str) -> bool {
 pub fn resolve_vertex_api_key(
     api_key: Option<&str>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     api_key
         .map(str::trim)
         .filter(|key| !key.is_empty())
@@ -51,7 +51,7 @@ pub fn resolve_vertex_api_key(
         .or_else(|| env_lookup(VERTEX_AI_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
         .or_else(|| env_lookup(VERTEXAI_API_KEY_ENV).filter(|key| !key.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::Auth(
+            Error::Auth(
                 "Missing Vertex AI access token - pass api_key or provide Authorization via extra_headers"
                     .to_string(),
             )
@@ -61,12 +61,12 @@ pub fn resolve_vertex_api_key(
 fn vertex_project(
     params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     string_param(params, &["vertex_project", "vertex_ai_project"])
         .map(str::to_string)
         .or_else(|| env_lookup(VERTEXAI_PROJECT_ENV).filter(|value| !value.trim().is_empty()))
         .ok_or_else(|| {
-            CoreError::InvalidRequest(
+            Error::InvalidRequest(
                 "Missing vertex_project - Set VERTEXAI_PROJECT environment variable or pass vertex_project parameter"
                     .to_string(),
             )
@@ -99,7 +99,7 @@ pub fn complete_vertex_mistral_url(
     model: &str,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let project = vertex_project(optional_params, env_lookup)?;
     let location = vertex_location(optional_params, env_lookup);
     let base = vertex_mistral_api_base(api_base, &location);
@@ -112,7 +112,7 @@ pub fn complete_vertex_deepseek_url(
     api_base: Option<&str>,
     optional_params: &Map<String, Value>,
     env_lookup: &dyn Fn(&str) -> Option<String>,
-) -> CoreResult<String> {
+) -> Result<String, Error> {
     let project = vertex_project(optional_params, env_lookup)?;
     let location = vertex_location(optional_params, env_lookup);
     let base = api_base
@@ -125,20 +125,20 @@ pub fn complete_vertex_deepseek_url(
     ))
 }
 
-fn document_content_item(document: &Value) -> CoreResult<Value> {
-    let object = document.as_object().ok_or_else(|| CoreError::InvalidType {
+fn document_content_item(document: &Value) -> Result<Value, Error> {
+    let object = document.as_object().ok_or_else(|| Error::InvalidType {
         expected: "object",
         actual: json_type_name(document),
     })?;
     let doc_type = object
         .get("type")
         .and_then(Value::as_str)
-        .ok_or(CoreError::MissingField("document.type"))?;
+        .ok_or(Error::MissingField("document.type"))?;
     let url_field = match doc_type {
         "image_url" => "image_url",
         "document_url" => "document_url",
         other => {
-            return Err(CoreError::InvalidRequest(format!(
+            return Err(Error::InvalidRequest(format!(
                 "Unsupported document type: {other}. Expected 'image_url' or 'document_url'"
             )));
         }
@@ -147,7 +147,7 @@ fn document_content_item(document: &Value) -> CoreResult<Value> {
         .get(url_field)
         .and_then(Value::as_str)
         .filter(|value| !value.is_empty())
-        .ok_or(CoreError::MissingField(url_field))?;
+        .ok_or(Error::MissingField(url_field))?;
 
     Ok(json!({
         "type": "image_url",
@@ -163,7 +163,7 @@ fn deepseek_model_name(model: &str) -> String {
     }
 }
 
-fn first_choice_content(response: &Value) -> CoreResult<Value> {
+fn first_choice_content(response: &Value) -> Result<Value, Error> {
     response
         .get("choices")
         .and_then(Value::as_array)
@@ -176,9 +176,7 @@ fn first_choice_content(response: &Value) -> CoreResult<Value> {
             Value::Object(_) => true,
             _ => false,
         })
-        .ok_or_else(|| {
-            CoreError::InvalidResponse("No content in DeepSeek OCR response".to_string())
-        })
+        .ok_or_else(|| Error::InvalidResponse("No content in DeepSeek OCR response".to_string()))
 }
 
 fn ocr_data_from_content(content: Value, usage: Option<Value>, model: &str) -> Value {
@@ -219,7 +217,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_request(model, document, optional_params)
     }
 
@@ -227,7 +225,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         MISTRAL_OCR_CONFIG.transform_ocr_response(model, response_json)
     }
 
@@ -237,7 +235,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_vertex_mistral_url(api_base, model, optional_params, env_lookup)
     }
 
@@ -245,7 +243,7 @@ impl OcrProviderConfig for VertexAiOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_vertex_api_key(api_key, env_lookup)
     }
 
@@ -264,7 +262,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         model: &str,
         document: Value,
         optional_params: Map<String, Value>,
-    ) -> CoreResult<OcrRequestData> {
+    ) -> Result<OcrRequestData, Error> {
         let mut data = Map::new();
         data.insert(
             "model".to_string(),
@@ -289,10 +287,10 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         &self,
         model: &str,
         response_json: Value,
-    ) -> CoreResult<OcrResponseData> {
+    ) -> Result<OcrResponseData, Error> {
         let response = response_json
             .as_object()
-            .ok_or_else(|| CoreError::InvalidType {
+            .ok_or_else(|| Error::InvalidType {
                 expected: "object",
                 actual: json_type_name(&response_json),
             })?;
@@ -314,7 +312,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
             });
         }
 
-        let object = ocr_data.as_object().ok_or_else(|| CoreError::InvalidType {
+        let object = ocr_data.as_object().ok_or_else(|| Error::InvalidType {
             expected: "object",
             actual: json_type_name(&ocr_data),
         })?;
@@ -346,7 +344,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         _model: &str,
         optional_params: &Map<String, Value>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         complete_vertex_deepseek_url(api_base, optional_params, env_lookup)
     }
 
@@ -354,7 +352,7 @@ impl OcrProviderConfig for VertexAiDeepSeekOcrConfig {
         &self,
         api_key: Option<&str>,
         env_lookup: &dyn Fn(&str) -> Option<String>,
-    ) -> CoreResult<String> {
+    ) -> Result<String, Error> {
         resolve_vertex_api_key(api_key, env_lookup)
     }
 }
diff --git a/litellm-rust/crates/core/src/realtime/transformation.rs b/litellm-rust/crates/core/src/realtime/transformation.rs
index 69b88687000..b08084514ef 100644
--- a/litellm-rust/crates/core/src/realtime/transformation.rs
+++ b/litellm-rust/crates/core/src/realtime/transformation.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::realtime::types::{RealtimeEvent, RealtimeTransformResult};
 
 pub trait RealtimeProviderConfig {
@@ -11,12 +11,12 @@ pub trait RealtimeProviderConfig {
         &self,
         event: &RealtimeEvent,
         model: &str,
-    ) -> CoreResult<RealtimeTransformResult>;
+    ) -> Result<RealtimeTransformResult, Error>;
 
     /// Transform a backend → client event before it is forwarded downstream.
     fn transform_realtime_response(
         &self,
         event: &RealtimeEvent,
         model: &str,
-    ) -> CoreResult<RealtimeTransformResult>;
+    ) -> Result<RealtimeTransformResult, Error>;
 }
diff --git a/litellm-rust/crates/core/src/responses/instrumentation.rs b/litellm-rust/crates/core/src/responses/instrumentation.rs
index ec04571da14..b1098f4d386 100644
--- a/litellm-rust/crates/core/src/responses/instrumentation.rs
+++ b/litellm-rust/crates/core/src/responses/instrumentation.rs
@@ -5,9 +5,9 @@ use std::time::{SystemTime, UNIX_EPOCH};
 
 use serde_json::Value;
 
+use crate::Error;
 use crate::call_lifecycle::{CallLifecycleContext, CallLifecycleHooks, CallLifecycleTiming};
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsEventType};
-use crate::{CoreError, CoreResult};
 
 #[derive(Clone, Debug, Default, PartialEq, Eq)]
 pub struct ResponsesWsUsage {
@@ -205,7 +205,7 @@ impl ResponsesWsInstrumentation {
     }
 }
 
-type LifecycleFuture<'a, T> = Pin<Box<dyn Future<Output = CoreResult<T>> + Send + 'a>>;
+type LifecycleFuture<'a, T> = Pin<Box<dyn Future<Output = Result<T, Error>> + Send + 'a>>;
 
 impl CallLifecycleHooks<(), (), ()> for ResponsesWsInstrumentation {
     type PreCallFuture<'a> = LifecycleFuture<'a, ()>;
@@ -246,7 +246,7 @@ impl CallLifecycleHooks<(), (), ()> for ResponsesWsInstrumentation {
     fn async_log_failure_event<'a>(
         &'a self,
         _context: &'a CallLifecycleContext,
-        _error: &'a CoreError,
+        _error: &'a Error,
         _timing: &'a CallLifecycleTiming,
     ) -> Self::FailureFuture<'a> {
         Box::pin(async move {
@@ -342,7 +342,7 @@ mod tests {
                 ),
                 (),
                 &instrumentation,
-                |_| async { Ok::<(), CoreError>(()) },
+                |_| async { Ok::<(), Error>(()) },
             )
             .await;
 
diff --git a/litellm-rust/crates/core/src/responses/websocket.rs b/litellm-rust/crates/core/src/responses/websocket.rs
index 92dc19627a0..5d037e9cf1b 100644
--- a/litellm-rust/crates/core/src/responses/websocket.rs
+++ b/litellm-rust/crates/core/src/responses/websocket.rs
@@ -1,4 +1,4 @@
-use crate::CoreResult;
+use crate::Error;
 use crate::constants::{OPENAI_RESPONSES_DEFAULT_API_BASE, OPENAI_RESPONSES_PATH};
 use crate::responses::types::{ResponsesWsEvent, ResponsesWsEventType, ResponsesWsTransformResult};
 
@@ -19,13 +19,13 @@ pub trait ResponsesWebSocketProviderConfig: Sync {
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult>;
+    ) -> Result<ResponsesWsTransformResult, Error>;
 
     fn transform_ws_response(
         &self,
         event: &ResponsesWsEvent,
         model: &str,
-    ) -> CoreResult<ResponsesWsTransformResult>;
+    ) -> Result<ResponsesWsTransformResult, Error>;
 }
 
 pub fn complete_websocket_url(
diff --git a/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs b/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
index 656ba033b62..8a8a5ea263a 100644
--- a/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
+++ b/litellm-rust/crates/core/tests/workspace_crate_allowlist.rs
@@ -1,7 +1,8 @@
-//! Enforcement: the litellm-rust workspace has exactly three crates.
+//! Enforcement: the litellm-rust workspace has exactly four crates.
 //!
-//! `core` (pure translation), `ai-gateway` (routes + all network I/O), and
-//! `python-bridge` (the PyO3 cdylib). Adding or removing a crate must be a
+//! `core` (the Rust SDK), `ai-gateway` (the HTTP/WebSocket host),
+//! `python-interop` (domain-neutral PyO3 primitives), and `python-bridge` (the
+//! PyO3 cdylib). Adding or removing a crate must be a
 //! deliberate act: this test fails until the allowlist here is updated, forcing
 //! whoever changes the crate set to justify the new crate per the rule that a
 //! crate is a layer needing independent compilation / its own deps / a separate
@@ -16,10 +17,15 @@ use std::path::{Path, PathBuf};
 
 /// The one true crate set. Update BOTH this and `litellm-rust/AGENTS.md` when the
 /// workspace legitimately gains or loses a crate.
-const EXPECTED_MEMBERS: &[&str] = &["crates/core", "crates/ai-gateway", "crates/python-bridge"];
+const EXPECTED_MEMBERS: &[&str] = &[
+    "crates/core",
+    "crates/ai-gateway",
+    "crates/python-interop",
+    "crates/python-bridge",
+];
 
 /// The crate subdirectory names that must exist under `crates/`.
-const EXPECTED_CRATE_DIRS: &[&str] = &["core", "ai-gateway", "python-bridge"];
+const EXPECTED_CRATE_DIRS: &[&str] = &["core", "ai-gateway", "python-interop", "python-bridge"];
 
 const MISMATCH: &str = "litellm-rust crate set changed — update this allowlist AND litellm-rust/AGENTS.md, and justify the crate per the rule (crate = layer needing independent compilation / its own deps / a separate artifact).";
 
diff --git a/litellm-rust/crates/python-bridge/AGENTS.md b/litellm-rust/crates/python-bridge/AGENTS.md
index ad3cddfa5fd..42282ca4da4 100644
--- a/litellm-rust/crates/python-bridge/AGENTS.md
+++ b/litellm-rust/crates/python-bridge/AGENTS.md
@@ -1,3 +1,3 @@
-litellm-python-bridge is the PyO3 cdylib that exposes Rust to the litellm Python SDK — a thin adapter (Python objects → Rust calls → Python results) over the litellm-core route entrypoints (e.g. `litellm_core::messages::messages`).
+litellm-python-bridge is the PyO3 cdylib that exposes LiteLLM Rust APIs to the Python SDK. Keep API registration, domain dependency wiring, request assembly, and Python exception mapping here. Put domain-neutral Python/Serde conversion and GIL primitives in litellm-python-interop.
 
 Keep it thin: no business logic, no transforms, no I/O orchestration — just marshal in/out and call the core entrypoint.
diff --git a/litellm-rust/crates/python-bridge/CLAUDE.md b/litellm-rust/crates/python-bridge/CLAUDE.md
index 3ce8b8c639a..d25ae5a8130 100644
--- a/litellm-rust/crates/python-bridge/CLAUDE.md
+++ b/litellm-rust/crates/python-bridge/CLAUDE.md
@@ -5,8 +5,9 @@ Rules for `litellm-rust/crates/python-bridge`.
 ## Responsibility
 
 `python-bridge` is the PyO3 boundary between Python LiteLLM and Rust transforms.
-Keep this crate thin. It adapts Python objects to Rust payloads and returns
-Python-compatible dictionaries.
+Keep this crate thin. It exposes LiteLLM Rust APIs, assembles domain requests,
+maps domain errors to Python exceptions, and delegates generic conversion and
+GIL handling to `litellm-python-interop`.
 
 ## Bridge Shape
 
diff --git a/litellm-rust/crates/python-bridge/Cargo.toml b/litellm-rust/crates/python-bridge/Cargo.toml
index 0c4a753f762..637e5580170 100644
--- a/litellm-rust/crates/python-bridge/Cargo.toml
+++ b/litellm-rust/crates/python-bridge/Cargo.toml
@@ -10,21 +10,27 @@ name = "_native"
 crate-type = ["cdylib"]
 
 [features]
-default = ["extension-module"]
+default = ["abi3"]
+abi3 = ["pyo3/abi3-py310"]
 extension-module = ["pyo3/extension-module"]
+panic-test = []
 
 [dependencies]
+futures-util.workspace = true
+tracing.workspace = true
+tracing-subscriber.workspace = true
 litellm-core = { workspace = true, features = ["bedrock-auth"] }
 litellm-ai-gateway = { workspace = true, default-features = false }
+litellm-python-interop.workspace = true
 pyo3.workspace = true
 pyo3-async-runtimes.workspace = true
-pythonize.workspace = true
 serde.workspace = true
 serde_json.workspace = true
 tokio.workspace = true
 
 [dev-dependencies]
 criterion = "0.8.2"
+tokio-tungstenite.workspace = true
 
 [[bench]]
 name = "serialization"
diff --git a/litellm-rust/crates/python-bridge/benches/serialization.rs b/litellm-rust/crates/python-bridge/benches/serialization.rs
index 8a90cf667d0..0b9436d0cb7 100644
--- a/litellm-rust/crates/python-bridge/benches/serialization.rs
+++ b/litellm-rust/crates/python-bridge/benches/serialization.rs
@@ -2,6 +2,7 @@ use std::hint::black_box;
 use std::time::Duration;
 
 use criterion::{BenchmarkId, Criterion, criterion_group, criterion_main};
+use litellm_python_interop::{from_py, to_py};
 use pyo3::prelude::*;
 use pyo3::types::PyDict;
 use serde_json::{Value, json};
@@ -25,7 +26,7 @@ fn former_json_roundtrip_from_py(py: Python<'_>, value: &Bound<'_, PyAny>) -> Va
 }
 
 fn pythonize_from_py(value: &Bound<'_, PyAny>) -> Value {
-    pythonize::depythonize(value).expect("payload should depythonize")
+    from_py(value).expect("payload should depythonize")
 }
 
 fn former_json_roundtrip_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
@@ -37,12 +38,10 @@ fn former_json_roundtrip_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
 }
 
 fn pythonize_to_py(py: Python<'_>, value: &Value) -> Py<PyAny> {
-    pythonize::pythonize(py, value)
-        .expect("response should pythonize")
-        .unbind()
+    to_py(py, value).expect("response should pythonize")
 }
 
-fn serialization(c: &mut Criterion) {
+fn bridge_serialization(c: &mut Criterion) {
     Python::initialize();
     Python::attach(|py| {
         for &(label, payload_bytes) in PAYLOAD_SIZES {
@@ -98,6 +97,6 @@ criterion_group! {
         .sample_size(20)
         .warm_up_time(Duration::from_secs(1))
         .measurement_time(Duration::from_secs(4));
-    targets = serialization
+    targets = bridge_serialization
 }
 criterion_main!(benches);
diff --git a/litellm-rust/crates/python-bridge/src/constants.rs b/litellm-rust/crates/python-bridge/src/constants.rs
new file mode 100644
index 00000000000..07b2836b838
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/constants.rs
@@ -0,0 +1 @@
+pub(crate) const FUNCTION_TRACE_TARGET: &str = "litellm::function_trace";
diff --git a/litellm-rust/crates/python-bridge/src/diagnostics.rs b/litellm-rust/crates/python-bridge/src/diagnostics.rs
new file mode 100644
index 00000000000..cc153a89b8f
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/diagnostics.rs
@@ -0,0 +1,23 @@
+use litellm_python_interop::release_count;
+use pyo3::prelude::*;
+use pyo3::types::PyDict;
+
+#[pyfunction]
+fn gil_stats(py: Python<'_>) -> PyResult<Py<PyAny>> {
+    let stats = PyDict::new(py);
+    stats.set_item("releases", release_count())?;
+    Ok(stats.into_any().unbind())
+}
+
+#[cfg(feature = "panic-test")]
+#[pyfunction]
+fn _panic_for_test() {
+    panic!("intentional PyO3 panic smoke test");
+}
+
+pub(crate) fn register(module: &Bound<'_, PyModule>) -> PyResult<()> {
+    module.add_function(wrap_pyfunction!(gil_stats, module)?)?;
+    #[cfg(feature = "panic-test")]
+    module.add_function(wrap_pyfunction!(_panic_for_test, module)?)?;
+    Ok(())
+}
diff --git a/litellm-rust/crates/python-bridge/src/errors.rs b/litellm-rust/crates/python-bridge/src/errors.rs
new file mode 100644
index 00000000000..914e2e1e033
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/errors.rs
@@ -0,0 +1,61 @@
+use litellm_core::error::Error;
+use pyo3::exceptions::{PyRuntimeError, PyValueError};
+use pyo3::prelude::*;
+
+pyo3::create_exception!(
+    _native,
+    RustBridgeDeclined,
+    pyo3::exceptions::PyException,
+    "The route declined before calling the provider, so the host may retry on its own path."
+);
+
+pyo3::create_exception!(
+    _native,
+    RustUpstreamError,
+    pyo3::exceptions::PyException,
+    "The provider call was already issued and failed. Args are (status, message); status is 0 when there was no HTTP response."
+);
+
+pub(crate) fn core_error_to_pyerr(err: Error) -> PyErr {
+    match err {
+        Error::Auth(message) => PyValueError::new_err(message),
+        Error::InvalidProvider(_)
+        | Error::InvalidRequest(_)
+        | Error::InvalidType { .. }
+        | Error::MissingField(_) => PyValueError::new_err(err.to_string()),
+        other => PyRuntimeError::new_err(other.to_string()),
+    }
+}
+
+/// Map a core error for a route whose host keeps a Python implementation.
+///
+/// The distinction the host needs is whether the provider was already called.
+/// Everything raised before the request goes out is safe for the host to retry
+/// on its own path; anything after it is not, because the provider has already
+/// done the work and billed for it.
+pub(crate) fn chat_completions_error_to_pyerr(err: Error) -> PyErr {
+    match err {
+        Error::Unsupported(_)
+        | Error::Auth(_)
+        | Error::InvalidProvider(_)
+        | Error::InvalidRequest(_)
+        | Error::InvalidType { .. }
+        | Error::MissingField(_)
+        | Error::Routing(_)
+        // Nothing reached the provider, so serving it on Python cannot double
+        // bill and is the only way the caller gets an answer at all.
+        | Error::Connect(_) => RustBridgeDeclined::new_err(err.to_string()),
+        Error::Http { status, body } => {
+            RustUpstreamError::new_err((status, format!("{status}: {body}")))
+        }
+        Error::Network(message) | Error::InvalidResponse(message) => {
+            RustUpstreamError::new_err((0u16, message))
+        }
+    }
+}
+
+pub(crate) fn register(module: &Bound<'_, PyModule>) -> PyResult<()> {
+    let py = module.py();
+    module.add("RustBridgeDeclined", py.get_type::<RustBridgeDeclined>())?;
+    module.add("RustUpstreamError", py.get_type::<RustUpstreamError>())
+}
diff --git a/litellm-rust/crates/python-bridge/src/execution.rs b/litellm-rust/crates/python-bridge/src/execution.rs
new file mode 100644
index 00000000000..f3648158cf6
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/execution.rs
@@ -0,0 +1,423 @@
+use std::future::Future;
+use std::panic::AssertUnwindSafe;
+use std::time::Duration;
+
+use futures_util::FutureExt;
+use litellm_core::error::Error;
+use litellm_python_interop::{Pythonized, panic_to_pyerr, release_gil};
+use pyo3::exceptions::PyRuntimeError;
+use pyo3::prelude::*;
+use serde::Serialize;
+use tokio::runtime::{Handle, Runtime};
+use tokio::time::{self, MissedTickBehavior};
+
+pub(crate) fn run_sync<T, F>(
+    py: Python<'_>,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Py<PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    run_sync_on(
+        py,
+        pyo3_async_runtimes::tokio::get_runtime(),
+        future,
+        map_error,
+    )
+}
+
+fn run_sync_on<T, F>(
+    py: Python<'_>,
+    runtime: &Runtime,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Py<PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    if Handle::try_current().is_ok() {
+        return Err(PyRuntimeError::new_err(
+            "synchronous native routes cannot run from a Tokio context; use the async route",
+        ));
+    }
+
+    let result = release_gil(py, move || runtime.block_on(wait_for_sync_result(future)))?;
+    let result = map_core_result(result, map_error)?;
+    Pythonized(result).into_pyobject(py).map(Bound::unbind)
+}
+
+pub(crate) fn run_async<T, F>(
+    py: Python<'_>,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Bound<'_, PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    pyo3_async_runtimes::tokio::future_into_py(py, async move {
+        let result = catch_future_panic(future).await?;
+        let result = map_core_result(result, map_error)?;
+        Ok(Pythonized(result))
+    })
+}
+
+fn map_core_result<T>(result: Result<T, Error>, map_error: fn(Error) -> PyErr) -> PyResult<T> {
+    match result {
+        Ok(value) => Ok(value),
+        Err(error) => Err(
+            std::panic::catch_unwind(AssertUnwindSafe(|| map_error(error)))
+                .map_err(panic_to_pyerr)?,
+        ),
+    }
+}
+
+async fn catch_future_panic<T, F>(future: F) -> PyResult<Result<T, Error>>
+where
+    F: Future<Output = Result<T, Error>>,
+{
+    AssertUnwindSafe(future)
+        .catch_unwind()
+        .await
+        .map_err(panic_to_pyerr)
+}
+
+async fn wait_for_sync_result<T, F>(future: F) -> PyResult<Result<T, Error>>
+where
+    F: Future<Output = Result<T, Error>>,
+{
+    let future = catch_future_panic(future);
+    tokio::pin!(future);
+
+    let signal_interval = Duration::from_millis(50);
+    let mut signal_checks =
+        time::interval_at(time::Instant::now() + signal_interval, signal_interval);
+    signal_checks.set_missed_tick_behavior(MissedTickBehavior::Delay);
+    loop {
+        tokio::select! {
+            result = &mut future => return result,
+            _ = signal_checks.tick() => Python::attach(|py| py.check_signals())?,
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use std::ffi::CString;
+    use std::future::poll_fn;
+    use std::sync::atomic::{AtomicUsize, Ordering};
+    use std::sync::{Arc, mpsc};
+    use std::task::Poll;
+    use std::thread;
+    use std::time::Instant;
+
+    use pyo3::panic::PanicException;
+    use pyo3::types::{PyDict, PyModule};
+    use serde::Serializer;
+    use tokio::runtime::Builder;
+
+    use super::*;
+
+    fn runtime_error(error: Error) -> PyErr {
+        PyRuntimeError::new_err(error.to_string())
+    }
+
+    fn panicking_error_mapper(_error: Error) -> PyErr {
+        panic!("error mapper panicked")
+    }
+
+    struct PanickingOutput;
+
+    static ASYNC_PROBE_COMPLETED: AtomicUsize = AtomicUsize::new(0);
+
+    impl Serialize for PanickingOutput {
+        fn serialize<S>(&self, _serializer: S) -> Result<S::Ok, S::Error>
+        where
+            S: Serializer,
+        {
+            panic!("serializer panicked")
+        }
+    }
+
+    #[pyfunction]
+    fn async_serialization_panic(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
+        run_async(py, async { Ok(PanickingOutput) }, runtime_error)
+    }
+
+    #[pyfunction]
+    fn async_runtime_probe(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
+        run_async(
+            py,
+            async {
+                ASYNC_PROBE_COMPLETED.fetch_add(1, Ordering::SeqCst);
+                Ok(true)
+            },
+            runtime_error,
+        )
+    }
+
+    #[pyfunction]
+    fn runtime_worker_count() -> usize {
+        pyo3_async_runtimes::tokio::get_runtime()
+            .metrics()
+            .num_workers()
+    }
+
+    #[pyfunction]
+    fn runtime_is_responsive(_py: Python<'_>, expected_completions: usize) -> bool {
+        let completion_deadline = Instant::now() + Duration::from_secs(2);
+        while ASYNC_PROBE_COMPLETED.load(Ordering::SeqCst) < expected_completions {
+            if Instant::now() >= completion_deadline {
+                return false;
+            }
+            thread::sleep(Duration::from_millis(1));
+        }
+
+        let (heartbeat_tx, heartbeat_rx) = mpsc::sync_channel(1);
+        pyo3_async_runtimes::tokio::get_runtime().spawn(async move {
+            let _ = heartbeat_tx.send(());
+        });
+        heartbeat_rx.recv_timeout(Duration::from_secs(2)).is_ok()
+    }
+
+    fn extract_bool(py: Python<'_>, result: PyResult<Py<PyAny>>) -> bool {
+        result
+            .expect("route should complete")
+            .bind(py)
+            .extract()
+            .expect("result should convert")
+    }
+
+    #[test]
+    fn sync_runner_polls_future_on_the_caller_thread() {
+        Python::initialize();
+        Python::attach(|py| {
+            let caller_thread = std::thread::current().id();
+            let result = run_sync(
+                py,
+                async move { Ok(std::thread::current().id() == caller_thread) },
+                runtime_error,
+            );
+
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_releases_gil_while_waiting() {
+        Python::initialize();
+        Python::attach(|py| {
+            let result = run_sync(
+                py,
+                async {
+                    let gil_acquired = tokio::time::timeout(
+                        Duration::from_secs(2),
+                        tokio::task::spawn_blocking(|| Python::attach(|_| true)),
+                    )
+                    .await;
+                    Ok(matches!(gil_acquired, Ok(Ok(true))))
+                },
+                runtime_error,
+            );
+
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_rejects_calls_from_a_tokio_context() {
+        Python::initialize();
+        let runtime = Builder::new_current_thread()
+            .enable_all()
+            .build()
+            .expect("runtime should build");
+
+        let error = runtime.block_on(async {
+            Python::attach(|py| {
+                run_sync::<bool, _>(py, async { Ok(true) }, runtime_error)
+                    .expect_err("sync route should reject a nested Tokio runtime")
+            })
+        });
+
+        assert_eq!(
+            error.to_string(),
+            "RuntimeError: synchronous native routes cannot run from a Tokio context; use the async route"
+        );
+    }
+
+    #[test]
+    fn sync_runner_can_drive_a_current_thread_runtime() {
+        Python::initialize();
+        let runtime = Builder::new_current_thread()
+            .enable_all()
+            .build()
+            .expect("runtime should build");
+        Python::attach(|py| {
+            let result = run_sync_on(
+                py,
+                &runtime,
+                async {
+                    tokio::task::yield_now().await;
+                    Ok(true)
+                },
+                runtime_error,
+            );
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_maps_a_panicked_future() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync::<bool, _>(
+                py,
+                poll_fn(|_| -> Poll<Result<bool, Error>> { panic!("route future panicked") }),
+                runtime_error,
+            )
+            .expect_err("panicked route should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: route future panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_maps_a_panicked_error_mapper() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync::<bool, _>(
+                py,
+                async { Err(Error::InvalidRequest("invalid".to_string())) },
+                panicking_error_mapper,
+            )
+            .expect_err("panicked mapper should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: error mapper panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_surfaces_serializer_panics() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync(py, async { Ok(PanickingOutput) }, runtime_error)
+                .expect_err("serializer panic should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: serializer panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_supports_concurrent_callers_on_the_shared_runtime() {
+        Python::initialize();
+        let barrier = Arc::new(tokio::sync::Barrier::new(2));
+        let callers: Vec<_> = (0..2)
+            .map(|_| {
+                let barrier = Arc::clone(&barrier);
+                thread::spawn(move || {
+                    Python::attach(|py| {
+                        extract_bool(
+                            py,
+                            run_sync(
+                                py,
+                                async move {
+                                    Ok(tokio::time::timeout(Duration::from_secs(2), barrier.wait())
+                                        .await
+                                        .is_ok())
+                                },
+                                runtime_error,
+                            ),
+                        )
+                    })
+                })
+            })
+            .collect();
+        let results: Vec<_> = callers
+            .into_iter()
+            .map(|caller| caller.join().expect("caller should not panic"))
+            .collect();
+
+        assert_eq!(results, vec![true, true]);
+    }
+
+    #[test]
+    fn async_runner_surfaces_serializer_panics() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "runtime").expect("module should be created");
+            module
+                .add_function(
+                    wrap_pyfunction!(async_serialization_panic, &module)
+                        .expect("function should wrap"),
+                )
+                .expect("function should register");
+            let locals = PyDict::new(py);
+            locals
+                .set_item("runtime", &module)
+                .expect("module should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    try:
+        await runtime.async_serialization_panic()
+    except BaseException as error:
+        assert type(error).__name__ == "PanicException"
+        assert str(error) == "serializer panicked"
+    else:
+        raise AssertionError("serializer panic was not raised")
+
+asyncio.run(exercise())
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("serializer panic should reach the Python awaiter");
+        });
+    }
+
+    #[test]
+    fn async_result_delivery_does_not_stall_tokio_workers() {
+        Python::initialize();
+        ASYNC_PROBE_COMPLETED.store(0, Ordering::SeqCst);
+        Python::attach(|py| {
+            let module = PyModule::new(py, "runtime").expect("module should be created");
+            for function in [
+                wrap_pyfunction!(async_runtime_probe, &module).expect("function should wrap"),
+                wrap_pyfunction!(runtime_worker_count, &module).expect("function should wrap"),
+                wrap_pyfunction!(runtime_is_responsive, &module).expect("function should wrap"),
+            ] {
+                module
+                    .add_function(function)
+                    .expect("function should register");
+            }
+            let locals = PyDict::new(py);
+            locals
+                .set_item("runtime", &module)
+                .expect("module should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    worker_count = runtime.runtime_worker_count()
+    awaitables = [runtime.async_runtime_probe() for _ in range(worker_count)]
+    assert runtime.runtime_is_responsive(worker_count)
+    assert await asyncio.gather(*awaitables) == [True] * worker_count
+
+asyncio.run(exercise())
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("result delivery should leave Tokio workers responsive");
+        });
+    }
+}
diff --git a/litellm-rust/crates/python-bridge/src/function_trace.rs b/litellm-rust/crates/python-bridge/src/function_trace.rs
new file mode 100644
index 00000000000..420d237c79d
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/function_trace.rs
@@ -0,0 +1,216 @@
+use std::future::Future;
+use std::sync::{Arc, Mutex};
+
+use serde::Serialize;
+use tracing::instrument::WithSubscriber;
+use tracing::span::{Attributes, Id};
+use tracing::{Dispatch, Level, Subscriber};
+use tracing_subscriber::filter::{LevelFilter, filter_fn};
+use tracing_subscriber::layer::Context;
+use tracing_subscriber::prelude::*;
+use tracing_subscriber::registry::LookupSpan;
+use tracing_subscriber::{Layer, Registry};
+
+use crate::constants::FUNCTION_TRACE_TARGET;
+
+#[derive(Serialize)]
+#[serde(untagged)]
+pub(crate) enum TraceResponse<T> {
+    Plain(T),
+    Traced {
+        response: T,
+        trace: Vec<FunctionTraceEvent>,
+    },
+}
+
+pub(crate) async fn trace_call<T, E>(
+    future: impl Future<Output = Result<T, E>>,
+    enabled: bool,
+) -> Result<TraceResponse<T>, E> {
+    if !enabled {
+        return future.await.map(TraceResponse::Plain);
+    }
+    let trace = FunctionTrace::default();
+    let response = future.with_subscriber(trace.dispatcher()).await?;
+    Ok(TraceResponse::Traced {
+        response,
+        trace: trace.events(),
+    })
+}
+
+#[derive(Clone, Debug, PartialEq, Serialize)]
+pub struct FunctionTraceEvent {
+    pub function: &'static str,
+    pub depth: usize,
+}
+
+#[derive(Clone, Default)]
+pub struct FunctionTrace {
+    events: Arc<Mutex<Vec<FunctionTraceEvent>>>,
+}
+
+impl FunctionTrace {
+    pub fn dispatcher(&self) -> Dispatch {
+        let filter = filter_fn(|metadata| {
+            metadata.is_span()
+                && metadata.target() == FUNCTION_TRACE_TARGET
+                && *metadata.level() == Level::TRACE
+        })
+        .with_max_level_hint(LevelFilter::TRACE);
+        Dispatch::new(
+            Registry::default().with(
+                FunctionTraceLayer {
+                    trace: self.clone(),
+                }
+                .with_filter(filter),
+            ),
+        )
+    }
+
+    pub fn events(&self) -> Vec<FunctionTraceEvent> {
+        self.events
+            .lock()
+            .unwrap_or_else(|error| error.into_inner())
+            .clone()
+    }
+}
+
+struct FunctionTraceLayer {
+    trace: FunctionTrace,
+}
+
+impl<S> Layer<S> for FunctionTraceLayer
+where
+    S: Subscriber + for<'lookup> LookupSpan<'lookup>,
+{
+    fn on_new_span(&self, attributes: &Attributes<'_>, id: &Id, context: Context<'_, S>) {
+        let depth = context
+            .span(id)
+            .map(|span| span.scope().skip(1).count())
+            .unwrap_or_default();
+        self.trace
+            .events
+            .lock()
+            .unwrap_or_else(|error| error.into_inner())
+            .push(FunctionTraceEvent {
+                function: attributes.metadata().name(),
+                depth,
+            });
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+    async fn outer() {
+        tokio::task::yield_now().await;
+        inner().await;
+    }
+
+    #[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]
+    async fn inner() {
+        tokio::task::yield_now().await;
+    }
+
+    #[tokio::test]
+    async fn concurrent_futures_keep_separate_traces_across_yields() {
+        use tracing::instrument::WithSubscriber;
+
+        let first = FunctionTrace::default();
+        let second = FunctionTrace::default();
+        let outside = FunctionTrace::default();
+
+        async {
+            tokio::join!(
+                outer().with_subscriber(first.dispatcher()),
+                inner().with_subscriber(second.dispatcher()),
+            );
+            inner().await;
+        }
+        .with_subscriber(outside.dispatcher())
+        .await;
+
+        assert_eq!(
+            first.events(),
+            vec![
+                FunctionTraceEvent {
+                    function: "outer",
+                    depth: 0
+                },
+                FunctionTraceEvent {
+                    function: "inner",
+                    depth: 1
+                },
+            ],
+        );
+        assert_eq!(
+            second.events(),
+            vec![FunctionTraceEvent {
+                function: "inner",
+                depth: 0
+            }],
+        );
+        assert_eq!(
+            outside.events(),
+            vec![FunctionTraceEvent {
+                function: "inner",
+                depth: 0
+            }],
+        );
+    }
+
+    #[test]
+    fn records_matching_spans_in_creation_order() {
+        let trace = FunctionTrace::default();
+        let dispatch = trace.dispatcher();
+
+        tracing::dispatcher::with_default(&dispatch, || {
+            let _ignored = tracing::trace_span!(target: "other", "ignored");
+            let _first = tracing::trace_span!(target: FUNCTION_TRACE_TARGET, "same_name");
+            let _wrong_level = tracing::debug_span!(target: FUNCTION_TRACE_TARGET, "wrong_level");
+            let _second = tracing::trace_span!(target: FUNCTION_TRACE_TARGET, "same_name");
+        });
+
+        assert_eq!(
+            trace.events(),
+            vec![
+                FunctionTraceEvent {
+                    function: "same_name",
+                    depth: 0,
+                },
+                FunctionTraceEvent {
+                    function: "same_name",
+                    depth: 0,
+                },
+            ]
+        );
+    }
+
+    #[test]
+    fn records_matching_span_nesting_depth() {
+        let trace = FunctionTrace::default();
+        let dispatch = trace.dispatcher();
+
+        tracing::dispatcher::with_default(&dispatch, || {
+            let outer = tracing::trace_span!(target: FUNCTION_TRACE_TARGET, "outer");
+            let _outer_guard = outer.enter();
+            let _inner = tracing::trace_span!(target: FUNCTION_TRACE_TARGET, "inner");
+        });
+
+        assert_eq!(
+            trace.events(),
+            vec![
+                FunctionTraceEvent {
+                    function: "outer",
+                    depth: 0,
+                },
+                FunctionTraceEvent {
+                    function: "inner",
+                    depth: 1,
+                },
+            ]
+        );
+    }
+}
diff --git a/litellm-rust/crates/python-bridge/src/gil.rs b/litellm-rust/crates/python-bridge/src/gil.rs
deleted file mode 100644
index e887c8ec1e3..00000000000
--- a/litellm-rust/crates/python-bridge/src/gil.rs
+++ /dev/null
@@ -1,32 +0,0 @@
-//! GIL accounting.
-//!
-//! A single chokepoint for releasing the GIL around blocking work. Every
-//! blocking call in the bridge goes through [`release_gil`] instead of calling
-//! `Python::detach` directly, so the release count stays accurate and we
-//! have one place to extend later (timing histograms, per-call labels, etc.).
-
-use std::sync::atomic::{AtomicU64, Ordering};
-
-use pyo3::prelude::*;
-
-/// Number of times the bridge has released the GIL since process start.
-static GIL_RELEASES: AtomicU64 = AtomicU64::new(0);
-
-/// Release the GIL around `f`, recording the release.
-///
-/// `f` must not touch any Python state — that is what makes releasing the GIL
-/// safe. Returning the value back to Python re-acquires the GIL at the call
-/// site, after `f` has finished.
-pub fn release_gil<T, F>(py: Python<'_>, f: F) -> T
-where
-    F: FnOnce() -> T + Send,
-    T: Send,
-{
-    GIL_RELEASES.fetch_add(1, Ordering::Relaxed);
-    py.detach(f)
-}
-
-/// Total GIL releases performed by the bridge so far.
-pub fn release_count() -> u64 {
-    GIL_RELEASES.load(Ordering::Relaxed)
-}
diff --git a/litellm-rust/crates/python-bridge/src/lib.rs b/litellm-rust/crates/python-bridge/src/lib.rs
index f9e75f45f75..5f36a22370a 100644
--- a/litellm-rust/crates/python-bridge/src/lib.rs
+++ b/litellm-rust/crates/python-bridge/src/lib.rs
@@ -1,146 +1,18 @@
-use std::collections::HashMap;
-use std::time::Duration;
-
-use litellm_ai_gateway::io::audio_transcription::{
-    AudioTranscriptionRequest, audio_transcription as run_audio_transcription,
-};
-use litellm_ai_gateway::io::ocr::{OcrRequest, ocr as run_ocr};
-use litellm_ai_gateway::io::responses_ws::ResponsesWebSocketConnection as RustResponsesWebSocketConnection;
-use litellm_core::chat_completions::types::{ChatCompletionsRequest, ChatCompletionsResponse};
-use litellm_core::chat_completions::{
-    chat_completions as run_chat_completions, chat_completions_decline_reason,
-};
-use litellm_core::error::CoreError;
-use litellm_core::messages::messages as run_messages;
-use litellm_core::messages::types::{AnthropicMessagesResponse, MessagesRequest};
-use pyo3::exceptions::{PyRuntimeError, PyValueError};
-use pyo3::prelude::*;
-use pyo3::types::{PyAny, PyDict};
-use serde_json::{Map, Value};
-
-mod gil;
+mod constants;
+mod diagnostics;
+mod errors;
+mod execution;
+pub mod function_trace;
 mod marshal;
+mod routes;
 
-use marshal::{from_py, to_py};
+use litellm_ai_gateway::io::responses_ws::ResponsesWebSocketConnection as RustResponsesWebSocketConnection;
+use pyo3::prelude::*;
+use pyo3::types::PyAny;
+use serde_json::Value;
 
-pyo3::create_exception!(
-    _native,
-    RustBridgeDeclined,
-    pyo3::exceptions::PyException,
-    "The route declined before calling the provider, so the host may retry on its own path."
-);
-
-pyo3::create_exception!(
-    _native,
-    RustUpstreamError,
-    pyo3::exceptions::PyException,
-    "The provider call was already issued and failed. Args are (status, message); status is 0 when there was no HTTP response."
-);
-
-type MarshaledOcrInputs = (
-    Value,
-    Option<Map<String, Value>>,
-    Map<String, Value>,
-    Option<Duration>,
-);
-
-fn messages_response_to_py(
-    py: Python<'_>,
-    response: AnthropicMessagesResponse,
-) -> PyResult<Py<PyAny>> {
-    to_py(py, &response)
-}
-
-fn chat_completions_response_to_py(
-    py: Python<'_>,
-    response: ChatCompletionsResponse,
-) -> PyResult<Py<PyAny>> {
-    to_py(py, &response)
-}
-
-fn core_error_to_pyerr(err: CoreError) -> PyErr {
-    match err {
-        CoreError::Auth(message) => PyValueError::new_err(message),
-        CoreError::InvalidProvider(_)
-        | CoreError::InvalidRequest(_)
-        | CoreError::InvalidType { .. }
-        | CoreError::MissingField(_) => PyValueError::new_err(err.to_string()),
-        other => PyRuntimeError::new_err(other.to_string()),
-    }
-}
-
-/// Map a core error for a route whose host keeps a Python implementation.
-///
-/// The distinction the host needs is whether the provider was already called.
-/// Everything raised before the request goes out is safe for the host to retry
-/// on its own path; anything after it is not, because the provider has already
-/// done the work and billed for it.
-fn chat_completions_error_to_pyerr(err: CoreError) -> PyErr {
-    match err {
-        CoreError::Unsupported(_)
-        | CoreError::Auth(_)
-        | CoreError::InvalidProvider(_)
-        | CoreError::InvalidRequest(_)
-        | CoreError::InvalidType { .. }
-        | CoreError::MissingField(_)
-        | CoreError::Routing(_)
-        // Nothing reached the provider, so serving it on Python cannot double
-        // bill and is the only way the caller gets an answer at all.
-        | CoreError::Connect(_) => RustBridgeDeclined::new_err(err.to_string()),
-        CoreError::Http { status, body } => {
-            RustUpstreamError::new_err((status, format!("{status}: {body}")))
-        }
-        CoreError::Network(message) | CoreError::InvalidResponse(message) => {
-            RustUpstreamError::new_err((0u16, message))
-        }
-    }
-}
-
-fn optional_object_to_map(
-    py: Python<'_>,
-    name: &'static str,
-    value: Option<Py<PyAny>>,
-) -> PyResult<Map<String, Value>> {
-    match value {
-        Some(value) => match from_py(value.bind(py))? {
-            Value::Object(map) => Ok(map),
-            _ => Err(PyValueError::new_err(format!("{name} must be a dict"))),
-        },
-        None => Ok(Map::new()),
-    }
-}
-
-fn optional_timeout(timeout_seconds: Option<f64>) -> Option<Duration> {
-    timeout_seconds.and_then(|secs| {
-        if secs.is_finite() && secs > 0.0 {
-            Some(Duration::from_secs_f64(secs))
-        } else {
-            None
-        }
-    })
-}
-
-fn marshal_headers(
-    py: Python<'_>,
-    headers: Option<Py<PyAny>>,
-) -> PyResult<HashMap<String, String>> {
-    let value = match headers {
-        Some(headers) => from_py(headers.bind(py))?,
-        None => Value::Object(Map::new()),
-    };
-    let Value::Object(headers) = value else {
-        return Err(PyValueError::new_err("headers must be a dict"));
-    };
-    headers
-        .into_iter()
-        .map(|(name, value)| {
-            value
-                .as_str()
-                .map(|value| (name, value.to_string()))
-                .ok_or_else(|| PyValueError::new_err("header values must be strings"))
-        })
-        .collect()
-}
+use crate::errors::core_error_to_pyerr;
+use crate::marshal::{marshal_headers, optional_timeout};
 
 #[pyclass]
 struct ResponsesWebSocketConnection {
@@ -155,16 +27,16 @@ impl ResponsesWebSocketConnection {
         _cls: &Bound<'py, pyo3::types::PyType>,
         py: Python<'py>,
         url: String,
-        headers: Option<Py<PyAny>>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)] headers: Option<Value>,
         timeout_seconds: Option<f64>,
     ) -> PyResult<Bound<'py, PyAny>> {
-        let headers = marshal_headers(py, headers)?;
+        let headers = marshal_headers(headers)?;
         let timeout = optional_timeout(timeout_seconds);
         pyo3_async_runtimes::tokio::future_into_py(py, async move {
             let inner = RustResponsesWebSocketConnection::connect_url(&url, &headers, timeout)
                 .await
                 .map_err(core_error_to_pyerr)?;
-            Python::attach(|py| Py::new(py, ResponsesWebSocketConnection { inner }))
+            Ok(ResponsesWebSocketConnection { inner })
         })
     }
 
@@ -190,445 +62,126 @@ impl ResponsesWebSocketConnection {
     }
 }
 
-fn marshal_inputs(
-    py: Python<'_>,
-    document: Py<PyAny>,
-    extra_headers: Option<Py<PyAny>>,
-    optional_params: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<MarshaledOcrInputs> {
-    let document = from_py(document.bind(py))?;
-    let extra_headers = match extra_headers {
-        Some(headers) => Some(optional_object_to_map(py, "extra_headers", Some(headers))?),
-        None => None,
-    };
-    let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
-    let timeout = optional_timeout(timeout_seconds);
+#[pymodule(gil_used = false)]
+mod _native {
+    use pyo3::prelude::*;
 
-    Ok((document, extra_headers, optional_params, timeout))
-}
-
-#[pyfunction]
-#[pyo3(signature = (model, document, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn ocr(
-    py: Python<'_>,
-    model: String,
-    document: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    optional_params: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Py<PyAny>> {
-    let (document, extra_headers, optional_params, timeout) = marshal_inputs(
-        py,
-        document,
-        extra_headers,
-        optional_params,
-        timeout_seconds,
-    )?;
-
-    let result = gil::release_gil(py, || {
-        pyo3_async_runtimes::tokio::get_runtime().block_on(run_ocr(OcrRequest {
-            model: &model,
-            document,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            optional_params,
-            timeout,
-            callbacks: Vec::new(),
-            guardrails: Vec::new(),
-            request_metadata: Default::default(),
-            litellm_call_id: None,
-        }))
-    });
-
-    match result {
-        Ok(value) => to_py(py, &value),
-        Err(err) => Err(core_error_to_pyerr(err)),
+    #[pymodule_init]
+    fn init(module: &Bound<'_, PyModule>) -> PyResult<()> {
+        super::errors::register(module)?;
+        super::routes::register(module)?;
+        module.add_class::<super::ResponsesWebSocketConnection>()?;
+        super::diagnostics::register(module)
     }
 }
 
-#[pyfunction]
-#[pyo3(signature = (model, document, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn aocr(
-    py: Python<'_>,
-    model: String,
-    document: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    optional_params: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Bound<'_, PyAny>> {
-    let (document, extra_headers, optional_params, timeout) = marshal_inputs(
-        py,
-        document,
-        extra_headers,
-        optional_params,
-        timeout_seconds,
-    )?;
+#[cfg(test)]
+mod tests {
+    use std::ffi::CString;
+    use std::time::Duration;
 
-    pyo3_async_runtimes::tokio::future_into_py(py, async move {
-        let value = run_ocr(OcrRequest {
-            model: &model,
-            document,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            optional_params,
-            timeout,
-            callbacks: Vec::new(),
-            guardrails: Vec::new(),
-            request_metadata: Default::default(),
-            litellm_call_id: None,
-        })
-        .await
-        .map_err(core_error_to_pyerr)?;
+    use futures_util::{SinkExt, StreamExt};
+    use pyo3::types::PyDict;
+    use tokio::net::TcpListener;
+    use tokio_tungstenite::{accept_async, tungstenite::Message};
 
-        Python::attach(|py| to_py(py, &value))
-    })
-}
+    use super::*;
 
-#[pyfunction]
-#[pyo3(signature = (model, audio, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn transcription(
-    py: Python<'_>,
-    model: String,
-    audio: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    optional_params: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Py<PyAny>> {
-    let audio = from_py(audio.bind(py))?;
-    let extra_headers = match extra_headers {
-        Some(headers) => Some(optional_object_to_map(py, "extra_headers", Some(headers))?),
-        None => None,
-    };
-    let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
-    let timeout = optional_timeout(timeout_seconds);
-    let result = gil::release_gil(py, || {
-        pyo3_async_runtimes::tokio::get_runtime().block_on(run_audio_transcription(
-            AudioTranscriptionRequest {
-                model: &model,
-                audio,
-                api_key: api_key.as_deref(),
-                api_base: api_base.as_deref(),
-                custom_llm_provider: custom_llm_provider.as_deref(),
-                extra_headers,
-                optional_params,
-                timeout,
-                callbacks: Vec::new(),
-                guardrails: Vec::new(),
-                request_metadata: Default::default(),
-                litellm_call_id: None,
-            },
-        ))
-    });
-    match result {
-        Ok(value) => to_py(py, &value),
-        Err(err) => Err(core_error_to_pyerr(err)),
+    #[test]
+    fn module_registration_preserves_the_public_surface() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = pyo3::wrap_pymodule!(_native)(py).into_bound(py);
+
+            let expected = [
+                "RustBridgeDeclined",
+                "RustUpstreamError",
+                "ocr",
+                "aocr",
+                "transcription",
+                "atranscription",
+                "messages",
+                "amessages",
+                "chat_completions_decline",
+                "chat_completions",
+                "achat_completions",
+                "ResponsesWebSocketConnection",
+                "gil_stats",
+            ];
+
+            let public_names: Vec<String> = module
+                .dict()
+                .keys()
+                .extract::<Vec<String>>()
+                .expect("module names should be strings")
+                .into_iter()
+                .filter(|name| !name.starts_with("__"))
+                .collect();
+            assert_eq!(public_names, expected);
+        });
+    }
+
+    #[test]
+    fn responses_websocket_connection_round_trips_through_python() {
+        Python::initialize();
+        let runtime = pyo3_async_runtimes::tokio::get_runtime();
+        let listener = runtime
+            .block_on(TcpListener::bind("127.0.0.1:0"))
+            .expect("listener should bind");
+        let address = listener
+            .local_addr()
+            .expect("listener should have an address");
+        let server = runtime.spawn(async move {
+            let (stream, _) = listener.accept().await.expect("server should accept");
+            let mut socket = accept_async(stream)
+                .await
+                .expect("handshake should succeed");
+
+            let message = socket
+                .next()
+                .await
+                .expect("client should send a frame")
+                .expect("client frame should be valid");
+            assert_eq!(message, Message::Text("from-python".into()));
+            socket
+                .send(Message::Text("from-server".into()))
+                .await
+                .expect("server should reply");
+            assert!(matches!(socket.next().await, Some(Ok(Message::Close(_)))));
+        });
+
+        Python::attach(|py| {
+            let module = pyo3::wrap_pymodule!(_native)(py).into_bound(py);
+            let locals = PyDict::new(py);
+            locals
+                .set_item("native", &module)
+                .expect("module should enter Python locals");
+            locals
+                .set_item("url", format!("ws://{address}"))
+                .expect("URL should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    connection = await native.ResponsesWebSocketConnection.connect(url)
+    assert type(connection) is native.ResponsesWebSocketConnection
+    await connection.send_text("from-python")
+    assert await connection.recv_text() == "from-server"
+    await connection.close()
+    assert await connection.recv_text() is None
+
+asyncio.run(asyncio.wait_for(exercise(), timeout=5))
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("Python WebSocket methods should round trip");
+        });
+
+        runtime
+            .block_on(async { tokio::time::timeout(Duration::from_secs(5), server).await })
+            .expect("server should finish")
+            .expect("server task should not panic");
     }
 }
-
-#[pyfunction]
-#[pyo3(signature = (model, audio, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn atranscription(
-    py: Python<'_>,
-    model: String,
-    audio: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    optional_params: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Bound<'_, PyAny>> {
-    let audio = from_py(audio.bind(py))?;
-    let extra_headers = match extra_headers {
-        Some(headers) => Some(optional_object_to_map(py, "extra_headers", Some(headers))?),
-        None => None,
-    };
-    let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
-    let timeout = optional_timeout(timeout_seconds);
-    pyo3_async_runtimes::tokio::future_into_py(py, async move {
-        let value = run_audio_transcription(AudioTranscriptionRequest {
-            model: &model,
-            audio,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            optional_params,
-            timeout,
-            callbacks: Vec::new(),
-            guardrails: Vec::new(),
-            request_metadata: Default::default(),
-            litellm_call_id: None,
-        })
-        .await
-        .map_err(core_error_to_pyerr)?;
-        Python::attach(|py| to_py(py, &value))
-    })
-}
-
-type MarshaledMessagesInputs = (Value, Option<Map<String, Value>>, Option<Duration>);
-
-fn marshal_messages_inputs(
-    py: Python<'_>,
-    body: Py<PyAny>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<MarshaledMessagesInputs> {
-    let body: Value = from_py(body.bind(py))?;
-    if !body.is_object() {
-        return Err(PyValueError::new_err("body must be a dict"));
-    }
-    let extra_headers = match extra_headers {
-        Some(headers) => Some(optional_object_to_map(py, "extra_headers", Some(headers))?),
-        None => None,
-    };
-    Ok((body, extra_headers, optional_timeout(timeout_seconds)))
-}
-
-#[pyfunction]
-#[pyo3(signature = (model, body, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn messages(
-    py: Python<'_>,
-    model: String,
-    body: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Py<PyAny>> {
-    let (body, extra_headers, timeout) =
-        marshal_messages_inputs(py, body, extra_headers, timeout_seconds)?;
-
-    let result = gil::release_gil(py, || {
-        pyo3_async_runtimes::tokio::get_runtime().block_on(run_messages(MessagesRequest {
-            model: &model,
-            body,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            timeout,
-        }))
-    });
-
-    match result {
-        Ok(response) => messages_response_to_py(py, response),
-        Err(err) => Err(core_error_to_pyerr(err)),
-    }
-}
-
-#[pyfunction]
-#[pyo3(signature = (model, body, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn amessages(
-    py: Python<'_>,
-    model: String,
-    body: Py<PyAny>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Bound<'_, PyAny>> {
-    let (body, extra_headers, timeout) =
-        marshal_messages_inputs(py, body, extra_headers, timeout_seconds)?;
-
-    pyo3_async_runtimes::tokio::future_into_py(py, async move {
-        let response = run_messages(MessagesRequest {
-            model: &model,
-            body,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            timeout,
-        })
-        .await
-        .map_err(core_error_to_pyerr)?;
-
-        Python::attach(|py| messages_response_to_py(py, response))
-    })
-}
-
-type MarshaledChatCompletionsInputs = (
-    Value,
-    Map<String, Value>,
-    Option<Map<String, Value>>,
-    Option<Duration>,
-);
-
-fn marshal_chat_completions_inputs(
-    py: Python<'_>,
-    messages: Py<PyAny>,
-    optional_params: Option<Py<PyAny>>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<MarshaledChatCompletionsInputs> {
-    let messages: Value = from_py(messages.bind(py))?;
-    if !messages.is_array() {
-        return Err(PyValueError::new_err("messages must be a list"));
-    }
-    let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
-    let extra_headers = match extra_headers {
-        Some(headers) => Some(optional_object_to_map(py, "extra_headers", Some(headers))?),
-        None => None,
-    };
-    Ok((
-        messages,
-        optional_params,
-        extra_headers,
-        optional_timeout(timeout_seconds),
-    ))
-}
-
-/// The decline reason for this request, or `None` when the Rust path accepts
-/// it. Resolves no credentials and performs no I/O, so a host can ask before
-/// committing to either path.
-#[pyfunction]
-#[pyo3(signature = (model, messages, optional_params=None, custom_llm_provider=None))]
-fn chat_completions_decline(
-    py: Python<'_>,
-    model: String,
-    messages: Py<PyAny>,
-    optional_params: Option<Py<PyAny>>,
-    custom_llm_provider: Option<String>,
-) -> PyResult<Option<String>> {
-    let messages = from_py(messages.bind(py))?;
-    let optional_params = optional_object_to_map(py, "optional_params", optional_params)?;
-    Ok(chat_completions_decline_reason(
-        &model,
-        custom_llm_provider.as_deref(),
-        messages,
-        &optional_params,
-    )
-    .map(str::to_string))
-}
-
-#[pyfunction]
-#[pyo3(signature = (model, messages, optional_params=None, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn chat_completions(
-    py: Python<'_>,
-    model: String,
-    messages: Py<PyAny>,
-    optional_params: Option<Py<PyAny>>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Py<PyAny>> {
-    let (messages, optional_params, extra_headers, timeout) = marshal_chat_completions_inputs(
-        py,
-        messages,
-        optional_params,
-        extra_headers,
-        timeout_seconds,
-    )?;
-
-    let result = gil::release_gil(py, || {
-        pyo3_async_runtimes::tokio::get_runtime().block_on(run_chat_completions(
-            ChatCompletionsRequest {
-                model: &model,
-                messages,
-                optional_params,
-                api_key: api_key.as_deref(),
-                api_base: api_base.as_deref(),
-                custom_llm_provider: custom_llm_provider.as_deref(),
-                extra_headers,
-                timeout,
-            },
-        ))
-    });
-
-    match result {
-        Ok(response) => chat_completions_response_to_py(py, response),
-        Err(err) => Err(chat_completions_error_to_pyerr(err)),
-    }
-}
-
-#[pyfunction]
-#[pyo3(signature = (model, messages, optional_params=None, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None))]
-#[allow(clippy::too_many_arguments)]
-fn achat_completions(
-    py: Python<'_>,
-    model: String,
-    messages: Py<PyAny>,
-    optional_params: Option<Py<PyAny>>,
-    api_key: Option<String>,
-    api_base: Option<String>,
-    custom_llm_provider: Option<String>,
-    extra_headers: Option<Py<PyAny>>,
-    timeout_seconds: Option<f64>,
-) -> PyResult<Bound<'_, PyAny>> {
-    let (messages, optional_params, extra_headers, timeout) = marshal_chat_completions_inputs(
-        py,
-        messages,
-        optional_params,
-        extra_headers,
-        timeout_seconds,
-    )?;
-
-    pyo3_async_runtimes::tokio::future_into_py(py, async move {
-        let response = run_chat_completions(ChatCompletionsRequest {
-            model: &model,
-            messages,
-            optional_params,
-            api_key: api_key.as_deref(),
-            api_base: api_base.as_deref(),
-            custom_llm_provider: custom_llm_provider.as_deref(),
-            extra_headers,
-            timeout,
-        })
-        .await
-        .map_err(chat_completions_error_to_pyerr)?;
-
-        Python::attach(|py| chat_completions_response_to_py(py, response))
-    })
-}
-
-#[pyfunction]
-fn gil_stats(py: Python<'_>) -> PyResult<Py<PyAny>> {
-    let stats = PyDict::new(py);
-    stats.set_item("releases", gil::release_count())?;
-    Ok(stats.into_any().unbind())
-}
-
-#[pymodule]
-fn _native(module: &Bound<'_, PyModule>) -> PyResult<()> {
-    let py = module.py();
-    module.add_function(wrap_pyfunction!(ocr, module)?)?;
-    module.add_function(wrap_pyfunction!(aocr, module)?)?;
-    module.add_function(wrap_pyfunction!(transcription, module)?)?;
-    module.add_function(wrap_pyfunction!(atranscription, module)?)?;
-    module.add_function(wrap_pyfunction!(messages, module)?)?;
-    module.add_function(wrap_pyfunction!(amessages, module)?)?;
-    module.add("RustBridgeDeclined", py.get_type::<RustBridgeDeclined>())?;
-    module.add("RustUpstreamError", py.get_type::<RustUpstreamError>())?;
-    module.add_function(wrap_pyfunction!(chat_completions_decline, module)?)?;
-    module.add_function(wrap_pyfunction!(chat_completions, module)?)?;
-    module.add_function(wrap_pyfunction!(achat_completions, module)?)?;
-    module.add_class::<ResponsesWebSocketConnection>()?;
-    module.add_function(wrap_pyfunction!(gil_stats, module)?)?;
-    Ok(())
-}
diff --git a/litellm-rust/crates/python-bridge/src/marshal.rs b/litellm-rust/crates/python-bridge/src/marshal.rs
index c3d0638427c..a14e4b55d82 100644
--- a/litellm-rust/crates/python-bridge/src/marshal.rs
+++ b/litellm-rust/crates/python-bridge/src/marshal.rs
@@ -1,20 +1,104 @@
+use std::collections::HashMap;
+use std::time::Duration;
+
 use pyo3::exceptions::PyValueError;
 use pyo3::prelude::*;
-use serde::Serialize;
-use serde::de::DeserializeOwned;
+use serde_json::{Map, Value};
 
-pub fn from_py<T>(value: &Bound<'_, PyAny>) -> PyResult<T>
-where
-    T: DeserializeOwned,
-{
-    pythonize::depythonize(value).map_err(|error| PyValueError::new_err(error.to_string()))
+pub(crate) struct RouteOptions {
+    pub(crate) model: String,
+    pub(crate) api_key: Option<String>,
+    pub(crate) api_base: Option<String>,
+    pub(crate) custom_llm_provider: Option<String>,
+    pub(crate) extra_headers: Option<Map<String, Value>>,
+    pub(crate) timeout: Option<Duration>,
 }
 
-pub fn to_py<T>(py: Python<'_>, value: &T) -> PyResult<Py<PyAny>>
-where
-    T: Serialize + ?Sized,
-{
-    pythonize::pythonize(py, value)
-        .map(Bound::unbind)
-        .map_err(|error| PyValueError::new_err(error.to_string()))
+pub(crate) struct RouteOptionsInputs {
+    pub(crate) model: String,
+    pub(crate) api_key: Option<String>,
+    pub(crate) api_base: Option<String>,
+    pub(crate) custom_llm_provider: Option<String>,
+    pub(crate) extra_headers: Option<Value>,
+    pub(crate) timeout_seconds: Option<f64>,
+}
+
+impl RouteOptions {
+    pub(crate) fn from_python(inputs: RouteOptionsInputs) -> PyResult<Self> {
+        Ok(Self {
+            model: inputs.model,
+            api_key: inputs.api_key,
+            api_base: inputs.api_base,
+            custom_llm_provider: inputs.custom_llm_provider,
+            extra_headers: optional_object("extra_headers", inputs.extra_headers)?,
+            timeout: optional_timeout(inputs.timeout_seconds),
+        })
+    }
+}
+
+pub(crate) fn required_value(
+    name: &'static str,
+    value: Value,
+    expected: fn(&Value) -> bool,
+    expected_name: &'static str,
+) -> PyResult<Value> {
+    if expected(&value) {
+        return Ok(value);
+    }
+    Err(PyValueError::new_err(format!(
+        "{name} must be a {expected_name}"
+    )))
+}
+
+pub(crate) fn object_or_empty(
+    name: &'static str,
+    value: Option<Value>,
+) -> PyResult<Map<String, Value>> {
+    match value {
+        Some(value) => object(name, value),
+        None => Ok(Map::new()),
+    }
+}
+
+fn optional_object(
+    name: &'static str,
+    value: Option<Value>,
+) -> PyResult<Option<Map<String, Value>>> {
+    value.map(|value| object(name, value)).transpose()
+}
+
+fn object(name: &'static str, value: Value) -> PyResult<Map<String, Value>> {
+    match value {
+        Value::Object(map) => Ok(map),
+        _ => Err(PyValueError::new_err(format!("{name} must be a dict"))),
+    }
+}
+
+pub(crate) fn optional_timeout(timeout_seconds: Option<f64>) -> Option<Duration> {
+    timeout_seconds.and_then(|secs| {
+        if secs.is_finite() && secs > 0.0 {
+            Some(Duration::from_secs_f64(secs))
+        } else {
+            None
+        }
+    })
+}
+
+pub(crate) fn marshal_headers(headers: Option<Value>) -> PyResult<HashMap<String, String>> {
+    let value = match headers {
+        Some(headers) => headers,
+        None => Value::Object(Map::new()),
+    };
+    let Value::Object(headers) = value else {
+        return Err(PyValueError::new_err("headers must be a dict"));
+    };
+    headers
+        .into_iter()
+        .map(|(name, value)| {
+            value
+                .as_str()
+                .map(|value| (name, value.to_string()))
+                .ok_or_else(|| PyValueError::new_err("header values must be strings"))
+        })
+        .collect()
 }
diff --git a/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs b/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs
new file mode 100644
index 00000000000..10b86132be7
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/audio_transcription.rs
@@ -0,0 +1,71 @@
+use litellm_core::Error;
+use std::future::Future;
+
+use litellm_core::audio_transcription::{
+    AudioTranscriptionRequest, audio_transcription as run_audio_transcription,
+};
+use pyo3::prelude::*;
+use serde_json::Value;
+
+use crate::errors::core_error_to_pyerr;
+use crate::marshal::{RouteOptions, RouteOptionsInputs, object_or_empty};
+
+fn prepare_transcription(
+    inputs: AudioTranscriptionInputs,
+) -> PyResult<impl Future<Output = Result<Value, Error>> + Send + 'static> {
+    let audio = inputs.audio;
+    let options = RouteOptions::from_python(RouteOptionsInputs {
+        model: inputs.model,
+        api_key: inputs.api_key,
+        api_base: inputs.api_base,
+        custom_llm_provider: inputs.custom_llm_provider,
+        extra_headers: inputs.extra_headers,
+        timeout_seconds: inputs.timeout_seconds,
+    })?;
+    let optional_params = object_or_empty("optional_params", inputs.optional_params)?;
+
+    Ok(async move {
+        let RouteOptions {
+            model,
+            api_key,
+            api_base,
+            custom_llm_provider,
+            extra_headers,
+            timeout,
+        } = options;
+        run_audio_transcription(AudioTranscriptionRequest {
+            model: &model,
+            audio,
+            api_key: api_key.as_deref(),
+            api_base: api_base.as_deref(),
+            custom_llm_provider: custom_llm_provider.as_deref(),
+            extra_headers,
+            optional_params,
+            timeout,
+        })
+        .await
+    })
+}
+
+bridge_route! {
+    sync = transcription,
+    asynchronous = atranscription,
+    inputs = AudioTranscriptionInputs,
+    required = {
+        model: String,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        audio: Value,
+    },
+    optional = {
+        api_key: Option<String>,
+        api_base: Option<String>,
+        custom_llm_provider: Option<String>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        extra_headers: Option<Value>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        optional_params: Option<Value>,
+        timeout_seconds: Option<f64>,
+    },
+    prepare = prepare_transcription,
+    errors = core_error_to_pyerr,
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/chat_completions.rs b/litellm-rust/crates/python-bridge/src/routes/chat_completions.rs
new file mode 100644
index 00000000000..68b7762cb10
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/chat_completions.rs
@@ -0,0 +1,91 @@
+use litellm_core::Error;
+use std::future::Future;
+
+use litellm_core::chat_completions::types::{ChatCompletionsRequest, ChatCompletionsResponse};
+use litellm_core::chat_completions::{
+    chat_completions as run_chat_completions, chat_completions_decline_reason,
+};
+use pyo3::prelude::*;
+use serde_json::Value;
+
+use crate::errors::chat_completions_error_to_pyerr;
+use crate::marshal::{RouteOptions, RouteOptionsInputs, object_or_empty, required_value};
+
+fn prepare_chat_completions(
+    inputs: ChatCompletionsInputs,
+) -> PyResult<impl Future<Output = Result<ChatCompletionsResponse, Error>> + Send + 'static> {
+    let messages = required_value("messages", inputs.messages, Value::is_array, "list")?;
+    let optional_params = object_or_empty("optional_params", inputs.optional_params)?;
+    let options = RouteOptions::from_python(RouteOptionsInputs {
+        model: inputs.model,
+        api_key: inputs.api_key,
+        api_base: inputs.api_base,
+        custom_llm_provider: inputs.custom_llm_provider,
+        extra_headers: inputs.extra_headers,
+        timeout_seconds: inputs.timeout_seconds,
+    })?;
+
+    Ok(async move {
+        let RouteOptions {
+            model,
+            api_key,
+            api_base,
+            custom_llm_provider,
+            extra_headers,
+            timeout,
+        } = options;
+        run_chat_completions(ChatCompletionsRequest {
+            model: &model,
+            messages,
+            optional_params,
+            api_key: api_key.as_deref(),
+            api_base: api_base.as_deref(),
+            custom_llm_provider: custom_llm_provider.as_deref(),
+            extra_headers,
+            timeout,
+        })
+        .await
+    })
+}
+
+#[pyfunction]
+#[pyo3(signature = (model, messages, optional_params=None, custom_llm_provider=None))]
+fn chat_completions_decline(
+    model: String,
+    #[pyo3(from_py_with = litellm_python_interop::from_py)] messages: Value,
+    #[pyo3(from_py_with = litellm_python_interop::from_py)] optional_params: Option<Value>,
+    custom_llm_provider: Option<String>,
+) -> PyResult<Option<String>> {
+    let optional_params = object_or_empty("optional_params", optional_params)?;
+    Ok(chat_completions_decline_reason(
+        &model,
+        custom_llm_provider.as_deref(),
+        messages,
+        &optional_params,
+    )
+    .map(str::to_string))
+}
+
+bridge_route! {
+    sync = chat_completions,
+    asynchronous = achat_completions,
+    inputs = ChatCompletionsInputs,
+    required = {
+        model: String,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        messages: Value,
+    },
+    optional = {
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        optional_params: Option<Value>,
+        api_key: Option<String>,
+        api_base: Option<String>,
+        custom_llm_provider: Option<String>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        extra_headers: Option<Value>,
+        timeout_seconds: Option<f64>,
+    },
+    prepare = prepare_chat_completions,
+    errors = chat_completions_error_to_pyerr,
+    extra = [chat_completions_decline],
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/definition.rs b/litellm-rust/crates/python-bridge/src/routes/definition.rs
new file mode 100644
index 00000000000..21a7fd5a766
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/definition.rs
@@ -0,0 +1,429 @@
+use pyo3::exceptions::PyRuntimeError;
+use pyo3::prelude::*;
+use pyo3::types::PyCFunction;
+
+macro_rules! bridge_route {
+    (
+        sync = $sync_name:ident,
+        asynchronous = $async_name:ident,
+        inputs = $inputs:ident,
+        required = { $($(#[$required_attr:meta])* $required_name:ident: $required_type:ty),+ $(,)? },
+        optional = { $($(#[$optional_attr:meta])* $optional_name:ident: $optional_type:ty),* $(,)? },
+        prepare = $prepare:path,
+        errors = $map_error:path
+        $(, extra = [$($extra:ident),* $(,)?])?
+        $(,)?
+    ) => {
+        struct $inputs {
+            $($required_name: $required_type,)*
+            $($optional_name: $optional_type),*
+        }
+
+        #[pyfunction]
+        #[pyo3(signature = ($($required_name),*, $($optional_name=None,)* trace=false))]
+        #[allow(clippy::too_many_arguments)]
+        fn $sync_name(
+            py: pyo3::Python<'_>,
+            $($(#[$required_attr])* $required_name: $required_type,)*
+            $($(#[$optional_attr])* $optional_name: $optional_type,)*
+            trace: bool,
+        ) -> pyo3::PyResult<pyo3::Py<pyo3::PyAny>> {
+            let future = $prepare($inputs {
+                $($required_name,)*
+                $($optional_name),*
+            })?;
+            $crate::execution::run_sync(
+                py,
+                $crate::function_trace::trace_call(future, trace),
+                $map_error,
+            )
+        }
+
+        #[pyfunction]
+        #[pyo3(signature = ($($required_name),*, $($optional_name=None,)* trace=false))]
+        #[allow(clippy::too_many_arguments)]
+        fn $async_name(
+            py: pyo3::Python<'_>,
+            $($(#[$required_attr])* $required_name: $required_type,)*
+            $($(#[$optional_attr])* $optional_name: $optional_type,)*
+            trace: bool,
+        ) -> pyo3::PyResult<pyo3::Bound<'_, pyo3::PyAny>> {
+            let future = $prepare($inputs {
+                $($required_name,)*
+                $($optional_name),*
+            })?;
+            $crate::execution::run_async(
+                py,
+                $crate::function_trace::trace_call(future, trace),
+                $map_error,
+            )
+        }
+
+        pub(super) fn register(
+            module: &pyo3::Bound<'_, pyo3::types::PyModule>,
+        ) -> pyo3::PyResult<()> {
+            $($($crate::routes::definition::add_function(module, pyo3::wrap_pyfunction!($extra, module)?)?;)*)?
+            $crate::routes::definition::add_function(module, pyo3::wrap_pyfunction!($sync_name, module)?)?;
+            $crate::routes::definition::add_function(module, pyo3::wrap_pyfunction!($async_name, module)?)?;
+            Ok(())
+        }
+    };
+}
+
+pub(super) fn add_function(
+    module: &Bound<'_, PyModule>,
+    function: Bound<'_, PyCFunction>,
+) -> PyResult<()> {
+    let name: String = function.getattr("__name__")?.extract()?;
+    if module.hasattr(&name)? {
+        return Err(PyRuntimeError::new_err(format!(
+            "duplicate native route: {name}"
+        )));
+    }
+    module.add_function(function)
+}
+
+#[cfg(test)]
+mod tests {
+    use std::ffi::CString;
+    use std::sync::atomic::{AtomicBool, Ordering};
+
+    use litellm_core::error::Error;
+    use pyo3::exceptions::PyLookupError;
+    use pyo3::types::{PyDict, PyList};
+
+    use super::*;
+
+    mod synthetic {
+        use std::future::{Future, pending};
+
+        use super::*;
+
+        static FUTURE_DROPPED: AtomicBool = AtomicBool::new(false);
+
+        struct DropGuard;
+
+        impl Drop for DropGuard {
+            fn drop(&mut self) {
+                FUTURE_DROPPED.store(true, Ordering::SeqCst);
+            }
+        }
+
+        #[pyfunction]
+        fn future_dropped() -> bool {
+            FUTURE_DROPPED.load(Ordering::SeqCst)
+        }
+
+        bridge_route! {
+            sync = echo,
+            asynchronous = aecho,
+            inputs = EchoInputs,
+            required = { value: String },
+            optional = {},
+            prepare = prepare_echo,
+            errors = map_error,
+            extra = [future_dropped],
+        }
+
+        fn prepare_echo(
+            inputs: EchoInputs,
+        ) -> PyResult<impl Future<Output = Result<String, Error>> + Send + 'static> {
+            FUTURE_DROPPED.store(false, Ordering::SeqCst);
+            let drop_guard = (inputs.value == "pending").then_some(DropGuard);
+            Ok(async move {
+                let _drop_guard = drop_guard;
+                tokio::task::yield_now().await;
+                match inputs.value.as_str() {
+                    "error" => Err(Error::InvalidRequest("synthetic error".to_string())),
+                    "map_panic" => Err(Error::InvalidRequest("panic in mapper".to_string())),
+                    "panic" => panic!("synthetic panic"),
+                    "pending" => {
+                        pending::<()>().await;
+                        unreachable!()
+                    }
+                    _ => Ok(inputs.value),
+                }
+            })
+        }
+
+        fn map_error(error: Error) -> PyErr {
+            if matches!(&error, Error::InvalidRequest(message) if message == "panic in mapper") {
+                panic!("synthetic mapper panic")
+            }
+            PyLookupError::new_err(error.to_string())
+        }
+    }
+
+    #[test]
+    fn sync_and_async_route_signatures_match_the_python_contract() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "routes").expect("module should be created");
+            crate::routes::register(&module).expect("routes should register");
+            let routes = [
+                (
+                    "ocr",
+                    "aocr",
+                    "(model, document, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None, trace=False)",
+                ),
+                (
+                    "transcription",
+                    "atranscription",
+                    "(model, audio, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, optional_params=None, timeout_seconds=None, trace=False)",
+                ),
+                (
+                    "messages",
+                    "amessages",
+                    "(model, body, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None, trace=False)",
+                ),
+                (
+                    "chat_completions",
+                    "achat_completions",
+                    "(model, messages, optional_params=None, api_key=None, api_base=None, custom_llm_provider=None, extra_headers=None, timeout_seconds=None, trace=False)",
+                ),
+            ];
+
+            for (sync_name, async_name, expected) in routes {
+                let sync_signature: String = module
+                    .getattr(sync_name)
+                    .and_then(|function| function.getattr("__text_signature__"))
+                    .and_then(|signature| signature.extract())
+                    .expect("sync signature should be available");
+                let async_signature: String = module
+                    .getattr(async_name)
+                    .and_then(|function| function.getattr("__text_signature__"))
+                    .and_then(|signature| signature.extract())
+                    .expect("async signature should be available");
+
+                assert_eq!(sync_signature, expected);
+                assert_eq!(async_signature, expected);
+            }
+        });
+    }
+
+    #[test]
+    fn sync_and_async_routes_apply_the_same_input_validation() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "routes").expect("module should be created");
+            crate::routes::register(&module).expect("routes should register");
+
+            let invalid_messages = PyDict::new(py);
+            let sync_chat_error = module
+                .getattr("chat_completions")
+                .and_then(|function| function.call1(("model", &invalid_messages)))
+                .expect_err("sync chat should reject a non-list messages value");
+            let async_chat_error = module
+                .getattr("achat_completions")
+                .and_then(|function| function.call1(("model", &invalid_messages)))
+                .expect_err("async chat should reject a non-list messages value");
+
+            assert_eq!(
+                sync_chat_error.to_string(),
+                "ValueError: messages must be a list"
+            );
+            assert_eq!(async_chat_error.to_string(), sync_chat_error.to_string());
+
+            let invalid_body = PyList::empty(py);
+            let sync_messages_error = module
+                .getattr("messages")
+                .and_then(|function| function.call1(("model", &invalid_body)))
+                .expect_err("sync Messages should reject a non-dict body");
+            let async_messages_error = module
+                .getattr("amessages")
+                .and_then(|function| function.call1(("model", &invalid_body)))
+                .expect_err("async Messages should reject a non-dict body");
+
+            assert_eq!(
+                sync_messages_error.to_string(),
+                "ValueError: body must be a dict"
+            );
+            assert_eq!(
+                async_messages_error.to_string(),
+                sync_messages_error.to_string()
+            );
+
+            let invalid_headers = PyList::empty(py);
+            let kwargs = PyDict::new(py);
+            kwargs
+                .set_item("extra_headers", &invalid_headers)
+                .expect("kwargs should accept extra_headers");
+            let document = PyDict::new(py);
+
+            for (sync_name, async_name) in [("ocr", "aocr"), ("transcription", "atranscription")] {
+                let sync_error = module
+                    .getattr(sync_name)
+                    .and_then(|function| function.call(("model", &document), Some(&kwargs)))
+                    .expect_err("sync route should reject non-dict extra_headers");
+                let async_error = module
+                    .getattr(async_name)
+                    .and_then(|function| function.call(("model", &document), Some(&kwargs)))
+                    .expect_err("async route should reject non-dict extra_headers");
+
+                assert_eq!(
+                    sync_error.to_string(),
+                    "ValueError: extra_headers must be a dict"
+                );
+                assert_eq!(async_error.to_string(), sync_error.to_string());
+            }
+        });
+    }
+
+    #[test]
+    fn route_input_validation_preserves_left_to_right_order() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "routes").expect("module should be created");
+            crate::routes::register(&module).expect("routes should register");
+            let invalid = PyList::empty(py);
+
+            let chat_kwargs = PyDict::new(py);
+            chat_kwargs
+                .set_item("optional_params", &invalid)
+                .expect("kwargs should accept optional_params");
+            chat_kwargs
+                .set_item("extra_headers", &invalid)
+                .expect("kwargs should accept extra_headers");
+            let invalid_messages = PyDict::new(py);
+            let error = module
+                .getattr("chat_completions")
+                .and_then(|function| {
+                    function.call(("model", &invalid_messages), Some(&chat_kwargs))
+                })
+                .expect_err("messages should be validated first");
+            assert_eq!(error.to_string(), "ValueError: messages must be a list");
+
+            let valid_messages = PyList::empty(py);
+            let error = module
+                .getattr("chat_completions")
+                .and_then(|function| function.call(("model", &valid_messages), Some(&chat_kwargs)))
+                .expect_err("optional_params should be validated before headers");
+            assert_eq!(
+                error.to_string(),
+                "ValueError: optional_params must be a dict"
+            );
+
+            let headers_kwargs = PyDict::new(py);
+            headers_kwargs
+                .set_item("extra_headers", &invalid)
+                .expect("kwargs should accept extra_headers");
+            let invalid_body = PyList::empty(py);
+            let error = module
+                .getattr("messages")
+                .and_then(|function| function.call(("model", &invalid_body), Some(&headers_kwargs)))
+                .expect_err("body should be validated before headers");
+            assert_eq!(error.to_string(), "ValueError: body must be a dict");
+
+            let invalid_payload =
+                PyModule::new(py, "invalid_payload").expect("invalid payload should be created");
+            for name in ["ocr", "transcription"] {
+                let error = module
+                    .getattr(name)
+                    .and_then(|function| {
+                        function.call(("model", &invalid_payload), Some(&headers_kwargs))
+                    })
+                    .expect_err("payload should be validated before headers");
+                assert!(!error.to_string().contains("extra_headers"));
+            }
+        });
+    }
+
+    #[test]
+    fn generated_routes_execute_sync_and_async_contracts() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "synthetic").expect("module should be created");
+            synthetic::register(&module).expect("routes should register");
+
+            let sync_value: String = module
+                .getattr("echo")
+                .and_then(|function| function.call1(("sync",)))
+                .and_then(|value| value.extract())
+                .expect("sync route should return its value");
+            assert_eq!(sync_value, "sync");
+
+            let sync_error = module
+                .getattr("echo")
+                .and_then(|function| function.call1(("error",)))
+                .expect_err("sync route should map its error");
+            assert!(sync_error.is_instance_of::<PyLookupError>(py));
+            assert_eq!(
+                sync_error.to_string(),
+                "LookupError: invalid request: synthetic error"
+            );
+
+            let locals = PyDict::new(py);
+            locals
+                .set_item("routes", &module)
+                .expect("module should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    assert await routes.aecho("async") == "async"
+
+    try:
+        await routes.aecho("error")
+    except LookupError as error:
+        assert str(error) == "invalid request: synthetic error"
+    else:
+        raise AssertionError("mapped error was not raised")
+
+    try:
+        await routes.aecho("panic")
+    except BaseException as error:
+        assert type(error).__name__ == "PanicException"
+        assert str(error) == "synthetic panic"
+    else:
+        raise AssertionError("panic was not raised")
+
+    try:
+        await routes.aecho("map_panic")
+    except BaseException as error:
+        assert type(error).__name__ == "PanicException"
+        assert str(error) == "synthetic mapper panic"
+    else:
+        raise AssertionError("mapper panic was not raised")
+
+    task = asyncio.ensure_future(routes.aecho("pending"))
+    await asyncio.sleep(0)
+    task.cancel()
+    try:
+        await task
+    except asyncio.CancelledError:
+        pass
+    else:
+        raise AssertionError("cancelled route completed")
+
+    for _ in range(100):
+        if routes.future_dropped():
+            break
+        await asyncio.sleep(0.001)
+    assert routes.future_dropped()
+
+asyncio.run(exercise())
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("async route contract should hold");
+        });
+    }
+
+    #[test]
+    fn route_registration_rejects_duplicate_python_names() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "synthetic").expect("module should be created");
+            synthetic::register(&module).expect("first registration should succeed");
+            let error = synthetic::register(&module)
+                .expect_err("duplicate registration should be rejected");
+
+            assert_eq!(
+                error.to_string(),
+                "RuntimeError: duplicate native route: future_dropped"
+            );
+        });
+    }
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/messages.rs b/litellm-rust/crates/python-bridge/src/routes/messages.rs
new file mode 100644
index 00000000000..2bb64a7a763
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/messages.rs
@@ -0,0 +1,65 @@
+use litellm_core::Error;
+use litellm_core::messages::messages as run_messages;
+use litellm_core::messages::types::{AnthropicMessagesResponse, MessagesRequest};
+use pyo3::prelude::*;
+use serde_json::Value;
+use std::future::Future;
+
+use crate::errors::core_error_to_pyerr;
+use crate::marshal::{RouteOptions, RouteOptionsInputs, required_value};
+
+fn prepare_messages(
+    inputs: MessagesInputs,
+) -> PyResult<impl Future<Output = Result<AnthropicMessagesResponse, Error>> + Send + 'static> {
+    let body = required_value("body", inputs.body, Value::is_object, "dict")?;
+    let options = RouteOptions::from_python(RouteOptionsInputs {
+        model: inputs.model,
+        api_key: inputs.api_key,
+        api_base: inputs.api_base,
+        custom_llm_provider: inputs.custom_llm_provider,
+        extra_headers: inputs.extra_headers,
+        timeout_seconds: inputs.timeout_seconds,
+    })?;
+
+    Ok(async move {
+        let RouteOptions {
+            model,
+            api_key,
+            api_base,
+            custom_llm_provider,
+            extra_headers,
+            timeout,
+        } = options;
+        run_messages(MessagesRequest {
+            model: &model,
+            body,
+            api_key: api_key.as_deref(),
+            api_base: api_base.as_deref(),
+            custom_llm_provider: custom_llm_provider.as_deref(),
+            extra_headers,
+            timeout,
+        })
+        .await
+    })
+}
+
+bridge_route! {
+    sync = messages,
+    asynchronous = amessages,
+    inputs = MessagesInputs,
+    required = {
+        model: String,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        body: Value,
+    },
+    optional = {
+        api_key: Option<String>,
+        api_base: Option<String>,
+        custom_llm_provider: Option<String>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        extra_headers: Option<Value>,
+        timeout_seconds: Option<f64>,
+    },
+    prepare = prepare_messages,
+    errors = core_error_to_pyerr,
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/mod.rs b/litellm-rust/crates/python-bridge/src/routes/mod.rs
new file mode 100644
index 00000000000..bf611c26d44
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/mod.rs
@@ -0,0 +1,16 @@
+use pyo3::prelude::*;
+
+#[macro_use]
+mod definition;
+
+mod audio_transcription;
+mod chat_completions;
+mod messages;
+mod ocr;
+
+pub(crate) fn register(module: &Bound<'_, PyModule>) -> PyResult<()> {
+    ocr::register(module)?;
+    audio_transcription::register(module)?;
+    messages::register(module)?;
+    chat_completions::register(module)
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr.rs b/litellm-rust/crates/python-bridge/src/routes/ocr.rs
new file mode 100644
index 00000000000..5588c400972
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/ocr.rs
@@ -0,0 +1,73 @@
+use litellm_core::Error;
+use std::future::Future;
+
+use litellm_ai_gateway::io::ocr::{OcrRequest, ocr as run_ocr};
+use pyo3::prelude::*;
+use serde_json::Value;
+
+use crate::errors::core_error_to_pyerr;
+use crate::marshal::{RouteOptions, RouteOptionsInputs, object_or_empty};
+
+fn prepare_ocr(
+    inputs: OcrInputs,
+) -> PyResult<impl Future<Output = Result<Value, Error>> + Send + 'static> {
+    let document = inputs.document;
+    let options = RouteOptions::from_python(RouteOptionsInputs {
+        model: inputs.model,
+        api_key: inputs.api_key,
+        api_base: inputs.api_base,
+        custom_llm_provider: inputs.custom_llm_provider,
+        extra_headers: inputs.extra_headers,
+        timeout_seconds: inputs.timeout_seconds,
+    })?;
+    let optional_params = object_or_empty("optional_params", inputs.optional_params)?;
+
+    Ok(async move {
+        let RouteOptions {
+            model,
+            api_key,
+            api_base,
+            custom_llm_provider,
+            extra_headers,
+            timeout,
+        } = options;
+        run_ocr(OcrRequest {
+            model: &model,
+            document,
+            api_key: api_key.as_deref(),
+            api_base: api_base.as_deref(),
+            custom_llm_provider: custom_llm_provider.as_deref(),
+            extra_headers,
+            optional_params,
+            timeout,
+            callbacks: Vec::new(),
+            guardrails: Vec::new(),
+            request_metadata: Default::default(),
+            litellm_call_id: None,
+        })
+        .await
+    })
+}
+
+bridge_route! {
+    sync = ocr,
+    asynchronous = aocr,
+    inputs = OcrInputs,
+    required = {
+        model: String,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        document: Value,
+    },
+    optional = {
+        api_key: Option<String>,
+        api_base: Option<String>,
+        custom_llm_provider: Option<String>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        extra_headers: Option<Value>,
+        #[pyo3(from_py_with = litellm_python_interop::from_py)]
+        optional_params: Option<Value>,
+        timeout_seconds: Option<f64>,
+    },
+    prepare = prepare_ocr,
+    errors = core_error_to_pyerr,
+}
diff --git a/litellm-rust/crates/python-bridge/src/routes/runtime.rs b/litellm-rust/crates/python-bridge/src/routes/runtime.rs
new file mode 100644
index 00000000000..87a0c3e0104
--- /dev/null
+++ b/litellm-rust/crates/python-bridge/src/routes/runtime.rs
@@ -0,0 +1,423 @@
+use std::future::Future;
+use std::panic::AssertUnwindSafe;
+use std::time::Duration;
+
+use futures_util::FutureExt;
+use litellm_core::error::Error;
+use litellm_python_interop::{Pythonized, panic_to_pyerr, release_gil};
+use pyo3::exceptions::PyRuntimeError;
+use pyo3::prelude::*;
+use serde::Serialize;
+use tokio::runtime::{Handle, Runtime};
+use tokio::time::{self, MissedTickBehavior};
+
+pub(super) fn run_sync<T, F>(
+    py: Python<'_>,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Py<PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    run_sync_on(
+        py,
+        pyo3_async_runtimes::tokio::get_runtime(),
+        future,
+        map_error,
+    )
+}
+
+fn run_sync_on<T, F>(
+    py: Python<'_>,
+    runtime: &Runtime,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Py<PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    if Handle::try_current().is_ok() {
+        return Err(PyRuntimeError::new_err(
+            "synchronous native routes cannot run from a Tokio context; use the async route",
+        ));
+    }
+
+    let result = release_gil(py, move || runtime.block_on(wait_for_sync_result(future)))?;
+    let result = map_core_result(result, map_error)?;
+    Pythonized(result).into_pyobject(py).map(Bound::unbind)
+}
+
+pub(super) fn run_async<T, F>(
+    py: Python<'_>,
+    future: F,
+    map_error: fn(Error) -> PyErr,
+) -> PyResult<Bound<'_, PyAny>>
+where
+    T: Serialize + Send + 'static,
+    F: Future<Output = Result<T, Error>> + Send + 'static,
+{
+    pyo3_async_runtimes::tokio::future_into_py(py, async move {
+        let result = catch_route_panic(future).await?;
+        let result = map_core_result(result, map_error)?;
+        Ok(Pythonized(result))
+    })
+}
+
+fn map_core_result<T>(result: Result<T, Error>, map_error: fn(Error) -> PyErr) -> PyResult<T> {
+    match result {
+        Ok(value) => Ok(value),
+        Err(error) => Err(
+            std::panic::catch_unwind(AssertUnwindSafe(|| map_error(error)))
+                .map_err(panic_to_pyerr)?,
+        ),
+    }
+}
+
+async fn catch_route_panic<T, F>(future: F) -> PyResult<Result<T, Error>>
+where
+    F: Future<Output = Result<T, Error>>,
+{
+    AssertUnwindSafe(future)
+        .catch_unwind()
+        .await
+        .map_err(panic_to_pyerr)
+}
+
+async fn wait_for_sync_result<T, F>(future: F) -> PyResult<Result<T, Error>>
+where
+    F: Future<Output = Result<T, Error>>,
+{
+    let future = catch_route_panic(future);
+    tokio::pin!(future);
+
+    let signal_interval = Duration::from_millis(50);
+    let mut signal_checks =
+        time::interval_at(time::Instant::now() + signal_interval, signal_interval);
+    signal_checks.set_missed_tick_behavior(MissedTickBehavior::Delay);
+    loop {
+        tokio::select! {
+            result = &mut future => return result,
+            _ = signal_checks.tick() => Python::attach(|py| py.check_signals())?,
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use std::ffi::CString;
+    use std::future::poll_fn;
+    use std::sync::atomic::{AtomicUsize, Ordering};
+    use std::sync::{Arc, mpsc};
+    use std::task::Poll;
+    use std::thread;
+    use std::time::Instant;
+
+    use pyo3::panic::PanicException;
+    use pyo3::types::{PyDict, PyModule};
+    use serde::Serializer;
+    use tokio::runtime::Builder;
+
+    use super::*;
+
+    fn runtime_error(error: Error) -> PyErr {
+        PyRuntimeError::new_err(error.to_string())
+    }
+
+    fn panicking_error_mapper(_error: Error) -> PyErr {
+        panic!("error mapper panicked")
+    }
+
+    struct PanickingOutput;
+
+    static ASYNC_PROBE_COMPLETED: AtomicUsize = AtomicUsize::new(0);
+
+    impl Serialize for PanickingOutput {
+        fn serialize<S>(&self, _serializer: S) -> Result<S::Ok, S::Error>
+        where
+            S: Serializer,
+        {
+            panic!("serializer panicked")
+        }
+    }
+
+    #[pyfunction]
+    fn async_serialization_panic(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
+        run_async(py, async { Ok(PanickingOutput) }, runtime_error)
+    }
+
+    #[pyfunction]
+    fn async_runtime_probe(py: Python<'_>) -> PyResult<Bound<'_, PyAny>> {
+        run_async(
+            py,
+            async {
+                ASYNC_PROBE_COMPLETED.fetch_add(1, Ordering::SeqCst);
+                Ok(true)
+            },
+            runtime_error,
+        )
+    }
+
+    #[pyfunction]
+    fn runtime_worker_count() -> usize {
+        pyo3_async_runtimes::tokio::get_runtime()
+            .metrics()
+            .num_workers()
+    }
+
+    #[pyfunction]
+    fn runtime_is_responsive(_py: Python<'_>, expected_completions: usize) -> bool {
+        let completion_deadline = Instant::now() + Duration::from_secs(2);
+        while ASYNC_PROBE_COMPLETED.load(Ordering::SeqCst) < expected_completions {
+            if Instant::now() >= completion_deadline {
+                return false;
+            }
+            thread::sleep(Duration::from_millis(1));
+        }
+
+        let (heartbeat_tx, heartbeat_rx) = mpsc::sync_channel(1);
+        pyo3_async_runtimes::tokio::get_runtime().spawn(async move {
+            let _ = heartbeat_tx.send(());
+        });
+        heartbeat_rx.recv_timeout(Duration::from_secs(2)).is_ok()
+    }
+
+    fn extract_bool(py: Python<'_>, result: PyResult<Py<PyAny>>) -> bool {
+        result
+            .expect("route should complete")
+            .bind(py)
+            .extract()
+            .expect("result should convert")
+    }
+
+    #[test]
+    fn sync_runner_polls_future_on_the_caller_thread() {
+        Python::initialize();
+        Python::attach(|py| {
+            let caller_thread = std::thread::current().id();
+            let result = run_sync(
+                py,
+                async move { Ok(std::thread::current().id() == caller_thread) },
+                runtime_error,
+            );
+
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_releases_gil_while_waiting() {
+        Python::initialize();
+        Python::attach(|py| {
+            let result = run_sync(
+                py,
+                async {
+                    let gil_acquired = tokio::time::timeout(
+                        Duration::from_secs(2),
+                        tokio::task::spawn_blocking(|| Python::attach(|_| true)),
+                    )
+                    .await;
+                    Ok(matches!(gil_acquired, Ok(Ok(true))))
+                },
+                runtime_error,
+            );
+
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_rejects_calls_from_a_tokio_context() {
+        Python::initialize();
+        let runtime = Builder::new_current_thread()
+            .enable_all()
+            .build()
+            .expect("runtime should build");
+
+        let error = runtime.block_on(async {
+            Python::attach(|py| {
+                run_sync::<bool, _>(py, async { Ok(true) }, runtime_error)
+                    .expect_err("sync route should reject a nested Tokio runtime")
+            })
+        });
+
+        assert_eq!(
+            error.to_string(),
+            "RuntimeError: synchronous native routes cannot run from a Tokio context; use the async route"
+        );
+    }
+
+    #[test]
+    fn sync_runner_can_drive_a_current_thread_runtime() {
+        Python::initialize();
+        let runtime = Builder::new_current_thread()
+            .enable_all()
+            .build()
+            .expect("runtime should build");
+        Python::attach(|py| {
+            let result = run_sync_on(
+                py,
+                &runtime,
+                async {
+                    tokio::task::yield_now().await;
+                    Ok(true)
+                },
+                runtime_error,
+            );
+            assert!(extract_bool(py, result));
+        });
+    }
+
+    #[test]
+    fn sync_runner_maps_a_panicked_future() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync::<bool, _>(
+                py,
+                poll_fn(|_| -> Poll<Result<bool, Error>> { panic!("route future panicked") }),
+                runtime_error,
+            )
+            .expect_err("panicked route should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: route future panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_maps_a_panicked_error_mapper() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync::<bool, _>(
+                py,
+                async { Err(Error::InvalidRequest("invalid".to_string())) },
+                panicking_error_mapper,
+            )
+            .expect_err("panicked mapper should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: error mapper panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_surfaces_serializer_panics() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = run_sync(py, async { Ok(PanickingOutput) }, runtime_error)
+                .expect_err("serializer panic should become a Python exception");
+
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: serializer panicked");
+        });
+    }
+
+    #[test]
+    fn sync_runner_supports_concurrent_callers_on_the_shared_runtime() {
+        Python::initialize();
+        let barrier = Arc::new(tokio::sync::Barrier::new(2));
+        let callers: Vec<_> = (0..2)
+            .map(|_| {
+                let barrier = Arc::clone(&barrier);
+                thread::spawn(move || {
+                    Python::attach(|py| {
+                        extract_bool(
+                            py,
+                            run_sync(
+                                py,
+                                async move {
+                                    Ok(tokio::time::timeout(Duration::from_secs(2), barrier.wait())
+                                        .await
+                                        .is_ok())
+                                },
+                                runtime_error,
+                            ),
+                        )
+                    })
+                })
+            })
+            .collect();
+        let results: Vec<_> = callers
+            .into_iter()
+            .map(|caller| caller.join().expect("caller should not panic"))
+            .collect();
+
+        assert_eq!(results, vec![true, true]);
+    }
+
+    #[test]
+    fn async_runner_surfaces_serializer_panics() {
+        Python::initialize();
+        Python::attach(|py| {
+            let module = PyModule::new(py, "runtime").expect("module should be created");
+            module
+                .add_function(
+                    wrap_pyfunction!(async_serialization_panic, &module)
+                        .expect("function should wrap"),
+                )
+                .expect("function should register");
+            let locals = PyDict::new(py);
+            locals
+                .set_item("runtime", &module)
+                .expect("module should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    try:
+        await runtime.async_serialization_panic()
+    except BaseException as error:
+        assert type(error).__name__ == "PanicException"
+        assert str(error) == "serializer panicked"
+    else:
+        raise AssertionError("serializer panic was not raised")
+
+asyncio.run(exercise())
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("serializer panic should reach the Python awaiter");
+        });
+    }
+
+    #[test]
+    fn async_result_delivery_does_not_stall_tokio_workers() {
+        Python::initialize();
+        ASYNC_PROBE_COMPLETED.store(0, Ordering::SeqCst);
+        Python::attach(|py| {
+            let module = PyModule::new(py, "runtime").expect("module should be created");
+            for function in [
+                wrap_pyfunction!(async_runtime_probe, &module).expect("function should wrap"),
+                wrap_pyfunction!(runtime_worker_count, &module).expect("function should wrap"),
+                wrap_pyfunction!(runtime_is_responsive, &module).expect("function should wrap"),
+            ] {
+                module
+                    .add_function(function)
+                    .expect("function should register");
+            }
+            let locals = PyDict::new(py);
+            locals
+                .set_item("runtime", &module)
+                .expect("module should enter Python locals");
+            let code = CString::new(
+                r#"
+import asyncio
+
+async def exercise():
+    worker_count = runtime.runtime_worker_count()
+    awaitables = [runtime.async_runtime_probe() for _ in range(worker_count)]
+    assert runtime.runtime_is_responsive(worker_count)
+    assert await asyncio.gather(*awaitables) == [True] * worker_count
+
+asyncio.run(exercise())
+"#,
+            )
+            .expect("Python source should not contain null bytes");
+            py.run(&code, Some(&locals), Some(&locals))
+                .expect("result delivery should leave Tokio workers responsive");
+        });
+    }
+}
diff --git a/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs b/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
index 6a6ede22e85..d397d20b9fd 100644
--- a/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
+++ b/litellm-rust/crates/python-bridge/tests/marshal_boundary.rs
@@ -1,7 +1,7 @@
 use std::fs;
 use std::path::{Path, PathBuf};
 
-const DISALLOWED_OUTSIDE_MARSHAL: &[&str] = &[
+const DISALLOWED_OUTSIDE_INTEROP: &[&str] = &[
     "py.import(\"json\")",
     "pythonize::",
     "serde_json::to_string",
@@ -33,18 +33,15 @@ fn rust_sources(directory: &Path) -> Vec<PathBuf> {
 }
 
 #[test]
-fn serialization_is_centralized_in_marshal_module() {
+fn serialization_uses_the_interop_boundary() {
     let root = source_root();
 
     for path in rust_sources(&root) {
-        if path == root.join("marshal.rs") {
-            continue;
-        }
         let source = fs::read_to_string(&path).expect("bridge source should be readable");
-        for disallowed in DISALLOWED_OUTSIDE_MARSHAL {
+        for disallowed in DISALLOWED_OUTSIDE_INTEROP {
             assert!(
                 !source.contains(disallowed),
-                "{} bypasses the typed marshal module with `{disallowed}`",
+                "{} bypasses litellm-python-interop with `{disallowed}`",
                 path.display()
             );
         }
diff --git a/litellm-rust/crates/python-interop/AGENTS.md b/litellm-rust/crates/python-interop/AGENTS.md
new file mode 100644
index 00000000000..d1d61e5dfa0
--- /dev/null
+++ b/litellm-rust/crates/python-interop/AGENTS.md
@@ -0,0 +1 @@
+litellm-python-interop is the domain-neutral PyO3 foundation. Keep generic Python/Serde conversion and interpreter primitives here. Do not add LiteLLM domain crates, route types, API registration, or cdylib build features.
diff --git a/litellm-rust/crates/python-interop/Cargo.toml b/litellm-rust/crates/python-interop/Cargo.toml
new file mode 100644
index 00000000000..9da6af6e2e2
--- /dev/null
+++ b/litellm-rust/crates/python-interop/Cargo.toml
@@ -0,0 +1,15 @@
+[package]
+name = "litellm-python-interop"
+version = "0.1.0"
+edition.workspace = true
+license.workspace = true
+repository.workspace = true
+
+[dependencies]
+pyo3.workspace = true
+pythonize.workspace = true
+serde.workspace = true
+
+[dev-dependencies]
+rstest.workspace = true
+serde_json.workspace = true
diff --git a/litellm-rust/crates/python-interop/src/gil.rs b/litellm-rust/crates/python-interop/src/gil.rs
new file mode 100644
index 00000000000..04b966a6002
--- /dev/null
+++ b/litellm-rust/crates/python-interop/src/gil.rs
@@ -0,0 +1,21 @@
+use std::sync::atomic::{AtomicU64, Ordering};
+
+use pyo3::prelude::*;
+
+static GIL_RELEASES: AtomicU64 = AtomicU64::new(0);
+
+/// Runs work detached from the interpreter and records the release.
+///
+/// `f` must not access Python state while the interpreter is detached.
+pub fn release_gil<T, F>(py: Python<'_>, f: F) -> T
+where
+    F: FnOnce() -> T + Send,
+    T: Send,
+{
+    GIL_RELEASES.fetch_add(1, Ordering::Relaxed);
+    py.detach(f)
+}
+
+pub fn release_count() -> u64 {
+    GIL_RELEASES.load(Ordering::Relaxed)
+}
diff --git a/litellm-rust/crates/python-interop/src/lib.rs b/litellm-rust/crates/python-interop/src/lib.rs
new file mode 100644
index 00000000000..2e562bdae70
--- /dev/null
+++ b/litellm-rust/crates/python-interop/src/lib.rs
@@ -0,0 +1,5 @@
+mod gil;
+mod marshal;
+
+pub use gil::{release_count, release_gil};
+pub use marshal::{Pythonized, from_py, panic_to_pyerr, to_py};
diff --git a/litellm-rust/crates/python-interop/src/marshal.rs b/litellm-rust/crates/python-interop/src/marshal.rs
new file mode 100644
index 00000000000..a16d1e0ae13
--- /dev/null
+++ b/litellm-rust/crates/python-interop/src/marshal.rs
@@ -0,0 +1,92 @@
+use std::any::Any;
+use std::panic::{AssertUnwindSafe, catch_unwind};
+
+use pyo3::exceptions::PyValueError;
+use pyo3::panic::PanicException;
+use pyo3::prelude::*;
+use serde::Serialize;
+use serde::de::DeserializeOwned;
+
+pub fn from_py<T>(value: &Bound<'_, PyAny>) -> PyResult<T>
+where
+    T: DeserializeOwned,
+{
+    pythonize::depythonize(value).map_err(|error| PyValueError::new_err(error.to_string()))
+}
+
+pub fn to_py<T>(py: Python<'_>, value: &T) -> PyResult<Py<PyAny>>
+where
+    T: Serialize + ?Sized,
+{
+    pythonize::pythonize(py, value)
+        .map(Bound::unbind)
+        .map_err(|error| PyValueError::new_err(error.to_string()))
+}
+
+pub struct Pythonized<T>(pub T);
+
+impl<'py, T> IntoPyObject<'py> for Pythonized<T>
+where
+    T: Serialize,
+{
+    type Target = PyAny;
+    type Output = Bound<'py, PyAny>;
+    type Error = PyErr;
+
+    fn into_pyobject(self, py: Python<'py>) -> PyResult<Self::Output> {
+        catch_unwind(AssertUnwindSafe(|| pythonize::pythonize(py, &self.0)))
+            .map_err(panic_to_pyerr)?
+            .map_err(|error| PyValueError::new_err(error.to_string()))
+    }
+}
+
+pub fn panic_to_pyerr(payload: Box<dyn Any + Send>) -> PyErr {
+    let message = payload
+        .downcast_ref::<String>()
+        .map(String::as_str)
+        .or_else(|| payload.downcast_ref::<&str>().copied())
+        .unwrap_or("panic from Rust code");
+    PanicException::new_err(message.to_string())
+}
+
+#[cfg(test)]
+mod tests {
+    use serde::Serializer;
+
+    use super::*;
+
+    struct PanickingSerializer;
+
+    impl Serialize for PanickingSerializer {
+        fn serialize<S>(&self, _serializer: S) -> Result<S::Ok, S::Error>
+        where
+            S: Serializer,
+        {
+            panic!("serializer panicked")
+        }
+    }
+
+    #[test]
+    fn pythonized_converts_on_the_attached_thread() {
+        Python::initialize();
+        Python::attach(|py| {
+            let value: Vec<i32> = Pythonized(vec![1, 2, 3])
+                .into_pyobject(py)
+                .and_then(|value| value.extract())
+                .expect("value should convert");
+            assert_eq!(value, vec![1, 2, 3]);
+        });
+    }
+
+    #[test]
+    fn pythonized_maps_serializer_panics_to_a_base_exception() {
+        Python::initialize();
+        Python::attach(|py| {
+            let error = Pythonized(PanickingSerializer)
+                .into_pyobject(py)
+                .expect_err("serializer panic should become a Python exception");
+            assert!(error.is_instance_of::<PanicException>(py));
+            assert_eq!(error.to_string(), "PanicException: serializer panicked");
+        });
+    }
+}
diff --git a/litellm-rust/crates/python-interop/tests/interop.rs b/litellm-rust/crates/python-interop/tests/interop.rs
new file mode 100644
index 00000000000..9c456dcb938
--- /dev/null
+++ b/litellm-rust/crates/python-interop/tests/interop.rs
@@ -0,0 +1,44 @@
+use pyo3::Python;
+use rstest::{fixture, rstest};
+use serde_json::{Value, json};
+
+use litellm_python_interop::{from_py, release_count, release_gil, to_py};
+
+struct InitializedPython;
+
+impl InitializedPython {
+    fn attach<F, R>(&self, f: F) -> R
+    where
+        F: for<'py> FnOnce(Python<'py>) -> R,
+    {
+        Python::attach(f)
+    }
+}
+
+#[fixture]
+#[once]
+fn initialized_python() -> InitializedPython {
+    Python::initialize();
+    InitializedPython
+}
+
+#[rstest]
+fn serde_values_round_trip_through_python(#[from(initialized_python)] python: &InitializedPython) {
+    python.attach(|py| {
+        let expected = json!({"model": "test", "items": [1, true, null]});
+        let python_value = to_py(py, &expected).expect("value should convert to Python");
+        let actual: Value =
+            from_py(python_value.bind(py)).expect("Python value should convert to serde");
+
+        assert_eq!(actual, expected);
+    });
+}
+
+#[rstest]
+fn release_gil_runs_work_and_records_it(#[from(initialized_python)] python: &InitializedPython) {
+    let before = release_count();
+    let result = python.attach(|py| release_gil(py, || 42));
+
+    assert_eq!(result, 42);
+    assert_eq!(release_count(), before + 1);
+}
diff --git a/litellm/__init__.py b/litellm/__init__.py
index c83e72a78b4..44f2e7c1f02 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -7,6 +7,9 @@ warnings.filterwarnings("ignore", message=".*conflict with protected namespace.*
 # Suppress Pydantic 2.11+ deprecation warning about accessing model_fields on instances
 # This warning can accumulate during streaming and cause memory leaks
 warnings.filterwarnings("ignore", message=".*Accessing the.*attribute on the instance is deprecated.*")
+# ReadOnly on TypedDict fields is repo-wide static discipline (LIT012); pydantic warns it
+# cannot enforce it at runtime, which floods proxy boot once such a type is schema-walked
+warnings.filterwarnings("ignore", message=".*`ReadOnly` qualifier.*")
 ### INIT VARIABLES #########################
 import threading
 import os
@@ -26,7 +29,7 @@ def _dev_env_hot_reload_enabled() -> bool:
 if os.getenv("LITELLM_MODE", "DEV") == "DEV":
     _dotenv.load_dotenv(override=_dev_env_hot_reload_enabled())
 
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from typing import (
     Any,
     Callable,
@@ -487,6 +490,7 @@ public_mcp_hub_strict_whitelist: bool = True
 public_model_groups: Optional[List[str]] = None
 public_agent_groups: Optional[List[str]] = None
 agent_search_embedding_model: Optional[str] = None
+mcp_tool_search: Optional[Mapping[str, object]] = None
 # Supports both old format (Dict[str, str]) and new format (Dict[str, Dict[str, Any]])
 # New format: { "displayName": { "url": "...", "index": 0 } }
 # Old format: { "displayName": "url" } (for backward compatibility)
@@ -656,6 +660,8 @@ aiml_models: Set = set()
 deepgram_models: Set = set()
 elevenlabs_models: Set = set()
 dashscope_models: Set = set()
+qwencloud_models: Set = set()
+qwen_ai_platform_models: Set = set()
 moonshot_models: Set = set()
 publicai_models: Set = set()
 darkbloom_models: Set = set()
@@ -906,6 +912,10 @@ def _populate_provider_model_sets(model_cost_map: Dict) -> None:
             heroku_models.add(key)
         elif value.get("litellm_provider") == "dashscope":
             dashscope_models.add(key)
+        elif value.get("litellm_provider") == "qwencloud":
+            qwencloud_models.add(key)
+        elif value.get("litellm_provider") == "qwen_ai_platform":
+            qwen_ai_platform_models.add(key)
         elif value.get("litellm_provider") == "modelscope":
             modelscope_models.add(key)
         elif value.get("litellm_provider") == "moonshot":
@@ -1069,6 +1079,8 @@ model_list = list(
     | deepgram_models
     | elevenlabs_models
     | dashscope_models
+    | qwencloud_models
+    | qwen_ai_platform_models
     | moonshot_models
     | publicai_models
     | darkbloom_models
@@ -1175,6 +1187,8 @@ def _build_models_by_provider() -> dict:
         "elevenlabs": elevenlabs_models,
         "heroku": heroku_models,
         "dashscope": dashscope_models,
+        "qwencloud": qwencloud_models,
+        "qwen_ai_platform": qwen_ai_platform_models,
         "modelscope": modelscope_models,
         "moonshot": moonshot_models,
         "publicai": publicai_models,
@@ -1403,7 +1417,7 @@ from .skills.main import (
 )
 from .containers.main import *
 from .ocr.main import *
-from .rust_bridge.ocr import use_litellm_rust
+from .rust_bridge import use_litellm_rust
 from .rag.main import *
 from .sandbox.main import *
 from .search.main import *
@@ -2011,6 +2025,24 @@ if TYPE_CHECKING:
     from .llms.dashscope.rerank.transformation import (
         DashScopeRerankConfig as DashScopeRerankConfig,
     )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudChatConfig as QwenCloudChatConfig,
+    )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudEmbeddingConfig as QwenCloudEmbeddingConfig,
+    )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudRerankConfig as QwenCloudRerankConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformChatConfig as QwenAIPlatformChatConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformEmbeddingConfig as QwenAIPlatformEmbeddingConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformRerankConfig as QwenAIPlatformRerankConfig,
+    )
     from .llms.modelscope.chat.transformation import (
         ModelScopeChatConfig as ModelScopeChatConfig,
     )
diff --git a/litellm/_lazy_imports.py b/litellm/_lazy_imports.py
index d7e00a81b38..553aeb6680d 100644
--- a/litellm/_lazy_imports.py
+++ b/litellm/_lazy_imports.py
@@ -17,7 +17,7 @@ until they're actually needed.
 
 import importlib
 import sys
-from collections.abc import Callable
+from collections.abc import Callable, Mapping
 from types import ModuleType
 from typing import TYPE_CHECKING, Any, Final, cast
 
@@ -57,10 +57,11 @@ from ._lazy_imports_registry import (
 )
 
 if TYPE_CHECKING:
+    import httpx
     from tiktoken import Encoding
 
 
-def get_litellm_globals() -> dict:
+def get_litellm_globals() -> dict[str, object]:
     """
     Get the globals dictionary of the litellm module.
 
@@ -70,7 +71,7 @@ def get_litellm_globals() -> dict:
     return sys.modules["litellm"].__dict__
 
 
-def _get_utils_globals() -> dict:
+def _get_utils_globals() -> dict[str, object]:
     """
     Get the globals dictionary of the utils module.
 
@@ -80,6 +81,11 @@ def _get_utils_globals() -> dict:
     return sys.modules["litellm.utils"].__dict__
 
 
+def _get_module_level_client_timeout(litellm_globals: Mapping[str, Any]) -> "float | httpx.Timeout | None":
+    """Read the configured `litellm.request_timeout` used for the module level http clients."""
+    return litellm_globals.get("request_timeout")
+
+
 # These are special lazy loaders for things that are used internally
 # They're separate from the main lazy import system because they have specific use cases
 
@@ -435,8 +441,8 @@ def _lazy_import_http_handlers(name: str) -> object:
         from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
 
         # Get timeout from module config (if set)
-        timeout = _globals.get("request_timeout")
-        params: Final = {"timeout": timeout, "client_alias": "module level aclient"}
+        async_timeout: Final = _get_module_level_client_timeout(_globals)
+        params: Final = {"timeout": async_timeout, "client_alias": "module level aclient"}
 
         # Create the client instance
         provider_id: Final = cast(Any, "litellm_module_level_client")
@@ -453,8 +459,8 @@ def _lazy_import_http_handlers(name: str) -> object:
         # Create a sync HTTP client
         from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
-        timeout = _globals.get("request_timeout")
-        sync_client: Final = HTTPHandler(timeout=timeout)
+        sync_timeout: Final = _get_module_level_client_timeout(_globals)
+        sync_client: Final = HTTPHandler(timeout=sync_timeout)
 
         # Cache it
         _globals["module_level_client"] = sync_client
diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py
index 1c833256598..e9199e1ec80 100644
--- a/litellm/_lazy_imports_registry.py
+++ b/litellm/_lazy_imports_registry.py
@@ -310,6 +310,8 @@ LLM_CONFIG_NAMES: Final = (
     "GigaChatConfig",
     "GigaChatEmbeddingConfig",
     "DashScopeChatConfig",
+    "QwenCloudChatConfig",
+    "QwenAIPlatformChatConfig",
     "ModelScopeChatConfig",
     "MoonshotChatConfig",
     "DockerModelRunnerChatConfig",
@@ -1172,6 +1174,14 @@ _LLM_CONFIGS_IMPORT_MAP: Final = {
         ".llms.dashscope.chat.transformation",
         "DashScopeChatConfig",
     ),
+    "QwenCloudChatConfig": (
+        ".llms.dashscope.qwencloud",
+        "QwenCloudChatConfig",
+    ),
+    "QwenAIPlatformChatConfig": (
+        ".llms.dashscope.qwen_ai_platform",
+        "QwenAIPlatformChatConfig",
+    ),
     "GDCGeminiConfig": (
         ".llms.gdc.chat.transformation",
         "GDCGeminiConfig",
diff --git a/litellm/_logging.py b/litellm/_logging.py
index fbb35b72be2..14cda772234 100644
--- a/litellm/_logging.py
+++ b/litellm/_logging.py
@@ -6,6 +6,7 @@ import sys
 from datetime import datetime
 from logging import Formatter
 from typing import Any, Final, TextIO
+from urllib.parse import unquote
 
 import litellm
 from litellm.constants import (
@@ -146,6 +147,72 @@ class SecretRedactionFilter(logging.Filter):
 _secret_filter: Final = SecretRedactionFilter()
 
 
+_MAX_SCRUBBED_ACCESS_ARG: Final = 512
+
+_REDACTION_PLACEHOLDER: Final = "REDACTED"
+
+
+def _hides_a_credential(value: str) -> bool:
+    """Whether *value* only looks clean until it is percent-decoded."""
+    decoded: Final = unquote(value)
+    return _redact_string(decoded) != decoded
+
+
+def _drop_encoded_credential(scrubbed: str) -> str:
+    """Drop the part of a request target that only decoding shows to be a secret.
+
+    The request parser decodes query names and values, so `?k%65y=sk%2D...` is a
+    working credential that the patterns, which match literal text, do not see.
+    The decoded text is never logged back: it can carry a newline, and forging
+    log lines is not a trade worth making for a readable request target.
+    """
+    path, separator, _query = scrubbed.partition("?")
+    if _hides_a_credential(path):
+        return _REDACTION_PLACEHOLDER
+    if separator and _hides_a_credential(scrubbed):
+        return f"{path}?{_REDACTION_PLACEHOLDER}"
+    return scrubbed
+
+
+def _scrub_access_arg(value: str) -> str:
+    """Redact one access-log positional arg, bounding the scanned length.
+
+    The request target is the only input to the secret regex an unauthenticated
+    caller controls end to end, so it is cut back to a whole query parameter
+    before it is scanned; a half-parameter would be too short to match its
+    pattern and would then be logged raw.
+    """
+    if len(value) <= _MAX_SCRUBBED_ACCESS_ARG:
+        return _drop_encoded_credential(_redact_string(value))
+    head: Final = value[:_MAX_SCRUBBED_ACCESS_ARG]
+    kept: Final = head[: max(head.rfind("?"), head.rfind("&"))] if "?" in head else head
+    scrubbed: Final = _drop_encoded_credential(_redact_string(kept))
+    return f"{scrubbed}... ({len(value) - len(kept)} more chars truncated) ..."
+
+
+class AccessLogRedactionFilter(logging.Filter):
+    """Scrubs known secret/credential patterns from HTTP access-log records.
+
+    uvicorn's AccessFormatter unpacks ``record.args`` as a five-element tuple at
+    emit time, so SecretRedactionFilter cannot be reused here: it collapses the
+    record into ``record.msg`` and clears the args, and the formatter then raises.
+    """
+
+    def filter(self, record: logging.LogRecord) -> bool:
+        if not _ENABLE_SECRET_REDACTION:
+            return True
+        if isinstance(record.args, tuple) and record.args:
+            record.args = tuple(  # rebind-ok: a Filter scrubs records in place
+                _scrub_access_arg(arg) if isinstance(arg, str) else arg for arg in record.args
+            )
+            return True
+        # No positional args means everything is in msg, where collapsing is correct.
+        return _secret_filter.filter(record)
+
+
+_access_log_filter: Final = AccessLogRedactionFilter()
+
+
 def _get_max_string_length_stdout_log() -> int:
     """Read the limit per record so a value loaded later via proxy config
     environment_variables is honored."""
@@ -264,13 +331,17 @@ def _plain_log_format(stdout: TextIO | None, stderr: TextIO | None) -> str:
 
 
 class LevelRoutingStreamHandler(logging.StreamHandler):
-    """Writes records below WARNING to stdout and WARNING and above to stderr.
+    """Writes records below WARNING and invalid-key warnings to stdout, others to stderr.
 
     Collectors that derive severity from the stream report every stderr line as an error.
+    Invalid-key warnings route to stdout so LITELLM_LOG=ERROR can suppress them.
     """
 
     def emit(self, record: logging.LogRecord) -> None:
-        preferred: Final = sys.stdout if record.levelno < logging.WARNING else sys.stderr
+        is_stdout_record: Final = record.levelno < logging.WARNING or (
+            record.levelno == logging.WARNING and record.name == verbose_proxy_stdout_logger.name
+        )
+        preferred: Final = sys.stdout if is_stdout_record else sys.stderr
         if preferred is None or getattr(preferred, "closed", False):
             self.stream = sys.stderr  # rebind-ok: fall back to the pre-fix stream rather than raising per record
         else:
@@ -508,6 +579,9 @@ else:
     handler.setFormatter(formatter)
 
 verbose_proxy_logger = logging.getLogger("LiteLLM Proxy")
+# Malformed virtual key rejections log through this child; LevelRoutingStreamHandler
+# writes its WARNING records to stdout. It has no handler or level of its own.
+verbose_proxy_stdout_logger: Final = verbose_proxy_logger.getChild("stdout")
 verbose_router_logger = logging.getLogger("LiteLLM Router")
 verbose_logger = logging.getLogger("LiteLLM")
 
@@ -520,6 +594,7 @@ verbose_logger.addHandler(handler)
 # handlers (JSON mode, uvicorn log config, a host app's root handler).
 verbose_router_logger.addFilter(_stdout_truncation_filter)
 verbose_proxy_logger.addFilter(_stdout_truncation_filter)
+verbose_proxy_stdout_logger.addFilter(_stdout_truncation_filter)
 verbose_logger.addFilter(_stdout_truncation_filter)
 
 
@@ -545,6 +620,14 @@ _REDACTED_THIRD_PARTY_LOGGERS: Final[tuple[str, ...]] = (
     "uvicorn.error",
 )
 
+# Access loggers, which emit the full request target, so a credential passed as a
+# query parameter (e.g. `/key/info?key=`) lands on stdout verbatim. uvicorn.access
+# covers uvicorn.run, --run_gunicorn (its worker_class is UvicornWorker, so the
+# access line is still uvicorn's) and an embedding host app. --run_hypercorn and
+# --run_granian log through their own loggers in their own record shapes, and
+# both ship with access logging off.
+_REDACTED_ACCESS_LOGGERS: Final[tuple[str, ...]] = ("uvicorn.access",)
+
 
 def _redact_third_party_loggers() -> None:
     """Extend secret redaction to records litellm does not emit directly.
@@ -567,6 +650,8 @@ def _redact_third_party_loggers() -> None:
     """
     for name in _REDACTED_THIRD_PARTY_LOGGERS:
         logging.getLogger(name).addFilter(_secret_filter)
+    for name in _REDACTED_ACCESS_LOGGERS:
+        logging.getLogger(name).addFilter(_access_log_filter)
 
 
 # Call the suppression function
@@ -683,6 +768,7 @@ def _turn_on_json():
     - Adds a JSON formatter to all loggers
     """
     handler: Final = LevelRoutingStreamHandler()
+    handler.setLevel(numeric_level)
     handler.setFormatter(JsonFormatter())
     _initialize_loggers_with_handler(handler)
     # Set up exception handlers
@@ -700,12 +786,14 @@ def _disable_debugging():
     verbose_logger.disabled = True
     verbose_router_logger.disabled = True
     verbose_proxy_logger.disabled = True
+    verbose_proxy_stdout_logger.disabled = True
 
 
 def _enable_debugging():
     verbose_logger.disabled = False
     verbose_router_logger.disabled = False
     verbose_proxy_logger.disabled = False
+    verbose_proxy_stdout_logger.disabled = False
 
 
 def print_verbose(print_statement):
diff --git a/litellm/_redis.py b/litellm/_redis.py
index 9381357931e..3e68d50cf16 100644
--- a/litellm/_redis.py
+++ b/litellm/_redis.py
@@ -13,6 +13,7 @@ import json
 # s/o [@Frank Colson](https://www.linkedin.com/in/frank-colson-422b9b183/) for this redis implementation
 import os
 from collections.abc import Callable, Mapping
+from types import MappingProxyType
 from typing import Final
 from urllib.parse import urlsplit, urlunsplit
 
@@ -38,9 +39,25 @@ from ._logging import verbose_logger
 AZURE_REDIS_SCOPE: Final = "https://redis.azure.com/.default"
 
 
-def _get_redis_kwargs():
-    arg_spec: Final = inspect.getfullargspec(redis.Redis)
+def _unwrapped_init_args(cls: type) -> frozenset[str]:
+    """Every parameter on a single class's own ``__init__``, decorator-unwrapped.
 
+    Unlike ``_init_arg_names`` below, this does not walk the MRO: ``redis.Redis``
+    and ``redis.RedisCluster`` (sync and async) each declare every real
+    constructor parameter directly on their own ``__init__``, so MRO-walking is
+    unnecessary — and it actively breaks the several tests here that mock the
+    class with ``patch(..., autospec=True)``, since ``inspect.getmro`` needs a
+    real ``__mro__`` that an autospec'd stand-in for a class does not provide.
+
+    Still unwraps first: redis-py >= 7.4 decorates these ``__init__``s with
+    ``@deprecated_args`` too, which the same class of bug as ``_init_arg_names``
+    would otherwise silently empty this allowlist through (see its docstring).
+    """
+    spec: Final = inspect.getfullargspec(inspect.unwrap(cls.__init__))
+    return frozenset(spec.args + spec.kwonlyargs)
+
+
+def _get_redis_kwargs():
     # Only allow primitive arguments
     exclude_args: Final = {
         "self",
@@ -60,7 +77,7 @@ def _get_redis_kwargs():
         "azure_client_secret",
     }
 
-    available_args: Final = {x for x in arg_spec.args if x not in exclude_args} | include_args
+    available_args: Final = {x for x in _unwrapped_init_args(redis.Redis) if x not in exclude_args} | include_args
 
     return available_args
 
@@ -120,15 +137,23 @@ def _get_redis_url_kwargs(client: type | None = None) -> tuple[str, ...]:
     return tuple(x for x in _init_arg_names(connection_cls) if x not in exclude_args) + include_args
 
 
-def _get_redis_cluster_kwargs(client=None):
+def _get_redis_cluster_kwargs(client: type | None = None):
+    """Config kwargs the target cluster client's constructor actually accepts.
+
+    Defaults to the sync ``redis.RedisCluster``, but the async cluster client
+    (``redis.asyncio.cluster.RedisCluster``) declares connection settings such as
+    ``decode_responses`` on its own constructor, where the sync class takes them
+    through ``**kwargs`` and so never names them in its signature. Introspecting
+    only the sync class regardless of which client is actually built silently
+    drops those for every async cluster caller.
+    """
     if client is None:
-        client = redis.Redis.from_url
-    arg_spec: Final = inspect.getfullargspec(redis.RedisCluster)
+        client = redis.RedisCluster
 
     # Only allow primitive arguments
     exclude_args: Final = {"self", "connection_pool", "retry", "host", "port", "startup_nodes"}
 
-    available_args = {x for x in arg_spec.args if x not in exclude_args}
+    available_args = {x for x in _unwrapped_init_args(client) if x not in exclude_args}
     available_args |= {
         "password",
         "username",
@@ -161,6 +186,79 @@ def _get_redis_env_kwarg_mapping():
     return {f"{PREFIX}{x.upper()}": x for x in _get_redis_kwargs() if x not in exclude_from_environment}
 
 
+def _str_to_bool(value: str) -> bool:
+    return value.lower() in ("true", "1", "yes")
+
+
+def _coerce_redis_kwargs_types(
+    redis_kwargs: Mapping[str, object],
+    client: type | tuple[type, ...] = redis.Redis,
+) -> dict[str, object]:  # mutable-ok: a caller mutates the returned kwargs before constructing its client
+    """Coerces string values to the numeric/boolean type ``client``'s constructor
+    declares for that parameter. ``client`` may be a tuple of client classes; a
+    parameter's type is taken from the first signature that declares it, which
+    lets cluster callers coerce cluster-only kwargs such as
+    ``cluster_error_retry_attempts`` alongside the shared connection kwargs.
+
+    Environment variables are always strings, and Helm ``--set`` stringifies values
+    too, so a config value like ``health_check_interval`` or ``socket_timeout``
+    can arrive as ``"30"``/``"5.5"`` rather than a real number. redis-py's own
+    connection-health-check arithmetic (``loop.time() + self.health_check_interval``)
+    then raises ``TypeError`` on every Redis operation instead of connecting.
+
+    ``max_connections``, ``socket_timeout``, and ``socket_connect_timeout`` use an
+    explicit target type rather than the parameter's own signature default: redis-py
+    8.x changed the timeout defaults from ``None`` to int ``5``, so inferring the
+    type from the default would make a fractional ``"5.5"`` fail ``int()`` and get
+    silently dropped on 8.x while working on older versions. ``socket_keepalive``
+    is explicit too: its signature default is ``None``, which carries no type to
+    infer from, and leaving it a string makes ``"false"`` truthy.
+    """
+    signatures: Final = tuple(inspect.signature(c) for c in (client if isinstance(client, tuple) else (client,)))
+    explicit_param_types: Final = MappingProxyType(
+        {
+            "max_connections": int,
+            "socket_timeout": float,
+            "socket_connect_timeout": float,
+            "socket_keepalive": bool,
+        }
+    )
+    result: Final = dict(redis_kwargs)  # mutable-ok: per-key try/except coercion below needs to drop individual keys
+    for key, value in redis_kwargs.items():
+        if not isinstance(value, str):
+            continue
+        param = next((sig.parameters[key] for sig in signatures if key in sig.parameters), None)
+        if param is None:
+            continue
+        explicit_type = explicit_param_types.get(key)
+        if explicit_type is bool:
+            result[key] = _str_to_bool(value)
+            continue
+        if explicit_type is not None:
+            try:
+                result[key] = explicit_type(value)
+            except (ValueError, TypeError):
+                del result[key]
+            continue
+        default: object = param.default  # pyright: ignore[reportAny]  # inspect.Parameter.default is stubbed as Any
+        if default is inspect.Parameter.empty:
+            continue
+        # bool must be checked before int, since bool subclasses int
+        if isinstance(default, bool):
+            result[key] = _str_to_bool(value)
+        elif isinstance(default, int):
+            try:
+                result[key] = int(value)
+            except (ValueError, TypeError):
+                del result[key]
+        elif isinstance(default, float):
+            try:
+                result[key] = float(value)
+            except (ValueError, TypeError):
+                del result[key]
+    return result
+
+
 def _redis_kwargs_from_environment():
     mapping: Final = _get_redis_env_kwarg_mapping()
 
@@ -505,7 +603,12 @@ def _get_redis_client_logic(**env_overrides):
         raise ValueError("Either 'host' or 'url' must be specified for redis.")
 
     # litellm.print_verbose(f"redis_kwargs: {redis_kwargs}")
-    return redis_kwargs
+    coercion_client: Final = (
+        (redis.Redis, redis.RedisCluster, async_redis.RedisCluster)
+        if redis_kwargs.get("startup_nodes")
+        else redis.Redis
+    )
+    return _coerce_redis_kwargs_types(redis_kwargs, client=coercion_client)
 
 
 def init_redis_cluster(redis_kwargs) -> redis.RedisCluster:
@@ -657,7 +760,9 @@ def get_redis_client(**env_overrides):
     if "sentinel_nodes" in redis_kwargs and "service_name" in redis_kwargs:
         return _init_redis_sentinel(redis_kwargs)
 
-    return redis.Redis(**redis_kwargs)
+    return redis.Redis(  # pyright: ignore[reportCallIssue]  # object-valued kwargs match no overload statically
+        **redis_kwargs,  # pyright: ignore[reportArgumentType]  # allow-listed and coerced against this signature
+    )
 
 
 def get_redis_async_client(
@@ -669,7 +774,7 @@ def get_redis_async_client(
     if "startup_nodes" in redis_kwargs:
         from redis.cluster import ClusterNode
 
-        args = _get_redis_cluster_kwargs()
+        args = _get_redis_cluster_kwargs(async_redis.RedisCluster)
         cluster_kwargs: Final = {}
         for arg in redis_kwargs:
             if arg in args:
diff --git a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
index 32252711997..1e8cc4ff90e 100644
--- a/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
+++ b/litellm/a2a_protocol/providers/bedrock_agentcore/transformation.py
@@ -10,8 +10,19 @@ from collections.abc import AsyncIterator, Mapping
 from typing import Any, Final
 
 from litellm._logging import verbose_logger
+from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+    A2A_USER_API_KEY_HASH_PARAM,
+)
+from litellm.a2a_protocol.utils import (
+    get_session_id_from_a2a_params,
+    scope_session_to_principal,
+)
+from litellm.exceptions import BadRequestError
 from litellm.llms.bedrock.chat.agentcore.transformation import AmazonAgentCoreConfig
 
+RUNTIME_SESSION_ID_MIN_LENGTH: Final = 33
+RUNTIME_SESSION_ID_MAX_LENGTH: Final = 256
+
 # Reserved outbound header names that must never be sourced from per-request
 # ``agent_extra_headers`` for AgentCore requests. ``agent_extra_headers`` carries
 # values rewritten from the client-controlled ``x-a2a-{agent}-*`` convention, so
@@ -19,8 +30,9 @@ from litellm.llms.bedrock.chat.agentcore.transformation import AmazonAgentCoreCo
 # request identity / SigV4 metadata by overwriting headers the proxy sets from
 # trusted server-side config.
 #
-# The runtime headers (session / user id) are derived server-side from
-# ``runtimeSessionId`` / ``runtimeUserId`` in the agent's ``litellm_params``;
+# The runtime headers (session / user id) are derived server-side from the A2A
+# ``message.contextId`` and ``runtimeSessionId`` / ``runtimeUserId`` in the
+# agent's ``litellm_params``;
 # ``authorization`` is set by the AgentCore signer (JWT or SigV4); ``host`` and
 # the ``x-amz-*`` family are owned by SigV4 itself.
 _RESERVED_EXACT_HEADERS: Final = frozenset(
@@ -66,6 +78,31 @@ def _filter_reserved_headers(
     return filtered or None
 
 
+def _request_scoped_runtime_session_id(
+    params: Mapping[str, Any],
+    litellm_params: Mapping[str, Any],
+) -> str | None:
+    context_id: Final = get_session_id_from_a2a_params(params)
+    if not isinstance(context_id, str) or not context_id:
+        return None
+    return scope_session_to_principal(context_id, litellm_params.get(A2A_USER_API_KEY_HASH_PARAM))
+
+
+def _validate_runtime_session_id(session_id: str, model: str) -> str:
+    if RUNTIME_SESSION_ID_MIN_LENGTH <= len(session_id) <= RUNTIME_SESSION_ID_MAX_LENGTH:
+        return session_id
+    raise BadRequestError(
+        message=(
+            f"Invalid AgentCore runtime session id {session_id!r}: AWS requires "
+            f"{RUNTIME_SESSION_ID_MIN_LENGTH}-{RUNTIME_SESSION_ID_MAX_LENGTH} characters. It is built from the A2A "
+            "message.contextId (prefixed with a 16-hex-char hash of the calling key and '-') when set, "
+            "otherwise from the agent's configured runtimeSessionId."
+        ),
+        model=model,
+        llm_provider="bedrock",
+    )
+
+
 class BedrockAgentCoreA2ATransformation:
     """
     Request/response transformation for Bedrock AgentCore A2A agents.
@@ -100,7 +137,9 @@ class BedrockAgentCoreA2ATransformation:
                 here to prevent a caller-controlled ``x-a2a-{agent}-*`` header from
                 spoofing the AgentCore runtime user id or other SigV4 metadata. Use
                 ``api_key`` / ``runtimeUserId`` / ``runtimeSessionId`` in litellm_params
-                (not ``agent_extra_headers``) to override those values.
+                (not ``agent_extra_headers``) to override those values. The runtime
+                session id is taken from ``params["message"]["contextId"]`` (scoped to
+                the calling key) when present, then ``runtimeSessionId``, else generated.
 
         Returns:
             Tuple of (url, signed_headers, signed_body_bytes)
@@ -139,7 +178,11 @@ class BedrockAgentCoreA2ATransformation:
         # Set required AgentCore session headers (normally set by transform_request,
         # which we skip because it also builds {"prompt": "..."})
         headers: Final[dict] = {}
-        session_id: Final = agentcore_config._get_runtime_session_id(optional_params)
+        session_id: Final = _validate_runtime_session_id(
+            _request_scoped_runtime_session_id(params, litellm_params)
+            or agentcore_config._get_runtime_session_id(optional_params),
+            model=model,
+        )
         headers["X-Amzn-Bedrock-AgentCore-Runtime-Session-Id"] = session_id
         runtime_user_id: Final = agentcore_config._get_runtime_user_id(optional_params)
         if runtime_user_id:
diff --git a/litellm/a2a_protocol/utils.py b/litellm/a2a_protocol/utils.py
index f2e61f66105..7c459daf720 100644
--- a/litellm/a2a_protocol/utils.py
+++ b/litellm/a2a_protocol/utils.py
@@ -2,6 +2,8 @@
 Utility functions for A2A protocol.
 """
 
+import hashlib
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 import litellm
@@ -140,6 +142,29 @@ class A2ARequestUtils:
         return prompt_tokens, completion_tokens, total_tokens
 
 
+def get_session_id_from_a2a_params(params: Mapping[str, Any]) -> str | None:
+    message: Final = params.get("message", {})
+    if isinstance(message, dict):
+        return message.get("contextId")
+    return getattr(message, "contextId", None)
+
+
+def scope_session_to_principal(session_id: str, principal: str | None) -> str:
+    """
+    Bind a client-supplied A2A contextId to the authenticated principal.
+
+    Without this, two distinct keys authorized for the same agent could set the
+    same contextId and read/append to each other's backend memory. The
+    principal is hashed (it is already a hashed token) so the raw value is never
+    sent to the agent backend, while the original contextId is kept as a suffix
+    for operator-side correlation.
+    """
+    if not principal:
+        return session_id
+    principal_prefix: Final = hashlib.sha256(principal.encode("utf-8")).hexdigest()[:16]
+    return f"{principal_prefix}-{session_id}"
+
+
 # Backwards compatibility aliases
 def extract_text_from_a2a_message(message: Any) -> str:
     return A2ARequestUtils.extract_text_from_message(message)
diff --git a/litellm/caching/caching.py b/litellm/caching/caching.py
index cefe6aae9ed..754815fce47 100644
--- a/litellm/caching/caching.py
+++ b/litellm/caching/caching.py
@@ -12,6 +12,7 @@ import hashlib
 import json
 import time
 import traceback
+from collections.abc import Mapping
 from enum import Enum
 from typing import Any, Final
 
@@ -506,7 +507,7 @@ class Cache:
 
     def _get_cache_logic(
         self,
-        cached_result: Any | None,
+        cached_result: object | None,
         max_age: float | None,
     ):
         """
@@ -538,8 +539,8 @@ class Cache:
         return cached_result
 
     @staticmethod
-    def _get_safe_cache_lookup_kwargs(kwargs: dict[str, Any]) -> dict[str, Any]:
-        cache_lookup_kwargs: Final[dict[str, Any]] = {}
+    def _get_safe_cache_lookup_kwargs(kwargs: Mapping[str, object]) -> dict[str, object]:
+        cache_lookup_kwargs: Final[dict[str, object]] = {}
         for prompt_kwarg in ("messages", "input"):
             if prompt_kwarg in kwargs:
                 cache_lookup_kwargs[prompt_kwarg] = kwargs[prompt_kwarg]
@@ -552,7 +553,7 @@ class Cache:
 
     @staticmethod
     def _update_metadata_from_cache_lookup_kwargs(
-        original_kwargs: dict[str, Any], cache_lookup_kwargs: dict[str, Any]
+        original_kwargs: Mapping[str, object], cache_lookup_kwargs: Mapping[str, object]
     ) -> None:
         original_metadata: Final = original_kwargs.get("metadata")
         cache_lookup_metadata: Final = cache_lookup_kwargs.get("metadata")
diff --git a/litellm/caching/qdrant_semantic_cache.py b/litellm/caching/qdrant_semantic_cache.py
index 4898700c403..c5876e993d3 100644
--- a/litellm/caching/qdrant_semantic_cache.py
+++ b/litellm/caching/qdrant_semantic_cache.py
@@ -12,7 +12,7 @@ import ast
 import asyncio
 import json
 import os
-from typing import TYPE_CHECKING, Any, Final, cast
+from typing import TYPE_CHECKING, Any, Final, Protocol, cast
 
 import litellm
 from litellm._logging import print_verbose
@@ -39,6 +39,12 @@ if TYPE_CHECKING:
     from litellm.router import Router
 
 
+class _QdrantCollectionDetailsResponse(Protocol):
+    """The qdrant `/collections/{name}` response, whose body is kept as an opaque JSON object."""
+
+    def json(self) -> dict[str, object]: ...
+
+
 class QdrantSemanticCache(BaseCache):
     CACHE_KEY_FIELD_NAME = "litellm_cache_key"
     embedding_max_input_tokens: int | None = None
@@ -115,15 +121,15 @@ class QdrantSemanticCache(BaseCache):
             raise ValueError(f"Error from qdrant checking if /collections exist {collection_exists.text}")
 
         if collection_exists.json()["result"]["exists"]:
-            collection_details = self.sync_client.get(
+            collection_details: _QdrantCollectionDetailsResponse = self.sync_client.get(
                 url=f"{self.qdrant_api_base}/collections/{self.collection_name}",
                 headers=self.headers,
             )
-            self.collection_info = collection_details.json()
+            self.collection_info: dict[str, object] = collection_details.json()
             print_verbose(f"Collection already exists.\nCollection details:{self.collection_info}")
             self._ensure_cache_key_payload_index()
         else:
-            quantization_params: dict[str, Any]
+            quantization_params: dict[str, dict[str, object]]
             if quantization_config is None or quantization_config == "binary":
                 quantization_params = {
                     "binary": {
@@ -214,7 +220,7 @@ class QdrantSemanticCache(BaseCache):
             resolve_embedding_max_input_tokens(self.embedding_max_input_tokens, self.embedding_model, router),
         )
 
-    def _get_embedding(self, prompt: str, metadata: dict[str, Any] | None = None) -> EmbeddingResponse:
+    def _get_embedding(self, prompt: str, metadata: dict[str, object] | None = None) -> EmbeddingResponse:
         """Embed via the proxy Router when it serves the model, else direct."""
         try:
             from litellm.proxy.proxy_server import llm_model_list, llm_router
@@ -241,7 +247,7 @@ class QdrantSemanticCache(BaseCache):
             num_retries=0,
         )
 
-    async def _get_async_embedding(self, prompt: str, metadata: dict[str, Any] | None = None) -> EmbeddingResponse:
+    async def _get_async_embedding(self, prompt: str, metadata: dict[str, object] | None = None) -> EmbeddingResponse:
         try:
             from litellm.proxy.proxy_server import llm_model_list, llm_router
         except ImportError:
diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py
index f1c80eaacbe..2b04a075114 100644
--- a/litellm/caching/redis_cache.py
+++ b/litellm/caching/redis_cache.py
@@ -18,7 +18,7 @@ import time
 from collections.abc import Awaitable, Callable, Sequence
 from contextvars import ContextVar
 from datetime import timedelta
-from typing import TYPE_CHECKING, Any, Final, TypeVar, cast
+from typing import TYPE_CHECKING, Any, Final, Protocol, TypeVar, cast
 
 import litellm
 from litellm._logging import print_verbose, verbose_logger
@@ -58,6 +58,26 @@ else:
     Span = Any
 
 
+class _AsyncRedisCommands(Protocol):
+    """Async redis commands this cache issues.
+
+    redis-py's type stubs omit these methods on RedisCluster, so the union returned by
+    init_async_client() is untyped at every call site without this protocol.
+    """
+
+    def ping(self) -> Awaitable[bool]: ...
+
+    def delete(self, *names: str) -> Awaitable[int]: ...
+
+    def ttl(self, name: str) -> Awaitable[int]: ...
+
+    def rpush(self, name: str, *values: str | bytes | float) -> Awaitable[int]: ...
+
+    def lpop(self, name: str, count: int | None = None) -> Awaitable[object]: ...
+
+    def pipeline(self, transaction: bool = True) -> "Pipeline[bytes]": ...
+
+
 def _get_call_stack_info(num_frames: int = 2) -> str:
     """
     Get the function names from the previous 1-2 functions in the call stack.
@@ -429,6 +449,9 @@ class RedisCache(BaseCache):
         self.redis_async_client = redis_async_client
         return redis_async_client
 
+    def _async_commands(self) -> _AsyncRedisCommands:
+        return self.init_async_client()
+
     def check_and_fix_namespace(self, key: str) -> str:
         """
         Make sure each key starts with the given namespace
@@ -1055,19 +1078,17 @@ class RedisCache(BaseCache):
         await self.async_set_cache_pipeline(self.redis_batch_writing_buffer)
         self.redis_batch_writing_buffer = []
 
-    def _get_cache_logic(self, cached_response: Any):
+    def _get_cache_logic(self, cached_response: bytes | str | None):
         """
         Common 'get_cache_logic' across sync + async redis client implementations
         """
         if cached_response is None:
-            return cached_response
-        # cached_response is in `b{} convert it to ModelResponse
-        cached_response = cached_response.decode("utf-8")  # Convert bytes to string
+            return None
+        decoded: Final = cached_response.decode("utf-8") if isinstance(cached_response, bytes) else cached_response
         try:
-            cached_response = json.loads(cached_response)  # Convert string to dictionary
+            return json.loads(decoded)
         except Exception:
-            cached_response = ast.literal_eval(cached_response)
-        return cached_response
+            return ast.literal_eval(decoded)
 
     def get_cache(self, key, parent_otel_span: Span | None = None, **kwargs):
         try:
@@ -1314,8 +1335,7 @@ class RedisCache(BaseCache):
             raise e
 
     async def ping(self) -> bool:
-        # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `ping`
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         start_time: Final = time.time()
         print_verbose("Pinging Async Redis Cache")
         try:
@@ -1349,8 +1369,7 @@ class RedisCache(BaseCache):
 
     @_redis_circuit_breaker_guard
     async def delete_cache_keys(self, keys):
-        # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `delete`
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         keys = [self.check_and_fix_namespace(key=key) for key in keys]
         # keys is a list, unpack it so it gets passed as individual elements to delete
         await _redis_client.delete(*keys)
@@ -1415,8 +1434,7 @@ class RedisCache(BaseCache):
 
     @_redis_circuit_breaker_guard
     async def async_delete_cache(self, key: str):
-        # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `delete`
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         key = self.check_and_fix_namespace(key=key)
         # keys is str
         return await _redis_client.delete(key)
@@ -1523,8 +1541,7 @@ class RedisCache(BaseCache):
         Redis ref: https://redis.io/docs/latest/commands/ttl/
         """
         try:
-            # typed as Any, redis python lib has incomplete type stubs for RedisCluster and does not include `ttl`
-            _redis_client: Final[Any] = self.init_async_client()
+            _redis_client: Final = self._async_commands()
             key = self.check_and_fix_namespace(key=key)
             ttl: Final = await _redis_client.ttl(key)
             if ttl <= -1:  # -1 means the key does not exist, -2 key does not exist
@@ -1554,7 +1571,7 @@ class RedisCache(BaseCache):
         Returns:
             int: The length of the list after the push operation
         """
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         key = self.check_and_fix_namespace(key=key)
         start_time: Final = time.time()
         try:
@@ -1621,7 +1638,7 @@ class RedisCache(BaseCache):
         if len(rpush_list) == 0:
             return []
 
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         start_time: Final = time.time()
 
         try:
@@ -1678,7 +1695,7 @@ class RedisCache(BaseCache):
         parent_otel_span: Span | None = None,
         **kwargs,
     ) -> Any | list[Any]:
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         key = self.check_and_fix_namespace(key=key)
         start_time: Final = time.time()
         print_verbose(f"LPOP from Redis list: key: {key}, count: {count}")
@@ -1810,7 +1827,7 @@ class RedisCache(BaseCache):
         if len(lpop_list) == 0:
             return []
 
-        _redis_client: Final[Any] = self.init_async_client()
+        _redis_client: Final = self._async_commands()
         start_time: Final = time.time()
 
         try:
diff --git a/litellm/caching/valkey_semantic_cache.py b/litellm/caching/valkey_semantic_cache.py
index c66f6873383..58b76d98d6d 100644
--- a/litellm/caching/valkey_semantic_cache.py
+++ b/litellm/caching/valkey_semantic_cache.py
@@ -17,6 +17,7 @@ RedisSemanticCache since those are backend agnostic.
 import asyncio
 import hashlib
 import os
+from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
 from typing import Any, Final
 
@@ -64,7 +65,7 @@ class ValkeySemanticCache(RedisSemanticCache):
         async_client: AsyncRedis | None = None,
         embedding_max_input_tokens: int | None = None,
         embedding_timeout: float | None = None,
-        **kwargs: Any,
+        **kwargs: object,
     ):
         if similarity_threshold is None:
             raise ValueError("similarity_threshold must be provided, passed None")
@@ -87,11 +88,13 @@ class ValkeySemanticCache(RedisSemanticCache):
         self.key_prefix = f"{self.index_name}:"
         self._index_dim: int | None = None
 
-        resolved_url = None
-        if sync_client is None or async_client is None:
-            resolved_url = redis_url or self._build_valkey_url(host, port, password, ssl)
-        self.sync_client = sync_client if sync_client is not None else Redis.from_url(resolved_url)
-        self.async_client = async_client if async_client is not None else AsyncRedis.from_url(resolved_url)
+        if sync_client is not None and async_client is not None:
+            self.sync_client = sync_client
+            self.async_client = async_client
+        else:
+            resolved_url: Final = redis_url or self._build_valkey_url(host, port, password, ssl)
+            self.sync_client = sync_client if sync_client is not None else Redis.from_url(resolved_url)
+            self.async_client = async_client if async_client is not None else AsyncRedis.from_url(resolved_url)
 
         print_verbose(f"Valkey semantic-cache initializing index - {self.index_name}")
 
@@ -118,7 +121,7 @@ class ValkeySemanticCache(RedisSemanticCache):
         return hashlib.sha256(str(key).encode("utf-8")).hexdigest()
 
     @staticmethod
-    def _embedding_to_bytes(embedding: list[float]) -> bytes:
+    def _embedding_to_bytes(embedding: Sequence[float]) -> bytes:
         return pack_vector(embedding)
 
     def _index_schema(self, dim: int) -> tuple[TagField, VectorField]:
@@ -192,7 +195,9 @@ class ValkeySemanticCache(RedisSemanticCache):
     def _doc_key(self, key: str) -> str:
         return f"{self.key_prefix}{self._scope_tag(key)}:{uuid.uuid4()}"
 
-    def _doc_mapping(self, key: str, prompt: str, value_str: str, embedding: list[float]) -> dict:
+    def _doc_mapping(
+        self, key: str, prompt: str, value_str: str, embedding: Sequence[float]
+    ) -> Mapping[str | bytes, str | bytes]:
         return {
             self.CACHE_KEY_FIELD_NAME: self._scope_tag(key),
             self.PROMPT_FIELD_NAME: prompt,
@@ -208,30 +213,49 @@ class ValkeySemanticCache(RedisSemanticCache):
         )
         return Query(query_string).return_fields(self.RESPONSE_FIELD_NAME, self.DISTANCE_FIELD_NAME).dialect(2)
 
+    async def _async_search(self, key: str, embedding: Sequence[float]) -> object:
+        """Run the KNN query on the async client, stopping the untyped search surface here."""
+        return await self.async_client.ft(self.index_name).search(
+            self._knn_query(key),
+            query_params={"vec": self._embedding_to_bytes(embedding)},  # pyright: ignore[reportArgumentType]  # redis stubs omit bytes; KNN vectors are raw bytes at runtime
+        )
+
     @classmethod
-    def _first_hit(cls, search_result: Any) -> _ValkeyCacheHit | None:
-        docs: Final = getattr(search_result, "docs", [])
+    def _first_hit(cls, search_result: object) -> _ValkeyCacheHit | None:
+        docs: Final[Sequence[object]] = getattr(search_result, "docs", [])
         if not docs:
             return None
         doc: Final = docs[0]
+        response_field: Final[object] = getattr(doc, cls.RESPONSE_FIELD_NAME)
+        distance_field: Final[str | bytes | float] = getattr(doc, cls.DISTANCE_FIELD_NAME)
         return _ValkeyCacheHit(
-            response=str(getattr(doc, cls.RESPONSE_FIELD_NAME)),
-            distance=float(getattr(doc, cls.DISTANCE_FIELD_NAME)),
+            response=str(response_field),
+            distance=float(distance_field),
         )
 
-    def _resolve_hit(self, hit: _ValkeyCacheHit | None, key: str, **kwargs: Any) -> Any:
+    @staticmethod
+    def _record_similarity(kwargs: dict[str, Any], similarity: float) -> None:
+        """Stamp the semantic-similarity score onto the request metadata carried in ``kwargs``."""
+        kwargs.setdefault("metadata", {})["semantic-similarity"] = similarity
+
+    @staticmethod
+    def _embedding_metadata(kwargs: dict[str, Any]) -> dict[str, Any] | None:
+        """The request metadata forwarded to the embedding call."""
+        return kwargs.get("metadata")
+
+    def _resolve_hit(self, hit: _ValkeyCacheHit | None, key: str, **kwargs: object) -> object:
         if hit is None:
-            kwargs.setdefault("metadata", {})["semantic-similarity"] = 0.0
+            self._record_similarity(kwargs, 0.0)
             return None
 
         similarity: Final = 1 - hit.distance
-        kwargs.setdefault("metadata", {})["semantic-similarity"] = similarity
+        self._record_similarity(kwargs, similarity)
 
         if similarity < self.similarity_threshold:
             return None
         return self._get_cache_logic(cached_response=hit.response)
 
-    def set_cache(self, key: str, value: Any, **kwargs: Any) -> None:
+    def set_cache(self, key: str, value: object, **kwargs: object) -> None:
         print_verbose(f"Valkey semantic-cache set_cache, kwargs: {kwargs}")
         try:
             prompt: Final = self._get_prompt_from_kwargs(**kwargs)
@@ -250,12 +274,12 @@ class ValkeySemanticCache(RedisSemanticCache):
         except Exception as e:
             print_verbose(f"Error in Valkey semantic-cache set_cache: {e}")
 
-    def get_cache(self, key: str, **kwargs: Any) -> Any:
+    def get_cache(self, key: str, **kwargs: object) -> object:
         print_verbose(f"Valkey semantic-cache get_cache, kwargs: {kwargs}")
         try:
             prompt: Final = self._get_prompt_from_kwargs(**kwargs)
             if prompt is None:
-                kwargs.setdefault("metadata", {})["semantic-similarity"] = 0.0
+                self._record_similarity(kwargs, 0.0)
                 return None
 
             embedding: Final = self._get_embedding(prompt)
@@ -263,14 +287,14 @@ class ValkeySemanticCache(RedisSemanticCache):
 
             search_result: Final = self.sync_client.ft(self.index_name).search(
                 self._knn_query(key),
-                query_params={"vec": self._embedding_to_bytes(embedding)},
+                query_params={"vec": self._embedding_to_bytes(embedding)},  # pyright: ignore[reportArgumentType]  # redis stubs omit bytes; KNN vectors are raw bytes at runtime
             )
             return self._resolve_hit(self._first_hit(search_result), key, **kwargs)
         except Exception as e:
             print_verbose(f"Error in Valkey semantic-cache get_cache: {e}")
-            kwargs.setdefault("metadata", {})["semantic-similarity"] = 0.0
+            self._record_similarity(kwargs, 0.0)
 
-    async def async_set_cache(self, key: str, value: Any, **kwargs: Any) -> None:
+    async def async_set_cache(self, key: str, value: object, **kwargs: object) -> None:
         print_verbose(f"Async Valkey semantic-cache set_cache, kwargs: {kwargs}")
         try:
             prompt: Final = self._get_prompt_from_kwargs(**kwargs)
@@ -278,7 +302,7 @@ class ValkeySemanticCache(RedisSemanticCache):
                 print_verbose("No prompt provided for semantic caching")
                 return
 
-            embedding: Final = await self._get_async_embedding(prompt, metadata=kwargs.get("metadata"))
+            embedding: Final = await self._get_async_embedding(prompt, metadata=self._embedding_metadata(kwargs))
             await self._ensure_index_async(len(embedding))
 
             doc_key: Final = self._doc_key(key)
@@ -289,31 +313,28 @@ class ValkeySemanticCache(RedisSemanticCache):
         except Exception as e:
             print_verbose(f"Error in async Valkey semantic-cache set_cache: {e}")
 
-    async def async_get_cache(self, key: str, **kwargs: Any) -> Any:
+    async def async_get_cache(self, key: str, **kwargs: object) -> object:
         print_verbose(f"Async Valkey semantic-cache get_cache, kwargs: {kwargs}")
         try:
             prompt: Final = self._get_prompt_from_kwargs(**kwargs)
             if prompt is None:
-                kwargs.setdefault("metadata", {})["semantic-similarity"] = 0.0
+                self._record_similarity(kwargs, 0.0)
                 return None
 
-            embedding: Final = await self._get_async_embedding(prompt, metadata=kwargs.get("metadata"))
+            embedding: Final = await self._get_async_embedding(prompt, metadata=self._embedding_metadata(kwargs))
             await self._ensure_index_async(len(embedding))
 
-            search_result: Final = await self.async_client.ft(self.index_name).search(
-                self._knn_query(key),
-                query_params={"vec": self._embedding_to_bytes(embedding)},
-            )
+            search_result: Final[object] = await self._async_search(key, embedding)
             return self._resolve_hit(self._first_hit(search_result), key, **kwargs)
         except Exception as e:
             print_verbose(f"Error in async Valkey semantic-cache get_cache: {e}")
-            kwargs.setdefault("metadata", {})["semantic-similarity"] = 0.0
+            self._record_similarity(kwargs, 0.0)
 
-    async def async_set_cache_pipeline(self, cache_list: list[tuple[str, Any]], **kwargs: Any) -> None:
+    async def async_set_cache_pipeline(self, cache_list: list[tuple[str, object]], **kwargs: object) -> None:
         try:
             await asyncio.gather(*[self.async_set_cache(key, value, **kwargs) for key, value in cache_list])
         except Exception as e:
             print_verbose(f"Error in Valkey semantic-cache async_set_cache_pipeline: {e}")
 
-    async def _index_info(self) -> dict:
+    async def _index_info(self) -> Mapping[str, object]:
         return await self.async_client.ft(self.index_name).info()
diff --git a/litellm/completion_extras/litellm_responses_transformation/handler.py b/litellm/completion_extras/litellm_responses_transformation/handler.py
index 727c39c16ec..f494d6610a1 100644
--- a/litellm/completion_extras/litellm_responses_transformation/handler.py
+++ b/litellm/completion_extras/litellm_responses_transformation/handler.py
@@ -45,14 +45,14 @@ class ResponsesToCompletionBridgeHandler:
         return bool(stream)
 
     @staticmethod
-    def _is_preformatted_cached_chat_stream(result: Any) -> bool:
+    def _is_preformatted_cached_chat_stream(result: object) -> bool:
         from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
 
         return isinstance(result, CustomStreamWrapper) and result.custom_llm_provider == "cached_response"
 
     @staticmethod
     def _coerce_response_object(
-        response_obj: Any,
+        response_obj: object,
         hidden_params: dict | None,
     ) -> "ResponsesAPIResponse":
         if isinstance(response_obj, ResponsesAPIResponse):
@@ -78,8 +78,8 @@ class ResponsesToCompletionBridgeHandler:
         for _ in stream_iter:
             pass
 
-        completed: Final = getattr(stream_iter, "completed_response", None)
-        response_obj: Final = getattr(completed, "response", None) if completed else None
+        completed: Final[object] = getattr(stream_iter, "completed_response", None)
+        response_obj: Final[object] = getattr(completed, "response", None) if completed else None
         if response_obj is None:
             raise ValueError("Stream ended without a completed response")
 
@@ -93,8 +93,8 @@ class ResponsesToCompletionBridgeHandler:
         async for _ in stream_iter:
             pass
 
-        completed: Final = getattr(stream_iter, "completed_response", None)
-        response_obj: Final = getattr(completed, "response", None) if completed else None
+        completed: Final[object] = getattr(stream_iter, "completed_response", None)
+        response_obj: Final[object] = getattr(completed, "response", None) if completed else None
         if response_obj is None:
             raise ValueError("Stream ended without a completed response")
 
@@ -157,7 +157,7 @@ class ResponsesToCompletionBridgeHandler:
     def completion(
         self, *args, **kwargs
     ) -> Union[
-        Coroutine[Any, Any, Union["ModelResponse", "CustomStreamWrapper"]],
+        Coroutine[None, None, Union["ModelResponse", "CustomStreamWrapper"]],
         "ModelResponse",
         "CustomStreamWrapper",
     ]:
diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py
index 85fb0bc8dc6..7368de1e968 100644
--- a/litellm/completion_extras/litellm_responses_transformation/transformation.py
+++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py
@@ -212,7 +212,8 @@ def _tool_call_dict_from_output_item(item: Mapping[str, Any], index: int) -> _Ch
         LiteLLMCompletionResponsesConfig,
     )
 
-    is_custom: Final = item.get("type") == "custom_tool_call"
+    item_type: Final[object] = item.get("type")
+    is_custom: Final = item_type == "custom_tool_call"
     arguments: Final = (item.get("input") if is_custom else item.get("arguments")) or ""
     name: Final = item.get("name") or ("custom_tool" if is_custom else "")
     function_chunk: Final = ChatCompletionToolCallFunctionChunk(name=name, arguments=arguments)
@@ -222,7 +223,7 @@ def _tool_call_dict_from_output_item(item: Mapping[str, Any], index: int) -> _Ch
         function=function_chunk,
         index=index,
     )
-    raw_provider_fields: Final = item.get("provider_specific_fields")
+    raw_provider_fields: Final[object] = item.get("provider_specific_fields")
     if isinstance(raw_provider_fields, dict):
         provider_specific_fields = raw_provider_fields
     elif raw_provider_fields and hasattr(raw_provider_fields, "__dict__"):
@@ -507,7 +508,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
 
     def _merge_responses_api_request_into_request_data(
         self,
-        request_data: dict[str, Any],
+        request_data: dict[str, object],
         responses_api_request: "ResponsesAPIOptionalRequestParams",
         instructions: str | None,
     ) -> None:
diff --git a/litellm/constants.py b/litellm/constants.py
index cc6db6c10cc..c7b74e176db 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -9,10 +9,48 @@ DEFAULT_HEALTH_CHECK_PROMPT: Final = str(os.getenv("DEFAULT_HEALTH_CHECK_PROMPT"
 AZURE_DEFAULT_RESPONSES_API_VERSION: Final = str(os.getenv("AZURE_DEFAULT_RESPONSES_API_VERSION", "preview"))
 ROUTER_MAX_FALLBACKS: Final = int(os.getenv("ROUTER_MAX_FALLBACKS", 5))
 ROUTER_FALLBACK_ERROR_DETAIL_MAX_CHARS: Final = 2000
+RUNTIME_UPDATABLE_ROUTER_SETTINGS: Final[frozenset[str]] = frozenset(
+    {
+        "routing_strategy_args",
+        "routing_strategy",
+        "routing_groups",
+        "allowed_fails",
+        "cooldown_time",
+        "num_retries",
+        "timeout",
+        "max_retries",
+        "retry_after",
+        "fallbacks",
+        "context_window_fallbacks",
+        "retry_policy",
+        "model_group_retry_policy",
+        "model_group_alias",
+        "enable_weighted_failover",
+        "enable_tag_filtering",
+        "tag_routing_prefix",
+        "optional_pre_call_checks",
+    }
+)
+ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG: Final[frozenset[str]] = frozenset(
+    {
+        "model_list",
+        "search_tools",
+        "assistants_config",
+        "router_general_settings",
+        "ignore_invalid_deployments",
+        "fallback_access_check",
+    }
+)
 DEFAULT_BATCH_SIZE: Final = int(os.getenv("DEFAULT_BATCH_SIZE", 512))
 DEFAULT_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_FLUSH_INTERVAL_SECONDS", 5))
 DEFAULT_S3_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_S3_FLUSH_INTERVAL_SECONDS", 10))
 DEFAULT_S3_BATCH_SIZE: Final = int(os.getenv("DEFAULT_S3_BATCH_SIZE", 512))
+# https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-keys.html
+MAX_S3_OBJECT_KEY_BYTES: Final = 1024
+S3_BOUNDED_OBJECT_KEY_HEAD_BYTES: Final = 64
+S3_PREFIX_DIGEST_CHARS: Final = 16
+# s3 allows 2048 bytes of combined metadata headers, which Content-Disposition counts against
+MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES: Final = 1024
 DEFAULT_SQS_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_SQS_FLUSH_INTERVAL_SECONDS", 10))
 DEFAULT_NUM_WORKERS_LITELLM_PROXY: Final = int(os.getenv("DEFAULT_NUM_WORKERS_LITELLM_PROXY", 1))
 DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE = int(os.getenv("DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE", 1))
@@ -130,6 +168,7 @@ MCP_CLIENT_TIMEOUT: Final = float(os.getenv("LITELLM_MCP_CLIENT_TIMEOUT", "60.0"
 MCP_TOOL_LISTING_TIMEOUT: Final = float(os.getenv("LITELLM_MCP_TOOL_LISTING_TIMEOUT", "30.0"))
 MCP_METADATA_TIMEOUT: Final = float(os.getenv("LITELLM_MCP_METADATA_TIMEOUT", "10.0"))
 MCP_HEALTH_CHECK_TIMEOUT: Final = float(os.getenv("LITELLM_MCP_HEALTH_CHECK_TIMEOUT", "10.0"))
+MCP_TOOL_LISTING_MAX_PAGES: Final = 1000
 
 # Allowlist of commands permitted for MCP stdio transport.
 # Prevents arbitrary command execution via /mcp-rest/test/* endpoints or server creation.
@@ -484,6 +523,22 @@ FIREWORKS_AI_80_B: Final = int(os.getenv("FIREWORKS_AI_80_B", 80))
 #### Logging callback constants ####
 REDACTED_BY_LITELM_STRING: Final = "REDACTED_BY_LITELM"
 MAX_LANGFUSE_INITIALIZED_CLIENTS: Final = int(os.getenv("MAX_LANGFUSE_INITIALIZED_CLIENTS", 50))
+# Backpressure + lifetime bounds for the /v1/messages streaming relay (see
+# BaseAnthropicMessagesStreamingIterator.async_sse_wrapper). The relay queue is
+# bounded so a slow client throttles the upstream pump instead of letting it
+# buffer the whole response in memory; the detached-drain cap bounds how many
+# post-disconnect drains may run concurrently so client behavior can't create
+# unbounded worker state.
+ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE: Final = int(
+    os.getenv("ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", "1024")
+)
+# Setting this to 0 disables detached draining entirely: every post-disconnect
+# pump bills whatever partial output it has already collected and aborts the
+# upstream stream immediately, instead of continuing to drain for the real
+# terminal usage.
+ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS: Final = int(
+    os.getenv("ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", "100")
+)
 LOGGING_WORKER_CONCURRENCY: Final = int(os.getenv("LOGGING_WORKER_CONCURRENCY", 100))  # Must be above 0
 LOGGING_WORKER_MAX_QUEUE_SIZE: Final = int(os.getenv("LOGGING_WORKER_MAX_QUEUE_SIZE", 50_000))
 LOGGING_WORKER_MAX_TIME_PER_COROUTINE: Final = float(os.getenv("LOGGING_WORKER_MAX_TIME_PER_COROUTINE", 20.0))
@@ -614,6 +669,8 @@ LITELLM_CHAT_PROVIDERS: Final = [
     "nscale",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "publicai",
@@ -783,6 +840,7 @@ openai_compatible_endpoints: Final[list] = [
     "inference.api.nscale.com/v1",
     "api.studio.nebius.ai/v1",
     "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
+    "https://dashscope.aliyuncs.com/compatible-mode/v1",
     "https://api-inference.modelscope.cn/v1",
     "https://api.moonshot.ai/v1",
     "https://api.publicai.co/v1",
@@ -806,6 +864,7 @@ openai_compatible_endpoints: Final[list] = [
     "https://api.meta.ai/v1",
     "https://api.cognition.ai/v1",
     "https://api.scx.ai/v1",
+    "https://gigachat.devices.sberbank.ru/api/v1",
 ]
 
 
@@ -855,6 +914,8 @@ openai_compatible_providers: Final[list] = [
     "nscale",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "v0",
@@ -885,6 +946,8 @@ openai_text_completion_compatible_providers: Final[list] = [  # providers that s
     "featherless_ai",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "publicai",
@@ -1092,7 +1155,7 @@ nebius_models: Final[set] = set(
     ]
 )
 
-dashscope_models: Final[set] = set(
+dashscope_models: Final[frozenset] = frozenset(
     [
         "qwen-turbo",
         "qwen-plus",
@@ -1107,6 +1170,10 @@ dashscope_models: Final[set] = set(
     ]
 )
 
+qwencloud_models: Final[frozenset] = frozenset(dashscope_models)
+
+qwen_ai_platform_models: Final[frozenset] = frozenset(dashscope_models)
+
 nebius_embedding_models: Final[set] = set(
     [
         "BAAI/bge-en-icl",
@@ -1223,6 +1290,7 @@ BEDROCK_CONVERSE_MODELS: Final = [
     "openai.gpt-oss-120b-1:0",
     "anthropic.claude-haiku-4-5-20251001-v1:0",
     "anthropic.claude-sonnet-4-5-20250929-v1:0",
+    "anthropic.claude-fable-5-1",
     "anthropic.claude-fable-5",
     "anthropic.claude-sonnet-5",
     "anthropic.claude-opus-5",
@@ -1410,6 +1478,12 @@ DEFAULT_SOFT_BUDGET: Final = float(
 )  # by default all litellm proxy keys have a soft budget of 50.0
 # makes it clear this is a rate limit error for a litellm virtual key
 RATE_LIMIT_ERROR_MESSAGE_FOR_VIRTUAL_KEY: Final = "LiteLLM Virtual Key user_api_key_hash"
+# Prefix of the 401 raised when a submitted virtual key is not shaped like one.
+INVALID_VIRTUAL_KEY_ERROR_MESSAGE: Final = "LiteLLM Virtual Key expected"
+# Attribute stamped on that 401 at its raise site so log routing recognises it by
+# provenance. Message text is caller-influenceable on other 401s, so it must not
+# be used to classify.
+INVALID_VIRTUAL_KEY_ERROR_MARKER: Final = "_litellm_invalid_virtual_key_error"
 
 # Python garbage collection threshold configuration
 # Format: "gen0,gen1,gen2" e.g., "1000,50,50"
@@ -1548,6 +1622,7 @@ KEY_ROTATION_JOB_NAME: Final = "litellm_key_rotation_job"
 EXPIRED_UI_SESSION_KEY_CLEANUP_JOB_NAME: Final = "litellm_expired_ui_session_key_cleanup_job"
 WEEKLY_SPEND_REPORT_JOB_ID: Final = "weekly_spend_report_job"
 MONTHLY_SPEND_REPORT_JOB_ID: Final = "monthly_spend_report_job"
+USER_SPEND_ALERTS_JOB_ID: Final = "user_spend_alerts_job"
 PROMETHEUS_FALLBACK_STATS_JOB_ID: Final = "prometheus_fallback_stats_job"
 SLACK_DAILY_REPORT_LOCK_ID: Final = "slack_daily_report"
 SLACK_MODEL_DEPRECATION_LOCK_ID: Final = "slack_model_deprecation_warning"
@@ -1667,6 +1742,7 @@ LITELLM_SETTINGS_SAFE_DB_OVERRIDES: Final = [
     "anthropic_prompt_caching_ttl",
     "max_ui_session_budget",
     "budget_rollover",
+    "mcp_tool_search",
 ]
 SPECIAL_LITELLM_AUTH_TOKEN: Final = ["ui-token"]
 DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL = int(os.getenv("DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL", 60))
@@ -1728,6 +1804,7 @@ SENTRY_DENYLIST: Final = [
     "jwt_token",
     "private_key",
     "SLACK_WEBHOOK_URL",
+    "ALERTING_WEBHOOK_URL",
     "webhook_url",
     "LANGFUSE_SECRET_KEY",
     # Email Configuration
diff --git a/litellm/containers/main.py b/litellm/containers/main.py
index 97ca11872c1..90d59af009f 100644
--- a/litellm/containers/main.py
+++ b/litellm/containers/main.py
@@ -1,7 +1,7 @@
 import asyncio
 import contextvars
 import json
-from collections.abc import Coroutine, Mapping
+from collections.abc import Callable, Coroutine, Mapping
 from functools import partial
 from typing import Final, Literal, overload
 
@@ -47,6 +47,13 @@ __all__ = [
 
 
 ##### Container Create #######################
+async def _encode_created_container_id(
+    pending: Coroutine[object, object, ContainerObject],
+    encode: Callable[[ContainerObject], ContainerObject],
+) -> ContainerObject:
+    return encode(await pending)
+
+
 @client
 async def acreate_container(
     name: str,
@@ -256,16 +263,16 @@ def create_container(
             _is_async=_is_async,
         )
 
-        # Encode container_id with provider/model metadata for routing
+        encode: Final = partial(
+            ContainerRequestUtils.encode_container_id_in_response,
+            custom_llm_provider=custom_llm_provider,
+            litellm_metadata=kwargs.get("litellm_metadata"),
+            extra_body=extra_body,
+        )
         if isinstance(container_obj, ContainerObject):
-            container_obj = ContainerRequestUtils.encode_container_id_in_response(
-                response_obj=container_obj,
-                custom_llm_provider=custom_llm_provider,
-                litellm_metadata=kwargs.get("litellm_metadata"),
-                extra_body=extra_body,
-            )
+            return encode(container_obj)
 
-        return container_obj
+        return _encode_created_container_id(pending=container_obj, encode=encode)
 
     except Exception as e:
         raise litellm.exception_type(
diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index 3adc1c25dfd..b83e9b395a8 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -641,12 +641,12 @@ def cost_per_token(
         return xai_cost_per_token(model=model, usage=usage_block)
     elif custom_llm_provider == "lemonade":
         return lemonade_cost_per_token(model=model, usage=usage_block)
-    elif custom_llm_provider == "dashscope":
+    elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
         from litellm.llms.dashscope.cost_calculator import (
             cost_per_token as dashscope_cost_per_token,
         )
 
-        return dashscope_cost_per_token(model=model, usage=usage_block)
+        return dashscope_cost_per_token(model=model, usage=usage_block, custom_llm_provider=custom_llm_provider)
     elif custom_llm_provider == "azure_ai":
         return azure_ai_cost_per_token(
             model=model,
@@ -1910,12 +1910,15 @@ def ocr_cost(
     if credits is not None and cost_per_credit is not None:
         return cost_per_credit * credits, 0.0
 
-    ocr_cost_per_page: float | None = None
-    if model_info is not None:
-        ocr_cost_per_page = model_info.get("ocr_cost_per_page")
+    ocr_cost_per_page: Final = model_info.get("ocr_cost_per_page") if model_info is not None else None
+    annotation_cost_per_page: Final = model_info.get("annotation_cost_per_page") if model_info is not None else None
+    annotation_rate: Final = annotation_cost_per_page if annotation_cost_per_page is not None else ocr_cost_per_page
 
     pages_processed: Final = response.usage_info.pages_processed
-    if pages_processed is None:
+    annotation_pages: Final = response.usage_info.pages_processed_annotation or 0
+    has_billable_annotation_pages: Final = annotation_rate is not None and annotation_pages > 0
+
+    if pages_processed is None and not has_billable_annotation_pages:
         if cost_per_credit is not None or ocr_cost_per_page is None:
             # Surface missing usage data instead of silently under-reporting
             # cost. The previous behavior raised ValueError; we now return 0.0
@@ -1931,7 +1934,7 @@ def ocr_cost(
             return 0.0, 0.0
         raise ValueError("OCR response pages_processed is None")
 
-    if ocr_cost_per_page is None:
+    if ocr_cost_per_page is None and not has_billable_annotation_pages:
         # No per-page pricing configured. Either the model is on credit-based
         # pricing (and credits weren't returned, so the credit branch above did
         # not match) or the model has no OCR pricing entry at all. Surface a
@@ -1947,8 +1950,9 @@ def ocr_cost(
         )
         return 0.0, 0.0
 
-    total_ocr_processing_cost: Final[float] = ocr_cost_per_page * pages_processed
-    return total_ocr_processing_cost, 0.0
+    ocr_pages_cost: Final = (ocr_cost_per_page or 0.0) * (pages_processed or 0)
+    annotation_pages_cost: Final = (annotation_rate or 0.0) * annotation_pages
+    return ocr_pages_cost + annotation_pages_cost, 0.0
 
 
 def vector_store_search_cost(
@@ -2268,6 +2272,10 @@ def batch_cost_calculator(
     return total_prompt_cost, total_completion_cost
 
 
+def _attribute_value(obj: object, name: str) -> object:
+    return getattr(obj, name)
+
+
 def _summable_prompt_token_fields(prompt_tokens_details: BaseModel) -> list[str]:
     field_names: Final = list(type(prompt_tokens_details).model_fields)
     if getattr(prompt_tokens_details, "cache_write_tokens", None) is None:
@@ -2293,7 +2301,7 @@ class BaseTokenUsageProcessor:
         for usage in usage_objects:
             # Handle direct attributes by checking what exists in the model
             for attr in dir(usage):
-                if not attr.startswith("_") and not callable(getattr(usage, attr)):
+                if not attr.startswith("_") and not callable(_attribute_value(usage, attr)):
                     current_val = getattr(combined, attr, 0)
                     new_val = getattr(usage, attr, 0)
                     if (
@@ -2313,7 +2321,7 @@ class BaseTokenUsageProcessor:
                     if (
                         hasattr(usage.prompt_tokens_details, attr)
                         and not attr.startswith("_")
-                        and not callable(getattr(usage.prompt_tokens_details, attr))
+                        and not callable(_attribute_value(usage.prompt_tokens_details, attr))
                     ):
                         current_val = getattr(combined.prompt_tokens_details, attr, 0) or 0
                         new_val = getattr(usage.prompt_tokens_details, attr, 0) or 0
@@ -2332,7 +2340,9 @@ class BaseTokenUsageProcessor:
                 # Check what keys exist in the model's completion_tokens_details
                 # Access model_fields on the class, not the instance, to avoid Pydantic 2.11+ deprecation warnings
                 for attr in type(usage.completion_tokens_details).model_fields:
-                    if not attr.startswith("_") and not callable(getattr(usage.completion_tokens_details, attr)):
+                    if not attr.startswith("_") and not callable(
+                        _attribute_value(usage.completion_tokens_details, attr)
+                    ):
                         current_val = getattr(combined.completion_tokens_details, attr, 0) or 0
                         new_val = getattr(usage.completion_tokens_details, attr, 0) or 0
                         if isinstance(new_val, (int, float)):
diff --git a/litellm/endpoints/speech/speech_to_completion_bridge/handler.py b/litellm/endpoints/speech/speech_to_completion_bridge/handler.py
index 9e949db625a..6c33621ec89 100644
--- a/litellm/endpoints/speech/speech_to_completion_bridge/handler.py
+++ b/litellm/endpoints/speech/speech_to_completion_bridge/handler.py
@@ -115,9 +115,11 @@ class SpeechToCompletionBridgeHandler:
             **request_data,
         )
 
+        requested_response_format: Final = optional_params.get("response_format")
         if isinstance(result, ModelResponse):
             return self.transformation_handler.transform_response(
                 model_response=result,
+                response_format=requested_response_format if isinstance(requested_response_format, str) else None,
             )
         else:
             raise Exception(f"Unmapped response type. Got type: {type(result)}")
diff --git a/litellm/endpoints/speech/speech_to_completion_bridge/transformation.py b/litellm/endpoints/speech/speech_to_completion_bridge/transformation.py
index fb66edbf272..2ed140c0208 100644
--- a/litellm/endpoints/speech/speech_to_completion_bridge/transformation.py
+++ b/litellm/endpoints/speech/speech_to_completion_bridge/transformation.py
@@ -1,10 +1,14 @@
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Final, cast
 
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
 from litellm.constants import OPENAI_CHAT_COMPLETION_PARAMS
 
 if TYPE_CHECKING:
     from litellm import Logging as LiteLLMLoggingObj
-    from litellm.types.llms.openai import HttpxBinaryResponseContent
+    from litellm.types.llms.openai import ChatCompletionUserMessage, HttpxBinaryResponseContent
     from litellm.types.utils import ModelResponse
 
 
@@ -16,7 +20,64 @@ def _completion_response_cost(model_response: "ModelResponse") -> float | None:
     return response_cost if isinstance(response_cost, float) else None
 
 
+GEMINI_TTS_CHAT_AUDIO_FORMAT: Final = "pcm16"
+GEMINI_TTS_RAW_RESPONSE_FORMAT: Final = "pcm"
+GEMINI_TTS_SUPPORTED_RESPONSE_FORMATS: Final = frozenset({"wav", GEMINI_TTS_RAW_RESPONSE_FORMAT})
+
+
+class ChatAudioParam(TypedDict):
+    voice: ReadOnly[str]
+    format: ReadOnly[NotRequired[str]]
+
+
 class SpeechToCompletionBridgeTransformationHandler:
+    def _validate_response_format(
+        self, model: str, custom_llm_provider: str, optional_params: Mapping[str, object]
+    ) -> None:
+        if not self._is_gemini_tts_model(model):
+            return
+        response_format: Final = optional_params.get("response_format")
+        if not isinstance(response_format, str) or response_format in GEMINI_TTS_SUPPORTED_RESPONSE_FORMATS:
+            return
+        from litellm.exceptions import BadRequestError
+
+        supported: Final = ", ".join(sorted(GEMINI_TTS_SUPPORTED_RESPONSE_FORMATS))
+        raise BadRequestError(
+            message=(
+                f"Gemini TTS only produces raw PCM16 audio, so response_format='{response_format}'"
+                f" is not supported. Supported response formats: {supported}."
+            ),
+            model=model,
+            llm_provider=custom_llm_provider,
+        )
+
+    def _chat_completion_params(self, optional_params: Mapping[str, object]) -> Mapping[str, object]:
+        return MappingProxyType(
+            {
+                param: value
+                for param, value in optional_params.items()
+                if param in OPENAI_CHAT_COMPLETION_PARAMS and param != "response_format"
+            }
+        )
+
+    def _chat_audio_format(self, model: str, optional_params: Mapping[str, object]) -> str | None:
+        if self._is_gemini_tts_model(model):
+            return GEMINI_TTS_CHAT_AUDIO_FORMAT
+        response_format: Final = optional_params.get("response_format")
+        return response_format if isinstance(response_format, str) else None
+
+    def _chat_audio_param(
+        self, model: str, voice: str | Mapping[str, object] | None, optional_params: Mapping[str, object]
+    ) -> ChatAudioParam | None:
+        if not isinstance(voice, str):
+            return None
+        audio_format: Final = self._chat_audio_format(model, optional_params)
+        if audio_format is None:
+            voice_only: Final[ChatAudioParam] = {"voice": voice}
+            return voice_only
+        audio: Final[ChatAudioParam] = {"voice": voice, "format": audio_format}
+        return audio
+
     def transform_request(
         self,
         model: str,
@@ -28,36 +89,20 @@ class SpeechToCompletionBridgeTransformationHandler:
         litellm_logging_obj: "LiteLLMLoggingObj",
         custom_llm_provider: str,
     ) -> dict:
-        passed_optional_params: Final = {}
-        for op in optional_params:
-            if op in OPENAI_CHAT_COMPLETION_PARAMS:
-                passed_optional_params[op] = optional_params[op]
-
-        if voice is not None:
-            if isinstance(voice, str):
-                passed_optional_params["audio"] = {"voice": voice}
-                if "response_format" in optional_params:
-                    passed_optional_params["audio"]["format"] = optional_params["response_format"]
-
-        return_kwargs = {
+        self._validate_response_format(model, custom_llm_provider, optional_params)
+        user_message: Final[ChatCompletionUserMessage] = {"role": "user", "content": input}
+        return_kwargs: Final = {
             "model": model,
-            "messages": [
-                {
-                    "role": "user",
-                    "content": input,
-                }
-            ],
+            "messages": [user_message],
             "modalities": ["audio"],
-            **passed_optional_params,
+            **self._chat_completion_params(optional_params),
+            "audio": self._chat_audio_param(model, voice, optional_params),
             **litellm_params,
             "headers": headers,
             "litellm_logging_obj": litellm_logging_obj,
             "custom_llm_provider": custom_llm_provider,
         }
-
-        # filter out None values
-        return_kwargs = {k: v for k, v in return_kwargs.items() if v is not None}
-        return return_kwargs
+        return {k: v for k, v in return_kwargs.items() if v is not None}
 
     def _convert_pcm16_to_wav(self, pcm_data: bytes, sample_rate: int = 24000, channels: int = 1) -> bytes:
         """
@@ -103,7 +148,14 @@ class SpeechToCompletionBridgeTransformationHandler:
         """Check if the model is a Gemini TTS model that returns PCM16 data."""
         return "gemini" in model.lower() and ("tts" in model.lower() or "preview-tts" in model.lower())
 
-    def transform_response(self, model_response: "ModelResponse") -> "HttpxBinaryResponseContent":
+    def _gemini_tts_response_body(self, decoded_audio: bytes, response_format: str | None) -> tuple[bytes, str]:
+        if response_format == GEMINI_TTS_RAW_RESPONSE_FORMAT:
+            return decoded_audio, "audio/pcm"
+        return self._convert_pcm16_to_wav(decoded_audio), "audio/wav"
+
+    def transform_response(
+        self, model_response: "ModelResponse", response_format: str | None
+    ) -> "HttpxBinaryResponseContent":
         import base64
 
         import httpx
@@ -114,23 +166,17 @@ class SpeechToCompletionBridgeTransformationHandler:
         audio_part: Final = cast(Choices, model_response.choices[0]).message.audio
         if audio_part is None:
             raise ValueError("No audio part found in the response")
-        audio_content: Final = audio_part.data
+        decoded_audio: Final = base64.b64decode(audio_part.data)
 
-        # Decode base64 to get binary content
-        binary_data = base64.b64decode(audio_content)
-
-        # Check if this is a Gemini TTS model that returns raw PCM16 data
         model: Final = getattr(model_response, "model", "")
-        headers: Final = {}
-        if self._is_gemini_tts_model(model):
-            # Convert PCM16 to WAV format for proper audio file playback
-            binary_data = self._convert_pcm16_to_wav(binary_data)
-            headers["Content-Type"] = "audio/wav"
-        else:
-            headers["Content-Type"] = "audio/mpeg"
-
-        # Create an httpx.Response object
-        response: Final = httpx.Response(status_code=200, content=binary_data, headers=headers)
+        content, content_type = (
+            self._gemini_tts_response_body(decoded_audio, response_format)
+            if self._is_gemini_tts_model(model)
+            else (decoded_audio, "audio/mpeg")
+        )
+        response: Final = httpx.Response(
+            status_code=200, content=content, headers=MappingProxyType({"Content-Type": content_type})
+        )
         binary_response: Final = HttpxBinaryResponseContent(response)
         binary_response.set_response_cost(_completion_response_cost(model_response))
         return binary_response
diff --git a/litellm/experimental_mcp_client/client.py b/litellm/experimental_mcp_client/client.py
index f0a1bff8fdc..ea81e323da4 100644
--- a/litellm/experimental_mcp_client/client.py
+++ b/litellm/experimental_mcp_client/client.py
@@ -7,6 +7,7 @@ import base64
 import os
 from collections.abc import Awaitable, Callable, Generator
 from datetime import timedelta
+from functools import partial
 from importlib import metadata
 from typing import Any, Final, TypeVar
 
@@ -47,7 +48,8 @@ from mcp.types import Tool as MCPTool
 from pydantic import AnyUrl
 
 from litellm._logging import verbose_logger
-from litellm.constants import MCP_CLIENT_TIMEOUT, MCP_NPM_CACHE_DIR
+from litellm.constants import MCP_CLIENT_TIMEOUT, MCP_NPM_CACHE_DIR, MCP_TOOL_LISTING_TIMEOUT
+from litellm.experimental_mcp_client.tools import list_tools_with_pagination
 from litellm.llms.custom_httpx.http_handler import get_ssl_configuration
 from litellm.types.llms.custom_http import VerifyTypes
 from litellm.types.mcp import (
@@ -603,17 +605,19 @@ class MCPClient:
         """
         verbose_logger.debug("MCP client listing tools from %s", self.server_url or "stdio")
 
-        async def _list_tools_operation(session: ClientSession):
-            return await session.list_tools()
-
         try:
-            result: Final = await self.run_with_session(_list_tools_operation, quiet_on_error=raise_on_error)
-            tool_count: Final = len(result.tools)
-            tool_names: Final = [tool.name for tool in result.tools]
+            # A per-server timeout above the global default extends the whole-walk deadline
+            listing_deadline: Final = max(self.timeout, MCP_TOOL_LISTING_TIMEOUT)
+            tools: Final = await self.run_with_session(
+                partial(list_tools_with_pagination, listing_deadline=listing_deadline),
+                quiet_on_error=raise_on_error,
+            )
+            tool_count: Final = len(tools)
+            tool_names: Final = tuple(tool.name for tool in tools)
             verbose_logger.info(
                 "MCP client listed %s tools from %s: %s", tool_count, self.server_url or "stdio", tool_names
             )
-            return result.tools
+            return tools
         except asyncio.CancelledError:
             verbose_logger.warning("MCP client list_tools was cancelled")
             raise
diff --git a/litellm/experimental_mcp_client/tools.py b/litellm/experimental_mcp_client/tools.py
index 30d50e2a74b..51d2139ef3b 100644
--- a/litellm/experimental_mcp_client/tools.py
+++ b/litellm/experimental_mcp_client/tools.py
@@ -1,14 +1,22 @@
 import json
 from typing import Final, Literal
 
+import anyio
 from mcp import ClientSession
 from mcp.types import CallToolRequestParams as MCPCallToolRequestParams
 from mcp.types import CallToolResult as MCPCallToolResult
+from mcp.types import PaginatedRequestParams
 from mcp.types import Tool as MCPTool
 from openai.types.chat import ChatCompletionToolParam
 from openai.types.responses.function_tool_param import FunctionToolParam
 from openai.types.shared_params.function_definition import FunctionDefinition
 
+from litellm._logging import verbose_logger
+from litellm.constants import (
+    MCP_CLIENT_TIMEOUT,
+    MCP_TOOL_LISTING_MAX_PAGES,
+    MCP_TOOL_LISTING_TIMEOUT,
+)
 from litellm.types.llms.anthropic import AnthropicMessagesTool
 from litellm.types.utils import ChatCompletionMessageToolCall
 
@@ -90,6 +98,64 @@ def transform_mcp_tool_to_anthropic_tool(mcp_tool: MCPTool) -> AnthropicMessages
     )
 
 
+async def list_tools_with_pagination(
+    session: ClientSession, listing_deadline: float | None = None
+) -> list[MCPTool]:  # mutable-ok: list return contract
+    """Collect tools from every tools/list page by following nextCursor.
+
+    Stops and returns the tools collected so far when the upstream repeats a
+    cursor, the page cap is reached, or the whole-walk deadline expires, so a
+    buggy or slow upstream yields a partial catalog instead of an error.
+    listing_deadline overrides the default whole-walk deadline; callers with a
+    per-server timeout above the global default pass it through here.
+    """
+    tools: Final[list[MCPTool]] = []  # mutable-ok: accumulates each page's tools
+    seen_cursors: Final[set[str]] = set()  # mutable-ok: guards against cursor loops
+    cursor: str | None = None  # rebind-ok: advances to each page's nextCursor
+    # The per-request session read timeout restarts on every page, so a multi-page
+    # walk needs its own overall deadline. max() keeps the pre-pagination guarantee
+    # that a single page slower than the listing timeout but within the client
+    # timeout still succeeds.
+    effective_deadline: Final = (
+        listing_deadline if listing_deadline is not None else max(MCP_CLIENT_TIMEOUT, MCP_TOOL_LISTING_TIMEOUT)
+    )
+
+    with anyio.move_on_after(effective_deadline):
+        for _ in range(MCP_TOOL_LISTING_MAX_PAGES):
+            result = (
+                await session.list_tools()
+                if cursor is None
+                else await session.list_tools(params=PaginatedRequestParams(cursor=cursor))
+            )
+            tools.extend(result.tools)
+
+            next_cursor = getattr(result, "nextCursor", None)
+            if not isinstance(next_cursor, str) or not next_cursor:
+                return tools
+            if next_cursor in seen_cursors:
+                verbose_logger.warning(
+                    "MCP server repeated a tools/list cursor while listing tools; returning %s tools collected so far",
+                    len(tools),
+                )
+                return tools
+            seen_cursors.add(next_cursor)
+            cursor = next_cursor
+
+        verbose_logger.warning(
+            "MCP server tools/list pagination exceeded the maximum of %s pages; returning %s tools collected so far",
+            MCP_TOOL_LISTING_MAX_PAGES,
+            len(tools),
+        )
+        return tools
+
+    verbose_logger.warning(
+        "MCP server tools/list pagination exceeded the %s second listing deadline; returning %s tools collected so far",
+        effective_deadline,
+        len(tools),
+    )
+    return tools
+
+
 async def load_mcp_tools(
     session: ClientSession, format: Literal["mcp", "openai"] = "mcp"
 ) -> list[MCPTool] | list[ChatCompletionToolParam]:
@@ -103,10 +169,12 @@ async def load_mcp_tools(
 
     If format is set to "openai", the tools are converted to OpenAI API compatible tools.
     """
-    tools: Final = await session.list_tools()
+    tools: Final = await list_tools_with_pagination(session)
     if format == "openai":
-        return [transform_mcp_tool_to_openai_tool(mcp_tool=tool) for tool in tools.tools]
-    return tools.tools
+        return [  # mutable-ok: public API returns a list
+            transform_mcp_tool_to_openai_tool(mcp_tool=tool) for tool in tools
+        ]
+    return tools
 
 
 ########################################################
diff --git a/litellm/google_genai/adapters/transformation.py b/litellm/google_genai/adapters/transformation.py
index 7c86ceafd7f..6a698bb6018 100644
--- a/litellm/google_genai/adapters/transformation.py
+++ b/litellm/google_genai/adapters/transformation.py
@@ -1,8 +1,9 @@
 import json
-from collections.abc import AsyncIterator, Iterator, Sequence
-from typing import Any, Final, TypedDict, cast
+from collections.abc import AsyncIterator, Callable, Iterator, Mapping, Sequence
+from types import MappingProxyType
+from typing import Any, Final, TypeAlias, cast
 
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm import verbose_logger
 from litellm.litellm_core_utils.json_validation_rule import normalize_tool_schema
@@ -11,7 +12,6 @@ from litellm.types.llms.openai import (
     ChatCompletionAssistantMessage,
     ChatCompletionAssistantToolCall,
     ChatCompletionImageObject,
-    ChatCompletionRequest,
     ChatCompletionSystemMessage,
     ChatCompletionTextObject,
     ChatCompletionToolCallFunctionChunk,
@@ -23,35 +23,63 @@ from litellm.types.llms.openai import (
 from litellm.types.router import GenericLiteLLMParams
 from litellm.types.utils import (
     AdapterCompletionStreamWrapper,
+    ChatCompletionDeltaCustomToolCall,
+    ChatCompletionDeltaToolCall,
+    ChatCompletionMessageCustomToolCall,
+    ChatCompletionMessageToolCall,
     Choices,
+    Delta,
+    Function,
+    Message,
     ModelResponse,
     ModelResponseStream,
     StreamingChoices,
-    Usage,
 )
 
-
-class _GenAITextPart(TypedDict, total=False):
-    text: ReadOnly[str]
+_JsonDict: TypeAlias = dict[str, object]
+_JsonDictList: TypeAlias = list[_JsonDict]
 
 
-class _GenAISystemInstruction(TypedDict, total=False):
-    parts: ReadOnly[list[_GenAITextPart]]
+class _ToolCallAccumulator(TypedDict):
+    name: ReadOnly[str]
+    arguments: ReadOnly[str]
+
+
+class _GenAIFunctionCall(TypedDict):
+    name: ReadOnly[str]
+    args: ReadOnly[Mapping[str, object]]
 
 
 class _GenAIPart(TypedDict, total=False):
     text: ReadOnly[str]
-    functionCall: ReadOnly[dict[str, object]]
+    functionCall: ReadOnly[_GenAIFunctionCall]
+
+
+class _GenAIFunctionResponse(TypedDict, total=False):
+    name: ReadOnly[str]
+    response: ReadOnly[object]
+
+
+class _GenAIRequestFunctionCall(TypedDict, total=False):
+    name: ReadOnly[str]
+    args: ReadOnly[Mapping[str, object]]
+
+
+class _GenAIContentPart(TypedDict, total=False):
+    text: ReadOnly[str]
+    inline_data: ReadOnly[Mapping[str, str]]
+    functionResponse: ReadOnly[_GenAIFunctionResponse]
+    functionCall: ReadOnly[_GenAIRequestFunctionCall]
 
 
 class _GenAIFunctionDeclaration(TypedDict, total=False):
     name: ReadOnly[str]
     description: ReadOnly[str]
-    parametersJsonSchema: ReadOnly[dict[str, object]]
+    parametersJsonSchema: ReadOnly[object]
 
 
 class _GenAITool(TypedDict, total=False):
-    functionDeclarations: ReadOnly[list[_GenAIFunctionDeclaration]]
+    functionDeclarations: ReadOnly[Sequence[_GenAIFunctionDeclaration]]
 
 
 class _GenAIFunctionCallingConfig(TypedDict, total=False):
@@ -62,9 +90,11 @@ class _GenAIToolConfig(TypedDict, total=False):
     functionCallingConfig: ReadOnly[_GenAIFunctionCallingConfig]
 
 
-def _decode_tool_call_arguments(raw_arguments: str) -> object:
-    """Decode a tool call's JSON-encoded arguments into the value Google GenAI expects."""
-    return json.loads(raw_arguments)
+class _GenAISystemInstruction(TypedDict, total=False):
+    parts: ReadOnly[Sequence[Mapping[str, str]]]
+
+
+_EMPTY_STR_MAPPING: Final[Mapping[str, str]] = MappingProxyType({})
 
 
 class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
@@ -74,12 +104,11 @@ class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
     """
 
     sent_first_chunk: bool = False
-    # State tracking for accumulating partial tool calls
-    accumulated_tool_calls: dict[int, dict[str, str]]
+    _parse_accumulated_args: Callable[[str], Mapping[str, object]] = staticmethod(json.loads)
 
     def __init__(self, completion_stream: object):
         self.sent_first_chunk = False
-        self.accumulated_tool_calls = {}
+        self.accumulated_tool_calls = dict[int, _ToolCallAccumulator]()
         self._returned_response = False
         super().__init__(completion_stream)
 
@@ -124,7 +153,7 @@ class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
             # After the stream is exhausted, check for any remaining accumulated tool calls
             if self.accumulated_tool_calls:
                 try:
-                    parts: Final[list[_GenAIPart]] = []
+                    parts: Final = list[_GenAIPart]()
                     for (
                         tool_call_index,
                         tool_call_data,
@@ -132,7 +161,9 @@ class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
                         try:
                             # For tool calls with no arguments, accumulated_args will be "", which is not valid JSON.
                             # We default to an empty JSON object in this case.
-                            parsed_args = _decode_tool_call_arguments(tool_call_data["arguments"] or "{}")
+                            parsed_args: Mapping[str, object] = self._parse_accumulated_args(
+                                tool_call_data["arguments"] or "{}"
+                            )
                             function_call_part: _GenAIPart = {
                                 "functionCall": {
                                     "name": tool_call_data["name"] or "undefined_tool_name",
@@ -149,7 +180,7 @@ class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
                                 tool_call_data["arguments"],
                             )
                     if parts:
-                        final_chunk: Final[dict[str, object]] = {
+                        final_chunk: Final = {
                             "candidates": [
                                 {
                                     "content": {"parts": parts, "role": "model"},
@@ -211,14 +242,16 @@ class GoogleGenAIStreamWrapper(AdapterCompletionStreamWrapper):
 class GoogleGenAIAdapter:
     """Adapter for transforming Google GenAI generate_content requests to/from litellm.completion format"""
 
+    _parse_tool_call_args: Callable[[str], Mapping[str, object]] = staticmethod(json.loads)
+
     def __init__(self) -> None:
         pass
 
     def translate_generate_content_to_completion(
         self,
         model: str,
-        contents: list[dict[str, Any]] | dict[str, Any],
-        config: dict[str, Any] | None = None,
+        contents: _JsonDictList | _JsonDict,
+        config: Mapping[str, object] | None = None,
         litellm_params: GenericLiteLLMParams | None = None,
         **kwargs,
     ) -> dict[str, Any]:
@@ -250,7 +283,7 @@ class GoogleGenAIAdapter:
         messages: Final = self._transform_contents_to_messages(contents_list, system_instruction=system_instruction)
 
         # Create base request as dict (which is compatible with ChatCompletionRequest)
-        completion_request: Final[ChatCompletionRequest] = {
+        completion_request: Final[_JsonDict] = {
             "model": model,
             "messages": messages,
         }
@@ -312,9 +345,9 @@ class GoogleGenAIAdapter:
 
     def _add_generic_litellm_params_to_request(
         self,
-        completion_request_dict: dict[str, object],
+        completion_request_dict: _JsonDict,
         litellm_params: GenericLiteLLMParams | None = None,
-    ) -> dict[str, object]:
+    ) -> _JsonDict:
         """Add generic litellm params to request. e.g add api_base, api_key, api_version, etc.
 
         Args:
@@ -326,7 +359,7 @@ class GoogleGenAIAdapter:
         """
         allowed_fields: Final = GenericLiteLLMParams.model_fields.keys()
         if litellm_params:
-            litellm_dict: Final = litellm_params.model_dump(exclude_none=True)
+            litellm_dict: Final[_JsonDict] = litellm_params.model_dump(exclude_none=True)
             for key, value in litellm_dict.items():
                 if key in allowed_fields:
                     completion_request_dict[key] = value
@@ -346,12 +379,12 @@ class GoogleGenAIAdapter:
         tools: Sequence[_GenAITool],
     ) -> list[ChatCompletionToolParam]:
         """Transform Google GenAI tools to OpenAI tools format"""
-        openai_tools: Final[list[dict[str, object]]] = []
+        openai_tools: Final = list[_JsonDict]()
 
         for tool in tools:
             if "functionDeclarations" in tool:
                 for func_decl in tool["functionDeclarations"]:
-                    function_chunk: dict[str, object] = {
+                    function_chunk: _JsonDict = {
                         "name": func_decl.get("name", ""),
                     }
 
@@ -360,7 +393,7 @@ class GoogleGenAIAdapter:
                     if "parametersJsonSchema" in func_decl:
                         function_chunk["parameters"] = func_decl["parametersJsonSchema"]
 
-                    openai_tool: dict[str, object] = {"type": "function", "function": function_chunk}
+                    openai_tool: _JsonDict = {"type": "function", "function": function_chunk}
                     openai_tools.append(openai_tool)
 
         # normalize the tool schemas
@@ -391,13 +424,13 @@ class GoogleGenAIAdapter:
 
         # Handle system instruction
         if system_instruction:
-            system_parts: Final = system_instruction.get("parts", [])
+            system_parts: Final[Sequence[Mapping[str, str]]] = system_instruction.get("parts", [])
             if system_parts and "text" in system_parts[0]:
                 messages.append(ChatCompletionSystemMessage(role="system", content=system_parts[0]["text"]))
 
         for content in contents:
             role = content.get("role", "user")
-            parts = content.get("parts", [])
+            parts: Sequence[_GenAIContentPart | str | None] = content.get("parts", [])
 
             if role == "user":
                 # Handle user messages with potential function responses
@@ -500,7 +533,7 @@ class GoogleGenAIAdapter:
     def translate_completion_to_generate_content(
         self,
         response: ModelResponse,
-    ) -> dict[str, object]:
+    ) -> _JsonDict:
         """
         Transform litellm completion response to Google GenAI generate_content format
 
@@ -523,13 +556,13 @@ class GoogleGenAIAdapter:
             parts = self._transform_openai_message_to_google_genai_parts(choice.message)
         else:
             # Fallback for generic choice objects
-            message_content = getattr(choice, "message", {}).get("content", "") or getattr(choice, "delta", {}).get(
-                "content", ""
-            )
+            message_content: str = getattr(choice, "message", _EMPTY_STR_MAPPING).get("content", "") or getattr(
+                choice, "delta", _EMPTY_STR_MAPPING
+            ).get("content", "")
             parts = [{"text": message_content}] if message_content else []
 
         # Create Google GenAI format response
-        generate_content_response: Final[dict[str, object]] = {
+        generate_content_response: Final[_JsonDict] = {
             "candidates": [
                 {
                     "content": {"parts": parts, "role": "model"},
@@ -563,7 +596,7 @@ class GoogleGenAIAdapter:
         self,
         response: ModelResponse | ModelResponseStream,
         wrapper: GoogleGenAIStreamWrapper,
-    ) -> dict[str, object] | None:
+    ) -> Mapping[str, object] | None:
         """
         Transform streaming litellm completion chunk to Google GenAI generate_content format
 
@@ -590,7 +623,7 @@ class GoogleGenAIAdapter:
             finish_reason: str | None = getattr(choice, "finish_reason", None)
         else:
             # Fallback for generic choice objects
-            message_content: Final = getattr(choice, "delta", {}).get("content", "")
+            message_content: Final[str] = getattr(choice, "delta", _EMPTY_STR_MAPPING).get("content", "")
             parts = [{"text": message_content}] if message_content else []
             finish_reason = getattr(choice, "finish_reason", None)
 
@@ -599,7 +632,7 @@ class GoogleGenAIAdapter:
             return None
 
         # Create Google GenAI streaming format response
-        streaming_chunk: Final[dict[str, object]] = {
+        streaming_chunk: Final[_JsonDict] = {
             "candidates": [
                 {
                     "content": {"parts": parts, "role": "model"},
@@ -635,10 +668,10 @@ class GoogleGenAIAdapter:
 
     def _transform_openai_message_to_google_genai_parts(
         self,
-        message: Any,
-    ) -> list[_GenAIPart]:
+        message: Message,
+    ) -> Sequence[_GenAIPart]:
         """Transform OpenAI message to Google GenAI parts format"""
-        parts: Final[list[_GenAIPart]] = []
+        parts: Final = list[_GenAIPart]()
 
         # Add text content if present
         if hasattr(message, "content") and message.content:
@@ -646,20 +679,22 @@ class GoogleGenAIAdapter:
 
         # Add tool calls if present
         if hasattr(message, "tool_calls") and message.tool_calls:
-            for tool_call in message.tool_calls:
-                if hasattr(tool_call, "function") and tool_call.function:
+            tool_calls: Final[Sequence[ChatCompletionMessageToolCall | ChatCompletionMessageCustomToolCall]] = (
+                message.tool_calls
+            )
+            for tool_call in tool_calls:
+                function: Function | None = getattr(tool_call, "function", None)
+                if function:
                     try:
-                        args = (
-                            _decode_tool_call_arguments(tool_call.function.arguments)
-                            if tool_call.function.arguments
-                            else {}
+                        args: Mapping[str, object] = (
+                            self._parse_tool_call_args(function.arguments) if function.arguments else {}
                         )
                     except json.JSONDecodeError:
                         args = {}
 
                     function_call_part: _GenAIPart = {
                         "functionCall": {
-                            "name": tool_call.function.name or "undefined_tool_name",
+                            "name": function.name or "undefined_tool_name",
                             "args": args,
                         }
                     }
@@ -668,24 +703,26 @@ class GoogleGenAIAdapter:
         return parts if parts else [{"text": ""}]
 
     def _transform_openai_delta_to_google_genai_parts_with_accumulation(
-        self, delta: Any, wrapper: GoogleGenAIStreamWrapper
-    ) -> list[_GenAIPart]:
+        self, delta: Delta, wrapper: GoogleGenAIStreamWrapper
+    ) -> Sequence[_GenAIPart]:
         """Transforms OpenAI delta to Google GenAI parts, accumulating streaming tool calls."""
 
         # 1. Initialize wrapper state if it doesn't exist
         if not hasattr(wrapper, "accumulated_tool_calls"):
             wrapper.accumulated_tool_calls = {}
 
-        parts: Final[list[_GenAIPart]] = []
+        parts: Final = list[_GenAIPart]()
 
         if hasattr(delta, "content") and delta.content:
             parts.append({"text": delta.content})
 
         # 2. Ensure tool_calls is iterable
-        tool_calls: Final = delta.tool_calls or []
+        tool_calls: Final[Sequence[ChatCompletionDeltaToolCall | ChatCompletionDeltaCustomToolCall]] = (
+            delta.tool_calls or []
+        )
 
         for tool_call in tool_calls:
-            if not hasattr(tool_call, "function"):
+            if not hasattr(tool_call, "function") or isinstance(tool_call, ChatCompletionDeltaCustomToolCall):
                 continue
 
             # 3. Use `index` as the primary key for accumulation
@@ -701,19 +738,20 @@ class GoogleGenAIAdapter:
                 }
 
             # Accumulate name and arguments
-            function_name = getattr(tool_call.function, "name", None)
-            args_chunk = getattr(tool_call.function, "arguments", None)
+            delta_function: Function | None = getattr(tool_call, "function", None)
+            function_name: str | None = getattr(delta_function, "name", None)
+            args_chunk: str | None = getattr(delta_function, "arguments", None)
 
             # Optimization: Skip chunks that have no new data
             if not function_name and not args_chunk:
                 verbose_logger.debug("Skipping empty tool call chunk for index: %s", tool_call_index)
                 continue
 
-            if function_name:
-                wrapper.accumulated_tool_calls[tool_call_index]["name"] = function_name
-
-            if args_chunk:
-                wrapper.accumulated_tool_calls[tool_call_index]["arguments"] += args_chunk
+            previous_data: _ToolCallAccumulator = wrapper.accumulated_tool_calls[tool_call_index]
+            wrapper.accumulated_tool_calls[tool_call_index] = _ToolCallAccumulator(
+                name=function_name or previous_data["name"],
+                arguments=previous_data["arguments"] + (args_chunk or ""),
+            )
 
             # Attempt to parse and emit a complete tool call
             accumulated_data = wrapper.accumulated_tool_calls[tool_call_index]
@@ -723,7 +761,7 @@ class GoogleGenAIAdapter:
             # 5. Attempt to parse arguments even if name hasn't arrived.
             try:
                 # Attempt to parse the accumulated arguments string
-                parsed_args = _decode_tool_call_arguments(accumulated_args)
+                parsed_args: Mapping[str, object] = self._parse_tool_call_args(accumulated_args)
 
                 # If parsing succeeds, but we don't have a name yet, wait.
                 # The part will be created by a later chunk that brings the name.
@@ -757,7 +795,7 @@ class GoogleGenAIAdapter:
 
         return mapping.get(finish_reason, "STOP")
 
-    def _map_usage(self, usage: Usage | None) -> dict[str, int]:
+    def _map_usage(self, usage: object) -> Mapping[str, int]:
         """Map OpenAI usage to Google GenAI usage format"""
         return {
             "promptTokenCount": getattr(usage, "prompt_tokens", 0) or 0,
diff --git a/litellm/google_genai/main.py b/litellm/google_genai/main.py
index b5815bd3f7c..c1822e4720d 100644
--- a/litellm/google_genai/main.py
+++ b/litellm/google_genai/main.py
@@ -52,10 +52,10 @@ class GenerateContentSetupResult(BaseModel):
     model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True)
 
     model: str
-    request_body: dict[str, Any]
+    request_body: dict[str, object]
     custom_llm_provider: str
     generate_content_provider_config: BaseGoogleGenAIGenerateContentConfig | None
-    generate_content_config_dict: dict[str, Any]
+    generate_content_config_dict: dict[str, object]
     native_request_fields: dict[str, object]
     litellm_params: GenericLiteLLMParams
     litellm_logging_obj: LiteLLMLoggingObj
@@ -68,7 +68,7 @@ class GenerateContentHelper:
     @staticmethod
     def mock_generate_content_response(
         mock_response: str = "This is a mock response from Google GenAI generate_content.",
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Mock response for generate_content for testing purposes"""
         return {
             "text": mock_response,
@@ -239,9 +239,9 @@ async def agenerate_content(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -307,9 +307,9 @@ def generate_content(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -397,9 +397,9 @@ async def agenerate_content_stream(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -492,9 +492,9 @@ def generate_content_stream(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
diff --git a/litellm/images/main.py b/litellm/images/main.py
index 1688087c2da..6a94e7c8df2 100644
--- a/litellm/images/main.py
+++ b/litellm/images/main.py
@@ -3,7 +3,7 @@ import contextvars
 import importlib
 from collections.abc import Coroutine
 from functools import partial
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, cast, overload
+from typing import TYPE_CHECKING, Final, Literal, Optional, cast, overload
 
 if TYPE_CHECKING:
     from litellm.images.utils import ImageEditRequestUtils
@@ -151,7 +151,7 @@ def image_generation(
     *,
     aimg_generation: Literal[True],
     **kwargs,
-) -> Coroutine[Any, Any, ImageResponse]: 
+) -> Coroutine[object, object, ImageResponse]:
     ...
 
 
@@ -197,7 +197,7 @@ def image_generation(
     api_version: str | None = None,
     custom_llm_provider=None,
     **kwargs,
-) -> ImageResponse | Coroutine[Any, Any, ImageResponse]:
+) -> ImageResponse | Coroutine[object, object, ImageResponse]:
     """
     Maps the https://api.openai.com/v1/images/generations endpoint.
 
@@ -386,6 +386,8 @@ def image_generation(
             litellm.LlmProviders.VERTEX_AI,
             litellm.LlmProviders.OPENROUTER,
             litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
         ):
             if image_generation_config is None:
                 raise ValueError(f"image generation config is not supported for {custom_llm_provider}")
@@ -723,14 +725,14 @@ def image_edit(
     user: str | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
     **kwargs,
-) -> ImageResponse | Coroutine[Any, Any, ImageResponse]:
+) -> ImageResponse | Coroutine[object, object, ImageResponse]:
     """
     Maps the image edit functionality, similar to OpenAI's images/edits endpoint.
     """
@@ -769,7 +771,7 @@ def image_edit(
         images: Final = image if isinstance(image, list) else ([image] if image is not None else [])
 
         headers_from_kwargs: Final = kwargs.get("headers")
-        merged_extra_headers: Final[dict[str, Any]] = {}
+        merged_extra_headers: Final[dict[str, object]] = {}
         if isinstance(headers_from_kwargs, dict):
             merged_extra_headers.update(headers_from_kwargs)
         if isinstance(extra_headers, dict):
@@ -974,9 +976,9 @@ async def aimage_edit(
     user: str | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -1044,7 +1046,7 @@ async def aimage_edit(
         )
 
 
-def __getattr__(name: str) -> Any:
+def __getattr__(name: str) -> type["ImageEditRequestUtils"]:
     """Lazy import handler for images.main module"""
     if name == "ImageEditRequestUtils":
         # Lazy load ImageEditRequestUtils to avoid heavy import from images.utils at module load time
diff --git a/litellm/integrations/SlackAlerting/slack_alerting.py b/litellm/integrations/SlackAlerting/slack_alerting.py
index d7d06387d85..dc41c7dadc8 100644
--- a/litellm/integrations/SlackAlerting/slack_alerting.py
+++ b/litellm/integrations/SlackAlerting/slack_alerting.py
@@ -68,6 +68,7 @@ from .utils import process_slack_alerting_variables
 
 if TYPE_CHECKING:
     from litellm.proxy.db.db_transaction_queue.pod_lock_manager import PodLockManager
+    from litellm.proxy.utils import PrismaClient
     from litellm.router import Router as _Router
 
     Router = _Router
@@ -545,7 +546,6 @@ class SlackAlerting(CustomBatchLogger):
         # Get the appropriate budget alert type handler
         budget_alert_class: Final = get_budget_alert_type(type)
         _id: Final = budget_alert_class.get_id(user_info)
-        user_info_json: Final = user_info.model_dump(exclude_none=True)
         user_info_str: Final = self._get_user_info_str(user_info)
         event_message = budget_alert_class.get_event_message()
 
@@ -575,7 +575,22 @@ class SlackAlerting(CustomBatchLogger):
                 webhook_event = WebhookEvent(
                     event=event,
                     event_message=event_message,
-                    **user_info_json,
+                    spend=user_info.spend,
+                    max_budget=user_info.max_budget,
+                    soft_budget=user_info.soft_budget,
+                    token=user_info.token,
+                    customer_id=user_info.customer_id,
+                    user_id=user_info.user_id,
+                    team_id=user_info.team_id,
+                    team_alias=user_info.team_alias,
+                    organization_id=user_info.organization_id,
+                    user_email=user_info.user_email,
+                    key_alias=user_info.key_alias,
+                    projected_exceeded_date=user_info.projected_exceeded_date,
+                    projected_spend=user_info.projected_spend,
+                    event_group=user_info.event_group,
+                    alert_emails=user_info.alert_emails,
+                    max_budget_alert_emails=user_info.max_budget_alert_emails,
                 )
                 await self.send_alert(
                     message=event_message + "\n\n" + user_info_str,
@@ -657,7 +672,7 @@ class SlackAlerting(CustomBatchLogger):
         """
         Create a standard message for a budget alert
         """
-        _all_fields_as_dict: Final = user_info.model_dump(exclude_none=True)
+        _all_fields_as_dict: Final[dict[str, object]] = user_info.model_dump(exclude_none=True)
         _all_fields_as_dict.pop("token")
         msg = ""
         for k, v in _all_fields_as_dict.items():
@@ -1006,7 +1021,7 @@ class SlackAlerting(CustomBatchLogger):
         except Exception:
             pass
 
-    async def model_added_alert(self, model_name: str, litellm_model_name: str, passed_model_info: Any):
+    async def model_added_alert(self, model_name: str, litellm_model_name: str, passed_model_info: object):
         base_model_from_user: Final = getattr(passed_model_info, "base_model", None)
         model_info = {}
         base_model = ""
@@ -1485,9 +1500,9 @@ Model Info:
             elif self.default_webhook_url is not None:
                 _digest_webhook = self.default_webhook_url
             else:
-                _digest_webhook = os.getenv("SLACK_WEBHOOK_URL", None)
+                _digest_webhook = os.getenv("SLACK_WEBHOOK_URL") or os.getenv("ALERTING_WEBHOOK_URL")
             if _digest_webhook is None:
-                raise ValueError("Missing SLACK_WEBHOOK_URL from environment")
+                raise ValueError("Missing SLACK_WEBHOOK_URL / ALERTING_WEBHOOK_URL from environment")
 
             digest_key: Final = f"{alert_type_name_str}:{request_model or ''}:{api_base or ''}"
 
@@ -1516,10 +1531,10 @@ Model Info:
         elif self.default_webhook_url is not None:
             slack_webhook_url = self.default_webhook_url
         else:
-            slack_webhook_url = os.getenv("SLACK_WEBHOOK_URL", None)
+            slack_webhook_url = os.getenv("SLACK_WEBHOOK_URL") or os.getenv("ALERTING_WEBHOOK_URL")
 
         if slack_webhook_url is None:
-            raise ValueError("Missing SLACK_WEBHOOK_URL from environment")
+            raise ValueError("Missing SLACK_WEBHOOK_URL / ALERTING_WEBHOOK_URL from environment")
         payload: Final = {"text": formatted_message}
         headers: Final = {"Content-type": "application/json"}
 
@@ -1930,6 +1945,68 @@ Model Info:
         except Exception as e:
             verbose_proxy_logger.exception("Error sending weekly spend report %s", e)
 
+    async def send_user_spend_alerts(self, prisma_client: "PrismaClient | None" = None) -> None:
+        """Check per-user daily/monthly spend thresholds and spend anomalies, alerting once per user per period."""
+        if self.alerting is None or "slack" not in self.alerting:
+            return
+
+        thresholds_enabled: Final = AlertType.user_spend_thresholds in self.alert_types
+        anomalies_enabled: Final = AlertType.user_spend_anomalies in self.alert_types
+        if not thresholds_enabled and not anomalies_enabled:
+            return
+
+        from litellm.proxy.proxy_server import prisma_client as global_prisma_client
+
+        client: Final = prisma_client if prisma_client is not None else global_prisma_client
+        if client is None:
+            return
+
+        from litellm.integrations.SlackAlerting.user_spend_alerts import (
+            evaluate_user_spend,
+            fetch_user_spend_rows,
+        )
+
+        try:
+            today: Final = datetime.datetime.now(datetime.timezone.utc).date()
+            rows: Final = await fetch_user_spend_rows(
+                prisma_client=client,
+                today=today,
+                baseline_days=self.alerting_args.spend_anomaly_baseline_days,
+            )
+            all_events: Final = tuple(
+                event
+                for row in rows
+                for event in evaluate_user_spend(
+                    row=row,
+                    args=self.alerting_args,
+                    today=today,
+                    thresholds_enabled=thresholds_enabled,
+                    anomalies_enabled=anomalies_enabled,
+                )
+            )
+            cached_flags: Final = await asyncio.gather(
+                *(self.internal_usage_cache.async_get_cache(key=event.cache_key) for event in all_events)
+            )
+            new_events: Final = tuple(event for event, cached in zip(all_events, cached_flags) if not cached)
+            for alert_type in (AlertType.user_spend_thresholds, AlertType.user_spend_anomalies):
+                typed_events = tuple(event for event in new_events if event.alert_type == alert_type)
+                if not typed_events:
+                    continue
+                await self.send_alert(
+                    message="\n\n".join(event.message for event in typed_events),
+                    level="High",
+                    alert_type=alert_type,
+                    alerting_metadata={},  # mutable-ok: send_alert takes a dict payload
+                )
+                for event in typed_events:
+                    await self.internal_usage_cache.async_set_cache(
+                        key=event.cache_key,
+                        value="SENT",
+                        ttl=event.cache_ttl,
+                    )
+        except Exception as e:  # noqa: BLE001  # background job must not crash the scheduler
+            verbose_proxy_logger.exception("Error sending user spend alerts: %s", e)
+
     async def send_fallback_stats_from_prometheus(self):
         """
         Helper to send fallback statistics from prometheus server -> to slack
@@ -1973,7 +2050,7 @@ Model Info:
         try:
             message = f"`{event_name}`\n"
 
-            key_event_dict: Final = key_event.model_dump()
+            key_event_dict: Final[dict[str, object]] = key_event.model_dump()
 
             # Add Created by information first
             message += "*Action Done by:*\n"
diff --git a/litellm/integrations/SlackAlerting/user_spend_alerts.py b/litellm/integrations/SlackAlerting/user_spend_alerts.py
new file mode 100644
index 00000000000..38794735c1b
--- /dev/null
+++ b/litellm/integrations/SlackAlerting/user_spend_alerts.py
@@ -0,0 +1,139 @@
+"""Per-user daily/monthly spend threshold alerts and spend anomaly detection."""
+
+import datetime
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Final, Literal
+
+from pydantic import TypeAdapter
+
+from litellm.constants import HOURS_IN_A_DAY
+from litellm.types.integrations.slack_alerting import AlertType, SlackAlertingArgs
+
+if TYPE_CHECKING:
+    from litellm.proxy.utils import PrismaClient
+
+DAY_SECONDS: Final = HOURS_IN_A_DAY * 60 * 60
+MONTHLY_ALERT_TTL_SECONDS: Final = 32 * DAY_SECONDS
+
+USER_SPEND_QUERY: Final = """
+SELECT
+    user_id,
+    COALESCE(SUM(spend) FILTER (WHERE date = $1), 0)::float AS daily_spend,
+    COALESCE(SUM(spend) FILTER (WHERE date >= $2), 0)::float AS monthly_spend,
+    COALESCE(SUM(spend) FILTER (WHERE date >= $3 AND date < $1), 0)::float AS baseline_spend
+FROM "LiteLLM_DailyUserSpend"
+WHERE date >= LEAST($2, $3) AND user_id IS NOT NULL
+GROUP BY user_id
+HAVING COALESCE(SUM(spend) FILTER (WHERE date >= $2), 0) > 0
+"""
+
+
+@dataclass(frozen=True, slots=True)
+class UserSpendRow:
+    user_id: str
+    daily_spend: float
+    monthly_spend: float
+    baseline_spend: float
+
+
+@dataclass(frozen=True, slots=True)
+class UserSpendAlertEvent:
+    kind: Literal["daily_threshold", "monthly_threshold", "anomaly"]
+    alert_type: AlertType
+    message: str
+    cache_key: str
+    cache_ttl: int
+
+
+USER_SPEND_ROWS_ADAPTER: Final = TypeAdapter(tuple[UserSpendRow, ...])
+
+
+async def fetch_user_spend_rows(
+    prisma_client: "PrismaClient",
+    today: datetime.date,
+    baseline_days: int,
+) -> tuple[UserSpendRow, ...]:
+    today_str: Final = today.strftime("%Y-%m-%d")
+    month_start_str: Final = today.replace(day=1).strftime("%Y-%m-%d")
+    baseline_start_str: Final = (today - datetime.timedelta(days=max(baseline_days, 1))).strftime("%Y-%m-%d")
+    raw: Final = await prisma_client.db.query_raw(USER_SPEND_QUERY, today_str, month_start_str, baseline_start_str)
+    return USER_SPEND_ROWS_ADAPTER.validate_python(raw)
+
+
+def _daily_threshold_event(row: UserSpendRow, args: SlackAlertingArgs, today_str: str) -> UserSpendAlertEvent | None:
+    threshold: Final = args.daily_spend_per_user_threshold
+    if threshold is None or row.daily_spend < threshold:
+        return None
+    return UserSpendAlertEvent(
+        kind="daily_threshold",
+        alert_type=AlertType.user_spend_thresholds,
+        message=(
+            f"User Daily Spend Threshold Crossed:\n"
+            f"User: `{row.user_id}`\n"
+            f"Spend Today: `${row.daily_spend:.2f}`\n"
+            f"Daily Threshold: `${threshold:.2f}`"
+        ),
+        cache_key=f"user_spend_alert_daily_{row.user_id}_{today_str}",
+        cache_ttl=DAY_SECONDS,
+    )
+
+
+def _monthly_threshold_event(row: UserSpendRow, args: SlackAlertingArgs, month_str: str) -> UserSpendAlertEvent | None:
+    threshold: Final = args.monthly_spend_per_user_threshold
+    if threshold is None or row.monthly_spend < threshold:
+        return None
+    return UserSpendAlertEvent(
+        kind="monthly_threshold",
+        alert_type=AlertType.user_spend_thresholds,
+        message=(
+            f"User Monthly Spend Threshold Crossed:\n"
+            f"User: `{row.user_id}`\n"
+            f"Spend This Month: `${row.monthly_spend:.2f}`\n"
+            f"Monthly Threshold: `${threshold:.2f}`"
+        ),
+        cache_key=f"user_spend_alert_monthly_{row.user_id}_{month_str}",
+        cache_ttl=MONTHLY_ALERT_TTL_SECONDS,
+    )
+
+
+def _anomaly_event(row: UserSpendRow, args: SlackAlertingArgs, today_str: str) -> UserSpendAlertEvent | None:
+    if row.daily_spend < args.spend_anomaly_min_spend:
+        return None
+    baseline_daily_avg: Final = row.baseline_spend / args.spend_anomaly_baseline_days
+    if row.baseline_spend > 0 and row.daily_spend <= args.spend_anomaly_multiplier * baseline_daily_avg:
+        return None
+    return UserSpendAlertEvent(
+        kind="anomaly",
+        alert_type=AlertType.user_spend_anomalies,
+        message=(
+            f"User Spend Anomaly Detected:\n"
+            f"User: `{row.user_id}`\n"
+            f"Spend Today: `${row.daily_spend:.2f}`\n"
+            f"Daily Average (last {args.spend_anomaly_baseline_days} days): `${baseline_daily_avg:.2f}`\n"
+            f"Trigger: spend above `{args.spend_anomaly_multiplier}x` the daily average "
+            f"(minimum `${args.spend_anomaly_min_spend:.2f}`)"
+        ),
+        cache_key=f"user_spend_alert_anomaly_{row.user_id}_{today_str}",
+        cache_ttl=DAY_SECONDS,
+    )
+
+
+def evaluate_user_spend(
+    row: UserSpendRow,
+    args: SlackAlertingArgs,
+    today: datetime.date,
+    thresholds_enabled: bool,
+    anomalies_enabled: bool,
+) -> tuple[UserSpendAlertEvent, ...]:
+    today_str: Final = today.strftime("%Y-%m-%d")
+    month_str: Final = today.strftime("%Y-%m")
+    threshold_events: Final = (
+        (
+            _daily_threshold_event(row=row, args=args, today_str=today_str),
+            _monthly_threshold_event(row=row, args=args, month_str=month_str),
+        )
+        if thresholds_enabled
+        else ()
+    )
+    anomaly_events: Final = (_anomaly_event(row=row, args=args, today_str=today_str),) if anomalies_enabled else ()
+    return tuple(event for event in (*threshold_events, *anomaly_events) if event is not None)
diff --git a/litellm/integrations/anthropic_cache_control_hook.py b/litellm/integrations/anthropic_cache_control_hook.py
index 545b0f40018..3519240dda9 100644
--- a/litellm/integrations/anthropic_cache_control_hook.py
+++ b/litellm/integrations/anthropic_cache_control_hook.py
@@ -755,6 +755,7 @@ class AnthropicCacheControlHook(CustomPromptManagement):
     def record_gateway_injection(
         request_kwargs: Mapping[str, object],
         added: int,
+        injected_for_every_deployment: bool = False,
     ) -> None:
         """Name the deployment whose payload the gateway, not the client, put breakpoints on.
 
@@ -771,7 +772,16 @@ class AnthropicCacheControlHook(CustomPromptManagement):
 
         A pass that runs before a deployment is chosen, which is what the proxy does for
         prompt templates, injects into the payload every leg goes on to send, so it marks
-        the request for all of them rather than for one.
+        the request for all of them rather than for one. Such a pass says so with
+        ``injected_for_every_deployment`` instead of relying on the shape of
+        ``request_kwargs``: the router's prompt-management factory stamps a provisional
+        deployment's ``model_info`` into kwargs before the prompt pass runs, and billing
+        the request through any other deployment would silently drop the credit. An
+        every-deployment mark, once written, also never narrows: a later per-leg stamp
+        (the Bedrock converse tool_config one included) describes one leg of a payload
+        every leg sends, so narrowing to it would uncredit whichever leg gets billed
+        after a failover. Both losses are fail-closed under-crediting, which is why the
+        guard only protects the sentinel and per-leg marks still overwrite each other.
 
         Only what this pass actually placed counts. A ``tool_config`` point is placed by
         the Bedrock converse transform, and only when the request carries tools, so the
@@ -801,13 +811,19 @@ class AnthropicCacheControlHook(CustomPromptManagement):
             ),
             None,
         )
-        if bucket is not None:
-            model_info: Final = request_kwargs.get("model_info")
-            bucket[GATEWAY_INJECTED_CACHE_METADATA_KEY] = (
-                model_info.get("id", GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT)
-                if isinstance(model_info, dict)
-                else GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT
-            )
+        if bucket is None:
+            return
+        if bucket.get(GATEWAY_INJECTED_CACHE_METADATA_KEY) == GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT:
+            return
+        if injected_for_every_deployment:
+            bucket[GATEWAY_INJECTED_CACHE_METADATA_KEY] = GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT
+            return
+        model_info: Final = request_kwargs.get("model_info")
+        bucket[GATEWAY_INJECTED_CACHE_METADATA_KEY] = (
+            model_info.get("id", GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT)
+            if isinstance(model_info, dict)
+            else GATEWAY_INJECTED_FOR_EVERY_DEPLOYMENT
+        )
 
     @staticmethod
     def maybe_inject_cache_control(
diff --git a/litellm/integrations/arize/arize_phoenix_prompt_manager.py b/litellm/integrations/arize/arize_phoenix_prompt_manager.py
index 71f4902bbe5..0c9e868c146 100644
--- a/litellm/integrations/arize/arize_phoenix_prompt_manager.py
+++ b/litellm/integrations/arize/arize_phoenix_prompt_manager.py
@@ -3,10 +3,12 @@ Arize Phoenix prompt manager that integrates with LiteLLM's prompt management sy
 Fetches prompt versions from Arize Phoenix and provides workspace-based access control.
 """
 
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, cast
 
 from jinja2 import DictLoader, select_autoescape
 from jinja2.sandbox import ImmutableSandboxedEnvironment
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.integrations.custom_prompt_management import CustomPromptManagement
 from litellm.integrations.prompt_management_base import (
@@ -20,6 +22,31 @@ from litellm.types.utils import StandardCallbackDynamicParams
 from .arize_phoenix_client import ArizePhoenixClient
 
 
+class ArizePhoenixContentPart(TypedDict, total=False):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+
+
+class ArizePhoenixTemplateMessage(TypedDict, total=False):
+    role: ReadOnly[str]
+    content: ReadOnly[Sequence[ArizePhoenixContentPart]]
+
+
+class ArizePhoenixTemplateBody(TypedDict, total=False):
+    messages: ReadOnly[Sequence[ArizePhoenixTemplateMessage]]
+
+
+class ArizePhoenixPromptMetadata(TypedDict):
+    model_name: ReadOnly[str | None]
+    model_provider: ReadOnly[str | None]
+    description: ReadOnly[str]
+    template_type: ReadOnly[str | None]
+    template_format: ReadOnly[str]
+    invocation_parameters: ReadOnly[Mapping[str, Mapping[str, object]]]
+    temperature: ReadOnly[float | None]
+    max_tokens: ReadOnly[int | None]
+
+
 class ArizePhoenixPromptTemplate:
     """
     Represents a prompt template loaded from Arize Phoenix.
@@ -28,10 +55,10 @@ class ArizePhoenixPromptTemplate:
     def __init__(
         self,
         template_id: str,
-        messages: list[dict[str, Any]],
-        metadata: dict[str, Any],
+        messages: Sequence[ArizePhoenixTemplateMessage],
+        metadata: ArizePhoenixPromptMetadata,
         model: str | None = None,
-    ):
+    ) -> None:
         self.template_id = template_id
         self.messages = messages
         self.metadata = metadata
@@ -43,7 +70,7 @@ class ArizePhoenixPromptTemplate:
         self.description = metadata.get("description", "")
         self.template_format = metadata.get("template_format", "MUSTACHE")
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return f"ArizePhoenixPromptTemplate(id='{self.template_id}', model='{self.model}')"
 
 
@@ -109,7 +136,7 @@ class ArizePhoenixTemplateManager:
 
     def _parse_prompt_data(self, data: dict[str, Any], prompt_version_id: str) -> ArizePhoenixPromptTemplate:
         """Parse Arize Phoenix prompt data and extract messages and metadata."""
-        template_data: Final = data.get("template", {})
+        template_data: Final[ArizePhoenixTemplateBody] = data.get("template", {})
         messages: Final = template_data.get("messages", [])
 
         # Extract invocation parameters
@@ -129,7 +156,7 @@ class ArizePhoenixTemplateManager:
                     break
 
         # Build metadata dictionary
-        metadata: Final = {
+        metadata: Final[ArizePhoenixPromptMetadata] = {
             "model_name": data.get("model_name"),
             "model_provider": data.get("model_provider"),
             "description": data.get("description", ""),
@@ -146,7 +173,9 @@ class ArizePhoenixTemplateManager:
             metadata=metadata,
         )
 
-    def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> list[AllMessageValues]:
+    def render_template(
+        self, template_id: str, variables: Mapping[str, object] | None = None
+    ) -> list[AllMessageValues]:
         """Render a template with the given variables and return formatted messages."""
         if template_id not in self.prompts:
             raise ValueError(f"Template '{template_id}' not found")
@@ -174,7 +203,9 @@ class ArizePhoenixTemplateManager:
             # Combine rendered content
             final_content = " ".join(rendered_content_parts)
 
-            rendered_messages.append({"role": role, "content": final_content})
+            rendered_messages.append(
+                cast("AllMessageValues", {"role": role, "content": final_content})  # cast-ok: Phoenix roles are OpenAI
+            )
 
         return rendered_messages
 
@@ -243,8 +274,8 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
     def get_prompt_template(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
-    ) -> tuple[list[AllMessageValues], dict[str, Any]]:
+        prompt_variables: Mapping[str, object] | None = None,
+    ) -> tuple[list[AllMessageValues], dict[str, object]]:
         """
         Get a prompt template and render it with variables.
 
@@ -263,7 +294,7 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
         rendered_messages: Final = self.prompt_manager.render_template(prompt_id, prompt_variables or {})
 
         # Extract metadata
-        metadata: Final = {
+        metadata: Final[dict[str, object]] = {
             "model": template.model,
             "temperature": template.temperature,
             "max_tokens": template.max_tokens,
@@ -271,7 +302,7 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
 
         # Add additional invocation parameters
         invocation_params: Final = template.invocation_parameters
-        provider_params = {}
+        provider_params: Mapping[str, object] = {}
 
         if "openai" in invocation_params:
             provider_params = invocation_params["openai"]
@@ -289,12 +320,12 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
         self,
         user_id: str | None,
         messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: dict[str, object] | str | None = None,
+        litellm_params: dict[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: dict[str, object] | None = None,
         **kwargs,
-    ) -> tuple[list[AllMessageValues], dict[str, Any] | None]:
+    ) -> tuple[list[AllMessageValues], dict[str, object] | None]:
         """
         Pre-call hook that processes the prompt template before making the LLM call.
         """
@@ -335,9 +366,9 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
 
         except Exception as e:
             # Log error but don't fail the call
-            import litellm
+            from litellm._logging import verbose_proxy_logger
 
-            litellm._logging.verbose_proxy_logger.error("Error in Arize Phoenix prompt pre_call_hook: %s", e)
+            verbose_proxy_logger.error("Error in Arize Phoenix prompt pre_call_hook: %s", e)
             return messages, litellm_params
 
     def get_available_prompts(self) -> list[str]:
@@ -393,7 +424,8 @@ class ArizePhoenixPromptManager(CustomPromptManagement):
             rendered_messages, prompt_metadata = self.get_prompt_template(prompt_id, prompt_variables)
 
             # Extract model from metadata (if specified)
-            template_model: Final = prompt_metadata.get("model")
+            raw_template_model: Final = prompt_metadata.get("model")
+            template_model: Final = raw_template_model if isinstance(raw_template_model, str) else None
 
             # Extract optional parameters from metadata
             optional_params: Final = {}
diff --git a/litellm/integrations/bitbucket/bitbucket_client.py b/litellm/integrations/bitbucket/bitbucket_client.py
index 9c964d8c10c..e7256da0237 100644
--- a/litellm/integrations/bitbucket/bitbucket_client.py
+++ b/litellm/integrations/bitbucket/bitbucket_client.py
@@ -163,15 +163,11 @@ class BitBucketClient:
             response.raise_for_status()
 
             data: Final[BitBucketSrcListing] = response.json()
-            files: Final[list[str]] = []
-
-            for item in data.get("values", []):
-                if item.get("type") == "commit_file":
-                    file_path = item.get("path", "")
-                    if file_path.endswith(file_extension):
-                        files.append(file_path)
-
-            return files
+            return [
+                file_path
+                for item in data.get("values", [])
+                if item.get("type") == "commit_file" and (file_path := item.get("path", "")).endswith(file_extension)
+            ]
 
         except Exception as e:
             # Check if it's an HTTP error
diff --git a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
index 6a03e3ee93c..ff34bd91e31 100644
--- a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
+++ b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
@@ -3,6 +3,7 @@ BitBucket prompt manager that integrates with LiteLLM's prompt management system
 Fetches .prompt files from BitBucket repositories and provides team-based access control.
 """
 
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 from jinja2 import DictLoader, select_autoescape
@@ -65,7 +66,7 @@ class BitBucketTemplateManager:
 
     def __init__(
         self,
-        bitbucket_config: dict[str, Any],
+        bitbucket_config: Mapping[str, object],
         prompt_id: str | None = None,
     ):
         self.bitbucket_config = bitbucket_config
@@ -123,7 +124,7 @@ class BitBucketTemplateManager:
             template_content = content
 
         # Parse YAML frontmatter
-        metadata: dict[str, Any] = {}
+        metadata: dict[str, object] = {}
         if frontmatter_str:
             try:
                 import yaml
@@ -141,9 +142,9 @@ class BitBucketTemplateManager:
             metadata=metadata,
         )
 
-    def _parse_yaml_basic(self, yaml_str: str) -> dict[str, Any]:
+    def _parse_yaml_basic(self, yaml_str: str) -> dict[str, object]:
         """Basic YAML parser for simple cases when PyYAML is not available."""
-        result: Final[dict[str, Any]] = {}
+        result: Final[dict[str, object]] = {}
         for line in yaml_str.split("\n"):
             line = line.strip()
             if ":" in line and not line.startswith("#"):
@@ -162,7 +163,7 @@ class BitBucketTemplateManager:
                     result[key] = value.strip("\"'")
         return result
 
-    def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> str:
+    def render_template(self, template_id: str, variables: Mapping[str, object] | None = None) -> str:
         """Render a template with the given variables."""
         if template_id not in self.prompts:
             raise ValueError(f"Template '{template_id}' not found")
@@ -209,7 +210,7 @@ class BitBucketPromptManager(CustomPromptManagement):
 
     def __init__(
         self,
-        bitbucket_config: dict[str, Any],
+        bitbucket_config: Mapping[str, object],
         prompt_id: str | None = None,
     ):
         self.bitbucket_config = bitbucket_config
@@ -234,7 +235,7 @@ class BitBucketPromptManager(CustomPromptManagement):
     def get_prompt_template(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
     ) -> tuple[str, dict[str, Any]]:
         """
         Get a prompt template and render it with variables.
@@ -267,12 +268,12 @@ class BitBucketPromptManager(CustomPromptManagement):
         self,
         user_id: str | None,
         messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: dict[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         **kwargs,
-    ) -> tuple[list[AllMessageValues], dict[str, Any] | None]:
+    ) -> tuple[list[AllMessageValues], dict[str, object] | None]:
         """
         Pre-call hook that processes the prompt template before making the LLM call.
         """
@@ -316,9 +317,9 @@ class BitBucketPromptManager(CustomPromptManagement):
 
         except Exception as e:
             # Log error but don't fail the call
-            import litellm
+            from litellm._logging import verbose_proxy_logger
 
-            litellm._logging.verbose_proxy_logger.error("Error in BitBucket prompt pre_call_hook: %s", e)
+            verbose_proxy_logger.error("Error in BitBucket prompt pre_call_hook: %s", e)
             return messages, litellm_params
 
     def _parse_prompt_to_messages(self, prompt_content: str) -> list[AllMessageValues]:
@@ -384,14 +385,14 @@ class BitBucketPromptManager(CustomPromptManagement):
     def post_call_hook(
         self,
         user_id: str | None,
-        response: Any,
+        response: object,
         input_messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: Mapping[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         **kwargs,
-    ) -> Any:
+    ) -> object:
         """
         Post-call hook for any post-processing after the LLM call.
         """
diff --git a/litellm/integrations/cloudzero/transform.py b/litellm/integrations/cloudzero/transform.py
index f0d4d67fc22..ffc8fe1c1f5 100644
--- a/litellm/integrations/cloudzero/transform.py
+++ b/litellm/integrations/cloudzero/transform.py
@@ -19,14 +19,29 @@
 """Transform LiteLLM data to CloudZero AnyCost CBF format."""
 
 from datetime import datetime
-from typing import Any, Final
+from typing import Final, SupportsFloat, SupportsIndex, SupportsInt
 
 import polars as pl
+from typing_extensions import Buffer
 
 from ...types.integrations.cloudzero import CBFRecord
 from .cz_resource_names import CZEntityType, CZRNGenerator
 
 
+def _as_int(value: object) -> int:
+    """The integer form of a spend table cell, computed the way :func:`int` computes it."""
+    if isinstance(value, (str, Buffer, SupportsInt, SupportsIndex)):
+        return int(value)
+    raise TypeError(f"int() argument must be a string or a number, not {type(value).__name__!r}")
+
+
+def _as_float(value: object) -> float:
+    """The floating point form of a spend table cell, computed the way :func:`float` computes it."""
+    if isinstance(value, (str, Buffer, SupportsFloat, SupportsIndex)):
+        return float(value)
+    raise TypeError(f"float() argument must be a string or a number, not {type(value).__name__!r}")
+
+
 class CBFTransformer:
     """Transform LiteLLM usage data to CloudZero Billing Format (CBF)."""
 
@@ -82,15 +97,15 @@ class CBFTransformer:
 
         return pl.DataFrame(cbf_data)
 
-    def _create_cbf_record(self, row: dict[str, Any]) -> CBFRecord:
+    def _create_cbf_record(self, row: dict[str, object]) -> CBFRecord:
         """Create a single CBF record from LiteLLM daily spend row."""
 
         # Parse date (daily spend tables use date strings like '2025-04-19')
         usage_date: Final = self._parse_date(row.get("date"))
 
         # Calculate total tokens
-        prompt_tokens: Final = int(row.get("prompt_tokens", 0))
-        completion_tokens: Final = int(row.get("completion_tokens", 0))
+        prompt_tokens: Final = _as_int(row.get("prompt_tokens", 0))
+        completion_tokens: Final = _as_int(row.get("completion_tokens", 0))
         total_tokens: Final = prompt_tokens + completion_tokens
 
         # Create CloudZero Resource Name (CZRN) as resource_id
@@ -154,7 +169,7 @@ class CBFTransformer:
             "time/usage_start": (
                 usage_date.isoformat() if usage_date else None
             ),  # Required: ISO-formatted UTC datetime
-            "cost/cost": float(row.get("spend", 0.0)),  # Required: billed cost
+            "cost/cost": _as_float(row.get("spend", 0.0)),  # Required: billed cost
             "resource/id": resource_id,  # CZRN (CloudZero Resource Name)
             # Usage metrics for token consumption
             "usage/amount": total_tokens,  # Numeric value of tokens consumed
@@ -187,7 +202,7 @@ class CBFTransformer:
 
         return CBFRecord(cbf_record)
 
-    def _parse_date(self, date_str) -> datetime | None:
+    def _parse_date(self, date_str: object) -> datetime | None:
         """Parse date string from daily spend tables (e.g., '2025-04-19')."""
         if date_str is None:
             return None
diff --git a/litellm/integrations/compression_interception/handler.py b/litellm/integrations/compression_interception/handler.py
index 321c7896d63..1be7a01ba3a 100644
--- a/litellm/integrations/compression_interception/handler.py
+++ b/litellm/integrations/compression_interception/handler.py
@@ -7,7 +7,10 @@ litellm_content_retrieve tool calls server-side via the typed agentic loop plan.
 
 import time
 import uuid
-from typing import TYPE_CHECKING, Any, ClassVar, Final, cast
+from collections.abc import Mapping, Sequence
+from typing import Any, ClassVar, Final, Protocol, cast
+
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_logger
 from litellm.compression import compress
@@ -22,13 +25,23 @@ from litellm.types.integrations.custom_logger import (
 )
 from litellm.types.utils import CallTypes
 
-if TYPE_CHECKING:
-    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-
 LITELLM_CONTENT_RETRIEVE_TOOL_NAME: Final = "litellm_content_retrieve"
 _CACHE_TTL_SECONDS: Final = 15 * 60
 
 
+class _AgenticLoopParams(TypedDict, total=False):
+    """The ``agentic_loop_params`` entry the agentic loop driver records on the logging object."""
+
+    model: ReadOnly[str]
+
+
+class _AgenticLoopLoggingObj(Protocol):
+    """Logging object view exposing the untyped call details this handler reads."""
+
+    @property
+    def model_call_details(self) -> Mapping[str, _AgenticLoopParams]: ...
+
+
 def _compression_savings_from_counts(
     original_tokens: object, compressed_tokens: object
 ) -> CompressionSavingsMetadata | None:
@@ -83,7 +96,7 @@ class CompressionInterceptionLogger(CustomLogger):
         compression_trigger: int = 200_000,
         compression_target: int | None = None,
         embedding_model: str | None = None,
-        embedding_model_params: dict[str, Any] | None = None,
+        embedding_model_params: dict[str, object] | None = None,
     ):
         super().__init__()
         self.enabled = enabled
@@ -106,7 +119,7 @@ class CompressionInterceptionLogger(CustomLogger):
     @staticmethod
     def initialize_from_proxy_config(
         litellm_settings: dict[str, Any],
-        callback_specific_params: dict[str, Any],
+        callback_specific_params: Mapping[str, object],
     ) -> "CompressionInterceptionLogger":
         compression_params: CompressionInterceptionConfig = {}
         if "compression_interception_params" in litellm_settings:
@@ -120,7 +133,9 @@ class CompressionInterceptionLogger(CustomLogger):
             )
         return CompressionInterceptionLogger.from_config_yaml(compression_params)
 
-    async def async_pre_call_deployment_hook(self, kwargs: dict[str, Any], call_type: CallTypes | None) -> dict | None:
+    async def async_pre_call_deployment_hook(
+        self, kwargs: dict[str, Any], call_type: CallTypes | None
+    ) -> dict[str, object] | None:
         if not self.enabled:
             return None
         if call_type is not None and call_type != CallTypes.anthropic_messages:
@@ -150,7 +165,7 @@ class CompressionInterceptionLogger(CustomLogger):
 
         cache: Final = cast(dict[str, str], compressed.get("cache", {}))
         skip_reason: Final = cast(str | None, compressed.get("compression_skipped_reason"))
-        compressed_tools: Final = cast(list[dict[str, Any]], compressed.get("tools", []))
+        compressed_tools: Final = cast(list[dict[str, object]], compressed.get("tools", []))
 
         # Only mutate kwargs when compression actually produced a result.
         # If compression was a no-op (below trigger, invalid tool sequence, etc.),
@@ -161,7 +176,7 @@ class CompressionInterceptionLogger(CustomLogger):
             kwargs["messages"] = compressed["messages"]
             if compressed_tools:
                 kwargs["tools"] = self._merge_tools(
-                    existing_tools=cast(list[dict[str, Any]] | None, kwargs.get("tools")),
+                    existing_tools=cast(list[dict[str, object]] | None, kwargs.get("tools")),
                     compressed_tools=compressed_tools,
                 )
             call_id = cast(str | None, kwargs.get("litellm_call_id"))
@@ -194,14 +209,14 @@ class CompressionInterceptionLogger(CustomLogger):
 
     async def async_should_run_agentic_loop(
         self,
-        response: Any,
+        response: object,
         model: str,
-        messages: list[dict],
-        tools: list[dict] | None,
+        messages: Sequence[Mapping[str, object]],
+        tools: Sequence[Mapping[str, object]] | None,
         stream: bool,
         custom_llm_provider: str,
-        kwargs: dict,
-    ) -> tuple[bool, dict]:
+        kwargs: Mapping[str, object],
+    ) -> tuple[bool, dict[str, object]]:
         if not self.enabled:
             return False, {}
         if not self._has_retrieval_tool(tools):
@@ -219,19 +234,19 @@ class CompressionInterceptionLogger(CustomLogger):
 
     async def async_build_agentic_loop_plan(
         self,
-        tools: dict,
+        tools: Mapping[str, object],
         model: str,
-        messages: list[dict],
-        response: Any,
-        anthropic_messages_provider_config: Any,
-        anthropic_messages_optional_request_params: dict,
-        logging_obj: "LiteLLMLoggingObj | None",
+        messages: list[dict[str, object]],
+        response: object,
+        anthropic_messages_provider_config: object,
+        anthropic_messages_optional_request_params: Mapping[str, object],
+        logging_obj: _AgenticLoopLoggingObj | None,
         stream: bool,
-        kwargs: dict,
+        kwargs: Mapping[str, object],
     ) -> AgenticLoopPlan:
         self._prune_expired_cache()
-        tool_calls: Final = cast(list[dict[str, Any]], tools.get("tool_calls", []))
-        thinking_blocks: Final = cast(list[dict[str, Any]], tools.get("thinking_blocks", []))
+        tool_calls: Final = cast(list[dict[str, object]], tools.get("tool_calls", []))
+        thinking_blocks: Final = cast(list[dict[str, object]], tools.get("thinking_blocks", []))
 
         call_id: Final = self._resolve_call_id(logging_obj=logging_obj, kwargs=kwargs)
         cache: Final = self._get_cache(call_id=call_id)
@@ -274,7 +289,7 @@ class CompressionInterceptionLogger(CustomLogger):
         full_model_name = model
         if logging_obj is not None:
             agentic_params: Final = logging_obj.model_call_details.get("agentic_loop_params", {})
-            full_model_name = cast(str, agentic_params.get("model", model))
+            full_model_name = agentic_params.get("model", model)
 
         request_patch: Final = AgenticLoopRequestPatch(
             model=full_model_name,
@@ -309,15 +324,15 @@ class CompressionInterceptionLogger(CustomLogger):
             return {}
         return cache_entry[0]
 
-    def _resolve_call_id(self, logging_obj: Any, kwargs: dict[str, Any]) -> str | None:
+    def _resolve_call_id(self, logging_obj: _AgenticLoopLoggingObj | None, kwargs: Mapping[str, object]) -> str | None:
         if logging_obj is not None:
             logging_call_id: Final = getattr(logging_obj, "litellm_call_id", None)
             if isinstance(logging_call_id, str) and logging_call_id:
                 return logging_call_id
         kwargs_call_id: Final = kwargs.get("litellm_call_id")
-        return cast(str | None, kwargs_call_id if isinstance(kwargs_call_id, str) else None)
+        return kwargs_call_id if isinstance(kwargs_call_id, str) else None
 
-    def _resolve_retrieval_content(self, tool_call: dict[str, Any], cache: dict[str, str]) -> str:
+    def _resolve_retrieval_content(self, tool_call: Mapping[str, object], cache: Mapping[str, str]) -> str:
         raw_input: Final = tool_call.get("input", {})
         key = ""
         if isinstance(raw_input, dict):
@@ -328,7 +343,9 @@ class CompressionInterceptionLogger(CustomLogger):
             return cache[key]
         return f"[compressed content key '{key}' not found]"
 
-    def _extract_retrieval_tool_calls(self, response: Any) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
+    def _extract_retrieval_tool_calls(
+        self, response: object
+    ) -> tuple[list[dict[str, object]], list[dict[str, object]]]:
         if isinstance(response, dict):
             content = response.get("content", [])
         else:
@@ -337,8 +354,8 @@ class CompressionInterceptionLogger(CustomLogger):
         if not isinstance(content, list):
             return [], []
 
-        tool_calls: Final[list[dict[str, Any]]] = []
-        thinking_blocks: Final[list[dict[str, Any]]] = []
+        tool_calls: Final[list[dict[str, object]]] = []
+        thinking_blocks: Final[list[dict[str, object]]] = []
 
         for block in content:
             if isinstance(block, dict):
@@ -385,13 +402,13 @@ class CompressionInterceptionLogger(CustomLogger):
 
         return tool_calls, thinking_blocks
 
-    def _prepare_followup_kwargs(self, kwargs: dict[str, Any]) -> dict[str, Any]:
+    def _prepare_followup_kwargs(self, kwargs: Mapping[str, object]) -> dict[str, object]:
         internal_keys: Final = {"litellm_logging_obj"}
         return {
             k: v for k, v in kwargs.items() if not k.startswith("_compression_interception") and k not in internal_keys
         }
 
-    def _has_retrieval_tool(self, tools: Any) -> bool:
+    def _has_retrieval_tool(self, tools: object) -> bool:
         if not isinstance(tools, list):
             return False
         for tool in tools:
@@ -407,9 +424,9 @@ class CompressionInterceptionLogger(CustomLogger):
 
     def _merge_tools(
         self,
-        existing_tools: list[dict[str, Any]] | None,
-        compressed_tools: list[dict[str, Any]],
-    ) -> list[dict[str, Any]]:
+        existing_tools: Sequence[Mapping[str, object]] | None,
+        compressed_tools: Sequence[Mapping[str, object]],
+    ) -> list[Mapping[str, object]]:
         merged: Final = list(existing_tools or [])
         if self._has_retrieval_tool(merged):
             return merged
diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py
index 8dc6881d23e..372c9bf6b91 100644
--- a/litellm/integrations/custom_guardrail.py
+++ b/litellm/integrations/custom_guardrail.py
@@ -1,7 +1,9 @@
 import contextvars
+import copy
 import hashlib
 import os
 import secrets
+from collections.abc import Mapping
 from datetime import datetime
 from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, Optional, get_args
 
@@ -38,6 +40,7 @@ except ImportError:
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
 dc: Final = DualCache()
 
 
@@ -227,13 +230,13 @@ class CustomGuardrail(CustomLogger):
                 )
         super().__init__(**kwargs)
 
-    def render_violation_message(self, default: str, context: dict[str, Any] | None = None) -> str:
+    def render_violation_message(self, default: str, context: Mapping[str, object] | None = None) -> str:
         """Return a custom violation message if template is configured."""
 
         if not self.violation_message_template:
             return default
 
-        format_context: Final[dict[str, Any]] = {"default_message": default}
+        format_context: Final[dict[str, object]] = {"default_message": default}
         if context:
             format_context.update(context)
         try:
@@ -661,7 +664,7 @@ class CustomGuardrail(CustomLogger):
         value: Final = self._get_admin_metadata(data).get("opted_out_global_guardrails")
         return value if isinstance(value, list) else []
 
-    def _is_valid_response_type(self, result: Any) -> bool:
+    def _is_valid_response_type(self, result: object) -> bool:
         """
         Check if result is a valid LLMResponseTypes instance.
 
@@ -722,7 +725,7 @@ class CustomGuardrail(CustomLogger):
             return None
         return f"{_PRE_CALL_EXECUTED_TOKEN}:{name}"
 
-    def mark_pre_call_hook_ran(self, data: dict[str, Any]) -> None:
+    def mark_pre_call_hook_ran(self, data: dict[str, object]) -> None:
         """
         Record that this guardrail's ``async_pre_call_hook`` already ran for this
         request, so the deployment-level hook does not run it a second time.
@@ -747,7 +750,7 @@ class CustomGuardrail(CustomLogger):
                 return
         data["metadata"] = {PRE_CALL_EXECUTED_GUARDRAILS_KEY: [marker]}
 
-    def _pre_call_hook_already_ran(self, data: dict[str, Any]) -> bool:
+    def _pre_call_hook_already_ran(self, data: dict[str, object]) -> bool:
         marker: Final = self._pre_call_marker()
         if marker is None:
             return False
@@ -851,6 +854,69 @@ class CustomGuardrail(CustomLogger):
 
         return result
 
+    async def async_logging_hook(
+        self,
+        kwargs: dict,  # mutable-ok: CustomLogger.async_logging_hook contract
+        result: object,
+        call_type: str,
+    ) -> tuple[dict, object]:  # mutable-ok: CustomLogger.async_logging_hook contract
+        """logging_only: run apply_guardrail on copies of the logged request/response and record the verdict."""
+        from litellm.llms import get_guardrail_translation_mapping
+
+        if not self.uses_apply_guardrail_interface() or self.use_native_lifecycle_hooks:
+            return kwargs, result
+        try:
+            translation: Final = get_guardrail_translation_mapping(CallTypes(call_type))()
+        except ValueError:
+            verbose_logger.debug(
+                "Guardrail %s: no guardrail translation for call_type=%s, skipping logging_only scan",
+                self.guardrail_name,
+                call_type,
+            )
+            return kwargs, result
+        litellm_params: Final = kwargs.get("litellm_params") or {}
+        scratch_metadata: Final = {
+            key: value
+            for key, value in (litellm_params.get("metadata") or {}).items()
+            if key != "standard_logging_guardrail_information"
+        }
+        try:
+            await self._scan_logged_call(kwargs, result, translation, scratch_metadata)
+        except Exception as e:
+            verbose_logger.warning("Guardrail %s: logging_only scan raised: %s", self.guardrail_name, e)
+        recorded: Final = scratch_metadata.get("standard_logging_guardrail_information")
+        standard_logging_object: Final = kwargs.get("standard_logging_object")
+        if not recorded or not isinstance(standard_logging_object, dict):
+            return kwargs, result
+        entries: Final = recorded if isinstance(recorded, list) else [recorded]
+        existing: Final = standard_logging_object.get("guardrail_information") or []
+        return {
+            **kwargs,
+            "standard_logging_object": {**standard_logging_object, "guardrail_information": [*existing, *entries]},
+        }, result
+
+    async def _scan_logged_call(
+        self,
+        kwargs: dict,  # mutable-ok: CustomLogger.async_logging_hook contract
+        result: object,
+        translation: "BaseTranslation",
+        scratch_metadata: dict,  # mutable-ok: apply_guardrail records its verdict into request metadata
+    ) -> None:
+        optional_params: Final = kwargs.get("optional_params") or {}
+        scratch_input: Final = copy.deepcopy(kwargs.get("messages") or kwargs.get("input"))
+        scratch_request: Final = {
+            "model": kwargs.get("model"),
+            "messages": scratch_input,
+            "input": scratch_input,
+            "tools": copy.deepcopy(optional_params.get("tools")),
+            "litellm_call_id": kwargs.get("litellm_call_id"),
+            "metadata": scratch_metadata,
+        }
+        await translation.process_input_messages(data=scratch_request, guardrail_to_apply=self)
+        await translation.process_output_response(
+            response=copy.deepcopy(result), guardrail_to_apply=self, request_data=scratch_request
+        )
+
     def supports_scan_only_tool_results(self) -> bool:
         """Whether this guardrail can scan tool-result content.
 
@@ -1170,7 +1236,7 @@ class CustomGuardrail(CustomLogger):
         This gets logged on downsteam Langfuse, DataDog, etc.
         """
         # Convert None to empty dict to satisfy type requirements
-        guardrail_response: dict[str, Any] | str = {} if response is None else response
+        guardrail_response: dict[str, object] | str = {} if response is None else response
 
         # For apply_guardrail functions in custom_code_guardrail scenario,
         # simplify the logged response to "allow", "deny", or "mask"
diff --git a/litellm/integrations/custom_logger.py b/litellm/integrations/custom_logger.py
index 41caf732db0..8f03e08f02d 100644
--- a/litellm/integrations/custom_logger.py
+++ b/litellm/integrations/custom_logger.py
@@ -2,7 +2,7 @@
 #    On success, logs events to Promptlayer
 import re
 import traceback
-from collections.abc import AsyncGenerator, Mapping
+from collections.abc import AsyncGenerator, Mapping, Sequence
 from typing import TYPE_CHECKING, Any, ClassVar, Final, Optional
 
 from pydantic import BaseModel
@@ -31,6 +31,9 @@ if TYPE_CHECKING:
 
     from litellm.caching.caching import DualCache
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.llms.base_llm.anthropic_messages.transformation import (
+        BaseAnthropicMessagesConfig,
+    )
     from litellm.proxy._types import UserAPIKeyAuth
     from litellm.types.mcp import (
         MCPPostCallResponseObject,
@@ -39,7 +42,7 @@ if TYPE_CHECKING:
     )
     from litellm.types.router import PreRoutingHookResponse
 
-    Span = _Span | Any
+    Span = _Span
 else:
     Span = Any
     LiteLLMLoggingObj = Any
@@ -123,11 +126,11 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
             return []
 
         callbacks: Final = AllCallbacks()
-        callback_info: Final = getattr(callbacks, lookup_name, None)
+        callback_info: Final[object] = getattr(callbacks, lookup_name, None)
         if callback_info is None:
             return []
 
-        params: Final = getattr(callback_info, "litellm_callback_params", None)
+        params: Final[Sequence[str] | None] = getattr(callback_info, "litellm_callback_params", None)
         if not params:
             return []
 
@@ -268,7 +271,9 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
     ) -> list[dict]:
         return healthy_deployments
 
-    async def async_pre_call_deployment_hook(self, kwargs: dict[str, Any], call_type: CallTypes | None) -> dict | None:
+    async def async_pre_call_deployment_hook(
+        self, kwargs: dict[str, object], call_type: CallTypes | None
+    ) -> dict | None:
         """
         Allow modifying the request just before it's sent to the deployment.
 
@@ -344,9 +349,9 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
     async def async_post_call_streaming_deployment_hook(
         self,
         request_data: dict,
-        response_chunk: Any,
+        response_chunk: object,
         call_type: CallTypes | None,
-    ) -> Any | None:
+    ) -> object | None:
         """
         Allow modifying streaming chunks just before they're returned to the user.
 
@@ -378,7 +383,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         """
 
     def translate_completion_output_params_streaming(
-        self, completion_stream: Any
+        self, completion_stream: object
     ) -> AdapterCompletionStreamWrapper | None:
         """
         Translates the streaming chunk, from the OpenAI format to the custom format.
@@ -418,9 +423,9 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         self,
         data: dict,
         user_api_key_dict: UserAPIKeyAuth,
-        response: Any,
+        response: object,
         request_headers: dict[str, str] | None = None,
-        litellm_call_info: dict[str, Any] | None = None,
+        litellm_call_info: dict[str, object] | None = None,
     ) -> dict[str, str] | None:
         """
         Called after an LLM API call (success or failure) to allow injecting custom HTTP response headers.
@@ -471,11 +476,11 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
     ) -> Any:
         pass
 
-    async def async_logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]:
+    async def async_logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]:
         """For masking logged request/response. Return a modified version of the request/result."""
         return kwargs, result
 
-    def logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]:
+    def logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]:
         """For masking logged request/response. Return a modified version of the request/result."""
         return kwargs, result
 
@@ -581,7 +586,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     async def async_should_run_agentic_loop(
         self,
-        response: Any,
+        response: object,
         model: str,
         messages: list[dict],
         tools: list[dict] | None,
@@ -642,8 +647,8 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         tools: dict,
         model: str,
         messages: list[dict],
-        response: Any,
-        anthropic_messages_provider_config: Any,
+        response: object,
+        anthropic_messages_provider_config: "BaseAnthropicMessagesConfig | None",
         anthropic_messages_optional_request_params: dict,
         logging_obj: "LiteLLMLoggingObj",
         stream: bool,
@@ -711,8 +716,8 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         tools: dict,
         model: str,
         messages: list[dict],
-        response: Any,
-        anthropic_messages_provider_config: Any,
+        response: object,
+        anthropic_messages_provider_config: "BaseAnthropicMessagesConfig | None",
         anthropic_messages_optional_request_params: dict,
         logging_obj: "LiteLLMLoggingObj",
         stream: bool,
@@ -728,7 +733,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     async def async_post_agentic_loop_response_hook(
         self,
-        response: Any,
+        response: object,
         plan: AgenticLoopPlan,
         kwargs: dict,
     ) -> Any:
@@ -767,7 +772,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     async def async_should_run_chat_completion_agentic_loop(
         self,
-        response: Any,
+        response: object,
         model: str,
         messages: list[dict],
         tools: list[dict] | None,
@@ -785,12 +790,12 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         tools: dict,
         model: str,
         messages: list[dict],
-        response: Any,
+        response: object,
         optional_params: dict,
         logging_obj: "LiteLLMLoggingObj",
         stream: bool,
         kwargs: dict,
-    ) -> Any:
+    ) -> object:
         """
         Hook to execute chat completion agentic loop based on context from should_run hook.
         """
@@ -800,7 +805,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
         tools: dict,
         model: str,
         messages: list[dict],
-        response: Any,
+        response: object,
         optional_params: dict,
         logging_obj: "LiteLLMLoggingObj",
         stream: bool,
@@ -851,7 +856,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
             - Converting to string and then truncating the logged content catches this
         2. We want to avoid modifying the original `messages`, `response`, and `error_str` in the logging payload since these are in kwargs and could be returned to the user
         """
-        field_value: Final = standard_logging_object.get(field_name)
+        field_value: Final[object] = standard_logging_object.get(field_name)
         if field_value:
             str_value: Final = str(field_value)
             if len(str_value) > max_length:
@@ -1005,8 +1010,8 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
           • Keep untyped or text content.
           • Recursively redact inline base64 blobs in *any* string field, at any depth.
         """
-        raw_messages: Final[Any] = payload.get("messages", [])
-        messages: Final[list[Any]] = raw_messages if isinstance(raw_messages, list) else []
+        raw_messages: Final[object] = payload.get("messages", [])
+        messages: Final[list[object]] = raw_messages if isinstance(raw_messages, list) else []
         verbose_logger.debug("[CustomLogger] Stripping base64 from %s messages", len(messages))
 
         if messages:
@@ -1037,8 +1042,8 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
           • Keep untyped or text content.
           • Recursively redact inline base64 blobs in *any* string field, at any depth.
         """
-        raw_messages: Final[Any] = payload.get("messages", [])
-        messages: Final[list[Any]] = raw_messages if isinstance(raw_messages, list) else []
+        raw_messages: Final[object] = payload.get("messages", [])
+        messages: Final[list[object]] = raw_messages if isinstance(raw_messages, list) else []
         verbose_logger.debug("[CustomLogger] Stripping base64 from %s messages", len(messages))
 
         if messages:
@@ -1056,10 +1061,10 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     def _redact_base64(
         self,
-        value: Any,
+        value: object,
         depth: int = 0,
         max_depth: int = DEFAULT_MAX_RECURSE_DEPTH_SENSITIVE_DATA_MASKER,
-    ) -> Any:
+    ) -> object:
         """Recursively redact inline base64 from any nested structure with a max recursion depth limit."""
         if depth > max_depth:
             verbose_logger.warning("[CustomLogger] Max recursion depth %s reached while redacting base64", max_depth)
@@ -1079,7 +1084,7 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
         return value
 
-    def _should_keep_content(self, content: Any) -> bool:
+    def _should_keep_content(self, content: object) -> bool:
         """Return True if this content item should be retained."""
         if not isinstance(content, dict):
             return True
@@ -1090,16 +1095,16 @@ class CustomLogger:  # https://docs.litellm.ai/docs/observability/custom_callbac
 
     def _process_messages(
         self,
-        messages: list[Any],
+        messages: list[object],
         max_depth: int = DEFAULT_MAX_RECURSE_DEPTH_SENSITIVE_DATA_MASKER,
-    ) -> list[dict[str, Any]]:
-        filtered_messages: Final[list[dict[str, Any]]] = []
+    ) -> list[dict[str, object]]:
+        filtered_messages: Final[list[dict[str, object]]] = []
         for msg in messages:
             if not isinstance(msg, dict):
                 continue
-            contents: Any = msg.get("content")
+            contents: object = msg.get("content")
             if isinstance(contents, list):
-                cleaned: list[Any] = []
+                cleaned: list[object] = []
                 for c in contents:
                     if self._should_keep_content(content=c):
                         cleaned.append(self._redact_base64(value=c, max_depth=max_depth))
diff --git a/litellm/integrations/datadog/datadog.py b/litellm/integrations/datadog/datadog.py
index 04f1c6dff15..866076a3c49 100644
--- a/litellm/integrations/datadog/datadog.py
+++ b/litellm/integrations/datadog/datadog.py
@@ -20,10 +20,11 @@ import time
 import traceback
 from collections.abc import Sequence
 from datetime import datetime as datetimeObj
-from typing import Any, Final
+from typing import TYPE_CHECKING, Any, Final
 
 import httpx
 from httpx import Response
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -62,6 +63,18 @@ from litellm.types.utils import StandardLoggingPayload
 
 from ..additional_logging_utils import AdditionalLoggingUtils
 
+if TYPE_CHECKING:
+    from fastapi import HTTPException
+
+    from litellm.proxy._types import UserAPIKeyAuth
+
+
+class _DatadogLoggingKwargs(TypedDict, total=False):
+    """The subset of logging ``kwargs`` that the Datadog payload builder reads."""
+
+    standard_logging_object: ReadOnly[StandardLoggingPayload | None]
+
+
 # max number of logs DD API can accept
 
 
@@ -87,6 +100,11 @@ def _resolve_dd_batch_size() -> int:
     return max(1, min(value, DD_MAX_BATCH_SIZE))
 
 
+def _span_attribute(span: object, name: str) -> object:
+    """Read an optional attribute off whatever span object the active tracer hands back."""
+    return getattr(span, name, None)
+
+
 class DataDogLogger(
     CustomBatchLogger,
     AdditionalLoggingUtils,
@@ -271,9 +289,9 @@ class DataDogLogger(
         self,
         request_data: dict,
         original_exception: Exception,
-        user_api_key_dict: Any,
+        user_api_key_dict: "UserAPIKeyAuth",
         traceback_str: str | None = None,
-    ) -> Any | None:
+    ) -> "HTTPException | None":
         """
         Log proxy-level failures (e.g. 401 auth, DB connection errors) to Datadog.
 
@@ -297,7 +315,7 @@ class DataDogLogger(
                 status_code = int(_code)
 
             # Use project-standard sanitized user context when running in proxy
-            user_context: dict[str, Any] = {}
+            user_context: dict[str, object] = {}
             try:
                 from litellm.proxy.litellm_pre_call_utils import (
                     LiteLLMProxyRequestSetup,
@@ -553,8 +571,8 @@ class DataDogLogger(
 
     def create_datadog_logging_payload(
         self,
-        kwargs: dict | Any,
-        response_obj: Any,
+        kwargs: _DatadogLoggingKwargs,
+        response_obj: object,
         start_time: datetime.datetime,
         end_time: datetime.datetime,
     ) -> DatadogPayload:
@@ -562,8 +580,8 @@ class DataDogLogger(
         Helper function to create a datadog payload for logging
 
         Args:
-            kwargs (Union[dict, Any]): request kwargs
-            response_obj (Any): llm api response
+            kwargs: request kwargs, read for its standard logging object
+            response_obj: llm api response
             start_time (datetime.datetime): start time of request
             end_time (datetime.datetime): end time of request
 
@@ -625,7 +643,7 @@ class DataDogLogger(
         self,
         payload: ServiceLoggerPayload,
         error: str | None = "",
-        parent_otel_span: Any | None = None,
+        parent_otel_span: object = None,
         start_time: datetimeObj | float | None = None,
         end_time: float | datetimeObj | None = None,
         event_metadata: dict | None = None,
@@ -659,7 +677,7 @@ class DataDogLogger(
         self,
         payload: ServiceLoggerPayload,
         error: str | None = "",
-        parent_otel_span: Any | None = None,
+        parent_otel_span: object = None,
         start_time: datetimeObj | float | None = None,
         end_time: float | datetimeObj | None = None,
         event_metadata: dict | None = None,
@@ -696,7 +714,7 @@ class DataDogLogger(
 
     def _create_v0_logging_payload(
         self,
-        kwargs: dict | Any,
+        kwargs: dict,
         response_obj: Any,
         start_time: datetime.datetime,
         end_time: datetime.datetime,
@@ -810,11 +828,11 @@ class DataDogLogger(
             if current_span is None:
                 return None
 
-            trace_id: Final = getattr(current_span, "trace_id", None)
+            trace_id: Final = _span_attribute(current_span, "trace_id")
             if trace_id is None:
                 return None
 
-            span_id: Final = getattr(current_span, "span_id", None)
+            span_id: Final = _span_attribute(current_span, "span_id")
             trace_context: Final[dict[str, str]] = {"trace_id": str(trace_id)}
             if span_id is not None:
                 trace_context["span_id"] = str(span_id)
diff --git a/litellm/integrations/datadog/datadog_llm_obs.py b/litellm/integrations/datadog/datadog_llm_obs.py
index 704f0323e95..5e116b7301a 100644
--- a/litellm/integrations/datadog/datadog_llm_obs.py
+++ b/litellm/integrations/datadog/datadog_llm_obs.py
@@ -9,7 +9,9 @@ API Reference: https://docs.datadoghq.com/llm_observability/setup/api/?tab=examp
 import asyncio
 import json
 import os
+from collections.abc import Mapping, Sequence
 from datetime import datetime
+from types import MappingProxyType
 from typing import Any, Final, Literal
 
 import httpx
@@ -29,12 +31,16 @@ from litellm.integrations.datadog.datadog_mock_client import (
 )
 from litellm.litellm_core_utils.dd_tracing import tracer
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    convert_content_list_to_str,
     handle_any_messages_to_chat_completion_str_messages_conversion,
 )
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.litellm_core_utils.safe_json_loads import safe_json_loads
 from litellm.llms.custom_httpx.http_handler import (
     get_async_httpx_client,
     httpxSpecialProvider,
 )
+from litellm.proxy.spend_tracking.savings import extract_cache_creation_tokens, extract_cache_read_tokens
 from litellm.types.integrations.datadog_llm_obs import *
 from litellm.types.utils import (
     CallTypes,
@@ -43,6 +49,189 @@ from litellm.types.utils import (
     StandardLoggingPayloadErrorInformation,
 )
 
+_EMPTY_MAPPING: Final[Mapping[str, Any]] = MappingProxyType({})
+_EMPTY_MESSAGE: Final[Message] = {"role": "", "content": ""}
+_MAX_PARSED_TOOL_ARGUMENT_CHARS: Final = 256 * 1024
+
+
+def _mapping_field(source: Mapping[str, Any], key: str) -> Mapping[str, Any]:
+    """The value at `key` when it is a mapping, else an empty one."""
+    value: Final = source.get(key)
+    return value if isinstance(value, dict) else _EMPTY_MAPPING
+
+
+def _content_blocks(message: Mapping[str, Any]) -> tuple[Mapping[str, Any], ...]:
+    content: Final = message.get("content")
+    if not isinstance(content, list):
+        return ()
+    return tuple(block for block in content if isinstance(block, dict))
+
+
+def _to_dd_arguments(raw_arguments: object) -> dict[str, Any] | str:
+    """
+    Arguments as the object LLM Obs types them as, or the raw string when they are not one.
+
+    Strings past the size bound ship unparsed: decoding multiplies memory on hostile compact
+    JSON, and the raw string is what the intake receives either way.
+    """
+    if not isinstance(raw_arguments, str):
+        return raw_arguments if isinstance(raw_arguments, dict) else str(raw_arguments)
+    if len(raw_arguments) > _MAX_PARSED_TOOL_ARGUMENT_CHARS:
+        return raw_arguments
+    parsed: Final = safe_json_loads(raw_arguments)
+    return parsed if isinstance(parsed, dict) else raw_arguments
+
+
+def _to_dd_tool_calls(message: Mapping[str, Any]) -> tuple[ToolCall, ...]:
+    """
+    The tool calls a message carries, in LLM Obs' ToolCall schema, from either dialect.
+
+    OpenAI puts them in `tool_calls` with the callee nested under `function` and `arguments`
+    serialized; Anthropic puts them in `content` as `tool_use` blocks with `input` already an
+    object. LLM Obs reads `name` / `arguments` / `tool_id` either way.
+    """
+    raw_tool_calls: Final = message.get("tool_calls")
+    openai_calls: Final = tuple(
+        ToolCall(
+            name=function.get("name", ""),
+            arguments=_to_dd_arguments(function.get("arguments", "")),
+            tool_id=tool_call.get("id", ""),
+            type=tool_call.get("type", "function"),
+        )
+        for tool_call in (raw_tool_calls if isinstance(raw_tool_calls, list) else ())
+        if isinstance(tool_call, dict)
+        for function in [_mapping_field(tool_call, "function")]
+    )
+    anthropic_calls: Final = tuple(
+        ToolCall(
+            name=block.get("name", ""),
+            arguments=_to_dd_arguments(block.get("input") or {}),
+            tool_id=block.get("id", ""),
+            type="tool_use",
+        )
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_use"
+    )
+    return openai_calls + anthropic_calls
+
+
+def _to_dd_tool_results(message: Mapping[str, Any], tool_call_names: Mapping[str, str]) -> tuple[ToolResult, ...]:
+    """
+    The tool results a message carries, linked back to the call each answers.
+
+    OpenAI models a result as a whole `role: "tool"` message keyed by `tool_call_id`;
+    Anthropic nests `tool_result` blocks inside a user message, keyed by `tool_use_id`.
+    """
+
+    def to_result(tool_id: str, result: object) -> ToolResult:
+        return ToolResult(
+            name=tool_call_names.get(tool_id, ""),
+            result=result if isinstance(result, str) else safe_dumps(result),
+            tool_id=tool_id,
+            type="function",
+        )
+
+    if message.get("role") == "tool":
+        return (to_result(str(message.get("tool_call_id", "")), message.get("content") or ""),)
+    return tuple(
+        to_result(str(block.get("tool_use_id", "")), block.get("content") or "")
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_result"
+    )
+
+
+def _tool_call_names_by_id(messages: Sequence[object]) -> Mapping[str, str]:
+    """Ids to tool names for result linking; reads names structurally and parses nothing."""
+    openai_pairs: Final = tuple(
+        (tool_call.get("id"), function.get("name", ""))
+        for message in messages
+        if isinstance(message, dict) and isinstance(message.get("tool_calls"), list)
+        for tool_call in message["tool_calls"]
+        if isinstance(tool_call, dict)
+        for function in [_mapping_field(tool_call, "function")]
+    )
+    anthropic_pairs: Final = tuple(
+        (block.get("id"), block.get("name", ""))
+        for message in messages
+        if isinstance(message, dict)
+        for block in _content_blocks(message)
+        if block.get("type") == "tool_use"
+    )
+    return MappingProxyType({str(tool_id): str(name) for tool_id, name in openai_pairs + anthropic_pairs if tool_id})
+
+
+def _to_dd_message(message: object, tool_call_names: Mapping[str, str]) -> Message:
+    """
+    Map one chat message onto LLM Obs' Message schema, adding fields and never destroying content.
+
+    Content collapses to its text only when it has text; a content list with none (tool blocks,
+    images) rides along unchanged so nothing the caller logged is lost. Tool calls and results
+    move into the fields the LLM Obs Tools panel reads, from both the OpenAI and Anthropic shapes.
+    """
+    if not isinstance(message, dict):
+        converted: Final = handle_any_messages_to_chat_completion_str_messages_conversion(message)
+        return converted[0] if converted else _EMPTY_MESSAGE
+
+    text: Final = convert_content_list_to_str(message)  # pyright: ignore[reportArgumentType]  # caller-supplied dict
+    original_content: Final = message.get("content")
+    content: Final = (
+        text if text or not isinstance(original_content, list) or not original_content else original_content
+    )
+    reasoning: Final = message.get("reasoning_content")
+    tool_calls: Final = _to_dd_tool_calls(message)
+    tool_results: Final = _to_dd_tool_results(message, tool_call_names)
+    dd_message: Final[Message] = {
+        "role": message.get("role", ""),
+        "content": content,
+        **({"reasoning_content": reasoning} if reasoning is not None else {}),
+        **({"tool_calls": tool_calls} if tool_calls else {}),
+        **({"tool_results": tool_results} if tool_results else {}),
+    }
+    return dd_message
+
+
+def _to_dd_messages(messages: object) -> tuple[Message, ...]:
+    """Map a whole conversation, resolving each tool result against the calls that precede it."""
+    if messages is None:
+        return ()
+    if not isinstance(messages, list):
+        return tuple(handle_any_messages_to_chat_completion_str_messages_conversion(messages))
+    tool_call_names: Final = _tool_call_names_by_id(messages)
+    return tuple(_to_dd_message(message, tool_call_names) for message in messages)
+
+
+def _to_dd_tool_definition(entry: Mapping[str, Any]) -> ToolDefinition | None:
+    function: Final = entry.get("function")
+    declared: Final[Mapping[str, Any]] = function if isinstance(function, dict) else entry
+    name: Final = declared.get("name")
+    if not name:
+        return None
+    schema: Final = declared.get("parameters") or declared.get("input_schema")
+    description: Final = declared.get("description", "")
+    if not isinstance(schema, dict):
+        return ToolDefinition(name=name, description=description)
+    return ToolDefinition(name=name, description=description, schema=schema)
+
+
+def _to_dd_tool_definitions(model_parameters: object) -> tuple[ToolDefinition, ...]:
+    """
+    Map the request's declared tools onto LLM Obs' ToolDefinition schema.
+
+    Handles the wrapped chat-completions shape and the bare shape the Anthropic and
+    Responses surfaces use, since both reach this logger through `model_parameters`.
+    """
+    if not isinstance(model_parameters, dict):
+        return ()
+    raw_tools: Final = model_parameters.get("tools") or model_parameters.get("functions")
+    if not isinstance(raw_tools, list):
+        return ()
+    return tuple(
+        definition
+        for entry in raw_tools
+        if isinstance(entry, dict)
+        if (definition := _to_dd_tool_definition(entry)) is not None
+    )
+
 
 class DataDogLLMObsLogger(CustomBatchLogger):
     def __init__(self, **kwargs):
@@ -221,12 +410,9 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         if standard_logging_payload is None:
             raise Exception("DataDogLLMObs: standard_logging_object is not set")
 
-        messages = standard_logging_payload["messages"]
-        messages = self._ensure_string_content(messages=messages)
-
         metadata: Final = kwargs.get("litellm_params", {}).get("metadata", {})
 
-        input_meta: Final = InputMeta(messages=handle_any_messages_to_chat_completion_str_messages_conversion(messages))
+        input_meta: Final = InputMeta(messages=_to_dd_messages(standard_logging_payload["messages"]))
         output_meta: Final = OutputMeta(
             messages=self._get_response_messages(
                 standard_logging_payload=standard_logging_payload,
@@ -240,22 +426,20 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         if isinstance(metadata, dict):
             metadata_parent_id = metadata.get("parent_id")
 
-        meta: Final = Meta(
-            kind=self._get_datadog_span_kind(standard_logging_payload.get("call_type"), metadata_parent_id),
-            input=input_meta,
-            output=output_meta,
-            metadata=self._get_dd_llm_obs_payload_metadata(standard_logging_payload),
-            error=error_info,
-        )
+        tool_definitions: Final = _to_dd_tool_definitions(standard_logging_payload.get("model_parameters"))
+        span_kind: Final = self._get_datadog_span_kind(standard_logging_payload.get("call_type"), metadata_parent_id)
+        payload_metadata: Final = self._get_dd_llm_obs_payload_metadata(standard_logging_payload)
 
-        # Calculate metrics (you may need to adjust these based on available data)
-        metrics: Final = LLMMetrics(
-            input_tokens=float(standard_logging_payload.get("prompt_tokens", 0)),
-            output_tokens=float(standard_logging_payload.get("completion_tokens", 0)),
-            total_tokens=float(standard_logging_payload.get("total_tokens", 0)),
-            total_cost=float(standard_logging_payload.get("response_cost", 0)),
-            time_to_first_token=self._get_time_to_first_token_seconds(standard_logging_payload),
-        )
+        meta: Final[Meta] = {
+            "kind": span_kind,
+            "input": input_meta,
+            "output": output_meta,
+            "metadata": payload_metadata,
+            "error": error_info,
+            **({"tool_definitions": tool_definitions} if tool_definitions else {}),
+        }
+
+        metrics: Final = self._assemble_metrics(standard_logging_payload)
 
         payload: Final[LLMObsPayload] = LLMObsPayload(
             parent_id=metadata_parent_id if metadata_parent_id else "undefined",
@@ -313,6 +497,45 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 )
         return error_info
 
+    def _assemble_metrics(self, standard_logging_payload: StandardLoggingPayload) -> LLMMetrics:
+        """
+        Build the span metrics, including the prompt-cache counts LLM Obs charts cache savings from.
+
+        Cache counts resolve through the same owners the savings dashboard uses, so every provider
+        spelling is covered, and `non_cached_input_tokens` subtracts BOTH cache categories because
+        litellm's normalized prompt count includes both (the invariant the cost calculator's custom
+        pricing helper documents). A zero residual on a fully cached request is real data and is
+        emitted; a zero read or write count is absence and is not.
+        """
+        prompt_tokens: Final = float(standard_logging_payload.get("prompt_tokens", 0))
+        completion_tokens: Final = float(standard_logging_payload.get("completion_tokens", 0))
+        total_tokens: Final = float(standard_logging_payload.get("total_tokens", 0))
+        total_cost: Final = float(standard_logging_payload.get("response_cost", 0))
+        time_to_first_token: Final = self._get_time_to_first_token_seconds(standard_logging_payload)
+
+        raw_usage: Final = (standard_logging_payload.get("metadata") or {}).get("usage_object")
+        usage_object: Final = raw_usage if isinstance(raw_usage, dict) else None
+        cache_read: Final = float(extract_cache_read_tokens(usage_object))
+        cache_write: Final = float(extract_cache_creation_tokens(usage_object))
+
+        metrics: Final[LLMMetrics] = {
+            "input_tokens": prompt_tokens,
+            "output_tokens": completion_tokens,
+            "total_tokens": total_tokens,
+            "total_cost": total_cost,
+            "time_to_first_token": time_to_first_token,
+            **(
+                {
+                    **({"cache_read_input_tokens": cache_read} if cache_read else {}),
+                    **({"cache_write_input_tokens": cache_write} if cache_write else {}),
+                    "non_cached_input_tokens": max(prompt_tokens - cache_read - cache_write, 0.0),
+                }
+                if cache_read or cache_write
+                else {}
+            ),
+        }
+        return metrics
+
     def _get_time_to_first_token_seconds(self, standard_logging_payload: StandardLoggingPayload) -> float:
         """
         Get the time to first token in seconds
@@ -334,7 +557,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
     def _get_response_messages(
         self, standard_logging_payload: StandardLoggingPayload, call_type: str | None
-    ) -> list[Any]:
+    ) -> tuple[Message, ...]:
         """
         Get the messages from the response object
 
@@ -343,7 +566,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
         response_obj = standard_logging_payload.get("response")
         if response_obj is None:
-            return []
+            return ()
 
         # edge case: handle response_obj is a string representation of a dict
         if isinstance(response_obj, str):
@@ -356,7 +579,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                     # fallback to json parsing
                     response_obj = json.loads(str(response_obj))
                 except json.JSONDecodeError:
-                    return []
+                    return ()
 
         if call_type in [
             CallTypes.completion.value,
@@ -374,12 +597,12 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 if isinstance(response_obj, dict) and "choices" in response_obj:
                     choices: Final = response_obj["choices"]
                     if choices and len(choices) > 0 and "message" in choices[0]:
-                        return [choices[0]["message"]]
-                return []
+                        return _to_dd_messages([choices[0]["message"]])
+                return ()
             except (KeyError, IndexError, TypeError):
                 # In case of any error accessing the response structure, return empty list
-                return []
-        return []
+                return ()
+        return ()
 
     def _get_datadog_span_kind(
         self, call_type: str | None, parent_id: str | None = None
@@ -484,22 +707,11 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         # Default fallback for unknown or passthrough operations
         return "llm"
 
-    def _ensure_string_content(self, messages: str | list[Any] | dict[Any, Any] | None) -> list[Any]:
-        if messages is None:
-            return []
-        if isinstance(messages, str):
-            return [messages]
-        elif isinstance(messages, list):
-            return [message for message in messages]
-        elif isinstance(messages, dict):
-            return [str(messages.get("content", ""))]
-        return []
-
-    def _get_dd_llm_obs_payload_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, Any]:
+    def _get_dd_llm_obs_payload_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, object]:
         """
         Fields to track in DD LLM Observability metadata from litellm standard logging payload
         """
-        _metadata: Final[dict[str, Any]] = {
+        _metadata: Final[dict[str, object]] = {
             "model_name": standard_logging_payload.get("model", "unknown"),
             "model_provider": standard_logging_payload.get("custom_llm_provider", "unknown"),
             "id": standard_logging_payload.get("id", "unknown"),
@@ -523,10 +735,6 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         spend_metrics: Final = self._get_spend_metrics(standard_logging_payload)
         _metadata.update({"spend_metrics": dict(spend_metrics)})
 
-        ## extract tool calls and add to metadata
-        tool_call_metadata: Final = self._extract_tool_call_metadata(standard_logging_payload)
-        _metadata.update(tool_call_metadata)
-
         _standard_logging_metadata: Final[dict] = dict(standard_logging_payload.get("metadata", {})) or {}
         _metadata.update(_standard_logging_metadata)
         return _metadata
@@ -646,107 +854,3 @@ class DataDogLLMObsLogger(CustomBatchLogger):
                 verbose_logger.debug("Original value: %s", user_api_key_budget_reset_at)
 
         return spend_metrics
-
-    def _process_input_messages_preserving_tool_calls(self, messages: list[Any]) -> list[dict[str, Any]]:
-        """
-        Process input messages while preserving tool_calls and tool message types.
-
-        This bypasses the lossy string conversion when tool calls are present,
-        allowing complex nested tool_calls objects to be preserved for Datadog.
-        """
-        processed: Final = []
-        for msg in messages:
-            if isinstance(msg, dict):
-                # Preserve messages with tool_calls or tool role as-is
-                if "tool_calls" in msg or msg.get("role") == "tool":
-                    processed.append(msg)
-                else:
-                    # For regular messages, still apply string conversion
-                    converted = handle_any_messages_to_chat_completion_str_messages_conversion([msg])
-                    processed.extend(converted)
-            else:
-                # For non-dict messages, apply string conversion
-                converted = handle_any_messages_to_chat_completion_str_messages_conversion([msg])
-                processed.extend(converted)
-        return processed
-
-    @staticmethod
-    def _tool_calls_kv_pair(tool_calls: list[dict[str, Any]]) -> dict[str, Any]:
-        """
-        Extract tool call information into key-value pairs for Datadog metadata.
-
-        Similar to OpenTelemetry's implementation but adapted for Datadog's format.
-        """
-        kv_pairs: Final[dict[str, Any]] = {}
-        for idx, tool_call in enumerate(tool_calls):
-            try:
-                # Extract tool call ID
-                tool_id = tool_call.get("id")
-                if tool_id:
-                    kv_pairs[f"tool_calls.{idx}.id"] = tool_id
-
-                # Extract tool call type
-                tool_type = tool_call.get("type")
-                if tool_type:
-                    kv_pairs[f"tool_calls.{idx}.type"] = tool_type
-
-                # Extract function information
-                function = tool_call.get("function")
-                if function:
-                    function_name = function.get("name")
-                    if function_name:
-                        kv_pairs[f"tool_calls.{idx}.function.name"] = function_name
-
-                    function_arguments = function.get("arguments")
-                    if function_arguments:
-                        # Store arguments as JSON string for Datadog
-                        if isinstance(function_arguments, str):
-                            kv_pairs[f"tool_calls.{idx}.function.arguments"] = function_arguments
-                        else:
-                            import json
-
-                            kv_pairs[f"tool_calls.{idx}.function.arguments"] = json.dumps(function_arguments)
-            except (KeyError, TypeError, ValueError) as e:
-                verbose_logger.debug("DataDogLLMObs: Error processing tool call %s: %s", idx, e)
-                continue
-
-        return kv_pairs
-
-    def _extract_tool_call_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, Any]:
-        """
-        Extract tool call information from both input messages and response for Datadog metadata.
-        """
-        tool_call_metadata: Final[dict[str, Any]] = {}
-
-        try:
-            # Extract tool calls from input messages
-            messages: Final = standard_logging_payload.get("messages", [])
-            if messages and isinstance(messages, list):
-                for message in messages:
-                    if isinstance(message, dict) and "tool_calls" in message:
-                        tool_calls = message.get("tool_calls")
-                        if tool_calls:
-                            input_tool_calls_kv = self._tool_calls_kv_pair(tool_calls)
-                            # Prefix with "input_" to distinguish from response tool calls
-                            for key, value in input_tool_calls_kv.items():
-                                tool_call_metadata[f"input_{key}"] = value
-
-            # Extract tool calls from response
-            response_obj: Final = standard_logging_payload.get("response")
-            if response_obj and isinstance(response_obj, dict):
-                choices: Final = response_obj.get("choices", [])
-                for choice in choices:
-                    if isinstance(choice, dict):
-                        message = choice.get("message")
-                        if message and isinstance(message, dict):
-                            tool_calls = message.get("tool_calls")
-                            if tool_calls:
-                                response_tool_calls_kv = self._tool_calls_kv_pair(tool_calls)
-                                # Prefix with "output_" to distinguish from input tool calls
-                                for key, value in response_tool_calls_kv.items():
-                                    tool_call_metadata[f"output_{key}"] = value
-
-        except Exception as e:
-            verbose_logger.debug("DataDogLLMObs: Error extracting tool call metadata: %s", e)
-
-        return tool_call_metadata
diff --git a/litellm/integrations/dotprompt/prompt_manager.py b/litellm/integrations/dotprompt/prompt_manager.py
index fd0b17ba746..9c82ff7c5ba 100644
--- a/litellm/integrations/dotprompt/prompt_manager.py
+++ b/litellm/integrations/dotprompt/prompt_manager.py
@@ -3,12 +3,21 @@ Based on Google's GenAI Kit dotprompt implementation: https://google.github.io/d
 """
 
 import re
+from collections.abc import Mapping
 from pathlib import Path
 from typing import Any, Final
 
 import yaml
 from jinja2 import DictLoader, select_autoescape
 from jinja2.sandbox import ImmutableSandboxedEnvironment
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
+
+class _PromptFileJson(TypedDict):
+    """JSON form of a .prompt file: rendered template text plus its frontmatter."""
+
+    content: ReadOnly[NotRequired[str]]
+    metadata: ReadOnly[NotRequired[dict[str, object]]]
 
 
 def strip_version_suffix(prompt_id: str) -> str | None:
@@ -167,7 +176,7 @@ class PromptManager:
             template_id=prompt_id,
         )
 
-    def _parse_frontmatter(self, content: str) -> tuple[dict[str, Any], str]:
+    def _parse_frontmatter(self, content: str) -> tuple[dict[str, object], str]:
         """Parse YAML frontmatter from prompt content."""
         # Match YAML frontmatter between --- delimiters
         frontmatter_pattern: Final = r"^---\s*\n(.*?)\n---\s*\n(.*)$"
@@ -178,7 +187,7 @@ class PromptManager:
             template_content = match.group(2)
 
             try:
-                frontmatter = yaml.safe_load(frontmatter_yaml) or {}
+                frontmatter: dict[str, object] = yaml.safe_load(frontmatter_yaml) or {}
             except yaml.YAMLError as e:
                 raise ValueError(f"Invalid YAML frontmatter: {e}")
         else:
@@ -191,7 +200,7 @@ class PromptManager:
     def render(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         version: int | None = None,
     ) -> str:
         """
@@ -231,7 +240,7 @@ class PromptManager:
         except Exception as e:
             raise ValueError(f"Error rendering template '{prompt_id}': {e}")
 
-    def _validate_input(self, variables: dict[str, Any], schema: dict[str, Any]) -> None:
+    def _validate_input(self, variables: Mapping[str, object], schema: Mapping[str, str]) -> None:
         """Basic validation of input variables against schema."""
         for field_name, field_type in schema.items():
             if field_name in variables:
@@ -291,7 +300,7 @@ class PromptManager:
         """Get a list of all available prompt IDs."""
         return list(self.prompts.keys())
 
-    def get_prompt_metadata(self, prompt_id: str) -> dict[str, Any] | None:
+    def get_prompt_metadata(self, prompt_id: str) -> dict[str, object] | None:
         """Get metadata for a specific prompt."""
         template: Final = self.prompts.get(prompt_id)
         return template.metadata if template else None
@@ -302,12 +311,12 @@ class PromptManager:
         if self.prompt_directory:
             self._load_prompts()
 
-    def add_prompt(self, prompt_id: str, content: str, metadata: dict[str, Any] | None = None) -> None:
+    def add_prompt(self, prompt_id: str, content: str, metadata: dict[str, object] | None = None) -> None:
         """Add a prompt template programmatically."""
         template: Final = PromptTemplate(content=content, metadata=metadata or {}, template_id=prompt_id)
         self.prompts[prompt_id] = template
 
-    def prompt_file_to_json(self, file_path: str | Path) -> dict[str, Any]:
+    def prompt_file_to_json(self, file_path: str | Path) -> _PromptFileJson:
         """Convert a .prompt file to JSON format.
 
         Args:
@@ -324,7 +333,7 @@ class PromptManager:
 
         return {"content": template_content.strip(), "metadata": frontmatter}
 
-    def json_to_prompt_file(self, prompt_data: dict[str, Any]) -> str:
+    def json_to_prompt_file(self, prompt_data: _PromptFileJson) -> str:
         """Convert JSON prompt data to .prompt file format.
 
         Args:
diff --git a/litellm/integrations/galileo.py b/litellm/integrations/galileo.py
index 23727801a6f..b27618993a3 100644
--- a/litellm/integrations/galileo.py
+++ b/litellm/integrations/galileo.py
@@ -6,10 +6,11 @@ import re
 import uuid
 from collections.abc import Mapping, Sequence
 from datetime import datetime, timezone, tzinfo
-from typing import Any, Final, TypedDict, cast
+from typing import Any, Final, Protocol, cast
 
 import httpx
 from pydantic import BaseModel, Field
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -35,6 +36,34 @@ GALILEO_CLOUD_API_BASE_URL: Final = "https://api.galileo.ai"
 GALILEO_MAX_IN_MEMORY_RECORDS: Final = 1000
 
 
+class _GalileoLoginBody(TypedDict):
+    """Decoded body of the Galileo login response."""
+
+    access_token: ReadOnly[str]
+
+
+class _GalileoLoginResponse(Protocol):
+    """The login call's HTTP response, read for the access token it carries."""
+
+    def json(self) -> _GalileoLoginBody: ...
+
+
+class _JsonResponse(Protocol):
+    """An HTTP response read only for whatever JSON body it decodes to."""
+
+    def json(self) -> object: ...
+
+
+def _login_access_token(response: _GalileoLoginResponse) -> str:
+    """Read the bearer token out of a Galileo login response body."""
+    return response.json()["access_token"]
+
+
+def _decoded_body(response: _JsonResponse) -> object:
+    """Decode a response body without asserting anything about its shape."""
+    return response.json()
+
+
 class GalileoStandardLoggingFields(TypedDict, total=False):
     call_type: str
     model: str
@@ -156,7 +185,7 @@ class GalileoObserve(CustomLogger):
             },
         )
         galileo_login_response.raise_for_status()
-        access_token: Final = galileo_login_response.json()["access_token"]
+        access_token: Final = _login_access_token(galileo_login_response)
         self.headers = {
             "accept": "application/json",
             "Content-Type": "application/json",
@@ -421,7 +450,7 @@ class GalileoObserve(CustomLogger):
         try:
             verbose_logger.debug(
                 "Galileo Logger HTTP error response json: %s",
-                response.json(),
+                _decoded_body(response),
             )
         except Exception:
             pass
diff --git a/litellm/integrations/gitlab/gitlab_client.py b/litellm/integrations/gitlab/gitlab_client.py
index 0690ccc8c15..813a2ef2821 100644
--- a/litellm/integrations/gitlab/gitlab_client.py
+++ b/litellm/integrations/gitlab/gitlab_client.py
@@ -4,12 +4,80 @@ Now supports selecting a tag via `config["tag"]`; falls back to branch ("main").
 """
 
 import base64
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, Protocol, TypedDict
 from urllib.parse import quote
 
+from typing_extensions import ReadOnly
+
 from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
 
+class GitLabFilePayload(TypedDict, total=False):
+    """A repository-files API entry."""
+
+    content: ReadOnly[str]
+    encoding: ReadOnly[str]
+
+
+class GitLabTreeEntry(TypedDict, total=False):
+    """A repository-tree API entry."""
+
+    path: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class GitLabBranch(TypedDict, total=False):
+    """A repository-branches API entry."""
+
+    name: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class GitLabFileMetadata(TypedDict):
+    """The response headers a raw file request exposes as metadata."""
+
+    content_type: ReadOnly[str | None]
+    content_length: ReadOnly[str | None]
+    last_modified: ReadOnly[str | None]
+
+
+class _FileJsonResponse(Protocol):
+    def json(self) -> GitLabFilePayload: ...
+
+
+class _TreeJsonResponse(Protocol):
+    def json(self) -> Sequence[GitLabTreeEntry] | None: ...
+
+
+class _ProjectJsonResponse(Protocol):
+    def json(self) -> Mapping[str, object]: ...
+
+
+class _BranchesJsonResponse(Protocol):
+    def json(self) -> Sequence[GitLabBranch] | None: ...
+
+
+def _file_payload(resp: _FileJsonResponse) -> GitLabFilePayload:
+    """The JSON body of a repository-files response."""
+    return resp.json()
+
+
+def _tree_entries(resp: _TreeJsonResponse) -> Sequence[GitLabTreeEntry]:
+    """The entries of a repository-tree response."""
+    return resp.json() or []
+
+
+def _project_info(resp: _ProjectJsonResponse) -> Mapping[str, object]:
+    """The JSON body of a project response."""
+    return resp.json()
+
+
+def _branch_entries(resp: _BranchesJsonResponse) -> Sequence[GitLabBranch] | None:
+    """The JSON body of a repository-branches response."""
+    return resp.json()
+
+
 class GitLabClient:
     """
     Client for interacting with the GitLab API to fetch files.
@@ -42,12 +110,12 @@ class GitLabClient:
 
         self.project: str | int = project
         self.access_token: str = str(access_token)
-        self.auth_method = config.get("auth_method", "token")  # 'token' or 'oauth'
+        self.auth_method: str = config.get("auth_method", "token")  # 'token' or 'oauth'
         self.branch = config.get("branch", None)
         if not self.branch:
             self.branch = "main"
         self.tag = config.get("tag")
-        self.base_url = config.get("base_url", "https://gitlab.com/api/v4")
+        self.base_url: str = config.get("base_url", "https://gitlab.com/api/v4")
 
         if not all([self.project, self.access_token]):
             raise ValueError("project and access_token are required")
@@ -159,7 +227,7 @@ class GitLabClient:
             if resp.status_code == 404:
                 return None
             resp.raise_for_status()
-            data: Final = resp.json()
+            data: Final = _file_payload(resp)
             content: Final = data.get("content")
             encoding: Final = data.get("encoding", "")
             if content and encoding == "base64":
@@ -208,7 +276,7 @@ class GitLabClient:
                 return []
             resp.raise_for_status()
 
-            data: Final = resp.json() or []
+            data: Final = _tree_entries(resp)
             files: Final[list[str]] = []
             for item in data:
                 if item.get("type") == "blob":
@@ -229,13 +297,13 @@ class GitLabClient:
                 raise Exception("Authentication failed. Check your GitLab token and auth_method.")
             raise Exception(f"Failed to list files in '{directory_path}': {e}")
 
-    def get_repository_info(self) -> dict[str, Any]:
+    def get_repository_info(self) -> Mapping[str, object]:
         """Get information about the project/repository."""
         url: Final = f"{self.base_url}/projects/{self._project_enc}"
         try:
             resp: Final = self.http_handler.get(url, headers=self.headers)
             resp.raise_for_status()
-            return resp.json()
+            return _project_info(resp)
         except Exception as e:
             raise Exception(f"Failed to get repository info: {e}")
 
@@ -247,18 +315,18 @@ class GitLabClient:
         except Exception:
             return False
 
-    def get_branches(self) -> list[dict[str, Any]]:
+    def get_branches(self) -> list[GitLabBranch]:
         """Get list of branches in the repository."""
         url: Final = f"{self.base_url}/projects/{self._project_enc}/repository/branches"
         try:
             resp: Final = self.http_handler.get(url, headers=self.headers)
             resp.raise_for_status()
-            data: Final = resp.json()
+            data: Final = _branch_entries(resp)
             return data if isinstance(data, list) else []
         except Exception as e:
             raise Exception(f"Failed to get branches: {e}")
 
-    def get_file_metadata(self, file_path: str, *, ref: str | None = None) -> dict[str, Any] | None:
+    def get_file_metadata(self, file_path: str, *, ref: str | None = None) -> GitLabFileMetadata | None:
         """
         Get minimal metadata about a file via RAW endpoint headers at a given ref.
 
diff --git a/litellm/integrations/gitlab/gitlab_prompt_manager.py b/litellm/integrations/gitlab/gitlab_prompt_manager.py
index c41d9dd240f..d4602176650 100644
--- a/litellm/integrations/gitlab/gitlab_prompt_manager.py
+++ b/litellm/integrations/gitlab/gitlab_prompt_manager.py
@@ -2,10 +2,12 @@
 GitLab prompt manager with configurable prompts folder.
 """
 
-from typing import TYPE_CHECKING, Any, Final
+from collections.abc import Mapping
+from typing import TYPE_CHECKING, Any, Final, TypeVar
 
 from jinja2 import DictLoader, select_autoescape
 from jinja2.sandbox import ImmutableSandboxedEnvironment
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.integrations.custom_prompt_management import CustomPromptManagement
 
@@ -24,6 +26,19 @@ from litellm.types.utils import StandardCallbackDynamicParams
 
 GITLAB_PREFIX: Final = "gitlab::"
 
+_ResponseT = TypeVar("_ResponseT")
+
+
+class GitLabCachedPrompt(TypedDict):
+    id: ReadOnly[str]
+    path: ReadOnly[str]
+    content: ReadOnly[str]
+    metadata: ReadOnly[Mapping[str, object]]
+    model: ReadOnly[str | None]
+    temperature: ReadOnly[float | None]
+    max_tokens: ReadOnly[int | None]
+    optional_params: ReadOnly[Mapping[str, object]]
+
 
 def encode_prompt_id(raw_id: str) -> str:
     """Convert GitLab path IDs like 'invoice/extract' → 'gitlab::invoice::extract'"""
@@ -206,7 +221,7 @@ class GitLabTemplateManager:
                     result[key] = value.strip("\"'")
         return result
 
-    def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> str:
+    def render_template(self, template_id: str, variables: Mapping[str, object] | None = None) -> str:
         if template_id not in self.prompts:
             raise ValueError(f"Template '{template_id}' not found")
         template: Final = self.prompts[template_id]
@@ -313,7 +328,7 @@ class GitLabPromptManager(CustomPromptManagement):
     def get_prompt_template(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         *,
         ref: str | None = None,
     ) -> tuple[str, dict[str, Any]]:
@@ -338,13 +353,13 @@ class GitLabPromptManager(CustomPromptManagement):
         self,
         user_id: str | None,
         messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: dict[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         prompt_version: str | None = None,
         **kwargs,
-    ) -> tuple[list[AllMessageValues], dict[str, Any] | None]:
+    ) -> tuple[list[AllMessageValues], dict[str, object] | None]:
         if not prompt_id:
             return messages, litellm_params
         try:
@@ -377,9 +392,9 @@ class GitLabPromptManager(CustomPromptManagement):
 
             return final_messages, litellm_params
         except Exception as e:
-            import litellm
+            from litellm._logging import verbose_proxy_logger
 
-            litellm._logging.verbose_proxy_logger.error("Error in GitLab prompt pre_call_hook: %s", e)
+            verbose_proxy_logger.error("Error in GitLab prompt pre_call_hook: %s", e)
             return messages, litellm_params
 
     def _parse_prompt_to_messages(self, prompt_content: str) -> list[AllMessageValues]:
@@ -435,14 +450,14 @@ class GitLabPromptManager(CustomPromptManagement):
     def post_call_hook(
         self,
         user_id: str | None,
-        response: Any,
+        response: _ResponseT,
         input_messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: Mapping[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         **kwargs,
-    ) -> Any:
+    ) -> _ResponseT:
         return response
 
     def get_available_prompts(self) -> list[str]:
@@ -498,7 +513,7 @@ class GitLabPromptManager(CustomPromptManagement):
             messages: Final = self._parse_prompt_to_messages(rendered_prompt)
             template_model: Final = prompt_metadata.get("model")
 
-            optional_params: Final[dict[str, Any]] = {}
+            optional_params: Final[dict[str, object]] = {}
             for param in [
                 "temperature",
                 "max_tokens",
@@ -658,14 +673,14 @@ class GitLabPromptCache:
         self.template_manager: GitLabTemplateManager = self.prompt_manager.prompt_manager
 
         # In-memory stores
-        self._by_file: dict[str, dict[str, Any]] = {}
-        self._by_id: dict[str, dict[str, Any]] = {}
+        self._by_file: dict[str, GitLabCachedPrompt] = {}
+        self._by_id: dict[str, GitLabCachedPrompt] = {}
 
     # -------------------------
     # Public API
     # -------------------------
 
-    def load_all(self, *, recursive: bool = True) -> dict[str, dict[str, Any]]:
+    def load_all(self, *, recursive: bool = True) -> dict[str, GitLabCachedPrompt]:
         """
         Scan GitLab for all .prompt files under prompts_path, load and parse each,
         and return the mapping of repo file path -> JSON-like dict.
@@ -695,7 +710,7 @@ class GitLabPromptCache:
 
         return self._by_id
 
-    def reload(self, *, recursive: bool = True) -> dict[str, dict[str, Any]]:
+    def reload(self, *, recursive: bool = True) -> dict[str, GitLabCachedPrompt]:
         """Clear the cache and re-load from GitLab."""
         self._by_file.clear()
         self._by_id.clear()
@@ -709,11 +724,11 @@ class GitLabPromptCache:
         """Return the template IDs (relative to prompts_path, without extension) currently cached."""
         return list(self._by_id.keys())
 
-    def get_by_file(self, file_path: str) -> dict[str, Any] | None:
+    def get_by_file(self, file_path: str) -> GitLabCachedPrompt | None:
         """Get a cached prompt JSON by repo file path."""
         return self._by_file.get(file_path)
 
-    def get_by_id(self, prompt_id: str) -> dict[str, Any] | None:
+    def get_by_id(self, prompt_id: str) -> GitLabCachedPrompt | None:
         """Get a cached prompt JSON by prompt ID (relative to prompts_path)."""
         if prompt_id in self._by_id:
             return self._by_id[prompt_id]
@@ -728,7 +743,7 @@ class GitLabPromptCache:
     # Internals
     # -------------------------
 
-    def _template_to_json(self, prompt_id: str, tmpl: GitLabPromptTemplate) -> dict[str, Any]:
+    def _template_to_json(self, prompt_id: str, tmpl: GitLabPromptTemplate) -> GitLabCachedPrompt:
         """
         Normalize a GitLabPromptTemplate into a JSON-like dict that is easy to serialize.
         """
diff --git a/litellm/integrations/langfuse/langfuse.py b/litellm/integrations/langfuse/langfuse.py
index 296c2b5714e..9576eabaa34 100644
--- a/litellm/integrations/langfuse/langfuse.py
+++ b/litellm/integrations/langfuse/langfuse.py
@@ -89,7 +89,7 @@ def _extract_cache_read_input_tokens(usage_obj) -> int:
 
     # Check prompt_tokens_details.cached_tokens (used by Gemini and other providers)
     if hasattr(usage_obj, "prompt_tokens_details"):
-        prompt_tokens_details: Final = getattr(usage_obj, "prompt_tokens_details", None)
+        prompt_tokens_details: Final[object] = getattr(usage_obj, "prompt_tokens_details", None)
         if prompt_tokens_details is not None and hasattr(prompt_tokens_details, "cached_tokens"):
             cached_tokens: Final = getattr(prompt_tokens_details, "cached_tokens", None)
             if cached_tokens is not None and isinstance(cached_tokens, (int, float)) and cached_tokens > 0:
@@ -623,9 +623,16 @@ class LangFuseLogger:
             )
 
             # Apply custom masking function if provided
-            if masking_function is not None and callable(masking_function):
-                input = self._apply_masking_function(input, masking_function)
-                output = self._apply_masking_function(output, masking_function)
+            masked_input: Final[object] = (
+                self._apply_masking_function(input, masking_function)
+                if masking_function is not None and callable(masking_function)
+                else input
+            )
+            masked_output: Final[object] = (
+                self._apply_masking_function(output, masking_function)
+                if masking_function is not None and callable(masking_function)
+                else output
+            )
 
             clean_metadata = redact_user_api_key_info(metadata=clean_metadata)
 
@@ -651,15 +658,15 @@ class LangFuseLogger:
 
                 # Special keys that are found in the function arguments and not the metadata
                 if "input" in update_trace_keys:
-                    trace_params["input"] = input if not mask_input else "redacted-by-litellm"
+                    trace_params["input"] = masked_input if not mask_input else "redacted-by-litellm"
                 if "output" in update_trace_keys:
-                    trace_params["output"] = output if not mask_output else "redacted-by-litellm"
+                    trace_params["output"] = masked_output if not mask_output else "redacted-by-litellm"
             else:  # don't overwrite an existing trace
                 trace_params = {
                     "id": trace_id,
                     "name": trace_name,
                     "session_id": session_id,
-                    "input": input if not mask_input else "redacted-by-litellm",
+                    "input": masked_input if not mask_input else "redacted-by-litellm",
                     "version": clean_metadata.pop(
                         "trace_version", clean_metadata.get("version", None)
                     ),  # If provided just version, it will applied to the trace as well, if applied a trace version it will take precedence
@@ -669,9 +676,9 @@ class LangFuseLogger:
                     trace_params[key.replace("trace_", "")] = clean_metadata.pop(key, None)
 
                 if level == "ERROR":
-                    trace_params["status_message"] = output
+                    trace_params["status_message"] = masked_output
                 else:
-                    trace_params["output"] = output if not mask_output else "redacted-by-litellm"
+                    trace_params["output"] = masked_output if not mask_output else "redacted-by-litellm"
 
             if debug is True or (isinstance(debug, str) and debug.lower() == "true"):
                 debug_metadata: Final = {
@@ -708,7 +715,7 @@ class LangFuseLogger:
                 ("aws_region_name", aws_region_name, bool(aws_region_name)),
                 ("cache_hit", kwargs.get("cache_hit") or False, self._supports_tags() and "cache_hit" in kwargs),
             )
-            enrichments: Final[Mapping[str, Any]] = {
+            enrichments: Final[Mapping[str, object]] = {
                 key: value for key, value, include in candidate_enrichments if include
             }
 
@@ -802,8 +809,8 @@ class LangFuseLogger:
                 "end_time": end_time,
                 "model": model_name,
                 "model_parameters": optional_params,
-                "input": input if not mask_input else "redacted-by-litellm",
-                "output": output if not mask_output else "redacted-by-litellm",
+                "input": masked_input if not mask_input else "redacted-by-litellm",
+                "output": masked_output if not mask_output else "redacted-by-litellm",
                 "usage": usage,
                 "usage_details": usage_details,
                 "metadata": {
@@ -825,8 +832,8 @@ class LangFuseLogger:
                     prompt_management_metadata=prompt_management_metadata,
                     langfuse_client=self.Langfuse,
                 )
-            if output is not None and isinstance(output, str) and level == "ERROR":
-                generation_params["status_message"] = output
+            if masked_output is not None and isinstance(masked_output, str) and level == "ERROR":
+                generation_params["status_message"] = masked_output
 
             if self._supports_completion_start_time():
                 generation_params["completion_start_time"] = kwargs.get("completion_start_time", None)
@@ -935,7 +942,7 @@ class LangFuseLogger:
         return Version(self.langfuse_sdk_version) >= Version("2.7.3")
 
     @staticmethod
-    def _apply_masking_function(data: Any, masking_function: Callable[[Any], Any]) -> Any:
+    def _apply_masking_function(data: object, masking_function: Callable[[object], object]) -> object:
         """
         Apply a masking function to data, handling different data types.
 
@@ -1049,7 +1056,7 @@ def _add_prompt_to_generation_params(
     generation_params: dict,
     clean_metadata: dict,
     prompt_management_metadata: StandardLoggingPromptManagementMetadata | None,
-    langfuse_client: Any,
+    langfuse_client: object,
 ) -> dict:
     from langfuse import Langfuse
     from langfuse.model import (
diff --git a/litellm/integrations/opik/opik.py b/litellm/integrations/opik/opik.py
index fae93f03d1e..ce47d7fe27a 100644
--- a/litellm/integrations/opik/opik.py
+++ b/litellm/integrations/opik/opik.py
@@ -4,9 +4,12 @@ Opik Logger that logs LLM events to an Opik server
 
 import asyncio
 import traceback
+from collections.abc import Mapping
 from datetime import datetime
 from typing import Any, Final
 
+from typing_extensions import ReadOnly, TypedDict, Unpack
+
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_batch_logger import CustomBatchLogger
 from litellm.llms.custom_httpx.http_handler import (
@@ -23,7 +26,7 @@ except Exception:
     opik_client = None
 
 
-def _should_skip_event(kwargs: dict[str, Any]) -> bool:
+def _should_skip_event(kwargs: Mapping[str, object]) -> bool:
     """Check if event should be skipped due to missing standard_logging_object."""
     if kwargs.get("standard_logging_object") is None:
         verbose_logger.debug("OpikLogger skipping event; no standard_logging_object found")
@@ -31,12 +34,24 @@ def _should_skip_event(kwargs: dict[str, Any]) -> bool:
     return False
 
 
+class _OpikLoggerKwargs(TypedDict, total=False):
+    """Constructor options accepted by ``OpikLogger``."""
+
+    project_name: ReadOnly[str | None]
+    url: ReadOnly[str | None]
+    api_key: ReadOnly[str | None]
+    workspace: ReadOnly[str | None]
+    batch_size: ReadOnly[int | None]
+    flush_interval: ReadOnly[int | None]
+    max_queue_size: ReadOnly[int | None]
+
+
 class OpikLogger(CustomBatchLogger):
     """
     Opik Logger for logging events to an Opik Server
     """
 
-    def __init__(self, **kwargs: Any) -> None:
+    def __init__(self, **kwargs: Unpack[_OpikLoggerKwargs]) -> None:
         self.async_httpx_client = get_async_httpx_client(llm_provider=httpxSpecialProvider.LoggingCallback)
         self.sync_httpx_client = _get_httpx_client()
 
@@ -95,7 +110,7 @@ class OpikLogger(CustomBatchLogger):
 
     async def async_log_success_event(
         self,
-        kwargs: dict[str, Any],
+        kwargs: dict[str, object],
         response_obj: Any,
         start_time: datetime,
         end_time: datetime,
@@ -163,7 +178,7 @@ class OpikLogger(CustomBatchLogger):
         except Exception as e:
             verbose_logger.exception("OpikLogger failed to log success event - %s\n%s", e, traceback.format_exc())
 
-    def _sync_send(self, url: str, headers: dict[str, str], batch: dict[str, Any]) -> None:
+    def _sync_send(self, url: str, headers: dict[str, str], batch: dict[str, object]) -> None:
         try:
             response: Final = self.sync_httpx_client.post(
                 url=url,
@@ -178,7 +193,7 @@ class OpikLogger(CustomBatchLogger):
 
     def log_success_event(
         self,
-        kwargs: dict[str, Any],
+        kwargs: dict[str, object],
         response_obj: Any,
         start_time: datetime,
         end_time: datetime,
@@ -247,7 +262,7 @@ class OpikLogger(CustomBatchLogger):
         except Exception as e:
             verbose_logger.exception("OpikLogger failed to log success event - %s\n%s", e, traceback.format_exc())
 
-    async def _submit_batch(self, url: str, headers: dict[str, str], batch: dict[str, Any]) -> None:
+    async def _submit_batch(self, url: str, headers: dict[str, str], batch: dict[str, object]) -> None:
         try:
             response: Final = await self.async_httpx_client.post(
                 url=url,
diff --git a/litellm/integrations/opik/opik_payload_builder/extractors.py b/litellm/integrations/opik/opik_payload_builder/extractors.py
index 92a7eca7f3e..4dd3d40fae3 100644
--- a/litellm/integrations/opik/opik_payload_builder/extractors.py
+++ b/litellm/integrations/opik/opik_payload_builder/extractors.py
@@ -1,6 +1,7 @@
 """Data extraction functions for Opik payload building."""
 
 import json
+from collections.abc import Mapping
 from typing import Any, Final
 
 from litellm import _logging
@@ -35,8 +36,8 @@ def normalize_provider_name(provider: str | None) -> str | None:
 
 
 def extract_opik_metadata(
-    litellm_metadata: dict[str, Any],
-    standard_logging_metadata: dict[str, Any],
+    litellm_metadata: Mapping[str, Any],
+    standard_logging_metadata: Mapping[str, Any],
 ) -> dict[str, Any]:
     """
     Merge Opik metadata from three sources in increasing priority order:
@@ -97,7 +98,7 @@ def extract_span_identifiers(
 
 
 def extract_tags(
-    opik_metadata: dict[str, Any],
+    opik_metadata: Mapping[str, Any],
     custom_llm_provider: str | None,
 ) -> list[str]:
     """
@@ -122,7 +123,7 @@ def apply_proxy_header_overrides(
     project_name: str,
     tags: list[str],
     thread_id: str | None,
-    proxy_headers: dict[str, Any],
+    proxy_headers: Mapping[str, str],
 ) -> tuple[str, list[str], str | None]:
     """
     Apply overrides from proxy request headers (opik_* prefix).
@@ -148,7 +149,7 @@ def apply_proxy_header_overrides(
             thread_id = value
         elif param_key == "tags":
             try:
-                parsed_tags = json.loads(value)
+                parsed_tags: object = json.loads(value)
                 if isinstance(parsed_tags, list):
                     tags.extend(parsed_tags)
             except (json.JSONDecodeError, TypeError):
@@ -158,11 +159,11 @@ def apply_proxy_header_overrides(
 
 
 def extract_and_build_metadata(
-    opik_metadata: dict[str, Any],
-    standard_logging_metadata: dict[str, Any],
-    standard_logging_object: dict[str, Any],
-    litellm_kwargs: dict[str, Any],
-) -> dict[str, Any]:
+    opik_metadata: Mapping[str, object],
+    standard_logging_metadata: Mapping[str, object],
+    standard_logging_object: Mapping[str, object],
+    litellm_kwargs: Mapping[str, object],
+) -> dict[str, object]:
     """
     Build the complete metadata dictionary from all available sources.
 
diff --git a/litellm/integrations/opik/opik_payload_builder/payload_builders.py b/litellm/integrations/opik/opik_payload_builder/payload_builders.py
index e40d72ea542..855b84ba4c8 100644
--- a/litellm/integrations/opik/opik_payload_builder/payload_builders.py
+++ b/litellm/integrations/opik/opik_payload_builder/payload_builders.py
@@ -17,12 +17,12 @@ def build_trace_payload(
     end_time: datetime,
     input_data: Any,
     output_data: Any,
-    metadata: dict[str, Any],
+    metadata: dict[str, object],
     tags: list[str],
     thread_id: str | None,
 ) -> types.TracePayload:
     """Build a complete trace payload."""
-    trace_name: Final = response_obj.get("object", "unknown type")
+    trace_name: Final[str] = response_obj.get("object", "unknown type")
 
     return types.TracePayload(
         project_name=project_name,
@@ -47,7 +47,7 @@ def build_span_payload(
     end_time: datetime,
     input_data: Any,
     output_data: Any,
-    metadata: dict[str, Any],
+    metadata: dict[str, object],
     tags: list[str],
     usage: dict[str, int],
     provider: str | None = None,
@@ -56,9 +56,9 @@ def build_span_payload(
     """Build a complete span payload."""
     span_id: Final = utils.create_uuid7()
 
-    model: Final = response_obj.get("model", "unknown-model")
-    obj_type: Final = response_obj.get("object", "unknown-object")
-    created: Final = response_obj.get("created", 0)
+    model: Final[str] = response_obj.get("model", "unknown-model")
+    obj_type: Final[str] = response_obj.get("object", "unknown-object")
+    created: Final[int] = response_obj.get("created", 0)
     span_name: Final = f"{model}_{obj_type}_{created}"
 
     _logging.verbose_logger.debug("OpikLogger creating span with id %s for trace %s", span_id, trace_id)
diff --git a/litellm/integrations/otel/langfuse_logger.py b/litellm/integrations/otel/langfuse_logger.py
new file mode 100644
index 00000000000..ed47533e700
--- /dev/null
+++ b/litellm/integrations/otel/langfuse_logger.py
@@ -0,0 +1,60 @@
+from collections.abc import AsyncGenerator, AsyncIterator, Callable, Mapping
+from typing import TYPE_CHECKING, Final
+
+from litellm._logging import verbose_logger
+from litellm.integrations.otel.logger import OpenTelemetryV2
+from litellm.integrations.otel.mappers.langfuse import LANGFUSE_OBSERVATION_INPUT, LANGFUSE_OBSERVATION_OUTPUT
+from litellm.integrations.otel.model.request_io import request_input, response_output, stream_output
+from litellm.integrations.otel.plumbing.context import request_root_span
+
+if TYPE_CHECKING:
+    from litellm.proxy._types import UserAPIKeyAuth
+    from litellm.types.utils import ModelResponseStream
+
+
+class LangfuseOpenTelemetryV2(OpenTelemetryV2):
+    """Stamps the request's input and output on the root observation while it is still recording.
+
+    Langfuse shows a trace's input and output from its root observation. The proxy's root span ends
+    when the response is sent, before the success callback runs, so both stamps come from the
+    post-call hooks in the request task: the request as it stands after the pre-call chain and the
+    response as it is returned, for the call types whose response renders as a message.
+    """
+
+    async def async_post_call_success_hook(
+        self,
+        data: Mapping[str, object],
+        user_api_key_dict: "UserAPIKeyAuth",
+        response: object,
+    ) -> None:
+        self._stamp_root_io(data, lambda: response_output(response))
+
+    async def async_post_call_streaming_iterator_hook(
+        self,
+        user_api_key_dict: "UserAPIKeyAuth",
+        response: "AsyncIterator[ModelResponseStream]",
+        request_data: Mapping[str, object],
+    ) -> "AsyncGenerator[ModelResponseStream, None]":
+        relayed: Final[list[ModelResponseStream]] = []  # mutable-ok: relayed as they arrive, assembled at end of stream
+        async for chunk in response:
+            relayed.append(chunk)
+            yield chunk
+        self._stamp_root_io(request_data, lambda: stream_output(tuple(relayed), request_data))
+
+    def _stamp_root_io(self, data: Mapping[str, object], render_output: Callable[[], str | None]) -> None:
+        root: Final = request_root_span()
+        if root is None or not root.is_recording():
+            return
+        try:
+            output: Final = render_output()
+            if output is None:
+                return
+            root.set_attribute(LANGFUSE_OBSERVATION_OUTPUT, output)
+            rendered_input: Final = request_input(data)
+        except Exception:  # noqa: BLE001  # telemetry must never fail the request it describes
+            verbose_logger.debug(
+                "otel v2 langfuse: could not render the root observation input or output", exc_info=True
+            )
+            return
+        if rendered_input is not None:
+            root.set_attribute(LANGFUSE_OBSERVATION_INPUT, rendered_input)
diff --git a/litellm/integrations/otel/logger.py b/litellm/integrations/otel/logger.py
index d2a32ef73b6..a550dca6cc8 100644
--- a/litellm/integrations/otel/logger.py
+++ b/litellm/integrations/otel/logger.py
@@ -4,6 +4,7 @@ from collections import OrderedDict
 from collections.abc import Callable, Iterator, Mapping, Sequence
 from contextlib import contextmanager
 from datetime import datetime
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, cast
 
 from opentelemetry.context import Context, attach, get_current
@@ -909,3 +910,29 @@ def phase_span(name: str) -> "Iterator[Span | None]":
         return
     with logger.start_phase_span(name) as span:
         yield span
+
+
+def build_otel_v2_logger(
+    config: OpenTelemetryV2Config,
+    callback_name: str | None = None,
+    tracer_provider: TracerProvider | None = None,
+    logger_provider: LoggerProvider | None = None,
+    meter_provider: "MeterProvider | None" = None,
+    settings: Mapping[str, object] = MappingProxyType({}),
+) -> OpenTelemetryV2:
+    return _logger_class(config)(
+        config=config,
+        callback_name=callback_name,
+        tracer_provider=tracer_provider,
+        logger_provider=logger_provider,
+        meter_provider=meter_provider,
+        **settings,
+    )
+
+
+def _logger_class(config: OpenTelemetryV2Config) -> type[OpenTelemetryV2]:
+    if "langfuse" not in config.mapper_names or not config.capture_span_content:
+        return OpenTelemetryV2
+    from litellm.integrations.otel.langfuse_logger import LangfuseOpenTelemetryV2
+
+    return LangfuseOpenTelemetryV2
diff --git a/litellm/integrations/otel/mappers/genai.py b/litellm/integrations/otel/mappers/genai.py
index b09498f9292..3ac92b04c27 100644
--- a/litellm/integrations/otel/mappers/genai.py
+++ b/litellm/integrations/otel/mappers/genai.py
@@ -62,6 +62,8 @@ class GenAIMapper:
         GenAI.RESPONSE_TIME_TO_FIRST_CHUNK: lambda d: d.time_to_first_chunk_seconds,
         GenAI.USAGE_INPUT_TOKENS: lambda d: d.usage.input_tokens,
         GenAI.USAGE_OUTPUT_TOKENS: lambda d: d.usage.output_tokens,
+        GenAI.USAGE_CACHE_CREATION_INPUT_TOKENS: lambda d: d.usage.cache_creation_input_tokens,
+        GenAI.USAGE_CACHE_READ_INPUT_TOKENS: lambda d: d.usage.cache_read_input_tokens,
         Error.TYPE: lambda d: d.error.error_type if d.error else None,
         Server.ADDRESS: lambda d: d.server.address if d.server else None,
         Server.PORT: lambda d: d.server.port if d.server else None,
diff --git a/litellm/integrations/otel/mappers/langfuse.py b/litellm/integrations/otel/mappers/langfuse.py
index 6d4f1b4fd0a..01063d85355 100644
--- a/litellm/integrations/otel/mappers/langfuse.py
+++ b/litellm/integrations/otel/mappers/langfuse.py
@@ -11,6 +11,7 @@ the JSON-serialized payloads. ``_llm_call`` just applies both tables.
 
 import json
 from collections.abc import Callable
+from typing import Final
 
 from litellm.integrations.otel.mappers.base import AttributeMap, AttrValue, SpanData
 from litellm.integrations.otel.mappers.utils import (
@@ -25,6 +26,9 @@ from litellm.integrations.otel.model.payloads import (
     LLMUsage,
 )
 
+LANGFUSE_OBSERVATION_INPUT: Final = "langfuse.observation.input"
+LANGFUSE_OBSERVATION_OUTPUT: Final = "langfuse.observation.output"
+
 
 class LangfuseMapper:
     _LLM_CALL_ATTRS: dict[str, Callable[[LLMCallSpanData], AttrValue | None]] = {
@@ -56,8 +60,8 @@ class LangfuseMapper:
         "langfuse.observation.model.parameters": lambda d: json_if(
             collect(LangfuseMapper._MODEL_PARAMS, d.request_params)
         ),
-        "langfuse.observation.input": lambda d: serialize_messages(d.messages_in),
-        "langfuse.observation.output": lambda d: serialize_messages(output_messages(d)),
+        LANGFUSE_OBSERVATION_INPUT: lambda d: serialize_messages(d.messages_in),
+        LANGFUSE_OBSERVATION_OUTPUT: lambda d: serialize_messages(output_messages(d)),
         "langfuse.observation.usage_details": lambda d: json_if(collect(LangfuseMapper._USAGE_FIELDS, d.usage)),
         "langfuse.observation.cost_details": lambda d: (
             json.dumps({"total": d.response_cost}) if d.response_cost is not None else None
diff --git a/litellm/integrations/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py
index f70c777e1a7..e8ed269f6cb 100644
--- a/litellm/integrations/otel/model/payloads.py
+++ b/litellm/integrations/otel/model/payloads.py
@@ -6,6 +6,7 @@ import json
 from collections.abc import Mapping
 from dataclasses import dataclass, field
 from enum import Enum
+from types import MappingProxyType
 from typing import TYPE_CHECKING, ClassVar, Final, cast
 from urllib.parse import urlsplit
 
@@ -62,6 +63,31 @@ if TYPE_CHECKING:
 # --- typed sub-structures ---------------------------------------------------- #
 
 
+def _cache_token_value(*values: object) -> int | None:
+    explicit_zero = False
+    invalid_before_zero = False
+    for raw_value in values:
+        if raw_value is None:
+            continue
+        if isinstance(raw_value, bool):
+            parsed = None
+        else:
+            try:
+                parsed = as_int(raw_value)
+            except (OverflowError, ValueError):
+                parsed = None
+        if parsed is None:
+            if not explicit_zero:
+                invalid_before_zero = True
+        elif parsed > 0:
+            return parsed
+        elif parsed == 0:
+            explicit_zero = True
+        elif not explicit_zero:
+            invalid_before_zero = True
+    return 0 if explicit_zero and not invalid_before_zero else None
+
+
 @dataclass(frozen=True)
 class LLMRequestParams:
     temperature: float | None = None
@@ -95,6 +121,35 @@ class LLMUsage:
     input_tokens: int | None = None
     output_tokens: int | None = None
     total_tokens: int | None = None
+    cache_creation_input_tokens: int | None = None
+    cache_read_input_tokens: int | None = None
+
+    @classmethod
+    def from_standard_logging_payload(cls, payload: StandardLoggingPayload) -> LLMUsage:
+        # Cache token counts only exist on the raw provider usage object under metadata
+        metadata: Final[Mapping[str, object]] = payload.get("metadata") or {}
+        raw_usage: Final = metadata.get("usage_object")
+        usage_object: Final[Mapping[str, object]] = raw_usage if isinstance(raw_usage, Mapping) else {}
+        raw_details: Final = usage_object.get("prompt_tokens_details")
+        prompt_details: Final[Mapping[str, object]] = (
+            raw_details if isinstance(raw_details, Mapping) else MappingProxyType({})
+        )
+        return cls(
+            input_tokens=as_int(payload.get("prompt_tokens")),
+            output_tokens=as_int(payload.get("completion_tokens")),
+            total_tokens=as_int(payload.get("total_tokens")),
+            cache_creation_input_tokens=_cache_token_value(
+                usage_object.get("cache_creation_input_tokens"),
+                prompt_details.get("cache_write_tokens"),
+                prompt_details.get("cache_creation_tokens"),
+                prompt_details.get("cache_creation_input_tokens"),
+            ),
+            cache_read_input_tokens=_cache_token_value(
+                usage_object.get("cache_read_input_tokens"),
+                prompt_details.get("cached_tokens"),
+                usage_object.get("prompt_cache_hit_tokens"),
+            ),
+        )
 
 
 @dataclass(frozen=True)
@@ -363,11 +418,7 @@ class LLMCallSpanData:
             response_model=context.response_model,
             response_id=as_str(response.get("id")),
             request_params=LLMRequestParams.from_model_parameters(params),
-            usage=LLMUsage(
-                input_tokens=as_int(payload.get("prompt_tokens")),
-                output_tokens=as_int(payload.get("completion_tokens")),
-                total_tokens=as_int(payload.get("total_tokens")),
-            ),
+            usage=LLMUsage.from_standard_logging_payload(payload),
             finish_reasons=finish_reasons,
             error=_parse_error(payload),
             response_cost=as_float(payload.get("response_cost")),
diff --git a/litellm/integrations/otel/model/request_io.py b/litellm/integrations/otel/model/request_io.py
new file mode 100644
index 00000000000..4e80fb91993
--- /dev/null
+++ b/litellm/integrations/otel/model/request_io.py
@@ -0,0 +1,90 @@
+from collections.abc import Mapping, Sequence
+from typing import Final, Literal
+
+from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, ValidationError
+from typing_extensions import ReadOnly, TypedDict
+
+import litellm
+from litellm.integrations.otel.mappers.utils import json_or_none
+from litellm.proxy.guardrails.anthropic_sse import assemble_anthropic_sse_stream, is_raw_sse_stream
+from litellm.types.llms.openai import ResponseCompletedEvent, ResponsesAPIResponse
+from litellm.types.utils import ModelResponse, ModelResponseStream
+
+_SYSTEM_KEYS: Final = ("system", "instructions")
+_TURNS: Final = TypeAdapter(tuple[object, ...])
+_MESSAGES: Final = TypeAdapter(list[object] | None)
+
+
+class _Turn(TypedDict):
+    role: ReadOnly[str]
+    content: ReadOnly[object]
+
+
+class _AnthropicMessage(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    type: Literal["message"] = Field(exclude=True)
+    role: str = "assistant"
+    content: object = None
+
+
+def request_input(data: Mapping[str, object]) -> str | None:
+    turns: Final = data.get("messages", data.get("input"))
+    if turns is None:
+        return None
+    return json_or_none((*_system_turns(data), *_user_turns(turns)))
+
+
+def _system_turns(data: Mapping[str, object]) -> tuple[_Turn, ...]:
+    return tuple(_Turn(role="system", content=data[key]) for key in _SYSTEM_KEYS if data.get(key) is not None)
+
+
+def _user_turns(turns: object) -> tuple[object, ...]:
+    if isinstance(turns, str):
+        return (_Turn(role="user", content=turns),)
+    try:
+        return _TURNS.validate_python(turns)
+    except ValidationError:
+        return (_Turn(role="user", content=turns),)
+
+
+def response_output(response: object) -> str | None:
+    match response:
+        case ModelResponse():
+            return json_or_none(tuple(choice.message.model_dump(exclude_none=True) for choice in response.choices))
+        case ResponsesAPIResponse():
+            return json_or_none(response.model_dump(exclude_none=True).get("output"))
+        case _:
+            return _anthropic_message_output(response)
+
+
+def _anthropic_message_output(message: object) -> str | None:
+    try:
+        parsed: Final = _AnthropicMessage.model_validate(message)
+    except ValidationError:
+        return None
+    return json_or_none((parsed.model_dump(),))
+
+
+def stream_output(chunks: Sequence[object], data: Mapping[str, object]) -> str | None:
+    if not chunks:
+        return None
+    if is_raw_sse_stream(chunks):
+        return response_output(assemble_anthropic_sse_stream(chunks))
+    if all(isinstance(chunk, ModelResponseStream) for chunk in chunks):
+        return response_output(_assembled_chat_stream(chunks, data))
+    return response_output(_completed_response(chunks))
+
+
+def _assembled_chat_stream(chunks: Sequence[object], data: Mapping[str, object]) -> object:
+    try:
+        return litellm.stream_chunk_builder(  # pyright: ignore[reportUnknownMemberType]  # upstream types chunks as a bare list
+            chunks=list(chunks),  # mutable-ok: stream_chunk_builder takes a list
+            messages=_MESSAGES.validate_python(data.get("messages")),
+        )
+    except (litellm.APIError, ValidationError):
+        return None
+
+
+def _completed_response(chunks: Sequence[object]) -> ResponsesAPIResponse | None:
+    return next((chunk.response for chunk in reversed(chunks) if isinstance(chunk, ResponseCompletedEvent)), None)
diff --git a/litellm/integrations/otel/model/semconv.py b/litellm/integrations/otel/model/semconv.py
index 4ad0cb5d1b4..f7a6280f95b 100644
--- a/litellm/integrations/otel/model/semconv.py
+++ b/litellm/integrations/otel/model/semconv.py
@@ -110,6 +110,8 @@ class GenAI:
     # usage
     USAGE_INPUT_TOKENS: Final = "gen_ai.usage.input_tokens"
     USAGE_OUTPUT_TOKENS: Final = "gen_ai.usage.output_tokens"
+    USAGE_CACHE_CREATION_INPUT_TOKENS: Final = "gen_ai.usage.cache_creation.input_tokens"
+    USAGE_CACHE_READ_INPUT_TOKENS: Final = "gen_ai.usage.cache_read.input_tokens"
     # content (opt-in, gated by capture mode)
     INPUT_MESSAGES: Final = "gen_ai.input.messages"
     OUTPUT_MESSAGES: Final = "gen_ai.output.messages"
diff --git a/litellm/integrations/otel/plumbing/metrics.py b/litellm/integrations/otel/plumbing/metrics.py
index c7e491c002a..e1623f4697f 100644
--- a/litellm/integrations/otel/plumbing/metrics.py
+++ b/litellm/integrations/otel/plumbing/metrics.py
@@ -11,9 +11,10 @@ identical metrics. The attribute cardinality filter is reused from v1 by import
 from collections.abc import Mapping
 from dataclasses import dataclass
 from datetime import datetime
-from typing import Any, Final, TypeAlias
+from typing import Any, Final, Literal, Protocol, TypeAlias
 
 from opentelemetry.metrics import Histogram, Meter
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -151,6 +152,29 @@ METRIC_ATTRIBUTE_CEILING: Final[frozenset[str]] = frozenset(
 BOUNDED_HIDDEN_PARAM_KEYS: Final[tuple[str, ...]] = ("model_id",)
 
 
+class _TokenUsage(TypedDict, total=False):
+    """The token counts a response's ``usage`` carries, as the recorder reads them."""
+
+    prompt_tokens: ReadOnly[int]
+    completion_tokens: ReadOnly[int]
+
+
+class _ResponseView(Protocol):
+    """The one read the recorder makes on a litellm response object."""
+
+    def get(self, key: Literal["usage"], /) -> _TokenUsage | None: ...
+
+
+class _MetricKwargs(TypedDict, total=False):
+    """The logging kwargs the recorder reads directly."""
+
+    call_type: ReadOnly[str | None]
+    litellm_params: ReadOnly[Mapping[str, object] | None]
+    response_cost: ReadOnly[float | None]
+    completion_start_time: ReadOnly[datetime | float | str | None]
+    api_call_start_time: ReadOnly[datetime | float | str | None]
+
+
 def resolve_error_type(kwargs: Mapping[str, Any]) -> str:
     """The ``error.type`` value for a failed request.
 
@@ -192,8 +216,8 @@ class GenAIMetricRecorder:
 
     def record(
         self,
-        kwargs: Mapping[str, Any],
-        response_obj: Any,
+        kwargs: _MetricKwargs,
+        response_obj: _ResponseView | None,
         start_time: datetime,
         end_time: datetime,
     ) -> None:
@@ -218,7 +242,7 @@ class GenAIMetricRecorder:
 
     def record_failure(
         self,
-        kwargs: Mapping[str, Any],
+        kwargs: _MetricKwargs,
         start_time: datetime,
         end_time: datetime,
     ) -> None:
@@ -342,7 +366,7 @@ class GenAIMetricRecorder:
     #  Per-metric recording
     # ------------------------------------------------------------------ #
 
-    def _record_token_usage(self, response_obj: Any, common_attrs: dict) -> None:
+    def _record_token_usage(self, response_obj: _ResponseView | None, common_attrs: dict) -> None:
         if not response_obj:
             return
         usage: Final = response_obj.get("usage")
@@ -353,7 +377,7 @@ class GenAIMetricRecorder:
         self._metrics.token_usage.record(usage.get("prompt_tokens", 0), attributes=in_attrs)
         self._metrics.token_usage.record(usage.get("completion_tokens", 0), attributes=out_attrs)
 
-    def _record_time_to_first_token(self, kwargs: Mapping[str, Any], common_attrs: dict) -> None:
+    def _record_time_to_first_token(self, kwargs: _MetricKwargs, common_attrs: dict) -> None:
         time_to_first_chunk: Final = time_to_first_chunk_seconds(kwargs)
         if time_to_first_chunk is None:
             return
@@ -361,15 +385,14 @@ class GenAIMetricRecorder:
 
     def _record_time_per_output_token(
         self,
-        kwargs: Mapping[str, Any],
-        response_obj: Any,
+        kwargs: _MetricKwargs,
+        response_obj: _ResponseView | None,
         end_time: datetime,
         duration_s: float,
         common_attrs: dict,
     ) -> None:
-        completion_tokens = None
-        if response_obj and (usage := response_obj.get("usage")):
-            completion_tokens = usage.get("completion_tokens")
+        usage: Final = response_obj.get("usage") if response_obj else None
+        completion_tokens: Final = usage.get("completion_tokens") if usage else None
         if completion_tokens is None or completion_tokens <= 0:
             return
 
diff --git a/litellm/integrations/posthog.py b/litellm/integrations/posthog.py
index db9610a5a3c..4f7dff952e6 100644
--- a/litellm/integrations/posthog.py
+++ b/litellm/integrations/posthog.py
@@ -12,7 +12,10 @@ For batching specific details see CustomBatchLogger class
 import asyncio
 import atexit
 import os
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Final
+
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_logger
 from litellm._uuid import uuid
@@ -34,6 +37,21 @@ from litellm.types.integrations.posthog import (
 from litellm.types.utils import StandardCallbackDynamicParams, StandardLoggingPayload
 
 
+class PostHogBatchPayload(TypedDict):
+    api_key: ReadOnly[str]
+    batch: ReadOnly[Sequence[PostHogEventPayload]]
+
+
+class PostHogLiteLLMParams(TypedDict, total=False):
+    metadata: ReadOnly[Mapping[str, object]]
+
+
+class PostHogLogKwargs(TypedDict, total=False):
+    standard_logging_object: ReadOnly[StandardLoggingPayload]
+    standard_callback_dynamic_params: ReadOnly[StandardCallbackDynamicParams]
+    litellm_params: ReadOnly[PostHogLiteLLMParams]
+
+
 class PostHogLogger(CustomBatchLogger):
     def __init__(self, **kwargs):
         """
@@ -137,7 +155,7 @@ class PostHogLogger(CustomBatchLogger):
         if len(self.log_queue) >= self.batch_size:
             await self.flush_queue()
 
-    def create_posthog_event_payload(self, kwargs: dict[str, Any]) -> PostHogEventPayload:
+    def create_posthog_event_payload(self, kwargs: PostHogLogKwargs) -> PostHogEventPayload:
         """
         Helper function to create a PostHog event payload for logging
 
@@ -171,11 +189,11 @@ class PostHogLogger(CustomBatchLogger):
     def _create_posthog_properties(
         self,
         standard_logging_object: StandardLoggingPayload,
-        kwargs: dict[str, Any],
+        kwargs: PostHogLogKwargs,
         event_name: str,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Create PostHog properties following LLM Analytics spec"""
-        properties: Final = {}
+        properties: Final[dict[str, object]] = {}
 
         # Core model information
         properties["$ai_model"] = self._safe_get(standard_logging_object, "model", "")
@@ -211,16 +229,19 @@ class PostHogLogger(CustomBatchLogger):
                 properties["$ai_error"] = error_str
 
         # Add trace properties
-        self._add_trace_properties(properties, kwargs)
+        self._add_trace_properties(properties, standard_logging_object, kwargs)
 
         # Add custom metadata fields
         self._add_custom_metadata_properties(properties, kwargs)
 
         return properties
 
-    def _add_trace_properties(self, properties: dict[str, Any], kwargs: dict[str, Any]):
-        standard_logging_object: Final = self._safe_get(kwargs, "standard_logging_object", {})
-
+    def _add_trace_properties(
+        self,
+        properties: dict[str, object],
+        standard_logging_object: StandardLoggingPayload,
+        kwargs: PostHogLogKwargs,
+    ) -> None:
         trace_id: Final = self._safe_get(standard_logging_object, "trace_id", self._safe_uuid())
         properties["$ai_trace_id"] = trace_id
 
@@ -232,7 +253,7 @@ class PostHogLogger(CustomBatchLogger):
         if parent_id:
             properties["$ai_parent_id"] = parent_id
 
-    def _add_custom_metadata_properties(self, properties: dict[str, Any], kwargs: dict[str, Any]):
+    def _add_custom_metadata_properties(self, properties: dict[str, object], kwargs: PostHogLogKwargs) -> None:
         """Add custom metadata fields to PostHog properties"""
         metadata: Final = self._extract_metadata(kwargs)
         if not isinstance(metadata, dict):
@@ -277,7 +298,7 @@ class PostHogLogger(CustomBatchLogger):
             if key not in litellm_internal_fields:
                 properties[key] = value
 
-    def _get_distinct_id(self, standard_logging_object: StandardLoggingPayload, kwargs: dict[str, Any]) -> str:
+    def _get_distinct_id(self, standard_logging_object: StandardLoggingPayload, kwargs: PostHogLogKwargs) -> str:
         metadata: Final = self._extract_metadata(kwargs)
         user_id: Final = self._safe_get(metadata, "user_id")
         if user_id:
@@ -291,7 +312,7 @@ class PostHogLogger(CustomBatchLogger):
 
         return self._safe_uuid()
 
-    def _get_credentials_for_request(self, kwargs: dict[str, Any]) -> tuple[str | None, str | None]:
+    def _get_credentials_for_request(self, kwargs: PostHogLogKwargs) -> tuple[str | None, str | None]:
         """
         Get PostHog credentials for this request.
 
@@ -334,7 +355,7 @@ class PostHogLogger(CustomBatchLogger):
                 verbose_logger.debug("[POSTHOG MOCK] Mock mode enabled - API calls will be intercepted")
 
             # Group events by credentials for batch sending
-            batches_by_credentials: Final[dict[tuple[str, str], list]] = {}
+            batches_by_credentials: Final[dict[tuple[str, str], list[PostHogEventPayload]]] = {}
             for item in self.log_queue:
                 key = (item["api_key"], item["api_url"])
                 if key not in batches_by_credentials:
@@ -380,18 +401,19 @@ class PostHogLogger(CustomBatchLogger):
                 verbose_logger.error("PostHog: Failed to initialize async components: %s", e)
                 raise
 
-    def _extract_metadata(self, kwargs: dict[str, Any]) -> dict[str, Any]:
-        litellm_params: Final = kwargs.get("litellm_params", {}) or {}
-        return litellm_params.get("metadata", {}) or {}
+    def _extract_metadata(self, kwargs: PostHogLogKwargs) -> Mapping[str, object]:
+        litellm_params: Final[PostHogLiteLLMParams] = kwargs.get("litellm_params", {}) or {}
+        metadata: Final[Mapping[str, object]] = litellm_params.get("metadata", {}) or {}
+        return metadata
 
     def _safe_uuid(self) -> str:
         return str(uuid.uuid4())
 
-    def _create_posthog_payload(self, events: list, api_key: str) -> dict[str, Any]:
+    def _create_posthog_payload(self, events: Sequence[PostHogEventPayload], api_key: str) -> PostHogBatchPayload:
         return {"api_key": api_key, "batch": events}
 
-    def _safe_get(self, obj: Any, key: str, default: Any = None) -> Any:
-        if obj is None or not hasattr(obj, "get"):
+    def _safe_get(self, obj: Mapping[str, object] | None, key: str, default: object = None) -> object:
+        if not isinstance(obj, Mapping):
             return default
         return obj.get(key, default)
 
@@ -412,7 +434,7 @@ class PostHogLogger(CustomBatchLogger):
 
         try:
             # Group events by credentials (same logic as async_send_batch)
-            batches_by_credentials: Final[dict[tuple[str, str], list]] = {}
+            batches_by_credentials: Final[dict[tuple[str, str], list[PostHogEventPayload]]] = {}
             for item in self.log_queue:
                 key = (item["api_key"], item["api_url"])
                 if key not in batches_by_credentials:
diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 467ec72dc4a..975a9bd8639 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -8,6 +8,7 @@ import math
 import os
 import sys
 from collections.abc import Awaitable, Callable, Mapping, Sequence
+from dataclasses import replace
 from datetime import datetime, timedelta
 from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeVar, cast
 
@@ -58,7 +59,10 @@ from litellm.types.utils import (
 
 if TYPE_CHECKING:
     from apscheduler.schedulers.asyncio import AsyncIOScheduler
+    from prometheus_client import Gauge
     from prometheus_client.metrics import MetricWrapperBase
+
+    from litellm.router import Router
 else:
     AsyncIOScheduler = Any
 
@@ -67,6 +71,8 @@ _TableRowT: Final = TypeVar("_TableRowT", bound=BaseModel)
 
 _DEFAULT_BUDGET_METRICS_PER_REQUEST_TIMEOUT: Final = 5.0
 
+UNRECOGNIZED_REQUESTED_MODEL_LABEL: Final = "other"
+
 _NON_ENUM_METRIC_LABELS: Final[frozenset[str]] = frozenset(
     (
         "guardrail_name",
@@ -154,6 +160,44 @@ def _get_budget_metrics_per_request_timeout() -> float:
     return parsed
 
 
+def _get_proxy_llm_router() -> Router | None:
+    try:
+        from litellm.proxy.proxy_server import llm_router
+    except Exception:
+        return None
+    return llm_router
+
+
+def _bounded_requested_model_label(requested_model: str | None, router_originated: bool = False) -> str | None:
+    """
+    Bound ``requested_model`` label cardinality: names the router recognizes
+    (model names, deployment ids, aliases, routing groups, team public model
+    names) or matches via a global or team wildcard/pattern route keep their
+    own label value; any other client-supplied string collapses into the
+    single ``other`` bucket. With no proxy router to vouch for the string,
+    client-supplied values collapse to ``other`` while ``router_originated``
+    values (emitted by an SDK ``Router``'s own deployment failure and
+    fallback events, where the proxy router never exists) pass through.
+    """
+    if not requested_model:
+        return requested_model
+    llm_router: Final = _get_proxy_llm_router()
+    if llm_router is None:
+        return requested_model if router_originated else UNRECOGNIZED_REQUESTED_MODEL_LABEL
+    if llm_router.is_recognized_model(requested_model):
+        return requested_model
+    if requested_model in llm_router.team_public_model_names:
+        return requested_model
+    if llm_router.pattern_router.route(requested_model) is not None:
+        return requested_model
+    if any(
+        team_pattern_router.route(requested_model) is not None
+        for team_pattern_router in llm_router.team_pattern_routers.values()
+    ):
+        return requested_model
+    return UNRECOGNIZED_REQUESTED_MODEL_LABEL
+
+
 class PrometheusLogger(CustomLogger):
     # Class variables or attributes
 
@@ -434,6 +478,30 @@ class PrometheusLogger(CustomLogger):
                 labelnames=self.get_labels_for_metric("litellm_remaining_api_key_tokens_for_model"),
             )
 
+            self.litellm_api_key_rate_limit_allowed_metric = self._gauge_factory(
+                "litellm_api_key_rate_limit_allowed_metric",
+                "Configured rate limit for the API Key in the current window (rpm_limit / tpm_limit), by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_api_key_rate_limit_allowed_metric"),
+            )
+
+            self.litellm_api_key_rate_limit_used_metric = self._gauge_factory(
+                "litellm_api_key_rate_limit_used_metric",
+                "Requests or tokens the API Key has consumed in the current rate limit window, by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_api_key_rate_limit_used_metric"),
+            )
+
+            self.litellm_team_rate_limit_allowed_metric = self._gauge_factory(
+                "litellm_team_rate_limit_allowed_metric",
+                "Configured rate limit for the Team in the current window (team rpm_limit / tpm_limit), by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_team_rate_limit_allowed_metric"),
+            )
+
+            self.litellm_team_rate_limit_used_metric = self._gauge_factory(
+                "litellm_team_rate_limit_used_metric",
+                "Requests or tokens the Team has consumed in the current rate limit window, by rate_limit_type",
+                labelnames=self.get_labels_for_metric("litellm_team_rate_limit_used_metric"),
+            )
+
             ########################################
             # LLM API Deployment Metrics / analytics
             ########################################
@@ -1433,6 +1501,11 @@ class PrometheusLogger(CustomLogger):
             model_id=enum_values.model_id,
         )
 
+        self._set_key_and_team_rate_limit_metrics(
+            standard_logging_payload=standard_logging_payload,  # pyright: ignore[reportArgumentType]  # isinstance(dict) above narrows the TypedDict to dict[Unknown, Unknown]
+            enum_values=enum_values,
+        )
+
         # set latency metrics
         self._set_latency_metrics(
             kwargs=kwargs,
@@ -1960,17 +2033,102 @@ class PrometheusLogger(CustomLogger):
         """
         if standard_logging_payload is None:
             return None
+        return PrometheusLogger._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-model_per_key-remaining-{rate_limit_type}",
+        )
+
+    @staticmethod
+    def _get_int_from_v3_rate_limit_headers(
+        standard_logging_payload: StandardLoggingPayload,
+        header_name: str,
+    ) -> int | None:
         hidden_params: Final = standard_logging_payload.get("hidden_params")
         if hidden_params is None:
             return None
-        additional_headers: Final = hidden_params.get("additional_headers")
+        additional_headers: Final[Mapping[str, object] | None] = hidden_params.get("additional_headers")
         if additional_headers is None:
             return None
-        value: Final = dict(additional_headers).get(f"x-ratelimit-model_per_key-remaining-{rate_limit_type}")
+        value: Final = additional_headers.get(header_name)
         if isinstance(value, bool) or not isinstance(value, int):
             return None
         return value
 
+    def _set_key_and_team_rate_limit_metrics(
+        self,
+        standard_logging_payload: StandardLoggingPayload,
+        enum_values: UserAPIKeyLabelValues,
+    ) -> None:
+        """
+        Export the key-level and team-level RPM / TPM limit and current window
+        usage from the ``x-ratelimit-{api_key,team}-{limit,remaining}-*``
+        headers the v3 rate limiter mirrors into the logging payload. The
+        limiter already read these counters (from Redis when configured) on
+        the request path, so no extra store lookup happens here. Descriptors
+        without a configured limit emit no header, so their series is removed
+        rather than left at the value from before the limit was dropped.
+        """
+        descriptor_gauges: Final[
+            tuple[tuple[Literal["api_key", "team"], DEFINED_PROMETHEUS_METRICS, Gauge, Gauge], ...]
+        ] = (
+            (
+                "api_key",
+                "litellm_api_key_rate_limit_allowed_metric",
+                self.litellm_api_key_rate_limit_allowed_metric,
+                self.litellm_api_key_rate_limit_used_metric,
+            ),
+            (
+                "team",
+                "litellm_team_rate_limit_allowed_metric",
+                self.litellm_team_rate_limit_allowed_metric,
+                self.litellm_team_rate_limit_used_metric,
+            ),
+        )
+        for descriptor_key, metric_name, allowed_gauge, used_gauge in descriptor_gauges:
+            for rate_limit_type in ("requests", "tokens"):
+                self._set_rate_limit_allowed_and_used_gauges(
+                    standard_logging_payload=standard_logging_payload,
+                    enum_values=enum_values,
+                    descriptor_key=descriptor_key,
+                    metric_name=metric_name,
+                    allowed_gauge=allowed_gauge,
+                    used_gauge=used_gauge,
+                    rate_limit_type=rate_limit_type,
+                )
+
+    def _set_rate_limit_allowed_and_used_gauges(
+        self,
+        standard_logging_payload: StandardLoggingPayload,
+        enum_values: UserAPIKeyLabelValues,
+        descriptor_key: Literal["api_key", "team"],
+        metric_name: DEFINED_PROMETHEUS_METRICS,
+        allowed_gauge: Gauge,
+        used_gauge: Gauge,
+        rate_limit_type: Literal["requests", "tokens"],
+    ) -> None:
+        limit: Final = self._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-{descriptor_key}-limit-{rate_limit_type}",
+        )
+        remaining: Final = self._get_int_from_v3_rate_limit_headers(
+            standard_logging_payload=standard_logging_payload,
+            header_name=f"x-ratelimit-{descriptor_key}-remaining-{rate_limit_type}",
+        )
+        labelled_values: Final = replace(enum_values, rate_limit_type=rate_limit_type)
+        labelnames: Final = self.get_labels_for_metric(metric_name)
+        labels: Final = prometheus_label_factory(
+            supported_enum_labels=labelnames,
+            enum_values=labelled_values,
+            label_context=PrometheusLabelFactoryContext(labelled_values),
+        )
+        if limit is None or remaining is None:
+            label_values: Final = tuple(labels.get(label) for label in labelnames)
+            self._bounded_prometheus_series_tracker.remove_series(allowed_gauge, label_values)
+            self._bounded_prometheus_series_tracker.remove_series(used_gauge, label_values)
+            return
+        allowed_gauge.labels(**labels).set(limit)
+        used_gauge.labels(**labels).set(limit - remaining)
+
     def _set_virtual_key_rate_limit_metrics(
         self,
         user_api_key: str | None,
@@ -2407,7 +2565,7 @@ class PrometheusLogger(CustomLogger):
                 team_alias=user_api_key_dict.team_alias,
                 org_id=user_api_key_dict.org_id,
                 org_alias=user_api_key_dict.organization_alias,
-                requested_model=request_data.get("model", ""),
+                requested_model=_bounded_requested_model_label(request_data.get("model", "")),
                 status_code=str(status_code),
                 exception_status=str(status_code),
                 exception_class=self._get_exception_class_name(original_exception),
@@ -2627,7 +2785,9 @@ class PrometheusLogger(CustomLogger):
                 label_model_id = ""
                 label_api_base = ""
                 label_api_provider = ""
-                label_requested_model = litellm_model_name or model_group or ""
+                label_requested_model = (
+                    _bounded_requested_model_label(litellm_model_name or model_group, router_originated=True) or ""
+                )
 
             enum_values: Final = UserAPIKeyLabelValues(
                 litellm_model_name=label_litellm_model_name,
@@ -3186,7 +3346,7 @@ class PrometheusLogger(CustomLogger):
         _tags: Final = cast(list[str], kwargs.get("tags") or [])
 
         enum_values: Final = UserAPIKeyLabelValues(
-            requested_model=original_model_group,
+            requested_model=_bounded_requested_model_label(original_model_group, router_originated=True),
             fallback_model=_new_model,
             hashed_api_key=standard_metadata["user_api_key_hash"],
             api_key_alias=standard_metadata["user_api_key_alias"],
@@ -3227,7 +3387,7 @@ class PrometheusLogger(CustomLogger):
         )
 
         enum_values: Final = UserAPIKeyLabelValues(
-            requested_model=original_model_group,
+            requested_model=_bounded_requested_model_label(original_model_group, router_originated=True),
             fallback_model=_new_model,
             hashed_api_key=standard_metadata["user_api_key_hash"],
             api_key_alias=standard_metadata["user_api_key_alias"],
diff --git a/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py b/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
index c54790b8ae7..c1ccf09d5d6 100644
--- a/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
+++ b/litellm/integrations/prometheus_helpers/bounded_prometheus_series_tracker.py
@@ -60,6 +60,10 @@ class BoundedPrometheusSeriesTracker:
                         break
                     del series[tracked_label_values]
 
+    def remove_series(self, metric: object, label_values: tuple[str | None, ...]) -> bool:
+        """Drop one child series, True when it is gone (removed or never existed)."""
+        return self._remove_metric_child(metric, label_values)
+
     def _should_run_ttl_cleanup(
         self,
         metric_name: str,
diff --git a/litellm/integrations/rubrik.py b/litellm/integrations/rubrik.py
index a474a11601d..c9e511905a6 100644
--- a/litellm/integrations/rubrik.py
+++ b/litellm/integrations/rubrik.py
@@ -8,11 +8,12 @@ import uuid
 from collections import Counter
 from collections.abc import Awaitable, Mapping, Sequence
 from dataclasses import dataclass
+from datetime import datetime
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypedDict
+from typing import TYPE_CHECKING, Final, Literal, Optional, Protocol, TypedDict, overload
 
 import httpx
-from typing_extensions import Never, ReadOnly
+from typing_extensions import Never, ReadOnly, Required
 
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_batch_logger import CustomBatchLogger
@@ -30,6 +31,7 @@ from litellm.llms.custom_httpx.http_handler import (
     httpxSpecialProvider,
 )
 from litellm.types.guardrails import GuardrailEventHooks
+from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolCallChunk
 from litellm.types.utils import (
     ChatCompletionMessageToolCall,
     Function,
@@ -52,17 +54,102 @@ _DROP_WARNING_INTERVAL_SECONDS: Final = 60.0
 _EMPTY_MAPPING: Final[Mapping[str, Never]] = MappingProxyType({})
 
 
-class _ServiceToolCall(TypedDict):
-    id: ReadOnly[str]
+class _ModerationToolCall(TypedDict, total=False):
+    id: ReadOnly[Required[str]]
 
 
-class _ServiceMessage(TypedDict, total=False):
+class _ModerationMessage(TypedDict, total=False):
+    content: ReadOnly[str | None]
+    tool_calls: ReadOnly[Sequence[_ModerationToolCall] | None]
+
+
+class _ModerationChoice(TypedDict, total=False):
+    message: ReadOnly[_ModerationMessage | None]
+
+
+class _ModerationResponse(TypedDict, total=False):
+    choices: ReadOnly[Sequence[_ModerationChoice]]
+
+
+class _LogEventKwargs(TypedDict, total=False):
+    standard_logging_object: ReadOnly[Required[StandardLoggingPayload]]
+    litellm_call_id: ReadOnly[str]
+
+
+class _HasCallId(Protocol):
+    def get(self, key: Literal["litellm_call_id"], /) -> str | None: ...
+
+
+class _HasModelAttr(Protocol):
+    model: str | None
+
+
+class _ResponseSource(Protocol):
+    def get(self, key: Literal["response"], /) -> "_HasModelAttr | None": ...
+
+
+class _ModelSource(Protocol):
+    def get(self, key: Literal["model"], default: str, /) -> str: ...
+
+
+class _FallbackSource(Protocol):
+    @overload
+    def get(self, key: Literal["start_time"], /) -> datetime | None: ...
+    @overload
+    def get(self, key: str, /) -> object | None: ...
+
+
+class _RequestContextSource(Protocol):
+    @overload
+    def get(self, key: Literal["optional_params"], /) -> Mapping[str, object] | None: ...
+    @overload
+    def get(self, key: str, /) -> object | None: ...
+    def __contains__(self, key: object, /) -> bool: ...
+    def __getitem__(self, key: str, /) -> object: ...
+
+
+class _ToolCallLike(Protocol):
+    id: str | None
+    type: str | None
+    function: Function
+
+
+class _ModerationSourceToolCall(TypedDict, total=False):
+    function: ReadOnly[Mapping[str, object] | None]
+
+
+class _ModerationSourceMessage(TypedDict, total=False):
+    role: ReadOnly[str]
+    function_call: ReadOnly[Mapping[str, object] | None]
+    tool_calls: ReadOnly[Sequence[_ModerationSourceToolCall | None] | None]
+
+
+class _FlattenedModerationMessage(TypedDict):
+    role: ReadOnly[str | None]
     content: ReadOnly[str]
-    tool_calls: ReadOnly[Sequence[_ServiceToolCall]]
 
 
-class _ServiceChoice(TypedDict, total=False):
-    message: ReadOnly[_ServiceMessage]
+class _CorrelatablePayload(TypedDict):
+    id: str  # writable-ok: _apply_correlation_id overwrites the provider id on a deep-copied payload
+
+
+class _SystemPromptCarrier(TypedDict, total=False):
+    messages: object  # writable-ok: _prepend_system_prompt rebinds messages on the copied payload by design
+
+
+class _BlockFailurePayload(TypedDict, total=False):
+    id: object  # writable-ok: correlation id is pinned after copying the base payload
+    model: ReadOnly[object]
+    model_group: ReadOnly[object]
+    model_id: ReadOnly[str]
+    model_parameters: ReadOnly[object]
+    startTime: ReadOnly[float | None]
+    endTime: ReadOnly[float | None]
+    completionStartTime: ReadOnly[float | None]
+    messages: object  # writable-ok: passed to _prepend_system_prompt, which rebinds messages
+    metadata: ReadOnly[StandardLoggingUserAPIKeyMetadata]
+    response: str  # writable-ok: block failure text replaces the copied response
+    status: ReadOnly[str]
 
 
 class _MalformedToolBlockingResponseError(Exception):
@@ -385,7 +472,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
     @staticmethod
     def _stash_block_context(
         logging_obj: Optional["LiteLLMLoggingObj"],
-        request_data: dict,
+        request_data: dict[str, object],
     ) -> None:
         """Stash signals so the deferred success-event skips this request and
         ``async_post_call_failure_hook`` can build the failure payload.
@@ -414,12 +501,16 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         request_data["_rubrik_logging_obj"] = logging_obj
 
     @staticmethod
-    def _normalize_tool_calls(tool_calls: Sequence[object]) -> tuple[ChatCompletionMessageToolCall, ...]:
+    def _normalize_tool_calls(
+        tool_calls: Sequence[ChatCompletionToolCallChunk | ChatCompletionMessageToolCall | _ToolCallLike],
+    ) -> tuple[ChatCompletionMessageToolCall, ...]:
         """Convert tool_calls from inputs to ChatCompletionMessageToolCall objects."""
         return tuple(RubrikLogger._normalize_tool_call(tc) for tc in tool_calls)
 
     @staticmethod
-    def _normalize_tool_call(tc: Any) -> ChatCompletionMessageToolCall:
+    def _normalize_tool_call(
+        tc: ChatCompletionToolCallChunk | ChatCompletionMessageToolCall | _ToolCallLike,
+    ) -> ChatCompletionMessageToolCall:
         if isinstance(tc, ChatCompletionMessageToolCall):
             return tc
         if isinstance(tc, dict):
@@ -460,12 +551,15 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         ``content`` is sent so the webhook can moderate the response text;
         ``None`` when the assistant produced no text (tool-call-only response).
         """
-        message: Final[dict[str, object]] = {
+        message: Final[Mapping[str, object]] = {
             "role": "assistant",
             "content": content or None,
+            **(
+                {"tool_calls": tuple(tc.model_dump(exclude_none=True) for tc in tool_calls)}
+                if tool_calls
+                else _EMPTY_MAPPING
+            ),
         }
-        if tool_calls:
-            message["tool_calls"] = tuple(tc.model_dump(exclude_none=True) for tc in tool_calls)
         return {
             "id": request_id or f"chatcmpl-{uuid.uuid4()}",
             "object": "chat.completion",
@@ -481,7 +575,9 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         }
 
     @staticmethod
-    def _flatten_messages_for_moderation(messages: Sequence[object] | None) -> tuple[Mapping[str, Any], ...]:
+    def _flatten_messages_for_moderation(
+        messages: Sequence[AllMessageValues | None] | None,
+    ) -> tuple[_FlattenedModerationMessage, ...]:
         """Collapse each message's content to a plain string for the webhook.
 
         litellm normalizes Anthropic ``/v1/messages`` requests to OpenAI shape,
@@ -502,7 +598,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         )
 
     @staticmethod
-    def _moderation_text_parts(message: Mapping[str, Any]) -> tuple[str, ...]:
+    def _moderation_text_parts(message: _ModerationSourceMessage) -> tuple[str, ...]:
         """Every attacker-controlled text segment of a message: its content plus
         the arguments of any tool call or deprecated function call."""
         fc: Final = message.get("function_call")
@@ -530,16 +626,8 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         ``/v1/messages`` requests too. Optional fields are sent only when
         present so the payload stays clean.
         """
-        payload: Final[dict[str, object]] = {
-            "model": inputs.get("model") or request_data.get("model") or "",
-            "messages": RubrikLogger._flatten_messages_for_moderation(inputs.get("structured_messages")),
-        }
         tools: Final = inputs.get("tools")
-        if tools is not None:
-            payload["tools"] = tools
         user: Final = request_data.get("user")
-        if user:
-            payload["user"] = user
         # Fall back to litellm_call_id, the stable cross-provider join key the
         # response/tool path uses (see _correlation_id). LiteLLM does not
         # populate request_data["correlation_key"]; it carries litellm_call_id.
@@ -547,14 +635,18 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         # when correlation_key is empty, so without this the block fires but no
         # log is ever written. An explicit correlation_key still wins.
         correlation_key: Final = request_data.get("correlation_key") or request_data.get("litellm_call_id")
-        if correlation_key:
-            payload["correlation_key"] = correlation_key
-        return payload
+        return {
+            "model": inputs.get("model") or request_data.get("model") or "",
+            "messages": RubrikLogger._flatten_messages_for_moderation(inputs.get("structured_messages")),
+            **({"tools": tools} if tools is not None else _EMPTY_MAPPING),
+            **({"user": user} if user else _EMPTY_MAPPING),
+            **({"correlation_key": correlation_key} if correlation_key else _EMPTY_MAPPING),
+        }
 
     @staticmethod
     def _extract_request_data(
-        call_details: Mapping[str, Any],
-        request_data: Mapping[str, object] | None,
+        call_details: _RequestContextSource,
+        request_data: _RequestContextSource | None,
     ) -> Mapping[str, object]:
         """Extract original request data from model_call_details for the
         response moderation service envelope.
@@ -590,7 +682,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         }
 
     @staticmethod
-    def _sanitize_proxy_server_request(proxy_server_request: object) -> object:
+    def _sanitize_proxy_server_request(proxy_server_request: Mapping[str, object] | str | None) -> object:
         """Allowlist only routing fields (``url``, ``method``) when forwarding
         ``proxy_server_request`` to an external webhook, dropping inbound
         ``headers`` (Authorization, Cookie, x-api-key, ...) and the raw
@@ -600,18 +692,19 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         return {key: proxy_server_request[key] for key in ("url", "method") if key in proxy_server_request}
 
     @staticmethod
-    def _resolve_model(request_data: Mapping[str, object], call_details: Mapping[str, str]) -> str:
+    def _resolve_model(request_data: _ResponseSource, call_details: _ModelSource) -> str:
         """Get the model name for the ModifyResponseException."""
         response: Final = request_data.get("response")
         if response and hasattr(response, "model"):
-            response_model: Final[str | None] = getattr(response, "model", None)
-            return response_model or "unknown"
+            return response.model or "unknown"
         return call_details.get("model", "unknown")
 
     # -- Logging hooks ---------------------------------------------------------
 
     @staticmethod
-    def _correlation_id(call_details: Mapping[str, str], request_data: Mapping[str, str] | None = None) -> str | None:
+    def _correlation_id(
+        call_details: _HasCallId | _LogEventKwargs, request_data: _HasCallId | None = None
+    ) -> str | None:
         """The id that joins a blocked request's two S3 logs by filename: the
         moderation (``_blocking``) log and the failure (response) log.
 
@@ -625,7 +718,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         return call_details.get("litellm_call_id") or (request_data or _EMPTY_MAPPING).get("litellm_call_id")
 
     @classmethod
-    def _apply_correlation_id(cls, payload: dict[str, object], source: Mapping[str, str]) -> None:
+    def _apply_correlation_id(cls, payload: _CorrelatablePayload, source: _HasCallId | _LogEventKwargs) -> None:
         """Pin ``payload["id"]`` to ``litellm_call_id`` in place so this log
         shares its S3 filename id with the moderation (``_blocking``) and
         failure logs for the same request -- for every provider.
@@ -645,7 +738,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
             payload["id"] = correlated
 
     @staticmethod
-    def _prepend_system_prompt(payload: dict[str, object], source: Mapping[str, object]) -> None:
+    def _prepend_system_prompt(payload: _SystemPromptCarrier, source: Mapping[str, object]) -> None:
         """Prepend ``source["system"]`` onto ``payload["messages"]``.
 
         Builds a NEW messages list rather than mutating ``payload["messages"]``
@@ -673,9 +766,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
                 exc_info=True,
             )
 
-    async def _prepare_log_payload(
-        self, kwargs: Mapping[str, object], event_type: str
-    ) -> StandardLoggingPayload | None:
+    async def _prepare_log_payload(self, kwargs: _LogEventKwargs, event_type: str) -> StandardLoggingPayload | None:
         """Shared logic for success logging (sampled)."""
         if random.random() > self.sampling_rate:
             verbose_logger.debug("Skipping Rubrik %s logging (sampling_rate=%s)", event_type, self.sampling_rate)
@@ -684,12 +775,12 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         # Deep-copy so mutations don't affect other callbacks sharing this object
         standard_logging_payload: Final[StandardLoggingPayload] = safe_deep_copy(kwargs["standard_logging_object"])
 
-        self._apply_correlation_id(standard_logging_payload, kwargs)  # pyright: ignore[reportArgumentType]  # StandardLoggingPayload is dict[str,Any] at runtime
+        self._apply_correlation_id(standard_logging_payload, kwargs)
         self._prepend_system_prompt(standard_logging_payload, kwargs)  # pyright: ignore[reportArgumentType]  # StandardLoggingPayload is dict[str,Any] at runtime
 
         return standard_logging_payload
 
-    async def _append_and_maybe_flush(self, payload) -> None:
+    async def _append_and_maybe_flush(self, payload: Mapping[str, object]) -> None:
         self._ensure_periodic_flush_task()
         self.log_queue.append(payload)
         self._enforce_max_queue_size()
@@ -714,7 +805,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
             self._dropped_since_warning = 0
             self._last_drop_warning_time = now
 
-    async def _enqueue_log_event(self, kwargs: Mapping[str, object], event_type: str):
+    async def _enqueue_log_event(self, kwargs: _LogEventKwargs, event_type: str):
         try:
             payload: Final = await self._prepare_log_payload(kwargs, event_type)
             if payload is None:
@@ -835,7 +926,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         logging_obj: "LiteLLMLoggingObj",
         exception: "ModifyResponseException",
         user_api_key_dict: "UserAPIKeyAuth",
-    ) -> StandardLoggingPayload:
+    ) -> _BlockFailurePayload:
         """Build a failure-style payload using the exception text as response.
 
         Blocked-tool events are security-relevant and **bypass sampling**:
@@ -877,9 +968,9 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         call_details: Final = logging_obj.model_call_details
         exception_text: Final = f"{type(exception).__name__}: {exception.message}"
 
-        base: Final = call_details.get("standard_logging_object")
+        base: Final[StandardLoggingPayload | None] = call_details.get("standard_logging_object")
         if base is not None:
-            payload: dict[str, object] = safe_deep_copy(base)
+            payload: _BlockFailurePayload = self._copy_block_payload_base(base)
         else:
             verbose_logger.debug(
                 "Rubrik: standard_logging_object not yet on model_call_details "
@@ -901,6 +992,10 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
 
         return payload
 
+    @staticmethod
+    def _copy_block_payload_base(base: StandardLoggingPayload) -> _BlockFailurePayload:
+        return safe_deep_copy(base)
+
     @staticmethod
     def _caller_metadata(user_api_key_dict: "UserAPIKeyAuth") -> StandardLoggingUserAPIKeyMetadata:
         """Identify the caller whose request was blocked.
@@ -923,9 +1018,9 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
     @classmethod
     def _build_fallback_payload(
         cls,
-        call_details: Mapping[str, Any],
+        call_details: _FallbackSource,
         user_api_key_dict: "UserAPIKeyAuth",
-    ) -> dict[str, object]:
+    ) -> _BlockFailurePayload:
         # Convert datetime to a Unix float so json.dumps can serialize it.
         # httpx's json= parameter uses stdlib json.dumps with no custom encoder.
         _raw_start: Final = call_details.get("start_time")
@@ -959,7 +1054,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
             response: Final = await self.async_httpx_client.post(
                 url=self.logging_endpoint,
                 json=data,
-                headers=self._headers,
+                headers=dict(self._headers),
             )
             response.raise_for_status()
         except httpx.HTTPStatusError as e:
@@ -1013,7 +1108,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
 
     # -- Webhook services ------------------------------------------------------
 
-    async def _post_json(self, endpoint: str, payload: Mapping[str, object], service_name: str) -> Mapping[str, Any]:
+    async def _post_json(self, endpoint: str, payload: Mapping[str, object], service_name: str) -> _ModerationResponse:
         """POST ``payload`` to a Rubrik webhook and return its dict response.
 
         Raises:
@@ -1023,11 +1118,11 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         verbose_logger.debug("Sending request to %s: %s", service_name, endpoint)
         http_response: Final = await self.moderation_client.post(
             endpoint,
-            json=payload,
-            headers=self._headers,
+            json=dict(payload),
+            headers=dict(self._headers),
         )
         http_response.raise_for_status()
-        result: Final[object] = http_response.json()
+        result: Final[_ModerationResponse | None] = http_response.json()
         if not isinstance(result, dict):
             raise TypeError(
                 f"{service_name} returned non-dict JSON "
@@ -1040,7 +1135,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         self,
         response_data: Mapping[str, object],
         request_data: Mapping[str, object],
-    ) -> Mapping[str, Any]:
+    ) -> _ModerationResponse:
         """Post the ``{request, response}`` envelope to the after_completion
         webhook and return its (possibly rewritten) response.
 
@@ -1056,7 +1151,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
             "Response moderation service",
         )
 
-    async def _post_to_prompt_moderation_endpoint(self, payload: Mapping[str, object]) -> Mapping[str, Any]:
+    async def _post_to_prompt_moderation_endpoint(self, payload: Mapping[str, object]) -> _ModerationResponse:
         """Post a bare OpenAI request to the before_prompt webhook.
 
         Returns ``{}`` (passthrough) or a synthetic chat.completion (block).
@@ -1064,14 +1159,14 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         return await self._post_json(self.prompt_moderation_endpoint, payload, "Prompt moderation service")
 
     @staticmethod
-    def _extract_prompt_refusal(service_response: Mapping[str, Any]) -> str | None:
+    def _extract_prompt_refusal(service_response: _ModerationResponse) -> str | None:
         """Return the refusal text when the prompt was blocked, else None.
 
         The before_prompt webhook returns ``{}`` (passthrough) or a synthetic
         chat.completion whose ``choices[0].message.content`` is the refusal
         explanation.
         """
-        choices: Final[Sequence[_ServiceChoice] | None] = service_response.get("choices")
+        choices: Final = service_response.get("choices")
         if not choices:
             return None
         message: Final = choices[0].get("message") or _EMPTY_MAPPING
@@ -1080,7 +1175,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
 
     @staticmethod
     def _extract_response_block(
-        service_response: Mapping[str, Any],
+        service_response: _ModerationResponse,
         all_tool_calls: Sequence[ChatCompletionMessageToolCall],
         sent_content: str,
     ) -> BlockedResponseResult | None:
@@ -1103,7 +1198,7 @@ class RubrikLogger(CustomGuardrail, CustomBatchLogger):
         Expects service_response in OpenAI chat completion format:
             {"choices": [{"message": {"tool_calls": [...], "content": "..."}}]}
         """
-        choices: Final[Sequence[_ServiceChoice]] = service_response.get("choices") or ()
+        choices: Final = service_response.get("choices") or ()
         if not choices:
             raise _MalformedToolBlockingResponseError("Response moderation service returned empty response")
 
diff --git a/litellm/integrations/s3.py b/litellm/integrations/s3.py
index ddeb410c54a..8ce461eea5b 100644
--- a/litellm/integrations/s3.py
+++ b/litellm/integrations/s3.py
@@ -1,11 +1,18 @@
 #### What this does ####
 #    On success + failure, log events to Supabase
 
+import hashlib
 from datetime import datetime
 from typing import Final, cast
 
 import litellm
 from litellm._logging import print_verbose, verbose_logger
+from litellm.constants import (
+    MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES,
+    MAX_S3_OBJECT_KEY_BYTES,
+    S3_BOUNDED_OBJECT_KEY_HEAD_BYTES,
+    S3_PREFIX_DIGEST_CHARS,
+)
 from litellm.types.utils import StandardLoggingPayload
 
 
@@ -133,9 +140,7 @@ class S3Logger:
                 s3_file_name,
             )
 
-            s3_object_download_filename: Final = (
-                "time-" + start_time.strftime("%Y-%m-%dT%H-%M-%S-%f") + "_" + payload["id"] + ".json"
-            )
+            s3_object_download_filename: Final = get_s3_object_download_filename(start_time, payload["id"])
 
             from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
 
@@ -198,6 +203,47 @@ def resolve_sse_params(
     return algorithm, valid_key_id
 
 
+S3_MIN_BOUNDED_FILE_NAME_BYTES: Final = 64
+
+
+def _truncate_to_utf8_bytes(value: str, max_bytes: int) -> str:
+    """Trim `value` so its UTF-8 encoding fits `max_bytes`, never splitting a character."""
+    if max_bytes <= 0:
+        return ""
+    encoded: Final = value.encode("utf-8")
+    if len(encoded) <= max_bytes:
+        return value
+    return encoded[:max_bytes].decode("utf-8", errors="ignore")
+
+
+def get_s3_object_download_filename(start_time: datetime, response_id: str) -> str:
+    """Content-Disposition filename for the uploaded object, bounded to the metadata header cap."""
+    sanitized_response_id: Final = response_id.replace("/", "_").replace('"', "_")
+    file_name: Final = f"time-{start_time.strftime('%Y-%m-%dT%H-%M-%S-%f')}_{response_id}"
+    sanitized_file_name: Final = f"time-{start_time.strftime('%Y-%m-%dT%H-%M-%S-%f')}_{sanitized_response_id}"
+    budget: Final = MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES - len(b".json")
+    if len(sanitized_file_name.encode("utf-8")) <= budget:
+        return sanitized_file_name + ".json"
+    return _bounded_s3_file_name(file_name, sanitized_file_name, budget) + ".json"
+
+
+def _bounded_s3_file_name(s3_file_name: str, sanitized_s3_file_name: str, max_bytes: int) -> str:
+    """As much of the file name as `max_bytes` allows, then the sha256 of the whole name."""
+    digest: Final = hashlib.sha256(s3_file_name.encode("utf-8")).hexdigest()
+    head_budget: Final = min(S3_BOUNDED_OBJECT_KEY_HEAD_BYTES, max_bytes - len(digest) - 1)
+    head: Final = _truncate_to_utf8_bytes(sanitized_s3_file_name, head_budget)
+    return f"{head}_{digest}" if head else digest
+
+
+def _bounded_s3_prefix(configured_prefix: str, max_bytes: int) -> str:
+    """As much of the configured prefix as fits, then a digest segment naming the full prefix."""
+    digest_segment: Final = hashlib.sha256(configured_prefix.encode("utf-8")).hexdigest()[:S3_PREFIX_DIGEST_CHARS] + "/"
+    if max_bytes < len(digest_segment):
+        return ""
+    head: Final = _truncate_to_utf8_bytes(configured_prefix, max_bytes - len(digest_segment) - 1).rstrip("/")
+    return f"{head}/{digest_segment}" if head else digest_segment
+
+
 def get_s3_object_key(
     s3_path: str,
     prefix: str,
@@ -205,12 +251,23 @@ def get_s3_object_key(
     s3_file_name: str,
 ) -> str:
     sanitized_s3_file_name: Final = s3_file_name.replace("/", "_")
-    s3_object_key = (
-        (s3_path.rstrip("/") + "/" if s3_path else "")
-        + prefix
-        + start_time.strftime("%Y-%m-%d")
-        + "/"
-        + sanitized_s3_file_name
-    )  # we need the s3 key to include the time, so we log cache hits too
-    s3_object_key += ".json"
-    return s3_object_key
+    configured_prefix: Final = (s3_path.rstrip("/") + "/" if s3_path else "") + prefix
+    date_segment: Final = start_time.strftime("%Y-%m-%d") + "/"
+    # we need the s3 key to include the time, so we log cache hits too
+    s3_object_key: Final = configured_prefix + date_segment + sanitized_s3_file_name + ".json"
+    if len(s3_object_key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES:
+        return s3_object_key
+
+    # shorten the response id first and only trim the configured prefix if that is what does not
+    # fit, so prefix scoped IAM policies and lifecycle rules keep matching
+    budget: Final = MAX_S3_OBJECT_KEY_BYTES - len(date_segment.encode("utf-8")) - len(b".json")
+    prefix_bytes: Final = len(configured_prefix.encode("utf-8"))
+    if prefix_bytes + S3_MIN_BOUNDED_FILE_NAME_BYTES <= budget:
+        bounded_file_name: Final = _bounded_s3_file_name(s3_file_name, sanitized_s3_file_name, budget - prefix_bytes)
+        return configured_prefix + date_segment + bounded_file_name + ".json"
+
+    shortest_file_name: Final = _bounded_s3_file_name(
+        s3_file_name, sanitized_s3_file_name, S3_MIN_BOUNDED_FILE_NAME_BYTES
+    )
+    bounded_prefix: Final = _bounded_s3_prefix(configured_prefix, budget - len(shortest_file_name.encode("utf-8")))
+    return bounded_prefix + date_segment + shortest_file_name + ".json"
diff --git a/litellm/integrations/s3_v2.py b/litellm/integrations/s3_v2.py
index 9f6ae72fb3a..712ce41d09e 100644
--- a/litellm/integrations/s3_v2.py
+++ b/litellm/integrations/s3_v2.py
@@ -16,7 +16,11 @@ from urllib.parse import quote
 import litellm
 from litellm._logging import print_verbose, verbose_logger
 from litellm.constants import DEFAULT_S3_BATCH_SIZE, DEFAULT_S3_FLUSH_INTERVAL_SECONDS
-from litellm.integrations.s3 import get_s3_object_key, resolve_sse_params
+from litellm.integrations.s3 import (
+    get_s3_object_download_filename,
+    get_s3_object_key,
+    resolve_sse_params,
+)
 from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
 from litellm.litellm_core_utils.sensitive_data_masker import SensitiveDataMasker
@@ -259,11 +263,11 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM):
             now: Final = datetime.now(timezone.utc)
             audit_log_id: Final = audit_log.get("id", "unknown")
 
-            s3_path = cast(str | None, self.s3_path) or ""
-            s3_path = s3_path.rstrip("/") + "/" if s3_path else ""
-
-            s3_object_key: Final = (
-                f"{s3_path}audit_logs/{now.strftime('%Y-%m-%d')}/{now.strftime('%H-%M-%S')}_{audit_log_id}.json"
+            s3_object_key: Final = get_s3_object_key(
+                cast(str | None, self.s3_path) or "",
+                "audit_logs/",
+                now,
+                f"{now.strftime('%H-%M-%S')}_{audit_log_id}",
             )
 
             element: Final = s3BatchLoggingElement(
@@ -463,9 +467,7 @@ class S3Logger(CustomBatchLogger, BaseAWSLLM):
         )
         verbose_logger.debug("s3_object_key=%s", s3_object_key)
 
-        s3_object_download_filename: Final = (
-            f"time-{start_time.strftime('%Y-%m-%dT%H-%M-%S-%f')}_{standard_logging_payload['id']}.json"
-        )
+        s3_object_download_filename: Final = get_s3_object_download_filename(start_time, standard_logging_payload["id"])
 
         return s3BatchLoggingElement(
             payload=dict(standard_logging_payload),
diff --git a/litellm/integrations/shadow_eval_logger.py b/litellm/integrations/shadow_eval_logger.py
index cf8aa38d86e..27da785331a 100644
--- a/litellm/integrations/shadow_eval_logger.py
+++ b/litellm/integrations/shadow_eval_logger.py
@@ -1,8 +1,11 @@
 """Shadow Eval Logger: samples a shadowed key's successful LLM requests (chat completions,
 Anthropic Messages, and Responses API surfaces, each normalized to chat shape), duplicates
-each against the job's other arm in a detached task (the auto-router for a forward job, the
-fixed baseline model for a reverse one), blind-judges real vs shadow, and appends one
-``LiteLLM_ShadowEvalAttempt`` row (verdict or error) as the feature's only hot-path write.
+each through every shadow arm in one detached task (each candidate auto-router for a
+forward job, the fixed baseline model for a reverse one), blind-judges real vs each arm,
+and appends one ``LiteLLM_ShadowEvalAttempt`` row per arm (verdict or error) as the
+feature's only hot-path write. A multi-router job's arms therefore score the identical
+sampled requests against the identical real responses, which is what makes their win
+rates comparable head-to-head.
 Counts, status, and spend derive from those rows at read time, so nothing can disagree
 across pods or stop races; the hook reads active jobs through a short-TTL cache."""
 
@@ -498,12 +501,16 @@ def _decision_classifier_cost(metadata: Mapping[str, object]) -> float:
     return float(raw) if isinstance(raw, (int, float)) else 0.0
 
 
-def _request_was_routed_by(request_metadata: Mapping[str, object], router_name: str) -> bool:
-    """Whether the router under evaluation served this request, which is what decides
-    the direction it belongs to. A forward job skips its own router's traffic, since
-    duplicating it would compare the router to itself: guaranteed ties, judge spend for
-    zero information. A reverse job samples exactly that traffic and nothing else."""
-    return _routing_decision(request_metadata).get("router_model_name") == router_name
+def _direction_admits(request_metadata: Mapping[str, object], job: "ActiveShadowEvalJob") -> bool:
+    """Whether this request belongs to the job's direction. A forward job skips traffic
+    any of its candidate routers served: duplicating a router's own request compares it
+    to itself (guaranteed ties), and judging a sibling against another candidate's live
+    response would score candidates against each other instead of against the incumbent.
+    A reverse job samples exactly its one router's traffic and nothing else."""
+    routed_by: Final = _routing_decision(request_metadata).get("router_model_name")
+    if job.direction == "reverse":
+        return routed_by == job.router_name
+    return routed_by not in job.arm_router_names
 
 
 @dataclass(frozen=True, slots=True)
@@ -546,6 +553,7 @@ class ActiveShadowEvalJob(BaseModel):
 
     id: str
     router_name: str
+    router_names: tuple[str, ...] = ()
     direction: ShadowEvalDirection = "forward"
     baseline_model: str | None = None
     shadow_percentage: float
@@ -567,12 +575,25 @@ class ActiveShadowEvalJob(BaseModel):
             raise ValueError("baseline_model is set for exactly the reverse jobs")
         return self
 
+    @model_validator(mode="after")
+    def _reverse_evaluates_one_router(self) -> "ActiveShadowEvalJob":
+        """A reverse row naming several routers is unsamplable (there is no one traffic
+        slice they share) and fails closed."""
+        if self.direction == "reverse" and len(self.arm_router_names) > 1:
+            raise ValueError("a reverse job evaluates exactly one router")
+        return self
+
     @property
-    def shadow_target(self) -> str:
-        """The model the duplicated arm calls: the router itself for a forward job, the
-        fixed baseline for a reverse one. Total because the validator above pins
+    def arm_router_names(self) -> tuple[str, ...]:
+        """The job's full router set; rows from before router_names existed hold it in
+        router_name alone. The one place that reading lives on the sampling side."""
+        return self.router_names or (self.router_name,)
+
+    def arm_target(self, arm_router: str) -> str:
+        """The model one duplicated arm calls: the candidate router itself for a forward
+        job, the fixed baseline for a reverse one. Total because the validator above pins
         baseline_model to reverse jobs and only those."""
-        return self.baseline_model or self.router_name
+        return self.baseline_model or arm_router
 
 
 def _as_active_job(record: object, attempts: int, spend: float) -> ActiveShadowEvalJob | None:
@@ -592,7 +613,12 @@ _JOBS_CACHE_KEY: Final = "shadow_eval:active_jobs"
 
 
 class ShadowEvalLogger(CustomLogger):
-    """Fires blind pairwise shadow evaluations for keys with an active shadow-eval job."""
+    """Fires blind pairwise shadow evaluations for targets with an active shadow-eval job.
+
+    A job targets a virtual key, a team, or a user; a request qualifies for a job when
+    any of its resolved identities (key hash, team id, user id) matches the job's
+    target, so team and user jobs cover JWT-authenticated traffic, which carries no
+    key hash at all."""
 
     def __init__(
         self,
@@ -617,10 +643,10 @@ class ShadowEvalLogger(CustomLogger):
         # generation; the refill absorbs written rows and resets.
         self._job_starts: dict[str, int] = {}  # mutable-ok: per-generation counter
 
-    async def _active_jobs(self) -> Mapping[str, tuple[ActiveShadowEvalJob, ...]]:
-        """Active jobs by api_key_id, cache-first. A key holds at most one job per
-        direction, so the value is a collection. A DB fault returns empty without
-        caching, so sampling pauses for that request and the next one retries."""
+    async def _active_jobs(self) -> Mapping[tuple[str, str], tuple[ActiveShadowEvalJob, ...]]:
+        """Active jobs by (target_type, target_id), cache-first. A target holds at most
+        one job per direction, so the value is a collection. A DB fault returns empty
+        without caching, so sampling pauses for that request and the next one retries."""
         cached: Final = await self._jobs_cache.async_get_cache(_JOBS_CACHE_KEY)
         if cached is not None:
             return cached  # pyright: ignore[reportReturnType]  # cache stores exactly this mapping shape
@@ -652,10 +678,10 @@ class ShadowEvalLogger(CustomLogger):
                 )
                 for row in grouped or []
             }
-            by_key: Final = tuple(
+            by_target: Final = tuple(
                 sorted(
                     (
-                        (str(record.api_key_id), job)
+                        ((str(record.target_type), str(record.target_id)), job)
                         for record in records or []
                         if (job := _as_active_job(record, *attempt_stats.get(str(record.id), (0, 0.0)))) is not None
                     ),
@@ -663,7 +689,7 @@ class ShadowEvalLogger(CustomLogger):
                 )
             )
             jobs: Final = MappingProxyType(
-                {key: tuple(job for _, job in group) for key, group in groupby(by_key, key=itemgetter(0))}
+                {target: tuple(job for _, job in group) for target, group in groupby(by_target, key=itemgetter(0))}
             )
             await self._jobs_cache.async_set_cache(_JOBS_CACHE_KEY, jobs)
             self._job_starts = {}  # rebind-ok: new generation, counts absorbed into the fill
@@ -691,7 +717,7 @@ class ShadowEvalLogger(CustomLogger):
                 now >= job.ends_at
                 or job.attempts + self._job_starts.get(job.id, 0) >= job.max_turns
                 or (job.max_budget is not None and job.spend >= job.max_budget)
-                or _request_was_routed_by(request_metadata, job.router_name) != (job.direction == "reverse")
+                or not _direction_admits(request_metadata, job)
             ):
                 continue
             if not _sample_hits(request_id, job.id, job.shadow_percentage):
@@ -720,8 +746,18 @@ class ShadowEvalLogger(CustomLogger):
             if should_redact_message_logging(dict(kwargs)):  # mutable-ok: predicate takes a plain dict
                 return
             metadata: Final = payload.get("metadata") or _EMPTY_METADATA
-            api_key_hash: Final = metadata.get("user_api_key_hash")
-            if not api_key_hash:
+            # Each identity the request resolved to is a candidate target; JWT-auth
+            # requests carry no key hash but do carry a team and user.
+            targets: Final = tuple(
+                (target_type, str(value))
+                for target_type, value in (
+                    ("key", metadata.get("user_api_key_hash")),
+                    ("team", metadata.get("user_api_key_team_id")),
+                    ("user", metadata.get("user_api_key_user_id")),
+                )
+                if value
+            )
+            if not targets:
                 return
             request_id: Final = payload.get("id") or ""
             if not request_id:
@@ -731,8 +767,11 @@ class ShadowEvalLogger(CustomLogger):
                 return  # only surfaces this table can normalize are comparable; unknown types fail closed
             if ops.wire_params and _request_mutating_guardrail_ran(request_metadata):
                 return  # the wire-body snapshot predates the rewrite; replaying it would resurrect stripped content
+            active_jobs: Final = await self._active_jobs()
             eligible: Final = self._sampled_jobs(
-                (await self._active_jobs()).get(str(api_key_hash), ()), request_metadata, request_id
+                tuple(job for target in targets for job in active_jobs.get(target, ())),
+                request_metadata,
+                request_id,
             )
             if not eligible:
                 return
@@ -755,7 +794,10 @@ class ShadowEvalLogger(CustomLogger):
                 if self._inflight_shadow_tasks >= _MAX_CONCURRENT_SHADOW_TASKS:
                     self._record_funnel(job.id, "shed")
                     continue
-                self._job_starts[job.id] = self._job_starts.get(job.id, 0) + 1
+                # One start writes one attempt row per arm, and max_turns is a row
+                # ceiling, so admission must pre-count every arm or a multi-router
+                # job overshoots the valve N-fold within a cache generation.
+                self._job_starts[job.id] = self._job_starts.get(job.id, 0) + len(job.arm_router_names)
                 self._inflight_shadow_tasks += 1
                 asyncio.create_task(
                     self._run_shadow_eval(
@@ -794,32 +836,74 @@ class ShadowEvalLogger(CustomLogger):
         shadow_params: Mapping[str, object],
         parent_metadata: Mapping[str, object],
     ) -> None:
-        """Budget gate -> shadow call -> blind judge -> one attempt row, and every exit
-        in exactly one coverage bucket: the gates that decline to spend on an admitted
-        sample (no DB to record into, an over-budget key, an unverifiable or exhausted
-        eval budget) count it withheld, so eligible traffic still reconciles as
-        not_sampled + unjudgeable + shed + withheld + attempt rows. The prisma gate sits
-        above the dispatch so no provider spend happens without a place to record the
-        outcome, and the budget read lives here rather than in the success hook."""
+        """Budget gates once per sampled request, then every router arm in turn: shadow
+        call -> blind judge -> one attempt row stamped with the arm. The gates that
+        decline to spend on an admitted sample (no DB to record into, an over-budget key,
+        an unverifiable or exhausted eval budget) count the REQUEST withheld before any
+        arm runs, so funnel counters stay per-request and a leg's eligible traffic still
+        reconciles as not_sampled + unjudgeable + shed + withheld + sampled requests,
+        where each sampled request writes one attempt row per arm. A budget crossed
+        mid-loop lets the remaining arms overshoot by one round, the same class of
+        overshoot as the samples already in flight when the cap is crossed. The prisma
+        gate sits above the dispatch so no provider spend happens without a place to
+        record the outcome, and the budget read lives here rather than in the success
+        hook."""
         prisma: Final = self._prisma_provider()
+        if prisma is None:
+            self._record_funnel(job.id, "withheld")
+            return
+        if await _key_or_team_is_over_budget(parent_metadata):
+            self._record_funnel(job.id, "withheld")
+            return
+        if job.max_budget is not None:
+            try:
+                spend: Final = await self._read_job_spend(_job_spend_counter_key(job.id), job.spend, job.max_budget)
+            except Exception as e:  # noqa: BLE001  # unverifiable budget: skip the sample rather than spend on it
+                verbose_logger.warning("shadow_eval: budget unverifiable for %s, sample skipped: %s", job.id, e)
+                self._record_funnel(job.id, "withheld")
+                return
+            if spend >= job.max_budget:
+                self._record_funnel(job.id, "withheld")
+                return
+        for arm_router in job.arm_router_names:
+            await self._run_shadow_arm(
+                prisma=prisma,
+                job=job,
+                arm_router=arm_router,
+                request_id=request_id,
+                messages=messages,
+                real_text=real_text,
+                real_model=real_model,
+                real_cost=real_cost,
+                real_classifier_cost=real_classifier_cost,
+                real_cache_hit=real_cache_hit,
+                control_tier=control_tier,
+                shadow_params=shadow_params,
+                parent_metadata=parent_metadata,
+            )
+
+    async def _run_shadow_arm(
+        self,
+        prisma: "PrismaClient",
+        job: ActiveShadowEvalJob,
+        arm_router: str,
+        request_id: str,
+        messages: Sequence[Mapping[str, object]],
+        real_text: str,
+        real_model: str,
+        real_cost: float,
+        real_classifier_cost: float,
+        real_cache_hit: bool,
+        control_tier: str | None,
+        shadow_params: Mapping[str, object],
+        parent_metadata: Mapping[str, object],
+    ) -> None:
+        """One arm's pipeline: shadow call -> blind judge -> one attempt row, every exit
+        recording this arm's outcome, so one arm's fault never silences a sibling arm."""
         try:
-            if prisma is None:
-                self._record_funnel(job.id, "withheld")
-                return
-            if await _key_or_team_is_over_budget(parent_metadata):
-                self._record_funnel(job.id, "withheld")
-                return
-            if job.max_budget is not None:
-                try:
-                    spend: Final = await self._read_job_spend(_job_spend_counter_key(job.id), job.spend, job.max_budget)
-                except Exception as e:  # noqa: BLE001  # unverifiable budget: skip the sample rather than spend on it
-                    verbose_logger.warning("shadow_eval: budget unverifiable for %s, sample skipped: %s", job.id, e)
-                    self._record_funnel(job.id, "withheld")
-                    return
-                if spend >= job.max_budget:
-                    self._record_funnel(job.id, "withheld")
-                    return
-            shadow: Final = await self._call_router_shadow(job.shadow_target, messages, shadow_params, parent_metadata)
+            shadow: Final = await self._call_router_shadow(
+                job.arm_target(arm_router), messages, shadow_params, parent_metadata
+            )
         except Exception as e:  # noqa: BLE001  # detached task: nothing billed yet, record and never raise
             verbose_logger.debug("shadow_eval: pipeline failed for %s: %s", request_id, e)
             await self._record_attempt(
@@ -827,6 +911,7 @@ class ShadowEvalLogger(CustomLogger):
                 job,
                 request_id,
                 control_tier,
+                router_name=arm_router,
                 outcome="error",
                 error=f"pipeline error: {e}",
                 real_cost=real_cost,
@@ -840,6 +925,7 @@ class ShadowEvalLogger(CustomLogger):
                 job,
                 request_id,
                 control_tier,
+                router_name=arm_router,
                 outcome="error",
                 error=shadow.error,
                 shadow_cost=shadow.cost,
@@ -864,6 +950,7 @@ class ShadowEvalLogger(CustomLogger):
                     job,
                     request_id,
                     control_tier,
+                    router_name=arm_router,
                     outcome="error",
                     error=verdict.error,
                     shadow=shadow,
@@ -880,6 +967,7 @@ class ShadowEvalLogger(CustomLogger):
                 job,
                 request_id,
                 control_tier,
+                router_name=arm_router,
                 outcome=verdict.preference,
                 shadow=shadow,
                 real_model=real_model,
@@ -898,6 +986,7 @@ class ShadowEvalLogger(CustomLogger):
                 job,
                 request_id,
                 control_tier,
+                router_name=arm_router,
                 outcome="error",
                 error=f"pipeline error: {e}",
                 shadow=shadow,
@@ -915,6 +1004,7 @@ class ShadowEvalLogger(CustomLogger):
         request_id: str,
         control_tier: str | None,
         *,
+        router_name: str,
         outcome: str,
         real_cost: float,
         real_classifier_cost: float,
@@ -937,6 +1027,7 @@ class ShadowEvalLogger(CustomLogger):
                 data={  # mutable-ok: Prisma payload
                     "job_id": job.id,
                     "request_id": request_id,
+                    "router_name": router_name,
                     "outcome": outcome,
                     "tier": control_tier if job.direction == "reverse" else (shadow.tier if shadow else None),
                     "real_model": real_model or None,
@@ -1056,7 +1147,7 @@ class ShadowEvalLogger(CustomLogger):
         )
 
 
-_EMPTY_JOBS: Final[Mapping[str, tuple[ActiveShadowEvalJob, ...]]] = MappingProxyType({})
+_EMPTY_JOBS: Final[Mapping[tuple[str, str], tuple[ActiveShadowEvalJob, ...]]] = MappingProxyType({})
 
 
 def _default_prisma_provider() -> "PrismaClient | None":
diff --git a/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py b/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
index aa29162ba1f..07d4f959489 100644
--- a/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
+++ b/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
@@ -13,7 +13,7 @@ from litellm._logging import verbose_logger
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
 from litellm.types.prompts.init_prompts import PromptSpec
-from litellm.types.utils import StandardCallbackDynamicParams
+from litellm.types.utils import CallTypes, StandardCallbackDynamicParams
 from litellm.types.vector_stores import (
     LiteLLM_ManagedVectorStore,
     VectorStoreResultContent,
@@ -226,7 +226,7 @@ class VectorStorePreCallHook(CustomLogger):
         self,
         request_data: dict,
         response: Any,
-        call_type: Any | None,
+        call_type: CallTypes | None,
     ) -> Any | None:
         """
         Add search results to the response after successful LLM call.
@@ -283,7 +283,7 @@ class VectorStorePreCallHook(CustomLogger):
         self,
         request_data: dict,
         response_chunk: Any,
-        call_type: Any | None,
+        call_type: CallTypes | None,
     ) -> Any | None:
         """
         Add search results to the final streaming chunk.
diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py
index 13a16947fb4..2d737bc34e7 100644
--- a/litellm/integrations/websearch_interception/handler.py
+++ b/litellm/integrations/websearch_interception/handler.py
@@ -10,7 +10,7 @@ import asyncio
 import math
 import uuid
 from collections.abc import AsyncIterator, Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Final, TypedDict, cast
+from typing import TYPE_CHECKING, Any, Final, Literal, Never, TypedDict, TypeVar, cast
 
 from typing_extensions import ReadOnly
 
@@ -46,7 +46,13 @@ from litellm.types.integrations.websearch_interception import (
     AnthropicServerToolUseBlock,
     WebSearchInterceptionConfig,
 )
-from litellm.types.llms.openai import AllMessageValues
+from litellm.types.llms.anthropic import AnthropicThinkingParam
+from litellm.types.llms.openai import (
+    AllMessageValues,
+    ChatCompletionAudioParam,
+    ChatCompletionPredictionContentParam,
+    OpenAIWebSearchOptions,
+)
 from litellm.types.utils import (
     AgenticLoopParams,
     CallTypes,
@@ -56,6 +62,8 @@ from litellm.types.utils import (
 from litellm.utils import ProviderConfigManager
 
 if TYPE_CHECKING:
+    from aiohttp import ClientSession
+
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.llms.base_llm.anthropic_messages.transformation import (
         BaseAnthropicMessagesConfig,
@@ -77,6 +85,10 @@ WEBSEARCH_EMIT_NATIVE_BLOCKS_KEY: Final = "_websearch_interception_emit_native_b
 # ``web_search_tool_result`` blocks to inject into the final response.
 WEBSEARCH_NATIVE_BLOCKS_METADATA_KEY: Final = "websearch_native_blocks"
 
+_RESPONSE_CONTENT_FIELD: Final = "content"
+
+_ResponseT: Final = TypeVar("_ResponseT")
+
 
 class _PlanMetadataView(TypedDict):
     websearch_native_blocks: Sequence[Mapping[str, object]] | None
@@ -90,23 +102,98 @@ class _WebSearchSettingsView(TypedDict):
     websearch_interception_params: WebSearchInterceptionConfig
 
 
+class _SearchToolLitellmParams(TypedDict, total=False):
+    search_provider: ReadOnly[str | None]
+
+
 class _SearchToolConfig(TypedDict, total=False):
     search_tool_name: str
-    litellm_params: Mapping[str, object] | None
+    litellm_params: ReadOnly[_SearchToolLitellmParams | None]
 
 
-class _DeploymentKwargsView(TypedDict):
-    """Typed reads of the untyped request kwargs seen by the deployment hook."""
-
+class _LitellmParamsProviderView(TypedDict, total=False):
     custom_llm_provider: ReadOnly[str]
-    litellm_params: ReadOnly[Mapping[str, object]]
+
+
+class _DeploymentCallKwargsView(TypedDict):
+    custom_llm_provider: ReadOnly[str]
+    litellm_params: ReadOnly[_LitellmParamsProviderView]
     model: ReadOnly[str]
 
 
-class _UserAuthView(TypedDict):
-    """Typed read of the optional team attached to the caller's auth object."""
+class _AcreateNamedParams(TypedDict, total=False):
+    metadata: ReadOnly[Never]
+    stop_sequences: ReadOnly[Never]
+    stream: ReadOnly[bool | None]
+    system: ReadOnly[str | None]
+    temperature: ReadOnly[float | None]
+    thinking: ReadOnly[Never]
+    tool_choice: ReadOnly[Never]
+    tools: ReadOnly[Never]
+    top_k: ReadOnly[int | None]
+    top_p: ReadOnly[float | None]
+    container: ReadOnly[Never]
 
-    team_id: ReadOnly[str | None]
+
+class _AsearchNamedParams(TypedDict, total=False):
+    max_results: ReadOnly[int | None]
+    search_domain_filter: ReadOnly[Never]
+    max_tokens_per_page: ReadOnly[int | None]
+    country: ReadOnly[str | None]
+    api_key: ReadOnly[str | None]
+    api_base: ReadOnly[str | None]
+    timeout: ReadOnly[float | None]
+    extra_headers: ReadOnly[Never]
+
+
+class _AcompletionNamedParams(TypedDict, total=False):
+    functions: ReadOnly[Never]
+    function_call: ReadOnly[str | None]
+    timeout: ReadOnly[float | None]
+    temperature: ReadOnly[float | None]
+    top_p: ReadOnly[float | None]
+    n: ReadOnly[int | None]
+    stream: ReadOnly[bool | None]
+    stream_options: ReadOnly[Never]
+    stop: ReadOnly[Never]
+    max_tokens: ReadOnly[int | None]
+    max_completion_tokens: ReadOnly[int | None]
+    modalities: ReadOnly[Never]
+    prediction: ReadOnly[ChatCompletionPredictionContentParam | None]
+    audio: ReadOnly[ChatCompletionAudioParam | None]
+    presence_penalty: ReadOnly[float | None]
+    frequency_penalty: ReadOnly[float | None]
+    logit_bias: ReadOnly[Never]
+    user: ReadOnly[str | None]
+    response_format: ReadOnly[Never]
+    seed: ReadOnly[int | None]
+    tools: ReadOnly[Never]
+    tool_choice: ReadOnly[Never]
+    parallel_tool_calls: ReadOnly[bool | None]
+    logprobs: ReadOnly[bool | None]
+    top_logprobs: ReadOnly[int | None]
+    deployment_id: ReadOnly[str | None]
+    reasoning_effort: ReadOnly[Literal["none", "minimal", "low", "medium", "high", "xhigh", "default"] | None]
+    verbosity: ReadOnly[Literal["low", "medium", "high"] | None]
+    safety_identifier: ReadOnly[str | None]
+    service_tier: ReadOnly[str | None]
+    store: ReadOnly[bool | None]
+    prompt_cache_key: ReadOnly[str | None]
+    base_url: ReadOnly[str | None]
+    api_version: ReadOnly[str | None]
+    api_key: ReadOnly[str | None]
+    model_list: ReadOnly[Never]
+    extra_headers: ReadOnly[Never]
+    thinking: ReadOnly[AnthropicThinkingParam | None]
+    web_search_options: ReadOnly[OpenAIWebSearchOptions | None]
+    include_server_side_tool_invocations: ReadOnly[bool | None]
+    shared_session: ReadOnly["ClientSession | None"]
+    enable_json_schema_validation: ReadOnly[bool | None]
+
+
+_NO_ACREATE_NAMED: Final[_AcreateNamedParams] = {}
+_NO_ASEARCH_NAMED: Final[_AsearchNamedParams] = {}
+_NO_ACOMPLETION_NAMED: Final[_AcompletionNamedParams] = {}
 
 
 class WebSearchInterceptionLogger(CustomLogger):
@@ -308,17 +395,17 @@ class WebSearchInterceptionLogger(CustomLogger):
         """
         # Check if this is for an enabled provider
         # Try top-level kwargs first, then nested litellm_params, then derive from model name
-        kwargs_view: Final[_DeploymentKwargsView] = {
+        call_kwargs_view: Final[_DeploymentCallKwargsView] = {
             "custom_llm_provider": kwargs.get("custom_llm_provider", ""),
             "litellm_params": kwargs.get("litellm_params", {}),
             "model": kwargs.get("model", ""),
         }
-        custom_llm_provider = kwargs_view["custom_llm_provider"] or kwargs_view["litellm_params"].get(
+        custom_llm_provider = call_kwargs_view["custom_llm_provider"] or call_kwargs_view["litellm_params"].get(
             "custom_llm_provider", ""
         )
         if not custom_llm_provider:
             try:
-                _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=kwargs_view["model"])
+                _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=call_kwargs_view["model"])
             except Exception:
                 custom_llm_provider = ""
         if custom_llm_provider not in self.enabled_providers:
@@ -332,7 +419,6 @@ class WebSearchInterceptionLogger(CustomLogger):
         if call_type in (CallTypes.responses, CallTypes.aresponses):
             return self._convert_responses_tools(kwargs=kwargs, tools=tools)
 
-        # Check if any tool is a web search tool (native or already LiteLLM standard)
         has_websearch: Final = any(is_web_search_tool(t) for t in tools)
 
         if not has_websearch:
@@ -948,17 +1034,17 @@ class WebSearchInterceptionLogger(CustomLogger):
         )
 
     @staticmethod
-    def _inject_native_blocks(response: Any, native_blocks: Sequence[Mapping[str, object]]) -> Any:
+    def _inject_native_blocks(response: _ResponseT, native_blocks: Sequence[Mapping[str, object]]) -> _ResponseT:
         """Prepend native blocks to response content, dict or object form."""
         if not native_blocks:
             return response
         if isinstance(response, dict):
-            existing = response.get("content") or []
-            response["content"] = list(native_blocks) + list(existing)
+            existing = response.get(_RESPONSE_CONTENT_FIELD) or []
+            response[_RESPONSE_CONTENT_FIELD] = list(native_blocks) + list(existing)
             return response
-        existing = getattr(response, "content", None) or []
+        existing = getattr(response, _RESPONSE_CONTENT_FIELD, None) or []
         try:
-            response.content = list(native_blocks) + list(existing)
+            setattr(response, _RESPONSE_CONTENT_FIELD, list(native_blocks) + list(existing))
         except (AttributeError, TypeError):
             # Object refused write — fall through and leave the response
             # untouched rather than crash the request.
@@ -1214,10 +1300,10 @@ class WebSearchInterceptionLogger(CustomLogger):
         messages: list[dict],
         tool_calls: list[dict],
         thinking_blocks: list[dict],
-        anthropic_messages_optional_request_params: dict,
+        anthropic_messages_optional_request_params: Mapping[str, object],
         logging_obj: "LiteLLMLoggingObj | None",
         stream: bool,
-        kwargs: dict,
+        kwargs: Mapping[str, object],
     ) -> "AnthropicMessagesResponse | AsyncIterator[object]":
         """Legacy path: execute search + build patch + run follow-up call."""
         request_patch, structured_results = await self._build_anthropic_request_patch(
@@ -1225,9 +1311,9 @@ class WebSearchInterceptionLogger(CustomLogger):
             messages=messages,
             tool_calls=tool_calls,
             thinking_blocks=thinking_blocks,
-            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
+            anthropic_messages_optional_request_params=dict[str, object](anthropic_messages_optional_request_params),
             logging_obj=logging_obj,
-            kwargs=kwargs,
+            kwargs=dict[str, object](kwargs),
         )
         if request_patch.messages is None:
             raise ValueError("WebSearchInterception: missing follow-up messages")
@@ -1242,12 +1328,14 @@ class WebSearchInterceptionLogger(CustomLogger):
         if max_tokens is None:
             max_tokens = cast(int, kwargs.get("max_tokens", 1024))
 
+        patch_kwargs: Final = dict[str, object](request_patch.kwargs)
         response: AnthropicMessagesResponse | AsyncIterator[object] = await anthropic_messages.acreate(
             max_tokens=max_tokens,
             messages=request_patch.messages,
             model=request_patch.model or model,
+            **_NO_ACREATE_NAMED,
             **optional_params,
-            **request_patch.kwargs,
+            **patch_kwargs,
         )
 
         # Legacy path: the new path goes through the typed plan + core
@@ -1389,12 +1477,13 @@ class WebSearchInterceptionLogger(CustomLogger):
 
             search_tool: Final = self._select_search_tool_from_router(llm_router=llm_router)
             search_provider: str | None = None
-            search_litellm_params: dict[str, Any] = {}
+            search_litellm_params: Mapping[str, object] = {}
             search_tool_name: Final = self._selected_search_tool_name(search_tool=search_tool)
             if search_tool is not None:
                 await self._authorize_search_tool(search_tool=search_tool, kwargs=kwargs)
-                search_litellm_params = dict(search_tool.get("litellm_params", {}) or {})
-                search_provider = search_litellm_params.get("search_provider")
+                tool_params: Final[_SearchToolLitellmParams] = search_tool.get("litellm_params", {}) or {}
+                search_litellm_params = dict[str, object](tool_params)
+                search_provider = tool_params.get("search_provider")
 
             # Fallback to perplexity if no router or no search tools configured
             if not search_provider:
@@ -1422,12 +1511,15 @@ class WebSearchInterceptionLogger(CustomLogger):
                 if key != "search_provider" and value is not None
             }
             result: Final = (
-                await litellm.asearch(query=query, search_provider=search_provider, **search_kwargs)
+                await litellm.asearch(
+                    query=query, search_provider=search_provider, **_NO_ASEARCH_NAMED, **search_kwargs
+                )
                 if search_metadata is None
                 else await litellm.asearch(
                     query=query,
                     search_provider=search_provider,
                     litellm_metadata=search_metadata,
+                    **_NO_ASEARCH_NAMED,
                     **search_kwargs,
                 )
             )
@@ -1467,8 +1559,7 @@ class WebSearchInterceptionLogger(CustomLogger):
             valid_token=user_api_key_auth,
         )
 
-        auth_view: Final[_UserAuthView] = {"team_id": getattr(user_api_key_auth, "team_id", None)}
-        team_id: Final = auth_view["team_id"]
+        team_id: Final[str | None] = getattr(user_api_key_auth, "team_id", None)
         if team_id:
             from litellm.proxy.proxy_server import (
                 prisma_client,
@@ -1541,16 +1632,18 @@ class WebSearchInterceptionLogger(CustomLogger):
     def _select_search_tool_from_router(self, llm_router: object) -> "_SearchToolConfig | None":
         if llm_router is None or not hasattr(llm_router, "search_tools"):
             return None
-        search_tools: Final = list(getattr(llm_router, "search_tools") or [])
+        search_tools: Final = tuple(getattr(llm_router, "search_tools", None) or ())
         return self._select_search_tool_from_list(search_tools=search_tools, source="router")
 
     def _select_search_tool_from_list(
         self,
-        search_tools: list[_SearchToolConfig],
+        search_tools: Sequence[_SearchToolConfig],
         source: str,
     ) -> "_SearchToolConfig | None":
         if self.search_tool_name:
-            matching_tools = [tool for tool in search_tools if tool.get("search_tool_name") == self.search_tool_name]
+            matching_tools: Final = tuple(
+                tool for tool in search_tools if tool.get("search_tool_name") == self.search_tool_name
+            )
             if matching_tools:
                 search_provider = (matching_tools[0].get("litellm_params", {}) or {}).get("search_provider")
                 verbose_logger.debug(
@@ -1583,10 +1676,10 @@ class WebSearchInterceptionLogger(CustomLogger):
         model: str,
         messages: list[dict],
         tool_calls: list[dict],
-        optional_params: dict,
+        optional_params: Mapping[str, object],
         logging_obj: "LiteLLMLoggingObj | None",
         stream: bool,
-        kwargs: dict,
+        kwargs: Mapping[str, object],
         response_format: str = "openai",
     ) -> "ModelResponse | CustomStreamWrapper":
         """Legacy path: execute search + build patch + run follow-up call."""
@@ -1594,8 +1687,8 @@ class WebSearchInterceptionLogger(CustomLogger):
             model=model,
             messages=messages,
             tool_calls=tool_calls,
-            optional_params=optional_params,
-            kwargs=kwargs,
+            optional_params=dict[str, object](optional_params),
+            kwargs=dict[str, object](kwargs),
             response_format=response_format,
         )
         if request_patch.messages is None:
@@ -1603,11 +1696,13 @@ class WebSearchInterceptionLogger(CustomLogger):
         params: Final = dict(optional_params)
         params.update(request_patch.optional_params)
         params.pop("tool_choice", None)
+        patch_kwargs: Final = dict[str, object](request_patch.kwargs)
         return await litellm.acompletion(
             model=request_patch.model or model,
             messages=request_patch.messages,
+            **_NO_ACOMPLETION_NAMED,
             **params,
-            **request_patch.kwargs,
+            **patch_kwargs,
         )
 
     async def _build_chat_completion_request_patch(
diff --git a/litellm/litellm_core_utils/audio_utils/utils.py b/litellm/litellm_core_utils/audio_utils/utils.py
index 3b3775a8fe6..dab3e48f91a 100644
--- a/litellm/litellm_core_utils/audio_utils/utils.py
+++ b/litellm/litellm_core_utils/audio_utils/utils.py
@@ -7,7 +7,13 @@ import os
 from dataclasses import dataclass
 from typing import Final
 
-from litellm.types.files import get_file_mime_type_from_extension
+from litellm.types.files import (
+    AUDIO_FILE_TYPES,
+    FILE_EXTENSIONS,
+    FILE_MIME_TYPES,
+    FileType,
+    get_file_mime_type_from_extension,
+)
 from litellm.types.utils import FileTypes
 
 
@@ -323,3 +329,75 @@ def calculate_request_duration(file: FileTypes) -> float | None:
     except Exception:
         # Silently fail if duration extraction fails
         return None
+
+
+DEFAULT_SPEECH_MEDIA_TYPE: Final = "audio/mpeg"
+
+
+def _speech_media_type_for_response_format(response_format: str) -> str | None:
+    file_type: Final = next(
+        (candidate for candidate, extensions in FILE_EXTENSIONS.items() if response_format.lower() in extensions),
+        None,
+    )
+    if file_type is None or file_type not in AUDIO_FILE_TYPES:
+        return None
+    return FILE_MIME_TYPES[file_type]
+
+
+def resolve_speech_media_type(upstream_content_type: str | None, response_format: str | None) -> str:
+    upstream_media_type: Final = (upstream_content_type or "").split(";", 1)[0].strip().lower()
+    if upstream_media_type.startswith("audio/"):
+        return upstream_media_type
+    requested_media_type: Final = (
+        None if response_format is None else _speech_media_type_for_response_format(response_format)
+    )
+    return requested_media_type or DEFAULT_SPEECH_MEDIA_TYPE
+
+
+_OGG_OPUS_HEAD_WINDOW: Final = 64
+_ADTS_SYNC_AND_LAYER_MASK: Final = 0xF6
+_ADTS_SYNC_AND_LAYER: Final = 0xF0
+_ADTS_SAMPLE_RATE_INDEX_LIMIT: Final = 13
+_MPEG_SYNC_MASK: Final = 0xE0
+_MPEG_LAYER_MASK: Final = 0x06
+_MPEG_RESERVED_VERSION: Final = 0x01
+_MPEG_INVALID_BITRATE_INDEX: Final = 0x0F
+_MPEG_RESERVED_SAMPLE_RATE_INDEX: Final = 0x03
+
+
+def _adts_aac_frame_media_type(header: bytes) -> str | None:
+    sample_rate_index: Final = (header[2] >> 2) & 0x0F
+    return FILE_MIME_TYPES[FileType.AAC] if sample_rate_index < _ADTS_SAMPLE_RATE_INDEX_LIMIT else None
+
+
+def _mpeg_audio_frame_media_type(header: bytes) -> str | None:
+    version: Final = (header[1] >> 3) & 0x03
+    layer: Final = header[1] & _MPEG_LAYER_MASK
+    bitrate_index: Final = header[2] >> 4
+    sample_rate_index: Final = (header[2] >> 2) & 0x03
+    if (
+        (header[1] & _MPEG_SYNC_MASK) != _MPEG_SYNC_MASK
+        or version == _MPEG_RESERVED_VERSION
+        or layer == 0
+        or bitrate_index == _MPEG_INVALID_BITRATE_INDEX
+        or sample_rate_index == _MPEG_RESERVED_SAMPLE_RATE_INDEX
+    ):
+        return None
+    return FILE_MIME_TYPES[FileType.MP3]
+
+
+def speech_media_type_from_audio_bytes(audio: bytes) -> str | None:
+    if audio[:4] == b"RIFF" and audio[8:12] == b"WAVE":
+        return FILE_MIME_TYPES[FileType.WAV]
+    if audio[:4] == b"fLaC":
+        return FILE_MIME_TYPES[FileType.FLAC]
+    if audio[:4] == b"OggS":
+        is_opus: Final = b"OpusHead" in audio[:_OGG_OPUS_HEAD_WINDOW]
+        return FILE_MIME_TYPES[FileType.OPUS if is_opus else FileType.OGG]
+    if audio[:3] == b"ID3":
+        return FILE_MIME_TYPES[FileType.MP3]
+    if len(audio) < 3 or audio[0] != 0xFF:
+        return None
+    if (audio[1] & _ADTS_SYNC_AND_LAYER_MASK) == _ADTS_SYNC_AND_LAYER:
+        return _adts_aac_frame_media_type(audio)
+    return _mpeg_audio_frame_media_type(audio)
diff --git a/litellm/litellm_core_utils/get_litellm_params.py b/litellm/litellm_core_utils/get_litellm_params.py
index b12c715c9f5..389e6f7f501 100644
--- a/litellm/litellm_core_utils/get_litellm_params.py
+++ b/litellm/litellm_core_utils/get_litellm_params.py
@@ -50,6 +50,9 @@ OPTIONAL_KWARGS_KEYS: Final = (
             "vertex_ai_project",
             "vertex_ai_location",
             "vertex_ai_credentials",
+            "gigachat_scope",
+            "gigachat_auth_url",
+            "gigachat_access_token",
             "tpm",
             "rpm",
             "itpm",
diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 74a1d3e5008..ce51fb19970 100644
--- a/litellm/litellm_core_utils/get_llm_provider_logic.py
+++ b/litellm/litellm_core_utils/get_llm_provider_logic.py
@@ -127,7 +127,7 @@ def handle_anthropic_text_model_custom_llm_provider(
     return model, custom_llm_provider
 
 
-def declared_authenticating_provider(model: str, custom_llm_provider: str | None = None) -> str | None:
+def declared_authenticating_provider(model: str | None, custom_llm_provider: str | None = None) -> str | None:
     """The authenticating provider this pair already names, or None.
 
     get_llm_provider runs the OAuth device flow for github_copilot and chatgpt, because their
@@ -135,7 +135,7 @@ def declared_authenticating_provider(model: str, custom_llm_provider: str | None
     and for a declared pair the resolver's answer is the declaration itself, so metadata callers
     adopt the declaration instead of resolving.
     """
-    declared: Final = custom_llm_provider or model.split("/", 1)[0]
+    declared: Final = custom_llm_provider or (model.split("/", 1)[0] if model and "/" in model else None)
     return declared if declared in PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO else None
 
 
@@ -369,6 +369,9 @@ def get_llm_provider(
                     elif endpoint == "https://api.meta.ai/v1":
                         custom_llm_provider = "meta"
                         dynamic_api_key = get_secret_str("META_API_KEY")
+                    elif endpoint == "https://gigachat.devices.sberbank.ru/api/v1":
+                        custom_llm_provider = "gigachat"
+                        dynamic_api_key = get_secret_str("GIGACHAT_API_KEY")
                     elif (json_provider := JSONProviderRegistry.get_by_base_url(endpoint)) is not None:
                         custom_llm_provider = json_provider.slug
                         dynamic_api_key = api_key if api_key is not None else get_secret_str(json_provider.api_key_env)
@@ -533,6 +536,14 @@ def get_llm_provider(
             )
 
 
+def _dashscope_family_chat_config(custom_llm_provider: str) -> "litellm.DashScopeChatConfig":
+    if custom_llm_provider == "qwencloud":
+        return litellm.QwenCloudChatConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        return litellm.QwenAIPlatformChatConfig()
+    return litellm.DashScopeChatConfig()
+
+
 def _get_openai_compatible_provider_info(
     model: str,
     api_base: str | None,
@@ -782,11 +793,11 @@ def _get_openai_compatible_provider_info(
             api_base,
             dynamic_api_key,
         ) = litellm.HerokuChatConfig()._get_openai_compatible_provider_info(api_base, api_key)
-    elif custom_llm_provider == "dashscope":
+    elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
         (
             api_base,
             dynamic_api_key,
-        ) = litellm.DashScopeChatConfig()._get_openai_compatible_provider_info(api_base, api_key)
+        ) = _dashscope_family_chat_config(custom_llm_provider)._get_openai_compatible_provider_info(api_base, api_key)
     elif custom_llm_provider == "modelscope":
         (
             api_base,
@@ -867,6 +878,9 @@ def _get_openai_compatible_provider_info(
         # Manus is OpenAI compatible for responses API
         api_base = api_base or get_secret_str("MANUS_API_BASE") or "https://api.manus.im"
         dynamic_api_key = api_key or get_secret_str("MANUS_API_KEY")
+    elif custom_llm_provider == "gigachat":
+        api_base = api_base or get_secret_str("GIGACHAT_API_BASE") or "https://gigachat.devices.sberbank.ru/api/v1"
+        dynamic_api_key = api_key or get_secret_str("GIGACHAT_API_KEY")
 
     if api_base is not None and not isinstance(api_base, str):
         raise Exception(f"api base needs to be a string. api_base={api_base}")
diff --git a/litellm/litellm_core_utils/get_model_cost_map.py b/litellm/litellm_core_utils/get_model_cost_map.py
index 2043a9e2f89..9cba5db8ab7 100644
--- a/litellm/litellm_core_utils/get_model_cost_map.py
+++ b/litellm/litellm_core_utils/get_model_cost_map.py
@@ -12,6 +12,7 @@ import asyncio
 import json
 import os
 import random
+import time
 from collections.abc import Awaitable, Callable
 from dataclasses import dataclass
 from datetime import datetime, timezone
@@ -154,18 +155,6 @@ class GetModelCostMap:
 
         return True
 
-    @staticmethod
-    def fetch_remote_model_cost_map(url: str, timeout: int = 5) -> dict:
-        """
-        Fetch the model cost map from a remote URL.
-
-        Returns the parsed JSON dict. Raises on network/parse errors
-        (caller is expected to handle).
-        """
-        response: Final = httpx.get(url, timeout=timeout)
-        response.raise_for_status()
-        return response.json()
-
 
 RETRYABLE_FETCH_STATUS_CODES: Final = frozenset({429, 500, 502, 503, 504})
 MODEL_COST_MAP_FETCH_MAX_ATTEMPTS: Final = 3
@@ -212,6 +201,13 @@ class _AsyncGetClient(Protocol):
     def get(self, url: str, *, timeout: float | None = None) -> Awaitable[httpx.Response]: ...
 
 
+class _SyncGetClient(Protocol):
+    def get(self, url: str, *, timeout: float | None = None) -> httpx.Response: ...
+
+
+_FetchAttemptOutcome = ModelCostMapReloaded | ModelCostMapReloadUnavailable | _FetchAttemptRetryable
+
+
 def _default_reload_client() -> _AsyncGetClient:
     from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
     from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -219,13 +215,30 @@ def _default_reload_client() -> _AsyncGetClient:
     return get_async_httpx_client(llm_provider=httpxSpecialProvider.ModelCostMap)
 
 
-async def _attempt_fetch(
-    client: _AsyncGetClient, url: str, timeout: int
-) -> ModelCostMapReloaded | ModelCostMapReloadUnavailable | _FetchAttemptRetryable:
+def _classify_fetch_error(error: httpx.HTTPError | httpx.InvalidURL, url: str) -> _FetchAttemptOutcome:
+    reason: Final = f"{type(error).__name__} fetching {url}: {error}"
+    if isinstance(error, (httpx.InvalidURL, httpx.UnsupportedProtocol)):
+        return ModelCostMapReloadUnavailable(reason=reason)
+    return _FetchAttemptRetryable(reason=reason, retry_after_seconds=None)
+
+
+async def _attempt_fetch(client: _AsyncGetClient, url: str, timeout: int) -> _FetchAttemptOutcome:
     try:
         response: Final = await client.get(url, timeout=timeout)
-    except httpx.HTTPError as e:
-        return _FetchAttemptRetryable(reason=f"{type(e).__name__} fetching {url}: {e}", retry_after_seconds=None)
+    except (httpx.HTTPError, httpx.InvalidURL) as e:
+        return _classify_fetch_error(e, url)
+    return _classify_fetch_response(response, url)
+
+
+def _attempt_fetch_sync(client: _SyncGetClient, url: str, timeout: int) -> _FetchAttemptOutcome:
+    try:
+        response: Final = client.get(url, timeout=timeout)
+    except (httpx.HTTPError, httpx.InvalidURL) as e:
+        return _classify_fetch_error(e, url)
+    return _classify_fetch_response(response, url)
+
+
+def _classify_fetch_response(response: httpx.Response, url: str) -> _FetchAttemptOutcome:
     if response.status_code in RETRYABLE_FETCH_STATUS_CODES:
         return _FetchAttemptRetryable(
             reason=f"HTTP {response.status_code} from {url}",
@@ -242,6 +255,22 @@ async def _attempt_fetch(
     return ModelCostMapReloaded(model_cost_map=parsed)
 
 
+def _next_retry_wait(
+    outcome: _FetchAttemptRetryable, attempt: int, max_attempts: int, rng: random.Random
+) -> float | ModelCostMapReloadUnavailable:
+    if attempt == max_attempts:
+        return ModelCostMapReloadUnavailable(reason=f"{outcome.reason} (after {max_attempts} attempts)")
+    wait_seconds: Final = _retry_wait_seconds(outcome=outcome, attempt=attempt, rng=rng)
+    verbose_logger.warning(
+        "LiteLLM: model cost map fetch attempt %d/%d failed (%s); retrying in %.1fs",
+        attempt,
+        max_attempts,
+        outcome.reason,
+        wait_seconds,
+    )
+    return wait_seconds
+
+
 async def _fetch_remote_model_cost_map_with_retry(
     url: str,
     timeout: int,
@@ -254,20 +283,32 @@ async def _fetch_remote_model_cost_map_with_retry(
         outcome = await _attempt_fetch(client=client, url=url, timeout=timeout)
         if not isinstance(outcome, _FetchAttemptRetryable):
             return outcome
-        if attempt == max_attempts:
-            return ModelCostMapReloadUnavailable(reason=f"{outcome.reason} (after {max_attempts} attempts)")
-        wait_seconds = _retry_wait_seconds(outcome=outcome, attempt=attempt, rng=rng)
-        verbose_logger.warning(
-            "LiteLLM: model cost map fetch attempt %d/%d failed (%s); retrying in %.1fs",
-            attempt,
-            max_attempts,
-            outcome.reason,
-            wait_seconds,
-        )
+        wait_seconds = _next_retry_wait(outcome=outcome, attempt=attempt, max_attempts=max_attempts, rng=rng)
+        if isinstance(wait_seconds, ModelCostMapReloadUnavailable):
+            return wait_seconds
         await sleep(wait_seconds)
     return ModelCostMapReloadUnavailable(reason="model cost map fetch failed")
 
 
+def _fetch_remote_model_cost_map_with_retry_sync(
+    url: str,
+    timeout: int,
+    max_attempts: int,
+    sleep: Callable[[float], None],
+    rng: random.Random,
+    client: _SyncGetClient,
+) -> ModelCostMapReloadResult:
+    for attempt in range(1, max_attempts + 1):
+        outcome = _attempt_fetch_sync(client=client, url=url, timeout=timeout)
+        if not isinstance(outcome, _FetchAttemptRetryable):
+            return outcome
+        wait_seconds = _next_retry_wait(outcome=outcome, attempt=attempt, max_attempts=max_attempts, rng=rng)
+        if isinstance(wait_seconds, ModelCostMapReloadUnavailable):
+            return wait_seconds
+        sleep(wait_seconds)
+    return ModelCostMapReloadUnavailable(reason="model cost map fetch failed")
+
+
 async def refetch_model_cost_map(
     url: str,
     timeout: int = 5,
@@ -423,13 +464,21 @@ def _finalize_model_cost_map(model_cost: dict) -> dict:
     return _expand_model_aliases(model_cost)
 
 
-def get_model_cost_map(url: str) -> dict:
+def get_model_cost_map(
+    url: str,
+    timeout: int = 5,
+    max_attempts: int = MODEL_COST_MAP_FETCH_MAX_ATTEMPTS,
+    sleep: Callable[[float], None] = time.sleep,
+    rng: random.Random | None = None,
+    client: "_SyncGetClient | None" = None,
+) -> dict:
     """
     Public entry point — returns the model cost map dict.
 
     1. If ``LITELLM_LOCAL_MODEL_COST_MAP`` is set, uses the local backup only.
-    2. Otherwise fetches from ``url``, validates integrity, and falls back
-       to the local backup on any failure.
+    2. Otherwise fetches from ``url``, retrying transient HTTP errors
+       (429/5xx/transport) with Retry-After-aware backoff, validates
+       integrity, and falls back to the local backup on any failure.
 
     Only the backup model count is cached (a single int) for validation.
     The full backup dict is only parsed when it must be *returned* as a
@@ -448,17 +497,24 @@ def get_model_cost_map(url: str) -> dict:
     _cost_map_source_info.url = url
     _cost_map_source_info.is_env_forced = False
 
-    try:
-        content: Final = GetModelCostMap.fetch_remote_model_cost_map(url)
-    except Exception as e:
+    result: Final = _fetch_remote_model_cost_map_with_retry_sync(
+        url=url,
+        timeout=timeout,
+        max_attempts=max_attempts,
+        sleep=sleep,
+        rng=rng if rng is not None else random.Random(),
+        client=client if client is not None else httpx,
+    )
+    if isinstance(result, ModelCostMapReloadUnavailable):
         verbose_logger.warning(
             "LiteLLM: Failed to fetch remote model cost map from %s: %s. Falling back to local backup.",
             url,
-            str(e),
+            result.reason,
         )
         _cost_map_source_info.source = "local"
-        _cost_map_source_info.fallback_reason = f"Remote fetch failed: {e}"
+        _cost_map_source_info.fallback_reason = f"Remote fetch failed: {result.reason}"
         return _finalize_model_cost_map(GetModelCostMap.load_local_model_cost_map())
+    content: Final = result.model_cost_map
 
     # Validate using cached count (cheap int comparison, no file I/O)
     if not GetModelCostMap.validate_model_cost_map(
diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 97c4d038734..f54eeca5178 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -111,6 +111,7 @@ from litellm.types.mcp import MCPPostCallResponseObject
 from litellm.types.prompts.init_prompts import PromptSpec
 from litellm.types.rerank import RerankResponse
 from litellm.types.utils import (
+    DEPLOYMENT_SCOPED_PRICING_FIELDS,
     CachingDetails,
     CallTypes,
     CostBreakdown,
@@ -255,6 +256,7 @@ _STANDARD_LOGGING_METADATA_KEYS: Final[frozenset[str]] = frozenset(StandardLoggi
 
 # Cache custom pricing keys as frozenset for O(1) lookups instead of looping through 49 keys
 _CUSTOM_PRICING_KEYS: Final[frozenset[str]] = frozenset(CustomPricingLiteLLMParams.model_fields.keys())
+_MODEL_INFO_CUSTOM_PRICING_KEYS: Final[frozenset[str]] = _CUSTOM_PRICING_KEYS | DEPLOYMENT_SCOPED_PRICING_FIELDS
 
 sentry_sdk_instance = None
 capture_exception = None
@@ -899,6 +901,7 @@ class Logging(LiteLLMLoggingBaseClass):
         prompt_label: str | None = None,
         prompt_version: int | None = None,
         request_kwargs: dict[str, object] | None = None,  # mutable-ok: marker stamped into live request kwargs
+        injected_for_every_deployment: bool = False,
     ) -> tuple[str, list[AllMessageValues], dict]:
         from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook
 
@@ -931,6 +934,7 @@ class Logging(LiteLLMLoggingBaseClass):
                 AnthropicCacheControlHook.record_gateway_injection(
                     request_kwargs,
                     AnthropicCacheControlHook.count_request_cache_breakpoints(messages) - breakpoints_before,
+                    injected_for_every_deployment=injected_for_every_deployment,
                 )
         self.messages = messages
         return model, messages, non_default_params
@@ -948,6 +952,7 @@ class Logging(LiteLLMLoggingBaseClass):
         prompt_label: str | None = None,
         prompt_version: int | None = None,
         request_kwargs: dict[str, object] | None = None,  # mutable-ok: marker stamped into live request kwargs
+        injected_for_every_deployment: bool = False,
     ) -> tuple[str, list[AllMessageValues], dict]:
         from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook
 
@@ -983,6 +988,7 @@ class Logging(LiteLLMLoggingBaseClass):
                 AnthropicCacheControlHook.record_gateway_injection(
                     request_kwargs,
                     AnthropicCacheControlHook.count_request_cache_breakpoints(messages) - breakpoints_before,
+                    injected_for_every_deployment=injected_for_every_deployment,
                 )
         self.messages = messages
         return model, messages, non_default_params
@@ -2141,6 +2147,9 @@ class Logging(LiteLLMLoggingBaseClass):
 
             logging_result: Final = self.normalize_logging_result(result=result)
 
+            if isinstance(result, Response) and isinstance(logging_result, (ModelResponse, EmbeddingResponse)):
+                result = logging_result
+
             if standard_logging_object is None and result is not None and self.stream is not True:
                 if self._is_recognized_call_type_for_logging(logging_result=logging_result) or isinstance(
                     logging_result, (dict, list)
@@ -2954,13 +2963,25 @@ class Logging(LiteLLMLoggingBaseClass):
                     "Model=%s not found in completion cost map. Setting 'response_cost' to None", self.model
                 )
                 self.model_call_details["response_cost"] = None
+            except Exception:  # noqa: BLE001  # cost calculation must never block later callbacks (slot release)
+                verbose_logger.exception(
+                    "Error calculating streaming response cost for model=%s. Setting 'response_cost' to None",
+                    self.model,
+                )
+                self.model_call_details["response_cost"] = None
 
             self._merge_hidden_params_from_response_into_metadata(complete_streaming_response)
 
             ## STANDARDIZED LOGGING PAYLOAD
-            self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload(
-                complete_streaming_response, start_time, end_time
-            )
+            try:
+                self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload(
+                    complete_streaming_response, start_time, end_time
+                )
+            except Exception:  # noqa: BLE001  # payload build must never block later callbacks (slot release)
+                verbose_logger.exception(
+                    "LiteLLM.LoggingError: [Non-Blocking] Exception building the standard logging payload "
+                    "for a streaming response; callbacks still run without it"
+                )
 
             # print standard logging payload
             if (standard_logging_payload := self.model_call_details.get("standard_logging_object")) is not None:
@@ -3000,32 +3021,39 @@ class Logging(LiteLLMLoggingBaseClass):
         ## LOGGING HOOK ##
 
         for callback in callbacks:
-            if isinstance(callback, CustomGuardrail):
-                from litellm.types.guardrails import GuardrailEventHooks
+            try:
+                if isinstance(callback, CustomGuardrail):
+                    from litellm.types.guardrails import GuardrailEventHooks
 
-                if (
-                    callback.should_run_guardrail(
-                        data=self.model_call_details,
-                        event_type=GuardrailEventHooks.logging_only,
+                    if (
+                        callback.should_run_guardrail(
+                            data=self.model_call_details,
+                            event_type=GuardrailEventHooks.logging_only,
+                        )
+                        is not True
+                    ):
+                        continue
+
+                    self.model_call_details, result = await callback.async_logging_hook(
+                        kwargs=self.model_call_details,
+                        result=result,
+                        call_type=self.call_type,
                     )
-                    is not True
-                ):
-                    continue
-
-                self.model_call_details, result = await callback.async_logging_hook(
-                    kwargs=self.model_call_details,
-                    result=result,
-                    call_type=self.call_type,
-                )
-            elif isinstance(callback, CustomLogger):
-                result = redact_message_input_output_from_custom_logger(
-                    result=result, litellm_logging_obj=self, custom_logger=callback
-                )
-                self.model_call_details, result = await callback.async_logging_hook(
-                    kwargs=self.model_call_details,
-                    result=result,
-                    call_type=self.call_type,
+                elif isinstance(callback, CustomLogger):
+                    result = redact_message_input_output_from_custom_logger(
+                        result=result, litellm_logging_obj=self, custom_logger=callback
+                    )
+                    self.model_call_details, result = await callback.async_logging_hook(
+                        kwargs=self.model_call_details,
+                        result=result,
+                        call_type=self.call_type,
+                    )
+            except Exception:  # noqa: BLE001  # one failing hook must not skip later callbacks (slot release)
+                verbose_logger.error(
+                    "LiteLLM.LoggingError: [Non-Blocking] Exception occurred in async_logging_hook %s",
+                    traceback.format_exc(),
                 )
+                self._handle_callback_failure(callback=callback)
 
         self.has_run_logging(event_type="async_success")
 
@@ -4366,13 +4394,15 @@ def _init_custom_logger_compatible_class(
             from litellm.integrations.otel.model.config import is_otel_v2_enabled
 
             if is_otel_v2_enabled():
-                from litellm.integrations.otel.logger import OpenTelemetryV2
+                from litellm.integrations.otel.logger import OpenTelemetryV2, build_otel_v2_logger
+                from litellm.integrations.otel.model.config import OpenTelemetryV2Config
 
                 for callback in _in_memory_loggers:
-                    if type(callback) is OpenTelemetryV2:
+                    if isinstance(callback, OpenTelemetryV2):
                         return callback
-                otel_logger_v2: Final = OpenTelemetryV2(
-                    **_get_custom_logger_settings_from_proxy_server(callback_name=logging_integration)
+                otel_settings: Final = _get_custom_logger_settings_from_proxy_server(callback_name=logging_integration)
+                otel_logger_v2: Final = build_otel_v2_logger(
+                    config=OpenTelemetryV2Config(**otel_settings), settings=otel_settings
                 )
                 _in_memory_loggers.append(otel_logger_v2)
                 _maybe_auto_initialize_arize_phoenix(_in_memory_loggers)
@@ -4735,7 +4765,7 @@ def _maybe_construct_otel_v2(callback_name: str, _in_memory_loggers: list[Custom
 
     if not is_otel_v2_enabled():
         return None
-    from litellm.integrations.otel.logger import OpenTelemetryV2
+    from litellm.integrations.otel.logger import OpenTelemetryV2, build_otel_v2_logger
     from litellm.integrations.otel.presets import PRESET_BY_CALLBACK
 
     preset_fn: Final = PRESET_BY_CALLBACK.get(callback_name)
@@ -4750,7 +4780,7 @@ def _maybe_construct_otel_v2(callback_name: str, _in_memory_loggers: list[Custom
         # If env vars are missing or the preset raises, defer to the legacy path
         # so customers get the same error story they had before V2 landed.
         return None
-    v2_logger: Final = OpenTelemetryV2(config=config, callback_name=callback_name)
+    v2_logger: Final = build_otel_v2_logger(config=config, callback_name=callback_name)
     _in_memory_loggers.append(v2_logger)
     return v2_logger
 
@@ -5030,7 +5060,9 @@ def use_custom_pricing_for_model(litellm_params: dict | None) -> bool:
     """
     Check if the model uses custom pricing
 
-    Returns True if any of `SPECIAL_MODEL_INFO_PARAMS` are present in `litellm_params` or `model_info`
+    Returns True if any custom pricing field is present in `litellm_params`, or if
+    any custom pricing or deployment-scoped pricing field (such as
+    ``off_peak_pricing``) is present in the metadata ``model_info``
     """
     if litellm_params is None:
         return False
@@ -5048,7 +5080,7 @@ def use_custom_pricing_for_model(litellm_params: dict | None) -> bool:
         model_info: dict = metadata.get("model_info", {}) or {}
 
         if model_info:
-            matching_keys = _CUSTOM_PRICING_KEYS & model_info.keys()
+            matching_keys = _MODEL_INFO_CUSTOM_PRICING_KEYS & model_info.keys()
             for key in matching_keys:
                 if model_info.get(key) is not None:
                     return True
@@ -6152,7 +6184,10 @@ def get_standard_logging_object_payload(
 
 def emit_standard_logging_payload(payload: StandardLoggingPayload):
     if os.getenv("LITELLM_PRINT_STANDARD_LOGGING_PAYLOAD"):
-        print(json.dumps(payload, indent=4), flush=True)  # noqa: T201
+        try:
+            print(json.dumps(payload, indent=4, default=str), flush=True)  # noqa: T201
+        except Exception as e:  # noqa: BLE001 # Safe catch-all for verbose logging
+            verbose_logger.exception("Error serializing standard logging payload for debug output: %s", e)
 
 
 def get_standard_logging_metadata(
diff --git a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py
index 9250b92e268..5504756ceb8 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py
@@ -3,7 +3,7 @@ Helper utilities for tracking the cost of built-in tools.
 """
 
 from collections.abc import Mapping
-from typing import Any, Final, Literal
+from typing import Final, Literal
 
 import litellm
 from litellm.constants import OPENAI_FILE_SEARCH_COST_PER_1K_CALLS
@@ -16,6 +16,7 @@ from litellm.types.llms.openai import (
     WebSearchOptions,
 )
 from litellm.types.utils import (
+    ChatCompletionAnnotation,
     Message,
     ModelInfo,
     ModelResponse,
@@ -49,7 +50,7 @@ class StandardBuiltInToolCostTracking:
     @staticmethod
     def get_cost_for_built_in_tools(
         model: str,
-        response_object: Any,
+        response_object: object,
         usage: Usage | None = None,
         custom_llm_provider: str | None = None,
         standard_built_in_tools_params: StandardBuiltInToolsParams | None = None,
@@ -201,8 +202,7 @@ class StandardBuiltInToolCostTracking:
         model_info: Final = StandardBuiltInToolCostTracking._safe_get_model_info(
             model=model, custom_llm_provider=custom_llm_provider
         )
-        file_search_raw: Final[Any] = standard_built_in_tools_params.get("file_search", {})
-        file_search_usage: Final[FileSearchTool | None] = FileSearchTool(**file_search_raw) if file_search_raw else None
+        file_search_usage: Final[FileSearchTool | None] = standard_built_in_tools_params.get("file_search") or None
 
         # Convert model_info to dict and extract usage parameters
         model_info_dict: Final = dict(model_info) if model_info is not None else None
@@ -245,7 +245,7 @@ class StandardBuiltInToolCostTracking:
 
     @staticmethod
     def _extract_file_search_params(
-        file_search_usage: Any,
+        file_search_usage: object,
     ) -> tuple[float | None, float | None]:
         """Extract and convert file search parameters safely."""
         storage_gb = None
@@ -335,7 +335,7 @@ class StandardBuiltInToolCostTracking:
 
     @staticmethod
     def _extract_token_counts(
-        computer_use_usage: Any,
+        computer_use_usage: object,
     ) -> tuple[int | None, int | None]:
         """Extract and convert token counts safely."""
         input_tokens = None
@@ -351,9 +351,9 @@ class StandardBuiltInToolCostTracking:
         return input_tokens, output_tokens
 
     @staticmethod
-    def _safe_convert_to_int(value: Any) -> int | None:
+    def _safe_convert_to_int(value: object) -> int | None:
         """Safely convert a value to int."""
-        if value is not None:
+        if isinstance(value, (int, float, str)):
             try:
                 return int(value)
             except (TypeError, ValueError):
@@ -381,7 +381,7 @@ class StandardBuiltInToolCostTracking:
         return usage.model_copy(update={"server_tool_use": server_tool_use})
 
     @staticmethod
-    def response_object_includes_web_search_call(response_object: Any, usage: Usage | None = None) -> bool:
+    def response_object_includes_web_search_call(response_object: object, usage: Usage | None = None) -> bool:
         """
         Check if the response object includes a web search call.
 
@@ -446,7 +446,7 @@ class StandardBuiltInToolCostTracking:
 
     @staticmethod
     def response_object_includes_file_search_call(
-        response_object: Any,
+        response_object: object,
     ) -> bool:
         """
         Check if the response object includes a file search call.
@@ -477,11 +477,11 @@ class StandardBuiltInToolCostTracking:
                 message: Message | None = getattr(choice, "message", None)
                 if message is None:
                     continue
-                if annotations := getattr(message, "annotations", None):
-                    if len(annotations) > 0:
-                        for annotation in annotations:
-                            if annotation.get("type", None) == annotation_type:
-                                return True
+                annotations: list[ChatCompletionAnnotation] | None = getattr(message, "annotations", None)
+                if annotations:
+                    for annotation in annotations:
+                        if annotation.get("type", None) == annotation_type:
+                            return True
         return False
 
     @staticmethod
@@ -522,10 +522,8 @@ class StandardBuiltInToolCostTracking:
         if model_info is None:
             return 0.0
 
-        search_context_raw: Final[Any] = model_info.get("search_context_cost_per_query", {})
-        search_context_pricing: Final[SearchContextCostPerQuery] = (
-            SearchContextCostPerQuery(**search_context_raw) if search_context_raw else SearchContextCostPerQuery()
-        )
+        search_context_raw: Final = model_info.get("search_context_cost_per_query")
+        search_context_pricing: Final[SearchContextCostPerQuery] = search_context_raw or SearchContextCostPerQuery()
         if web_search_options.get("search_context_size", None) == "low":
             return search_context_pricing.get("search_context_size_low", 0.0)
         elif web_search_options.get("search_context_size", None) == "medium":
@@ -545,10 +543,8 @@ class StandardBuiltInToolCostTracking:
         """
         if model_info is None:
             return 0.0
-        search_context_raw: Final[Any] = model_info.get("search_context_cost_per_query", {}) or {}
-        search_context_pricing: Final[SearchContextCostPerQuery] = (
-            SearchContextCostPerQuery(**search_context_raw) if search_context_raw else SearchContextCostPerQuery()
-        )
+        search_context_raw: Final = model_info.get("search_context_cost_per_query")
+        search_context_pricing: Final[SearchContextCostPerQuery] = search_context_raw or SearchContextCostPerQuery()
         return search_context_pricing.get("search_context_size_medium", 0.0)
 
     @staticmethod
@@ -714,7 +710,7 @@ class StandardBuiltInToolCostTracking:
         response_object: ModelResponse,
     ) -> bool:
         for _choice in response_object.choices:
-            message = getattr(_choice, "message", None)
+            message: Message | None = getattr(_choice, "message", None)
             if (
                 message is not None
                 and hasattr(message, "annotations")
diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 19e3f624268..b34c416cd40 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -2,10 +2,12 @@
 ## Helper utilities for cost_per_token()
 
 import re
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
+from datetime import datetime, timezone, tzinfo
 from types import MappingProxyType
 from typing import Any, Final, Literal, TypedDict, cast
+from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
 
 import litellm
 from litellm._logging import verbose_logger
@@ -290,10 +292,187 @@ def _get_tiered_base_costs(model_info: ModelInfo, usage: Usage) -> tuple[float,
     )
 
 
+def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_time: datetime | None = None) -> bool:
+    """Return True if current_time (UTC, defaulting to now) falls inside any off-peak window.
+
+    off_peak_hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of such strings for providers
+    with multiple daily windows (e.g. ["16:30-00:30", "04:00-06:00"]). A window may wrap past
+    midnight, and a window whose start equals its end covers the whole day. The start is
+    inclusive and the end is exclusive; malformed windows are ignored.
+
+    An aware current_time is converted to UTC. A naive one is taken to already be UTC rather
+    than being localised, so callers must pass datetime.now(timezone.utc), never datetime.now(),
+    or every window shifts by the host's offset.
+    """
+    reference: Final = current_time if current_time is not None else datetime.now(timezone.utc)
+    now: Final = (reference.astimezone(timezone.utc) if reference.tzinfo is not None else reference).time()
+    windows: Final = (off_peak_hours_utc,) if isinstance(off_peak_hours_utc, str) else off_peak_hours_utc
+    for window in windows:
+        try:
+            start_str, end_str = window.split("-")
+            start = datetime.strptime(start_str.strip(), "%H:%M").replace(tzinfo=timezone.utc).time()
+            end = datetime.strptime(end_str.strip(), "%H:%M").replace(tzinfo=timezone.utc).time()
+        except (ValueError, AttributeError):
+            continue
+        if start < end:
+            if start <= now < end:
+                return True
+        elif now >= start or now < end:
+            return True
+    return False
+
+
+_WEEKDAY_NUMBERS: Final = MappingProxyType(
+    {
+        "mon": 1,
+        "monday": 1,
+        "tue": 2,
+        "tues": 2,
+        "tuesday": 2,
+        "wed": 3,
+        "wednesday": 3,
+        "thu": 4,
+        "thur": 4,
+        "thurs": 4,
+        "thursday": 4,
+        "fri": 5,
+        "friday": 5,
+        "sat": 6,
+        "saturday": 6,
+        "sun": 7,
+        "sunday": 7,
+    }
+)
+
+
+def _normalize_weekday(value: object) -> int | None:
+    if isinstance(value, bool):
+        return None
+    if isinstance(value, int):
+        return value if 1 <= value <= 7 else None
+    if isinstance(value, str):
+        return _WEEKDAY_NUMBERS.get(value.strip().lower())
+    return None
+
+
+def _weekday_calendar(weekday_timezone: object) -> tzinfo:
+    if isinstance(weekday_timezone, str) and weekday_timezone.strip():
+        try:
+            return ZoneInfo(weekday_timezone.strip())
+        except (ValueError, ZoneInfoNotFoundError):
+            return timezone.utc
+    return timezone.utc
+
+
+def _matches_weekdays(reference_utc: datetime, weekdays: object, weekday_timezone: object) -> bool:
+    """Return True when reference_utc falls on one of the rule's weekdays, read on the calendar
+    named by weekday_timezone (default UTC). An absent weekdays means every day. The calendar
+    matters even when UTC and vendor-local weekdays agree at every currently priced hour: a
+    window past 16:00 UTC is where an Asia/Shanghai weekday diverges from the UTC one.
+    """
+    if weekdays is None:
+        return True
+    if isinstance(weekdays, str) or not isinstance(weekdays, Sequence):
+        return False
+    allowed: Final = frozenset(day for day in map(_normalize_weekday, weekdays) if day is not None)
+    return reference_utc.astimezone(_weekday_calendar(weekday_timezone)).isoweekday() in allowed
+
+
+def _as_window_strings(value: object) -> tuple[str, ...]:
+    if isinstance(value, str):
+        return (value,)
+    if isinstance(value, Sequence):
+        return tuple(entry for entry in value if isinstance(entry, str))
+    return ()
+
+
+def _is_off_peak(off_peak: Mapping[str, object], current_time: datetime | None = None) -> bool:
+    """Return True when current_time (UTC, defaulting to now) is off-peak under the block's
+    rules: the flat hours_utc windows, which apply every day, or any entry in windows, whose
+    hours apply only on its weekdays.
+    """
+    reference: Final = current_time if current_time is not None else datetime.now(timezone.utc)
+    reference_utc: Final = (
+        reference.astimezone(timezone.utc) if reference.tzinfo is not None else reference.replace(tzinfo=timezone.utc)
+    )
+    flat_windows: Final = _as_window_strings(off_peak.get("hours_utc"))
+    if flat_windows and _is_within_off_peak_window(flat_windows, reference_utc):
+        return True
+    windows: Final = off_peak.get("windows")
+    if isinstance(windows, str) or not isinstance(windows, Sequence):
+        return False
+    weekday_timezone: Final = off_peak.get("weekday_timezone")
+    for rule in windows:
+        if not isinstance(rule, Mapping):
+            continue
+        rule_windows = _as_window_strings(rule.get("hours_utc"))
+        if not rule_windows:
+            continue
+        if not _matches_weekdays(reference_utc, rule.get("weekdays"), weekday_timezone):
+            continue
+        if _is_within_off_peak_window(rule_windows, reference_utc):
+            return True
+    return False
+
+
+def _coerce_off_peak_rate(value: object, default: float) -> float:
+    if isinstance(value, bool):
+        return default
+    if isinstance(value, (int, float)):
+        return float(value)
+    if isinstance(value, str):
+        try:
+            return float(value)
+        except ValueError:
+            return default
+    return default
+
+
+def _apply_off_peak_pricing(
+    model_info: ModelInfo,
+    current_time: datetime | None,
+    prompt_base_cost: float,
+    completion_base_cost: float,
+    cache_read_cost: float,
+) -> tuple[float, float, float]:
+    """Swap in off-peak per-token rates when the current UTC time is inside one of the model's
+    off_peak_pricing rules, the every-day hours_utc windows or a day-of-week-qualified entry in
+    windows. An off-peak rate replaces the rate that would otherwise apply rather than
+    discounting it, so a model that also has tiered or above-threshold pricing bills the flat
+    off-peak rate for the whole request while the window is open. Any rate left unset in
+    off_peak_pricing falls back to the standard rate.
+    """
+    off_peak: Final = model_info.get("off_peak_pricing")
+    if not isinstance(off_peak, Mapping) or not _is_off_peak(off_peak, current_time):
+        return prompt_base_cost, completion_base_cost, cache_read_cost
+    return (
+        _coerce_off_peak_rate(off_peak.get("input_cost_per_token"), prompt_base_cost),
+        _coerce_off_peak_rate(off_peak.get("output_cost_per_token"), completion_base_cost),
+        _coerce_off_peak_rate(off_peak.get("cache_read_input_token_cost"), cache_read_cost),
+    )
+
+
+def _apply_off_peak_to_base_costs(
+    model_info: ModelInfo,
+    current_time: datetime | None,
+    base_costs: tuple[float, float, float, float, float],
+) -> tuple[float, float, float, float, float]:
+    """Apply off-peak rates to an already-resolved set of base costs, whichever pricing path
+    produced them. Cache-creation rates are passed through untouched, since off_peak_pricing
+    has no field for them.
+    """
+    prompt, completion, cache_creation, cache_creation_above_1hr, cache_read = base_costs
+    off_peak_prompt, off_peak_completion, off_peak_cache_read = _apply_off_peak_pricing(
+        model_info, current_time, prompt, completion, cache_read
+    )
+    return (off_peak_prompt, off_peak_completion, cache_creation, cache_creation_above_1hr, off_peak_cache_read)
+
+
 def _get_token_base_cost(
     model_info: ModelInfo,
     usage: Usage,
     service_tier: str | None = None,
+    current_time: datetime | None = None,
     *,
     threshold_is_inclusive: bool = False,
 ) -> tuple[float, float, float, float, float]:
@@ -311,7 +490,7 @@ def _get_token_base_cost(
     """
     tiered_base_costs: Final = _get_tiered_base_costs(model_info=model_info, usage=usage)
     if tiered_base_costs is not None:
-        return tiered_base_costs
+        return _apply_off_peak_to_base_costs(model_info, current_time, tiered_base_costs)
 
     # Get service tier aware cost keys
     input_cost_key: Final = _get_service_tier_cost_key("input_cost_per_token", service_tier)
@@ -345,12 +524,16 @@ def _get_token_base_cost(
         k for k in model_info if k.startswith("input_cost_per_token_above_") and not k.endswith(_SERVICE_TIER_SUFFIXES)
     ]
     if not threshold_keys:
-        return (
-            prompt_base_cost,
-            completion_base_cost,
-            cache_creation_cost,
-            cache_creation_cost_above_1hr,
-            cache_read_cost,
+        return _apply_off_peak_to_base_costs(
+            model_info,
+            current_time,
+            (
+                prompt_base_cost,
+                completion_base_cost,
+                cache_creation_cost,
+                cache_creation_cost_above_1hr,
+                cache_read_cost,
+            ),
         )
 
     # Only sort the threshold keys (typically 1-2 keys instead of 66+)
@@ -451,12 +634,16 @@ def _get_token_base_cost(
             except Exception:
                 continue
 
-    return (
-        prompt_base_cost,
-        completion_base_cost,
-        cache_creation_cost,
-        cache_creation_cost_above_1hr,
-        cache_read_cost,
+    return _apply_off_peak_to_base_costs(
+        model_info,
+        current_time,
+        (
+            prompt_base_cost,
+            completion_base_cost,
+            cache_creation_cost,
+            cache_creation_cost_above_1hr,
+            cache_read_cost,
+        ),
     )
 
 
diff --git a/litellm/litellm_core_utils/llm_response_utils/response_metadata.py b/litellm/litellm_core_utils/llm_response_utils/response_metadata.py
index ac8cf438a9b..b53a2d36753 100644
--- a/litellm/litellm_core_utils/llm_response_utils/response_metadata.py
+++ b/litellm/litellm_core_utils/llm_response_utils/response_metadata.py
@@ -2,6 +2,8 @@ import datetime
 from collections.abc import Mapping
 from typing import Any, Final
 
+import httpx
+
 from litellm.constants import LITELLM_DETAILED_TIMING
 from litellm.litellm_core_utils.core_helpers import process_response_headers
 from litellm.litellm_core_utils.llm_response_utils.get_api_base import get_api_base
@@ -59,11 +61,7 @@ class ResponseMetadata:
     @property
     def supports_response_time(self) -> bool:
         """Check if response type supports timing metrics"""
-        return (
-            isinstance(self.result, ModelResponse)
-            or isinstance(self.result, EmbeddingResponse)
-            or isinstance(self.result, TranscriptionResponse)
-        )
+        return isinstance(self.result, (ModelResponse, EmbeddingResponse, TranscriptionResponse))
 
     def set_hidden_params(self, logging_obj: LiteLLMLoggingObject, model: str | None, kwargs: dict) -> None:
         """Set hidden parameters on the response"""
@@ -79,7 +77,7 @@ class ResponseMetadata:
                 result=self.result, litellm_model_name=model, router_model_id=model_id
             ),
             "additional_headers": process_response_headers(
-                self._get_value_from_hidden_params("additional_headers") or {},
+                self._get_additional_headers_from_hidden_params() or {},
                 preserve_litellm_internal_headers=True,
             ),
             "litellm_model_name": model,
@@ -98,12 +96,12 @@ class ResponseMetadata:
             for key, value in new_params.items():
                 setattr(self._hidden_params, key, value)
 
-    def _get_value_from_hidden_params(self, key: str) -> Any | None:
-        """Get value from hidden params - handles when self._hidden_params is a dict or HiddenParams object"""
+    def _get_additional_headers_from_hidden_params(self) -> httpx.Headers | dict[str, str] | None:
+        """Get `additional_headers` from hidden params - handles when self._hidden_params is a dict or HiddenParams object"""
         if isinstance(self._hidden_params, dict):
-            return self._hidden_params.get(key, None)
+            return self._hidden_params.get("additional_headers", None)
         elif isinstance(self._hidden_params, HiddenParams):
-            return getattr(self._hidden_params, key, None)
+            return getattr(self._hidden_params, "additional_headers", None)
 
     def set_timing_metrics(
         self,
@@ -129,7 +127,7 @@ class ResponseMetadata:
         #########################################################
         # 2. Add callback processing duration
         #########################################################
-        callback_duration_ms: Final = getattr(logging_obj, "callback_duration_ms", None)
+        callback_duration_ms: Final[float | None] = getattr(logging_obj, "callback_duration_ms", None)
         if callback_duration_ms is not None:
             self._update_hidden_params(
                 {
@@ -142,17 +140,17 @@ class ResponseMetadata:
         #########################################################
         llm_api_duration_ms: Final = logging_obj.model_call_details.get("llm_api_duration_ms")
         if LITELLM_DETAILED_TIMING and llm_api_duration_ms is not None:
-            detailed: Final[dict] = {
+            detailed: Final[dict[str, float]] = {
                 "timing_llm_api_ms": round(llm_api_duration_ms, 4),
             }
 
             # message copy time from Logging.__init__()
-            msg_copy_ms: Final = getattr(logging_obj, "message_copy_duration_ms", None)
+            msg_copy_ms: Final[float | None] = getattr(logging_obj, "message_copy_duration_ms", None)
             if msg_copy_ms is not None:
                 detailed["timing_message_copy_ms"] = round(msg_copy_ms, 4)
 
             # pre-processing = time from request start to LLM API call start
-            api_call_start: Final = logging_obj.model_call_details.get("api_call_start_time")
+            api_call_start: Final[datetime.datetime | None] = logging_obj.model_call_details.get("api_call_start_time")
             if api_call_start is not None and start_time is not None:
                 pre_ms: Final = (api_call_start - start_time).total_seconds() * 1000
                 detailed["timing_pre_processing_ms"] = round(pre_ms, 4)
diff --git a/litellm/litellm_core_utils/model_response_utils.py b/litellm/litellm_core_utils/model_response_utils.py
index 7bf667164ae..dc4f375daa7 100644
--- a/litellm/litellm_core_utils/model_response_utils.py
+++ b/litellm/litellm_core_utils/model_response_utils.py
@@ -144,7 +144,6 @@ def _is_choice_non_empty(choice: StreamingChoices) -> bool:
     # Check model_extra for dynamically added fields on the choice
     choice_extra_fields: Final[Mapping[str, object]] = choice.model_extra or {}
     for extra_field_name, extra_field_value in choice_extra_fields.items():
-        # Skip certain structural fields that are just default/None placeholders
         if extra_field_name == "index" and extra_field_value == 0:
             continue
         if extra_field_name in {"finish_reason", "logprobs"} and extra_field_value is None:
@@ -192,7 +191,6 @@ def _is_delta_non_empty(delta: Delta) -> bool:
     # Check model_extra for dynamically added fields (this is where Pydantic stores them)
     delta_extra_fields: Final[Mapping[str, object]] = delta.model_extra or {}
     for extra_field_value in delta_extra_fields.values():
-        # Even structural fields are meaningful if they have actual content
         if _has_meaningful_content(extra_field_value):
             return True
 
diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 1c8f10d3307..ff46440ff5c 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -205,6 +205,41 @@ def is_non_content_values_set(message: AllMessageValues) -> bool:
     return any(message.get(key, None) is not None for key in message if key not in ignore_keys)
 
 
+_IMAGE_CONTENT_PART_TYPES: Final = frozenset({"image_url", "input_image", "image"})
+_IMAGE_SCAN_MAX_DEPTH: Final = 4
+
+
+def _content_parts_contain_image(parts: Sequence[object]) -> bool:
+    """Depth-bounded frontier walk over nested content lists, iterative because the repo bans
+    recursion; an Anthropic tool_result nests its image parts exactly one level down."""
+    frontier = parts  # rebind-ok: depth-bounded frontier walk
+    for _ in range(_IMAGE_SCAN_MAX_DEPTH):
+        if any(isinstance(part, Mapping) and part.get("type") in _IMAGE_CONTENT_PART_TYPES for part in frontier):
+            return True
+        frontier = tuple(  # rebind-ok: depth-bounded frontier walk
+            nested
+            for part in frontier
+            if isinstance(part, Mapping)
+            for content in (part.get("content"),)
+            if isinstance(content, list)
+            for nested in content
+        )
+        if not frontier:
+            return False
+    return False
+
+
+def request_contains_image_content(messages: Sequence[Mapping[str, object]]) -> bool:
+    """Whether any message carries an image content part, across the dialects that reach
+    pre-routing hooks untranslated: chat-completions ``image_url``, Responses ``input_image``,
+    and Anthropic Messages ``image``, including images nested inside ``tool_result`` blocks."""
+    return any(
+        isinstance(content, list) and _content_parts_contain_image(content)
+        for message in messages
+        for content in (message.get("content"),)
+    )
+
+
 def _audio_or_image_in_message_content(message: AllMessageValues) -> bool:
     """
     Checks if message content contains an image or audio
@@ -520,10 +555,10 @@ def update_messages_with_model_file_ids(
 
 
 def update_responses_input_with_model_file_ids(
-    input: Any,
+    input: object,
     model_id: str | None = None,
     model_file_id_mapping: dict[str, dict[str, str]] | None = None,
-) -> str | list[dict[str, Any]]:
+) -> object:
     """
     Updates responses API input with provider-specific file IDs.
     File IDs are always inside the content array, not as direct input_file items.
@@ -604,8 +639,8 @@ def update_responses_input_with_model_file_ids(
 
 
 def _decode_vector_store_ids_in_tools(
-    tools: list[dict[str, Any]] | None,
-) -> list[dict[str, Any]] | None:
+    tools: list[dict[str, object]] | None,
+) -> list[dict[str, object]] | None:
     """
     Decodes unified (LiteLLM-managed) vector_store_ids in file_search tools to
     provider-native IDs.  Non-unified IDs are passed through unchanged.
@@ -657,10 +692,10 @@ def _decode_vector_store_ids_in_tools(
 
 
 def update_responses_tools_with_model_file_ids(
-    tools: list[dict[str, Any]] | None,
+    tools: list[dict[str, object]] | None,
     model_id: str | None = None,
     model_file_id_mapping: dict[str, dict[str, str]] | None = None,
-) -> list[dict[str, Any]] | None:
+) -> list[dict[str, object]] | None:
     """
     Updates responses API tools with provider-specific file IDs.
 
@@ -853,7 +888,7 @@ def extract_file_data(file_data: FileTypes) -> ExtractedFileData:
 # ---------------------------------------------------------------------------
 
 
-def _estimate_json_bytes(obj: Any) -> int:
+def _estimate_json_bytes(obj: object) -> int:
     """Estimate the JSON-serialised byte size of ``obj`` without materialising
     JSON. Walks iteratively (no recursion stack risk).
 
@@ -1246,6 +1281,19 @@ def flatten_top_level_schema_combinators(schema: Mapping[str, object]) -> Mappin
     return _flatten_schema_against_root(schema, schema, frozenset(), 0, {})  # mutable-ok: fresh per-call $ref memo
 
 
+def tool_with_flattened_parameters(tool: Mapping[str, object]) -> Mapping[str, object]:
+    function: Final = tool.get("function")
+    if not isinstance(function, dict):
+        return tool
+    parameters: Final = function.get("parameters")
+    if not isinstance(parameters, dict):
+        return tool
+    flattened: Final = flatten_top_level_schema_combinators(parameters)
+    if flattened is parameters:
+        return tool
+    return {**tool, "function": {**function, "parameters": flattened}}  # mutable-ok: request tools are JSON dicts
+
+
 def _get_image_mime_type_from_url(url: str) -> str | None:
     """
     Get mime type for common image URLs
@@ -1944,7 +1992,7 @@ def drop_tool_reference_parts_from_tool_messages(
     return [_drop_tool_reference_parts(message) for message in messages]  # mutable-ok: pipelines mutate message lists
 
 
-def _attempt_json_repair(s: str) -> Any | None:
+def _attempt_json_repair(s: str) -> object | None:
     """
     Attempt to repair truncated JSON produced by LLM tool calls.
 
@@ -2060,7 +2108,7 @@ def parse_tool_call_arguments(
         raise ValueError(error_message) from original_error
 
 
-def split_concatenated_json_objects(raw: str) -> list[dict[str, Any]]:
+def split_concatenated_json_objects(raw: str) -> list[dict[str, object]]:
     """
     Split a string that contains one or more concatenated JSON objects into
     a list of parsed dicts.
@@ -2096,7 +2144,7 @@ def split_concatenated_json_objects(raw: str) -> list[dict[str, Any]]:
         return []
 
     decoder: Final = json.JSONDecoder()
-    results: Final[list[dict[str, Any]]] = []
+    results: Final[list[dict[str, object]]] = []
     idx = 0
     length: Final = len(raw)
 
diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index 795fb36961e..ba59e3fa997 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -1694,6 +1694,18 @@ def convert_function_to_anthropic_tool_invoke(
         raise e
 
 
+def _find_server_tool_result(
+    tool_id: str,
+    web_search_results: Sequence[object] | None,
+    tool_results: Sequence[object] | None,
+) -> dict[str, object] | None:
+    candidates: Final = (*(web_search_results or ()), *(tool_results or ()))
+    return next(
+        (result for result in candidates if isinstance(result, dict) and result.get("tool_use_id") == tool_id),
+        None,
+    )
+
+
 def convert_to_anthropic_tool_invoke(
     tool_calls: list[ChatCompletionAssistantToolCall],
     web_search_results: list[Any] | None = None,
@@ -1758,32 +1770,22 @@ def convert_to_anthropic_tool_invoke(
             context="Anthropic tool invoke",
         )
 
-        # Check if this is a server-side tool (web_search, tool_search, etc.)
-        # Server tool IDs start with "srvtoolu_"
-        if tool_id.startswith("srvtoolu_"):
-            # Create server_tool_use block instead of tool_use
-            _anthropic_server_tool_use: dict[str, object] = {
-                "type": "server_tool_use",
-                "id": tool_id,
-                "name": tool_name,
-                "input": tool_input,
-            }
-            anthropic_tool_invoke.append(_anthropic_server_tool_use)
-
-            # Add corresponding tool result if available.
-            # Check both web_search_results (web_search_tool_result / web_fetch_tool_result)
-            # and tool_results (bash_code_execution_tool_result, etc.)
-            _all_tool_results: list[Any] = []
-            if web_search_results:
-                _all_tool_results.extend(web_search_results)
-            if tool_results:
-                _all_tool_results.extend(tool_results)
-            for result in _all_tool_results:
-                if result.get("tool_use_id") == tool_id:
-                    anthropic_tool_invoke.append(result)
-                    break
+        server_tool_result = (
+            _find_server_tool_result(tool_id, web_search_results, tool_results)
+            if tool_id.startswith("srvtoolu_")
+            else None
+        )
+        if server_tool_result is not None:
+            anthropic_tool_invoke.append(
+                {
+                    "type": "server_tool_use",
+                    "id": tool_id,
+                    "name": tool_name,
+                    "input": tool_input,
+                }
+            )
+            anthropic_tool_invoke.append(server_tool_result)
         else:
-            # Regular tool_use
             sanitized_tool_id = _sanitize_anthropic_tool_use_id(tool_id)
             _anthropic_tool_use_param = AnthropicMessagesToolUseParam(
                 type="tool_use",
@@ -4955,10 +4957,13 @@ def make_valid_bedrock_tool_name(input_tool_name: str) -> str:
 
 
 def add_cache_point_tool_block(tool: dict, model: str | None = None) -> BedrockToolBlock | None:
-    from litellm.llms.bedrock.common_utils import is_claude_4_5_on_bedrock
+    from litellm.llms.bedrock.common_utils import (
+        bedrock_model_accepts_cache_points,
+        is_claude_4_5_on_bedrock,
+    )
 
     cache_control: Final = tool.get("cache_control", None)
-    if cache_control is not None:
+    if cache_control is not None and bedrock_model_accepts_cache_points(model):
         cache_point: Final = cache_control.get("type", "ephemeral")
         if cache_point == "ephemeral":
             cache_point_block: Final[CachePointBlock] = {"type": "default"}
diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py
index 9125ed6e70a..8479e108d17 100644
--- a/litellm/litellm_core_utils/realtime_streaming.py
+++ b/litellm/litellm_core_utils/realtime_streaming.py
@@ -1500,6 +1500,6 @@ class RealTimeStreaming:
                     pass
 
 
-def client_sent_openai_beta_realtime_header(websocket: Any) -> bool:
+def client_sent_openai_beta_realtime_header(websocket: _ScopedWebSocket) -> bool:
     """True when the client WebSocket includes ``OpenAI-Beta: realtime=v1``."""
     return RealTimeStreaming._detect_beta_header(websocket)
diff --git a/litellm/litellm_core_utils/secret_redaction.py b/litellm/litellm_core_utils/secret_redaction.py
index 5d5bd547d22..e93ab155786 100644
--- a/litellm/litellm_core_utils/secret_redaction.py
+++ b/litellm/litellm_core_utils/secret_redaction.py
@@ -30,6 +30,11 @@ def _build_secret_patterns() -> "re.Pattern[str]":
         r"Basic\s+[A-Za-z0-9+/]{10,}={0,2}",
         # OpenAI / Anthropic sk- prefixed keys
         rf"sk-[A-Za-z0-9\-_]{{{MINIMUM_CUSTOM_KEY_LENGTH - len('sk-')},}}",
+        # Credentials passed as URL query params. Terminated by "&" like the key=
+        # and sig= patterns below, so the rest of the request line survives in an
+        # access log. Must precede the generic patterns to win at the same position.
+        r"(?<=[?&])(?:api[_-]?key|\w*(?:token|password|passwd|client_secret|secret_key|_secret))"
+        r"=[^\s&'\"]+",
         # Generic api_key / api-key / apikey (handles 'key': 'value' dict repr)
         r"(?:api[_-]?key)['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]{8,}",
         # x-api-key / api-key header values (handles 'key': 'value' dict repr)
@@ -45,8 +50,10 @@ def _build_secret_patterns() -> "re.Pattern[str]":
         # Word boundary prevents O(n^2) backtracking on long word-char runs.
         r"(?:^|(?<=\W))\w*(?:password|passwd|client_secret|secret_key|_secret)"
         r"['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]+",
-        # Database connection string credentials (scheme://user:pass@host)
-        r"(?<=://)[^\s'\"]*:[^\s'\"@]+(?=@)",
+        # Database connection string credentials (scheme://user:pass@host).
+        # The user half stops at the ":" separator and both halves are length-capped,
+        # so a long attacker-supplied URL cannot backtrack quadratically.
+        r"(?<=://)[^\s'\":]{0,4096}:[^\s'\"]{1,4096}(?=@)",
         # Databricks personal access tokens
         r"dapi[0-9a-f]{32}",
         # Module-level provider keys logged as litellm.<provider>_key=<value>
@@ -67,8 +74,10 @@ def _build_secret_patterns() -> "re.Pattern[str]":
         r"""['\"]?\s*[:=]\s*['\"]?[^\s,'\"})\]{}>]+""",
         # Raw JWTs (without Bearer prefix)
         r"\beyJ[A-Za-z0-9_-]{10,}\.[A-Za-z0-9_-]+\.[A-Za-z0-9_-]*",
-        # Azure SAS tokens in URLs
-        r"[?&]sig=[A-Za-z0-9%+/=]+",
+        # Azure SAS tokens in URLs. The delimiter is a lookbehind, like the
+        # `key=` pattern above, so the `?` or `&` survives and the redacted URL
+        # stays well formed (this string is often a request line in a log).
+        r"(?<=[?&])sig=[A-Za-z0-9%+/=]+",
         # Full JSON service-account blobs (single-line and multi-line)
         r'\{[^{}]*"type"\s*:\s*"service_account"[^{}]*(?:\{[^{}]*\}[^{}]*)*\}',
     ]
diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
index 0e2139d688b..0e01577b20e 100644
--- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
+++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
@@ -36,6 +36,8 @@ from litellm.types.utils import (
 from litellm.utils import print_verbose, token_counter
 
 if TYPE_CHECKING:
+    from openai.types.completion_usage import CompletionUsage
+
     from litellm.litellm_core_utils.litellm_logging import Logging
     from litellm.types.litellm_core_utils.streaming_chunk_builder_utils import (
         UsagePerChunk,
@@ -73,6 +75,18 @@ class _ContentChunk(TypedDict):
     choices: Sequence[_ContentChoice]
 
 
+class _FunctionCallDelta(TypedDict):
+    function_call: ReadOnly[FunctionCall]
+
+
+class _FunctionCallChoice(TypedDict):
+    delta: ReadOnly[_FunctionCallDelta]
+
+
+class _FunctionCallChunk(TypedDict):
+    choices: ReadOnly[Sequence[_FunctionCallChoice]]
+
+
 class _AudioDelta(TypedDict, total=False):
     audio: ChatCompletionAudioDelta | None
 
@@ -588,7 +602,7 @@ class ChunkProcessor:
 
         return tool_calls_list
 
-    def get_combined_function_call_content(self, function_call_chunks: list[dict[str, Any]]) -> FunctionCall:
+    def get_combined_function_call_content(self, function_call_chunks: Sequence["_FunctionCallChunk"]) -> FunctionCall:
         argument_list: Final = []
         delta = function_call_chunks[0]["choices"][0]["delta"]
         function_call = delta.get("function_call", "")
@@ -782,7 +796,7 @@ class ChunkProcessor:
 
     @staticmethod
     def _extract_usage_chunk(chunk: "_UsageBearingChunk | ModelResponse | ModelResponseStream") -> Usage | None:
-        usage_chunk: Usage | None = None
+        usage_chunk: Usage | CompletionUsage | None = None
         if hasattr(chunk, "usage") and chunk.usage is not None:
             usage_chunk = chunk.usage
         elif "usage" in chunk:
@@ -794,7 +808,9 @@ class ChunkProcessor:
 
         if isinstance(usage_chunk, dict):
             return Usage(**usage_chunk)
-        return usage_chunk
+        if usage_chunk is None or isinstance(usage_chunk, Usage):
+            return usage_chunk
+        return Usage(**usage_chunk.model_dump())
 
     def _calculate_usage_per_chunk(
         self,
diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py
index 1e0b778d244..480b1921c18 100644
--- a/litellm/litellm_core_utils/streaming_handler.py
+++ b/litellm/litellm_core_utils/streaming_handler.py
@@ -93,7 +93,7 @@ def print_verbose(print_statement: object):
 
 @dataclass(frozen=True, slots=True)
 class _ProviderChunkParsed:
-    response_obj: dict[str, Any]
+    response_obj: dict[str, object]
 
 
 @dataclass(frozen=True, slots=True)
@@ -862,6 +862,8 @@ class CustomStreamWrapper:
         model_response: Final = ModelResponseStream(**args)
         if self.response_id is not None:
             model_response.id = self.response_id
+        elif model_response.id:
+            self.response_id = model_response.id
         if self.system_fingerprint is not None:
             model_response.system_fingerprint = self.system_fingerprint
 
@@ -1288,7 +1290,7 @@ class CustomStreamWrapper:
                 for key, value in anthropic_response_obj["provider_specific_fields"].items():
                     setattr(model_response, key, value)
 
-            response_obj = cast(dict[str, Any], anthropic_response_obj)
+            response_obj = cast(dict[str, object], anthropic_response_obj)
         elif self.model == "replicate" or self.custom_llm_provider == "replicate":
             response_obj = self.handle_replicate_chunk(chunk)
             completion_obj["content"] = response_obj["text"]
@@ -1444,7 +1446,7 @@ class CustomStreamWrapper:
             if not isinstance(chunk, str):
                 raise ValueError(f"chunk is not a string: {chunk}")
             response_obj = cast(
-                dict[str, Any],
+                dict[str, object],
                 litellm.CodestralTextCompletionConfig()._chunk_parser(chunk),
             )
             completion_obj["content"] = response_obj["text"]
@@ -2551,7 +2553,7 @@ def calculate_total_usage(chunks: list[ModelResponse]) -> Usage:
 
     prompt_tokens: int = 0
     completion_tokens: int = 0
-    latest_usage_chunk = None
+    latest_usage_chunk: Usage | Mapping[str, int] | None = None
     prompt_tokens_details: PromptTokensDetailsWrapper | None = None
     completion_tokens_details: CompletionTokensDetailsWrapper | None = None
     cache_creation_token_details: CacheCreationTokenDetails | None = None
diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py
index 256bee7b348..3732ffd734c 100644
--- a/litellm/litellm_core_utils/token_counter.py
+++ b/litellm/litellm_core_utils/token_counter.py
@@ -4,8 +4,9 @@ import base64
 import io
 import struct
 from collections.abc import Callable, Iterable, Mapping, Sequence
-from typing import Any, Final, Literal, cast
+from typing import Final, Literal, cast
 
+import httpx
 import tiktoken
 
 import litellm
@@ -171,6 +172,10 @@ def calculate_tiles_needed(
     return total_tiles
 
 
+def _unpack_ints(fmt: str, buffer: bytes) -> tuple[int, ...]:
+    return struct.unpack(fmt, buffer)
+
+
 def get_image_type(image_data: bytes) -> str | None:
     """take an image (really only the first ~100 bytes max are needed)
     and return 'png' 'gif' 'jpeg' 'webp' 'heic' or None. method added to
@@ -210,9 +215,9 @@ def get_image_dimensions(
     if data.startswith(("http://", "https://")):
         try:
             client: Final = _get_httpx_client()
-            response: Final = safe_get(client, data)
+            response: Final[httpx.Response] = safe_get(client, data)
             max_bytes: Final = int(MAX_IMAGE_URL_DOWNLOAD_SIZE_MB * 1024 * 1024)
-            content_length: Final = response.headers.get("Content-Length")
+            content_length: Final[str | None] = response.headers.get("Content-Length")
             if content_length is not None and int(content_length) > max_bytes:
                 pass  # skip download; img_data stays None
             else:
@@ -229,10 +234,10 @@ def get_image_dimensions(
     img_type: Final = get_image_type(img_data)
 
     if img_type == "png":
-        w, h = struct.unpack(">LL", img_data[16:24])
+        w, h = _unpack_ints(">LL", img_data[16:24])
         return w, h
     elif img_type == "gif":
-        w, h = struct.unpack("<HH", img_data[6:10])
+        w, h = _unpack_ints("<HH", img_data[6:10])
         return w, h
     elif img_type == "jpeg":
         with io.BytesIO(img_data) as fhandle:
@@ -245,25 +250,25 @@ def get_image_dimensions(
                 while ord(byte) == 0xFF:
                     byte = fhandle.read(1)
                 ftype = ord(byte)
-                size = struct.unpack(">H", fhandle.read(2))[0] - 2
+                size = _unpack_ints(">H", fhandle.read(2))[0] - 2
             fhandle.seek(1, 1)
-            h, w = struct.unpack(">HH", fhandle.read(4))
+            h, w = _unpack_ints(">HH", fhandle.read(4))
         return w, h
     elif img_type == "webp":
         # For WebP, the dimensions are stored at different offsets depending on the format
         # Check for VP8X (extended format)
         if img_data[12:16] == b"VP8X":
-            w = struct.unpack("<I", img_data[24:27] + b"\x00")[0] + 1
-            h = struct.unpack("<I", img_data[27:30] + b"\x00")[0] + 1
+            w = _unpack_ints("<I", img_data[24:27] + b"\x00")[0] + 1
+            h = _unpack_ints("<I", img_data[27:30] + b"\x00")[0] + 1
             return w, h
         # Check for VP8 (lossy format)
         elif img_data[12:16] == b"VP8 ":
-            w = struct.unpack("<H", img_data[26:28])[0] & 0x3FFF
-            h = struct.unpack("<H", img_data[28:30])[0] & 0x3FFF
+            w = _unpack_ints("<H", img_data[26:28])[0] & 0x3FFF
+            h = _unpack_ints("<H", img_data[28:30])[0] & 0x3FFF
             return w, h
         # Check for VP8L (lossless format)
         elif img_data[12:16] == b"VP8L":
-            bits: Final = struct.unpack("<I", img_data[21:25])[0]
+            bits: Final = _unpack_ints("<I", img_data[21:25])[0]
             w = (bits & 0x3FFF) + 1
             h = ((bits >> 14) & 0x3FFF) + 1
             return w, h
@@ -420,8 +425,8 @@ def token_counter(
 
 def _count_function_call_tokens(
     key: str,
-    value: Any,
-    message: Mapping[str, Any],
+    value: object,
+    message: Mapping[str, object],
     count_function: TokenCounterFunction,
 ) -> int:
     """
@@ -587,7 +592,7 @@ def _fix_model_name(model: str) -> str:
 
 
 def _count_image_tokens(
-    image_url: Any,
+    image_url: object,
     use_default_image_token_count: bool,
 ) -> int:
     """
@@ -627,7 +632,7 @@ def _count_image_tokens(
         raise ValueError(f"Invalid image_url type: {type(image_url).__name__}. Expected str or dict with 'url' field.")
 
 
-def _validate_anthropic_content(content: Mapping[str, Any]) -> type:
+def _validate_anthropic_content(content: Mapping[str, object]) -> type:
     """
     Validate and determine which Anthropic TypedDict applies.
 
@@ -642,7 +647,7 @@ def _validate_anthropic_content(content: Mapping[str, Any]) -> type:
         "tool_result": AnthropicMessagesToolResultParam,
     }
 
-    expected_cls: Final = mapping.get(content_type)
+    expected_cls: Final = mapping.get(content_type) if isinstance(content_type, str) else None
     if expected_cls is None:
         raise ValueError(f"Unknown Anthropic content type: '{content_type}'")
 
@@ -693,8 +698,28 @@ def _count_document_tokens(
     )
 
 
+def _count_file_tokens(
+    file_value: object,
+    count_function: TokenCounterFunction,
+    use_default_image_token_count: bool,
+) -> int:
+    """An OpenAI `file` block is the chat-completions spelling of a document, so it prices like one."""
+    if not isinstance(file_value, Mapping):
+        return 0
+    filename: Final = file_value.get("filename")
+    file_data: Final = file_value.get("file_data")
+    name_tokens: Final = count_function(filename) if isinstance(filename, str) and filename else 0
+    if not isinstance(file_data, str) or not file_data:
+        return name_tokens
+    return name_tokens + calculate_img_tokens(
+        data=file_data,
+        mode="auto",
+        use_default_image_token_count=use_default_image_token_count,
+    )
+
+
 def _count_anthropic_content(
-    content: Mapping[str, Any],
+    content: Mapping[str, object],
     count_function: TokenCounterFunction,
     use_default_image_token_count: bool,
     default_token_count: int | None,
@@ -709,7 +734,7 @@ def _count_anthropic_content(
     avoiding hardcoded field names.
     """
     typeddict_cls: Final = _validate_anthropic_content(content)
-    type_hints: Final = getattr(typeddict_cls, "__annotations__", {})
+    type_hints: Final[Mapping[str, object]] = getattr(typeddict_cls, "__annotations__", {})
     tokens = 0
 
     # Fields to skip (metadata/identifiers that don't contribute to prompt tokens)
@@ -778,6 +803,12 @@ def _count_content_list(
                     use_default_image_token_count,
                     default_token_count,
                 )
+            elif c["type"] == "file":
+                num_tokens += _count_file_tokens(
+                    c.get("file"),
+                    count_function,
+                    use_default_image_token_count,
+                )
             elif c["type"] in ("tool_use", "tool_result"):
                 num_tokens += _count_anthropic_content(
                     c,
@@ -807,7 +838,7 @@ def _count_content_list(
                 raise ValueError(
                     f"Invalid content item type: {content_type}. "
                     f"Expected str or dict with 'type' field "
-                    f"(text, image_url, image, document, tool_use, tool_result, thinking, tool_reference)."
+                    f"(text, image_url, image, document, file, tool_use, tool_result, thinking, tool_reference)."
                 )
         return num_tokens
     except Exception as e:
diff --git a/litellm/litellm_core_utils/url_utils.py b/litellm/litellm_core_utils/url_utils.py
index 125baa4743a..1e43117933d 100644
--- a/litellm/litellm_core_utils/url_utils.py
+++ b/litellm/litellm_core_utils/url_utils.py
@@ -417,7 +417,7 @@ def _extract_redirect_url(response: httpx.Response, request_url: str) -> str:
     return str(httpx.URL(request_url).join(location))
 
 
-def safe_get(client: Any, url: str, **kwargs: Any) -> Any:
+def safe_get(client: Any, url: str, **kwargs: Any) -> httpx.Response:
     """
     Fetch a user-supplied URL with SSRF protection on every redirect hop.
 
@@ -460,7 +460,7 @@ def safe_get(client: Any, url: str, **kwargs: Any) -> Any:
     raise SSRFError("Too many redirects")
 
 
-async def async_safe_get(client: Any, url: str, **kwargs: Any) -> Any:
+async def async_safe_get(client: Any, url: str, **kwargs: Any) -> httpx.Response:
     """Async version of safe_get."""
     if not getattr(litellm, "user_url_validation", True):
         kwargs.setdefault("follow_redirects", True)
diff --git a/litellm/llms/a2a/chat/guardrail_translation/handler.py b/litellm/llms/a2a/chat/guardrail_translation/handler.py
index 1c5ba951942..f1c7451796d 100644
--- a/litellm/llms/a2a/chat/guardrail_translation/handler.py
+++ b/litellm/llms/a2a/chat/guardrail_translation/handler.py
@@ -11,8 +11,11 @@ A2A Protocol Format:
 """
 
 import json
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Optional
 
+from typing_extensions import ReadOnly, TypedDict
+
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
 from litellm.types.utils import GenericGuardrailAPIInputs
@@ -23,6 +26,13 @@ if TYPE_CHECKING:
     from litellm.proxy._types import UserAPIKeyAuth
 
 
+class _A2ATextPart(TypedDict, total=False):
+    """The subset of an A2A message part this handler reads text from."""
+
+    kind: ReadOnly[str]
+    text: ReadOnly[str]
+
+
 class A2AGuardrailHandler(BaseTranslation):
     """
     Handler for processing A2A Protocol messages with guardrails.
@@ -41,7 +51,7 @@ class A2AGuardrailHandler(BaseTranslation):
         data: dict,
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
-    ) -> Any:
+    ) -> dict:
         """
         Process A2A input messages by applying guardrails to text content.
 
@@ -214,12 +224,12 @@ class A2AGuardrailHandler(BaseTranslation):
 
     async def process_output_streaming_response(
         self,
-        responses_so_far: list[Any],
+        responses_so_far: list[object],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
         request_data: dict | None = None,
-    ) -> list[Any]:
+    ) -> list[object]:
         """
         Process A2A streaming output by applying guardrails to accumulated text.
 
@@ -305,11 +315,12 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _parse_streaming_responses(
         self,
-        responses_so_far: list[Any],
-    ) -> tuple[list[dict[str, Any] | None], list[tuple[int, dict[str, Any]]]]:
+        responses_so_far: list[object],
+    ) -> tuple[list[dict[str, object] | None], list[tuple[int, dict[str, object]]]]:
         """Parse JSON-RPC items, returning aligned parsed list and valid entries."""
-        parsed: Final[list[dict[str, Any] | None]] = [None] * len(responses_so_far)
+        parsed: Final[list[dict[str, object] | None]] = [None] * len(responses_so_far)
         for i, item in enumerate(responses_so_far):
+            obj: dict[str, object]
             if isinstance(item, dict):
                 obj = item
             elif isinstance(item, str):
@@ -326,7 +337,7 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _collect_text_from_parsed_chunks(
         self,
-        valid_parsed: list[tuple[int, dict[str, Any]]],
+        valid_parsed: list[tuple[int, dict[str, object]]],
     ) -> tuple[str, list[int]]:
         """Collect text from parsed chunks, returning combined text and indices."""
         from litellm.llms.a2a.common_utils import extract_text_from_a2a_response
@@ -411,7 +422,7 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _extract_texts_from_parts(
         self,
-        parts: list[dict[str, Any]],
+        parts: Sequence[_A2ATextPart],
         path: tuple[str, ...],
         texts_to_check: list[str],
         task_mappings: list[tuple[tuple[str, ...], int]],
diff --git a/litellm/llms/anthropic/batches/transformation.py b/litellm/llms/anthropic/batches/transformation.py
index 6b39adc511e..4f4d39f09b0 100644
--- a/litellm/llms/anthropic/batches/transformation.py
+++ b/litellm/llms/anthropic/batches/transformation.py
@@ -1,9 +1,11 @@
 import json
 import time
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final, Literal, cast
 
 import httpx
 from httpx import Headers, Response
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.litellm_core_utils.url_utils import encode_url_path_segment
 from litellm.llms.base_llm.batches.transformation import BaseBatchesConfig
@@ -21,6 +23,29 @@ else:
     LoggingClass = Any
 
 
+class AnthropicBatchRequestCounts(TypedDict, total=False):
+    """The ``request_counts`` object of an Anthropic Message Batch."""
+
+    processing: ReadOnly[int]
+    succeeded: ReadOnly[int]
+    errored: ReadOnly[int]
+    canceled: ReadOnly[int]
+    expired: ReadOnly[int]
+
+
+class AnthropicMessageBatch(TypedDict, total=False):
+    """The fields of an Anthropic Message Batch that map onto an OpenAI Batch."""
+
+    id: ReadOnly[str]
+    processing_status: ReadOnly[str]
+    created_at: ReadOnly[str | None]
+    ended_at: ReadOnly[str | None]
+    expires_at: ReadOnly[str | None]
+    cancel_initiated_at: ReadOnly[str | None]
+    archived_at: ReadOnly[str | None]
+    request_counts: ReadOnly[AnthropicBatchRequestCounts]
+
+
 class AnthropicBatchesConfig(BaseBatchesConfig):
     def __init__(self):
         from ..chat.transformation import AnthropicConfig
@@ -85,7 +110,7 @@ class AnthropicBatchesConfig(BaseBatchesConfig):
         create_batch_data: CreateBatchRequest,
         optional_params: dict,
         litellm_params: dict,
-    ) -> bytes | str | dict[str, Any]:
+    ) -> bytes | str | dict[str, object]:
         """
         Transform the batch creation request to Anthropic format.
 
@@ -135,7 +160,7 @@ class AnthropicBatchesConfig(BaseBatchesConfig):
         batch_id: str,
         optional_params: dict,
         litellm_params: dict,
-    ) -> bytes | str | dict[str, Any]:
+    ) -> bytes | str | dict[str, object]:
         """
         Transform batch retrieval request for Anthropic.
 
@@ -154,7 +179,7 @@ class AnthropicBatchesConfig(BaseBatchesConfig):
     ) -> LiteLLMBatch:
         """Transform Anthropic MessageBatch retrieval response to LiteLLM format."""
         try:
-            response_data: Final = raw_response.json()
+            response_data: Final[AnthropicMessageBatch] = raw_response.json()
         except Exception as e:
             raise ValueError(f"Failed to parse Anthropic batch response: {e}")
 
@@ -163,18 +188,20 @@ class AnthropicBatchesConfig(BaseBatchesConfig):
         processing_status: Final = response_data.get("processing_status", "in_progress")
 
         # Map Anthropic processing_status to OpenAI status
-        status_mapping: dict[
-            str,
-            Literal[
-                "validating",
-                "failed",
-                "in_progress",
-                "finalizing",
-                "completed",
-                "expired",
-                "cancelling",
-                "cancelled",
-            ],
+        status_mapping: Final[
+            Mapping[
+                str,
+                Literal[
+                    "validating",
+                    "failed",
+                    "in_progress",
+                    "finalizing",
+                    "completed",
+                    "expired",
+                    "cancelling",
+                    "cancelled",
+                ],
+            ]
         ] = {
             "in_progress": "in_progress",
             "canceling": "cancelling",
@@ -281,7 +308,7 @@ class AnthropicBatchesConfig(BaseBatchesConfig):
                 if not line:
                     continue
                 try:
-                    response_json = json.loads(line)
+                    response_json: Mapping[str, Mapping[str, dict[str, object]]] = json.loads(line)
                     # Update model_response with the parsed JSON
                     completion_response = response_json["result"]["message"]
                     transformed_response = self.anthropic_chat_config.transform_parsed_response(
diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py
index b9ca18c7843..c7d12e5cf3a 100644
--- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py
+++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py
@@ -16,9 +16,9 @@ import json
 from collections.abc import Mapping, Sequence
 from copy import deepcopy
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Final, cast
+from typing import TYPE_CHECKING, Any, Final, Protocol, cast, overload, runtime_checkable
 
-from typing_extensions import assert_never
+from typing_extensions import ReadOnly, TypedDict, assert_never
 
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.anthropic.chat.transformation import AnthropicConfig
@@ -58,6 +58,8 @@ from litellm.types.utils import (
 )
 
 if TYPE_CHECKING:
+    from fastapi import HTTPException
+
     from litellm.integrations.custom_guardrail import (
         CustomGuardrail,
         ModifyResponseException,
@@ -98,6 +100,38 @@ InputWriteBackTarget = (
 )
 
 
+def _as_str_mapping(value: Mapping[str, object]) -> Mapping[str, object]:
+    return value
+
+
+def _content_block_at(blocks: Sequence[object], index: int) -> object:
+    return blocks[index]
+
+
+@runtime_checkable
+class _ModelDumpBlock(Protocol):
+    def model_dump(self) -> Mapping[str, object]: ...
+
+
+@runtime_checkable
+class _TextAttrBlock(Protocol):
+    text: str
+
+
+class _WritableMessage(Protocol):
+    @overload
+    def get(self, key: str, /) -> object | None: ...
+
+    @overload
+    def get(self, key: str, default: object, /) -> object: ...
+
+    def __setitem__(self, key: str, value: object, /) -> None: ...
+
+
+def _as_writable(value: _WritableMessage) -> _WritableMessage:
+    return value
+
+
 @dataclass(frozen=True, slots=True)
 class ScannedText:
     text: str
@@ -113,6 +147,16 @@ class ExtractedInput:
 EMPTY_EXTRACTED_INPUT: Final = ExtractedInput(scanned=(), images=())
 
 
+class _AnthropicSSEDelta(TypedDict, total=False):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+    stop_reason: ReadOnly[str | None]
+
+
+class _AnthropicSSEEvent(TypedDict, total=False):
+    delta: ReadOnly[_AnthropicSSEDelta]
+
+
 class AnthropicMessagesHandler(BaseTranslation):
     """Process Anthropic messages with guardrails.
 
@@ -126,7 +170,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _build_streaming_usage_response(
-        responses_so_far: list[object],
+        responses_so_far: Sequence[object],
         request_data: dict | None,
     ) -> ModelResponse | None:
         chunks: Final = tuple(response for response in responses_so_far if isinstance(response, (str, bytes)))
@@ -144,7 +188,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         self,
         exc: "ModifyResponseException",
         stream_started: bool = False,
-        responses_so_far: list[object] | None = None,
+        responses_so_far: Sequence[object] | None = None,
     ) -> list[bytes]:
         """
         Build an Anthropic SSE sequence delivering the guardrail block message
@@ -162,9 +206,22 @@ class AnthropicMessagesHandler(BaseTranslation):
           would make Anthropic clients reject the stream.
         """
         if stream_started:
-            return self._block_continuation_chunks(exc, responses_so_far or [])
+            return list(self._block_continuation_chunks(exc, responses_so_far or []))
         return self._standalone_block_chunks(exc)
 
+    def build_stream_error_items(
+        self,
+        exc: "HTTPException",
+        responses_so_far: Sequence[Any] | None = None,
+    ) -> Sequence[Any] | None:
+        from litellm.proxy.common_request_processing import (
+            serialize_http_exception_detail,
+        )
+        from litellm.proxy.guardrails.anthropic_sse import anthropic_sse_error_frames
+
+        message, _ = serialize_http_exception_detail(exc.detail)
+        return tuple(anthropic_sse_error_frames(message))
+
     def _standalone_block_chunks(self, exc: "ModifyResponseException") -> list[bytes]:
         import uuid
 
@@ -187,7 +244,9 @@ class AnthropicMessagesHandler(BaseTranslation):
         )
         return list(FakeAnthropicMessagesStreamIterator(response=block_response))
 
-    def _block_continuation_chunks(self, exc: "ModifyResponseException", responses_so_far: list[object]) -> list[bytes]:
+    def _block_continuation_chunks(
+        self, exc: "ModifyResponseException", responses_so_far: Sequence[object]
+    ) -> Sequence[bytes]:
         """Continue an already-started message: close the open content block,
         append the block message as a new text block, then end the message --
         without a second message_start."""
@@ -199,7 +258,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         def _sse(event_type: str, payload: dict) -> bytes:
             return f"event: {event_type}\ndata: {json.dumps(payload)}\n\n".encode()
 
-        output_tokens: Final = blocked_response_usage(getattr(exc, "original_response", None))["output_tokens"]
+        output_tokens: Final = blocked_response_usage(getattr(exc, "original_response", None)).get("output_tokens", 0)
         open_index, max_index = self._content_block_state(responses_so_far)
         new_index: Final = (max_index + 1) if max_index is not None else 0
         chunks: list[bytes] = []
@@ -237,7 +296,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _content_block_state(
-        responses_so_far: list[object],
+        responses_so_far: Sequence[object],
     ) -> tuple[int | None, int | None]:
         """From the SSE chunks already sent to the client, return (open
         content-block index or None, highest content-block index seen or None).
@@ -263,7 +322,20 @@ class AnthropicMessagesHandler(BaseTranslation):
         return open_index, max_index
 
     @staticmethod
-    def _iter_sse_events(item: object) -> list[dict[str, object]]:
+    def _parse_sse_data_line(raw_line: str) -> tuple[Mapping[str, object], ...]:
+        line: Final = raw_line.strip()
+        if not line.startswith("data:"):
+            return ()
+        try:
+            parsed: Final[object] = json.loads(line[len("data:") :].strip())
+        except json.JSONDecodeError:
+            return ()
+        if not isinstance(parsed, dict):
+            return ()
+        return (_as_str_mapping(parsed),)
+
+    @staticmethod
+    def _iter_sse_events(item: object) -> Sequence[Mapping[str, object]]:
         """Yield the event-data dicts in one stream chunk.
 
         Handles both formats this stream can carry (see
@@ -271,24 +343,15 @@ class AnthropicMessagesHandler(BaseTranslation):
         several events separated by a blank line -- and an already-parsed event
         ``dict``."""
         if isinstance(item, dict):
-            return [item]
+            return (_as_str_mapping(item),)
         if not isinstance(item, (bytes, bytearray)):
-            return []
-        events: Final[list[dict[str, object]]] = []
-        for block in item.decode("utf-8", errors="replace").split("\n\n"):
-            for line in block.split("\n"):
-                line = line.strip()
-                if not line.startswith("data:"):
-                    continue
-                try:
-                    parsed: str | int | float | bool | None | Sequence[object] | Mapping[str, object] = json.loads(
-                        line[len("data:") :].strip()
-                    )
-                except json.JSONDecodeError:
-                    continue
-                if isinstance(parsed, dict):
-                    events.append(parsed)
-        return events
+            return ()
+        return tuple(
+            event
+            for block in item.decode("utf-8", errors="replace").split("\n\n")
+            for line in block.split("\n")
+            for event in AnthropicMessagesHandler._parse_sse_data_line(line)
+        )
 
     def _translate_to_openai(self, data: dict) -> ChatCompletionRequest:
         """Translate Anthropic request to OpenAI chat completion format."""
@@ -321,7 +384,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         data: dict,
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-    ) -> Any:
+    ) -> Mapping[str, object]:
         """
         Process input messages by applying guardrails to text content.
         """
@@ -481,7 +544,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _openai_system_message_to_anthropic(
-        message: dict[str, object],
+        message: Mapping[str, object],
     ) -> dict[str, object] | None:  # mutable-ok: API message payload
         """Convert an OpenAI system message to the client's Anthropic-shaped entry."""
         content: Final = message.get("content")
@@ -561,7 +624,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _defer_systems_inside_tool_exchanges(
-        structured_messages: list,  # mutable-ok: API message payload
+        structured_messages: Sequence[Mapping[str, object]],
     ) -> list:
         """Hold a system row until the tool exchange around it completes so the call/result pair converts together."""
         from litellm.litellm_core_utils.prompt_templates.factory import group_tool_exchanges
@@ -755,7 +818,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         if scan_only_tool_results:
             return EMPTY_EXTRACTED_INPUT
 
-        text_str: Final = content_item.get("text", None)
+        text_str: Final[str | None] = content_item.get("text")
         return ExtractedInput(
             scanned=(
                 () if text_str is None else (ScannedText(text_str, ContentBlockTextTarget(msg_idx, content_idx)),)
@@ -796,16 +859,32 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _image_sources(block: Mapping[str, object]) -> tuple[str, ...]:
+        """Normalize an Anthropic image block into strings a guardrail can read.
+
+        base64 becomes a data URI so the format travels with the payload, which is what
+        the OpenAI path already puts in this field. A file source yields nothing: those
+        bytes live behind the Files API and this extractor has no client to fetch them.
+        """
         source: Final = block.get("source")
         if not isinstance(source, Mapping):
             return ()
-        # Could be base64 or url
+
+        source_type: Final = source.get("type")
+        if source_type == "url":
+            url: Final = source.get("url")
+            return (url,) if isinstance(url, str) and url else ()
+
         data: Final = source.get("data")
-        return (data,) if data else ()
+        if not isinstance(data, str) or not data:
+            return ()
+        media_type: Final = source.get("media_type")
+        if isinstance(media_type, str) and media_type:
+            return (f"data:{media_type};base64,{data}",)
+        return (data,)
 
     async def _apply_guardrail_responses_to_input(
         self,
-        messages: list[dict[str, object]],
+        messages: Sequence[_WritableMessage],
         responses: list[str],
         scanned: tuple[ScannedText, ...],
     ) -> None:
@@ -931,7 +1010,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
         user_api_key_dict: "UserAPIKeyAuth | None" = None,
         request_data: dict | None = None,
-    ) -> list[Any]:
+    ) -> Sequence[object]:
         """
         Process output streaming response by applying guardrails to text content.
 
@@ -1027,7 +1106,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         return request_data
 
     @staticmethod
-    def _get_response_content(response: object) -> list[Any]:
+    def _get_response_content(response: object) -> Sequence[object]:
         """Extract content list from a dict or object response."""
         if isinstance(response, dict):
             return response.get("content", []) or []
@@ -1037,7 +1116,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     def _extract_from_content_blocks(
         self,
-        response_content: list[Any],
+        response_content: Sequence[object],
         texts_to_check: list[str],
         images_to_check: list[str],
         task_mappings: list[tuple[int, int | None]],
@@ -1045,21 +1124,10 @@ class AnthropicMessagesHandler(BaseTranslation):
     ) -> None:
         """Extract text, images, and tool calls from content blocks."""
         for content_idx, content_block in enumerate(response_content):
-            block_dict: dict[str, object] = {}
-            if isinstance(content_block, dict):
-                block_type = content_block.get("type")
-                block_dict = cast(dict[str, object], content_block)
-            elif hasattr(content_block, "type"):
-                block_type = getattr(content_block, "type", None)
-                if hasattr(content_block, "model_dump"):
-                    block_dict = content_block.model_dump()
-                else:
-                    block_dict = {
-                        "type": block_type,
-                        "text": getattr(content_block, "text", None),
-                    }
-            else:
+            fields = self._output_block_fields(content_block)
+            if fields is None:
                 continue
+            block_type, block_dict = fields
 
             if block_type in ["text", "tool_use"]:
                 self._extract_output_text_and_images(
@@ -1071,6 +1139,21 @@ class AnthropicMessagesHandler(BaseTranslation):
                     tool_calls_to_check=tool_calls_to_check,
                 )
 
+    @staticmethod
+    def _output_block_fields(content_block: object) -> "tuple[object, Mapping[str, object]] | None":
+        if isinstance(content_block, dict):
+            block_dict: Final = _as_str_mapping(content_block)
+            return block_dict.get("type"), block_dict
+        if not hasattr(content_block, "type"):
+            return None
+        block_type: Final = getattr(content_block, "type", None)
+        if isinstance(content_block, _ModelDumpBlock):
+            return block_type, content_block.model_dump()
+        return block_type, {
+            "type": block_type,
+            "text": getattr(content_block, "text", None),
+        }
+
     @staticmethod
     def _build_guardrail_inputs(
         texts_to_check: list[str],
@@ -1093,7 +1176,7 @@ class AnthropicMessagesHandler(BaseTranslation):
             inputs["model"] = response_model
         return inputs
 
-    def get_streaming_string_so_far(self, responses_so_far: list[Any]) -> str:
+    def get_streaming_string_so_far(self, responses_so_far: Sequence[object]) -> str:
         """
         Parse streaming responses and extract accumulated text content.
 
@@ -1164,8 +1247,8 @@ class AnthropicMessagesHandler(BaseTranslation):
                 # Only process content_block_delta events
                 if event_type == "content_block_delta" and data_line:
                     try:
-                        data = json.loads(data_line)
-                        delta = data.get("delta", {})
+                        data: _AnthropicSSEEvent = json.loads(data_line)
+                        delta: _AnthropicSSEDelta = data.get("delta", {})
                         if delta.get("type") == "text_delta":
                             text += delta.get("text", "")
                     except json.JSONDecodeError:
@@ -1176,7 +1259,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
         return text
 
-    def _check_streaming_has_ended(self, responses_so_far: list[Any]) -> bool:
+    def _check_streaming_has_ended(self, responses_so_far: Sequence[object]) -> bool:
         """
         Check if streaming response has ended by looking for non-null stop_reason.
 
@@ -1227,9 +1310,9 @@ class AnthropicMessagesHandler(BaseTranslation):
                         # Check for message_delta event with stop_reason
                         if event_type == "message_delta" and data_line:
                             try:
-                                data = json.loads(data_line)
-                                delta = data.get("delta", {})
-                                stop_reason = delta.get("stop_reason")
+                                data: _AnthropicSSEEvent = json.loads(data_line)
+                                delta: _AnthropicSSEDelta = data.get("delta", {})
+                                stop_reason: str | None = delta.get("stop_reason")
                                 if stop_reason is not None:
                                     return True
                             except json.JSONDecodeError:
@@ -1271,7 +1354,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     def _extract_output_text_and_images(
         self,
-        content_block: dict[str, object],
+        content_block: Mapping[str, object],
         content_idx: int,
         texts_to_check: list[str],
         images_to_check: list[str],
@@ -1294,7 +1377,7 @@ class AnthropicMessagesHandler(BaseTranslation):
                 task_mappings.append((content_idx, None))
 
         # Extract tool calls
-        elif content_type == "tool_use":
+        elif content_type == "tool_use" and isinstance(content_block, dict):
             tool_call: Final = AnthropicConfig.convert_tool_use_to_openai_format(
                 anthropic_tool_content=content_block,
                 index=content_idx,
@@ -1319,7 +1402,7 @@ class AnthropicMessagesHandler(BaseTranslation):
             content_idx = cast(int, mapping[0])
 
             # Handle both dict and object responses
-            response_content: list[Any] = []
+            response_content: Sequence[object] = []
             if isinstance(response, dict):
                 response_content = response.get("content", []) or []
             elif hasattr(response, "content"):
@@ -1335,14 +1418,15 @@ class AnthropicMessagesHandler(BaseTranslation):
             if content_idx >= len(response_content):
                 continue
 
-            content_block = response_content[content_idx]
+            content_block = _content_block_at(response_content, content_idx)
 
             # Verify it's a text block and update the text field
             # Handle both dict and Pydantic object content blocks
             if isinstance(content_block, dict):
-                if content_block.get("type") == "text":
-                    cast(dict[str, object], content_block)["text"] = guardrail_response
+                block = _as_writable(content_block)
+                if block.get("type") == "text":
+                    block["text"] = guardrail_response
             elif hasattr(content_block, "type") and getattr(content_block, "type", None) == "text":
                 # Update Pydantic object's text attribute
-                if hasattr(content_block, "text"):
+                if isinstance(content_block, _TextAttrBlock):
                     content_block.text = guardrail_response
diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py
index cd47cdd57d6..c82be07a5c5 100644
--- a/litellm/llms/anthropic/chat/handler.py
+++ b/litellm/llms/anthropic/chat/handler.py
@@ -66,6 +66,10 @@ if TYPE_CHECKING:
     from litellm.llms.base_llm.chat.transformation import BaseConfig
 
 
+def _loads_stream_chunk(payload: str) -> dict[str, object]:
+    return json.loads(payload)
+
+
 async def make_call(
     client: AsyncHTTPHandler | None,
     api_base: str,
@@ -78,7 +82,7 @@ async def make_call(
     json_mode: bool,
     speed: str | None = None,
     tool_name_reverse_map: dict[str, str] | None = None,
-) -> tuple[Any, httpx.Headers]:
+) -> tuple["ModelResponseIterator", httpx.Headers]:
     if client is None:
         client = litellm.module_level_aclient
 
@@ -93,7 +97,7 @@ async def make_call(
         )
     except httpx.HTTPStatusError as e:
         error_headers = getattr(e, "headers", None)
-        error_response: Final = getattr(e, "response", None)
+        error_response: Final[object] = getattr(e, "response", None)
         if error_headers is None and error_response:
             error_headers = getattr(error_response, "headers", None)
         raise AnthropicError(
@@ -138,7 +142,7 @@ def make_sync_call(
     json_mode: bool,
     speed: str | None = None,
     tool_name_reverse_map: dict[str, str] | None = None,
-) -> tuple[Any, httpx.Headers]:
+) -> tuple["ModelResponseIterator", httpx.Headers]:
     if client is None:
         client = litellm.module_level_client  # re-use a module level client
 
@@ -153,7 +157,7 @@ def make_sync_call(
         )
     except httpx.HTTPStatusError as e:
         error_headers = getattr(e, "headers", None)
-        error_response: Final = getattr(e, "response", None)
+        error_response: Final[object] = getattr(e, "response", None)
         if error_headers is None and error_response:
             error_headers = getattr(error_response, "headers", None)
         raise AnthropicError(
@@ -292,7 +296,7 @@ class AnthropicChatCompletion(BaseLLM):
             status_code: Final = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
             error_text = getattr(e, "text", str(e))
-            error_response: Final = getattr(e, "response", None)
+            error_response: Final[object] = getattr(e, "response", None)
             if error_headers is None and error_response:
                 error_headers = getattr(error_response, "headers", None)
             if error_response and hasattr(error_response, "text"):
@@ -593,7 +597,7 @@ class AnthropicChatCompletion(BaseLLM):
                     status_code: Final = getattr(e, "status_code", 500)
                     error_headers = getattr(e, "headers", None)
                     error_text = getattr(e, "text", str(e))
-                    error_response: Final = getattr(e, "response", None)
+                    error_response: Final[object] = getattr(e, "response", None)
                     if error_headers is None and error_response:
                         error_headers = getattr(error_response, "headers", None)
                     if error_response and hasattr(error_response, "text"):
@@ -664,10 +668,10 @@ class ModelResponseIterator:
 
         # Accumulate web_search_tool_result blocks for multi-turn reconstruction
         # See: https://github.com/BerriAI/litellm/issues/17737
-        self.web_search_results: list[dict[str, Any]] = []
+        self.web_search_results: list[dict[str, object]] = []
 
         # Accumulate compaction blocks for multi-turn reconstruction
-        self.compaction_blocks: list[dict[str, Any]] = []
+        self.compaction_blocks: list[dict[str, object]] = []
 
         # Accumulate streamed thinking text so final usage can split reasoning
         # tokens from regular output tokens.
@@ -727,7 +731,7 @@ class ModelResponseIterator:
         str,
         ChatCompletionToolCallChunk | None,
         list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock],
-        dict[str, Any],
+        dict[str, object],
         str | None,
     ]:
         """
@@ -735,7 +739,7 @@ class ModelResponseIterator:
         """
         text = ""
         tool_use: ChatCompletionToolCallChunk | None = None
-        provider_specific_fields: Final = {}
+        provider_specific_fields: Final[dict[str, object]] = {}
         reasoning_content: str | None = None
         content_block: Final = ContentBlockDelta(**chunk)
         thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] = []
@@ -809,8 +813,8 @@ class ModelResponseIterator:
     def _handle_redacted_thinking_content(
         self,
         content_block_start: ContentBlockStart,
-        provider_specific_fields: dict[str, Any],
-    ) -> tuple[list[ChatCompletionRedactedThinkingBlock], dict[str, Any]]:
+        provider_specific_fields: dict[str, object],
+    ) -> tuple[list[ChatCompletionRedactedThinkingBlock], dict[str, object]]:
         """
         Handle the redacted thinking content
         """
@@ -878,7 +882,7 @@ class ModelResponseIterator:
             tool_use: ChatCompletionToolCallChunk | None = None
             finish_reason = ""
             usage: Usage | None = None
-            provider_specific_fields: dict[str, Any] = {}
+            provider_specific_fields: dict[str, object] = {}
             reasoning_content: str | None = None
             thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None = None
 
@@ -1212,7 +1216,7 @@ class ModelResponseIterator:
 
         # Try to parse as valid JSON first
         try:
-            data_json: Final = json.loads(data_str)
+            data_json: Final = _loads_stream_chunk(data_str)
             return self.chunk_parser(chunk=data_json)
         except json.JSONDecodeError:
             # Switch to accumulation mode and start accumulating
@@ -1330,7 +1334,7 @@ class ModelResponseIterator:
             str_line = str_line[index:]
 
         if str_line.startswith("data:"):
-            data_json: Final = json.loads(str_line[5:])
+            data_json: Final = _loads_stream_chunk(str_line[5:])
             return self.chunk_parser(chunk=data_json)
         else:
             return ModelResponseStream(id=self.response_id)
diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index e1387a9068c..5f7ac73c919 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any, Final, NoReturn, cast
 
 import httpx
 from pydantic import ValidationError
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm.constants import (
@@ -125,7 +126,25 @@ else:
 _ANTHROPIC_TOOL_NAME_INVALID_CHARS: Final = re.compile(r"[^a-zA-Z0-9_-]")
 _ANTHROPIC_TOOL_NAME_MAX_LEN: Final = 128
 
-_ENUM_TYPE_CHECKS: Final[Mapping[str, Callable[[Any], bool]]] = MappingProxyType(
+
+class _AnthropicUsageIteration(TypedDict, total=False):
+    """One entry of the ``usage.iterations`` array on an Anthropic response."""
+
+    input_tokens: ReadOnly[int | None]
+    output_tokens: ReadOnly[int | None]
+    cache_creation_input_tokens: ReadOnly[int | None]
+    cache_read_input_tokens: ReadOnly[int | None]
+
+
+class _AnthropicToolResultBlock(TypedDict, total=False):
+    """A ``*_tool_result`` content block on an Anthropic response."""
+
+    type: ReadOnly[str]
+    tool_use_id: ReadOnly[str]
+    content: ReadOnly[object]
+
+
+_ENUM_TYPE_CHECKS: Final[Mapping[str, Callable[[object], bool]]] = MappingProxyType(
     {
         "null": lambda v: v is None,
         "boolean": lambda v: isinstance(v, bool),
@@ -440,7 +459,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         optional_params.pop("speed", None)
 
     @staticmethod
-    def _raise_invalid_reasoning_effort(model: str, value: Any, llm_provider: str) -> NoReturn:
+    def _raise_invalid_reasoning_effort(model: str, value: object, llm_provider: str) -> NoReturn:
         """Raise a ``BadRequestError`` for an unrecognised ``reasoning_effort``.
 
         Args:
@@ -1466,7 +1485,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
                 )
 
                 if _tool_choice is not None:
-                    optional_params["tool_choice"] = _tool_choice
+                    optional_params["tool_choice"] = AnthropicConfig._apply_forced_tool_choice(
+                        model=model, tool_choice=_tool_choice, drop_params=drop_params
+                    )
             elif param == "stream" and value is True:
                 optional_params["stream"] = value
             elif param == "stop" and (isinstance(value, str) or isinstance(value, list)):
@@ -1495,7 +1516,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
                     _tool = self.map_response_format_to_anthropic_tool(value, optional_params, is_thinking_enabled)
                     if _tool is None:
                         continue
-                    if not is_thinking_enabled:
+                    if not is_thinking_enabled and not AnthropicModelInfo.forced_tool_use_unsupported(model):
                         _tool_choice = {
                             "name": RESPONSE_FORMAT_TOOL_NAME,
                             "type": "tool",
@@ -1544,6 +1565,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
                         optional_params.pop("thinking", None)
                 else:
                     optional_params["thinking"] = value
+                    AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model(
+                        model=model, optional_params=optional_params, custom_llm_provider=self._resolved_provider
+                    )
             elif param == "reasoning_effort":
                 # Accept both string ("low") and dict ({"effort": "low",
                 # "summary": "concise"}). The Responses->Chat parser keeps the
@@ -1992,19 +2016,35 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         return data
 
     def _apply_output_config(self, data: dict, model: str, optional_params: dict) -> None:
-        """Validate and apply output_config to the request data."""
+        """Validate and apply output_config to the request data.
+
+        The ``drop_params`` gate here is an effort gate: ``format`` is a
+        structured-output field, not an effort field, so it survives the drop
+        and is vetted where it is consumed (the map's
+        ``supports_native_structured_output`` flag on emission paths).
+        """
         if "output_config" not in optional_params:
             return
         output_config: Final = optional_params.get("output_config")
         if not output_config or not isinstance(output_config, dict):
             return
-        if litellm.drop_params is True and not self._model_supports_effort_param(model, self._resolved_provider):
+        if (
+            litellm.drop_params is True
+            and any(key != "format" for key in output_config)
+            and not self._model_supports_effort_param(model, self._resolved_provider)
+        ):
             litellm.verbose_logger.warning(
                 DROP_UNSUPPORTED_OUTPUT_CONFIG_WARNING,
                 model,
             )
-            optional_params.pop("output_config", None)
-            data.pop("output_config", None)
+            preserved_format: Final = output_config.get("format")
+            if preserved_format is None:
+                optional_params.pop("output_config", None)
+                data.pop("output_config", None)
+                return
+            format_only: Final = {"format": preserved_format}  # mutable-ok: json body
+            optional_params["output_config"] = format_only  # rebind-ok: out-param store
+            data["output_config"] = format_only  # rebind-ok: out-param store
             return
         effort: Final = output_config.get("effort")
         valid_efforts: Final = ["high", "medium", "low", "xhigh", "max"]
@@ -2059,22 +2099,22 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         self, completion_response: dict
     ) -> tuple[
         str,
-        list[Any] | None,
+        list[object] | None,
         list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None,
         str | None,
         list[ChatCompletionToolCallChunk],
-        list[Any] | None,
-        list[Any] | None,
-        list[Any] | None,
+        list[object] | None,
+        list[_AnthropicToolResultBlock] | None,
+        list[object] | None,
     ]:
         text_content = ""
-        citations: list[Any] | None = None
+        citations: list[object] | None = None
         thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None = None
         reasoning_content: str | None = None
         tool_calls: Final[list[ChatCompletionToolCallChunk]] = []
-        web_search_results: list[Any] | None = None
-        tool_results: list[Any] | None = None
-        compaction_blocks: list[Any] | None = None
+        web_search_results: list[object] | None = None
+        tool_results: list[_AnthropicToolResultBlock] | None = None
+        compaction_blocks: list[object] | None = None
         for idx, content in enumerate(completion_response["content"]):
             if content["type"] == "text":
                 text_content += content["text"]
@@ -2284,7 +2324,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         raw_speed: Final = _usage.get("speed")
         resolved_speed: Final = raw_speed if isinstance(raw_speed, str) else speed
 
-        iterations: Final[list[Any] | None] = _usage.get("iterations")
+        iterations: Final[Sequence[_AnthropicUsageIteration] | None] = _usage.get("iterations")
         if iterations:
             prompt_tokens = sum(it.get("input_tokens", 0) or 0 for it in iterations)
             completion_tokens = sum(it.get("output_tokens", 0) or 0 for it in iterations)
@@ -2377,7 +2417,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
 
     def _build_code_interpreter_results(
         self,
-        tool_results: list[Any],
+        tool_results: Sequence[_AnthropicToolResultBlock],
         code_by_id: dict[str, str],
         container_id: str | None,
     ) -> list[OutputCodeInterpreterCall]:
@@ -2403,11 +2443,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
     def _build_provider_specific_fields(
         self,
         completion_response: dict,
-        citations: list[Any] | None,
+        citations: Sequence[object] | None,
         thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None,
-        web_search_results: list[Any] | None,
-        tool_results: list[Any] | None,
-        compaction_blocks: list[Any] | None,
+        web_search_results: Sequence[object] | None,
+        tool_results: Sequence[_AnthropicToolResultBlock] | None,
+        compaction_blocks: Sequence[object] | None,
         tool_calls: list[ChatCompletionToolCallChunk],
     ) -> dict[str, Any]:
         provider_specific_fields: Final[dict[str, Any]] = {
diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py
index d8d6a7fc9f8..6079b709bcc 100644
--- a/litellm/llms/anthropic/common_utils.py
+++ b/litellm/llms/anthropic/common_utils.py
@@ -13,7 +13,12 @@ import httpx
 from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError
 
 import litellm
-from litellm.constants import DEFAULT_MODEL_CREATED_AT_TIME
+from litellm.constants import (
+    DEFAULT_MODEL_CREATED_AT_TIME,
+    DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
+    DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
+    DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET,
+)
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     get_file_ids_from_messages,
 )
@@ -28,10 +33,15 @@ from litellm.types.llms.anthropic import (
     ANTHROPIC_OAUTH_TOKEN_PREFIX,
     AllAnthropicToolsValues,
     AnthropicMcpServerTool,
+    AnthropicMessagesToolChoice,
 )
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.proxy.model_listing import ModelInfoResponse
 
+DROP_FORCED_TOOL_CHOICE_WARNING: Final = (
+    "Downgrading forced tool_choice to 'auto' for model=%s (drop_params=True): this model rejects tool_choice type "
+    "'any'/'tool' with a 400 because thinking is always on and a forced call would skip it."
+)
 DROP_DISABLED_THINKING_WARNING: Final = (
     "Dropping `thinking={'type': 'disabled'}` for model=%s: thinking is always on for this model and cannot be "
     "disabled (the alternative is a provider 400). The model will still think adaptively, its response can contain "
@@ -320,6 +330,45 @@ class AnthropicModelInfo(BaseLLMModelInfo):
                 status_code=400,
             )
 
+    @staticmethod
+    def forced_tool_use_unsupported(model: str) -> bool:
+        return AnthropicModelInfo._get_model_capability(model, "supports_forced_tool_use") is False
+
+    @staticmethod
+    def forced_tool_use_downgraded(model: str, drop_params: bool) -> bool:
+        """True when the model map flags the model with
+        ``supports_forced_tool_use: false`` (Fable 5.1 / Mythos 5.1 400 on
+        ``any``/``tool``) and ``drop_params`` asks for the ``auto`` downgrade;
+        raises a clean client-side 400 for such models without ``drop_params``."""
+        if not AnthropicModelInfo.forced_tool_use_unsupported(model):
+            return False
+        if not (litellm.drop_params or drop_params):
+            raise litellm.utils.UnsupportedParamsError(
+                message=(
+                    f"{model} does not support forced tool use (tool_choice='required' or a named tool). "
+                    "Use tool_choice='auto' and tell the model in the prompt when to call the tool, or set "
+                    "`litellm.drop_params = True` to downgrade to 'auto' automatically."
+                ),
+                status_code=400,
+            )
+        litellm.verbose_logger.warning(DROP_FORCED_TOOL_CHOICE_WARNING, model)
+        return True
+
+    @staticmethod
+    def _apply_forced_tool_choice(
+        model: str,
+        tool_choice: AnthropicMessagesToolChoice,
+        drop_params: bool,
+    ) -> AnthropicMessagesToolChoice:
+        if tool_choice["type"] not in ("any", "tool"):
+            return tool_choice
+        if not AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+            return tool_choice
+        disable_parallel: Final = tool_choice.get("disable_parallel_tool_use")
+        if disable_parallel is None:
+            return AnthropicMessagesToolChoice(type="auto")
+        return AnthropicMessagesToolChoice(type="auto", disable_parallel_tool_use=disable_parallel)
+
     @staticmethod
     def _strip_version_suffix(model: str) -> str:
         at: Final = model.rfind("@")
@@ -490,6 +539,51 @@ class AnthropicModelInfo(BaseLLMModelInfo):
         )
         optional_params.pop("thinking", None)
 
+    @staticmethod
+    def translate_legacy_thinking_for_adaptive_model(
+        model: str,
+        optional_params: MutableMapping[str, object],  # mutable-ok: in-place out-param like the sibling helpers
+        custom_llm_provider: str,
+    ) -> None:
+        """Translate legacy ``thinking.type=enabled`` to adaptive for the
+        adaptive-thinking models that reject it (4.7+ and the 5 families).
+        Models flagged ``supports_legacy_thinking`` (the 4.6 family) accept the
+        legacy shape natively, so it is forwarded verbatim and the caller's
+        ``budget_tokens`` cap keeps applying. Caller-provided
+        ``output_config.effort`` is never overridden.
+        """
+        if not AnthropicModelInfo._is_adaptive_thinking_model(model, custom_llm_provider):
+            return
+        if AnthropicModelInfo._supports_legacy_thinking(model, custom_llm_provider):
+            return
+        thinking: Final = optional_params.get("thinking")
+        if not isinstance(thinking, dict) or thinking.get("type") != "enabled":
+            return
+
+        effort: Final = AnthropicModelInfo._legacy_budget_to_effort(
+            model=model,
+            budget_tokens=int(thinking.get("budget_tokens") or 0),
+            custom_llm_provider=custom_llm_provider,
+        )
+        existing_output_config: Final = optional_params.get("output_config")
+        optional_params["thinking"] = {"type": "adaptive"}
+        optional_params["output_config"] = {
+            "effort": effort,
+            **(existing_output_config if isinstance(existing_output_config, dict) else MappingProxyType({})),
+        }
+
+    @staticmethod
+    def _legacy_budget_to_effort(model: str, budget_tokens: int, custom_llm_provider: str) -> str:
+        if budget_tokens >= DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET and (
+            AnthropicModelInfo._supports_model_capability(model, "supports_xhigh_reasoning_effort", custom_llm_provider)
+        ):
+            return "xhigh"
+        if budget_tokens >= DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET:
+            return "high"
+        if budget_tokens >= DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET:
+            return "medium"
+        return "low"
+
     def is_effort_used(
         self,
         optional_params: dict | None,
@@ -865,13 +959,9 @@ class AnthropicModelInfo(BaseLLMModelInfo):
                 f"Failed to fetch models from Anthropic. Status code: {response.status_code}, Response: {response.text}"
             )
 
-        models: Final = response.json()["data"]
+        models: Final[Sequence[Mapping[str, str]]] = response.json()["data"]
 
-        litellm_model_names: Final = []
-        for model in models:
-            stripped_model_name = model["id"]
-            litellm_model_name = "anthropic/" + stripped_model_name
-            litellm_model_names.append(litellm_model_name)
+        litellm_model_names: Final = ["anthropic/" + model["id"] for model in models]
         return litellm_model_names
 
     def get_token_counter(self) -> BaseTokenCounter | None:
@@ -1077,7 +1167,7 @@ def strip_empty_content_blocks_from_anthropic_messages(
     return out
 
 
-def _is_empty_text_block(block: Any) -> bool:
+def _is_empty_text_block(block: object) -> bool:
     if not isinstance(block, dict) or block.get("type") != "text":
         return False
     text: Final = block.get("text")
@@ -1131,7 +1221,7 @@ def normalize_anthropic_tool_use_id(raw_id: str) -> str:
     return sanitized or "tool_use_id"
 
 
-def _sanitize_tool_use_id_content_block(block: Any) -> Any:
+def _sanitize_tool_use_id_content_block(block: object) -> object:
     if not isinstance(block, dict):
         return block
     block_type: Final = block.get("type")
@@ -1321,6 +1411,97 @@ def flatten_unencrypted_web_search_results_in_anthropic_messages(  # mutable-ok:
     return [_flatten_web_search_results_in_message(m) for m in messages]  # mutable-ok: JSON wire format
 
 
+def _normalized_cache_control(cache_control: object) -> dict[str, str] | None:  # mutable-ok: JSON wire format
+    if not isinstance(cache_control, Mapping):
+        return None
+    cache_type: Final = cache_control.get("type")
+    return {"type": cache_type if isinstance(cache_type, str) else "ephemeral"}  # mutable-ok: JSON wire format
+
+
+def _with_portable_cache_control(block: Mapping[str, object]) -> dict[str, object]:  # mutable-ok: JSON wire format
+    if "cache_control" not in block:
+        return dict(block)  # mutable-ok: JSON wire format
+    normalized: Final = _normalized_cache_control(block["cache_control"])
+    rest: Final = {key: value for key, value in block.items() if key != "cache_control"}  # mutable-ok: JSON wire format
+    return rest if normalized is None else {**rest, "cache_control": normalized}  # mutable-ok: JSON wire format
+
+
+def _with_portable_cache_control_in_blocks(blocks: object) -> object:
+    if isinstance(blocks, str) or not isinstance(blocks, Sequence):
+        return blocks
+    return [  # mutable-ok: JSON wire format
+        _with_portable_cache_control(block) if isinstance(block, Mapping) else block for block in blocks
+    ]
+
+
+def _with_portable_cache_control_in_content_block(block: object) -> object:
+    if not isinstance(block, Mapping):
+        return block
+    portable: Final = _with_portable_cache_control(block)
+    if portable.get("type") != "tool_result" or "content" not in portable:
+        return portable
+    return {  # mutable-ok: JSON wire format
+        **portable,
+        "content": _with_portable_cache_control_in_blocks(portable["content"]),
+    }
+
+
+def _with_portable_cache_control_in_message(message: object) -> object:
+    if not isinstance(message, Mapping) or "content" not in message:
+        return message
+    content: Final = message["content"]
+    if isinstance(content, str) or not isinstance(content, Sequence):
+        return message
+    return {  # mutable-ok: JSON wire format
+        **message,
+        "content": [  # mutable-ok: JSON wire format
+            _with_portable_cache_control_in_content_block(block) for block in content
+        ],
+    }
+
+
+def _with_portable_cache_control_in_messages(messages: object) -> object:
+    if isinstance(messages, str) or not isinstance(messages, Sequence):
+        return messages
+    return [  # mutable-ok: JSON wire format
+        _with_portable_cache_control_in_message(message) for message in messages
+    ]
+
+
+def _with_portable_cache_control_in_scoped_value(key: str, value: object) -> object:
+    match key:
+        case "system" | "tools":
+            return _with_portable_cache_control_in_blocks(value)
+        case "messages":
+            return _with_portable_cache_control_in_messages(value)
+        case _:
+            return value
+
+
+def normalize_cache_control_in_anthropic_payload(
+    payload: Mapping[str, object],
+) -> dict[str, object]:  # mutable-ok: JSON wire format
+    """
+    Return a copy of an Anthropic /v1/messages payload with every
+    ``cache_control`` entry reduced to ``{"type": <its type, or "ephemeral">}``
+    at the places the Messages API defines it: the request itself, system
+    blocks, tools, message content blocks, and ``tool_result`` content blocks.
+    Application data such as ``tool_use.input`` and tool ``input_schema`` is
+    never touched, even when it happens to contain a ``cache_control`` key.
+
+    Anthropic itself accepts prompt-caching extensions such as ``ttl``, but
+    strict non-Anthropic implementations of the Messages API validate the field
+    literally and reject the whole request (``cache_control.ttl: 1h is not
+    supported``, ``cache_control.type is required``), which 400s clients like
+    Claude Code that send cache hints. Non-dict ``cache_control`` values are
+    dropped entirely. The caller's payload is never mutated.
+    """
+    portable: Final = _with_portable_cache_control(payload)
+    return {  # mutable-ok: JSON wire format
+        key: _with_portable_cache_control_in_scoped_value(key, value) for key, value in portable.items()
+    }
+
+
 def process_anthropic_headers(headers: httpx.Headers | dict) -> dict:
     openai_headers: Final = {}
     if "anthropic-ratelimit-requests-limit" in headers:
@@ -1338,31 +1519,38 @@ def process_anthropic_headers(headers: httpx.Headers | dict) -> dict:
     return additional_headers
 
 
-def _anthropic_model_entry(model: ModelInfoResponse, created_at: str) -> Mapping[str, object]:
+def _anthropic_model_entry(
+    model: ModelInfoResponse, created_at: str, display_names: Mapping[str, str]
+) -> Mapping[str, object]:
     return {  # mutable-ok: JSON response body, serialized by the route and never mutated
         "type": "model",
         "id": model["id"],
-        "display_name": model["id"],
+        "display_name": display_names.get(model["id"], model["id"]),
         "created_at": created_at,
         "max_input_tokens": model.get("max_input_tokens"),
         "max_tokens": model.get("max_output_tokens"),
     }
 
 
-def create_anthropic_model_list_response(models: Sequence[ModelInfoResponse]) -> Mapping[str, object]:
+def create_anthropic_model_list_response(
+    models: Sequence[ModelInfoResponse],
+    display_names: Mapping[str, str] = MappingProxyType({}),
+) -> Mapping[str, object]:
     """Build the Anthropic-native /v1/models envelope.
 
     Clients that send an anthropic-version header parse the Anthropic Models API
     shape (type/display_name/created_at plus has_more/first_id/last_id) and filter
     the list themselves, so every model is returned here. The token limits carry
     over from the OpenAI-shaped listing, named as the Messages API names them, and
-    are always present because the vendor shape declares them nullable, not optional
+    are always present because the vendor shape declares them nullable, not optional.
+    display_names maps a listed model id to a configured human-readable name; ids
+    without an entry fall back to the id itself, matching the vendor behavior
     """
     created_at: Final = (
         datetime.fromtimestamp(DEFAULT_MODEL_CREATED_AT_TIME, tz=timezone.utc).isoformat().replace("+00:00", "Z")
     )
     data: Final = [  # mutable-ok: JSON response body, serialized by the route and never mutated
-        _anthropic_model_entry(model, created_at) for model in models
+        _anthropic_model_entry(model, created_at, display_names) for model in models
     ]
     return {  # mutable-ok: JSON response body, serialized by the route and never mutated
         "data": data,
diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
index 411df267442..199a8ab77e7 100644
--- a/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py
@@ -18,6 +18,24 @@ TOOL_NAME_PREFIX_LENGTH: Final = OPENAI_MAX_TOOL_NAME_LENGTH - TOOL_NAME_HASH_LE
 PROVIDERS_PROXYING_AN_UNKNOWN_BACKEND: Final = frozenset({"litellm_proxy"})
 
 
+def _optional_attr(source: object, name: str) -> object:
+    return getattr(source, name, None)
+
+
+def _as_string_mapping(value: object) -> Mapping[str, object] | None:
+    if isinstance(value, Mapping):
+        return value
+    return None
+
+
+def _thought_signature(provider_specific_fields: object) -> str | None:
+    fields: Final = _as_string_mapping(provider_specific_fields)
+    if fields is None:
+        return None
+    signature: Final = fields.get("thought_signature")
+    return signature if isinstance(signature, str) else None
+
+
 _ANTHROPIC_TOOL_SCHEMA_KEYS: Final = frozenset(
     {"name", "type", "input_schema", "description", "cache_control", "strict"}
 )
@@ -56,7 +74,7 @@ def truncate_tool_name(name: str) -> str:
 
 
 def create_tool_name_mapping(
-    tools: list[dict[str, Any]],
+    tools: Sequence[Mapping[str, object]],
 ) -> dict[str, str]:
     """
     Create a mapping of truncated tool names to original names.
@@ -70,6 +88,8 @@ def create_tool_name_mapping(
     mapping: Final[dict[str, str]] = {}
     for tool in tools:
         original_name = tool.get("name", "")
+        if not isinstance(original_name, str):
+            continue
         truncated_name = truncate_tool_name(original_name)
         if truncated_name != original_name:
             mapping[truncated_name] = original_name
@@ -286,44 +306,44 @@ class LiteLLMAnthropicMessagesAdapter:
 
     ### FOR [BETA] `/v1/messages` endpoint support
 
-    def _extract_signature_from_tool_call(self, tool_call: Any) -> str | None:
+    def _extract_signature_from_tool_call(self, tool_call: object) -> str | None:
         """
         Extract signature from a tool call's provider_specific_fields.
         Only checks provider_specific_fields, not thinking blocks.
         """
-        signature = None
+        fields: Final = _optional_attr(tool_call, "provider_specific_fields")
+        if fields:
+            return _thought_signature(fields)
 
-        if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields:
-            if "thought_signature" in tool_call.provider_specific_fields:
-                signature = tool_call.provider_specific_fields["thought_signature"]
-        elif hasattr(tool_call.function, "provider_specific_fields") and tool_call.function.provider_specific_fields:
-            if "thought_signature" in tool_call.function.provider_specific_fields:
-                signature = tool_call.function.provider_specific_fields["thought_signature"]
+        function_fields: Final = _optional_attr(_optional_attr(tool_call, "function"), "provider_specific_fields")
+        if function_fields:
+            return _thought_signature(function_fields)
 
-        return signature
+        return None
 
-    def _extract_signature_from_tool_use_content(self, content: dict[str, Any]) -> str | None:
+    def _extract_signature_from_tool_use_content(self, content: Mapping[str, object]) -> str | None:
         """
         Extract signature from a tool_use content block's provider_specific_fields.
         """
-        provider_specific_fields: Final = content.get("provider_specific_fields", {})
+        provider_specific_fields: Final = _as_string_mapping(content.get("provider_specific_fields", {}))
         if provider_specific_fields:
-            return provider_specific_fields.get("signature")
+            signature: Final = provider_specific_fields.get("signature")
+            return signature if isinstance(signature, str) else None
         return None
 
     def _add_cache_control_if_applicable(
         self,
-        source: Any,
-        target: Any,
+        source: object,
+        target: object,
         model: str | None,
     ) -> None:
         """
         Extract cache_control from source and add to target if it should be preserved.
 
-        This method accepts Any type to support both regular dicts and TypedDict objects.
-        TypedDict objects (like ChatCompletionTextObject, ChatCompletionImageObject, etc.)
-        are dicts at runtime but have specific types at type-check time. Using Any allows
-        this method to work with both while maintaining runtime correctness.
+        This method accepts an unconstrained type to support both regular dicts and
+        TypedDict objects. TypedDict objects (like ChatCompletionTextObject,
+        ChatCompletionImageObject, etc.) are dicts at runtime but have specific types at
+        type-check time, so the widest parameter type works with both.
 
         Args:
             source: Dict or TypedDict containing potential cache_control field
@@ -751,7 +771,7 @@ class LiteLLMAnthropicMessagesAdapter:
 
         return new_tools, tool_name_mapping
 
-    def translate_anthropic_output_format_to_openai(self, output_format: Any) -> dict[str, object] | None:
+    def translate_anthropic_output_format_to_openai(self, output_format: object) -> dict[str, object] | None:
         """
         Translate Anthropic's output_format to OpenAI's response_format.
 
@@ -1366,7 +1386,7 @@ class LiteLLMAnthropicMessagesAdapter:
 
     @classmethod
     def _first_positive_prompt_tokens_detail_value(cls, usage: Usage, field_names: tuple[str, ...]) -> int:
-        prompt_tokens_details: Final = getattr(usage, "prompt_tokens_details", None)
+        prompt_tokens_details: Final = _optional_attr(usage, "prompt_tokens_details")
         if prompt_tokens_details is None:
             return 0
 
@@ -1374,7 +1394,7 @@ class LiteLLMAnthropicMessagesAdapter:
             if isinstance(prompt_tokens_details, dict):
                 value = cls._positive_int(prompt_tokens_details.get(field_name))
             else:
-                value = cls._positive_int(getattr(prompt_tokens_details, field_name, None))
+                value = cls._positive_int(_optional_attr(prompt_tokens_details, field_name))
             if value > 0:
                 return value
         return 0
diff --git a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py
index c8cbbba8784..050ab67c86c 100644
--- a/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py
+++ b/litellm/llms/anthropic/experimental_pass_through/context_management/editors/compact.py
@@ -13,10 +13,10 @@ Mirrors Anthropic's native ``compact_20260112`` for non-Anthropic providers:
 """
 
 import re
-from collections.abc import Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Final, Literal, NotRequired, Optional, TypedDict, Union, cast
+from collections.abc import Awaitable, Mapping, Sequence
+from typing import TYPE_CHECKING, Final, Literal, Optional, Protocol, TypeVar, Union, cast
 
-from typing_extensions import ReadOnly
+from typing_extensions import NotRequired, ReadOnly, TypedDict, Unpack
 
 import litellm
 from litellm._logging import verbose_logger
@@ -29,6 +29,7 @@ from litellm.types.llms.anthropic import (
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
     from litellm.proxy._types import UserAPIKeyAuth
+    from litellm.proxy.hooks.parallel_request_limiter_v3 import RateLimitDescriptor, RateLimitResponse
     from litellm.router import Router
     from litellm.types.llms.anthropic import (
         AllAnthropicPassThroughMessageValues,
@@ -84,6 +85,77 @@ _PROPAGATED_METADATA_KEYS: Final = (
 
 _SUMMARY_TAG_RE: Final = re.compile(r"<summary>(.*?)</summary>", re.IGNORECASE | re.DOTALL)
 
+_MsgT: Final = TypeVar("_MsgT", bound=Mapping[str, object])
+
+
+def _as_object(value: object) -> object:
+    return value
+
+
+def _is_tool_result_block(block: object) -> bool:
+    return isinstance(block, dict) and block.get("type") in ("tool_result",)
+
+
+class _SummaryCallKwargs(TypedDict):
+    model: ReadOnly[str]
+    max_tokens: ReadOnly[int]
+    timeout: ReadOnly[float]
+    litellm_metadata: ReadOnly[Mapping[str, object]]
+    user: ReadOnly[NotRequired[str]]
+    allowed_model_region: ReadOnly[NotRequired[str]]
+
+
+class _SummaryOptionalKwargs(TypedDict, total=False):
+    user: ReadOnly[str]
+    allowed_model_region: ReadOnly[str]
+
+
+class _SummaryAcompletion(Protocol):
+    def __call__(
+        self,
+        *,
+        messages: Sequence[Mapping[str, object]],
+        **kwargs: Unpack[_SummaryCallKwargs],  # kwargs-ok: forwarded verbatim to acompletion, which owns them
+    ) -> "Awaitable[ModelResponse | CustomStreamWrapper]": ...
+
+
+class _CreateRateLimitDescriptors(Protocol):
+    def __call__(
+        self,
+        *,
+        user_api_key_dict: "UserAPIKeyAuth",
+        data: Mapping[str, str],
+        rpm_limit_type: object,
+        tpm_limit_type: object,
+        model_has_failures: bool,
+    ) -> "Sequence[RateLimitDescriptor]": ...
+
+
+class _AddModelRateLimitDescriptor(Protocol):
+    def __call__(
+        self,
+        *,
+        user_api_key_dict: "UserAPIKeyAuth",
+        requested_model: str,
+        descriptors: "Sequence[RateLimitDescriptor]",
+    ) -> None: ...
+
+
+class _CreateOrgRateLimitDescriptors(Protocol):
+    def __call__(
+        self, user_api_key_dict: "UserAPIKeyAuth", requested_model: str | None = None
+    ) -> "Sequence[RateLimitDescriptor]": ...
+
+
+class _ShouldRateLimit(Protocol):
+    def __call__(
+        self,
+        *,
+        descriptors: "Sequence[RateLimitDescriptor]",
+        parent_otel_span: object,
+        read_only: bool,
+    ) -> "Awaitable[RateLimitResponse]": ...
+
 
 def _read_summary_model_setting() -> str | None:
     """Look up the configured summarization model from proxy general_settings."""
@@ -159,11 +231,11 @@ async def _check_summary_model_access(
         return True
 
     key_models: Final = list(getattr(user_api_key_auth, "models", None) or [])
-    team_id: Final = getattr(user_api_key_auth, "team_id", None)
-    team_model_aliases: Final = getattr(user_api_key_auth, "team_model_aliases", None)
+    team_id: Final[str | None] = getattr(user_api_key_auth, "team_id", None)
+    team_model_aliases: Final[dict[str, str] | None] = getattr(user_api_key_auth, "team_model_aliases", None)
     team_models: Final = list(getattr(user_api_key_auth, "team_models", None) or [])
-    user_id: Final = getattr(user_api_key_auth, "user_id", None)
-    project_id: Final = getattr(user_api_key_auth, "project_id", None)
+    user_id: Final[str | None] = getattr(user_api_key_auth, "user_id", None)
+    project_id: Final[str | None] = getattr(user_api_key_auth, "project_id", None)
 
     checks: Final[tuple[tuple[Literal["key", "team"], list[str]], ...]] = (
         ("key", key_models),
@@ -371,8 +443,10 @@ async def _check_summary_model_budget(
             )
             return False
 
-    end_user_model_max_budget: Final = getattr(user_api_key_auth, "end_user_model_max_budget", None)
-    end_user_id: Final = getattr(user_api_key_auth, "end_user_id", None)
+    end_user_model_max_budget: Final[dict[str, object] | None] = getattr(
+        user_api_key_auth, "end_user_model_max_budget", None
+    )
+    end_user_id: Final[str | None] = getattr(user_api_key_auth, "end_user_id", None)
     if isinstance(end_user_model_max_budget, dict) and end_user_model_max_budget and end_user_id is not None:
         try:
             await model_max_budget_limiter.is_end_user_within_model_budget(
@@ -424,40 +498,57 @@ async def _check_summary_model_rate_limit(
     except Exception:
         return True
 
-    limiter: Final = getattr(proxy_logging_obj, "max_parallel_request_limiter", None)
+    limiter: Final[object] = getattr(proxy_logging_obj, "max_parallel_request_limiter", None)
+    should_rate_limit_check: Final[_ShouldRateLimit | None] = getattr(limiter, "should_rate_limit", None)
+    create_descriptors: Final[_CreateRateLimitDescriptors | None] = getattr(
+        limiter, "_create_rate_limit_descriptors", None
+    )
+    add_team_descriptor: Final[_AddModelRateLimitDescriptor | None] = getattr(
+        limiter, "_add_team_model_rate_limit_descriptor_from_metadata", None
+    )
+    add_project_descriptor: Final[_AddModelRateLimitDescriptor | None] = getattr(
+        limiter, "_add_project_model_rate_limit_descriptor_from_metadata", None
+    )
+    create_org_descriptors: Final[_CreateOrgRateLimitDescriptors | None] = getattr(
+        limiter, "create_organization_rate_limit_descriptor", None
+    )
     if (
         limiter is None
-        or not hasattr(limiter, "should_rate_limit")
-        or not hasattr(limiter, "_create_rate_limit_descriptors")
+        or should_rate_limit_check is None
+        or create_descriptors is None
+        or add_team_descriptor is None
+        or add_project_descriptor is None
+        or create_org_descriptors is None
     ):
         return True
 
     try:
-        metadata: Final = getattr(user_api_key_auth, "metadata", None) or {}
+        metadata: Final[Mapping[str, object]] = getattr(user_api_key_auth, "metadata", None) or {}
         data: Final = {"model": summary_model}
-        descriptors: Final = limiter._create_rate_limit_descriptors(
+        base_descriptors: Final = create_descriptors(
             user_api_key_dict=user_api_key_auth,
             data=data,
             rpm_limit_type=metadata.get("rpm_limit_type"),
             tpm_limit_type=metadata.get("tpm_limit_type"),
             model_has_failures=False,
         )
-        limiter._add_team_model_rate_limit_descriptor_from_metadata(
+        add_team_descriptor(
             user_api_key_dict=user_api_key_auth,
             requested_model=summary_model,
-            descriptors=descriptors,
+            descriptors=base_descriptors,
         )
-        limiter._add_project_model_rate_limit_descriptor_from_metadata(
+        add_project_descriptor(
             user_api_key_dict=user_api_key_auth,
             requested_model=summary_model,
-            descriptors=descriptors,
+            descriptors=base_descriptors,
         )
-        descriptors.extend(limiter.create_organization_rate_limit_descriptor(user_api_key_auth, summary_model))
+        descriptors: Final = (*base_descriptors, *create_org_descriptors(user_api_key_auth, summary_model))
         if not descriptors:
             return True
-        response: Final = await limiter.should_rate_limit(
+        parent_otel_span: Final[object] = getattr(user_api_key_auth, "parent_otel_span", None)
+        response: Final[RateLimitResponse] = await should_rate_limit_check(
             descriptors=descriptors,
-            parent_otel_span=getattr(user_api_key_auth, "parent_otel_span", None),
+            parent_otel_span=parent_otel_span,
             read_only=True,
         )
     except Exception as e:
@@ -471,7 +562,7 @@ async def _check_summary_model_rate_limit(
 
 
 def _find_latest_compaction_index(
-    messages: list[dict[str, object]],
+    messages: Sequence[Mapping[str, object]],
 ) -> tuple[int | None, int | None]:
     """Return (message_index, block_index) of the most recent compaction block.
 
@@ -490,8 +581,8 @@ def _find_latest_compaction_index(
 
 
 def _slice_around_compaction_block(
-    messages: list[dict[str, Any]],
-) -> tuple[list[dict[str, object]], dict[str, object] | None]:
+    messages: Sequence[_MsgT],
+) -> tuple[Sequence[_MsgT | dict[str, object]], dict[str, object] | None]:
     """Apply Anthropic's "drop everything before the compaction block" rule.
 
     Returns ``(sliced_messages_with_compaction_block, compaction_block_dict)``
@@ -506,19 +597,21 @@ def _slice_around_compaction_block(
 
     original_msg: Final = messages[msg_idx]
     original_content: Final = original_msg["content"]
-    compaction_block: Final = cast(dict[str, object], original_content[blk_idx])
+    if not isinstance(original_content, list):
+        return messages, None
+    original_blocks: Final = cast("Sequence[dict[str, object]]", original_content)
+    compaction_block: Final = original_blocks[blk_idx]
 
     # Per Anthropic's contract everything before the compaction block is
     # dropped, including earlier blocks within the same assistant message.
-    sliced_content: Final = list(original_content[blk_idx:])
+    sliced_content: Final = list(original_blocks[blk_idx:])
 
-    sliced_messages: Final[list[dict[str, object]]] = [{**original_msg, "content": sliced_content}]
-    sliced_messages.extend(messages[msg_idx + 1 :])
+    sliced_messages: Final = [{**original_msg, "content": sliced_content}, *messages[msg_idx + 1 :]]
     return sliced_messages, compaction_block
 
 
 def _strip_compaction_blocks(
-    messages: list[dict[str, object]],
+    messages: Sequence[dict[str, object]],
 ) -> list[dict[str, object]]:
     """Drop any ``compaction`` content blocks from messages.
 
@@ -625,7 +718,7 @@ def _propagate_metadata(
 
 def _count_effective_tokens(
     model: str,
-    effective_messages: list[dict[str, object]],
+    effective_messages: Sequence[dict[str, object]],
     compaction_block: CompactionBlock | None,
     tools: list[dict[str, object]] | None,
     system: str | list[dict[str, object]] | None = None,
@@ -704,17 +797,18 @@ def _system_to_text(
         return ""
     if isinstance(system, str):
         return system
-    parts: Final[list[str]] = []
-    for block in system:
-        if isinstance(block, dict) and block.get("type") == "text":
-            text = block.get("text")
-            if isinstance(text, str) and text:
-                parts.append(text)
-    return "\n".join(parts)
+    return "\n".join(
+        text
+        for block in system
+        if isinstance(block, dict)
+        and block.get("type") == "text"
+        and isinstance(text := block.get("text"), str)
+        and text
+    )
 
 
 def _select_last_user_question(
-    messages: list[dict[str, object]],
+    messages: Sequence[dict[str, object]],
 ) -> list[dict[str, object]]:
     """Pick the most recent ``user`` turn that is a real question.
 
@@ -729,16 +823,18 @@ def _select_last_user_question(
     turns, or contained no user turns at all). The downstream call always
     needs a non-empty user message.
     """
+    blocks: Sequence[object]
     for msg in reversed(messages):
         if msg.get("role") != "user":
             continue
         content = msg.get("content")
         if isinstance(content, list):
-            filtered = [blk for blk in content if not (isinstance(blk, dict) and blk.get("type") == "tool_result")]
+            blocks = [*map(_as_object, content)]
+            filtered = [blk for blk in blocks if not _is_tool_result_block(blk)]
             if not filtered:
                 # Purely tool_result — skip and look for an earlier turn.
                 continue
-            if len(filtered) < len(content):
+            if len(filtered) < len(blocks):
                 return [{**msg, "content": filtered}]
         return [msg]
     return [
@@ -760,7 +856,7 @@ def _extract_summary_text(raw: str | None) -> str | None:
 
 
 def _system_to_openai_message(
-    system: str | list[dict[str, Any]] | None,
+    system: str | list[dict[str, object]] | None,
 ) -> dict[str, object] | None:
     """Translate Anthropic-shaped ``system`` to an OpenAI system message.
 
@@ -772,17 +868,19 @@ def _system_to_openai_message(
     if isinstance(system, str):
         return {"role": "system", "content": system} if system else None
     if isinstance(system, list):
-        parts = [block.get("text", "") for block in system if isinstance(block, dict) and block.get("type") == "text"]
-        joined: Final = "\n\n".join(part for part in parts if part)
+        parts: Final[list[object]] = [
+            block.get("text", "") for block in system if isinstance(block, dict) and block.get("type") == "text"
+        ]
+        joined: Final = "\n\n".join(part for part in parts if isinstance(part, str) and part)
         return {"role": "system", "content": joined} if joined else None
     return None
 
 
 def _build_summary_messages(
-    effective_messages: list[dict[str, object]],
+    effective_messages: Sequence[dict[str, object]],
     prompt: str,
     system: str | list[dict[str, object]] | None = None,
-) -> list[dict[str, object]]:
+) -> Sequence[Mapping[str, object]]:
     """Build the OpenAI-shape message list for the summary call.
 
     The caller's ``system`` prompt is prepended (the default summarization
@@ -810,7 +908,7 @@ def _build_summary_messages(
         )
         openai_messages = stripped
 
-    summary_messages: Final[list[dict[str, object]]] = []
+    summary_messages: Final[list[Mapping[str, object]]] = []
     system_message: Final = _system_to_openai_message(system)
     if system_message is not None:
         summary_messages.append(system_message)
@@ -845,35 +943,17 @@ def _append_text_to_content(content: object, extra_text: str) -> object:
     if isinstance(content, str):
         return f"{content}\n\n{extra_text}"
     if isinstance(content, list):
-        appended: Final[list[object]] = [*content, {"type": "text", "text": extra_text}]
+        appended: Final[Sequence[object]] = [*map(_as_object, content), {"type": "text", "text": extra_text}]
         return appended
     return [content, {"type": "text", "text": extra_text}]
 
 
-class _SummaryCallUserKwarg(TypedDict, total=False):
-    user: ReadOnly[object]
-
-
-class _SummaryCallRegionKwarg(TypedDict, total=False):
-    allowed_model_region: ReadOnly[str]
-
-
-class _SummaryCallKwargs(TypedDict):
-    model: ReadOnly[str]
-    messages: ReadOnly[list[dict[str, object]]]
-    max_tokens: ReadOnly[int]
-    timeout: ReadOnly[float]
-    litellm_metadata: ReadOnly[Mapping[str, object]]
-    user: NotRequired[ReadOnly[object]]
-    allowed_model_region: NotRequired[ReadOnly[str]]
-
-
 async def _call_summary_model(
     *,
     summary_model: str,
-    summary_messages: list[dict[str, object]],
+    summary_messages: Sequence[Mapping[str, object]],
     metadata: Mapping[str, object],
-    llm_router: Any,
+    llm_router: Optional["Router"],
     allowed_model_region: str | None = None,
     max_tokens: int = COMPACT_SUMMARY_MAX_TOKENS,
 ) -> Union["ModelResponse", "CustomStreamWrapper"]:
@@ -909,28 +989,37 @@ async def _call_summary_model(
     # than from ``litellm_metadata``, so without it the summary tokens would not
     # debit the caller's end-user counters.
     end_user_id: Final = metadata.get("user_api_key_end_user_id")
+    user_kwargs: Final = (
+        _SummaryOptionalKwargs(user=end_user_id)
+        if isinstance(end_user_id, str) and end_user_id
+        else _SummaryOptionalKwargs()
+    )
+    region_kwargs: Final = (
+        _SummaryOptionalKwargs(allowed_model_region=allowed_model_region)
+        if allowed_model_region is not None
+        else _SummaryOptionalKwargs()
+    )
     call_kwargs: Final[_SummaryCallKwargs] = {
         "model": summary_model,
-        "messages": summary_messages,
         "max_tokens": max_tokens,
         "timeout": COMPACT_SUMMARY_TIMEOUT_SECONDS,
         "litellm_metadata": metadata,
-        **(_SummaryCallUserKwarg(user=end_user_id) if end_user_id else _SummaryCallUserKwarg()),
-        **(
-            _SummaryCallRegionKwarg(allowed_model_region=allowed_model_region)
-            if allowed_model_region is not None
-            else _SummaryCallRegionKwarg()
-        ),
+        **user_kwargs,
+        **region_kwargs,
     }
-    if llm_router is not None and hasattr(llm_router, "acompletion"):
-        return await llm_router.acompletion(**call_kwargs)
-    return await litellm.acompletion(**call_kwargs)
+    router_acompletion: Final[_SummaryAcompletion | None] = getattr(llm_router, "acompletion", None)
+    if llm_router is not None and router_acompletion is not None:
+        return await router_acompletion(messages=summary_messages, **call_kwargs)
+    return await litellm.acompletion(messages=[*summary_messages], **call_kwargs)
 
 
-def _extract_response_text(response: Any) -> str | None:
+def _extract_response_text(response: object) -> str | None:
     try:
-        choice: Final = response.choices[0]
-        message: Final = choice.message
+        choices: Final[Sequence[object] | None] = getattr(response, "choices", None)
+        if choices is None:
+            return None
+        choice: Final = choices[0]
+        message: Final = getattr(choice, "message", None)
         content: Final = getattr(message, "content", None)
         if isinstance(content, str):
             return content
@@ -946,13 +1035,12 @@ def _extract_response_text(response: Any) -> str | None:
 
 
 def _extract_usage(response: object) -> tuple[int, int]:
-    usage: Final = getattr(response, "usage", None)
+    usage: Final[object] = getattr(response, "usage", None)
     if usage is None:
         return 0, 0
-    return (
-        int(getattr(usage, "prompt_tokens", 0) or 0),
-        int(getattr(usage, "completion_tokens", 0) or 0),
-    )
+    prompt_tokens: Final[int | None] = getattr(usage, "prompt_tokens", 0)
+    completion_tokens: Final[int | None] = getattr(usage, "completion_tokens", 0)
+    return int(prompt_tokens or 0), int(completion_tokens or 0)
 
 
 def apply_client_compaction_block_history(
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
index 69985bcdaa3..b82903d6f87 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/handler.py
@@ -99,6 +99,10 @@ def _deployment_passes_through_anthropic_messages(model_info: object) -> bool:
     return isinstance(supported_endpoints, (list, tuple)) and "/v1/messages" in supported_endpoints
 
 
+def _deployment_supports_cache_control_ttl(model_info: object) -> bool:
+    return isinstance(model_info, dict) and model_info.get("cache_control_ttl") is True
+
+
 ####### ENVIRONMENT VARIABLES ###################
 # Initialize any necessary instances or variables here
 base_llm_http_handler = BaseLLMHTTPHandler()
@@ -568,7 +572,9 @@ def anthropic_messages_handler(
             OpenAILikeAnthropicMessagesConfig,
         )
 
-        anthropic_messages_provider_config = OpenAILikeAnthropicMessagesConfig()
+        anthropic_messages_provider_config = OpenAILikeAnthropicMessagesConfig(
+            cache_control_ttl=_deployment_supports_cache_control_ttl(kwargs.get("model_info")),
+        )
     if anthropic_messages_provider_config is None:
         # Route to Responses API for OpenAI / Azure, chat/completions for everything else.
         if _should_route_to_responses_api(custom_llm_provider, original_model, model):
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
index a282d5f4d4f..66e36dab2ba 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
@@ -8,6 +8,10 @@ import httpx
 from pydantic import TypeAdapter
 from typing_extensions import TypedDict
 
+from litellm.constants import (
+    ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS,
+    ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE,
+)
 from litellm.litellm_core_utils.core_helpers import process_response_headers
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
@@ -21,6 +25,9 @@ from litellm.types.utils import GenericStreamingChunk, ModelResponseStream
 
 GLOBAL_PASS_THROUGH_SUCCESS_HANDLER_OBJ: Final = PassThroughEndpointLogging()
 
+_UPSTREAM_PUMP_TASKS: Final[set[asyncio.Task[None]]] = set()  # mutable-ok: stdlib strong-ref set for pump tasks
+_DETACHED_STREAM_DRAINS: Final[set[asyncio.Task[None]]] = set()  # mutable-ok: bounded strong-ref set, detached drains
+
 INCOMPLETE_STREAM_ERROR_MESSAGE: Final = (
     "Provider stream ended before emitting a message_stop event; "
     "the response is incomplete and any partial content (e.g. tool_use input JSON) may be truncated."
@@ -79,22 +86,41 @@ def _decoded_sse_data_line(line: bytes) -> object | None:
         return None
 
 
-def _anthropic_error_event_payload(chunk: object) -> Mapping[str, object] | None:
+def _anthropic_event_payload(chunk: object, event_type: str) -> Mapping[str, object] | None:
     if isinstance(chunk, dict):
-        return chunk if chunk.get("type") == "error" else None
+        return chunk if chunk.get("type") == event_type else None
     if isinstance(chunk, (bytes, bytearray)):
         decoded_lines: Final = (_decoded_sse_data_line(line) for line in chunk.splitlines())
         return next(
             (
                 candidate
                 for candidate in decoded_lines
-                if isinstance(candidate, dict) and candidate.get("type") == "error"
+                if isinstance(candidate, dict) and candidate.get("type") == event_type
             ),
             None,
         )
     return None
 
 
+def _anthropic_error_event_payload(chunk: object) -> Mapping[str, object] | None:
+    return _anthropic_event_payload(chunk, "error")
+
+
+def parse_anthropic_refusal_stop_details(chunk: object) -> Mapping[str, object] | None:
+    """
+    Return the ``stop_details`` object of an Anthropic SSE ``message_delta``
+    chunk whose delta carries ``stop_reason: "refusal"`` (a safeguard refusal:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback),
+    or None for any other chunk, a plain refusal without ``stop_details`` included.
+    """
+    payload: Final = _anthropic_event_payload(chunk, "message_delta")
+    delta: Final = payload.get("delta") if payload is not None else None
+    if not isinstance(delta, dict) or delta.get("stop_reason") != "refusal":
+        return None
+    stop_details: Final = delta.get("stop_details")
+    return stop_details if isinstance(stop_details, dict) else None
+
+
 def _anthropic_error_body(chunk: object) -> Mapping[str, object] | None:
     """Return the ``error`` object of an Anthropic SSE ``event: error`` chunk, or None."""
     payload: Final = _anthropic_error_event_payload(chunk)
@@ -133,6 +159,34 @@ def _is_terminal_stream_chunk(chunk: object) -> bool:
     return _is_message_stop_chunk(chunk) or _is_provider_error_chunk(chunk)
 
 
+def _try_claim_detached_drain_slot() -> bool:
+    """Claim a detached-drain slot for the current task, bounding concurrency.
+
+    Returns True if a slot was claimed (the caller may keep draining upstream
+    for billing) or False if the cap is already reached (the caller should stop
+    and bill what it has). Only touched from the event loop, so the check +
+    insert need no lock.
+    """
+    if len(_DETACHED_STREAM_DRAINS) >= ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS:
+        return False
+    current_task: Final = asyncio.current_task()
+    if current_task is not None:
+        _DETACHED_STREAM_DRAINS.add(current_task)
+        current_task.add_done_callback(_DETACHED_STREAM_DRAINS.discard)
+    return True
+
+
+def _exception_left_unconsumed(queue: "asyncio.Queue[bytes | None | BaseException]", exc: BaseException) -> bool:
+    """After client detach the relay never reads the queue again, so drain it here.
+
+    The forwarded exception still sitting in the queue means the relay tore
+    down before re-raising it, so the proxy's failure handling never ran and
+    the caller must salvage spend itself.
+    """
+    remaining: Final = tuple(queue.get_nowait() for _ in range(queue.qsize()))
+    return any(item is exc for item in remaining)
+
+
 def _sse_event(event_type: str, payload: Mapping[str, object]) -> bytes:
     return f"event: {event_type}\ndata: {json.dumps(payload)}\n\n".encode()
 
@@ -414,17 +468,167 @@ class BaseAnthropicMessagesStreamingIterator:
 
     async def async_sse_wrapper(
         self,
-        completion_stream: AsyncIterator[bytes | GenericStreamingChunk | ModelResponseStream | dict],
+        completion_stream: AsyncIterator[bytes | GenericStreamingChunk | ModelResponseStream | Mapping[str, object]],
     ) -> AsyncIterator[bytes]:
         """
         Generic async SSE wrapper that converts streaming chunks to SSE format
         and handles logging.
 
+        The upstream read runs in a detached background task (``_pump_upstream``)
+        so that a client disconnect tears down only this client-facing generator,
+        never the upstream drain + billing. The provider (e.g. Bedrock) keeps
+        generating and billing the full response regardless of the client, so
+        draining it to completion is what lets spend tracking see the real
+        terminal ``message_delta`` / ``message_stop`` usage instead of a
+        truncated placeholder count.
+
+        Chunks reach the client through a bounded queue. While the client is
+        connected the pump blocks on a full queue (racing the disconnect
+        signal), so a slow reader throttles the upstream read exactly as the old
+        direct ``yield`` did instead of letting the whole response buffer in
+        memory. Once the client goes away the pump stops enqueueing and only
+        keeps a single ``collected_chunks`` copy for billing, and the number of
+        such post-disconnect drains running at once is capped so client behavior
+        can't create unbounded worker state; over the cap the pump bills what it
+        has rather than draining further. Detached-drain lifetime is otherwise
+        bounded by the upstream stream/read timeout.
+
+        An upstream failure (Bedrock read / decode / chunk-conversion error)
+        that happens while the client is still connected is forwarded through
+        the queue and re-raised here, so the original provider exception (and
+        its status) reaches the proxy's failure handling unchanged rather than
+        being masked by a generic incomplete-stream event.
+
         This method provides the common logic for both Anthropic and Bedrock implementations.
         """
-        collected_chunks: Final = []
-        saw_terminal_event = False
+        queue: Final[asyncio.Queue[bytes | None | BaseException]] = asyncio.Queue(
+            maxsize=ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE
+        )
+        client_detached: Final = asyncio.Event()
 
+        pump_task: Final = asyncio.create_task(self._pump_upstream_to_queue(completion_stream, queue, client_detached))
+        _UPSTREAM_PUMP_TASKS.add(pump_task)
+        pump_task.add_done_callback(_UPSTREAM_PUMP_TASKS.discard)
+
+        reached_end = False  # rebind-ok: flipped once the relay consumes the end-of-stream sentinel
+        try:
+            while True:
+                item = await queue.get()
+                if item is None:
+                    reached_end = True
+                    break
+                if isinstance(item, BaseException):
+                    raise item
+                yield item
+        finally:
+            client_detached.set()
+            if not reached_end:
+                self._dispatch_pending_deferred_logging()
+
+    def _dispatch_pending_deferred_logging(self) -> None:
+        """Fire deferred billing that a torn-down response would otherwise drop.
+
+        When the pump finishes draining while the client is still connected it
+        stores the logging coroutine for ProxyLogging._fire_deferred_stream_logging,
+        which the proxy only fires on a normally completed response: a client
+        disconnect (GeneratorExit / CancelledError) re-raises past it. Without
+        this dispatch that window loses the spend row entirely.
+        """
+        deferred_cb: Final = getattr(self.litellm_logging_obj, "_on_deferred_stream_complete", None)
+        deferred_args: Final = getattr(self.litellm_logging_obj, "_deferred_stream_complete_args", None)
+        if deferred_cb is None or deferred_args is None:
+            return
+        self.litellm_logging_obj._on_deferred_stream_complete = None
+        self.litellm_logging_obj._deferred_stream_complete_args = None
+        GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(async_coroutine=deferred_cb(*deferred_args))
+
+    async def _bill_collected_chunks(
+        self,
+        collected_chunks: list[bytes],  # mutable-ok: SSE buffer forwarded to list-typed _handle_streaming_logging
+        *,
+        stream_teardown: bool,
+    ) -> None:
+        from litellm._logging import verbose_proxy_logger
+
+        try:
+            await self._handle_streaming_logging(collected_chunks, stream_teardown=stream_teardown)
+        except Exception as exc:  # noqa: BLE001  # billing is best-effort; never crash the pump
+            verbose_proxy_logger.warning(
+                "async_sse_wrapper billing failed after %d chunks: %s(%s)",
+                len(collected_chunks),
+                type(exc).__name__,
+                exc,
+            )
+
+    @staticmethod
+    async def _abort_upstream(
+        completion_stream: AsyncIterator[bytes | GenericStreamingChunk | ModelResponseStream | Mapping[str, object]],
+    ) -> None:
+        """Close the upstream provider stream so it stops generating and billing."""
+        from litellm._logging import verbose_proxy_logger
+
+        try:
+            await aclose_if_supported(completion_stream)
+        except Exception as exc:  # noqa: BLE001  # abort is best-effort; log and continue
+            verbose_proxy_logger.warning(
+                "async_sse_wrapper failed to abort upstream stream: %s(%s)",
+                type(exc).__name__,
+                exc,
+            )
+
+    @staticmethod
+    async def _enqueue_for_client(
+        queue: "asyncio.Queue[bytes | None | BaseException]",
+        client_detached: "asyncio.Event",
+        item: bytes | None | BaseException,
+    ) -> bool:
+        """Deliver one item to the client, applying backpressure.
+
+        Returns True if the item was queued, False if the client disconnected
+        before there was room (the item is then dropped, since a gone client
+        can't receive it). Never blocks once the client has detached.
+        """
+        if client_detached.is_set():
+            return False
+        try:
+            queue.put_nowait(item)
+        except asyncio.QueueFull:
+            pass
+        else:
+            return True
+        put_task: Final = asyncio.ensure_future(queue.put(item))
+        detached_task: Final = asyncio.ensure_future(client_detached.wait())
+        try:
+            await asyncio.wait(frozenset((put_task, detached_task)), return_when=asyncio.FIRST_COMPLETED)
+        finally:
+            if not detached_task.done():
+                detached_task.cancel()
+        if put_task.done() and not put_task.cancelled():
+            return True
+        put_task.cancel()
+        return False
+
+    async def _pump_upstream_to_queue(
+        self,
+        completion_stream: AsyncIterator[bytes | GenericStreamingChunk | ModelResponseStream | Mapping[str, object]],
+        queue: "asyncio.Queue[bytes | None | BaseException]",
+        client_detached: "asyncio.Event",
+    ) -> None:
+        """Drain the whole upstream into ``queue`` (backpressured) and bill once.
+
+        Runs detached so a client disconnect can't interrupt the upstream read;
+        see ``async_sse_wrapper`` for the full rationale. On a completed drain
+        the success billing (or deferred park) happens before the end-of-stream
+        sentinel is enqueued: the relay can only tear down after consuming the
+        sentinel, so its teardown can never outrun the park and get mistaken
+        for a client disconnect, and a sentinel the client never consumes falls
+        back to dispatching the parked billing here.
+        """
+        from litellm._logging import verbose_proxy_logger
+
+        collected_chunks: Final[list[bytes]] = []  # mutable-ok: SSE billing buffer appended to across the drain
+        saw_terminal_event = False  # rebind-ok: accumulates across the upstream loop
+        draining_detached = False  # rebind-ok: set once this pump claims a detached-drain slot
         try:
             async for chunk in completion_stream:
                 if self.completion_start_time is None:
@@ -432,17 +636,62 @@ class BaseAnthropicMessagesStreamingIterator:
                 saw_terminal_event = saw_terminal_event or _is_terminal_stream_chunk(chunk)
                 encoded_chunk = self._convert_chunk_to_sse_format(chunk)
                 collected_chunks.append(encoded_chunk)
-                yield encoded_chunk
-        except (GeneratorExit, asyncio.CancelledError):
-            # A client disconnect tears the generator down at the yield, so the
-            # post-loop logging below never runs and the tokens already streamed
-            # (and billed by the provider) would never reach spend tracking. See LIT-5839.
-            if collected_chunks:
-                await self._handle_streaming_logging(collected_chunks, stream_teardown=True)
-            raise
+                if not client_detached.is_set():
+                    await self._enqueue_for_client(queue, client_detached, encoded_chunk)
+                    continue
+                if not draining_detached:
+                    if not _try_claim_detached_drain_slot():
+                        verbose_proxy_logger.warning(
+                            "async_sse_wrapper: detached-drain cap (%d) reached; billing %d partial "
+                            "chunks and aborting the upstream stream to stop provider billing",
+                            ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS,
+                            len(collected_chunks),
+                        )
+                        await self._bill_collected_chunks(collected_chunks, stream_teardown=True)
+                        await self._abort_upstream(completion_stream)
+                        return
+                    draining_detached = True
+        except Exception as exc:  # noqa: BLE001  # upstream errors are handled/forwarded by _handle_pump_upstream_error
+            await self._handle_pump_upstream_error(queue, client_detached, collected_chunks, exc)
+            return
 
-        if not saw_terminal_event:
-            yield _incomplete_stream_error_sse_event()
+        if client_detached.is_set():
+            await self._bill_collected_chunks(collected_chunks, stream_teardown=True)
+            return
+        if not saw_terminal_event and not await self._enqueue_for_client(
+            queue, client_detached, _incomplete_stream_error_sse_event()
+        ):
+            await self._bill_collected_chunks(collected_chunks, stream_teardown=True)
+            return
+        await self._bill_collected_chunks(collected_chunks, stream_teardown=False)
+        if not await self._enqueue_for_client(queue, client_detached, None):
+            self._dispatch_pending_deferred_logging()
 
-        # Handle logging after all chunks are processed
-        await self._handle_streaming_logging(collected_chunks)
+    async def _handle_pump_upstream_error(
+        self,
+        queue: "asyncio.Queue[bytes | None | BaseException]",
+        client_detached: "asyncio.Event",
+        collected_chunks: list[bytes],  # mutable-ok: SSE buffer forwarded to list-typed _bill_collected_chunks
+        exc: BaseException,
+    ) -> None:
+        """Forward a provider error to a still-connected client, else salvage partial spend.
+
+        Handing the original exception to the client-facing generator lets it
+        re-raise so the proxy's failure handling keeps the provider status and
+        owns logging (no success-bill). If the client already went away, or
+        disconnects before ever consuming the queued exception, no failure hook
+        runs, so bill the partial instead of dropping the request.
+        """
+        from litellm._logging import verbose_proxy_logger
+
+        if not client_detached.is_set() and await self._enqueue_for_client(queue, client_detached, exc):
+            await client_detached.wait()
+            if not _exception_left_unconsumed(queue, exc):
+                return
+        verbose_proxy_logger.warning(
+            "async_sse_wrapper upstream pump failed after client disconnect (%d chunks): %s(%s)",
+            len(collected_chunks),
+            type(exc).__name__,
+            exc,
+        )
+        await self._bill_collected_chunks(collected_chunks, stream_teardown=True)
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
index 3d62b8b4784..988f81c9eb4 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/transformation.py
@@ -3,11 +3,6 @@ from typing import Any, Final
 
 import httpx
 
-from litellm.constants import (
-    DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET,
-    DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET,
-    DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET,
-)
 from litellm.exceptions import AuthenticationError
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.litellm_core_utils.litellm_logging import verbose_logger
@@ -400,46 +395,6 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
             existing_output_config.setdefault("effort", mapped_effort)
             optional_params["output_config"] = existing_output_config
 
-    @staticmethod
-    def _translate_legacy_thinking_for_adaptive_model(
-        model: str, optional_params: dict, custom_llm_provider: str
-    ) -> None:
-        """Translate legacy ``thinking.type=enabled`` to adaptive for the
-        adaptive-thinking models that reject it (4.7+ and the 5 families).
-        Models flagged ``supports_legacy_thinking`` (the 4.6 family) accept the
-        legacy shape natively, so it is forwarded verbatim and the caller's
-        ``budget_tokens`` cap keeps applying. Caller-provided
-        ``output_config.effort`` is never overridden.
-        """
-        from litellm.llms.anthropic.chat.transformation import AnthropicConfig
-
-        if not AnthropicModelInfo._is_adaptive_thinking_model(model, custom_llm_provider):
-            return
-        if AnthropicModelInfo._supports_legacy_thinking(model, custom_llm_provider):
-            return
-        thinking: Final = optional_params.get("thinking")
-        if not isinstance(thinking, dict) or thinking.get("type") != "enabled":
-            return
-
-        budget: Final = int(thinking.get("budget_tokens") or 0)
-        if budget >= DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET and (
-            AnthropicConfig._supports_effort_level(model, "xhigh", custom_llm_provider)
-        ):
-            effort = "xhigh"
-        elif budget >= DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET:
-            effort = "high"
-        elif budget >= DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET:
-            effort = "medium"
-        else:
-            effort = "low"
-
-        optional_params["thinking"] = {"type": "adaptive"}
-        existing_output_config = optional_params.get("output_config")
-        if not isinstance(existing_output_config, dict):
-            existing_output_config = {}
-        existing_output_config.setdefault("effort", effort)
-        optional_params["output_config"] = existing_output_config
-
     @staticmethod
     def _translate_adaptive_effort_for_non_adaptive_model(
         model: str, optional_params: dict, max_tokens: int | None, custom_llm_provider: str
@@ -606,7 +561,7 @@ class AnthropicMessagesConfig(BaseAnthropicMessagesConfig):
             custom_llm_provider=self._resolved_provider,
         )
 
-        self._translate_legacy_thinking_for_adaptive_model(
+        AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model(
             model=model,
             optional_params=anthropic_messages_optional_request_params,
             custom_llm_provider=self._resolved_provider,
diff --git a/litellm/llms/anthropic/experimental_pass_through/messages/utils.py b/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
index 02d82887dde..9deff950724 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/utils.py
@@ -1,11 +1,40 @@
+from collections.abc import Mapping
 from functools import lru_cache
-from typing import Any, Final, cast, get_type_hints
+from typing import TYPE_CHECKING, Any, Final, cast, get_type_hints
 
 from litellm.types.llms.anthropic import AnthropicMessagesRequestOptionalParams
 from litellm.types.llms.anthropic_messages.anthropic_response import (
     AnthropicMessagesResponse,
 )
 
+if TYPE_CHECKING:
+    from litellm.exceptions import ContentPolicyViolationError
+
+
+def get_safeguard_refusal_stop_details(response: object) -> Mapping[str, Any] | None:
+    """
+    Return the ``stop_details`` of an Anthropic Messages response refused by a
+    safeguard (``stop_reason: "refusal"`` carrying ``stop_details``:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback),
+    or None for any other response, a plain refusal without ``stop_details`` included.
+    """
+    if not isinstance(response, dict) or response.get("stop_reason") != "refusal":
+        return None
+    stop_details: Final = response.get("stop_details")
+    return stop_details if isinstance(stop_details, dict) else None
+
+
+def safeguard_refusal_error(model: str, stop_details: Mapping[str, object]) -> "ContentPolicyViolationError":
+    """The exception a safeguard-refused Anthropic response converts into so the
+    content-policy fallback chain can re-dispatch it."""
+    from litellm.exceptions import ContentPolicyViolationError
+
+    return ContentPolicyViolationError(
+        message=f"Anthropic safeguard refusal (category: {stop_details.get('category')}).",
+        model=model,
+        llm_provider="anthropic",
+    )
+
 
 @lru_cache(maxsize=1)
 def _anthropic_messages_optional_param_keys() -> frozenset[str]:
@@ -100,14 +129,12 @@ def mock_response(
             model=model,
         )
     return AnthropicMessagesResponse(
-        **{
-            "content": [{"text": mock_response, "type": "text"}],
-            "id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
-            "model": "claude-sonnet-4-20250514",
-            "role": "assistant",
-            "stop_reason": "end_turn",
-            "stop_sequence": None,
-            "type": "message",
-            "usage": {"input_tokens": 2095, "output_tokens": 503},
-        }
+        content=[{"text": mock_response, "type": "text"}],
+        id="msg_013Zva2CMHLNnXjNJJKqJ2EF",
+        model="claude-sonnet-4-20250514",
+        role="assistant",
+        stop_reason="end_turn",
+        stop_sequence=None,
+        type="message",
+        usage={"input_tokens": 2095, "output_tokens": 503},
     )
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/handler.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/handler.py
index b6ec9520e79..ec0560016da 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/handler.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/handler.py
@@ -160,7 +160,7 @@ class LiteLLMMessagesToResponsesAPIHandler:
         top_k: int | None = None,
         top_p: float | None = None,
         output_format: AnthropicOutputSchema | None = None,
-        **kwargs,
+        **kwargs: object,
     ) -> AnthropicMessagesResponse | AsyncIterator[bytes]:
         responses_kwargs: Final = _build_responses_kwargs(
             max_tokens=max_tokens,
@@ -214,7 +214,7 @@ class LiteLLMMessagesToResponsesAPIHandler:
         top_p: float | None = None,
         output_format: AnthropicOutputSchema | None = None,
         _is_async: bool = False,
-        **kwargs,
+        **kwargs: object,
     ) -> (
         AnthropicMessagesResponse
         | AsyncIterator[bytes]
diff --git a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
index ace7fc25dc9..0eb0e38a46e 100644
--- a/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
+++ b/litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
@@ -179,14 +179,14 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
         )
 
     @staticmethod
-    def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, Any]]) -> str:
+    def _assistant_block_group_key(indexed_block: tuple[int, Mapping[str, object]]) -> str:
         """Group a run of consecutive thinking blocks together; keep every other block alone."""
         index, block = indexed_block
         return "thinking" if block.get("type") == "thinking" else f"block:{index}"
 
     @classmethod
     def _assistant_group_to_input_item(
-        cls, group: tuple[Mapping[str, Any], ...]
+        cls, group: tuple[Mapping[str, object], ...]
     ) -> dict[str, Any] | None:  # mutable-ok: API message payload
         first: Final = group[0]
         btype: Final = first.get("type")
@@ -206,7 +206,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     def translate_messages_to_responses_input(
         self,
         messages: list[AllAnthropicPassThroughMessageValues],
-    ) -> list[dict[str, Any]]:
+    ) -> list[dict[str, object]]:
         """
         Convert Anthropic messages list to Responses API `input` items.
 
@@ -220,7 +220,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
           assistant thinking -> reasoning
           assistant tool_use -> function_call
         """
-        input_items: Final[list[dict[str, Any]]] = []
+        input_items: Final[list[dict[str, object]]] = []
 
         for m in messages:
             if m["role"] == "system":
@@ -248,7 +248,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
                         }
                     )
                 elif isinstance(content, list):
-                    user_parts: list[dict[str, Any]] = []
+                    user_parts: list[Mapping[str, object]] = []
                     tool_image_parts: list[dict[str, Any]] = []  # mutable-ok: json content parts
                     for block in content:
                         if not isinstance(block, dict):
@@ -379,9 +379,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     def translate_tools_to_responses_api(
         self,
         tools: list[AllAnthropicToolsValues],
-    ) -> list[dict[str, Any]]:
+    ) -> list[dict[str, object]]:
         """Convert Anthropic tool definitions to Responses API function tools."""
-        result: Final[list[dict[str, Any]]] = []
+        result: Final[list[dict[str, object]]] = []
         for tool in tools:
             tool_dict = cast(dict[str, Any], tool)
             tool_type = tool_dict.get("type", "")
@@ -392,7 +392,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
                 continue
             # Responses turns strict mode on when `strict` is omitted, silently rewriting
             # `required` to every property. Anthropic tools are non-strict unless asked.
-            func_tool: dict[str, Any] = {
+            func_tool: dict[str, object] = {
                 "type": "function",
                 "name": tool_name,
                 "strict": bool(tool_dict.get("strict")),
@@ -407,7 +407,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
     @staticmethod
     def translate_tool_choice_to_responses_api(
         tool_choice: AnthropicMessagesToolChoice,
-    ) -> str | dict[str, Any]:
+    ) -> str | dict[str, object]:
         """Convert Anthropic tool_choice to Responses API tool_choice."""
         tc_type: Final = tool_choice.get("type")
         if tc_type == "any":
@@ -420,8 +420,8 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
 
     @staticmethod
     def translate_context_management_to_responses_api(
-        context_management: dict[str, Any],
-    ) -> list[dict[str, Any]] | None:
+        context_management: dict[str, object],
+    ) -> list[dict[str, object]] | None:
         """
         Convert Anthropic context_management dict to OpenAI Responses API array format.
 
@@ -435,13 +435,13 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
         if not isinstance(edits, list):
             return None
 
-        result: Final[list[dict[str, Any]]] = []
+        result: Final[list[dict[str, object]]] = []
         for edit in edits:
             if not isinstance(edit, dict):
                 continue
             edit_type = edit.get("type", "")
             if edit_type == "compact_20260112":
-                entry: dict[str, Any] = {"type": "compaction"}
+                entry: dict[str, object] = {"type": "compaction"}
                 trigger = edit.get("trigger")
                 if isinstance(trigger, dict) and trigger.get("value") is not None:
                     entry["compact_threshold"] = int(trigger["value"])
@@ -451,9 +451,9 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
 
     @staticmethod
     def translate_thinking_to_reasoning(
-        thinking: dict[str, Any],
-        output_config: dict[str, Any] | None = None,
-    ) -> dict[str, Any] | None:
+        thinking: dict[str, object],
+        output_config: dict[str, object] | None = None,
+    ) -> dict[str, object] | None:
         """
         Convert Anthropic thinking param to Responses API reasoning param.
 
@@ -473,12 +473,14 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
             if isinstance(output_config, dict) and output_config.get("effort"):
                 effort = output_config["effort"]
         elif thinking_type == "enabled":
-            effort = reasoning_effort_from_thinking_budget(thinking.get("budget_tokens", 0))
+            raw_budget: Final = thinking.get("budget_tokens", 0)
+            budget_tokens: Final = int(raw_budget) if isinstance(raw_budget, (int, float)) else 0
+            effort = reasoning_effort_from_thinking_budget(budget_tokens)
         else:
             return None
 
         auto_summary: Final = is_reasoning_auto_summary_enabled()
-        result: Final[dict[str, Any]] = {"effort": effort}
+        result: Final[dict[str, object]] = {"effort": effort}
         summary: Final = thinking.get("summary")
         if summary:
             result["summary"] = summary
@@ -570,7 +572,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
         # output_format / output_config.format -> text format
         # output_format: {"type": "json_schema", "schema": {...}}
         # output_config: {"format": {"type": "json_schema", "schema": {...}}}
-        output_format: Any = anthropic_request.get("output_format")
+        output_format: object = anthropic_request.get("output_format")
         output_config = anthropic_request.get("output_config")
         if not isinstance(output_format, dict) and isinstance(output_config, dict):
             output_format = output_config.get("format")
@@ -620,7 +622,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
             ResponseReasoningItem,
         )
 
-        content: Final[list[dict[str, Any]]] = []
+        content: Final[list[dict[str, object]]] = []
         stop_reason: AnthropicFinishReason = "end_turn"
 
         for item in response.output:
diff --git a/litellm/llms/anthropic/files/handler.py b/litellm/llms/anthropic/files/handler.py
index 5fdf2ceff7f..dfd62ca575b 100644
--- a/litellm/llms/anthropic/files/handler.py
+++ b/litellm/llms/anthropic/files/handler.py
@@ -2,7 +2,7 @@ import asyncio
 import json
 import time
 from collections.abc import Coroutine
-from typing import Any, Final
+from typing import Final
 
 import httpx
 
@@ -116,7 +116,7 @@ class AnthropicFilesHandler:
         api_key: str | None = None,
         timeout: float | httpx.Timeout = 600.0,
         max_retries: int | None = None,
-    ) -> HttpxBinaryResponseContent | Coroutine[Any, Any, HttpxBinaryResponseContent]:
+    ) -> HttpxBinaryResponseContent | Coroutine[object, object, HttpxBinaryResponseContent]:
         """
         Retrieve file content from Anthropic.
 
diff --git a/litellm/llms/azure/azure.py b/litellm/llms/azure/azure.py
index 2bcc830851a..46a9dd1a531 100644
--- a/litellm/llms/azure/azure.py
+++ b/litellm/llms/azure/azure.py
@@ -2,7 +2,7 @@ import asyncio
 import json
 import time
 from collections.abc import Callable, Coroutine
-from typing import Any, Final
+from typing import Final
 
 import httpx
 from openai import (
@@ -374,7 +374,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         except Exception as e:
             status_code: Final = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
-            error_response: Final = getattr(e, "response", None)
+            error_response: Final[object] = getattr(e, "response", None)
             error_body: Final = getattr(e, "body", None)
             if error_headers is None and error_response:
                 error_headers = getattr(error_response, "headers", None)
@@ -392,7 +392,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         model: str,
         api_base: str,
         data: dict,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         dynamic_params: bool,
         model_response: ModelResponse,
         logging_obj: LiteLLMLoggingObj,
@@ -502,7 +502,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         dynamic_params: bool,
         data: dict[str, object],
         model: str,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         max_retries: int,
         azure_ad_token: str | None = None,
         azure_ad_token_provider: Callable | None = None,
@@ -578,7 +578,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         dynamic_params: bool,
         data: dict,
         model: str,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         max_retries: int,
         azure_ad_token: str | None = None,
         azure_ad_token_provider: Callable | None = None,
@@ -634,7 +634,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         except Exception as e:
             status_code: Final = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
-            error_response: Final = getattr(e, "response", None)
+            error_response: Final[object] = getattr(e, "response", None)
             message: Final = getattr(e, "message", str(e))
             error_body: Final = getattr(e, "body", None)
             if error_headers is None and error_response:
@@ -754,7 +754,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         aembedding=None,
         headers: dict | None = None,
         litellm_params: dict | None = None,
-    ) -> EmbeddingResponse | Coroutine[Any, Any, EmbeddingResponse]:
+    ) -> EmbeddingResponse | Coroutine[object, object, EmbeddingResponse]:
         if headers:
             optional_params["extra_headers"] = headers
         if self._client_session is None:
@@ -1268,7 +1268,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
                     headers["Authorization"] = f"Bearer {azure_ad_token}"
 
             # init AzureOpenAI Client
-            azure_client_params: Final[dict[str, Any]] = self.initialize_azure_sdk_client(
+            azure_client_params: Final[dict[str, object]] = self.initialize_azure_sdk_client(
                 litellm_params=litellm_params or {},
                 api_key=api_key,
                 model_name=model or "",
diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py
index 2df4ab731ab..0ac0662205a 100644
--- a/litellm/llms/azure/chat/gpt_transformation.py
+++ b/litellm/llms/azure/chat/gpt_transformation.py
@@ -1,3 +1,5 @@
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 from httpx._models import Headers, Response
@@ -6,6 +8,7 @@ import litellm
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     drop_tool_reference_parts_from_tool_messages,
     hoist_images_from_tool_messages,
+    tool_with_flattened_parameters,
 )
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_azure_openai_messages,
@@ -32,6 +35,19 @@ else:
     LoggingClass = Any
 
 
+_NO_TOOLS_UPDATE: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def flattened_tools_update(optional_params: Mapping[str, object]) -> Mapping[str, object]:
+    tools: Final = optional_params.get("tools")
+    if not isinstance(tools, list):
+        return _NO_TOOLS_UPDATE
+    flattened: Final = [  # mutable-ok: request tools are a JSON list
+        tool_with_flattened_parameters(tool) if isinstance(tool, dict) else tool for tool in tools
+    ]
+    return MappingProxyType({"tools": flattened})
+
+
 class AzureOpenAIConfig(BaseConfig):
     """
     Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions
@@ -261,6 +277,7 @@ class AzureOpenAIConfig(BaseConfig):
             "model": model,
             "messages": azure_messages,
             **optional_params,
+            **flattened_tools_update(optional_params),
         }
 
     def transform_response(
diff --git a/litellm/llms/azure/chat/o_series_transformation.py b/litellm/llms/azure/chat/o_series_transformation.py
index 6cbd91bab5d..246bf69cb5f 100644
--- a/litellm/llms/azure/chat/o_series_transformation.py
+++ b/litellm/llms/azure/chat/o_series_transformation.py
@@ -20,6 +20,7 @@ from litellm.types.llms.openai import AllMessageValues
 from litellm.utils import get_model_info, supports_reasoning
 
 from ...openai.chat.o_series_transformation import OpenAIOSeriesConfig
+from .gpt_transformation import flattened_tools_update
 
 
 class AzureOpenAIO1Config(OpenAIOSeriesConfig):
@@ -108,4 +109,8 @@ class AzureOpenAIO1Config(OpenAIOSeriesConfig):
         headers: dict,
     ) -> dict:
         model = model.replace("o_series/", "")  # handle o_series/my-random-deployment-name
-        return super().transform_request(model, messages, optional_params, litellm_params, headers)
+        flattened_params: Final = {  # mutable-ok: transform_request's contract takes a plain JSON params dict
+            **optional_params,
+            **flattened_tools_update(optional_params),
+        }
+        return super().transform_request(model, messages, flattened_params, litellm_params, headers)
diff --git a/litellm/llms/azure_ai/agents/handler.py b/litellm/llms/azure_ai/agents/handler.py
index a13b1300e55..f7382190fca 100644
--- a/litellm/llms/azure_ai/agents/handler.py
+++ b/litellm/llms/azure_ai/agents/handler.py
@@ -51,15 +51,13 @@ else:
     AsyncHTTPHandler = Any
 
 
-class _AzureRawAnnotation(TypedDict, total=False):
-    type: ReadOnly[str]
+class _AzureRawAnnotation(ChatCompletionAnnotation, total=False):
     text: ReadOnly[str]
     start_index: ReadOnly[int]
     end_index: ReadOnly[int]
-    url_citation: ReadOnly[ChatCompletionAnnotationURLCitation]
 
 
-_TransformedAnnotation: TypeAlias = ChatCompletionAnnotation | _AzureRawAnnotation
+_TransformedAnnotation: TypeAlias = ChatCompletionAnnotation
 
 
 class _AzureText(TypedDict, total=False):
@@ -223,18 +221,11 @@ class AzureAIAgentsHandler:
         """Build the ModelResponse from agent output."""
         from litellm.types.utils import Choices, Message, Usage
 
-        message_kwargs: Final[dict[str, Any]] = {
-            "content": content,
-            "role": "assistant",
-        }
-        if annotations:
-            message_kwargs["annotations"] = annotations
-
         model_response.choices = [
             Choices(
                 finish_reason="stop",
                 index=0,
-                message=Message(**message_kwargs),
+                message=Message(content=content, role="assistant", annotations=annotations or None),
             )
         ]
         model_response.model = model
@@ -655,9 +646,6 @@ class AzureAIAgentsHandler:
 
                 if data_str == "[DONE]":
                     # Send final chunk with finish_reason
-                    final_delta_kwargs: dict[str, Any] = {"content": None}
-                    if collected_annotations:
-                        final_delta_kwargs["annotations"] = collected_annotations
                     final_chunk = ModelResponseStream(
                         id=response_id,
                         created=created,
@@ -667,7 +655,7 @@ class AzureAIAgentsHandler:
                             StreamingChoices(
                                 finish_reason="stop",
                                 index=0,
-                                delta=Delta(**final_delta_kwargs),
+                                delta=Delta(content=None, annotations=collected_annotations or None),
                             )
                         ],
                     )
diff --git a/litellm/llms/azure_ai/anthropic/transformation.py b/litellm/llms/azure_ai/anthropic/transformation.py
index c5053448627..864d2134a84 100644
--- a/litellm/llms/azure_ai/anthropic/transformation.py
+++ b/litellm/llms/azure_ai/anthropic/transformation.py
@@ -17,13 +17,14 @@ def _promote_extra_body_to_optional_params(optional_params: dict) -> None:
     ``output_config`` get auto-routed into ``extra_body`` by
     ``add_provider_specific_params_to_optional_params``. For the Azure→Anthropic
     route those keys must reach the request body and be validated, so promote
-    them. ``setdefault`` keeps explicit top-level values authoritative.
+    them. The caller's values overwrite mapped top-level duplicates, matching
+    the native ``anthropic`` provider, where the same passthrough lands on
+    top-level ``optional_params`` after mapping.
     """
     extra_body: Final = optional_params.get("extra_body")
     if not isinstance(extra_body, dict) or not extra_body:
         return
-    for k, v in extra_body.items():
-        optional_params.setdefault(k, v)
+    optional_params.update(extra_body)
     optional_params.pop("extra_body", None)
 
 
diff --git a/litellm/llms/azure_ai/vector_stores/transformation.py b/litellm/llms/azure_ai/vector_stores/transformation.py
index 5e61d0a1dd9..64e72b819b1 100644
--- a/litellm/llms/azure_ai/vector_stores/transformation.py
+++ b/litellm/llms/azure_ai/vector_stores/transformation.py
@@ -19,6 +19,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -115,6 +116,7 @@ class AzureAIVectorStoreConfig(BaseVectorStoreConfig, BaseAzureLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, Any]]:
         """
         Transform search request for Azure AI Search API
diff --git a/litellm/llms/base_llm/files/azure_blob_storage_backend.py b/litellm/llms/base_llm/files/azure_blob_storage_backend.py
index e22cf528856..a192226110c 100644
--- a/litellm/llms/base_llm/files/azure_blob_storage_backend.py
+++ b/litellm/llms/base_llm/files/azure_blob_storage_backend.py
@@ -7,16 +7,36 @@ to reuse all authentication and Azure Storage operations.
 """
 
 import time
+from pathlib import Path
 from typing import Final
 from urllib.parse import quote, urlparse
 
 from litellm._logging import verbose_logger
 from litellm._uuid import uuid
 from litellm.integrations.azure_storage.azure_storage import AzureBlobStorageLogger
+from litellm.proxy.common_utils.path_utils import safe_filename
 
 from .storage_backend import BaseFileStorageBackend
 
 
+def _safe_basename(original_filename: str) -> str:
+    try:
+        return safe_filename(original_filename)
+    except ValueError:
+        return "file"
+
+
+def _safe_extension(original_filename: str) -> str:
+    """The extension off a basename, with no path separators or traversal sequences.
+
+    original_filename.split(".")[-1] does not parse path structure, so a filename
+    like "a.jsonl/../../etc/cron.d/x" would put "../../etc/cron.d/x" straight into
+    the blob path built below. Path.suffix only ever looks at the last path
+    component, so routing through safe_filename() first closes that off.
+    """
+    return Path(_safe_basename(original_filename)).suffix.lstrip(".")
+
+
 class AzureBlobStorageBackend(BaseFileStorageBackend, AzureBlobStorageLogger):
     """
     Azure Blob Storage backend implementation.
@@ -81,16 +101,15 @@ class AzureBlobStorageBackend(BaseFileStorageBackend, AzureBlobStorageLogger):
     def _generate_file_name(self, original_filename: str, file_naming_strategy: str) -> str:
         """Generate file name based on naming strategy."""
         if file_naming_strategy == "original_filename":
-            # Use original filename, but sanitize it
-            return quote(original_filename, safe="")
+            return quote(_safe_basename(original_filename), safe="")
         elif file_naming_strategy == "timestamp":
             # Use timestamp
-            extension = original_filename.split(".")[-1] if "." in original_filename else ""
+            extension = _safe_extension(original_filename)
             timestamp: Final = int(time.time() * 1000)  # milliseconds
             return f"{timestamp}.{extension}" if extension else str(timestamp)
         else:  # default to "uuid"
             # Use UUID
-            extension = original_filename.split(".")[-1] if "." in original_filename else ""
+            extension = _safe_extension(original_filename)
             file_uuid: Final = str(uuid.uuid4())
             return f"{file_uuid}.{extension}" if extension else file_uuid
 
diff --git a/litellm/llms/base_llm/guardrail_translation/base_translation.py b/litellm/llms/base_llm/guardrail_translation/base_translation.py
index ba96ab3dc99..220fcedb0f8 100644
--- a/litellm/llms/base_llm/guardrail_translation/base_translation.py
+++ b/litellm/llms/base_llm/guardrail_translation/base_translation.py
@@ -1,8 +1,11 @@
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, Final, Optional
 
 if TYPE_CHECKING:
+    from fastapi import HTTPException
+
     from litellm.integrations.custom_guardrail import (
         CustomGuardrail,
         ModifyResponseException,
@@ -73,6 +76,31 @@ class BaseTranslation(ABC):
 
         return transformed
 
+    @staticmethod
+    def merge_user_api_key_metadata_into_request(
+        request_data: dict[str, Any],  # mutable-ok: proxy hooks share and mutate the request payload dict in place
+        user_api_key_dict: Optional["UserAPIKeyAuth"],
+    ) -> None:
+        """
+        Add the prefixed ``user_api_key_*`` metadata to the request's resolved
+        metadata bucket without overwriting existing keys.
+
+        Writes must go through ``get_or_create_metadata_bucket``: creating a
+        ``litellm_metadata`` key on a route whose bucket is ``metadata`` (chat
+        completions) flips the bucket for every later metadata write, and spend
+        logging never sees those writes (e.g. guardrail_information).
+        """
+        from litellm.litellm_core_utils.core_helpers import (
+            get_or_create_metadata_bucket,
+        )
+
+        user_metadata: Final = BaseTranslation.transform_user_api_key_dict_to_metadata(user_api_key_dict)
+        if not user_metadata:
+            return
+        _, metadata_bucket = get_or_create_metadata_bucket(request_data)
+        for key, value in user_metadata.items():
+            metadata_bucket.setdefault(key, value)
+
     @abstractmethod
     async def process_input_messages(
         self,
@@ -127,8 +155,8 @@ class BaseTranslation(ABC):
         self,
         exc: "ModifyResponseException",
         stream_started: bool = False,
-        responses_so_far: list[Any] | None = None,
-    ) -> list[bytes] | None:
+        responses_so_far: Sequence[Any] | None = None,
+    ) -> Sequence[bytes] | None:
         """
         Build the streaming chunks that deliver a guardrail block message and
         cleanly terminate the stream in this provider's wire format.
@@ -147,6 +175,26 @@ class BaseTranslation(ABC):
         """
         return None
 
+    def build_stream_error_items(
+        self,
+        exc: "HTTPException",
+        responses_so_far: Sequence[Any] | None = None,
+    ) -> Sequence[Any] | None:
+        """
+        Build the stream items that surface a guardrail HTTPException (a block
+        with the default exception-on-block config, or a failed scan) after the
+        response has already started streaming, in this endpoint's wire format.
+
+        Called only once chunks have been sent: the HTTP status is gone, so the
+        failure must travel as an in-stream error frame. ``responses_so_far``
+        holds the chunks the client has already received, for formats whose
+        error frame continues the stream (e.g. sequence numbers).
+
+        Returns None when the format has no in-stream error frame; the caller
+        then re-raises ``exc``. Override in endpoint subclasses.
+        """
+        return None
+
     def get_structured_messages(self, data: dict) -> list["AllMessageValues"] | None:
         """
         Convert request data to OpenAI-spec structured messages.
diff --git a/litellm/llms/base_llm/guardrail_translation/utils.py b/litellm/llms/base_llm/guardrail_translation/utils.py
index f09ee210e6c..9b6f9c47105 100644
--- a/litellm/llms/base_llm/guardrail_translation/utils.py
+++ b/litellm/llms/base_llm/guardrail_translation/utils.py
@@ -124,6 +124,61 @@ def blocked_responses_api_usage(original_response: object) -> ResponseAPIUsage:
     )
 
 
+def stream_item_field(item: object, field: str) -> object | None:
+    if isinstance(item, dict):
+        return item.get(field)
+    return getattr(item, field, None)
+
+
+def blocked_chat_stream_usage(original_response: object) -> tuple[int, int]:
+    """
+    ``(prompt_tokens, completion_tokens)`` for a synthetic guardrail-blocked
+    chat completions stream.
+
+    A mid-stream block carries the chunks received so far as a list; real usage
+    rides on the final chunk when the upstream sent one
+    (``stream_options.include_usage``). Non-list originals defer to
+    ``blocked_response_usage``.
+    """
+    if not isinstance(original_response, list):
+        usage: Final = blocked_response_usage(original_response)
+        return usage.get("input_tokens", 0), usage.get("output_tokens", 0)
+    usage_obj: Final = next(
+        (
+            chunk_usage
+            for item in reversed(original_response)
+            if (chunk_usage := stream_item_field(item, "usage")) is not None
+        ),
+        None,
+    )
+    return (
+        _usage_tokens(usage_obj, "prompt_tokens", "input_tokens"),
+        _usage_tokens(usage_obj, "completion_tokens", "output_tokens"),
+    )
+
+
+def blocked_responses_stream_usage(original_response: object) -> ResponseAPIUsage:
+    """
+    ``ResponseAPIUsage`` for a synthetic guardrail-blocked /v1/responses stream.
+
+    A mid-stream block carries the events received so far as a list; real usage
+    rides on the ``response.completed`` event's response when the upstream sent
+    one. Non-list originals defer to ``blocked_responses_api_usage``.
+    """
+    if not isinstance(original_response, list):
+        return blocked_responses_api_usage(original_response)
+    completed: Final = next(
+        (
+            response
+            for item in reversed(original_response)
+            if stream_item_field(item, "type") == "response.completed"
+            and (response := stream_item_field(item, "response")) is not None
+        ),
+        None,
+    )
+    return blocked_responses_api_usage(completed)
+
+
 def effective_skip_system_message_for_guardrail(guardrail_to_apply: Any) -> bool:
     per: Final = getattr(guardrail_to_apply, "skip_system_message_in_guardrail", None)
     if per is not None:
diff --git a/litellm/llms/base_llm/managed_resources/base_managed_resource.py b/litellm/llms/base_llm/managed_resources/base_managed_resource.py
index cced330d873..4fbc0ce51b0 100644
--- a/litellm/llms/base_llm/managed_resources/base_managed_resource.py
+++ b/litellm/llms/base_llm/managed_resources/base_managed_resource.py
@@ -5,7 +5,8 @@
 import base64
 import json
 from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING, Any, Final, Generic, TypeVar, cast
+from collections.abc import Mapping
+from typing import TYPE_CHECKING, Any, Final, Generic, Protocol, TypeVar, cast, runtime_checkable
 
 from litellm import verbose_logger
 from litellm.llms.base_llm.managed_resources.isolation import (
@@ -38,6 +39,30 @@ else:
 ResourceObjectType = TypeVar("ResourceObjectType")
 
 
+@runtime_checkable
+class _HasIdentifier(Protocol):
+    id: str
+
+
+class _ManagedResourceRecord(Protocol[ResourceObjectType]):
+    unified_resource_id: str
+    resource_object: ResourceObjectType
+
+    def model_dump(self) -> dict[str, object]: ...
+
+
+class _ManagedResourceTable(Protocol[ResourceObjectType]):
+    async def create(self, *, data: Mapping[str, object]) -> object: ...
+
+    async def find_first(self, *, where: Mapping[str, object]) -> _ManagedResourceRecord[ResourceObjectType] | None: ...
+
+    async def find_many(
+        self, *, where: Mapping[str, object], take: int, order: Mapping[str, str]
+    ) -> list[_ManagedResourceRecord[ResourceObjectType]]: ...
+
+    async def delete(self, *, where: Mapping[str, object]) -> object: ...
+
+
 class BaseManagedResource(ABC, Generic[ResourceObjectType]):
     """
     Base class for managing resources with target_model_names support.
@@ -64,6 +89,9 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
         self.internal_usage_cache = internal_usage_cache
         self.prisma_client = prisma_client
 
+    def _resource_table(self) -> _ManagedResourceTable[ResourceObjectType]:
+        return getattr(self.prisma_client.db, self.table_name)
+
     # ============================================================================
     #                          ABSTRACT METHODS
     # ============================================================================
@@ -137,7 +165,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
         litellm_parent_otel_span: Span | None,
         model_mappings: dict[str, str],
         user_api_key_dict: UserAPIKeyAuth,
-        additional_db_fields: dict[str, Any] | None = None,
+        additional_db_fields: Mapping[str, object] | None = None,
     ) -> None:
         """
         Store unified resource ID with model mappings in cache and database.
@@ -153,7 +181,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
         verbose_logger.info("Storing LiteLLM Managed %s with id=%s in cache", self.resource_type, unified_resource_id)
 
         # Prepare cache data
-        cache_data: Final = {
+        cache_data: Final[dict[str, object]] = {
             "unified_resource_id": unified_resource_id,
             "resource_object": resource_object,
             "model_mappings": model_mappings,
@@ -176,7 +204,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
             )
 
         # Prepare database data
-        db_data: Final = {
+        db_data: Final[dict[str, object]] = {
             "unified_resource_id": unified_resource_id,
             "model_mappings": json.dumps(model_mappings),
             "flat_model_resource_ids": list(model_mappings.values()),
@@ -205,7 +233,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
             db_data.update(additional_db_fields)
 
         # Store in database
-        table: Final = getattr(self.prisma_client.db, self.table_name)
+        table: Final = self._resource_table()
         result: Final = await table.create(data=db_data)
 
         verbose_logger.debug(
@@ -240,7 +268,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
             return result
 
         # Check database
-        table: Final = getattr(self.prisma_client.db, self.table_name)
+        table: Final = self._resource_table()
         db_object: Final = await table.find_first(where={"unified_resource_id": unified_resource_id})
 
         if db_object:
@@ -264,7 +292,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
             The deleted resource object or None if not found
         """
         # Get old value from database
-        table: Final = getattr(self.prisma_client.db, self.table_name)
+        table: Final = self._resource_table()
         initial_value: Final = await table.find_first(where={"unified_resource_id": unified_resource_id})
 
         if initial_value is None:
@@ -515,7 +543,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
         user_api_key_dict: UserAPIKeyAuth,
         limit: int | None = None,
         after: str | None = None,
-        additional_filters: dict[str, Any] | None = None,
+        additional_filters: Mapping[str, object] | None = None,
     ) -> dict[str, Any]:
         """
         List resources created by a user.
@@ -533,7 +561,7 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
         if owner_filter is None:
             return build_list_page([])
 
-        where_clause: Final[dict[str, Any]] = {**owner_filter}
+        where_clause: Final[dict[str, object]] = {**owner_filter}
 
         if after:
             where_clause["id"] = {"gt": after}
@@ -544,14 +572,14 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
 
         # Fetch resources
         fetch_limit: Final = limit or 20
-        table: Final = getattr(self.prisma_client.db, self.table_name)
+        table: Final = self._resource_table()
         resources: Final = await table.find_many(
             where=where_clause,
             take=fetch_limit,
             order={"created_at": "desc"},
         )
 
-        resource_objects: Final[list[Any]] = []
+        resource_objects: Final[list[object]] = []
         for resource in resources:
             try:
                 # Stop once we have enough
@@ -559,12 +587,13 @@ class BaseManagedResource(ABC, Generic[ResourceObjectType]):
                     break
 
                 # Parse resource object
-                resource_data = resource.resource_object
-                if isinstance(resource_data, str):
-                    resource_data = json.loads(resource_data)
+                stored_resource = resource.resource_object
+                resource_data: object = (
+                    json.loads(stored_resource) if isinstance(stored_resource, str) else stored_resource
+                )
 
                 # Set unified ID
-                if hasattr(resource_data, "id"):
+                if isinstance(resource_data, _HasIdentifier):
                     resource_data.id = resource.unified_resource_id
                 elif isinstance(resource_data, dict):
                     resource_data["id"] = resource.unified_resource_id
diff --git a/litellm/llms/base_llm/ocr/transformation.py b/litellm/llms/base_llm/ocr/transformation.py
index d1c77186ea8..3b302837032 100644
--- a/litellm/llms/base_llm/ocr/transformation.py
+++ b/litellm/llms/base_llm/ocr/transformation.py
@@ -75,6 +75,7 @@ class OCRUsageInfo(LiteLLMPydanticObjectBase):
     """Usage information from OCR response."""
 
     pages_processed: int | None = None
+    pages_processed_annotation: int | None = None
     credits: float | None = None
     doc_size_bytes: int | None = None
 
diff --git a/litellm/llms/base_llm/vector_store/transformation.py b/litellm/llms/base_llm/vector_store/transformation.py
index 02a51a8bace..63e99c0915a 100644
--- a/litellm/llms/base_llm/vector_store/transformation.py
+++ b/litellm/llms/base_llm/vector_store/transformation.py
@@ -17,6 +17,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     from ..chat.transformation import BaseLLMException as _BaseLLMException
 
@@ -57,6 +58,7 @@ class BaseVectorStoreConfig:
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         pass
 
@@ -69,6 +71,7 @@ class BaseVectorStoreConfig:
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """
         Optional async version of transform_search_vector_store_request.
@@ -84,6 +87,7 @@ class BaseVectorStoreConfig:
             litellm_logging_obj=litellm_logging_obj,
             litellm_params=litellm_params,
             extra_body=extra_body,
+            router=router,
         )
 
     @abstractmethod
@@ -197,6 +201,7 @@ class BaseDirectVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: Mapping[str, object],
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> NoReturn:
         raise NotImplementedError("Direct vector store providers execute the search themselves; no HTTP request shape")
 
diff --git a/litellm/llms/bedrock/base_aws_llm.py b/litellm/llms/bedrock/base_aws_llm.py
index 852cfaa24f2..1e634ced29b 100644
--- a/litellm/llms/bedrock/base_aws_llm.py
+++ b/litellm/llms/bedrock/base_aws_llm.py
@@ -1442,7 +1442,7 @@ class BaseAWSLLM:
     @tracer.wrap()
     def get_request_headers(
         self,
-        credentials: Credentials,
+        credentials: Credentials | None,
         aws_region_name: str,
         extra_headers: dict | None,
         endpoint_url: str,
@@ -1469,9 +1469,13 @@ class BaseAWSLLM:
             try:
                 from botocore.auth import SigV4Auth
                 from botocore.awsrequest import AWSRequest
+                from botocore.exceptions import NoCredentialsError
             except ImportError:
                 raise ImportError("Missing boto3 to call bedrock. Run 'pip install boto3'.")
 
+            if credentials is None:
+                raise NoCredentialsError()
+
             # Filter headers for AWS signature calculation
             # AWS SigV4 only includes specific headers in signature calculation
             aws_signature_headers: Final = self._filter_headers_for_aws_signature(headers)
diff --git a/litellm/llms/bedrock/chat/converse_handler.py b/litellm/llms/bedrock/chat/converse_handler.py
index ca5f1298360..7d5f99ca893 100644
--- a/litellm/llms/bedrock/chat/converse_handler.py
+++ b/litellm/llms/bedrock/chat/converse_handler.py
@@ -1,4 +1,6 @@
 import json
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Any, Final
 
 import httpx
@@ -24,6 +26,22 @@ from ..common_utils import BedrockError, _get_all_bedrock_regions
 from .invoke_handler import AWSEventStreamDecoder, MockResponseIterator, make_call
 
 
+def _sigv4_principal(credentials: Credentials | None) -> Mapping[str, str]:
+    if credentials is None:
+        return MappingProxyType({})
+    return MappingProxyType(
+        {
+            key: value
+            for key, value in (
+                ("aws_access_key_id", credentials.access_key),
+                ("aws_secret_access_key", credentials.secret_key),
+                ("aws_session_token", credentials.token),
+            )
+            if value is not None
+        }
+    )
+
+
 def make_sync_call(
     client: HTTPHandler | None,
     api_base: str,
@@ -95,7 +113,7 @@ class BedrockConverseLLM(BaseAWSLLM):
         stream,
         optional_params: dict,
         litellm_params: dict,
-        credentials: Credentials,
+        credentials: Credentials | None,
         logger_fn=None,
         headers={},
         client: AsyncHTTPHandler | None = None,
@@ -167,7 +185,7 @@ class BedrockConverseLLM(BaseAWSLLM):
         stream,
         optional_params: dict,
         litellm_params: dict,
-        credentials: Credentials,
+        credentials: Credentials | None,
         logger_fn=None,
         headers: dict = {},
         client: AsyncHTTPHandler | None = None,
@@ -331,7 +349,7 @@ class BedrockConverseLLM(BaseAWSLLM):
 
         litellm_params["aws_region_name"] = aws_region_name  # [DO NOT DELETE] important for async calls
 
-        credentials: Final[Credentials] = self.get_credentials(
+        credentials: Final[Credentials | None] = self.get_credentials(
             aws_access_key_id=aws_access_key_id,
             aws_secret_access_key=aws_secret_access_key,
             aws_session_token=aws_session_token,
@@ -368,19 +386,13 @@ class BedrockConverseLLM(BaseAWSLLM):
         # The Rust core owns the whole call for the subset it accepts. Ask
         # before transforming so whichever path runs emits pre_call once, and
         # hand down the credentials, region and endpoint this handler already
-        # resolved so both paths sign as the same principal.
+        # resolved so both paths sign as the same principal. Bearer-token auth
+        # resolves no SigV4 principal at all, and each path reads that token
+        # itself.
         rust_optional_params: Final = {  # mutable-ok: json.dumps in the bridge rejects a mappingproxy
             **optional_params,
-            **{  # mutable-ok: merged into its mutable parent above
-                key: value
-                for key, value in (
-                    ("aws_access_key_id", credentials.access_key),
-                    ("aws_secret_access_key", credentials.secret_key),
-                    ("aws_session_token", credentials.token),
-                    ("aws_region_name", aws_region_name),
-                )
-                if value is not None
-            },
+            **_sigv4_principal(credentials),
+            "aws_region_name": aws_region_name,
         }
         serves_via_rust: Final = rust_chat_completions_accepts(
             model=model,
diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index db9c8a5cedd..e097805f54a 100644
--- a/litellm/llms/bedrock/chat/converse_transformation.py
+++ b/litellm/llms/bedrock/chat/converse_transformation.py
@@ -87,6 +87,7 @@ from ..common_utils import (
     BedrockError,
     BedrockModelInfo,
     bedrock_converse_supports_parallel_tool_use_config,
+    bedrock_model_accepts_cache_points,
     get_anthropic_beta_from_headers,
     get_bedrock_tool_name,
     is_bedrock_application_inference_profile_arn,
@@ -588,6 +589,10 @@ class AmazonConverseConfig(BaseConfig):
             supported_params.append("context_management")
         return supported_params
 
+    @staticmethod
+    def _auto_tool_choice() -> ToolChoiceValuesBlock:
+        return ToolChoiceValuesBlock(auto={})
+
     def map_tool_choice_values(
         self, model: str, tool_choice: str | dict, drop_params: bool
     ) -> ToolChoiceValuesBlock | None:
@@ -600,10 +605,14 @@ class AmazonConverseConfig(BaseConfig):
                     status_code=400,
                 )
         elif tool_choice == "required":
+            if AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+                return self._auto_tool_choice()
             return ToolChoiceValuesBlock(any={})
         elif tool_choice == "auto":
-            return ToolChoiceValuesBlock(auto={})
+            return self._auto_tool_choice()
         elif isinstance(tool_choice, dict):
+            if AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+                return self._auto_tool_choice()
             # only supported for anthropic + mistral models - https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ToolChoice.html
             specific_tool: Final = SpecificToolChoiceBlock(
                 name=make_valid_bedrock_tool_name(tool_choice.get("function", {}).get("name", ""))
@@ -934,6 +943,9 @@ class AmazonConverseConfig(BaseConfig):
                         litellm.verbose_logger.warning(DROP_UNSUPPORTED_ADAPTIVE_THINKING_WARNING, model)
                 else:
                     optional_params["thinking"] = value
+                    AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model(
+                        model=model, optional_params=optional_params, custom_llm_provider="bedrock"
+                    )
             elif param == "reasoning_effort" and isinstance(value, str):
                 self._handle_reasoning_effort_parameter(
                     model=model, reasoning_effort=value, optional_params=optional_params
@@ -1065,6 +1077,7 @@ class AmazonConverseConfig(BaseConfig):
             if (
                 litellm.utils.supports_tool_choice(model=model, custom_llm_provider=self.custom_llm_provider)
                 and not is_thinking_enabled
+                and not AnthropicModelInfo.forced_tool_use_unsupported(model)
             ):
                 optional_params["tool_choice"] = ToolChoiceValuesBlock(
                     tool=SpecificToolChoiceBlock(name=RESPONSE_FORMAT_TOOL_NAME)
@@ -1140,7 +1153,7 @@ class AmazonConverseConfig(BaseConfig):
         model: str | None = None,
     ) -> SystemContentBlock | ContentBlock | None:
         cache_control: Final = message_block.get("cache_control", None)
-        if cache_control is None:
+        if cache_control is None or not bedrock_model_accepts_cache_points(model):
             return None
 
         cache_point: Final = self._build_cache_point_block(cache_control, model)
@@ -1324,6 +1337,7 @@ class AmazonConverseConfig(BaseConfig):
             )
 
         additional_request_params.pop("parallel_tool_calls", None)
+        additional_request_params.pop("client_metadata", None)
 
         # Only set the topK value in for models that support it
         additional_request_params.update(self._handle_top_k_value(model, inference_params, drop_params))
@@ -1604,7 +1618,7 @@ class AmazonConverseConfig(BaseConfig):
 
         # Append cachePoint to tools if cache_control_injection_points has tool_config
         cache_injection_points: Final = additional_request_params.pop("cache_control_injection_points", None)
-        if cache_injection_points and len(bedrock_tools) > 0:
+        if cache_injection_points and len(bedrock_tools) > 0 and bedrock_model_accepts_cache_points(model):
             for point in cache_injection_points:
                 if point.get("location") == "tool_config":
                     cache_point = self._build_cache_point_block(point.get("control"), model)
@@ -1631,6 +1645,11 @@ class AmazonConverseConfig(BaseConfig):
                 bedrock_tool_config["toolChoice"] = tool_choice_values
                 self._drop_tool_choice_type_conflicting_with_tool_config(additional_request_params)
 
+        config_block_entries: Final = tuple(
+            (config_name, config_class, inference_params.pop(config_name, None))
+            for config_name, config_class in self.get_config_blocks().items()
+        )
+
         data: Final[CommonRequestObject] = {
             "inferenceConfig": self._transform_inference_params(inference_params=inference_params),
         }
@@ -1641,9 +1660,7 @@ class AmazonConverseConfig(BaseConfig):
         if system_content_blocks:
             data["system"] = system_content_blocks
 
-        # Handle all config blocks
-        for config_name, config_class in self.get_config_blocks().items():
-            config_value = inference_params.pop(config_name, None)
+        for config_name, config_class, config_value in config_block_entries:
             if config_value is not None:
                 data[config_name] = config_class(**config_value)
 
diff --git a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
index 40b90014f3b..67720451c00 100644
--- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
@@ -3,7 +3,7 @@ from typing import TYPE_CHECKING, Any, Final
 import httpx
 
 from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers
-from litellm.litellm_core_utils.litellm_logging import verbose_logger
+from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_anthropic_image_obj,
 )
@@ -12,21 +12,21 @@ from litellm.litellm_core_utils.prompt_templates.image_handling import (
     convert_url_to_base64,
 )
 from litellm.llms.anthropic.chat.transformation import AnthropicConfig
+from litellm.llms.anthropic.common_utils import AnthropicModelInfo
 from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation import (
     AmazonInvokeConfig,
 )
 from litellm.llms.bedrock.common_utils import (
-    convert_bedrock_invoke_output_format_to_inline_schema,
+    apply_bedrock_invoke_structured_output,
     get_anthropic_beta_from_headers,
     normalize_bedrock_opus_output_config_effort,
     normalize_custom_field_on_tools,
     normalize_tool_input_schema_types_for_bedrock_invoke,
-    pop_bedrock_invoke_output_config_format,
+    strip_unsupported_bedrock_invoke_output_config_keys,
 )
 from litellm.types.llms.anthropic import ANTHROPIC_TOOL_SEARCH_BETA_HEADER
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse
-from litellm.utils import _supports_factory
 
 if TYPE_CHECKING:
     import tiktoken
@@ -76,10 +76,14 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
         drop_params: bool,
     ) -> dict:
         # Force tool-based structured outputs for Bedrock Invoke
-        # (similar to VertexAI fix in #19201)
-        # Bedrock Invoke doesn't support output_format parameter
+        # (similar to VertexAI fix in #19201) unless the model map advertises
+        # native structured output
+        from litellm.utils import supports_native_structured_output
+
         original_model: Final = model
-        if "response_format" in non_default_params:
+        if "response_format" in non_default_params and not supports_native_structured_output(
+            model=model, custom_llm_provider="bedrock"
+        ):
             # Use a model name that forces tool-based approach
             model = "claude-3-sonnet-20240229"
 
@@ -103,6 +107,20 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
         # Restore original model name
         model = original_model
 
+        AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model(
+            model=original_model, optional_params=optional_params, custom_llm_provider="bedrock"
+        )
+
+        # The stub model hides the original model from the parent's forced-tool-use backstop
+        response_format_tool_choice: Final = optional_params.get("tool_choice")
+        if (
+            "response_format" in non_default_params
+            and isinstance(response_format_tool_choice, dict)
+            and response_format_tool_choice.get("name") == RESPONSE_FORMAT_TOOL_NAME
+            and AnthropicModelInfo.forced_tool_use_unsupported(original_model)
+        ):
+            optional_params.pop("tool_choice")
+
         return optional_params
 
     @staticmethod
@@ -212,36 +230,14 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
         anthropic_request.pop("model", None)
         anthropic_request.pop("stream", None)
         anthropic_request.pop("stream_chunk_size", None)
-        output_format: Final = anthropic_request.pop("output_format", None)
-        output_config_format: Final = pop_bedrock_invoke_output_config_format(anthropic_request)
-        if output_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_format,
-                request_body=anthropic_request,
-            )
-        elif output_config_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_config_format,
-                request_body=anthropic_request,
-            )
-        if not (
-            _supports_factory(
-                model=model,
-                custom_llm_provider="bedrock",
-                key="supports_output_config",
-            )
-            or AnthropicConfig._model_supports_effort_param(model, "bedrock")
-        ):
-            if anthropic_request.pop("output_config", None) is not None:
-                verbose_logger.warning(
-                    "Bedrock Invoke: stripping unsupported `output_config` for "
-                    "model=%s — neither `supports_output_config` nor any "
-                    "`supports_*_reasoning_effort` flag is set in "
-                    "model_prices_and_context_window.json. Add the capability "
-                    "flag to the model JSON entry if this model accepts "
-                    "`output_config`.",
-                    model,
-                )
+        apply_bedrock_invoke_structured_output(
+            model=model,
+            request_body=anthropic_request,
+        )
+        strip_unsupported_bedrock_invoke_output_config_keys(
+            model=model,
+            request_body=anthropic_request,
+        )
         if "anthropic_version" not in anthropic_request:
             anthropic_request["anthropic_version"] = self.anthropic_version
 
diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py
index 72e3cc1b326..1e5329c90dd 100644
--- a/litellm/llms/bedrock/common_utils.py
+++ b/litellm/llms/bedrock/common_utils.py
@@ -177,6 +177,95 @@ def convert_bedrock_invoke_output_format_to_inline_schema(
     request_body["messages"] = new_messages
 
 
+def _bedrock_model_supports(model: str, key: str) -> bool:
+    from litellm.utils import _supports_factory
+
+    return _supports_factory(model=model, custom_llm_provider="bedrock", key=key)
+
+
+def apply_bedrock_invoke_structured_output(
+    model: str,
+    request_body: dict[str, object],  # mutable-ok: edited in place like siblings
+) -> None:
+    """
+    Route Anthropic structured-output params to what the Bedrock model supports.
+
+    Consumes the legacy top-level ``output_format`` and the newer
+    ``output_config.format``, keeping the pre-existing precedence of the legacy
+    field when a request carries both. Models flagged
+    ``supports_native_structured_output`` in the model map get the schema
+    forwarded as ``output_config.format``, which Bedrock relays to the model for
+    enforced structured output. For every other model the schema is inlined into
+    the last user message as best-effort text, with a warning because nothing
+    enforces it.
+    """
+    legacy_output_format: Final = request_body.pop("output_format", None)
+    output_config_format: Final = pop_bedrock_invoke_output_config_format(request_body)
+    schema_format: Final = legacy_output_format if isinstance(legacy_output_format, dict) else output_config_format
+    if schema_format is None:
+        return
+
+    if _bedrock_model_supports(model, "supports_native_structured_output"):
+        existing_output_config: Final = request_body.get("output_config")
+        if isinstance(existing_output_config, dict):
+            existing_output_config["format"] = schema_format
+        else:
+            request_body["output_config"] = {"format": schema_format}  # rebind-ok: out-param  # mutable-ok: json
+        return
+
+    verbose_logger.warning(
+        "Bedrock Invoke: model=%s does not advertise `supports_native_structured_output` "
+        "in model_prices_and_context_window.json, so the JSON schema was inlined into "
+        "the last user message and is NOT enforced by the model.",
+        model,
+    )
+    convert_bedrock_invoke_output_format_to_inline_schema(
+        output_format=schema_format,
+        request_body=request_body,
+    )
+
+
+def strip_unsupported_bedrock_invoke_output_config_keys(
+    model: str,
+    request_body: dict[str, object],  # mutable-ok: edited in place like siblings
+) -> None:
+    """
+    Drop ``output_config`` keys the Bedrock model does not accept.
+
+    ``format`` survives unconditionally: it is only attached for models whose map
+    entry advertises ``supports_native_structured_output``. Effort-bearing keys
+    survive only when the map flags ``supports_output_config`` or a
+    ``supports_*_reasoning_effort`` tier; otherwise they are dropped with a
+    warning so Bedrock does not reject the request.
+    """
+    from litellm.llms.anthropic.chat.transformation import AnthropicConfig
+
+    output_config: Final = request_body.get("output_config")
+    if not isinstance(output_config, dict):
+        return
+    if all(key == "format" for key in output_config):
+        return
+    if _bedrock_model_supports(model, "supports_output_config") or AnthropicConfig._model_supports_effort_param(
+        model, "bedrock"
+    ):
+        return
+
+    verbose_logger.warning(
+        "Bedrock Invoke: stripping unsupported `output_config` keys for "
+        "model=%s: neither `supports_output_config` nor any "
+        "`supports_*_reasoning_effort` flag is set in "
+        "model_prices_and_context_window.json. Add the capability "
+        "flag to the model JSON entry if this model accepts "
+        "`output_config`.",
+        model,
+    )
+    preserved_format: Final = output_config.get("format")
+    if preserved_format is None:
+        request_body.pop("output_config", None)
+    else:
+        request_body["output_config"] = {"format": preserved_format}  # rebind-ok: out-param  # mutable-ok: json
+
+
 def normalize_custom_field_on_tools(request_body: dict) -> None:
     """
     Drop the ``custom`` field from each tool, first hoisting a boolean
@@ -659,6 +748,15 @@ def strip_bedrock_throughput_suffix(model: str) -> str:
 
 
 MANTLE_MESSAGES_PATH: Final = "/anthropic/v1/messages"
+_MANTLE_OPENAI_BASE_SUFFIXES: Final = ("/openai/v1", "/v1")
+
+
+def _mantle_api_base_from_env() -> str | None:
+    env_base: Final = get_secret_str("BEDROCK_MANTLE_API_BASE")
+    if env_base is None:
+        return None
+    base: Final = env_base.rstrip("/")
+    return next((base[: -len(suffix)] for suffix in _MANTLE_OPENAI_BASE_SUFFIXES if base.endswith(suffix)), base)
 
 
 def build_mantle_messages_url(
@@ -669,12 +767,15 @@ def build_mantle_messages_url(
     """Build the bedrock-mantle Anthropic /messages URL.
 
     Honors an explicit endpoint override (``api_base``, then
-    ``aws_bedrock_runtime_endpoint``) so private VPC / VPCE / GovCloud Mantle
-    endpoints are reachable; otherwise falls back to the public regional host.
+    ``aws_bedrock_runtime_endpoint``, then ``BEDROCK_MANTLE_API_BASE``) so
+    private VPC / VPCE / GovCloud Mantle endpoints are reachable; otherwise
+    falls back to the public regional host.
     The mantle messages path is appended unless the override already carries it,
-    so callers can pass either the host or the full messages URL.
+    so callers can pass either the host or the full messages URL. The env var is
+    shared with the OpenAI-surface ``bedrock_mantle/*`` routes, which need it to
+    carry their ``/v1`` or ``/openai/v1`` base, so that suffix is dropped first.
     """
-    override: Final = api_base or aws_bedrock_runtime_endpoint
+    override: Final = api_base or aws_bedrock_runtime_endpoint or _mantle_api_base_from_env()
     if override:
         base: Final = override.rstrip("/")
         if base.endswith(MANTLE_MESSAGES_PATH):
@@ -727,6 +828,30 @@ def bedrock_converse_supports_parallel_tool_use_config(model: str) -> bool:
     )
 
 
+def bedrock_model_accepts_cache_points(model: str | None) -> bool:
+    """
+    Whether Converse ``cachePoint`` blocks may be sent to this model.
+
+    Bedrock rejects requests carrying cachePoint blocks for models without prompt
+    caching support ("You invoked an unsupported model or your request did not allow
+    prompt caching"), so a model whose cost-map entry does not declare
+    ``supports_prompt_caching`` must not receive them. A model absent from the map
+    (an application inference profile ARN, a model newer than the map) keeps emitting
+    so existing caching setups never silently degrade. ``litellm.utils.supports_prompt_caching``
+    is not reusable here: it returns False for unmapped models, the opposite polarity.
+    """
+    if model is None:
+        return True
+    entries: Final = tuple(
+        entry
+        for candidate in (model, get_bedrock_base_model(model))
+        if (entry := litellm.model_cost.get(candidate)) is not None
+    )
+    if not entries:
+        return True
+    return any(entry.get("supports_prompt_caching") is True for entry in entries)
+
+
 def is_claude_4_5_on_bedrock(model: str) -> bool:
     """
     Check if the model supports Bedrock prompt caching with an extended '1h' TTL
@@ -1487,6 +1612,7 @@ class CommonBatchFilesUtils:
             aws_role_name=optional_params.get("aws_role_name"),
             aws_web_identity_token=optional_params.get("aws_web_identity_token"),
             aws_sts_endpoint=optional_params.get("aws_sts_endpoint"),
+            aws_external_id=optional_params.get("aws_external_id"),
         )
 
         # Prepare the request data
diff --git a/litellm/llms/bedrock/files/handler.py b/litellm/llms/bedrock/files/handler.py
index 13718d41cc1..e74c3802d20 100644
--- a/litellm/llms/bedrock/files/handler.py
+++ b/litellm/llms/bedrock/files/handler.py
@@ -113,6 +113,7 @@ class BedrockFilesHandler(BaseAWSLLM):
             aws_role_name=optional_params.get("aws_role_name"),
             aws_web_identity_token=optional_params.get("aws_web_identity_token"),
             aws_sts_endpoint=optional_params.get("aws_sts_endpoint"),
+            aws_external_id=optional_params.get("aws_external_id"),
         )
 
         # Create S3 client
diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py
index f442608a288..33b27943ad8 100644
--- a/litellm/llms/bedrock/files/transformation.py
+++ b/litellm/llms/bedrock/files/transformation.py
@@ -146,6 +146,7 @@ class _BedrockS3RequestParams(BaseModel):
     aws_role_name: str | None = None
     aws_web_identity_token: str | None = None
     aws_sts_endpoint: str | None = None
+    aws_external_id: str | None = None
     s3_region_name: str | None = None
     s3_endpoint_url: str | None = None
 
@@ -1029,6 +1030,7 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig):
             aws_role_name=optional_params.get("aws_role_name"),
             aws_web_identity_token=optional_params.get("aws_web_identity_token"),
             aws_sts_endpoint=optional_params.get("aws_sts_endpoint"),
+            aws_external_id=optional_params.get("aws_external_id"),
         )
 
         # Calculate SHA256 hash of the content (REQUIRED for S3)
@@ -1290,6 +1292,7 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig):
             aws_role_name=request_params.aws_role_name,
             aws_web_identity_token=request_params.aws_web_identity_token,
             aws_sts_endpoint=request_params.aws_sts_endpoint,
+            aws_external_id=request_params.aws_external_id,
         )
 
         empty_body_hash: Final = hashlib.sha256(b"").hexdigest()
diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
index f74a290d773..6ff9f0155f9 100644
--- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
@@ -29,14 +29,14 @@ from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation
     AmazonInvokeConfig,
 )
 from litellm.llms.bedrock.common_utils import (
-    convert_bedrock_invoke_output_format_to_inline_schema,
+    apply_bedrock_invoke_structured_output,
     ensure_bedrock_anthropic_messages_tool_names,
     get_anthropic_beta_from_headers,
     is_claude_4_5_on_bedrock,
     normalize_bedrock_opus_output_config_effort,
     normalize_custom_field_on_tools,
     normalize_tool_input_schema_types_for_bedrock_invoke,
-    pop_bedrock_invoke_output_config_format,
+    strip_unsupported_bedrock_invoke_output_config_keys,
 )
 from litellm.llms.bedrock.request_metadata import (
     bedrock_request_metadata_headers,
@@ -51,7 +51,6 @@ from litellm.types.llms.openai import AllMessageValues
 from litellm.types.router import GenericLiteLLMParams
 from litellm.types.utils import GenericStreamingChunk, ModelResponseStream
 from litellm.types.utils import GenericStreamingChunk as GChunk
-from litellm.utils import _supports_factory
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
@@ -708,52 +707,25 @@ class AmazonAnthropicClaudeMessagesConfig(
         # 4. Remove `ttl` field from cache_control in messages (Bedrock doesn't support it for older models)
         self._remove_ttl_from_cache_control(anthropic_messages_request=anthropic_messages_request, model=model)
 
-        # 5. Convert structured-output params to inline schema.
-        # Bedrock Invoke doesn't support top-level `output_format`; its
-        # accepted `output_config` subset is also narrower than Anthropic's, so
-        # consume the newer `output_config.format` shape here instead of
-        # forwarding it as an unknown nested key.
+        # 5. Route structured-output params (`output_format` /
+        # `output_config.format`) to native enforcement or the inline-schema
+        # fallback, then strip `output_config` keys the model does not accept.
+        # Ref: https://github.com/BerriAI/litellm/issues/22797
         existing_output_config: Final = anthropic_messages_request.get("output_config")
         if isinstance(existing_output_config, dict):
             anthropic_messages_request["output_config"] = dict(existing_output_config)
-        output_format: Final = anthropic_messages_request.pop("output_format", None)
-        output_config_format: Final = pop_bedrock_invoke_output_config_format(anthropic_messages_request)
-        if output_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_format,
-                request_body=anthropic_messages_request,
-            )
-        elif output_config_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_config_format,
-                request_body=anthropic_messages_request,
-            )
+        apply_bedrock_invoke_structured_output(
+            model=model,
+            request_body=anthropic_messages_request,
+        )
         normalize_bedrock_opus_output_config_effort(
             model=model,
             output_config=anthropic_messages_request.get("output_config"),
         )
-
-        # 5a. Bedrock Invoke supports output_config (effort) for Claude 4.6+ models,
-        # but older models do not — strip it to avoid request rejection.
-        # Ref: https://github.com/BerriAI/litellm/issues/22797
-        if not (
-            _supports_factory(
-                model=model,
-                custom_llm_provider="bedrock",
-                key="supports_output_config",
-            )
-            or AnthropicConfig._model_supports_effort_param(model, "bedrock")
-        ):
-            if anthropic_messages_request.pop("output_config", None) is not None:
-                verbose_logger.warning(
-                    "Bedrock Invoke: stripping unsupported `output_config` for "
-                    "model=%s — neither `supports_output_config` nor any "
-                    "`supports_*_reasoning_effort` flag is set in "
-                    "model_prices_and_context_window.json. Add the capability "
-                    "flag to the model JSON entry if this model accepts "
-                    "`output_config`.",
-                    model,
-                )
+        strip_unsupported_bedrock_invoke_output_config_keys(
+            model=model,
+            request_body=anthropic_messages_request,
+        )
 
         # 5b. Hoist `custom.defer_loading` then drop `custom` (Bedrock doesn't support it)
         # Ref: https://github.com/BerriAI/litellm/issues/22847
@@ -774,9 +746,11 @@ class AmazonAnthropicClaudeMessagesConfig(
         if filtered_betas:
             anthropic_messages_request["anthropic_beta"] = filtered_betas
 
+        remaining_output_config: Final = anthropic_messages_request.get("output_config")
         if (
             litellm.drop_params is True
-            and "output_config" in anthropic_messages_request
+            and isinstance(remaining_output_config, dict)
+            and any(key != "format" for key in remaining_output_config)
             and not AnthropicConfig._model_supports_effort_param(model, "bedrock")
         ):
             verbose_logger.warning(
diff --git a/litellm/llms/bedrock/realtime/handler.py b/litellm/llms/bedrock/realtime/handler.py
index 96d7a79c6d8..42fe8941443 100644
--- a/litellm/llms/bedrock/realtime/handler.py
+++ b/litellm/llms/bedrock/realtime/handler.py
@@ -7,13 +7,18 @@ This uses aws_sdk_bedrock_runtime for bidirectional streaming with Nova Sonic.
 import asyncio
 import contextlib
 import json
+from collections.abc import AsyncIterator, Mapping
 from typing import Final, Protocol
 
 from pydantic import JsonValue, TypeAdapter
 
+import litellm
 from litellm._logging import _redact_string, verbose_proxy_logger
 from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
+from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
+from litellm.litellm_core_utils.realtime_streaming import DefaultLoggedRealTimeEventTypes
+from litellm.types.llms.openai import OpenAIRealtimeEvents
 from litellm.types.realtime import RealtimeResponseTransformInput
 
 from ..base_aws_llm import BaseAWSLLM
@@ -32,6 +37,17 @@ def _json_str(value: JsonValue) -> str | None:
     return value if isinstance(value, str) else None
 
 
+def _should_log_event(openai_message: Mapping[str, object]) -> bool:
+    logged_types: Final = (
+        litellm.logged_real_time_event_types
+        if litellm.logged_real_time_event_types is not None
+        else DefaultLoggedRealTimeEventTypes
+    )
+    if logged_types == "*":
+        return True
+    return openai_message.get("type") in logged_types
+
+
 class RealtimeClientWebSocket(Protocol):
     """The client-facing websocket surface the realtime bridge talks to."""
 
@@ -94,7 +110,7 @@ class BedrockRealtime(BaseAWSLLM):
         aws_sts_endpoint: str | None = None,
         aws_bedrock_runtime_endpoint: str | None = None,
         aws_external_id: str | None = None,
-        **kwargs,
+        **kwargs: object,
     ):
         """
         Establish bidirectional streaming connection with Bedrock Nova Sonic.
@@ -166,13 +182,16 @@ class BedrockRealtime(BaseAWSLLM):
         )
         bedrock_client: Final = BedrockRuntimeClient(config=config)
 
+        async def open_bidirectional_stream() -> BedrockBidirectionalStream:
+            return await bedrock_client.invoke_model_with_bidirectional_stream(
+                InvokeModelWithBidirectionalStreamOperationInput(model_id=model)
+            )
+
         transformation_config: Final = BedrockRealtimeConfig()
 
         try:
             # Initialize the bidirectional stream
-            bedrock_stream: Final = await bedrock_client.invoke_model_with_bidirectional_stream(
-                InvokeModelWithBidirectionalStreamOperationInput(model_id=model)
-            )
+            bedrock_stream: Final = await open_bidirectional_stream()
 
             verbose_proxy_logger.debug("Bedrock Realtime: Bidirectional stream established")
 
@@ -202,16 +221,22 @@ class BedrockRealtime(BaseAWSLLM):
                 )
             )
 
-            bedrock_to_client_task: Final = asyncio.create_task(
-                self._forward_bedrock_to_client(
-                    bedrock_stream,
-                    websocket,
-                    transformation_config,
-                    model,
-                    logging_obj,
-                    session_state,
+            async def forward_bedrock_and_collect_logged_events() -> tuple[OpenAIRealtimeEvents, ...]:
+                return tuple(
+                    [
+                        event
+                        async for event in self._forward_bedrock_to_client(
+                            bedrock_stream,
+                            websocket,
+                            transformation_config,
+                            model,
+                            logging_obj,
+                            session_state,
+                        )
+                    ]
                 )
-            )
+
+            bedrock_to_client_task: Final = asyncio.create_task(forward_bedrock_and_collect_logged_events())
 
             # Wait for both tasks to complete
             await asyncio.gather(
@@ -220,6 +245,27 @@ class BedrockRealtime(BaseAWSLLM):
                 return_exceptions=True,
             )
 
+            forwarded_logged_events: Final = (
+                bedrock_to_client_task.result()
+                if not bedrock_to_client_task.cancelled() and bedrock_to_client_task.exception() is None
+                else ()
+            )
+            logged_events: Final = (
+                *forwarded_logged_events,
+                *(
+                    leftover_event
+                    for leftover_event in transformation_config.leftover_usage_done_events()
+                    if _should_log_event(leftover_event)
+                ),
+            )
+            if logged_events:
+                GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(
+                    logging_obj.dispatch_success_handlers(
+                        list(logged_events),  # mutable-ok: realtime spend logging requires a list result
+                        prefer_async_handlers=True,
+                    )
+                )
+
         except Exception as e:
             verbose_proxy_logger.exception("Error in BedrockRealtime.async_realtime: %s", e)
             try:
@@ -243,10 +289,11 @@ class BedrockRealtime(BaseAWSLLM):
             InvokeModelWithBidirectionalStreamInputChunk,
         )
 
+        def build_input_chunk(payload: bytes) -> object:
+            return InvokeModelWithBidirectionalStreamInputChunk(value=BidirectionalInputPayloadPart(bytes_=payload))
+
         async def send_to_bedrock(bedrock_message: str) -> None:
-            event: Final = InvokeModelWithBidirectionalStreamInputChunk(
-                value=BidirectionalInputPayloadPart(bytes_=bedrock_message.encode("utf-8"))
-            )
+            event: Final = build_input_chunk(bedrock_message.encode("utf-8"))
             await bedrock_stream.input_stream.send(event)
             verbose_proxy_logger.debug("Bedrock Realtime: Sent to Bedrock: %s", bedrock_message[:200])
 
@@ -300,8 +347,8 @@ class BedrockRealtime(BaseAWSLLM):
         model: str,
         logging_obj: LiteLLMLogging,
         session_state: RealtimeResponseTransformInput,
-    ):
-        """Forward messages from Bedrock stream to client WebSocket."""
+    ) -> AsyncIterator[OpenAIRealtimeEvents]:
+        """Forward messages from Bedrock to the client, yielding the ones to record for spend logging."""
         try:
             while True:
                 # Receive from Bedrock
@@ -349,11 +396,14 @@ class BedrockRealtime(BaseAWSLLM):
                     )
 
                     # Send transformed messages to client
-                    openai_messages = transformed_response.get("response", [])
+                    response_value = transformed_response["response"]
+                    openai_messages = response_value if isinstance(response_value, list) else (response_value,)
                     for openai_message in openai_messages:
                         message_json = json.dumps(openai_message)
                         await client_ws.send_text(message_json)
                         verbose_proxy_logger.debug("Bedrock Realtime: Sent to client: %s", message_json[:200])
+                        if _should_log_event(openai_message):
+                            yield openai_message
 
         except Exception as e:
             verbose_proxy_logger.debug("Bedrock to client forwarding ended: %s", e, exc_info=True)
diff --git a/litellm/llms/bedrock/realtime/transformation.py b/litellm/llms/bedrock/realtime/transformation.py
index 951bf636b2f..1f4c81d6491 100644
--- a/litellm/llms/bedrock/realtime/transformation.py
+++ b/litellm/llms/bedrock/realtime/transformation.py
@@ -7,7 +7,7 @@ Transforms between OpenAI Realtime API format and Bedrock Nova Sonic format.
 import base64
 import json
 import uuid as uuid_lib
-from typing import Any, Final
+from typing import Final, cast
 
 from pydantic import BaseModel
 
@@ -20,29 +20,54 @@ from litellm.types.llms.openai import (
     OpenAIRealtimeContentPartDone,
     OpenAIRealtimeDoneEvent,
     OpenAIRealtimeEvents,
+    OpenAIRealtimeInputAudioBufferSpeechEvent,
+    OpenAIRealtimeInputAudioTranscriptionCompleted,
+    OpenAIRealtimeInputAudioTranscriptionDelta,
     OpenAIRealtimeOutputItemDone,
     OpenAIRealtimeResponseAudioDone,
     OpenAIRealtimeResponseContentPartAdded,
     OpenAIRealtimeResponseDelta,
     OpenAIRealtimeResponseDoneObject,
     OpenAIRealtimeResponseTextDone,
+    OpenAIRealtimeResponseUsage,
     OpenAIRealtimeStreamResponseBaseObject,
     OpenAIRealtimeStreamResponseOutputItemAdded,
     OpenAIRealtimeStreamSession,
     OpenAIRealtimeStreamSessionEvents,
+    OpenAIRealtimeUsageTokenDetails,
 )
 from litellm.types.realtime import (
     ALL_DELTA_TYPES,
     RealtimeResponseTransformInput,
     RealtimeResponseTypedDict,
 )
-from litellm.utils import get_empty_usage
 
 
 class BedrockContentEnd(BaseModel):
     stopReason: str | None = None
 
 
+class BedrockUsageTokenDetails(BaseModel):
+    speechTokens: int = 0
+    textTokens: int = 0
+
+
+class BedrockUsageDetailsTotal(BaseModel):
+    input: BedrockUsageTokenDetails = BedrockUsageTokenDetails()
+    output: BedrockUsageTokenDetails = BedrockUsageTokenDetails()
+
+
+class BedrockUsageDetails(BaseModel):
+    total: BedrockUsageDetailsTotal = BedrockUsageDetailsTotal()
+
+
+class BedrockUsageEvent(BaseModel):
+    totalInputTokens: int = 0
+    totalOutputTokens: int = 0
+    totalTokens: int = 0
+    details: BedrockUsageDetails = BedrockUsageDetails()
+
+
 TRIGGER_AUDIO_SAMPLE_RATE_HERTZ: Final = 16000
 TRIGGER_AUDIO_BYTES_PER_SECOND: Final = TRIGGER_AUDIO_SAMPLE_RATE_HERTZ * 2
 TRIGGER_LEADING_SILENCE: Final = bytes(TRIGGER_AUDIO_BYTES_PER_SECOND // 2)
@@ -87,6 +112,15 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         # Text configuration
         self.text_media_type = "text/plain"
 
+        # Response-stream state (Bedrock events carry no role on textOutput,
+        # so the USER/ASSISTANT split from contentStart is tracked here)
+        self._user_transcript_active = False
+        self._user_transcript_generation_stage: str | None = None
+        self._user_item_id: str | None = None
+        self._user_transcript_buffer = ""
+        self._cumulative_usage = BedrockUsageEvent()
+        self._reported_usage = BedrockUsageEvent()
+
     def validate_environment(self, headers: dict, model: str, api_key: str | None = None) -> dict:
         """Validate environment - no special validation needed for Bedrock."""
         return headers
@@ -599,7 +633,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
             List of Bedrock format messages (JSON strings)
         """
         try:
-            json_message: Final = json.loads(message)
+            json_message: Final[dict[str, object]] = json.loads(message)
         except json.JSONDecodeError:
             verbose_logger.warning("Invalid JSON message: %s", message[:200])
             return []
@@ -691,6 +725,11 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         role: Final = content_start.get("role")
 
         if role != "ASSISTANT":
+            if role == "USER" and content_start.get("type") == "TEXT":
+                self._user_transcript_active = True
+                self._user_transcript_generation_stage = self._parse_generation_stage(
+                    content_start.get("additionalModelFields")
+                )
             return (
                 [],
                 current_response_id,
@@ -700,6 +739,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
             )
 
         verbose_logger.debug("Handling ASSISTANT contentStart")
+        is_new_response: Final = current_response_id is None
 
         # Initialize IDs if needed
         if not current_response_id:
@@ -715,7 +755,8 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
 
         returned_messages: Final[list[OpenAIRealtimeEvents]] = []
 
-        # Send response.created
+        # Send response.created only once per response (a response can contain
+        # multiple content blocks, e.g. TEXT then AUDIO)
         response_created: Final = OpenAIRealtimeStreamResponseBaseObject(
             type="response.created",
             event_id=f"event_{uuid.uuid4()}",
@@ -727,7 +768,8 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
                 "conversation_id": current_conversation_id,
             },
         )
-        returned_messages.append(response_created)
+        if is_new_response:
+            returned_messages.append(response_created)
 
         # Send response.output_item.added
         output_item_added: Final = OpenAIRealtimeStreamResponseOutputItemAdded(
@@ -767,6 +809,108 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
             current_delta_type,
         )
 
+    @staticmethod
+    def _parse_generation_stage(additional_model_fields: object) -> str | None:
+        if not isinstance(additional_model_fields, str):
+            return None
+        try:
+            parsed: Final = json.loads(additional_model_fields)
+        except json.JSONDecodeError:
+            return None
+        stage: Final = parsed.get("generationStage") if isinstance(parsed, dict) else None
+        return stage if isinstance(stage, str) else None
+
+    def _current_user_item_id(self, new_utterance: bool = False) -> str:
+        """Item id shared by all events of one user utterance (speech boundaries and transcript)."""
+        if new_utterance or self._user_item_id is None:
+            self._user_item_id = f"item_{uuid.uuid4()}"
+        return self._user_item_id
+
+    def transform_user_speech_event(self, is_speech_start: bool) -> tuple[OpenAIRealtimeEvents, ...]:
+        """Transform Bedrock userSpeechStart/userSpeechEnd to OpenAI speech boundary events."""
+        verbose_logger.debug("Handling userSpeech%s", "Start" if is_speech_start else "End")
+        speech_event: Final[OpenAIRealtimeInputAudioBufferSpeechEvent] = {
+            "type": "input_audio_buffer.speech_started" if is_speech_start else "input_audio_buffer.speech_stopped",
+            "event_id": f"event_{uuid.uuid4()}",
+            "item_id": self._current_user_item_id(new_utterance=is_speech_start),
+        }
+        return (speech_event,)
+
+    def transform_usage_event(self, usage_event: BedrockUsageEvent) -> None:
+        """Record Bedrock's session-cumulative usage totals for the next response.done."""
+        verbose_logger.debug("Handling usageEvent")
+        self._cumulative_usage = usage_event
+
+    def _take_usage_delta(self) -> OpenAIRealtimeResponseUsage:
+        """Usage for the response now completing: cumulative totals minus what prior response.done events reported."""
+        prior: Final = self._reported_usage
+        latest: Final = self._cumulative_usage
+        self._reported_usage = latest
+        input_details: Final[OpenAIRealtimeUsageTokenDetails] = {
+            "audio_tokens": latest.details.total.input.speechTokens - prior.details.total.input.speechTokens,
+            "text_tokens": latest.details.total.input.textTokens - prior.details.total.input.textTokens,
+            "cached_tokens": 0,
+        }
+        output_details: Final[OpenAIRealtimeUsageTokenDetails] = {
+            "audio_tokens": latest.details.total.output.speechTokens - prior.details.total.output.speechTokens,
+            "text_tokens": latest.details.total.output.textTokens - prior.details.total.output.textTokens,
+        }
+        usage_delta: Final[OpenAIRealtimeResponseUsage] = {
+            "input_tokens": latest.totalInputTokens - prior.totalInputTokens,
+            "output_tokens": latest.totalOutputTokens - prior.totalOutputTokens,
+            "total_tokens": latest.totalTokens - prior.totalTokens,
+            "input_token_details": input_details,
+            "output_token_details": output_details,
+        }
+        return usage_delta
+
+    def leftover_usage_done_events(self) -> tuple[OpenAIRealtimeEvents, ...]:
+        """Logged-only response.done for usage Bedrock reports after the final turn's contentEnd."""
+        if self._cumulative_usage == self._reported_usage:
+            return ()
+        usage: Final = self._take_usage_delta()
+        leftover_done: Final = OpenAIRealtimeDoneEvent(
+            type="response.done",
+            event_id=f"event_{uuid.uuid4()}",
+            response=OpenAIRealtimeResponseDoneObject(
+                object="realtime.response",
+                id=f"resp_{uuid.uuid4()}",
+                status="completed",
+                conversation_id=f"conv_{uuid.uuid4()}",
+                usage=dict(usage),  # mutable-ok: OpenAIRealtimeResponseDoneObject types usage as plain dict
+            ),
+        )
+        return (leftover_done,)
+
+    def transform_user_transcript_event(self, transcript: str) -> tuple[OpenAIRealtimeEvents, ...]:
+        """Transform a USER-role Bedrock textOutput (ASR transcript) to an OpenAI transcription delta."""
+        verbose_logger.debug("Handling USER textOutput (ASR transcript)")
+        delta_event: Final[OpenAIRealtimeInputAudioTranscriptionDelta] = {
+            "type": "conversation.item.input_audio_transcription.delta",
+            "event_id": f"event_{uuid.uuid4()}",
+            "item_id": self._current_user_item_id(),
+            "content_index": 0,
+            "delta": transcript,
+        }
+        if self._user_transcript_generation_stage != "SPECULATIVE":
+            self._user_transcript_buffer += transcript
+        return (delta_event,)
+
+    def user_transcript_completed_events(self) -> tuple[OpenAIRealtimeEvents, ...]:
+        """One completed event with the full transcript once the FINAL user content block ends."""
+        transcript: Final = self._user_transcript_buffer
+        if not transcript:
+            return ()
+        self._user_transcript_buffer = ""
+        completed_event: Final[OpenAIRealtimeInputAudioTranscriptionCompleted] = {
+            "type": "conversation.item.input_audio_transcription.completed",
+            "event_id": f"event_{uuid.uuid4()}",
+            "item_id": self._current_user_item_id(),
+            "content_index": 0,
+            "transcript": transcript,
+        }
+        return (completed_event,)
+
     def transform_text_output_event(
         self,
         event: dict,
@@ -985,7 +1129,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         if not current_response_id or not current_conversation_id:
             return [], None, None, None
 
-        usage_obj: Final = get_empty_usage()
+        usage: Final = self._take_usage_delta()
         response_done: Final = OpenAIRealtimeDoneEvent(
             type="response.done",
             event_id=f"event_{uuid.uuid4()}",
@@ -995,11 +1139,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
                 status="completed",
                 output=[],
                 conversation_id=current_conversation_id,
-                usage={
-                    "prompt_tokens": usage_obj.prompt_tokens,
-                    "completion_tokens": usage_obj.completion_tokens,
-                    "total_tokens": usage_obj.total_tokens,
-                },
+                usage=dict(usage),
             ),
         )
 
@@ -1042,9 +1182,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
 
         # Create a function call arguments done event
         # This is a custom event format that matches what clients expect
-        from typing import cast
-
-        function_call_event: Final[dict[str, Any]] = {
+        function_call_event: Final[dict[str, object]] = {
             "type": "response.function_call_arguments.done",
             "event_id": f"event_{uuid.uuid4()}",
             "response_id": current_response_id,
@@ -1194,18 +1332,26 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
             returned_messages.extend(events)
 
         elif "textOutput" in event:
-            events, current_delta_chunks = self.transform_text_output_event(
-                event,
-                current_output_item_id,
-                current_response_id,
-                current_delta_chunks,
-            )
-            returned_messages.extend(events)
+            if self._user_transcript_active:
+                returned_messages.extend(self.transform_user_transcript_event(event["textOutput"].get("content", "")))
+            else:
+                events, current_delta_chunks = self.transform_text_output_event(
+                    event,
+                    current_output_item_id,
+                    current_response_id,
+                    current_delta_chunks,
+                )
+                returned_messages.extend(events)
 
         elif "audioOutput" in event:
             events = self.transform_audio_output_event(event, current_output_item_id, current_response_id)
             returned_messages.extend(events)
 
+        elif "contentEnd" in event and self._user_transcript_active:
+            self._user_transcript_active = False
+            self._user_transcript_generation_stage = None
+            returned_messages.extend(self.user_transcript_completed_events())
+
         elif "contentEnd" in event:
             events, current_delta_chunks = self.transform_content_end_event(
                 event,
@@ -1224,6 +1370,12 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
                 ) = self._response_done_events(current_response_id, current_conversation_id)
                 returned_messages.extend(done_events)
 
+        elif "userSpeechStart" in event or "userSpeechEnd" in event:
+            returned_messages.extend(self.transform_user_speech_event("userSpeechStart" in event))
+
+        elif "usageEvent" in event:
+            self.transform_usage_event(BedrockUsageEvent.model_validate(event["usageEvent"]))
+
         elif "toolUse" in event:
             events, tool_call_id, tool_name = self.transform_tool_use_event(
                 event, current_output_item_id, current_response_id
diff --git a/litellm/llms/bedrock/vector_stores/transformation.py b/litellm/llms/bedrock/vector_stores/transformation.py
index 2d72db0cdba..bad17a2181d 100644
--- a/litellm/llms/bedrock/vector_stores/transformation.py
+++ b/litellm/llms/bedrock/vector_stores/transformation.py
@@ -27,6 +27,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -196,6 +197,7 @@ class BedrockVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         if isinstance(query, list):
             query = " ".join(query)
diff --git a/litellm/llms/black_forest_labs/image_edit/handler.py b/litellm/llms/black_forest_labs/image_edit/handler.py
index 1ff02a6f8d9..178acb0de0d 100644
--- a/litellm/llms/black_forest_labs/image_edit/handler.py
+++ b/litellm/llms/black_forest_labs/image_edit/handler.py
@@ -8,9 +8,11 @@ then we poll until the result is ready.
 
 import asyncio
 import time
-from typing import Any, Final
+from collections.abc import Coroutine, Mapping
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,6 +35,42 @@ from ..common_utils import (
 from .transformation import BlackForestLabsImageEditConfig
 
 
+class _BFLSubmitBody(TypedDict, total=False):
+    """Decoded body of the BFL submit response, which hands back a polling URL."""
+
+    errors: ReadOnly[object]
+    polling_url: ReadOnly[str]
+
+
+class _BFLPollBody(TypedDict, total=False):
+    """Decoded body of a BFL polling response."""
+
+    status: ReadOnly[str]
+
+
+class _BFLSubmitResponse(Protocol):
+    """The submit call's HTTP response, read for its status, body text and decoded body."""
+
+    @property
+    def status_code(self) -> int: ...
+
+    @property
+    def text(self) -> str: ...
+
+    def json(self) -> _BFLSubmitBody: ...
+
+
+class _BFLPollResponse(Protocol):
+    """A polling call's HTTP response, read only for the task status it carries."""
+
+    def json(self) -> _BFLPollBody: ...
+
+
+def _poll_status(response: _BFLPollResponse) -> str | None:
+    """Read the task status out of a BFL polling response body."""
+    return response.json().get("status")
+
+
 class BlackForestLabsImageEdit:
     """
     Black Forest Labs Image Edit handler.
@@ -53,10 +91,10 @@ class BlackForestLabsImageEdit:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, object] | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         aimage_edit: bool = False,
-    ) -> ImageResponse | Any:
+    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
         """
         Main entry point for image edit requests.
 
@@ -185,7 +223,7 @@ class BlackForestLabsImageEdit:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, object] | None = None,
         client: AsyncHTTPHandler | None = None,
     ) -> ImageResponse:
         """
@@ -281,7 +319,7 @@ class BlackForestLabsImageEdit:
 
     def _poll_for_result_sync(
         self,
-        initial_response: httpx.Response,
+        initial_response: _BFLSubmitResponse,
         headers: dict,
         sync_client: HTTPHandler,
         max_wait: float = DEFAULT_MAX_POLLING_TIME,
@@ -356,8 +394,7 @@ class BlackForestLabsImageEdit:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
-            status = data.get("status")
+            status = _poll_status(response)
 
             verbose_logger.debug("BFL poll status: %s", status)
 
@@ -383,7 +420,7 @@ class BlackForestLabsImageEdit:
 
     async def _poll_for_result_async(
         self,
-        initial_response: httpx.Response,
+        initial_response: _BFLSubmitResponse,
         headers: dict,
         async_client: AsyncHTTPHandler,
         max_wait: float = DEFAULT_MAX_POLLING_TIME,
@@ -447,8 +484,7 @@ class BlackForestLabsImageEdit:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
-            status = data.get("status")
+            status = _poll_status(response)
 
             verbose_logger.debug("BFL poll status: %s", status)
 
diff --git a/litellm/llms/black_forest_labs/image_generation/handler.py b/litellm/llms/black_forest_labs/image_generation/handler.py
index 03e4999c5aa..879bef37b58 100644
--- a/litellm/llms/black_forest_labs/image_generation/handler.py
+++ b/litellm/llms/black_forest_labs/image_generation/handler.py
@@ -8,9 +8,11 @@ then we poll until the result is ready.
 
 import asyncio
 import time
-from typing import Any, Final
+from collections.abc import Coroutine, Mapping
+from typing import Final, Protocol, TypedDict
 
 import httpx
+from typing_extensions import ReadOnly
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,6 +35,23 @@ from ..common_utils import (
 from .transformation import BlackForestLabsImageGenerationConfig
 
 
+class _BFLTaskPayload(TypedDict, total=False):
+    """The body BFL returns for a submitted or polled generation task."""
+
+    errors: ReadOnly[object]
+    polling_url: ReadOnly[str]
+    status: ReadOnly[str]
+
+
+class _TaskJsonResponse(Protocol):
+    def json(self) -> _BFLTaskPayload: ...
+
+
+def _task_payload(response: _TaskJsonResponse) -> _BFLTaskPayload:
+    """The JSON body of a BFL task submission or poll response."""
+    return response.json()
+
+
 class BlackForestLabsImageGeneration:
     """
     Black Forest Labs Image Generation handler.
@@ -53,10 +72,10 @@ class BlackForestLabsImageGeneration:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, str] | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         aimg_generation: bool = False,
-    ) -> ImageResponse | Any:
+    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
         """
         Main entry point for image generation requests.
 
@@ -187,7 +206,7 @@ class BlackForestLabsImageGeneration:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, str] | None = None,
         client: AsyncHTTPHandler | None = None,
     ) -> ImageResponse:
         """
@@ -305,7 +324,7 @@ class BlackForestLabsImageGeneration:
 
         # Parse initial response to get polling URL
         try:
-            response_data: Final = initial_response.json()
+            response_data: Final = _task_payload(initial_response)
         except Exception as e:
             raise BlackForestLabsError(
                 status_code=initial_response.status_code,
@@ -350,7 +369,7 @@ class BlackForestLabsImageGeneration:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
+            data = _task_payload(response)
             status = data.get("status")
 
             verbose_logger.debug("BFL poll status: %s", status)
@@ -396,7 +415,7 @@ class BlackForestLabsImageGeneration:
 
         # Parse initial response to get polling URL
         try:
-            response_data: Final = initial_response.json()
+            response_data: Final = _task_payload(initial_response)
         except Exception as e:
             raise BlackForestLabsError(
                 status_code=initial_response.status_code,
@@ -441,7 +460,7 @@ class BlackForestLabsImageGeneration:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
+            data = _task_payload(response)
             status = data.get("status")
 
             verbose_logger.debug("BFL poll status: %s", status)
diff --git a/litellm/llms/chatgpt/chat/streaming_utils.py b/litellm/llms/chatgpt/chat/streaming_utils.py
index d4a168a6984..ee3120bacea 100644
--- a/litellm/llms/chatgpt/chat/streaming_utils.py
+++ b/litellm/llms/chatgpt/chat/streaming_utils.py
@@ -49,10 +49,10 @@ class ChatGPTToolCallNormalizer:
     def __getattr__(self, name: str) -> object:
         return getattr(self._stream, name)
 
-    def __iter__(self):
+    def __iter__(self) -> "ChatGPTToolCallNormalizer":
         return self
 
-    def __aiter__(self):
+    def __aiter__(self) -> "ChatGPTToolCallNormalizer":
         return self
 
     def __next__(self) -> ModelResponseStream:
diff --git a/litellm/llms/codestral/completion/handler.py b/litellm/llms/codestral/completion/handler.py
index 8c08b2bc33c..f8486d3b274 100644
--- a/litellm/llms/codestral/completion/handler.py
+++ b/litellm/llms/codestral/completion/handler.py
@@ -4,9 +4,10 @@
 import json
 from collections.abc import Callable
 from functools import partial
-from typing import Final
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
@@ -23,6 +24,53 @@ from litellm.types.utils import TextChoices
 from litellm.utils import CustomStreamWrapper, TextCompletionResponse
 
 
+class _CodestralChoiceMessage(TypedDict):
+    """`choices[].message` of a Codestral FIM completion."""
+
+    role: ReadOnly[NotRequired[str]]
+    content: ReadOnly[NotRequired[str | None]]
+
+
+class _CodestralChoice(TypedDict):
+    """One entry of `choices` in a Codestral FIM completion."""
+
+    index: ReadOnly[int]
+    message: ReadOnly[NotRequired[_CodestralChoiceMessage]]
+    finish_reason: ReadOnly[NotRequired[str | None]]
+    logprobs: ReadOnly[NotRequired[dict[str, object] | None]]
+
+
+class _CodestralUsage(TypedDict):
+    """Token accounting returned alongside a Codestral FIM completion."""
+
+    prompt_tokens: ReadOnly[NotRequired[int]]
+    completion_tokens: ReadOnly[NotRequired[int]]
+    total_tokens: ReadOnly[NotRequired[int]]
+
+
+class _CodestralCompletionResponse(TypedDict):
+    """Body returned by the Codestral `/v1/fim/completions` endpoint."""
+
+    id: ReadOnly[NotRequired[str]]
+    created: ReadOnly[NotRequired[int]]
+    model: ReadOnly[NotRequired[str]]
+    object: ReadOnly[NotRequired[str]]
+    usage: ReadOnly[NotRequired[_CodestralUsage]]
+    choices: ReadOnly[NotRequired[list[_CodestralChoice]]]
+
+
+class _CodestralHTTPResponse(Protocol):
+    """The Codestral completion response as this handler reads it."""
+
+    @property
+    def status_code(self) -> int: ...
+
+    @property
+    def text(self) -> str: ...
+
+    def json(self) -> _CodestralCompletionResponse: ...
+
+
 class TextCompletionCodestralError(Exception):
     def __init__(
         self,
@@ -115,7 +163,7 @@ class CodestralTextCompletion:
     def process_text_completion_response(
         self,
         model: str,
-        response: httpx.Response,
+        response: _CodestralHTTPResponse,
         model_response: TextCompletionResponse,
         stream: bool,
         logging_obj: LiteLLMLogging,
diff --git a/litellm/llms/compactifai/chat/transformation.py b/litellm/llms/compactifai/chat/transformation.py
index 63a5427d211..3c5a889ce63 100644
--- a/litellm/llms/compactifai/chat/transformation.py
+++ b/litellm/llms/compactifai/chat/transformation.py
@@ -2,13 +2,16 @@
 CompactifAI chat completion transformation
 """
 
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.openai.common_utils import OpenAIError
 from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse
 
 from ...openai.chat.gpt_transformation import OpenAIGPTConfig
@@ -23,6 +26,18 @@ else:
     LiteLLMLoggingObj = Any
 
 
+class CompactifAIResponseFields(TypedDict, total=False):
+    """The chat completion fields of a CompactifAI response body."""
+
+    id: ReadOnly[str]
+    choices: ReadOnly[Sequence[Mapping[str, object]]]
+    created: ReadOnly[int]
+    model: ReadOnly[str]
+    system_fingerprint: ReadOnly[str | None]
+    usage: ReadOnly[Mapping[str, object]]
+    object: ReadOnly[str]
+
+
 class CompactifAIChatConfig(OpenAIGPTConfig):
     """
     Configuration class for CompactifAI chat completions.
@@ -47,10 +62,10 @@ class CompactifAIChatConfig(OpenAIGPTConfig):
         raw_response: httpx.Response,
         model_response: ModelResponse,
         logging_obj: LiteLLMLoggingObj,
-        request_data: dict,
-        messages: list,
-        optional_params: dict,
-        litellm_params: dict,
+        request_data: Mapping[str, object],
+        messages: Sequence[AllMessageValues],
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
         encoding: "tiktoken.Encoding | None",
         api_key: str | None = None,
         json_mode: bool | None = None,
@@ -81,14 +96,18 @@ class CompactifAIChatConfig(OpenAIGPTConfig):
                         message["content"] = tool_calls[0]["function"].get("arguments", "")
                         message["tool_calls"] = None
 
-        returned_response: Final = ModelResponse(**response_json)
+        response_fields: Final[CompactifAIResponseFields] = response_json
+
+        returned_response: Final = ModelResponse(**response_fields)
 
         # Set model name with provider prefix
         returned_response.model = f"compactifai/{model}"
 
         return returned_response
 
-    def get_error_class(self, error_message: str, status_code: int, headers: dict | httpx.Headers) -> BaseLLMException:
+    def get_error_class(
+        self, error_message: str, status_code: int, headers: dict[str, str] | httpx.Headers
+    ) -> BaseLLMException:
         """
         Get the appropriate error class for CompactifAI errors.
         Since CompactifAI is OpenAI-compatible, we use OpenAI error handling.
diff --git a/litellm/llms/custom_httpx/aiohttp_transport.py b/litellm/llms/custom_httpx/aiohttp_transport.py
index b6586481fd3..73adf9c7455 100644
--- a/litellm/llms/custom_httpx/aiohttp_transport.py
+++ b/litellm/llms/custom_httpx/aiohttp_transport.py
@@ -3,6 +3,7 @@ import concurrent.futures
 import contextlib
 import os
 import ssl
+import sys
 import typing
 import urllib.request
 from collections.abc import Callable, Generator
@@ -75,10 +76,22 @@ except ImportError:
     pass
 
 
+def _current_task_is_cancelling() -> bool:
+    task: Final = asyncio.current_task()
+    if task is None or sys.version_info < (3, 11):
+        return True
+    return task.cancelling() > 0
+
+
 @contextlib.contextmanager
 def map_aiohttp_exceptions() -> Generator[None, None, None]:
     try:
         yield
+    except asyncio.CancelledError as exc:
+        # a closing connector cancels its shielded DNS task; that surfaces here without the request task being cancelled
+        if _current_task_is_cancelling():
+            raise
+        raise httpx.ConnectError("aiohttp transport cancelled the request internally") from exc
     except Exception as exc:
         mapped_exc: type[Exception] | None = None
 
diff --git a/litellm/llms/custom_httpx/container_handler.py b/litellm/llms/custom_httpx/container_handler.py
index 91d68aa3bfb..dd20a8c2ed4 100644
--- a/litellm/llms/custom_httpx/container_handler.py
+++ b/litellm/llms/custom_httpx/container_handler.py
@@ -6,11 +6,12 @@ endpoint defined in endpoints.json, eliminating the need for individual handler
 """
 
 import json
-from collections.abc import Coroutine
+from collections.abc import Coroutine, Mapping, Sequence
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm.litellm_core_utils.url_utils import encode_url_path_segment
@@ -32,26 +33,58 @@ if TYPE_CHECKING:
     from litellm.llms.base_llm.containers.transformation import BaseContainerConfig
 
 
+class EndpointConfig(TypedDict):
+    """One endpoint entry of ``litellm/containers/endpoints.json``."""
+
+    name: ReadOnly[str]
+    async_name: ReadOnly[str]
+    path: ReadOnly[str]
+    method: ReadOnly[str]
+    path_params: ReadOnly[Sequence[str]]
+    query_params: ReadOnly[Sequence[str]]
+    response_type: ReadOnly[str]
+    is_multipart: NotRequired[ReadOnly[bool]]
+    returns_binary: NotRequired[ReadOnly[bool]]
+
+
+class EndpointsConfig(TypedDict):
+    """The parsed ``litellm/containers/endpoints.json`` document."""
+
+    endpoints: ReadOnly[Sequence[EndpointConfig]]
+
+
+class ContainerErrorDetail(TypedDict, total=False):
+    """The ``error`` object of a container API error body."""
+
+    message: ReadOnly[str]
+
+
+class ContainerResponseBody(TypedDict, total=False):
+    """The fields this handler reads off a container API JSON body."""
+
+    error: ReadOnly[ContainerErrorDetail]
+
+
+_ContainerResponseModel = ContainerFileListResponse | ContainerFileObject | DeleteContainerFileResponse
+
 # Response type mapping
-RESPONSE_TYPES: Final[dict[str, type]] = {
+RESPONSE_TYPES: Final[Mapping[str, type[_ContainerResponseModel]]] = {
     "ContainerFileListResponse": ContainerFileListResponse,
     "ContainerFileObject": ContainerFileObject,
     "DeleteContainerFileResponse": DeleteContainerFileResponse,
 }
 
-ContainerEndpointResponse = (
-    ContainerFileListResponse | ContainerFileObject | DeleteContainerFileResponse | bytes | dict[str, object]
-)
+ContainerEndpointResponse = _ContainerResponseModel | bytes | ContainerResponseBody
 
 
-def _load_endpoints_config() -> dict:
+def _load_endpoints_config() -> EndpointsConfig:
     """Load the endpoints configuration from JSON file."""
     config_path: Final = Path(__file__).parent.parent.parent / "containers" / "endpoints.json"
     with open(config_path) as f:
         return json.load(f)
 
 
-def _get_endpoint_config(endpoint_name: str) -> dict | None:
+def _get_endpoint_config(endpoint_name: str) -> EndpointConfig | None:
     """Get config for a specific endpoint by name."""
     config: Final = _load_endpoints_config()
     for endpoint in config["endpoints"]:
@@ -60,10 +93,15 @@ def _get_endpoint_config(endpoint_name: str) -> dict | None:
     return None
 
 
+def _response_model(response_type_name: str) -> type[_ContainerResponseModel] | None:
+    """The pydantic model a container endpoint's ``response_type`` names."""
+    return RESPONSE_TYPES.get(response_type_name)
+
+
 def _build_url(
     api_base: str,
     path_template: str,
-    path_params: dict[str, str],
+    path_params: Mapping[str, object],
 ) -> str:
     """Build the full URL by substituting path parameters.
 
@@ -93,16 +131,12 @@ def _build_url(
 
 
 def _build_query_params(
-    query_param_names: list,
-    kwargs: dict[str, Any],
-) -> dict[str, str]:
+    query_param_names: Sequence[str],
+    kwargs: Mapping[str, object],
+) -> dict[str, object]:
     """Build query parameters from kwargs."""
-    params: Final = {}
-    for param_name in query_param_names:
-        value = kwargs.get(param_name)
-        if value is not None:
-            params[param_name] = str(value) if not isinstance(value, str) else value
-    return params
+    supplied: Final = ((param_name, kwargs.get(param_name)) for param_name in query_param_names)
+    return {name: value if isinstance(value, str) else str(value) for name, value in supplied if value is not None}
 
 
 def _error_message_from_response(response: httpx.Response) -> str:
@@ -136,24 +170,24 @@ def _transform_response(
     if returns_binary:
         return response.content
 
-    response_json: Final = response.json()
+    response_json: Final[ContainerResponseBody] = response.json()
     if "error" in response_json:
         raise BaseLLMException(
             status_code=response.status_code,
-            message=response_json.get("error", {}).get("message", str(response_json)),
+            message=response_json["error"].get("message", str(response_json)),
             headers=dict(response.headers),
         )
 
-    response_type: Final = RESPONSE_TYPES.get(response_type_name)
+    response_type: Final = _response_model(response_type_name)
     if response_type:
-        return response_type(**response_json)
+        return response_type.model_validate(response_json)
     return response_json
 
 
 def _prepare_multipart_file_upload(
     file: Any,
-    headers: dict[str, Any],
-) -> tuple:
+    headers: dict[str, object],
+) -> tuple[dict[str, tuple[str, bytes, str]], dict[str, object]]:
     """
     Prepare file and headers for multipart upload.
 
@@ -178,6 +212,52 @@ def _prepare_multipart_file_upload(
     return files, headers_copy
 
 
+def _request_headers(
+    container_provider_config: "BaseContainerConfig",
+    extra_headers: dict[str, object] | None,
+    litellm_params: GenericLiteLLMParams,
+) -> dict[str, object]:
+    """The provider auth headers for a container request."""
+    return container_provider_config.validate_environment(
+        headers=extra_headers or {},
+        api_key=litellm_params.get("api_key", None),
+    )
+
+
+def _request_api_base(
+    container_provider_config: "BaseContainerConfig",
+    litellm_params: GenericLiteLLMParams,
+) -> str:
+    """The provider base URL for a container request."""
+    return container_provider_config.get_complete_url(
+        api_base=litellm_params.get("api_base", None),
+        litellm_params=dict(litellm_params),
+    )
+
+
+def _sync_http_client(
+    client: HTTPHandler | AsyncHTTPHandler | None,
+    litellm_params: GenericLiteLLMParams,
+) -> HTTPHandler:
+    """The sync HTTP client for a container request, reusing the caller's when usable."""
+    if client is None or not isinstance(client, HTTPHandler):
+        return _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
+    return client
+
+
+def _async_http_client(
+    client: HTTPHandler | AsyncHTTPHandler | None,
+    litellm_params: GenericLiteLLMParams,
+) -> AsyncHTTPHandler:
+    """The async HTTP client for a container request, reusing the caller's when usable."""
+    if client is None or not isinstance(client, AsyncHTTPHandler):
+        return get_async_httpx_client(
+            llm_provider=litellm.LlmProviders.OPENAI,
+            params={"ssl_verify": litellm_params.get("ssl_verify", None)},
+        )
+    return client
+
+
 class GenericContainerHandler:
     """
     Generic handler for container file API endpoints.
@@ -192,13 +272,13 @@ class GenericContainerHandler:
         container_provider_config: "BaseContainerConfig",
         litellm_params: GenericLiteLLMParams,
         logging_obj: "LiteLLMLoggingObj",
-        extra_headers: dict[str, Any] | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_headers: dict[str, object] | None = None,
+        extra_query: dict[str, object] | None = None,
         timeout: float | httpx.Timeout = 600,
         _is_async: bool = False,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
-        **kwargs,
-    ) -> Any | Coroutine[Any, Any, Any]:
+        **kwargs: object,
+    ) -> Any | Coroutine[object, object, Any]:
         """
         Generic handler for any container file endpoint.
 
@@ -245,11 +325,11 @@ class GenericContainerHandler:
         container_provider_config: "BaseContainerConfig",
         litellm_params: GenericLiteLLMParams,
         logging_obj: "LiteLLMLoggingObj",
-        extra_headers: dict[str, Any] | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_headers: dict[str, object] | None = None,
+        extra_query: dict[str, object] | None = None,
         timeout: float | httpx.Timeout = 600,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
-        **kwargs,
+        **kwargs: object,
     ) -> Any:
         """Synchronous request handler."""
         endpoint_config: Final = _get_endpoint_config(endpoint_name)
@@ -257,23 +337,14 @@ class GenericContainerHandler:
             raise ValueError(f"Unknown endpoint: {endpoint_name}")
 
         # Get HTTP client
-        if client is None or not isinstance(client, HTTPHandler):
-            http_client = _get_httpx_client(params={"ssl_verify": litellm_params.get("ssl_verify", None)})
-        else:
-            http_client = client
+        http_client: Final = _sync_http_client(client, litellm_params)
 
         # Build request
-        headers = container_provider_config.validate_environment(
-            headers=extra_headers or {},
-            api_key=litellm_params.get("api_key", None),
-        )
+        headers = _request_headers(container_provider_config, extra_headers, litellm_params)
         if extra_headers:
             headers.update(extra_headers)
 
-        api_base: Final = container_provider_config.get_complete_url(
-            api_base=litellm_params.get("api_base", None),
-            litellm_params=dict(litellm_params),
-        )
+        api_base: Final = _request_api_base(container_provider_config, litellm_params)
 
         # Build URL with path params
         path_params: Final = {p: kwargs.get(p, "") for p in endpoint_config.get("path_params", [])}
@@ -334,11 +405,11 @@ class GenericContainerHandler:
         container_provider_config: "BaseContainerConfig",
         litellm_params: GenericLiteLLMParams,
         logging_obj: "LiteLLMLoggingObj",
-        extra_headers: dict[str, Any] | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_headers: dict[str, object] | None = None,
+        extra_query: dict[str, object] | None = None,
         timeout: float | httpx.Timeout = 600,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
-        **kwargs,
+        **kwargs: object,
     ) -> Any:
         """Asynchronous request handler."""
         endpoint_config: Final = _get_endpoint_config(endpoint_name)
@@ -346,26 +417,14 @@ class GenericContainerHandler:
             raise ValueError(f"Unknown endpoint: {endpoint_name}")
 
         # Get HTTP client
-        if client is None or not isinstance(client, AsyncHTTPHandler):
-            http_client = get_async_httpx_client(
-                llm_provider=litellm.LlmProviders.OPENAI,
-                params={"ssl_verify": litellm_params.get("ssl_verify", None)},
-            )
-        else:
-            http_client = client
+        http_client: Final = _async_http_client(client, litellm_params)
 
         # Build request
-        headers = container_provider_config.validate_environment(
-            headers=extra_headers or {},
-            api_key=litellm_params.get("api_key", None),
-        )
+        headers = _request_headers(container_provider_config, extra_headers, litellm_params)
         if extra_headers:
             headers.update(extra_headers)
 
-        api_base: Final = container_provider_config.get_complete_url(
-            api_base=litellm_params.get("api_base", None),
-            litellm_params=dict(litellm_params),
-        )
+        api_base: Final = _request_api_base(container_provider_config, litellm_params)
 
         # Build URL with path params
         path_params: Final = {p: kwargs.get(p, "") for p in endpoint_config.get("path_params", [])}
diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py
index 777ab576de2..b6e93f590ca 100644
--- a/litellm/llms/custom_httpx/http_handler.py
+++ b/litellm/llms/custom_httpx/http_handler.py
@@ -9,7 +9,7 @@ import threading
 import time
 from collections.abc import AsyncIterable, Callable, Iterable, Mapping
 from http.cookiejar import CookieJar, DefaultCookiePolicy
-from typing import TYPE_CHECKING, Any, ClassVar, Final, Optional, TypeAlias, TypedDict
+from typing import TYPE_CHECKING, Any, ClassVar, Final, NoReturn, Optional, TypeAlias, TypedDict
 
 import certifi
 import httpx
@@ -447,7 +447,7 @@ def _safe_read_response(response: httpx.Response, timeout: float | None = None)
         return b""
 
 
-def _raise_masked_sync_error(e: httpx.HTTPStatusError, stream: bool) -> None:
+def _raise_masked_sync_error(e: httpx.HTTPStatusError, stream: bool) -> NoReturn:
     """Raise a MaskedHTTPStatusError for sync HTTP handlers."""
     if stream:
         try:
@@ -467,7 +467,7 @@ def _raise_masked_sync_error(e: httpx.HTTPStatusError, stream: bool) -> None:
     raise MaskedHTTPStatusError(e, message=_text, text=_text) from None
 
 
-async def _raise_masked_async_error(e: httpx.HTTPStatusError, stream: bool) -> None:
+async def _raise_masked_async_error(e: httpx.HTTPStatusError, stream: bool) -> NoReturn:
     """Raise a MaskedHTTPStatusError for async HTTP handlers."""
     if stream:
         try:
diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py
index 834f7d564a2..26c085a95e6 100644
--- a/litellm/llms/custom_httpx/llm_http_handler.py
+++ b/litellm/llms/custom_httpx/llm_http_handler.py
@@ -1,6 +1,5 @@
 import asyncio
 import json
-import os
 import ssl
 from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence
 from contextlib import asynccontextmanager
@@ -29,6 +28,7 @@ from litellm.litellm_core_utils.audio_utils.subtitle_utils import (
     SUBTITLE_RESPONSE_FORMATS,
     synthesize_subtitle_document,
 )
+from litellm.litellm_core_utils.get_litellm_params import AWS_CREDENTIAL_KWARGS_KEYS
 from litellm.litellm_core_utils.llm_request_utils import serialize_multipart_form_fields
 from litellm.litellm_core_utils.realtime_errors import realtime_error_event, websocket_close_reason
 from litellm.litellm_core_utils.realtime_streaming import RealTimeStreaming
@@ -159,7 +159,11 @@ def _rust_responses_websocket_enabled(
     custom_llm_provider: str | None,
     litellm_params: GenericLiteLLMParams,
 ) -> bool:
-    return custom_llm_provider == "openai" and litellm_params.get("rust") is True
+    from litellm.rust_bridge.configuration import rust_enabled
+
+    raw_request_override: Final = litellm_params.get("rust")
+    request_override: Final = raw_request_override if isinstance(raw_request_override, bool) else None
+    return custom_llm_provider == "openai" and rust_enabled(request_override=request_override)
 
 
 from .http_handler import get_shared_realtime_ssl_context
@@ -178,6 +182,7 @@ if TYPE_CHECKING:
         AnthropicMessagesStreamingResponse,
     )
     from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
+    from litellm.router import Router
     from litellm.types.llms.openai_evals import (
         CancelEvalResponse,
         CancelRunResponse,
@@ -270,6 +275,16 @@ def _has_pre_call_deployment_hook(logging_obj: LiteLLMLoggingObj) -> bool:
     return False
 
 
+def _aws_signing_overrides(optional_params: Mapping[str, Any], litellm_params: Mapping[str, Any]) -> Mapping[str, Any]:
+    return MappingProxyType(
+        {
+            key: litellm_params[key]
+            for key in AWS_CREDENTIAL_KWARGS_KEYS
+            if optional_params.get(key) is None and litellm_params.get(key) is not None
+        }
+    )
+
+
 def _collect_ws_project_quota_callbacks() -> tuple[ProjectQuotaCallback, ...]:
     """Duck-type discover proxy hooks exposing per-frame project ITPM/OTPM
     enforcement, so the Responses WebSocket loop can charge every
@@ -534,7 +549,10 @@ class BaseLLMHTTPHandler:
 
         headers, signed_json_body = provider_config.sign_request(
             headers=headers,
-            optional_params=optional_params,
+            optional_params={
+                **optional_params,
+                **_aws_signing_overrides(optional_params, litellm_params),
+            },
             request_data=data,
             api_base=api_base,
             api_key=api_key,
@@ -2363,10 +2381,6 @@ class BaseLLMHTTPHandler:
             "anthropic_messages",
         )
 
-    @staticmethod
-    def _rust_env_enabled() -> bool:
-        return os.getenv("LITELLM_RUST", "").strip().lower() in {"1", "true", "yes", "on"}
-
     @staticmethod
     async def _maybe_rust_anthropic_messages(
         *,
@@ -2382,7 +2396,11 @@ class BaseLLMHTTPHandler:
     ) -> AnthropicMessagesResponse | None:
         if custom_llm_provider not in ("azure_ai", "anthropic"):
             return None
-        if litellm_params.get("rust") is not True and not BaseLLMHTTPHandler._rust_env_enabled():
+        from litellm.rust_bridge.configuration import rust_enabled
+
+        raw_request_override: Final = litellm_params.get("rust")
+        request_override: Final = raw_request_override if isinstance(raw_request_override, bool) else None
+        if not rust_enabled(request_override=request_override):
             return None
         if has_agentic_hook:
             return None
@@ -2923,7 +2941,7 @@ class BaseLLMHTTPHandler:
         final_response: Final = await self._call_agentic_completion_hooks(
             response=initial_response,
             model=model,
-            messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),
+            messages=(input if isinstance(input, list) else [{"role": "user", "content": input}]),  # pyright: ignore[reportArgumentType]  # pre-existing mismatch surfaced by the Router import; the hook accepts response input items at runtime
             anthropic_messages_provider_config=responses_api_provider_config,
             anthropic_messages_optional_request_params=response_api_optional_request_params,
             logging_obj=logging_obj,
@@ -5415,7 +5433,7 @@ class BaseLLMHTTPHandler:
         try:
             response: ResponsesAPIResponse | BaseResponsesAPIStreamingIterator = await litellm.aresponses(
                 model=patch.model or model,
-                input=patch.messages,
+                input=patch.messages,  # pyright: ignore[reportArgumentType]  # pre-existing mismatch surfaced by the Router import; patch messages are valid response input at runtime
                 **optional_params,
                 **kwargs_for_followup,
             )
@@ -9688,6 +9706,7 @@ class BaseLLMHTTPHandler:
         timeout: float | httpx.Timeout | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         _is_async: bool = False,
+        router: "Router | None" = None,
     ) -> VectorStoreSearchResponse:
         if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
             self._pre_call_direct_vector_store_search(
@@ -9738,6 +9757,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
             )
         else:
             (
@@ -9751,6 +9771,7 @@ class BaseLLMHTTPHandler:
                 litellm_logging_obj=logging_obj,
                 litellm_params=dict(litellm_params),
                 extra_body=extra_body,
+                router=router,
             )
         all_optional_params: Final[dict[str, object]] = dict(litellm_params)
         all_optional_params.update(vector_store_search_optional_params or {})
@@ -9802,6 +9823,7 @@ class BaseLLMHTTPHandler:
         timeout: float | httpx.Timeout | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         _is_async: bool = False,
+        router: "Router | None" = None,
     ) -> VectorStoreSearchResponse | Coroutine[object, object, VectorStoreSearchResponse]:
         if _is_async:
             return self.async_vector_store_search_handler(
@@ -9816,6 +9838,7 @@ class BaseLLMHTTPHandler:
                 extra_body=extra_body,
                 timeout=timeout,
                 client=client,
+                router=router,
             )
 
         if isinstance(vector_store_provider_config, BaseDirectVectorStoreConfig):
@@ -9862,6 +9885,7 @@ class BaseLLMHTTPHandler:
             litellm_logging_obj=logging_obj,
             litellm_params=dict(litellm_params),
             extra_body=extra_body,
+            router=router,
         )
 
         all_optional_params: Final[dict[str, object]] = dict(litellm_params)
diff --git a/litellm/llms/dashscope/chat/transformation.py b/litellm/llms/dashscope/chat/transformation.py
index 5ab7fbf3658..26e60fa959d 100644
--- a/litellm/llms/dashscope/chat/transformation.py
+++ b/litellm/llms/dashscope/chat/transformation.py
@@ -54,6 +54,9 @@ class DashScopeChatConfig(OpenAIGPTConfig):
         dynamic_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
         return api_base, dynamic_api_key
 
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or "https://dashscope.aliyuncs.com/compatible-mode/v1"
+
     def get_complete_url(
         self,
         api_base: str | None,
@@ -66,10 +69,7 @@ class DashScopeChatConfig(OpenAIGPTConfig):
         """
         If api_base is not provided, use the default DashScope /chat/completions endpoint.
         """
-        if not api_base:
-            api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
-
-        if not api_base.endswith("/chat/completions"):
-            api_base = f"{api_base}/chat/completions"
-
-        return api_base
+        resolved_api_base: Final = self._resolve_chat_api_base(api_base)
+        if resolved_api_base.endswith("/chat/completions"):
+            return resolved_api_base
+        return f"{resolved_api_base}/chat/completions"
diff --git a/litellm/llms/dashscope/common_utils.py b/litellm/llms/dashscope/common_utils.py
index 9a7dd4da8d3..b7c97893a15 100644
--- a/litellm/llms/dashscope/common_utils.py
+++ b/litellm/llms/dashscope/common_utils.py
@@ -2,9 +2,89 @@
 Common utilities for the DashScope LLM provider.
 """
 
+from typing import TYPE_CHECKING
+
 import httpx
 
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.secret_managers.main import get_secret_str
+
+if TYPE_CHECKING:
+    from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+    from litellm.llms.base_llm.image_generation.transformation import (
+        BaseImageGenerationConfig,
+    )
+    from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
+
+
+def get_dashscope_family_embedding_config(custom_llm_provider: str) -> "BaseEmbeddingConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudEmbeddingConfig
+
+        return QwenCloudEmbeddingConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import (
+            QwenAIPlatformEmbeddingConfig,
+        )
+
+        return QwenAIPlatformEmbeddingConfig()
+    from litellm.llms.dashscope.embed.transformation import DashScopeEmbeddingConfig
+
+    return DashScopeEmbeddingConfig()
+
+
+def get_dashscope_family_rerank_config(custom_llm_provider: str) -> "BaseRerankConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudRerankConfig
+
+        return QwenCloudRerankConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import QwenAIPlatformRerankConfig
+
+        return QwenAIPlatformRerankConfig()
+    from litellm.llms.dashscope.rerank.transformation import DashScopeRerankConfig
+
+    return DashScopeRerankConfig()
+
+
+def get_dashscope_family_image_generation_config(
+    custom_llm_provider: str,
+) -> "BaseImageGenerationConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudImageGenerationConfig
+
+        return QwenCloudImageGenerationConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import (
+            QwenAIPlatformImageGenerationConfig,
+        )
+
+        return QwenAIPlatformImageGenerationConfig()
+    from litellm.llms.dashscope.image_generation.transformation import (
+        DashScopeImageGenerationConfig,
+    )
+
+    return DashScopeImageGenerationConfig()
+
+
+def resolve_dashscope_family_api_key(custom_llm_provider: str, api_key: str | None) -> str | None:
+    if custom_llm_provider == "dashscope":
+        return api_key or get_secret_str("DASHSCOPE_API_KEY")
+    return api_key or get_secret_str(f"{custom_llm_provider.upper()}_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def missing_dashscope_family_key_message(custom_llm_provider: str) -> str:
+    if custom_llm_provider == "qwencloud":
+        return (
+            "Missing API key for QwenCloud. Set QWENCLOUD_API_KEY or "
+            "DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        )
+    if custom_llm_provider == "qwen_ai_platform":
+        return (
+            "Missing API key for Qwen AI Platform. Set QWEN_AI_PLATFORM_API_KEY or "
+            "DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        )
+    return "Missing API key for DashScope. Set DASHSCOPE_API_KEY environment variable or pass api_key parameter."
 
 
 class DashScopeError(BaseLLMException):
diff --git a/litellm/llms/dashscope/cost_calculator.py b/litellm/llms/dashscope/cost_calculator.py
index 771ce140f66..dd5bee1fe8b 100644
--- a/litellm/llms/dashscope/cost_calculator.py
+++ b/litellm/llms/dashscope/cost_calculator.py
@@ -110,7 +110,7 @@ def _calculate_completion_cost(
     return (breakdown.completion_tokens * output_cost) + (breakdown.reasoning_tokens * reasoning_cost)
 
 
-def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
+def cost_per_token(model: str, usage: Usage, custom_llm_provider: str = "dashscope") -> tuple[float, float]:
     """
     Calculate cost per token for Dashscope models.
 
@@ -119,11 +119,12 @@ def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
     Args:
         model: Model name without provider prefix
         usage: LiteLLM Usage block
+        custom_llm_provider: The provider id the request resolved to; dashscope or one of its brand aliases
 
     Returns:
         Tuple[float, float] - (prompt_cost_in_usd, completion_cost_in_usd)
     """
-    model_info: Final = get_model_info(model=model, custom_llm_provider="dashscope")
+    model_info: Final = get_model_info(model=model, custom_llm_provider=custom_llm_provider)
     breakdown: Final = _extract_token_breakdown(usage)
     raw_tiers: Final = model_info.get("tiered_pricing")
     tiered_pricing: Final = raw_tiers if isinstance(raw_tiers, list) else None
diff --git a/litellm/llms/dashscope/embed/transformation.py b/litellm/llms/dashscope/embed/transformation.py
index 6d13f1e53f7..63ee984a65c 100644
--- a/litellm/llms/dashscope/embed/transformation.py
+++ b/litellm/llms/dashscope/embed/transformation.py
@@ -62,6 +62,17 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
             # for drop_params=False before this method is called.
         return optional_params
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key if api_key is not None else get_secret_str("DASHSCOPE_API_KEY")
+        if resolved_api_key is None:
+            raise ValueError(
+                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
+            )
+        return resolved_api_key
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("DASHSCOPE_API_BASE") or DEFAULT_API_BASE
+
     def validate_environment(
         self,
         headers: dict,
@@ -72,17 +83,11 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
         api_key: str | None = None,
         api_base: str | None = None,
     ) -> dict:
-        if api_key is None:
-            api_key = get_secret_str("DASHSCOPE_API_KEY")
-        if api_key is None:
-            raise ValueError(
-                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
-            )
-        default_headers: Final = {
+        return {
             "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
+            "Authorization": f"Bearer {self._resolve_api_key(api_key)}",
+            **headers,
         }
-        return {**default_headers, **headers}
 
     def get_complete_url(
         self,
@@ -93,8 +98,7 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
         litellm_params: dict,
         stream: bool | None = None,
     ) -> str:
-        base = api_base or get_secret_str("DASHSCOPE_API_BASE") or DEFAULT_API_BASE
-        base = base.rstrip("/")
+        base: Final = self._resolve_embedding_api_base(api_base).rstrip("/")
         if base.endswith("/embeddings"):
             return base
         return f"{base}/embeddings"
diff --git a/litellm/llms/dashscope/image_generation/transformation.py b/litellm/llms/dashscope/image_generation/transformation.py
index a7f0e98865f..c0e278a96ef 100644
--- a/litellm/llms/dashscope/image_generation/transformation.py
+++ b/litellm/llms/dashscope/image_generation/transformation.py
@@ -91,6 +91,15 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
                 mapped[k] = v
         return mapped
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
+        if not resolved_api_key:
+            raise ValueError("DASHSCOPE_API_KEY is not set")
+        return resolved_api_key
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("DASHSCOPE_API_BASE_IMAGE") or DEFAULT_API_BASE
+
     def get_complete_url(
         self,
         api_base: str | None,
@@ -103,7 +112,7 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
         image_api_base: Final = (
             api_base if api_base and not api_base.rstrip("/").endswith(CHAT_COMPATIBLE_MODE_PATH) else None
         )
-        return image_api_base or get_secret_str("DASHSCOPE_API_BASE_IMAGE") or DEFAULT_API_BASE
+        return self._resolve_image_api_base(image_api_base)
 
     def validate_environment(
         self,
@@ -115,10 +124,7 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
         api_key: str | None = None,
         api_base: str | None = None,
     ) -> dict:
-        final_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
-        if not final_api_key:
-            raise ValueError("DASHSCOPE_API_KEY is not set")
-        headers["Authorization"] = f"Bearer {final_api_key}"
+        headers["Authorization"] = f"Bearer {self._resolve_api_key(api_key)}"
         headers["Content-Type"] = "application/json"
         return headers
 
diff --git a/litellm/llms/dashscope/qwen_ai_platform.py b/litellm/llms/dashscope/qwen_ai_platform.py
new file mode 100644
index 00000000000..9a44eaf574a
--- /dev/null
+++ b/litellm/llms/dashscope/qwen_ai_platform.py
@@ -0,0 +1,62 @@
+from typing import Final
+
+from litellm.secret_managers.main import get_secret_str
+
+from .chat.transformation import DashScopeChatConfig
+from .embed.transformation import DashScopeEmbeddingConfig
+from .image_generation.transformation import DashScopeImageGenerationConfig
+from .rerank.transformation import DashScopeRerankConfig
+
+QWEN_AI_PLATFORM_API_BASE: Final = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+QWEN_AI_PLATFORM_RERANK_API_BASE: Final = "https://dashscope.aliyuncs.com/compatible-api/v1/reranks"
+QWEN_AI_PLATFORM_IMAGE_API_BASE: Final = (
+    "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
+)
+
+
+def _resolve_qwen_ai_platform_api_key(api_key: str | None) -> str | None:
+    return api_key or get_secret_str("QWEN_AI_PLATFORM_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def _require_qwen_ai_platform_api_key(api_key: str | None) -> str:
+    resolved: Final = _resolve_qwen_ai_platform_api_key(api_key)
+    if resolved is None:
+        raise ValueError(
+            "Qwen AI Platform API key is required. Set 'QWEN_AI_PLATFORM_API_KEY' or 'DASHSCOPE_API_KEY' env var "
+            "or pass api_key explicitly."
+        )
+    return resolved
+
+
+class QwenAIPlatformChatConfig(DashScopeChatConfig):
+    def _get_openai_compatible_provider_info(
+        self, api_base: str | None, api_key: str | None
+    ) -> tuple[str | None, str | None]:
+        return self._resolve_chat_api_base(api_base), _resolve_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE") or QWEN_AI_PLATFORM_API_BASE
+
+
+class QwenAIPlatformEmbeddingConfig(DashScopeEmbeddingConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE") or QWEN_AI_PLATFORM_API_BASE
+
+
+class QwenAIPlatformRerankConfig(DashScopeRerankConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE_RERANK") or QWEN_AI_PLATFORM_RERANK_API_BASE
+
+
+class QwenAIPlatformImageGenerationConfig(DashScopeImageGenerationConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE_IMAGE") or QWEN_AI_PLATFORM_IMAGE_API_BASE
diff --git a/litellm/llms/dashscope/qwencloud.py b/litellm/llms/dashscope/qwencloud.py
new file mode 100644
index 00000000000..d8d53e340ef
--- /dev/null
+++ b/litellm/llms/dashscope/qwencloud.py
@@ -0,0 +1,62 @@
+from typing import Final
+
+from litellm.secret_managers.main import get_secret_str
+
+from .chat.transformation import DashScopeChatConfig
+from .embed.transformation import DashScopeEmbeddingConfig
+from .image_generation.transformation import DashScopeImageGenerationConfig
+from .rerank.transformation import DashScopeRerankConfig
+
+QWENCLOUD_API_BASE: Final = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
+QWENCLOUD_RERANK_API_BASE: Final = "https://dashscope-intl.aliyuncs.com/compatible-api/v1/reranks"
+QWENCLOUD_IMAGE_API_BASE: Final = (
+    "https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
+)
+
+
+def _resolve_qwencloud_api_key(api_key: str | None) -> str | None:
+    return api_key or get_secret_str("QWENCLOUD_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def _require_qwencloud_api_key(api_key: str | None) -> str:
+    resolved: Final = _resolve_qwencloud_api_key(api_key)
+    if resolved is None:
+        raise ValueError(
+            "QwenCloud API key is required. Set 'QWENCLOUD_API_KEY' or 'DASHSCOPE_API_KEY' env var "
+            "or pass api_key explicitly."
+        )
+    return resolved
+
+
+class QwenCloudChatConfig(DashScopeChatConfig):
+    def _get_openai_compatible_provider_info(
+        self, api_base: str | None, api_key: str | None
+    ) -> tuple[str | None, str | None]:
+        return self._resolve_chat_api_base(api_base), _resolve_qwencloud_api_key(api_key)
+
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE") or QWENCLOUD_API_BASE
+
+
+class QwenCloudEmbeddingConfig(DashScopeEmbeddingConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE") or QWENCLOUD_API_BASE
+
+
+class QwenCloudRerankConfig(DashScopeRerankConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE_RERANK") or QWENCLOUD_RERANK_API_BASE
+
+
+class QwenCloudImageGenerationConfig(DashScopeImageGenerationConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("QWENCLOUD_API_BASE_IMAGE") or QWENCLOUD_IMAGE_API_BASE
diff --git a/litellm/llms/dashscope/rerank/transformation.py b/litellm/llms/dashscope/rerank/transformation.py
index 98be4e4f2e7..3dd3996b2ee 100644
--- a/litellm/llms/dashscope/rerank/transformation.py
+++ b/litellm/llms/dashscope/rerank/transformation.py
@@ -58,19 +58,30 @@ class DashScopeRerankConfig(BaseRerankConfig):
     def __init__(self) -> None:
         pass
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key if api_key is not None else get_secret_str("DASHSCOPE_API_KEY")
+        if resolved_api_key is None:
+            raise ValueError(
+                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
+            )
+        return resolved_api_key
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        if api_base is not None:
+            return api_base
+        return get_secret_str("DASHSCOPE_API_BASE_RERANK") or DEFAULT_RERANK_URL
+
     def get_complete_url(
         self,
         api_base: str | None,
         model: str,
         optional_params: dict | None = None,
     ) -> str:
-        if api_base is None:
-            api_base = get_secret_str("DASHSCOPE_API_BASE_RERANK") or DEFAULT_RERANK_URL
+        resolved_api_base: Final = self._resolve_rerank_api_base(api_base)
+        if resolved_api_base == DEFAULT_RERANK_URL:
+            return resolved_api_base
 
-        if api_base == DEFAULT_RERANK_URL:
-            return DEFAULT_RERANK_URL
-
-        cleaned: Final = api_base.rstrip("/")
+        cleaned: Final = resolved_api_base.rstrip("/")
         if cleaned.endswith("/reranks") or cleaned.endswith("/rerank"):
             return cleaned
 
@@ -88,19 +99,12 @@ class DashScopeRerankConfig(BaseRerankConfig):
         optional_params: dict | None = None,
         litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
-        if api_key is None:
-            api_key = get_secret_str("DASHSCOPE_API_KEY")
-        if api_key is None:
-            raise ValueError(
-                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
-            )
-
-        default_headers: Final = {
-            "Authorization": f"Bearer {api_key}",
+        return {
+            "Authorization": f"Bearer {self._resolve_api_key(api_key)}",
             "accept": "application/json",
             "content-type": "application/json",
+            **headers,
         }
-        return {**default_headers, **headers}
 
     def get_supported_cohere_rerank_params(self, model: str) -> list:
         return ["query", "documents", "top_n", "return_documents"]
diff --git a/litellm/llms/databricks/chat/transformation.py b/litellm/llms/databricks/chat/transformation.py
index c587146005f..65622d62af2 100644
--- a/litellm/llms/databricks/chat/transformation.py
+++ b/litellm/llms/databricks/chat/transformation.py
@@ -330,6 +330,10 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig):
     ) -> dict:
         is_thinking_enabled: Final = self.is_thinking_enabled(non_default_params)
         mapped_params: Final = super().map_openai_params(non_default_params, optional_params, model, drop_params)
+        if "claude" in model:
+            AnthropicConfig.translate_legacy_thinking_for_adaptive_model(
+                model=model, optional_params=mapped_params, custom_llm_provider="databricks"
+            )
         if "tools" in mapped_params:
             mapped_params["tools"] = self._map_openai_to_dbrx_tool(model=model, tools=mapped_params["tools"])
         if "max_completion_tokens" in non_default_params and replace_max_completion_tokens_with_max_tokens:
diff --git a/litellm/llms/deepinfra/rerank/transformation.py b/litellm/llms/deepinfra/rerank/transformation.py
index e52c56af82b..a3d0482af0a 100644
--- a/litellm/llms/deepinfra/rerank/transformation.py
+++ b/litellm/llms/deepinfra/rerank/transformation.py
@@ -2,10 +2,11 @@
 Translate between Cohere's `/rerank` format and Deepinfra's `/rerank` format.
 """
 
-from collections.abc import Mapping
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._uuid import uuid
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
@@ -24,6 +25,36 @@ from litellm.types.rerank import (
 )
 
 
+class _DeepinfraInferenceStatus(TypedDict, total=False):
+    """The ``inference_status`` block of a DeepInfra rerank response."""
+
+    status: ReadOnly[str]
+    runtime_ms: ReadOnly[float]
+    cost: ReadOnly[float]
+    tokens_generated: ReadOnly[int]
+    tokens_input: ReadOnly[int]
+
+
+class _DeepinfraRerankResponse(TypedDict, total=False):
+    """Body of a DeepInfra ``/rerank`` response."""
+
+    scores: ReadOnly[Sequence[float]]
+    input_tokens: ReadOnly[int]
+    request_id: ReadOnly[str | None]
+    inference_status: ReadOnly[_DeepinfraInferenceStatus]
+
+
+class _DeepinfraRerankResponseSource(Protocol):
+    """The DeepInfra ``/rerank`` HTTP response, read for the body it decodes to."""
+
+    def json(self) -> _DeepinfraRerankResponse: ...
+
+
+def _deepinfra_rerank_body(response: _DeepinfraRerankResponseSource) -> _DeepinfraRerankResponse:
+    """Decode the body of a DeepInfra ``/rerank`` response."""
+    return response.json()
+
+
 class DeepinfraRerankConfig(BaseRerankConfig):
     """
     Deepinfra Rerank - Follows the same Spec as Cohere Rerank
@@ -95,7 +126,7 @@ class DeepinfraRerankConfig(BaseRerankConfig):
         model: str,
         drop_params: bool,
         query: str,
-        documents: list[str | dict[str, Any]],
+        documents: list[str | dict[str, object]],
         custom_llm_provider: str | None = None,
         top_n: int | None = None,
         rank_fields: list[str] | None = None,
@@ -150,7 +181,7 @@ class DeepinfraRerankConfig(BaseRerankConfig):
         litellm_params: dict = {},
     ) -> RerankResponse:
         try:
-            response_json: Final = raw_response.json()
+            response_json: Final = _deepinfra_rerank_body(raw_response)
             logging_obj.post_call(original_response=raw_response.text)
 
             # Extract the scores from the response
diff --git a/litellm/llms/e2b/sandbox/transformation.py b/litellm/llms/e2b/sandbox/transformation.py
index 9cd9ade77a4..4928ca0c092 100644
--- a/litellm/llms/e2b/sandbox/transformation.py
+++ b/litellm/llms/e2b/sandbox/transformation.py
@@ -8,7 +8,7 @@ Talks to e2b's REST API directly over httpx (no e2b SDK dependency):
 """
 
 import json
-from typing import Final, cast
+from typing import Final
 
 import httpx
 
@@ -68,13 +68,10 @@ class E2BSandboxConfig(BaseSandboxConfig):
         if metadata:
             body["metadata"] = metadata
 
-        response: Final = cast(
-            httpx.Response,
-            await self._http(client).post(
-                url=f"{base}/sandboxes",
-                headers={"X-API-Key": key, "Content-Type": "application/json"},
-                json=body,
-            ),
+        response: Final = await self._http(client).post(
+            url=f"{base}/sandboxes",
+            headers={"X-API-Key": key, "Content-Type": "application/json"},
+            json=body,
         )
         data: Final = response.json()
 
@@ -117,14 +114,11 @@ class E2BSandboxConfig(BaseSandboxConfig):
             headers["E2B-Traffic-Access-Token"] = traffic_token
 
         url: Final = f"https://{JUPYTER_PORT}-{handle.id}.{handle.domain}/execute"
-        response: Final = cast(
-            httpx.Response,
-            await self._http(client).post(
-                url=url,
-                headers=headers,
-                json={"code": code, "context_id": None, "env_vars": env_vars},
-                stream=True,
-            ),
+        response: Final = await self._http(client).post(
+            url=url,
+            headers=headers,
+            json={"code": code, "context_id": None, "env_vars": env_vars},
+            stream=True,
         )
         lines: Final = await self._read_capped_lines(response)
         return self._parse_lines(lines)
@@ -142,12 +136,9 @@ class E2BSandboxConfig(BaseSandboxConfig):
         key: Final = api_key or handle._hidden_params.get("api_key") or self.validate_environment()
         base: Final = api_base or handle._hidden_params.get("api_base") or E2B_API_BASE
         try:
-            response: Final = cast(
-                httpx.Response,
-                await self._http(client).delete(
-                    url=f"{base}/sandboxes/{handle.id}",
-                    headers={"X-API-Key": key},
-                ),
+            response: Final = await self._http(client).delete(
+                url=f"{base}/sandboxes/{handle.id}",
+                headers={"X-API-Key": key},
             )
         except httpx.HTTPStatusError as e:
             if e.response.status_code == 404:
diff --git a/litellm/llms/gdc/chat/transformation.py b/litellm/llms/gdc/chat/transformation.py
index 2d0322bf10f..03037512551 100644
--- a/litellm/llms/gdc/chat/transformation.py
+++ b/litellm/llms/gdc/chat/transformation.py
@@ -6,11 +6,25 @@ import json
 import os
 import re
 import threading
-from typing import Any, Final
+from collections.abc import Callable
+from typing import Any, Final, Protocol
 from urllib.parse import urlsplit
 
 import litellm
 from litellm.llms.openai_like.chat.transformation import OpenAILikeChatConfig
+from litellm.types.llms.openai import AllMessageValues
+
+
+class _GDCHAudienceCredentials(Protocol):
+    """A GDCH service account credential already bound to an audience, ready to mint a bearer token."""
+
+    @property
+    def valid(self) -> bool: ...
+
+    @property
+    def token(self) -> str: ...
+
+    def refresh(self, request: object) -> None: ...
 
 
 class GDCGeminiConfig(OpenAILikeChatConfig):
@@ -21,7 +35,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
     def __init__(self, **kwargs: Any) -> None:
         super().__init__(**kwargs)
         self._creds_lock = threading.Lock()
-        self._gdch_creds_cache: dict = {}
+        self._gdch_creds_cache: dict[tuple[str, str], _GDCHAudienceCredentials] = {}
 
     def get_supported_openai_params(self, model: str) -> list:
         return [
@@ -110,7 +124,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
 
         return f"{api_base}/v1/projects/{project}/locations/{location}/chat/completions"
 
-    def _read_env_bool(self, val: Any, env_var: str, default: bool = True) -> bool | str:
+    def _read_env_bool(self, val: bool | str | None, env_var: str, default: bool = True) -> bool | str:
         def _parse(s: str) -> bool | str:
             cleaned: Final = s.strip().lower()
             if cleaned in ("false", "0", "no", "off"):
@@ -129,7 +143,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
             return default
         return _parse(_env_val)
 
-    def _fetch_auth(self, gdch_creds: Any, ssl_verify: bool | str) -> None:
+    def _fetch_auth(self, gdch_creds: _GDCHAudienceCredentials, ssl_verify: bool | str) -> None:
         import requests
         from google.auth.transport import requests as auth_requests
 
@@ -138,13 +152,24 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
         auth_request: Final = auth_requests.Request(session=auth_session)
         gdch_creds.refresh(auth_request)
 
-    def _cached_fetch_token(self, creds: Any, audience: str, ssl_verify: bool | str, api_key: str | None = None) -> str:
+    def _with_gdch_audience(self, creds: object, audience: str) -> _GDCHAudienceCredentials:
+        """The credential rebound to ``audience``, which GDCH requires before a token refresh."""
+        bind_audience: Final[Callable[[str], _GDCHAudienceCredentials] | None] = getattr(
+            creds, "with_gdch_audience", None
+        )
+        if bind_audience is None:
+            raise AttributeError("GDC credentials must expose with_gdch_audience to be bound to a request audience")
+        return bind_audience(audience)
+
+    def _cached_fetch_token(
+        self, creds: object, audience: str, ssl_verify: bool | str, api_key: str | None = None
+    ) -> str:
         # Key cache by both audience and credential identity to prevent cross-caller contamination
         cache_key: Final = (audience.rstrip("/"), api_key or str(id(creds)))
 
         with self._creds_lock:
             if cache_key not in self._gdch_creds_cache:
-                self._gdch_creds_cache[cache_key] = creds.with_gdch_audience(audience.rstrip("/"))
+                self._gdch_creds_cache[cache_key] = self._with_gdch_audience(creds, audience.rstrip("/"))
 
             gdch_creds: Final = self._gdch_creds_cache[cache_key]
 
@@ -155,7 +180,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
 
         return token
 
-    def _load_creds_from_key(self, api_key: str) -> tuple[Any, bool]:
+    def _load_creds_from_key(self, api_key: str) -> tuple[object | None, bool]:
         import google.auth
 
         try:
@@ -175,7 +200,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
         self,
         headers: dict,
         model: str,
-        messages: list[Any],
+        messages: list[AllMessageValues],
         optional_params: dict,
         litellm_params: dict,
         api_key: str | None = None,
@@ -230,7 +255,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
             if self._read_env_bool(litellm_params.get("gdc_token_caching"), "GDC_TOKEN_CACHING", default=False):
                 token = self._cached_fetch_token(creds, audience, ssl_verify, api_key)
             else:
-                gdch_creds: Final = creds.with_gdch_audience(audience)
+                gdch_creds: Final = self._with_gdch_audience(creds, audience)
                 self._fetch_auth(gdch_creds, ssl_verify)
                 token = gdch_creds.token
             headers["Authorization"] = f"Bearer {token}"
@@ -252,7 +277,7 @@ class GDCGeminiConfig(OpenAILikeChatConfig):
     def transform_request(
         self,
         model: str,
-        messages: list[Any],
+        messages: list[AllMessageValues],
         optional_params: dict,
         litellm_params: dict,
         headers: dict,
diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py
index bd2b124605c..78e6e6aaf82 100644
--- a/litellm/llms/gemini/common_utils.py
+++ b/litellm/llms/gemini/common_utils.py
@@ -2,7 +2,7 @@ import base64
 import datetime
 import json
 import math
-from collections.abc import Sequence
+from collections.abc import Mapping, Sequence
 from typing import Any, Final
 
 import httpx
@@ -128,24 +128,35 @@ def is_gemini_image_model(model: str) -> bool:
     return "gemini" in base_model
 
 
+def _parse_image_config_string(raw_image_config: str, model: str) -> object:
+    try:
+        return json.loads(raw_image_config)
+    except json.JSONDecodeError as exc:
+        raise litellm.UnsupportedParamsError(
+            model=model,
+            message="`imageConfig` must be valid JSON when provided as a string.",
+        ) from exc
+
+
 def map_openai_image_params_to_gemini(
-    params: dict[str, Any],
+    params: Mapping[str, object],
     model: str,
     supported_params: Sequence[str],
-    optional_params: dict[str, Any] | None = None,
+    optional_params: Mapping[str, object] | None = None,
     parse_image_config_string: bool = False,
-) -> dict[str, Any]:
-    optional_params = optional_params or {}
+) -> dict[str, object]:
+    already_mapped: Final[Mapping[str, object]] = optional_params or {}
     filtered_params: Final = {key: value for key, value in params.items() if key in supported_params}
 
-    mapped_params: Final[dict[str, Any]] = {}
+    mapped_params: Final[dict[str, object]] = {}
 
-    if "n" in filtered_params and "n" not in optional_params:
+    if "n" in filtered_params and "n" not in already_mapped:
         mapped_params["sampleCount"] = filtered_params["n"]
 
-    if "size" in filtered_params and "size" not in optional_params:
+    size_param: Final = filtered_params.get("size")
+    if isinstance(size_param, str) and "size" not in already_mapped:
         image_config: Final = map_openai_size_to_gemini_image_config(
-            filtered_params["size"],
+            size_param,
             model,
         )
         if image_config is not None:
@@ -156,33 +167,30 @@ def map_openai_image_params_to_gemini(
                 if "imageSize" in image_config:
                     mapped_params["imageSize"] = image_config["imageSize"]
 
-    image_config_param = filtered_params.get("imageConfig")
-    if isinstance(image_config_param, str) and parse_image_config_string:
-        try:
-            image_config_param = json.loads(image_config_param)
-        except json.JSONDecodeError as exc:
-            raise litellm.UnsupportedParamsError(
-                model=model,
-                message="`imageConfig` must be valid JSON when provided as a string.",
-            ) from exc
+    raw_image_config: Final = filtered_params.get("imageConfig")
+    image_config_param: Final[object] = (
+        _parse_image_config_string(raw_image_config, model)
+        if isinstance(raw_image_config, str) and parse_image_config_string
+        else raw_image_config
+    )
     if isinstance(image_config_param, dict):
         mapped_params["imageConfig"] = image_config_param
 
     for key, value in filtered_params.items():
-        if key not in ("n", "size", "imageConfig", "tools", "web_search_options") and key not in optional_params:
+        if key not in ("n", "size", "imageConfig", "tools", "web_search_options") and key not in already_mapped:
             mapped_params[key] = value
 
     return mapped_params
 
 
-def _dedupe_gemini_search_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
+def _dedupe_gemini_search_tools(tools: list[dict[str, object]]) -> list[dict[str, object]]:
     from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
         VertexGeminiConfig,
     )
 
     search_tool_keys: Final = VertexGeminiConfig._search_tool_keys()
     seen_search_keys: Final[set[str]] = set()
-    deduped_tools: Final[list[dict[str, Any]]] = []
+    deduped_tools: Final[list[dict[str, object]]] = []
 
     for tool in tools:
         if not isinstance(tool, dict):
@@ -203,7 +211,7 @@ def _dedupe_gemini_search_tools(tools: list[dict[str, Any]]) -> list[dict[str, A
     return deduped_tools
 
 
-def _has_gemini_search_tool(tools: list[Any]) -> bool:
+def _has_gemini_search_tool(tools: list[object]) -> bool:
     from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
         VertexGeminiConfig,
     )
@@ -213,9 +221,9 @@ def _has_gemini_search_tool(tools: list[Any]) -> bool:
 
 
 def map_gemini_image_tools_params(
-    non_default_params: dict[str, Any],
-    mapped_params: dict[str, Any],
-) -> dict[str, Any]:
+    non_default_params: Mapping[str, object],
+    mapped_params: Mapping[str, object],
+) -> dict[str, object]:
     from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
         VertexGeminiConfig,
     )
@@ -239,21 +247,24 @@ def map_gemini_image_tools_params(
 
     gemini_config._drop_search_tools_mixed_with_functions(result)
 
-    if isinstance(result.get("tools"), list):
-        result["tools"] = _dedupe_gemini_search_tools(result["tools"])
+    resolved_tools: Final = result.get("tools")
+    if isinstance(resolved_tools, list):
+        result["tools"] = _dedupe_gemini_search_tools(resolved_tools)
 
     return result
 
 
 def get_gemini_image_web_search_requests(
-    response_data: dict[str, Any],
+    response_data: Mapping[str, object],
 ) -> int | None:
     from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
         VertexGeminiConfig,
     )
 
-    grounding_metadata: Final[list[dict[str, Any]]] = []
-    for candidate in response_data.get("candidates", []):
+    raw_candidates: Final = response_data.get("candidates")
+    candidates: Final[list[object]] = raw_candidates if isinstance(raw_candidates, list) else []
+    grounding_metadata: Final[list[dict[str, object]]] = []
+    for candidate in candidates:
         if not isinstance(candidate, dict):
             continue
         candidate_grounding = candidate.get("groundingMetadata")
@@ -267,13 +278,14 @@ def get_gemini_image_web_search_requests(
 
 def get_gemini_image_generation_config(
     model: str,
-    optional_params: dict[str, Any],
-) -> dict[str, Any]:
-    generation_config: Final[dict[str, Any]] = {"response_modalities": ["IMAGE", "TEXT"]}
+    optional_params: Mapping[str, object],
+) -> dict[str, object]:
+    generation_config: Final[dict[str, object]] = {"response_modalities": ["IMAGE", "TEXT"]}
 
-    image_config: Final[dict[str, Any]] = {}
-    if isinstance(optional_params.get("imageConfig"), dict):
-        image_config.update(optional_params["imageConfig"])
+    raw_image_config: Final = optional_params.get("imageConfig")
+    image_config: Final[dict[str, object]] = {}
+    if isinstance(raw_image_config, dict):
+        image_config.update(raw_image_config)
 
     if not supports_gemini_image_size(model):
         image_config.pop("imageSize", None)
@@ -398,7 +410,7 @@ class GeminiModelInfo(BaseLLMModelInfo):
                 f"Failed to fetch models from Gemini. Status code: {response.status_code}, Response: {response.json()}"
             )
 
-        models: Final = response.json()["models"]
+        models: Final[list[dict[str, str]]] = response.json()["models"]
 
         litellm_model_names: Final = self.process_model_name(models)
         return litellm_model_names
@@ -473,12 +485,12 @@ class GoogleAIStudioTokenCounter(BaseTokenCounter):
     async def count_tokens(
         self,
         model_to_use: str,
-        messages: list[dict[str, Any]] | None,
-        contents: list[dict[str, Any]] | None,
+        messages: list[dict[str, object]] | None,
+        contents: list[dict[str, object]] | None,
         deployment: dict[str, Any] | None = None,
         request_model: str = "",
-        tools: list[dict[str, Any]] | None = None,
-        system: Any | None = None,
+        tools: list[dict[str, object]] | None = None,
+        system: object | None = None,
     ) -> TokenCountResponse | None:
         import copy
 
diff --git a/litellm/llms/gemini/files/transformation.py b/litellm/llms/gemini/files/transformation.py
index dee83407cb5..2c62e04c5a3 100644
--- a/litellm/llms/gemini/files/transformation.py
+++ b/litellm/llms/gemini/files/transformation.py
@@ -5,11 +5,13 @@ For vertex ai, check out the vertex_ai/files/handler.py file.
 """
 
 import time
-from typing import Any, Final, Literal
+from collections.abc import Mapping
+from typing import Final, Literal, TypedDict
 from urllib.parse import urlparse
 
 import httpx
 from openai.types.file_deleted import FileDeleted
+from typing_extensions import ReadOnly, Required
 
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.prompt_templates.common_utils import extract_file_data
@@ -18,7 +20,6 @@ from litellm.llms.base_llm.files.transformation import (
     BaseFilesConfig,
     LiteLLMLoggingObj,
 )
-from litellm.types.llms.gemini import GeminiCreateFilesResponseObject
 from litellm.types.llms.openai import (
     AllMessageValues,
     CreateFileRequest,
@@ -31,6 +32,25 @@ from litellm.types.utils import LlmProviders
 from ..common_utils import GeminiModelInfo
 
 
+class _GeminiFileMetadata(TypedDict, total=False):
+    name: ReadOnly[str]
+    uri: ReadOnly[Required[str]]
+    displayName: ReadOnly[Required[str]]
+    mimeType: ReadOnly[str]
+    sizeBytes: ReadOnly[Required[str]]
+    createTime: ReadOnly[Required[str]]
+    updateTime: ReadOnly[str]
+    expirationTime: ReadOnly[str]
+    sha256Hash: ReadOnly[str]
+    state: ReadOnly[str]
+    source: ReadOnly[str]
+    error: ReadOnly[Mapping[str, object]]
+
+
+class _GeminiCreateFileResponse(TypedDict):
+    file: ReadOnly[_GeminiFileMetadata]
+
+
 class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig):
     def __init__(self):
         pass
@@ -41,14 +61,14 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig):
 
     def validate_environment(
         self,
-        headers: dict[Any, Any],
+        headers: dict[str, str],
         model: str,
         messages: list[AllMessageValues],
-        optional_params: dict[Any, Any],
-        litellm_params: dict[Any, Any],
+        optional_params: dict[str, object],
+        litellm_params: dict[str, object],
         api_key: str | None = None,
         api_base: str | None = None,
-    ) -> dict[Any, Any]:
+    ) -> dict[str, str]:
         """
         Validate environment and add Gemini API key to headers.
         Google AI Studio uses x-goog-api-key header for authentication.
@@ -164,9 +184,9 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig):
         Transform Gemini's file upload response into OpenAI-style FileObject
         """
         try:
-            response_json: Final = raw_response.json()
+            response_json: Final[_GeminiCreateFileResponse] = raw_response.json()
 
-            response_object: Final = GeminiCreateFilesResponseObject(**response_json.get("file", {}))
+            response_object: Final = response_json["file"]
 
             # Extract file information from Gemini response
 
@@ -262,7 +282,7 @@ class GoogleAIStudioFilesHandler(GeminiModelInfo, BaseFilesConfig):
         """
         try:
             verbose_logger.debug("Retrieve file response: %s", raw_response.text)
-            response_json: Final = raw_response.json()
+            response_json: Final[_GeminiFileMetadata] = raw_response.json()
             verbose_logger.debug("Response JSON: %s", response_json)
             # Map Gemini state to OpenAI status
             gemini_state: Final = response_json.get("state", "STATE_UNSPECIFIED")
diff --git a/litellm/llms/gemini/interactions/transformation.py b/litellm/llms/gemini/interactions/transformation.py
index dcd2e4e3471..6d0f211ed7b 100644
--- a/litellm/llms/gemini/interactions/transformation.py
+++ b/litellm/llms/gemini/interactions/transformation.py
@@ -12,9 +12,10 @@ Schema versioning:
   litellm.use_legacy_interactions_schema = True. Remove flag after June 8, 2026.
 """
 
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol, TypeAlias
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -41,6 +42,53 @@ else:
     LiteLLMLoggingObj = Any
 
 
+_JsonObject: TypeAlias = dict[str, object]
+
+
+class _InteractionPayload(TypedDict, total=False):
+    """JSON body of an Interactions API interaction, keyed as ``InteractionsAPIResponse`` fields."""
+
+    id: ReadOnly[str | None]
+    object: ReadOnly[str | None]
+    model: ReadOnly[str | None]
+    agent: ReadOnly[str | None]
+    status: ReadOnly[str | None]
+    created: ReadOnly[str | None]
+    updated: ReadOnly[str | None]
+    outputs: ReadOnly[list[_JsonObject] | None]
+    steps: ReadOnly[list[_JsonObject] | None]
+    usage: ReadOnly[_JsonObject | None]
+
+
+class _CancelPayload(TypedDict, total=False):
+    """JSON body of an Interactions API cancel response."""
+
+    id: ReadOnly[str | None]
+    status: ReadOnly[str | None]
+
+
+class _InteractionPayloadSource(Protocol):
+    """An Interactions API HTTP response, read for the interaction body it decodes to."""
+
+    def json(self) -> _InteractionPayload: ...
+
+
+class _CancelPayloadSource(Protocol):
+    """An Interactions API cancel HTTP response, read for the body it decodes to."""
+
+    def json(self) -> _CancelPayload: ...
+
+
+def _interaction_body(response: _InteractionPayloadSource) -> _InteractionPayload:
+    """Decode the body of an Interactions API interaction response."""
+    return response.json()
+
+
+def _cancel_body(response: _CancelPayloadSource) -> _CancelPayload:
+    """Decode the body of an Interactions API cancel response."""
+    return response.json()
+
+
 class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
     """
     Configuration for Google AI Studio Interactions API.
@@ -143,7 +191,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         """
         use_legacy: Final[bool] = litellm.use_legacy_interactions_schema
 
-        request_body: Final[dict[str, Any]] = {}
+        request_body: Final[dict[str, object]] = {}
 
         # Model or Agent (one required)
         if model:
@@ -189,7 +237,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
                 and (not isinstance(response_format, dict) or "mime_type" not in response_format)
             ):
                 # Wrap the legacy schema into the new polymorphic format.
-                new_rf: Final[dict[str, Any]] = {
+                new_rf: Final[dict[str, object]] = {
                     "type": "text",
                     "mime_type": response_mime_type,
                 }
@@ -215,7 +263,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
 
                 if image_config is not None:
                     # Move image_config to response_format with type=image.
-                    image_rf: Final[dict[str, Any]] = {"type": "image", **image_config}
+                    image_rf: Final[_JsonObject] = {"type": "image", **image_config}
                     existing_rf: Final = request_body.get("response_format")
                     if existing_rf is None:
                         request_body["response_format"] = image_rf
@@ -239,7 +287,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
                 original_response=raw_response.text,
                 additional_args={"complete_input_dict": {}},
             )
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _interaction_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
@@ -290,7 +338,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> InteractionsAPIResponse:
         try:
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _interaction_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
@@ -355,7 +403,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> CancelInteractionResult:
         try:
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _cancel_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py
index 367619db37d..c92af7de145 100644
--- a/litellm/llms/gemini/realtime/transformation.py
+++ b/litellm/llms/gemini/realtime/transformation.py
@@ -7,6 +7,8 @@ from collections import OrderedDict
 from collections.abc import Mapping, Sequence
 from typing import Any, Final, cast
 
+from typing_extensions import ReadOnly, Required, TypedDict
+
 import litellm
 from litellm import verbose_logger
 from litellm._uuid import uuid
@@ -96,6 +98,23 @@ def _gemini_live_speech_config(voice: object) -> Mapping[str, object] | None:
     return VertexGeminiConfig()._map_audio_params({"voice": voice})
 
 
+class _GeminiLiveSetupEnvelope(TypedDict, total=False):
+    setup: ReadOnly[BidiGenerateContentSetup]
+
+
+class _OpenAIRealtimeClientEvent(TypedDict, total=False):
+    type: ReadOnly[str]
+    audio: ReadOnly[Required[str]]
+    session: ReadOnly[dict[str, object]]
+    item: ReadOnly[dict[str, object]]
+
+
+def _parse_setup(session_configuration_request: str) -> BidiGenerateContentSetup:
+    envelope: Final[_GeminiLiveSetupEnvelope] = json.loads(session_configuration_request)
+    empty_setup: Final[BidiGenerateContentSetup] = {}
+    return envelope.get("setup", empty_setup)
+
+
 # Google bills Live transcription at an estimated 25 audio tokens/sec of input and
 # 175 text tokens/min of output (ai.google.dev/gemini-api/docs/pricing).
 GEMINI_LIVE_TRANSCRIBE_AUDIO_TOKENS_PER_SECOND: Final = 25
@@ -130,7 +149,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         return True
 
     @staticmethod
-    def _usage_detail_alias(details: Any, defaults: dict[str, int]) -> dict[str, Any]:
+    def _usage_detail_alias(details: Mapping[str, int | None] | None, defaults: dict[str, int]) -> dict[str, int]:
         if not isinstance(details, dict):
             return dict(defaults)
         return {
@@ -139,7 +158,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         }
 
     @staticmethod
-    def _add_pipecat_usage_detail_aliases(usage_dict: dict[str, Any]) -> dict[str, Any]:
+    def _add_pipecat_usage_detail_aliases(usage_dict: dict[str, Any]) -> dict[str, object]:
         usage_dict.setdefault(
             "input_token_details",
             GeminiRealtimeConfig._usage_detail_alias(
@@ -222,8 +241,10 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         if not session_configuration_request:
             return False
         try:
-            setup: Final = json.loads(session_configuration_request).get("setup", {})
-            automatic_detection: Final = setup.get("realtimeInputConfig", {}).get("automaticActivityDetection", {})
+            setup: Final = _parse_setup(session_configuration_request)
+            automatic_detection: Final[object] = setup.get("realtimeInputConfig", {}).get(
+                "automaticActivityDetection", {}
+            )
             return isinstance(automatic_detection, dict) and automatic_detection.get("disabled") is True
         except (json.JSONDecodeError, TypeError, AttributeError):
             return False
@@ -406,7 +427,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         return "TEXT" if GeminiRealtimeConfig._is_text_only_live_model(model) else "AUDIO"
 
     @staticmethod
-    def _coerce_response_modalities(model: str, modalities: Sequence[Any]) -> tuple[str, ...]:
+    def _coerce_response_modalities(model: str, modalities: Sequence[object]) -> tuple[str, ...]:
         """Swap responseModalities a Live model cannot produce: TEXT to AUDIO for
         audio-only models, AUDIO to TEXT for text-only ones (e.g. transcribe-live)."""
         normalized: Final = tuple(
@@ -431,7 +452,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
 
     def _handle_session_update(
         self,
-        json_message: dict,
+        json_message: _OpenAIRealtimeClientEvent,
         model: str,
         session_configuration_request: str | None,
     ) -> list[str]:
@@ -445,7 +466,8 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         with a 1007, tearing the session down). To carry tools/instructions, send
         them on the first session.update before any conversation content.
         """
-        session_payload = json_message.get("session") or {}
+        empty_session: Final[dict[str, object]] = {}
+        session_payload = json_message.get("session") or empty_session
         # Normalize GA-remapped fields (``output_modalities``,
         # nested ``audio.input.transcription``,
         # ``audio.input.turn_detection``) back to their flat beta keys so
@@ -486,14 +508,15 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
             verbose_logger.debug("Gemini Realtime: Ignoring session.update (setup already sent)")
         return []
 
-    def _handle_conversation_item(self, json_message: dict) -> list[str]:
+    def _handle_conversation_item(self, json_message: _OpenAIRealtimeClientEvent) -> list[str]:
         """
         Handle conversation.item.create for user text or function call output.
 
         Converts OpenAI format to Gemini's clientContent (for user text) or
         toolResponse (for function outputs).
         """
-        item: Final = json_message.get("item", {})
+        empty_item: Final[dict[str, object]] = {}
+        item: Final = json_message.get("item", empty_item)
         item_type: Final = item.get("type")
 
         if item_type == "function_call_output":
@@ -524,7 +547,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
                 call_id,
             )
 
-        function_response: Final[dict[str, Any]] = {"response": output_dict}
+        function_response: Final[dict[str, object]] = {"response": output_dict}
         if self._include_function_response_id() and call_id:
             function_response["id"] = call_id
         if function_name:
@@ -559,7 +582,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
     ) -> list[str]:
         realtime_input_dict: BidiGenerateContentRealtimeInput = {}
         try:
-            json_message: Final = json.loads(message)
+            json_message: Final[_OpenAIRealtimeClientEvent] = json.loads(message)
         except json.JSONDecodeError:
             if isinstance(message, bytes):
                 message_str = message.decode("utf-8", errors="replace")
@@ -610,9 +633,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         session_configuration_request: str | None = None,
     ) -> OpenAIRealtimeStreamSessionEvents:
         if session_configuration_request:
-            session_configuration_request_dict: BidiGenerateContentSetup = json.loads(
-                session_configuration_request
-            ).get("setup", {})
+            session_configuration_request_dict: BidiGenerateContentSetup = _parse_setup(session_configuration_request)
         else:
             session_configuration_request_dict = {}
 
@@ -663,7 +684,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         session_configuration_request_dict: BidiGenerateContentSetup = {}
         if session_configuration_request is not None:
             try:
-                session_configuration_request_dict = json.loads(session_configuration_request).get("setup", {})
+                session_configuration_request_dict = _parse_setup(session_configuration_request)
             except json.JSONDecodeError:
                 session_configuration_request_dict = {}
         generation_config: Final = session_configuration_request_dict.get("generationConfig", {})
@@ -931,9 +952,9 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
         return events
 
     @staticmethod
-    def get_nested_value(obj: dict, path: str) -> Any:
+    def get_nested_value(obj: dict, path: str) -> object | None:
         keys: Final = path.split(".")
-        current = obj
+        current: object = obj
         for key in keys:
             if isinstance(current, dict) and key in current:
                 current = current[key]
@@ -1011,9 +1032,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
             current_response_id = f"resp_{uuid.uuid4()}"
 
         if session_configuration_request:
-            session_configuration_request_dict: BidiGenerateContentSetup = json.loads(
-                session_configuration_request
-            ).get("setup", {})
+            session_configuration_request_dict: BidiGenerateContentSetup = _parse_setup(session_configuration_request)
         else:
             session_configuration_request_dict = {}
 
@@ -1337,7 +1356,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig):
                 session_setup: BidiGenerateContentSetup = {}
                 if session_configuration_request is not None:
                     try:
-                        session_setup = json.loads(session_configuration_request).get("setup", {})
+                        session_setup = _parse_setup(session_configuration_request)
                     except (json.JSONDecodeError, TypeError):
                         session_setup = {}
                 tool_call_generation_config = session_setup.get("generationConfig", {}) or {}
diff --git a/litellm/llms/gemini/vector_stores/transformation.py b/litellm/llms/gemini/vector_stores/transformation.py
index f6525a449b6..82586b1f638 100644
--- a/litellm/llms/gemini/vector_stores/transformation.py
+++ b/litellm/llms/gemini/vector_stores/transformation.py
@@ -33,6 +33,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -168,6 +169,7 @@ class GeminiVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """
         Transform search request to Gemini's generateContent format.
diff --git a/litellm/llms/gemini/videos/transformation.py b/litellm/llms/gemini/videos/transformation.py
index 6a1fc144c42..ff4c675b02f 100644
--- a/litellm/llms/gemini/videos/transformation.py
+++ b/litellm/llms/gemini/videos/transformation.py
@@ -1,4 +1,5 @@
 import base64
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
@@ -54,8 +55,13 @@ def _convert_image_to_gemini_format(image_file) -> dict[str, str]:
     return {"bytesBase64Encoded": base64_encoded, "mimeType": mime_type}
 
 
+def _json_payload(raw_response: httpx.Response) -> object:
+    """Read an HTTP response body as an opaque JSON payload."""
+    return raw_response.json()
+
+
 def _usage_video_resolution_from_parameters(
-    parameters: dict[str, Any],
+    parameters: Mapping[str, object],
 ) -> str | None:
     """Normalize Veo ``parameters.resolution`` for usage and cost tracking."""
     res: Final = parameters.get("resolution")
@@ -97,7 +103,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         video_create_optional_params: VideoCreateOptionalRequestParams,
         model: str,
         drop_params: bool,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Map OpenAI-style parameters to Veo format.
 
@@ -111,7 +117,7 @@ class GeminiVideoConfig(BaseVideoConfig):
 
         All other params are passed through as-is to support Gemini-specific parameters.
         """
-        mapped_params: Final[dict[str, Any]] = {}
+        mapped_params: Final[dict[str, object]] = {}
 
         # Get supported OpenAI params (exclude "model" and "prompt" which are handled separately)
         supported_openai_params: Final = self.get_supported_openai_params(model)
@@ -312,11 +318,11 @@ class GeminiVideoConfig(BaseVideoConfig):
         - status: "processing"
         - usage: includes duration_seconds and optional video_resolution for cost calculation
         """
-        response_data: Final = raw_response.json()
+        response_data: Final = _json_payload(raw_response)
 
         # Parse response using Pydantic model for type safety
         try:
-            operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+            operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
         except Exception as e:
             raise ValueError(f"Failed to parse operation response: {e}")
 
@@ -336,7 +342,7 @@ class GeminiVideoConfig(BaseVideoConfig):
             model=model,
         )
 
-        usage_data: Final[dict[str, Any]] = {}
+        usage_data: Final[dict[str, float | str]] = {}
         if request_data:
             parameters: Final = request_data.get("parameters", {})
             duration: Final = parameters.get("durationSeconds") or DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS
@@ -367,7 +373,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         """
         operation_name: Final = extract_original_video_id(video_id)
         url: Final = f"{api_base.rstrip('/')}/v1beta/{operation_name}"
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
 
         return url, params
 
@@ -403,9 +409,9 @@ class GeminiVideoConfig(BaseVideoConfig):
             }
         }
         """
-        response_data: Final = raw_response.json()
+        response_data: Final = _json_payload(raw_response)
         # Parse response using Pydantic model for type safety
-        operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+        operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
 
         operation_name: Final = operation_response.name
         is_done: Final = operation_response.done
@@ -443,9 +449,9 @@ class GeminiVideoConfig(BaseVideoConfig):
         client: Final = litellm.module_level_client
         status_response: Final = client.get(url=status_url, headers=headers)
         status_response.raise_for_status()
-        response_data: Final = status_response.json()
+        response_data: Final = _json_payload(status_response)
 
-        operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+        operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
 
         if not operation_response.done:
             raise ValueError(
@@ -458,7 +464,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         generated_samples: Final = operation_response.response.generateVideoResponse.generatedSamples
         download_url: Final = generated_samples[0].video.uri
 
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
 
         return download_url, params
 
@@ -480,7 +486,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         api_base: str,
         litellm_params: GenericLiteLLMParams,
         headers: dict,
-        extra_body: dict[str, Any] | None = None,
+        extra_body: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """
         Video remix is not supported by Veo API.
@@ -506,7 +512,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         after: str | None = None,
         limit: int | None = None,
         order: str | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_query: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """
         Video list is not supported by Veo API.
@@ -547,7 +553,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         """Video delete is not supported."""
         raise NotImplementedError("Video delete is not supported by Google Veo.")
 
-    def transform_video_create_character_request(self, name, video, api_base, litellm_params, headers):
+    def transform_video_create_character_request(self, name, video: object, api_base, litellm_params, headers):
         raise NotImplementedError("video create character is not supported for Gemini")
 
     def transform_video_create_character_response(self, raw_response, logging_obj):
diff --git a/litellm/llms/gigachat/__init__.py b/litellm/llms/gigachat/__init__.py
index 3ddbd7864d9..e7c2206ffaa 100644
--- a/litellm/llms/gigachat/__init__.py
+++ b/litellm/llms/gigachat/__init__.py
@@ -15,9 +15,11 @@ API Documentation: https://developers.sber.ru/docs/ru/gigachat/api/overview
 
 from .chat.transformation import GigaChatConfig, GigaChatError
 from .embedding.transformation import GigaChatEmbeddingConfig
+from .passthrough.transformation import GigaChatPassthroughConfig
 
-__all__ = [
+__all__ = (
     "GigaChatConfig",
     "GigaChatEmbeddingConfig",
     "GigaChatError",
-]
+    "GigaChatPassthroughConfig",
+)
diff --git a/litellm/llms/gigachat/authenticator.py b/litellm/llms/gigachat/authenticator.py
index 9ef6fe7a93c..73086ba395b 100644
--- a/litellm/llms/gigachat/authenticator.py
+++ b/litellm/llms/gigachat/authenticator.py
@@ -7,6 +7,8 @@ Based on official GigaChat SDK authentication flow.
 
 import time
 import uuid
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Final
 
 import httpx
@@ -16,7 +18,7 @@ from litellm.caching.caching import InMemoryCache
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.custom_httpx.http_handler import (
     HTTPHandler,
-    _get_httpx_client,
+    _get_httpx_client,  # pyright: ignore[reportPrivateUsage]  # house cached-client factory has no public alias
     get_async_httpx_client,
 )
 from litellm.secret_managers.main import get_secret_str
@@ -31,8 +33,8 @@ GIGACHAT_SCOPE: Final = "GIGACHAT_API_PERS"
 # Token expiry buffer in milliseconds (refresh token 60s before expiry)
 TOKEN_EXPIRY_BUFFER_MS: Final = 60000
 
-# Cache for access tokens
 _token_cache: Final = InMemoryCache()
+_NO_LITELLM_PARAMS: Final[Mapping[str, object]] = MappingProxyType({})
 
 
 class GigaChatAuthError(BaseLLMException):
@@ -63,6 +65,7 @@ def get_access_token(
     credentials: str | None = None,
     scope: str | None = None,
     auth_url: str | None = None,
+    litellm_params: Mapping[str, object] | None = None,
 ) -> str:
     """
     Get valid access token, using cache if available.
@@ -78,71 +81,79 @@ def get_access_token(
     Raises:
         GigaChatAuthError: If authentication fails
     """
-    credentials = credentials or _get_credentials()
-    if not credentials:
+    params: Final = litellm_params or _NO_LITELLM_PARAMS
+
+    access_token: Final = params.get("gigachat_access_token") or get_secret_str("GIGACHAT_ACCESS_TOKEN")
+    if access_token:
+        return access_token
+
+    effective_credentials: Final = credentials or _get_credentials()
+    if not effective_credentials:
         raise GigaChatAuthError(
             status_code=401,
             message="GigaChat credentials not provided. Set GIGACHAT_CREDENTIALS or GIGACHAT_API_KEY environment variable.",
         )
 
-    scope = scope or _get_scope()
-    auth_url = auth_url or _get_auth_url()
+    effective_scope: Final = scope or params.get("gigachat_scope") or _get_scope()
+    effective_auth_url: Final = auth_url or params.get("gigachat_auth_url") or _get_auth_url()
 
-    # Check cache
-    cache_key: Final = f"gigachat_token:{credentials[:16]}"
+    cache_key: Final = f"gigachat_token:{effective_credentials[:16]}"
     cached: Final = _token_cache.get_cache(cache_key)
     if cached:
-        token, expires_at = cached
-        # Check if token is still valid (with buffer)
-        if time.time() * 1000 < expires_at - TOKEN_EXPIRY_BUFFER_MS:
+        _token, _expires_at = cached
+        if time.time() * 1000 < _expires_at - TOKEN_EXPIRY_BUFFER_MS:
             verbose_logger.debug("Using cached GigaChat access token")
-            return token
+            return _token
 
-    # Request new token
-    token, expires_at = _request_token_sync(credentials, scope, auth_url)
+    new_token, new_expires_at = _request_token_sync(effective_credentials, effective_scope, effective_auth_url)  # pyright: ignore[reportArgumentType]  # credential keys may be broader than str
 
-    # Cache token
-    ttl_seconds: Final = max(0, (expires_at - TOKEN_EXPIRY_BUFFER_MS - time.time() * 1000) / 1000)
-    if ttl_seconds > 0:
-        _token_cache.set_cache(cache_key, (token, expires_at), ttl=ttl_seconds)
+    if new_expires_at:
+        ttl_seconds: Final = max(0, (new_expires_at - TOKEN_EXPIRY_BUFFER_MS - time.time() * 1000) / 1000)
+        if ttl_seconds > 0:
+            _token_cache.set_cache(cache_key, (new_token, new_expires_at), ttl=ttl_seconds)
 
-    return token
+    return new_token
 
 
 async def get_access_token_async(
     credentials: str | None = None,
     scope: str | None = None,
     auth_url: str | None = None,
+    litellm_params: Mapping[str, object] | None = None,
 ) -> str:
     """Async version of get_access_token."""
-    credentials = credentials or _get_credentials()
-    if not credentials:
+    params: Final = litellm_params or _NO_LITELLM_PARAMS
+
+    access_token: Final = params.get("gigachat_access_token") or get_secret_str("GIGACHAT_ACCESS_TOKEN")
+    if access_token:
+        return access_token
+
+    effective_credentials: Final = credentials or _get_credentials()
+    if not effective_credentials:
         raise GigaChatAuthError(
             status_code=401,
             message="GigaChat credentials not provided. Set GIGACHAT_CREDENTIALS or GIGACHAT_API_KEY environment variable.",
         )
 
-    scope = scope or _get_scope()
-    auth_url = auth_url or _get_auth_url()
+    effective_scope: Final = scope or params.get("gigachat_scope") or _get_scope()
+    effective_auth_url: Final = auth_url or params.get("gigachat_auth_url") or _get_auth_url()
 
-    # Check cache
-    cache_key: Final = f"gigachat_token:{credentials[:16]}"
+    cache_key: Final = f"gigachat_token:{effective_credentials[:16]}"
     cached: Final = _token_cache.get_cache(cache_key)
     if cached:
-        token, expires_at = cached
-        if time.time() * 1000 < expires_at - TOKEN_EXPIRY_BUFFER_MS:
+        _token, _expires_at = cached
+        if time.time() * 1000 < _expires_at - TOKEN_EXPIRY_BUFFER_MS:
             verbose_logger.debug("Using cached GigaChat access token")
-            return token
+            return _token
 
-    # Request new token
-    token, expires_at = await _request_token_async(credentials, scope, auth_url)
+    new_token, new_expires_at = await _request_token_async(effective_credentials, effective_scope, effective_auth_url)  # pyright: ignore[reportArgumentType]  # credential keys may be broader than str
 
-    # Cache token
-    ttl_seconds: Final = max(0, (expires_at - TOKEN_EXPIRY_BUFFER_MS - time.time() * 1000) / 1000)
-    if ttl_seconds > 0:
-        _token_cache.set_cache(cache_key, (token, expires_at), ttl=ttl_seconds)
+    if new_expires_at:
+        ttl_seconds: Final = max(0, (new_expires_at - TOKEN_EXPIRY_BUFFER_MS - time.time() * 1000) / 1000)
+        if ttl_seconds > 0:
+            _token_cache.set_cache(cache_key, (new_token, new_expires_at), ttl=ttl_seconds)
 
-    return token
+    return new_token
 
 
 def _request_token_sync(
@@ -154,7 +165,7 @@ def _request_token_sync(
     Request new access token from GigaChat OAuth endpoint (sync).
 
     Returns:
-        Tuple of (access_token, expires_at_ms)
+        tuple of (access_token, expires_at_ms)
     """
     headers: Final = {
         "Authorization": f"Basic {credentials}",
@@ -169,7 +180,7 @@ def _request_token_sync(
         client: Final = _get_http_client()
         response: Final = client.post(auth_url, headers=headers, data=data, timeout=30)
         response.raise_for_status()
-        return _parse_token_response(response)
+        return _parse_token_response(response)  # pyright: ignore[reportArgumentType]  # httpx Response may be None at type level
     except httpx.HTTPStatusError as e:
         raise GigaChatAuthError(
             status_code=e.response.status_code,
@@ -204,7 +215,7 @@ async def _request_token_async(
         )
         response: Final = await client.post(auth_url, headers=headers, data=data, timeout=30)
         response.raise_for_status()
-        return _parse_token_response(response)
+        return _parse_token_response(response)  # pyright: ignore[reportArgumentType]  # httpx Response may be None at type level
     except httpx.HTTPStatusError as e:
         raise GigaChatAuthError(
             status_code=e.response.status_code,
@@ -223,7 +234,7 @@ def _parse_token_response(response: httpx.Response) -> tuple[str, int]:
 
     # GigaChat returns either 'tok'/'exp' or 'access_token'/'expires_at'
     access_token: Final = data.get("tok") or data.get("access_token")
-    expires_at = data.get("exp") or data.get("expires_at")
+    expires_at_raw: Final = data.get("exp") or data.get("expires_at")
 
     if not access_token:
         raise GigaChatAuthError(
@@ -232,8 +243,11 @@ def _parse_token_response(response: httpx.Response) -> tuple[str, int]:
         )
 
     # expires_at is in milliseconds
-    if isinstance(expires_at, str):
-        expires_at = int(expires_at)
+    expires_at: int  # rebind-ok: conditionally assigned from str or int
+    if isinstance(expires_at_raw, str):
+        expires_at = int(expires_at_raw)  # rebind-ok: conditionally assigned from str or int
+    else:
+        expires_at = expires_at_raw  # pyright: ignore[reportAssignmentType]  # raw value is int or str; converted above; rebind-ok: conditionally assigned from str or int
 
     verbose_logger.debug("GigaChat access token obtained successfully")
     return access_token, expires_at
diff --git a/litellm/llms/gigachat/chat/__init__.py b/litellm/llms/gigachat/chat/__init__.py
index eb9492b90b3..0f9be19fedd 100644
--- a/litellm/llms/gigachat/chat/__init__.py
+++ b/litellm/llms/gigachat/chat/__init__.py
@@ -5,8 +5,8 @@ GigaChat Chat Module
 from .streaming import GigaChatModelResponseIterator
 from .transformation import GigaChatConfig, GigaChatError
 
-__all__ = [
+__all__ = (
     "GigaChatConfig",
     "GigaChatError",
     "GigaChatModelResponseIterator",
-]
+)
diff --git a/litellm/llms/gigachat/chat/streaming.py b/litellm/llms/gigachat/chat/streaming.py
index 219209773ea..0a4cbd8e520 100644
--- a/litellm/llms/gigachat/chat/streaming.py
+++ b/litellm/llms/gigachat/chat/streaming.py
@@ -4,13 +4,15 @@ GigaChat Streaming Response Handler
 
 import json
 import uuid
+from collections.abc import Mapping, Sequence
 from typing import Any, Final
 
+from litellm.llms.gigachat.utils import convert_usage
 from litellm.types.llms.openai import (
     ChatCompletionToolCallChunk,
     ChatCompletionToolCallFunctionChunk,
 )
-from litellm.types.utils import GenericStreamingChunk
+from litellm.types.utils import ChatCompletionUsageBlock, GenericStreamingChunk
 
 
 class GigaChatModelResponseIterator:
@@ -26,14 +28,9 @@ class GigaChatModelResponseIterator:
         self.response_iterator = self.streaming_response
         self.json_mode = json_mode
 
-    def chunk_parser(self, chunk: dict) -> GenericStreamingChunk:
+    def chunk_parser(self, chunk: Mapping[str, object]) -> GenericStreamingChunk:
         """Parse a single streaming chunk from GigaChat."""
-        text = ""
-        tool_use: ChatCompletionToolCallChunk | None = None
-        is_finished = False
-        finish_reason: str | None = None
-
-        choices: Final = chunk.get("choices", [])
+        choices: Sequence = chunk.get("choices") or ()  # mutable-ok: tuple literal as default
         if not choices:
             return GenericStreamingChunk(
                 text="",
@@ -45,40 +42,62 @@ class GigaChatModelResponseIterator:
             )
 
         choice: Final = choices[0]
-        delta: Final = choice.get("delta", {})
-        finish_reason = choice.get("finish_reason")
+        delta: Mapping[str, object] = choice.get("delta") or {}  # mutable-ok: empty dict default for get
+        chunk_finish_reason: Final = choice.get("finish_reason")
 
         # Extract text content
-        text = delta.get("content", "") or ""
+        text: Final = delta.get("content", "") or ""
 
-        # Handle function_call in stream
-        if finish_reason == "function_call" and delta.get("function_call"):
-            func_call: Final = delta["function_call"]
-            args = func_call.get("arguments", {})
+        usage_block: ChatCompletionUsageBlock | None = None  # rebind-ok: conditionally assigned after stop detection
+        tool_use: ChatCompletionToolCallChunk | None = None  # rebind-ok: conditionally assigned on function_call
+        finish_reason: str | None = chunk_finish_reason
 
-            if isinstance(args, dict):
-                args = json.dumps(args, ensure_ascii=False)
+        raw_function_call: Final = delta.get("function_call")
+        if chunk_finish_reason == "function_call" and isinstance(raw_function_call, Mapping) and raw_function_call:
+            func_call: Final[Mapping[str, object]] = raw_function_call
+            args_raw: Final[object] = func_call.get("arguments") or {}
+            args_str: str  # rebind-ok: conditionally assigned from dict or str
+            if isinstance(args_raw, dict):
+                args_str = json.dumps(args_raw, ensure_ascii=False)  # rebind-ok: build from dict
+            else:
+                args_str = str(args_raw)
 
+            name_raw: Final = func_call.get("name")
             tool_use = ChatCompletionToolCallChunk(
                 id=f"call_{uuid.uuid4().hex[:24]}",
                 type="function",
                 function=ChatCompletionToolCallFunctionChunk(
-                    name=func_call.get("name", ""),
-                    arguments=args,
+                    name=name_raw if isinstance(name_raw, str) else "",
+                    arguments=args_str,
                 ),
                 index=0,
             )
             finish_reason = "tool_calls"
 
-        if finish_reason is not None:
-            is_finished = True
+        usage_data: Final = chunk.get("usage") or {}  # mutable-ok: empty dict default
+        if usage_data and isinstance(usage_data, dict):
+            validated_usage: Final = {k: int(v) for k, v in usage_data.items()}
+            usage = convert_usage(validated_usage)
+            _prompt_details: dict | None = (
+                usage.prompt_tokens_details.model_dump() if usage.prompt_tokens_details else None
+            )  # rebind-ok: conditional
+            _completion_details: dict | None = (
+                usage.completion_tokens_details.model_dump() if usage.completion_tokens_details else None
+            )  # rebind-ok: conditional
+            usage_block = ChatCompletionUsageBlock(  # pyright: ignore[reportCallIssue]  # TypedDict kwarg constructor
+                prompt_tokens=usage.prompt_tokens,
+                completion_tokens=usage.completion_tokens,
+                total_tokens=usage.total_tokens,
+                prompt_tokens_details=_prompt_details,
+                completion_tokens_details=_completion_details,
+            )
 
         return GenericStreamingChunk(
-            text=text,
+            text=str(text),
             tool_use=tool_use,
-            is_finished=is_finished,
+            is_finished=chunk_finish_reason is not None,
             finish_reason=finish_reason or "",
-            usage=None,
+            usage=usage_block,
             index=choice.get("index", 0),
         )
 
diff --git a/litellm/llms/gigachat/chat/transformation.py b/litellm/llms/gigachat/chat/transformation.py
index b859a843251..89920ebd27b 100644
--- a/litellm/llms/gigachat/chat/transformation.py
+++ b/litellm/llms/gigachat/chat/transformation.py
@@ -4,19 +4,23 @@ GigaChat Chat Transformation
 Transforms OpenAI-format requests to GigaChat format and back.
 """
 
+from __future__ import annotations
+
 import json
 import time
 import uuid
-from collections.abc import AsyncIterator, Iterator
+from collections.abc import AsyncIterator, Iterator, Mapping, Sequence
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
 
 from litellm._logging import verbose_logger
 from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException
+from litellm.llms.gigachat.utils import convert_usage, get_api_base
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import AllMessageValues
-from litellm.types.utils import Choices, Message, ModelResponse, Usage
+from litellm.types.utils import Choices, Message, ModelResponse
 
 from ..authenticator import get_access_token
 from ..file_handler import upload_file_sync
@@ -30,8 +34,8 @@ if TYPE_CHECKING:
 else:
     LiteLLMLoggingObj = Any
 
-# GigaChat API endpoint
-GIGACHAT_BASE_URL: Final = "https://gigachat.devices.sberbank.ru/api/v1"
+
+_EMPTY_FUNCTION: Final[Mapping[str, object]] = MappingProxyType({})
 
 
 def is_valid_json(value: str) -> bool:
@@ -90,32 +94,30 @@ class GigaChatConfig(BaseConfig):
         api_base: str | None,
         api_key: str | None,
         model: str,
-        optional_params: dict,
-        litellm_params: dict,
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
         stream: bool | None = None,
     ) -> str:
         """Get complete API URL for chat completions."""
-        base: Final = api_base or get_secret_str("GIGACHAT_API_BASE") or GIGACHAT_BASE_URL
+        base: Final = get_api_base(api_base)
         return f"{base}/chat/completions"
 
     def validate_environment(
         self,
-        headers: dict,
+        headers: dict,  # mutable-ok: mutates in place per GigaChat OAuth setup
         model: str,
-        messages: list[AllMessageValues],
-        optional_params: dict,
-        litellm_params: dict,
+        messages: Sequence[AllMessageValues],
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
         api_key: str | None = None,
         api_base: str | None = None,
-    ) -> dict:
+    ) -> dict:  # mutable-ok: base class contract returns dict for httpx
         """
         Set up headers with OAuth token.
         """
-        # Get access token
         credentials: Final = api_key or get_secret_str("GIGACHAT_CREDENTIALS") or get_secret_str("GIGACHAT_API_KEY")
-        access_token: Final = get_access_token(credentials=credentials)
+        access_token: Final = get_access_token(credentials=credentials, litellm_params=litellm_params)
 
-        # Store credentials for image uploads
         self._current_credentials = credentials
         self._current_api_base = api_base
 
@@ -125,9 +127,9 @@ class GigaChatConfig(BaseConfig):
 
         return headers
 
-    def get_supported_openai_params(self, model: str) -> list[str]:
+    def get_supported_openai_params(self, model: str) -> list[str]:  # mutable-ok: base class contract returns list
         """Return list of supported OpenAI parameters."""
-        return [
+        return [  # mutable-ok: base class contract returns list
             "stream",
             "temperature",
             "top_p",
@@ -143,11 +145,11 @@ class GigaChatConfig(BaseConfig):
 
     def map_openai_params(
         self,
-        non_default_params: dict,
-        optional_params: dict,
+        non_default_params: Mapping[str, object],
+        optional_params: dict,  # mutable-ok: mutated in place per GigaChat mapping
         model: str,
         drop_params: bool,
-    ) -> dict:
+    ) -> dict:  # mutable-ok: base class contract returns dict
         """Map OpenAI parameters to GigaChat parameters."""
         for param, value in non_default_params.items():
             if param == "stream":
@@ -167,53 +169,61 @@ class GigaChatConfig(BaseConfig):
                 pass
             elif param == "tools":
                 # Convert tools to functions format
-                optional_params["functions"] = self._convert_tools_to_functions(value)
+                if isinstance(value, Sequence):
+                    optional_params["functions"] = self._convert_tools_to_functions(value)
             elif param == "tool_choice":
                 # Map OpenAI tool_choice to GigaChat function_call
-                mapped_choice = self._map_tool_choice(value)
-                if mapped_choice is not None:
-                    optional_params["function_call"] = mapped_choice
+                if isinstance(value, (str, Mapping)):
+                    mapped_choice = self._map_tool_choice(value)
+                    if mapped_choice is not None:
+                        optional_params["function_call"] = mapped_choice
             elif param == "functions":
                 optional_params["functions"] = value
             elif param == "function_call":
                 optional_params["function_call"] = value
             elif param == "response_format":
                 # Handle structured output via function calling
-                if value.get("type") == "json_schema":
+                if isinstance(value, Mapping) and value.get("type") == "json_schema":
                     json_schema = value.get("json_schema", {})
                     schema_name = json_schema.get("name", "structured_output")
                     schema = json_schema.get("schema", {})
 
-                    function_def = {
+                    function_def = {  # mutable-ok: request payload for httpx
                         "name": schema_name,
                         "description": f"Output structured response: {schema_name}",
                         "parameters": schema,
                     }
 
-                    if "functions" not in optional_params:
-                        optional_params["functions"] = []
-                    optional_params["functions"].append(function_def)
-                    optional_params["function_call"] = {"name": schema_name}
+                    existing_functions = optional_params.get("functions")
+                    optional_params["functions"] = [
+                        *(
+                            existing_functions
+                            if isinstance(existing_functions, Sequence) and not isinstance(existing_functions, str)
+                            else ()
+                        ),
+                        function_def,
+                    ]
+                    optional_params["function_call"] = {"name": schema_name}  # mutable-ok: request payload
                     optional_params["_structured_output"] = True
 
         return optional_params
 
-    def _convert_tools_to_functions(self, tools: list[dict]) -> list[dict]:
+    def _convert_tools_to_functions(self, tools: Sequence) -> Sequence[dict]:
         """Convert OpenAI tools format to GigaChat functions format."""
-        functions: Final = []
-        for tool in tools:
-            if tool.get("type") == "function":
-                func = tool.get("function", {})
-                functions.append(
-                    {
-                        "name": func.get("name", ""),
-                        "description": func.get("description", ""),
-                        "parameters": func.get("parameters", {}),
-                    }
-                )
-        return functions
+        return [
+            {
+                "name": function.get("name", ""),
+                "description": function.get("description", ""),
+                "parameters": function.get("parameters", {}),
+            }
+            for function in (
+                tool.get("function", _EMPTY_FUNCTION)
+                for tool in tools
+                if isinstance(tool, dict) and tool.get("type") == "function"
+            )
+        ]
 
-    def _map_tool_choice(self, tool_choice: str | dict) -> str | dict | None:
+    def _map_tool_choice(self, tool_choice: str | Mapping[str, object]) -> str | Mapping[str, object] | None:
         """
         Map OpenAI tool_choice to GigaChat function_call format.
 
@@ -246,8 +256,9 @@ class GigaChatConfig(BaseConfig):
             # OpenAI format: {"type": "function", "function": {"name": "func_name"}}
             # GigaChat format: {"name": "func_name"}
             if tool_choice.get("type") == "function":
-                func_name: Final = tool_choice.get("function", {}).get("name")
-                if func_name:
+                function_spec: Final = tool_choice.get("function")
+                func_name: Final = function_spec.get("name") if isinstance(function_spec, Mapping) else None
+                if isinstance(func_name, str) and func_name:
                     return {"name": func_name}
 
         # Default to None (don't set function_call)
@@ -273,25 +284,52 @@ class GigaChatConfig(BaseConfig):
             verbose_logger.error("Failed to upload image: %s", e)
             return None
 
+    def _transform_list_content(self, content: Sequence) -> tuple[str, Sequence[str]]:
+        """
+        Extract text and image attachments from a multimodal message content list.
+
+        Args:
+            content: List of content parts (OpenAI multimodal format)
+
+        Returns:
+            Tuple of (combined text, list of attachment file ids)
+        """
+        texts: Final[list[str]] = []  # mutable-ok: accumulator
+        attachments: Final[list[str]] = []  # mutable-ok: accumulator
+        for part in content:
+            if isinstance(part, dict):
+                if part.get("type") == "text":
+                    texts.append(part.get("text", ""))
+                elif part.get("type") == "image_url":
+                    image_url: object = part.get("image_url", {})
+                    upload_url: str
+                    if isinstance(image_url, str):
+                        upload_url = image_url
+                    else:
+                        upload_url = str(image_url.get("url", "")) if isinstance(image_url, dict) else ""
+                    if upload_url:
+                        file_id = self._upload_image(upload_url)
+                        if file_id:
+                            attachments.append(file_id)
+        text: Final = "\n".join(texts) if texts else ""
+        return text, attachments
+
     def transform_request(
         self,
         model: str,
-        messages: list[AllMessageValues],
-        optional_params: dict,
-        litellm_params: dict,
-        headers: dict,
-    ) -> dict:
+        messages: Sequence[AllMessageValues],
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
+        headers: Mapping[str, object],
+    ) -> dict:  # mutable-ok: request payload sent to httpx
         """Transform OpenAI request to GigaChat format."""
-        # Transform messages
         giga_messages: Final = self._transform_messages(messages)
 
-        # Build request
-        request_data: Final = {
+        request_data: Final[dict[str, object]] = {
             "model": model.replace("gigachat/", ""),
             "messages": giga_messages,
         }
 
-        # Add optional params
         for key in [
             "temperature",
             "top_p",
@@ -303,7 +341,6 @@ class GigaChatConfig(BaseConfig):
             if key in optional_params:
                 request_data[key] = optional_params[key]
 
-        # Add functions if present
         if "functions" in optional_params:
             request_data["functions"] = optional_params["functions"]
         if "function_call" in optional_params:
@@ -311,17 +348,15 @@ class GigaChatConfig(BaseConfig):
 
         return request_data
 
-    def _transform_messages(self, messages: list[AllMessageValues]) -> list[dict]:
+    def _transform_messages(self, messages: Sequence[AllMessageValues]) -> Sequence[dict]:
         """Transform OpenAI messages to GigaChat format."""
-        transformed: Final = []
+        transformed: Final[list[dict]] = []  # mutable-ok: accumulator for building transformed messages
 
         for i, msg in enumerate(messages):
             message = dict(msg)
 
-            # Remove unsupported fields
             message.pop("name", None)
 
-            # Transform roles
             role = message.get("role", "user")
             if role == "developer":
                 message["role"] = "system"
@@ -334,35 +369,15 @@ class GigaChatConfig(BaseConfig):
                 if not isinstance(content, str) or not is_valid_json(content):
                     message["content"] = json.dumps(content, ensure_ascii=False)
 
-            # Handle None content
             if message.get("content") is None:
                 message["content"] = ""
 
-            # Handle list content (multimodal) - extract text and images
             content = message.get("content")
             if isinstance(content, list):
-                texts = []
-                attachments = []
-                for part in content:
-                    if isinstance(part, dict):
-                        if part.get("type") == "text":
-                            texts.append(part.get("text", ""))
-                        elif part.get("type") == "image_url":
-                            # Extract image URL and upload to GigaChat
-                            image_url = part.get("image_url", {})
-                            if isinstance(image_url, str):
-                                url = image_url
-                            else:
-                                url = image_url.get("url", "")
-                            if url:
-                                file_id = self._upload_image(url)
-                                if file_id:
-                                    attachments.append(file_id)
-                message["content"] = "\n".join(texts) if texts else ""
+                message["content"], attachments = self._transform_list_content(content)
                 if attachments:
                     message["attachments"] = attachments
 
-            # Transform tool_calls to function_call
             tool_calls = message.get("tool_calls")
             if tool_calls and isinstance(tool_calls, list) and len(tool_calls) > 0:
                 tool_call = tool_calls[0]
@@ -393,7 +408,7 @@ class GigaChatConfig(BaseConfig):
         messages: list[AllMessageValues],
         optional_params: dict,
         litellm_params: dict,
-        encoding: "tiktoken.Encoding | None",
+        encoding: tiktoken.Encoding | None,
         api_key: str | None = None,
         json_mode: bool | None = None,
     ) -> ModelResponse:
@@ -408,18 +423,16 @@ class GigaChatConfig(BaseConfig):
 
         is_structured_output: Final = optional_params.get("_structured_output", False)
 
-        choices: Final = []
+        choices: Final[list[Choices]] = []  # mutable-ok: accumulator for building response choices
         for choice in response_json.get("choices", []):
             message_data = choice.get("message", {})
             finish_reason = choice.get("finish_reason", "stop")
 
-            # Transform function_call to tool_calls or content
             if finish_reason == "function_call" and message_data.get("function_call"):
                 func_call = message_data["function_call"]
                 args = func_call.get("arguments", {})
 
                 if is_structured_output:
-                    # Convert to content for structured output
                     if isinstance(args, dict):
                         content = json.dumps(args, ensure_ascii=False)
                     else:
@@ -429,7 +442,6 @@ class GigaChatConfig(BaseConfig):
                     message_data.pop("functions_state_id", None)
                     finish_reason = "stop"
                 else:
-                    # Convert to tool_calls format
                     if isinstance(args, dict):
                         args = json.dumps(args, ensure_ascii=False)
                     message_data["tool_calls"] = [
@@ -445,7 +457,6 @@ class GigaChatConfig(BaseConfig):
                     message_data.pop("function_call", None)
                     finish_reason = "tool_calls"
 
-            # Clean up GigaChat-specific fields
             message_data.pop("functions_state_id", None)
 
             choices.append(
@@ -462,11 +473,7 @@ class GigaChatConfig(BaseConfig):
 
         # Build usage
         usage_data: Final = response_json.get("usage", {})
-        usage: Final = Usage(
-            prompt_tokens=usage_data.get("prompt_tokens", 0),
-            completion_tokens=usage_data.get("completion_tokens", 0),
-            total_tokens=usage_data.get("total_tokens", 0),
-        )
+        usage: Final = convert_usage(usage_data)
 
         model_response.id = response_json.get("id", f"chatcmpl-{uuid.uuid4().hex[:12]}")
         model_response.created = response_json.get("created", int(time.time()))
diff --git a/litellm/llms/gigachat/embedding/transformation.py b/litellm/llms/gigachat/embedding/transformation.py
index bb495cea423..0db4475be8f 100644
--- a/litellm/llms/gigachat/embedding/transformation.py
+++ b/litellm/llms/gigachat/embedding/transformation.py
@@ -5,6 +5,8 @@ Transforms OpenAI /v1/embeddings format to GigaChat format.
 API Documentation: https://developers.sber.ru/docs/ru/gigachat/api/reference/rest/post-embeddings
 """
 
+from __future__ import annotations
+
 import types
 from typing import Final
 
@@ -14,14 +16,12 @@ from litellm import LlmProviders
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+from litellm.llms.gigachat.utils import get_api_base
 from litellm.types.llms.openai import AllEmbeddingInputValues, AllMessageValues
 from litellm.types.utils import EmbeddingResponse
 
 from ..authenticator import get_access_token
 
-# GigaChat API endpoint
-GIGACHAT_BASE_URL: Final = "https://gigachat.devices.sberbank.ru/api/v1"
-
 
 class GigaChatEmbeddingError(BaseLLMException):
     """GigaChat Embedding API error."""
@@ -78,9 +78,9 @@ class GigaChatEmbeddingConfig(BaseEmbeddingConfig):
         Returns provider info for GigaChat.
 
         Returns:
-            Tuple of (custom_llm_provider, api_base, dynamic_api_key)
+            tuple of (custom_llm_provider, api_base, dynamic_api_key)
         """
-        api_base = api_base or GIGACHAT_BASE_URL
+        api_base = get_api_base(api_base)
         return LlmProviders.GIGACHAT.value, api_base, api_key
 
     def get_complete_url(
@@ -93,7 +93,7 @@ class GigaChatEmbeddingConfig(BaseEmbeddingConfig):
         stream: bool | None = None,
     ) -> str:
         """Get the complete URL for embeddings endpoint."""
-        base: Final = api_base or GIGACHAT_BASE_URL
+        base: Final = get_api_base(api_base)
         return f"{base}/embeddings"
 
     def transform_embedding_request(
@@ -112,20 +112,10 @@ class GigaChatEmbeddingConfig(BaseEmbeddingConfig):
             "input": ["text1", "text2", ...]
         }
         """
-        # Normalize input to list
-        if isinstance(input, str):
-            input_list: list = [input]
-        elif isinstance(input, list):
-            input_list = input
-        else:
-            input_list = [input]
-
-        # Remove gigachat/ prefix from model if present
-        model = model.removeprefix("gigachat/")
-
+        normalized_input: Final = [input] if isinstance(input, str) else input  # mutable-ok: preserve list API
         return {
-            "model": model,
-            "input": input_list,
+            "model": model.removeprefix("gigachat/"),
+            "input": normalized_input,
         }
 
     def transform_embedding_response(
@@ -191,7 +181,7 @@ class GigaChatEmbeddingConfig(BaseEmbeddingConfig):
         Set up headers with OAuth token for GigaChat.
         """
         # Get access token via OAuth
-        access_token: Final = get_access_token(api_key)
+        access_token: Final = get_access_token(credentials=api_key, litellm_params=litellm_params)
 
         default_headers: Final = {
             "Content-Type": "application/json",
diff --git a/litellm/llms/gigachat/file_handler.py b/litellm/llms/gigachat/file_handler.py
index 4cbde551fa2..163e944f124 100644
--- a/litellm/llms/gigachat/file_handler.py
+++ b/litellm/llms/gigachat/file_handler.py
@@ -9,6 +9,7 @@ import base64
 import hashlib
 import re
 import uuid
+from collections.abc import Mapping
 from typing import Final
 
 from litellm._logging import verbose_logger
@@ -16,13 +17,11 @@ from litellm.llms.custom_httpx.http_handler import (
     _get_httpx_client,
     get_async_httpx_client,
 )
+from litellm.llms.gigachat.utils import get_api_base
 from litellm.types.utils import LlmProviders
 
 from .authenticator import get_access_token, get_access_token_async
 
-# GigaChat API endpoint
-GIGACHAT_BASE_URL: Final = "https://gigachat.devices.sberbank.ru/api/v1"
-
 # Simple in-memory cache for file IDs
 _file_cache: Final[dict[str, str]] = {}
 
@@ -82,6 +81,7 @@ def upload_file_sync(
     image_url: str,
     credentials: str | None = None,
     api_base: str | None = None,
+    litellm_params: Mapping[str, object] | None = None,
 ) -> str | None:
     """
     Upload file to GigaChat and return file_id (sync).
@@ -114,10 +114,10 @@ def upload_file_sync(
         filename: Final = f"{uuid.uuid4()}.{ext}"
 
         # Get access token
-        access_token: Final = get_access_token(credentials)
+        access_token: Final = get_access_token(credentials=credentials, litellm_params=litellm_params)
 
         # Upload to GigaChat
-        base_url: Final = api_base or GIGACHAT_BASE_URL
+        base_url: Final = get_api_base(api_base)
         upload_url: Final = f"{base_url}/files"
 
         client: Final = _get_httpx_client(params={"ssl_verify": False})
@@ -147,6 +147,7 @@ async def upload_file_async(
     image_url: str,
     credentials: str | None = None,
     api_base: str | None = None,
+    litellm_params: Mapping[str, object] | None = None,
 ) -> str | None:
     """
     Upload file to GigaChat and return file_id (async).
@@ -179,10 +180,10 @@ async def upload_file_async(
         filename: Final = f"{uuid.uuid4()}.{ext}"
 
         # Get access token
-        access_token: Final = await get_access_token_async(credentials)
+        access_token: Final = await get_access_token_async(credentials=credentials, litellm_params=litellm_params)
 
         # Upload to GigaChat
-        base_url: Final = api_base or GIGACHAT_BASE_URL
+        base_url: Final = get_api_base(api_base)
         upload_url: Final = f"{base_url}/files"
 
         client: Final = get_async_httpx_client(
diff --git a/litellm/llms/gigachat/passthrough/__init__.py b/litellm/llms/gigachat/passthrough/__init__.py
new file mode 100644
index 00000000000..a66a078dbeb
--- /dev/null
+++ b/litellm/llms/gigachat/passthrough/__init__.py
@@ -0,0 +1,7 @@
+"""
+GigaChat passthrough Module
+"""
+
+from .transformation import GigaChatPassthroughConfig
+
+__all__ = ("GigaChatPassthroughConfig",)
diff --git a/litellm/llms/gigachat/passthrough/transformation.py b/litellm/llms/gigachat/passthrough/transformation.py
new file mode 100644
index 00000000000..e1f73d04275
--- /dev/null
+++ b/litellm/llms/gigachat/passthrough/transformation.py
@@ -0,0 +1,211 @@
+from __future__ import annotations
+
+import json
+from collections.abc import Mapping, Sequence
+from typing import TYPE_CHECKING, Final
+
+import httpx
+
+from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
+from litellm.llms.gigachat.authenticator import get_access_token
+from litellm.llms.gigachat.chat.streaming import GigaChatModelResponseIterator
+from litellm.llms.gigachat.utils import GIGACHAT_BASE_URL
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import EmbeddingResponse
+
+if TYPE_CHECKING:
+    from httpx import URL, Response
+
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.types.utils import CostResponseTypes
+
+
+class GigaChatPassthroughConfig(BasePassthroughConfig):
+    def is_streaming_request(self, endpoint: str, request_data: Mapping[str, object]) -> bool:
+        return request_data.get("stream", False)
+
+    def get_complete_url(
+        self,
+        api_base: str | None,
+        api_key: str | None,
+        model: str,
+        endpoint: str,
+        request_query_params: Mapping[str, object] | None,
+        litellm_params: Mapping[str, object],
+    ) -> tuple[URL, str]:
+        """Get complete API URL for chat completions."""
+        base_target_url: Final = self.get_api_base(api_base)
+
+        if base_target_url is None:
+            raise Exception("GigaChat api base not found")
+
+        complete_url: Final = f"{base_target_url}/{endpoint.lstrip('/')}"
+
+        return (
+            httpx.URL(complete_url),
+            base_target_url,
+        )
+
+    def validate_environment(
+        self,
+        headers: dict,  # mutable-ok: mutates in place to set OAuth headers
+        model: str,
+        messages: Sequence[AllMessageValues],
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
+        api_key: str | None = None,
+        api_base: str | None = None,
+    ) -> dict:  # mutable-ok: base class contract returns dict for httpx
+        """
+        Set up headers with OAuth token.
+        """
+        access_token: Final = get_access_token(credentials=api_key, litellm_params=litellm_params)
+
+        headers["Authorization"] = f"Bearer {access_token}"  # rebind-ok: mutating for OAuth setup
+        headers["Content-Type"] = "application/json"  # rebind-ok: mutating for OAuth setup
+        headers["Accept"] = "application/json"  # rebind-ok: mutating for OAuth setup
+
+        return headers
+
+    def logging_non_streaming_response(
+        self,
+        model: str,
+        custom_llm_provider: str,
+        httpx_response: Response,
+        request_data: Mapping[str, object],
+        logging_obj: LiteLLMLoggingObj,
+        endpoint: str,
+    ) -> CostResponseTypes | None:
+        from litellm import encoding
+        from litellm.types.utils import LlmProviders, ModelResponse
+        from litellm.utils import ProviderConfigManager
+
+        if "completions" in endpoint:
+            provider_chat_config: Final = ProviderConfigManager.get_provider_chat_config(
+                provider=LlmProviders(custom_llm_provider),
+                model=model,
+            )
+
+            if provider_chat_config is None:
+                raise ValueError(f"No provider config found for model: {model}")
+
+            raw_messages: Final = request_data.get("messages")
+            litellm_model_response: Final = provider_chat_config.transform_response(
+                model=model,
+                messages=list(raw_messages)
+                if isinstance(raw_messages, list)
+                else [],  # mutable-ok: transform_response wants a list
+                raw_response=httpx_response,
+                model_response=ModelResponse(),
+                logging_obj=logging_obj,
+                optional_params={},  # mutable-ok: empty dict kwarg for transform_response
+                litellm_params={},  # mutable-ok: empty dict kwarg for transform_response
+                api_key="",
+                request_data=dict(request_data),  # mutable-ok: transform_response wants a dict
+                encoding=encoding,
+            )
+
+            return litellm_model_response
+
+        if "embeddings" in endpoint:
+            provider_embedding_config: Final = ProviderConfigManager.get_provider_embedding_config(
+                provider=LlmProviders(custom_llm_provider),
+                model=model,
+            )
+
+            if provider_embedding_config is None:
+                raise ValueError(f"No provider config found for model: {model}")
+
+            litellm_embedding_response: Final[EmbeddingResponse] = (
+                provider_embedding_config.transform_embedding_response(
+                    model=model,
+                    raw_response=httpx_response,
+                    model_response=EmbeddingResponse(),
+                    logging_obj=logging_obj,
+                    optional_params={},  # mutable-ok: empty dict kwarg for transform_embedding_response
+                    api_key="",
+                    request_data=dict(request_data),  # mutable-ok: transform_embedding_response wants a dict
+                    litellm_params={},  # mutable-ok: empty dict kwarg for transform_embedding_response
+                )
+            )
+
+            return litellm_embedding_response
+
+        return None
+
+    def handle_logging_collected_chunks(
+        self,
+        all_chunks: Sequence[str],
+        litellm_logging_obj: LiteLLMLoggingObj,
+        model: str,
+        custom_llm_provider: str,
+        endpoint: str,
+    ) -> CostResponseTypes | None:
+        """
+        1. Convert all_chunks to a ModelResponseStream
+        2. combine model_response_stream to model_response
+        3. Return the model_response
+        """
+
+        from litellm.litellm_core_utils.streaming_handler import (
+            convert_generic_chunk_to_model_response_stream,
+            generic_chunk_has_all_required_fields,
+        )
+        from litellm.main import stream_chunk_builder
+        from litellm.types.utils import ModelResponseStream
+
+        all_translated_chunks: Final[list[object]] = []  # mutable-ok: accumulator
+
+        for chunk in all_chunks:
+            chunk = chunk.strip()
+            if not chunk or chunk == "[DONE]":
+                continue
+            chunk = chunk.removeprefix("data: ")
+            try:
+                message = json.loads(chunk)
+            except json.JSONDecodeError:
+                continue
+
+            gigachat_iterator = GigaChatModelResponseIterator(
+                streaming_response=None,
+                sync_stream=False,
+            )
+            translated_chunk = gigachat_iterator.chunk_parser(chunk=message)
+
+            if isinstance(translated_chunk, dict) and generic_chunk_has_all_required_fields(  # pyright: ignore[reportUnnecessaryIsInstance]  # runtime guard for patched chunk_parser
+                dict(translated_chunk)
+            ):
+                chunk_obj = convert_generic_chunk_to_model_response_stream(
+                    translated_chunk  # pyright: ignore[reportArgumentType]  # validated TypedDict
+                )
+            elif isinstance(translated_chunk, ModelResponseStream):
+                chunk_obj = translated_chunk
+            else:
+                continue
+
+            all_translated_chunks.append(chunk_obj)
+
+        if len(all_translated_chunks) > 0:
+            return stream_chunk_builder(
+                chunks=all_translated_chunks,
+                logging_obj=litellm_logging_obj,
+            )
+        return None
+
+    @staticmethod
+    def get_api_base(api_base: str | None = None) -> str | None:
+        return api_base or get_secret_str("GIGACHAT_API_BASE") or GIGACHAT_BASE_URL
+
+    @staticmethod
+    def get_api_key(
+        api_key: str | None = None,
+    ) -> str | None:
+        return api_key or get_secret_str("GIGACHAT_API_KEY")
+
+    @staticmethod
+    def get_base_model(model: str) -> str | None:
+        return model
+
+    def get_models(self, api_key: str | None = None, api_base: str | None = None) -> list[str]:
+        return list(super().get_models(api_key, api_base))
diff --git a/litellm/llms/gigachat/utils.py b/litellm/llms/gigachat/utils.py
new file mode 100644
index 00000000000..ce7e848ed7f
--- /dev/null
+++ b/litellm/llms/gigachat/utils.py
@@ -0,0 +1,25 @@
+from collections.abc import Mapping
+from typing import Final
+
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.utils import PromptTokensDetailsWrapper, Usage
+
+GIGACHAT_BASE_URL: Final = "https://gigachat.devices.sberbank.ru/api/v1"
+
+
+def convert_usage(usage_data: Mapping[str, int]) -> Usage:
+    precached_prompt_tokens: Final = usage_data.get("precached_prompt_tokens", 0)
+    prompt_tokens_details: Final = (
+        PromptTokensDetailsWrapper(cached_tokens=precached_prompt_tokens) if precached_prompt_tokens > 0 else None
+    )
+
+    return Usage(
+        prompt_tokens=usage_data.get("prompt_tokens", 0) + precached_prompt_tokens,
+        completion_tokens=usage_data.get("completion_tokens", 0),
+        prompt_tokens_details=prompt_tokens_details,
+        total_tokens=usage_data.get("total_tokens", 0) + precached_prompt_tokens,
+    )
+
+
+def get_api_base(api_base: str | None = None) -> str | None:
+    return api_base or get_secret_str("GIGACHAT_API_BASE") or GIGACHAT_BASE_URL
diff --git a/litellm/llms/hosted_vllm/embedding/README.md b/litellm/llms/hosted_vllm/embedding/README.md
index 2c58e16fc23..50474aabdeb 100644
--- a/litellm/llms/hosted_vllm/embedding/README.md
+++ b/litellm/llms/hosted_vllm/embedding/README.md
@@ -4,13 +4,12 @@ VLLM is a superset of OpenAI's `embedding` endpoint.
 
 ## `encoding_format`
 
-For OpenAI-compatible embedding calls (including `openai/...` with a custom `api_base` pointing at vLLM), LiteLLM resolves `encoding_format` when it is not set on the request:
+For OpenAI-compatible embedding calls (including `openai/...` with a custom `api_base` pointing at vLLM), LiteLLM resolves `encoding_format` when it is not set on the request. `hosted_vllm/...` models use a separate handler that never adds the field on its own, so this resolution applies to the `openai/...`-style routes only:
 
 1. Explicit value on the embedding call (`encoding_format=...`).
 2. Model config (`litellm_params.encoding_format` on the proxy `model_list` entry).
 3. Environment variable `LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT` (e.g. in `.env` or container env).
-4. Default **`float`**.
 
-That avoids forwarding `encoding_format=None` to the provider/SDK where some servers behave poorly.
+If none of those is set, or the winning value is the literal string `none`, the field is omitted from the upstream request entirely (LiteLLM also bypasses the OpenAI SDK's own base64 default), so OpenAI-compatible servers that reject `encoding_format` keep working.
 
-To pass provider-specific parameters, see [provider-specific params](https://docs.litellm.ai/docs/completion/provider_specific_params).
\ No newline at end of file
+To pass provider-specific parameters, see [provider-specific params](https://docs.litellm.ai/docs/completion/provider_specific_params).
diff --git a/litellm/llms/hosted_vllm/rerank/transformation.py b/litellm/llms/hosted_vllm/rerank/transformation.py
index 0e8fa294f5d..764d80c6f82 100644
--- a/litellm/llms/hosted_vllm/rerank/transformation.py
+++ b/litellm/llms/hosted_vllm/rerank/transformation.py
@@ -3,16 +3,20 @@ Transformation logic for Hosted VLLM rerank
 """
 
 from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Any, Final
 
 import httpx
+from pydantic import ValidationError
 
 from litellm._uuid import uuid
+from litellm.exceptions import UnsupportedParamsError
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.rerank import (
+    HostedVLLMRerankTruncationParams,
     OptionalRerankParams,
     RerankBilledUnits,
     RerankRequest,
@@ -34,6 +38,13 @@ class HostedVLLMRerankError(BaseLLMException):
         super().__init__(status_code=status_code, message=message, headers=headers)
 
 
+def validated_truncation_params(non_default_params: Mapping[str, object] | None) -> HostedVLLMRerankTruncationParams:
+    try:
+        return HostedVLLMRerankTruncationParams.model_validate(non_default_params or MappingProxyType({}))
+    except ValidationError as error:
+        raise UnsupportedParamsError(status_code=400, message=f"hosted_vllm rerank: {error}") from error
+
+
 class HostedVLLMRerankConfig(BaseRerankConfig):
     def __init__(self) -> None:
         pass
@@ -62,7 +73,11 @@ class HostedVLLMRerankConfig(BaseRerankConfig):
             "top_n",
             "rank_fields",
             "return_documents",
+            "max_tokens_per_doc",
             "instruction",
+            "truncate_prompt_tokens",
+            "truncation_side",
+            "max_tokens_per_query",
         ]
 
     def map_cohere_rerank_params(
@@ -100,7 +115,15 @@ class HostedVLLMRerankConfig(BaseRerankConfig):
         if instruction is not None:
             mapped_params["instruction"] = instruction
 
-        return dict(mapped_params)
+        truncation: Final = validated_truncation_params(non_default_params)
+        forwarded: Final[OptionalRerankParams] = {
+            **mapped_params,
+            "max_tokens_per_doc": max_tokens_per_doc,
+            "truncate_prompt_tokens": truncation.truncate_prompt_tokens,
+            "truncation_side": truncation.truncation_side,
+            "max_tokens_per_query": truncation.max_tokens_per_query,
+        }
+        return dict(forwarded)
 
     def validate_environment(
         self,
@@ -138,6 +161,7 @@ class HostedVLLMRerankConfig(BaseRerankConfig):
         if "documents" not in optional_rerank_params:
             raise ValueError("documents is required for Hosted VLLM rerank")
 
+        truncation: Final = HostedVLLMRerankTruncationParams.model_validate(optional_rerank_params)
         rerank_request: Final = RerankRequest(
             model=model,
             query=optional_rerank_params["query"],
@@ -146,6 +170,10 @@ class HostedVLLMRerankConfig(BaseRerankConfig):
             rank_fields=optional_rerank_params.get("rank_fields", None),
             return_documents=optional_rerank_params.get("return_documents", None),
             instruction=optional_rerank_params.get("instruction", None),
+            max_tokens_per_doc=truncation.max_tokens_per_doc,
+            truncate_prompt_tokens=truncation.truncate_prompt_tokens,
+            truncation_side=truncation.truncation_side,
+            max_tokens_per_query=truncation.max_tokens_per_query,
         )
         return rerank_request.model_dump(exclude_none=True)
 
diff --git a/litellm/llms/huggingface/embedding/transformation.py b/litellm/llms/huggingface/embedding/transformation.py
index d3db3530109..f6fe7f2fa10 100644
--- a/litellm/llms/huggingface/embedding/transformation.py
+++ b/litellm/llms/huggingface/embedding/transformation.py
@@ -1,8 +1,9 @@
 import json
 import os
 import time
+from collections.abc import Sequence
 from copy import deepcopy
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 
 import httpx
 
@@ -24,6 +25,8 @@ from litellm.utils import token_counter
 from ..common_utils import HuggingFaceError, hf_task_list, hf_tasks, output_parser
 
 if TYPE_CHECKING:
+    import tiktoken
+
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 
     LoggingClass = LiteLLMLoggingObj
@@ -31,6 +34,12 @@ else:
     LoggingClass = Any
 
 
+class _TokenEncoding(Protocol):
+    """Tokenizer handle the caller passes in; only `encode` is used, to count completion tokens."""
+
+    def encode(self, text: str, /) -> Sequence[object]: ...
+
+
 tgi_models_cache = None
 conv_models_cache = None
 
@@ -369,7 +378,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         model_response: ModelResponse,
         task: hf_tasks | None,
         optional_params: dict,
-        encoding: Any,
+        encoding: "_TokenEncoding | None",
         messages: list[AllMessageValues],
         model: str,
     ):
@@ -439,9 +448,10 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         if output_text is not None and len(output_text) > 0:
             completion_tokens = 0
             try:
-                completion_tokens = len(
-                    encoding.encode(model_response["choices"][0]["message"].get("content", ""))
-                )  ##[TODO] use the llama2 tokenizer here
+                if encoding is not None:
+                    completion_tokens = len(
+                        encoding.encode(model_response["choices"][0]["message"].get("content", ""))
+                    )  ##[TODO] use the llama2 tokenizer here
             except Exception:
                 # this should remain non blocking we should not block a response returning if calculating usage fails
                 pass
@@ -469,7 +479,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         messages: list[AllMessageValues],
         optional_params: dict,
         litellm_params: dict,
-        encoding: Any,
+        encoding: "tiktoken.Encoding | None",
         api_key: str | None = None,
         json_mode: bool | None = None,
     ) -> ModelResponse:
diff --git a/litellm/llms/infinity/rerank/transformation.py b/litellm/llms/infinity/rerank/transformation.py
index 2526eb3b6a4..e089b3fecbe 100644
--- a/litellm/llms/infinity/rerank/transformation.py
+++ b/litellm/llms/infinity/rerank/transformation.py
@@ -4,10 +4,11 @@ Transformation logic from Cohere's /v1/rerank format to Infinity's  `/v1/rerank`
 Why separate file? Make it easy to see how transformation works
 """
 
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from typing import Final
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm._uuid import uuid
@@ -26,6 +27,31 @@ from litellm.types.rerank import (
 from ..common_utils import InfinityError
 
 
+class _InfinityRerankUsage(TypedDict, extra_items=ReadOnly[int]):
+    """The token counters Infinity reports in the ``usage`` block of a rerank response."""
+
+
+class _InfinityRerankResult(TypedDict):
+    """One scored document in an Infinity ``/v1/rerank`` response."""
+
+    index: ReadOnly[int]
+    relevance_score: ReadOnly[float]
+    document: ReadOnly[str]
+
+
+class _InfinityRerankResponse(TypedDict):
+    """The JSON body returned by Infinity's ``/v1/rerank`` endpoint."""
+
+    id: ReadOnly[NotRequired[str]]
+    usage: ReadOnly[NotRequired[_InfinityRerankUsage]]
+    results: ReadOnly[Sequence[_InfinityRerankResult]]
+
+
+def _parse_rerank_response(raw_response: httpx.Response) -> _InfinityRerankResponse:
+    """Read the untyped JSON body of an Infinity rerank response."""
+    return raw_response.json()
+
+
 class InfinityRerankConfig(CohereRerankConfig):
     def get_complete_url(
         self,
@@ -82,7 +108,7 @@ class InfinityRerankConfig(CohereRerankConfig):
         No transformation required, Infinity follows Cohere API response format
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _parse_rerank_response(raw_response)
         except Exception:
             raise InfinityError(message=raw_response.text, status_code=raw_response.status_code)
 
diff --git a/litellm/llms/langflow/a2a.py b/litellm/llms/langflow/a2a.py
index cae750d586e..060dc0a4d05 100644
--- a/litellm/llms/langflow/a2a.py
+++ b/litellm/llms/langflow/a2a.py
@@ -1,28 +1,9 @@
-import hashlib
 from typing import Any, Final
 
-
-def get_session_id_from_a2a_params(params: dict[str, Any]) -> str | None:
-    message: Final = params.get("message", {})
-    if isinstance(message, dict):
-        return message.get("contextId")
-    return getattr(message, "contextId", None)
-
-
-def scope_session_to_principal(session_id: str, principal: str | None) -> str:
-    """
-    Bind a client-supplied A2A contextId to the authenticated principal.
-
-    Without this, two distinct keys authorized for the same LangFlow agent could
-    set the same contextId and read/append to each other's LangFlow memory. The
-    principal is hashed (it is already a hashed token) so the raw value is never
-    sent to the LangFlow backend, while the original contextId is kept as a
-    suffix for operator-side correlation.
-    """
-    if not principal:
-        return session_id
-    principal_prefix: Final = hashlib.sha256(principal.encode("utf-8")).hexdigest()[:16]
-    return f"{principal_prefix}-{session_id}"
+from litellm.a2a_protocol.utils import (
+    get_session_id_from_a2a_params,
+    scope_session_to_principal,
+)
 
 
 def merge_a2a_session_into_litellm_params(
diff --git a/litellm/llms/litellm_proxy/skills/code_execution.py b/litellm/llms/litellm_proxy/skills/code_execution.py
index d435994ce20..fbc287589b3 100644
--- a/litellm/llms/litellm_proxy/skills/code_execution.py
+++ b/litellm/llms/litellm_proxy/skills/code_execution.py
@@ -13,12 +13,111 @@ Generated files are returned directly in the response - no separate storage need
 
 import base64
 import json
+from collections.abc import Mapping, Sequence
 from enum import Enum
-from typing import Any, Final
+from typing import Any, Final, Protocol, TypedDict
+
+from typing_extensions import ReadOnly
 
 from litellm._logging import verbose_logger
 
 
+class _ToolParameterSchema(TypedDict, total=False):
+    type: ReadOnly[str]
+    description: ReadOnly[str]
+
+
+class _ToolArgumentSchema(TypedDict, total=False):
+    type: ReadOnly[str]
+    properties: ReadOnly[Mapping[str, _ToolParameterSchema]]
+    required: ReadOnly[Sequence[str]]
+
+
+class _OpenAIToolFunction(TypedDict, total=False):
+    name: ReadOnly[str]
+    description: ReadOnly[str]
+    parameters: ReadOnly[_ToolArgumentSchema]
+
+
+class _OpenAIToolSpec(TypedDict, total=False):
+    type: ReadOnly[str]
+    function: ReadOnly[_OpenAIToolFunction]
+
+
+class _AnthropicToolSpec(TypedDict, total=False):
+    name: ReadOnly[str]
+    description: ReadOnly[str]
+    input_schema: ReadOnly[_ToolArgumentSchema]
+
+
+class _CodeExecutionArguments(TypedDict, total=False):
+    code: ReadOnly[str]
+
+
+class _GeneratedFile(TypedDict, total=False):
+    name: ReadOnly[str]
+    mime_type: ReadOnly[str]
+    content_base64: ReadOnly[str]
+    size: ReadOnly[int]
+
+
+class _SandboxGeneratedFile(TypedDict):
+    name: ReadOnly[str]
+    mime_type: ReadOnly[str]
+    content_base64: ReadOnly[str]
+
+
+class _SandboxExecutionResult(TypedDict):
+    success: ReadOnly[bool]
+    output: ReadOnly[str]
+    error: ReadOnly[str]
+    files: ReadOnly[Sequence[_SandboxGeneratedFile]]
+
+
+class _ExecutionResult(TypedDict, total=False):
+    iteration: ReadOnly[int]
+    success: ReadOnly[bool]
+    output: ReadOnly[str]
+    error: ReadOnly[str]
+    files: ReadOnly[Sequence[str]]
+
+
+class _ToolCallFunction(Protocol):
+    name: str
+    arguments: str
+
+
+class _ToolCall(Protocol):
+    id: str
+    function: _ToolCallFunction
+
+
+class _AssistantMessage(Protocol):
+    content: str | None
+    tool_calls: Sequence[_ToolCall] | None
+
+
+class _ResponseChoice(Protocol):
+    message: _AssistantMessage
+    finish_reason: str | None
+
+
+class _CompletionResponse(Protocol):
+    choices: Sequence[_ResponseChoice]
+
+
+class _CodeExecutionOutcome(TypedDict, total=False):
+    response: ReadOnly[_CompletionResponse | None]
+    files: ReadOnly[Sequence[_GeneratedFile]]
+    execution_results: ReadOnly[Sequence[_ExecutionResult]]
+    messages: ReadOnly[Sequence[dict[str, object]]]
+    max_iterations_reached: ReadOnly[bool]
+
+
+def _parse_code_execution_arguments(serialized_arguments: str) -> _CodeExecutionArguments:
+    return json.loads(serialized_arguments)
+
+
 class LiteLLMInternalTools(str, Enum):
     """
     Enum for internal LiteLLM tools that are injected into requests.
@@ -30,7 +129,7 @@ class LiteLLMInternalTools(str, Enum):
     CODE_EXECUTION = "litellm_code_execution"
 
 
-def get_litellm_code_execution_tool() -> dict[str, Any]:
+def get_litellm_code_execution_tool() -> _OpenAIToolSpec:
     """
     Returns the litellm_code_execution tool definition in OpenAI format.
 
@@ -51,7 +150,7 @@ def get_litellm_code_execution_tool() -> dict[str, Any]:
     }
 
 
-def get_litellm_code_execution_tool_anthropic() -> dict[str, Any]:
+def get_litellm_code_execution_tool_anthropic() -> _AnthropicToolSpec:
     """
     Returns the litellm_code_execution tool definition in Anthropic/messages API format.
 
@@ -98,12 +197,12 @@ class CodeExecutionHandler:
     async def execute_with_code_execution(
         self,
         model: str,
-        messages: list[dict],
-        tools: list[dict],
+        messages: list[dict[str, object]],
+        tools: list[_OpenAIToolSpec],
         skill_files: dict[str, bytes],
         skill_id: str | None = None,
         **kwargs,
-    ) -> dict[str, Any]:
+    ) -> _CodeExecutionOutcome:
         """
         Execute an LLM call with automatic code execution handling.
 
@@ -134,8 +233,8 @@ class CodeExecutionHandler:
         )
 
         current_messages: Final = list(messages)
-        generated_files: Final[list[dict[str, Any]]] = []  # Files returned directly
-        execution_results: Final[list[dict]] = []
+        generated_files: Final[list[_GeneratedFile]] = []  # Files returned directly
+        execution_results: Final[list[_ExecutionResult]] = []
 
         executor: Final = SkillsSandboxExecutor(timeout=self.sandbox_timeout)
         response: Any = None  # Initialize to avoid possibly unbound error
@@ -151,11 +250,12 @@ class CodeExecutionHandler:
                 **kwargs,
             )
 
-            assistant_message = response.choices[0].message
-            stop_reason = response.choices[0].finish_reason
+            choice: _ResponseChoice = response.choices[0]
+            assistant_message = choice.message
+            stop_reason = choice.finish_reason
 
             # Build assistant message for conversation history
-            assistant_msg_dict: dict[str, Any] = {
+            assistant_msg_dict: dict[str, object] = {
                 "role": "assistant",
                 "content": assistant_message.content,
             }
@@ -190,25 +290,27 @@ class CodeExecutionHandler:
                 if tool_name == LiteLLMInternalTools.CODE_EXECUTION.value:
                     # Execute code in sandbox
                     try:
-                        args = json.loads(tool_call.function.arguments)
+                        args = _parse_code_execution_arguments(tool_call.function.arguments)
                         code = args.get("code", "")
 
                         verbose_logger.debug("CodeExecutionHandler: Executing code (%s chars)", len(code))
 
-                        exec_result = executor.execute(
+                        exec_result: _SandboxExecutionResult = executor.execute(
                             code=code,
                             skill_files=skill_files,
                         )
 
                         verbose_logger.debug("CodeExecutionHandler: Execution result: %s", exec_result)
 
+                        sandbox_files: Sequence[_SandboxGeneratedFile] = exec_result["files"]
+
                         execution_results.append(
                             {
                                 "iteration": iteration,
                                 "success": exec_result["success"],
                                 "output": exec_result["output"],
                                 "error": exec_result["error"],
-                                "files": [f["name"] for f in exec_result["files"]],
+                                "files": [f["name"] for f in sandbox_files],
                             }
                         )
 
@@ -216,9 +318,9 @@ class CodeExecutionHandler:
                         tool_result = exec_result["output"] or ""
 
                         # Collect generated files (returned directly, no storage)
-                        if exec_result["files"]:
+                        if sandbox_files:
                             tool_result += "\n\nGenerated files:"
-                            for f in exec_result["files"]:
+                            for f in sandbox_files:
                                 file_content = base64.b64decode(f["content_base64"])
                                 # Add to generated files list (returned in response)
                                 generated_files.append(
@@ -278,7 +380,7 @@ class CodeExecutionHandler:
         }
 
 
-def has_code_execution_tool(tools: list[dict] | None) -> bool:
+def has_code_execution_tool(tools: list[_OpenAIToolSpec] | None) -> bool:
     """Check if litellm_code_execution tool is in the tools list."""
     if not tools:
         return False
@@ -289,7 +391,7 @@ def has_code_execution_tool(tools: list[dict] | None) -> bool:
     return False
 
 
-def add_code_execution_tool(tools: list[dict] | None) -> list[dict]:
+def add_code_execution_tool(tools: list[_OpenAIToolSpec] | None) -> list[_OpenAIToolSpec]:
     """Add litellm_code_execution tool if not already present."""
     tools = tools or []
     if not has_code_execution_tool(tools):
diff --git a/litellm/llms/milvus/vector_stores/transformation.py b/litellm/llms/milvus/vector_stores/transformation.py
index 34f0cd854c4..c3581abfbcc 100644
--- a/litellm/llms/milvus/vector_stores/transformation.py
+++ b/litellm/llms/milvus/vector_stores/transformation.py
@@ -19,6 +19,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -123,6 +124,7 @@ class MilvusVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, Any]]:
         """
         Transform search request for Azure AI Search API
diff --git a/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py
index 008a5a5780f..046b4e29a0a 100644
--- a/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py
+++ b/litellm/llms/nvidia_riva/audio_transcription/audio_utils.py
@@ -16,7 +16,7 @@ import io
 import os
 import tempfile
 from dataclasses import dataclass
-from typing import Any, Final, cast
+from typing import Final, Protocol, cast
 
 from litellm.llms.nvidia_riva.audio_transcription.transformation import (
     RIVA_TARGET_NUM_CHANNELS,
@@ -24,10 +24,30 @@ from litellm.llms.nvidia_riva.audio_transcription.transformation import (
 )
 from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException
 
-# Keep this as Any: the module intentionally avoids importing numpy at module
-# import time (optional dependency), and project-wide mypy config evaluates this
-# file in contexts where conditional type aliases can degrade to "FloatArray?".
-FloatArray = Any
+
+class FloatArray(Protocol):
+    """Structural view of the ``numpy.ndarray`` surface this module relies on."""
+
+    @property
+    def ndim(self) -> int: ...
+
+    @property
+    def shape(self) -> tuple[int, ...]: ...
+
+    @property
+    def size(self) -> int: ...
+
+    def mean(self, axis: int) -> "FloatArray": ...
+
+    def ravel(self) -> "FloatArray": ...
+
+    def astype(self, dtype: object) -> "FloatArray": ...
+
+    def tobytes(self) -> bytes: ...
+
+    def __getitem__(self, key: object) -> "FloatArray": ...
+
+    def __mul__(self, other: float) -> "FloatArray": ...
 
 
 _INSTALL_HINT = "Install Riva STT extras to enable automatic audio resampling: `pip install 'litellm[stt-nvidia-riva]'`"
diff --git a/litellm/llms/oci/chat/cohere.py b/litellm/llms/oci/chat/cohere.py
index 384e7ec4cf8..6e9bb83b0a0 100644
--- a/litellm/llms/oci/chat/cohere.py
+++ b/litellm/llms/oci/chat/cohere.py
@@ -9,7 +9,7 @@ response parsing, and streaming chunk parsing for models served with
 import datetime
 import json
 from collections.abc import Iterable, Mapping, Sequence
-from typing import Any, Final
+from typing import Final
 
 import httpx
 from pydantic import JsonValue, TypeAdapter, ValidationError
@@ -76,7 +76,7 @@ def _content_text(content: str | Iterable[Mapping[str, object]] | None) -> str:
     return str(content)
 
 
-def _extract_text_content(content: Any) -> str:
+def _extract_text_content(content: str | Iterable[Mapping[str, object]] | None) -> str:
     """Return the plain-text representation of a message content value."""
     return _content_text(content)
 
diff --git a/litellm/llms/oci/common_utils.py b/litellm/llms/oci/common_utils.py
index 5c3962bc05d..3f703564b5a 100644
--- a/litellm/llms/oci/common_utils.py
+++ b/litellm/llms/oci/common_utils.py
@@ -5,10 +5,11 @@ import os
 import re
 from dataclasses import dataclass
 from email.utils import formatdate
-from typing import Any, Final, Protocol
+from typing import Final, Protocol
 from urllib.parse import urlparse
 
 import httpx
+from pydantic import JsonValue
 
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
 
@@ -64,7 +65,7 @@ class OCISignerProtocol(Protocol):
     See: https://docs.oracle.com/en-us/iaas/tools/python/latest/api/signing.html
     """
 
-    def do_request_sign(self, request: Any, *, enforce_content_headers: bool = False) -> None:
+    def do_request_sign(self, request: "OCIRequestWrapper", *, enforce_content_headers: bool = False) -> None:
         pass
 
 
@@ -113,7 +114,7 @@ def build_signature_string(method: str, path: str, headers: dict, signed_headers
     return "\n".join(lines)
 
 
-def load_private_key_from_str(key_str: str) -> Any:
+def load_private_key_from_str(key_str: str) -> "rsa.RSAPrivateKey":
     _require_cryptography()
     key: Final = serialization.load_pem_private_key(
         key_str.encode("utf-8"),
@@ -124,7 +125,7 @@ def load_private_key_from_str(key_str: str) -> Any:
     return key
 
 
-def load_private_key_from_file(file_path: str) -> Any:
+def load_private_key_from_file(file_path: str) -> "rsa.RSAPrivateKey":
     """Loads a private key from a file path."""
     try:
         with open(file_path, "r", encoding="utf-8") as f:
@@ -421,16 +422,17 @@ OCI_JSON_TO_PYTHON_TYPES: Final[dict[str, str]] = {
 }
 
 
-def resolve_oci_schema_refs(schema: dict[str, Any]) -> dict[str, Any]:
+def resolve_oci_schema_refs(schema: JsonValue) -> JsonValue:
     """Inline all ``$ref``/``$defs`` references — OCI does not support JSON Schema ``$ref``."""
-    defs: Final = schema.get("$defs", {})
-    resolving_stack: Final[set] = set()
+    raw_defs: Final = schema.get("$defs") if isinstance(schema, dict) else None
+    defs: Final[dict[str, JsonValue]] = raw_defs if isinstance(raw_defs, dict) else {}
+    resolving_stack: Final[set[str]] = set()
 
-    def _resolve(obj: Any) -> Any:
+    def _resolve(obj: JsonValue) -> JsonValue:
         if isinstance(obj, dict):
-            if "$ref" in obj:
-                ref: Final = obj["$ref"]
-                if ref.startswith("#/$defs/"):
+            ref: Final = obj.get("$ref")
+            if ref is not None:
+                if isinstance(ref, str) and ref.startswith("#/$defs/"):
                     key: Final = ref.split("/")[-1]
                     if key in resolving_stack:
                         return {"type": "object"}  # break cycles
@@ -451,7 +453,7 @@ def resolve_oci_schema_refs(schema: dict[str, Any]) -> dict[str, Any]:
     return resolved
 
 
-def resolve_oci_schema_anyof(obj: Any) -> Any:
+def resolve_oci_schema_anyof(obj: JsonValue) -> JsonValue:
     """Resolve Pydantic v2 ``Optional[T]`` → ``anyOf`` patterns.
 
     Pydantic v2 emits ``{"anyOf": [{"type": "T"}, {"type": "null"}]}`` for
@@ -459,10 +461,13 @@ def resolve_oci_schema_anyof(obj: Any) -> Any:
     first non-null branch and merge top-level metadata into it.
     """
     if isinstance(obj, dict):
-        if "anyOf" in obj and "type" not in obj:
-            non_null: Final = [t for t in obj["anyOf"] if not (isinstance(t, dict) and t.get("type") == "null")]
+        raw_any_of: Final = obj.get("anyOf")
+        if raw_any_of is not None and "type" not in obj:
+            branches: Final = raw_any_of if isinstance(raw_any_of, list) else []
+            non_null: Final = [t for t in branches if not (isinstance(t, dict) and t.get("type") == "null")]
             if non_null:
-                resolved: Final = {**obj, **non_null[0]}
+                first: Final = non_null[0]
+                resolved: Final[dict[str, JsonValue]] = {**obj, **first} if isinstance(first, dict) else {**obj}
                 resolved.pop("anyOf", None)
                 return resolve_oci_schema_anyof(resolved)
         return {k: resolve_oci_schema_anyof(v) for k, v in obj.items()}
@@ -471,7 +476,7 @@ def resolve_oci_schema_anyof(obj: Any) -> Any:
     return obj
 
 
-def sanitize_oci_schema(schema: Any) -> Any:
+def sanitize_oci_schema(schema: JsonValue) -> JsonValue:
     """Recursively remove OCI-incompatible fields from a JSON schema.
 
     Strips ``title`` keys, removes ``None``-valued ``default`` entries,
@@ -483,7 +488,7 @@ def sanitize_oci_schema(schema: Any) -> Any:
     if not isinstance(schema, dict):
         return schema
 
-    sanitized: Final[dict[str, Any]] = {}
+    sanitized: Final[dict[str, JsonValue]] = {}
     for key, value in schema.items():
         if key == "title":
             continue
@@ -513,7 +518,7 @@ def sanitize_oci_schema(schema: Any) -> Any:
     return sanitized
 
 
-def enrich_cohere_param_description(description: str, param_schema: dict[str, Any]) -> str:
+def enrich_cohere_param_description(description: str, param_schema: dict[str, JsonValue]) -> str:
     """Embed schema constraints into a Cohere parameter description.
 
     ``CohereParameterDefinition`` only has ``type``, ``description``, and
diff --git a/litellm/llms/ollama/chat/transformation.py b/litellm/llms/ollama/chat/transformation.py
index de626b468f0..181894646e3 100644
--- a/litellm/llms/ollama/chat/transformation.py
+++ b/litellm/llms/ollama/chat/transformation.py
@@ -423,6 +423,7 @@ class OllamaChatConfig(BaseConfig):
 class OllamaChatCompletionResponseIterator(BaseModelResponseIterator):
     started_reasoning_content: bool = False
     finished_reasoning_content: bool = False
+    seen_tool_calls: bool = False
 
     def _is_function_call_complete(self, function_args: str | dict) -> bool:
         if isinstance(function_args, dict):
@@ -468,6 +469,7 @@ class OllamaChatCompletionResponseIterator(BaseModelResponseIterator):
             # process tool calls - if complete function arg - add id to tool call
             tool_calls: Final = chunk["message"].get("tool_calls")
             if tool_calls is not None:
+                self.seen_tool_calls = True
                 for tool_call in tool_calls:
                     function_args = tool_call.get("function").get("arguments")
                     if function_args is not None and len(function_args) > 0:
@@ -508,9 +510,10 @@ class OllamaChatCompletionResponseIterator(BaseModelResponseIterator):
 
             if chunk["done"] is True:
                 finish_reason = chunk.get("done_reason") or "stop"
-                # Override finish_reason when tool_calls are present
+                # Override finish_reason when tool_calls appeared in any chunk
                 # Fixes: https://github.com/BerriAI/litellm/issues/18922
-                if tool_calls is not None:
+                # Fixes: https://github.com/BerriAI/litellm/issues/34692
+                if self.seen_tool_calls:
                     finish_reason = "tool_calls"
                 choices = [
                     StreamingChoices(
diff --git a/litellm/llms/ollama/completion/handler.py b/litellm/llms/ollama/completion/handler.py
index 6e490f3ff15..449952217b5 100644
--- a/litellm/llms/ollama/completion/handler.py
+++ b/litellm/llms/ollama/completion/handler.py
@@ -4,16 +4,32 @@ Ollama /chat/completion calls handled in llm_http_handler.py
 [TODO]: migrate embeddings to a base handler as well.
 """
 
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, Protocol, TypedDict
+
+from typing_extensions import NotRequired, ReadOnly
 
 import litellm
 from litellm.types.utils import EmbeddingResponse
 
 
+class TokenEncoder(Protocol):
+    """The tokenizer surface used to estimate prompt tokens."""
+
+    def encode(self, text: str, /) -> Sequence[int]: ...
+
+
+class OllamaEmbeddingResponse(TypedDict):
+    """Body of an Ollama ``/api/embed`` response."""
+
+    embeddings: ReadOnly[list[list[float]]]
+    prompt_eval_count: ReadOnly[NotRequired[int]]
+
+
 def _prepare_ollama_embedding_payload(
-    model: str, prompts: list[str], optional_params: dict[str, Any]
-) -> dict[str, Any]:
-    data: Final[dict[str, Any]] = {"model": model, "input": prompts}
+    model: str, prompts: list[str], optional_params: Mapping[str, object]
+) -> dict[str, object]:
+    data: Final[dict[str, object]] = {"model": model, "input": prompts}
     special_optional_params: Final = ["truncate", "options", "keep_alive", "dimensions"]
 
     for k, v in optional_params.items():
@@ -27,12 +43,12 @@ def _prepare_ollama_embedding_payload(
 
 
 def _process_ollama_embedding_response(
-    response_json: dict,
+    response_json: OllamaEmbeddingResponse,
     prompts: list[str],
     model: str,
     model_response: EmbeddingResponse,
     logging_obj: Any,
-    encoding: Any,
+    encoding: TokenEncoder | None,
 ) -> EmbeddingResponse:
     output_data: Final = []
     embeddings: Final[list[list[float]]] = response_json["embeddings"]
@@ -72,7 +88,7 @@ async def ollama_aembeddings(
     model_response: EmbeddingResponse,
     optional_params: dict,
     logging_obj: Any,
-    encoding: Any,
+    encoding: TokenEncoder | None,
 ):
     if not api_base.endswith("/api/embed"):
         api_base += "/api/embed"
@@ -80,7 +96,7 @@ async def ollama_aembeddings(
     data: Final = _prepare_ollama_embedding_payload(model, prompts, optional_params)
 
     response: Final = await litellm.module_level_aclient.post(url=api_base, json=data)
-    response_json: Final = response.json()
+    response_json: Final[OllamaEmbeddingResponse] = response.json()
 
     return _process_ollama_embedding_response(
         response_json=response_json,
@@ -99,7 +115,7 @@ def ollama_embeddings(
     optional_params: dict,
     model_response: EmbeddingResponse,
     logging_obj: Any,
-    encoding: Any = None,
+    encoding: TokenEncoder | None = None,
 ):
     if not api_base.endswith("/api/embed"):
         api_base += "/api/embed"
@@ -107,7 +123,7 @@ def ollama_embeddings(
     data: Final = _prepare_ollama_embedding_payload(model, prompts, optional_params)
 
     response: Final = litellm.module_level_client.post(url=api_base, json=data)
-    response_json: Final = response.json()
+    response_json: Final[OllamaEmbeddingResponse] = response.json()
 
     return _process_ollama_embedding_response(
         response_json=response_json,
diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index 5894658e5d2..9afc6331d96 100644
--- a/litellm/llms/openai/chat/gpt_transformation.py
+++ b/litellm/llms/openai/chat/gpt_transformation.py
@@ -4,7 +4,8 @@ Support for gpt model family
 
 import json
 import os
-from collections.abc import AsyncIterator, Coroutine, Iterator
+from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal, Optional, cast, overload
 from urllib.parse import urlparse
 
@@ -21,6 +22,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
     drop_tool_reference_parts_from_tool_messages,
     get_tool_call_names,
     hoist_images_from_tool_messages,
+    tool_with_flattened_parameters,
 )
 from litellm.litellm_core_utils.prompt_templates.image_handling import (
     async_convert_url_to_base64,
@@ -65,6 +67,9 @@ else:
     LiteLLMLoggingObj = Any
 
 
+_NO_TOOLS_UPDATE: Final[Mapping[str, object]] = MappingProxyType({})
+
+
 class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     """
     Reference: https://platform.openai.com/docs/api-reference/chat/create
@@ -170,16 +175,20 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         if model != "gpt-3.5-turbo-16k" and model != "gpt-4":  # gpt-4 does not support 'response_format'
             model_specific_params.append("response_format")
 
-        # Normalize model name for responses API (e.g., "responses/gpt-4.1" -> "gpt-4.1")
-        model_for_check: Final = model.split("responses/", 1)[1] if "responses/" in model else model
-        if (
-            model_for_check in litellm.open_ai_chat_completion_models
-        ) or model_for_check in litellm.open_ai_text_completion_models:
+        if OpenAIGPTConfig.is_openai_catalog_model(model):
             model_specific_params.append(
                 "user"
             )  # user is not a param supported by all openai-compatible endpoints - e.g. azure ai
         return base_params + model_specific_params
 
+    @staticmethod
+    def is_openai_catalog_model(model: str) -> bool:
+        model_for_check: Final = model.split("responses/", 1)[1] if "responses/" in model else model
+        return (
+            model_for_check in litellm.open_ai_chat_completion_models
+            or model_for_check in litellm.open_ai_text_completion_models
+        )
+
     def _map_openai_params(
         self,
         non_default_params: dict,
@@ -321,7 +330,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     @overload
     def _transform_messages(
         self, messages: list[AllMessageValues], model: str, is_async: Literal[True]
-    ) -> Coroutine[Any, Any, list[AllMessageValues]]: 
+    ) -> Coroutine[object, object, list[AllMessageValues]]:
         ...
 
     @overload
@@ -337,7 +346,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
 
     def _transform_messages(
         self, messages: list[AllMessageValues], model: str, is_async: bool = False
-    ) -> list[AllMessageValues] | Coroutine[Any, Any, list[AllMessageValues]]:
+    ) -> list[AllMessageValues] | Coroutine[object, object, list[AllMessageValues]]:
         """OpenAI no longer supports image_url as a string, so we need to convert it to a dict"""
         stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(messages)
         hoisted_messages: Final = hoist_images_from_tool_messages(stripped_messages)
@@ -393,6 +402,21 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                 )
         return messages, tools
 
+    def _targets_openai_hosted_endpoint(
+        self,
+        custom_llm_provider: str | None,
+        api_base: str | None,
+    ) -> bool:
+        if custom_llm_provider != "openai":
+            return False
+        resolved_api_base = api_base or litellm.api_base or os.getenv("OPENAI_BASE_URL") or os.getenv("OPENAI_API_BASE")
+        if not resolved_api_base:
+            return True
+        hostname: Final = urlparse(resolved_api_base).hostname
+        if hostname is None:
+            return True
+        return hostname == "openai.com" or hostname.endswith(".openai.com")
+
     def _should_preserve_cache_control_for_endpoint(
         self,
         custom_llm_provider: str | None,
@@ -404,15 +428,34 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         api_base. Those can understand cache_control, so it must survive there.
         Real OpenAI cannot, so it is still stripped for an openai.com host.
         """
-        if custom_llm_provider != "openai":
-            return False
-        resolved_api_base = api_base or litellm.api_base or os.getenv("OPENAI_BASE_URL") or os.getenv("OPENAI_API_BASE")
-        if not resolved_api_base:
-            return False
-        hostname: Final = urlparse(resolved_api_base).hostname
-        if hostname is None:
-            return False
-        return hostname != "openai.com" and not hostname.endswith(".openai.com")
+        return custom_llm_provider == "openai" and not self._targets_openai_hosted_endpoint(
+            custom_llm_provider, api_base
+        )
+
+    def _flattened_tools_update_for_openai(
+        self,
+        optional_params: Mapping[str, object],
+        litellm_params: Mapping[str, object],
+    ) -> Mapping[str, object]:
+        """
+        OpenAI's chat completions validator rejects tool `parameters` carrying
+        'oneOf'/'anyOf'/'allOf'/'enum'/'const'/'not' at the top level for every
+        model family, unlike the Responses API, where GPT-5+ accepts them.
+        """
+        tools: Final = optional_params.get("tools")
+        if not isinstance(tools, list):
+            return _NO_TOOLS_UPDATE
+        provider: Final = litellm_params.get("custom_llm_provider")
+        raw_api_base: Final = litellm_params.get("api_base")
+        if not self._targets_openai_hosted_endpoint(
+            provider if isinstance(provider, str) else None,
+            raw_api_base if isinstance(raw_api_base, str) else None,
+        ):
+            return _NO_TOOLS_UPDATE
+        flattened: Final = [  # mutable-ok: request tools are a JSON list
+            tool_with_flattened_parameters(tool) if isinstance(tool, dict) else tool for tool in tools
+        ]
+        return MappingProxyType({"tools": flattened})
 
     def transform_request(
         self,
@@ -439,11 +482,14 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                 optional_params["tools"] = tools
 
         optional_params.pop("max_retries", None)
+        if not optional_params.get("tools") and not optional_params.get("functions"):
+            optional_params.pop("tool_choice", None)
 
         return {
             "model": model,
             "messages": messages,
             **optional_params,
+            **self._flattened_tools_update_for_openai(optional_params, litellm_params),
         }
 
     async def async_transform_request(
@@ -469,10 +515,13 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             if tools is not None and len(tools) > 0:
                 optional_params["tools"] = tools
         if self.__class__._is_base_class:
+            if not optional_params.get("tools") and not optional_params.get("functions"):
+                optional_params.pop("tool_choice", None)
             return {
                 "model": model,
                 "messages": transformed_messages,
                 **optional_params,
+                **self._flattened_tools_update_for_openai(optional_params, litellm_params),
             }
         else:
             ## allow for any object specific behaviour to be handled
@@ -493,8 +542,12 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             return None
         tool_call_names: Final = get_tool_call_names(optional_params.get("tools", []))
         try:
-            json_content: Final = json.loads(content)
-            if json_content.get("type") == "function" and json_content.get("name") in tool_call_names:
+            json_content: Final[object] = json.loads(content)
+            if (
+                isinstance(json_content, dict)
+                and json_content.get("type") == "function"
+                and json_content.get("name") in tool_call_names
+            ):
                 return ChatCompletionMessageToolCall(
                     function=Function(
                         name=json_content.get("name"),
@@ -618,7 +671,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
 
         ## RESPONSE OBJECT
         try:
-            completion_response: Final = raw_response.json()
+            completion_response: Final[dict[str, object]] = raw_response.json()
         except Exception as e:
             response_headers: Final = getattr(raw_response, "headers", None)
             raise OpenAIError(
@@ -755,6 +808,14 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         )
 
 
+class OpenAIUnknownModelConfig(OpenAIGPTConfig):
+    """A model the openai provider does not recognize is typically a LiteLLM proxy alias, so
+    forward reasoning_effort and let the server decide whether it is supported."""
+
+    def get_supported_openai_params(self, model: str) -> list:  # mutable-ok: inherited contract
+        return super().get_supported_openai_params(model) + ["reasoning_effort"]  # mutable-ok: inherited contract
+
+
 class OpenAIChatCompletionStreamingHandler(BaseModelResponseIterator):
     def _map_reasoning_to_reasoning_content(self, choices: list) -> list:
         """
diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index 54673c77f80..96a5ed663fc 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -14,8 +14,14 @@ Pattern Overview:
 This pattern can be replicated for other message formats (e.g., Anthropic).
 """
 
+import json
+import time
+import uuid
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.base_llm.guardrail_translation.base_translation import (
@@ -23,6 +29,7 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import (
     StreamTransformSink,
 )
 from litellm.llms.base_llm.guardrail_translation.utils import (
+    blocked_chat_stream_usage,
     effective_scan_only_tool_results_for_guardrail,
     effective_skip_system_message_for_guardrail,
     effective_skip_tool_message_for_guardrail,
@@ -31,6 +38,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import (
     openai_tool_name,
     role_out_of_guardrail_scope,
     scoped_structured_message_indices,
+    stream_item_field,
 )
 from litellm.main import stream_chunk_builder
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam
@@ -46,8 +54,14 @@ from litellm.types.utils import (
 )
 
 if TYPE_CHECKING:
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    from fastapi import HTTPException
+
+    from litellm.integrations.custom_guardrail import (
+        CustomGuardrail,
+        ModifyResponseException,
+    )
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.proxy._types import UserAPIKeyAuth
 
 
 class OpenAIChatCompletionsHandler(BaseTranslation):
@@ -77,7 +91,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         data: dict,
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-    ) -> Any:
+    ) -> dict:
         """
         Process input messages by applying guardrails to text content.
         """
@@ -326,9 +340,9 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         response: "ModelResponse",
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-        user_api_key_dict: Any | None = None,
+        user_api_key_dict: "UserAPIKeyAuth | None" = None,
         request_data: dict | None = None,
-    ) -> Any:
+    ) -> ModelResponse:
         """
         Process output response by applying guardrails to text content.
 
@@ -382,11 +396,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                 if "response" not in request_data:
                     request_data["response"] = response
 
-            # Add user API key metadata with prefixed keys
-            if "litellm_metadata" not in request_data:
-                user_metadata: Final = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-                if user_metadata:
-                    request_data["litellm_metadata"] = user_metadata
+            self.merge_user_api_key_metadata_into_request(request_data, user_api_key_dict)
 
             inputs: Final = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:
@@ -437,7 +447,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-        user_api_key_dict: Any | None = None,
+        user_api_key_dict: "UserAPIKeyAuth | None" = None,
         request_data: dict | None = None,
         stream_transform_sink: StreamTransformSink | None = None,
     ) -> list["ModelResponseStream"]:
@@ -487,7 +497,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None",
-        user_api_key_dict: Any | None,
+        user_api_key_dict: "UserAPIKeyAuth | None",
         request_data: dict | None,
     ) -> list["ModelResponseStream"]:
         """Block-only streaming path: run the guardrail so an in-flight BLOCK can
@@ -555,11 +565,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                 if "responses" not in request_data:
                     request_data["responses"] = responses_so_far
 
-            # Add user API key metadata with prefixed keys
-            if "litellm_metadata" not in request_data:
-                user_metadata: Final = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-                if user_metadata:
-                    request_data["litellm_metadata"] = user_metadata
+            self.merge_user_api_key_metadata_into_request(request_data, user_api_key_dict)
 
             inputs: Final = GenericGuardrailAPIInputs(texts=texts_to_check)
             if images_to_check:
@@ -591,6 +597,18 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
 
         return responses_so_far
 
+    def build_stream_error_items(
+        self,
+        exc: "HTTPException",
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes] | None:
+        import json
+
+        from litellm.proxy.common_request_processing import sse_error_payload
+
+        _, error_obj = sse_error_payload(exc)
+        return (f'data: {{"error": {json.dumps(error_obj)}}}\n\n'.encode(),)
+
     @staticmethod
     def _accumulate_string_content_by_choice_index(
         responses_so_far: list["ModelResponseStream"],
@@ -623,7 +641,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None",
-        user_api_key_dict: Any | None,
+        user_api_key_dict: "UserAPIKeyAuth | None",
         request_data: dict | None,
         sink: StreamTransformSink,
     ) -> None:
@@ -653,10 +671,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
             request_data = {"responses": responses_so_far}
         elif "responses" not in request_data:
             request_data["responses"] = responses_so_far
-        if "litellm_metadata" not in request_data:
-            user_metadata: Final = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
-            if user_metadata:
-                request_data["litellm_metadata"] = user_metadata
+        self.merge_user_api_key_metadata_into_request(request_data, user_api_key_dict)
 
         inputs: Final = GenericGuardrailAPIInputs(texts=texts_to_check)
         if responses_so_far and getattr(responses_so_far[0], "model", None):
@@ -790,7 +805,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
 
         # Determine content source and tool calls based on choice type
         content = None
-        tool_calls: list[Any] | None = None
+        tool_calls: Sequence[object] | None = None
         if isinstance(choice, litellm.Choices):
             content = choice.message.content
             tool_calls = choice.message.tool_calls
@@ -1000,3 +1015,129 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                                 else:
                                     # Subsequent chunks - clear the text
                                     content_item["text"] = ""
+
+    def _check_streaming_has_ended(self, responses_so_far: Sequence[object]) -> bool:
+        """
+        True once any relayed chunk carries a non-null ``finish_reason``.
+
+        The unified guardrail's ``end_of_stream_only`` streaming path probes
+        this via ``hasattr`` to withhold the terminal chunks until
+        end-of-stream moderation runs, so a block can replace the finish
+        instead of trailing after a ``finish_reason`` the client already saw.
+        """
+        return any(
+            stream_item_field(choice, "finish_reason") is not None
+            for item in responses_so_far
+            for choice in _stream_chunk_choices(item)
+        )
+
+    def build_block_sse_chunks(
+        self,
+        exc: "ModifyResponseException",
+        stream_started: bool = False,
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes]:
+        """
+        Build OpenAI chat-completions SSE chunks that deliver the guardrail
+        block message and terminate the stream cleanly, mirroring the
+        non-streaming block response: ``finish_reason`` ``content_filter`` plus
+        the real usage the upstream call consumed.
+
+        - ``stream_started`` False (buffered / pre-stream): nothing has been
+          sent, so open a standalone completion with a ``role`` delta.
+        - ``stream_started`` True (sampling / mid-stream): chunks already
+          reached the client, so continue the in-progress completion (reuse its
+          id/created/model, content-only delta).
+
+        The proxy's data generator appends ``data: [DONE]`` itself.
+        """
+        chunk_id, created, model = _blocked_stream_identity(exc, responses_so_far or ())
+        prompt_tokens, completion_tokens = blocked_chat_stream_usage(exc.original_response)
+        continuation_delta: Final[_BlockedChunkDelta] = {"content": exc.message}
+        standalone_delta: Final[_BlockedChunkDelta] = {"role": "assistant", "content": exc.message}
+        message_chunk: Final[_BlockedChunk] = {
+            "id": chunk_id,
+            "object": "chat.completion.chunk",
+            "created": created,
+            "model": model,
+            "choices": (
+                {
+                    "index": 0,
+                    "delta": continuation_delta if stream_started else standalone_delta,
+                    "finish_reason": None,
+                },
+            ),
+        }
+        final_chunk: Final[_BlockedChunk] = {
+            "id": chunk_id,
+            "object": "chat.completion.chunk",
+            "created": created,
+            "model": model,
+            "choices": ({"index": 0, "delta": {}, "finish_reason": "content_filter"},),
+            "usage": {
+                "prompt_tokens": prompt_tokens,
+                "completion_tokens": completion_tokens,
+                "total_tokens": prompt_tokens + completion_tokens,
+            },
+        }
+        return _chat_sse_chunk(message_chunk), _chat_sse_chunk(final_chunk)
+
+
+class _BlockedChunkDelta(TypedDict, total=False):
+    role: ReadOnly[str]
+    content: ReadOnly[str]
+
+
+class _BlockedChunkChoice(TypedDict):
+    index: ReadOnly[int]
+    delta: ReadOnly[_BlockedChunkDelta]
+    finish_reason: ReadOnly[str | None]
+
+
+class _BlockedChunkUsage(TypedDict):
+    prompt_tokens: ReadOnly[int]
+    completion_tokens: ReadOnly[int]
+    total_tokens: ReadOnly[int]
+
+
+class _BlockedChunk(TypedDict):
+    id: ReadOnly[str]
+    object: ReadOnly[str]
+    created: ReadOnly[int]
+    model: ReadOnly[str]
+    choices: ReadOnly[tuple[_BlockedChunkChoice, ...]]
+    usage: NotRequired[ReadOnly[_BlockedChunkUsage]]
+
+
+def _chat_sse_chunk(payload: _BlockedChunk) -> bytes:
+    return f"data: {json.dumps(payload)}\n\n".encode()
+
+
+def _stream_chunk_choices(item: object) -> Sequence[object]:
+    choices: Final = stream_item_field(item, "choices")
+    if isinstance(choices, Sequence) and not isinstance(choices, (str, bytes)):
+        return choices
+    return ()
+
+
+def _blocked_stream_identity(
+    exc: "ModifyResponseException", responses_so_far: Sequence[object]
+) -> tuple[str, int, str]:
+    identified: Final = next(
+        (
+            (chunk_id, item)
+            for item in responses_so_far
+            if isinstance(chunk_id := stream_item_field(item, "id"), str) and chunk_id
+        ),
+        None,
+    )
+    if identified is None:
+        return f"chatcmpl-{uuid.uuid4()}", int(time.time()), exc.model
+    chunk_id, source = identified
+    created: Final = stream_item_field(source, "created")
+    model: Final = stream_item_field(source, "model")
+    return (
+        chunk_id,
+        created if isinstance(created, int) else int(time.time()),
+        model if isinstance(model, str) and model else exc.model,
+    )
diff --git a/litellm/llms/openai/common_utils.py b/litellm/llms/openai/common_utils.py
index 1b1ab80e85d..4d774f6f165 100644
--- a/litellm/llms/openai/common_utils.py
+++ b/litellm/llms/openai/common_utils.py
@@ -268,6 +268,7 @@ class BaseOpenAILLM:
             "max_retries",
             "organization",
             "api_base",
+            "workload_identity_config",
         )
         openai_client_fields: Final = (
             BaseOpenAILLM.get_openai_client_initialization_param_fields(client_type=client_type)
diff --git a/litellm/llms/openai/containers/transformation.py b/litellm/llms/openai/containers/transformation.py
index 6fc50458aa3..1a5211d5ff5 100644
--- a/litellm/llms/openai/containers/transformation.py
+++ b/litellm/llms/openai/containers/transformation.py
@@ -1,6 +1,8 @@
-from typing import TYPE_CHECKING, Any, Final
+from collections.abc import Mapping
+from typing import TYPE_CHECKING, Any, Final, Literal
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import (
@@ -11,9 +13,11 @@ from litellm.secret_managers.main import get_secret_str
 from litellm.types.containers.main import (
     ContainerCreateOptionalRequestParams,
     ContainerFileListResponse,
+    ContainerFileObject,
     ContainerListResponse,
     ContainerObject,
     DeleteContainerResult,
+    ExpiresAfter,
 )
 from litellm.types.router import GenericLiteLLMParams
 
@@ -32,6 +36,46 @@ else:
     BaseLLMException = Any
 
 
+class OpenAIContainerPayload(TypedDict):
+    """The JSON body OpenAI returns for a single container."""
+
+    id: ReadOnly[str]
+    object: ReadOnly[Literal["container"]]
+    created_at: ReadOnly[int]
+    status: ReadOnly[str]
+    expires_after: ReadOnly[ExpiresAfter | None]
+    last_active_at: ReadOnly[int | None]
+    name: ReadOnly[str | None]
+
+
+class OpenAIContainerListPayload(TypedDict):
+    """The JSON body OpenAI returns for a page of containers."""
+
+    object: ReadOnly[Literal["list"]]
+    data: ReadOnly[list[ContainerObject]]
+    first_id: ReadOnly[str | None]
+    last_id: ReadOnly[str | None]
+    has_more: ReadOnly[bool]
+
+
+class OpenAIContainerDeletedPayload(TypedDict):
+    """The JSON body OpenAI returns for a deleted container."""
+
+    id: ReadOnly[str]
+    object: ReadOnly[Literal["container.deleted"]]
+    deleted: ReadOnly[bool]
+
+
+class OpenAIContainerFileListPayload(TypedDict):
+    """The JSON body OpenAI returns for a page of container files."""
+
+    object: ReadOnly[Literal["list"]]
+    data: ReadOnly[list[ContainerFileObject]]
+    first_id: ReadOnly[str | None]
+    last_id: ReadOnly[str | None]
+    has_more: ReadOnly[bool]
+
+
 class OpenAIContainerConfig(BaseContainerConfig):
     """Configuration class for OpenAI container API."""
 
@@ -87,7 +131,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
     def transform_container_create_request(
         self,
         name: str,
-        container_create_optional_request_params: dict,
+        container_create_optional_request_params: Mapping[str, object],
         litellm_params: GenericLiteLLMParams,
         headers: dict,
     ) -> dict:
@@ -111,10 +155,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> ContainerObject:
         """Transform the OpenAI container creation response."""
-        response_data: Final = raw_response.json()
-
-        # Transform the response data
-        container_obj: Final = ContainerObject(**response_data)
+        container_obj: Final = ContainerObject.model_validate(raw_response.json())
 
         # Add cost for container creation (OpenAI containers are code interpreter sessions)
         # https://platform.openai.com/docs/pricing
@@ -140,7 +181,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         after: str | None = None,
         limit: int | None = None,
         order: str | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_query: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """Transform the container list request for OpenAI API.
 
@@ -151,7 +192,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         url: Final = api_base
 
         # Prepare query parameters
-        params: Final = {}
+        params: Final[dict[str, object]] = {}
         if after is not None:
             params["after"] = after
         if limit is not None:
@@ -171,10 +212,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> ContainerListResponse:
         """Transform the OpenAI container list response."""
-        response_data: Final = raw_response.json()
-
-        # Transform the response data
-        container_list: Final = ContainerListResponse(**response_data)
+        container_list: Final = ContainerListResponse.model_validate(raw_response.json())
 
         return container_list
 
@@ -191,7 +229,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}")
 
         # No additional data needed for GET request
-        data: Final[dict[str, Any]] = {}
+        data: Final[dict[str, str]] = {}
 
         return url, data
 
@@ -201,9 +239,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> ContainerObject:
         """Transform the OpenAI container retrieve response."""
-        response_data: Final = raw_response.json()
-        # Transform the response data
-        container_obj: Final = ContainerObject(**response_data)
+        container_obj: Final = ContainerObject.model_validate(raw_response.json())
 
         return container_obj
 
@@ -224,7 +260,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}")
 
         # No data needed for DELETE request
-        data: Final[dict[str, Any]] = {}
+        data: Final[dict[str, str]] = {}
 
         return url, data
 
@@ -234,10 +270,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> DeleteContainerResult:
         """Transform the OpenAI container delete response."""
-        response_data: Final = raw_response.json()
-
-        # Transform the response data
-        delete_result: Final = DeleteContainerResult(**response_data)
+        delete_result: Final = DeleteContainerResult.model_validate(raw_response.json())
 
         return delete_result
 
@@ -250,7 +283,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         after: str | None = None,
         limit: int | None = None,
         order: str | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_query: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """Transform the container file list request for OpenAI API.
 
@@ -262,7 +295,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}/files")
 
         # Prepare query parameters
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
         if after is not None:
             params["after"] = after
         if limit is not None:
@@ -282,10 +315,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> ContainerFileListResponse:
         """Transform the OpenAI container file list response."""
-        response_data: Final = raw_response.json()
-
-        # Transform the response data
-        file_list: Final = ContainerFileListResponse(**response_data)
+        file_list: Final = ContainerFileListResponse.model_validate(raw_response.json())
 
         return file_list
 
@@ -308,7 +338,7 @@ class OpenAIContainerConfig(BaseContainerConfig):
         url: Final = join_container_api_base_path(api_base, f"/{encoded_container_id}/files/{encoded_file_id}/content")
 
         # No query parameters needed
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, str]] = {}
 
         return url, params
 
diff --git a/litellm/llms/openai/openai.py b/litellm/llms/openai/openai.py
index 6e66c998acf..1cfc6e06ee9 100644
--- a/litellm/llms/openai/openai.py
+++ b/litellm/llms/openai/openai.py
@@ -12,9 +12,14 @@ if TYPE_CHECKING:
 
 import openai
 from openai import AsyncOpenAI, OpenAI
+from openai._base_client import make_request_options
+from openai._constants import RAW_RESPONSE_HEADER
+from openai._legacy_response import LegacyAPIResponse
+from openai._types import RequestOptions
+from openai.types import CreateEmbeddingResponse
 from openai.types.beta.assistant_deleted import AssistantDeleted
 from openai.types.file_deleted import FileDeleted
-from pydantic import BaseModel
+from pydantic import BaseModel, TypeAdapter
 from typing_extensions import overload
 
 import litellm
@@ -43,6 +48,7 @@ from litellm.utils import (
 from ...types.llms.openai import *
 from ..base import BaseLLM
 from .chat.gpt_5_transformation import OpenAIGPT5Config
+from .chat.gpt_transformation import OpenAIGPTConfig, OpenAIUnknownModelConfig
 from .chat.o_series_transformation import OpenAIOSeriesConfig
 from .common_utils import (
     BaseOpenAILLM,
@@ -51,6 +57,7 @@ from .common_utils import (
     drop_params_from_unprocessable_entity_error,
     is_output_token_limit_error,
 )
+from .workload_identity import resolve_openai_workload_identity_config
 
 openaiOSeriesConfig: Final = OpenAIOSeriesConfig()
 openAIGPT5Config: Final = OpenAIGPT5Config()
@@ -188,7 +195,12 @@ class OpenAIConfig(BaseConfig):
         elif litellm.openAIGPTAudioConfig.is_model_gpt_audio_model(model=model):
             return litellm.openAIGPTAudioConfig.get_supported_openai_params(model=model)
         else:
-            return litellm.openAIGPTConfig.get_supported_openai_params(model=model)
+            return self._gpt_config_for_model(model).get_supported_openai_params(model=model)
+
+    def _gpt_config_for_model(self, model: str) -> OpenAIGPTConfig:
+        if type(self) is OpenAIConfig and not OpenAIGPTConfig.is_openai_catalog_model(model):
+            return OpenAIUnknownModelConfig()
+        return litellm.openAIGPTConfig
 
     def _map_openai_params(self, non_default_params: dict, optional_params: dict, model: str) -> dict:
         supported_openai_params: Final = self.get_supported_openai_params(model)
@@ -230,7 +242,7 @@ class OpenAIConfig(BaseConfig):
                 drop_params=drop_params,
             )
 
-        return litellm.openAIGPTConfig.map_openai_params(
+        return self._gpt_config_for_model(model).map_openai_params(
             non_default_params=non_default_params,
             optional_params=optional_params,
             model=model,
@@ -322,6 +334,28 @@ class OpenAIChatCompletionResponseIterator(BaseModelResponseIterator):
             raise e
 
 
+_EXTRA_HEADERS_ADAPTER: Final = TypeAdapter(dict[str, str] | None)
+_EXTRA_QUERY_ADAPTER: Final = TypeAdapter(dict[str, object] | None)
+_NO_EXTRA_HEADERS: Final[Mapping[str, str]] = types.MappingProxyType({})
+_SDK_OPTION_KEYS: Final = frozenset(("extra_headers", "extra_query", "extra_body"))
+
+
+def _embedding_request_without_sdk_defaults(
+    data: Mapping[str, object], timeout: float | httpx.Timeout
+) -> tuple[Mapping[str, object], RequestOptions]:
+    body: Final = {  # mutable-ok: the SDK json-encodes the body and needs a plain dict
+        k: v for k, v in data.items() if k not in _SDK_OPTION_KEYS
+    }
+    extra_headers: Final = _EXTRA_HEADERS_ADAPTER.validate_python(data.get("extra_headers")) or _NO_EXTRA_HEADERS
+    options: Final = make_request_options(
+        extra_headers=types.MappingProxyType({**extra_headers, RAW_RESPONSE_HEADER: "true"}),
+        extra_query=_EXTRA_QUERY_ADAPTER.validate_python(data.get("extra_query")),
+        extra_body=data.get("extra_body"),
+        timeout=timeout,
+    )
+    return body, options
+
+
 class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
     def __init__(self) -> None:
         super().__init__()
@@ -349,6 +383,7 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         client: OpenAI | AsyncOpenAI | None = None,
         shared_session: Optional["ClientSession"] = None,
     ) -> OpenAI | AsyncOpenAI | None:
+        workload_identity_config: Final = resolve_openai_workload_identity_config(api_key=api_key, api_base=api_base)
         client_initialization_params: Final[dict] = locals()
         if client is None:
             if not isinstance(max_retries, int):
@@ -364,28 +399,49 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
             if cached_client:
                 if isinstance(cached_client, OpenAI) or isinstance(cached_client, AsyncOpenAI):
                     return cached_client
-            http_client: Final[httpx.Client | httpx.AsyncClient | None] = (
-                OpenAIChatCompletion._get_async_http_client(shared_session=shared_session)
-                if is_async
-                else OpenAIChatCompletion._get_sync_http_client()
-            )
             if is_async:
-                _new_client: OpenAI | AsyncOpenAI = AsyncOpenAI(
-                    api_key=api_key,
-                    base_url=api_base,
-                    http_client=http_client,
-                    timeout=timeout,
-                    max_retries=max_retries,
-                    organization=organization,
+                async_http_client: Final = OpenAIChatCompletion._get_async_http_client(shared_session=shared_session)
+                http_client: httpx.Client | httpx.AsyncClient | None = async_http_client
+                _new_client: OpenAI | AsyncOpenAI = (
+                    AsyncOpenAI(
+                        workload_identity=workload_identity_config.to_sdk_workload_identity(),
+                        base_url=api_base,
+                        http_client=async_http_client,
+                        timeout=timeout,
+                        max_retries=max_retries,
+                        organization=organization,
+                    )
+                    if workload_identity_config is not None
+                    else AsyncOpenAI(
+                        api_key=api_key,
+                        base_url=api_base,
+                        http_client=async_http_client,
+                        timeout=timeout,
+                        max_retries=max_retries,
+                        organization=organization,
+                    )
                 )
             else:
-                _new_client = OpenAI(
-                    api_key=api_key,
-                    base_url=api_base,
-                    http_client=http_client,
-                    timeout=timeout,
-                    max_retries=max_retries,
-                    organization=organization,
+                sync_http_client: Final = OpenAIChatCompletion._get_sync_http_client()
+                http_client = sync_http_client
+                _new_client = (
+                    OpenAI(
+                        workload_identity=workload_identity_config.to_sdk_workload_identity(),
+                        base_url=api_base,
+                        http_client=sync_http_client,
+                        timeout=timeout,
+                        max_retries=max_retries,
+                        organization=organization,
+                    )
+                    if workload_identity_config is not None
+                    else OpenAI(
+                        api_key=api_key,
+                        base_url=api_base,
+                        http_client=sync_http_client,
+                        timeout=timeout,
+                        max_retries=max_retries,
+                        organization=organization,
+                    )
                 )
 
             ## SAVE CACHE KEY
@@ -1148,19 +1204,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         data: dict,
         timeout: float | httpx.Timeout,
         logging_obj: LiteLLMLoggingObj,
-    ):
-        """
-        Helper to:
-        - call embeddings.create.with_raw_response when litellm.return_response_headers is True
-        - call embeddings.create by default
-        """
-        try:
-            raw_response = await openai_aclient.embeddings.with_raw_response.create(**data, timeout=timeout)
-            headers: Final = dict(raw_response.headers)
-            response: Final = raw_response.parse()
-            return headers, response
-        except Exception as e:
-            raise e
+    ) -> LegacyAPIResponse[CreateEmbeddingResponse]:
+        if "encoding_format" not in data:
+            body, options = _embedding_request_without_sdk_defaults(data, timeout)
+            bypass_response: Final = await openai_aclient.post(
+                "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse
+            )
+            assert isinstance(bypass_response, LegacyAPIResponse)
+            return bypass_response
+        return await openai_aclient.embeddings.with_raw_response.create(**data, timeout=timeout)
 
     @track_llm_api_timing()
     def make_sync_openai_embedding_request(
@@ -1169,20 +1221,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
         data: dict,
         timeout: float | httpx.Timeout,
         logging_obj: LiteLLMLoggingObj,
-    ):
-        """
-        Helper to:
-        - call embeddings.create.with_raw_response when litellm.return_response_headers is True
-        - call embeddings.create by default
-        """
-        try:
-            raw_response = openai_client.embeddings.with_raw_response.create(**data, timeout=timeout)
-
-            headers: Final = dict(raw_response.headers)
-            response: Final = raw_response.parse()
-            return headers, response
-        except Exception as e:
-            raise e
+    ) -> LegacyAPIResponse[CreateEmbeddingResponse]:
+        if "encoding_format" not in data:
+            body, options = _embedding_request_without_sdk_defaults(data, timeout)
+            bypass_response: Final = openai_client.post(
+                "/embeddings", body=body, options=options, cast_to=CreateEmbeddingResponse
+            )
+            assert isinstance(bypass_response, LegacyAPIResponse)
+            return bypass_response
+        return openai_client.embeddings.with_raw_response.create(**data, timeout=timeout)
 
     async def aembedding(
         self,
@@ -1207,14 +1254,15 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
                 client=client,
                 shared_session=shared_session,
             )
-            headers, response = await self.make_openai_embedding_request(
+            raw_response: Final = await self.make_openai_embedding_request(
                 openai_aclient=openai_aclient,
                 data=data,
                 timeout=timeout,
                 logging_obj=logging_obj,
             )
+            headers: Final = dict(raw_response.headers)
             logging_obj.model_call_details["response_headers"] = headers
-            stringified_response: Final = response.model_dump()
+            stringified_response: Final = raw_response.parse().model_dump()
             ## LOGGING
             logging_obj.post_call(
                 input=input,
@@ -1306,13 +1354,14 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM):
             )
 
             ## embedding CALL
-            headers: dict | None = None
-            headers, sync_embedding_response = self.make_sync_openai_embedding_request(
+            raw_response: Final = self.make_sync_openai_embedding_request(
                 openai_client=openai_client,
                 data=data,
                 timeout=timeout,
                 logging_obj=logging_obj,
             )
+            headers: Final = dict(raw_response.headers)
+            sync_embedding_response: Final = raw_response.parse()
 
             ## LOGGING
             logging_obj.model_call_details["response_headers"] = headers
diff --git a/litellm/llms/openai/responses/count_tokens/transformation.py b/litellm/llms/openai/responses/count_tokens/transformation.py
index 6b2f4535df1..88f04c59e01 100644
--- a/litellm/llms/openai/responses/count_tokens/transformation.py
+++ b/litellm/llms/openai/responses/count_tokens/transformation.py
@@ -4,7 +4,100 @@ OpenAI Responses API token counting transformation logic.
 This module handles the transformation of requests to OpenAI's /v1/responses/input_tokens endpoint.
 """
 
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, Literal
+
+from typing_extensions import ReadOnly, TypedDict
+
+
+class ResponsesInputTextPart(TypedDict):
+    type: ReadOnly[Literal["input_text"]]
+    text: ReadOnly[str]
+
+
+class ResponsesInputImagePart(TypedDict):
+    type: ReadOnly[Literal["input_image"]]
+    image_url: ReadOnly[str]
+    detail: ReadOnly[str]
+
+
+class ResponsesInputFilePart(TypedDict):
+    type: ReadOnly[Literal["input_file"]]
+    filename: ReadOnly[str]
+    file_data: ReadOnly[str]
+
+
+ResponsesInputPart = ResponsesInputTextPart | ResponsesInputImagePart | ResponsesInputFilePart
+
+ResponsesContentRole = Literal["user", "assistant"]
+
+
+def _chat_image_block_to_responses_part(image_url: object) -> ResponsesInputImagePart | None:
+    url: Final = image_url.get("url") if isinstance(image_url, Mapping) else image_url
+    if not isinstance(url, str) or not url:
+        return None
+    detail: Final = image_url.get("detail") if isinstance(image_url, Mapping) else None
+    part: Final[ResponsesInputImagePart] = {
+        "type": "input_image",
+        "image_url": url,
+        "detail": detail if isinstance(detail, str) and detail else "auto",
+    }
+    return part
+
+
+def _chat_file_block_to_responses_part(file_value: object) -> ResponsesInputFilePart | None:
+    """Only an inline file round trips: OpenAI rejects `file_data` without the `filename` beside it."""
+    if not isinstance(file_value, Mapping):
+        return None
+    filename: Final = file_value.get("filename")
+    file_data: Final = file_value.get("file_data")
+    if not isinstance(filename, str) or not filename or not isinstance(file_data, str) or not file_data:
+        return None
+    part: Final[ResponsesInputFilePart] = {
+        "type": "input_file",
+        "filename": filename,
+        "file_data": file_data,
+    }
+    return part
+
+
+def _chat_block_to_responses_part(block: object, role: ResponsesContentRole) -> ResponsesInputPart | None:
+    if isinstance(block, str):
+        bare: Final[ResponsesInputTextPart] = {"type": "input_text", "text": block}
+        return bare
+    if not isinstance(block, Mapping):
+        return None
+    match block.get("type"):
+        case "text":
+            text_value: Final = block.get("text")
+            text: Final[ResponsesInputTextPart] = {
+                "type": "input_text",
+                "text": text_value if isinstance(text_value, str) else "",
+            }
+            return text
+        case "image_url" if role == "user":
+            return _chat_image_block_to_responses_part(block.get("image_url"))
+        case "file" if role == "user":
+            return _chat_file_block_to_responses_part(block.get("file"))
+        case _:
+            return None
+
+
+def chat_content_blocks_to_responses_content(
+    content: Sequence[object],
+    role: ResponsesContentRole,
+) -> str | tuple[ResponsesInputPart, ...]:
+    """Text-only content collapses to a joined string, which every role accepts and counts identically.
+
+    Only a user turn may carry an image or file part: the Responses API rejects any part but
+    output_text and refusal inside an assistant turn.
+    """
+    parts: Final = tuple(
+        part for part in (_chat_block_to_responses_part(block, role) for block in content) if part is not None
+    )
+    if any(part["type"] != "input_text" for part in parts):
+        return parts
+    return "\n".join(part["text"] for part in parts if part["type"] == "input_text")
 
 
 class OpenAICountTokensConfig:
@@ -120,18 +213,13 @@ class OpenAICountTokensConfig:
                     instructions_parts.append("\n".join(text_parts))
             elif role == "user":
                 if isinstance(content, list):
-                    # Extract text from content blocks for Responses API
-                    text_parts = []
-                    for block in content:
-                        if isinstance(block, dict) and block.get("type") == "text":
-                            text_parts.append(block.get("text", ""))
-                        elif isinstance(block, str):
-                            text_parts.append(block)
-                    content = "\n".join(text_parts)
+                    content = chat_content_blocks_to_responses_content(content, "user")
                 input_items.append({"role": "user", "content": content})
             elif role == "assistant":
                 # Map tool_calls to Responses API function_call items
                 tool_calls = msg.get("tool_calls")
+                if isinstance(content, list):
+                    content = chat_content_blocks_to_responses_content(content, "assistant")
                 if content:
                     input_items.append({"role": "assistant", "content": content})
                 if tool_calls:
diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 7c5d8ac99ad..1530c154e93 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -28,12 +28,16 @@ Output: response.output is List[GenericResponseOutputItem] where each has:
     - text: str
 """
 
-from collections.abc import Sequence
+import time
+import uuid
+from collections.abc import Mapping, Sequence
+from dataclasses import dataclass
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
 from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
 from openai.types.responses.tool_param import FunctionToolParam
-from pydantic import BaseModel
+from pydantic import BaseModel, TypeAdapter
 from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
@@ -41,15 +45,33 @@ from litellm.completion_extras.litellm_responses_transformation.transformation i
     OpenAiResponsesToChatCompletionStreamIterator,
 )
 from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.llms.base_llm.guardrail_translation.utils import (
+    blocked_responses_stream_usage,
+    stream_item_field,
+)
 from litellm.responses.litellm_completion_transformation.transformation import (
     LiteLLMCompletionResponsesConfig,
 )
 from litellm.types.llms.openai import (
     AllMessageValues,
+    BaseLiteLLMOpenAIResponseObject,
     ChatCompletionToolCallChunk,
     ChatCompletionToolParam,
+    ContentPartAddedEvent,
+    ContentPartDoneEvent,
+    ContentPartDonePartOutputText,
+    ErrorEvent,
+    ErrorEventError,
     OpenAIMcpServerTool,
+    OutputItemAddedEvent,
+    OutputItemDoneEvent,
+    OutputTextDeltaEvent,
+    OutputTextDoneEvent,
+    ResponseAPIUsage,
+    ResponseCompletedEvent,
+    ResponsesAPIResponse,
     ResponsesAPIStreamEvents,
+    ResponsesAPIStreamingResponse,
 )
 from litellm.types.responses.main import (
     GenericResponseOutputItem,
@@ -59,11 +81,15 @@ from litellm.types.responses.main import (
 from litellm.types.utils import GenericGuardrailAPIInputs
 
 if TYPE_CHECKING:
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    from fastapi import HTTPException
+
+    from litellm.integrations.custom_guardrail import (
+        CustomGuardrail,
+        ModifyResponseException,
+    )
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.proxy._types import UserAPIKeyAuth
     from litellm.types.llms.openai import ResponseInputParam
-    from litellm.types.utils import ResponsesAPIResponse
 
 
 class ResponseOutputEnvelope(TypedDict, total=False):
@@ -78,6 +104,18 @@ class ResponsesStreamChunk(TypedDict, total=False):
 
     type: ReadOnly[str]
     text: ReadOnly[str]
+    delta: ReadOnly[str]
+    item_id: ReadOnly[str]
+    output_index: ReadOnly[int]
+    content_index: ReadOnly[int]
+
+
+def _next_stream_sequence_number(responses_so_far: Sequence[Any] | None) -> int:
+    sequence_numbers: Final = (
+        item.get("sequence_number") if isinstance(item, dict) else getattr(item, "sequence_number", None)
+        for item in reversed(responses_so_far or ())
+    )
+    return next((n + 1 for n in sequence_numbers if isinstance(n, int)), 0)
 
 
 class OpenAIResponsesHandler(BaseTranslation):
@@ -620,11 +658,58 @@ class OpenAIResponsesHandler(BaseTranslation):
         }
         return responses_so_far[-1].get("type") in terminal_types
 
+    def build_stream_error_items(
+        self,
+        exc: "HTTPException",
+        responses_so_far: Sequence[Any] | None = None,
+    ) -> Sequence[Any] | None:
+        from litellm.proxy.common_request_processing import (
+            serialize_http_exception_detail,
+        )
+
+        message, _ = serialize_http_exception_detail(exc.detail)
+        return (
+            ErrorEvent(
+                type=ResponsesAPIStreamEvents.ERROR,
+                sequence_number=_next_stream_sequence_number(responses_so_far),
+                error=ErrorEventError(
+                    type="guardrail_error",
+                    code=str(exc.status_code),
+                    message=message,
+                    param=None,
+                ),
+            ),
+        )
+
     def get_streaming_string_so_far(self, responses_so_far: Sequence[ResponsesStreamChunk]) -> str:
         """
         Get the string so far from the responses so far.
+
+        ``response.output_text.done`` events carry the whole part in ``text``, while
+        ``response.output_text.delta`` events carry fragments in ``delta``. A stream
+        that dies before its done event (``response.failed`` / ``response.incomplete``)
+        has text only in deltas, so per content part the done text wins when present
+        and the joined deltas fill in otherwise, never both.
         """
-        return "".join([response.get("text", "") for response in responses_so_far])
+        keyed_events: Final = tuple(
+            (
+                (event.get("item_id"), event.get("output_index"), event.get("content_index")),
+                event.get("text"),
+                event.get("delta"),
+            )
+            for event in responses_so_far
+            if isinstance(event.get("text"), str) or isinstance(event.get("delta"), str)
+        )
+
+        def part_text(part_key: tuple[object, object, object]) -> str:
+            done_texts: Final = tuple(
+                text for key, text, _ in keyed_events if key == part_key and isinstance(text, str)
+            )
+            if done_texts:
+                return done_texts[-1]
+            return "".join(delta for key, _, delta in keyed_events if key == part_key and isinstance(delta, str))
+
+        return "".join(part_text(key) for key in dict.fromkeys(key for key, _, _ in keyed_events))
 
     def _has_text_content(self, response: "ResponsesAPIResponse") -> bool:
         """
@@ -802,3 +887,331 @@ class OpenAIResponsesHandler(BaseTranslation):
                         content[content_idx]["text"] = guardrail_response
                     elif hasattr(content[content_idx], "text"):
                         content[content_idx].text = guardrail_response
+
+    def build_block_sse_chunks(
+        self,
+        exc: "ModifyResponseException",
+        stream_started: bool = False,
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes]:
+        """
+        Build Responses API SSE events that deliver the guardrail block message
+        and terminate the stream cleanly, mirroring the non-streaming block
+        response: a completed response whose only output is the violation text,
+        with the real usage the upstream call consumed.
+
+        - ``stream_started`` False (buffered / pre-stream): nothing has been
+          sent, so emit the full synthetic sequence (``response.created``
+          through ``response.completed``).
+        - ``stream_started`` True (sampling / mid-stream): events already
+          reached the client, so continue the in-progress response: close the
+          output item still open on the wire, deliver the block message as a
+          new output item under the same response id, and close with a
+          ``response.completed`` carrying only the replacement item.
+
+        The proxy's data generator appends ``data: [DONE]`` itself.
+        """
+        events: Final = (
+            self._block_continuation_events(exc, responses_so_far or ())
+            if stream_started
+            else self._standalone_block_events(exc)
+        )
+        return tuple(
+            f"data: {event.model_dump_json(exclude_none=True, exclude_unset=True, serialize_as_any=True)}\n\n".encode()
+            for event in events
+        )
+
+    @staticmethod
+    def _standalone_block_events(exc: "ModifyResponseException") -> Sequence[ResponsesAPIStreamingResponse]:
+        from litellm.responses.streaming_iterator import build_synthetic_response_events
+
+        return build_synthetic_response_events(
+            transformed=_blocked_response(exc, response_id=f"resp_{uuid.uuid4()}", model=exc.model),
+            logging_obj=None,
+            chunk_size=max(len(exc.message), 1),
+        )
+
+    @staticmethod
+    def _block_continuation_events(
+        exc: "ModifyResponseException", responses_so_far: Sequence[object]
+    ) -> Sequence[ResponsesAPIStreamingResponse]:
+        response_id, model, output_index = _continuation_identity(exc, responses_so_far)
+        item: Final = _blocked_output_item(exc)
+        item_id: Final = item.id
+        part: Final[_BlockedContentPart] = {"type": "output_text", "text": exc.message, "annotations": ()}
+        done_part: Final[_BlockedDoneContentPart] = {
+            "type": "output_text",
+            "text": exc.message,
+            "annotations": (),
+            "logprobs": None,
+        }
+        return (
+            *_open_item_closing_events(responses_so_far),
+            OutputItemAddedEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
+                output_index=output_index,
+                item=item,
+            ),
+            ContentPartAddedEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_ADDED,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                part=BaseLiteLLMOpenAIResponseObject.model_validate(part),
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                delta=exc.message,
+            ),
+            OutputTextDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                text=exc.message,
+            ),
+            ContentPartDoneEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_DONE,
+                item_id=item_id,
+                output_index=output_index,
+                content_index=0,
+                part=ContentPartDonePartOutputText.model_validate(done_part),
+            ),
+            OutputItemDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+                output_index=output_index,
+                item=item,
+            ),
+            ResponseCompletedEvent(
+                type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
+                response=_blocked_response(exc, response_id=response_id, model=model, output_item=item),
+            ),
+        )
+
+
+class _BlockedContentPart(TypedDict):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+    annotations: ReadOnly[tuple[object, ...]]
+
+
+class _BlockedDoneContentPart(TypedDict):
+    type: ReadOnly[str]
+    text: ReadOnly[str]
+    annotations: ReadOnly[tuple[object, ...]]
+    logprobs: ReadOnly[None]
+
+
+class _BlockedItemPayload(TypedDict):
+    type: ReadOnly[str]
+    id: ReadOnly[str]
+    status: ReadOnly[str]
+    role: ReadOnly[str]
+    content: ReadOnly[tuple[_BlockedContentPart, ...]]
+
+
+class _BlockedResponsePayload(TypedDict):
+    id: ReadOnly[str]
+    object: ReadOnly[str]
+    created_at: ReadOnly[int]
+    model: ReadOnly[str]
+    output: ReadOnly[tuple[GenericResponseOutputItem, ...]]
+    status: ReadOnly[str]
+    usage: ReadOnly[ResponseAPIUsage]
+
+
+def _blocked_output_item(exc: "ModifyResponseException") -> GenericResponseOutputItem:
+    payload: Final[_BlockedItemPayload] = {
+        "type": "message",
+        "id": f"msg_{uuid.uuid4()}",
+        "status": "completed",
+        "role": "assistant",
+        "content": ({"type": "output_text", "text": exc.message, "annotations": ()},),
+    }
+    return GenericResponseOutputItem.model_validate(payload)
+
+
+def _blocked_response(
+    exc: "ModifyResponseException",
+    response_id: str,
+    model: str,
+    output_item: GenericResponseOutputItem | None = None,
+) -> ResponsesAPIResponse:
+    payload: Final[_BlockedResponsePayload] = {
+        "id": response_id,
+        "object": "response",
+        "created_at": int(time.time()),
+        "model": model,
+        "output": (output_item if output_item is not None else _blocked_output_item(exc),),
+        "status": "completed",
+        "usage": blocked_responses_stream_usage(exc.original_response),
+    }
+    return ResponsesAPIResponse.model_validate(payload)
+
+
+def _continuation_identity(exc: "ModifyResponseException", responses_so_far: Sequence[object]) -> tuple[str, str, int]:
+    responses: Final = tuple(
+        response for item in responses_so_far if (response := stream_item_field(item, "response")) is not None
+    )
+    response_id: Final = next(
+        (rid for response in responses if isinstance(rid := stream_item_field(response, "id"), str) and rid),
+        f"resp_{uuid.uuid4()}",
+    )
+    model: Final = next(
+        (m for response in responses if isinstance(m := stream_item_field(response, "model"), str) and m),
+        exc.model,
+    )
+    indices: Final = tuple(
+        index for item in responses_so_far if isinstance(index := stream_item_field(item, "output_index"), int)
+    )
+    return response_id, model, max(indices) + 1 if indices else 0
+
+
+@dataclass(frozen=True, slots=True)
+class _OpenItemState:
+    item_id: str
+    item_type: str
+    role: str
+    output_index: int
+    content_index: int
+    text: str
+    part_open: bool
+    payload: object
+
+
+def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | None:
+    typed: Final = tuple((stream_item_field(event, "type"), event) for event in responses_so_far)
+    added: Final = tuple(
+        (added_index, stream_item_field(event, "item"))
+        for event_type, event in typed
+        if event_type == "response.output_item.added"
+        and isinstance(added_index := stream_item_field(event, "output_index"), int)
+    )
+    done_indices: Final = frozenset(
+        done_index
+        for event_type, event in typed
+        if event_type == "response.output_item.done"
+        and isinstance(done_index := stream_item_field(event, "output_index"), int)
+    )
+    open_added: Final = tuple((index, payload) for index, payload in added if index not in done_indices)
+    if not open_added:
+        return None
+    output_index, item_payload = open_added[-1]
+    if item_payload is None:
+        return None
+    item_id: Final = stream_item_field(item_payload, "id")
+    if not isinstance(item_id, str) or not item_id:
+        return None
+    raw_type: Final = stream_item_field(item_payload, "type")
+    raw_role: Final = stream_item_field(item_payload, "role")
+    part_added: Final = tuple(
+        part_index
+        for event_type, event in typed
+        if event_type == "response.content_part.added"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(part_index := stream_item_field(event, "content_index"), int)
+    )
+    part_done: Final = frozenset(
+        part_done_index
+        for event_type, event in typed
+        if event_type == "response.content_part.done"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(part_done_index := stream_item_field(event, "content_index"), int)
+    )
+    open_parts: Final = tuple(index for index in part_added if index not in part_done)
+    text: Final = "".join(
+        delta
+        for event_type, event in typed
+        if event_type == "response.output_text.delta"
+        and stream_item_field(event, "item_id") == item_id
+        and isinstance(delta := stream_item_field(event, "delta"), str)
+    )
+    return _OpenItemState(
+        item_id=item_id,
+        item_type=raw_type if isinstance(raw_type, str) and raw_type else "message",
+        role=raw_role if isinstance(raw_role, str) and raw_role else "assistant",
+        output_index=output_index,
+        content_index=open_parts[-1] if open_parts else 0,
+        text=text,
+        part_open=bool(open_parts),
+        payload=item_payload,
+    )
+
+
+_item_fields_adapter: Final = TypeAdapter(Mapping[str, object])
+_no_item_fields: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def _incomplete_item_fields(payload: object) -> Mapping[str, object]:
+    raw: Final = payload.model_dump() if isinstance(payload, BaseModel) else payload
+    if not isinstance(raw, dict):
+        return _no_item_fields
+    return _item_fields_adapter.validate_python(raw)
+
+
+def _open_item_closing_events(responses_so_far: Sequence[object]) -> Sequence[ResponsesAPIStreamingResponse]:
+    """Close the output item still in progress on the relayed stream before the
+    block item is appended: strict Responses clients reject a
+    ``response.completed`` that arrives while an earlier ``output_item.added``
+    was never closed. A message item closes ``completed`` with exactly the text
+    the client has received so far; any other item type (a function call the
+    guardrail rejected, for instance) closes ``incomplete`` so the synthetic
+    done event can never authorize acting on it."""
+    open_item: Final = _open_item_state(responses_so_far)
+    if open_item is None:
+        return ()
+    if open_item.item_type != "message":
+        return (
+            OutputItemDoneEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+                output_index=open_item.output_index,
+                item=BaseLiteLLMOpenAIResponseObject.model_validate(
+                    MappingProxyType({**_incomplete_item_fields(open_item.payload), "status": "incomplete"})
+                ),
+            ),
+        )
+    partial_part: Final[_BlockedContentPart] = {
+        "type": "output_text",
+        "text": open_item.text,
+        "annotations": (),
+    }
+    closed_payload: Final[_BlockedItemPayload] = {
+        "type": open_item.item_type,
+        "id": open_item.item_id,
+        "status": "completed",
+        "role": open_item.role,
+        "content": (partial_part,),
+    }
+    item_done: Final = OutputItemDoneEvent(
+        type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
+        output_index=open_item.output_index,
+        item=GenericResponseOutputItem.model_validate(closed_payload),
+    )
+    if not open_item.part_open:
+        return (item_done,)
+    partial_done_part: Final[_BlockedDoneContentPart] = {
+        "type": "output_text",
+        "text": open_item.text,
+        "annotations": (),
+        "logprobs": None,
+    }
+    return (
+        OutputTextDoneEvent(
+            type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE,
+            item_id=open_item.item_id,
+            output_index=open_item.output_index,
+            content_index=open_item.content_index,
+            text=open_item.text,
+        ),
+        ContentPartDoneEvent(
+            type=ResponsesAPIStreamEvents.CONTENT_PART_DONE,
+            item_id=open_item.item_id,
+            output_index=open_item.output_index,
+            content_index=open_item.content_index,
+            part=ContentPartDonePartOutputText.model_validate(partial_done_part),
+        ),
+        item_done,
+    )
diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py
index eac844a790d..01313e95878 100644
--- a/litellm/llms/openai/responses/transformation.py
+++ b/litellm/llms/openai/responses/transformation.py
@@ -1,10 +1,11 @@
 from collections.abc import Mapping, Sequence
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, cast, get_type_hints
+from typing import TYPE_CHECKING, Any, Final, Protocol, cast, get_type_hints
 
 import httpx
 from openai.types.responses import ResponseReasoningItem
 from pydantic import BaseModel, ValidationError
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -14,6 +15,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo
 )
 from litellm.litellm_core_utils.url_utils import encode_url_path_segment
 from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
+from litellm.responses.litellm_completion_transformation.custom_tools import TOOL_CALL_ITEM_ID_PREFIX_BY_TYPE
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import *
 from litellm.types.responses.main import *
@@ -21,6 +23,7 @@ from litellm.types.router import GenericLiteLLMParams
 from litellm.types.utils import LlmProviders
 
 from ..common_utils import OpenAIError
+from ..workload_identity import get_workload_identity_bearer_token, resolve_openai_workload_identity_config
 
 OPENAI_RESPONSES_API_MIN_MAX_OUTPUT_TOKENS: Final = 16
 
@@ -34,6 +37,37 @@ else:
 _NO_TOOL_UPDATE: Final[Mapping[str, object]] = MappingProxyType({})
 _MODEL_FAMILIES_REJECTING_TOP_LEVEL_SCHEMA_COMBINATORS: Final = ("gpt-4", "gpt-3.5", "chatgpt-4o", "o1", "o3", "o4")
 _PROVIDERS_WITH_COMBINATOR_REJECTING_VALIDATOR: Final = frozenset({LlmProviders.AZURE, LlmProviders.OPENAI})
+_PROVIDERS_VALIDATING_TOOL_CALL_ITEM_IDS: Final = frozenset({LlmProviders.AZURE, LlmProviders.OPENAI})
+
+
+class _DeleteResponseBody(TypedDict):
+    """Decoded body of the Responses API delete call."""
+
+    id: ReadOnly[str | None]
+    object: ReadOnly[str | None]
+    deleted: ReadOnly[bool | None]
+
+
+class _DeleteResponse(Protocol):
+    """The delete call's HTTP response, read for the decoded body it carries."""
+
+    def json(self) -> _DeleteResponseBody: ...
+
+
+class _JsonObjectResponse(Protocol):
+    """A Responses API HTTP response, read for the JSON object it decodes to."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _delete_response_body(response: _DeleteResponse) -> _DeleteResponseBody:
+    """Decode a delete response body into the id, object and deleted fields it carries."""
+    return response.json()
+
+
+def _json_object_body(response: _JsonObjectResponse) -> dict[str, object]:
+    """Decode a Responses API response body into its JSON object form."""
+    return response.json()
 
 
 class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
@@ -178,8 +212,9 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         )
         if sanitized_tools is not None:
             response_api_optional_request_params["tools"] = sanitized_tools
+        replay_safe_input: Final = self._drop_foreign_tool_call_item_ids(input)
         final_request_params: Final = dict(
-            ResponsesAPIRequestParams(model=model, input=input, **response_api_optional_request_params)
+            ResponsesAPIRequestParams(model=model, input=replay_safe_input, **response_api_optional_request_params)
         )
 
         return final_request_params
@@ -216,6 +251,23 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
 
         return input, tools
 
+    def _drop_foreign_tool_call_item_ids(self, input: str | ResponseInputParam) -> str | ResponseInputParam:
+        if self.custom_llm_provider not in _PROVIDERS_VALIDATING_TOOL_CALL_ITEM_IDS or not isinstance(input, list):
+            return input
+        sanitized_items: Final = [self._without_foreign_tool_call_item_id(item) for item in input]
+        return cast("ResponseInputParam", sanitized_items)  # cast-ok: items keep their shape, minus a rejected id
+
+    @staticmethod
+    def _without_foreign_tool_call_item_id(item: object) -> object:
+        if not isinstance(item, dict):
+            return item
+        item_type: Final = item.get("type")
+        item_id: Final = item.get("id")
+        genuine_prefix: Final = TOOL_CALL_ITEM_ID_PREFIX_BY_TYPE.get(item_type) if isinstance(item_type, str) else None
+        if genuine_prefix is None or not isinstance(item_id, str) or item_id.startswith(genuine_prefix):
+            return item
+        return {key: value for key, value in item.items() if key != "id"}  # mutable-ok: outgoing JSON request item
+
     def _flatten_tool_schema_combinators_for_openai(
         self,
         model: str,
@@ -392,6 +444,14 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         litellm_params = litellm_params or GenericLiteLLMParams()
         api_key = litellm_params.api_key or litellm.api_key or litellm.openai_key or get_secret_str("OPENAI_API_KEY")
         headers.setdefault("Content-Type", "application/json")
+        workload_identity_config: Final = (
+            resolve_openai_workload_identity_config(api_key=api_key, api_base=litellm_params.api_base)
+            if self.custom_llm_provider is LlmProviders.OPENAI
+            else None
+        )
+        if workload_identity_config is not None:
+            headers["Authorization"] = f"Bearer {get_workload_identity_bearer_token(workload_identity_config)}"
+            return headers
         headers["Authorization"] = f"Bearer {api_key}"
         return headers
 
@@ -460,7 +520,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         return None
 
     @staticmethod
-    def get_event_model_class(event_type: str) -> Any:
+    def get_event_model_class(event_type: str) -> type[BaseLiteLLMOpenAIResponseObject]:
         """
         Returns the appropriate event model class based on the event type.
 
@@ -574,7 +634,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the delete response API response into a DeleteResponseResult
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _delete_response_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         return DeleteResponseResult(**raw_response_json)
@@ -609,7 +669,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the get response API response into a ResponsesAPIResponse
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         raw_response_headers: Final = dict(raw_response.headers)
@@ -637,7 +697,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
     ) -> tuple[str, dict]:
         encoded_response_id: Final = encode_url_path_segment(response_id, field_name="response_id")
         url: Final = f"{api_base}/{encoded_response_id}/input_items"
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
         if after is not None:
             params["after"] = after
         if before is not None:
@@ -656,7 +716,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> dict:
         try:
-            return raw_response.json()
+            return _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
 
@@ -690,7 +750,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the cancel response API response into a ResponsesAPIResponse
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         raw_response_headers: Final = dict(raw_response.headers)
@@ -733,7 +793,10 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         )
         if sanitized_tools is not None:
             response_api_optional_request_params["tools"] = sanitized_tools
-        data: Final = dict(ResponsesAPIRequestParams(model=model, input=input, **response_api_optional_request_params))
+        replay_safe_input: Final = self._drop_foreign_tool_call_item_ids(input)
+        data: Final = dict(
+            ResponsesAPIRequestParams(model=model, input=replay_safe_input, **response_api_optional_request_params)
+        )
 
         return url, data
 
diff --git a/litellm/llms/openai/vector_stores/transformation.py b/litellm/llms/openai/vector_stores/transformation.py
index f6c093f2e2a..4e925494039 100644
--- a/litellm/llms/openai/vector_stores/transformation.py
+++ b/litellm/llms/openai/vector_stores/transformation.py
@@ -21,6 +21,7 @@ from litellm.utils import add_openai_metadata
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -99,6 +100,7 @@ class OpenAIVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
         url: Final = f"{api_base}/{encoded_vector_store_id}/search"
diff --git a/litellm/llms/openai/workload_identity.py b/litellm/llms/openai/workload_identity.py
new file mode 100644
index 00000000000..ecec161ed46
--- /dev/null
+++ b/litellm/llms/openai/workload_identity.py
@@ -0,0 +1,100 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from functools import lru_cache
+from typing import TYPE_CHECKING, Final
+from urllib.parse import urlparse
+
+import litellm
+from litellm.secret_managers.main import get_secret_str, normalize_nonempty_secret_str
+
+from .common_utils import OpenAIError
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
+    from openai.auth import SubjectTokenProvider, WorkloadIdentity, WorkloadIdentityAuth
+
+OPENAI_WIF_CLIENT_ID: Final = "litellm"
+_OPENAI_API_HOST: Final = "api.openai.com"
+_SDK_UPGRADE_MESSAGE: Final = (
+    "OpenAI workload identity federation requires openai>=2.32.0. "
+    "Upgrade the installed openai package to use OPENAI_IDENTITY_PROVIDER_ID / "
+    "OPENAI_SERVICE_ACCOUNT_ID / OPENAI_IDENTITY_TOKEN_FILE."
+)
+
+
+@dataclass(frozen=True, slots=True)
+class OpenAIWorkloadIdentityConfig:
+    identity_provider_id: str
+    service_account_id: str
+    token_file: str
+
+    def to_sdk_workload_identity(self) -> WorkloadIdentity:
+        k8s_token_provider: Final = _load_sdk_k8s_token_provider()
+        workload_identity: Final[WorkloadIdentity] = {
+            "client_id": OPENAI_WIF_CLIENT_ID,
+            "identity_provider_id": self.identity_provider_id,
+            "service_account_id": self.service_account_id,
+            "provider": k8s_token_provider(self.token_file),
+        }
+        return workload_identity
+
+
+def resolve_openai_workload_identity_config(
+    api_key: str | None,
+    api_base: str | None,
+) -> OpenAIWorkloadIdentityConfig | None:
+    static_api_key: Final = normalize_nonempty_secret_str(api_key) or normalize_nonempty_secret_str(
+        get_secret_str("OPENAI_API_KEY")
+    )
+    if static_api_key is not None:
+        return None
+    effective_api_base: Final = (
+        api_base or litellm.api_base or get_secret_str("OPENAI_BASE_URL") or get_secret_str("OPENAI_API_BASE")
+    )
+    if not _targets_openai_api(effective_api_base):
+        return None
+    identity_provider_id: Final = get_secret_str("OPENAI_IDENTITY_PROVIDER_ID")
+    service_account_id: Final = get_secret_str("OPENAI_SERVICE_ACCOUNT_ID")
+    token_file: Final = get_secret_str("OPENAI_IDENTITY_TOKEN_FILE")
+    if not identity_provider_id or not service_account_id or not token_file:
+        return None
+    return OpenAIWorkloadIdentityConfig(
+        identity_provider_id=identity_provider_id,
+        service_account_id=service_account_id,
+        token_file=token_file,
+    )
+
+
+def get_workload_identity_bearer_token(config: OpenAIWorkloadIdentityConfig) -> str:
+    return _workload_identity_auth(config).get_token()
+
+
+def _targets_openai_api(api_base: str | None) -> bool:
+    if api_base is None:
+        return True
+    parsed: Final = urlparse(api_base)
+    return parsed.scheme == "https" and parsed.hostname == _OPENAI_API_HOST
+
+
+@lru_cache(maxsize=16)
+def _workload_identity_auth(config: OpenAIWorkloadIdentityConfig) -> WorkloadIdentityAuth:
+    sdk_workload_identity_auth: Final = _load_sdk_workload_identity_auth()
+    return sdk_workload_identity_auth(workload_identity=config.to_sdk_workload_identity())
+
+
+def _load_sdk_workload_identity_auth() -> type[WorkloadIdentityAuth]:
+    try:
+        from openai.auth import WorkloadIdentityAuth as sdk_workload_identity_auth
+    except ImportError as e:
+        raise OpenAIError(status_code=500, message=_SDK_UPGRADE_MESSAGE) from e
+    return sdk_workload_identity_auth
+
+
+def _load_sdk_k8s_token_provider() -> Callable[[str], SubjectTokenProvider]:
+    try:
+        from openai.auth import k8s_service_account_token_provider
+    except ImportError as e:
+        raise OpenAIError(status_code=500, message=_SDK_UPGRADE_MESSAGE) from e
+    return k8s_service_account_token_provider
diff --git a/litellm/llms/openai_like/README.md b/litellm/llms/openai_like/README.md
index e9aaafe48a1..e1409b81c35 100644
--- a/litellm/llms/openai_like/README.md
+++ b/litellm/llms/openai_like/README.md
@@ -54,7 +54,10 @@ That's it! The provider will be automatically loaded and available.
     "constraints": {
       "temperature_max": 1.0,
       "temperature_min": 0.0,
-      "temperature_min_with_n_gt_1": 0.3
+      "temperature_min_with_n_gt_1": 0.3,
+      // /v1/messages providers only: keep Anthropic cache_control extensions
+      // such as ttl instead of stripping them down to {"type": ...}
+      "cache_control_ttl": true
     },
     
     // Optional: Special handling flags
diff --git a/litellm/llms/openai_like/chat/handler.py b/litellm/llms/openai_like/chat/handler.py
index 8c548b6b0d6..855c49c320b 100644
--- a/litellm/llms/openai_like/chat/handler.py
+++ b/litellm/llms/openai_like/chat/handler.py
@@ -5,10 +5,11 @@ For handling OpenAI-like chat completions, like IBM WatsonX, etc.
 """
 
 import json
-from collections.abc import Callable
-from typing import Any, Final
+from collections.abc import Callable, Mapping, Sequence
+from typing import Final, TypedDict
 
 import httpx
+from typing_extensions import ReadOnly
 
 import litellm
 from litellm import LlmProviders
@@ -25,6 +26,23 @@ from ..common_utils import OpenAILikeBase, OpenAILikeError
 from .transformation import OpenAILikeChatConfig
 
 
+class _OpenAILikeChatCompletion(TypedDict, total=False):
+    """The chat-completion JSON body an OpenAI-like provider returns for a non-streamed call."""
+
+    id: ReadOnly[str]
+    choices: ReadOnly[Sequence[Mapping[str, object]]]
+    created: ReadOnly[int]
+    model: ReadOnly[str]
+    system_fingerprint: ReadOnly[str]
+    usage: ReadOnly[Mapping[str, object]]
+    object: ReadOnly[str]
+
+
+def _fake_streamed_model_response(payload: _OpenAILikeChatCompletion) -> ModelResponse:
+    """Build the single response a fake-streamed provider call replays as one chunk."""
+    return ModelResponse(**payload)
+
+
 async def make_call(
     client: AsyncHTTPHandler | None,
     api_base: str,
@@ -42,9 +60,9 @@ async def make_call(
     response: Final = await client.post(api_base, headers=headers, data=data, stream=not fake_stream)
 
     if streaming_decoder is not None:
-        completion_stream: Any = streaming_decoder.aiter_bytes(response.aiter_bytes(chunk_size=1024))
+        completion_stream = streaming_decoder.aiter_bytes(response.aiter_bytes(chunk_size=1024))
     elif fake_stream:
-        model_response: Final = ModelResponse(**response.json())
+        model_response: Final = _fake_streamed_model_response(response.json())
         completion_stream = MockResponseIterator(model_response=model_response)
     else:
         completion_stream = ModelResponseIterator(streaming_response=response.aiter_lines(), sync_stream=False)
@@ -82,7 +100,7 @@ def make_sync_call(
     if streaming_decoder is not None:
         completion_stream = streaming_decoder.iter_bytes(response.iter_bytes(chunk_size=1024))
     elif fake_stream:
-        model_response: Final = ModelResponse(**response.json())
+        model_response: Final = _fake_streamed_model_response(response.json())
         completion_stream = MockResponseIterator(model_response=model_response)
     else:
         completion_stream = ModelResponseIterator(streaming_response=response.iter_lines(), sync_stream=True)
diff --git a/litellm/llms/openai_like/messages/transformation.py b/litellm/llms/openai_like/messages/transformation.py
index 11dc236064d..ac99617521c 100644
--- a/litellm/llms/openai_like/messages/transformation.py
+++ b/litellm/llms/openai_like/messages/transformation.py
@@ -1,11 +1,13 @@
 from typing import Any, Final
 
 import litellm
+from litellm.llms.anthropic.common_utils import normalize_cache_control_in_anthropic_payload
 from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
     AnthropicMessagesConfig,
 )
 from litellm.llms.openai_like.json_loader import SimpleProviderConfig
 from litellm.secret_managers.main import get_secret_str
+from litellm.types.router import GenericLiteLLMParams
 
 DEFAULT_ANTHROPIC_API_VERSION: Final = "2023-06-01"
 
@@ -19,10 +21,17 @@ class OpenAILikeAnthropicMessagesConfig(AnthropicMessagesConfig):
     ``"/v1/messages"``. The inbound Anthropic payload (system, cache_control,
     thinking, tools, ...) is forwarded essentially unchanged to
     ``{api_base}/v1/messages``, so Anthropic-only features that the
-    Anthropic->OpenAI translation would otherwise drop are preserved. Response
-    parsing and streaming are inherited from the native Anthropic config.
+    Anthropic->OpenAI translation would otherwise drop are preserved. The one
+    exception is ``cache_control``, whose Anthropic-only extensions (``ttl``)
+    are stripped unless the deployment opts in with
+    ``model_info.cache_control_ttl: true``. Response parsing and streaming are
+    inherited from the native Anthropic config.
     """
 
+    def __init__(self, cache_control_ttl: bool = False) -> None:
+        super().__init__()
+        self._cache_control_ttl: Final = cache_control_ttl
+
     def validate_anthropic_messages_environment(
         self,
         headers: dict[str, str],
@@ -53,6 +62,35 @@ class OpenAILikeAnthropicMessagesConfig(AnthropicMessagesConfig):
     def should_filter_anthropic_beta_headers(self) -> bool:
         return False
 
+    def supports_cache_control_ttl(self) -> bool:
+        return self._cache_control_ttl
+
+    def transform_anthropic_messages_request(
+        self,
+        model: str,
+        messages: list[dict],  # mutable-ok: matches dict-typed base signature
+        anthropic_messages_optional_request_params: dict,  # mutable-ok: matches dict-typed base signature
+        litellm_params: GenericLiteLLMParams,
+        headers: dict,  # mutable-ok: matches dict-typed base signature
+    ) -> dict:  # mutable-ok: matches dict-typed base signature
+        """
+        Anthropic ignores prompt-caching hints it cannot honor, but strict
+        non-Anthropic implementations of the Messages API 400 the whole request
+        on Anthropic-only ``cache_control`` extensions (``cache_control.ttl: 1h
+        is not supported``), so unless the provider declares ttl support the
+        hints are reduced to their portable ``{"type": ...}`` core.
+        """
+        request: Final = super().transform_anthropic_messages_request(
+            model=model,
+            messages=messages,
+            anthropic_messages_optional_request_params=anthropic_messages_optional_request_params,
+            litellm_params=litellm_params,
+            headers=headers,
+        )
+        if self.supports_cache_control_ttl():
+            return request
+        return normalize_cache_control_in_anthropic_payload(request)
+
     def get_complete_url(
         self,
         api_base: str | None,
@@ -81,7 +119,7 @@ class JSONProviderAnthropicMessagesConfig(OpenAILikeAnthropicMessagesConfig):
     """
 
     def __init__(self, provider: SimpleProviderConfig):
-        super().__init__()
+        super().__init__(cache_control_ttl=bool(provider.constraints.get("cache_control_ttl")))
         self._provider = provider
 
     @property
diff --git a/litellm/llms/opensandbox/sandbox/transformation.py b/litellm/llms/opensandbox/sandbox/transformation.py
index 49a7fb08c4a..5126db9bbc9 100644
--- a/litellm/llms/opensandbox/sandbox/transformation.py
+++ b/litellm/llms/opensandbox/sandbox/transformation.py
@@ -1,7 +1,7 @@
 import asyncio
 import json
 import time
-from typing import Final, cast
+from typing import Final
 
 import httpx
 
@@ -86,13 +86,10 @@ class OpenSandboxSandboxConfig(BaseSandboxConfig):
             secure_access=secure_access,
         )
 
-        response: Final = cast(
-            httpx.Response,
-            await self._http(client).post(
-                url=f"{base}/sandboxes",
-                headers=self._lifecycle_headers(key),
-                json=body,
-            ),
+        response: Final = await self._http(client).post(
+            url=f"{base}/sandboxes",
+            headers=self._lifecycle_headers(key),
+            json=body,
         )
         data: Final = response.json()
         sandbox_id: Final = str(data["id"])
@@ -182,12 +179,9 @@ class OpenSandboxSandboxConfig(BaseSandboxConfig):
         base: Final = str(handle._hidden_params.get("api_base") or self._api_base(api_base))
         key: Final = self._api_key(api_key=api_key, handle=handle)
         try:
-            response: Final = cast(
-                httpx.Response,
-                await self._http(client).delete(
-                    url=f"{base}/sandboxes/{handle.id}",
-                    headers=self._lifecycle_headers(key),
-                ),
+            response: Final = await self._http(client).delete(
+                url=f"{base}/sandboxes/{handle.id}",
+                headers=self._lifecycle_headers(key),
             )
         except httpx.HTTPStatusError as e:
             if e.response.status_code == 404:
@@ -245,12 +239,9 @@ class OpenSandboxSandboxConfig(BaseSandboxConfig):
     ) -> None:
         deadline: Final = time.monotonic() + ready_timeout
         while True:
-            response = cast(
-                httpx.Response,
-                await self._http(client).get(
-                    url=f"{api_base}/sandboxes/{sandbox_id}",
-                    headers=headers,
-                ),
+            response = await self._http(client).get(
+                url=f"{api_base}/sandboxes/{sandbox_id}",
+                headers=headers,
             )
             data = response.json()
             state = self._sandbox_state(data)
@@ -306,13 +297,10 @@ class OpenSandboxSandboxConfig(BaseSandboxConfig):
         use_server_proxy: bool,
         client: AsyncHTTPHandler | None,
     ) -> tuple[str, dict[str, str]]:
-        response: Final = cast(
-            httpx.Response,
-            await self._http(client).get(
-                url=f"{api_base}/sandboxes/{sandbox_id}/endpoints/{OPEN_SANDBOX_EXECD_PORT}",
-                headers=headers,
-                params={"use_server_proxy": use_server_proxy},
-            ),
+        response: Final = await self._http(client).get(
+            url=f"{api_base}/sandboxes/{sandbox_id}/endpoints/{OPEN_SANDBOX_EXECD_PORT}",
+            headers=headers,
+            params={"use_server_proxy": use_server_proxy},
         )
         data: Final = response.json()
         endpoint: Final = data.get("endpoint")
@@ -329,15 +317,12 @@ class OpenSandboxSandboxConfig(BaseSandboxConfig):
         client: AsyncHTTPHandler | None,
     ) -> list[str]:
         timeout: Final = httpx.Timeout(connect=30.0, read=None, write=30.0, pool=None)
-        response: Final = cast(
-            httpx.Response,
-            await self._http(client).post(
-                url=url,
-                headers=headers,
-                timeout=timeout,
-                json=body,
-                stream=True,
-            ),
+        response: Final = await self._http(client).post(
+            url=url,
+            headers=headers,
+            timeout=timeout,
+            json=body,
+            stream=True,
         )
         return await self._read_capped_lines(response)
 
diff --git a/litellm/llms/parallel_ai/search/cost_calculator.py b/litellm/llms/parallel_ai/search/cost_calculator.py
new file mode 100644
index 00000000000..809cd280cc8
--- /dev/null
+++ b/litellm/llms/parallel_ai/search/cost_calculator.py
@@ -0,0 +1,90 @@
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
+from typing import Final
+
+from pydantic import TypeAdapter, ValidationError
+
+from litellm.utils import get_model_info
+
+PARALLEL_AI_DEFAULT_RESULTS: Final = 10
+PARALLEL_AI_ADDITIONAL_RESULT_COST: Final = 0.001
+PARALLEL_AI_USAGE_PARAM: Final = "_parallel_ai_usage"
+PARALLEL_AI_STANDARD_SEARCH_MODEL: Final = "parallel_ai/search"
+PARALLEL_AI_FAST_SEARCH_MODEL: Final = "parallel_ai/search-fast"
+PARALLEL_AI_TURBO_SEARCH_MODEL: Final = "parallel_ai/search-turbo"
+PARALLEL_AI_PRICING_MODEL_BY_MODE: Final[Mapping[str, str]] = MappingProxyType(
+    {
+        "fast": PARALLEL_AI_FAST_SEARCH_MODEL,
+        "turbo": PARALLEL_AI_TURBO_SEARCH_MODEL,
+    }
+)
+ADVANCED_SETTINGS_ADAPTER: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object])
+
+
+def _non_negative_int(value: object) -> int | None:
+    if isinstance(value, bool) or not isinstance(value, int) or value < 0:
+        return None
+    return value
+
+
+def _usage_count(usage: Sequence[Mapping[str, object]], sku: str) -> int | None:
+    counts: Final = tuple(
+        count
+        for item in usage
+        if item.get("name") == sku
+        if (count := _non_negative_int(item.get("count"))) is not None
+    )
+    return sum(counts) if counts else None
+
+
+def _effective_mode(optional_params: Mapping[str, object]) -> str:
+    mode: Final = optional_params.get("mode")
+    if isinstance(mode, str):
+        return mode
+
+    processor: Final = optional_params.get("processor")
+    if processor == "pro":
+        return "advanced"
+    return "basic"
+
+
+def _effective_max_results(optional_params: Mapping[str, object]) -> int:
+    try:
+        advanced_settings: Final = ADVANCED_SETTINGS_ADAPTER.validate_python(optional_params.get("advanced_settings"))
+        advanced_max_results: Final = _non_negative_int(advanced_settings.get("max_results"))
+        if advanced_max_results is not None:
+            return advanced_max_results
+    except ValidationError:
+        pass
+
+    max_results: Final = _non_negative_int(optional_params.get("max_results"))
+    return max_results if max_results is not None else PARALLEL_AI_DEFAULT_RESULTS
+
+
+def _request_cost(mode: str) -> float:
+    pricing_model: Final = PARALLEL_AI_PRICING_MODEL_BY_MODE.get(mode, PARALLEL_AI_STANDARD_SEARCH_MODEL)
+    model_info: Final = get_model_info(model=pricing_model, custom_llm_provider="parallel_ai")
+    return float(model_info.get("input_cost_per_query") or 0.0)
+
+
+def _additional_results(
+    optional_params: Mapping[str, object],
+    usage: Sequence[Mapping[str, object]] | None,
+) -> int:
+    usage_count: Final = _usage_count(usage, "sku_search_additional_results") if usage is not None else None
+    if usage_count is not None:
+        return usage_count
+    if usage is not None:
+        return 0
+    return max(_effective_max_results(optional_params) - PARALLEL_AI_DEFAULT_RESULTS, 0)
+
+
+def parallel_ai_search_cost(
+    optional_params: Mapping[str, object],
+    usage: Sequence[Mapping[str, object]] | None,
+) -> float:
+    request_cost: Final = _request_cost(_effective_mode(optional_params))
+    request_count_from_usage: Final = _usage_count(usage, "sku_search") if usage is not None else None
+    request_count: Final = request_count_from_usage if request_count_from_usage is not None else 1
+    additional_results: Final = _additional_results(optional_params, usage)
+    return request_count * request_cost + additional_results * PARALLEL_AI_ADDITIONAL_RESULT_COST
diff --git a/litellm/llms/parallel_ai/search/transformation.py b/litellm/llms/parallel_ai/search/transformation.py
index ea21d1153fe..bde7b7b86db 100644
--- a/litellm/llms/parallel_ai/search/transformation.py
+++ b/litellm/llms/parallel_ai/search/transformation.py
@@ -4,9 +4,13 @@ Calls Parallel AI's /v1/search endpoint to search the web.
 Parallel AI API Reference: https://docs.parallel.ai/api-reference/search/search
 """
 
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import Final, TypedDict
 
 import httpx
+from pydantic import BaseModel, ConfigDict
+from typing_extensions import ReadOnly
 
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.search.transformation import (
@@ -14,9 +18,29 @@ from litellm.llms.base_llm.search.transformation import (
     SearchResponse,
     SearchResult,
 )
+from litellm.llms.parallel_ai.search.cost_calculator import PARALLEL_AI_USAGE_PARAM
 from litellm.secret_managers.main import get_secret_str
 
 
+class _ParallelAIV1SearchResult(BaseModel):
+    model_config = ConfigDict(extra="ignore")
+
+    url: str | None = None
+    title: str | None = None
+    publish_date: str | None = None
+    excerpts: Sequence[str] | None = None
+
+
+class _ParallelAIV1SearchResponse(BaseModel):
+    model_config = ConfigDict(extra="ignore")
+
+    search_id: str | None = None
+    session_id: str | None = None
+    results: Sequence[_ParallelAIV1SearchResult] = ()
+    usage: Sequence[Mapping[str, object]] | None = None
+    warnings: Sequence[Mapping[str, object]] | None = None
+
+
 class _ParallelAISourcePolicy(TypedDict, total=False):
     include_domains: list[str]
     exclude_domains: list[str]
@@ -27,10 +51,16 @@ class _ParallelAIExcerptSettings(TypedDict, total=False):
     max_chars_per_result: int
 
 
+class _ParallelAIFetchPolicy(TypedDict, total=False):
+    max_age_seconds: ReadOnly[int]
+    timeout_seconds: ReadOnly[float]
+    disable_cache_fallback: ReadOnly[bool]
+
+
 class _ParallelAIAdvancedSettings(TypedDict, total=False):
     source_policy: _ParallelAISourcePolicy
     excerpt_settings: _ParallelAIExcerptSettings
-    fetch_policy: dict
+    fetch_policy: _ParallelAIFetchPolicy
     location: str
     max_results: int
 
@@ -43,14 +73,14 @@ class ParallelAISearchRequest(TypedDict, total=False):
 
     search_queries: list[str]  # Required - at least one keyword search query
     objective: str  # Optional - natural-language description of search goal
-    mode: str  # Optional - 'turbo', 'basic', or 'advanced' (default 'advanced')
+    mode: str  # Optional - 'turbo', 'fast', 'basic', or 'advanced' (default 'advanced')
     max_chars_total: int  # Optional - upper bound on total excerpt characters
     session_id: str  # Optional - tracks calls across search/extract requests
     client_model: str  # Optional - model consuming the results
     advanced_settings: _ParallelAIAdvancedSettings
 
 
-LEGACY_PROCESSOR_TO_MODE: Final = {"base": "basic", "pro": "advanced"}
+LEGACY_PROCESSOR_TO_MODE: Final = MappingProxyType({"base": "basic", "pro": "advanced"})
 
 
 class ParallelAISearchConfig(BaseSearchConfig):
@@ -67,16 +97,16 @@ class ParallelAISearchConfig(BaseSearchConfig):
         api_base: str | None = None,
         **kwargs,
     ) -> dict:
-        api_key = self.resolve_server_api_key(
+        resolved_api_key: Final = self.resolve_server_api_key(
             caller_api_key=api_key,
             caller_api_base=api_base,
             key_env_vars=("PARALLEL_AI_API_KEY", "PARALLEL_API_KEY"),
             base_env_var="PARALLEL_AI_API_BASE",
             default_api_base=self.PARALLEL_AI_API_BASE,
         )
-        if not api_key:
+        if not resolved_api_key:
             raise ValueError("PARALLEL_API_KEY is not set. Set `PARALLEL_API_KEY` environment variable.")
-        headers["x-api-key"] = api_key
+        headers["x-api-key"] = resolved_api_key
         headers["Content-Type"] = "application/json"
         return headers
 
@@ -87,13 +117,12 @@ class ParallelAISearchConfig(BaseSearchConfig):
         data: dict | list[dict] | None = None,
         **kwargs,
     ) -> str:
-        api_base = api_base or get_secret_str("PARALLEL_AI_API_BASE") or self.PARALLEL_AI_API_BASE
+        resolved_api_base: Final = api_base or get_secret_str("PARALLEL_AI_API_BASE") or self.PARALLEL_AI_API_BASE
 
-        api_base = api_base.rstrip("/")
-        if not api_base.endswith("/v1/search"):
-            api_base = f"{api_base.removesuffix('/v1')}/v1/search"
-
-        return api_base
+        trimmed: Final = resolved_api_base.rstrip("/")
+        if trimmed.endswith("/v1/search"):
+            return trimmed
+        return f"{trimmed.removesuffix('/v1')}/v1/search"
 
     def transform_search_request(
         self,
@@ -109,14 +138,17 @@ class ParallelAISearchConfig(BaseSearchConfig):
                 - If string: maps to `search_queries` (single item) and `objective`
                 - If list: maps to `search_queries` (keyword queries)
             optional_params: Optional parameters for the request
-                - mode: Search mode ('turbo', 'basic', 'advanced'); defaults to 'basic'
+                - mode: Search mode ('turbo', 'fast', 'basic', 'advanced'); defaults to 'basic'
                 - processor: Legacy v1beta param; 'base' maps to mode 'basic', 'pro' to 'advanced'
                 - max_results: Maximum number of search results -> `advanced_settings.max_results`
-                - search_domain_filter: Domains to include -> `advanced_settings.source_policy.include_domains`
+                - search_domain_filter / include_domains: Domains to include -> `advanced_settings.source_policy.include_domains`
                 - exclude_domains: Domains to exclude -> `advanced_settings.source_policy.exclude_domains`
-                - country: ISO 3166-1 alpha-2 code -> `advanced_settings.location`
+                - after_date: RFC 3339 date (YYYY-MM-DD) -> `advanced_settings.source_policy.after_date`
+                - country / location: ISO 3166-1 alpha-2 code -> `advanced_settings.location`
                 - max_chars_per_result: -> `advanced_settings.excerpt_settings.max_chars_per_result`
-                - Any other params are passed through to the request body as-is
+                - fetch_policy: Cache vs live-fetch policy -> `advanced_settings.fetch_policy`
+                - Any other params (objective, max_chars_total, session_id, client_model, ...)
+                  are passed through to the request body as-is
 
         Returns:
             Dict with request data following the v1 search request spec
@@ -137,7 +169,7 @@ class ParallelAISearchConfig(BaseSearchConfig):
             mode = LEGACY_PROCESSOR_TO_MODE.get(processor, processor)
         # the v1 API defaults to 'advanced' when mode is omitted; default to 'basic'
         # instead to keep v1beta's default tier (processor 'base') and litellm's
-        # $0.004/query cost map entry for `parallel_ai/search` accurate
+        # cost map entry for `parallel_ai/search` accurate
         request_data["mode"] = mode or "basic"
 
         advanced_settings: Final[_ParallelAIAdvancedSettings] = {}
@@ -148,17 +180,29 @@ class ParallelAISearchConfig(BaseSearchConfig):
         if "country" in params:
             advanced_settings["location"] = params.pop("country")
 
+        if "location" in params:
+            advanced_settings["location"] = params.pop("location")
+
         if "max_chars_per_result" in params:
             advanced_settings["excerpt_settings"] = {"max_chars_per_result": params.pop("max_chars_per_result")}
 
+        if "fetch_policy" in params:
+            advanced_settings["fetch_policy"] = params.pop("fetch_policy")
+
         source_policy: Final[_ParallelAISourcePolicy] = {}
 
         if "search_domain_filter" in params:
             source_policy["include_domains"] = params.pop("search_domain_filter")
 
+        if "include_domains" in params:
+            source_policy["include_domains"] = params.pop("include_domains")
+
         if "exclude_domains" in params:
             source_policy["exclude_domains"] = params.pop("exclude_domains")
 
+        if "after_date" in params:
+            source_policy["after_date"] = params.pop("after_date")
+
         if source_policy:
             advanced_settings["source_policy"] = source_policy
 
@@ -170,9 +214,11 @@ class ParallelAISearchConfig(BaseSearchConfig):
         # unified-spec param with no v1 equivalent
         params.pop("max_tokens_per_page", None)
 
-        result_data: Final[dict] = dict(request_data)
-        result_data.update(params)
-        return result_data
+        # reserved for the provider's own reported usage, which prices the request;
+        # a caller-supplied value would otherwise set its own cost
+        params.pop(PARALLEL_AI_USAGE_PARAM, None)
+
+        return {**request_data, **params}
 
     def transform_search_response(
         self,
@@ -186,26 +232,49 @@ class ParallelAISearchConfig(BaseSearchConfig):
         Parallel AI -> LiteLLM mappings:
         - results[].title -> SearchResult.title
         - results[].url -> SearchResult.url
-        - results[].excerpts (array) -> SearchResult.snippet (joined string)
+        - results[].excerpts (array) -> SearchResult.snippet (joined string); the raw
+          array is preserved as an extra `excerpts` field on each result
         - results[].publish_date -> SearchResult.date
+        - search_id / session_id / warnings are preserved as extra fields on the
+          response; usage is preserved as `parallel_usage` (the `usage` name is
+          reserved for LiteLLM's token-usage object)
         """
-        response_json: Final = raw_response.json()
+        parsed: Final = _ParallelAIV1SearchResponse.model_validate(raw_response.json())
 
-        results: Final = []
-        for result in response_json.get("results", []):
-            excerpts = result.get("excerpts") or []
-            snippet = " ... ".join(excerpts) if excerpts else ""
+        # written unconditionally: leaving a caller-supplied value in place when the
+        # provider reports no usage would let the caller price its own request
+        logging_obj.optional_params = {
+            **logging_obj.optional_params,
+            PARALLEL_AI_USAGE_PARAM: parsed.usage,
+        }
 
-            search_result = SearchResult(
-                title=result.get("title") or "",
-                url=result.get("url") or "",
-                snippet=snippet,
-                date=result.get("publish_date"),
-                last_updated=None,
+        results: Final = tuple(
+            SearchResult.model_validate(
+                MappingProxyType(
+                    {
+                        "title": result.title or "",
+                        "url": result.url or "",
+                        "snippet": " ... ".join(result.excerpts or ()),
+                        "date": result.publish_date,
+                        "last_updated": None,
+                        "excerpts": result.excerpts or (),
+                    }
+                )
             )
-            results.append(search_result)
-
-        return SearchResponse(
-            results=results,
-            object="search",
+            for result in parsed.results
         )
+
+        extra_fields: Final = MappingProxyType(
+            {
+                key: value
+                for key, value in (
+                    ("search_id", parsed.search_id),
+                    ("session_id", parsed.session_id),
+                    ("parallel_usage", parsed.usage),
+                    ("warnings", parsed.warnings),
+                )
+                if value is not None
+            }
+        )
+
+        return SearchResponse.model_validate(MappingProxyType({"results": results, "object": "search", **extra_fields}))
diff --git a/litellm/llms/pg_vector/vector_stores/transformation.py b/litellm/llms/pg_vector/vector_stores/transformation.py
index e4b06c36bf4..9de1f589ae4 100644
--- a/litellm/llms/pg_vector/vector_stores/transformation.py
+++ b/litellm/llms/pg_vector/vector_stores/transformation.py
@@ -8,6 +8,7 @@ from litellm.types.vector_stores import VectorStoreSearchOptionalRequestParams
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -80,6 +81,7 @@ class PGVectorStoreConfig(OpenAIVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         encoded_vector_store_id: Final = encode_url_path_segment(vector_store_id, field_name="vector_store_id")
         url: Final = f"{api_base}/{encoded_vector_store_id}/search"
diff --git a/litellm/llms/ragflow/vector_stores/transformation.py b/litellm/llms/ragflow/vector_stores/transformation.py
index 282cb7a92a7..ffa6c9e1076 100644
--- a/litellm/llms/ragflow/vector_stores/transformation.py
+++ b/litellm/llms/ragflow/vector_stores/transformation.py
@@ -17,6 +17,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -92,6 +93,7 @@ class RAGFlowVectorStoreConfig(BaseVectorStoreConfig):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """RAGFlow vector stores are management-only, search is not supported."""
         raise NotImplementedError("RAGFlow vector stores support dataset management only, not search/retrieval")
diff --git a/litellm/llms/runwayml/image_generation/transformation.py b/litellm/llms/runwayml/image_generation/transformation.py
index cde65addb65..5913709c8a0 100644
--- a/litellm/llms/runwayml/image_generation/transformation.py
+++ b/litellm/llms/runwayml/image_generation/transformation.py
@@ -1,8 +1,10 @@
 import asyncio
 import time
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_logger
 from litellm.constants import (
@@ -29,6 +31,16 @@ else:
     LiteLLMLoggingObj = Any
 
 
+class _RunwayMLTask(TypedDict, total=False):
+    """The RunwayML task payload returned by POST /v1/text_to_image and GET /v1/tasks/{id}."""
+
+    id: ReadOnly[str]
+    status: ReadOnly[str]
+    output: ReadOnly[Sequence[str | Mapping[str, str]]]
+    failure: ReadOnly[str]
+    failureCode: ReadOnly[str]
+
+
 class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
     """
     Configuration for RunwayML image generation models.
@@ -80,7 +92,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
 
     @staticmethod
     def _transform_runwayml_response_to_openai(
-        response_data: dict[str, Any],
+        response_data: _RunwayMLTask,
         model_response: ImageResponse,
     ) -> ImageResponse:
         """
@@ -155,7 +167,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             raise TimeoutError(f"RunwayML task polling timed out after {timeout_secs} seconds")
 
     @staticmethod
-    def _check_task_status(response_data: dict[str, Any]) -> str:
+    def _check_task_status(response_data: _RunwayMLTask) -> str:
         """
         Check RunwayML task status from response.
 
@@ -227,7 +239,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             response = client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayMLTask = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -276,7 +288,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             response = await client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayMLTask = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -322,7 +334,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
         }
         """
         try:
-            response_data = raw_response.json()
+            response_data: _RunwayMLTask = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error transforming image generation response: {e}",
@@ -382,7 +394,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
         We need to poll the task until it completes (status SUCCEEDED) using async polling.
         """
         try:
-            response_data = raw_response.json()
+            response_data: _RunwayMLTask = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error transforming image generation response: {e}",
diff --git a/litellm/llms/runwayml/text_to_speech/transformation.py b/litellm/llms/runwayml/text_to_speech/transformation.py
index 1da8f0c66f0..19e6d8ff494 100644
--- a/litellm/llms/runwayml/text_to_speech/transformation.py
+++ b/litellm/llms/runwayml/text_to_speech/transformation.py
@@ -6,10 +6,11 @@ Maps OpenAI TTS spec to RunwayML Text-to-Speech API
 
 import asyncio
 import time
-from collections.abc import Coroutine
-from typing import TYPE_CHECKING, Any, Final, Union
+from collections.abc import Coroutine, Sequence
+from typing import TYPE_CHECKING, Any, Final, TypedDict, Union
 
 import httpx
+from typing_extensions import ReadOnly
 
 import litellm
 from litellm._logging import verbose_logger
@@ -31,6 +32,14 @@ else:
     HttpxBinaryResponseContent = Any
 
 
+class _RunwayTtsTaskResponse(TypedDict, total=False):
+    id: ReadOnly[str]
+    status: ReadOnly[str]
+    output: ReadOnly[Sequence[object]]
+    failure: ReadOnly[str]
+    failureCode: ReadOnly[str]
+
+
 class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
     """
     Configuration for RunwayML Text-to-Speech
@@ -64,7 +73,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         litellm_params_dict: dict,
         logging_obj: "LiteLLMLoggingObj",
         timeout: float | httpx.Timeout,
-        extra_headers: dict[str, Any] | None,
+        extra_headers: dict[str, object] | None,
         base_llm_http_handler: Any,
         aspeech: bool,
         api_base: str | None,
@@ -72,7 +81,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         **kwargs: Any,
     ) -> Union[
         "HttpxBinaryResponseContent",
-        Coroutine[Any, Any, "HttpxBinaryResponseContent"],
+        Coroutine[object, object, "HttpxBinaryResponseContent"],
     ]:
         """
         Dispatch method to handle RunwayML TTS requests
@@ -242,7 +251,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
             raise TimeoutError(f"RunwayML TTS task polling timed out after {timeout_secs} seconds")
 
     @staticmethod
-    def _check_task_status(response_data: dict[str, Any]) -> str:
+    def _check_task_status(response_data: _RunwayTtsTaskResponse) -> str:
         """
         Check RunwayML task status from response.
 
@@ -314,7 +323,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
             response = client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayTtsTaskResponse = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -362,7 +371,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
             response = await client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayTtsTaskResponse = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -453,7 +462,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         from litellm.types.llms.openai import HttpxBinaryResponseContent
 
         try:
-            response_data: Final = raw_response.json()
+            response_data: Final[_RunwayTtsTaskResponse] = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error parsing RunwayML TTS response: {e}",
@@ -483,7 +492,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         )
 
         # Get the completed task data
-        task_data: Final = polled_response.json()
+        task_data: Final[_RunwayTtsTaskResponse] = polled_response.json()
 
         verbose_logger.debug("RunwayML TTS polling complete, downloading audio")
 
@@ -522,7 +531,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         from litellm.types.llms.openai import HttpxBinaryResponseContent
 
         try:
-            response_data: Final = raw_response.json()
+            response_data: Final[_RunwayTtsTaskResponse] = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error parsing RunwayML TTS response: {e}",
@@ -552,7 +561,7 @@ class RunwayMLTextToSpeechConfig(BaseTextToSpeechConfig):
         )
 
         # Get the completed task data
-        task_data: Final = polled_response.json()
+        task_data: Final[_RunwayTtsTaskResponse] = polled_response.json()
 
         verbose_logger.debug("RunwayML TTS polling complete (async), downloading audio")
 
diff --git a/litellm/llms/runwayml/videos/transformation.py b/litellm/llms/runwayml/videos/transformation.py
index 8dd77db08c0..c7696a1cb29 100644
--- a/litellm/llms/runwayml/videos/transformation.py
+++ b/litellm/llms/runwayml/videos/transformation.py
@@ -117,6 +117,10 @@ class RunwayMLVideoConfig(BaseVideoConfig):
     def __init__(self):
         super().__init__()
 
+    @staticmethod
+    def _parse_task_response(raw_response: httpx.Response) -> _RunwayTaskResponse:
+        return raw_response.json()
+
     def get_supported_openai_params(self, model: str) -> list:
         """
         Get the list of supported OpenAI parameters for video generation.
@@ -141,7 +145,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         video_create_optional_params: VideoCreateOptionalRequestParams,
         model: str,
         drop_params: bool,
-    ) -> dict:
+    ) -> dict[str, object]:
         """
         Map OpenAI parameters to RunwayML format.
 
@@ -151,37 +155,42 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         - size -> ratio (convert "WIDTHxHEIGHT" to "WIDTH:HEIGHT")
         - seconds -> duration (convert to integer)
         """
-        mapped_params: Final[dict[str, object]] = {}
+        supported_openai_params: Final = self.get_supported_openai_params(model)
+        return {
+            **self._prompt_image_param(video_create_optional_params),
+            **self._ratio_param(video_create_optional_params),
+            **self._duration_param(video_create_optional_params),
+            **{key: value for key, value in video_create_optional_params.items() if key not in supported_openai_params},
+        }
 
+    @staticmethod
+    def _prompt_image_param(video_create_optional_params: VideoCreateOptionalRequestParams) -> Mapping[str, object]:
         # Handle input_reference parameter - map to promptImage
         if "input_reference" in video_create_optional_params:
-            input_reference: Final = video_create_optional_params["input_reference"]
-            # RunwayML supports URLs and data URIs directly
-            mapped_params["promptImage"] = input_reference
+            return {"promptImage": video_create_optional_params["input_reference"]}
+        return {}
 
+    @staticmethod
+    def _ratio_param(video_create_optional_params: VideoCreateOptionalRequestParams) -> Mapping[str, str]:
         # Handle size parameter - convert "1280x720" to "1280:720"
         if "size" in video_create_optional_params:
             size: Final = video_create_optional_params["size"]
             if isinstance(size, str) and "x" in size:
-                mapped_params["ratio"] = size.replace("x", ":")
+                return {"ratio": size.replace("x", ":")}
+        return {}
 
+    @staticmethod
+    def _duration_param(video_create_optional_params: VideoCreateOptionalRequestParams) -> Mapping[str, int]:
         # Handle seconds parameter - convert to integer
         if "seconds" in video_create_optional_params:
             seconds: Final = video_create_optional_params["seconds"]
             if seconds is not None:
                 try:
-                    mapped_params["duration"] = int(float(seconds)) if isinstance(seconds, str) else int(seconds)
+                    return {"duration": int(float(seconds)) if isinstance(seconds, str) else int(seconds)}
                 except (ValueError, TypeError):
                     # If conversion fails, use default duration
                     pass
-
-        # Pass through other parameters that aren't OpenAI-specific
-        supported_openai_params: Final = self.get_supported_openai_params(model)
-        for key, value in video_create_optional_params.items():
-            if key not in supported_openai_params:
-                mapped_params[key] = value
-
-        return mapped_params
+        return {}
 
     def validate_environment(
         self,
@@ -236,7 +245,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         model: str,
         prompt: str,
         api_base: str,
-        video_create_optional_request_params: dict,
+        video_create_optional_request_params: dict[str, object],
         litellm_params: GenericLiteLLMParams,
         headers: dict,
     ) -> tuple[dict, RequestFiles, str]:
@@ -406,20 +415,18 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         # Get task status to retrieve video URL
         url: Final = f"{api_base}/tasks/{encoded_video_id}"
 
-        params: Final[dict[str, str]] = {}
+        return url, dict[str, str]()
 
-        return url, params
-
-    def _extract_video_url_from_response(self, response_data: dict[str, Any]) -> str:
+    def _extract_video_url_from_response(self, response_data: _RunwayTaskResponse) -> str:
         """
         Helper method to extract video URL from RunwayML response.
         Shared between sync and async transforms.
         """
         # Extract video URL from the output field
         video_url = None
-        if "output" in response_data and response_data["output"]:
-            output: Final = response_data["output"]
-            video_url = output[0] if isinstance(output, list) else output
+        raw_output: Final = response_data.get("output")
+        if raw_output:
+            video_url = raw_output if isinstance(raw_output, str) else raw_output[0]
 
         if not video_url:
             # Check if the video generation failed or is still processing
@@ -453,7 +460,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
             "output":["https://dnznrvs05pmza.cloudfront.net/.../video.mp4?_jwt=..."]
         }
         """
-        response_data: Final = raw_response.json()
+        response_data: Final[_RunwayTaskResponse] = self._parse_task_response(raw_response)
         video_url: Final = self._extract_video_url_from_response(response_data)
 
         # Download the video from the CloudFront URL synchronously
@@ -482,7 +489,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
             "output":["https://dnznrvs05pmza.cloudfront.net/.../video.mp4?_jwt=..."]
         }
         """
-        response_data: Final = raw_response.json()
+        response_data: Final[_RunwayTaskResponse] = self._parse_task_response(raw_response)
         video_url: Final = self._extract_video_url_from_response(response_data)
 
         # Download the video from the CloudFront URL asynchronously
@@ -564,9 +571,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         # Construct the URL for task cancellation
         url: Final = f"{api_base}/tasks/{encoded_video_id}/cancel"
 
-        data: Final[dict[str, str]] = {}
-
-        return url, data
+        return url, dict[str, str]()
 
     def transform_video_delete_response(
         self,
@@ -604,9 +609,7 @@ class RunwayMLVideoConfig(BaseVideoConfig):
         url: Final = f"{api_base}/tasks/{encoded_video_id}"
 
         # Empty dict for GET request (no body)
-        data: Final[dict[str, str]] = {}
-
-        return url, data
+        return url, dict[str, str]()
 
     def transform_video_status_retrieve_response(
         self,
diff --git a/litellm/llms/s3_vectors/vector_stores/transformation.py b/litellm/llms/s3_vectors/vector_stores/transformation.py
index 5be35ae4148..733358381fe 100644
--- a/litellm/llms/s3_vectors/vector_stores/transformation.py
+++ b/litellm/llms/s3_vectors/vector_stores/transformation.py
@@ -1,8 +1,8 @@
-import re
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
 
+from litellm.caching._embedding_router import resolve_embedding_router
 from litellm.llms.base_llm.vector_store.transformation import BaseVectorStoreConfig
 from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 from litellm.types.router import GenericLiteLLMParams
@@ -18,6 +18,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.router import Router
 else:
     LiteLLMLoggingObj = Any
 
@@ -58,13 +59,20 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         return headers
 
     def get_complete_url(self, api_base: str | None, litellm_params: dict) -> str:
-        aws_region_name: Final = litellm_params.get("aws_region_name")
-        if not aws_region_name:
-            raise ValueError("aws_region_name is required for S3 Vectors")
-        if not re.match(r"^[a-z][a-z0-9-]*$", aws_region_name):
-            raise ValueError("Invalid aws_region_name format")
+        # Resolve region the same way the ingestion path does:
+        # dynamic param -> AWS_REGION_NAME -> AWS_REGION -> default (us-west-2)
+        aws_region_name: Final = self.get_aws_region_name_for_non_llm_api_calls(litellm_params.get("aws_region_name"))
         return f"https://s3vectors.{aws_region_name}.api.aws"
 
+    def _resolve_query_embedding_router(self, embedding_model: str, router: "Router | None") -> "Router | None":
+        """Return the router iff it serves ``embedding_model`` as a deployment."""
+        if router is None:
+            return None
+        model_list: Final = [
+            dict(m) for m in (router.get_model_list() or ())
+        ]  # mutable-ok: resolve_embedding_router requires list[dict]
+        return resolve_embedding_router(embedding_model=embedding_model, llm_router=router, llm_model_list=model_list)
+
     def transform_search_vector_store_request(
         self,
         vector_store_id: str,
@@ -74,6 +82,7 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """Sync version - generates embedding synchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
@@ -99,10 +108,16 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
 
         # Generate embedding for the query
         embedding_model: Final = litellm_params.get("embedding_model", "text-embedding-3-small")
+        embedding_router: Final = self._resolve_query_embedding_router(embedding_model=embedding_model, router=router)
 
         import litellm as litellm_module
 
-        embedding_response: Final = litellm_module.embedding(model=embedding_model, input=[query])
+        embedding_input: Final = [query]  # mutable-ok: the embedding API takes list input
+        embedding_response: Final = (
+            embedding_router.embedding(model=embedding_model, input=embedding_input)
+            if embedding_router is not None
+            else litellm_module.embedding(model=embedding_model, input=embedding_input)
+        )
         query_embedding: Final = embedding_response.data[0]["embedding"]
 
         url: Final = f"{api_base}/QueryVectors"
@@ -128,6 +143,7 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: dict[str, Any] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict]:
         """Async version - generates embedding asynchronously."""
         # For S3 Vectors, vector_store_id should be in format: bucket_name:index_name
@@ -153,10 +169,16 @@ class S3VectorsVectorStoreConfig(BaseVectorStoreConfig, BaseAWSLLM):
 
         # Generate embedding for the query asynchronously
         embedding_model: Final = litellm_params.get("embedding_model", "text-embedding-3-small")
+        embedding_router: Final = self._resolve_query_embedding_router(embedding_model=embedding_model, router=router)
 
         import litellm as litellm_module
 
-        embedding_response: Final = await litellm_module.aembedding(model=embedding_model, input=[query])
+        embedding_input: Final = [query]  # mutable-ok: the embedding API takes list input
+        embedding_response: Final = (
+            await embedding_router.aembedding(model=embedding_model, input=embedding_input)
+            if embedding_router is not None
+            else await litellm_module.aembedding(model=embedding_model, input=embedding_input)
+        )
         query_embedding: Final = embedding_response.data[0]["embedding"]
 
         url: Final = f"{api_base}/QueryVectors"
diff --git a/litellm/llms/sap/credentials.py b/litellm/llms/sap/credentials.py
index d7743d4d337..a2a93b6114a 100644
--- a/litellm/llms/sap/credentials.py
+++ b/litellm/llms/sap/credentials.py
@@ -8,9 +8,10 @@ from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from threading import Lock
-from typing import Any, Final
+from typing import Any, Final, Protocol
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,8 +34,8 @@ def _get_home() -> str:
     return os.getenv(HOME_PATH_ENV_VAR, DEFAULT_HOME_PATH)
 
 
-def _get_nested(d: dict[str, Any] | str, path: Sequence[str]) -> Any:
-    cur: Any = d
+def _get_nested(d: object, path: Sequence[str]) -> object:
+    cur: object = d
     if isinstance(cur, str):
         # This shouldn't happen if service keys are pre-parsed correctly
         try:
@@ -54,7 +55,7 @@ def _get_nested(d: dict[str, Any] | str, path: Sequence[str]) -> Any:
     return cur
 
 
-def _load_json_env(var_name: str) -> dict[str, Any] | None:
+def _load_json_env(var_name: str) -> dict[str, object] | None:
     raw: Final = os.environ.get(var_name)
     if not raw:
         return None
@@ -64,7 +65,7 @@ def _load_json_env(var_name: str) -> dict[str, Any] | None:
         return None
 
 
-def _str_or_none(value) -> str | None:
+def _str_or_none(value: object) -> str | None:
     try:
         return str(value) if value is not None else None
     except Exception:
@@ -124,7 +125,7 @@ CREDENTIAL_VALUES: Final[list[CredentialsValue]] = [
 ]
 
 
-def init_conf(profile: str | None = None) -> dict[str, Any]:
+def init_conf(profile: str | None = None) -> dict[str, object]:
     """
     Loads config JSON from:
       1) $AICORE_CONFIG if set, otherwise
@@ -191,7 +192,7 @@ def resolve_resource_group(sources: list[Source]) -> str | None:
 
 def _parse_service_key_once(
     service_key: str | dict | None,
-) -> dict[str, Any] | None:
+) -> dict[str, object] | None:
     """
     Pre-parse service_key if it's a string to avoid repeated JSON parsing.
 
@@ -348,8 +349,33 @@ def validate_credentials(
         )
 
 
+class _TokenBody(TypedDict):
+    """Decoded body of the SAP AI Core OAuth2 token response."""
+
+    access_token: ReadOnly[str]
+    expires_in: ReadOnly[NotRequired[int]]
+
+
+class _TokenResponse(Protocol):
+    """The token endpoint's HTTP response, read for the decoded token body it carries."""
+
+    def json(self) -> _TokenBody: ...
+
+
+def _bearer_token_and_expiry(response: _TokenResponse) -> tuple[str, datetime]:
+    """Read a token response into the Authorization header value and the token's absolute expiry."""
+    payload: Final = response.json()
+    expires_in: Final = int(payload.get("expires_in", 3600))
+    access_token: Final = payload["access_token"]
+    return f"Bearer {access_token}", datetime.now(timezone.utc) + timedelta(seconds=expires_in)
+
+
 def _request_token(
-    client_id: str, auth_url: str, timeout: float, cert_pair=None, client_secret=None
+    client_id: str,
+    auth_url: str,
+    timeout: float,
+    cert_pair: tuple[str, str] | None = None,
+    client_secret: str | None = None,
 ) -> tuple[str, datetime]:
     data: Final = {"grant_type": "client_credentials", "client_id": client_id}
     if client_secret:
@@ -361,15 +387,10 @@ def _request_token(
             with httpx.Client(cert=cert_pair) as raw_client:
                 handler = HTTPHandler(client=raw_client)
                 resp = handler.post(auth_url, data=data, timeout=timeout)
-                payload = resp.json()
-        else:
-            handler = _get_httpx_client()
-            resp = handler.post(auth_url, data=data, timeout=timeout)
-            payload = resp.json()
-        access_token: Final = payload["access_token"]
-        expires_in: Final = int(payload.get("expires_in", 3600))
-        expiry_date: Final = datetime.now(timezone.utc) + timedelta(seconds=expires_in)
-        return f"Bearer {access_token}", expiry_date
+                return _bearer_token_and_expiry(resp)
+        handler = _get_httpx_client()
+        resp = handler.post(auth_url, data=data, timeout=timeout)
+        return _bearer_token_and_expiry(resp)
     except Exception as e:
         msg: Final = resp.text if resp is not None else getattr(e, "text", str(e))
         raise RuntimeError(f"Token request failed: {msg}") from e
diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py
index 1de2337d8eb..a36c920dda0 100644
--- a/litellm/llms/vertex_ai/common_utils.py
+++ b/litellm/llms/vertex_ai/common_utils.py
@@ -1,7 +1,7 @@
 import re
 from copy import deepcopy
 from enum import Enum
-from typing import Any, Final, Literal, get_type_hints
+from typing import Any, Final, Literal, cast, get_type_hints
 
 import httpx
 
@@ -31,7 +31,7 @@ class VertexAIError(BaseLLMException):
         super().__init__(message=message, status_code=status_code, headers=headers)
 
 
-def redact_vertex_ai_metadata_from_logged_object(obj: Any) -> None:
+def redact_vertex_ai_metadata_from_logged_object(obj: object) -> None:
     if isinstance(obj, dict):
         for field in VERTEX_AI_PROVIDER_METADATA_FIELDS:
             if field in obj:
@@ -651,7 +651,7 @@ def _build_json_schema(parameters: dict) -> dict:
     return parameters
 
 
-def _filter_anyof_fields(schema_dict: dict[str, Any]) -> dict[str, Any]:
+def _filter_anyof_fields(schema_dict: dict[str, object]) -> dict[str, object]:
     """
     When anyof is present, only keep the anyof field and its contents - otherwise VertexAI will throw an error - https://github.com/BerriAI/litellm/issues/11164
     Filter out other fields in the same dict.
@@ -704,7 +704,7 @@ def process_items(schema, depth=0):
                         process_items(item, depth + 1)
 
 
-def set_schema_property_ordering(schema: dict[str, Any], depth: int = 0) -> dict[str, Any]:
+def set_schema_property_ordering(schema: dict[str, object], depth: int = 0) -> dict[str, object]:
     """
     vertex ai and generativeai apis order output of fields alphabetically, unless you specify the order.
     python dicts retain order, so we just use that. Note that this field only applies to structured outputs, and not tools.
@@ -724,14 +724,16 @@ def set_schema_property_ordering(schema: dict[str, Any], depth: int = 0) -> dict
         # retain propertyOrdering as an escape hatch if user already specifies it
         if "propertyOrdering" not in schema:
             schema["propertyOrdering"] = [k for k, v in schema["properties"].items()]
-        for k, v in schema["properties"].items():
-            set_schema_property_ordering(v, depth + 1)
-    if "items" in schema:
-        set_schema_property_ordering(schema["items"], depth + 1)
+        for v in schema["properties"].values():
+            if isinstance(v, dict):
+                set_schema_property_ordering(cast("dict[str, object]", v), depth + 1)  # cast-ok: JSON Schema child
+    items: Final = schema.get("items")
+    if isinstance(items, dict):
+        set_schema_property_ordering(cast("dict[str, object]", items), depth + 1)  # cast-ok: JSON Schema child
     return schema
 
 
-def filter_schema_fields(schema_dict: dict[str, Any], valid_fields: set[str], processed=None) -> dict[str, Any]:
+def filter_schema_fields(schema_dict: dict[str, object], valid_fields: set[str], processed=None) -> dict[str, object]:
     """
     Recursively filter a schema dictionary to keep only valid fields.
     """
@@ -905,7 +907,7 @@ def _convert_schema_types(schema, depth=0):
                 "maxProperties",
             }
 
-            any_of: Final[list[dict[str, Any]]] = []
+            any_of: Final[list[dict[str, object]]] = []
             for t in type_val:
                 if not isinstance(t, str):
                     continue
@@ -916,7 +918,7 @@ def _convert_schema_types(schema, depth=0):
 
                 # For object/array types, include type-specific fields
                 if t in ("object", "array"):
-                    item_schema = {"type": t}
+                    item_schema: dict[str, object] = {"type": t}
                     # Move type-specific fields into this anyOf item
                     for field in type_specific_fields:
                         if field in schema:
@@ -1110,11 +1112,11 @@ class VertexAITokenCounter(BaseTokenCounter):
         self,
         model_to_use: str,
         messages: list[dict[str, Any]] | None,
-        contents: list[dict[str, Any]] | None,
+        contents: list[dict[str, object]] | None,
         deployment: dict[str, Any] | None = None,
         request_model: str = "",
-        tools: list[dict[str, Any]] | None = None,
-        system: Any | None = None,
+        tools: list[dict[str, object]] | None = None,
+        system: object | None = None,
     ) -> TokenCountResponse | None:
         import copy
 
@@ -1131,25 +1133,26 @@ class VertexAITokenCounter(BaseTokenCounter):
             partner_models_handler: Final = VertexAIPartnerModels()
 
             # Extract vertex-specific params from litellm_params
-            vertex_project = count_tokens_params_request.get("vertex_project") or count_tokens_params_request.get(
+            partner_litellm_params: Final[dict[str, object]] = count_tokens_params_request
+            vertex_project = partner_litellm_params.get("vertex_project") or partner_litellm_params.get(
                 "vertex_ai_project"
             )
 
-            vertex_location = count_tokens_params_request.get("vertex_location") or count_tokens_params_request.get(
+            vertex_location = partner_litellm_params.get("vertex_location") or partner_litellm_params.get(
                 "vertex_ai_location"
             )
 
             # Count tokens not available on global location: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/partner-models/claude/count-tokens
-            vertex_location = count_tokens_params_request.get("vertex_count_tokens_location") or vertex_location
+            vertex_location = partner_litellm_params.get("vertex_count_tokens_location") or vertex_location
 
-            vertex_credentials: Final = count_tokens_params_request.get(
-                "vertex_credentials"
-            ) or count_tokens_params_request.get("vertex_ai_credentials")
+            vertex_credentials: Final = partner_litellm_params.get("vertex_credentials") or partner_litellm_params.get(
+                "vertex_ai_credentials"
+            )
 
             result = await partner_models_handler.count_tokens(
                 model=model_to_use,
                 messages=messages or [],
-                litellm_params=count_tokens_params_request,
+                litellm_params=partner_litellm_params,
                 vertex_project=vertex_project,
                 vertex_location=vertex_location,
                 vertex_credentials=vertex_credentials,
diff --git a/litellm/llms/vertex_ai/files/transformation.py b/litellm/llms/vertex_ai/files/transformation.py
index b7f91bfba0d..b6ad9fbcc04 100644
--- a/litellm/llms/vertex_ai/files/transformation.py
+++ b/litellm/llms/vertex_ai/files/transformation.py
@@ -12,7 +12,7 @@ from urllib.parse import quote, unquote
 import httpx
 from httpx import Headers, Response
 from openai.types.file_deleted import FileDeleted
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, Required
 
 import litellm
 from litellm._uuid import uuid
@@ -104,6 +104,27 @@ class _VertexBatchRow(TypedDict, total=False):
     processed_time: ReadOnly[str]
 
 
+class _VertexEmbeddingVector(TypedDict):
+    values: ReadOnly[list[float]]
+
+
+class _VertexEmbeddingUsageMetadata(TypedDict, total=False):
+    promptTokenCount: ReadOnly[int]
+
+
+class _VertexEmbeddingResponse(TypedDict, total=False):
+    embedding: ReadOnly[Required[_VertexEmbeddingVector]]
+    usageMetadata: ReadOnly[_VertexEmbeddingUsageMetadata]
+    tokenCount: ReadOnly[int]
+
+
+class _VertexEmbeddingBatchRow(TypedDict, total=False):
+    key: ReadOnly[str]
+    request: ReadOnly[Mapping[str, object]]
+    status: ReadOnly[Required[str]]
+    response: ReadOnly[Required[_VertexEmbeddingResponse]]
+
+
 class _OpenAIBatchOutputError(TypedDict):
     code: ReadOnly[str]
     message: ReadOnly[str]
@@ -111,7 +132,7 @@ class _OpenAIBatchOutputError(TypedDict):
 
 class _OpenAIBatchOutputResponse(TypedDict):
     status_code: ReadOnly[int]
-    request_id: ReadOnly[str]
+    request_id: ReadOnly[object]
     body: ReadOnly[Mapping[str, object]]
 
 
@@ -218,7 +239,7 @@ def _get_litellm_batch_custom_id_from_labels(labels: Mapping[str, object] | None
     return str(labels.get("litellm_custom_id", "unknown"))
 
 
-def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, Any]) -> bool:
+def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, object]) -> bool:
     """
     Whether a Vertex batch output row came from an `EmbedContentRequest`.
 
@@ -237,7 +258,7 @@ def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, Any])
 
 def _openai_batch_output_row(
     custom_id: str,
-    body: Mapping[str, Any] | None = None,
+    body: Mapping[str, object] | None = None,
     error_code: str | None = None,
     error_message: str = "",
 ) -> _OpenAIBatchOutputRow:
@@ -259,7 +280,7 @@ def _openai_batch_output_row(
     }
 
 
-def _split_vertex_batch_key(vertex_output_row: Mapping[str, Any]) -> tuple[str, int, int]:
+def _split_vertex_batch_key(vertex_output_row: Mapping[str, object]) -> tuple[str, int, int]:
     """
     Resolve `(custom_id, index within that custom_id, group size)` for a Vertex batch
     output row.
@@ -278,7 +299,7 @@ def _split_vertex_batch_key(vertex_output_row: Mapping[str, Any]) -> tuple[str,
     return unquote(match["custom_id"]), int(match["index"]), int(match["total"])
 
 
-def _embedding_prompt_token_count(vertex_response: Mapping[str, Any]) -> int:
+def _embedding_prompt_token_count(vertex_response: _VertexEmbeddingResponse) -> int:
     """
     Prompt tokens billed for one Vertex Gemini Embedding batch row.
 
@@ -293,7 +314,7 @@ def _embedding_prompt_token_count(vertex_response: Mapping[str, Any]) -> int:
 
 def _vertex_embeddings_rows_to_openai_batch_output_row(
     custom_id: str,
-    vertex_output_rows: tuple[Mapping[str, Any], ...],
+    vertex_output_rows: tuple[_VertexEmbeddingBatchRow, ...],
     element_indices: tuple[int, ...],
     element_count: int,
     model: str | None,
@@ -348,7 +369,7 @@ def _vertex_embeddings_rows_to_openai_batch_output_row(
 
 
 def _transform_vertex_embeddings_batch_output_to_openai(
-    vertex_output_rows: Iterable[Mapping[str, Any]],
+    vertex_output_rows: Iterable[_VertexEmbeddingBatchRow],
     model: str | None,
 ) -> tuple[_OpenAIBatchOutputRow, ...]:
     """
@@ -388,7 +409,7 @@ def _model_from_managed_gcs_url(url: str) -> str | None:
     return match.group(1) if match else None
 
 
-def _is_embeddings_batch_entry(openai_entry: Mapping[str, Any]) -> bool:
+def _is_embeddings_batch_entry(openai_entry: Mapping[str, object]) -> bool:
     """
     Whether an OpenAI batch JSONL line targets the embeddings endpoint.
 
@@ -431,7 +452,7 @@ def _vertex_batch_embeddings_key(custom_id: str, index: int, total: int) -> str:
     return encoded_custom_id if total < 2 else f"{encoded_custom_id}#{index}/{total}"
 
 
-def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str, Any]) -> Mapping[str, Any]:
+def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str, object]) -> Mapping[str, object]:
     """
     One Vertex Gemini Embedding batch input row.
 
@@ -453,8 +474,8 @@ def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str,
 
 
 def _openai_batch_jsonl_entry_to_vertex_embeddings_rows(
-    openai_entry: Mapping[str, Any],
-) -> tuple[Mapping[str, Any], ...]:
+    openai_entry: Mapping[str, object],
+) -> tuple[Mapping[str, object], ...]:
     """
     Transforms a single OpenAI `/v1/embeddings` batch entry into Vertex Gemini Embedding
     batch rows, one per requested embedding.
@@ -512,7 +533,7 @@ def _openai_batch_jsonl_entry_to_vertex_embeddings_rows(
 def _openai_batch_jsonl_entry_to_vertex_rows(
     openai_entry: dict[str, Any],
     map_openai_to_vertex_params: Callable[[dict[str, Any]], dict[str, Any]],
-) -> tuple[Mapping[str, Any], ...]:
+) -> tuple[Mapping[str, object], ...]:
     """
     Transforms a single OpenAI JSONL batch entry into the Vertex rows it maps to.
 
@@ -533,7 +554,7 @@ def _openai_batch_jsonl_entry_to_vertex_rows(
         cached_content=None,
     )
 
-    custom_id: Final = openai_entry.get("custom_id")
+    custom_id: Final[object] = openai_entry.get("custom_id")
     if custom_id is not None:
         if "labels" not in vertex_request_body:
             vertex_request_body["labels"] = {}
diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py
index 11c026010ee..e2d62be6a69 100644
--- a/litellm/llms/vertex_ai/gemini/transformation.py
+++ b/litellm/llms/vertex_ai/gemini/transformation.py
@@ -250,7 +250,7 @@ def _gs_uri_requires_content_type_metadata(url: str) -> bool:
 
 
 def _image_url_payload_may_need_sync_gcs_metadata_fetch(
-    raw_image_url: Any,
+    raw_image_url: object,
 ) -> bool:
     """
     True when this image_url value (content-part image_url or assistant ``images[]``
@@ -326,7 +326,7 @@ def _openai_messages_may_need_sync_gcs_metadata_fetch(
 def _get_gcs_object_content_type(
     image_url: str,
     vertex_project: str | None = None,
-    vertex_credentials: Any | None = None,
+    vertex_credentials: object = None,
 ) -> str | None:
     """
     Resolve content type from GCS object metadata.
@@ -479,7 +479,7 @@ def _process_gemini_media(
     model: str | None = None,
     video_metadata: dict[str, Any] | None = None,
     vertex_project: str | None = None,
-    vertex_credentials: Any | None = None,
+    vertex_credentials: object = None,
 ) -> PartType:
     """
     Given a media URL (image, audio, or video), return the appropriate PartType for Gemini
@@ -1002,7 +1002,7 @@ def _gemini_convert_messages_with_history(
                     if isinstance(_ss_invocations, list):
                         for invocation in _ss_invocations:
                             # Re-inject toolCall part
-                            tc_part: dict[str, Any] = {
+                            tc_part: dict[str, object] = {
                                 "toolCall": {
                                     "toolType": invocation.get("tool_type"),
                                     "id": invocation.get("id"),
@@ -1015,13 +1015,13 @@ def _gemini_convert_messages_with_history(
 
                             # Re-inject toolResponse part if response is present
                             if "response" in invocation:
-                                tr_dict: dict[str, Any] = {
+                                tr_dict: dict[str, object] = {
                                     "id": invocation.get("id"),
                                     "response": invocation.get("response"),
                                 }
                                 if invocation.get("tool_type"):
                                     tr_dict["toolType"] = invocation["tool_type"]
-                                tr_part: dict[str, Any] = {"toolResponse": tr_dict}
+                                tr_part: dict[str, object] = {"toolResponse": tr_dict}
                                 if "response_thought_signature" in invocation:
                                     tr_part["thoughtSignature"] = invocation["response_thought_signature"]
                                 assistant_content.append(tr_part)
@@ -1090,7 +1090,7 @@ def _pop_and_merge_extra_body(data: RequestBody, optional_params: dict) -> None:
                 data_dict[k] = v
 
 
-def _has_google_maps_tool(tools: Any | None) -> bool:
+def _has_google_maps_tool(tools: object) -> bool:
     """Return True if any tool object in the list has a 'googleMaps' key."""
     if not isinstance(tools, list):
         return False
@@ -1127,7 +1127,7 @@ def _rewrite_mime_type_to_response_format(generation_config: GenerationConfig) -
         schema = generation_config.pop("response_schema", None)
     generation_config.pop("response_mime_type", None)
 
-    response_format: Final[dict[str, Any]] = {"text": {"mimeType": "APPLICATION_JSON"}}
+    response_format: Final[dict[str, dict[str, object]]] = {"text": {"mimeType": "APPLICATION_JSON"}}
     if schema is not None:
         response_format["text"]["schema"] = schema
     generation_config["responseFormat"] = response_format
@@ -1316,7 +1316,7 @@ async def async_transform_request_body(
     timeout: float | httpx.Timeout | None,
     extra_headers: dict | None,
     optional_params: dict,
-    logging_obj: litellm.litellm_core_utils.litellm_logging.Logging,
+    logging_obj: LiteLLMLoggingObj,
     custom_llm_provider: Literal["vertex_ai", "vertex_ai_beta", "gemini"],
     litellm_params: dict,
     vertex_project: str | None,
diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
index d8b1e7ba17c..69fe5678de9 100644
--- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
+++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py
@@ -949,7 +949,7 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig):
         # For Gemini 3+ models, use thinkingLevel instead of thinkingBudget
         if model and VertexGeminiConfig._is_gemini_3_or_newer(model):
             if thinking_enabled:
-                if thinking_budget is None or thinking_budget == 0:
+                if thinking_budget == 0:
                     params["includeThoughts"] = False
                 else:
                     params["includeThoughts"] = True
diff --git a/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
index 5889a8eba06..725a7f39917 100644
--- a/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
+++ b/litellm/llms/vertex_ai/image_edit/vertex_gemini_transformation.py
@@ -182,7 +182,6 @@ class VertexAIGeminiImageEditConfig(BaseImageEditConfig, VertexLLM):
             else None
         )
 
-        # Generation config with proper structure for image editing
         generation_config: Final[dict[str, object]] = {
             key: value for key, value in (("response_modalities", ["IMAGE"]), ("image_config", image_config)) if value
         }
diff --git a/litellm/llms/vertex_ai/ocr/deepseek_transformation.py b/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
index 2603552152d..b57a87c3325 100644
--- a/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
+++ b/litellm/llms/vertex_ai/ocr/deepseek_transformation.py
@@ -177,8 +177,9 @@ class VertexAIDeepSeekOCRConfig(BaseOCRConfig):
             content_item = {"type": "image_url", "image_url": document_url}
 
         # Build DeepSeek OCR request
+        provider_model: Final = model if model.startswith("deepseek-ai/") else f"deepseek-ai/{model}"
         data: Final = {
-            "model": "deepseek-ai/" + model,
+            "model": provider_model,
             "messages": [{"role": "user", "content": [content_item]}],
         }
 
diff --git a/litellm/llms/vertex_ai/text_to_speech/transformation.py b/litellm/llms/vertex_ai/text_to_speech/transformation.py
index cf14ab88751..332f892ae6b 100644
--- a/litellm/llms/vertex_ai/text_to_speech/transformation.py
+++ b/litellm/llms/vertex_ai/text_to_speech/transformation.py
@@ -7,10 +7,14 @@ Reference: https://cloud.google.com/text-to-speech/docs/reference/rest/v1/text/s
 
 import base64
 from collections.abc import Coroutine
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Union
 
 import httpx
 
+from litellm.litellm_core_utils.audio_utils.utils import (
+    speech_media_type_from_audio_bytes,
+)
 from litellm.llms.base_llm.text_to_speech.transformation import (
     BaseTextToSpeechConfig,
     TextToSpeechRequestData,
@@ -457,12 +461,11 @@ class VertexAITextToSpeechConfig(BaseTextToSpeechConfig, VertexBase):
         if not response_content:
             raise ValueError("No audioContent in Vertex AI TTS response")
 
-        # Decode base64 to get binary content
         binary_data: Final = base64.b64decode(response_content)
-
-        # Create an httpx.Response object with the binary data
+        media_type: Final = speech_media_type_from_audio_bytes(binary_data)
         response: Final = httpx.Response(
             status_code=200,
+            headers=None if media_type is None else MappingProxyType({"content-type": media_type}),
             content=binary_data,
         )
 
diff --git a/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py b/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
index c80a02c3683..36b57e7c995 100644
--- a/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
+++ b/litellm/llms/vertex_ai/vector_stores/rag_api/transformation.py
@@ -21,6 +21,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -97,7 +98,7 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
     def __init__(self):
         super().__init__()
 
-    def get_auth_credentials(self, litellm_params: dict) -> BaseVectorStoreAuthCredentials:
+    def get_auth_credentials(self, litellm_params: Mapping[str, object]) -> BaseVectorStoreAuthCredentials:
         # Get credentials and project info
         vertex_credentials: Final = self.get_vertex_ai_credentials(dict(litellm_params))
         vertex_project: Final = self.get_vertex_ai_project(dict(litellm_params))
@@ -122,7 +123,9 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
             "write": [("POST", "/ragCorpora")],
         }
 
-    def validate_environment(self, headers: dict, litellm_params: GenericLiteLLMParams | None) -> dict:
+    def validate_environment(
+        self, headers: dict[str, str], litellm_params: GenericLiteLLMParams | None
+    ) -> dict[str, str]:
         """
         Validate and set up authentication for Vertex AI RAG API
         """
@@ -135,7 +138,7 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
     def get_complete_url(
         self,
         api_base: str | None,
-        litellm_params: dict,
+        litellm_params: dict[str, object],
     ) -> str:
         """
         Get the Base endpoint for Vertex AI RAG API
@@ -159,6 +162,7 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, object]]:
         """
         Transform search request for Vertex AI RAG API
@@ -201,7 +205,6 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
             if value is not None
         }
 
-        # Build the request body for Vertex AI RAG API
         query_body: Final[Mapping[str, object]] = {
             key: value
             for key, value in (("text", query), ("rag_retrieval_config", rag_retrieval_config or None))
@@ -292,7 +295,6 @@ class VertexVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
         # Add metadata if provided
         metadata: Final = vector_store_create_optional_params.get("metadata")
 
-        # Build the request body for Vertex AI RAG Corpus creation
         request_body: Final[dict[str, object]] = {
             key: value
             for key, value in (
diff --git a/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py b/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
index 0bcf16ee06f..f0812e3ed9f 100644
--- a/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
+++ b/litellm/llms/vertex_ai/vector_stores/search_api/transformation.py
@@ -25,6 +25,7 @@ from litellm.types.vector_stores import (
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.router import Router
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -245,6 +246,7 @@ class VertexSearchAPIVectorStoreConfig(BaseVectorStoreConfig, VertexBase):
         litellm_logging_obj: LiteLLMLoggingObj,
         litellm_params: dict,
         extra_body: Mapping[str, object] | None = None,
+        router: "Router | None" = None,
     ) -> tuple[str, dict[str, object]]:
         """
         Transform a search request for the Vertex AI Search (Discovery Engine) API.
diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
index d7ad69593c6..7579bc8c02e 100644
--- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
+++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
@@ -153,14 +153,17 @@ class VertexAIAnthropicConfig(AnthropicConfig):
         drop_params: bool,
     ) -> dict:
         """
-        Override parent method to ensure VertexAI always uses tool-based structured outputs.
-        VertexAI doesn't support the output_format parameter, so we force all models
-        to use the tool-based approach for structured outputs.
+        Override parent method so VertexAI uses tool-based structured outputs
+        unless the vertex map entry advertises native structured output
+        (``output_format``, which Vertex AI Claude forwards for those models).
         """
-        # Temporarily override model name to force tool-based approach
-        # This ensures Claude Sonnet 4.5 uses tools instead of output_format
+        from litellm.llms.anthropic.common_utils import AnthropicModelInfo
+
         original_model: Final = model
-        if "response_format" in non_default_params:
+        native_structured_output: Final = AnthropicModelInfo._get_provider_resolved_capability(
+            model, "supports_native_structured_output", "vertex_ai"
+        )
+        if "response_format" in non_default_params and native_structured_output is not True:
             model = "claude-3-sonnet-20240229"  # Use a model that will use tool-based approach
 
         # Call parent method with potentially modified model name
@@ -174,6 +177,10 @@ class VertexAIAnthropicConfig(AnthropicConfig):
         # Restore original model name for any other processing
         model = original_model
 
+        AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model(
+            model=original_model, optional_params=optional_params, custom_llm_provider="vertex_ai"
+        )
+
         return optional_params
 
     def transform_response(
diff --git a/litellm/llms/vertex_ai/vertex_llm_base.py b/litellm/llms/vertex_ai/vertex_llm_base.py
index 75098515deb..1942bc850f1 100644
--- a/litellm/llms/vertex_ai/vertex_llm_base.py
+++ b/litellm/llms/vertex_ai/vertex_llm_base.py
@@ -9,7 +9,7 @@ import json
 import os
 import threading
 from collections.abc import Mapping
-from typing import TYPE_CHECKING, Any, Final, Literal
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol
 from urllib.parse import urlparse
 
 import litellm
@@ -27,6 +27,15 @@ from .common_utils import (
     get_vertex_base_url,
 )
 
+
+def _graft_default_vertex_path(api_base: str, default_url: str) -> str:
+    parsed_api_base: Final = urlparse(api_base)
+    default_segments: Final = urlparse(default_url).path.lstrip("/").split("/")
+    graft_segments: Final = default_segments[1:] if default_segments[0] in ("v1", "v1beta1") else default_segments
+    grafted_path: Final = parsed_api_base.path.rstrip("/") + "/" + "/".join(graft_segments)
+    return parsed_api_base._replace(path=grafted_path).geturl()
+
+
 GOOGLE_IMPORT_ERROR_MESSAGE: Final = (
     "Google Cloud SDK not found. Install it with: pip install 'litellm[google]' or pip install google-cloud-aiplatform"
 )
@@ -38,6 +47,21 @@ else:
     GoogleCredentialsObject = Any
 
 
+class _VertexCredentialsObject(Protocol):
+    """Structural view of the google-auth credentials handle that this class caches and refreshes."""
+
+    @property
+    def token(self) -> object: ...
+
+    @property
+    def quota_project_id(self) -> str | None: ...
+
+    @property
+    def expired(self) -> object: ...
+
+    def refresh(self, request: object) -> None: ...
+
+
 class VertexBase:
     def __init__(self) -> None:
         super().__init__()
@@ -46,7 +70,7 @@ class VertexBase:
         self._credentials: GoogleCredentialsObject | None = None
         self._credentials_project_mapping: dict[
             tuple[VERTEX_CREDENTIALS_TYPES | None, str | None],
-            tuple[GoogleCredentialsObject, str | None],
+            tuple[_VertexCredentialsObject, str | None],
         ] = {}
         self.project_id: str | None = None
         self.async_handler: AsyncHTTPHandler | None = None
@@ -100,7 +124,7 @@ class VertexBase:
         self,
         credentials: VERTEX_CREDENTIALS_TYPES | None,
         project_id: str | None,
-    ) -> tuple[Any, str]:
+    ) -> tuple[_VertexCredentialsObject | None, str]:
         if credentials is not None:
             if isinstance(credentials, str):
                 _is_path: Final = os.path.exists(
@@ -200,7 +224,7 @@ class VertexBase:
         return creds, project_id
 
     # Google Auth Helpers -- extracted for mocking purposes in tests
-    def _credentials_from_identity_pool(self, json_obj, scopes):
+    def _credentials_from_identity_pool(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import identity_pool
         except ImportError:
@@ -211,7 +235,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_pluggable(self, json_obj, scopes):
+    def _credentials_from_pluggable(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import pluggable
         except ImportError:
@@ -222,7 +246,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_identity_pool_with_aws(self, json_obj, scopes):
+    def _credentials_from_identity_pool_with_aws(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import aws
         except ImportError:
@@ -233,7 +257,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_authorized_user(self, json_obj, scopes):
+    def _credentials_from_authorized_user(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             import google.oauth2.credentials
         except ImportError:
@@ -241,7 +265,7 @@ class VertexBase:
 
         return google.oauth2.credentials.Credentials.from_authorized_user_info(json_obj, scopes=scopes)
 
-    def _credentials_from_service_account(self, json_obj, scopes):
+    def _credentials_from_service_account(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             import google.oauth2.service_account
         except ImportError:
@@ -249,7 +273,7 @@ class VertexBase:
 
         return google.oauth2.service_account.Credentials.from_service_account_info(json_obj, scopes=scopes)
 
-    def _credentials_from_default_auth(self, scopes):
+    def _credentials_from_default_auth(self, scopes) -> tuple[_VertexCredentialsObject, str | None]:
         try:
             import google.auth as google_auth
         except ImportError:
@@ -341,7 +365,7 @@ class VertexBase:
         )
         return api_base
 
-    def refresh_auth(self, credentials: Any) -> None:
+    def refresh_auth(self, credentials: _VertexCredentialsObject) -> None:
         try:
             from google.auth.transport.requests import (
                 Request,
@@ -417,7 +441,7 @@ class VertexBase:
         self,
         credential_cache_key: tuple,
         project_id: str | None,
-    ) -> tuple[str, str, "TokenState", Any, str | None] | None:
+    ) -> tuple[str, str, "TokenState", _VertexCredentialsObject, str | None] | None:
         """
         Look up cached credentials and return usable token info for FRESH or
         STALE tokens (both are still valid for outbound requests). STALE
@@ -440,7 +464,9 @@ class VertexBase:
             return None
         return creds.token, resolved_project, token_state, creds, cached_project_id
 
-    def _unpack_cached_credentials(self, credential_cache_key: tuple) -> tuple[Any, str | None]:
+    def _unpack_cached_credentials(
+        self, credential_cache_key: tuple
+    ) -> tuple[_VertexCredentialsObject | None, str | None]:
         """
         Return (credentials, project_id) from the cache, or (None, None) if
         not cached. Handles both tuple and legacy cache formats.
@@ -452,7 +478,7 @@ class VertexBase:
             return cached_entry
         return cached_entry, cached_entry.quota_project_id or getattr(cached_entry, "project_id", None)
 
-    def _get_token_state(self, credentials: Any) -> "TokenState":
+    def _get_token_state(self, credentials: _VertexCredentialsObject) -> "TokenState":
         """
         Return the token state using google-auth's TokenState enum.
 
@@ -476,7 +502,7 @@ class VertexBase:
         credentials: VERTEX_CREDENTIALS_TYPES | None,
         project_id: str | None,
         credential_cache_key: tuple,
-    ) -> tuple[Any, str | None]:
+    ) -> tuple[_VertexCredentialsObject, str | None]:
         """Load credentials via load_auth (in thread) and cache the result."""
         try:
             _credentials, credential_project_id = await asyncify(self.load_auth)(
@@ -496,7 +522,7 @@ class VertexBase:
 
     async def _background_refresh_credentials(
         self,
-        credentials: Any,
+        credentials: _VertexCredentialsObject,
         credential_cache_key: tuple,
         credential_project_id: str | None,
     ) -> None:
@@ -548,7 +574,7 @@ class VertexBase:
 
     def _schedule_background_refresh(
         self,
-        credentials: Any,
+        credentials: _VertexCredentialsObject,
         credential_cache_key: tuple,
         credential_project_id: str | None,
     ) -> None:
@@ -566,7 +592,7 @@ class VertexBase:
             self._background_refresh_credentials(credentials, credential_cache_key, credential_project_id)
         )
 
-        def _drop_background_refresh_task(_fut: asyncio.Future[Any]) -> None:
+        def _drop_background_refresh_task(_fut: asyncio.Future[None]) -> None:
             if self._background_refresh_tasks.get(credential_cache_key) is _fut:
                 self._background_refresh_tasks.pop(credential_cache_key, None)
 
@@ -621,8 +647,9 @@ class VertexBase:
 
         Handles custom api_base for:
         1. Gemini (Google AI Studio) - constructs /models/{model}:{endpoint}
-        2. Vertex AI with standard proxies - constructs {api_base}:{endpoint};
-           if api_base has no path (bare host), grafts the default vertex URL path onto it
+        2. Vertex AI with standard proxies - grafts the default vertex URL path onto the
+           api_base when its path is empty or only an API version (/v1, /v1beta1);
+           otherwise constructs {api_base}:{endpoint}
         3. Vertex AI with PSC endpoints - constructs full path structure
            {api_base}/v1/projects/{project}/locations/{location}/endpoints/{model}:{endpoint}
            (only when use_psc_endpoint_format=True)
@@ -669,10 +696,14 @@ class VertexBase:
                     )
                 elif urlparse(api_base).path in ("", "/"):
                     url = api_base.rstrip("/") + urlparse(url).path
+                elif urlparse(api_base).path.rstrip("/") in ("/v1", "/v1beta1") and "/projects/" in urlparse(url).path:
+                    url = _graft_default_vertex_path(api_base=api_base, default_url=url)
                 else:
                     url = f"{api_base}:{endpoint}"
             if stream is True:
-                url = url + "?alt=sse"
+                parsed_stream_url: Final = urlparse(url)
+                stream_query: Final = f"{parsed_stream_url.query}&alt=sse" if parsed_stream_url.query else "alt=sse"
+                url = parsed_stream_url._replace(query=stream_query).geturl()
         return auth_header, url
 
     def _get_token_and_url(
@@ -874,7 +905,7 @@ class VertexBase:
         # Convert dict credentials to string for caching
         cache_credentials: Final = json.dumps(credentials) if isinstance(credentials, dict) else credentials
         credential_cache_key: Final = (cache_credentials, project_id)
-        _credentials: GoogleCredentialsObject | None = None
+        _credentials: _VertexCredentialsObject | None = None
 
         verbose_logger.debug("Checking cached credentials for project_id: %s", project_id)
 
diff --git a/litellm/main.py b/litellm/main.py
index c341db08155..0128e4defe5 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -141,7 +141,6 @@ from litellm.utils import (
     convert_to_model_response_object,
     create_pretrained_tokenizer,
     create_tokenizer,
-    get_api_key,
     get_llm_provider,
     get_model_info,
     get_non_default_completion_params,
@@ -5507,6 +5506,9 @@ def completion(
             tpm=kwargs.get("tpm"),
             rpm=kwargs.get("rpm"),
             use_xai_oauth=kwargs.get("use_xai_oauth", False),
+            gigachat_scope=kwargs.get("gigachat_scope"),
+            gigachat_auth_url=kwargs.get("gigachat_auth_url"),
+            gigachat_access_token=kwargs.get("gigachat_access_token"),
             **{key: kwargs[key] for key in FORWARDED_KWARGS_KEYS if key in kwargs},
         )
         cast(LiteLLMLoggingObj, logging).update_environment_variables(
@@ -6289,18 +6291,15 @@ def embedding(
             if headers is not None and headers != {}:
                 optional_params["extra_headers"] = headers
 
-            if encoding_format is not None:
-                optional_params["encoding_format"] = encoding_format
+            requested_encoding_format: Final = (
+                encoding_format
+                or optional_params.get("encoding_format")
+                or get_secret_str("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT")
+            )
+            if requested_encoding_format is None or requested_encoding_format.strip().lower() == "none":
+                optional_params.pop("encoding_format", None)
             else:
-                env_fmt: Final = get_secret_str("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT")
-                if env_fmt is not None and env_fmt.strip().lower() == "none":
-                    optional_params.pop("encoding_format", None)
-                else:
-                    _default_fmt: Final = optional_params.get("encoding_format") or env_fmt or "float"
-                    if _default_fmt.strip().lower() == "none":
-                        optional_params.pop("encoding_format", None)
-                    else:
-                        optional_params["encoding_format"] = _default_fmt
+                optional_params["encoding_format"] = requested_encoding_format
 
             api_version = None
 
@@ -6949,12 +6948,18 @@ def embedding(
                 aembedding=aembedding,
                 headers=headers,
             )
-        elif custom_llm_provider == "dashscope":
-            dashscope_key: Final = api_key or litellm.api_key or get_secret_str("DASHSCOPE_API_KEY")
+        elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
+            from litellm.llms.dashscope.common_utils import (
+                missing_dashscope_family_key_message,
+                resolve_dashscope_family_api_key,
+            )
+
+            dashscope_key: Final = resolve_dashscope_family_api_key(
+                custom_llm_provider=custom_llm_provider,
+                api_key=api_key or litellm.api_key,
+            )
             if dashscope_key is None:
-                raise ValueError(
-                    "Missing API key for DashScope. Set DASHSCOPE_API_KEY environment variable or pass api_key parameter."
-                )
+                raise ValueError(missing_dashscope_family_key_message(custom_llm_provider))
             if extra_headers is not None and isinstance(extra_headers, dict):
                 headers = extra_headers
             else:
@@ -8631,6 +8636,16 @@ def _set_stream_builder_response_cost(response: ModelResponse, logging_obj: Opti
     hidden_params["response_cost"] = response_cost
 
 
+def _stamp_streaming_usage_cost(usage: Usage, response: ModelResponse, logging_obj: Optional["Logging"]) -> None:
+    if logging_obj is None:
+        return
+    if isinstance(getattr(usage, "cost", None), (int, float)):
+        return
+    computed_cost: Final = logging_obj._response_cost_calculator(result=response)
+    if isinstance(computed_cost, (int, float)) and computed_cost > 0:
+        setattr(usage, "cost", computed_cost)
+
+
 def stream_chunk_builder(
     chunks: list,
     messages: list | None = None,
@@ -8725,12 +8740,7 @@ def stream_chunk_builder(
                     )
                     break
 
-            if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-                setattr(
-                    usage,
-                    "cost",
-                    logging_obj._response_cost_calculator(result=response),
-                )
+            _stamp_streaming_usage_cost(usage, response, logging_obj)
             _set_stream_builder_response_cost(response, logging_obj)
 
             processor.apply_provider_assembled_streaming_metadata(response, chunks, logging_obj)
@@ -8909,10 +8919,7 @@ def stream_chunk_builder(
                 )
                 break
 
-        # Add cost to usage object if include_cost_in_streaming_usage is True
-        if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-            setattr(usage, "cost", logging_obj._response_cost_calculator(result=response))
-
+        _stamp_streaming_usage_cost(usage, response, logging_obj)
         _set_stream_builder_response_cost(response, logging_obj)
 
         processor.apply_provider_assembled_streaming_metadata(response, chunks, logging_obj)
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 05c1cfd3179..d8a8f84b032 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -553,6 +553,27 @@
         "supports_response_schema": true,
         "supports_vision": true
     },
+    "amazon.nova-sonic-v1:0": {
+        "deprecation_date": "2026-09-14",
+        "input_cost_per_audio_token": 3.4e-06,
+        "input_cost_per_token": 6e-08,
+        "litellm_provider": "bedrock",
+        "mode": "realtime",
+        "output_cost_per_audio_token": 1.36e-05,
+        "output_cost_per_token": 2.4e-07,
+        "supports_audio_input": true,
+        "supports_audio_output": true
+    },
+    "amazon.nova-2-sonic-v1:0": {
+        "input_cost_per_audio_token": 3e-06,
+        "input_cost_per_token": 3.3e-07,
+        "litellm_provider": "bedrock",
+        "mode": "realtime",
+        "output_cost_per_audio_token": 1.2e-05,
+        "output_cost_per_token": 2.75e-06,
+        "supports_audio_input": true,
+        "supports_audio_output": true
+    },
     "amazon.rerank-v1:0": {
         "input_cost_per_query": 0.001,
         "input_cost_per_token": 0.0,
@@ -1430,6 +1451,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "global.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.25e-05,
         "cache_creation_input_token_cost_above_1hr": 2e-05,
@@ -1467,6 +1526,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "global.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "us.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1504,6 +1601,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "us.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "eu.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1541,6 +1676,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "eu.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "anthropic.claude-opus-5": {
         "bedrock_converse_supports_strict_tools": false,
         "supports_adaptive_thinking": true,
@@ -1571,7 +1744,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1607,7 +1780,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1643,7 +1816,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1679,7 +1852,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1715,7 +1888,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1751,7 +1924,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -2044,7 +2217,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2081,7 +2254,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2118,7 +2291,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2155,7 +2328,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2192,7 +2365,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2229,7 +2402,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -3025,6 +3198,7 @@
         "prompt_cache_min_tokens": 2048
     },
     "azure_ai/claude-fable-5": {
+        "deprecation_date": "2027-12-05",
         "supports_mid_conversation_system": true,
         "input_cost_per_token": 1e-05,
         "output_cost_per_token": 5e-05,
@@ -3057,7 +3231,43 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "azure_ai/claude-fable-5-1": {
+        "supports_mid_conversation_system": true,
+        "input_cost_per_token": 1e-05,
+        "output_cost_per_token": 5e-05,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "azure_ai/claude-opus-5": {
+        "deprecation_date": "2027-07-08",
         "supports_mid_conversation_system": true,
         "supports_adaptive_thinking": true,
         "input_cost_per_token": 5e-06,
@@ -3090,6 +3300,7 @@
         "prompt_cache_min_tokens": 512
     },
     "azure_ai/claude-opus-4-8": {
+        "deprecation_date": "2027-09-01",
         "supports_mid_conversation_system": true,
         "supports_adaptive_thinking": true,
         "input_cost_per_token": 5e-06,
@@ -3168,6 +3379,7 @@
         "prompt_cache_min_tokens": 1024
     },
     "azure_ai/claude-sonnet-5": {
+        "deprecation_date": "2027-06-30",
         "supports_mid_conversation_system": true,
         "cache_creation_input_token_cost": 2.5e-06,
         "cache_creation_input_token_cost_above_1hr": 4e-06,
@@ -3726,7 +3938,7 @@
         "output_cost_per_token": 0,
         "litellm_provider": "azure_ai",
         "mode": "chat",
-        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-services/",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/",
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-        "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/gpt-realtime-whisper",
+        "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper",
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-        "source": "https://azuremarketplace.microsoft.com/en-us/marketplace/apps/cohere.cohere-embed-v3-english-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/cohere.cohere-embed-v3-english-offer?tab=PlansAndPrice",
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         "output_vector_size": 1024,
-        "source": "https://azuremarketplace.microsoft.com/en-us/marketplace/apps/cohere.cohere-embed-v3-english-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/cohere.cohere-embed-v3-english-offer?tab=PlansAndPrice",
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         "output_cost_per_image": 0.04,
-        "source": "https://azuremarketplace.microsoft.com/pt-br/marketplace/apps/cohere.cohere-embed-4-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/pt-br/marketplace/apps/cohere.cohere-embed-4-offer?tab=PlansAndPrice",
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@@ -9431,7 +9643,8 @@
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-        ]
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@@ -9444,7 +9657,8 @@
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+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/metagenai.meta-llama-3-2-11b-vision-instruct-offer?tab=Overview",
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+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/metagenai.meta-llama-3-2-90b-vision-instruct-offer?tab=Overview",
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-        "source": "https://azuremarketplace.microsoft.com/en/marketplace/apps/metagenai.llama-3-3-70b-instruct-offer?tab=Overview",
+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/metagenai.llama-3-3-70b-instruct-offer?tab=Overview",
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-        "source": "https://azuremarketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-405b-instruct-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-405b-instruct-offer?tab=PlansAndPrice",
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-        "source": "https://azuremarketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-70b-instruct-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-70b-instruct-offer?tab=PlansAndPrice",
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+        "source": "https://marketplace.microsoft.com/en-us/marketplace/apps/metagenai.meta-llama-3-1-8b-instruct-offer?tab=PlansAndPrice",
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@@ -9756,7 +9970,7 @@
         "supported_endpoints": [
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-        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/"
+        "source": "https://ai.azure.com/catalog/models/mistral-document-ai-2512"
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@@ -9957,6 +10173,24 @@
         "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
         "supports_function_calling": true,
         "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "cache_read_input_token_cost": 2.8e-08,
+        "supports_prompt_caching": true
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+    "azure_ai/DeepSeek-V4-Flash-0731": {
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+        "deprecation_date": "2026-12-03",
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+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.32e-06,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/deepseek/",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
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@@ -9967,7 +10201,7 @@
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         "output_vector_size": 3072,
-        "source": "https://azuremarketplace.microsoft.com/pt-br/marketplace/apps/cohere.cohere-embed-4-offer?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/pt-br/marketplace/apps/cohere.cohere-embed-4-offer?tab=PlansAndPrice",
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@@ -10151,7 +10385,7 @@
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         "output_cost_per_token": 0.00971,
-        "source": "https://azure.microsoft.com/en-us/products/ai-services/ai-foundry/models/jais-30b-chat"
+        "source": "https://ai.azure.com/catalog/models/jais-30b-chat"
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@@ -10172,11 +10406,13 @@
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         "mode": "chat",
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-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/kimi-k2-5-now-in-microsoft-foundry/4492321",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
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         "supports_tool_choice": true,
         "supports_video_input": true,
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@@ -10187,7 +10423,7 @@
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-        "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/introducing-kimi-k2-6-in-microsoft-foundry/4513125",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
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             "image"
@@ -10198,7 +10434,9 @@
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-        "supports_vision": true
+        "supports_vision": true,
+        "cache_read_input_token_cost": 1.6e-07,
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@@ -10208,7 +10446,7 @@
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         "output_cost_per_token": 4e-08,
-        "source": "https://azuremarketplace.microsoft.com/en/marketplace/apps/000-000.ministral-3b-2410-offer?tab=Overview",
+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/000-000.ministral-3b-2410-offer?tab=Overview",
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@@ -10231,7 +10469,7 @@
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-        "source": "https://azuremarketplace.microsoft.com/en/marketplace/apps/000-000.mistral-ai-large-2407-offer?tab=Overview",
+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/000-000.mistral-ai-large-2407-offer?tab=Overview",
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@@ -10243,7 +10481,7 @@
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-        "source": "https://azuremarketplace.microsoft.com/en/marketplace/apps/000-000.mistral-ai-large-2407-offer?tab=Overview",
+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/000-000.mistral-ai-large-2407-offer?tab=Overview",
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-        "source": "https://azuremarketplace.microsoft.com/en/marketplace/apps/000-000.mistral-nemo-12b-2407?tab=PlansAndPrice",
+        "source": "https://marketplace.microsoft.com/en/marketplace/apps/000-000.mistral-nemo-12b-2407?tab=PlansAndPrice",
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@@ -11882,7 +12120,7 @@
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         "max_tokens": 2048,
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@@ -12267,6 +12505,7 @@
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     "cerebras/zai-glm-4.7": {
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         "max_input_tokens": 128000,
@@ -12315,7 +12554,8 @@
         "output_cost_per_token": 1e-05,
         "supported_endpoints": [
             "/v1/audio/transcriptions"
-        ]
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+        "deprecation_date": "2027-02-26"
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     "claude-haiku-4-5-20251001": {
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@@ -13001,6 +13241,47 @@
         "supports_native_structured_output": true,
         "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview"
     },
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+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "anthropic",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
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+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
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+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "provider_specific_entry": {
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+        "prompt_cache_min_tokens": 512,
+        "supports_native_structured_output": true,
+        "source": "https://platform.claude.com/docs/en/models/fable-5-1/overview"
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@@ -14697,6 +14978,1910 @@
             "/v1/images/generations"
         ]
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@@ -15080,6 +17265,62 @@
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+        "source": "https://www.databricks.com/product/pricing/foundation-model-serving",
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+        "source": "https://www.databricks.com/product/pricing/foundation-model-serving",
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@@ -17767,7 +20008,8 @@
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@@ -19564,6 +21806,61 @@
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+        "mode": "chat",
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@@ -20554,6 +22851,7 @@
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@@ -21226,6 +23524,63 @@
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         "google_maps_grounding_cost_per_query": 0.014
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-        "source": "https://ai.google.dev/pricing/gemini-3",
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+        "google_maps_grounding_cost_per_query": 0.014
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@@ -23775,8 +26246,10 @@
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-        "source": "https://ai.google.dev/gemini-api/docs/video",
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@@ -23790,7 +26263,8 @@
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-        "source": "https://ai.google.dev/gemini-api/docs/video",
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@@ -23818,8 +26292,10 @@
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@@ -23833,7 +26309,8 @@
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@@ -24342,7 +26819,7 @@
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@@ -24404,6 +26881,15 @@
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         "output_vector_size": 2560
     },
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@@ -25327,7 +27813,7 @@
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@@ -25650,7 +28136,7 @@
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@@ -25787,7 +28273,8 @@
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@@ -25809,7 +28296,7 @@
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@@ -25847,7 +28334,7 @@
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+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/kimi/",
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
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+    },
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+        "litellm_provider": "bedrock",
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+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
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+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
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+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
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+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-west-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": {
+        "input_cost_per_token": 7.2e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.88e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2": {
+        "input_cost_per_token": 2.4e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_system_messages": true,
+        "supports_vision": true
+    },
+    "bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 256000,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 7.8e-07,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0": {
+        "input_cost_per_token": 8.4e-08,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3.6e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0": {
+        "input_cost_per_token": 1.8e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 128000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 7.2e-07,
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-sonnet-5": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": false,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock/us-gov-east-1/anthropic.claude-opus-4-8": {
+        "bedrock_converse_supports_strict_tools": false,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+        "input_cost_per_token": 6e-06,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 3e-05,
+        "prompt_cache_min_tokens": 1024,
+        "supports_adaptive_thinking": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_mid_conversation_system": true,
+        "supports_native_structured_output": true,
+        "supports_output_config": true,
+        "supports_parallel_tool_use_config": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-terra": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-06,
+        "input_cost_per_token_above_272k_tokens": 5.28e-06,
+        "cache_creation_input_token_cost": 3.3e-06,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06,
+        "cache_read_input_token_cost": 2.64e-07,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-07,
+        "output_cost_per_token": 1.584e-05,
+        "output_cost_per_token_above_272k_tokens": 2.376e-05
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-luna": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 2.64e-07,
+        "input_cost_per_token_above_272k_tokens": 5.28e-07,
+        "cache_creation_input_token_cost": 3.3e-07,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07,
+        "cache_read_input_token_cost": 2.64e-08,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-08,
+        "output_cost_per_token": 1.584e-06,
+        "output_cost_per_token_above_272k_tokens": 2.376e-06
+    },
+    "bedrock_mantle/us-gov-west-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "bedrock_mantle/us-gov-west-1/xai.grok-4.3": {
+        "use_openai_responses_path": true,
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "source": "https://aws.amazon.com/bedrock/pricing/",
+        "input_cost_per_token": 1.5e-06,
+        "output_cost_per_token": 3e-06,
+        "cache_read_input_token_cost": 2.4e-07
+    },
+    "bedrock_mantle/us-gov-east-1/openai.gpt-5.4": {
+        "litellm_provider": "bedrock_mantle",
+        "max_input_tokens": 1050000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "responses",
+        "use_openai_responses_path": true,
+        "supported_endpoints": [
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "input_cost_per_token": 3.3e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "output_cost_per_token": 1.98e-05
+    },
+    "azure/us-gov/gpt-5.1": {
+        "cache_read_input_token_cost": 1.71875e-07,
+        "default_reasoning_effort": "none",
+        "input_cost_per_token": 1.71875e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 272000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 1.375e-05,
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/batch",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text",
+            "image"
+        ],
+        "supports_function_calling": true,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "azure/us-gov/o3-mini": {
+        "cache_read_input_token_cost": 7.57e-07,
+        "input_cost_per_token": 1.513e-06,
+        "litellm_provider": "azure",
+        "max_input_tokens": 200000,
+        "max_output_tokens": 100000,
+        "max_tokens": 100000,
+        "mode": "chat",
+        "output_cost_per_token": 6.05e-06,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": false
+    },
+    "azure/us-gov/text-embedding-3-large": {
+        "input_cost_per_token": 1.63e-07,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "azure/us-gov/text-embedding-3-small": {
+        "input_cost_per_token": 2.5e-08,
+        "litellm_provider": "azure",
+        "max_input_tokens": 8191,
+        "max_tokens": 8191,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0
+    },
+    "cloudflare/@cf/openai/whisper": {
+        "input_cost_per_second": 7.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
+    },
+    "cloudflare/@cf/openai/whisper-large-v3-turbo": {
+        "input_cost_per_second": 8.5e-06,
+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper-large-v3-turbo/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
     }
 }
diff --git a/litellm/models/base.py b/litellm/models/base.py
index 7eedf10212e..8125bfd0205 100644
--- a/litellm/models/base.py
+++ b/litellm/models/base.py
@@ -33,6 +33,6 @@ class DomainModel(BaseModel):
             return cls(**record.dict())
         return cls(**dict(record))
 
-    def to_db_dict(self, exclude_unset: bool = False) -> dict[str, Any]:
+    def to_db_dict(self, exclude_unset: bool = False) -> dict[str, object]:
         """Convert domain model to a dictionary for database operations."""
         return self.model_dump(exclude_none=True, exclude_unset=exclude_unset)
diff --git a/litellm/models/model.py b/litellm/models/model.py
index 209f26d4837..a0c840341ab 100644
--- a/litellm/models/model.py
+++ b/litellm/models/model.py
@@ -29,6 +29,8 @@ class LiteLLM_ProxyModelTable(LiteLLMPydanticObjectBase):
     @model_validator(mode="before")
     @classmethod
     def check_potential_json_str(cls, values):
+        if not isinstance(values, dict):
+            return values
         if isinstance(values.get("litellm_params"), str):
             try:
                 values["litellm_params"] = json.loads(values["litellm_params"])
diff --git a/litellm/models/user.py b/litellm/models/user.py
index 259c3440d87..82f78c28078 100644
--- a/litellm/models/user.py
+++ b/litellm/models/user.py
@@ -7,7 +7,7 @@ Canonical definition for ``litellm_usertable``. Re-exported from
 
 from datetime import datetime
 
-from pydantic import ConfigDict, Field, model_validator
+from pydantic import BaseModel, ConfigDict, Field, model_validator
 
 from litellm.models.object_permission import LiteLLM_ObjectPermissionTable
 from litellm.models.organization_membership import (
@@ -67,3 +67,11 @@ class LiteLLM_UserTable(LiteLLMPydanticObjectBase):
         if not self.models:
             return True
         return model_name in self.models
+
+
+class SCIMPlaceholder(BaseModel):
+    """A user row keyed by a value that names another account by SSO identity or email."""
+
+    placeholder_user_id: str
+    resolved_user_ids: tuple[str, ...]
+    team_ids: tuple[str, ...]
diff --git a/litellm/ocr/main.py b/litellm/ocr/main.py
index b918f013700..b260ec6e06f 100644
--- a/litellm/ocr/main.py
+++ b/litellm/ocr/main.py
@@ -194,6 +194,12 @@ def _rust_ocr_supported(prepared_request: _PreparedOCRRequest) -> bool:
     return prepared_request.custom_llm_provider in _RUST_OCR_PROVIDERS
 
 
+def _rust_ocr_enabled(prepared_request: _PreparedOCRRequest) -> bool:
+    raw_request_override: Final = prepared_request.litellm_params.get("rust")
+    request_override: Final = raw_request_override if isinstance(raw_request_override, bool) else None
+    return rust_ocr_bridge.rust_ocr_enabled(request_override=request_override)
+
+
 def _rust_bridge_optional_params(
     prepared_request: _PreparedOCRRequest,
     resolve_secret: Callable[[str], str | None],
@@ -422,7 +428,7 @@ async def aocr(
         custom_llm_provider = prepared.custom_llm_provider
         completion_kwargs.update({"model": model, "custom_llm_provider": custom_llm_provider})
 
-        if _rust_ocr_supported(prepared) and rust_ocr_bridge.rust_ocr_enabled():
+        if _rust_ocr_supported(prepared) and _rust_ocr_enabled(prepared):
             from litellm.secret_managers.main import get_secret_str
 
             rust_response: Final = await _run_rust_aocr(
@@ -694,7 +700,7 @@ def ocr(
         custom_llm_provider = prepared.custom_llm_provider
         completion_kwargs.update({"model": model, "custom_llm_provider": custom_llm_provider})
 
-        if _rust_ocr_supported(prepared) and rust_ocr_bridge.rust_ocr_enabled():
+        if _rust_ocr_supported(prepared) and _rust_ocr_enabled(prepared):
             from litellm.secret_managers.main import get_secret_str
 
             rust_response: Final = _run_rust_ocr(
diff --git a/litellm/passthrough/main.py b/litellm/passthrough/main.py
index 4b30afb2f98..7076683f294 100644
--- a/litellm/passthrough/main.py
+++ b/litellm/passthrough/main.py
@@ -2,17 +2,22 @@
 This module is used to pass through requests to the LLM APIs.
 """
 
+from __future__ import annotations
+
 import asyncio
 import contextvars
-from collections.abc import AsyncGenerator, Coroutine, Generator
+from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Coroutine, Generator, Iterator
 from functools import partial
-from typing import TYPE_CHECKING, Any, Final, Optional, cast
+from types import TracebackType
+from typing import Any, Final, cast
 
 import httpx
-from httpx._types import CookieTypes, QueryParamTypes, RequestFiles
+from httpx._types import CookieTypes, QueryParamTypes, RequestContent, RequestFiles
 
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
 from litellm.passthrough.utils import CommonUtils
@@ -21,9 +26,220 @@ from litellm.utils import client
 base_llm_http_handler = BaseLLMHTTPHandler()
 from .utils import BasePassthroughUtils
 
-if TYPE_CHECKING:
-    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-    from litellm.llms.base_llm.passthrough.transformation import BasePassthroughConfig
+
+async def _as_async_generator(iterable: AsyncIterator[bytes]) -> AsyncGenerator[bytes, bytes]:
+    async for chunk in iterable:
+        yield chunk
+
+
+def _as_generator(iterable: Iterator[bytes]) -> Generator[bytes, bytes, None]:
+    yield from iterable
+
+
+class AsyncPassthroughStreamingResponse(AsyncGenerator[bytes, bytes]):
+    def __init__(
+        self,
+        response: Awaitable[httpx.Response],
+        litellm_logging_obj: LiteLLMLoggingObj,
+        provider_config: BasePassthroughConfig,
+    ) -> None:
+        self._initialized = False
+        self._status_code: int = 0
+        self._headers = httpx.Headers()
+        self._response_coro = response
+        self._response: httpx.Response
+        self._iterator: AsyncGenerator[bytes, bytes]
+        self._litellm_logging_obj = litellm_logging_obj
+        self._provider_config = provider_config
+        self._raw_bytes: list[bytes] = []  # mutable-ok: instance buffer for streaming chunks
+        self._flush_scheduled = False
+        self._background_tasks: set[asyncio.Task] = set()  # mutable-ok: instance set for background task tracking
+        self._hidden_params: dict[str, object] = {}  # mutable-ok: router attaches response headers here in place
+
+    @property
+    def status_code(self) -> int:
+        if not self._initialized:
+            raise RuntimeError("AsyncPassthroughStreamingResponse must be awaited before accessing status_code")
+        return self._status_code
+
+    @status_code.setter
+    def status_code(self, value: int) -> None:
+        self._status_code = value
+
+    @property
+    def headers(self) -> httpx.Headers:
+        if not self._initialized:
+            raise RuntimeError("AsyncPassthroughStreamingResponse must be awaited before accessing headers")
+        return self._headers
+
+    @headers.setter
+    def headers(self, value: httpx.Headers) -> None:
+        self._headers = value
+
+    def __await__(self) -> Iterator[Any]:
+        async def _init():
+            if not self._initialized:
+                self._response = await self._response_coro
+                self.headers = self._response.headers
+                self.status_code = self._response.status_code
+                self._initialized = True
+                try:
+                    self._response.raise_for_status()
+                    self._iterator = _as_async_generator(self._response.aiter_bytes())
+                except Exception:  # noqa: BLE001 # Safe catch-all for cleanup logic
+                    try:
+                        await self._response.aread()
+                    except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                        pass
+                    try:
+                        await self._response.aclose()
+                    except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                        pass
+                    raise
+            return self
+
+        return _init().__await__()
+
+    def _start_flush(self) -> None:
+        if self._flush_scheduled or not self._raw_bytes:
+            return
+        self._flush_scheduled = True
+
+        try:
+            task: Final = asyncio.create_task(
+                self._litellm_logging_obj.async_flush_passthrough_collected_chunks(
+                    raw_bytes=self._raw_bytes,
+                    provider_config=self._provider_config,
+                )
+            )
+
+            self._background_tasks.add(task)
+
+            task.add_done_callback(self._background_tasks.discard)
+        except Exception as e:  # noqa: BLE001 # Safe catch-all for verbose logging
+            verbose_logger.exception(
+                "Failed to schedule passthrough spend-tracking flush; %d buffered chunks dropped: %s",
+                len(self._raw_bytes),
+                e,
+            )
+
+    def __aiter__(self) -> AsyncPassthroughStreamingResponse:
+        return self
+
+    def aiter_bytes(self) -> AsyncPassthroughStreamingResponse:
+        return self
+
+    async def __anext__(self) -> bytes:
+        if not self._initialized:
+            await self  # pyright: ignore[reportGeneralTypeIssues]  # structural type check misses __await__
+        try:
+            chunk: Final = await anext(self._iterator)
+            self._raw_bytes.append(chunk)
+        except Exception:  # noqa: BLE001 # Safe catch-all for cleanup logic
+            self._start_flush()
+            try:
+                await self._response.aclose()
+            except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                pass
+            raise
+        else:
+            return chunk
+
+    async def asend(self, value: bytes) -> bytes:
+        if not self._initialized:
+            await self  # pyright: ignore[reportGeneralTypeIssues]  # structural type check misses __await__
+        return await self._iterator.asend(value)
+
+    async def athrow(
+        self,
+        typ: BaseException | type[BaseException],
+        val: BaseException | object = None,
+        tb: TracebackType | None = None,
+    ) -> bytes:
+        if not self._initialized:
+            await self  # pyright: ignore[reportGeneralTypeIssues]  # structural type check misses __await__
+        return await self._iterator.athrow(typ, val, tb)  # pyright: ignore[reportCallIssue, reportArgumentType]  # matches one of the athrow overloads
+
+    async def aclose(self) -> None:
+        self._start_flush()
+        try:
+            if self._initialized:
+                await self._iterator.aclose()
+                await self._response.aclose()
+        except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+            pass
+
+
+class PassthroughStreamingResponse(Generator[bytes, bytes, None]):
+    def __init__(
+        self,
+        response: httpx.Response,
+        litellm_logging_obj: LiteLLMLoggingObj,
+        provider_config: BasePassthroughConfig,
+    ) -> None:
+        self._response = response
+        self.headers = response.headers
+        self.status_code = response.status_code
+        self._litellm_logging_obj = litellm_logging_obj
+        self._provider_config = provider_config
+        self._iterator: Generator[bytes, bytes, None] = _as_generator(response.iter_bytes())
+        self._raw_bytes: list[bytes] = []  # mutable-ok: instance buffer for streaming chunks
+        self._flush_scheduled = False
+
+    def _start_flush(self) -> None:
+        if self._flush_scheduled or not self._raw_bytes:
+            return
+        self._flush_scheduled = True
+
+        from litellm.utils import executor
+
+        try:
+            executor.submit(
+                self._litellm_logging_obj.flush_passthrough_collected_chunks,
+                raw_bytes=self._raw_bytes,
+                provider_config=self._provider_config,
+            )
+        except Exception as e:  # noqa: BLE001 # Safe catch-all for verbose logging
+            verbose_logger.exception(
+                "Failed to schedule passthrough spend-tracking flush; %d buffered chunks dropped: %s",
+                len(self._raw_bytes),
+                e,
+            )
+
+    def __iter__(self) -> PassthroughStreamingResponse:
+        return self
+
+    def __next__(self) -> bytes:
+        try:
+            chunk: Final = next(self._iterator)
+            self._raw_bytes.append(chunk)
+        except Exception:  # noqa: BLE001 # Safe catch-all for cleanup logic
+            self._start_flush()
+            try:
+                self._response.close()
+            except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                pass
+            raise
+        else:
+            return chunk
+
+    def send(self, value: bytes) -> bytes:
+        return self._iterator.send(value)
+
+    def throw(
+        self,
+        typ: BaseException | type[BaseException],
+        val: BaseException | object = None,
+        tb: TracebackType | None = None,
+    ) -> bytes:
+        return self._iterator.throw(typ, val, tb)  # pyright: ignore[reportCallIssue, reportArgumentType]  # matches one of the throw overloads
+
+    def close(self) -> None:
+        self._start_flush()
+        try:
+            self._response.close()
+        except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+            pass
 
 
 @client
@@ -37,15 +253,15 @@ async def allm_passthrough_route(
     api_key: str | None = None,
     request_query_params: dict | None = None,
     request_headers: dict | None = None,
-    content: Any | None = None,
+    content: RequestContent | None = None,
     data: dict | None = None,
     files: RequestFiles | None = None,
-    json: Any | None = None,
+    json: object | None = None,
     params: QueryParamTypes | None = None,
     cookies: CookieTypes | None = None,
     client: HTTPHandler | AsyncHTTPHandler | None = None,
     **kwargs,
-) -> httpx.Response | AsyncGenerator[Any, Any]:
+) -> httpx.Response | AsyncGenerator[bytes, bytes]:
     """
     Async: Reranks a list of documents based on their relevance to the query
     """
@@ -64,7 +280,7 @@ async def allm_passthrough_route(
         from litellm.utils import ProviderConfigManager
 
         provider_config = cast(
-            Optional["BasePassthroughConfig"], kwargs.get("provider_config")
+            BasePassthroughConfig | None, kwargs.get("provider_config")
         ) or ProviderConfigManager.get_provider_passthrough_config(
             provider=LlmProviders(custom_llm_provider),
             model=model,
@@ -132,12 +348,12 @@ async def allm_passthrough_route(
         if resolved_custom_llm_provider:
             try:
                 provider_config = cast(
-                    Optional["BasePassthroughConfig"], kwargs.get("provider_config")
+                    BasePassthroughConfig | None, kwargs.get("provider_config")
                 ) or ProviderConfigManager.get_provider_passthrough_config(
                     provider=LlmProviders(resolved_custom_llm_provider),
                     model=model,
                 )
-            except Exception:
+            except Exception:  # noqa: BLE001 S110
                 # If we can't get provider config, pass None
                 pass
 
@@ -162,20 +378,20 @@ def llm_passthrough_route(
     api_key: str | None = None,
     request_query_params: dict | None = None,
     request_headers: dict | None = None,
-    content: Any | None = None,
+    content: RequestContent | None = None,
     data: dict | None = None,
     files: RequestFiles | None = None,
-    json: Any | None = None,
+    json: object | None = None,
     params: QueryParamTypes | None = None,
     cookies: CookieTypes | None = None,
     client: HTTPHandler | AsyncHTTPHandler | None = None,
     **kwargs,
 ) -> (
     httpx.Response
-    | Coroutine[Any, Any, httpx.Response]
-    | Coroutine[Any, Any, httpx.Response | AsyncGenerator[Any, Any]]
-    | Generator[Any, Any, Any]
-    | AsyncGenerator[Any, Any]
+    | Coroutine[object, object, httpx.Response]
+    | Coroutine[object, object, httpx.Response | AsyncGenerator[bytes, bytes]]
+    | Generator[bytes, bytes, None]
+    | AsyncGenerator[bytes, bytes]
 ):
     """
     Pass through requests to the LLM APIs.
@@ -190,7 +406,9 @@ def llm_passthrough_route(
 
     _is_async: Final = bool(kwargs.get("allm_passthrough_route", False))
 
-    litellm_logging_obj: Final = cast("LiteLLMLoggingObj", kwargs.get("litellm_logging_obj"))
+    litellm_logging_obj: Final = cast(
+        LiteLLMLoggingObj, kwargs.get("litellm_logging_obj")
+    )  # cast-ok: logging obj is constructed upstream; tests inject mocks
 
     model, custom_llm_provider, api_key, api_base = get_llm_provider(
         model=model,
@@ -235,7 +453,7 @@ def llm_passthrough_route(
     )
 
     provider_config: Final = cast(
-        Optional["BasePassthroughConfig"], kwargs.get("provider_config")
+        BasePassthroughConfig | None, kwargs.get("provider_config")
     ) or ProviderConfigManager.get_provider_passthrough_config(
         provider=LlmProviders(custom_llm_provider),
         model=model,
@@ -276,10 +494,13 @@ def llm_passthrough_route(
         forward_headers=False,
     )
 
+    _request_data: dict | None = (
+        data if isinstance(data, dict) else (json if isinstance(json, dict) else None)
+    )  # rebind-ok: conditional
     headers, signed_json_body = provider_config.sign_request(
         headers=headers,
         litellm_params=litellm_params_dict,
-        request_data=data if data else json,
+        request_data=_request_data,
         api_base=str(updated_url),
         model=model,
     )
@@ -301,9 +522,12 @@ def llm_passthrough_route(
     )
 
     ## IS STREAMING REQUEST
+    _streaming_request_data: dict = (
+        data if isinstance(data, dict) else (json if isinstance(json, dict) else {})
+    )  # rebind-ok: conditional
     is_streaming_request: Final = provider_config.is_streaming_request(
         endpoint=endpoint,
-        request_data=data or json or {},
+        request_data=_streaming_request_data,
     )
 
     # Update logging object with streaming status
@@ -334,18 +558,25 @@ def llm_passthrough_route(
         else:
             # Sync path - client.client.send returns Response directly
             response: httpx.Response = client.client.send(request=request, stream=is_streaming_request)
-            response.raise_for_status()
+            try:
+                response.raise_for_status()
+            except Exception:  # noqa: BLE001 # Safe catch-all for cleanup logic
+                try:
+                    response.read()
+                except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                    pass
+                try:
+                    response.close()
+                except Exception:  # noqa: BLE001 S110 # Safe catch-all for cleanup logic
+                    pass
+                raise
 
-            if (
-                hasattr(response, "iter_bytes") and is_streaming_request
-            ):  # yield the chunk, so we can store it in the logging object
-                return _sync_streaming(response, litellm_logging_obj, provider_config)
+            if hasattr(response, "iter_bytes") and is_streaming_request:
+                return PassthroughStreamingResponse(response, litellm_logging_obj, provider_config)
             else:
-                # For non-streaming responses, yield the entire response
                 return response
     except Exception as e:
-        if provider_config is None:
-            raise e
+        assert provider_config is not None
         raise base_llm_http_handler._handle_error(
             e=e,
             provider_config=provider_config,
@@ -356,9 +587,9 @@ async def _async_passthrough_request(
     client: HTTPHandler | AsyncHTTPHandler,
     request: httpx.Request,
     is_streaming_request: bool,
-    litellm_logging_obj: "LiteLLMLoggingObj",
-    provider_config: "BasePassthroughConfig",
-) -> httpx.Response | AsyncGenerator[Any, Any]:
+    litellm_logging_obj: LiteLLMLoggingObj,
+    provider_config: BasePassthroughConfig,
+) -> httpx.Response | AsyncGenerator[bytes, bytes]:
     """
     Handle async passthrough requests.
     Uses async client to send request and properly handles streaming.
@@ -369,8 +600,7 @@ async def _async_passthrough_request(
     # Check if it's a coroutine and await it
     if asyncio.iscoroutine(response_result):
         if is_streaming_request:
-            # Pass the coroutine to _async_streaming which will await it
-            return _async_streaming(
+            return await AsyncPassthroughStreamingResponse(  # pyright: ignore[reportGeneralTypeIssues]  # structural type check misses __await__
                 response=response_result,
                 litellm_logging_obj=litellm_logging_obj,
                 provider_config=provider_config,
@@ -383,84 +613,3 @@ async def _async_passthrough_request(
     else:
         # Fallback for sync-like behavior (shouldn't happen in async path)
         raise Exception("Expected coroutine from async client")
-
-
-def _sync_streaming(
-    response: httpx.Response,
-    litellm_logging_obj: "LiteLLMLoggingObj",
-    provider_config: "BasePassthroughConfig",
-):
-    from litellm.utils import executor
-
-    raw_bytes: Final[list[bytes]] = []
-    flush_scheduled = False
-    try:
-        for chunk in response.iter_bytes():
-            raw_bytes.append(chunk)
-            yield chunk
-    finally:
-        if not flush_scheduled and raw_bytes:
-            flush_scheduled = True
-            try:
-                executor.submit(
-                    litellm_logging_obj.flush_passthrough_collected_chunks,
-                    raw_bytes=raw_bytes,
-                    provider_config=provider_config,
-                )
-            except Exception as e:
-                verbose_logger.exception(
-                    "Failed to schedule passthrough spend-tracking flush "
-                    "in _sync_streaming; %d buffered chunks dropped: %s",
-                    len(raw_bytes),
-                    e,
-                )
-
-
-async def _async_streaming(
-    response: Coroutine[Any, Any, httpx.Response],
-    litellm_logging_obj: "LiteLLMLoggingObj",
-    provider_config: "BasePassthroughConfig",
-):
-    iter_response: Final = await response
-
-    try:
-        iter_response.raise_for_status()
-    except Exception:
-        try:
-            await iter_response.aclose()
-        except Exception:
-            pass
-        raise
-
-    raw_bytes: Final[list[bytes]] = []
-    flush_scheduled = False
-    try:
-        async for chunk in iter_response.aiter_bytes():
-            raw_bytes.append(chunk)
-            yield chunk
-    except Exception:
-        try:
-            await iter_response.aclose()
-        except Exception:
-            pass
-        raise
-    finally:
-        # GeneratorExit (raised on client disconnect) is not caught by
-        # `except Exception`; the finally block ensures partial usage
-        # still gets flushed for spend tracking. See LIT-2642.
-        if not flush_scheduled and raw_bytes:
-            flush_scheduled = True
-            try:
-                asyncio.create_task(
-                    litellm_logging_obj.async_flush_passthrough_collected_chunks(
-                        raw_bytes=raw_bytes,
-                        provider_config=provider_config,
-                    )
-                )
-            except Exception as e:
-                verbose_logger.exception(
-                    "Failed to schedule passthrough spend-tracking flush "
-                    "in _async_streaming; %d buffered chunks dropped: %s",
-                    len(raw_bytes),
-                    e,
-                )
diff --git a/litellm/provider_endpoints_support_backup.json b/litellm/provider_endpoints_support_backup.json
index ead26ab65c5..9d6b1e18f59 100644
--- a/litellm/provider_endpoints_support_backup.json
+++ b/litellm/provider_endpoints_support_backup.json
@@ -671,6 +671,42 @@
         "interactions": true
       }
     },
+    "qwencloud": {
+      "display_name": "QwenCloud (`qwencloud`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
+    "qwen_ai_platform": {
+      "display_name": "Qwen AI Platform (`qwen_ai_platform`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
     "databricks": {
       "display_name": "Databricks (`databricks`)",
       "url": "https://docs.litellm.ai/docs/providers/databricks",
diff --git a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
index 425f82794e6..66d4aedba06 100644
--- a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
+++ b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py
@@ -1149,10 +1149,11 @@ class MCPRequestHandler:
         would miss a real outage wrapped inside it."""
         from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler
 
-        if PrismaDBExceptionHandler.is_database_service_unavailable_error_in_chain(e):
+        outage: Final = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(e)
+        if outage is not None:
             raise HTTPException(
                 status_code=503,
-                detail="Service Unavailable, the authentication database is temporarily unreachable. Please retry shortly.",
+                detail=PrismaDBExceptionHandler.database_unavailable_message(outage),
             ) from None
 
     @staticmethod
diff --git a/litellm/proxy/_experimental/mcp_server/bridge_token_flow.py b/litellm/proxy/_experimental/mcp_server/bridge_token_flow.py
index 09a3703e904..35a30127e27 100644
--- a/litellm/proxy/_experimental/mcp_server/bridge_token_flow.py
+++ b/litellm/proxy/_experimental/mcp_server/bridge_token_flow.py
@@ -101,18 +101,29 @@ class _ResolvedKey:
     key: "UserAPIKeyAuth"
 
 
-_KeyResolutionFailure = Literal["no_active_key", "unavailable", "unresolvable"]
+_KeyResolutionFailure = Literal["no_active_key", "unavailable", "faulted", "unresolvable"]
 """Why a token request yielded no active litellm key, kept distinct so a caller statuses each truthfully
 instead of blaming the client for a gateway problem:
 - ``no_active_key``: none was presented, or the presented key is unknown / blocked / expired (the
   caller's request is at fault)
 - ``unavailable``: the auth database was transiently unreachable while resolving (retryable)
+- ``faulted``: the auth database's query engine reported a fault that retrying will not clear (still a
+  503, but the wording must not tell the operator to wait)
 - ``unresolvable``: the gateway cannot resolve identity right now (no DB connection, or an unexpected
   error) -- a gateway fault, not the caller's
 The classification mirrors admission's ``_reload_admitted_key`` so the mint (ingress) and admission
 (egress) never disagree on the status of the same outage."""
 
 
+def _database_failure(exc: Exception) -> Literal["unavailable", "faulted"]:
+    from litellm.proxy.db.exception_handler import (  # noqa: PLC0415  # inline import avoids a module-load circular import
+        PrismaDBExceptionHandler,
+    )
+
+    fault: Final = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(exc) or exc
+    return "faulted" if PrismaDBExceptionHandler.is_permanent_database_fault(fault) else "unavailable"
+
+
 async def _resolve_active_litellm_key(request: Request) -> "_ResolvedKey | _KeyResolutionFailure":
     """Resolve the presented litellm key to an active key record, or say precisely why not.
 
@@ -170,7 +181,7 @@ async def _reload_active_key_by_hash(key_hash: str) -> "_ResolvedKey | _KeyResol
         return "no_active_key"
     except Exception as exc:  # noqa: BLE001  # classify: a DB outage is retryable, anything else is an opaque gateway fault
         if PrismaDBExceptionHandler.is_database_service_unavailable_error(exc):
-            return "unavailable"
+            return _database_failure(exc)
         verbose_logger.debug(
             "_reload_active_key_by_hash: unexpected key-resolution error (%s)",
             type(exc).__name__,
@@ -225,8 +236,9 @@ async def load_active_user_by_id(user_id: str) -> "LiteLLM_UserTable | _KeyResol
     except (ProxyException, HTTPException):
         return "no_active_key"
     except Exception as exc:  # noqa: BLE001  # a DB outage is retryable; a missing user (get_user_object's wrapped ValueError) or any other resolution failure fails closed as no_active_key, never a 500
-        if PrismaDBExceptionHandler.is_database_service_unavailable_error_in_chain(exc):
-            return "unavailable"
+        outage: Final = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(exc)
+        if outage is not None:
+            return _database_failure(outage)
         verbose_logger.debug("_reload_active_user_by_id: user-resolution error (%s)", type(exc).__name__)
         return "no_active_key"
     if user_object is None:
@@ -383,6 +395,7 @@ _BridgeMintError = Literal[
     "no_identity",
     "invalid_refresh",
     "identity_unavailable",
+    "identity_faulted",
     "identity_unresolvable",
     "not_configured",
     "no_upstream_token",
@@ -433,6 +446,13 @@ def _bridge_mint_error_response(error: _BridgeMintError) -> JSONResponse:
                 "temporarily_unavailable",
                 "the authentication database is temporarily unreachable; retry shortly",
             )
+        case "identity_faulted":
+            status, code, desc = (
+                503,
+                "temporarily_unavailable",
+                "the authentication database reported a fault that is not a transient outage; "
+                "retrying will not help until the gateway deployment is repaired",
+            )
         case "identity_unresolvable":
             status, code, desc = (
                 500,
@@ -485,6 +505,8 @@ def _key_resolution_failure_to_mint_error(failure: _KeyResolutionFailure) -> _Br
             return "no_identity"
         case "unavailable":
             return "identity_unavailable"
+        case "faulted":
+            return "identity_faulted"
         case "unresolvable":
             return "identity_unresolvable"
         case _:
@@ -569,6 +591,8 @@ def _refresh_key_failure_to_mint_error(failure: _KeyResolutionFailure) -> _Bridg
             return "invalid_refresh"
         case "unavailable":
             return "identity_unavailable"
+        case "faulted":
+            return "identity_faulted"
         case "unresolvable":
             return "identity_unresolvable"
         case _:
diff --git a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
index eff467072a8..94bca9460dd 100644
--- a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
@@ -1096,8 +1096,7 @@ async def exchange_token_with_server(
             headers={"Accept": "application/json", **token_request.headers},
             data=token_data,
         )
-        if response is not None:
-            response.raise_for_status()
+        response.raise_for_status()
     except httpx.HTTPStatusError as exc:
         fault: Final = classify_upstream_token_rejection(
             exc.response,
@@ -1119,11 +1118,6 @@ async def exchange_token_with_server(
             )
             return _bridge_mint_error_response("invalid_refresh")
         return render_token_fault(fault)
-    if response is None:
-        raise HTTPException(
-            status_code=502,
-            detail="MCP upstream token endpoint returned no response",
-        )
     token_response = response.json()
 
     # Validate token response against server-configured rules before any storage.
@@ -1536,16 +1530,10 @@ async def _post_dcr_registration(
             headers=headers,
             json=register_data,
         )
-        if response is not None:
-            response.raise_for_status()
+        response.raise_for_status()
     except httpx.HTTPStatusError as exc:
         status_code, detail = dcr_fault_detail(classify_upstream_dcr_rejection(exc.response, log_context=server_id))
         raise HTTPException(status_code=status_code, detail=detail) from exc
-    if response is None:
-        raise HTTPException(
-            status_code=502,
-            detail="MCP upstream registration endpoint returned no response",
-        )
     return response
 
 
diff --git a/litellm/proxy/_experimental/mcp_server/gateway_dcr_flow.py b/litellm/proxy/_experimental/mcp_server/gateway_dcr_flow.py
index a43e762a456..c7b0045dde5 100644
--- a/litellm/proxy/_experimental/mcp_server/gateway_dcr_flow.py
+++ b/litellm/proxy/_experimental/mcp_server/gateway_dcr_flow.py
@@ -150,11 +150,18 @@ _CLIENT_RECORD_DEBUG_KEY: Final = "gateway_dcr_client"
 _CONNECT_FLOW_DEBUG_KEY: Final = "gateway_connect_flow"
 _AUTH_CODE_DEBUG_KEY: Final = "gateway_authorization_code"
 
-ReloadUserFailure = Literal["unresolvable", "unavailable", "no_active_key"]
+ReloadUserFailure = Literal["unresolvable", "unavailable", "faulted", "no_active_key"]
 ReloadUser = Callable[[str], Awaitable[ReloadUserFailure | None]]
 """Injected live-user revalidation (the token endpoint's mirror of admission):
-``None`` means the user is active; ``unavailable`` is a retryable DB outage; anything
-else fails the grant closed."""
+``None`` means the user is active; ``unavailable`` is a retryable DB outage; ``faulted`` is
+a DB fault retrying will not clear (still 503, worded so nobody just waits); anything else
+fails the grant closed."""
+
+_DB_UNAVAILABLE_DESCRIPTION: Final = "the gateway database is unavailable; retry"
+_DB_FAULTED_DESCRIPTION: Final = (
+    "the gateway database reported a fault that is not a transient outage; "
+    "retrying will not help until the gateway deployment is repaired"
+)
 
 PROXY_API_AUDIENCE: Final[SessionAudience] = "proxy_api"
 """The audience a native client (``lite login --pkce``, a Go CLI) asks for by sending the
@@ -659,7 +666,9 @@ def _set_flow_cookie(response: Response, request: Request, handle: str, flow: _C
 def _consent_lookup_failure_response(failure: ReloadUserFailure) -> Response:
     match failure:
         case "unavailable":
-            return _oauth_error(503, "temporarily_unavailable", "the gateway database is unavailable; retry")
+            return _oauth_error(503, "temporarily_unavailable", _DB_UNAVAILABLE_DESCRIPTION)
+        case "faulted":
+            return _oauth_error(503, "temporarily_unavailable", _DB_FAULTED_DESCRIPTION)
         case "unresolvable":
             return _oauth_error(500, "server_error", "the gateway is not configured to resolve users")
         case "no_active_key":
@@ -962,7 +971,9 @@ def _reload_failure_response(failure: ReloadUserFailure) -> Response:
     ``ReloadUserFailure`` member is a type error here rather than silently 400ing."""
     match failure:
         case "unavailable":
-            return _oauth_error(503, "temporarily_unavailable", "the gateway database is unavailable; retry")
+            return _oauth_error(503, "temporarily_unavailable", _DB_UNAVAILABLE_DESCRIPTION)
+        case "faulted":
+            return _oauth_error(503, "temporarily_unavailable", _DB_FAULTED_DESCRIPTION)
         case "unresolvable":
             return _oauth_error(500, "server_error", "the gateway is not configured to resolve users")
         case "no_active_key":
@@ -981,7 +992,7 @@ def _mint_failure_response(failure: ProxyCredentialMintFailure) -> Response:
             return _oauth_error(
                 400, "invalid_grant", "this user belongs to a team; sign in again and pick the team for this credential"
             )
-        case "unavailable" | "unresolvable" | "no_active_key":
+        case "unavailable" | "faulted" | "unresolvable" | "no_active_key":
             return _reload_failure_response(failure)
         case _:
             assert_never(failure)
@@ -1297,8 +1308,8 @@ async def introspect_gateway_token(
         if peeked == "claimed":
             return _inactive_introspection_response()
     failure: Final = await reload_user(opened.principal.user_id)
-    if failure == "unavailable":
-        return _oauth_error(503, "temporarily_unavailable", "the gateway database is unavailable; retry")
+    if failure == "unavailable" or failure == "faulted":
+        return _reload_failure_response(failure)
     if failure is not None:
         return _inactive_introspection_response()
     return _active_introspection_response(opened)
diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
index 2330120adad..1f552ff3e13 100644
--- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
+++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
@@ -13,7 +13,7 @@ import json
 import os
 import re
 import time
-from collections.abc import AsyncIterator, Callable, Mapping, Sequence
+from collections.abc import AsyncIterator, Awaitable, Callable, Mapping, Sequence
 from contextlib import asynccontextmanager
 from dataclasses import dataclass, replace
 from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias, TypedDict, cast
@@ -1206,7 +1206,7 @@ def _deserialize_json_dict(data: str | _StringMap | None) -> dict[str, str] | No
         return data
 
 
-def _deserialize_json_list(data: Any) -> list[dict[str, Any]] | None:
+def _deserialize_json_list(data: object) -> list[dict[str, Any]] | None:
     """Deserialize a JSON array stored in the DB (``env_vars`` and friends).
 
     Returns ``None`` for empty / null / unparseable input. Accepts strings
@@ -1219,7 +1219,7 @@ def _deserialize_json_list(data: Any) -> list[dict[str, Any]] | None:
         return None
     if isinstance(data, str):
         try:
-            parsed: Final = json.loads(data)
+            parsed: Final[object] = json.loads(data)
         except (json.JSONDecodeError, TypeError):
             return None
         data = parsed
@@ -1914,7 +1914,7 @@ class MCPServerManager:
 
     async def load_servers_from_config(
         self,
-        mcp_servers_config: dict[str, Any],
+        mcp_servers_config: dict[str, MCPServerConfig],
         mcp_aliases: dict[str, str] | None = None,
     ):
         """
@@ -3068,7 +3068,7 @@ class MCPServerManager:
             return {}
 
         cache_key: Final = "toolset_perms:" + ",".join(sorted(toolset_ids))
-        cached: Final = await user_api_key_cache.async_get_cache(key=cache_key)
+        cached: Final[dict[str, list[str]] | None] = await user_api_key_cache.async_get_cache(key=cache_key)
         if cached is not None:
             return cached
 
@@ -5154,7 +5154,7 @@ class MCPServerManager:
 
         # Wrapped so the bridge runs inside the task: the caller only holds the task and
         # gathers it later, so there is no other point that still sees a block here.
-        async def _run_during_call_hook() -> Mapping[str, Any] | None:
+        async def _run_during_call_hook() -> Mapping[str, object] | None:
             try:
                 return await proxy_logging_obj.during_call_hook(
                     user_api_key_dict=user_api_key_auth,
@@ -5656,7 +5656,7 @@ class MCPServerManager:
 
     async def _gather_openapi_tool_tasks(
         self,
-        tasks: list[Any],
+        tasks: Sequence[Awaitable[object]],
         proxy_logging_obj: ProxyLogging | None,
     ) -> CallToolResult:
         """Await OpenAPI tool tasks and return the tool call result."""
diff --git a/litellm/proxy/_experimental/mcp_server/oauth2_flow_backfill.py b/litellm/proxy/_experimental/mcp_server/oauth2_flow_backfill.py
index c09106273e1..150900e7ff2 100644
--- a/litellm/proxy/_experimental/mcp_server/oauth2_flow_backfill.py
+++ b/litellm/proxy/_experimental/mcp_server/oauth2_flow_backfill.py
@@ -36,7 +36,10 @@ a healed fleet has no null rows and the backfill exits after one query.
 
 import json
 from collections import Counter
-from typing import Any, Final, Literal
+from collections.abc import Mapping, Sequence
+from typing import Final, Literal, Protocol
+
+from pydantic import JsonValue
 
 from litellm._logging import verbose_proxy_logger
 from litellm.proxy._experimental.mcp_server.db import _decode_oauth_payload, decrypt_credentials
@@ -55,9 +58,59 @@ BackfillRule = Literal[
 _BACKFILL_AUDIT_ACTOR: Final = "oauth2_flow_backfill"
 
 
-def _decrypted_credentials(raw_credentials: Any) -> MCPCredentials | None:
+class _MCPServerRow(Protocol):
+    """The ``LiteLLM_MCPServerTable`` columns this backfill reads."""
+
+    @property
+    def server_id(self) -> str: ...
+
+    @property
+    def authorization_url(self) -> str | None: ...
+
+    @property
+    def registration_url(self) -> str | None: ...
+
+    @property
+    def token_url(self) -> str | None: ...
+
+    @property
+    def credentials(self) -> str | Mapping[str, JsonValue] | None: ...
+
+
+class _MCPUserCredentialRow(Protocol):
+    """The ``LiteLLM_MCPUserCredentials`` columns this backfill reads."""
+
+    @property
+    def server_id(self) -> str: ...
+
+    @property
+    def credential_b64(self) -> str: ...
+
+
+class _MCPServerTable(Protocol):
+    async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_MCPServerRow]: ...
+
+    async def update_many(self, *, where: Mapping[str, object], data: Mapping[str, str]) -> object: ...
+
+
+class _MCPUserCredentialsTable(Protocol):
+    async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_MCPUserCredentialRow]: ...
+
+
+def _mcp_server_table(prisma_client: PrismaClient) -> _MCPServerTable:
+    """The MCP server table, typed so the untyped prisma client surface stops here."""
+    return prisma_client.db.litellm_mcpservertable
+
+
+def _mcp_user_credentials_table(prisma_client: PrismaClient) -> _MCPUserCredentialsTable:
+    """The per-user MCP credential table, typed so the untyped prisma client surface stops here."""
+    return prisma_client.db.litellm_mcpusercredentials
+
+
+def _decrypted_credentials(raw_credentials: str | Mapping[str, JsonValue] | None) -> MCPCredentials | None:
     if raw_credentials is None:
         return None
+    parsed: JsonValue | Mapping[str, JsonValue]
     if isinstance(raw_credentials, str):
         try:
             parsed = json.loads(raw_credentials)
@@ -92,14 +145,14 @@ def classify_null_flow_row(
 async def backfill_null_oauth2_flows(prisma_client: PrismaClient) -> dict[BackfillRule, int]:
     """Classify every ``auth_type=oauth2`` row whose ``oauth2_flow`` is null; stamp the provable
     ones, warn on the ambiguous ones, and return counts per rule."""
-    null_rows: Final[list[Any]] = await prisma_client.db.litellm_mcpservertable.find_many(
+    null_rows: Final[Sequence[_MCPServerRow]] = await _mcp_server_table(prisma_client).find_many(
         where={"auth_type": "oauth2", "oauth2_flow": None},
     )
     if not null_rows:
         return {}
 
     server_ids: Final = [row.server_id for row in null_rows]
-    token_rows: Final[list[Any]] = await prisma_client.db.litellm_mcpusercredentials.find_many(
+    token_rows: Final[Sequence[_MCPUserCredentialRow]] = await _mcp_user_credentials_table(prisma_client).find_many(
         where={"server_id": {"in": server_ids}},
     )
     server_ids_with_oauth_tokens: Final[set[str]] = {
@@ -141,7 +194,7 @@ async def backfill_null_oauth2_flows(prisma_client: PrismaClient) -> dict[Backfi
     stamped_flows: Final = {flow for _, (flow, _) in classified if flow is not None}
     for stamped_flow in stamped_flows:
         server_ids_for_flow = [row.server_id for row, (row_flow, _) in classified if row_flow == stamped_flow]
-        await prisma_client.db.litellm_mcpservertable.update_many(
+        await _mcp_server_table(prisma_client).update_many(
             where={"server_id": {"in": server_ids_for_flow}, "oauth2_flow": None},
             data={"oauth2_flow": stamped_flow, "updated_by": _BACKFILL_AUDIT_ACTOR},
         )
diff --git a/litellm/proxy/_experimental/mcp_server/outbound_credentials/client_credentials.py b/litellm/proxy/_experimental/mcp_server/outbound_credentials/client_credentials.py
index da00abfe604..ad18d1bb10f 100644
--- a/litellm/proxy/_experimental/mcp_server/outbound_credentials/client_credentials.py
+++ b/litellm/proxy/_experimental/mcp_server/outbound_credentials/client_credentials.py
@@ -19,9 +19,9 @@ Implements the client-credentials behavior contract for the v2 resolver:
   identity.
 
 The token-endpoint POST is injected (``M2MTokenEndpointPost``) so the grant orchestration is
-testable without a live IdP; ``post_client_credentials_grant`` is the httpx edge and the one
-place the untyped response boundary is contained. Failures are values: the source returns
-``Result[OAuthToken, CredError]``; only the httpx edge touches exceptions.
+testable without a live IdP; ``post_client_credentials_grant`` is the httpx edge. Failures are
+values: the source returns ``Result[OAuthToken, CredError]``; only the httpx edge touches
+exceptions.
 """
 
 from __future__ import annotations
@@ -95,18 +95,17 @@ async def post_client_credentials_grant(
 ) -> TokenEndpointOutcome:
     """POST the grant to the token endpoint and classify the transport outcome.
 
-    The httpx edge: litellm's handler is partially typed (and raises ``HTTPStatusError`` itself on
-    a 4xx/5xx), so the untyped boundary is contained here and every field the caller reads comes
-    out of a validated ``TokenEndpointOutcome``.
+    The httpx edge: litellm's handler raises ``HTTPStatusError`` itself on a 4xx/5xx, and every
+    field the caller reads comes out of a validated ``TokenEndpointOutcome``.
     """
     from litellm.llms.custom_httpx.http_handler import (  # noqa: PLC0415  # defer heavy handler import to call time
-        get_async_httpx_client,  # pyright: ignore[reportUnknownVariableType]  # handler is partially typed
+        get_async_httpx_client,  # pyright: ignore[reportUnknownVariableType]  # handler factory params are coarsely typed
     )
     from litellm.types.llms.custom_http import httpxSpecialProvider  # noqa: PLC0415  # deferred with the handler import
 
     try:
         client: Final = get_async_httpx_client(llm_provider=httpxSpecialProvider.Oauth2Check)
-        response = await client.post(  # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType]  # handler is partially typed
+        response: Final = await client.post(  # pyright: ignore[reportUnknownMemberType]  # handler params are coarsely typed
             url, headers={"Accept": "application/json", **headers}, data=form
         )
     except httpx.HTTPStatusError as status_err:
@@ -114,8 +113,6 @@ async def post_client_credentials_grant(
         return TokenEndpointDenied(status_code=status_code, detail=f"token endpoint returned HTTP {status_code}")
     except Exception as exc:  # noqa: BLE001  # any transport failure is the same outcome: unreachable
         return TokenEndpointUnreachable(detail=str(exc))
-    if not isinstance(response, httpx.Response):
-        return TokenEndpointUnreachable(detail="token endpoint returned no response")
     try:
         body: Final = _TOKEN_BODY_ADAPTER.validate_json(response.content)
     except ValidationError:
diff --git a/litellm/proxy/_experimental/mcp_server/outbound_credentials/token_endpoint.py b/litellm/proxy/_experimental/mcp_server/outbound_credentials/token_endpoint.py
index f6d40b82eda..84f714db449 100644
--- a/litellm/proxy/_experimental/mcp_server/outbound_credentials/token_endpoint.py
+++ b/litellm/proxy/_experimental/mcp_server/outbound_credentials/token_endpoint.py
@@ -111,9 +111,6 @@ class TokenEndpointClient:
             return Error(
                 CredError.of_upstream_unavailable("token exchange failed: token endpoint returned a non-JSON response")
             )
-        if raw is None:
-            verbose_proxy_logger.warning("MCP token endpoint %s returned no response", endpoint)
-            return Error(CredError.of_upstream_unavailable("token exchange failed: no response from token endpoint"))
         try:
             parsed: Final = _TokenEndpointResponse.model_validate(raw)
         except ValidationError:
@@ -199,7 +196,7 @@ def _cache_ttl_seconds(expires_in: int | None) -> int:
     )
 
 
-async def _post_form(endpoint: str, data: dict[str, str]) -> object | None:
+async def _post_form(endpoint: str, data: dict[str, str]) -> object:
     # litellm's httpx handler and httpx.Response are only partially typed; the token endpoint
     # returns a JSON object that `_TokenEndpointResponse` validates, so the untyped boundary is
     # contained here. A non-2xx raises `httpx.HTTPStatusError`, an unreachable endpoint raises
@@ -208,8 +205,6 @@ async def _post_form(endpoint: str, data: dict[str, str]) -> object | None:
     # each to a CredError.
     client = get_async_httpx_client(llm_provider=httpxSpecialProvider.MCP)  # pyright: ignore[reportUnknownVariableType]  # litellm http handler is untyped
     response = await client.post(endpoint, data=data)  # pyright: ignore[reportUnknownMemberType,reportUnknownVariableType]  # litellm http handler is untyped
-    if response is None:
-        return None
     response.raise_for_status()
     return response.json()  # pyright: ignore[reportAny]  # untyped JSON; validated by _TokenEndpointResponse in fetch
 
diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index 3efb6429326..37474f85fe7 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -1,13 +1,16 @@
 import asyncio
 import importlib
-from collections.abc import Awaitable, Callable, Mapping
+from collections.abc import Awaitable, Callable, Mapping, Sequence
 from datetime import datetime
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal
 
+import anyio
 import httpx
 from fastapi import APIRouter, Depends, HTTPException, Query, Request, status
 
 from litellm._logging import verbose_logger
+from litellm.constants import MCP_CLIENT_TIMEOUT, MCP_TOOL_LISTING_TIMEOUT
 from litellm.exceptions import (
     BlockedPiiEntityError,
     GuardrailRaisedException,
@@ -18,8 +21,11 @@ from litellm.proxy._experimental.mcp_server.exceptions import (
     MCPUpstreamAuthError,
 )
 from litellm.proxy._experimental.mcp_server.faults.list_outcomes import (
+    ServerListOk,
+    ServerOutcome,
     classify_list_exception,
     list_fault_http_status,
+    outcome_wire_value,
 )
 from litellm.proxy._experimental.mcp_server.ui_session_utils import (
     acting_user_auth,
@@ -68,7 +74,13 @@ _MCP_GUARDRAIL_REJECTIONS: Final = (
 )
 
 
-def _connection_error_message(exc: BaseException) -> str:
+def _connection_error_message(exc: BaseException, url: str | None, timeout_seconds: float) -> str:
+    if isinstance(exc, TimeoutError):
+        return (
+            f"Failed to connect to MCP server: no response from {url or 'the server'} "
+            f"within {timeout_seconds:.0f}s. Check that the LiteLLM proxy can reach this URL "
+            "from its network (DNS, egress rules, firewalls) and that the server answers MCP requests."
+        )
     if isinstance(exc, httpx.LocalProtocolError):
         return (
             "Failed to connect to MCP server: a request header is malformed. "
@@ -88,6 +100,7 @@ def _connection_error_message(exc: BaseException) -> str:
 if MCP_AVAILABLE:
     from mcp.types import Tool as MCPTool
 
+    from litellm.experimental_mcp_client.client import MCPClient
     from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
         _UPSTREAM_OAUTH_DISCOVERY_AUTH_TYPES,
         global_mcp_server_manager,
@@ -99,6 +112,7 @@ if MCP_AVAILABLE:
         ListMCPToolsRestAPIResponseObject,
         MCPInfo,
         MCPServer,
+        _aggregate_server_key,  # pyright: ignore[reportPrivateUsage]  # same per-server key as the tools/list _meta outcomes
         _apply_toolset_scope,
         _fire_mcp_tool_call_logging,
         execute_mcp_tool,
@@ -803,9 +817,6 @@ if MCP_AVAILABLE:
                 list(allowed_server_ids_set), _rest_client_ip
             )
 
-            list_tools_result: Final = []
-            error_message = None
-
             # If server_id is specified, only query that specific server
             if server_id:
                 return await _list_tools_for_single_server(
@@ -849,22 +860,19 @@ if MCP_AVAILABLE:
                     else {}
                 )
 
-                # Query all servers the user has access to
-                errors: Final = []
-                for allowed_server_id in allowed_server_ids:
-                    server = global_mcp_server_manager.get_mcp_server_by_id(allowed_server_id)
-                    if server is None:
-                        continue
-
-                    server_auth_header = _get_server_auth_header(server, mcp_server_auth_headers, mcp_auth_header)
-                    user_oauth_extra_headers = await _get_user_oauth_extra_headers(
+                async def list_server(
+                    server: MCPServer,
+                ) -> tuple[Sequence[ListMCPToolsRestAPIResponseObject], ServerOutcome]:
+                    server_auth_header: Final = _get_server_auth_header(
+                        server, mcp_server_auth_headers, mcp_auth_header
+                    )
+                    user_oauth_extra_headers: Final = await _get_user_oauth_extra_headers(
                         server,
                         user_api_key_dict,
                         prefetched_creds=prefetched_oauth_creds,
                     )
-
                     try:
-                        tools_result = await _get_tools_for_single_server(
+                        tools_result: Final = await _get_tools_for_single_server(
                             server,
                             server_auth_header,
                             raw_headers_from_request,
@@ -872,24 +880,35 @@ if MCP_AVAILABLE:
                             extra_headers=user_oauth_extra_headers,
                             apply_tool_filters=apply_tool_filters,
                         )
-                        list_tools_result.extend(tools_result)
                     except Exception as e:
                         verbose_logger.exception("Error getting tools from %s: %s", server.name, e)
-                        errors.append(
-                            f"{get_server_prefix(server)}: {classify_list_exception(e).tag}"
-                            if isinstance(e, (MCPServerListError, MCPUpstreamAuthError))
-                            else f"{get_server_prefix(server)}: {e}"
-                        )
-                        continue
+                        return (), classify_list_exception(e)
+                    return tools_result, ServerListOk(tool_count=len(tools_result))
 
-                if errors and not list_tools_result:
-                    error_message = "Failed to get tools from servers: " + "; ".join(errors)
-
-            return {
-                "tools": list_tools_result,
-                "error": "partial_failure" if error_message else None,
-                "message": (error_message if error_message else "Successfully retrieved tools"),
-            }
+                queried_servers: Final = tuple(
+                    server
+                    for server in map(global_mcp_server_manager.get_mcp_server_by_id, allowed_server_ids)
+                    if server is not None
+                )
+                listings: Final = tuple([await list_server(server) for server in queried_servers])
+                list_tools_result: Final = [tool for tools, _ in listings for tool in tools]
+                server_outcomes: Final = MappingProxyType(
+                    {_aggregate_server_key(server): outcome for server, (_, outcome) in zip(queried_servers, listings)}
+                )
+                errors: Final = tuple(
+                    f"{key}: {outcome.tag}" for key, outcome in server_outcomes.items() if outcome.tag != "ok"
+                )
+                error_message: Final = (
+                    "Failed to get tools from servers: " + "; ".join(errors)
+                    if errors and not list_tools_result
+                    else None
+                )
+                return {
+                    "tools": list_tools_result,
+                    "error": "partial_failure" if error_message else None,
+                    "message": (error_message if error_message else "Successfully retrieved tools"),
+                    "server_outcomes": {key: outcome_wire_value(outcome) for key, outcome in server_outcomes.items()},
+                }
 
         except MCPUpstreamAuthError as e:
             # Surface upstream pass-through 401/403 challenges to the client so
@@ -1130,12 +1149,18 @@ if MCP_AVAILABLE:
         scopes: Final[list[str] | None] = scopes_raw if isinstance(scopes_raw, list) else None
         return client_id, client_secret, scopes
 
+    async def _list_tools_within(client: MCPClient, deadline: float) -> list[MCPTool] | None:
+        with anyio.move_on_after(deadline):
+            return await client.list_tools(raise_on_error=True)
+        return None
+
     async def _execute_with_mcp_client(
         request: NewMCPServerRequest,
         operation: Callable[..., Awaitable[Mapping[str, object]]],
         mcp_auth_header: str | dict[str, str] | None = None,
         oauth2_headers: dict[str, str] | None = None,
         raw_headers: dict[str, str] | None = None,
+        timeout_seconds: float = MCP_TOOL_LISTING_TIMEOUT,
     ) -> Mapping[str, object]:
         """
         Create a temporary MCP client from *request*, run *operation*, and return the result.
@@ -1151,6 +1176,10 @@ if MCP_AVAILABLE:
             oauth2_headers: Headers extracted from the incoming request (may contain the
                 litellm API key — must NOT be forwarded for M2M servers).
             raw_headers: Raw request headers forwarded for stdio env construction.
+            timeout_seconds: Cap on OAuth discovery, connect, handshake, and *operation*
+                combined. Defaults to ``MCP_TOOL_LISTING_TIMEOUT`` (30s, below common LB
+                timeouts) so an unreachable upstream yields this endpoint's JSON error
+                instead of an opaque load-balancer 504 with an empty body.
 
         Returns:
             The dict returned by *operation*, or an error dict on failure.
@@ -1173,6 +1202,7 @@ if MCP_AVAILABLE:
                 transport=request.transport,
                 auth_type=request.auth_type,
                 mcp_info=request.mcp_info,
+                timeout=request.timeout,
                 command=request.command,
                 args=request.args,
                 env=request.env,
@@ -1240,15 +1270,16 @@ if MCP_AVAILABLE:
                 static_headers=request.static_headers,
             )
 
-            client: Final = await global_mcp_server_manager._create_mcp_client(
-                server=server_model,
-                mcp_auth_header=mcp_auth_header,
-                extra_headers=merged_headers,
-                stdio_env=stdio_env,
-                cred_provider=preview_cred_provider,
-            )
+            with anyio.fail_after(timeout_seconds):
+                client: Final = await global_mcp_server_manager._create_mcp_client(
+                    server=server_model,
+                    mcp_auth_header=mcp_auth_header,
+                    extra_headers=merged_headers,
+                    stdio_env=stdio_env,
+                    cred_provider=preview_cred_provider,
+                )
 
-            return await operation(client)
+                return await operation(client)
 
         except (KeyboardInterrupt, SystemExit, asyncio.CancelledError):
             raise
@@ -1257,7 +1288,7 @@ if MCP_AVAILABLE:
             return {
                 "status": "error",
                 "error": True,
-                "message": _connection_error_message(e),
+                "message": _connection_error_message(e, request.url, timeout_seconds),
             }
 
     async def _preview_openapi_tools(spec_path: str) -> dict:
@@ -1402,11 +1433,26 @@ if MCP_AVAILABLE:
             oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(headers)
 
         async def _list_tools_operation(client):
-            async def _list_tools_session_operation(session):
-                return await session.list_tools()
-
-            list_tools_response: Final = await client.run_with_session(_list_tools_session_operation)
-            list_tools_result: Final[list[MCPTool]] = list_tools_response.tools
+            # Bound the whole pagination walk: without this the preview is limited only by the
+            # per-request timeout times the page cap. max() keeps the pre-pagination guarantee
+            # that a single slow page within the client timeout still succeeds, and a
+            # per-server timeout above the global default extends the deadline with it.
+            listing_deadline: Final = max(
+                getattr(client, "timeout", MCP_CLIENT_TIMEOUT) or MCP_CLIENT_TIMEOUT,
+                MCP_TOOL_LISTING_TIMEOUT,
+            )
+            list_tools_result: Final = await _list_tools_within(client, listing_deadline)
+            if list_tools_result is None:
+                verbose_logger.warning(
+                    "MCP tools/list preview timed out after %s seconds while paginating upstream tools",
+                    listing_deadline,
+                )
+                return {  # mutable-ok: error response payload
+                    "status": "error",
+                    "error": True,
+                    "message": f"Timed out listing tools after {listing_deadline} seconds. "
+                    "The MCP server may be responding slowly or paginating excessively.",
+                }
             model_dumped_tools: Final[list[dict]] = [tool.model_dump() for tool in list_tools_result]
             return {
                 "tools": model_dumped_tools,
diff --git a/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py b/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
index 7ec0f4b5192..dcf1b01bc25 100644
--- a/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
+++ b/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
@@ -5,6 +5,7 @@ Filters MCP tools semantically for /chat/completions and /responses endpoints.
 """
 
 import asyncio
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
 from litellm._logging import verbose_logger
@@ -74,7 +75,7 @@ class SemanticMCPToolFilter:
         self.router_instance = litellm_router_instance
         self.tool_router: SemanticRouter | None = None
         self.context_window_error: str | None = None
-        self._tool_map: dict[str, Any] = {}  # MCPTool objects or OpenAI function dicts
+        self._tool_map: dict[str, object] = {}  # MCPTool objects or OpenAI function dicts
         self._index_sync_lock = asyncio.Lock()
 
     async def build_router_from_mcp_registry(self) -> None:
@@ -182,11 +183,11 @@ class SemanticMCPToolFilter:
                 return
             raise
 
-    def _has_tools_missing_from_index(self, tools: list[Any]) -> bool:
+    def _has_tools_missing_from_index(self, tools: Sequence[object]) -> bool:
         """Allocation-free check for any named tool not yet in the semantic index."""
         return any(name and name not in self._tool_map for name in (self._extract_tool_info(t)[0] for t in tools))
 
-    def _tools_missing_from_index(self, tools: list[Any]) -> dict[str, Any]:
+    def _tools_missing_from_index(self, tools: Sequence[object]) -> Mapping[str, object]:
         """Map name -> tool for every named tool not yet in the semantic index."""
         return {
             name: tool
@@ -194,7 +195,7 @@ class SemanticMCPToolFilter:
             if name and name not in self._tool_map
         }
 
-    async def _ensure_tools_indexed(self, available_tools: list[Any]) -> None:
+    async def _ensure_tools_indexed(self, available_tools: Sequence[object]) -> None:
         """
         Index request-time tools the startup build never saw.
 
@@ -385,7 +386,7 @@ class SemanticMCPToolFilter:
         separator: Final = client_name[-len(canonical) - 1]
         return separator in ("_", "-")
 
-    def _get_tools_by_names(self, tool_names: list[str], available_tools: list[Any]) -> list[Any]:
+    def _get_tools_by_names(self, tool_names: Sequence[str], available_tools: Sequence[object]) -> list[object]:
         """
         Get tools from available_tools by their names, preserving the
         semantic router's ordering.
@@ -401,14 +402,14 @@ class SemanticMCPToolFilter:
         # Exact matches win over suffix matches when both are present, and
         # each incoming tool is returned at most once even if two canonical
         # names happen to be tail-compatible with the same incoming name.
-        available_by_name: Final[dict[str, Any]] = {}
+        available_by_name: Final[dict[str, object]] = {}
         for tool in available_tools:
             client_name, _ = self._extract_tool_info(tool)
             if client_name and client_name not in available_by_name:
                 available_by_name[client_name] = tool
 
-        matched: Final[list[Any]] = []
-        used_ids: Final[set] = set()
+        matched: Final[list[object]] = []
+        used_ids: Final[set[int]] = set()
         for canonical in tool_names:
             tool = available_by_name.get(canonical)
             if tool is None:
@@ -430,7 +431,7 @@ class SemanticMCPToolFilter:
                 used_ids.add(id(tool))
         return matched
 
-    def extract_user_query(self, messages: list[dict[str, Any]]) -> str:
+    def extract_user_query(self, messages: Sequence[Mapping[str, object]]) -> str:
         """
         Extract user query from messages for /chat/completions or /responses.
 
diff --git a/litellm/proxy/_experimental/mcp_server/tool_search.py b/litellm/proxy/_experimental/mcp_server/tool_search.py
index f79765f6d01..4f6305d88cf 100644
--- a/litellm/proxy/_experimental/mcp_server/tool_search.py
+++ b/litellm/proxy/_experimental/mcp_server/tool_search.py
@@ -2,20 +2,31 @@ from __future__ import annotations
 
 import json
 from collections.abc import Mapping, Sequence
+from dataclasses import dataclass
 from datetime import datetime
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, TypedDict, assert_never
 
+from pydantic import ValidationError
 from typing_extensions import ReadOnly, Required
 
 import litellm
 from litellm.proxy.agent_endpoints.agent_search import DEFAULT_AGENT_SEARCH_TOP_K
+from litellm.proxy.common_utils.semantic_text_index import (
+    Embedder,
+    EmbeddingFailed,
+    SemanticTextIndex,
+    router_embedder,
+)
+from litellm.types.mcp import MCPToolSearchSettings
 
 if TYPE_CHECKING:
-    from mcp.types import CallToolResult
+    from mcp.types import CallToolResult, Tool
 
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
     from litellm.proxy._types import UserAPIKeyAuth
 
+MCP_TOOL_SEARCH_SETTINGS_KEY: Final[str] = "mcp_tool_search"
 MCP_TOOL_SEARCH_TOOL_NAME: Final[str] = "mcp_tool_search"
 MCP_TOOL_CALL_TOOL_NAME: Final[str] = "mcp_tool_call"
 AGENT_SEARCH_TOOL_NAME: Final[str] = "agent_search"
@@ -29,17 +40,91 @@ def coerce_top_k(value: Any, default: int = 5) -> int:
         return default
 
 
-def search_tools(query: str, tools: list[dict[str, Any]], top_k: int = 5) -> list[dict[str, Any]]:
+class ToolSearchResult(TypedDict, total=False):
+    name: Required[ReadOnly[str]]
+    description: Required[ReadOnly[str]]
+    inputSchema: Required[ReadOnly[Mapping[str, object]]]
+    score: ReadOnly[float]
+
+
+@dataclass(frozen=True, slots=True)
+class SemanticToolRanker:
+    embed: Embedder
+    embedding_model: str
+    index: SemanticTextIndex
+
+
+global_mcp_tool_search_index: Final = SemanticTextIndex()
+
+
+def mcp_tool_search_settings() -> MCPToolSearchSettings | ValidationError:
+    try:
+        return MCPToolSearchSettings.model_validate(litellm.mcp_tool_search or {})
+    except ValidationError as exc:
+        return exc
+
+
+def _tool_result(tool: Tool) -> ToolSearchResult:
+    return {"name": tool.name, "description": tool.description or "", "inputSchema": tool.inputSchema}
+
+
+def _scored_result(tool: Tool, score: float) -> ToolSearchResult:
+    return {"name": tool.name, "description": tool.description or "", "inputSchema": tool.inputSchema, "score": score}
+
+
+def _tool_text(tool: Tool) -> str:
+    return "\n".join(part for part in (tool.name, tool.description or "") if part)
+
+
+def _keyword_score(query: str, tool: Tool) -> float:
+    haystack: Final = _tool_text(tool).lower()
+    return float(sum(1 for token in query.lower().split() if token in haystack))
+
+
+def _split_core_tools(tools: Sequence[Tool], core_tools: Sequence[str]) -> tuple[tuple[Tool, ...], tuple[Tool, ...]]:
+    by_name: Final = MappingProxyType({tool.name: tool for tool in tools})
+    core: Final = tuple(by_name[name] for name in dict.fromkeys(core_tools) if name in by_name)
+    rest: Final = tuple(tool for tool in tools if tool.name not in frozenset(core_tools))
+    return core, rest
+
+
+def _top_hits(
+    tools: Sequence[Tool], scores: Sequence[float], minimum: float, limit: int
+) -> tuple[tuple[float, Tool], ...]:
+    hits: Final = ((score, tool) for score, tool in zip(scores, tools, strict=True) if score >= minimum)
+    return tuple(sorted(hits, key=lambda hit: hit[0], reverse=True)[:limit])
+
+
+def search_tools(query: str, tools: Sequence[Tool], top_k: int = 5) -> tuple[ToolSearchResult, ...]:
+    """Keyword fallback used when no embedding model is configured: one point per query token found in the tool."""
     if not query:
-        return []
-    tokens: Final = query.lower().split()
+        return ()
+    scores: Final = tuple(_keyword_score(query, tool) for tool in tools)
+    return tuple(_tool_result(tool) for _, tool in _top_hits(tools, scores, minimum=1.0, limit=top_k))
 
-    def _score(tool: dict[str, Any]) -> int:
-        haystack: Final = (tool.get("name", "") + " " + tool.get("description", "")).lower()
-        return sum(1 for t in tokens if t in haystack)
 
-    scored: Final = ((s, tool) for tool in tools if (s := _score(tool)) > 0)
-    return [tool for _, tool in sorted(scored, key=lambda x: x[0], reverse=True)[:top_k]]
+async def search_mcp_tools(
+    query: str,
+    tools: Sequence[Tool],
+    top_k: int,
+    settings: MCPToolSearchSettings,
+    ranker: SemanticToolRanker | None,
+) -> tuple[ToolSearchResult, ...] | EmbeddingFailed:
+    """Core tools the caller can access come first, then up to `top_k` ranked matches from the remaining tools."""
+    core, rest = _split_core_tools(tools, settings.core_tools)
+    limit: Final = min(top_k, settings.top_k)
+    core_results: Final = tuple(_tool_result(tool) for tool in core)
+    if ranker is None:
+        return (*core_results, *search_tools(query, rest, limit))
+    if not query:
+        return core_results
+    scores: Final = await ranker.index.scores(
+        query, tuple(_tool_text(tool) for tool in rest), ranker.embed, ranker.embedding_model
+    )
+    if isinstance(scores, EmbeddingFailed):
+        return scores
+    hits: Final = _top_hits(rest, scores, minimum=settings.similarity_threshold, limit=limit)
+    return (*core_results, *(_scored_result(tool, score) for score, tool in hits))
 
 
 class _ToolParamSchema(TypedDict, total=False):
@@ -66,11 +151,17 @@ def _json_array(*items: str) -> Sequence[str]:
 
 _MCP_TOOL_SEARCH_DEFINITION: Final[VirtualToolDefinition] = {
     "name": MCP_TOOL_SEARCH_TOOL_NAME,
-    "description": "Search for MCP tools by keyword. Returns top matching tools with names, descriptions, and input schemas.",
+    "description": (
+        "Search for MCP tools by describing what you need. "
+        "Returns top matching tools with names, descriptions, and input schemas."
+    ),
     "inputSchema": {
         "type": "object",
         "properties": {
-            "query": {"type": "string", "description": "Keywords to search for in tool names and descriptions."},
+            "query": {
+                "type": "string",
+                "description": "What the tool should do, matched against names and descriptions.",
+            },
             "top_k": {"type": "integer", "description": "Maximum number of results to return.", "default": 5},
         },
         "required": _json_array("query"),
@@ -165,10 +256,28 @@ async def handle_mcp_tool_search(
     oauth2_headers: dict[str, str] | None = None,
     raw_headers: dict[str, str] | None = None,
 ) -> CallToolResult:
-    from mcp.types import CallToolResult, TextContent
-
     from litellm.proxy._experimental.mcp_server.server import _list_mcp_tools
+    from litellm.proxy.proxy_server import llm_router
 
+    settings: Final = mcp_tool_search_settings()
+    if isinstance(settings, ValidationError):
+        return _text_tool_result(
+            f"litellm_settings.{MCP_TOOL_SEARCH_SETTINGS_KEY} is invalid: {settings}", is_error=True
+        )
+    if settings.embedding_model is not None and llm_router is None:
+        return _text_tool_result(
+            f"litellm_settings.{MCP_TOOL_SEARCH_SETTINGS_KEY}.embedding_model needs a model_list so it can be called",
+            is_error=True,
+        )
+    ranker: Final = (
+        SemanticToolRanker(
+            embed=router_embedder(llm_router, settings.embedding_model, user_api_key_dict),
+            embedding_model=settings.embedding_model,
+            index=global_mcp_tool_search_index,
+        )
+        if settings.embedding_model is not None and llm_router is not None
+        else None
+    )
     mcp_listing: Final = await _list_mcp_tools(
         user_api_key_auth=user_api_key_dict,
         mcp_servers=mcp_servers,
@@ -178,17 +287,10 @@ async def handle_mcp_tool_search(
         oauth2_headers=oauth2_headers,
         raw_headers=raw_headers,
     )
-    mcp_tools: Final = mcp_listing.tools
-    tools: Final = [
-        {
-            "name": t.name,
-            "description": t.description or "",
-            "inputSchema": t.inputSchema,
-        }
-        for t in mcp_tools
-    ]
-    results: Final = search_tools(query, tools, top_k)
-    return CallToolResult(content=[TextContent(type="text", text=json.dumps(results))], isError=False)
+    results: Final = await search_mcp_tools(query, mcp_listing.tools, top_k, settings, ranker)
+    if isinstance(results, EmbeddingFailed):
+        return _text_tool_result(results.reason, is_error=True)
+    return _text_tool_result(json.dumps(results), is_error=False)
 
 
 async def handle_mcp_tool_call(
diff --git a/litellm/proxy/_experimental/mcp_server/toolset_db.py b/litellm/proxy/_experimental/mcp_server/toolset_db.py
index 9672383a572..ecaaf35e817 100644
--- a/litellm/proxy/_experimental/mcp_server/toolset_db.py
+++ b/litellm/proxy/_experimental/mcp_server/toolset_db.py
@@ -1,5 +1,9 @@
 import json
-from typing import Final
+from collections.abc import Mapping, Sequence
+from datetime import datetime
+from typing import Final, Protocol
+
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm._uuid import uuid
@@ -7,18 +11,73 @@ from litellm.proxy.utils import PrismaClient
 from litellm.repositories.table_repositories import MCPToolsetRepository
 from litellm.types.mcp_server.mcp_toolset import (
     MCPToolset,
+    MCPToolsetTool,
     NewMCPToolsetRequest,
     UpdateMCPToolsetRequest,
 )
 
 
-def _toolset_from_row(row) -> MCPToolset:
+class MCPToolsetFields(TypedDict):
+    """The ``MCPToolset`` constructor keywords a toolset row expands into."""
+
+    toolset_id: ReadOnly[str]
+    toolset_name: ReadOnly[str]
+    description: NotRequired[ReadOnly[str | None]]
+    tools: NotRequired[ReadOnly[list[MCPToolsetTool]]]
+    created_at: NotRequired[ReadOnly[datetime | None]]
+    created_by: NotRequired[ReadOnly[str | None]]
+    updated_at: NotRequired[ReadOnly[datetime | None]]
+    updated_by: NotRequired[ReadOnly[str | None]]
+
+
+class MCPToolsetRowData(TypedDict):
+    """A toolset table row, whose ``tools`` column is stored as JSON."""
+
+    toolset_id: ReadOnly[str]
+    toolset_name: ReadOnly[str]
+    description: NotRequired[ReadOnly[str | None]]
+    tools: NotRequired[ReadOnly[str | list[MCPToolsetTool]]]
+    created_at: NotRequired[ReadOnly[datetime | None]]
+    created_by: NotRequired[ReadOnly[str | None]]
+    updated_at: NotRequired[ReadOnly[datetime | None]]
+    updated_by: NotRequired[ReadOnly[str | None]]
+
+
+class MCPToolsetRow(Protocol):
+    """A row of the toolset table, as the prisma client returns it."""
+
+    def model_dump(self) -> MCPToolsetRowData: ...
+
+
+class MCPToolsetTable(Protocol):
+    """The prisma table actions this module runs against the toolset table."""
+
+    async def create(self, data: Mapping[str, object]) -> MCPToolsetRow: ...
+
+    async def find_unique(self, where: Mapping[str, object]) -> MCPToolsetRow | None: ...
+
+    async def find_first(self, where: Mapping[str, object]) -> MCPToolsetRow | None: ...
+
+    async def find_many(self, where: Mapping[str, object]) -> Sequence[MCPToolsetRow]: ...
+
+    async def update(self, where: Mapping[str, object], data: Mapping[str, object]) -> MCPToolsetRow: ...
+
+    async def delete(self, where: Mapping[str, object]) -> MCPToolsetRow: ...
+
+
+def _toolset_table(prisma_client: PrismaClient) -> MCPToolsetTable:
+    """The toolset table actions of the prisma client."""
+    return MCPToolsetRepository(prisma_client).table
+
+
+def _toolset_from_row(row: MCPToolsetRow) -> MCPToolset:
     data: Final = row.model_dump()
-    tools = data.get("tools") or []
-    if isinstance(tools, str):
-        tools = json.loads(tools)
-    data["tools"] = tools
-    return MCPToolset(**data)
+    tools: Final = data.get("tools") or []
+    resolved: Final[MCPToolsetFields] = {
+        **data,
+        "tools": json.loads(tools) if isinstance(tools, str) else tools,
+    }
+    return MCPToolset(**resolved)
 
 
 async def create_mcp_toolset(
@@ -31,7 +90,7 @@ async def create_mcp_toolset(
     data_dict["tools"] = json.dumps(data_dict.get("tools", []))
     data_dict["created_by"] = touched_by
     data_dict["updated_by"] = touched_by
-    row: Final = await MCPToolsetRepository(prisma_client).table.create(data=data_dict)
+    row: Final = await _toolset_table(prisma_client).create(data=data_dict)
     return _toolset_from_row(row)
 
 
@@ -39,7 +98,7 @@ async def get_mcp_toolset(
     prisma_client: PrismaClient,
     toolset_id: str,
 ) -> MCPToolset | None:
-    row: Final = await MCPToolsetRepository(prisma_client).table.find_unique(where={"toolset_id": toolset_id})
+    row: Final = await _toolset_table(prisma_client).find_unique(where={"toolset_id": toolset_id})
     if row is None:
         return None
     return _toolset_from_row(row)
@@ -47,13 +106,11 @@ async def get_mcp_toolset(
 
 async def list_mcp_toolsets(
     prisma_client: PrismaClient,
-    toolset_ids: list[str] | None = None,
-) -> list[MCPToolset]:
+    toolset_ids: Sequence[str] | None = None,
+) -> Sequence[MCPToolset]:
     try:
-        where = {}
-        if toolset_ids is not None:
-            where = {"toolset_id": {"in": toolset_ids}}
-        rows: Final = await MCPToolsetRepository(prisma_client).table.find_many(where=where)
+        where: Final[Mapping[str, object]] = {} if toolset_ids is None else {"toolset_id": {"in": toolset_ids}}
+        rows: Final = await _toolset_table(prisma_client).find_many(where=where)
         return [_toolset_from_row(r) for r in rows]
     except Exception as e:
         verbose_proxy_logger.warning("litellm.proxy._experimental.mcp_server.toolset_db::list_mcp_toolsets - %s", e)
@@ -64,7 +121,7 @@ async def get_mcp_toolset_by_name(
     prisma_client: PrismaClient,
     toolset_name: str,
 ) -> MCPToolset | None:
-    row: Final = await MCPToolsetRepository(prisma_client).table.find_first(where={"toolset_name": toolset_name})
+    row: Final = await _toolset_table(prisma_client).find_first(where={"toolset_name": toolset_name})
     if row is None:
         return None
     return _toolset_from_row(row)
@@ -80,7 +137,7 @@ async def update_mcp_toolset(
         data_dict["tools"] = json.dumps(data_dict["tools"])
     data_dict["updated_by"] = touched_by
     try:
-        row: Final = await MCPToolsetRepository(prisma_client).table.update(
+        row: Final = await _toolset_table(prisma_client).update(
             where={"toolset_id": data.toolset_id},
             data=data_dict,
         )
@@ -98,7 +155,7 @@ async def delete_mcp_toolset(
     toolset_id: str,
 ) -> MCPToolset | None:
     try:
-        row: Final = await MCPToolsetRepository(prisma_client).table.delete(where={"toolset_id": toolset_id})
+        row: Final = await _toolset_table(prisma_client).delete(where={"toolset_id": toolset_id})
     except Exception as e:
         from prisma.errors import RecordNotFoundError
 
diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json
index 5af45b29226..13c7a4c7cfa 100644
--- a/litellm/proxy/_lazy_openapi_snapshot.json
+++ b/litellm/proxy/_lazy_openapi_snapshot.json
@@ -32002,6 +32002,62 @@
           "title": "SCIMPatchOperation",
           "type": "object"
         },
+        "SCIMPlaceholder": {
+          "description": "A user row keyed by a value that names another account by SSO identity or email.",
+          "properties": {
+            "placeholder_user_id": {
+              "title": "Placeholder User Id",
+              "type": "string"
+            },
+            "resolved_user_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Resolved User Ids",
+              "type": "array"
+            },
+            "team_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Team Ids",
+              "type": "array"
+            }
+          },
+          "required": [
+            "placeholder_user_id",
+            "resolved_user_ids",
+            "team_ids"
+          ],
+          "title": "SCIMPlaceholder",
+          "type": "object"
+        },
+        "SCIMPlaceholderMergeResult": {
+          "properties": {
+            "merged_into_user_id": {
+              "title": "Merged Into User Id",
+              "type": "string"
+            },
+            "placeholder_user_id": {
+              "title": "Placeholder User Id",
+              "type": "string"
+            },
+            "team_ids": {
+              "items": {
+                "type": "string"
+              },
+              "title": "Team Ids",
+              "type": "array"
+            }
+          },
+          "required": [
+            "placeholder_user_id",
+            "merged_into_user_id",
+            "team_ids"
+          ],
+          "title": "SCIMPlaceholderMergeResult",
+          "type": "object"
+        },
         "SCIMServiceProviderConfig": {
           "properties": {
             "authenticationSchemes": {
@@ -33641,6 +33697,129 @@
             "scim"
           ]
         }
+      },
+      "/scim/v2/placeholders": {
+        "get": {
+          "description": "List user rows whose id is another account's SSO identity or email.\n\nAn earlier release provisioned a group member it could not match as a user keyed\nby the raw member value, and that row now shadows the account the value really\nnames, so every push of that member is refused. This lists those rows so an\noperator can fold each one into the account it shadows with\n``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of\nits own or owns virtual keys is left out: someone uses that account.",
+          "operationId": "list_placeholders_scim_v2_placeholders_get",
+          "parameters": [
+            {
+              "in": "query",
+              "name": "feature",
+              "required": false,
+              "schema": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "title": "Feature"
+              }
+            }
+          ],
+          "responses": {
+            "200": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "items": {
+                      "$ref": "#/components/schemas/SCIMPlaceholder"
+                    },
+                    "title": "Response List Placeholders Scim V2 Placeholders Get",
+                    "type": "array"
+                  }
+                }
+              },
+              "description": "Successful Response"
+            },
+            "422": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/HTTPValidationError"
+                  }
+                }
+              },
+              "description": "Validation Error"
+            }
+          },
+          "security": [
+            {
+              "APIKeyHeader": []
+            }
+          ],
+          "summary": "List Placeholders",
+          "tags": [
+            "scim"
+          ]
+        }
+      },
+      "/scim/v2/placeholders/{user_id}/merge": {
+        "post": {
+          "description": "Fold a placeholder user into the one account its id names by SSO identity or email.\n\nThe account is added to every team the placeholder is on, then the placeholder is\ndeleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group\npush resolves the member value to the real account. Refused with 409 when the row\nhas an SSO identity of its own, owns virtual keys, or names no account or several.",
+          "operationId": "merge_placeholder_scim_v2_placeholders__user_id__merge_post",
+          "parameters": [
+            {
+              "in": "path",
+              "name": "user_id",
+              "required": true,
+              "schema": {
+                "title": "User ID",
+                "type": "string"
+              }
+            },
+            {
+              "in": "query",
+              "name": "feature",
+              "required": false,
+              "schema": {
+                "anyOf": [
+                  {
+                    "type": "string"
+                  },
+                  {
+                    "type": "null"
+                  }
+                ],
+                "title": "Feature"
+              }
+            }
+          ],
+          "responses": {
+            "200": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/SCIMPlaceholderMergeResult"
+                  }
+                }
+              },
+              "description": "Successful Response"
+            },
+            "422": {
+              "content": {
+                "application/json": {
+                  "schema": {
+                    "$ref": "#/components/schemas/HTTPValidationError"
+                  }
+                }
+              },
+              "description": "Validation Error"
+            }
+          },
+          "security": [
+            {
+              "APIKeyHeader": []
+            }
+          ],
+          "summary": "Merge Placeholder",
+          "tags": [
+            "scim"
+          ]
+        }
       }
     }
   },
diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py
index 5ba5e8fa1aa..2da7ceb2d50 100644
--- a/litellm/proxy/_types.py
+++ b/litellm/proxy/_types.py
@@ -422,6 +422,9 @@ class LiteLLMRoutes(enum.Enum):
         "/responses/{response_id}/cancel",
         "/v1/responses/{response_id}/cancel",
         "/openai/v1/responses/{response_id}/cancel",
+        "/responses/input_tokens",
+        "/v1/responses/input_tokens",
+        "/openai/v1/responses/input_tokens",
         # vector stores
         "/vector_stores",
         "/v1/vector_stores",
@@ -471,6 +474,7 @@ class LiteLLMRoutes(enum.Enum):
         "/vllm",
         "/mistral",
         "/milvus",
+        "/gigachat",
         "/watsonx",
     ]
 
@@ -1212,6 +1216,13 @@ class GenerateKeyRequest(KeyRequestBase):
     organization_id: str | None = None
     project_id: str | None = None
 
+    @field_validator("team_id", mode="before")
+    @classmethod
+    def treat_cleared_team_id_as_unset(cls, v: object) -> object:
+        if v == "":
+            return None
+        return v
+
 
 class GenerateKeyResponse(KeyRequestBase):
     key: str
@@ -2432,9 +2443,22 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase):
     database_socket_timeout: float | None = Field(
         None,
         description=(
-            "Prisma `socket_timeout` URL param (seconds). When set, an idle/slow "
-            "connection that has not produced data within this window is closed. "
-            "This is the main knob for capping idle DB connections from LiteLLM."
+            "Prisma `socket_timeout` URL param (seconds). When set, an in-flight "
+            "operation that has not produced data within this window is aborted. "
+            "For capping how long idle pooled connections are kept, see "
+            "`database_max_idle_connection_lifetime`."
+        ),
+    )
+    database_max_idle_connection_lifetime: float | None = Field(
+        60,
+        description=(
+            "Prisma `max_idle_connection_lifetime` URL param (seconds). A pooled "
+            "connection idle longer than this is closed and replaced instead of "
+            "being handed to the next request. Defaults to 60 so connections are "
+            "recycled before common infra idle timeouts (AWS NLB / RDS Proxy "
+            "~350s, many LBs 60-350s) silently drop them and requests fail with "
+            "`Error { kind: Closed }`. A value pinned on the DATABASE_URL or set "
+            "via `database_extra_connection_params` takes precedence."
         ),
     )
     database_extra_connection_params: dict[str, Any] | None = Field(
@@ -2484,6 +2508,14 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase):
         None,
         description="max batch input file size in MB for /v1/files uploads with purpose=batch, if a file is larger than this size it will be rejected before being forwarded to the provider",
     )
+    max_file_size_mb: int | None = Field(
+        None,
+        description="max file size in MB for /v1/files uploads, for any purpose, if a file is larger than this size it will be rejected before being forwarded to the provider",
+    )
+    blocked_file_extensions: tuple[str, ...] | None = Field(
+        None,
+        description="file extensions (e.g. ['.exe', '.sh']) rejected on /v1/files uploads, for any purpose, matched case-insensitively against the uploaded filename",
+    )
     max_response_size_mb: int | None = Field(
         None,
         description="max response size in MB, if a response is larger than this size it will be rejected",
@@ -2541,7 +2573,7 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase):
     )
     alerting: list | None = Field(
         None,
-        description="List of alerting integrations. Today, just slack - `alerting: ['slack']`",
+        description="List of alerting integrations - e.g. `alerting: ['slack', 'webhook', 'email']`. 'slack' posts Slack-format messages to any Slack-compatible webhook (Slack, Rocket.Chat, Mattermost); 'webhook' posts structured JSON budget alerts to WEBHOOK_URL",
     )
     alert_types: list[AlertType] | None = Field(
         None,
@@ -2672,6 +2704,40 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase):
         None,
         description="List of MCP server fields that must be filled in for a submission to pass standards checks (e.g. ['description', 'source_url', 'alias']).",
     )
+    password_policy_min_length: int | None = Field(
+        None,
+        description=(
+            "Minimum length required for a locally-managed user's password. Default is 12; "
+            "a value below 8 is floored to 8 rather than weakening the requirement further."
+        ),
+    )
+    password_policy_require_uppercase: bool | None = Field(
+        None,
+        description="If True (default), a locally-managed user's password must contain an uppercase letter.",
+    )
+    password_policy_require_lowercase: bool | None = Field(
+        None,
+        description="If True (default), a locally-managed user's password must contain a lowercase letter.",
+    )
+    password_policy_require_numbers: bool | None = Field(
+        None,
+        description="If True (default), a locally-managed user's password must contain a number.",
+    )
+    password_policy_require_special_characters: bool | None = Field(
+        None,
+        description="If True (default), a locally-managed user's password must contain a special (non-alphanumeric) character.",
+    )
+    disable_password_login_when_sso_enabled: bool | None = Field(
+        None,
+        description=(
+            "If True and SSO is configured (MICROSOFT_CLIENT_ID, GOOGLE_CLIENT_ID, "
+            "GENERIC_CLIENT_ID, or SAML_IDP_METADATA_URL/XML), disables username/password "
+            "login on /login, /v2/login, and /v3/login so SSO is the only way to reach the "
+            "Admin UI. An admin locked out of the UI can still administer the proxy over the "
+            "API with the master key; unset this setting and restart the proxy to restore "
+            "UI username/password login. Default is False."
+        ),
+    )
     disable_budget_reservation: bool | None = Field(
         None,
         description=(
@@ -3549,6 +3615,19 @@ class AllCallbacks(LiteLLMPydanticObjectBase):
     )
 
 
+class SpendLogsRouterMetadata(TypedDict):
+    """
+    Router provenance stamped on spend logs for deployments flagged with
+    model_info.internal_router_model, correlating the requested model group
+    with the provider deployment that served the call
+    """
+
+    requested_model: ReadOnly[str | None]
+    selected_model: ReadOnly[str | None]
+    selected_provider: ReadOnly[str | None]
+    router_correlation_id: ReadOnly[str | None]
+
+
 class SpendLogsMetadata(TypedDict):
     """
     Specific metadata k,v pairs logged to spendlogs for easier cost tracking
@@ -3591,6 +3670,7 @@ class SpendLogsMetadata(TypedDict):
     compression_savings: CompressionSavingsMetadata | None
     autorouter_savings: ReadOnly[float | None]  # stamped by the logging payload; None = not auto-routed
     litellm_gateway_injected_cache: ReadOnly[str | None]
+    router_metadata: ReadOnly[SpendLogsRouterMetadata | None]  # None = deployment not flagged internal_router_model
 
 
 class SpendLogsPayload(TypedDict):
diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py
index bd02cfdf907..28882484db4 100644
--- a/litellm/proxy/agent_endpoints/a2a_endpoints.py
+++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py
@@ -14,7 +14,7 @@ import json
 from collections.abc import AsyncGenerator, Mapping
 from copy import deepcopy
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 from urllib.parse import urlparse
 
 from fastapi import APIRouter, Depends, HTTPException, Request, Response
@@ -215,11 +215,20 @@ def _enforce_inbound_trace_id(agent: "AgentResponse", request: Request) -> None:
         )
 
 
+class _JsonRpcResponse(Protocol):
+    def json(self) -> dict[str, object]: ...
+
+
+def _jsonrpc_body(response: _JsonRpcResponse) -> dict[str, object]:
+    """The decoded JSON-RPC body of ``response``."""
+    return response.json()
+
+
 async def _forward_jsonrpc(
     agent_url: str,
     body: dict[str, object],
     extra_headers: Mapping[str, str] | None = None,
-) -> dict[str, Any]:
+) -> dict[str, object]:
     from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
     from litellm.types.llms.custom_http import httpxSpecialProvider
 
@@ -230,7 +239,7 @@ async def _forward_jsonrpc(
     )
     resp: Final = await handler.post(agent_url, json=body, headers=headers)
     try:
-        result: Final = resp.json()
+        result: Final = _jsonrpc_body(resp)
     except Exception:
         resp.raise_for_status()
         raise
@@ -940,8 +949,8 @@ async def invoke_agent_a2a(
             )
             result = await _forward_jsonrpc(agent_url, forward_body, extra_headers=caller_headers)
             if method == "agent/getAuthenticatedExtendedCard":
-                if isinstance(result.get("result"), dict):
-                    card: Final = result["result"]
+                card: Final = result.get("result")
+                if isinstance(card, dict):
                     proxy_url: Final = get_custom_url(str(request.base_url), route=f"a2a/{agent_id}")
                     # Rewrite the upstream agent URL in both 0.3 (top-level `url`)
                     # and 1.0 (`supportedInterfaces[0].url`) wire formats so that
@@ -1010,4 +1019,6 @@ async def invoke_agent_a2a(
             )
         except Exception:
             pass
+        if isinstance(e, litellm.BadRequestError):
+            return _jsonrpc_error(body.get("id"), -32602, e.message, 400)
         return _jsonrpc_error(body.get("id"), -32603, f"Internal error: {e}", 500)
diff --git a/litellm/proxy/agent_endpoints/agent_registry.py b/litellm/proxy/agent_endpoints/agent_registry.py
index 6d9a907324d..c7b6bca72cf 100644
--- a/litellm/proxy/agent_endpoints/agent_registry.py
+++ b/litellm/proxy/agent_endpoints/agent_registry.py
@@ -6,8 +6,12 @@ from datetime import datetime, timezone
 from types import MappingProxyType
 from typing import TYPE_CHECKING, Final, NamedTuple, Protocol, TypedDict
 
+from pydantic import TypeAdapter, ValidationError
+
 import litellm
+from litellm.constants import REDACTED_BY_LITELM_STRING
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.litellm_core_utils.sensitive_data_masker import SensitiveDataMasker
 from litellm.proxy.management_helpers.object_permission_utils import (
     handle_update_object_permission_common,
 )
@@ -52,6 +56,9 @@ class AgentRecord(Protocol):
     @property
     def agent_name(self) -> str: ...
 
+    @property
+    def litellm_params(self) -> Mapping[str, object] | None: ...
+
     @property
     def object_permission_id(self) -> str | None: ...
 
@@ -121,6 +128,188 @@ def _dump_agent_params(raw: Mapping[str, object]) -> dict[str, object]:
     return dict(raw) if raw else {}
 
 
+_AGENT_PARAMS_MASKER: Final = SensitiveDataMasker()
+_REDACT_AGENT_PARAMS_MAX_DEPTH: Final = 10
+_AGENT_PARAMS_ADAPTER: Final[TypeAdapter[dict[str, object]]] = TypeAdapter(
+    dict[str, object]
+)  # mutable-ok: safe_dumps() and AgentResponse.litellm_params both require a real dict, not a Mapping
+_AGENT_PARAMS_SEQUENCE_ADAPTER: Final[TypeAdapter[tuple[object, ...]]] = TypeAdapter(tuple[object, ...])
+_EMPTY_LITELLM_PARAMS: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def redact_sensitive_agent_litellm_params(litellm_params: object, _depth: int = 0) -> object:
+    """
+    Replace credential-bearing values in an agent's litellm_params with
+    ``REDACTED_BY_LITELM_STRING`` while preserving non-secret keys (``model``,
+    ``is_public``, rate-limit config). Used so list/get/create/update
+    responses never echo a stored provider credential back to the caller.
+
+    Handles a plain dict, a JSON-serialized string (some callers hold the
+    in-memory registry's params that way), and ``None`` at the top level;
+    anything else is passed through. Recursion depth is bounded to match the
+    convention documented in ``tests/code_coverage_tests/recursive_detector.py``.
+    """
+    if litellm_params is None:
+        return None
+    if isinstance(litellm_params, str):
+        if _depth >= _REDACT_AGENT_PARAMS_MAX_DEPTH:
+            return REDACTED_BY_LITELM_STRING
+        try:
+            parsed_params: Final = _AGENT_PARAMS_ADAPTER.validate_json(litellm_params)
+        except ValidationError:
+            return REDACTED_BY_LITELM_STRING
+        return json.dumps(_redact_agent_params_tree(parsed_params, _depth + 1))
+    return _redact_agent_params_tree(litellm_params, _depth)
+
+
+def _redact_agent_params_tree(value: object, _depth: int) -> object:
+    """Structural recursion over an already-parsed litellm_params value: a
+    dict redacts sensitive keys and recurses into the rest, a list redacts
+    each element (so a secret nested inside a list of provider configs is
+    still caught), and anything else -- including a plain string leaf, which
+    must never be re-interpreted as a JSON blob -- passes through unchanged.
+    """
+    if _depth >= _REDACT_AGENT_PARAMS_MAX_DEPTH:
+        return REDACTED_BY_LITELM_STRING
+    if isinstance(value, list):
+        typed_items: Final = _AGENT_PARAMS_SEQUENCE_ADAPTER.validate_python(value)
+        return tuple(_redact_agent_params_tree(item, _depth + 1) for item in typed_items)
+    if not isinstance(value, dict):
+        return value
+    typed_params: Final = _AGENT_PARAMS_ADAPTER.validate_python(value)
+    return {
+        key: (
+            REDACTED_BY_LITELM_STRING
+            if _AGENT_PARAMS_MASKER.is_sensitive_key(key)
+            else _redact_agent_params_tree(nested_value, _depth + 1)
+        )
+        for key, nested_value in typed_params.items()
+    }  # mutable-ok: consumed by json.dumps()/AgentResponse.litellm_params, both of which require a real dict
+
+
+def parse_agent_litellm_params(value: object) -> Mapping[str, object]:
+    """Normalize a stored litellm_params column to a read-only mapping.
+
+    The prisma Json column comes back as either an already-parsed dict or a
+    JSON string depending on the read path, so handle both rather than
+    assuming one. Only ever read from (merge-source lookups), never mutated
+    or re-serialized directly, so a read-only view is enough here.
+    """
+    if isinstance(value, str):
+        try:
+            return _AGENT_PARAMS_ADAPTER.validate_json(value)
+        except ValidationError:
+            return _EMPTY_LITELLM_PARAMS
+    if isinstance(value, Mapping):
+        try:
+            return _AGENT_PARAMS_ADAPTER.validate_python(value)
+        except ValidationError:
+            return _EMPTY_LITELLM_PARAMS
+    return _EMPTY_LITELLM_PARAMS
+
+
+_MISSING_AGENT_PARAM: Final = object()
+_RESTORE_AGENT_PARAMS_MAX_DEPTH: Final = 10
+
+
+def _restore_redacted_nested_value(incoming_value: object, existing_value: object, _depth: int) -> object:
+    """Recurse into a non-sensitively-named dict/list value so a secret
+    nested underneath it (e.g. inside a list of per-provider configs) is
+    still restored, not just top-level keys. Mirrors the shapes
+    ``redact_sensitive_agent_litellm_params`` recurses into on read, so
+    restore and redact stay symmetric.
+
+    List elements are paired with the existing list by position: with no
+    stable per-element identity in an arbitrary ``dict[str, object]`` schema,
+    index is the same correspondence every other part of this restore (and
+    the endpoints' existing full-replace-on-PUT semantics) already assumes.
+    This correctly preserves a masked secret across an ordinary edit of that
+    same entry's other fields; it does not protect against a caller who both
+    reorders/resizes the list AND echoes back a masked marker in the same
+    request, which is a known, narrow limitation (see LIT-6736 PR discussion)
+    rather than a cross-entry credential leak in the common case.
+
+    A value collapsed to the flat marker by the read side's depth cap is
+    recovered wholesale from ``existing_value`` (rather than the marker
+    string itself getting persisted) whenever ``existing_value`` isn't
+    already that same flat marker. Depth-bounded like its read-side
+    counterpart; a value at the cap is returned unchanged rather than
+    corrupted.
+    """
+    if incoming_value == REDACTED_BY_LITELM_STRING and existing_value != REDACTED_BY_LITELM_STRING:
+        return existing_value
+    if _depth >= _RESTORE_AGENT_PARAMS_MAX_DEPTH:
+        return incoming_value
+    if isinstance(incoming_value, Mapping):
+        typed_incoming_map: Final = _AGENT_PARAMS_ADAPTER.validate_python(incoming_value)
+        existing_map: Final = (
+            _AGENT_PARAMS_ADAPTER.validate_python(existing_value)
+            if isinstance(existing_value, Mapping)
+            else _EMPTY_LITELLM_PARAMS
+        )
+        return _restore_redacted_litellm_params(typed_incoming_map, existing_map, _depth + 1)
+    if isinstance(incoming_value, (list, tuple)):
+        typed_incoming_seq: Final = _AGENT_PARAMS_SEQUENCE_ADAPTER.validate_python(incoming_value)
+        existing_seq: Final = (
+            _AGENT_PARAMS_SEQUENCE_ADAPTER.validate_python(existing_value)
+            if isinstance(existing_value, (list, tuple))
+            else ()
+        )
+        return tuple(
+            _restore_redacted_nested_value(
+                item,
+                existing_seq[index] if index < len(existing_seq) else None,
+                _depth + 1,
+            )
+            for index, item in enumerate(typed_incoming_seq)
+        )
+    return incoming_value
+
+
+def _resolved_agent_param_value(
+    key: str,
+    incoming: Mapping[str, object],
+    existing: Mapping[str, object],
+    _depth: int,
+) -> object:
+    """The value ``key`` should end up with in a restored litellm_params, or
+    ``_MISSING_AGENT_PARAM`` when it should be dropped entirely."""
+    if key in incoming:
+        value: Final = incoming[key]
+        if _AGENT_PARAMS_MASKER.is_sensitive_key(key):
+            return existing.get(key, _MISSING_AGENT_PARAM) if value == REDACTED_BY_LITELM_STRING else value
+        return _restore_redacted_nested_value(value, existing.get(key), _depth)
+    if _AGENT_PARAMS_MASKER.is_sensitive_key(key):
+        return existing.get(key, _MISSING_AGENT_PARAM)
+    return _MISSING_AGENT_PARAM
+
+
+def _restore_redacted_litellm_params(
+    incoming: Mapping[str, object],
+    existing: Mapping[str, object],
+    _depth: int = 0,
+) -> dict[str, object]:
+    """Restore the real credential behind any litellm_params value the caller
+    echoed back as ``REDACTED_BY_LITELM_STRING``, and behind any sensitive key
+    omitted entirely, so an edit to an unrelated field never overwrites (or
+    silently drops) a stored provider credential -- the UI never has to
+    read-and-resend a secret to keep it. Recurses into nested dicts and lists
+    so a secret nested under a non-sensitively-named key is restored too.
+
+    A sensitive key given a real (non-marker) value, including an explicit
+    empty string, is treated as a deliberate update -- that's how a caller
+    clears a credential. Non-sensitive keys always take the incoming value
+    (recursed into), matching the endpoints' existing full-replace-on-PUT /
+    merge-on-PATCH semantics for everything that isn't a secret.
+    """
+    all_keys: Final = frozenset(incoming) | frozenset(existing)
+    return {
+        key: value
+        for key in all_keys
+        if (value := _resolved_agent_param_value(key, incoming, existing, _depth)) is not _MISSING_AGENT_PARAM
+    }  # mutable-ok: fed to safe_dumps() for JSON-column storage, which requires a real dict
+
+
 class GrantMigrationResult(NamedTuple):
     rewritten: int
     missed: int
@@ -301,9 +490,14 @@ class AgentRegistry:
         try:
             agent_name: Final = agent.get("agent_name")
 
-            # Serialize litellm_params
+            # Serialize litellm_params. A create has no stored row to restore a
+            # secret behind, so a sensitive key submitted as the redaction
+            # marker (e.g. a stray client re-post) is dropped rather than
+            # persisted as the literal placeholder string.
             litellm_params_obj: Final = agent.get("litellm_params", {})
-            litellm_params_dict: Final[dict[str, object]] = _dump_agent_params(litellm_params_obj)
+            litellm_params_dict: Final = _restore_redacted_litellm_params(
+                _dump_agent_params(litellm_params_obj), _EMPTY_LITELLM_PARAMS
+            )
             litellm_params: Final[str] = safe_dumps(litellm_params_dict)
 
             # Serialize agent_card_params
@@ -401,19 +595,23 @@ class AgentRegistry:
             The patched agent
         """
         try:
-            existing_row: Final = await AgentsRepository(prisma_client).table.find_unique(
-                where={"agent_id": agent_id}  # mutable-ok: prisma filters are plain dicts
-            )
-            if existing_row is None:
+            existing_record: Final = await agents_table(prisma_client).find_unique(where={"agent_id": agent_id})
+            if existing_record is None:
                 raise Exception(f"Agent with ID {agent_id} not found")
-            existing_agent: Final = dict(existing_row)
+            existing_agent: Final[Mapping[str, object]] = dict(existing_record)
 
             augment_agent: Final = {**existing_agent, **agent}
             update_data: Final[dict[str, object]] = {}
             if augment_agent.get("agent_name"):
                 update_data["agent_name"] = augment_agent.get("agent_name")
-            if augment_agent.get("litellm_params"):
-                update_data["litellm_params"] = safe_dumps(augment_agent.get("litellm_params"))
+            if "litellm_params" in agent:
+                existing_litellm_params: Final = parse_agent_litellm_params(existing_agent.get("litellm_params"))
+                update_data["litellm_params"] = safe_dumps(
+                    _restore_redacted_litellm_params(
+                        _dump_agent_params(agent.get("litellm_params") or _EMPTY_LITELLM_PARAMS),
+                        existing_litellm_params,
+                    )
+                )
             if augment_agent.get("agent_card_params"):
                 update_data["agent_card_params"] = safe_dumps(augment_agent.get("agent_card_params"))
 
@@ -433,7 +631,7 @@ class AgentRegistry:
                 update_data["extra_headers"] = extra_headers_value if extra_headers_value is not None else []
             if agent.get("object_permission") is not None:
                 agent_copy: Final = dict(augment_agent)
-                existing_object_permission_id: Final = existing_agent.get("object_permission_id")
+                existing_object_permission_id: Final = existing_record.object_permission_id
                 object_permission_id: Final = await handle_update_object_permission_common(
                     agent_copy,
                     existing_object_permission_id,
@@ -476,9 +674,22 @@ class AgentRegistry:
         try:
             agent_name: Final = agent.get("agent_name")
 
+            # A PUT fully replaces litellm_params from the request body, so the
+            # existing row is read up front to restore any sensitive key the
+            # caller echoed back redacted (or omitted) rather than persisting
+            # the marker -- or nothing -- over the real stored credential.
+            existing_row: Final = await agents_table(prisma_client).find_unique(
+                where={"agent_id": agent_id}  # mutable-ok: prisma's query builder rejects a Mapping/MappingProxyType
+            )
+            existing_litellm_params: Final = parse_agent_litellm_params(
+                existing_row.litellm_params if existing_row is not None else None
+            )
+
             # Serialize litellm_params
             litellm_params_obj: Final = agent.get("litellm_params", {})
-            litellm_params_dict: Final[dict[str, object]] = _dump_agent_params(litellm_params_obj)
+            litellm_params_dict: Final = _restore_redacted_litellm_params(
+                _dump_agent_params(litellm_params_obj), existing_litellm_params
+            )
             litellm_params: Final[str] = safe_dumps(litellm_params_dict)
 
             # Serialize agent_card_params
@@ -514,9 +725,8 @@ class AgentRegistry:
                     update_data[rate_field] = _val
 
             if agent.get("object_permission") is not None:
-                existing_agent: Final = await agents_table(prisma_client).find_unique(where={"agent_id": agent_id})
                 existing_object_permission_id: Final = (
-                    existing_agent.object_permission_id if existing_agent is not None else None
+                    existing_row.object_permission_id if existing_row is not None else None
                 )
                 agent_copy: Final = dict(agent)
                 object_permission_id: Final = await handle_update_object_permission_common(
diff --git a/litellm/proxy/agent_endpoints/agent_search.py b/litellm/proxy/agent_endpoints/agent_search.py
index 46ab36d7b72..76e3fe6c5ad 100644
--- a/litellm/proxy/agent_endpoints/agent_search.py
+++ b/litellm/proxy/agent_endpoints/agent_search.py
@@ -2,17 +2,18 @@
 
 from __future__ import annotations
 
-import math
-from collections.abc import Awaitable, Mapping, Sequence
+from collections.abc import Sequence
 from dataclasses import dataclass
-from itertools import chain
-from types import MappingProxyType
-from typing import TYPE_CHECKING, Final, Protocol, TypeAlias
+from typing import TYPE_CHECKING, Final, TypeAlias
 
-from openai import OpenAIError
 from pydantic import BaseModel, ConfigDict, ValidationError
 
-from litellm.exceptions import BudgetExceededError
+from litellm.proxy.common_utils.semantic_text_index import (
+    Embedder,
+    EmbeddingFailed,
+    SemanticTextIndex,
+    router_embedder,
+)
 from litellm.types.agents import AgentResponse
 
 if TYPE_CHECKING:
@@ -21,12 +22,6 @@ if TYPE_CHECKING:
 
 DEFAULT_AGENT_SEARCH_TOP_K: Final = 5
 
-Vector: TypeAlias = tuple[float, ...]
-
-
-class Embedder(Protocol):
-    def __call__(self, texts: Sequence[str]) -> Awaitable[Sequence[Vector]]: ...
-
 
 @dataclass(frozen=True, slots=True)
 class AgentSearchHit:
@@ -67,18 +62,6 @@ class _SearchableCard(BaseModel):
     skills: tuple[_SearchableSkill, ...] = ()
 
 
-class _EmbeddingItem(BaseModel):
-    model_config = ConfigDict(frozen=True, extra="ignore")
-
-    embedding: tuple[float, ...]
-
-
-class _EmbeddingData(BaseModel):
-    model_config = ConfigDict(frozen=True, extra="ignore")
-
-    data: tuple[_EmbeddingItem, ...]
-
-
 class AgentSearchResult(BaseModel):
     model_config = ConfigDict(frozen=True)
 
@@ -117,110 +100,21 @@ def agent_search_result(hit: AgentSearchHit) -> AgentSearchResult:
     )
 
 
-def cosine_similarity(left: Vector, right: Vector) -> float:
-    dot: Final = sum(a * b for a, b in zip(left, right, strict=True))
-    norms: Final = math.sqrt(sum(a * a for a in left)) * math.sqrt(sum(b * b for b in right))
-    return dot / norms if norms else 0.0
-
-
-def embedding_spend_metadata(user_api_key_dict: UserAPIKeyAuth) -> dict[str, object]:
-    from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
-
-    return {  # mutable-ok: the router mutates the metadata dict it is handed
-        **LiteLLMProxyRequestSetup.get_sanitized_user_information_from_key(user_api_key_dict),
-        "user_api_key": user_api_key_dict.api_key,
-    }
-
-
-def router_embedder(router: Router, embedding_model: str, user_api_key_dict: UserAPIKeyAuth) -> Embedder:
-    async def embed(texts: Sequence[str]) -> Sequence[Vector]:
-        batch: Final = list(texts)  # mutable-ok: Router.aembedding accepts only str | list input
-        response: Final = await router.aembedding(
-            model=embedding_model, input=batch, metadata=embedding_spend_metadata(user_api_key_dict)
-        )
-        return tuple(item.embedding for item in _EmbeddingData.model_validate(response.model_dump()).data)
-
-    return embed
-
-
-_NO_VECTORS: Final[Mapping[str, Vector]] = MappingProxyType({})
-
-
-async def _embed_all(embed: Embedder, texts: Sequence[str]) -> tuple[Vector, ...] | AgentSearchEmbeddingFailed:
-    try:
-        vectors: Final = tuple(await embed(texts))
-    except (OpenAIError, ValueError, BudgetExceededError) as exc:
-        return AgentSearchEmbeddingFailed(reason=f"embedding the search query failed: {exc}")
-    if len(vectors) != len(texts):
-        return AgentSearchEmbeddingFailed(
-            reason=f"embedding model returned {len(vectors)} vectors for {len(texts)} inputs"
-        )
-    return vectors
-
-
-@dataclass(frozen=True, slots=True)
-class _Embedded:
-    query_vector: Vector
-    vectors: Mapping[str, Vector]
-
-
-def _same_dimension(query_vector: Vector, vectors: Mapping[str, Vector], texts: Sequence[str]) -> bool:
-    return all(len(vectors[text]) == len(query_vector) for text in texts)
-
-
-async def _embed_query_and_agents(
-    embed: Embedder, query: str, texts: Sequence[str], cached: Mapping[str, Vector]
-) -> _Embedded | AgentSearchEmbeddingFailed:
-    missing: Final = tuple(dict.fromkeys(text for text in texts if text not in cached))
-    embedded: Final = await _embed_all(embed, (query, *missing))
-    if isinstance(embedded, AgentSearchEmbeddingFailed):
-        return embedded
-    vectors: Final = MappingProxyType(dict(chain(cached.items(), zip(missing, embedded[1:], strict=True))))
-    if _same_dimension(embedded[0], vectors, texts):
-        return _Embedded(query_vector=embedded[0], vectors=vectors)
-    unique: Final = tuple(dict.fromkeys(texts))
-    reembedded: Final = await _embed_all(embed, (query, *unique))
-    if isinstance(reembedded, AgentSearchEmbeddingFailed):
-        return reembedded
-    return _Embedded(
-        query_vector=reembedded[0], vectors=MappingProxyType(dict(zip(unique, reembedded[1:], strict=True)))
-    )
-
-
 class AgentSearchIndex:
     """Caches one vector per distinct agent text per embedding model, so repeat searches only embed the query."""
 
     def __init__(self) -> None:
-        self._vectors: Mapping[str, Mapping[str, Vector]] = MappingProxyType({})
-
-    def _merged(self, embedding_model: str, embedded: _Embedded) -> Mapping[str, Vector]:
-        kept: Final = {
-            text: vector
-            for text, vector in self._vectors.get(embedding_model, _NO_VECTORS).items()
-            if len(vector) == len(embedded.query_vector)
-        }
-        return MappingProxyType({**kept, **embedded.vectors})
+        self._index: Final = SemanticTextIndex()
 
     async def search(
         self, query: str, agents: Sequence[AgentResponse], top_k: int, embed: Embedder, embedding_model: str
     ) -> AgentSearchHits | AgentSearchEmbeddingFailed:
-        if not agents:
-            return AgentSearchHits(hits=())
         texts: Final = tuple(agent_search_text(agent) for agent in agents)
-        cached: Final = self._vectors.get(embedding_model, _NO_VECTORS)
-        embedded: Final = await _embed_query_and_agents(embed, query, texts, cached)
-        if isinstance(embedded, AgentSearchEmbeddingFailed):
-            return embedded
-        if not _same_dimension(embedded.query_vector, embedded.vectors, texts):
-            return AgentSearchEmbeddingFailed(
-                reason=f"embedding model {embedding_model} returned vectors of mixed dimensions"
-            )
-        self._vectors = MappingProxyType({**self._vectors, embedding_model: self._merged(embedding_model, embedded)})
+        scores: Final = await self._index.scores(query, texts, embed, embedding_model)
+        if isinstance(scores, EmbeddingFailed):
+            return AgentSearchEmbeddingFailed(reason=scores.reason)
         ranked: Final = sorted(
-            (
-                AgentSearchHit(agent=agent, score=cosine_similarity(embedded.query_vector, embedded.vectors[text]))
-                for agent, text in zip(agents, texts, strict=True)
-            ),
+            (AgentSearchHit(agent=agent, score=score) for agent, score in zip(agents, scores, strict=True)),
             key=lambda hit: hit.score,
             reverse=True,
         )
diff --git a/litellm/proxy/agent_endpoints/endpoints.py b/litellm/proxy/agent_endpoints/endpoints.py
index b6c41a17503..3e4dc07a521 100644
--- a/litellm/proxy/agent_endpoints/endpoints.py
+++ b/litellm/proxy/agent_endpoints/endpoints.py
@@ -20,7 +20,6 @@ from typing_extensions import ReadOnly, Required
 
 import litellm
 from litellm._logging import verbose_proxy_logger
-from litellm.litellm_core_utils.litellm_logging import _get_masked_values
 from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
 from litellm.proxy._types import (
     CommonProxyErrors,
@@ -33,6 +32,10 @@ from litellm.proxy.a2a.agent_card import (
     merge_agent_card,
     normalize_protocol_version,
 )
+from litellm.proxy.agent_endpoints.agent_registry import (
+    parse_agent_litellm_params,
+    redact_sensitive_agent_litellm_params,
+)
 from litellm.proxy.agent_endpoints.agent_search import (
     DEFAULT_AGENT_SEARCH_TOP_K,
     AgentSearchEmbeddingFailed,
@@ -139,25 +142,37 @@ async def _attach_keys_to_agents(agents: Sequence[AgentResponse], prisma_client)
         agent.keys = matched_keys or None
 
 
+def _redact_agent_litellm_params_dict(
+    litellm_params: Mapping[str, object],
+) -> dict[str, object]:  # mutable-ok: AgentResponse.litellm_params is declared as a plain dict, not Mapping
+    """Type-narrowing wrapper: a dict in always yields a dict back from
+    ``redact_sensitive_agent_litellm_params``, which the function's general
+    (possible-JSON-string, possibly-None) signature can't express."""
+    return dict(  # mutable-ok: AgentResponse.litellm_params is declared as a plain dict, not Mapping
+        parse_agent_litellm_params(redact_sensitive_agent_litellm_params(litellm_params))
+    )
+
+
 def _redact_sensitive_agent_fields(
     agents: Sequence[AgentResponse],
+    *,
+    is_admin: bool,
 ) -> list[AgentResponse]:
     """
-    Return copies of the given agents with sensitive configuration fields
-    redacted.  The original objects are not modified.
+    Return copies of the given agents with credential-bearing litellm_params
+    values replaced by a fixed marker (never returned to ANY caller,
+    admin included) and, for non-admin callers, virtual-key and header
+    fields stripped entirely. The original objects are not modified.
     """
     redacted: Final[list[AgentResponse]] = []
     for agent in agents:
         copy = agent.model_copy(deep=True)
-        copy.static_headers = None
-        copy.extra_headers = None
-        copy.keys = None
+        if not is_admin:
+            copy.static_headers = None
+            copy.extra_headers = None
+            copy.keys = None
         if copy.litellm_params:
-            copy.litellm_params = _get_masked_values(
-                copy.litellm_params,
-                unmasked_length=4,
-                number_of_asterisks=4,
-            )
+            copy.litellm_params = _redact_agent_litellm_params_dict(copy.litellm_params)
         redacted.append(copy)
     return redacted
 
@@ -345,13 +360,13 @@ async def get_agents(
                 global_agent_registry.ids_for_agent(agent.agent_id).isdisjoint(litellm.public_agent_groups)
             )
 
-        # Redact sensitive fields for non-admin users
+        # litellm_params secrets are always redacted; keys/headers stay
+        # admin-only.
         is_admin: Final = (
             user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN
             or user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value
         )
-        if not is_admin:
-            returned_agents = _redact_sensitive_agent_fields(returned_agents)
+        returned_agents = _redact_sensitive_agent_fields(returned_agents, is_admin=is_admin)
 
         if health_check:
             agents_with_url: Final = [agent for agent in returned_agents if (agent.agent_card_params or {}).get("url")]
@@ -505,7 +520,9 @@ async def create_agent(
                 "Failed to register agent '%s' (ID: %s) in memory: %s", agent_name, agent_id, reg_error
             )
 
-        return result
+        # The caller is a proxy admin (enforced above); litellm_params
+        # secrets are still never echoed back in the response.
+        return _redact_sensitive_agent_fields((result,), is_admin=True)[0]
 
     except HTTPException:
         raise
@@ -578,13 +595,13 @@ async def get_agent_by_id(
 
         await _attach_keys_to_agents([agent], prisma_client)
 
-        # Redact sensitive fields for non-admin users
+        # litellm_params secrets are always redacted; keys/headers stay
+        # admin-only.
         is_admin = (
             user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN
             or user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value
         )
-        if not is_admin:
-            agent = _redact_sensitive_agent_fields([agent])[0]
+        agent = _redact_sensitive_agent_fields((agent,), is_admin=is_admin)[0]
 
         return agent
     except HTTPException:
@@ -688,7 +705,7 @@ async def update_agent(
             "Successfully updated agent '%s' (ID: %s) in memory", existing_agent.get("agent_name"), agent_id
         )
 
-        return result
+        return _redact_sensitive_agent_fields((result,), is_admin=True)[0]
     except HTTPException:
         raise
     except Exception as e:
@@ -791,7 +808,7 @@ async def patch_agent(
             "Successfully updated agent '%s' (ID: %s) in memory", existing_agent.get("agent_name"), agent_id
         )
 
-        return result
+        return _redact_sensitive_agent_fields((result,), is_admin=True)[0]
     except HTTPException:
         raise
     except Exception as e:
diff --git a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
new file mode 100644
index 00000000000..7da5e5099fc
--- /dev/null
+++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
@@ -0,0 +1,174 @@
+"""
+Restamp the public ``model`` on the Anthropic Messages ``message_start`` event, the only
+stream event carrying a model, so streamed responses report the requested model like
+non-streaming ones do.
+
+Chunks reach the serializer either as already-encoded SSE frames (``bytes``/``str``, the
+provider passthrough path) or as event dicts (fake-stream and agentic paths).
+"""
+
+import json
+import re
+from collections.abc import Mapping
+from typing import Final
+
+from pydantic import TypeAdapter, ValidationError
+
+_MESSAGE_START_EVENT: Final = "message_start"
+_MESSAGE_START_MARKER: Final = b"message_start"
+_SSE_DATA_FIELD: Final = "data:"
+_SSE_FRAME_END_PATTERN: Final = re.compile(rb"\r\n\r\n|\r\r|\n\n")
+_MAX_HELD_BYTES: Final = 65536
+_PING_MARKERS: Final = (b"event: ping", b'"type": "ping"', b'"type":"ping"')
+
+_EVENT_ADAPTER: Final = TypeAdapter(Mapping[str, object])
+
+
+def _restamped_event(event: Mapping[str, object], requested_model: str) -> Mapping[str, object] | None:
+    message: Final = event.get("message")
+    if event.get("type") != _MESSAGE_START_EVENT or not isinstance(message, dict):
+        return None
+    if message.get("model") == requested_model:
+        return None
+    return {**event, "message": {**message, "model": requested_model}}  # mutable-ok: SSE payload, re-serialized as is
+
+
+def _restamped_data_line(line: str, requested_model: str) -> str | None:
+    stripped: Final = line.strip()
+    if not stripped.startswith(_SSE_DATA_FIELD):
+        return None
+    payload: Final = stripped[len(_SSE_DATA_FIELD) :].strip()
+    if not payload or payload == "[DONE]":
+        return None
+    try:
+        event: Final = _EVENT_ADAPTER.validate_json(payload)
+    except ValidationError:
+        return None
+    restamped: Final = _restamped_event(event, requested_model)
+    if restamped is None:
+        return None
+    terminator: Final = line[len(line.rstrip("\r\n")) :]
+    return f"data: {json.dumps(restamped, separators=(',', ':'))}{terminator}"
+
+
+def _restamped_frame(frame: str, requested_model: str) -> str | None:
+    lines: Final = frame.splitlines(keepends=True)
+    restamped: Final = tuple(_restamped_data_line(line, requested_model) for line in lines)
+    if all(line is None for line in restamped):
+        return None
+    return "".join(new if new is not None else old for new, old in zip(restamped, lines))
+
+
+def restamp_anthropic_stream_chunk_model(chunk: object, requested_model: str) -> object:
+    """
+    Return ``chunk`` with the ``message_start`` model replaced by ``requested_model``.
+
+    Chunks that carry no model are returned unchanged.
+    """
+    if isinstance(chunk, dict):
+        try:
+            event: Final = _EVENT_ADAPTER.validate_python(chunk)
+        except ValidationError:
+            return chunk
+        return _restamped_event(event, requested_model) or chunk
+
+    if isinstance(chunk, (bytes, bytearray)):
+        if _MESSAGE_START_EVENT.encode() not in chunk:
+            return chunk
+        restamped_bytes: Final = _restamped_frame(chunk.decode("utf-8", errors="ignore"), requested_model)
+        return chunk if restamped_bytes is None else restamped_bytes.encode("utf-8")
+
+    if isinstance(chunk, str):
+        if _MESSAGE_START_EVENT not in chunk:
+            return chunk
+        restamped_text: Final = _restamped_frame(chunk, requested_model)
+        return chunk if restamped_text is None else restamped_text
+
+    return chunk
+
+
+def _is_ping_frame(frame: bytes) -> bool:
+    return any(marker in frame for marker in _PING_MARKERS)
+
+
+class AnthropicStreamModelRestamper:
+    """
+    Per-stream restamper for the encoded passthrough path, where chunks are raw
+    transport reads: the ``message_start`` SSE frame can arrive split across
+    chunks or coalesced with later frames. Complete frames (``\\n\\n``,
+    ``\\r\\n\\r\\n``, or ``\\r\\r`` terminated) are emitted as their terminator
+    closes them and an incomplete tail is held until it completes, so the
+    restamp never misses a torn frame; ``flush`` returns whatever is still held
+    when the stream ends so no bytes are swallowed. Once ``message_start`` has
+    been handled, or the first real event proves the stream carries none, every
+    later chunk passes through untouched.
+    """
+
+    def __init__(self, requested_model: str) -> None:
+        self._requested_model: Final = requested_model
+        self._held = b""
+        self._armed = True
+
+    def process(self, chunk: object) -> object:
+        if not self._armed:
+            return chunk
+        if isinstance(chunk, (bytes, bytearray)):
+            return self._process_encoded(bytes(chunk))
+        if isinstance(chunk, str):
+            return self._process_encoded(chunk.encode("utf-8"))
+        restamped: Final = restamp_anthropic_stream_chunk_model(chunk, self._requested_model)
+        if isinstance(chunk, dict) and chunk.get("type") not in (None, "ping"):
+            self._armed = False
+        return restamped
+
+    def flush(self) -> bytes:
+        held: Final = self._held
+        self._held = b""
+        self._armed = False
+        if not held:
+            return b""
+        restamped: Final = restamp_anthropic_stream_chunk_model(held, self._requested_model)
+        return restamped if isinstance(restamped, bytes) else held
+
+    def _process_encoded(self, data: bytes) -> bytes:
+        combined: Final = self._held + data
+        boundaries: Final = tuple(match.end() for match in _SSE_FRAME_END_PATTERN.finditer(combined))
+        if not boundaries:
+            if len(combined) > _MAX_HELD_BYTES:
+                self._held = b""
+                self._armed = False
+                return combined
+            self._held = combined
+            return b""
+        emitted: Final = self._restamped_closed_block(combined[: boundaries[-1]])
+        tail: Final = combined[boundaries[-1] :]
+        if not self._armed:
+            self._held = b""
+            return emitted + tail
+        self._held = tail
+        return emitted
+
+    def _restamped_closed_block(self, closed: bytes) -> bytes:
+        boundaries: Final = tuple(match.end() for match in _SSE_FRAME_END_PATTERN.finditer(closed))
+        frames: Final = tuple(closed[start:end] for start, end in zip((0, *boundaries[:-1]), boundaries))
+        decider: Final = next(
+            (
+                index
+                for index, frame in enumerate(frames)
+                if _MESSAGE_START_MARKER in frame or (b"data:" in frame and not _is_ping_frame(frame))
+            ),
+            None,
+        )
+        if decider is None:
+            return closed
+        self._armed = False
+        if _MESSAGE_START_MARKER not in frames[decider]:
+            return closed
+        restamped_text: Final = _restamped_frame(
+            frames[decider].decode("utf-8", errors="ignore"), self._requested_model
+        )
+        if restamped_text is None:
+            return closed
+        return b"".join(
+            restamped_text.encode("utf-8") if index == decider else frame for index, frame in enumerate(frames)
+        )
diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py
index 5703c6cd5e8..0db4cbc3bf2 100644
--- a/litellm/proxy/auth/auth_checks.py
+++ b/litellm/proxy/auth/auth_checks.py
@@ -4705,6 +4705,13 @@ async def is_valid_fallback_model(
     return True
 
 
+# The shape abbreviate_api_key writes into LiteLLM_VerificationToken.key_name. The
+# last four characters are only barred from being whitespace or a control code,
+# because a custom key's can be anything else, punctuation and non-ASCII included;
+# a real key is at least MINIMUM_CUSTOM_KEY_LENGTH long, so it never fullmatches.
+_MASKED_KEY_NAME_RE: Final = re.compile(r"sk-\.\.\.(?:[^\s\x00-\x1f\x7f-\x9f]{4})?")
+
+
 def _apply_budget_exceeded_throttle(valid_token: UserAPIKeyAuth) -> bool:
     """
     Throttle an over-budget key instead of blocking it, when the key opted in
@@ -4785,10 +4792,15 @@ async def _virtual_key_max_budget_check(
         if math.isfinite(valid_token.max_budget) and spend >= valid_token.max_budget:
             if _apply_budget_exceeded_throttle(valid_token):
                 return
-            # name the key in the error so operators don't have to reverse-map
-            # spend back to a key; key_name is the masked form (last 4 chars)
+            # This message is returned to the caller, and key_name has no enforced
+            # shape (a direct DB write bypasses abbreviate_api_key), so echo it only
+            # when it still looks masked and fall back to the alias otherwise.
             key_label: Final = valid_token.key_alias or "key"
-            key_descriptor: Final = f"{key_label} ({valid_token.key_name})" if valid_token.key_name else key_label
+            key_descriptor: Final = (
+                f"{key_label} ({valid_token.key_name})"
+                if valid_token.key_name and _MASKED_KEY_NAME_RE.fullmatch(valid_token.key_name)
+                else key_label
+            )
             raise litellm.BudgetExceededError(
                 current_cost=spend,
                 max_budget=valid_token.max_budget,
diff --git a/litellm/proxy/auth/auth_exception_handler.py b/litellm/proxy/auth/auth_exception_handler.py
index a42187b3a44..b36c8a038fc 100644
--- a/litellm/proxy/auth/auth_exception_handler.py
+++ b/litellm/proxy/auth/auth_exception_handler.py
@@ -2,13 +2,14 @@
 Handles Authentication Errors
 """
 
+import logging
 from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 from fastapi import HTTPException, Request, status
 
 import litellm
-from litellm._logging import verbose_proxy_logger
+from litellm._logging import verbose_proxy_logger, verbose_proxy_stdout_logger
 from litellm.constants import EMPTY_MAPPING
 from litellm.integrations.otel.runtime import seed_request_identity
 from litellm.litellm_core_utils.core_helpers import is_expected_client_error
@@ -18,7 +19,11 @@ from litellm.proxy._types import (
     ProxyException,
     UserAPIKeyAuth,
 )
-from litellm.proxy.auth.auth_utils import _get_request_ip_address
+from litellm.proxy.auth.auth_utils import (
+    _get_request_ip_address,
+    is_invalid_virtual_key_error,
+    mark_invalid_virtual_key_error,
+)
 from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler
 from litellm.types.services import ServiceTypes
 
@@ -36,6 +41,39 @@ else:
     Span = Any
 
 
+def _as_proxy_exception(e: Exception) -> ProxyException:
+    """Convert an authentication failure into the ProxyException the client receives."""
+    if isinstance(e, litellm.BudgetExceededError):
+        return ProxyException(
+            message=e.message,
+            type=ProxyErrorTypes.budget_exceeded,
+            param=None,
+            code=getattr(e, "status_code", status.HTTP_429_TOO_MANY_REQUESTS),
+        )
+    if isinstance(e, HTTPException):
+        return ProxyException(
+            message=getattr(e, "detail", f"Authentication Error({e})"),
+            type=ProxyErrorTypes.auth_error,
+            param=getattr(e, "param", "None"),
+            code=getattr(e, "status_code", status.HTTP_401_UNAUTHORIZED),
+        )
+    if isinstance(e, ProxyException):
+        return e
+    if PrismaDBExceptionHandler.is_database_service_unavailable_error(e):
+        return ProxyException(
+            message=PrismaDBExceptionHandler.database_unavailable_message(e),
+            type=ProxyErrorTypes.no_db_connection,
+            param="None",
+            code=status.HTTP_503_SERVICE_UNAVAILABLE,
+        )
+    return ProxyException(
+        message="Authentication Error, " + str(e),
+        type=ProxyErrorTypes.auth_error,
+        param=getattr(e, "param", "None"),
+        code=status.HTTP_401_UNAUTHORIZED,
+    )
+
+
 def _with_requester_ip_address(request_data: dict[str, object], requester_ip: str | None) -> dict[str, object]:
     """Auth gate rejections are raised before `add_litellm_data_to_request` records the
     caller IP, so their failure logs would otherwise carry no IP nor key/user identity."""
@@ -110,16 +148,21 @@ class UserAPIKeyAuthExceptionHandler:
                 request=request,
                 use_x_forwarded_for=general_settings.get("use_x_forwarded_for") is True,
             )
-            log_fn: Final = (
-                verbose_proxy_logger.error
-                if is_expected_client_error(e) and not litellm.log_client_error_tracebacks
-                else verbose_proxy_logger.exception
-            )
-            log_fn(
+
+            # Log authentication failures before identity seeding and callbacks, so the log
+            # survives a raising callback pipeline. Classify and route malformed virtual-key
+            # rejections to WARNING on stdout (suppressible via LITELLM_LOG=ERROR).
+            log_extra: Final = {"requester_ip": requester_ip}
+            is_invalid_virtual_key: Final = is_invalid_virtual_key_error(e)
+            is_quiet_log: Final = is_invalid_virtual_key and not litellm.log_client_error_tracebacks
+            logger: Final = verbose_proxy_stdout_logger if is_quiet_log else verbose_proxy_logger
+            logger.log(
+                logging.WARNING if is_quiet_log else logging.ERROR,
                 "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - %s\nRequester IP Address:%s",
                 e,
                 requester_ip,
-                extra={"requester_ip": requester_ip},
+                exc_info=True if litellm.log_client_error_tracebacks or not is_expected_client_error(e) else None,
+                extra=log_extra,
             )
 
             # Log this exception to OTEL, Datadog etc. Reuse the identity resolved
@@ -167,35 +210,13 @@ class UserAPIKeyAuthExceptionHandler:
             if transformed_exception is not None:
                 e = transformed_exception
 
-            if isinstance(e, litellm.BudgetExceededError):
-                raise ProxyException(
-                    message=e.message,
-                    type=ProxyErrorTypes.budget_exceeded,
-                    param=None,
-                    code=getattr(e, "status_code", status.HTTP_429_TOO_MANY_REQUESTS),
+            final_exception: Final = mark_invalid_virtual_key_error(_as_proxy_exception(e), is_invalid_virtual_key)
+            # If a quiet-logged malformed-key transform yields non-401, escalate to ERROR
+            if is_quiet_log and str(final_exception.code) != str(status.HTTP_401_UNAUTHORIZED):
+                verbose_proxy_logger.error(
+                    "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - %s\nRequester IP Address:%s",
+                    final_exception,
+                    requester_ip,
+                    extra=log_extra,
                 )
-            if isinstance(e, HTTPException):
-                raise ProxyException(
-                    message=getattr(e, "detail", f"Authentication Error({e})"),
-                    type=ProxyErrorTypes.auth_error,
-                    param=getattr(e, "param", "None"),
-                    code=getattr(e, "status_code", status.HTTP_401_UNAUTHORIZED),
-                )
-            elif isinstance(e, ProxyException):
-                raise e
-            if PrismaDBExceptionHandler.is_database_service_unavailable_error(e):
-                raise ProxyException(
-                    message=(
-                        "Service Unavailable, the authentication database is "
-                        "temporarily unreachable. Please retry shortly."
-                    ),
-                    type=ProxyErrorTypes.no_db_connection,
-                    param="None",
-                    code=status.HTTP_503_SERVICE_UNAVAILABLE,
-                )
-            raise ProxyException(
-                message="Authentication Error, " + str(e),
-                type=ProxyErrorTypes.auth_error,
-                param=getattr(e, "param", "None"),
-                code=status.HTTP_401_UNAUTHORIZED,
-            )
+            raise final_exception
diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py
index 9b1a6ba5aa7..d6007a2d56e 100644
--- a/litellm/proxy/auth/auth_utils.py
+++ b/litellm/proxy/auth/auth_utils.py
@@ -1,3 +1,4 @@
+import importlib.util
 import os
 import re
 import sys
@@ -15,6 +16,7 @@ from litellm._logging import verbose_proxy_logger
 from litellm.constants import (
     BATCH_ENQUEUED_TOKEN_LIMIT_METADATA_KEY,
     EMPTY_MAPPING,
+    INVALID_VIRTUAL_KEY_ERROR_MARKER,
     MINIMUM_CUSTOM_KEY_LENGTH,
     STANDARD_CUSTOMER_ID_HEADERS,
 )
@@ -34,6 +36,43 @@ from litellm.types.router import CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS
 from litellm.types.utils import CustomPricingLiteLLMParams
 
 
+def is_invalid_virtual_key_error(exception: BaseException | None) -> bool:
+    """True when an authentication error rejects a malformed virtual key.
+
+    Classifies only by the marker stamped where that 401 is raised. Message
+    content is never inspected: other 401s interpolate caller-supplied values
+    (vector store ids, organization ids) into their messages, so a phrase
+    match would let a request body demote an authorization failure to the
+    quiet log path.
+    """
+    if not isinstance(exception, (HTTPException, ProxyException)):
+        return False
+
+    code: Final[object] = getattr(exception, "code", None)
+    status_code: Final[object] = code if code is not None else getattr(exception, "status_code", None)
+    if str(status_code) != str(status.HTTP_401_UNAUTHORIZED):
+        return False
+
+    return getattr(exception, INVALID_VIRTUAL_KEY_ERROR_MARKER, False) is True
+
+
+def mark_invalid_virtual_key_error(exception: ProxyException, is_invalid_virtual_key: bool) -> ProxyException:
+    """Return an independently marked malformed-key exception after callback transformations."""
+    if not is_invalid_virtual_key or str(exception.code) != str(status.HTTP_401_UNAUTHORIZED):
+        return exception
+    marked_exception: Final = ProxyException(
+        message=exception.message,
+        type=exception.type,
+        param=exception.param,
+        code=exception.code,
+        headers=exception.headers.copy(),
+        openai_code=None if exception.openai_code is None else str(exception.openai_code),
+        provider_specific_fields=exception.provider_specific_fields,
+    )
+    setattr(marked_exception, INVALID_VIRTUAL_KEY_ERROR_MARKER, True)
+    return marked_exception
+
+
 def _get_request_ip_address(request: Request, use_x_forwarded_for: bool | None = False) -> str | None:
     client_ip = None
     if use_x_forwarded_for is True and "x-forwarded-for" in request.headers:
@@ -956,7 +995,7 @@ def get_key_model_rpm_limit(
 
     # 2. Check model_max_budget
     if user_api_key_dict.model_max_budget:
-        model_rpm_limit: Final[dict[str, Any]] = {}
+        model_rpm_limit: Final[dict[str, int]] = {}
         for model, budget in user_api_key_dict.model_max_budget.items():
             if isinstance(budget, dict) and budget.get("rpm_limit") is not None:
                 model_rpm_limit[model] = budget["rpm_limit"]
@@ -999,7 +1038,7 @@ def get_key_model_tpm_limit(
 
     # 2. Check model_max_budget (iterate per-model like RPM does)
     if user_api_key_dict.model_max_budget:
-        model_tpm_limit: Final[dict[str, Any]] = {}
+        model_tpm_limit: Final[dict[str, int]] = {}
         for model, budget in user_api_key_dict.model_max_budget.items():
             if isinstance(budget, dict) and budget.get("tpm_limit") is not None:
                 model_tpm_limit[model] = budget["tpm_limit"]
@@ -1062,7 +1101,7 @@ def _validated_output_token_estimates_per_model(raw: object) -> Mapping[str, int
 
 
 def _estimated_output_tokens_from_metadata(
-    metadata: Mapping[str, Any] | None,
+    metadata: Mapping[str, object] | None,
     model_name: str | None,
 ) -> int | None:
     """Resolve the per-model, then global, estimate out of one metadata blob.
@@ -1364,7 +1403,7 @@ def is_pass_through_provider_route(route: str) -> bool:
     return False
 
 
-def _has_user_setup_sso() -> bool:
+def has_user_setup_sso() -> bool:
     """
     Check if the user has set up single sign-on (SSO).
 
@@ -1387,6 +1426,63 @@ def _has_user_setup_sso() -> bool:
     )
 
 
+def _is_google_ready() -> bool:
+    return bool(os.getenv("GOOGLE_CLIENT_ID")) and bool(os.getenv("GOOGLE_CLIENT_SECRET"))
+
+
+def _is_microsoft_ready() -> bool:
+    return (
+        bool(os.getenv("MICROSOFT_CLIENT_ID"))
+        and bool(os.getenv("MICROSOFT_CLIENT_SECRET"))
+        and bool(os.getenv("MICROSOFT_TENANT"))
+    )
+
+
+def _is_generic_oauth_ready() -> bool:
+    return (
+        bool(os.getenv("GENERIC_CLIENT_ID"))
+        and bool(os.getenv("GENERIC_CLIENT_SECRET"))
+        and bool(os.getenv("GENERIC_AUTHORIZATION_ENDPOINT"))
+        and bool(os.getenv("GENERIC_TOKEN_ENDPOINT"))
+        and bool(os.getenv("GENERIC_USERINFO_ENDPOINT"))
+    )
+
+
+def _is_saml_ready() -> bool:
+    if not (os.getenv("SAML_IDP_METADATA_URL") or os.getenv("SAML_IDP_METADATA_XML")):
+        return False
+    # SAML's runtime (python3-saml) is an optional dependency; the SAML
+    # handler itself fails closed on every request when it is missing
+    # (SAMLAuthHandler raises before touching the IdP), so metadata alone
+    # is not "ready" either. find_spec raises ModuleNotFoundError (rather
+    # than returning None) when the top-level package is absent entirely,
+    # so this must not be a bare boolean expression or every password
+    # login would 500 on a deployment that configured SAML metadata
+    # without installing the optional extra.
+    try:
+        return importlib.util.find_spec("onelogin.saml2.auth") is not None
+    except ModuleNotFoundError:
+        return False
+
+
+def is_sso_provider_fully_configured() -> bool:
+    """Whether ANY configured SSO provider has every companion setting it
+    needs to actually authenticate a user, not merely a client id.
+
+    A lone ``MICROSOFT_CLIENT_ID`` with no secret or tenant makes
+    ``has_user_setup_sso()`` return True while every real sign-in attempt
+    fails, so a gate that BLOCKS the password fallback (unlike the UI
+    discovery use of ``has_user_setup_sso()``, where a dead login button is
+    merely confusing) must check readiness here, or it can lock every admin
+    out with no way to sign in at all. Checks every provider independently
+    (mirroring ``/sso/readiness``'s per-provider requirements) rather than
+    stopping at the first one with a client id set, so a stray leftover
+    client id for an unused provider can never mask a different, fully
+    configured provider that would otherwise satisfy this gate.
+    """
+    return _is_google_ready() or _is_microsoft_ready() or _is_generic_oauth_ready() or _is_saml_ready()
+
+
 def get_customer_user_header_from_mapping(user_id_mapping) -> list | None:
     """Return the header_name mapped to CUSTOMER role, if any (dict-based)."""
     if not user_id_mapping:
@@ -1628,7 +1724,7 @@ def _dedupe_model_candidates(candidates: list[str]) -> list[str]:
     return deduped
 
 
-def _get_case_insensitive_mapping_value(mapping: Mapping[str, Any] | None, key: str) -> Any:
+def _get_case_insensitive_mapping_value(mapping: Mapping[str, object] | None, key: str) -> object:
     if not mapping:
         return None
     if key in mapping:
@@ -1732,8 +1828,8 @@ def _resolve_model_id_with_router(model_id: str | None, llm_router: Router | Non
 def _extract_model_candidates_from_request(
     request_data: dict,
     route: str,
-    request_headers: Mapping[str, Any] | None = None,
-    request_query_params: Mapping[str, Any] | None = None,
+    request_headers: Mapping[str, object] | None = None,
+    request_query_params: Mapping[str, object] | None = None,
     llm_router: Router | None = None,
 ) -> list[str]:
     candidates: Final[list[str]] = []
@@ -1825,8 +1921,8 @@ def request_dispatched_to_pass_through_endpoint(request: Request | None) -> bool
 def get_model_from_request(
     request_data: dict,
     route: str,
-    request_headers: Mapping[str, Any] | None = None,
-    request_query_params: Mapping[str, Any] | None = None,
+    request_headers: Mapping[str, object] | None = None,
+    request_query_params: Mapping[str, object] | None = None,
     llm_router: Router | None = None,
     request: Request | None = None,
 ) -> str | list[str] | None:
diff --git a/litellm/proxy/auth/handle_jwt.py b/litellm/proxy/auth/handle_jwt.py
index 39e6ca9a369..0795cee7409 100644
--- a/litellm/proxy/auth/handle_jwt.py
+++ b/litellm/proxy/auth/handle_jwt.py
@@ -14,8 +14,8 @@ import hashlib
 import os
 import re
 import time
-from collections.abc import Awaitable, Callable
-from typing import Any, Final, Literal, NoReturn, TypeVar, cast
+from collections.abc import Awaitable, Callable, Sequence
+from typing import Any, Final, Literal, NoReturn, Protocol, TypeVar, cast
 
 import httpx
 import jwt
@@ -24,6 +24,7 @@ from cryptography.hazmat.backends import default_backend
 from cryptography.hazmat.primitives import serialization
 from fastapi import HTTPException, status
 from jwt.api_jwk import PyJWK
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.litellm_core_utils.dot_notation_indexing import get_nested_value
@@ -93,6 +94,47 @@ UNREACHABLE_CACHE_KEY_PREFIX: Final = "litellm_jwks_unreachable_"
 _CachedValueT = TypeVar("_CachedValueT", bound=JWKKeyValue | str)
 
 
+class _JWTAuthSettings(Protocol):
+    """The JWT auth settings block this handler reads back through ``getattr``, when one is configured."""
+
+    @property
+    def issuers(self) -> Sequence[JWTIssuerConfig] | None: ...
+
+    @property
+    def public_key_ttl(self) -> float: ...
+
+    @property
+    def public_key_stale_ttl(self) -> float: ...
+
+
+class _OIDCDiscoveryBody(TypedDict, total=False):
+    """Decoded OIDC discovery document, read for the JWKS endpoint it advertises."""
+
+    jwks_uri: ReadOnly[str]
+
+
+class _OIDCDiscoveryResponse(Protocol):
+    """The discovery endpoint's HTTP response, read for the decoded document it carries."""
+
+    def json(self) -> _OIDCDiscoveryBody: ...
+
+
+class _UserInfoResponse(Protocol):
+    """The OIDC UserInfo endpoint's HTTP response, read for the identity document it carries."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _discovery_document(response: _OIDCDiscoveryResponse) -> _OIDCDiscoveryBody:
+    """Decode an OIDC discovery response body."""
+    return response.json()
+
+
+def _userinfo_document(response: _UserInfoResponse) -> dict[str, object]:
+    """Decode an OIDC UserInfo response body into its JSON object form."""
+    return response.json()
+
+
 def jwks_unavailable_exception(error: JWKSUnreachableError) -> ProxyException:
     return ProxyException(
         message=(
@@ -794,7 +836,7 @@ class JWTHandler:
                 f"JWT Auth: OIDC discovery endpoint {url} returned status {response.status_code}: {response.text}"
             )
         try:
-            discovery: Final = response.json()
+            discovery: Final = _discovery_document(response)
         except Exception as e:
             raise Exception(f"JWT Auth: Failed to parse OIDC discovery document at {url}: {e}")
 
@@ -806,13 +848,13 @@ class JWTHandler:
         return jwks_uri
 
     def _get_public_key_cache_ttl(self) -> float:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return 600
         return litellm_jwtauth.public_key_ttl
 
     def _get_public_key_stale_ttl(self) -> float:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return DEFAULT_JWKS_STALE_TTL
         return litellm_jwtauth.public_key_stale_ttl
@@ -938,7 +980,7 @@ class JWTHandler:
             if response.status_code != 200:
                 raise Exception(f"OIDC UserInfo endpoint returned status {response.status_code}: {response.text}")
 
-            userinfo: Final = response.json()
+            userinfo: Final = _userinfo_document(response)
             verbose_proxy_logger.debug("Received OIDC UserInfo: %s", userinfo)
 
             # Cache the userinfo response
@@ -996,7 +1038,7 @@ class JWTHandler:
         }
 
     def _get_configured_issuer(self, token: str) -> JWTIssuerConfig | None:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return None
 
diff --git a/litellm/proxy/auth/ip_address_utils.py b/litellm/proxy/auth/ip_address_utils.py
index 558ea54495f..c2614b85016 100644
--- a/litellm/proxy/auth/ip_address_utils.py
+++ b/litellm/proxy/auth/ip_address_utils.py
@@ -6,8 +6,11 @@ External callers (public IPs) only see servers with available_on_public_internet
 """
 
 import ipaddress
+import os
+from collections.abc import Mapping
 from dataclasses import dataclass
 from typing import Any, Final
+from urllib.parse import urlparse
 
 from fastapi import Request
 from pydantic import TypeAdapter, ValidationError
@@ -137,7 +140,7 @@ class IPAddressUtils:
     @staticmethod
     def is_request_from_trusted_proxy(
         request: Request,
-        general_settings: dict[str, Any] | None = None,
+        general_settings: Mapping[str, Any] | None = None,
     ) -> bool:
         """
         Return True if X-Forwarded-* headers on this request should be trusted.
@@ -190,6 +193,36 @@ class IPAddressUtils:
         trusted_networks: Final = IPAddressUtils.parse_trusted_proxy_networks(trusted_ranges)
         return IPAddressUtils.is_trusted_proxy(direct_ip, trusted_networks)
 
+    @staticmethod
+    def is_request_https(
+        request: Request,
+        general_settings: Mapping[str, Any] | None = None,
+    ) -> bool:
+        """
+        Whether this request's PUBLIC-facing origin is HTTPS, for deciding
+        whether a cookie set on the response should be marked ``Secure``.
+
+        litellm only sees a plain-HTTP hop whenever TLS terminates at a
+        reverse proxy, so ``request.url.scheme`` alone cannot answer this in
+        that deployment shape. Resolved from the first trusted signal:
+          1. ``PROXY_BASE_URL`` (operator-declared public origin).
+          2. ``X-Forwarded-Proto``, only when the request's direct peer is a
+             configured trusted proxy -- see ``is_request_from_trusted_proxy``.
+             An untrusted caller cannot spoof this header to strip Secure.
+          3. The request's own literal scheme (direct TLS termination, or no
+             reverse proxy in front of litellm).
+        """
+        configured_base_url: Final = os.environ.get("PROXY_BASE_URL", "").strip()
+        if configured_base_url:
+            return urlparse(configured_base_url).scheme == "https"
+
+        if IPAddressUtils.is_request_from_trusted_proxy(request, general_settings=general_settings):
+            forwarded_proto: Final = request.headers.get("X-Forwarded-Proto")
+            if forwarded_proto:
+                return forwarded_proto.split(",")[0].strip().lower() == "https"
+
+        return request.url.scheme == "https"
+
     @staticmethod
     def extract_client_ip_from_xff_hops(
         xff_header: str,
diff --git a/litellm/proxy/auth/login_utils.py b/litellm/proxy/auth/login_utils.py
index fba95972944..8d4f6f81363 100644
--- a/litellm/proxy/auth/login_utils.py
+++ b/litellm/proxy/auth/login_utils.py
@@ -7,7 +7,9 @@ login endpoints (e.g., /login and /v2/login).
 
 import os
 import secrets
+from collections.abc import Mapping
 from datetime import datetime, timedelta, timezone
+from types import MappingProxyType
 from typing import Final, Literal, cast
 
 import jwt
@@ -24,6 +26,7 @@ from litellm.proxy._types import (
     UpdateUserRequest,
     UserAPIKeyAuth,
 )
+from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
 from litellm.proxy.management_endpoints.internal_user_endpoints import user_update
 from litellm.proxy.management_endpoints.key_management_endpoints import (
     generate_key_helper_fn,
@@ -111,6 +114,7 @@ async def authenticate_user(
     password: str,
     master_key: str | None,
     prisma_client: PrismaClient | None,
+    general_settings: Mapping[str, object] = MappingProxyType({}),
 ) -> LoginResult:
     """
     Authenticate a user and generate an API key for UI access.
@@ -124,13 +128,40 @@ async def authenticate_user(
         password: Password from the login form
         master_key: Master key for the proxy (required)
         prisma_client: Prisma database client (optional)
+        general_settings: Proxy general_settings, checked for
+            `disable_password_login_when_sso_enabled`
 
     Returns:
         LoginResult: Object containing authentication data
 
     Raises:
-        ProxyException: If authentication fails or required configuration is missing
+        ProxyException: If authentication fails or required configuration is missing,
+            or if username/password login is disabled while SSO is configured
+
+    Recovery: an admin locked out of the UI by
+    `disable_password_login_when_sso_enabled` can still administer the proxy over
+    the API with the master key (Authorization: Bearer <master_key>), which never
+    goes through this function. To restore UI username/password login, unset the
+    setting in config.yaml (or the DB-persisted general_settings) and restart the
+    proxy; this is a deliberate, auditable config change rather than a hidden
+    bypass.
+
+    The gate below requires the SSO provider to be FULLY configured (every
+    companion secret/endpoint an actual sign-in needs), not merely that a
+    client id is present, so an incomplete SSO setup can never disable the
+    only working login path.
     """
+    if general_settings.get("disable_password_login_when_sso_enabled") is True and is_sso_provider_fully_configured():
+        raise ProxyException(
+            message=(
+                "Username/password login is disabled because SSO is configured "
+                "and 'disable_password_login_when_sso_enabled' is set. Sign in via SSO."
+            ),
+            type=ProxyErrorTypes.auth_error,
+            param="disable_password_login_when_sso_enabled",
+            code=403,
+        )
+
     if master_key is None:
         raise ProxyException(
             message="Master Key not set for Proxy. Please set Master Key to use Admin UI. Set `LITELLM_MASTER_KEY` in .env or set general_settings:master_key in config.yaml.  https://docs.litellm.ai/docs/proxy/virtual_keys. If set, use `--detailed_debug` to debug issue.",
diff --git a/litellm/proxy/auth/password_policy.py b/litellm/proxy/auth/password_policy.py
new file mode 100644
index 00000000000..ab7a565894a
--- /dev/null
+++ b/litellm/proxy/auth/password_policy.py
@@ -0,0 +1,92 @@
+"""Password-strength policy enforcement for locally-managed proxy users.
+
+Applied at every path that persists a new or changed password for a DB-backed
+user (``/user/update``, ``/user/bulk_update``, and the invitation onboarding
+claim flow), so the strength bar is configured in one place instead of
+per-endpoint.
+"""
+
+from collections.abc import Mapping
+from dataclasses import dataclass
+from typing import Final
+
+from litellm.proxy._types import ProxyErrorTypes, ProxyException
+
+DEFAULT_MIN_LENGTH: Final = 12
+MIN_ALLOWED_LENGTH: Final = 8
+
+
+def _has_uppercase(password: str) -> bool:
+    return any(ch.isupper() for ch in password)
+
+
+def _has_lowercase(password: str) -> bool:
+    return any(ch.islower() for ch in password)
+
+
+def _has_digit(password: str) -> bool:
+    return any(ch.isdigit() for ch in password)
+
+
+def _has_special_character(password: str) -> bool:
+    """Unicode-aware: a letter or digit from ANY script counts as
+    alphanumeric, not just ASCII, so an accented letter (e.g. the second
+    character of "Passwörd1234") cannot be miscounted as the required
+    special character the way an ASCII-only `[^A-Za-z0-9]` regex would."""
+    return any(not ch.isalnum() for ch in password)
+
+
+@dataclass(frozen=True, slots=True)
+class PasswordPolicy:
+    min_length: int
+    require_uppercase: bool
+    require_lowercase: bool
+    require_numbers: bool
+    require_special_characters: bool
+
+
+def _configured_min_length(general_settings: Mapping[str, object]) -> int:
+    """The configured minimum, floored at MIN_ALLOWED_LENGTH so a nonpositive
+    or too-low override (a typo, or `0`/`false` coercing through) cannot
+    silently disable the length requirement rather than merely relaxing it."""
+    min_length_setting: Final = general_settings.get("password_policy_min_length")
+    if isinstance(min_length_setting, bool) or not isinstance(min_length_setting, (int, float)):
+        return DEFAULT_MIN_LENGTH
+    return max(MIN_ALLOWED_LENGTH, int(min_length_setting))
+
+
+def get_password_policy(general_settings: Mapping[str, object]) -> PasswordPolicy:
+    return PasswordPolicy(
+        min_length=_configured_min_length(general_settings),
+        require_uppercase=general_settings.get("password_policy_require_uppercase", True) is not False,
+        require_lowercase=general_settings.get("password_policy_require_lowercase", True) is not False,
+        require_numbers=general_settings.get("password_policy_require_numbers", True) is not False,
+        require_special_characters=(
+            general_settings.get("password_policy_require_special_characters", True) is not False
+        ),
+    )
+
+
+def _policy_violations(password: str, policy: PasswordPolicy) -> tuple[str, ...]:
+    checks: Final = (
+        (len(password) < policy.min_length, f"be at least {policy.min_length} characters long"),
+        (policy.require_uppercase and not _has_uppercase(password), "include an uppercase letter"),
+        (policy.require_lowercase and not _has_lowercase(password), "include a lowercase letter"),
+        (policy.require_numbers and not _has_digit(password), "include a number"),
+        (policy.require_special_characters and not _has_special_character(password), "include a special character"),
+    )
+    return tuple(message for failed, message in checks if failed)
+
+
+def validate_password_policy(password: str, general_settings: Mapping[str, object]) -> None:
+    """Raise ``ProxyException`` (400) if ``password`` fails the configured policy."""
+    policy: Final = get_password_policy(general_settings)
+    violations: Final = _policy_violations(password, policy)
+    if not violations:
+        return
+    raise ProxyException(
+        message="Password does not meet the required policy: must " + ", ".join(violations) + ".",
+        type=ProxyErrorTypes.validation_error,
+        param="password",
+        code=400,
+    )
diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py
index e92d090a2fb..5fb6dad0cd7 100644
--- a/litellm/proxy/auth/user_api_key_auth.py
+++ b/litellm/proxy/auth/user_api_key_auth.py
@@ -19,12 +19,15 @@ import fastapi
 import orjson
 from fastapi import HTTPException, Request, WebSocket, status
 from fastapi.security.api_key import APIKeyHeader
+from starlette.exceptions import WebSocketException
 
 import litellm
 from litellm._logging import verbose_logger, verbose_proxy_logger
 from litellm._service_logger import ServiceLogging
 from litellm.constants import (
     GLOBAL_PROXY_SPEND_CACHE_KEY,
+    INVALID_VIRTUAL_KEY_ERROR_MARKER,
+    INVALID_VIRTUAL_KEY_ERROR_MESSAGE,
     LITELLM_PROXY_BUDGET_NAME,
     LITELLM_PROXY_MASTER_KEY_ALIAS,
 )
@@ -65,6 +68,7 @@ from litellm.proxy.auth.auth_utils import (
     get_model_from_request,
     get_request_route,
     get_request_route_template,
+    is_invalid_virtual_key_error,
     iter_request_fallback_targets,
     normalize_request_route,
     pre_db_read_auth_checks,
@@ -539,6 +543,8 @@ async def user_api_key_auth_websocket(websocket: WebSocket):
     try:
         return await user_api_key_auth(request=request, api_key=f"Bearer {api_key}")
     except Exception as e:
+        if is_invalid_virtual_key_error(e):
+            raise WebSocketException(code=status.WS_1008_POLICY_VIOLATION)
         verbose_proxy_logger.exception(e)
         await websocket.close(code=status.WS_1008_POLICY_VIOLATION)
         raise HTTPException(status_code=403, detail=str(e))
@@ -1867,13 +1873,17 @@ async def _user_api_key_auth_builder(
                 _masked_key: Final = f"{api_key[:4]}****{api_key[-4:]}" if len(api_key) > 8 else "****"
                 if not api_key.startswith("sk-"):
                     _hint = _JWT_AUTH_DISABLED_HINT if not enable_jwt_auth and JWTHandler.is_jwt(token=api_key) else ""
-                    raise HTTPException(
+                    _malformed_key_error = HTTPException(
                         status_code=status.HTTP_401_UNAUTHORIZED,
                         detail=(
-                            f"LiteLLM Virtual Key expected. Received={_masked_key}, "
+                            f"{INVALID_VIRTUAL_KEY_ERROR_MESSAGE}. Received={_masked_key}, "
                             f"expected to start with 'sk-'.{_hint}"
                         ),
                     )  # prevent token hashes from being used
+                    # Stamp provenance here so log routing classifies this 401 by
+                    # where it was raised, never by its message text.
+                    setattr(_malformed_key_error, INVALID_VIRTUAL_KEY_ERROR_MARKER, True)
+                    raise _malformed_key_error
             else:
                 verbose_logger.warning(
                     "litellm.proxy.proxy_server.user_api_key_auth(): Warning - Key is not a string. Got type={}".format(
diff --git a/litellm/proxy/client/cli/README.md b/litellm/proxy/client/cli/README.md
index fe417396317..3ddce35b53d 100644
--- a/litellm/proxy/client/cli/README.md
+++ b/litellm/proxy/client/cli/README.md
@@ -489,7 +489,7 @@ lite codex exec "summarize the repo"
 
 Each command resolves your LiteLLM key (logging in via SSO when none is stored and you are at a terminal; otherwise it expects `LITELLM_PROXY_API_KEY` or `--api-key`), checks the key against the proxy so bad credentials fail immediately instead of deep inside the agent, exports the environment variables the agent reads, then replaces itself with the agent process.
 
-The right variables are picked per agent. Claude Code gets `ANTHROPIC_BASE_URL` (the proxy root, so it appends `/v1/messages`) and `ANTHROPIC_AUTH_TOKEN`, with any stray `ANTHROPIC_API_KEY` cleared so the proxy token wins. Codex and OpenCode get `OPENAI_BASE_URL` (the proxy plus `/v1`) and `OPENAI_API_KEY`. Codex ignores `OPENAI_BASE_URL`, so it is additionally pointed at the proxy through a custom provider passed as `-c` config overrides (HTTP/SSE Responses transport, since the proxy does not speak the Responses WebSocket protocol).
+The right variables are picked per agent. Claude Code gets `ANTHROPIC_BASE_URL` (the proxy root, so it appends `/v1/messages`) and `ANTHROPIC_AUTH_TOKEN`, with any stray `ANTHROPIC_API_KEY` cleared so the proxy token wins, and `ENABLE_TOOL_SEARCH=true` (unless you already set it) so Claude Code keeps tool search on even though the base URL is a proxy rather than a first-party Anthropic host. Codex and OpenCode get `OPENAI_BASE_URL` (the proxy plus `/v1`) and `OPENAI_API_KEY`. Codex ignores `OPENAI_BASE_URL`, so it is additionally pointed at the proxy through a custom provider passed as `-c` config overrides (HTTP/SSE Responses transport, since the proxy does not speak the Responses WebSocket protocol).
 
 Options (these belong to the wrapper, so put them before the agent's own flags):
 
@@ -505,7 +505,7 @@ The credential is short-lived by design (default 24h, configurable via `LITELLM_
 
 ### Route Every Claude Code Session Through the Proxy
 
-`lite claude` wraps a single invocation, but `lite up` goes further: it patches `~/.claude/settings.json`, Claude Code's own config file, so that every Claude Code session started afterward -- from any terminal, launched normally with just `claude`, no wrapper needed -- routes through your LiteLLM proxy. It sets `env.ANTHROPIC_BASE_URL` to the proxy URL and `apiKeyHelper` to a `lite auth print-token` invocation, drops any stray static `ANTHROPIC_API_KEY` so the helper-issued token wins, and leaves every other setting in the file untouched. It backs up the original file before patching it.
+`lite claude` wraps a single invocation, but `lite up` goes further: it patches `~/.claude/settings.json`, Claude Code's own config file, so that every Claude Code session started afterward -- from any terminal, launched normally with just `claude`, no wrapper needed -- routes through your LiteLLM proxy. It sets `env.ANTHROPIC_BASE_URL` to the proxy URL, `env.ENABLE_TOOL_SEARCH` to `true` when that key is missing, and `apiKeyHelper` to a `lite auth print-token` invocation, drops any stray static `ANTHROPIC_API_KEY` so the helper-issued token wins, and leaves every other setting in the file untouched. It backs up the original file before patching it.
 
 Two things need to already be true: you've run `lite login` (or `lite login --pkce`, whose key the helper renews on its own), since the apiKeyHelper depends on that stored token, and the proxy is already reachable, since `lite up` does not start one for you.
 
@@ -529,7 +529,7 @@ Cursor is not supported: it has no equivalent file-based config to hot-patch thi
 lite --base-url https://your-proxy.example.com login --config-claude
 ```
 
-It writes the same two settings `lite up` does, `env.ANTHROPIC_BASE_URL` and `apiKeyHelper`, but persistently: there is no backup, nothing to restore, and no foreground process to keep alive. Every other key in `~/.claude/settings.json` is preserved, the file is created if it does not exist, and it is written atomically with owner-only permissions. Plain `lite login` is unchanged; nothing happens to your Claude Code config unless you pass the flag.
+It writes the same settings `lite up` does, `env.ANTHROPIC_BASE_URL`, `env.ENABLE_TOOL_SEARCH`, and `apiKeyHelper`, but persistently: there is no backup, nothing to restore, and no foreground process to keep alive. Every other key in `~/.claude/settings.json` is preserved, the file is created if it does not exist, and it is written atomically with owner-only permissions. Plain `lite login` is unchanged; nothing happens to your Claude Code config unless you pass the flag.
 
 Because the credential is reached through `apiKeyHelper` rather than copied into the file, a later `lite login` refreshes it with no further action: Claude Code re-runs the helper on every request and picks up whatever token the most recent login stored. Nothing secret is written to `settings.json`.
 
diff --git a/litellm/proxy/client/cli/commands/agents.py b/litellm/proxy/client/cli/commands/agents.py
index e05e85ae483..c591cbabee1 100644
--- a/litellm/proxy/client/cli/commands/agents.py
+++ b/litellm/proxy/client/cli/commands/agents.py
@@ -9,10 +9,13 @@ import click
 import requests
 
 from .auth import context_secret_vault, get_stored_api_key, login
+from .cmd_quoting import quote_for_cmd
 
 ANTHROPIC_BASE_URL_ENV: Final = "ANTHROPIC_BASE_URL"
 ANTHROPIC_AUTH_TOKEN_ENV: Final = "ANTHROPIC_AUTH_TOKEN"
 ANTHROPIC_API_KEY_ENV: Final = "ANTHROPIC_API_KEY"
+ENABLE_TOOL_SEARCH_ENV: Final = "ENABLE_TOOL_SEARCH"
+ENABLE_TOOL_SEARCH_VALUE: Final = "true"
 OPENAI_BASE_URL_ENV: Final = "OPENAI_BASE_URL"
 OPENAI_API_KEY_ENV: Final = "OPENAI_API_KEY"
 
@@ -61,7 +64,10 @@ def build_agent_env(
     Anthropic clients (Claude Code) append /v1/messages to ANTHROPIC_BASE_URL,
     so it stays the bare proxy root; OpenAI clients (Codex, OpenCode) expect the
     /v1 suffix on OPENAI_BASE_URL. ANTHROPIC_API_KEY is dropped so a stray
-    Anthropic key cannot win over the bearer token we set.
+    Anthropic key cannot win over the bearer token we set. ENABLE_TOOL_SEARCH
+    defaults to true because Claude Code turns tool search off when
+    ANTHROPIC_BASE_URL is not a first-party Anthropic host; a value already in
+    the environment is left alone.
     """
     env: Final = dict(base_env)
     root: Final = base_url.rstrip("/")
@@ -69,6 +75,8 @@ def build_agent_env(
         env[ANTHROPIC_BASE_URL_ENV] = root
         env[ANTHROPIC_AUTH_TOKEN_ENV] = api_key
         env.pop(ANTHROPIC_API_KEY_ENV, None)
+        if ENABLE_TOOL_SEARCH_ENV not in env:
+            env[ENABLE_TOOL_SEARCH_ENV] = ENABLE_TOOL_SEARCH_VALUE
     if PROFILE_OPENAI in profiles:
         env[OPENAI_BASE_URL_ENV] = root + "/v1"
         env[OPENAI_API_KEY_ENV] = api_key
@@ -144,31 +152,9 @@ def verify_proxy_key(
 
 
 _WINDOWS_SHIM_SUFFIXES: Final[frozenset[str]] = frozenset({".cmd", ".bat"})
-_CMD_PERCENT_GUARD: Final = "%%cd:~,%"
 _CMD_LINE_BREAKS: Final = ("\r", "\n")
 
 
-def _double_trailing_backslashes(segment: str) -> str:
-    bare: Final = segment.rstrip("\\")
-    return bare + "\\" * 2 * (len(segment) - len(bare))
-
-
-def _quote_for_cmd(token: str) -> str:
-    """Quote one token so both parsers that read it see the original text.
-
-    Follows the algorithm the Rust standard library settled on for batch files
-    after CVE-2024-24576. Two parsers see this token: cmd.exe, which ends a
-    quoted string on a lone `"` and so wants an embedded one doubled, and the
-    shim's own interpreter, which re-splits `%*` under C runtime rules where a
-    backslash escapes the quote that follows it, so every backslash run standing
-    before a quote is doubled. Quoting cannot stop cmd expanding `%VAR%`, so each
-    `%` is prefixed with `%%cd:~,`: the zero-length substring of the always
-    defined `cd` expands to nothing and leaves no `%` pair for cmd to match.
-    """
-    escaped: Final = '""'.join(_double_trailing_backslashes(part) for part in token.split('"'))
-    return '"' + escaped.replace("%", _CMD_PERCENT_GUARD) + '"'
-
-
 def _windows_command(path: str, args: Sequence[str]) -> str | tuple[str, ...]:
     """Build what CreateProcess runs, routing batch shims through cmd.exe.
 
@@ -195,7 +181,7 @@ def _windows_command(path: str, args: Sequence[str]) -> str | tuple[str, ...]:
             f"Cannot pass an argument containing a line break to `{os.path.basename(path)}` on "
             "Windows: cmd.exe ends the command line there, so the agent would silently lose it."
         )
-    inner: Final = " ".join(_quote_for_cmd(token) for token in (path, *rest))
+    inner: Final = " ".join(quote_for_cmd(token) for token in (path, *rest))
     return f'cmd.exe /d /e:on /v:off /s /c "{inner}"'
 
 
diff --git a/litellm/proxy/client/cli/commands/autoroute/settings.py b/litellm/proxy/client/cli/commands/autoroute/settings.py
index 9fcb11a585b..60729b5410d 100644
--- a/litellm/proxy/client/cli/commands/autoroute/settings.py
+++ b/litellm/proxy/client/cli/commands/autoroute/settings.py
@@ -9,6 +9,8 @@ API_KEY_HELPER_KEY: Final = "apiKeyHelper"
 ANTHROPIC_API_KEY_KEY: Final = "ANTHROPIC_API_KEY"
 ANTHROPIC_AUTH_TOKEN_KEY: Final = "ANTHROPIC_AUTH_TOKEN"
 ANTHROPIC_BASE_URL_KEY: Final = "ANTHROPIC_BASE_URL"
+ENABLE_TOOL_SEARCH_KEY: Final = "ENABLE_TOOL_SEARCH"
+ENABLE_TOOL_SEARCH_VALUE: Final = "true"
 # Force every one of Claude Code's own model tiers to request the auto-router by name.
 # Router's auto-router registry is keyed by the literal requested model string
 # (litellm/router.py:10711-10717) with no wildcard/pattern resolution, so a bare "*"
@@ -34,6 +36,7 @@ def merge_claude_settings_static_token(
     raw_env: Final = settings.get(ENV_KEY, {})
     base_env: Final = raw_env if isinstance(raw_env, dict) else {}
     env: Final[dict[str, JsonValue]] = {
+        ENABLE_TOOL_SEARCH_KEY: ENABLE_TOOL_SEARCH_VALUE,
         **base_env,
         ANTHROPIC_BASE_URL_KEY: base_url.rstrip("/"),
         ANTHROPIC_AUTH_TOKEN_KEY: auth_token,
diff --git a/litellm/proxy/client/cli/commands/claude_settings.py b/litellm/proxy/client/cli/commands/claude_settings.py
index e18e5b1b7ee..46af641636e 100644
--- a/litellm/proxy/client/cli/commands/claude_settings.py
+++ b/litellm/proxy/client/cli/commands/claude_settings.py
@@ -8,6 +8,7 @@ live here rather than in either command module.
 
 import shlex
 import shutil
+import sys
 from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
 from pathlib import Path
@@ -17,10 +18,14 @@ from pydantic import JsonValue, TypeAdapter, ValidationError
 
 from litellm.litellm_core_utils.private_json import write_private_json
 
+from .cmd_quoting import quote_for_cmd
+
 ENV_KEY: Final = "env"
 API_KEY_HELPER_KEY: Final = "apiKeyHelper"
 ANTHROPIC_BASE_URL_KEY: Final = "ANTHROPIC_BASE_URL"
 ANTHROPIC_API_KEY_KEY: Final = "ANTHROPIC_API_KEY"
+ENABLE_TOOL_SEARCH_KEY: Final = "ENABLE_TOOL_SEARCH"
+ENABLE_TOOL_SEARCH_VALUE: Final = "true"
 
 CLAUDE_SETTINGS_PATH: Final = Path.home() / ".claude" / "settings.json"
 BACKUP_PATH: Final = Path.home() / ".litellm" / "claude_settings_backup.json"
@@ -70,21 +75,27 @@ def merge_claude_settings(
 
     Only env.ANTHROPIC_BASE_URL and the top-level apiKeyHelper are overridden; a
     stray env.ANTHROPIC_API_KEY is dropped so it cannot outrank the helper-issued
-    token (same reasoning as build_agent_env in agents.py). Every other key is
-    preserved untouched.
+    token (same reasoning as build_agent_env in agents.py). ENABLE_TOOL_SEARCH
+    defaults to true because Claude Code turns tool search off when
+    ANTHROPIC_BASE_URL is not a first-party Anthropic host; an existing value is
+    left alone. Every other key is preserved untouched.
     """
     raw_env: Final = settings.get(ENV_KEY, {})
     base_env: Final = raw_env if isinstance(raw_env, dict) else {}
     env: Final = {
+        ENABLE_TOOL_SEARCH_KEY: ENABLE_TOOL_SEARCH_VALUE,
         **{key: value for key, value in base_env.items() if key != ANTHROPIC_API_KEY_KEY},
         ANTHROPIC_BASE_URL_KEY: base_url.rstrip("/"),
     }
     return {**settings, ENV_KEY: env, API_KEY_HELPER_KEY: api_key_helper}
 
 
-def resolve_api_key_helper(base_url: str) -> str:
+def resolve_api_key_helper(base_url: str, platform: str = sys.platform) -> str:
     """Build the shell command Claude Code should run for its apiKeyHelper.
 
+    Claude Code hands the string to the system shell, `sh` on POSIX and cmd.exe
+    on Windows, so every token is quoted for the shell that will read it.
+
     Resolves `lite` to an absolute path so the helper works regardless of the
     PATH visible to whatever subprocess Claude Code spawns it from. Passing
     --base-url explicitly (rather than relying on the bare invocation Claude
@@ -101,7 +112,8 @@ def resolve_api_key_helper(base_url: str) -> str:
         raise ClaudeSettingsError(
             "Could not find `lite` on your PATH. Claude Code's apiKeyHelper needs an absolute path to it."
         )
-    return f"{shlex.quote(lite_path)} --base-url {shlex.quote(base_url)} auth print-token"
+    quote: Final = quote_for_cmd if platform.startswith("win") else shlex.quote
+    return " ".join(quote(token) for token in (lite_path, "--base-url", base_url, "auth", "print-token"))
 
 
 def write_claude_settings(base_url: str, settings_path: Path, owners: Sequence[SettingsFileOwner]) -> None:
@@ -144,6 +156,8 @@ __all__ = (
     "AUTOROUTE_BACKUP_PATH",
     "BACKUP_PATH",
     "CLAUDE_SETTINGS_PATH",
+    "ENABLE_TOOL_SEARCH_KEY",
+    "ENABLE_TOOL_SEARCH_VALUE",
     "ENV_KEY",
     "SETTINGS_FILE_OWNERS",
     "ClaudeSettingsError",
diff --git a/litellm/proxy/client/cli/commands/cmd_quoting.py b/litellm/proxy/client/cli/commands/cmd_quoting.py
new file mode 100644
index 00000000000..efd6d584527
--- /dev/null
+++ b/litellm/proxy/client/cli/commands/cmd_quoting.py
@@ -0,0 +1,26 @@
+"""Quoting for command lines that cmd.exe reads before handing them to a program."""
+
+from typing import Final
+
+_CMD_PERCENT_GUARD: Final = "%%cd:~,%"
+
+
+def _double_trailing_backslashes(segment: str) -> str:
+    bare: Final = segment.rstrip("\\")
+    return bare + "\\" * 2 * (len(segment) - len(bare))
+
+
+def quote_for_cmd(token: str) -> str:
+    """Quote one token so both parsers that read it see the original text.
+
+    Follows the algorithm the Rust standard library settled on for batch files
+    after CVE-2024-24576. Two parsers see this token: cmd.exe, which ends a
+    quoted string on a lone `"` and so wants an embedded one doubled, and the
+    program's own C runtime argv split, where a backslash escapes the quote that
+    follows it, so every backslash run standing before a quote is doubled.
+    Quoting cannot stop cmd expanding `%VAR%`, so each `%` is prefixed with
+    `%%cd:~,`: the zero-length substring of the always defined `cd` expands to
+    nothing and leaves no `%` pair for cmd to match.
+    """
+    escaped: Final = '""'.join(_double_trailing_backslashes(part) for part in token.split('"'))
+    return '"' + escaped.replace("%", _CMD_PERCENT_GUARD) + '"'
diff --git a/litellm/proxy/client/cli/commands/teams.py b/litellm/proxy/client/cli/commands/teams.py
index 1f91d5559d8..1a941786f19 100644
--- a/litellm/proxy/client/cli/commands/teams.py
+++ b/litellm/proxy/client/cli/commands/teams.py
@@ -34,7 +34,7 @@ def teams():
     """Manage teams and team assignments"""
 
 
-def display_teams_table(teams: list[dict[str, Any]]) -> None:
+def display_teams_table(teams: Sequence[dict[str, Any]]) -> None:
     """Display teams in a formatted table"""
     console: Final = Console()
 
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index c6a6639409a..05ddef822f1 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -176,6 +176,9 @@ if TYPE_CHECKING:
     ProxyConfig = _ProxyConfig
 else:
     ProxyConfig = Any
+from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
+    AnthropicStreamModelRestamper,
+)
 from litellm.proxy.litellm_pre_call_utils import (
     add_litellm_data_to_request,
     refresh_proxy_server_request_body_snapshot,
@@ -502,7 +505,7 @@ def _as_success_dispatcher(logging_obj: _DispatchesSuccessHandlers) -> _Dispatch
     return logging_obj
 
 
-def _serialize_http_exception_detail(
+def serialize_http_exception_detail(
     detail: object,
 ) -> tuple[str, dict | None]:
     """
@@ -535,7 +538,7 @@ def _serialize_http_exception_detail(
 
 def proxy_exception_from_http_exception(exc: HTTPException, headers: dict[str, str]) -> ProxyException:
     raw_detail: Final = _getattr_object(exc, "detail", str(exc))
-    message, structured_fields = _serialize_http_exception_detail(raw_detail)
+    message, structured_fields = serialize_http_exception_detail(raw_detail)
     existing_fields: Final = getattr(exc, "provider_specific_fields", None) or {}
     merged_fields: Final = {**existing_fields, **structured_fields} if structured_fields else (existing_fields or None)
     return ProxyException(
@@ -818,7 +821,7 @@ async def _buffer_first_chunk_honoring_disconnect(
     raise _ClientDisconnectedBeforeFirstChunk()
 
 
-def _sse_error_payload(exc: BaseException) -> tuple[int, Mapping[str, object]]:
+def sse_error_payload(exc: BaseException) -> tuple[int, Mapping[str, object]]:
     """Build the ProxyException-shaped ``{"error": ...}`` body used in SSE error frames.
 
     Matches ``ProxyException.to_dict()`` so streaming and non-streaming error frames
@@ -827,7 +830,7 @@ def _sse_error_payload(exc: BaseException) -> tuple[int, Mapping[str, object]]:
     # Preserve status code from HTTPException (e.g. guardrail blocks)
     error_status: Final = getattr(exc, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR)
     raw_detail: Final = _getattr_object(exc, "detail", "Error processing stream start")
-    message, structured_fields = _serialize_http_exception_detail(raw_detail)
+    message, structured_fields = serialize_http_exception_detail(raw_detail)
 
     existing_fields: Final = getattr(exc, "provider_specific_fields", None) or {}
     merged_fields: Final = {**existing_fields, **structured_fields} if structured_fields else (existing_fields or None)
@@ -942,7 +945,7 @@ async def create_response(
         # Unexpected error consuming first chunk.
         verbose_proxy_logger.exception("Error consuming first chunk from generator: %s", e)
 
-        error_status, error_obj = _sse_error_payload(e)
+        error_status, error_obj = sse_error_payload(e)
 
         async def error_gen_message() -> AsyncGenerator[str, None]:
             for frame in _sse_error_frames(error_obj):
@@ -1119,7 +1122,7 @@ async def open_sse_before_first_byte(
                 # would never fire and the failure would go unaudited. The hook
                 # also gets to sanitize what reaches the client, by returning or
                 # raising a replacement, so its answer decides the frame.
-                _, error_obj = _sse_error_payload(await _sanitized_late_failure(exc, on_late_failure))
+                _, error_obj = sse_error_payload(await _sanitized_late_failure(exc, on_late_failure))
                 for frame in _sse_error_frames(error_obj):
                     yield frame.encode()
                 return
@@ -1495,6 +1498,35 @@ class ProxyBaseLLMRequestProcessing:
     def __init__(self, data: dict):
         self.data = data
 
+    @staticmethod
+    def _merge_passthrough_streaming_headers(
+        response_headers: httpx.Headers | dict | None,
+        custom_headers: dict,
+    ) -> dict:
+        """
+        Merge upstream passthrough headers with proxy/custom headers.
+
+        Proxy/custom headers win on key collisions.
+        """
+        excluded_headers: Final = {  # mutable-ok: set of header names to exclude from forwarding
+            "transfer-encoding",
+            "content-encoding",
+            "set-cookie",
+            "connection",
+            "keep-alive",
+            "proxy-authenticate",
+            "proxy-authorization",
+            "te",
+            "trailer",
+            "upgrade",
+        }
+
+        merged_headers: Final = {  # mutable-ok: dict comprehension for merged headers forwarded to httpx
+            key: value for key, value in dict(response_headers or {}).items() if key.lower() not in excluded_headers
+        }
+        merged_headers.update(custom_headers)
+        return merged_headers
+
     @staticmethod
     def get_custom_headers(
         *,
@@ -2380,54 +2412,25 @@ class ProxyBaseLLMRequestProcessing:
                 if requested_model_from_client:
                     self.data["_litellm_client_requested_model"] = requested_model_from_client
 
-                # Streaming: attach a closure that fires after all guardrail
-                # end-of-stream blocks complete.  CSW.__anext__ stores the
-                # assembled response on logging_obj; the outer consumer
-                # (ProxyLogging._fire_deferred_stream_logging) fires the
-                # closure after the full streaming pipeline finishes.
-                # The closure runs non-apply_guardrail hooks on the
-                # assembled response, then fires success logging.
-                # Only for CustomStreamWrapper — raw async generators from
-                # passthrough routes bypass CSW and would orphan the closure.
-                from litellm.litellm_core_utils.streaming_handler import (
-                    CustomStreamWrapper,
-                )
-
-                if _post_call_guardrails_active and isinstance(response, CustomStreamWrapper):
-                    # Intentionally a live reference (not a copy) — mirrors
-                    # ProxyLogging.post_call_success_hook which also mutates
-                    # data["guardrail_to_apply"] during iteration.
-                    _captured_data: Final = self.data
-                    _captured_user_api_key_dict: Final = user_api_key_dict
-                    _captured_logging_obj: Final = logging_obj
-
-                    async def _on_deferred_stream_complete(assembled_response: object, cache_hit: object) -> None:
-                        await ProxyBaseLLMRequestProcessing._run_deferred_stream_guardrails(
-                            captured_data=_captured_data,
-                            captured_user_api_key_dict=_captured_user_api_key_dict,
-                            captured_logging_obj=_captured_logging_obj,
-                            assembled_response=assembled_response,
-                            cache_hit=cache_hit,
-                        )
-
-                    logging_obj._on_deferred_stream_complete = _on_deferred_stream_complete
-                elif (
-                    _post_call_guardrails_active
-                    and route_type == "anthropic_messages"
-                    and self._is_streaming_response(response)
-                ):
-                    from litellm.litellm_core_utils.logging_worker import (
-                        GLOBAL_LOGGING_WORKER,
+                if _post_call_guardrails_active:
+                    self._arm_deferred_stream_dispatch(
+                        response=response,
+                        route_type=route_type,
+                        user_api_key_dict=user_api_key_dict,
+                        logging_obj=logging_obj,
                     )
 
-                    async def _on_deferred_native_stream_complete(
-                        logging_coroutine: Coroutine[object, object, object],
-                    ) -> None:
-                        GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(async_coroutine=logging_coroutine)
-
-                    logging_obj._on_deferred_stream_complete = _on_deferred_native_stream_complete
-
                 if route_type == "allm_passthrough_route":
+                    upstream_response_headers: Final = getattr(response, "headers", None)
+                    streaming_headers: Final = (
+                        ProxyBaseLLMRequestProcessing._merge_passthrough_streaming_headers(
+                            response_headers=upstream_response_headers,
+                            custom_headers=custom_headers,
+                        )
+                        if upstream_response_headers is not None
+                        else custom_headers
+                    )
+
                     # Check if response is an async generator
                     if self._is_streaming_response(response):
                         if asyncio.iscoroutine(response):
@@ -2457,11 +2460,11 @@ class ProxyBaseLLMRequestProcessing:
 
                         # For passthrough routes, stream directly without error parsing
                         # since we're dealing with raw binary data (e.g., AWS event streams)
-                        return StreamingResponse(
-                            content=generator,
-                            status_code=status.HTTP_200_OK,
+                        return _UpstreamClosingStreamingResponse(
+                            content=generator,  # pyright: ignore[reportArgumentType]  # generator-configured StreamingResponse
+                            status_code=getattr(response, "status_code", status.HTTP_200_OK),
                             media_type=self._passthrough_event_stream_media_type(),
-                            headers=custom_headers,
+                            headers=streaming_headers,
                         )
                     else:
                         _early = await self._handle_non_streaming_allm_passthrough_route(
@@ -2476,7 +2479,7 @@ class ProxyBaseLLMRequestProcessing:
                         return StreamingResponse(
                             content=response.aiter_bytes(),
                             status_code=response.status_code,
-                            headers=custom_headers,
+                            headers=streaming_headers,
                         )
                 elif route_type == "anthropic_messages":
                     # Check if response is actually a streaming response (async generator)
@@ -2490,6 +2493,9 @@ class ProxyBaseLLMRequestProcessing:
                             request_data=self.data,
                             proxy_logging_obj=proxy_logging_obj,
                             request=request,
+                            restamp_model=(
+                                None if _should_return_raw_model_name(self.data) else requested_model_from_client
+                            ),
                         )
                         return await create_response(
                             generator=wrap_sse_stream_with_keepalive_pings(
@@ -3096,6 +3102,94 @@ class ProxyBaseLLMRequestProcessing:
         except Exception as e:
             verbose_proxy_logger.exception("Error firing deferred logging: %s", e)
 
+    def _arm_deferred_stream_dispatch(
+        self,
+        response: object,
+        route_type: str,
+        user_api_key_dict: "UserAPIKeyAuth",
+        logging_obj: LiteLLMLoggingObj,
+    ) -> None:
+        """
+        Streaming with post-call guardrails active: attach a closure that
+        ProxyLogging._fire_deferred_stream_logging fires after all guardrail
+        end-of-stream blocks complete, so the spend log sees
+        guardrail_information.
+
+        Three closure shapes, matching who owns logging for the stream:
+        - CustomStreamWrapper (chat completions) stores
+          (assembled_response, cache_hit); the closure also runs
+          non-apply_guardrail post-call hooks via
+          _run_deferred_stream_guardrails.
+        - Bridged /v1/responses (LiteLLMCompletionStreamingIterator) shares
+          its inner CustomStreamWrapper's logging_obj, so it stores the same
+          (assembled_response, cache_hit) shape; the closure only dispatches
+          success logging, matching the route's pre-existing hook surface.
+        - Native anthropic_messages/aresponses iterators store a single
+          ready-made logging coroutine to enqueue.
+
+        Raw async generators from passthrough routes bypass all three and
+        would orphan the closure, so they are not armed here.
+
+        The router wraps iterators that cannot carry _hidden_params in
+        HiddenParamsAsyncIteratorWrapper, so class sniffing runs on the
+        unwrapped inner iterator.
+        """
+        from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
+        from litellm.router_utils.add_retry_fallback_headers import HiddenParamsAsyncIteratorWrapper
+
+        unwrapped: Final = response._inner if isinstance(response, HiddenParamsAsyncIteratorWrapper) else response
+
+        if isinstance(unwrapped, CustomStreamWrapper):
+            # Intentionally a live reference (not a copy) — mirrors
+            # ProxyLogging.post_call_success_hook which also mutates
+            # data["guardrail_to_apply"] during iteration.
+            _captured_data: Final = self.data
+            _captured_user_api_key_dict: Final = user_api_key_dict
+            _captured_logging_obj: Final = logging_obj
+
+            async def _on_deferred_stream_complete(assembled_response: object, cache_hit: object) -> None:
+                await ProxyBaseLLMRequestProcessing._run_deferred_stream_guardrails(
+                    captured_data=_captured_data,
+                    captured_user_api_key_dict=_captured_user_api_key_dict,
+                    captured_logging_obj=_captured_logging_obj,
+                    assembled_response=assembled_response,
+                    cache_hit=cache_hit,
+                )
+
+            logging_obj._on_deferred_stream_complete = _on_deferred_stream_complete
+            return
+
+        if route_type not in ("anthropic_messages", "aresponses") or not self._is_streaming_response(response):
+            return
+
+        from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+            LiteLLMCompletionStreamingIterator,
+        )
+
+        if isinstance(unwrapped, LiteLLMCompletionStreamingIterator):
+            _captured_bridge_logging_obj: Final = logging_obj
+
+            async def _on_deferred_bridged_stream_complete(assembled_response: object, cache_hit: object) -> None:
+                await _as_success_dispatcher(_captured_bridge_logging_obj).dispatch_success_handlers(
+                    assembled_response,
+                    cache_hit=cache_hit,
+                    start_time=None,
+                    end_time=None,
+                    prefer_async_handlers=True,
+                )
+
+            logging_obj._on_deferred_stream_complete = _on_deferred_bridged_stream_complete
+            return
+
+        from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
+
+        async def _on_deferred_native_stream_complete(
+            logging_coroutine: Coroutine[object, object, object],
+        ) -> None:
+            GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(async_coroutine=logging_coroutine)
+
+        logging_obj._on_deferred_stream_complete = _on_deferred_native_stream_complete
+
     @staticmethod
     async def _run_deferred_stream_guardrails(
         captured_data: dict,
@@ -3354,6 +3448,16 @@ class ProxyBaseLLMRequestProcessing:
         else:
             return chunk
 
+    @staticmethod
+    def _sse_chunk_serializer(restamper: AnthropicStreamModelRestamper | None) -> StreamChunkSerializer:
+        if restamper is None:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk
+
+        def serialize(chunk: object) -> str:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk(restamper.process(chunk))
+
+        return serialize
+
     @staticmethod
     async def _finalize_streaming_generator_cleanup(
         request: Request | None,
@@ -3414,11 +3518,16 @@ class ProxyBaseLLMRequestProcessing:
         serialize_chunk: StreamChunkSerializer,
         serialize_error: StreamErrorSerializer,
         request: Request | None = None,
+        flush_tail: Callable[[], bytes] | None = None,
     ) -> AsyncGenerator[str, None]:
         """
         Shared streaming data generator: runs proxy iterator hook, per-chunk hook,
         cost injection, then yields chunks via serialize_chunk; on exception runs
         failure hook and yields via serialize_error. Use for SSE or NDJSON.
+
+        ``flush_tail`` runs once after the upstream iterator completes cleanly and
+        its non-empty result is yielded, so a serializer that buffers bytes across
+        chunks can emit anything still held at end of stream.
         """
         verbose_proxy_logger.debug("inside generator")
         # Resolve per-stream (not per-chunk) whether the heavy per-chunk path
@@ -3481,6 +3590,9 @@ class ProxyBaseLLMRequestProcessing:
                 # so it must not suppress that refund.
                 delivered_chunk = delivered_chunk or chunk != STREAM_SSE_KEEPALIVE_PING_BYTES
                 yield serialize_chunk(chunk)
+            held_tail: Final = flush_tail() if flush_tail is not None else b""
+            if held_tail:
+                yield serialize_chunk(held_tail)
             stream_completed = True
         except (asyncio.CancelledError, GeneratorExit):
             # Client disconnected mid-stream. CancelledError / GeneratorExit
@@ -3491,8 +3603,7 @@ class ProxyBaseLLMRequestProcessing:
             # billing and release exactly once. This is the outermost generator
             # Starlette closes on disconnect, so the nested iterator hook (which
             # only sees GeneratorExit on GC) cannot own the refund.
-            if not stream_completed:
-                client_disconnected = True
+            client_disconnected = not stream_completed
             if not delivered_chunk and not _withheld_provider_output(response):
                 from litellm.proxy.spend_tracking.budget_reservation import (
                     release_budget_reservation_on_cancel,
@@ -3546,6 +3657,7 @@ class ProxyBaseLLMRequestProcessing:
         request_data: dict,
         proxy_logging_obj: ProxyLogging,
         request: Request | None = None,
+        restamp_model: str | None = None,
     ) -> AsyncGenerator[str, None]:
         """
         Anthropic /messages and Google /generateContent streaming data generator require SSE events.
@@ -3554,17 +3666,23 @@ class ProxyBaseLLMRequestProcessing:
         SSE serializers directly (rather than re-wrapping it in another
         ``async for: yield`` trampoline), so a streamed chunk traverses one
         fewer async-generator layer / coroutine resume on the hot path.
+
+        ``restamp_model`` publishes that name on the Anthropic ``message_start``
+        event in place of the provider's model, matching what the non-streaming
+        response reports.
         """
+        restamper: Final = AnthropicStreamModelRestamper(restamp_model) if restamp_model else None
         return ProxyBaseLLMRequestProcessing.async_streaming_data_generator(
             response=response,
             user_api_key_dict=user_api_key_dict,
             request_data=request_data,
             proxy_logging_obj=proxy_logging_obj,
-            serialize_chunk=ProxyBaseLLMRequestProcessing.return_sse_chunk,
+            serialize_chunk=ProxyBaseLLMRequestProcessing._sse_chunk_serializer(restamper),
             serialize_error=lambda proxy_exc: (
                 f"{STREAM_SSE_DATA_PREFIX}{json.dumps({'error': proxy_exc.to_dict()})}\n\n"
             ),
             request=request,
+            flush_tail=None if restamper is None else restamper.flush,
         )
 
     @overload
diff --git a/litellm/proxy/common_utils/callback_utils.py b/litellm/proxy/common_utils/callback_utils.py
index 9379a8577a3..39e74d2c8bd 100644
--- a/litellm/proxy/common_utils/callback_utils.py
+++ b/litellm/proxy/common_utils/callback_utils.py
@@ -1,6 +1,6 @@
 import copy
 import os
-from collections.abc import Callable, Iterable
+from collections.abc import Callable, Iterable, Mapping
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, Any, Final, Literal, NoReturn, Optional, TypeAlias
 
@@ -525,16 +525,16 @@ LITELLM_PROXY_INTERNAL_METADATA_KEYS: Final = frozenset(
 
 
 def sanitize_openai_provider_metadata(
-    metadata: dict[str, Any] | None,
-) -> dict[str, str] | None:
+    metadata: Mapping[str, object] | None,
+) -> Mapping[str, object] | None:
     """
     Keep only provider-safe OpenAI metadata entries (string keys -> string values).
 
     Strips LiteLLM proxy-internal tracking fields that must not be forwarded to
     OpenAI batch/file APIs.
     """
-    if not metadata:
-        return metadata
+    if metadata is None:
+        return None
     sanitized: Final[dict[str, str]] = {}
     for key, value in metadata.items():
         if key in LITELLM_PROXY_INTERNAL_METADATA_KEYS:
@@ -547,7 +547,7 @@ def sanitize_openai_provider_metadata(
                 key,
                 type(value).__name__,
             )
-    return sanitized or None
+    return None if metadata and not sanitized else sanitized
 
 
 def add_guardrail_to_applied_guardrails_header(request_data: dict, guardrail_name: str | None):
@@ -644,13 +644,13 @@ def process_callback(_callback: str, callback_type: str, environment_variables:
     return {"name": _callback, "variables": env_vars_dict, "type": callback_type}
 
 
-def normalize_callback_names(callbacks: Iterable[Any]) -> list[Any]:
+def normalize_callback_names(callbacks: Iterable[object] | None) -> list[object]:
     if callbacks is None:
         return []
     return [c.lower() if isinstance(c, str) else c for c in callbacks]
 
 
-def strip_callback_config(metadata: dict[str, Any] | None) -> dict[str, Any] | None:
+def strip_callback_config(metadata: dict[str, object] | None) -> dict[str, object] | None:
     """Return key/team metadata without the slots that carry callback credentials."""
     if not isinstance(metadata, dict):
         return metadata
@@ -674,7 +674,7 @@ def decrypt_callback_vars(metadata: Any) -> Any:
     return _transform_callback_vars(metadata, _decrypt_or_passthrough)
 
 
-def _transform_callback_vars(metadata: Any, transform: Callable[[str, Any], Any]) -> Any:
+def _transform_callback_vars(metadata: object, transform: Callable[[str, Any], Any]) -> object:
     if not isinstance(metadata, dict):
         return metadata
     out: Final = copy.deepcopy(metadata)
@@ -704,7 +704,7 @@ def is_sensitive_callback_key(
     return _CALLBACK_VAR_MASKER.is_sensitive_key(key)
 
 
-def _encrypt_if_plaintext(key: str, value: Any) -> Any:
+def _encrypt_if_plaintext(key: str, value: object) -> object:
     if not isinstance(value, str) or not value:
         return value
     if not is_sensitive_callback_key(key):
@@ -725,7 +725,7 @@ def _encrypt_if_plaintext(key: str, value: Any) -> Any:
         return value
 
 
-def _decrypt_or_passthrough(key: str, value: Any) -> Any:
+def _decrypt_or_passthrough(key: str, value: object) -> object:
     if not isinstance(value, str) or not value:
         return value
     if not value.startswith(_CALLBACK_VAR_ENCRYPTED_PREFIX):
diff --git a/litellm/proxy/common_utils/custom_openapi_spec.py b/litellm/proxy/common_utils/custom_openapi_spec.py
index bc7b80801fe..2a20e7b07ce 100644
--- a/litellm/proxy/common_utils/custom_openapi_spec.py
+++ b/litellm/proxy/common_utils/custom_openapi_spec.py
@@ -1,8 +1,12 @@
 from collections.abc import Mapping, Sequence
-from typing import Any, Final
+from typing import Final, TypeAlias, Union
 
 from litellm._logging import verbose_proxy_logger
 
+JsonValue: TypeAlias = Union["JsonObject", "JsonArray", str, int, float, bool, None]
+JsonObject: TypeAlias = dict[str, JsonValue]
+JsonArray: TypeAlias = list[JsonValue]
+
 
 class CustomOpenAPISpec:
     """
@@ -27,7 +31,20 @@ class CustomOpenAPISpec:
     RESPONSES_API_PATHS = ["/v1/responses", "/responses"]
 
     @staticmethod
-    def get_pydantic_schema(model_class) -> Mapping[str, object] | None:
+    def _as_object(node: JsonValue) -> JsonObject:
+        return node if isinstance(node, dict) else {}
+
+    @staticmethod
+    def _as_array(node: JsonValue) -> JsonArray:
+        return node if isinstance(node, list) else []
+
+    @staticmethod
+    def _components_schemas(openapi_schema: JsonObject) -> JsonObject:
+        components: Final = CustomOpenAPISpec._as_object(openapi_schema.setdefault("components", {}))
+        return CustomOpenAPISpec._as_object(components.setdefault("schemas", {}))
+
+    @staticmethod
+    def get_pydantic_schema(model_class) -> JsonObject | None:
         """
         Get JSON schema from a Pydantic model, handling both v1 and v2 APIs.
 
@@ -54,9 +71,7 @@ class CustomOpenAPISpec:
             return None
 
     @staticmethod
-    def add_schema_to_components(
-        openapi_schema: dict[str, Any], schema_name: str, schema_def: Mapping[str, object]
-    ) -> None:
+    def add_schema_to_components(openapi_schema: JsonObject, schema_name: str, schema_def: JsonObject) -> None:
         """
         Add a schema definition to the OpenAPI components/schemas section.
 
@@ -66,16 +81,25 @@ class CustomOpenAPISpec:
             schema_def: The schema definition
         """
         # Ensure components/schemas structure exists
-        if "components" not in openapi_schema:
-            openapi_schema["components"] = {}
-        if "schemas" not in openapi_schema["components"]:
-            openapi_schema["components"]["schemas"] = {}
+        _ = CustomOpenAPISpec._components_schemas(openapi_schema)
 
         # Add the schema
         CustomOpenAPISpec._move_defs_to_components(openapi_schema, {schema_name: schema_def})
 
     @staticmethod
-    def add_request_body_to_paths(openapi_schema: dict[str, Any], paths: Sequence[str], schema_ref: str) -> None:
+    def _expanded_request_field(field_name: str, field_def: JsonValue) -> JsonValue:
+        expanded: Final = CustomOpenAPISpec._rewrite_defs_refs(
+            CustomOpenAPISpec._expand_field_definition(CustomOpenAPISpec._as_object(field_def))
+        )
+        if field_name != "messages":
+            return expanded
+        return {
+            **CustomOpenAPISpec._as_object(expanded),
+            "example": [{"role": "user", "content": "Hello, how are you?"}],
+        }
+
+    @staticmethod
+    def add_request_body_to_paths(openapi_schema: JsonObject, paths: Sequence[str], schema_ref: str) -> None:
         """
         Add request body with expanded form fields for better Swagger UI display.
         This keeps the request body but expands it to show individual fields in the UI.
@@ -86,54 +110,58 @@ class CustomOpenAPISpec:
             schema_ref: Reference to the schema component (e.g., "#/components/schemas/ModelName")
         """
         for path in paths:
-            if path in openapi_schema.get("paths", {}) and "post" in openapi_schema["paths"][path]:
-                # Get the actual schema to extract ALL field definitions
-                schema_name = schema_ref.split("/")[-1]  # Extract "ProxyChatCompletionRequest" from the ref
-                actual_schema = openapi_schema.get("components", {}).get("schemas", {}).get(schema_name, {})
-                schema_properties = actual_schema.get("properties", {})
-                required_fields = actual_schema.get("required", [])
+            path_item = CustomOpenAPISpec._as_object(
+                CustomOpenAPISpec._as_object(openapi_schema.get("paths")).get(path)
+            )
+            if "post" not in path_item:
+                continue
 
-                # Extract $defs and add them to components/schemas
-                # This fixes Pydantic v2 $defs not being resolvable in Swagger/OpenAPI
-                if "$defs" in actual_schema:
-                    CustomOpenAPISpec._move_defs_to_components(openapi_schema, actual_schema["$defs"])
+            post_operation = CustomOpenAPISpec._as_object(path_item["post"])
 
-                # Create an expanded inline schema instead of just a $ref
-                # This makes Swagger UI show all individual fields in the request body editor
-                expanded_schema = {
-                    "type": "object",
-                    "required": required_fields,
-                    "properties": {},
-                }
+            # Get the actual schema to extract ALL field definitions
+            schema_name = schema_ref.split("/")[-1]  # Extract "ProxyChatCompletionRequest" from the ref
+            components = CustomOpenAPISpec._as_object(openapi_schema.get("components"))
+            actual_schema = CustomOpenAPISpec._as_object(
+                CustomOpenAPISpec._as_object(components.get("schemas")).get(schema_name)
+            )
+            schema_properties = CustomOpenAPISpec._as_object(actual_schema.get("properties"))
+            required_fields = actual_schema.get("required", [])
 
-                # Add all properties with their full definitions
-                for field_name, field_def in schema_properties.items():
-                    expanded_field = CustomOpenAPISpec._expand_field_definition(field_def)
+            # Extract $defs and add them to components/schemas
+            # This fixes Pydantic v2 $defs not being resolvable in Swagger/OpenAPI
+            if "$defs" in actual_schema:
+                CustomOpenAPISpec._move_defs_to_components(
+                    openapi_schema, CustomOpenAPISpec._as_object(actual_schema["$defs"])
+                )
 
-                    # Rewrite $defs references to use components/schemas instead
-                    expanded_field = CustomOpenAPISpec._rewrite_defs_refs(expanded_field)
+            # Create an expanded inline schema instead of just a $ref
+            # This makes Swagger UI show all individual fields in the request body editor
+            expanded_schema: JsonObject = {
+                "type": "object",
+                "required": required_fields,
+                "properties": {
+                    field_name: CustomOpenAPISpec._expanded_request_field(field_name, field_def)
+                    for field_name, field_def in schema_properties.items()
+                },
+            }
 
-                    # Add a simple example for the messages field
-                    if field_name == "messages":
-                        expanded_field["example"] = [{"role": "user", "content": "Hello, how are you?"}]
+            # Set the request body with the expanded schema
+            post_operation["requestBody"] = {
+                "required": True,
+                "content": {"application/json": {"schema": expanded_schema}},
+            }
 
-                    expanded_schema["properties"][field_name] = expanded_field
-
-                # Set the request body with the expanded schema
-                openapi_schema["paths"][path]["post"]["requestBody"] = {
-                    "required": True,
-                    "content": {"application/json": {"schema": expanded_schema}},
-                }
-
-                # Keep any existing parameters (like path parameters) but remove conflicting query params
-                if "parameters" in openapi_schema["paths"][path]["post"]:
-                    existing_params = openapi_schema["paths"][path]["post"]["parameters"]
-                    # Only keep path parameters, remove query params that conflict with request body
-                    filtered_params = [param for param in existing_params if param.get("in") == "path"]
-                    openapi_schema["paths"][path]["post"]["parameters"] = filtered_params
+            # Keep any existing parameters (like path parameters) but remove conflicting query params
+            if "parameters" in post_operation:
+                # Only keep path parameters, remove query params that conflict with request body
+                post_operation["parameters"] = [
+                    param
+                    for param in CustomOpenAPISpec._as_array(post_operation["parameters"])
+                    if CustomOpenAPISpec._as_object(param).get("in") == "path"
+                ]
 
     @staticmethod
-    def _move_defs_to_components(openapi_schema: dict[str, Any], defs: Mapping[str, Mapping[str, Any]]) -> None:
+    def _move_defs_to_components(openapi_schema: JsonObject, defs: Mapping[str, JsonValue]) -> None:
         """
         Move $defs from Pydantic v2 schema to OpenAPI components/schemas.
         This makes the definitions resolvable in Swagger/OpenAPI viewers.
@@ -146,23 +174,31 @@ class CustomOpenAPISpec:
             return
 
         # Ensure components/schemas exists
-        if "components" not in openapi_schema:
-            openapi_schema["components"] = {}
-        if "schemas" not in openapi_schema["components"]:
-            openapi_schema["components"]["schemas"] = {}
+        schemas: Final = CustomOpenAPISpec._components_schemas(openapi_schema)
 
         # Add each definition to components/schemas
         for def_name, def_schema in defs.items():
             # Recursively rewrite any nested $defs references within this definition
-            rewritten_def = CustomOpenAPISpec._rewrite_defs_refs(def_schema)
-            openapi_schema["components"]["schemas"][def_name] = rewritten_def
+            schemas[def_name] = CustomOpenAPISpec._rewrite_defs_refs(def_schema)
 
             # If this definition also has $defs, process them recursively
-            if "$defs" in def_schema:
-                CustomOpenAPISpec._move_defs_to_components(openapi_schema, def_schema["$defs"])
+            def_object = CustomOpenAPISpec._as_object(def_schema)
+            if "$defs" in def_object:
+                CustomOpenAPISpec._move_defs_to_components(
+                    openapi_schema, CustomOpenAPISpec._as_object(def_object["$defs"])
+                )
 
     @staticmethod
-    def _rewrite_defs_refs(schema: Any) -> Any:
+    def _rewritten_defs_entry(key: str, value: JsonValue) -> JsonValue:
+        if key == "$ref" and isinstance(value, str) and value.startswith("#/$defs/"):
+            # Rewrite the reference to use components/schemas
+            def_name: Final = value.replace("#/$defs/", "")
+            return f"#/components/schemas/{def_name}"
+        # Recursively process nested structures
+        return CustomOpenAPISpec._rewrite_defs_refs(value)
+
+    @staticmethod
+    def _rewrite_defs_refs(schema: JsonValue) -> JsonValue:
         """
         Recursively rewrite $ref values from #/$defs/... to #/components/schemas/...
         This converts Pydantic v2 references to OpenAPI-compatible references.
@@ -174,26 +210,17 @@ class CustomOpenAPISpec:
             Schema with rewritten references
         """
         if isinstance(schema, dict):
-            result: Final = {}
-            for key, value in schema.items():
-                if key == "$ref" and isinstance(value, str) and value.startswith("#/$defs/"):
-                    # Rewrite the reference to use components/schemas
-                    def_name = value.replace("#/$defs/", "")
-                    result[key] = f"#/components/schemas/{def_name}"
-                elif key == "$defs":
-                    # Remove $defs from the schema since they're moved to components
-                    continue
-                else:
-                    # Recursively process nested structures
-                    result[key] = CustomOpenAPISpec._rewrite_defs_refs(value)
-            return result
-        elif isinstance(schema, list):
+            return {
+                key: CustomOpenAPISpec._rewritten_defs_entry(key, value)
+                for key, value in schema.items()
+                if key != "$defs"
+            }
+        if isinstance(schema, list):
             return [CustomOpenAPISpec._rewrite_defs_refs(item) for item in schema]
-        else:
-            return schema
+        return schema
 
     @staticmethod
-    def _extract_field_schema(field_def: dict[str, Any]) -> dict[str, Any]:
+    def _extract_field_schema(field_def: JsonObject) -> JsonValue:
         """
         Extract a simple schema from a Pydantic field definition for parameter display.
 
@@ -209,10 +236,10 @@ class CustomOpenAPISpec:
 
         # Handle anyOf (Optional fields in Pydantic v2)
         if "anyOf" in field_def:
-            any_of: Final = field_def["anyOf"]
+            any_of: Final = CustomOpenAPISpec._as_array(field_def["anyOf"])
             # Find the non-null type
             for option in any_of:
-                if option.get("type") != "null":
+                if CustomOpenAPISpec._as_object(option).get("type") != "null":
                     return option
             # Fallback to string if all else fails
             return {"type": "string"}
@@ -221,7 +248,7 @@ class CustomOpenAPISpec:
         return {"type": "string"}
 
     @staticmethod
-    def _expand_field_definition(field_def: dict[str, object]) -> dict[str, object]:
+    def _expand_field_definition(field_def: JsonObject) -> JsonObject:
         """
         Expand a Pydantic field definition for inline use in OpenAPI schema.
         This creates a full field definition that Swagger UI can render as individual form fields.
@@ -237,12 +264,12 @@ class CustomOpenAPISpec:
 
     @staticmethod
     def add_request_schema(
-        openapi_schema: dict[str, object],
+        openapi_schema: JsonObject,
         model_class: type,
         schema_name: str,
         paths: Sequence[str],
         operation_name: str,
-    ) -> dict[str, object]:
+    ) -> JsonObject:
         """
         Generic method to add a request schema to OpenAPI specification.
 
@@ -282,8 +309,8 @@ class CustomOpenAPISpec:
 
     @staticmethod
     def add_chat_completion_request_schema(
-        openapi_schema: dict[str, object],
-    ) -> dict[str, object]:
+        openapi_schema: JsonObject,
+    ) -> JsonObject:
         """
         Add ProxyChatCompletionRequest schema to chat completion endpoints for documentation.
         This shows the request body in Swagger without runtime validation.
@@ -309,7 +336,7 @@ class CustomOpenAPISpec:
             return openapi_schema
 
     @staticmethod
-    def add_embedding_request_schema(openapi_schema: dict[str, object]) -> dict[str, object]:
+    def add_embedding_request_schema(openapi_schema: JsonObject) -> JsonObject:
         """
         Add EmbeddingRequest schema to embedding endpoints for documentation.
         This shows the request body in Swagger without runtime validation.
@@ -336,8 +363,8 @@ class CustomOpenAPISpec:
 
     @staticmethod
     def add_responses_api_request_schema(
-        openapi_schema: dict[str, object],
-    ) -> dict[str, object]:
+        openapi_schema: JsonObject,
+    ) -> JsonObject:
         """
         Add ResponsesAPIRequestParams schema to responses API endpoints for documentation.
         This shows the request body in Swagger without runtime validation.
@@ -364,8 +391,8 @@ class CustomOpenAPISpec:
 
     @staticmethod
     def add_llm_api_request_schema_body(
-        openapi_schema: dict[str, object],
-    ) -> dict[str, object]:
+        openapi_schema: JsonObject,
+    ) -> JsonObject:
         """
         Add LLM API request schema bodies to OpenAPI specification for documentation.
 
@@ -376,12 +403,10 @@ class CustomOpenAPISpec:
             OpenAPI schema with added request body schemas
         """
         # Add chat completion request schema
-        openapi_schema = CustomOpenAPISpec.add_chat_completion_request_schema(openapi_schema)
+        with_chat_completions: Final = CustomOpenAPISpec.add_chat_completion_request_schema(openapi_schema)
 
         # Add embedding request schema
-        openapi_schema = CustomOpenAPISpec.add_embedding_request_schema(openapi_schema)
+        with_embeddings: Final = CustomOpenAPISpec.add_embedding_request_schema(with_chat_completions)
 
         # Add responses API request schema
-        openapi_schema = CustomOpenAPISpec.add_responses_api_request_schema(openapi_schema)
-
-        return openapi_schema
+        return CustomOpenAPISpec.add_responses_api_request_schema(with_embeddings)
diff --git a/litellm/proxy/common_utils/debug_utils.py b/litellm/proxy/common_utils/debug_utils.py
index 3a1d18b48cc..554a6ae8d1a 100644
--- a/litellm/proxy/common_utils/debug_utils.py
+++ b/litellm/proxy/common_utils/debug_utils.py
@@ -6,9 +6,11 @@ import os
 import sys
 import tracemalloc
 from collections import Counter
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, NamedTuple, Protocol, TypedDict
 
 from fastapi import APIRouter, Depends, HTTPException, Query
+from typing_extensions import ReadOnly
 
 from litellm import get_secret_str
 from litellm._logging import verbose_proxy_logger
@@ -194,6 +196,42 @@ async def memory_usage_in_mem_cache_items(
     }
 
 
+class _ProcessMemoryInfo(Protocol):
+    """The resident and virtual sizes psutil reports for a process."""
+
+    @property
+    def rss(self) -> int: ...
+
+    @property
+    def vms(self) -> int: ...
+
+
+class _ProcessHandle(Protocol):
+    """The psutil process handle members this module reads."""
+
+    def memory_info(self) -> _ProcessMemoryInfo: ...
+
+    def memory_percent(self) -> float: ...
+
+
+class _ProcessMemoryUsage(NamedTuple):
+    """Memory usage of a single worker process."""
+
+    resident_megabytes: float
+    virtual_megabytes: float
+    percent: float
+
+
+def _process_memory_usage(process: _ProcessHandle) -> _ProcessMemoryUsage:
+    """Read resident/virtual megabytes and system memory share for ``process``."""
+    memory_info: Final = process.memory_info()
+    return _ProcessMemoryUsage(
+        resident_megabytes=memory_info.rss / (1024 * 1024),
+        virtual_megabytes=memory_info.vms / (1024 * 1024),
+        percent=process.memory_percent(),
+    )
+
+
 @router.get("/debug/memory/summary", include_in_schema=False)
 async def get_memory_summary(
     _: UserAPIKeyAuth = Depends(user_api_key_auth),
@@ -227,10 +265,9 @@ async def get_memory_summary(
     try:
         import psutil
 
-        process: Final = psutil.Process()
-        memory_info: Final = process.memory_info()
-        memory_mb: Final = memory_info.rss / (1024 * 1024)
-        memory_percent: Final = process.memory_percent()
+        usage: Final = _process_memory_usage(psutil.Process())
+        memory_mb: Final = usage.resident_megabytes
+        memory_percent: Final = usage.percent
 
         process_memory = {
             "summary": f"{memory_mb:.1f} MB ({memory_percent:.1f}% of system memory)",
@@ -252,7 +289,7 @@ async def get_memory_summary(
         process_memory["error"] = str(e)
 
     # Get cache information
-    caches: Final[dict[str, Any]] = {}
+    caches: Final[dict[str, object]] = {}
     total_cache_items = 0
 
     try:
@@ -313,7 +350,7 @@ async def get_memory_summary(
     }
 
 
-def _get_gc_statistics() -> dict[str, Any]:
+def _get_gc_statistics() -> Mapping[str, object]:
     """Get garbage collector statistics."""
     return {
         "enabled": gc.isenabled(),
@@ -341,30 +378,42 @@ def _get_gc_statistics() -> dict[str, Any]:
     }
 
 
-def _get_object_type_counts(top_n: int) -> tuple[int, list[dict[str, Any]]]:
+class _ObjectTypeCount(TypedDict):
+    """One row of the tracked-object histogram."""
+
+    type: ReadOnly[str]
+    count: ReadOnly[int]
+    count_readable: ReadOnly[str]
+
+
+def _type_name_counts(objects: Sequence[object]) -> Counter[str]:
+    """Count ``objects`` by the name of their type."""
+    return Counter(type(obj).__name__ for obj in objects)
+
+
+def _get_object_type_counts(top_n: int) -> tuple[int, list[_ObjectTypeCount]]:
     """Count objects by type and return total count and top N types."""
-    type_counts: Final[Counter] = Counter()
-    total_objects = 0
+    type_counts: Final = _type_name_counts(gc.get_objects())
 
-    for obj in gc.get_objects():
-        total_objects += 1
-        obj_type = type(obj).__name__
-        type_counts[obj_type] += 1
-
-    top_object_types: Final = [
+    top_object_types: Final[list[_ObjectTypeCount]] = [
         {"type": obj_type, "count": count, "count_readable": f"{count:,}"}
         for obj_type, count in type_counts.most_common(top_n)
     ]
 
-    return total_objects, top_object_types
+    return sum(type_counts.values()), top_object_types
 
 
-def _get_uncollectable_objects_info() -> dict[str, Any]:
+def _type_names(objects: Sequence[object]) -> Sequence[str]:
+    """The type name of each object in ``objects``."""
+    return [type(obj).__name__ for obj in objects]
+
+
+def _get_uncollectable_objects_info() -> Mapping[str, object]:
     """Get information about uncollectable objects (potential memory leaks)."""
     uncollectable: Final = gc.garbage
     return {
         "count": len(uncollectable),
-        "sample_types": [type(obj).__name__ for obj in uncollectable[:10]],
+        "sample_types": _type_names(uncollectable[:10]),
         "warning": (
             "If count > 0, you may have reference cycles preventing garbage collection"
             if len(uncollectable) > 0
@@ -373,9 +422,11 @@ def _get_uncollectable_objects_info() -> dict[str, Any]:
     }
 
 
-def _get_cache_memory_stats(user_api_key_cache, llm_router, proxy_logging_obj, redis_usage_cache) -> dict[str, Any]:
+def _get_cache_memory_stats(
+    user_api_key_cache, llm_router, proxy_logging_obj, redis_usage_cache
+) -> Mapping[str, object]:
     """Calculate memory usage for all caches."""
-    cache_stats: Final[dict[str, Any]] = {}
+    cache_stats: Final[dict[str, object]] = {}
     try:
         # User API key cache
         user_cache_size: Final = sys.getsizeof(user_api_key_cache.in_memory_cache.cache_dict)
@@ -439,9 +490,9 @@ def _get_cache_memory_stats(user_api_key_cache, llm_router, proxy_logging_obj, r
     return cache_stats
 
 
-def _get_router_memory_stats(llm_router) -> dict[str, Any]:
+def _get_router_memory_stats(llm_router) -> Mapping[str, object]:
     """Get memory usage statistics for LiteLLM router."""
-    litellm_router_memory: dict[str, Any] = {}
+    litellm_router_memory: dict[str, object] = {}
     try:
         if llm_router is not None:
             # Model list memory size
@@ -505,7 +556,7 @@ def _get_router_memory_stats(llm_router) -> dict[str, Any]:
     return litellm_router_memory
 
 
-def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> dict[str, Any] | None:
+def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> Mapping[str, object] | None:
     """Get process-level memory information using psutil."""
     if not include_process_info:
         return None
@@ -514,10 +565,10 @@ def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> dic
         import psutil
 
         process: Final = psutil.Process()
-        memory_info: Final = process.memory_info()
-        ram_usage_mb: Final = round(memory_info.rss / (1024 * 1024), 2)
-        virtual_memory_mb: Final = round(memory_info.vms / (1024 * 1024), 2)
-        memory_percent: Final = round(process.memory_percent(), 2)
+        usage: Final = _process_memory_usage(process)
+        ram_usage_mb: Final = round(usage.resident_megabytes, 2)
+        virtual_memory_mb: Final = round(usage.virtual_megabytes, 2)
+        memory_percent: Final = round(usage.percent, 2)
 
         return {
             "pid": worker_pid,
diff --git a/litellm/proxy/common_utils/model_listing_utils.py b/litellm/proxy/common_utils/model_listing_utils.py
index 9fd24162f7e..213a697b3dd 100644
--- a/litellm/proxy/common_utils/model_listing_utils.py
+++ b/litellm/proxy/common_utils/model_listing_utils.py
@@ -10,13 +10,36 @@ legacy internal names with `general_settings.use_team_public_model_name: false`.
 
 from __future__ import annotations
 
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Final, cast
 
 if TYPE_CHECKING:
     from litellm.router import Router
 
 
+def configured_display_names(
+    entries: Sequence[tuple[str, str]],
+    llm_router: Router | None,
+) -> Mapping[str, str]:
+    """response_id -> configured `model_info.display_name` for the listing entries
+    that have one.
+
+    Metadata is looked up by each entry's internal lookup id (so team-scoped rows
+    resolve), while the returned map is keyed by the public response id the
+    Anthropic-shaped listing is built from. Entries without a configured name are
+    omitted so the listing falls back to the id itself.
+    """
+    if llm_router is None:
+        return MappingProxyType({})
+    resolved: Final = (
+        (response_id, llm_router.get_configured_display_name(lookup_id)) for response_id, lookup_id in entries
+    )
+    return MappingProxyType(
+        {response_id: display_name for response_id, display_name in resolved if display_name is not None}
+    )
+
+
 class TeamModelNameTranslator:
     """Translates internal team routing keys to their public names for the model
     listing/retrieve responses. Stateless; the live router and general_settings
diff --git a/litellm/proxy/common_utils/semantic_text_index.py b/litellm/proxy/common_utils/semantic_text_index.py
new file mode 100644
index 00000000000..0820459af49
--- /dev/null
+++ b/litellm/proxy/common_utils/semantic_text_index.py
@@ -0,0 +1,142 @@
+"""Embedding-similarity ranking over short texts with a per-model vector cache, shared by agent search and MCP tool search."""
+
+from __future__ import annotations
+
+import math
+from collections.abc import Awaitable, Mapping, Sequence
+from dataclasses import dataclass
+from itertools import chain
+from types import MappingProxyType
+from typing import TYPE_CHECKING, Final, Protocol, TypeAlias
+
+from openai import OpenAIError
+from pydantic import BaseModel, ConfigDict
+
+from litellm.exceptions import BudgetExceededError
+
+if TYPE_CHECKING:
+    from litellm.proxy._types import UserAPIKeyAuth
+    from litellm.router import Router
+
+Vector: TypeAlias = tuple[float, ...]
+
+
+class Embedder(Protocol):
+    def __call__(self, texts: Sequence[str]) -> Awaitable[Sequence[Vector]]: ...
+
+
+@dataclass(frozen=True, slots=True)
+class EmbeddingFailed:
+    reason: str
+
+
+class _EmbeddingItem(BaseModel):
+    model_config = ConfigDict(frozen=True, extra="ignore")
+
+    embedding: tuple[float, ...]
+
+
+class _EmbeddingData(BaseModel):
+    model_config = ConfigDict(frozen=True, extra="ignore")
+
+    data: tuple[_EmbeddingItem, ...]
+
+
+def cosine_similarity(left: Vector, right: Vector) -> float:
+    dot: Final = sum(a * b for a, b in zip(left, right, strict=True))
+    norms: Final = math.sqrt(sum(a * a for a in left)) * math.sqrt(sum(b * b for b in right))
+    return dot / norms if norms else 0.0
+
+
+def embedding_spend_metadata(user_api_key_dict: UserAPIKeyAuth) -> dict[str, object]:  # mutable-ok: router mutates it
+    from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
+
+    return {  # mutable-ok: the router mutates the metadata dict it is handed
+        **LiteLLMProxyRequestSetup.get_sanitized_user_information_from_key(user_api_key_dict),
+        "user_api_key": user_api_key_dict.api_key,
+    }
+
+
+def router_embedder(router: Router, embedding_model: str, user_api_key_dict: UserAPIKeyAuth) -> Embedder:
+    async def embed(texts: Sequence[str]) -> Sequence[Vector]:
+        batch: Final = list(texts)  # mutable-ok: Router.aembedding accepts only str | list input
+        response: Final = await router.aembedding(
+            model=embedding_model, input=batch, metadata=embedding_spend_metadata(user_api_key_dict)
+        )
+        return tuple(item.embedding for item in _EmbeddingData.model_validate(response.model_dump()).data)
+
+    return embed
+
+
+_NO_VECTORS: Final[Mapping[str, Vector]] = MappingProxyType({})
+
+
+async def _embed_all(embed: Embedder, texts: Sequence[str]) -> tuple[Vector, ...] | EmbeddingFailed:
+    try:
+        vectors: Final = tuple(await embed(texts))
+    except (OpenAIError, ValueError, BudgetExceededError) as exc:
+        return EmbeddingFailed(reason=f"embedding the search query failed: {exc}")
+    if len(vectors) != len(texts):
+        return EmbeddingFailed(reason=f"embedding model returned {len(vectors)} vectors for {len(texts)} inputs")
+    return vectors
+
+
+@dataclass(frozen=True, slots=True)
+class _Embedded:
+    query_vector: Vector
+    vectors: Mapping[str, Vector]
+
+
+def _same_dimension(query_vector: Vector, vectors: Mapping[str, Vector], texts: Sequence[str]) -> bool:
+    return all(len(vectors[text]) == len(query_vector) for text in texts)
+
+
+async def _embed_query_and_texts(
+    embed: Embedder, query: str, texts: Sequence[str], cached: Mapping[str, Vector]
+) -> _Embedded | EmbeddingFailed:
+    missing: Final = tuple(dict.fromkeys(text for text in texts if text not in cached))
+    embedded: Final = await _embed_all(embed, (query, *missing))
+    if isinstance(embedded, EmbeddingFailed):
+        return embedded
+    vectors: Final = MappingProxyType(dict(chain(cached.items(), zip(missing, embedded[1:], strict=True))))
+    if _same_dimension(embedded[0], vectors, texts):
+        return _Embedded(query_vector=embedded[0], vectors=vectors)
+    unique: Final = tuple(dict.fromkeys(texts))
+    reembedded: Final = await _embed_all(embed, (query, *unique))
+    if isinstance(reembedded, EmbeddingFailed):
+        return reembedded
+    return _Embedded(
+        query_vector=reembedded[0], vectors=MappingProxyType(dict(zip(unique, reembedded[1:], strict=True)))
+    )
+
+
+class SemanticTextIndex:
+    """Caches one vector per distinct text per embedding model, so repeat searches only embed the query."""
+
+    def __init__(self) -> None:
+        self._vectors: Mapping[str, Mapping[str, Vector]] = MappingProxyType({})
+
+    def _merged(self, embedding_model: str, embedded: _Embedded) -> Mapping[str, Vector]:
+        kept: Final = MappingProxyType(
+            {
+                text: vector
+                for text, vector in self._vectors.get(embedding_model, _NO_VECTORS).items()
+                if len(vector) == len(embedded.query_vector)
+            }
+        )
+        return MappingProxyType({**kept, **embedded.vectors})
+
+    async def scores(
+        self, query: str, texts: Sequence[str], embed: Embedder, embedding_model: str
+    ) -> tuple[float, ...] | EmbeddingFailed:
+        """Cosine similarity of `query` to each entry of `texts`, in the same order."""
+        if not texts:
+            return ()
+        cached: Final = self._vectors.get(embedding_model, _NO_VECTORS)
+        embedded: Final = await _embed_query_and_texts(embed, query, texts, cached)
+        if isinstance(embedded, EmbeddingFailed):
+            return embedded
+        if not _same_dimension(embedded.query_vector, embedded.vectors, texts):
+            return EmbeddingFailed(reason=f"embedding model {embedding_model} returned vectors of mixed dimensions")
+        self._vectors = MappingProxyType({**self._vectors, embedding_model: self._merged(embedding_model, embedded)})
+        return tuple(cosine_similarity(embedded.query_vector, embedded.vectors[text]) for text in texts)
diff --git a/litellm/proxy/common_utils/user_api_key_cache.py b/litellm/proxy/common_utils/user_api_key_cache.py
index 589d8fe68d1..76982d30306 100644
--- a/litellm/proxy/common_utils/user_api_key_cache.py
+++ b/litellm/proxy/common_utils/user_api_key_cache.py
@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import Any, Final, TypeVar, cast, overload
+from typing import TYPE_CHECKING, Any, Final, TypeVar, cast, overload
 
 from pydantic import BaseModel
 
@@ -9,6 +9,9 @@ from litellm.caching.dual_cache import DualCache
 from litellm.constants import DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL
 from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec
 
+if TYPE_CHECKING:
+    from opentelemetry.trace import Span
+
 T = TypeVar("T", bound=BaseModel)
 
 
@@ -40,31 +43,32 @@ class UserApiKeyCache(DualCache):
     @overload
     def get_cache(
         self,
-        key: Any,
-        parent_otel_span: Any = None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
         *,
         model_type: type[T],
-        **kwargs: Any,
+        **kwargs: object,
     ) -> T | None: ...
 
     @overload
     def get_cache(
         self,
-        key: Any,
-        parent_otel_span: Any = None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
-        **kwargs: Any,
+        model_type: None = None,
+        **kwargs: object,
     ) -> Any: ...
 
     def get_cache(
         self,
-        key,
-        parent_otel_span=None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
         model_type: type[BaseModel] | None = None,
-        **kwargs,
-    ) -> Any | BaseModel | None:
+        **kwargs: object,
+    ) -> object:
         if model_type is None and "model_type" in kwargs:
             model_type = cast(type[BaseModel] | None, kwargs.pop("model_type", None))
         cached: Final = super().get_cache(key=key, parent_otel_span=parent_otel_span, local_only=local_only, **kwargs)
@@ -85,31 +89,32 @@ class UserApiKeyCache(DualCache):
     @overload
     async def async_get_cache(
         self,
-        key: Any,
-        parent_otel_span: Any = None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
         *,
         model_type: type[T],
-        **kwargs: Any,
+        **kwargs: object,
     ) -> T | None: ...
 
     @overload
     async def async_get_cache(
         self,
-        key: Any,
-        parent_otel_span: Any = None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
-        **kwargs: Any,
+        model_type: None = None,
+        **kwargs: object,
     ) -> Any: ...
 
     async def async_get_cache(
         self,
-        key,
-        parent_otel_span=None,
+        key: str,
+        parent_otel_span: Span | None = None,
         local_only: bool = False,
         model_type: type[BaseModel] | None = None,
-        **kwargs,
-    ) -> Any | BaseModel | None:
+        **kwargs: object,
+    ) -> object:
         if model_type is None and "model_type" in kwargs:
             model_type = cast(type[BaseModel] | None, kwargs.pop("model_type", None))
         cached: Final = await super().async_get_cache(
@@ -129,17 +134,17 @@ class UserApiKeyCache(DualCache):
             return None
         return decoded
 
-    def set_cache(self, key, value, local_only: bool = False, **kwargs):
+    def set_cache(self, key: str | None, value: object, local_only: bool = False, **kwargs: object):
         model_type: Final = cast(type[BaseModel] | None, kwargs.pop("model_type", None))
-        payload: Final = CacheCodec.serialize(value, model_type=model_type)
+        payload: Final[object] = CacheCodec.serialize(value, model_type=model_type)
         return super().set_cache(key=key, value=payload, local_only=local_only, **kwargs)
 
-    async def async_set_cache(self, key, value, local_only: bool = False, **kwargs):
+    async def async_set_cache(self, key: str | None, value: object, local_only: bool = False, **kwargs: object):
         model_type: Final = cast(type[BaseModel] | None, kwargs.pop("model_type", None))
-        payload: Final = CacheCodec.serialize(value, model_type=model_type)
+        payload: Final[object] = CacheCodec.serialize(value, model_type=model_type)
         return await super().async_set_cache(key=key, value=payload, local_only=local_only, **kwargs)
 
-    async def async_set_cache_pipeline(self, cache_list: list, local_only: bool = False, **kwargs) -> None:
+    async def async_set_cache_pipeline(self, cache_list: list, local_only: bool = False, **kwargs: object) -> None:
         """
         Batch writes with the same Codec boundary as ``async_set_cache`` without
         ``model_type``: ``BaseModel`` values become JSON-safe dicts; dicts/scalars unchanged.
diff --git a/litellm/proxy/container_endpoints/endpoints.py b/litellm/proxy/container_endpoints/endpoints.py
index 4a088140725..eaa3db336a9 100644
--- a/litellm/proxy/container_endpoints/endpoints.py
+++ b/litellm/proxy/container_endpoints/endpoints.py
@@ -208,7 +208,7 @@ async def list_containers(
 
     # Read query parameters
     query_params: Final = dict(request.query_params)
-    data: Final[dict[str, Any]] = {"query_params": query_params}
+    data: Final[dict[str, Any]] = {"query_params": query_params, "model": query_params.get("model")}
 
     # Extract custom_llm_provider using priority chain
     custom_llm_provider: Final = (
diff --git a/litellm/proxy/db/budget_window_spend_writer.py b/litellm/proxy/db/budget_window_spend_writer.py
index f9188f95cfd..8cf2f737063 100644
--- a/litellm/proxy/db/budget_window_spend_writer.py
+++ b/litellm/proxy/db/budget_window_spend_writer.py
@@ -7,20 +7,15 @@ instead of aggregating LiteLLM_SpendLogs every time a window counter goes cold
 (issue #35766). Raw SQL rather than the Prisma upsert helper because the
 conditional roll cannot be expressed through the query builder.
 
-Seeding a row that does not exist yet reads LiteLLM_SpendLogs once, excluding
-the requests whose increments are in the same batch so neither source counts
-them twice. One gap survives that exclusion: without the Redis transaction
-buffer every pod flushes its own increments, so a row seeded by one pod can
-include spend logs whose increments are still queued on another pod, and those
-increments are added again when that pod flushes. That is bounded by a single
-flush interval, happens at most once per window row, and only ever over-counts:
-the seed never omits spend, because every increment not yet in the row still
-reaches it on its own pod's next flush. A row therefore lags real spend by at
-most one flush interval of queued increments, the same lag the SpendLogs
-aggregate it replaces (and every other spend column) already has.
+Seeding a row that does not exist yet reads LiteLLM_SpendLogs once and takes
+off what the increments being flushed will add, so neither source counts the
+same request twice. A row therefore lags real spend by at most one flush
+interval of increments queued elsewhere: the same lag the SpendLogs aggregate
+it replaces (and every other spend column) already has.
 """
 
 from collections.abc import Sequence
+from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from typing import TYPE_CHECKING, Final, Protocol
 
@@ -67,33 +62,46 @@ _ROLL_WINDOW_SPEND_SQL: Final = (
 )
 
 _SEED_FROM_SPEND_LOGS_KEY_SQL: Final = (
-    'SELECT COALESCE(SUM(spend), 0.0) AS total FROM "LiteLLM_SpendLogs" '
-    "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC') "
-    "AND NOT (request_id = ANY($3::text[]) AND \"startTime\" >= ($4::timestamptz AT TIME ZONE 'UTC'))"
+    "SELECT COALESCE(SUM(spend), 0.0) AS total, "
+    "COALESCE(SUM(spend) FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) AS before_batch "
+    'FROM "LiteLLM_SpendLogs" '
+    "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')"
 )
 
 _SEED_FROM_SPEND_LOGS_TEAM_SQL: Final = (
-    'SELECT COALESCE(SUM(spend), 0.0) AS total FROM "LiteLLM_SpendLogs" '
-    "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC') "
-    "AND NOT (request_id = ANY($3::text[]) AND \"startTime\" >= ($4::timestamptz AT TIME ZONE 'UTC'))"
+    "SELECT COALESCE(SUM(spend), 0.0) AS total, "
+    "COALESCE(SUM(spend) FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) AS before_batch "
+    'FROM "LiteLLM_SpendLogs" '
+    "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')"
 )
 
 _SEED_FROM_SPEND_LOGS_KEY_UNBOUNDED_SQL: Final = (
-    'SELECT COALESCE(SUM(spend), 0.0) AS total FROM "LiteLLM_SpendLogs" '
+    "SELECT COALESCE(SUM(spend), 0.0) AS total, COALESCE(SUM(spend), 0.0) AS before_batch "
+    'FROM "LiteLLM_SpendLogs" '
     "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')"
 )
 
 _SEED_FROM_SPEND_LOGS_TEAM_UNBOUNDED_SQL: Final = (
-    'SELECT COALESCE(SUM(spend), 0.0) AS total FROM "LiteLLM_SpendLogs" '
+    "SELECT COALESCE(SUM(spend), 0.0) AS total, COALESCE(SUM(spend), 0.0) AS before_batch "
+    'FROM "LiteLLM_SpendLogs" '
     "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')"
 )
 
 _UPSERT_TRANSACTION_TIMEOUT: Final = timedelta(seconds=60)
 
 
+@dataclass(frozen=True, slots=True)
+class WindowSeedTotals:
+    """The two sums a seed needs: everything persisted for the window, and the
+    part of it that predates the batch being flushed."""
+
+    total: float
+    before_batch: float
+
+
 class WindowSpendLogsAggregate(Protocol):
-    """Sums LiteLLM_SpendLogs for one entity since window_start, ignoring the
-    requests whose ids are handed in.
+    """Sums LiteLLM_SpendLogs for one entity since window_start, split at the
+    batch's earliest request.
 
     Injected so the flush can be exercised without a database and so the
     expensive aggregate stays swappable.
@@ -105,21 +113,19 @@ class WindowSpendLogsAggregate(Protocol):
         entity_type: str,
         entity_id: str,
         window_start: datetime,
-        exclude_request_ids: Sequence[str],
-        exclude_started_at: datetime | None,
-    ) -> float | None: ...
+        batch_started_at: datetime | None,
+    ) -> WindowSeedTotals | None: ...
 
 
-async def spend_logs_total_excluding(
+async def spend_logs_seed_totals(
     prisma_client: "PrismaClient",
     entity_type: str,
     entity_id: str,
     window_start: datetime,
-    exclude_request_ids: Sequence[str],
-    exclude_started_at: datetime | None,
-) -> float | None:
-    """LiteLLM_SpendLogs spend for one entity since window_start, minus the
-    requests already accounted for by the increments being flushed.
+    batch_started_at: datetime | None,
+) -> WindowSeedTotals | None:
+    """LiteLLM_SpendLogs spend for one entity since window_start, both in full
+    and up to the start of the batch being flushed, in one scan.
 
     The spend log writer drains its own queue on a ~2s poll whenever anything
     is queued, while window increments flush on the much slower batch tick, so
@@ -127,13 +133,12 @@ async def spend_logs_total_excluding(
     already in the table. Counting them in the seed and again in the increment
     is what made a fresh row land at twice the true spend.
 
-    The exclusion is bounded to rows that started at or after the batch's
-    earliest request. request_id can be chosen by the client
-    (x-litellm-call-id), so an unbounded exclusion would let a replayed old id
-    erase a historical row from the seed while its increment still lands.
-    Without a known start the batch's ids are not excluded at all: that can
-    only over-count once, which enforcement tolerates, whereas under-counting
-    is a budget bypass.
+    Both halves are needed because neither is safe alone: the full sum
+    double-counts this batch, and the sum before the batch drops spend another
+    pod has already persisted but not yet incremented. _seed_base picks between
+    them. Without a known batch start the two are the same sum, so the seed
+    counts everything: that can only over-count once, which enforcement
+    tolerates, whereas under-counting is a budget bypass.
     """
     if entity_type == Litellm_EntityType.KEY.value:
         bounded_sql, unbounded_sql = _SEED_FROM_SPEND_LOGS_KEY_SQL, _SEED_FROM_SPEND_LOGS_KEY_UNBOUNDED_SQL
@@ -143,21 +148,23 @@ async def spend_logs_total_excluding(
         return None
     rows: Final = (
         await prisma_client.db.query_raw(unbounded_sql, entity_id, window_start)
-        if exclude_started_at is None or not exclude_request_ids
+        if batch_started_at is None
         else await prisma_client.db.query_raw(
             bounded_sql,
             entity_id,
             window_start,
-            tuple(exclude_request_ids),
-            _exclusion_lower_bound(exclude_started_at),
+            _exclusion_upper_bound(batch_started_at),
         )
     )
     if not rows:
-        return 0.0
-    return float(rows[0].get("total") or 0.0)
+        return WindowSeedTotals(total=0.0, before_batch=0.0)
+    return WindowSeedTotals(
+        total=float(rows[0].get("total") or 0.0),
+        before_batch=float(rows[0].get("before_batch") or 0.0),
+    )
 
 
-def _exclusion_lower_bound(started_at: datetime) -> datetime:
+def _exclusion_upper_bound(started_at: datetime) -> datetime:
     """LiteLLM_SpendLogs.startTime is TIMESTAMP(3); floor to the second so a
     millisecond rounding of the batch's own earliest row cannot slip under it."""
     return to_naive_utc(started_at).replace(microsecond=0)
@@ -194,20 +201,33 @@ async def _seed_base_for_missing_row(
 
     This is the LiteLLM_SpendLogs aggregate the window counter reseed runs on
     every cold counter today, but here it runs once per window lifetime and off
-    the request path, and it excludes this batch's own requests so they are
-    counted by their increments alone.
+    the request path, and it discounts the queued increments so they are
+    counted once.
     """
     if _primary_key(transaction) in existing_primary_keys:
         return 0.0
-    base: Final = await spend_logs_aggregate(
+    totals: Final = await spend_logs_aggregate(
         prisma_client=prisma_client,
         entity_type=transaction["entity_type"],
         entity_id=transaction["entity_id"],
         window_start=datetime.fromisoformat(transaction["window_start"]).replace(tzinfo=timezone.utc),
-        exclude_request_ids=transaction["request_ids"],
-        exclude_started_at=_transaction_started_at(transaction),
+        batch_started_at=_transaction_started_at(transaction),
     )
-    return float(base or 0.0)
+    if totals is None:
+        return 0.0
+    return _seed_base(totals=totals, batch_spend=transaction["spend"])
+
+
+def _seed_base(totals: WindowSeedTotals, batch_spend: float) -> float:
+    """What the window already held before the increments about to be applied.
+
+    Subtracting the batch's own spend from the full sum keeps every other
+    request in the seed, including the ones another pod persisted and has not
+    incremented yet, which a plain cutoff would drop for good if that pod died.
+    When this batch's own log rows have not landed yet the subtraction takes
+    spend that was never counted, so the sum before the batch is the floor.
+    """
+    return max(totals.total - batch_spend, totals.before_batch)
 
 
 def _transaction_started_at(transaction: WindowSpendTransaction) -> datetime | None:
@@ -241,7 +261,7 @@ def _upsert_params(
 async def commit_window_spend_updates(
     prisma_client: "PrismaClient",
     transactions: Sequence[WindowSpendTransaction],
-    spend_logs_aggregate: WindowSpendLogsAggregate = spend_logs_total_excluding,
+    spend_logs_aggregate: WindowSpendLogsAggregate = spend_logs_seed_totals,
 ) -> None:
     """Apply aggregated window increments to LiteLLM_BudgetWindowSpend.
 
diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py
index 641c07914d9..e6880d521f1 100644
--- a/litellm/proxy/db/db_spend_update_writer.py
+++ b/litellm/proxy/db/db_spend_update_writer.py
@@ -211,15 +211,11 @@ class DBSpendUpdateWriter:
         org_id: str | None,
         # Completion object fields
         kwargs: dict | None,
-        completion_response: litellm.ModelResponse | Any | Exception | None,
+        completion_response: object,
         start_time: datetime | None,
         end_time: datetime | None,
         response_cost: float | None,
-    ) -> str | None:
-        """Returns the LiteLLM_SpendLogs request_id this call was recorded
-        under, so the caller can tell the budget-window writer which log rows
-        its increments already cover. None when the payload could not be built.
-        """
+    ) -> None:
         from litellm.proxy.proxy_server import (
             disable_spend_logs,
             litellm_proxy_budget_name,
@@ -236,7 +232,7 @@ class DBSpendUpdateWriter:
                 team_id,
             )
             if ProxyUpdateSpend.disable_spend_updates() is True:
-                return None
+                return
             if token is not None and isinstance(token, str) and token.startswith("sk-"):
                 hashed_token = hash_token(token=token)
             else:
@@ -310,7 +306,6 @@ class DBSpendUpdateWriter:
             )
 
             verbose_proxy_logger.debug("Runs spend update on all tables")
-            return payload.get("request_id")
         except Exception:
             spend_log_error(
                 "Spend tracking - update_database failed. Spend log insertion or daily transaction enqueue "
@@ -323,12 +318,12 @@ class DBSpendUpdateWriter:
                 org_id,
                 end_user_id,
             )
-            return None
+            return
 
     async def _enqueue_tool_usage_transaction(
         self,
         payload: SpendLogsPayload,
-        completion_response: "litellm.ModelResponse | Any | Exception | None",
+        completion_response: object,
         prisma_client: "PrismaClient | None",
         kwargs: "dict | None" = None,
     ) -> None:
@@ -401,7 +396,7 @@ class DBSpendUpdateWriter:
     def _enqueue_tool_registry_upsert(
         self,
         kwargs: dict | None,
-        completion_response: Any | None,
+        completion_response: object,
         hashed_token: str | None = None,
         team_id: str | None = None,
     ) -> None:
@@ -854,7 +849,7 @@ class DBSpendUpdateWriter:
                 return
 
             # Parse tags from JSON string
-            tags = []
+            tags: Sequence[object] = []
             if isinstance(request_tags, str):
                 tags = safe_json_loads(request_tags, default=[])
                 if not tags:
@@ -2265,7 +2260,7 @@ class DBSpendUpdateWriter:
             verbose_proxy_logger.debug("request_tags is None for request. Skipping incrementing tag spend.")
             return
 
-        request_tags = []
+        request_tags: Sequence[str] = []
         if isinstance(payload["request_tags"], str):
             request_tags = json.loads(payload["request_tags"])
         elif isinstance(payload["request_tags"], list):
diff --git a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py
index 4dd23270bf8..c06f2e04aca 100644
--- a/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py
+++ b/litellm/proxy/db/db_transaction_queue/redis_update_buffer.py
@@ -46,6 +46,7 @@ from litellm.proxy.db.db_transaction_queue.spend_update_queue import SpendUpdate
 from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import (
     WindowSpendTransaction,
     WindowSpendUpdateQueue,
+    to_wire_payload,
 )
 from litellm.secret_managers.main import str_to_bool
 from litellm.types.caching import (
@@ -298,7 +299,7 @@ class RedisUpdateBuffer:
                 ServiceTypes.REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE,
             ),
             (
-                window_spend_update_transactions,
+                tuple(map(to_wire_payload, window_spend_update_transactions)),
                 REDIS_WINDOW_SPEND_UPDATE_BUFFER_KEY,
                 ServiceTypes.REDIS_WINDOW_SPEND_UPDATE_QUEUE,
             ),
@@ -484,7 +485,12 @@ class RedisUpdateBuffer:
             (daily_end_user_spend_update_transactions, REDIS_DAILY_END_USER_SPEND_UPDATE_BUFFER_KEY),
             (daily_agent_spend_update_transactions, REDIS_DAILY_AGENT_SPEND_UPDATE_BUFFER_KEY),
             (daily_tag_spend_update_transactions, REDIS_DAILY_TAG_SPEND_UPDATE_BUFFER_KEY),
-            (window_spend_update_transactions, REDIS_WINDOW_SPEND_UPDATE_BUFFER_KEY),
+            (
+                None
+                if window_spend_update_transactions is None
+                else tuple(map(to_wire_payload, window_spend_update_transactions)),
+                REDIS_WINDOW_SPEND_UPDATE_BUFFER_KEY,
+            ),
         )
 
         rpush_list: Final = tuple(
diff --git a/litellm/proxy/db/db_transaction_queue/window_spend_update_queue.py b/litellm/proxy/db/db_transaction_queue/window_spend_update_queue.py
index 04dea66165e..372a6666c02 100644
--- a/litellm/proxy/db/db_transaction_queue/window_spend_update_queue.py
+++ b/litellm/proxy/db/db_transaction_queue/window_spend_update_queue.py
@@ -26,17 +26,12 @@ class WindowSpendTransaction(TypedDict):
     window_start is an ISO-8601 string rather than a datetime so the
     transaction survives the JSON round trip through the Redis buffer.
 
-    request_ids carries the LiteLLM_SpendLogs ids this spend came from. The
-    one-time seed for a window that has no row yet subtracts them from its
-    LiteLLM_SpendLogs aggregate, because the spend log writer flushes on its
-    own ~2s poll and will usually have persisted these rows before the window
-    queue flushes; without the exclusion the seed and the increment would each
-    count them.
-
-    started_at is the earliest request start in the batch. The seed only
-    subtracts a request_id whose LiteLLM_SpendLogs.startTime is at or after it,
-    so a client that replays an old id through x-litellm-call-id cannot make the
-    seed drop the historical row that id already paid for.
+    started_at is the earliest request start in the batch. The one-time seed for
+    a window that has no row yet uses it to tell this batch's own
+    LiteLLM_SpendLogs rows from everything else, because the spend log writer
+    flushes on its own ~2s poll and will usually have persisted this batch's
+    rows before the window queue flushes; without that split the seed and the
+    increment would each count them.
     """
 
     entity_type: ReadOnly[str]
@@ -44,10 +39,37 @@ class WindowSpendTransaction(TypedDict):
     window_duration: ReadOnly[str]
     window_start: ReadOnly[str]
     spend: ReadOnly[float]
-    request_ids: ReadOnly[Sequence[str]]
     started_at: ReadOnly[str | None]
 
 
+class WindowSpendWirePayload(WindowSpendTransaction):
+    """How an increment is encoded in the shared Redis buffer.
+
+    request_ids is dead weight here: workers built before this field was
+    dropped index it while merging whatever they pop, and the pop is
+    destructive, so a leader still running one of those during a rolling deploy
+    would raise on a payload without the key and lose those increments. It is
+    always empty, which only makes such a leader seed without exclusions.
+
+    TODO: remove once no supported version reads it, i.e. one release after the
+    field stopped being written.
+    """
+
+    request_ids: ReadOnly[Sequence[str]]
+
+
+def to_wire_payload(transaction: WindowSpendTransaction) -> WindowSpendWirePayload:
+    return WindowSpendWirePayload(
+        entity_type=transaction["entity_type"],
+        entity_id=transaction["entity_id"],
+        window_duration=transaction["window_duration"],
+        window_start=transaction["window_start"],
+        spend=transaction["spend"],
+        started_at=transaction.get("started_at"),
+        request_ids=(),
+    )
+
+
 def to_naive_utc(value: datetime) -> datetime:
     """LiteLLM_BudgetWindowSpend.window_start is TIMESTAMP(3), which holds naive UTC."""
     if value.tzinfo is None:
@@ -72,7 +94,6 @@ def build_window_spend_transaction(
     window_duration: str,
     window_start: datetime,
     spend: float,
-    request_id: str | None = None,
     started_at: datetime | None = None,
 ) -> WindowSpendTransaction:
     return WindowSpendTransaction(
@@ -81,7 +102,6 @@ def build_window_spend_transaction(
         window_duration=window_duration,
         window_start=to_naive_utc(window_start).isoformat(timespec="microseconds"),
         spend=spend,
-        request_ids=() if request_id is None else (request_id,),
         started_at=None
         if started_at is None
         else to_naive_utc(started_at.astimezone(timezone.utc)).isoformat(timespec="microseconds"),
@@ -101,7 +121,6 @@ def _merge_window_spend_transactions(
         window_duration=first["window_duration"],
         window_start=first["window_start"],
         spend=math.fsum(payload["spend"] for payload in payloads),
-        request_ids=tuple(sorted(frozenset(chain.from_iterable(payload["request_ids"] for payload in payloads)))),
         started_at=min(started_ats) if started_ats else None,
     )
 
diff --git a/litellm/proxy/db/db_url_settings.py b/litellm/proxy/db/db_url_settings.py
index 1a39016b3a3..01f66e4f3c5 100644
--- a/litellm/proxy/db/db_url_settings.py
+++ b/litellm/proxy/db/db_url_settings.py
@@ -82,10 +82,30 @@ CONNECTION_PARAM_KEYS: Final[frozenset[str]] = frozenset(
         "pool_timeout",
         "connect_timeout",
         "socket_timeout",
+        "max_idle_connection_lifetime",
         "pgbouncer",
     }
 )
 
+# Quaint never tests pooled connections on checkout and keeps them idle for
+# 300s by default, past many infra idle timeouts, so dead sockets surface as
+# `Error { kind: Closed }`. 60s recycles them first; explicit values win.
+DEFAULT_MAX_IDLE_CONNECTION_LIFETIME: Final = 60
+IDLE_LIFETIME_DEFAULT_PARAMS: Final[Mapping[str, int]] = MappingProxyType(
+    {"max_idle_connection_lifetime": DEFAULT_MAX_IDLE_CONNECTION_LIFETIME}
+)
+
+
+def idle_lifetime_params(configured: float | None) -> Mapping[str, str | int | float]:
+    """The `max_idle_connection_lifetime` to add to URLs that do not pin one.
+
+    Applied via ``add_missing_query_params`` so a URL-pinned value always wins,
+    whether the operator configured `database_max_idle_connection_lifetime` or not.
+    """
+    if configured is None:
+        return IDLE_LIFETIME_DEFAULT_PARAMS
+    return MappingProxyType({"max_idle_connection_lifetime": configured})
+
 
 def add_missing_query_params(url: str, params: Mapping[str, str | int | float]) -> str:
     """Return ``url`` with the ``params`` it does not already carry appended.
diff --git a/litellm/proxy/db/exception_handler.py b/litellm/proxy/db/exception_handler.py
index 5502543b926..ef1c4a66203 100644
--- a/litellm/proxy/db/exception_handler.py
+++ b/litellm/proxy/db/exception_handler.py
@@ -1,4 +1,4 @@
-from collections.abc import Awaitable, Callable
+from collections.abc import Awaitable, Callable, Iterator
 from typing import Any, Final, TypeVar
 
 from litellm._logging import verbose_proxy_logger
@@ -9,10 +9,43 @@ from litellm.proxy._types import (
 )
 from litellm.secret_managers.main import str_to_bool
 
-# Bounds the __cause__/__context__ walk in is_database_service_unavailable_error_in_chain.
+# Bounds the __cause__/__context__ walk in find_database_service_unavailable_error_in_chain.
 # Real exception chains are a few links deep; the cap also makes the walk cycle-safe.
 _MAX_EXCEPTION_CHAIN_DEPTH: Final = 20
 
+_TRANSIENT_DB_UNAVAILABLE_MESSAGE: Final = (
+    "Service Unavailable, the authentication database is temporarily unreachable. Please retry shortly."
+)
+
+
+def _exception_chain(e: BaseException) -> Iterator[BaseException]:
+    current = e  # rebind-ok: advances one link per iteration of the bounded walk
+    for _ in range(_MAX_EXCEPTION_CHAIN_DEPTH):
+        yield current
+        following = current.__cause__ or current.__context__
+        if following is None:
+            return
+        current = following
+
+
+def _database_service_unavailable_errors(e: BaseException) -> tuple[Exception, ...]:
+    return tuple(
+        link
+        for link in _exception_chain(e)
+        if isinstance(link, Exception) and PrismaDBExceptionHandler.is_database_service_unavailable_error(link)
+    )
+
+
+def _exception_types(*candidates: object) -> tuple[type[BaseException], ...]:
+    """Keep only the real exception classes among ``candidates``.
+
+    The predicates below resolve prisma's error classes at call time, so a test
+    that swaps ``sys.modules["prisma"]`` for a ``MagicMock`` hands them mocks,
+    and ``isinstance`` against a mock raises ``TypeError`` instead of answering
+    False. Dropping the non-types lets the call fall through to the other checks.
+    """
+    return tuple(c for c in candidates if isinstance(c, type) and issubclass(c, BaseException))
+
 
 class PrismaDBExceptionHandler:
     """
@@ -59,7 +92,7 @@ class PrismaDBExceptionHandler:
 
         if isinstance(e, DB_CONNECTION_ERROR_TYPES):
             return True
-        if isinstance(e, prisma.engine.errors.EngineConnectionError):
+        if isinstance(e, _exception_types(prisma.engine.errors.EngineConnectionError)):
             return True
         return isinstance(e, ProxyException) and e.type == ProxyErrorTypes.no_db_connection
 
@@ -81,7 +114,7 @@ class PrismaDBExceptionHandler:
         """
         import prisma
 
-        data_layer_errors: Final = (
+        data_layer_errors: Final = _exception_types(
             prisma.errors.DataError,
             prisma.errors.UniqueViolationError,
             prisma.errors.ForeignKeyViolationError,
@@ -94,7 +127,7 @@ class PrismaDBExceptionHandler:
             return False
         if isinstance(e, DB_CONNECTION_ERROR_TYPES):
             return True
-        if isinstance(e, prisma.errors.PrismaError):
+        if isinstance(e, _exception_types(prisma.errors.PrismaError)):
             return True
         if isinstance(e, ProxyException) and e.type == ProxyErrorTypes.no_db_connection:
             return True
@@ -138,13 +171,13 @@ class PrismaDBExceptionHandler:
             return True
         if isinstance(
             e,
-            (
+            _exception_types(
                 prisma.errors.ClientNotConnectedError,
                 prisma.errors.HTTPClientClosedError,
             ),
         ):
             return True
-        if isinstance(e, prisma.errors.PrismaError):
+        if isinstance(e, _exception_types(prisma.errors.PrismaError)):
             error_message: Final = str(e).lower()
             connection_keywords: Final = (
                 "can't reach database server",
@@ -171,7 +204,7 @@ class PrismaDBExceptionHandler:
         """True iff ``e`` is a Postgres deadlock (P2034 / 40P01) surfaced through prisma."""
         import prisma
 
-        if not isinstance(e, prisma.errors.PrismaError):
+        if not isinstance(e, _exception_types(prisma.errors.PrismaError)):
             return False
         if getattr(e, "code", None) == "P2034":
             return True
@@ -202,7 +235,7 @@ class PrismaDBExceptionHandler:
         """
         import prisma
 
-        if isinstance(e, prisma.errors.PrismaError):
+        if isinstance(e, _exception_types(prisma.errors.PrismaError)):
             return False
         tb = getattr(e, "__traceback__", None)
         while tb is not None:
@@ -268,6 +301,51 @@ class PrismaDBExceptionHandler:
             ),
         )
 
+    @staticmethod
+    def is_permanent_database_fault(e: Exception) -> bool:
+        """True for a service-unavailable failure that will not clear on its
+        own: an engine-layer ``PrismaError`` (missing or version-skewed engine
+        binary, engine error status, misused transaction) that is neither the
+        transient ``EngineConnectionError`` nor a reconnectable transport failure.
+
+        Picks only the wording of a 503, never whether one is sent;
+        ``is_database_service_unavailable_error`` stays the status gate.
+        """
+        if PrismaDBExceptionHandler.is_database_connection_error(e):
+            return False
+        if PrismaDBExceptionHandler.is_database_transport_error(e):
+            return False
+        return PrismaDBExceptionHandler.is_database_infrastructure_error(e)
+
+    @staticmethod
+    def database_unavailable_message(e: Exception) -> str:
+        """The 503 detail for a service-unavailable database failure: retry
+        guidance for a transient outage, a pointer at the deployment for a
+        fault that retrying cannot fix. A permanent fault anywhere in the
+        exception chain wins, since the transport error that surfaced it is
+        not what blocks recovery."""
+        fault: Final = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(e) or e
+        if not PrismaDBExceptionHandler.is_permanent_database_fault(fault):
+            return _TRANSIENT_DB_UNAVAILABLE_MESSAGE
+        return (
+            "Service Unavailable, the authentication database query engine reported "
+            f"{type(fault).__name__}, which is not a transient outage and will not clear by retrying. "
+            "The proxy deployment needs attention."
+        )
+
+    @staticmethod
+    def find_database_service_unavailable_error_in_chain(e: BaseException) -> Exception | None:
+        """The exception in the ``__cause__`` / ``__context__`` chain that
+        ``is_database_service_unavailable_error`` accepts, or ``None``. Callers
+        that word a response by the kind of outage need the wrapped database
+        error itself, not just the fact that one is present. A permanent fault
+        outranks a transient one wherever it sits in the chain: a reconnect that
+        dies on a missing engine binary raises the transport error last, but the
+        binary is what keeps the database down."""
+        outages: Final = _database_service_unavailable_errors(e)
+        permanent: Final = next(filter(PrismaDBExceptionHandler.is_permanent_database_fault, outages), None)
+        return permanent if permanent is not None else next(iter(outages), None)
+
     @staticmethod
     def is_database_service_unavailable_error_in_chain(e: BaseException) -> bool:
         """Like ``is_database_service_unavailable_error`` but also walks the
@@ -285,14 +363,7 @@ class PrismaDBExceptionHandler:
 
         The walk is depth-bounded, which also makes it cycle-safe.
         """
-        current: BaseException | None = e
-        for _ in range(_MAX_EXCEPTION_CHAIN_DEPTH):
-            if not isinstance(current, Exception):
-                return False
-            if PrismaDBExceptionHandler.is_database_service_unavailable_error(current):
-                return True
-            current = current.__cause__ or current.__context__
-        return False
+        return PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(e) is not None
 
     @staticmethod
     def handle_db_exception(e: Exception):
diff --git a/litellm/proxy/db/tool_registry_writer.py b/litellm/proxy/db/tool_registry_writer.py
index 367552e783e..cd0aa75b859 100644
--- a/litellm/proxy/db/tool_registry_writer.py
+++ b/litellm/proxy/db/tool_registry_writer.py
@@ -6,9 +6,11 @@ Admins use the management endpoints to read and update input_policy / output_pol
 """
 
 import uuid
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from datetime import datetime, timezone
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Final, Protocol
+
+from pydantic import TypeAdapter
 
 from litellm._logging import verbose_proxy_logger
 from litellm.proxy._types import ToolDiscoveryQueueItem
@@ -27,6 +29,13 @@ if TYPE_CHECKING:
     from litellm.proxy.utils import PrismaClient
 
 
+class _ModelDumpMethod(Protocol):
+    def __call__(self) -> Mapping: ...
+
+
+_ROW_DICT: Final = TypeAdapter(dict)
+
+
 def _tool_table_actions(prisma_client: "PrismaClient") -> "TableActions[prisma_db_models.LiteLLM_ToolTable]":
     table: Final[TableActions[prisma_db_models.LiteLLM_ToolTable]] = ToolRepository(prisma_client).table
     return table
@@ -41,33 +50,35 @@ def _object_permission_table_actions(
     return table
 
 
-def _row_to_model(row: dict | Any) -> LiteLLM_ToolTableRow:
+def _row_to_model(row: object) -> LiteLLM_ToolTableRow:
     """Convert a Prisma model instance or dict to LiteLLM_ToolTableRow."""
-    model_dump: Final = getattr(row, "model_dump", None)
+    model_dump: Final[_ModelDumpMethod | None] = getattr(row, "model_dump", None)
     if callable(model_dump):
         row = model_dump()
     elif not isinstance(row, dict):
-        row = {
-            k: getattr(row, k, None)
-            for k in (
-                "tool_id",
-                "tool_name",
-                "origin",
-                "input_policy",
-                "output_policy",
-                "call_count",
-                "assignments",
-                "key_hash",
-                "team_id",
-                "key_alias",
-                "user_agent",
-                "last_used_at",
-                "created_at",
-                "updated_at",
-                "created_by",
-                "updated_by",
-            )
-        }
+        row = _ROW_DICT.validate_python(
+            {
+                k: getattr(row, k, None)
+                for k in (
+                    "tool_id",
+                    "tool_name",
+                    "origin",
+                    "input_policy",
+                    "output_policy",
+                    "call_count",
+                    "assignments",
+                    "key_hash",
+                    "team_id",
+                    "key_alias",
+                    "user_agent",
+                    "last_used_at",
+                    "created_at",
+                    "updated_at",
+                    "created_by",
+                    "updated_by",
+                )
+            }
+        )
     return LiteLLM_ToolTableRow(
         tool_id=row.get("tool_id", ""),
         tool_name=row.get("tool_name", ""),
@@ -190,7 +201,7 @@ async def update_tool_policy(
         _updated_by: Final = updated_by or "system"
         now: Final = datetime.now(timezone.utc)
 
-        create_data: Final[dict[str, object]] = {
+        create_data: Final[Mapping[str, str | datetime]] = {
             "tool_id": str(uuid.uuid4()),
             "tool_name": tool_name,
             "input_policy": input_policy or "untrusted",
@@ -200,14 +211,16 @@ async def update_tool_policy(
             "created_at": now,
             "updated_at": now,
         }
-        update_data: Final[dict[str, object]] = {
-            "updated_by": _updated_by,
-            "updated_at": now,
+        update_data: Final[Mapping[str, str | datetime]] = {
+            key: value
+            for key, value in (
+                ("updated_by", _updated_by),
+                ("updated_at", now),
+                ("input_policy", input_policy),
+                ("output_policy", output_policy),
+            )
+            if value is not None
         }
-        if input_policy is not None:
-            update_data["input_policy"] = input_policy
-        if output_policy is not None:
-            update_data["output_policy"] = output_policy
 
         await _tool_table_actions(prisma_client).upsert(
             where={"tool_name": tool_name},
@@ -338,7 +351,7 @@ class ToolPolicyRegistry:
             self._blocked_tools_by_op_id = {}
             for row in perms:
                 op_id = getattr(row, "object_permission_id", None)
-                blocked = getattr(row, "blocked_tools", None) or []
+                blocked: Sequence[str] = getattr(row, "blocked_tools", None) or []
                 if op_id:
                     self._blocked_tools_by_op_id[op_id] = list(blocked)
 
@@ -370,10 +383,12 @@ class ToolPolicyRegistry:
         """
         if not tool_names:
             return {}
-        blocked: Final[set[str]] = set()
-        for op_id in (object_permission_id, team_object_permission_id):
-            if op_id and op_id.strip():
-                blocked.update(self._blocked_tools_by_op_id.get(op_id.strip(), []))
+        blocked: Final[frozenset[str]] = frozenset(
+            tool
+            for op_id in (object_permission_id, team_object_permission_id)
+            if op_id and op_id.strip()
+            for tool in self._blocked_tools_by_op_id.get(op_id.strip(), [])
+        )
         result: Final[dict[str, str]] = {}
         for name in tool_names:
             if name in blocked:
@@ -408,13 +423,12 @@ async def add_tool_to_object_permission_blocked(
         )
         if row is None:
             return False
-        current: Final = list(getattr(row, "blocked_tools", []) or [])
+        current: Final[Sequence[str]] = getattr(row, "blocked_tools", []) or []
         if tool_name in current:
             return True
-        current.append(tool_name)
         await _object_permission_table_actions(prisma_client).update(
             where={"object_permission_id": object_permission_id},
-            data={"blocked_tools": current},
+            data={"blocked_tools": [*current, tool_name]},
         )
         return True
     except Exception as e:
@@ -436,13 +450,12 @@ async def remove_tool_from_object_permission_blocked(
         )
         if row is None:
             return False
-        current = list(getattr(row, "blocked_tools", []) or [])
+        current: Final[Sequence[str]] = getattr(row, "blocked_tools", []) or []
         if tool_name not in current:
             return False
-        current = [t for t in current if t != tool_name]
         await _object_permission_table_actions(prisma_client).update(
             where={"object_permission_id": object_permission_id},
-            data={"blocked_tools": current},
+            data={"blocked_tools": [t for t in current if t != tool_name]},
         )
         return True
     except Exception as e:
diff --git a/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py b/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py
index 64414b90ae7..c2053693f2e 100644
--- a/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py
+++ b/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py
@@ -14,7 +14,7 @@ router: Final = APIRouter()
 @router.get("/.well-known/litellm-ui-config", response_model=UiDiscoveryEndpoints)
 @router.get("/litellm/.well-known/litellm-ui-config", response_model=UiDiscoveryEndpoints)  # if mounted at root path
 async def get_ui_config():
-    from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+    from litellm.proxy.auth.auth_utils import has_user_setup_sso
     from litellm.proxy.proxy_server import general_settings
     from litellm.proxy.utils import get_proxy_base_url, get_server_root_path
 
@@ -28,7 +28,7 @@ async def get_ui_config():
         or general_settings.get("hide_default_credentials_hint", False) is True
     )
 
-    sso_configured: Final = _has_user_setup_sso()
+    sso_configured: Final = has_user_setup_sso()
 
     from litellm.proxy.proxy_server import proxy_config
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py b/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
index 3716d00774f..2c27531cea1 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
@@ -162,10 +162,10 @@ class AktoGuardrail(CustomGuardrail):
     def build_request_body(
         inputs: GenericGuardrailAPIInputs,
         request_data: dict | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the LLM request body from guardrail inputs (messages, model, tools)."""
         model: Final = inputs.get("model", "") or ""
-        body: Final[dict[str, Any]] = {"model": model}
+        body: Final[dict[str, object]] = {"model": model}
 
         structured: Final = inputs.get("structured_messages")
         if structured:
@@ -194,7 +194,7 @@ class AktoGuardrail(CustomGuardrail):
     def build_response_body(
         inputs: GenericGuardrailAPIInputs,
         request_data: dict | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the LLM response body, preferring the actual model response if available."""
         model_response: Final = request_data.get("response") if request_data else None
         if model_response is not None and hasattr(model_response, "model_dump"):
@@ -224,7 +224,7 @@ class AktoGuardrail(CustomGuardrail):
         *,
         status_code: int = 200,
         include_response: bool = False,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the flat MIRRORING payload sent to Akto's HTTP proxy endpoint.
 
         All body fields use double-encoding: json.dumps({"body": json.dumps(actual_body)})
diff --git a/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py
new file mode 100644
index 00000000000..75ea16f7a88
--- /dev/null
+++ b/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py
@@ -0,0 +1,34 @@
+from typing import TYPE_CHECKING, Final
+
+from litellm.types.guardrails import SupportedGuardrailIntegrations
+
+from .alice import AliceGuardrail
+
+if TYPE_CHECKING:
+    from litellm.types.guardrails import Guardrail, LitellmParams
+
+
+def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail"):
+    import litellm
+
+    _alice_guardrail_callback: Final = AliceGuardrail(
+        api_key=litellm_params.api_key,
+        api_base=litellm_params.api_base,
+        unreachable_fallback=getattr(litellm_params, "unreachable_fallback", "fail_closed"),
+        guardrail_name=guardrail.get("guardrail_name", ""),
+        event_hook=litellm_params.mode,
+        default_on=litellm_params.default_on,
+    )
+
+    litellm.logging_callback_manager.add_litellm_callback(_alice_guardrail_callback)
+    return _alice_guardrail_callback
+
+
+guardrail_initializer_registry: Final = {  # mutable-ok: module-level registry, built once and never mutated
+    SupportedGuardrailIntegrations.ALICE.value: initialize_guardrail,
+}
+
+
+guardrail_class_registry: Final = {  # mutable-ok: module-level registry, built once and never mutated
+    SupportedGuardrailIntegrations.ALICE.value: AliceGuardrail,
+}
diff --git a/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py b/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py
new file mode 100644
index 00000000000..9cabac2d0fa
--- /dev/null
+++ b/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py
@@ -0,0 +1,369 @@
+# +-------------------------------------------------------------+
+#
+#                    Use Alice for your LLM calls
+#                         https://alice.io/
+#
+# +-------------------------------------------------------------+
+
+import json
+import os
+from collections.abc import Mapping
+from itertools import islice
+from typing import (
+    TYPE_CHECKING,
+    Any,  # noqa: TID251  # **kwargs forwards verbatim to CustomGuardrail.__init__; see ruff-strict.toml
+    Final,
+    Literal,
+    Optional,
+)
+
+import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
+from litellm._logging import verbose_proxy_logger
+from litellm.exceptions import GuardrailRaisedException, Timeout
+from litellm.integrations.custom_guardrail import (
+    CustomGuardrail,
+    log_guardrail_information,
+)
+from litellm.llms.custom_httpx.http_handler import (
+    get_async_httpx_client,
+    httpxSpecialProvider,
+)
+from litellm.types.guardrails import GuardrailEventHooks
+from litellm.types.utils import GenericGuardrailAPIInputs
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+GUARDRAIL_NAME: Final = "alice"
+
+_DEFAULT_API_BASE: Final = "https://api.alice.io"
+_EVALUATE_PATH: Final = "/v2/evaluate/litellm"
+
+_VERDICT_ALLOW: Final = "ALLOW"
+_VERDICT_BLOCK: Final = "BLOCK"
+_VERDICT_MASK: Final = "MASK"
+_VERDICT_DETECT: Final = "DETECT"
+_KNOWN_VERDICTS: Final = frozenset({_VERDICT_ALLOW, _VERDICT_BLOCK, _VERDICT_MASK, _VERDICT_DETECT})
+
+_DEFAULT_BLOCK_MESSAGE: Final = "Blocked by your organization's content policy."
+
+# apply_guardrail selects nothing: it forwards whichever of these came populated and lets Alice
+# decide what is worth evaluating. Only skip the call when every one of them is empty — there is
+# then genuinely nothing to send.
+_SELECTABLE_INPUT_FIELDS: Final = ("texts", "images", "tools", "tool_calls", "structured_messages")
+
+# Caps on the outbound copy of request_data. A payload deeper or wider than this is malformed
+# rather than large, and serializing it would cost more than the evaluation it feeds.
+_MAX_DEPTH: Final = 12
+_MAX_ITEMS: Final = 5000
+
+# request_data carries the caller's raw credentials under these keys, at any nesting depth —
+# a real captured payload puts inbound headers at request_data["proxy_server_request"]["headers"],
+# again under ["metadata"]["headers"] / ["litellm_metadata"]["headers"], and again under
+# ["metadata"]["requester_metadata"]["headers"], any of which can carry an Authorization or
+# x-api-key value. LiteLLM's own spend-log sanitizer excludes `secret_fields` for the same reason
+# (spend_tracking_utils._SENSITIVE_REQUEST_BODY_KEYS): `secret_fields.raw_headers` holds the
+# caller's Authorization / x-api-key in the clear, and `api_key` can carry a forwarded provider
+# credential. Stripping by key name rather than by path means a new nesting path can never
+# reintroduce the leak. Posting any of these to a third-party guardrail endpoint would be worse
+# than what the proxy already refuses to persist in its own audit trail — so none of them leave
+# the process.
+_CREDENTIAL_KEYS_TO_STRIP: Final = frozenset(
+    {"secret_fields", "api_key", "raw_headers", "headers", "provider_specific_header"}
+)
+
+
+class AliceReplacement(TypedDict):
+    """A masked substitution, positional against the texts that were submitted."""
+
+    index: ReadOnly[NotRequired[int]]
+    text: ReadOnly[NotRequired[str]]
+
+
+class AliceVerdict(TypedDict):
+    """Body returned by Alice's LiteLLM evaluate endpoint."""
+
+    verdict: ReadOnly[NotRequired[str]]
+    categories: ReadOnly[NotRequired["tuple[str, ...]"]]
+    correlation_id: ReadOnly[NotRequired[str]]
+    message: ReadOnly[NotRequired[str]]
+    replacements: ReadOnly[NotRequired["tuple[AliceReplacement, ...]"]]
+
+
+class AliceGuardrailMissingSecrets(Exception):
+    """Raised when the Alice API key is not configured."""
+
+
+class AliceGuardrail(CustomGuardrail):
+    """
+    Alice — policy-based guardrails for prompts and model responses.
+
+    This forwards the hook's arguments as it received them and enforces the verdict that comes
+    back, with one deliberate exception: any key named `secret_fields`, `api_key`, `raw_headers`,
+    `headers`, or `provider_specific_header` is dropped from `request_data` at any nesting depth
+    before it is serialized, and never reaches Alice. Short of that, it selects nothing and
+    renames nothing: which parts of a conversation are worth evaluating, and how a verdict is
+    reached, are decided by Alice — so changing either is a change on their side rather than a
+    LiteLLM upgrade. A batch with nothing selectable at all (no `texts`, `images`, `tools`,
+    `tool_calls`, or `structured_messages`) still skips the call, since there would be nothing to
+    send.
+
+    Known limitation: the unified guardrail's `streaming_transform_mode` defaults to
+    `block_only`, whose streaming path discards any returned text rewrite. A MASK verdict is
+    therefore a no-op on a streamed response — the original, unmasked text still reaches the
+    caller — while BLOCK continues to function on both streamed and non-streamed responses.
+    This is `during_call`'s documented behavior generally, not specific to Alice; configure a
+    masking-aware `streaming_transform_mode` if that gap matters for your traffic.
+
+    Alice evaluates against policies configured per *application*, and one proxy typically fronts
+    several, so the application is named on the virtual key rather than in this config:
+
+        curl $PROXY/key/generate -H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
+          -d '{"key_alias": "payments-bot",
+               "metadata": {"alice_app_id": "payments-bot"}}'
+
+    Alice reads that off the authenticated key. Because the proxy strips caller-supplied
+    `user_api_key_*` from the request before a guardrail sees it, a caller cannot point its own
+    traffic at an application with laxer policies than the one its key was issued for.
+
+    Configuration example (litellm config YAML):
+        guardrails:
+          - guardrail_name: alice
+            litellm_params:
+              guardrail: alice
+              mode: [pre_call, post_call]
+              api_key: os.environ/ALICE_API_KEY
+              api_base: https://api.alice.io          # optional
+              unreachable_fallback: fail_closed       # optional
+    """
+
+    def __init__(
+        self,
+        api_key: str | None = None,
+        api_base: str | None = None,
+        unreachable_fallback: Literal["fail_closed", "fail_open"] = "fail_closed",
+        **kwargs: Any,  # kwargs-ok: forwarded verbatim to CustomGuardrail.__init__, whose param list is wide and evolving
+    ) -> None:
+        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+
+        alice_api_key: Final = api_key or os.environ.get("ALICE_API_KEY")
+        if not alice_api_key:
+            raise AliceGuardrailMissingSecrets(
+                "Alice API key is required. Set the `ALICE_API_KEY` environment variable or "
+                "pass `api_key` in the guardrail config."
+            )
+        self.alice_api_key: str = alice_api_key
+
+        base: Final = (api_base or os.environ.get("ALICE_API_BASE") or _DEFAULT_API_BASE).rstrip("/")
+        self.api_base: str = f"{base}{_EVALUATE_PATH}"
+        self.unreachable_fallback: Literal["fail_closed", "fail_open"] = unreachable_fallback
+
+        if "supported_event_hooks" not in kwargs:
+            kwargs["supported_event_hooks"] = [  # mutable-ok: CustomGuardrail.__init__ requires a list here
+                GuardrailEventHooks.pre_call,
+                GuardrailEventHooks.during_call,
+                GuardrailEventHooks.post_call,
+            ]
+
+        super().__init__(**kwargs)
+
+    @log_guardrail_information
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict[str, object],  # mutable-ok: overrides CustomGuardrail.apply_guardrail's plain-dict contract
+        input_type: Literal["request", "response"],
+        logging_obj: Optional["LiteLLMLoggingObj"] = None,
+    ) -> GenericGuardrailAPIInputs:
+        if not any(inputs.get(field) for field in _SELECTABLE_INPUT_FIELDS):
+            return inputs
+
+        try:
+            verdict: AliceVerdict = await self._evaluate(
+                inputs=inputs, request_data=request_data, input_type=input_type
+            )
+        except Timeout as e:
+            return self._on_unreachable(e, inputs)
+        except httpx.HTTPStatusError as e:
+            status_code: Final = getattr(getattr(e, "response", None), "status_code", None)
+            # Any 5xx is an outage on Alice's side, not our misconfiguration — route the whole
+            # class through the configured policy. A 4xx (rejected credential, bad request) is
+            # ours to fix and must never fail open, so it is deliberately left to propagate.
+            if isinstance(status_code, int) and 500 <= status_code < 600:
+                return self._on_unreachable(e, inputs)
+            raise
+        except httpx.RequestError as e:
+            return self._on_unreachable(e, inputs)
+        except (json.JSONDecodeError, UnicodeDecodeError, TypeError) as e:
+            # A body that cannot be decoded, cannot be parsed as JSON, or parses to something
+            # other than an object, is as unreachable as a dropped connection: this deployment's
+            # policy decides, not a raw exception. UnicodeDecodeError is named explicitly because
+            # it is a sibling of JSONDecodeError under ValueError, not a subclass of it.
+            return self._on_unreachable(e, inputs)
+
+        return self._enforce(verdict, inputs)
+
+    async def _evaluate(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: Mapping[str, object],
+        input_type: str,
+    ) -> AliceVerdict:
+        response: Final = await self.async_handler.post(
+            url=self.api_base,
+            json={  # mutable-ok: one-shot HTTP request body, never mutated after construction
+                "input_type": input_type,
+                "inputs": _json_safe(inputs),
+                "request_data": _json_safe(request_data, strip_keys=_CREDENTIAL_KEYS_TO_STRIP),
+            },
+            headers={  # mutable-ok: one-shot HTTP headers, never mutated after construction
+                "Content-Type": "application/json",
+                "af-api-key": self.alice_api_key,
+            },
+        )
+        response.raise_for_status()
+        body = response.json()
+        if not isinstance(body, dict):
+            raise TypeError("Alice returned a non-object body")
+        return body
+
+    def _enforce(self, verdict: AliceVerdict, inputs: GenericGuardrailAPIInputs) -> GenericGuardrailAPIInputs:
+        """Act on the verdict. An answer we cannot read is treated as unavailable, never as a pass."""
+        name: Final = verdict.get("verdict")
+        if name not in _KNOWN_VERDICTS:
+            return self._on_unreachable(ValueError(f"unrecognized verdict: {name!r}"), inputs)
+
+        if name == _VERDICT_BLOCK:
+            raise GuardrailRaisedException(
+                guardrail_name=GUARDRAIL_NAME,
+                message=verdict.get("message") or _DEFAULT_BLOCK_MESSAGE,
+                should_wrap_with_default_message=False,
+                blocked_content=True,
+            )
+
+        if name == _VERDICT_DETECT:
+            # Recorded by Alice and allowed through. The correlation id is what ties this request
+            # to that record; the evaluated text itself is never logged.
+            verbose_proxy_logger.warning(
+                "Alice guardrail: detection recorded, request allowed (correlation_id=%s, categories=%s)",
+                verdict.get("correlation_id"),
+                verdict.get("categories"),
+            )
+            return inputs
+
+        if name == _VERDICT_MASK:
+            self._apply_replacements(verdict, inputs)
+
+        return inputs
+
+    def _apply_replacements(self, verdict: AliceVerdict, inputs: GenericGuardrailAPIInputs) -> None:
+        """
+        Write each replacement onto the text it names.
+
+        Only `texts` is touched. The chat translation layer maps a returned `texts` list back onto
+        the request positionally, but takes a different branch entirely when `structured_messages`
+        comes back as a new object — which would drop these edits.
+
+        All-or-nothing: a single out-of-range or malformed replacement blocks the whole verdict
+        rather than being silently skipped, so content Alice meant to replace can never reach the
+        model unmasked alongside content that was replaced.
+        """
+        texts: Final = inputs.get("texts") or []  # mutable-ok: empty-list fallback, replaced wholesale below
+        replacements: Final = verdict.get("replacements") or []  # mutable-ok: empty-list fallback for iteration only
+
+        if not replacements:
+            raise self._mask_rejected(verdict)
+
+        for replacement in replacements:
+            index = replacement.get("index")
+            text = replacement.get("text")
+            if not (isinstance(index, int) and isinstance(text, str) and 0 <= index < len(texts)):
+                raise self._mask_rejected(verdict)
+            texts[index] = text  # mutable-ok: item assignment into the local working copy above
+
+        inputs["texts"] = texts
+
+    def _mask_rejected(self, verdict: AliceVerdict) -> GuardrailRaisedException:
+        """A MASK verdict that cannot be applied in full is refused outright, never partially —
+        see `_apply_replacements`."""
+        return GuardrailRaisedException(
+            guardrail_name=GUARDRAIL_NAME,
+            message=verdict.get("message") or _DEFAULT_BLOCK_MESSAGE,
+            should_wrap_with_default_message=False,
+            blocked_content=True,
+        )
+
+    def _on_unreachable(self, error: Exception, inputs: GenericGuardrailAPIInputs) -> GenericGuardrailAPIInputs:
+        """Apply the configured policy when Alice cannot be reached or cannot be understood."""
+        if self.unreachable_fallback == "fail_open":
+            verbose_proxy_logger.critical(
+                "Alice guardrail unreachable, allowing request per unreachable_fallback: %s",
+                error,
+            )
+            return inputs
+        raise GuardrailRaisedException(
+            guardrail_name=GUARDRAIL_NAME,
+            message="Alice guardrail is unavailable and this request cannot be checked",
+            should_wrap_with_default_message=False,
+        ) from error
+
+    @staticmethod
+    def get_config_model() -> type | None:
+        from litellm.types.proxy.guardrails.guardrail_hooks.alice import (
+            AliceGuardrailConfigModel,
+        )
+
+        return AliceGuardrailConfigModel
+
+
+def _json_safe(
+    value: object,
+    depth: int = 0,
+    seen: frozenset[int] = frozenset(),
+    strip_keys: frozenset[str] = frozenset(),
+) -> object:
+    """
+    Copy `value` into something `json.dumps` accepts, dropping only what cannot cross.
+
+    `request_data` carries live Python objects — an OpenTelemetry span among them — so it cannot
+    be serialized as it stands. What is dropped is decided by a mechanical rule rather than a
+    field list: a list drifts from what the far side needs, a rule cannot. Serializing naively
+    raises, and that error would be read as "guardrail unavailable" on every single request.
+
+    `strip_keys` drops a dict key by name at every depth it appears, not just the root — a caller
+    passes `_CREDENTIAL_KEYS_TO_STRIP` here so a credential nested under any path is caught the
+    same way a top-level one is, without maintaining a list of paths. The source object is never
+    mutated: every branch below builds a new container.
+    """
+    if isinstance(value, (str, int, float, bool)) or value is None:
+        return value
+    if depth >= _MAX_DEPTH or id(value) in seen:
+        return None
+
+    nested: Final = seen | frozenset((id(value),))
+
+    if isinstance(value, dict):
+        return {
+            key: _json_safe(item, depth + 1, nested, strip_keys)
+            for key, item in islice(value.items(), _MAX_ITEMS)
+            if isinstance(key, str) and key not in strip_keys
+        }
+
+    if isinstance(value, (list, tuple, set, frozenset)):
+        return [  # mutable-ok: return value is a one-shot list, discarded by the caller after use
+            _json_safe(item, depth + 1, nested, strip_keys) for item in islice(value, _MAX_ITEMS)
+        ]
+
+    dump: Final = getattr(value, "model_dump", None)
+    if callable(dump):
+        try:
+            return _json_safe(dump(mode="json"), depth + 1, nested, strip_keys)
+        except Exception:  # noqa: BLE001  # a model that will not dump is one we drop
+            return None
+
+    # Everything json.dumps handles natively — str, int, float, bool, None, dict, list — is
+    # caught above, and a dict/list subclass is caught by isinstance. So whatever reaches here
+    # (bytes, datetime, an OpenTelemetry span) cannot cross the wire.
+    return None
diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
index dd76a27c80f..30526d30dc5 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
@@ -18,6 +18,7 @@ import time
 from collections.abc import AsyncGenerator, Mapping, Sequence
 from datetime import datetime, timezone
 from itertools import accumulate, groupby
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, NamedTuple, Optional, cast
 
 import httpx
@@ -30,7 +31,11 @@ from litellm.caching import DualCache
 from litellm.constants import BEDROCK_APPLY_GUARDRAIL_CHUNK_BUDGET_CHARS
 from litellm.exceptions import ModifyResponseException
 from litellm.integrations.custom_guardrail import CustomGuardrail
+from litellm.litellm_core_utils.api_route_to_call_types import get_call_types_for_route
 from litellm.litellm_core_utils.core_helpers import redact_nested_match_and_regex_keys
+from litellm.litellm_core_utils.litellm_logging import (
+    _get_masked_values,  # pyright: ignore[reportPrivateUsage]  # the shared header-masking helper has no public name
+)
 from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import bedrock_guardrail_cost
 from litellm.llms.anthropic.chat.guardrail_translation.handler import AnthropicMessagesHandler
 from litellm.llms.base_llm.guardrail_translation.utils import (
@@ -42,7 +47,7 @@ from litellm.llms.custom_httpx.http_handler import (
     httpxSpecialProvider,
 )
 from litellm.proxy._types import UserAPIKeyAuth
-from litellm.proxy.common_request_processing import _serialize_http_exception_detail
+from litellm.proxy.common_request_processing import serialize_http_exception_detail
 from litellm.proxy.common_utils.sse_keepalive import keepalive_ping_has_fired
 from litellm.proxy.guardrails.anthropic_sse import (
     anthropic_sse_chunks_from_response,
@@ -52,7 +57,12 @@ from litellm.proxy.guardrails.anthropic_sse import (
     model_response_text,
 )
 from litellm.secret_managers.main import get_secret_str
-from litellm.types.guardrails import BedrockChecksConfigModel, GuardrailEventHooks
+from litellm.types.guardrails import (
+    BedrockChecksConfigModel,
+    BedrockGuardrailStreamingParams,
+    GuardrailEventHooks,
+    LitellmParams,
+)
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
 from litellm.types.proxy.guardrails.guardrail_hooks.bedrock_guardrails import (
     BedrockChecksMessage,
@@ -206,6 +216,16 @@ def _redact_assessment_match_fields(assessments: list[dict]) -> list[dict]:
     return redacted if isinstance(redacted, list) else assessments
 
 
+_RESPONSES_API_CALL_TYPES: Final = frozenset({CallTypes.responses, CallTypes.aresponses})
+
+
+def _is_responses_api_route(request_route: str | None) -> bool:
+    if request_route is None:
+        return False
+    call_types: Final = get_call_types_for_route(request_route)
+    return call_types is not None and any(call_type in _RESPONSES_API_CALL_TYPES for call_type in call_types)
+
+
 class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
     # During-call must use async_moderation_hook (not unified apply_guardrail), otherwise
     # OpenAI translation always passes input_type="request" and spend/UI show PRE-CALL.
@@ -221,9 +241,23 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         prompt_attack_threshold: float | None = 0.5,
         pii_confidence_threshold: float | None = 0.5,
         chunk_budget_chars: int = BEDROCK_APPLY_GUARDRAIL_CHUNK_BUDGET_CHARS,
+        streaming_buffer_until_moderated: bool | None = None,
+        streaming_sampling_rate: int | None = None,
+        streaming_end_of_stream_only: bool | None = None,
         **kwargs,
     ):
         self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+        self._set_streaming_params(
+            BedrockGuardrailStreamingParams.from_extras(
+                MappingProxyType(
+                    {
+                        "streaming_buffer_until_moderated": streaming_buffer_until_moderated,
+                        "streaming_sampling_rate": streaming_sampling_rate,
+                        "streaming_end_of_stream_only": streaming_end_of_stream_only,
+                    }
+                )
+            )
+        )
         self.guardrailIdentifier = guardrailIdentifier
         self.guardrailVersion = guardrailVersion
         self.guardrail_provider = "bedrock"
@@ -232,7 +266,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
 
         # Resource-less, detect-only InvokeGuardrailChecks mode. Present `checks`
         # routes the guardrail to InvokeGuardrailChecks; absent => ApplyGuardrail.
-        self.checks: dict[str, Any] | None = self._normalize_checks(checks)
+        self.checks: dict[str, object] | None = self._normalize_checks(checks)
         # Per-check block thresholds; a score >= threshold blocks. None => the
         # check is detect-only (logged, never blocks).
         self.content_filter_threshold = content_filter_threshold
@@ -278,6 +312,18 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
             list(self.checks.keys()) if self.checks else None,
         )
 
+    def _set_streaming_params(self, streaming_params: BedrockGuardrailStreamingParams) -> None:
+        self.streaming_buffer_until_moderated = streaming_params.streaming_buffer_until_moderated
+        self.streaming_sampling_rate = streaming_params.streaming_sampling_rate
+        self.streaming_end_of_stream_only = streaming_params.streaming_end_of_stream_only
+
+    def update_in_memory_litellm_params(self, litellm_params: LitellmParams) -> None:
+        super().update_in_memory_litellm_params(litellm_params)
+        self._set_streaming_params(BedrockGuardrailStreamingParams.from_extras(litellm_params.model_extra))
+
+    def _streams_incrementally(self) -> bool:
+        return not self.streaming_buffer_until_moderated and not self.mask_response_content
+
     @classmethod
     def get_supported_event_hooks(cls) -> list[GuardrailEventHooks]:
         return [
@@ -289,7 +335,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         ]
 
     @staticmethod
-    def _normalize_checks(checks: BedrockChecksConfigModel | Mapping[str, object] | None) -> dict[str, Any] | None:
+    def _normalize_checks(checks: BedrockChecksConfigModel | Mapping[str, object] | None) -> dict[str, object] | None:
         """Normalize the configured `checks` into a plain dict for the API body.
 
         Accepts a pydantic ``BedrockChecksConfigModel`` or a raw dict; drops None /
@@ -340,7 +386,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
 
     def _create_bedrock_output_content_request(
         self,
-        response: Any | ModelResponse,
+        response: object,
         messages: list[AllMessageValues] | None = None,
     ) -> BedrockRequest:
         """
@@ -364,9 +410,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         bedrock_request["content"] = bedrock_request_content
         return bedrock_request
 
-    def _build_response_content_items(
-        self, response: Any | ModelResponse, has_grounding: bool
-    ) -> list[BedrockContentItem]:
+    def _build_response_content_items(self, response: object, has_grounding: bool) -> list[BedrockContentItem]:
         """Build content item(s) from the model response. When the request supplied
         grounding, the response is qualified ``guard_content`` so Bedrock can score it.
         """
@@ -390,7 +434,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         self,
         source: Literal["INPUT", "OUTPUT"],
         messages: list[AllMessageValues] | None = None,
-        response: Any | ModelResponse | None = None,
+        response: object | None = None,
     ) -> BedrockRequest:
         """
         Convert the litellm messages/response to the bedrock request format.
@@ -913,7 +957,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
     async def _apply_guardrail_content_with_chunking(
         self,
         content: Sequence[BedrockContentItem],
-        base_request_data: Mapping[str, Any],
+        base_request_data: Mapping[str, object],
         credentials: "Credentials",
         aws_region_name: str,
         api_key: str | None,
@@ -1051,7 +1095,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
     async def _post_apply_guardrail_content_with_retry(
         self,
         content: Sequence[BedrockContentItem],
-        base_request_data: Mapping[str, Any],
+        base_request_data: Mapping[str, object],
         credentials: "Credentials",
         aws_region_name: str,
         api_key: str | None,
@@ -1101,7 +1145,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
     async def _post_apply_guardrail_content(
         self,
         content: Sequence[BedrockContentItem],
-        base_request_data: Mapping[str, Any],
+        base_request_data: Mapping[str, object],
         credentials: "Credentials",
         aws_region_name: str,
         api_key: str | None,
@@ -1140,11 +1184,12 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
             aws_region_name=aws_region_name,
             api_key=api_key,
         )
+        headers_dict: Final = dict(prepared_request.headers)  # mutable-ok: the masking helper requires a dict
         verbose_proxy_logger.debug(
             "Bedrock AI request body: %s, url %s, headers: %s",
             bedrock_request_data,
             prepared_request.url,
-            prepared_request.headers,
+            _get_masked_values(headers_dict),
         )
 
         httpx_response: Final = await self._sign_and_post(
@@ -1829,7 +1874,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
             return BedrockGuardrailResponse()
 
         credentials, aws_region_name = self._load_credentials()
-        body: Final[dict[str, Any]] = {"messages": checks_messages, "checks": self.checks}
+        body: Final[dict[str, object]] = {"messages": checks_messages, "checks": self.checks}
         api_key: Final[str | None] = request_data.get("api_key") if request_data else None
 
         prepared_request: Final = self._prepare_request(
@@ -2311,7 +2356,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
                 guardrail_name=self.guardrail_name,
             )
 
-        detail: Final[dict[str, Any]] = {
+        detail: Final[dict[str, object]] = {
             "error": "Violated guardrail policy",
             "bedrock_guardrail_response": bedrock_guardrail_output_text,
         }
@@ -2660,6 +2705,39 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         Collect content from the stream and run the bedrock OUTPUT scan
         (post_call only validates the response).
         """
+        if self._streams_incrementally():
+            from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import (
+                UnifiedLLMGuardrails,
+            )
+
+            async for streamed_chunk in UnifiedLLMGuardrails().async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=response,
+                request_data=request_data,
+                guardrail_to_apply=self,
+                buffer_until_moderated_default=False,
+            ):
+                yield streamed_chunk
+            return
+
+        # Responses-API events are neither chat-completions chunks nor raw
+        # Anthropic SSE, so the assembly below cannot scan them; the unified
+        # guardrail's translation layer can, with buffering semantics kept.
+        if _is_responses_api_route(user_api_key_dict.request_route):
+            from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import (
+                UnifiedLLMGuardrails,
+            )
+
+            async for translated_chunk in UnifiedLLMGuardrails().async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=response,
+                request_data=request_data,
+                guardrail_to_apply=self,
+                buffer_until_moderated_default=True,
+            ):
+                yield translated_chunk
+            return
+
         # Import here to avoid circular imports
         from litellm.llms.base_llm.base_model_iterator import MockResponseIterator
         from litellm.main import stream_chunk_builder
@@ -2716,7 +2794,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
                 )
                 if not raw_sse or (not is_block and not headers_flushed):
                     raise
-                block_message, _ = _serialize_http_exception_detail(block_detail)
+                block_message, _ = serialize_http_exception_detail(block_detail)
                 for error_frame in anthropic_sse_error_frames(
                     block_message if is_block else f"{block_exc.status_code}: {block_message}"
                 ):
@@ -2855,7 +2933,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         return updated_messages
 
     def _mask_content_list(
-        self, content_list: list[Any], masked_texts: list[str], masking_index: int
+        self, content_list: Sequence[object], masked_texts: list[str], masking_index: int
     ) -> tuple[list[Any], int]:
         """
         Apply masking to a list of content items.
@@ -2868,7 +2946,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         Returns:
             Updated content list with masked items
         """
-        new_content: Final[list[dict | str]] = []
+        new_content: Final[list[dict[str, object] | str]] = []
         for item in content_list:
             if isinstance(item, dict) and "text" in item:
                 new_item = item.copy()
@@ -2887,7 +2965,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
 
     def _apply_masking_to_response(
         self,
-        response: ModelResponse | Any,
+        response: object,
         bedrock_guardrail_response: BedrockGuardrailResponse,
     ) -> None:
         """
diff --git a/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py b/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py
index 8398ec9f141..5a6be1089b6 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/cisco_ai_defense/cisco_ai_defense_mcp.py
@@ -5,8 +5,9 @@ The public guardrail class imports this private mixin from
 while preserving the existing public import path.
 """
 
+from collections.abc import Sequence
 from datetime import datetime
-from typing import TYPE_CHECKING, Any, Final, Optional
+from typing import TYPE_CHECKING, Final, Optional
 
 from fastapi import HTTPException
 
@@ -23,7 +24,7 @@ if TYPE_CHECKING:
     from .cisco_ai_defense import _ScanContext
 
 
-def _serialize_mcp_content_item(item: object) -> dict[str, Any]:
+def _serialize_mcp_content_item(item: object) -> dict[str, object]:
     """Serialize an MCP content item to a JSON-friendly dict.
 
     Handles raw dicts, MCP SDK Pydantic models, and simple ``.text`` objects.
@@ -57,7 +58,7 @@ class _CiscoAIDefenseMcpMixin:
 
         def should_run_guardrail(self, data: dict, event_type: GuardrailEventHooks) -> bool: ...
 
-        async def _post_inspection(self, url: str, payload: dict[str, Any], surface: str) -> dict[str, Any]: ...
+        async def _post_inspection(self, url: str, payload: dict[str, object], surface: str) -> dict[str, object]: ...
 
         def _handle_api_error(
             self,
@@ -67,16 +68,16 @@ class _CiscoAIDefenseMcpMixin:
             start_time: datetime | None = ...,
             surface: str = ...,
             direction: str = ...,
-        ) -> dict[str, Any]: ...
+        ) -> dict[str, object]: ...
 
         def _finalize_inspection(
             self,
-            inspect_response: dict[str, Any],
+            inspect_response: dict[str, object],
             request_data: dict,
             context: "_ScanContext",
             start_time: datetime,
             response_obj: object = ...,
-        ) -> dict[str, Any]: ...
+        ) -> dict[str, object]: ...
 
     # ------------------------------------------------------------------
     # MCP post-tool hook (dispatcher contract)
@@ -95,7 +96,7 @@ class _CiscoAIDefenseMcpMixin:
         if self.inspection_type != "mcp":
             return None
 
-        request_data: Final[dict[str, Any]] = {}
+        request_data: Final[dict[str, object]] = {}
         for key in (
             "name",
             "litellm_call_id",
@@ -188,9 +189,9 @@ class _CiscoAIDefenseMcpMixin:
 
         original_hidden: Final = getattr(original_response_obj, "hidden_params", None)
         if isinstance(original_hidden, HiddenParams):
-            hidden_params: Any = original_hidden
+            hidden_params: HiddenParams = original_hidden
         else:
-            response_cost: Final = getattr(original_hidden, "response_cost", None)
+            response_cost: Final[float | None] = getattr(original_hidden, "response_cost", None)
             hidden_params = HiddenParams(response_cost=response_cost) if response_cost is not None else HiddenParams()
 
         return MCPPostCallResponseObject(
@@ -200,11 +201,11 @@ class _CiscoAIDefenseMcpMixin:
 
     @staticmethod
     def _replace_mcp_tool_response(response_obj: object, replacement_obj: object) -> bool:
-        replacement: Final = getattr(replacement_obj, "mcp_tool_call_response", None)
+        replacement: Final[list[object] | None] = getattr(replacement_obj, "mcp_tool_call_response", None)
         if replacement is None:
             return False
 
-        inner: Final = getattr(response_obj, "mcp_tool_call_response", None)
+        inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None)
         if inner is not None:
             if _CiscoAIDefenseMcpMixin._replace_mcp_tool_response(inner, replacement_obj):
                 return True
@@ -276,7 +277,7 @@ class _CiscoAIDefenseMcpMixin:
         self,
         data: dict,
         user_api_key_dict: UserAPIKeyAuth,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         del user_api_key_dict  # carried via logging metadata, not the wire payload
         url: Final = f"{self.api_base}{self.inspect_path}"
         payload: Final = self._build_mcp_request_payload(data=data)
@@ -312,7 +313,7 @@ class _CiscoAIDefenseMcpMixin:
         response: object,
         user_api_key_dict: UserAPIKeyAuth | None = None,
         redact_response_obj: object = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         del user_api_key_dict  # carried via logging metadata, not the wire payload
         url: Final = f"{self.api_base}{self.inspect_path}"
         payload: Final = self._build_mcp_response_payload(
@@ -349,7 +350,7 @@ class _CiscoAIDefenseMcpMixin:
     def _build_mcp_request_payload(
         self,
         data: dict,
-    ) -> dict[str, Any] | None:
+    ) -> dict[str, object] | None:
         """Build the JSON-RPC ``tools/call`` envelope sent to ``/inspect/mcp``.
 
         The Cisco AI Defense MCP inspect endpoint expects the JSON-RPC
@@ -390,7 +391,7 @@ class _CiscoAIDefenseMcpMixin:
         self,
         request_data: dict,
         response: object,
-    ) -> dict[str, Any] | None:
+    ) -> dict[str, object] | None:
         """Build the MCP response-inspection body sent to ``/inspect/mcp``."""
         request_payload: Final = self._build_mcp_request_payload(data=request_data)
         if request_payload is None:
@@ -415,7 +416,7 @@ class _CiscoAIDefenseMcpMixin:
         return payload
 
     @staticmethod
-    def _hydrate_mcp_tool_context(request_data: dict[str, Any]) -> None:
+    def _hydrate_mcp_tool_context(request_data: dict[str, object]) -> None:
         metadata = request_data.get("mcp_tool_call_metadata")
         if metadata is None:
             nested: Final = request_data.get("metadata") or request_data.get("litellm_metadata")
@@ -440,7 +441,7 @@ class _CiscoAIDefenseMcpMixin:
             request_data.setdefault("server_name", server_name)
 
     @staticmethod
-    def _normalize_mcp_response(response: object) -> dict[str, Any] | None:
+    def _normalize_mcp_response(response: object) -> dict[str, object] | None:
         """Normalize an MCP tool response into a JSON-RPC envelope.
 
         Handles JSON-RPC dicts, raw content lists, MCP SDK models, and
@@ -502,10 +503,10 @@ class _CiscoAIDefenseMcpMixin:
 
     @staticmethod
     def _build_mcp_result(
-        content: list[Any],
+        content: Sequence[object],
         source: object = None,
-    ) -> dict[str, Any]:
-        result: Final[dict[str, Any]] = {"content": [_serialize_mcp_content_item(item) for item in content]}
+    ) -> dict[str, object]:
+        result: Final[dict[str, object]] = {"content": [_serialize_mcp_content_item(item) for item in content]}
         for key in ("structuredContent", "isError"):
             value = source.get(key) if isinstance(source, dict) else getattr(source, key, None)
             if value is not None and (key != "isError" or isinstance(value, bool)):
@@ -522,7 +523,7 @@ class _CiscoAIDefenseMcpMixin:
         if response_obj is None:
             return False
 
-        inner: Final = getattr(response_obj, "mcp_tool_call_response", None)
+        inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None)
         if inner is not None:
             return _CiscoAIDefenseMcpMixin._set_mcp_tool_response_text(inner, text)
 
@@ -559,7 +560,7 @@ class _CiscoAIDefenseMcpMixin:
                 pass
         elif isinstance(response_obj, dict):
             result: Final = response_obj.get("result")
-            target: Final[dict[Any, Any]] = result if isinstance(result, dict) else response_obj
+            target: Final[dict[object, object]] = result if isinstance(result, dict) else response_obj
             if "structuredContent" in target:
                 target["structuredContent"] = replacement
                 replaced = True
@@ -567,11 +568,11 @@ class _CiscoAIDefenseMcpMixin:
         return replaced
 
     @staticmethod
-    def _coerce_to_content_list(response_obj: object) -> list[Any] | None:
+    def _coerce_to_content_list(response_obj: object) -> list[object] | None:
         """Find the MCP content list inside supported response shapes."""
         if response_obj is None:
             return None
-        inner: Final = getattr(response_obj, "mcp_tool_call_response", None)
+        inner: Final[object | None] = getattr(response_obj, "mcp_tool_call_response", None)
         if inner is not None:
             return _CiscoAIDefenseMcpMixin._coerce_to_content_list(inner)
         content: Final = getattr(response_obj, "content", None)
@@ -594,8 +595,8 @@ class _CiscoAIDefenseMcpMixin:
 
     @staticmethod
     def _extract_sanitized_mcp_arguments(
-        inspect_response: dict[str, Any],
-    ) -> dict[str, Any] | None:
+        inspect_response: dict[str, object],
+    ) -> dict[str, object] | None:
         """Pull sanitized MCP tool-call arguments off the verdict.
 
         Cisco can return them at the top level (``params.arguments``) or
diff --git a/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py b/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py
index 5c14d03f50e..1fc3c06e6bf 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py
@@ -748,7 +748,7 @@ class CompresrGuardrail(CustomGuardrail):
             }
 
         try:
-            raw_response: HttpxResponse | None = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]  # AsyncHTTPHandler.post is untyped
+            raw_response: HttpxResponse = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]  # AsyncHTTPHandler.post is untyped
                 url=url,
                 json=payload,
                 headers=self._request_headers(),
@@ -778,11 +778,11 @@ class CompresrGuardrail(CustomGuardrail):
                 {"detail": str(e)},
             )
             return None
-        if raw_response is None or not 200 <= raw_response.status_code < 300:
+        if not 200 <= raw_response.status_code < 300:
             self._handle_compress_failure(
                 "Compresr compression service returned an error",
                 {
-                    "status_code": getattr(raw_response, "status_code", None),
+                    "status_code": raw_response.status_code,
                     "body": _safe_response_text(raw_response),
                 },
             )
diff --git a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
index 955a868a0d6..48832f8ed5e 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
@@ -2,9 +2,10 @@
 
 import os
 import time
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional
+from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol
 
 from fastapi import HTTPException
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.integrations.custom_guardrail import (
@@ -27,6 +28,33 @@ if TYPE_CHECKING:
 GRAYSWAN_BLOCK_ERROR_MSG: Final = "Blocked by Gray Swan Guardrail"
 
 
+class _GraySwanMonitorResponse(TypedDict):
+    """Body returned by Gray Swan's `/cygnal/monitor` endpoint."""
+
+    violation: ReadOnly[NotRequired[float | None]]
+    violated_rules: ReadOnly[NotRequired[list[object]]]
+    violated_rule_descriptions: ReadOnly[NotRequired[list[object]]]
+    mutation: ReadOnly[NotRequired[bool | None]]
+    ipi: ReadOnly[NotRequired[bool | None]]
+
+
+class _GraySwanMonitorHTTPResponse(Protocol):
+    def raise_for_status(self) -> object: ...
+
+    def json(self) -> _GraySwanMonitorResponse: ...
+
+
+class _GraySwanMonitorHTTPClient(Protocol):
+    async def post(
+        self,
+        *,
+        url: str,
+        headers: dict[str, str],
+        json: dict[str, object],
+        timeout: float,
+    ) -> _GraySwanMonitorHTTPResponse: ...
+
+
 class GraySwanGuardrailMissingSecrets(Exception):
     """Raised when the Gray Swan API key is missing."""
 
@@ -77,7 +105,9 @@ class GraySwanGuardrail(CustomGuardrail):
         guardrail_timeout: float | None = 30.0,
         **kwargs: Any,
     ) -> None:
-        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+        self.async_handler: _GraySwanMonitorHTTPClient = get_async_httpx_client(
+            llm_provider=httpxSpecialProvider.GuardrailCallback
+        )
 
         api_key_value: Final = api_key or os.getenv("GRAYSWAN_API_KEY")
         if not api_key_value:
@@ -266,7 +296,7 @@ class GraySwanGuardrail(CustomGuardrail):
     # Legacy Test Interface (for backward compatibility)
     # ------------------------------------------------------------------
 
-    async def run_grayswan_guardrail(self, payload: dict) -> dict[str, Any]:
+    async def run_grayswan_guardrail(self, payload: dict[str, object]) -> _GraySwanMonitorResponse:
         """
         Run the GraySwan guardrail on a payload.
 
@@ -285,7 +315,7 @@ class GraySwanGuardrail(CustomGuardrail):
 
     def _process_grayswan_response(
         self,
-        response_json: dict,
+        response_json: _GraySwanMonitorResponse,
         data: dict | None = None,
         hook_type: GuardrailEventHooks | None = None,
     ) -> None:
@@ -385,7 +415,7 @@ class GraySwanGuardrail(CustomGuardrail):
     # Core GraySwan API interaction
     # ------------------------------------------------------------------
 
-    async def _call_grayswan_api(self, payload: dict) -> dict[str, Any]:
+    async def _call_grayswan_api(self, payload: dict[str, object]) -> _GraySwanMonitorResponse:
         """Call the GraySwan monitoring API."""
         headers: Final = self._prepare_headers()
 
@@ -406,7 +436,7 @@ class GraySwanGuardrail(CustomGuardrail):
 
     def _process_response_internal(
         self,
-        response_json: dict[str, Any],
+        response_json: _GraySwanMonitorResponse,
         request_data: dict,
         inputs: GenericGuardrailAPIInputs,
         is_output: bool,
@@ -534,8 +564,8 @@ class GraySwanGuardrail(CustomGuardrail):
         dynamic_body: dict,
         request_data: dict,
         logging_obj: Optional["LiteLLMLoggingObj"] = None,
-    ) -> dict[str, Any] | None:
-        payload: Final[dict[str, Any]] = {"messages": messages}
+    ) -> dict[str, object] | None:
+        payload: Final[dict[str, object]] = {"messages": messages}
 
         categories: Final = dynamic_body.get("categories") or self.categories
         if categories:
@@ -563,13 +593,13 @@ class GraySwanGuardrail(CustomGuardrail):
                 {**existing_headers, **inbound_headers} if isinstance(existing_headers, dict) else inbound_headers
             )
         if cleaned_litellm_metadata:
-            sanitized: Final = safe_json_loads(safe_dumps(cleaned_litellm_metadata), default={})
+            sanitized: Final[object] = safe_json_loads(safe_dumps(cleaned_litellm_metadata), default={})
             if isinstance(sanitized, dict) and sanitized:
                 payload["litellm_metadata"] = sanitized
 
         return payload
 
-    def _format_violation_message(self, detection_info: Any, is_output: bool = False) -> str:
+    def _format_violation_message(self, detection_info: object, is_output: bool = False) -> str:
         """
         Format detection info into a user-friendly violation message.
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
index e2d2fffb2df..fc881a60f43 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/headroom/headroom.py
@@ -10,6 +10,7 @@ from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, TypeGuard
 import httpx
 from fastapi import HTTPException
 from httpx import Response as HttpxResponse
+from pydantic import TypeAdapter
 
 import litellm
 from litellm._logging import verbose_proxy_logger
@@ -52,6 +53,10 @@ BYPASS_HEADER: Final = "x-headroom-bypass"
 HEADROOM_RETRIEVE_TOOL_NAME: Final = "headroom_retrieve"
 _HASH_PATTERN: Final = re.compile(r"hash=([a-f0-9]{24})")
 _HASH_CACHE_TTL_SECONDS: Final = 15 * 60
+# Narrows the base class's bare-dict ``request_data`` at the boundary so its
+# untranslated messages can be read with concrete types (values pass through by
+# reference, so this is a shallow top-level reconstruction).
+_REQUEST_DATA_ADAPTER: Final = TypeAdapter(dict[str, object])
 
 
 def _is_str_object_dict(value: object) -> TypeGuard[dict[str, object]]:  # guard-ok: isinstance narrows correctly; predicate is trivially correct  # fmt: skip
@@ -116,16 +121,119 @@ def _restore_content_shapes(
     return restored
 
 
-def _protected_indices(messages: Sequence[Mapping[str, object]]) -> frozenset[int]:
+def _tool_call_name(tool_call: Mapping[str, object]) -> str | None:
+    function: Final = tool_call.get("function")
+    if not _is_str_object_dict(function):
+        return None
+    name: Final = function.get("name")
+    return name if isinstance(name, str) else None
+
+
+def _is_retrieve_tool_name(name: str | None) -> bool:
+    """Match the retrieve tool whether called directly or via the MCP gateway.
+
+    Server-side the tool is ``headroom_retrieve``; exposed through LiteLLM's MCP
+    gateway a client calls it as ``mcp__<server>__headroom_retrieve``.
+    """
+    return name is not None and (
+        name == HEADROOM_RETRIEVE_TOOL_NAME or name.endswith(f"__{HEADROOM_RETRIEVE_TOOL_NAME}")
+    )
+
+
+def _retrieve_call_ids_in_message(message: Mapping[str, object]) -> frozenset[str]:
+    if message.get("role") != "assistant":
+        return frozenset()
+    tool_calls: Final = message.get("tool_calls")
+    if not _is_object_list(tool_calls):
+        return frozenset()
+    return frozenset(
+        str(tool_call["id"])
+        for tool_call in tool_calls
+        if _is_str_object_dict(tool_call) and tool_call.get("id") and _is_retrieve_tool_name(_tool_call_name(tool_call))
+    )
+
+
+def _anthropic_tool_use_retrieve_id(block: object) -> str | None:
+    if not _is_str_object_dict(block) or block.get("type") != "tool_use":
+        return None
+    name: Final = block.get("name")
+    call_id: Final = block.get("id")
+    if isinstance(name, str) and call_id is not None and _is_retrieve_tool_name(name):
+        return str(call_id)
+    return None
+
+
+def _anthropic_retrieve_ids_in_message(message: Mapping[str, object]) -> frozenset[str]:
+    content: Final = message.get("content")
+    if not _is_object_list(content):
+        return frozenset()
+    return frozenset(call_id for block in content if (call_id := _anthropic_tool_use_retrieve_id(block)) is not None)
+
+
+def _raw_retrieve_call_ids(messages: object) -> frozenset[str]:
+    """Retrieve-tool call ids read from the request's own, untranslated messages.
+
+    The guardrail otherwise scans an OpenAI-translated view where a tool name
+    over 64 chars is truncated to ``{prefix}_{hash}``, which drops the
+    ``__headroom_retrieve`` suffix a long ``mcp__<server>__`` prefix pushes past
+    the limit. Tool-call ids are never truncated, so pairing the tool result to
+    an id read from the original request keeps the match intact. Both wire
+    shapes are handled: OpenAI ``tool_calls`` and Anthropic ``tool_use`` blocks.
+    """
+    if not _is_object_list(messages):
+        return frozenset()
+    return frozenset(
+        call_id
+        for message in messages
+        if _is_str_object_dict(message)
+        for call_id in _retrieve_call_ids_in_message(message) | _anthropic_retrieve_ids_in_message(message)
+    )
+
+
+def _retrieval_result_indices(
+    messages: Sequence[Mapping[str, object]], extra_retrieve_call_ids: frozenset[str] = frozenset()
+) -> frozenset[int]:
+    """Indices of tool-result rows that carry ``headroom_retrieve`` output.
+
+    When the retrieve tool is exposed to a client that runs its own tool loop
+    (the LiteLLM MCP gateway path), the client executes the call and sends the
+    recovered original content back as a tool result on the next turn. That
+    content is exactly what a prior compression stubbed, so compressing it again
+    re-derives the identical content hash: a no-op that strands the model on the
+    marker and loops the agent. Hold those rows back so the expansion survives.
+
+    ``extra_retrieve_call_ids`` carries ids recovered from the untruncated
+    request so the pairing survives tool-name truncation (see
+    ``_raw_retrieve_call_ids``).
+    """
+    retrieve_call_ids: Final = extra_retrieve_call_ids | frozenset(
+        call_id for message in messages for call_id in _retrieve_call_ids_in_message(message)
+    )
+    if not retrieve_call_ids:
+        return frozenset()
+    return frozenset(
+        index
+        for index, message in enumerate(messages)
+        if message.get("role") in ("tool", "function") and str(message.get("tool_call_id")) in retrieve_call_ids
+    )
+
+
+def _protected_indices(
+    messages: Sequence[Mapping[str, object]], extra_retrieve_call_ids: frozenset[str] = frozenset()
+) -> frozenset[int]:
     """Indices headroom must not send to the compression service.
 
     ``get_protected_indices`` is litellm's own compression policy: the system
-    rows, the last user row, the last assistant row. It is expanded over whole
+    rows, the last user row, the last assistant row. Rows carrying just-retrieved
+    ``headroom_retrieve`` output are added so re-compression can't collapse them
+    back to the marker they were expanded from. The union is expanded over whole
     tool exchanges the way ``compress()`` expands it, so a protected assistant
     tool call cannot end up answered by a marker standing in for the result the
     model just asked for.
     """
-    protected: Final = frozenset(get_protected_indices(messages))
+    protected: Final = frozenset(get_protected_indices(messages)) | _retrieval_result_indices(
+        messages, extra_retrieve_call_ids
+    )
     return protected | frozenset(
         index
         for group in group_tool_exchanges(messages)
@@ -433,7 +541,7 @@ class HeadroomGuardrail(CustomGuardrail):
             payload["model"] = model
 
         try:
-            raw_response: HttpxResponse | None = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]
+            raw_response: HttpxResponse = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]  # AsyncHTTPHandler.post is untyped
                 url=f"{self.headroom_api_base}/v1/compress",
                 json=payload,
                 headers=self._request_headers(),
@@ -458,16 +566,6 @@ class HeadroomGuardrail(CustomGuardrail):
                 False,
                 {},
             )
-        if raw_response is None:
-            return (
-                self._handle_compress_failure(
-                    messages,
-                    "Headroom compression service returned no response",
-                    {},
-                ),
-                False,
-                {},
-            )
         response: Final[HttpxResponse] = raw_response
 
         if response.status_code != 200:
@@ -580,7 +678,7 @@ class HeadroomGuardrail(CustomGuardrail):
             params["query"] = query
 
         try:
-            raw_response: HttpxResponse | None = await self.async_handler.get(  # pyright: ignore[reportUnknownMemberType]
+            raw_response: HttpxResponse = await self.async_handler.get(  # pyright: ignore[reportUnknownMemberType]  # AsyncHTTPHandler.get is untyped
                 url=f"{self.headroom_api_base}/v1/retrieve/{hash_value}",
                 params=params,
                 headers=self._request_headers(),
@@ -589,7 +687,7 @@ class HeadroomGuardrail(CustomGuardrail):
             verbose_proxy_logger.warning("Headroom: retrieve failed for hash=%s: %s", hash_value, e)
             return f"[Headroom: retrieval failed for hash={hash_value}]"
 
-        if raw_response is None or raw_response.status_code == 404:
+        if raw_response.status_code == 404:
             return f"[Headroom: hash={hash_value} not found or expired]"
 
         if raw_response.status_code != 200:
@@ -644,7 +742,11 @@ class HeadroomGuardrail(CustomGuardrail):
         # /v1/compress grows a field for sending the live turn as the retrieval
         # query without compressing it: query-aware compression reads the newest
         # user message, so it is withheld here at some cost to history ranking.
-        protected_indices: Final = _protected_indices(messages)
+        # request_data is a bare dict on the base signature; narrow it before
+        # reading the untranslated messages so long tool names can be recovered.
+        raw_messages: Final = _REQUEST_DATA_ADAPTER.validate_python(request_data).get("messages")
+        raw_retrieve_call_ids: Final = _raw_retrieve_call_ids(raw_messages)
+        protected_indices: Final = _protected_indices(messages, raw_retrieve_call_ids)
         compressible: Final = [m for i, m in enumerate(messages) if i not in protected_indices]
         if not compressible:
             return inputs
diff --git a/litellm/proxy/guardrails/guardrail_hooks/hiddenlayer/hiddenlayer.py b/litellm/proxy/guardrails/guardrail_hooks/hiddenlayer/hiddenlayer.py
index f7ea1cb632f..68914a1989e 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/hiddenlayer/hiddenlayer.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/hiddenlayer/hiddenlayer.py
@@ -2,7 +2,7 @@ from __future__ import annotations
 
 import os
 from collections.abc import Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypedDict
+from typing import TYPE_CHECKING, Final, Literal, Protocol
 from urllib.parse import urlparse
 from uuid import uuid4
 
@@ -11,7 +11,7 @@ import requests
 from fastapi import HTTPException
 from httpx import HTTPStatusError
 from requests.auth import HTTPBasicAuth
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, TypedDict, Unpack
 
 from litellm._logging import verbose_proxy_logger
 from litellm.integrations.custom_guardrail import (
@@ -40,14 +40,21 @@ if TYPE_CHECKING:
 _AUTH_TIMEOUT_SECONDS: Final[float] = 30.0
 
 
+class _CustomGuardrailOptions(TypedDict, total=False, extra_items=object):
+    """Base-class constructor options carried by this guardrail's forwarded keyword arguments."""
+
+    guardrail_name: ReadOnly[str | None]
+    supported_event_hooks: list[GuardrailEventHooks] | None
+
+
 class _HiddenlayerEvaluation(TypedDict, total=False):
-    action: str
-    threat_level: str
+    action: ReadOnly[str]
+    threat_level: ReadOnly[str]
 
 
 class _HiddenlayerAnalysisEntry(TypedDict, total=False):
-    name: str
-    detected: bool
+    name: ReadOnly[str]
+    detected: ReadOnly[bool]
 
 
 class _HiddenlayerModifiedMessage(TypedDict):
@@ -59,9 +66,9 @@ class _HiddenlayerModifiedSide(TypedDict):
 
 
 class _HiddenlayerResponse(TypedDict, total=False):
-    evaluation: _HiddenlayerEvaluation
-    analysis: Sequence[_HiddenlayerAnalysisEntry]
-    modified_data: Mapping[str, _HiddenlayerModifiedSide]
+    evaluation: ReadOnly[_HiddenlayerEvaluation]
+    analysis: ReadOnly[Sequence[_HiddenlayerAnalysisEntry]]
+    modified_data: ReadOnly[Mapping[str, _HiddenlayerModifiedSide]]
 
 
 class _ProxyServerRequest(TypedDict, total=False):
@@ -149,6 +156,31 @@ def _header_value(headers: Mapping[str, str], key: str, default: str) -> str:
     return headers.get(key, default)
 
 
+def _is_image_part(item: object) -> bool:
+    """Whether a structured-message content part carries an image rather than text."""
+
+    if not isinstance(item, Mapping):
+        return False
+
+    part: Final[Mapping[object, object]] = item
+    return part.get("type") == "image_url"
+
+
+def _scannable_text(content: object) -> str:
+    """Flatten a structured message's content into the single string the v1 detection endpoint takes.
+
+    Image parts are dropped: the endpoint accepts one string, so an image would only reach it as
+    its stringified source (a base64 blob or a URL), which is not text the scanner can evaluate.
+    """
+
+    if not isinstance(content, list):
+        return str(content or "")
+
+    parts: Final[Sequence[object]] = content
+    text_parts: Final = [item for item in parts if not _is_image_part(item)]  # mutable-ok: sent as a list repr
+    return str(text_parts or "")
+
+
 def is_saas(host: str) -> bool:
     """Checks whether the connection is to the SaaS platform"""
 
@@ -194,7 +226,7 @@ class HiddenlayerGuardrail(CustomGuardrail):
         api_key: str | None = None,
         api_base: str | None = None,
         auth_url: str | None = None,
-        **kwargs: Any,
+        **kwargs: Unpack[_CustomGuardrailOptions],
     ) -> None:
         kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks()))
         self.hiddenlayer_client_id = api_id or os.getenv("HIDDENLAYER_CLIENT_ID")
@@ -263,7 +295,7 @@ class HiddenlayerGuardrail(CustomGuardrail):
                     "messages": [
                         {
                             "role": last_msg.get("role", "user"),
-                            "content": str(last_msg.get("content", "")),
+                            "content": _scannable_text(last_msg.get("content")),
                         }
                     ]
                 },
@@ -399,7 +431,7 @@ class HiddenlayerGuardrailV2(CustomGuardrail):
         api_key: str | None = None,
         api_base: str | None = None,
         auth_url: str | None = None,
-        **kwargs: Any,
+        **kwargs: Unpack[_CustomGuardrailOptions],
     ) -> None:
         self.hiddenlayer_client_id = api_id or os.getenv("HIDDENLAYER_CLIENT_ID")
         self.hiddenlayer_client_secret = api_key or os.getenv("HIDDENLAYER_CLIENT_SECRET")
@@ -530,7 +562,7 @@ class HiddenlayerGuardrailV2(CustomGuardrail):
         self,
         payload: _HiddenlayerV2Payload,
         input_type: Literal["request", "response"],
-        hl_headers: dict[str, str],
+        hl_headers: Mapping[str, str],
     ) -> httpx.Response:
         if input_type == "request":
             path = "detection/v2/request-evaluations"
diff --git a/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py b/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
index ea022510309..cf5da27e9ca 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
@@ -8,6 +8,7 @@
 import json
 import os
 import uuid
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict
 
 try:
@@ -128,7 +129,7 @@ class LassoGuardrail(CustomGuardrail):
 
     @staticmethod
     def _extract_tool_call_fields(
-        call: Any,
+        call: object,
     ) -> tuple[str | None, str | None, dict[str, object] | None]:
         """Extract (call_id, name, parsed_input) from a tool call.
 
@@ -476,7 +477,7 @@ class LassoGuardrail(CustomGuardrail):
     def _map_masked_messages_back(
         self,
         original_messages: list[dict[str, Any]],
-        masked_messages: list[dict[str, Any]],
+        masked_messages: Sequence[Mapping[str, object]],
     ) -> list[dict[str, object]]:
         """Map Lasso-format masked messages back onto the original OpenAI-format messages.
 
@@ -638,7 +639,7 @@ class LassoGuardrail(CustomGuardrail):
             },
         )
 
-    def _expand_messages_for_classification(self, messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    def _expand_messages_for_classification(self, messages: list[dict[str, Any]]) -> list[dict[str, object]]:
         """
         Convert raw OpenAI-format messages to Lasso API format with content blocks.
 
@@ -646,7 +647,7 @@ class LassoGuardrail(CustomGuardrail):
         - role=tool messages → developer role + tool_result block
         - plain text messages pass through unchanged
         """
-        expanded: Final[list[dict[str, Any]]] = []
+        expanded: Final[list[dict[str, object]]] = []
         for msg in messages:
             role = msg.get("role", "")
             content = msg.get("content")
@@ -917,7 +918,7 @@ class LassoGuardrail(CustomGuardrail):
     def _apply_masking_to_model_response(
         self,
         model_response: litellm.ModelResponse,
-        masked_messages: list[dict[str, Any]],
+        masked_messages: Sequence[Mapping[str, object]],
     ) -> None:
         """Apply masking to the actual model response when mask=True and masked content is available."""
         # Index masked tool_use blocks by id for O(1) lookup.
diff --git a/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py b/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py
index e2d7c06f7c5..a269ad31a6b 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/mcp_jwt_signer/mcp_jwt_signer.py
@@ -80,7 +80,7 @@ import jwt
 from cryptography.hazmat.primitives import serialization
 from cryptography.hazmat.primitives.asymmetric import rsa
 from cryptography.hazmat.primitives.asymmetric.rsa import RSAPrivateKey, RSAPublicKey
-from typing_extensions import NotRequired, TypedDict
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.caching import DualCache
@@ -89,6 +89,7 @@ from litellm.integrations.custom_guardrail import (
     log_guardrail_information,
 )
 from litellm.proxy._types import UserAPIKeyAuth
+from litellm.types.guardrail_base_init import GuardrailBaseInitKwargs
 from litellm.types.guardrails import GuardrailEventHooks
 from litellm.types.utils import CallTypesLiteral
 
@@ -107,6 +108,19 @@ class _JWTDecodeKwargs(TypedDict):
     issuer: NotRequired[str]
 
 
+class _DebugHeaderClaims(TypedDict, total=False):
+    sub: ReadOnly[object]
+    iss: ReadOnly[object]
+    exp: ReadOnly[object]
+    scope: ReadOnly[str]
+
+
+class _SignedClaimSummary(TypedDict):
+    sub: ReadOnly[object]
+    act: ReadOnly[Mapping[str, object]]
+    exp: ReadOnly[object]
+
+
 # Module-level singleton for the JWKS discovery endpoint to access.
 _mcp_jwt_signer_instance: Optional["MCPJWTSigner"] = None
 
@@ -265,7 +279,8 @@ class MCPJWTSigner(CustomGuardrail):
         **kwargs: Any,
     ) -> None:
         kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks()))
-        super().__init__(**kwargs)
+        base_kwargs: Final[GuardrailBaseInitKwargs] = kwargs
+        super().__init__(**base_kwargs)
 
         # --- Signing key setup ---
         key_material: Final = os.environ.get(self.SIGNING_KEY_ENV)
@@ -677,7 +692,7 @@ class MCPJWTSigner(CustomGuardrail):
         data: dict,
         jwt_claims: Mapping[str, object] | None = None,
         call_type: CallTypesLiteral | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Build JWT claims for the outbound MCP access token.
 
@@ -752,7 +767,7 @@ class MCPJWTSigner(CustomGuardrail):
     # ------------------------------------------------------------------
 
     @staticmethod
-    def _build_debug_header(claims: dict[str, Any], kid: str) -> str:
+    def _build_debug_header(claims: _DebugHeaderClaims, kid: str) -> str:
         """
         Build the x-litellm-mcp-debug header value.
 
@@ -873,16 +888,18 @@ class MCPJWTSigner(CustomGuardrail):
         # FR-9: Debug header
         # ------------------------------------------------------------------
         if self.debug_headers:
-            new_headers["x-litellm-mcp-debug"] = self._build_debug_header(claims, self._kid)
+            debug_claims: Final[_DebugHeaderClaims] = claims
+            new_headers["x-litellm-mcp-debug"] = self._build_debug_header(debug_claims, self._kid)
 
         hook_data["extra_headers"] = new_headers
 
+        logged_claims: Final[_SignedClaimSummary] = claims
         verbose_proxy_logger.debug(
             "MCPJWTSigner: signed JWT sub=%s act=%s tool=%s exp=%d verified=%s channel=%s call_type=%s",
-            claims.get("sub"),
-            claims.get("act", {}).get("sub"),
+            logged_claims.get("sub"),
+            logged_claims.get("act", {}).get("sub"),
             hook_data.get("mcp_tool_name"),
-            claims["exp"],
+            logged_claims["exp"],
             jwt_claims is not None,
             bool(self.channel_token_audience),
             call_type,
diff --git a/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py b/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py
index e9cd6addef8..292f395053b 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/noma/noma_v2.py
@@ -7,8 +7,9 @@
 import enum
 import json
 import os
+from collections.abc import Callable, Mapping
 from datetime import datetime
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, cast
+from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypeAlias, cast
 from urllib.parse import urlparse
 
 from litellm._logging import verbose_proxy_logger
@@ -23,6 +24,7 @@ from litellm.llms.custom_httpx.http_handler import (
     httpxSpecialProvider,
 )
 from litellm.proxy.guardrails.guardrail_hooks.noma.noma import NomaBlockedMessage
+from litellm.types.guardrail_base_init import GuardrailBaseInitKwargs
 from litellm.types.guardrails import GuardrailEventHooks
 from litellm.types.utils import GenericGuardrailAPIInputs, GuardrailStatus
 
@@ -36,6 +38,8 @@ _AIDR_SCAN_ENDPOINT: Final = "/litellm/guardrail"
 _INTERVENED_INPUT_FIELDS: Final = ("texts", "images", "tools", "tool_calls")
 _DEFAULT_API_BASE_HOSTNAME: Final = urlparse(_DEFAULT_API_BASE).hostname
 
+_GuardrailJsonResponse: TypeAlias = Exception | str | dict[str, object]
+
 _KEYS_DUPLICATING_SCAN_INPUTS: Final = ("messages", "input")
 _LOGGING_KEYS_DUPLICATING_SCAN_INPUTS: Final = _KEYS_DUPLICATING_SCAN_INPUTS + (
     "additional_args",
@@ -80,7 +84,8 @@ class NomaV2Guardrail(CustomGuardrail):
 
         kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks()))
 
-        super().__init__(**kwargs)
+        base_kwargs: Final[GuardrailBaseInitKwargs] = kwargs
+        super().__init__(**base_kwargs)
 
     @staticmethod
     def get_config_model() -> type["GuardrailConfigModel"] | None:
@@ -111,7 +116,7 @@ class NomaV2Guardrail(CustomGuardrail):
         return parsed.hostname == _DEFAULT_API_BASE_HOSTNAME
 
     @staticmethod
-    def _get_non_empty_str(value: Any) -> str | None:
+    def _get_non_empty_str(value: object) -> str | None:
         if not isinstance(value, str):
             return None
         stripped: Final = value.strip()
@@ -119,7 +124,7 @@ class NomaV2Guardrail(CustomGuardrail):
 
     def _resolve_action_from_response(
         self,
-        response_json: dict,
+        response_json: Mapping[str, object],
     ) -> _Action:
         action: Final = response_json.get("action")
         if isinstance(action, str):
@@ -153,7 +158,7 @@ class NomaV2Guardrail(CustomGuardrail):
                 else model_call_details
             )
 
-        payload: Final[dict[str, Any]] = {
+        payload: Final[dict[str, object]] = {
             "inputs": inputs,
             "request_data": payload_request_data,
             "input_type": input_type,
@@ -165,10 +170,11 @@ class NomaV2Guardrail(CustomGuardrail):
 
     @staticmethod
     def _sanitize_payload_for_transport(payload: dict) -> dict:
-        def _default(obj: Any) -> Any:
-            if hasattr(obj, "model_dump"):
+        def _default(obj: object) -> object:
+            model_dump: Final[Callable[[], Mapping[str, object]] | None] = getattr(obj, "model_dump", None)
+            if model_dump is not None:
                 try:
-                    return obj.model_dump()
+                    return model_dump()
                 except Exception:
                     pass
             return str(obj)
@@ -178,7 +184,7 @@ class NomaV2Guardrail(CustomGuardrail):
         except (ValueError, TypeError):
             json_str = safe_dumps(payload)
 
-        safe_payload: Final = safe_json_loads(json_str, default={})
+        safe_payload: Final[object] = safe_json_loads(json_str, default={})
         if safe_payload == {} and payload:
             verbose_proxy_logger.warning(
                 "Noma v2 guardrail: payload serialization failed, falling back to empty payload"
@@ -196,7 +202,7 @@ class NomaV2Guardrail(CustomGuardrail):
     async def _call_noma_scan(
         self,
         payload: dict,
-    ) -> dict:
+    ) -> dict[str, object]:
         headers: Final[dict[str, str]] = {"Content-Type": "application/json"}
         authorization_header: Final = self._get_authorization_header()
         if authorization_header:
@@ -215,7 +221,7 @@ class NomaV2Guardrail(CustomGuardrail):
             response.text,
         )
         response.raise_for_status()
-        response_json: Final = response.json()
+        response_json: Final[dict[str, object]] = response.json()
         verbose_proxy_logger.debug(
             "Noma v2 AIDR response parsed: %s",
             json.dumps(response_json, default=str),
@@ -227,7 +233,7 @@ class NomaV2Guardrail(CustomGuardrail):
         request_data: dict,
         start_time: datetime,
         guardrail_status: GuardrailStatus,
-        guardrail_json_response: Any,
+        guardrail_json_response: _GuardrailJsonResponse,
     ) -> None:
         end_time: Final = datetime.now()
         duration: Final = (end_time - start_time).total_seconds()
@@ -270,11 +276,11 @@ class NomaV2Guardrail(CustomGuardrail):
     ) -> GenericGuardrailAPIInputs:
         start_time: Final = datetime.now()
         guardrail_status: GuardrailStatus = "success"
-        guardrail_json_response: Any = {}
+        guardrail_json_response: _GuardrailJsonResponse = {}
         dynamic_params = self.get_guardrail_dynamic_request_body_params(request_data)
         if not isinstance(dynamic_params, dict):
             dynamic_params = {}
-        response_json: dict | None = None
+        response_json: dict[str, object] | None = None
 
         # Per-request dynamic params can override configured application context.
         application_id = self._get_non_empty_str(dynamic_params.get("application_id"))
@@ -320,8 +326,9 @@ class NomaV2Guardrail(CustomGuardrail):
 
         except NomaBlockedMessage as e:
             guardrail_status = "guardrail_intervened"
+            blocked_detail: Final[dict[str, object]] = {"error": "blocked"}
             guardrail_json_response = (
-                response_json if isinstance(response_json, dict) else getattr(e, "detail", {"error": "blocked"})
+                response_json if isinstance(response_json, dict) else getattr(e, "detail", blocked_detail)
             )
             raise
         except Exception as e:
diff --git a/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py b/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
index 78639ce4fd0..7021d41475b 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
@@ -8,11 +8,12 @@
 # Standard library imports
 import json
 import os
-from typing import TYPE_CHECKING, Any, Final, Literal
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol
 from urllib.parse import quote
 
 # Third-party imports
 from fastapi import HTTPException
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 # LiteLLM imports
 from litellm import DualCache
@@ -42,7 +43,34 @@ if TYPE_CHECKING:
 MAX_PILLAR_HEADER_VALUE_BYTES: Final = 8 * 1024
 
 
-def _encode_json_for_header(data: Any) -> str:
+class _PillarProtectResponse(TypedDict):
+    """Body returned by Pillar's `/api/v1/protect` endpoint."""
+
+    flagged: ReadOnly[NotRequired[bool]]
+    session_id: ReadOnly[NotRequired[str]]
+    scanners: ReadOnly[NotRequired[dict[str, object]]]
+    evidence: ReadOnly[NotRequired[list[object]]]
+    masked_session_messages: ReadOnly[NotRequired[list[object]]]
+
+
+class _PillarProtectHTTPResponse(Protocol):
+    def raise_for_status(self) -> object: ...
+
+    def json(self) -> _PillarProtectResponse: ...
+
+
+class _PillarProtectHTTPClient(Protocol):
+    async def post(
+        self,
+        *,
+        url: str,
+        headers: dict[str, str],
+        json: dict[str, object],
+        timeout: float,
+    ) -> _PillarProtectHTTPResponse: ...
+
+
+def _encode_json_for_header(data: object) -> str:
     """
     JSON-serialize and URL-encode data for safe header transmission.
     """
@@ -50,7 +78,9 @@ def _encode_json_for_header(data: Any) -> str:
     return quote(json_payload, safe="")
 
 
-def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER_VALUE_BYTES) -> tuple[Any, str, bool]:
+def _truncate_evidence_payload(
+    evidence: object, max_bytes: int = MAX_PILLAR_HEADER_VALUE_BYTES
+) -> tuple[object, str, bool]:
     """
     Truncate evidence payload so the encoded header value stays within max_bytes.
 
@@ -66,12 +96,12 @@ def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER
         truncated_value: Final = "[truncated]"
         return truncated_value, _encode_json_for_header(truncated_value), True
 
-    truncated: Final[list[Any]] = []
+    truncated: Final[list[object]] = []
     encoded = _encode_json_for_header(truncated)
     truncated_flag = False
 
     for entry in evidence:
-        working_entry: Any
+        working_entry: object
         if isinstance(entry, dict):
             working_entry = dict(entry)
         else:
@@ -105,7 +135,7 @@ def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER
     return truncated, encoded, truncated_flag
 
 
-def build_pillar_response_headers(metadata_store: dict[str, Any]) -> dict[str, str]:
+def build_pillar_response_headers(metadata_store: dict[str, object]) -> dict[str, str]:
     """
     Create URL-safe Pillar response headers and apply truncation metadata.
     """
@@ -191,7 +221,9 @@ class PillarGuardrail(CustomGuardrail):
             LiteLLM virtual key context (user_id, team_id, key_alias, etc.) is always
             automatically passed as X-LiteLLM-* headers to enable application/user tracking.
         """
-        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+        self.async_handler: _PillarProtectHTTPClient = get_async_httpx_client(
+            llm_provider=httpxSpecialProvider.GuardrailCallback
+        )
         self.api_key = api_key or os.environ.get("PILLAR_API_KEY")
 
         if self.api_key is None:
@@ -686,7 +718,7 @@ class PillarGuardrail(CustomGuardrail):
         )
         return payload
 
-    async def _call_pillar_api(self, headers: dict[str, str], payload: dict[str, Any]) -> dict[str, Any]:
+    async def _call_pillar_api(self, headers: dict[str, str], payload: dict[str, Any]) -> _PillarProtectResponse:
         """
         Call the Pillar API and return the response.
 
@@ -714,7 +746,7 @@ class PillarGuardrail(CustomGuardrail):
         verbose_proxy_logger.debug("Pillar Guardrail: Analysis complete - flagged=%s, session=%s", flagged, session_id)
         return res
 
-    def _process_pillar_response(self, pillar_response: dict[str, Any], original_data: dict) -> None:
+    def _process_pillar_response(self, pillar_response: _PillarProtectResponse, original_data: dict) -> None:
         """
         Process the Pillar API response and handle detections based on configuration.
 
@@ -774,7 +806,7 @@ class PillarGuardrail(CustomGuardrail):
 
         build_pillar_response_headers(metadata_store)
 
-    def _raise_pillar_detection_exception(self, pillar_response: dict[str, Any]) -> None:
+    def _raise_pillar_detection_exception(self, pillar_response: _PillarProtectResponse) -> None:
         """
         Raise an HTTPException for Pillar security detections.
 
@@ -784,7 +816,7 @@ class PillarGuardrail(CustomGuardrail):
         Raises:
             HTTPException: Always raises with security detection details
         """
-        pillar_response_dict: Final = {
+        pillar_response_dict: Final[dict[str, object]] = {
             "session_id": pillar_response.get("session_id"),
         }
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/presidio.py b/litellm/proxy/guardrails/guardrail_hooks/presidio.py
index 8d78393d687..70ea21320ee 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/presidio.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/presidio.py
@@ -11,10 +11,10 @@
 import asyncio
 import json
 import threading
-from collections.abc import AsyncGenerator, Sequence
+from collections.abc import AsyncGenerator, AsyncIterable, Awaitable, Sequence
 from contextlib import asynccontextmanager
 from datetime import datetime
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypedDict, cast
+from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, TypedDict, cast
 
 import aiohttp
 from typing_extensions import NotRequired, ReadOnly
@@ -68,6 +68,14 @@ class _PresidioAnonymizeResponse(TypedDict):
     items: ReadOnly[NotRequired[list[_PresidioAnonymizeItem]]]
 
 
+class _JsonResponse(Protocol):
+    def json(self) -> Awaitable[object]: ...
+
+
+async def _json_body(response: _JsonResponse) -> object:
+    return await response.json()
+
+
 _LoopSemaphores = dict[asyncio.AbstractEventLoop, asyncio.Semaphore]
 
 
@@ -389,7 +397,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
                             f"expected application/json Content-Type but received '{content_type}'; body: '{error_body[:200]}'"
                         )
 
-                    analyze_results: Final = await response.json()
+                    analyze_results: Final = await _json_body(response)
                     verbose_proxy_logger.debug("analyze_results: %s", analyze_results)
 
                 # Handle error responses from Presidio (e.g., {'error': 'No text provided'})
@@ -997,7 +1005,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
         except Exception as e:
             raise e
 
-    def logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]:
+    def logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]:
         from concurrent.futures import ThreadPoolExecutor
 
         def run_in_new_loop():
@@ -1025,7 +1033,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
             # No running event loop, we can safely run in this thread
             return run_in_new_loop()
 
-    async def async_logging_hook(self, kwargs: dict, result: Any, call_type: str) -> tuple[dict, Any]:
+    async def async_logging_hook(self, kwargs: dict, result: object, call_type: str) -> tuple[dict, object]:
         """
         Masks the input and output before logging to langfuse, datadog, etc.
         """
@@ -1092,9 +1100,9 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
                 and not isinstance(result.choices[0], StreamingChoices)
             ):
                 await self._process_response_for_pii(response=result, request_data=kwargs, mode="mask")
-            elif self._is_anthropic_message_response(result):
+            elif isinstance(result, dict) and self._is_anthropic_message_response(result):
                 await self._process_anthropic_response_for_pii(
-                    response=cast(dict, result),  # cast-ok: _is_anthropic_message_response narrows via isinstance
+                    response=result,
                     request_data=kwargs,
                     mode="mask",
                 )
@@ -1321,7 +1329,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
 
     async def _stream_apply_output_masking(
         self,
-        response: Any,
+        response: AsyncIterable[object],
         request_data: dict,
     ) -> AsyncGenerator[ModelResponseStream | bytes, None]:
         """Apply Presidio masking to streaming output (apply_to_output=True path)."""
@@ -1425,7 +1433,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
 
         return "\n".join(result_lines).encode("utf-8")
 
-    def _unmask_responses_api_completed_chunk(self, chunk: Any, pii_tokens: dict[str, str]) -> None:
+    def _unmask_responses_api_completed_chunk(self, chunk: object, pii_tokens: dict[str, str]) -> None:
         """
         Unmask PII tokens in-place for a ``response.completed`` Responses API event.
 
@@ -1434,7 +1442,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
         blocks; text blocks expose a ``.text`` string attribute.  We walk the tree
         and replace every PII token with its original value.
         """
-        response_obj: Final = getattr(chunk, "response", None)
+        response_obj: Final[object] = getattr(chunk, "response", None)
         if response_obj is None:
             return
 
@@ -1450,7 +1458,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
 
     async def _stream_pii_unmasking(
         self,
-        response: Any,
+        response: AsyncIterable[object],
         request_data: dict,
     ) -> AsyncGenerator[ModelResponseStream | bytes, None]:
         """Apply PII unmasking to streaming output (output_parse_pii=True path)."""
@@ -1526,7 +1534,7 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
     async def async_post_call_streaming_iterator_hook(
         self,
         user_api_key_dict: UserAPIKeyAuth,
-        response: Any,
+        response: AsyncIterable[object],
         request_data: dict,
     ) -> AsyncGenerator[ModelResponseStream | bytes, None]:
         """
@@ -1625,6 +1633,8 @@ class _OPTIONAL_PresidioPIIMasking(CustomGuardrail):
         Update the guardrails litellm params in memory
         """
         super().update_in_memory_litellm_params(litellm_params)
+        if self.apply_to_output:
+            self.output_parse_pii = False
         if litellm_params.pii_entities_config:
             self.pii_entities_config = litellm_params.pii_entities_config
         if litellm_params.presidio_score_thresholds:
diff --git a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/__init__.py
index fa1f9f3d36d..0aaba4016cd 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/__init__.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/__init__.py
@@ -20,6 +20,7 @@ def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail"
         guardrail_name=guardrail.get("guardrail_name", ""),
         event_hook=litellm_params.mode,
         default_on=litellm_params.default_on,
+        file_sanitization_fail_open=getattr(litellm_params, "file_sanitization_fail_open", None),
     )
     litellm.logging_callback_manager.add_litellm_callback(_prompt_security_callback)
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py
index 809d5e0fb31..84c4f118b00 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py
@@ -4,10 +4,12 @@ import os
 from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Final, Literal, Optional
 
+import httpx
 from fastapi import HTTPException
 from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
+from litellm.exceptions import Timeout as LiteLLMTimeout
 from litellm.integrations.custom_guardrail import (
     CustomGuardrail,
     log_guardrail_information,
@@ -24,6 +26,9 @@ if TYPE_CHECKING:
     from litellm.types.proxy.guardrails.guardrail_hooks.base import GuardrailConfigModel
 
 
+_SANITIZE_FILE_FAIL_OPEN_TIMEOUT_SECONDS: Final = 30.0
+
+
 class PromptSecurityGuardrailMissingSecrets(Exception):
     pass
 
@@ -63,6 +68,13 @@ class _SanitizeStatusResponse(TypedDict, total=False):
     metadata: ReadOnly[_SanitizeMetadata]
 
 
+class _SanitizeResult(TypedDict):
+    action: ReadOnly[str]
+    content: ReadOnly[str | None]
+    metadata: ReadOnly[_SanitizeMetadata]
+    violations: ReadOnly[Sequence[str]]
+
+
 class PromptSecurityGuardrail(CustomGuardrail):
     @classmethod
     def get_supported_event_hooks(cls) -> list[GuardrailEventHooks]:
@@ -79,6 +91,8 @@ class PromptSecurityGuardrail(CustomGuardrail):
         user: str | None = None,
         system_prompt: str | None = None,
         check_tool_results: bool | None = None,
+        file_sanitization_timeout: float = _SANITIZE_FILE_FAIL_OPEN_TIMEOUT_SECONDS,
+        file_sanitization_fail_open: bool | None = None,
         **kwargs,
     ):
         kwargs.setdefault("supported_event_hooks", list(self.get_supported_event_hooks()))
@@ -108,6 +122,8 @@ class PromptSecurityGuardrail(CustomGuardrail):
         # Configuration for file sanitization
         self.max_poll_attempts = 30  # Maximum number of polling attempts
         self.poll_interval = 2  # Seconds between polling attempts
+        self.file_sanitization_timeout = file_sanitization_timeout
+        self.file_sanitization_fail_open = file_sanitization_fail_open is not False
 
         super().__init__(**kwargs)
 
@@ -397,6 +413,39 @@ class PromptSecurityGuardrail(CustomGuardrail):
         Sanitize file content using Prompt Security API.
         Returns: dict with keys 'action', 'content', 'metadata'
         """
+        try:
+            return await asyncio.wait_for(
+                self._sanitize_file_content(file_data, filename, user_api_key_alias),
+                timeout=self.file_sanitization_timeout,
+            )
+        except (asyncio.TimeoutError, httpx.TimeoutException, LiteLLMTimeout) as exc:
+            if not self.file_sanitization_fail_open:
+                verbose_proxy_logger.error(
+                    "Prompt Security Guardrail: file sanitization for %s timed out with %s; failing closed",
+                    filename,
+                    type(exc).__name__,
+                )
+                raise HTTPException(status_code=408, detail="File sanitization timeout") from exc
+
+            verbose_proxy_logger.error(
+                "Prompt Security Guardrail: file sanitization for %s timed out with %s; failing open",
+                filename,
+                type(exc).__name__,
+            )
+            fail_open_result: Final[_SanitizeResult] = {
+                "action": "allow",
+                "content": None,
+                "metadata": {},
+                "violations": (),
+            }
+            return fail_open_result
+
+    async def _sanitize_file_content(
+        self,
+        file_data: bytes,
+        filename: str,
+        user_api_key_alias: str | None,
+    ) -> _SanitizeResult:
         headers: Final = {"APP-ID": self.api_key}
         if user_api_key_alias:
             headers["X-LiteLLM-Key-Alias"] = user_api_key_alias
diff --git a/litellm/proxy/guardrails/guardrail_hooks/repelloai/repelloai.py b/litellm/proxy/guardrails/guardrail_hooks/repelloai/repelloai.py
index 5f73a169215..8925cc5b3a6 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/repelloai/repelloai.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/repelloai/repelloai.py
@@ -197,14 +197,11 @@ class RepelloAIGuardrail(CustomGuardrail):
         repelloai_response: RepelloAIAnalyzeResponse | None = None
         try:
             verbose_proxy_logger.debug("RepelloAI Argus request: %s", request)
-            raw_response: HttpxResponse | None = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]
+            response: Final[HttpxResponse] = await self.async_handler.post(  # pyright: ignore[reportUnknownMemberType]  # AsyncHTTPHandler.post is untyped
                 url=endpoint,
                 headers={"X-API-Key": self.repelloai_api_key},
                 json=request,
             )
-            if raw_response is None:
-                raise ValueError("RepelloAI Argus returned no response")
-            response: Final[HttpxResponse] = raw_response
             self._raise_for_config_error(response)
             response.raise_for_status()
             try:
diff --git a/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py b/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
index e34beec4d3e..2fbd50b5863 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
@@ -6,7 +6,7 @@ via embedding similarity. Smarter than regex (understands intent), lighter
 than an LLM call (~20-50ms per request for embedding).
 """
 
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_guardrail import (
@@ -50,7 +50,7 @@ class SemanticGuardrail(CustomGuardrail):
         similarity_threshold: float,
         route_templates: list[str] | None = None,
         custom_routes_file: str | None = None,
-        custom_routes: list[dict[str, Any]] | None = None,
+        custom_routes: list[dict[str, object]] | None = None,
         on_flagged_action: str = "block",
         event_hook: GuardrailEventHooks | list[GuardrailEventHooks] | Mode | None = None,
         default_on: bool = False,
@@ -157,7 +157,14 @@ class SemanticGuardrail(CustomGuardrail):
         return response
 
 
-def _get_top_route_choice(result: Any) -> Any:
+class _RouteChoice(Protocol):
+    """The semantic-router match this guardrail reads: the route that fired, if any."""
+
+    @property
+    def name(self) -> str | None: ...
+
+
+def _get_top_route_choice(result: _RouteChoice | list[_RouteChoice] | None) -> _RouteChoice | None:
     """Extract the top RouteChoice from SemanticRouter result.
 
     SemanticRouter.__call__ can return RouteChoice or List[RouteChoice].
@@ -194,7 +201,7 @@ def _extract_response_text(response: Any) -> str:
     return ""
 
 
-def _content_to_text(content: Any) -> str:
+def _content_to_text(content: object) -> str:
     if isinstance(content, str):
         return content
     if isinstance(content, list):
diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
index 3c5625bc272..a8b33109900 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
@@ -1,9 +1,10 @@
 import json
 import re
 from collections.abc import AsyncGenerator, AsyncIterable, Mapping, Sequence
-from typing import Any, Final, Literal
+from typing import Any, Final, Literal, TypedDict
 
 from fastapi import HTTPException
+from typing_extensions import ReadOnly, Required
 
 from litellm import ChatCompletionToolParam
 from litellm._logging import verbose_proxy_logger
@@ -51,6 +52,27 @@ def _object_list(value: object) -> Sequence[object] | None:
     return value if isinstance(value, list) else None
 
 
+class _ToolPermissionRuleFields(TypedDict, total=False):
+    """The config-file shape a :class:`ToolPermissionRule` is built from."""
+
+    id: ReadOnly[Required[str]]
+    tool_name: ReadOnly[str | None]
+    tool_type: ReadOnly[str | None]
+    decision: ReadOnly[Required[Literal["allow", "deny"]]]
+    allowed_param_patterns: ReadOnly[dict[str, str] | None]
+
+
+def _rule_from_fields(fields: _ToolPermissionRuleFields) -> ToolPermissionRule:
+    """Validate one config-file rule entry into a :class:`ToolPermissionRule`."""
+    return ToolPermissionRule(**fields)
+
+
+def _is_tool_use_block(block: object) -> bool:
+    """Whether ``block`` is an Anthropic ``tool_use`` content block."""
+    fields: Final = _object_mapping(block)
+    return fields is not None and fields.get("type") == "tool_use"
+
+
 class ToolPermissionGuardrail(CustomGuardrail):
     def __init__(
         self,
@@ -101,7 +123,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         compiled_patterns: Final[dict[str, dict[str, re.Pattern]]] = {}
 
         for rule_item in rules or []:
-            rule = rule_item if isinstance(rule_item, ToolPermissionRule) else ToolPermissionRule(**rule_item)
+            rule = rule_item if isinstance(rule_item, ToolPermissionRule) else _rule_from_fields(rule_item)
 
             target_patterns: dict[str, re.Pattern | None] = {
                 "tool_name": None,
@@ -440,7 +462,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         return is_allowed, None, message
 
     @staticmethod
-    def _get_mapping_value(item: Any, key: str) -> Any:
+    def _get_mapping_value(item: object, key: str) -> Any:
         if isinstance(item, dict):
             return item.get(key)
         return getattr(item, key, None)
@@ -450,7 +472,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         return f"legacy_function_call_{choice_index}"
 
     def _legacy_function_call_to_tool_call(
-        self, function_call: Any, choice_index: int
+        self, function_call: object, choice_index: int
     ) -> ChatCompletionMessageToolCall | None:
         if function_call is None:
             return None
@@ -549,7 +571,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
     def _modify_anthropic_content_with_permission_errors(
         self,
         response: object,
-        content: tuple[Any, ...],
+        content: tuple[object, ...],
         denied_tools: tuple[tuple[ChatCompletionMessageToolCall, PermissionError], ...],
     ) -> None:
         if not denied_tools or not isinstance(response, dict):
@@ -557,27 +579,33 @@ class ToolPermissionGuardrail(CustomGuardrail):
 
         verbose_proxy_logger.info("Blocking %s unauthorized tool uses", len(denied_tools))
 
-        error_by_tool_use_id: Final = {  # mutable-ok: read-only lookup, never mutated after construction
+        error_by_tool_use_id: Final[
+            Mapping[object, str]
+        ] = {  # mutable-ok: read-only lookup, never mutated after construction
             tool_call.id: self._create_permission_error_result(tool_call, error).content
             for tool_call, error in denied_tools
         }
-        denied_block_ids: Final = frozenset(error_by_tool_use_id)
 
-        def _is_denied(block: object) -> bool:
-            return isinstance(block, dict) and block.get("type") == "tool_use" and block.get("id") in denied_block_ids
+        def _denied_message(block: object) -> str | None:
+            fields: Final = _object_mapping(block)
+            if fields is None or fields.get("type") != "tool_use":
+                return None
+            return error_by_tool_use_id.get(fields.get("id"))
 
-        error_messages: Final = tuple(error_by_tool_use_id[block["id"]] for block in content if _is_denied(block))
-        kept_blocks: Final = tuple(block for block in content if not _is_denied(block))
+        error_messages: Final = tuple(
+            message for message in (_denied_message(block) for block in content) if message is not None
+        )
+        kept_blocks: Final = tuple(block for block in content if _denied_message(block) is None)
         new_content: Final = [  # mutable-ok: response content is a JSON array on the wire
             *kept_blocks,
             {"type": "text", "text": "\n".join(error_messages)},  # mutable-ok: content block is a JSON object
         ]
 
         response["content"] = new_content  # rebind-ok: the guardrail rewrites the provider response in place
-        if not any(isinstance(block, dict) and block.get("type") == "tool_use" for block in kept_blocks):
+        if not any(_is_tool_use_block(block) for block in kept_blocks):
             response["stop_reason"] = "end_turn"  # rebind-ok: dropping every tool_use ends the turn
 
-    def _get_request_tool_name(self, tool: Any) -> tuple[str | None, str | None]:
+    def _get_request_tool_name(self, tool: object) -> tuple[str | None, str | None]:
         tool_type: Final = self._get_mapping_value(tool, "type")
         if tool_type != "function":
             return None, tool_type
@@ -586,7 +614,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         tool_name: Final = self._get_mapping_value(function, "name")
         return tool_name, tool_type
 
-    def _get_legacy_function_name(self, function: Any) -> str | None:
+    def _get_legacy_function_name(self, function: object) -> str | None:
         return self._get_mapping_value(function, "name")
 
     def _get_named_tool_choice(self, data: dict) -> str | None:
diff --git a/litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py b/litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py
index e95e97bfe74..46b00829b74 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/unified_guardrail/unified_guardrail.py
@@ -57,6 +57,9 @@ class _EndpointTranslation(Protocol):
     @property
     def build_block_sse_chunks(self) -> "Callable[..., Sequence[bytes] | None]": ...
 
+    @property
+    def build_stream_error_items(self) -> "Callable[..., Sequence[object] | None]": ...
+
 
 def _as_endpoint_translation(translation: _EndpointTranslation) -> _EndpointTranslation:
     return translation
@@ -408,14 +411,32 @@ class UnifiedLLMGuardrails(CustomLogger):
         call_type: str | None,
         responses_so_far: Sequence[object],
         request_data: dict,
+        endpoint_translation: _EndpointTranslation | None = None,
+        stream_started: bool = False,
+        responses_yielded: Sequence[object] | None = None,
     ) -> AsyncGenerator[object, None]:
-        """Surface a mid-stream HTTPException. For A2A call types the response has
-        already started, so emit an in-stream JSON-RPC error chunk; otherwise
-        re-raise so the proxy can report it.
+        """Surface a mid-stream HTTPException (a guardrail block with the default
+        exception-on-block config, or a failed scan).
+
+        A2A call types emit an in-stream JSON-RPC error chunk. For other call
+        types, once chunks have already reached the client the HTTP status is
+        gone, so the failure is delegated to the endpoint translation's
+        ``build_stream_error_items`` and travels as an in-stream error frame in
+        that endpoint's wire format. Before the first chunk (or when the format
+        has no in-stream error frame) the exception is re-raised so the proxy
+        can report it with a real HTTP status.
         """
         if call_type is not None and CallTypes(call_type) in A2A_CALL_TYPES:
             yield _a2a_jsonrpc_error_chunk(exc, _get_a2a_request_id(responses_so_far, request_data))
             return
+        if stream_started and endpoint_translation is not None:
+            error_items: Final = endpoint_translation.build_stream_error_items(
+                exc, responses_so_far=tuple(responses_yielded) if responses_yielded is not None else None
+            )
+            if error_items is not None:
+                for error_item in error_items:
+                    yield error_item
+                return
         raise exc
 
     def _build_transform_chunk(
@@ -586,7 +607,15 @@ class UnifiedLLMGuardrails(CustomLogger):
                 yield block_chunk
             raise _StreamTerminated()
         except HTTPException as e:
-            async for error_item in self._emit_streaming_http_error(e, call_type, responses_so_far, request_data):
+            async for error_item in self._emit_streaming_http_error(
+                e,
+                call_type,
+                responses_so_far,
+                request_data,
+                endpoint_translation=endpoint_translation,
+                stream_started=bool(responses_yielded),
+                responses_yielded=responses_yielded,
+            ):
                 yield error_item
             raise _StreamTerminated()
 
@@ -1070,11 +1099,17 @@ class UnifiedLLMGuardrails(CustomLogger):
                     return
                 except HTTPException as e:
                     # Response already started (we already yielded chunks); cannot send 400.
-                    # For A2A, yield an in-stream JSON-RPC error so the client sees it.
-                    if call_type is not None and CallTypes(call_type) in A2A_CALL_TYPES:
-                        yield _a2a_jsonrpc_error_chunk(e, _get_a2a_request_id(responses_so_far, request_data))
-                        return
-                    raise
+                    async for error_item in self._emit_streaming_http_error(
+                        e,
+                        call_type,
+                        responses_so_far,
+                        request_data,
+                        endpoint_translation=endpoint_translation,
+                        stream_started=chunks_yielded,
+                        responses_yielded=responses_yielded,
+                    ):
+                        yield error_item
+                    return
                 chunks_yielded = True
                 responses_yielded.append(original_item)
                 yield original_item
@@ -1133,7 +1168,13 @@ class UnifiedLLMGuardrails(CustomLogger):
                     yield block_chunk
                 return
             except HTTPException as e:
-                if call_type is not None and CallTypes(call_type) in A2A_CALL_TYPES:
-                    yield _a2a_jsonrpc_error_chunk(e, _get_a2a_request_id(responses_so_far, request_data))
-                else:
-                    raise
+                async for error_item in self._emit_streaming_http_error(
+                    e,
+                    call_type,
+                    responses_so_far,
+                    request_data,
+                    endpoint_translation=endpoint_translation,
+                    stream_started=bool(responses_yielded),
+                    responses_yielded=responses_yielded,
+                ):
+                    yield error_item
diff --git a/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py b/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
index 6b8148645aa..a5945a39589 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
@@ -433,7 +433,7 @@ class VigilGuardGuardrail(CustomGuardrail):
         return collected
 
     @staticmethod
-    def _clamp_metadata_value(value: Any) -> _MetadataValue | None:
+    def _clamp_metadata_value(value: object) -> _MetadataValue | None:
         if isinstance(value, bool):
             return None
         if isinstance(value, str):
diff --git a/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py b/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py
index ddb40dc3ca0..831df43692b 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/xecguard/xecguard.py
@@ -310,7 +310,7 @@ class XecGuardGuardrail(CustomGuardrail):
         scan_type: str,
         suppress_errors: bool = False,
     ) -> dict | None:
-        payload: Final[dict[str, Any]] = {
+        payload: Final[dict[str, object]] = {
             "model": self.xecguard_model,
             "scan_type": scan_type,
             "messages": messages,
@@ -385,7 +385,7 @@ class XecGuardGuardrail(CustomGuardrail):
     def _build_full_history(
         self,
         request_data: dict,
-        inputs: Any,
+        inputs: GenericGuardrailAPIInputs,
         input_type: str,
     ) -> list[dict]:
         """Assemble the full message list that will be sent to XecGuard.
diff --git a/litellm/proxy/guardrails/guardrail_initializers.py b/litellm/proxy/guardrails/guardrail_initializers.py
index 47aea62f4c2..16369abbfb0 100644
--- a/litellm/proxy/guardrails/guardrail_initializers.py
+++ b/litellm/proxy/guardrails/guardrail_initializers.py
@@ -2,6 +2,7 @@
 from typing import Any, Final
 
 import litellm
+from litellm.integrations.custom_guardrail import CustomGuardrail
 from litellm.proxy._types import CommonProxyErrors
 from litellm.types.guardrails import *
 
@@ -11,6 +12,7 @@ def initialize_bedrock(litellm_params: LitellmParams, guardrail: Guardrail):
         BedrockGuardrail,
     )
 
+    streaming_params: Final = BedrockGuardrailStreamingParams.from_extras(litellm_params.model_extra)
     _bedrock_callback: Final = BedrockGuardrail(
         guardrail_name=guardrail.get("guardrail_name", ""),
         event_hook=litellm_params.mode,
@@ -38,6 +40,9 @@ def initialize_bedrock(litellm_params: LitellmParams, guardrail: Guardrail):
         aws_bedrock_runtime_endpoint=litellm_params.aws_bedrock_runtime_endpoint,
         experimental_use_latest_role_message_only=litellm_params.experimental_use_latest_role_message_only,
         only_scan_new_messages=litellm_params.only_scan_new_messages or False,
+        streaming_buffer_until_moderated=streaming_params.streaming_buffer_until_moderated,
+        streaming_sampling_rate=streaming_params.streaming_sampling_rate,
+        streaming_end_of_stream_only=streaming_params.streaming_end_of_stream_only,
     )
     litellm.logging_callback_manager.add_litellm_callback(_bedrock_callback)
     return _bedrock_callback
@@ -81,7 +86,7 @@ def initialize_lakera_v2(litellm_params: LitellmParams, guardrail: Guardrail):
     return _lakera_v2_callback
 
 
-def initialize_presidio(litellm_params: LitellmParams, guardrail: Guardrail):
+def initialize_presidio(litellm_params: LitellmParams, guardrail: Guardrail) -> tuple[CustomGuardrail, ...]:
     from litellm.proxy.guardrails.guardrail_hooks.presidio import (
         _OPTIONAL_PresidioPIIMasking,
     )
@@ -90,7 +95,7 @@ def initialize_presidio(litellm_params: LitellmParams, guardrail: Guardrail):
     run_input: Final = filter_scope in ("input", "both")
     run_output: Final = filter_scope in ("output", "both")
 
-    def _make_presidio_callback(**overrides):
+    def _make_presidio_callback(**overrides) -> CustomGuardrail:
         params: Final = dict(
             guardrail_name=guardrail.get("guardrail_name", ""),
             event_hook=litellm_params.mode,
@@ -116,27 +121,27 @@ def initialize_presidio(litellm_params: LitellmParams, guardrail: Guardrail):
         litellm.logging_callback_manager.add_litellm_callback(callback)
         return callback
 
-    primary_callback = None
-
-    if run_input:
-        primary_callback = _make_presidio_callback()
-
-        if litellm_params.output_parse_pii:
-            _make_presidio_callback(
-                output_parse_pii=True,
-                event_hook=GuardrailEventHooks.post_call.value,
-            )
-
-    if run_output:
-        output_callback: Final = _make_presidio_callback(
+    input_callback: Final = _make_presidio_callback() if run_input else None
+    unmask_output_callback: Final = (
+        _make_presidio_callback(
+            output_parse_pii=True,
+            event_hook=GuardrailEventHooks.post_call.value,
+        )
+        if run_input and litellm_params.output_parse_pii
+        else None
+    )
+    mask_output_callback: Final = (
+        _make_presidio_callback(
             apply_to_output=True,
             event_hook=GuardrailEventHooks.post_call.value,
             output_parse_pii=False,
         )
-        if primary_callback is None:
-            primary_callback = output_callback
-
-    return primary_callback
+        if run_output
+        else None
+    )
+    return tuple(
+        callback for callback in (input_callback, unmask_output_callback, mask_output_callback) if callback is not None
+    )
 
 
 def initialize_hide_secrets(litellm_params: LitellmParams, guardrail: Guardrail):
diff --git a/litellm/proxy/guardrails/guardrail_registry.py b/litellm/proxy/guardrails/guardrail_registry.py
index 60873a1eeb1..003576ba555 100644
--- a/litellm/proxy/guardrails/guardrail_registry.py
+++ b/litellm/proxy/guardrails/guardrail_registry.py
@@ -3,10 +3,10 @@
 import asyncio
 import importlib
 import os
-from collections.abc import Callable, Iterator, Mapping
+from collections.abc import Callable, Iterator, Mapping, Sequence
 from datetime import datetime, timezone
 from itertools import chain, count
-from typing import TYPE_CHECKING, Final, Literal, Optional, Protocol
+from typing import TYPE_CHECKING, Final, Literal, Optional, Protocol, TypeAlias, cast
 
 from pydantic import ValidationError
 
@@ -90,6 +90,8 @@ guardrail_initializer_registry: Final = {
 
 CONFIG_GUARDRAIL_ID_NAMESPACE: Final = uuid.UUID("625f63f4-935a-50e5-98b5-fbe77babc74a")
 
+GuardrailCallbacks: TypeAlias = tuple[CustomGuardrail, ...]
+
 guardrail_class_registry: Final[dict[str, type[CustomGuardrail]]] = {
     SupportedGuardrailIntegrations.BEDROCK.value: BedrockGuardrail,
     SupportedGuardrailIntegrations.GRAYSWAN.value: GraySwanGuardrail,
@@ -424,6 +426,41 @@ def _apply_configured_bool_overrides(instance: CustomGuardrail, litellm_params:
         instance.scan_raw_request = bool(litellm_params.scan_raw_request)
 
 
+def _as_callback_tuple(
+    initialized: CustomGuardrail | Sequence[CustomGuardrail] | None,
+) -> GuardrailCallbacks:
+    if initialized is None:
+        return ()
+    if isinstance(initialized, (list, tuple)):
+        return tuple(initialized)
+    return (initialized,)
+
+
+def _configure_callback_scoping(
+    custom_guardrail_callback: CustomGuardrail, guardrail_name: str, litellm_params: LitellmParams
+) -> None:
+    for scoping_param in (
+        "skip_system_message_in_guardrail",
+        "skip_tool_message_in_guardrail",
+        "scan_only_tool_results",
+    ):
+        setattr(custom_guardrail_callback, scoping_param, getattr(litellm_params, scoping_param, None))
+    scan_only_tool_results_enabled: Final = effective_scan_only_tool_results_for_guardrail(custom_guardrail_callback)
+    if scan_only_tool_results_enabled and not custom_guardrail_callback.supports_scan_only_tool_results():
+        raise ValueError(
+            f"Guardrail {guardrail_name}: scan_only_tool_results is enabled, but this "
+            "guardrail's role filtering never scans tool results, so no request content would ever "
+            "be scanned. Remove scan_only_tool_results or the guardrail's role-filtering option."
+        )
+    if scan_only_tool_results_enabled and effective_skip_tool_message_for_guardrail(custom_guardrail_callback):
+        raise ValueError(
+            f"Guardrail {guardrail_name}: scan_only_tool_results and "
+            "skip_tool_message_in_guardrail are enabled together, which excludes every message from "
+            "scanning, so no request content would ever be scanned. Remove one of the two."
+        )
+    _apply_configured_bool_overrides(custom_guardrail_callback, litellm_params)
+
+
 class InMemoryGuardrailHandler:
     """
     Class that handles initializing guardrails and adding them to the CallbackManager
@@ -440,6 +477,8 @@ class InMemoryGuardrailHandler:
         Guardrail id to CustomGuardrail object mapping
         """
 
+        self.guardrail_id_to_sibling_callbacks: dict[str, GuardrailCallbacks] = {}  # mutable-ok: per-id registry
+
         self._sources: dict[str, Literal["db", "config"]] = {}
         """
         Guardrail id to provenance marker. "db" entries are reconciled against
@@ -474,7 +513,6 @@ class InMemoryGuardrailHandler:
             self._sources[guardrail_id] = source
             return self.IN_MEMORY_GUARDRAILS[guardrail_id]
 
-        custom_guardrail_callback: CustomGuardrail | None = None
         litellm_params_data: Final = guardrail["litellm_params"]
         verbose_proxy_logger.debug("litellm_params= %s", litellm_params_data)
 
@@ -498,54 +536,15 @@ class InMemoryGuardrailHandler:
         if guardrail_type is None:
             raise ValueError("guardrail_type is required")
 
-        initializer: Final = guardrail_initializer_registry.get(guardrail_type)
-
-        if initializer:
-            # Try to call with llm_router first, fall back to without if it fails
-            import inspect
-
-            sig: Final = inspect.signature(initializer)
-            if "llm_router" in sig.parameters:
-                custom_guardrail_callback = initializer(
-                    litellm_params,
-                    guardrail,
-                    llm_router,
-                )
-            else:
-                custom_guardrail_callback = initializer(litellm_params, guardrail)
-        elif isinstance(guardrail_type, str) and "." in guardrail_type:
-            custom_guardrail_callback = self.initialize_custom_guardrail(
-                guardrail=guardrail,
-                guardrail_type=guardrail_type,
-                litellm_params=litellm_params,
-                config_file_path=config_file_path,
-            )
-        else:
-            raise ValueError(f"Unsupported guardrail: {guardrail_type}")
-
-        if custom_guardrail_callback is not None:
-            for scoping_param in (
-                "skip_system_message_in_guardrail",
-                "skip_tool_message_in_guardrail",
-                "scan_only_tool_results",
-            ):
-                setattr(custom_guardrail_callback, scoping_param, getattr(litellm_params, scoping_param, None))
-            scan_only_tool_results_enabled: Final = effective_scan_only_tool_results_for_guardrail(
-                custom_guardrail_callback
-            )
-            if scan_only_tool_results_enabled and not custom_guardrail_callback.supports_scan_only_tool_results():
-                raise ValueError(
-                    f"Guardrail {guardrail['guardrail_name']}: scan_only_tool_results is enabled, but this "
-                    "guardrail's role filtering never scans tool results, so no request content would ever "
-                    "be scanned. Remove scan_only_tool_results or the guardrail's role-filtering option."
-                )
-            if scan_only_tool_results_enabled and effective_skip_tool_message_for_guardrail(custom_guardrail_callback):
-                raise ValueError(
-                    f"Guardrail {guardrail['guardrail_name']}: scan_only_tool_results and "
-                    "skip_tool_message_in_guardrail are enabled together, which excludes every message from "
-                    "scanning, so no request content would ever be scanned. Remove one of the two."
-                )
-            _apply_configured_bool_overrides(custom_guardrail_callback, litellm_params)
+        created_callbacks: Final = self._create_callbacks(
+            guardrail=guardrail,
+            guardrail_type=guardrail_type,
+            litellm_params=litellm_params,
+            config_file_path=config_file_path,
+            llm_router=llm_router,
+        )
+        for custom_guardrail_callback in created_callbacks:
+            _configure_callback_scoping(custom_guardrail_callback, guardrail["guardrail_name"], litellm_params)
 
         parsed_guardrail: Final = Guardrail(
             guardrail_id=guardrail.get("guardrail_id"),
@@ -556,11 +555,44 @@ class InMemoryGuardrailHandler:
 
         # store references to the guardrail in memory
         self.IN_MEMORY_GUARDRAILS[guardrail_id] = parsed_guardrail
-        self.guardrail_id_to_custom_guardrail[guardrail_id] = custom_guardrail_callback
+        self.guardrail_id_to_custom_guardrail[guardrail_id] = created_callbacks[0] if created_callbacks else None
+        self.guardrail_id_to_sibling_callbacks[guardrail_id] = created_callbacks[1:]
         self._sources[guardrail_id] = source
 
         return parsed_guardrail
 
+    def _create_callbacks(
+        self,
+        guardrail: Guardrail,
+        guardrail_type: str,
+        litellm_params: LitellmParams,
+        config_file_path: str | None,
+        llm_router: Optional["Router"],
+    ) -> GuardrailCallbacks:
+        initializer: Final = guardrail_initializer_registry.get(guardrail_type)
+        if initializer:
+            import inspect
+
+            sig: Final = inspect.signature(initializer)
+            if "llm_router" in sig.parameters:
+                return _as_callback_tuple(initializer(litellm_params, guardrail, llm_router))
+            return _as_callback_tuple(initializer(litellm_params, guardrail))
+        if isinstance(guardrail_type, str) and "." in guardrail_type:
+            return _as_callback_tuple(
+                self.initialize_custom_guardrail(
+                    guardrail=guardrail,
+                    guardrail_type=guardrail_type,
+                    litellm_params=litellm_params,
+                    config_file_path=config_file_path,
+                )
+            )
+        raise ValueError(f"Unsupported guardrail: {guardrail_type}")
+
+    def _tracked_callbacks(self, guardrail_id: str) -> GuardrailCallbacks:
+        primary: Final = self.guardrail_id_to_custom_guardrail.get(guardrail_id)
+        siblings: Final = self.guardrail_id_to_sibling_callbacks.get(guardrail_id, ())
+        return (() if primary is None else (primary,)) + siblings
+
     def initialize_custom_guardrail(
         self,
         guardrail: Guardrail,
@@ -615,6 +647,31 @@ class InMemoryGuardrailHandler:
 
         return _guardrail_callback
 
+    def update_in_memory_guardrail(
+        self,
+        guardrail_id: str,
+        guardrail: Guardrail,
+        source: Literal["db", "config"] = "db",
+    ) -> None:
+        """
+        Update a guardrail in memory
+
+        - updates the guardrail in memory
+        - updates the guardrail params in litellm.callback_manager
+        """
+        self.IN_MEMORY_GUARDRAILS[guardrail_id] = guardrail
+        self._sources[guardrail_id] = source
+
+        tracked_callbacks: Final = self._tracked_callbacks(guardrail_id)
+        if not tracked_callbacks:
+            return
+        updated_litellm_params: Final = cast(LitellmParams, guardrail.get("litellm_params", {}))
+        tracked_callbacks[0].update_in_memory_litellm_params(litellm_params=updated_litellm_params)
+        for sibling_callback in tracked_callbacks[1:]:
+            sibling_stage = sibling_callback.event_hook
+            sibling_callback.update_in_memory_litellm_params(litellm_params=updated_litellm_params)
+            sibling_callback.event_hook = sibling_stage
+
     def delete_in_memory_guardrail(self, guardrail_id: str) -> None:
         """
         Delete a guardrail in memory and remove from litellm callbacks.
@@ -628,11 +685,11 @@ class InMemoryGuardrailHandler:
         self.IN_MEMORY_GUARDRAILS.pop(guardrail_id, None)
         self._sources.pop(guardrail_id, None)
 
-        custom_guardrail_callback: Final = self.guardrail_id_to_custom_guardrail.pop(guardrail_id, None)
-        if custom_guardrail_callback is None:
-            return
-
-        litellm.logging_callback_manager.remove_callback_from_all_lists(custom_guardrail_callback)
+        tracked_callbacks: Final = self._tracked_callbacks(guardrail_id)
+        self.guardrail_id_to_custom_guardrail.pop(guardrail_id, None)
+        self.guardrail_id_to_sibling_callbacks.pop(guardrail_id, None)
+        for custom_guardrail_callback in tracked_callbacks:
+            litellm.logging_callback_manager.remove_callback_from_all_lists(custom_guardrail_callback)
 
     def list_in_memory_guardrails(self) -> list[Guardrail]:
         """
diff --git a/litellm/proxy/hooks/litellm_skills/main.py b/litellm/proxy/hooks/litellm_skills/main.py
index 569ec32c1a0..9edbc6dbf1c 100644
--- a/litellm/proxy/hooks/litellm_skills/main.py
+++ b/litellm/proxy/hooks/litellm_skills/main.py
@@ -67,6 +67,24 @@ class _ChatMessage(Protocol):
     def tool_calls(self) -> Sequence[_ChatToolCall] | None: ...
 
 
+class _ChatChoice(Protocol):
+    @property
+    def message(self) -> _ChatMessage: ...
+
+    @property
+    def finish_reason(self) -> str | None: ...
+
+
+class _ChatCompletion(Protocol):
+    @property
+    def choices(self) -> Sequence[_ChatChoice]: ...
+
+
+def _first_choice(response: _ChatCompletion) -> _ChatChoice:
+    """The first choice of an OpenAI shaped completion response."""
+    return response.choices[0]
+
+
 class SkillsInjectionHook(CustomLogger):
     """
     Pre/Post-call hook that processes skills from container.skills parameter.
@@ -738,8 +756,9 @@ print('No executable skill module found')
 
         for iteration in range(self.max_iterations):
             # OpenAI format response has choices[0].message
-            assistant_message: _ChatMessage = current_response.choices[0].message
-            stop_reason: str | None = current_response.choices[0].finish_reason
+            choice: _ChatChoice = _first_choice(current_response)
+            assistant_message: _ChatMessage = choice.message
+            stop_reason: str | None = choice.finish_reason
 
             # Build assistant message for conversation history
             assistant_msg_dict: dict[str, object] = {
diff --git a/litellm/proxy/hooks/mcp_semantic_filter/hook.py b/litellm/proxy/hooks/mcp_semantic_filter/hook.py
index 3ce406eef73..8b82842353c 100644
--- a/litellm/proxy/hooks/mcp_semantic_filter/hook.py
+++ b/litellm/proxy/hooks/mcp_semantic_filter/hook.py
@@ -5,10 +5,11 @@ Pre-call hook that filters MCP tools semantically before LLM inference.
 Reduces context window size and improves tool selection accuracy.
 """
 
-from collections.abc import Mapping, Sequence
-from typing import TYPE_CHECKING, Any, Final, Optional
+from collections.abc import Iterable, Mapping, Sequence
+from typing import TYPE_CHECKING, Final, Optional
 
 from fastapi import HTTPException
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.constants import (
@@ -30,6 +31,13 @@ if TYPE_CHECKING:
     from litellm.router import Router
 
 
+class SemanticToolFilterConfig(TypedDict, total=False):
+    enabled: ReadOnly[bool]
+    embedding_model: ReadOnly[str]
+    top_k: ReadOnly[int]
+    similarity_threshold: ReadOnly[float]
+
+
 def _truncate_csv_at_tool_name_boundary(tool_names_csv: str, max_length: int) -> str:
     """Cap a CSV of tool names to max_length, dropping any name that does not fit whole."""
     if len(tool_names_csv) <= max_length:
@@ -68,7 +76,7 @@ class SemanticToolFilterHook(CustomLogger):
             semantic_filter.top_k,
         )
 
-    def _should_expand_mcp_tools(self, tools: list[Any]) -> bool:
+    def _should_expand_mcp_tools(self, tools: Iterable[Mapping[str, object]]) -> bool:
         """
         Check if tools contain MCP references with server_url="litellm_proxy".
 
@@ -82,9 +90,9 @@ class SemanticToolFilterHook(CustomLogger):
 
     async def _expand_mcp_tools(
         self,
-        tools: list[Any],
+        tools: Iterable[Mapping[str, object]],
         user_api_key_dict: "UserAPIKeyAuth",
-    ) -> list[dict[str, Any]]:
+    ) -> list[dict[str, object]]:
         """
         Expand MCP references to actual tool definitions.
 
@@ -111,7 +119,7 @@ class SemanticToolFilterHook(CustomLogger):
         )
 
         # Convert Pydantic models to dicts for compatibility
-        openai_tools_as_dicts: Final = []
+        openai_tools_as_dicts: Final[list[dict[str, object]]] = []
         for tool in openai_tools:
             if hasattr(tool, "model_dump"):
                 tool_dict = tool.model_dump(exclude_none=True)
@@ -141,8 +149,8 @@ class SemanticToolFilterHook(CustomLogger):
     async def _filter_expanded_tools(
         self,
         data: dict,
-        expanded_tools: list[dict[str, Any]],
-    ) -> list[dict[str, Any]]:
+        expanded_tools: list[dict[str, object]],
+    ) -> list[dict[str, object]]:
         """
         Apply the semantic filter to expanded MCP tool definitions.
 
@@ -159,7 +167,7 @@ class SemanticToolFilterHook(CustomLogger):
 
         return await self.filter.filter_tools(query=user_query, available_tools=expanded_tools)
 
-    def _selected_tool_names(self, filtered_tools: list[dict[str, Any]]) -> list[str]:
+    def _selected_tool_names(self, filtered_tools: Sequence[object]) -> list[str]:
         """Names of the semantically selected tools, as produced by the MCP expansion."""
         names: Final = (self.filter._extract_tool_info(tool)[0] for tool in filtered_tools)
         return [name for name in names if name]
@@ -217,10 +225,10 @@ class SemanticToolFilterHook(CustomLogger):
     def _emit_filter_metadata(
         self,
         data: dict,
-        mcp_tools: list[object],
-        filtered_mcp_tools: list[object],
-        native_tools: list[object],
-        filtered_tools: list[object],
+        mcp_tools: Sequence[object],
+        filtered_mcp_tools: Sequence[object],
+        native_tools: Sequence[object],
+        filtered_tools: Sequence[object],
     ) -> None:
         """
         Emit response-header metadata when MCP tools were filtered.
@@ -252,10 +260,10 @@ class SemanticToolFilterHook(CustomLogger):
     def _emit_filter_metadata_safe(
         self,
         data: dict,
-        mcp_tools: list[object],
-        filtered_mcp_tools: list[object],
-        native_tools: list[object],
-        filtered_tools: list[object],
+        mcp_tools: Sequence[object],
+        filtered_mcp_tools: Sequence[object],
+        native_tools: Sequence[object],
+        filtered_tools: Sequence[object],
     ) -> None:
         """
         Emit filter metadata without letting an emission failure abort the
@@ -375,7 +383,7 @@ class SemanticToolFilterHook(CustomLogger):
             )
 
             if mcp_tools:
-                filtered_mcp_tools = await self.filter.filter_tools(
+                filtered_mcp_tools: list[object] = await self.filter.filter_tools(
                     query=user_query,
                     available_tools=mcp_tools,
                 )
@@ -419,9 +427,9 @@ class SemanticToolFilterHook(CustomLogger):
         self,
         data: dict,
         user_api_key_dict: "UserAPIKeyAuth",
-        response: Any,
+        response: object,
         request_headers: dict[str, str] | None = None,
-        litellm_call_info: dict[str, Any] | None = None,
+        litellm_call_info: dict[str, object] | None = None,
     ) -> dict[str, str] | None:
         """Add semantic filter stats and tool names to response headers."""
         from litellm.constants import MAX_MCP_SEMANTIC_FILTER_TOOLS_HEADER_LENGTH
@@ -446,7 +454,7 @@ class SemanticToolFilterHook(CustomLogger):
 
         return headers
 
-    def _get_tool_names_csv(self, tools: list[Any]) -> str:
+    def _get_tool_names_csv(self, tools: Sequence[object]) -> str:
         """Extract tool names and return as CSV string."""
         if not tools:
             return ""
@@ -461,7 +469,7 @@ class SemanticToolFilterHook(CustomLogger):
 
     @staticmethod
     async def initialize_from_config(
-        config: dict[str, Any] | None,
+        config: SemanticToolFilterConfig | None,
         llm_router: Optional["Router"],
     ) -> Optional["SemanticToolFilterHook"]:
         """
diff --git a/litellm/proxy/hooks/model_max_budget_limiter.py b/litellm/proxy/hooks/model_max_budget_limiter.py
index c5d10b2749b..efaaab277a9 100644
--- a/litellm/proxy/hooks/model_max_budget_limiter.py
+++ b/litellm/proxy/hooks/model_max_budget_limiter.py
@@ -1,6 +1,6 @@
 import json
 import time
-from collections.abc import Iterable, Mapping
+from collections.abc import Iterable, Mapping, Sequence
 from dataclasses import dataclass
 from types import MappingProxyType
 from typing import Final
@@ -199,18 +199,10 @@ async def build_model_max_budget_usage(
         )
         for budget_model, budget_config in budgets
     )
-    batched: Final = await cache.async_batch_get_cache(
-        keys=list(spend_keys)  # mutable-ok: async_batch_get_cache annotates keys as list, so one must exist here
-    )
-    # async_batch_get_cache returns None if it fails internally, and its result is
-    # index-aligned with `keys` otherwise. An unusable result reads as a miss,
-    # which is what a never-written counter already reads as.
-    current_spends: Final = (
-        tuple(batched) if isinstance(batched, list) and len(batched) == len(budgets) else (None,) * len(budgets)
-    )
+    current_spends: Final = await _current_window_spends(cache=cache, spend_keys=spend_keys)
     return {
         budget_model: {
-            "current_spend": round(_as_spend(current_spend), 4),
+            "current_spend": round(current_spend, 4),
             "budget_limit": budget_config.max_budget,
             "time_period": budget_config.budget_duration,
         }
@@ -218,6 +210,22 @@ async def build_model_max_budget_usage(
     }
 
 
+async def _current_window_spends(cache: DualCache, spend_keys: Sequence[str]) -> tuple[float, ...]:
+    """Redis holds the window total across replicas; the in-memory copy is one replica's share."""
+    keys: Final = list(spend_keys)  # mutable-ok: both batch readers annotate their key argument as list
+    redis_cache: Final = cache.redis_cache
+    if redis_cache is not None:
+        shared: Final = await redis_cache.async_batch_get_cache(key_list=keys)
+        return tuple(_as_spend(shared.get(key)) for key in keys)
+    # async_batch_get_cache returns None if it fails internally, and its result is
+    # index-aligned with `keys` otherwise. An unusable result reads as a miss,
+    # which is what a never-written counter already reads as.
+    batched: Final = await cache.async_batch_get_cache(keys=keys)
+    if not isinstance(batched, list) or len(batched) != len(keys):
+        return (0.0,) * len(keys)
+    return tuple(_as_spend(current_spend) for current_spend in batched)
+
+
 def _usable_budget_config(raw_budget_config: object) -> BudgetConfig | None:
     try:
         budget_config: Final = BudgetConfig.model_validate(raw_budget_config)
@@ -404,7 +412,10 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting):
         return current_spend + _as_spend(await self._cached_spend(legacy_spend_key))
 
     async def _cached_spend(self, spend_key: str) -> float | None:
-        return await self.dual_cache.async_get_cache(key=spend_key)
+        redis_cache: Final = self.dual_cache.redis_cache
+        if redis_cache is None:
+            return await self.dual_cache.async_get_cache(key=spend_key)
+        return await redis_cache.async_get_cache(key=spend_key)
 
     async def async_filter_deployments(
         self,
diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py
index 1e65da5b867..63129602082 100644
--- a/litellm/proxy/hooks/parallel_request_limiter_v3.py
+++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py
@@ -8,7 +8,7 @@ import asyncio
 import binascii
 import os
 import uuid
-from collections.abc import Callable, Mapping, Sequence, Set
+from collections.abc import Awaitable, Callable, Mapping, Sequence, Set
 from contextvars import ContextVar
 from dataclasses import dataclass, field
 from datetime import datetime
@@ -386,6 +386,12 @@ CacheCounterValues: TypeAlias = Sequence[CacheCounterValue | None]
 ParallelGaugeCacheValue: TypeAlias = dict[str, object] | int | float | str | bytes
 
 
+class _AsyncLuaScript(Protocol):
+    """A Lua script registered against the async Redis client, called with KEYS and ARGV."""
+
+    def __call__(self, *, keys: Sequence[str], args: Sequence[object]) -> Awaitable[list[CacheCounterValue]]: ...
+
+
 class RateLimitDescriptorRateLimitObject(TypedDict, total=False):
     requests_per_unit: int | None
     tokens_per_unit: int | None
@@ -577,6 +583,14 @@ def _parse_output_cap_value(raw_value: object) -> int | None:
 
 
 class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
+    batch_rate_limiter_script: _AsyncLuaScript | None
+    token_increment_script: _AsyncLuaScript | None
+    check_and_increment_by_n_script: _AsyncLuaScript | None
+    window_guarded_token_increment_script: _AsyncLuaScript | None
+    parallel_acquire_script: _AsyncLuaScript | None
+    parallel_release_script: _AsyncLuaScript | None
+    parallel_count_script: _AsyncLuaScript | None
+
     def __init__(
         self,
         internal_usage_cache: InternalUsageCache,
@@ -3855,7 +3869,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
                 expected_window_start = operation.get("expected_window_start")
                 if window_key is None or expected_window_start is None:
                     continue
-                active_window_start = await self.internal_usage_cache.async_get_cache(
+                active_window_start: CacheCounterValue | None = await self.internal_usage_cache.async_get_cache(
                     key=window_key,
                     litellm_parent_otel_span=parent_otel_span,
                     local_only=True,
@@ -4144,7 +4158,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
     def _collect_tpm_scope_targets(
         self,
         standard_logging_metadata: dict[str, Any],
-        kwargs: Any,
+        kwargs: object,
         model_group: str | None,
     ) -> list[tuple[str, str]]:
         """
@@ -4301,8 +4315,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
 
     def _build_success_event_pipeline_operations(
         self,
-        kwargs: Any,
-        response_obj: Any,
+        kwargs: dict[str, Any],
+        response_obj: object,
         rate_limit_type: Literal["output", "input", "total"],
     ) -> list[RedisPipelineIncrementOperation]:
         """Build Redis pipeline increment ops for TPM / parallel-request counters."""
diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py
index f02901f0e97..47aafda2337 100644
--- a/litellm/proxy/hooks/proxy_track_cost_callback.py
+++ b/litellm/proxy/hooks/proxy_track_cost_callback.py
@@ -587,7 +587,7 @@ async def _update_database_and_spend_counters(
     model_access_groups: Sequence[str] | None = None,
 ) -> None:
     try:
-        spend_log_request_id = await proxy_logging_obj.db_spend_update_writer.update_database(
+        await proxy_logging_obj.db_spend_update_writer.update_database(
             token=user_api_key,
             response_cost=response_cost,
             user_id=user_id,
@@ -623,7 +623,6 @@ async def _update_database_and_spend_counters(
             budget_reservation=budget_reservation,
             end_user_id=end_user_id,
             tags=request_tags,
-            request_id=spend_log_request_id,
             request_started_at=start_time,
             model_access_groups=model_access_groups,
         )
diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py
index ae55b7ab906..20f83085286 100644
--- a/litellm/proxy/litellm_pre_call_utils.py
+++ b/litellm/proxy/litellm_pre_call_utils.py
@@ -4,9 +4,10 @@ import json
 import re
 import time
 from collections import OrderedDict
-from collections.abc import Mapping, MutableMapping
+from collections.abc import Mapping, MutableMapping, Sequence
+from datetime import datetime
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, cast
 
 from fastapi import HTTPException, Request
 from pydantic import ValidationError as PydanticValidationError
@@ -55,7 +56,7 @@ from litellm.proxy.common_utils.http_parsing_utils import _safe_get_request_head
 from litellm.types.integrations.anthropic_cache_control_hook import GATEWAY_INJECTED_CACHE_METADATA_KEY
 
 # Cache special headers as a frozenset for O(1) lookup performance
-_SPECIAL_HEADERS_CACHE: Final = frozenset(v.value.lower() for v in SpecialHeaders._member_map_.values())
+_SPECIAL_HEADERS_CACHE: Final = frozenset(str(v.value).lower() for v in SpecialHeaders)
 
 _REDACTED_HEADER_VALUE: Final = "***REDACTED***"
 _CREDENTIAL_HEADER_NAMES: Final = SpecialHeaders.litellm_credential_header_names() | frozenset(
@@ -126,7 +127,7 @@ def _stampable_key_hash(user_api_key_dict: UserAPIKeyAuth) -> str | None:
 _ANTHROPIC_SESSION_ID_VALUE_RE: Final = re.compile(r"^[a-zA-Z0-9_\-]+$")
 
 
-def _sanitize_for_log(value: Any) -> str:
+def _sanitize_for_log(value: object) -> str:
     """
     Basic log sanitization helper to reduce log-injection risk.
 
@@ -164,7 +165,7 @@ _ENABLE_TEAM_STALE_ALIAS_BYPASS: bool | None = None
 
 if TYPE_CHECKING:
     from litellm.proxy.proxy_server import ProxyConfig as _ProxyConfig
-    from litellm.types.proxy.policy_engine import PolicyMatchContext
+    from litellm.types.proxy.policy_engine import Policy, PolicyMatchContext
 
     ProxyConfig = _ProxyConfig
 else:
@@ -328,7 +329,7 @@ _ALLOW_CLIENT_PRICING_OVERRIDE_METADATA_KEY: Final = "allow_client_pricing_overr
 _URL_DESTINATION_REQUEST_FIELDS: Final = ("model", "file_id")
 
 
-def _reject_url_valued_destinations(data: dict[str, Any]) -> None:
+def _reject_url_valued_destinations(data: dict[str, object]) -> None:
     """Reject URL-valued ``model``/``file_id`` unless admin-allowlisted.
 
     Some providers (HuggingFace, Oobabooga, Gemini files) accept a URL in the
@@ -387,7 +388,7 @@ def _invalid_metadata_type_error(field: str, value: object) -> ProxyException:
     )
 
 
-def _normalized_metadata_object(field: str, value: object) -> Mapping[str, Any]:
+def _normalized_metadata_object(field: str, value: object) -> Mapping[str, object]:
     """Return ``value`` as a metadata object or raise a 400 like OpenAI does.
 
     A JSON string that parses to an object is accepted because multipart/form-data
@@ -402,6 +403,23 @@ def _normalized_metadata_object(field: str, value: object) -> Mapping[str, Any]:
     raise _invalid_metadata_type_error(field=field, value=value)
 
 
+def _normalized_metadata_slot(
+    request_data: MutableMapping[str, object], metadata_variable_name: str
+) -> dict[str, object]:
+    """Return the request's metadata slot as a dict, normalising it in place first.
+
+    Metadata can arrive as a JSON string (multipart/form-data, ``extra_body``). Parsing it here keeps
+    existing entries alive through a merge instead of silently overwriting them with an empty dict.
+    """
+    raw: Final = request_data.get(metadata_variable_name)
+    if isinstance(raw, dict):
+        return raw
+    parsed: Final = safe_json_loads(raw) if isinstance(raw, str) else None
+    normalized: Final[dict[str, object]] = parsed if isinstance(parsed, dict) else {}
+    request_data[metadata_variable_name] = normalized
+    return normalized
+
+
 def _strip_untrusted_request_header_controls(
     headers: Any,
     *,
@@ -417,7 +435,7 @@ def _strip_untrusted_request_header_controls(
             headers.pop(header_name, None)
 
 
-def _is_false_like(value: Any) -> bool:
+def _is_false_like(value: object) -> bool:
     if isinstance(value, bool):
         return value is False
     if isinstance(value, str):
@@ -462,7 +480,7 @@ def _key_or_team_allows_client_pricing_override(
     )
 
 
-def _strip_client_message_redaction_opt_out(data: dict[str, Any]) -> None:
+def _strip_client_message_redaction_opt_out(data: dict[str, object]) -> None:
     stripped: Final[list[str]] = []
     if "turn_off_message_logging" in data and _is_false_like(data["turn_off_message_logging"]):
         stripped.append("turn_off_message_logging")
@@ -513,7 +531,7 @@ def _strip_client_callback_credentials(
         )
 
 
-def _strip_client_pricing_overrides(data: dict[str, Any]) -> None:
+def _strip_client_pricing_overrides(data: dict[str, object]) -> None:
     """Drop pricing overrides from the request body and any metadata variant.
 
     Skipped only when the calling key/team carries
@@ -580,9 +598,9 @@ def _get_metadata_variable_name(request: Request) -> str:
 
 
 def _promoted_trace_control_fields(
-    requester_metadata: Mapping[str, Any],
-    litellm_metadata: Mapping[str, Any],
-) -> tuple[tuple[str, Any], ...]:
+    requester_metadata: Mapping[str, object],
+    litellm_metadata: Mapping[str, object],
+) -> tuple[tuple[str, object], ...]:
     """Return the caller's trace-control fields that ``litellm_metadata`` does not already set."""
     return tuple(
         (key, value)
@@ -1193,7 +1211,7 @@ class LiteLLMProxyRequestSetup:
     def add_litellm_data_for_backend_llm_call(
         *,
         headers: dict,
-        request_data: Mapping[str, Any],
+        request_data: Mapping[str, object],
         user_api_key_dict: UserAPIKeyAuth,
         general_settings: dict[str, Any] | None = None,
     ) -> LitellmDataForBackendLLMCall:
@@ -1327,6 +1345,8 @@ class LiteLLMProxyRequestSetup:
     def get_sanitized_user_information_from_key(
         user_api_key_dict: UserAPIKeyAuth,
     ) -> StandardLoggingUserAPIKeyMetadata:
+        stripped_metadata: Final = strip_callback_config(user_api_key_dict.metadata)
+        auth_metadata: Final = cast("dict[str, str] | None", stripped_metadata)  # cast-ok: metadata is free-form JSON
         user_api_key_logged_metadata: Final = StandardLoggingUserAPIKeyMetadata(
             user_api_key_hash=user_api_key_dict.api_key,  # just the hashed token
             user_api_key_alias=user_api_key_dict.key_alias,
@@ -1349,7 +1369,7 @@ class LiteLLMProxyRequestSetup:
             user_api_key_budget_reset_at=(
                 user_api_key_dict.budget_reset_at.isoformat() if user_api_key_dict.budget_reset_at else None
             ),
-            user_api_key_auth_metadata=strip_callback_config(user_api_key_dict.metadata),
+            user_api_key_auth_metadata=auth_metadata,
         )
         return user_api_key_logged_metadata
 
@@ -1577,14 +1597,7 @@ class LiteLLMProxyRequestSetup:
             return
 
         _metadata_variable_name: Final = get_metadata_variable_name_from_kwargs(request_data)
-        metadata = request_data.get(_metadata_variable_name)
-        if isinstance(metadata, str):
-            parsed: Final = safe_json_loads(metadata)
-            metadata = parsed if isinstance(parsed, dict) else {}
-            request_data[_metadata_variable_name] = metadata
-        elif not isinstance(metadata, dict):
-            metadata = {}
-            request_data[_metadata_variable_name] = metadata
+        metadata: Final = _normalized_metadata_slot(request_data, _metadata_variable_name)
 
         existing_tags: Final = metadata.get("tags")
         metadata["tags"] = LiteLLMProxyRequestSetup._merge_tags(
@@ -1636,18 +1649,7 @@ class LiteLLMProxyRequestSetup:
         # from (litellm_metadata vs metadata) so the merged tags are visible
         # to _tag_max_budget_check.
         _metadata_variable_name: Final = get_metadata_variable_name_from_kwargs(request_data)
-        metadata = request_data.get(_metadata_variable_name)
-        # metadata can arrive as a JSON string (multipart/form-data, extra_body).
-        # Parse it so existing tags survive the merge — overwriting the string
-        # with {} would let a caller bypass _tag_max_budget_check on an
-        # over-budget body tag by also sending a within-budget header tag.
-        if isinstance(metadata, str):
-            parsed: Final = safe_json_loads(metadata)
-            metadata = parsed if isinstance(parsed, dict) else {}
-            request_data[_metadata_variable_name] = metadata
-        elif not isinstance(metadata, dict):
-            metadata = {}
-            request_data[_metadata_variable_name] = metadata
+        metadata: Final = _normalized_metadata_slot(request_data, _metadata_variable_name)
 
         existing_tags: Final = metadata.get("tags")
         metadata["tags"] = LiteLLMProxyRequestSetup._merge_tags(
@@ -1787,7 +1789,7 @@ async def add_litellm_data_to_request(
     # admin-injection strip below so the audit / spend-tracking consumers of
     # proxy_server_request["body"] see the cleaned metadata rather than
     # attacker-forged user_api_key_* fields.
-    _litellm_received_at: Final = getattr(request.state, "litellm_received_at", None)
+    _litellm_received_at: Final[datetime | None] = getattr(request.state, "litellm_received_at", None)
     arrival_time: Final = _litellm_received_at.timestamp() if _litellm_received_at is not None else time.time()
     data["proxy_server_request"] = {
         "url": str(request.url),
@@ -2472,16 +2474,16 @@ def _resolve_provider_from_deployment(
         if deployment is None:
             continue
 
-        litellm_params = getattr(deployment, "litellm_params", None)
+        litellm_params: object = getattr(deployment, "litellm_params", None)
         if litellm_params is None:
             continue
 
         custom_provider = getattr(litellm_params, "custom_llm_provider", None)
-        if custom_provider:
+        if isinstance(custom_provider, str) and custom_provider:
             return custom_provider
 
-        deployment_model = getattr(litellm_params, "model", "") or ""
-        if "/" in deployment_model:
+        deployment_model = getattr(litellm_params, "model", "")
+        if isinstance(deployment_model, str) and "/" in deployment_model:
             return deployment_model.split("/", 1)[0]
 
     return None
@@ -2904,8 +2906,8 @@ def _extract_policy_id(s: str) -> str | None:
 def _match_and_track_policies(
     data: dict,
     context: "PolicyMatchContext",
-    request_body_policies: Any,
-    policies_override: dict[str, Any] | None = None,
+    request_body_policies: Sequence[str],
+    policies_override: dict[str, "Policy"] | None = None,
 ) -> tuple[list[str], dict[str, str]]:
     """
     Match policies via attachments and request body, track them in metadata.
@@ -2963,7 +2965,7 @@ def _apply_resolved_guardrails_to_metadata(
     metadata_variable_name: str,
     context: "PolicyMatchContext",
     policy_names: list[str] | None = None,
-    policies: dict[str, Any] | None = None,
+    policies: dict[str, "Policy"] | None = None,
 ) -> None:
     """Apply resolved guardrails and pipelines to request metadata."""
     from litellm._logging import verbose_proxy_logger
@@ -3093,7 +3095,7 @@ async def add_guardrails_from_policy_engine(
                 request_body_names.append(item)
 
     # Resolve policy versions by ID from in-memory cache (populated by sync job; no DB in hot path)
-    merged_policies: Final[dict[str, Any]] = dict(registry.get_all_policies())
+    merged_policies: Final[dict[str, Policy]] = dict(registry.get_all_policies())
     fetched_policy_names: Final[list[str]] = []
     for policy_id in request_body_version_ids:
         result = registry.get_policy_by_id_for_request(policy_id=policy_id)
diff --git a/litellm/proxy/management_endpoints/auto_router_endpoints.py b/litellm/proxy/management_endpoints/auto_router_endpoints.py
index b5533d548e5..21e652114bc 100644
--- a/litellm/proxy/management_endpoints/auto_router_endpoints.py
+++ b/litellm/proxy/management_endpoints/auto_router_endpoints.py
@@ -7,7 +7,7 @@ POST /auto_router/validate_complexity_router_config - Dry-run the complexity-rou
 
 from collections.abc import Mapping, Sequence
 from datetime import datetime, timedelta, timezone
-from itertools import groupby
+from itertools import chain, groupby
 from operator import attrgetter
 from types import MappingProxyType
 from typing import TYPE_CHECKING, Annotated, Final, Protocol
@@ -58,10 +58,11 @@ from litellm.types.management_endpoints.auto_router_endpoints import (
     ComplexityRouterConfigValidationResponse,
     RequestComplexityRouterConfig,
     ShadowEvalDirection,
-    ShadowEvalJobKeyResponse,
     ShadowEvalJobResponse,
+    ShadowEvalJobTargetResponse,
     ShadowEvalResult,
     ShadowEvalSlice,
+    ShadowEvalTargetType,
     StartShadowEvalRequest,
 )
 
@@ -104,10 +105,43 @@ class _VerificationTokenTable(Protocol):
     async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_VerificationTokenRow]: ...
 
 
+class _TeamRow(Protocol):
+    @property
+    def team_id(self) -> str: ...
+
+    @property
+    def team_alias(self) -> str | None: ...
+
+
+class _TeamRowsTable(Protocol):
+    async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_TeamRow]: ...
+
+
+class _UserRow(Protocol):
+    @property
+    def user_id(self) -> str: ...
+
+    @property
+    def user_email(self) -> str | None: ...
+
+
+class _UserRowsTable(Protocol):
+    async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_UserRow]: ...
+
+
 class _ShadowEvalJobRow(Protocol):
     @property
     def id(self) -> str: ...
 
+    @property
+    def group_id(self) -> str: ...
+
+    @property
+    def target_type(self) -> str: ...
+
+    @property
+    def target_id(self) -> str: ...
+
 
 class _ShadowEvalJobTable(Protocol):
     async def find_many(self, *, where: Mapping[str, object]) -> Sequence[_ShadowEvalJobRow]: ...
@@ -138,6 +172,14 @@ def _verification_tokens(prisma_client: "PrismaClient") -> _VerificationTokenTab
     return prisma_client.db.litellm_verificationtoken
 
 
+def _team_rows(prisma_client: "PrismaClient") -> _TeamRowsTable:
+    return prisma_client.db.litellm_teamtable
+
+
+def _user_rows(prisma_client: "PrismaClient") -> _UserRowsTable:
+    return prisma_client.db.litellm_usertable
+
+
 def _shadow_eval_jobs(prisma_client: "PrismaClient") -> _ShadowEvalJobTable:
     return prisma_client.db.litellm_shadowevaljob
 
@@ -791,7 +833,7 @@ def _judge_collisions_for_team(
     return tuple(
         (role, model)
         for role, model in (
-            *_router_arm_models(llm_router, data.router_name),
+            *(arm for name in data.router_names for arm in _router_arm_models(llm_router, name)),
             *((("baseline", data.baseline_model),) if data.baseline_model is not None else ()),
         )
         if judge & judge_target(llm_router, model, team_id).models
@@ -836,7 +878,7 @@ def _validate_judge_is_not_a_candidate(
 
 
 def _is_unique_violation(error: Exception) -> bool:
-    """Whether a Prisma create failed on a unique index. One active job per key and
+    """Whether a Prisma create failed on a unique index. One active job per target and
     direction lives in a partial unique index (raw SQL in the migration; schema.prisma
     cannot express partial indexes), so the read-then-create check above it is advisory:
     two concurrent starts pass the read, and the loser must surface as the same 409
@@ -862,7 +904,7 @@ class _AttemptAggRow(BaseModel):
 
 _ATTEMPT_AGG_ROWS: Final = TypeAdapter(list[_AttemptAggRow])
 
-_ATTEMPT_AGG_SELECT: Final = """
+_ATTEMPT_AGG_COLUMNS: Final = """
     COUNT(*)::int AS turn_count,
     COUNT(*) FILTER (WHERE outcome = 'real')::int AS real_wins,
     COUNT(*) FILTER (WHERE outcome = 'shadow')::int AS shadow_wins,
@@ -871,21 +913,40 @@ _ATTEMPT_AGG_SELECT: Final = """
     COALESCE(SUM(real_cost + real_classifier_cost) FILTER (WHERE real_cost IS NOT NULL AND NOT real_cache_hit), 0)::float AS real_spend,
     COALESCE(SUM(shadow_cost + shadow_classifier_cost) FILTER (WHERE real_cost IS NOT NULL AND NOT real_cache_hit), 0)::float AS shadow_spend,
     COUNT(*) FILTER (WHERE real_cache_hit)::int AS cache_hit_turns
+"""
+
+_ATTEMPT_AGG_SELECT: Final = (
+    _ATTEMPT_AGG_COLUMNS
+    + """
 FROM "LiteLLM_ShadowEvalAttempt"
 WHERE job_id = ANY($1::text[]) AND outcome != 'error'
 GROUP BY 1
 """
+)
 
 _ATTEMPT_AGG_BY_TIER_SQL: Final = "SELECT COALESCE(tier, 'UNCLASSIFIED') AS grp," + _ATTEMPT_AGG_SELECT
 _ATTEMPT_AGG_BY_MODEL_SQL: Final = "SELECT COALESCE(real_model, 'unknown') AS grp," + _ATTEMPT_AGG_SELECT
 _ATTEMPT_AGG_BY_LEG_SQL: Final = "SELECT job_id AS grp," + _ATTEMPT_AGG_SELECT
 
+# Attempt rows from before arm stamping carry no router_name; they belong to the job's
+# own router, which the join reads off the leg.
+_ATTEMPT_AGG_BY_ROUTER_SQL: Final = (
+    "SELECT COALESCE(a.router_name, j.router_name) AS grp,"
+    + _ATTEMPT_AGG_COLUMNS
+    + """
+FROM "LiteLLM_ShadowEvalAttempt" a
+JOIN "LiteLLM_ShadowEvalJob" j ON j.id = a.job_id
+WHERE a.job_id = ANY($1::text[]) AND a.outcome != 'error'
+GROUP BY 1
+"""
+)
+
 # These guards derive spend from attempt rows, the cross-pod authority; the sampler also
 # reads the live counter, so admission can stop before a row-based guard would fire (safe
 # direction, and mid-deploy rows from old pods price as judge-only until the deploy ends).
 _SWEEP_FINISHED_JOBS_SQL: Final = """
 UPDATE "LiteLLM_ShadowEvalJob" j SET stopped_at = (NOW() AT TIME ZONE 'utc')
-WHERE j.api_key_id = ANY($1::text[]) AND j.stopped_at IS NULL
+WHERE j.target_type = $2 AND j.target_id = ANY($1::text[]) AND j.stopped_at IS NULL
   AND (
     j.ends_at <= (NOW() AT TIME ZONE 'utc')
     OR (SELECT COUNT(*) FROM "LiteLLM_ShadowEvalAttempt" a WHERE a.job_id = j.id) >= j.max_turns
@@ -966,10 +1027,10 @@ WHERE group_id IN (
 )
 """
 
-_LIST_LEGS_BY_KEY_SQL: Final = """
+_LIST_LEGS_BY_TARGET_SQL: Final = """
 SELECT * FROM "LiteLLM_ShadowEvalJob"
 WHERE group_id IN (
-    SELECT group_id FROM "LiteLLM_ShadowEvalJob" WHERE api_key_id = $2
+    SELECT group_id FROM "LiteLLM_ShadowEvalJob" WHERE target_type = $2 AND target_id = $3
     GROUP BY group_id ORDER BY MAX(created_at) DESC LIMIT $1::int
 )
 """
@@ -1007,16 +1068,18 @@ def _slices(rows: Sequence[_AttemptAggRow]) -> tuple[ShadowEvalSlice, ...]:
 
 class _LegRow(BaseModel):
     """One LiteLLM_ShadowEvalJob row, validated off the untyped prisma record. A row is
-    one key's leg of a job; the legs of a job share group_id and identical config, written
-    together by one create_many. The API's job id is the group id, so leg ids never leave
-    the server (attempts reference them internally)."""
+    one target's leg of a job; the legs of a job share group_id and identical config,
+    written together by one create_many. The API's job id is the group id, so leg ids
+    never leave the server (attempts reference them internally)."""
 
     model_config = ConfigDict(from_attributes=True)
 
     id: str
     group_id: str
-    api_key_id: str
+    target_type: ShadowEvalTargetType
+    target_id: str
     router_name: str
+    router_names: tuple[str, ...] = ()
     direction: ShadowEvalDirection
     baseline_model: str | None = None
     judge_model: str
@@ -1028,6 +1091,12 @@ class _LegRow(BaseModel):
     stopped_at: datetime | None = None
     stopped_by: str | None = None
 
+    @property
+    def arm_router_names(self) -> tuple[str, ...]:
+        """The job's full router set; rows from before router_names existed hold it in
+        router_name alone. The one place that reading lives on the endpoint side."""
+        return self.router_names or (self.router_name,)
+
     @field_validator("created_at", "ends_at", "stopped_at")
     @classmethod
     def _as_aware_utc(cls, value: datetime | None) -> datetime | None:
@@ -1068,18 +1137,19 @@ def _group_response(
     first: Final = legs[0]
     return ShadowEvalJobResponse(
         job_id=group_id,
-        keys=tuple(
-            ShadowEvalJobKeyResponse(
-                api_key_id=leg.api_key_id,
+        targets=tuple(
+            ShadowEvalJobTargetResponse(
+                target_type=leg.target_type,
+                target_id=leg.target_id,
                 max_turns=leg.max_turns,
                 max_budget=leg.max_budget,
                 stopped_at=leg.stopped_at,
                 attempt_count=stats.attempt_count if (stats := attempt_counts.get(leg.id)) else 0,
                 spend=round(stats.spend, 6) if stats else 0.0,
             )
-            for leg in sorted(legs, key=lambda leg: leg.api_key_id)
+            for leg in sorted(legs, key=lambda leg: (leg.target_type, leg.target_id))
         ),
-        router_name=first.router_name,
+        router_names=first.arm_router_names,
         direction=first.direction,
         baseline_model=first.baseline_model,
         judge_model=first.judge_model,
@@ -1090,34 +1160,85 @@ def _group_response(
     )
 
 
-_NO_KEY_LABELS: Final[tuple[str | None, str | None]] = (None, None)
+_NO_TARGET_LABELS: Final[tuple[str | None, str | None]] = (None, None)
 
 
-async def _with_key_labels(
+def _target_labels(
+    key_rows: Sequence[_VerificationTokenRow],
+    team_rows: Sequence[_TeamRow],
+    user_rows: Sequence[_UserRow],
+) -> Mapping[tuple[str, str], tuple[str | None, str | None]]:
+    """Display labels by (target_type, target_id): a key's (alias, masked name), a
+    team's (alias, None), a user's (email, None)."""
+    return MappingProxyType(
+        {  # mutable-ok: MappingProxyType needs a dict to wrap
+            key: value
+            for key, value in chain(
+                ((("key", row.token), (row.key_alias, row.key_name)) for row in key_rows),
+                ((("team", row.team_id), (row.team_alias, None)) for row in team_rows),
+                ((("user", row.user_id), (row.user_email, None)) for row in user_rows),
+            )
+        }
+    )
+
+
+def _target_ids_of(responses: Sequence[ShadowEvalJobResponse], target_type: ShadowEvalTargetType) -> tuple[str, ...]:
+    return tuple(
+        sorted(
+            frozenset(
+                target.target_id
+                for response in responses
+                for target in response.targets
+                if target.target_type == target_type
+            )
+        )
+    )
+
+
+async def _with_target_labels(
     prisma_client: "PrismaClient", responses: Sequence[ShadowEvalJobResponse]
 ) -> tuple[ShadowEvalJobResponse, ...]:
-    """Resolve every scoped key's hash to its alias and masked name in one batched read,
-    so the UI can say whose traffic a job shadows. Deleted keys resolve to None."""
+    """Resolve every scoped target's id to a display label in one batched read per kind,
+    so the UI can say whose traffic a job shadows: a key's alias and masked name, a
+    team's alias, a user's email. Deleted targets resolve to None."""
     if not responses:
         return ()
-    tokens: Final = sorted(frozenset(key.api_key_id for response in responses for key in response.keys))
-    key_rows: Final = await _verification_tokens(prisma_client).find_many(
-        where={"token": {"in": tokens}}  # mutable-ok: Prisma filter
+    tokens: Final = _target_ids_of(responses, "key")
+    team_ids: Final = _target_ids_of(responses, "team")
+    user_ids: Final = _target_ids_of(responses, "user")
+    key_rows: Final = (
+        await _verification_tokens(prisma_client).find_many(
+            where={"token": {"in": list(tokens)}}  # mutable-ok: Prisma filter
+        )
+        if tokens
+        else ()
     )
-    labels: Final[Mapping[str, tuple[str | None, str | None]]] = {
-        row.token: (row.key_alias, row.key_name) for row in key_rows or ()
-    }
+    team_rows: Final = (
+        await _team_rows(prisma_client).find_many(
+            where={"team_id": {"in": list(team_ids)}}  # mutable-ok: Prisma filter
+        )
+        if team_ids
+        else ()
+    )
+    user_rows: Final = (
+        await _user_rows(prisma_client).find_many(
+            where={"user_id": {"in": list(user_ids)}}  # mutable-ok: Prisma filter
+        )
+        if user_ids
+        else ()
+    )
+    labels: Final = _target_labels(key_rows or (), team_rows or (), user_rows or ())
     return tuple(
         response.model_copy(
             update={  # mutable-ok: pydantic update payload
-                "keys": tuple(
-                    key.model_copy(
+                "targets": tuple(
+                    target.model_copy(
                         update={  # mutable-ok: pydantic update payload
-                            "key_alias": labels.get(key.api_key_id, _NO_KEY_LABELS)[0],
-                            "key_name": labels.get(key.api_key_id, _NO_KEY_LABELS)[1],
+                            "target_alias": labels.get((target.target_type, target.target_id), _NO_TARGET_LABELS)[0],
+                            "key_name": labels.get((target.target_type, target.target_id), _NO_TARGET_LABELS)[1],
                         }
                     )
-                    for key in response.keys
+                    for target in response.targets
                 )
             }
         )
@@ -1125,29 +1246,40 @@ async def _with_key_labels(
     )
 
 
-async def _shadow_eval_results(prisma_client: "PrismaClient", legs: Sequence[_LegRow]) -> ShadowEvalResult | None:
-    """All three stratifications of one job's verdicts. Tier answers "where does the router
-    do well"; the model stratification groups by whichever model served the real arm, so it
-    answers "which of the models these keys use today would the router beat" forward, and
-    "for the turns the router sent to X, did X beat the baseline" in reverse; key answers
-    "which key's traffic does the router suit". Reads are bounded by the job's own attempts
-    (<= the sum of its keys' max_turns) via the job_id index."""
+async def _shadow_eval_results(
+    prisma_client: "PrismaClient", legs: Sequence[_LegRow]
+) -> tuple[ShadowEvalResult | None, Mapping[tuple[str, str], ShadowEvalSlice]]:
+    """One job's stratified verdicts, plus each target's own slice keyed by the
+    (target_type, target_id) pair so a key, team, and user sharing an id can never
+    collapse into one entry. Tier answers "where does the router do well"; the model
+    stratification groups by whichever model served the real arm, so it answers "which
+    of the models these targets use today would the router beat" forward, and "for the
+    turns the router sent to X, did X beat the baseline" in reverse; the per-target
+    slices answer "which target's traffic does the router suit". Reads are bounded by
+    the job's own attempts (<= the sum of its targets' max_turns) via the job_id index."""
     leg_ids: Final = [leg.id for leg in legs]  # mutable-ok: query param
     by_tier: Final = _ATTEMPT_AGG_ROWS.validate_python(
         await _query_raw(prisma_client, _ATTEMPT_AGG_BY_TIER_SQL, leg_ids) or ()
     )
     if not by_tier:
-        return None
+        return None, MappingProxyType({})
     by_model: Final = _ATTEMPT_AGG_ROWS.validate_python(
         await _query_raw(prisma_client, _ATTEMPT_AGG_BY_MODEL_SQL, leg_ids) or ()
     )
-    key_by_leg: Final = MappingProxyType({leg.id: leg.api_key_id for leg in legs})
+    target_by_leg: Final = MappingProxyType({leg.id: (leg.target_type, leg.target_id) for leg in legs})
     by_leg: Final = _ATTEMPT_AGG_ROWS.validate_python(
         await _query_raw(prisma_client, _ATTEMPT_AGG_BY_LEG_SQL, leg_ids) or ()
     )
-    by_key: Final = tuple(
-        row.model_copy(update={"grp": key_by_leg[row.grp]})  # mutable-ok: pydantic update payload
-        for row in by_leg
+    verdicts_by_target: Final[Mapping[tuple[str, str], ShadowEvalSlice]] = MappingProxyType(
+        {  # mutable-ok: MappingProxyType needs a dict to wrap
+            target_by_leg[slice.group]: slice.model_copy(
+                update={"group": target_by_leg[slice.group][1]}  # mutable-ok: pydantic update payload
+            )
+            for slice in _slices(by_leg)
+        }
+    )
+    by_router: Final = _ATTEMPT_AGG_ROWS.validate_python(
+        await _query_raw(prisma_client, _ATTEMPT_AGG_BY_ROUTER_SQL, leg_ids) or ()
     )
     total_turns: Final = sum(r.turn_count for r in by_tier)
     funnel_rows: Final = await _query_raw(prisma_client, _FUNNEL_TOTALS_SQL, leg_ids)
@@ -1155,10 +1287,10 @@ async def _shadow_eval_results(prisma_client: "PrismaClient", legs: Sequence[_Le
     # Coverage only when EVERY leg has a funnel row: a partial seed (one leg's insert
     # failed) must read as unknown, not as job-level counts missing a leg's traffic.
     funnel: Final = counted if counted is not None and counted.legs_with_rows == len(leg_ids) else None
-    return ShadowEvalResult(
+    result: Final = ShadowEvalResult(
         by_tier=_slices(by_tier),
         by_current_model=_slices(by_model),
-        by_key=_slices(by_key),
+        by_router=_slices(by_router),
         overall_shadow_win_rate_pct=_pct_of(sum(r.shadow_wins for r in by_tier), total_turns),
         overall_tie_rate_pct=_pct_of(sum(r.ties for r in by_tier), total_turns),
         sampled_real_spend=sum(r.real_spend for r in by_tier),
@@ -1168,6 +1300,7 @@ async def _shadow_eval_results(prisma_client: "PrismaClient", legs: Sequence[_Le
         shed_count=funnel.shed if funnel is not None else None,
         withheld_count=funnel.withheld if funnel is not None else None,
     )
+    return result, verdicts_by_target
 
 
 @router.post(
@@ -1182,59 +1315,126 @@ async def start_shadow_eval(
     user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
 ) -> ShadowEvalJobResponse:
     """
-    Start a shadow eval: duplicate a sampled slice of one or more keys' live traffic against
-    a second arm, judge the two responses blind, and stratify win rates by tier, by the model
-    that served the real arm, and by key.
+    Start a shadow eval: duplicate a sampled slice of one or more targets' live traffic
+    against a second arm, judge the two responses blind, and stratify win rates by tier,
+    by the model that served the real arm, and by target.
 
-    A forward job answers whether the keys should adopt router_name: it samples the requests
-    the router did not serve and duplicates them through it. A reverse job answers whether a
-    key already on the router still gains from it: it samples the requests the router did
-    serve and duplicates them against baseline_model. A key can hold one active job per
-    direction, so both questions can run at once.
+    A target is a virtual key, a team, or a user. Team and user targets match on the
+    identity every request resolves to at auth time, so they cover JWT-authenticated
+    traffic, which presents no virtual key; a user target samples that user's traffic
+    across all their teams, whether it arrives on a JWT or a key they own.
 
-    Shadow responses are never served to users. Each key samples until its recorded eval
-    spend, the shadow and judge calls' own cost, reaches max_budget dollars, the job's
-    window ends, or the job is stopped, so one key running out of budget does not end
-    sampling for the others; sampling changes propagate to pods within about 10 seconds.
-    Shadow and judge calls bill to the shadowed key but are excluded from request counts
-    and auto-router adoption metrics.
+    A forward job answers whether the targets should adopt router_name: it samples the
+    requests the router did not serve and duplicates them through it. A reverse job
+    answers whether a target already on the router still gains from it: it samples the
+    requests the router did serve and duplicates them against baseline_model. A target
+    can hold one active job per direction, so both questions can run at once, and a
+    request matching several jobs' targets (say its key and its team) is sampled by
+    each, separately budgeted.
+
+    Shadow responses are never served to users. Each target samples until its recorded
+    eval spend, the shadow and judge calls' own cost, reaches max_budget dollars, the
+    job's window ends, or the job is stopped, so one target running out of budget does
+    not end sampling for the others; sampling changes propagate to pods within about 10
+    seconds. Shadow and judge calls bill to the sampled request's own identity but are
+    excluded from request counts and auto-router adoption metrics.
     """
     from litellm.proxy.proxy_server import llm_router, prisma_client
 
     _require_admin_writer(user_api_key_dict, "start a shadow eval")
     if prisma_client is None:
         raise HTTPException(status_code=500, detail=CommonProxyErrors.db_not_connected_error.value)
-    if llm_router is None or not _is_configured_pre_routing_strategy(llm_router, data.router_name):
-        raise HTTPException(status_code=400, detail=f"'{data.router_name}' is not a configured auto-router")
-    token_rows: Final = await _verification_tokens(prisma_client).find_many(
-        where={"token": {"in": list(data.api_key_ids)}}  # mutable-ok: Prisma filter
+    unconfigured: Final = tuple(
+        name
+        for name in data.router_names
+        if llm_router is None or not _is_configured_pre_routing_strategy(llm_router, name)
     )
-    unknown: Final = tuple(sorted(frozenset(data.api_key_ids) - frozenset(row.token for row in token_rows or ())))
-    if unknown:
+    if unconfigured:
         raise HTTPException(
-            status_code=400,
-            detail=(
-                f"api_key_ids not on this proxy: {', '.join(unknown)}; pass each key's token hash, "
-                "the value the key list and key info endpoints report"
-            ),
+            status_code=400, detail=f"Not a configured auto-router: {', '.join(repr(n) for n in unconfigured)}"
         )
+    token_rows: Final = (
+        await _verification_tokens(prisma_client).find_many(
+            where={"token": {"in": list(data.api_key_ids)}}  # mutable-ok: Prisma filter
+        )
+        if data.api_key_ids
+        else ()
+    )
+    team_rows: Final = (
+        await _team_rows(prisma_client).find_many(
+            where={"team_id": {"in": list(data.team_ids)}}  # mutable-ok: Prisma filter
+        )
+        if data.team_ids
+        else ()
+    )
+    user_rows: Final = (
+        await _user_rows(prisma_client).find_many(
+            where={"user_id": {"in": list(data.user_ids)}}  # mutable-ok: Prisma filter
+        )
+        if data.user_ids
+        else ()
+    )
+    unknown_keys: Final = sorted(frozenset(data.api_key_ids) - frozenset(row.token for row in token_rows or ()))
+    unknown_teams: Final = sorted(frozenset(data.team_ids) - frozenset(row.team_id for row in team_rows or ()))
+    unknown_users: Final = sorted(frozenset(data.user_ids) - frozenset(row.user_id for row in user_rows or ()))
+    unknown_parts: Final = tuple(
+        part
+        for part in (
+            (
+                f"api_key_ids not on this proxy: {', '.join(unknown_keys)}; pass each key's token hash, "
+                "the value the key list and key info endpoints report"
+            )
+            if unknown_keys
+            else None,
+            f"team_ids not on this proxy: {', '.join(unknown_teams)}" if unknown_teams else None,
+            f"user_ids not on this proxy: {', '.join(unknown_users)}" if unknown_users else None,
+        )
+        if part is not None
+    )
+    if unknown_parts:
+        raise HTTPException(status_code=400, detail=". ".join(unknown_parts))
 
     # Every model check below runs once per team the job samples for, since that is the
     # identity the shadow and judge calls carry and therefore what the router selects on.
-    team_ids: Final = tuple(dict.fromkeys(row.team_id for row in token_rows or ()))
+    # A user target's traffic can span teams, so it validates unscoped (None); each
+    # sampled attempt still resolves the judge under its own request's team at eval time.
+    team_ids: Final = tuple(
+        dict.fromkeys(
+            (
+                *(row.team_id for row in token_rows or ()),
+                *data.team_ids,
+                *((None,) if data.user_ids else ()),
+            )
+        )
+    )
     _validate_plain_model(llm_router, data.judge_model, "judge_model", team_ids)
     if data.baseline_model is not None:
         _validate_plain_model(llm_router, data.baseline_model, "baseline_model", team_ids)
     _validate_judge_is_not_a_candidate(llm_router, data, team_ids)
 
+    requested_targets: Final[tuple[tuple[ShadowEvalTargetType, str], ...]] = (
+        *(("key", key) for key in data.api_key_ids),
+        *(("team", team) for team in data.team_ids),
+        *(("user", user) for user in data.user_ids),
+    )
+    requested_by_type: Final[tuple[tuple[ShadowEvalTargetType, tuple[str, ...]], ...]] = tuple(
+        (target_type, ids)
+        for target_type, ids in (("key", data.api_key_ids), ("team", data.team_ids), ("user", data.user_ids))
+        if ids
+    )
     # A job whose window passed or whose budget ran out stopped sampling on its own,
-    # but its legs still hold their slots in the per-key, per-direction partial unique index
-    # until stamped; free them so a new eval can start. Sweeping both directions is deliberate.
-    requested: Final = list(data.api_key_ids)  # mutable-ok: query param
-    await prisma_client.db.execute_raw(_SWEEP_FINISHED_JOBS_SQL, requested)
+    # but its legs still hold their slots in the per-target, per-direction partial unique
+    # index until stamped; free them so a new eval can start. Sweeping both directions is
+    # deliberate. Sweep and claim filter on exact (target_type, id) pairs so a team id
+    # that happens to equal a key hash never matches the other kind's slot.
+    for target_type, ids in requested_by_type:
+        await prisma_client.db.execute_raw(_SWEEP_FINISHED_JOBS_SQL, list(ids), target_type)  # mutable-ok: query param
     claimed: Final = await _shadow_eval_jobs(prisma_client).find_many(
         where={  # mutable-ok: Prisma filter
-            "api_key_id": {"in": requested},  # mutable-ok: Prisma filter
+            "OR": [  # mutable-ok: Prisma filter
+                {"target_type": target_type, "target_id": {"in": list(ids)}}  # mutable-ok: Prisma filter
+                for target_type, ids in requested_by_type
+            ],
             "direction": data.direction,
             "stopped_at": None,
         },
@@ -1244,7 +1444,7 @@ async def start_shadow_eval(
             status_code=409,
             detail=(
                 f"Already in an active {data.direction} shadow eval job: "
-                + ", ".join(sorted(f"{row.api_key_id} (job {row.group_id})" for row in claimed))
+                + ", ".join(sorted(f"{row.target_type} {row.target_id} (job {row.group_id})" for row in claimed))
                 + ". Stop it first."
             ),
         )
@@ -1253,7 +1453,9 @@ async def start_shadow_eval(
     ends_at: Final = now + timedelta(days=data.duration_days)
     shared_config: Final = {  # mutable-ok: Prisma payload
         "group_id": group_id,
-        "router_name": data.router_name,
+        # a pre-router_names pod samples router_name alone, so it must be a real arm
+        "router_name": data.router_names[0],
+        "router_names": list(data.router_names),  # mutable-ok: Prisma payload
         "direction": data.direction,
         "baseline_model": data.baseline_model,
         "judge_model": data.judge_model,
@@ -1268,10 +1470,16 @@ async def start_shadow_eval(
         # Leg ids are minted here rather than by the DB default so the funnel seed below
         # writes from the same values with no read-back, which a lagging read replica
         # (DATABASE_URL_READ_REPLICA) could otherwise return empty.
-        leg_ids: Final = tuple(str(uuid4()) for _ in data.api_key_ids)
+        leg_ids: Final = tuple(str(uuid4()) for _ in requested_targets)
         await _shadow_eval_jobs(prisma_client).create_many(
             data=[  # mutable-ok: Prisma payload
-                {**shared_config, "id": leg_id, "api_key_id": key} for leg_id, key in zip(leg_ids, data.api_key_ids)
+                {  # mutable-ok: Prisma payload
+                    **shared_config,
+                    "id": leg_id,
+                    "target_type": target_type,
+                    "target_id": target_id,
+                }  # mutable-ok: Prisma payload
+                for leg_id, (target_type, target_id) in zip(leg_ids, requested_targets)
             ]
         )
     except Exception as e:
@@ -1280,7 +1488,8 @@ async def start_shadow_eval(
         raise HTTPException(
             status_code=409,
             detail=(
-                f"A requested key was claimed by another {data.direction} shadow eval job concurrently. Stop it first."
+                f"A requested target was claimed by another {data.direction} shadow eval job concurrently. "
+                "Stop it first."
             ),
         ) from e
     # Seed a zero funnel row per leg NOW: a fully covered job never skips a request, so
@@ -1293,20 +1502,21 @@ async def start_shadow_eval(
         )
     except Exception as seed_err:  # noqa: BLE001  # coverage is advisory; the job must still start
         verbose_proxy_logger.error("shadow_eval: funnel seed failed for job %s: %s", group_id, seed_err)
-    labels: Final = MappingProxyType({row.token: row for row in token_rows})
+    labels: Final = _target_labels(token_rows or (), team_rows or (), user_rows or ())
     return ShadowEvalJobResponse(
         job_id=group_id,
-        keys=tuple(
-            ShadowEvalJobKeyResponse(
-                api_key_id=api_key_id,
+        targets=tuple(
+            ShadowEvalJobTargetResponse(
+                target_type=target_type,
+                target_id=target_id,
                 max_turns=SHADOW_EVAL_TURN_VALVE,
                 max_budget=data.max_budget,
-                key_alias=labels[api_key_id].key_alias,
-                key_name=labels[api_key_id].key_name,
+                target_alias=labels.get((target_type, target_id), _NO_TARGET_LABELS)[0],
+                key_name=labels.get((target_type, target_id), _NO_TARGET_LABELS)[1],
             )
-            for api_key_id in sorted(data.api_key_ids)
+            for target_type, target_id in sorted(requested_targets)
         ),
-        router_name=data.router_name,
+        router_names=data.router_names,
         direction=data.direction,
         baseline_model=data.baseline_model,
         judge_model=data.judge_model,
@@ -1324,22 +1534,29 @@ async def start_shadow_eval(
 )
 async def list_shadow_eval_jobs(
     user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
-    api_key_id: Annotated[
-        str | None, Query(description="Filter to jobs that shadow this key, alone or alongside others")
+    target_type: Annotated[
+        ShadowEvalTargetType | None, Query(description="Kind of target to filter on; requires target_id")
+    ] = None,
+    target_id: Annotated[
+        str | None, Query(description="Filter to jobs that shadow this target, alone or alongside others")
     ] = None,
     limit: Annotated[int, Query(ge=1, le=200, description="Newest jobs to return")] = 50,
 ) -> tuple[ShadowEvalJobResponse, ...]:
-    """List shadow eval jobs, newest first, each key with its attempt count so status is
-    accurate. Judged counts, spend, and results ride the detail endpoint only."""
+    """List shadow eval jobs, newest first, each target with its attempt count so status
+    is accurate. Judged counts, spend, and results ride the detail endpoint only."""
     from litellm.proxy.proxy_server import prisma_client
 
     _require_admin_viewer(user_api_key_dict, "view shadow evals")
     if prisma_client is None:
         raise HTTPException(status_code=500, detail=CommonProxyErrors.db_not_connected_error.value)
+    filter_type: Final = target_type if isinstance(target_type, str) else None
+    filter_id: Final = target_id if isinstance(target_id, str) else None
+    if (filter_type is None) != (filter_id is None):
+        raise HTTPException(status_code=400, detail="target_type and target_id filter together; pass both or neither")
     legs: Final = _LEG_ROWS.validate_python(
         (
-            await _query_raw(prisma_client, _LIST_LEGS_BY_KEY_SQL, limit, api_key_id)
-            if api_key_id
+            await _query_raw(prisma_client, _LIST_LEGS_BY_TARGET_SQL, limit, filter_type, filter_id)
+            if filter_type and filter_id
             else await _query_raw(prisma_client, _LIST_LEGS_SQL, limit)
         )
         or ()
@@ -1354,7 +1571,7 @@ async def list_shadow_eval_jobs(
         by_group, key=lambda group_id: max(leg.created_at for leg in by_group[group_id]), reverse=True
     )
     counts: Final = await _leg_attempt_counts(prisma_client, legs)
-    return await _with_key_labels(
+    return await _with_target_labels(
         prisma_client, tuple(_group_response(group_id, by_group[group_id], counts) for group_id in newest_first)
     )
 
@@ -1391,16 +1608,25 @@ async def get_shadow_eval_job(
         where={"job_id": {"in": leg_ids}, "outcome": "error"},  # mutable-ok: Prisma filter
         order={"created_at": "desc"},  # mutable-ok: Prisma order
     )
-    labeled: Final = await _with_key_labels(
+    labeled: Final = await _with_target_labels(
         prisma_client, (_group_response(job_id, legs, await _leg_attempt_counts(prisma_client, legs)),)
     )
+    results, verdicts_by_target = await _shadow_eval_results(prisma_client, legs)
     return labeled[0].model_copy(
         update={  # mutable-ok: pydantic update payload
             "judged_count": totals[0].judged_count if totals else 0,
             "error_count": totals[0].error_count if totals else 0,
             "judge_spend": round(totals[0].judge_spend, 6) if totals else 0.0,
             "last_error": latest_error.error if latest_error else None,
-            "results": await _shadow_eval_results(prisma_client, legs),
+            "results": results,
+            "targets": tuple(
+                target.model_copy(
+                    update={  # mutable-ok: pydantic update payload
+                        "verdicts": verdicts_by_target.get((target.target_type, target.target_id))
+                    }
+                )
+                for target in labeled[0].targets
+            ),
         }
     )
 
@@ -1415,8 +1641,8 @@ async def stop_shadow_eval_job(
     job_id: str,
     user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
 ) -> ShadowEvalJobResponse:
-    """Stop an active shadow eval job, every key it scopes at once. Attempts are kept;
-    sampling halts within ~10s. Keys that already stopped on their own budget keep the
+    """Stop an active shadow eval job, every target it scopes at once. Attempts are kept;
+    sampling halts within ~10s. Targets that already stopped on their own budget keep the
     stopped_at they earned. The statement is the whole state machine: it claims the job
     only while a leg still samples inside the window with no stop recorded, so a racing
     operator, a same-instant budget spend, and a repeat stop all read the same 400 with
@@ -1443,5 +1669,5 @@ async def stop_shadow_eval_job(
     current: Final = _group_response(job_id, legs, counts)
     if claimed == 0:
         raise HTTPException(status_code=400, detail=f"Job {job_id} is already {current.status}")
-    labeled: Final = await _with_key_labels(prisma_client, (current,))
+    labeled: Final = await _with_target_labels(prisma_client, (current,))
     return labeled[0]
diff --git a/litellm/proxy/management_endpoints/customer_endpoints.py b/litellm/proxy/management_endpoints/customer_endpoints.py
index 9ef3d2defef..d2d87331d55 100644
--- a/litellm/proxy/management_endpoints/customer_endpoints.py
+++ b/litellm/proxy/management_endpoints/customer_endpoints.py
@@ -626,11 +626,7 @@ async def update_end_user(
         # get non default values for key
         non_default_values: Final = dict[str, object]()
         for k, v in data_json.items():
-            if v is not None and v not in (
-                [],
-                {},
-                0,
-            ):  # models default to [], spend defaults to 0, we should not reset these values
+            if v is not None and ((isinstance(v, bool) and k in data.fields_set()) or v not in ([], {}, 0)):
                 non_default_values[k] = v
 
         ## Get end user table data ##
diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py
index 9a98bdbb6b1..5326074ad3c 100644
--- a/litellm/proxy/management_endpoints/internal_user_endpoints.py
+++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py
@@ -17,7 +17,7 @@ import json
 import traceback
 from collections.abc import Awaitable, Mapping, Sequence
 from datetime import datetime, timezone
-from typing import Any, Final, Literal, cast
+from typing import Any, Final, Literal, Protocol, cast, overload
 
 import fastapi
 from fastapi import APIRouter, Depends, Header, HTTPException, Request, status
@@ -27,6 +27,7 @@ from litellm._logging import verbose_proxy_logger
 from litellm._uuid import uuid
 from litellm.proxy._types import *
 from litellm.proxy.auth.auth_checks import get_team_object, get_user_object
+from litellm.proxy.auth.password_policy import validate_password_policy
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 from litellm.proxy.common_utils.user_api_key_cache import (
     object_permission_cache_key,
@@ -154,9 +155,10 @@ def _team_membership_table(
     return team_membership_table
 
 
-def _hash_password_in_dict(data: dict) -> None:
-    """Hash password field in-place if present."""
+def _hash_password_in_dict(data: dict, general_settings: Mapping[str, object]) -> None:
+    """Validate and hash password field in-place if present."""
     if "password" in data and data["password"] is not None:
+        validate_password_policy(data["password"], general_settings)
         data["password"] = hash_password(data["password"])
 
 
@@ -500,7 +502,7 @@ async def new_user(
     ```
     """
     try:
-        from litellm.proxy.proxy_server import _license_check, prisma_client
+        from litellm.proxy.proxy_server import _license_check, general_settings, prisma_client
 
         if prisma_client is None:
             raise HTTPException(status_code=400, detail=CommonProxyErrors.db_not_connected_error.value)
@@ -548,7 +550,7 @@ async def new_user(
         # generate_key_helper_fn only forwards object_permission_id, so without this the entitlement
         # the caller sent would be dropped on the floor.
         data_json = await _set_object_permission(data_json=data_json, prisma_client=prisma_client)
-        _hash_password_in_dict(data_json)
+        _hash_password_in_dict(data_json, general_settings)
         teams = data.teams
         if teams is None:
             teams = check_if_default_team_set()
@@ -735,10 +737,44 @@ def _enforce_user_info_access(user_id: str | None, user_api_key_dict: UserAPIKey
     )
 
 
-async def _get_user_info_teams(
-    prisma_client: Any,
+class _UserInfoDataClient(Protocol):
+    @overload
+    async def get_data(self, *, user_id: str) -> "prisma_models.LiteLLM_UserTable | None": ...
+
+    @overload
+    async def get_data(
+        self,
+        *,
+        user_id: str | None,
+        table_name: Literal["key"],
+        query_type: Literal["find_all"],
+    ) -> "Sequence[LiteLLM_VerificationToken] | None": ...
+
+    @overload
+    async def get_data(
+        self,
+        *,
+        team_id_list: list[str],
+        table_name: Literal["team"],
+        query_type: Literal["find_all"],
+    ) -> "Sequence[TeamListResponseObject] | None": ...
+
+
+async def _get_user_info_keys(
+    prisma_client: "_UserInfoDataClient",
     user_id: str | None,
-    user_info: Any | None,
+) -> "Sequence[LiteLLM_VerificationToken] | None":
+    return await prisma_client.get_data(
+        user_id=user_id,
+        table_name="key",
+        query_type="find_all",
+    )
+
+
+async def _get_user_info_teams(
+    prisma_client: "_UserInfoDataClient",
+    user_id: str | None,
+    user_info: "prisma_models.LiteLLM_UserTable",
     user_api_key_dict: UserAPIKeyAuth,
 ) -> tuple[list[TeamListResponseObject], list[TeamListResponseObject] | None]:
     """Fetch and merge teams from membership + user.teams field."""
@@ -759,7 +795,7 @@ async def _get_user_info_teams(
         team_list = teams_1
         team_id_list = [team.team_id for team in teams_1]
 
-    teams_2: list[TeamListResponseObject] | None = None
+    teams_2: Sequence[TeamListResponseObject] | None = None
     target_team_ids: Final = getattr(user_info, "teams", None)
 
     if target_team_ids and isinstance(target_team_ids, list):
@@ -769,8 +805,8 @@ async def _get_user_info_teams(
             query_type="find_all",
         )
     elif user_api_key_dict.user_id is not None and user_id is None:
-        caller_user_info: Final[object] = await prisma_client.get_data(user_id=user_api_key_dict.user_id)
-        caller_team_ids: Final = getattr(caller_user_info, "teams", None)
+        caller_user_info: Final = await prisma_client.get_data(user_id=user_api_key_dict.user_id)
+        caller_team_ids: Final = caller_user_info.teams if caller_user_info is not None else None
         if caller_team_ids:
             teams_2 = await prisma_client.get_data(
                 team_id_list=caller_team_ids,
@@ -807,7 +843,7 @@ def _redact_scim_enterprise_metadata(
 def _build_user_info_response(
     user_id: str | None,
     user_info: Any | None,
-    keys: list[LiteLLM_VerificationToken] | None,
+    keys: Sequence[LiteLLM_VerificationToken] | None,
     team_list: list[TeamListResponseObject],
     teams_1: list[TeamListResponseObject] | None,
     model_max_budget_usage: dict[str, dict[str, object]] | None = None,
@@ -894,11 +930,7 @@ async def user_info(
         )
 
         ## GET ALL KEYS ##
-        keys: Final = await prisma_client.get_data(
-            user_id=user_id,
-            table_name="key",
-            query_type="find_all",
-        )
+        keys: Final = await _get_user_info_keys(prisma_client, user_id)
 
         response_data: Final = _build_user_info_response(
             user_id=user_id,
@@ -997,6 +1029,14 @@ async def user_info_v2(
     This is the v2 replacement for /user/info, designed to avoid the "god endpoint" problem
     where the old endpoint loaded all keys and teams into memory.
 
+    Note on `spend`: this is the user's running budget counter, which the budget reset job
+    resets whenever `budget_reset_at` elapses (see `budget_duration`): to zero by default,
+    or to the overage above `max_budget` when `budget_rollover` is enabled. It is NOT
+    lifetime or per-period historical spend. For historical spend over a date range, use
+    `/user/daily/activity` or `/user/daily/activity/aggregated`, which read daily spend
+    records that only ever accumulate and are never reset. The two values are expected to
+    diverge once a budget reset has occurred within the queried period.
+
     Access control:
     - Proxy admins can query any user
     - Team admins can query users within their teams
@@ -1077,6 +1117,12 @@ async def user_info_v2(
         raise handle_exception_on_proxy(e)
 
 
+async def _fetch_admin_teams_and_keys_rows(
+    prisma_client: "PrismaClient", sql_query: str
+) -> Sequence[Mapping[str, Sequence[Mapping[str, object]] | None]]:
+    return await prisma_client.db.query_raw(sql_query)
+
+
 async def _get_user_info_for_proxy_admin(user_api_key_dict: UserAPIKeyAuth):
     """
     Admin UI Endpoint - Returns All Teams and Keys when Proxy Admin is querying
@@ -1100,22 +1146,25 @@ async def _get_user_info_for_proxy_admin(user_api_key_dict: UserAPIKeyAuth):
             "Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys"
         )
 
-    results: Final = await prisma_client.db.query_raw(sql_query)
+    results: Final = await _fetch_admin_teams_and_keys_rows(prisma_client, sql_query)
 
     verbose_proxy_logger.debug("results_keys: %s", results)
 
-    _keys_in_db: Final[Sequence[dict[str, object]]] = results[0]["keys"] or []
+    _keys_in_db: Final[Sequence[Mapping[str, object]]] = results[0]["keys"] or []
     # cast all keys to LiteLLM_VerificationToken
     keys_in_db: Final = []
     for key in _keys_in_db:
-        if key.get("models") is None:
-            key["models"] = []
-        keys_in_db.append(LiteLLM_VerificationToken.model_validate(key))
+        key_payload = dict[str, object](key)
+        if key_payload.get("models") is None:
+            key_payload["models"] = []
+        keys_in_db.append(LiteLLM_VerificationToken.model_validate(key_payload))
 
     # cast all teams to LiteLLM_TeamTable
-    _teams_in_db: list[LiteLLM_TeamTable] = results[0]["teams"] or []
-    _teams_in_db = [LiteLLM_TeamTable.model_validate(team) for team in _teams_in_db]
-    _teams_in_db.sort(key=lambda x: getattr(x, "team_alias", "") or "")
+    _teams_rows: Final[Sequence[Mapping[str, object]]] = results[0]["teams"] or []
+    _teams_in_db: Final = sorted(
+        (LiteLLM_TeamTable.model_validate(team) for team in _teams_rows),
+        key=lambda x: getattr(x, "team_alias", "") or "",
+    )
     returned_keys: Final = _process_keys_for_user_info(keys=keys_in_db, all_teams=_teams_in_db)
 
     # Get admin's own user_id and user_info
@@ -1140,7 +1189,7 @@ async def _get_user_info_for_proxy_admin(user_api_key_dict: UserAPIKeyAuth):
 
 
 def _process_keys_for_user_info(
-    keys: list[LiteLLM_VerificationToken] | None,
+    keys: Sequence[LiteLLM_VerificationToken] | None,
     all_teams: list[LiteLLM_TeamTable] | list[TeamListResponseObject] | None,
 ):
     from litellm.constants import UI_SESSION_TOKEN_TEAM_ID
@@ -1231,7 +1280,7 @@ def _update_internal_user_params(data_json: dict, data: UpdateUserRequest | Upda
 
 
 async def _schedule_user_update_audit_log(
-    response: dict[str, Any],
+    response: Mapping[str, object],
     existing_user_row: BaseModel | None,
     litellm_changed_by: str | None,
     user_api_key_dict: UserAPIKeyAuth,
@@ -1358,7 +1407,7 @@ async def _update_single_user_helper(
 
     Returns the updated user data or raises an exception on failure.
     """
-    from litellm.proxy.proxy_server import litellm_proxy_admin_name, prisma_client
+    from litellm.proxy.proxy_server import general_settings, litellm_proxy_admin_name, prisma_client
 
     if prisma_client is None:
         raise Exception("Not connected to DB!")
@@ -1373,7 +1422,7 @@ async def _update_single_user_helper(
 
     data_json: Final[dict] = user_request.model_dump(exclude_unset=True)
     non_default_values = _update_internal_user_params(data_json=data_json, data=user_request)
-    _hash_password_in_dict(non_default_values)
+    _hash_password_in_dict(non_default_values, general_settings)
 
     existing_user_row: BaseModel | None = None
     if user_request.user_id:
@@ -2687,6 +2736,11 @@ async def get_user_daily_activity(
 
     Meant to optimize querying spend data for analytics for a user.
 
+    Reads daily spend records that only ever accumulate and are never affected by budget
+    resets. Their total can legitimately exceed the `spend` field returned by
+    `/v2/user/info`, which is a running budget counter that every budget reset sets back
+    to zero (or to the overage above `max_budget` when `budget_rollover` is enabled).
+
     Returns:
     (by date)
     - spend
@@ -2800,6 +2854,11 @@ async def get_user_daily_activity_aggregated(
     """
     Aggregated analytics for a user's daily activity without pagination.
     Returns the same response shape as the paginated endpoint with page metadata set to single-page.
+
+    Reads daily spend records that only ever accumulate and are never affected by budget
+    resets. Their total can legitimately exceed the `spend` field returned by
+    `/v2/user/info`, which is a running budget counter that every budget reset sets back
+    to zero (or to the overage above `max_budget` when `budget_rollover` is enabled).
     """
     from litellm.proxy.proxy_server import prisma_client
 
diff --git a/litellm/proxy/management_endpoints/jwt_key_mapping_endpoints.py b/litellm/proxy/management_endpoints/jwt_key_mapping_endpoints.py
index 9f561eadfbd..ccfd5338ec4 100644
--- a/litellm/proxy/management_endpoints/jwt_key_mapping_endpoints.py
+++ b/litellm/proxy/management_endpoints/jwt_key_mapping_endpoints.py
@@ -1,4 +1,6 @@
-from typing import Final
+from collections.abc import Mapping, Sequence
+from datetime import datetime
+from typing import Final, Protocol
 
 from fastapi import APIRouter, Depends, HTTPException, Query
 
@@ -18,7 +20,59 @@ from litellm.repositories.table_repositories import JWTKeyMappingRepository
 router: Final = APIRouter()
 
 
-def _to_response(mapping) -> JWTKeyMappingResponse:
+class _JWTKeyMappingRecord(Protocol):
+    """A ``LiteLLM_JWTKeyMapping`` row, viewed through the columns these endpoints read."""
+
+    @property
+    def id(self) -> str: ...
+
+    @property
+    def jwt_claim_name(self) -> str: ...
+
+    @property
+    def jwt_claim_value(self) -> str: ...
+
+    @property
+    def description(self) -> str | None: ...
+
+    @property
+    def is_active(self) -> bool: ...
+
+    @property
+    def created_at(self) -> datetime: ...
+
+    @property
+    def updated_at(self) -> datetime: ...
+
+    @property
+    def created_by(self) -> str | None: ...
+
+    @property
+    def updated_by(self) -> str | None: ...
+
+
+class _JWTKeyMappingTable(Protocol):
+    """The Prisma table actions these endpoints issue against the JWT key mapping table."""
+
+    async def create(self, *, data: Mapping[str, object]) -> _JWTKeyMappingRecord: ...
+
+    async def find_unique(self, *, where: Mapping[str, object]) -> _JWTKeyMappingRecord | None: ...
+
+    async def update(self, *, where: Mapping[str, object], data: Mapping[str, object]) -> _JWTKeyMappingRecord: ...
+
+    async def delete(self, *, where: Mapping[str, object]) -> _JWTKeyMappingRecord | None: ...
+
+    async def find_many(self, *, skip: int, take: int, order: Mapping[str, str]) -> Sequence[_JWTKeyMappingRecord]: ...
+
+    async def count(self) -> int: ...
+
+
+def _mapping_table(prisma_client: object) -> _JWTKeyMappingTable:
+    """View the JWT key mapping repository's untyped Prisma table through the actions used here."""
+    return JWTKeyMappingRepository(prisma_client).table
+
+
+def _to_response(mapping: _JWTKeyMappingRecord) -> JWTKeyMappingResponse:
     """Convert a Prisma mapping object to a safe response (no hashed token)."""
     return JWTKeyMappingResponse(
         id=mapping.id,
@@ -62,7 +116,7 @@ async def create_jwt_key_mapping(
         if data.description is not None:
             create_data["description"] = data.description
 
-        new_mapping: Final = await JWTKeyMappingRepository(prisma_client).table.create(data=create_data)
+        new_mapping: Final = await _mapping_table(prisma_client).create(data=create_data)
 
         # Invalidate cache
         cache_key: Final = f"jwt_key_mapping:{data.jwt_claim_name}:{data.jwt_claim_value}"
@@ -110,7 +164,7 @@ async def update_jwt_key_mapping(
 
     try:
         # Get old mapping for cache invalidation
-        old_mapping: Final = await JWTKeyMappingRepository(prisma_client).table.find_unique(where={"id": data.id})
+        old_mapping: Final = await _mapping_table(prisma_client).find_unique(where={"id": data.id})
 
         if old_mapping is None:
             raise HTTPException(status_code=404, detail="Mapping not found")
@@ -118,9 +172,7 @@ async def update_jwt_key_mapping(
         cache_key = f"jwt_key_mapping:{old_mapping.jwt_claim_name}:{old_mapping.jwt_claim_value}"
         await user_api_key_cache.async_delete_cache(cache_key)
 
-        updated_mapping: Final = await JWTKeyMappingRepository(prisma_client).table.update(
-            where={"id": data.id}, data=update_data
-        )
+        updated_mapping: Final = await _mapping_table(prisma_client).update(where={"id": data.id}, data=update_data)
 
         if updated_mapping is None:
             raise HTTPException(status_code=404, detail="Mapping not found")
@@ -162,7 +214,7 @@ async def delete_jwt_key_mapping(
 
     try:
         # Get old mapping for cache invalidation
-        old_mapping: Final = await JWTKeyMappingRepository(prisma_client).table.find_unique(where={"id": data.id})
+        old_mapping: Final = await _mapping_table(prisma_client).find_unique(where={"id": data.id})
 
         if old_mapping is None:
             raise HTTPException(status_code=404, detail="Mapping not found")
@@ -170,7 +222,7 @@ async def delete_jwt_key_mapping(
         cache_key: Final = f"jwt_key_mapping:{old_mapping.jwt_claim_name}:{old_mapping.jwt_claim_value}"
         await user_api_key_cache.async_delete_cache(cache_key)
 
-        await JWTKeyMappingRepository(prisma_client).table.delete(where={"id": data.id})
+        await _mapping_table(prisma_client).delete(where={"id": data.id})
         return {"status": "success"}
     except HTTPException:
         raise
@@ -198,12 +250,12 @@ async def list_jwt_key_mappings(
 
     try:
         skip: Final = (page - 1) * size
-        mappings: Final = await JWTKeyMappingRepository(prisma_client).table.find_many(
+        mappings: Final = await _mapping_table(prisma_client).find_many(
             skip=skip,
             take=size,
             order={"created_at": "desc"},
         )
-        total_count: Final = await JWTKeyMappingRepository(prisma_client).table.count()
+        total_count: Final = await _mapping_table(prisma_client).count()
         return {
             "mappings": [_to_response(m) for m in mappings],
             "total_count": total_count,
@@ -235,7 +287,7 @@ async def info_jwt_key_mapping(
         raise HTTPException(status_code=500, detail="Database not connected")
 
     try:
-        mapping: Final = await JWTKeyMappingRepository(prisma_client).table.find_unique(where={"id": id})
+        mapping: Final = await _mapping_table(prisma_client).find_unique(where={"id": id})
         if mapping is None:
             raise HTTPException(status_code=404, detail="Mapping not found")
         return _to_response(mapping)
diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py
index 0d12b012c18..d7d20d168b5 100644
--- a/litellm/proxy/management_endpoints/key_management_endpoints.py
+++ b/litellm/proxy/management_endpoints/key_management_endpoints.py
@@ -18,13 +18,15 @@ import os
 import re
 import secrets
 import traceback
-from collections.abc import Awaitable, Callable, Mapping, Sequence
+from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence
 from datetime import datetime, timedelta, timezone
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, TypeVar, cast
 
 import fastapi
 import yaml
 from fastapi import APIRouter, Depends, Header, HTTPException, Query, Request, status
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_proxy_logger
@@ -110,6 +112,7 @@ from litellm.proxy.management_helpers.team_member_permission_checks import (
     TeamMemberPermissionChecks,
 )
 from litellm.proxy.management_helpers.utils import management_endpoint_wrapper
+from litellm.proxy.spend_tracking.budget_reservation import get_budget_window_start
 from litellm.proxy.spend_tracking.spend_tracking_utils import _is_master_key
 from litellm.proxy.ui_crud_endpoints.proxy_setting_endpoints import (
     get_ui_settings_cached,
@@ -154,6 +157,7 @@ from litellm.types.utils import (
 )
 
 if TYPE_CHECKING:
+    import prisma
     from prisma import Prisma
     from prisma import models as prisma_models
 
@@ -181,6 +185,14 @@ class _TxTables(Protocol):
     litellm_proxymodeltable: TableActions[object]
 
 
+class _ModelParamsUpdate(TypedDict):
+    litellm_params: ReadOnly["prisma.Json"]
+
+
+class _ModelRowWhere(TypedDict):
+    model_id: ReadOnly[str]
+
+
 class _ConfigTableActions(Protocol):
     """Config table surface this module needs; the shared repository seam exposes no ``update``."""
 
@@ -230,6 +242,48 @@ def _config_table(prisma_client: PrismaClient) -> _ConfigTableActions:
     )
 
 
+class _CustomKeyHooksModule(Protocol):
+    user_custom_key_generate: Callable[..., Awaitable[Mapping[str, object]]] | None
+    user_custom_key_update: Callable[..., Awaitable[Mapping[str, object]]] | None
+
+
+def _custom_key_generate_hook(
+    hooks: _CustomKeyHooksModule,
+) -> Callable[..., Awaitable[Mapping[str, object]]] | None:
+    return hooks.user_custom_key_generate
+
+
+def _custom_key_update_hook(
+    hooks: _CustomKeyHooksModule,
+) -> Callable[..., Awaitable[Mapping[str, object]]] | None:
+    return hooks.user_custom_key_update
+
+
+class _LegacyDumpable(Protocol):
+    def dict(self) -> Mapping[str, object]: ...
+
+
+def _legacy_model_dict(row: _LegacyDumpable) -> Mapping[str, object]:
+    return row.dict()
+
+
+def _as_object_dict(values: Mapping[str, object]) -> Mapping[str, object]:
+    return values
+
+
+def _model_items(model: BaseModel) -> Iterator[tuple[str, object]]:
+    return iter(model)
+
+
+class _EnvVarsParam(Protocol):
+    @property
+    def param_value(self) -> Mapping[str, str] | None: ...
+
+
+def _env_vars_param_value(param: _EnvVarsParam) -> Mapping[str, str] | None:
+    return param.param_value
+
+
 async def _check_custom_key_allowed(custom_key_value: str | None) -> None:
     """Raise 403 if custom API keys are disabled and a custom key was provided."""
     if custom_key_value is None:
@@ -684,6 +738,45 @@ def _check_allowed_routes_caller_permission(
     )
 
 
+_READ_ONLY_ALLOWED_ROUTES_PRESET: Final = frozenset(("info_routes",))
+
+
+def _is_safe_preset_route_transition(
+    incoming_allowed_routes: Sequence[str] | None,
+    existing_allowed_routes: Sequence[str] | None,
+) -> bool:
+    """
+    True when every route on BOTH sides is a safe `key_type` preset bucket
+    (empty = full access, which non-admins already get from a default
+    `/key/generate`), with one carve-out: a read-only (`info_routes`) key
+    stays read-only, so widening it needs an admin. Requiring the existing
+    side to be a safe preset keeps an owner from clearing an admin-set
+    custom route restriction (LIT-4139).
+    """
+    incoming: Final = frozenset(incoming_allowed_routes or ())
+    existing: Final = frozenset(existing_allowed_routes or ())
+    if not (incoming | existing) <= _NON_ADMIN_SAFE_ALLOWED_ROUTES_PRESETS:
+        return False
+    return existing != _READ_ONLY_ALLOWED_ROUTES_PRESET or incoming == existing
+
+
+def _enforce_allowed_routes_update_permission(
+    data: UpdateKeyRequest,
+    existing_key_row: LiteLLM_VerificationToken,
+    user_api_key_dict: UserAPIKeyAuth,
+) -> None:
+    if _is_safe_preset_route_transition(
+        incoming_allowed_routes=data.allowed_routes,
+        existing_allowed_routes=existing_key_row.allowed_routes,
+    ):
+        return
+    _check_allowed_routes_caller_permission(
+        allowed_routes=data.allowed_routes,
+        user_api_key_dict=user_api_key_dict,
+        allowed_routes_was_provided="allowed_routes" in data.model_fields_set,
+    )
+
+
 def _check_permissions_caller_permission(
     data: GenerateRequestBase,
     user_api_key_dict: UserAPIKeyAuth,
@@ -910,7 +1003,7 @@ async def _common_key_generation_helper(
 
     # check if user set default key/generate params on config.yaml
     if litellm.default_key_generate_params is not None:
-        for elem in data:
+        for elem in _model_items(data):
             key, value = elem
             if (
                 value is None
@@ -1692,11 +1785,11 @@ async def generate_key_fn(
     - user_id: (str) Unique user id - used for tracking spend across multiple keys for same user id.
     """
     try:
+        from litellm.proxy import proxy_server
         from litellm.proxy._types import CommonProxyErrors
         from litellm.proxy.proxy_server import (
             prisma_client,
             user_api_key_cache,
-            user_custom_key_generate,
         )
 
         if prisma_client is None:
@@ -1723,7 +1816,7 @@ async def generate_key_fn(
             )
 
         custom_key_generate_hook: Final[Callable[..., Awaitable[Mapping[str, object]]] | None] = (
-            user_custom_key_generate
+            _custom_key_generate_hook(proxy_server)
         )
         if custom_key_generate_hook is not None:
             if inspect.iscoroutinefunction(custom_key_generate_hook):
@@ -1892,11 +1985,11 @@ async def generate_service_account_key_fn(
     - user_id: (str) Unique user id - used for tracking spend across multiple keys for same user id.
 
     """
+    from litellm.proxy import proxy_server
     from litellm.proxy._types import CommonProxyErrors
     from litellm.proxy.proxy_server import (
         prisma_client,
         user_api_key_cache,
-        user_custom_key_generate,
     )
 
     if prisma_client is None:
@@ -1924,7 +2017,9 @@ async def generate_service_account_key_fn(
 
     verbose_proxy_logger.debug("entered /key/generate")
 
-    custom_key_generate_hook: Final[Callable[..., Awaitable[Mapping[str, object]]] | None] = user_custom_key_generate
+    custom_key_generate_hook: Final[Callable[..., Awaitable[Mapping[str, object]]] | None] = _custom_key_generate_hook(
+        proxy_server
+    )
     if custom_key_generate_hook is not None:
         if inspect.iscoroutinefunction(custom_key_generate_hook):
             result: Final = await custom_key_generate_hook(data)
@@ -1998,7 +2093,7 @@ def prepare_metadata_fields(data: BaseModel, non_default_values: dict, existing_
             )
         casted_metadata[reserved_field] = existing_value
 
-    data_json: Final[Mapping[str, object]] = data.model_dump(exclude_unset=True, exclude_none=True)
+    data_json: Final = _as_object_dict(data.model_dump(exclude_unset=True, exclude_none=True))
 
     try:
         for k, v in data_json.items():
@@ -2466,26 +2561,34 @@ async def _validate_mcp_servers_for_key_update(
     return normalized_object_permission
 
 
+def _require_prisma_client(prisma_client: PrismaClient | None) -> PrismaClient:
+    if prisma_client is None:
+        raise HTTPException(status_code=500, detail={"error": "Database not connected"})
+    return prisma_client
+
+
 async def _validate_update_key_data(
     data: UpdateKeyRequest,
     existing_key_row: LiteLLM_VerificationToken,
     user_api_key_dict: UserAPIKeyAuth,
     llm_router: Router | None,
     premium_user: bool,
-    prisma_client: Any,
+    prisma_client: PrismaClient | None,
     user_api_key_cache: UserApiKeyCache,
 ) -> None:
     """Validate permissions and constraints for key update."""
+    checked_prisma_client: Final = _require_prisma_client(prisma_client)
+
     # Reject NaN/±inf spend before it can reach the DB / spend counter.
     validate_finite_spend(data.spend)
     validate_budget_duration(data.budget_duration)
 
     _is_proxy_admin: Final = user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN.value
 
-    _check_allowed_routes_caller_permission(
-        allowed_routes=data.allowed_routes,
+    _enforce_allowed_routes_update_permission(
+        data=data,
+        existing_key_row=existing_key_row,
         user_api_key_dict=user_api_key_dict,
-        allowed_routes_was_provided="allowed_routes" in data.model_fields_set,
     )
     _check_passthrough_routes_caller_permission(
         data=data,
@@ -2513,7 +2616,7 @@ async def _validate_update_key_data(
     await TeamMemberPermissionChecks.can_team_member_execute_key_management_endpoint(
         user_api_key_dict=user_api_key_dict,
         route=KeyManagementRoutes.KEY_UPDATE,
-        prisma_client=prisma_client,
+        prisma_client=checked_prisma_client,
         existing_key_row=existing_key_row,
         user_api_key_cache=user_api_key_cache,
     )
@@ -2594,12 +2697,12 @@ async def _validate_update_key_data(
     # _check_key_admin_access that would otherwise require team/org admin status.
     _key_is_team_key: Final = getattr(existing_key_row, "team_id", None) is not None
     can_skip_admin_check: Final = (caller_is_creator or _key_is_team_key) and not _is_budget_change
-    if (not _is_proxy_admin) and prisma_client is not None and not can_skip_admin_check:
+    if (not _is_proxy_admin) and not can_skip_admin_check:
         hashed_key: Final = existing_key_row.token
         await _check_key_admin_access(
             user_api_key_dict=user_api_key_dict,
             hashed_token=hashed_key,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
             user_api_key_cache=user_api_key_cache,
             route=("/key/update (max_budget/spend)" if _is_budget_change else "/key/update"),
         )
@@ -2610,7 +2713,7 @@ async def _validate_update_key_data(
     if _team_id_to_check is not None:
         team_obj = await get_team_object(
             team_id=_team_id_to_check,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
             user_api_key_cache=user_api_key_cache,
             check_db_only=True,
         )
@@ -2626,7 +2729,7 @@ async def _validate_update_key_data(
             await _check_team_key_limits(
                 team_table=team_obj,
                 data=data,
-                prisma_client=prisma_client,
+                prisma_client=checked_prisma_client,
             )
 
     TeamMemberPermissionChecks.enforce_member_can_assign_access_groups(
@@ -2641,7 +2744,7 @@ async def _validate_update_key_data(
         await _check_project_key_limits(
             project_id=_project_id_to_check,
             data=data,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
             user_api_key_cache=user_api_key_cache,
         )
 
@@ -2656,7 +2759,7 @@ async def _validate_update_key_data(
         await _validate_caller_can_assign_key_org(
             user_api_key_dict=user_api_key_dict,
             organization_id=data.organization_id,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
         )
 
     # Check org key limits only when throughput-related fields or organization_id change
@@ -2672,7 +2775,7 @@ async def _validate_update_key_data(
         org_table: Final = await get_org_object(
             org_id=_org_id_to_check,
             user_api_key_cache=user_api_key_cache,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
         )
         if org_table is None:
             raise HTTPException(
@@ -2682,7 +2785,7 @@ async def _validate_update_key_data(
         await _check_org_key_limits(
             org_table=org_table,
             data=data,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
         )
 
     # if team change - check if this is possible
@@ -2712,7 +2815,7 @@ async def _validate_update_key_data(
             data=data,
             team_obj=team_obj,
             existing_key_row=existing_key_row,
-            prisma_client=prisma_client,
+            prisma_client=checked_prisma_client,
             user_api_key_cache=user_api_key_cache,
             is_proxy_admin=_is_proxy_admin,
         )
@@ -2805,13 +2908,13 @@ async def update_key_fn(
     }'
     ```
     """
+    from litellm.proxy import proxy_server
     from litellm.proxy.proxy_server import (
         llm_router,
         premium_user,
         prisma_client,
         proxy_logging_obj,
         user_api_key_cache,
-        user_custom_key_update,
     )
 
     try:
@@ -2842,7 +2945,9 @@ async def update_key_fn(
         )
 
         # Custom key update hook
-        custom_key_update_hook: Final[Callable[..., Awaitable[Mapping[str, object]]] | None] = user_custom_key_update
+        custom_key_update_hook: Final[Callable[..., Awaitable[Mapping[str, object]]] | None] = _custom_key_update_hook(
+            proxy_server
+        )
         if custom_key_update_hook is not None:
             if inspect.iscoroutinefunction(custom_key_update_hook):
                 result: Final = await custom_key_update_hook(data)
@@ -3004,14 +3109,16 @@ async def bulk_update_keys(
     }'
     ```
     """
+    from litellm.proxy import proxy_server
     from litellm.proxy.proxy_server import (
         llm_router,
         prisma_client,
         proxy_logging_obj,
         user_api_key_cache,
-        user_custom_key_update,
     )
 
+    custom_key_update_hook: Final = _custom_key_update_hook(proxy_server)
+
     if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN.value:
         raise HTTPException(
             status_code=403,
@@ -3057,7 +3164,7 @@ async def bulk_update_keys(
                 user_api_key_cache=user_api_key_cache,
                 proxy_logging_obj=proxy_logging_obj,
                 llm_router=llm_router,
-                user_custom_key_update=user_custom_key_update,
+                user_custom_key_update=custom_key_update_hook,
             )
 
             successful_updates.append(
@@ -3135,7 +3242,7 @@ def _build_failed_team_key_update(
         if hasattr(existing_key_row, "model_dump"):
             key_info = existing_key_row.model_dump()
         elif hasattr(existing_key_row, "dict"):
-            key_info = existing_key_row.dict()
+            key_info = dict[str, object](_legacy_model_dict(existing_key_row))
         if key_info:
             key_info.pop("token", None)
 
@@ -3166,14 +3273,16 @@ async def bulk_update_team_keys(
 
     Callable by proxy admins, or by team admins with `KEY_UPDATE` permission.
     """
+    from litellm.proxy import proxy_server
     from litellm.proxy.proxy_server import (
         llm_router,
         prisma_client,
         proxy_logging_obj,
         user_api_key_cache,
-        user_custom_key_update,
     )
 
+    custom_key_update_hook: Final = _custom_key_update_hook(proxy_server)
+
     if prisma_client is None:
         raise HTTPException(
             status_code=500,
@@ -3302,7 +3411,7 @@ async def bulk_update_team_keys(
                 user_api_key_cache=user_api_key_cache,
                 proxy_logging_obj=proxy_logging_obj,
                 llm_router=llm_router,
-                user_custom_key_update=user_custom_key_update,
+                user_custom_key_update=custom_key_update_hook,
                 existing_key_row=existing_by_token[db_token],
             )
 
@@ -3518,6 +3627,63 @@ async def _build_model_max_budget_usage(
     )
 
 
+def _window_max_budget(window: Mapping[str, object]) -> float | None:
+    """A window's max_budget as a float; None when absent or unparseable."""
+    value: Final = window.get("max_budget")
+    if not isinstance(value, (int, float, str)):
+        return None
+    try:
+        return float(value)
+    except ValueError:
+        return None
+
+
+async def _budget_window_usage(
+    window: Mapping[str, object], api_key_hash: str
+) -> tuple[str, Mapping[str, object]] | None:
+    """
+    (budget_duration, usage entry) for one budget window; None when the window
+    has no budget_duration to key it by.
+
+    Reads the same cross-pod counter (spend:key:{hashed_token}:window:{budget_duration})
+    that _virtual_key_multi_budget_check enforces against, passing the same
+    window_duration + window_start so a stale-low counter is re-checked against
+    the LiteLLM_BudgetWindowSpend row instead of a spend-log aggregate.
+    """
+    from litellm.proxy.proxy_server import get_current_spend
+
+    duration: Final = window.get("budget_duration")
+    if not isinstance(duration, str) or not duration:
+        return None
+    spend: Final = await get_current_spend(
+        counter_key=f"spend:key:{api_key_hash}:window:{duration}",
+        fallback_spend=0.0,
+        max_budget=_window_max_budget(window),
+        window_entity_type="Key",
+        window_entity_id=api_key_hash,
+        window_duration=duration,
+        window_start=get_budget_window_start(window),
+    )
+    return duration, MappingProxyType({"current_spend": round(spend, 4)})
+
+
+async def _build_budget_limits_usage(
+    budget_limits: Sequence[object] | str | None, api_key_hash: str
+) -> Mapping[str, Mapping[str, object]] | None:
+    """
+    Current-window spend per budget window, keyed by budget_duration, reported
+    next to the stored budget_limits (which is returned untouched). None when
+    the key has no windows, so the field only appears on keys that have them.
+    """
+    windows: Final = _budget_limit_windows(budget_limits)
+    if not windows:
+        return None
+    usages: Final = await asyncio.gather(
+        *(_budget_window_usage(window=window, api_key_hash=api_key_hash) for window in windows)
+    )
+    return MappingProxyType({duration: usage for duration, usage in (u for u in usages if u is not None)})
+
+
 @router.post(
     "/v2/key/info",
     tags=["key management"],
@@ -3560,7 +3726,6 @@ async def info_key_fn_v2(
                 status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
                 detail={"message": "Malformed request. No keys passed in."},
             )
-
         # Resolve key_aliases to tokens so we never pass token=None (unbounded query)
         tokens_to_query: Final = list(data.keys) if data.keys else []
         if data.key_aliases:
@@ -3602,6 +3767,13 @@ async def info_key_fn_v2(
                     model_max_budget=model_max_budget,
                     user_api_key_cache=model_max_budget_limiter.dual_cache,
                 )
+            if k_token_hash:
+                budget_limits_usage = await _build_budget_limits_usage(
+                    budget_limits=k_dict.get("budget_limits"),
+                    api_key_hash=k_token_hash,
+                )
+                if budget_limits_usage is not None:
+                    k_dict["budget_limits_usage"] = budget_limits_usage
 
             filtered_key_info.append(k_dict)
         return {"key": data.keys, "info": filtered_key_info}
@@ -3613,15 +3785,22 @@ async def info_key_fn_v2(
 @router.get("/key/info", tags=["key management"], dependencies=[Depends(user_api_key_auth)])
 @management_endpoint_wrapper
 async def info_key_fn(
-    key: str | None = fastapi.Query(default=None, description="Key in the request parameters"),
+    key: str | None = fastapi.Query(
+        default=None,
+        description=(
+            "Key to look up. Pass the key's sha256 hash so the raw key stays out of URLs and access "
+            "logs. Example key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa'"
+        ),
+    ),
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
     """
     Retrieve information about a key.
 
     Parameters:
-    - key: str | None (query parameter) - The key to look up. Accepts the plaintext key or its hash.
-      Defaults to the key in the Authorization header.
+    - key: str | None (query parameter) - The key to look up. Accepts the plaintext key or its hash;
+      prefer the hash, since a query parameter is recorded verbatim by any HTTP access log in front
+      of the proxy. Defaults to the key in the Authorization header.
 
     Returns:
     - key: str - The key that was looked up, echoed back as it was passed in
@@ -3638,6 +3817,10 @@ async def info_key_fn(
         - model_max_budget: dict - Per-model budgets, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}
         - model_max_budget_usage: dict | None - Current-window spend per model, present only when
           the key has per-model budgets
+        - budget_limits: list | None - Concurrent budget windows, exactly as stored
+        - budget_limits_usage: dict | None - Current-window spend per budget window, e.g.
+          {"1h": {"current_spend": 0.0009}}, present only when the key has budget windows
+          (read from the same cross-pod spend counter the budget enforcement uses)
         - models: list - Model_name's the key is allowed to call
         - tpm_limit / rpm_limit: int | None - Tokens and requests per minute limits
         - metadata: dict - Metadata for the key, e.g. {"team": "core-infra"}
@@ -3649,7 +3832,7 @@ async def info_key_fn(
 
     Example Curl:
     ```
-    curl -X GET "http://0.0.0.0:4000/key/info?key=sk-test-example-key-123" \
+    curl -X GET "http://0.0.0.0:4000/key/info?key=d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa" \
 -H "Authorization: Bearer sk-1234"
     ```
 
@@ -3705,7 +3888,7 @@ async def info_key_fn(
         except Exception:
             # if using pydantic v1
             key_info = key_info.dict()  # pyright: ignore[reportDeprecated]  # deliberate pydantic v1 fallback
-        key_token_hash: Final = key_info.pop("token")
+        key_token_hash: Final[str | None] = key_info.pop("token")
 
         model_max_budget = key_info.get("model_max_budget") or {}
         budget_table: Final = key_info.get("litellm_budget_table") or {}
@@ -3717,6 +3900,12 @@ async def info_key_fn(
                 model_max_budget=model_max_budget,
                 user_api_key_cache=model_max_budget_limiter.dual_cache,
             )
+        budget_limits_usage: Final = await _build_budget_limits_usage(
+            budget_limits=key_info.get("budget_limits"),
+            api_key_hash=key_token_hash,
+        )
+        if budget_limits_usage is not None:
+            key_info["budget_limits_usage"] = budget_limits_usage
 
         # Attach object_permission if object_permission_id is set
         key_info = await attach_object_permission_to_dict(key_info, prisma_client)
@@ -4301,7 +4490,7 @@ def _transform_verification_tokens_to_deleted_records(
                 "litellm_changed_by": litellm_changed_by,
             }
         )
-        record = deleted_record.model_dump()
+        record = dict[str, object](_as_object_dict(deleted_record.model_dump()))
 
         # Map org_id to organization_id (model uses org_id, but schema expects organization_id)
         org_id_value: object = record.pop("org_id", None)
@@ -4427,28 +4616,29 @@ async def _rotate_master_key(
     if models:
         decrypted_models: Final = proxy_config.decrypt_model_list_from_db(new_models=models)
         verbose_proxy_logger.debug("ABLE TO DECRYPT MODELS - len(decrypted_models): %s", len(decrypted_models))
-        new_models: Final[list[dict[str, object]]] = []
-        for model in decrypted_models:
-            new_model = await _add_model_to_db(
-                model_params=Deployment(**model),
-                user_api_key_dict=user_api_key_dict,
-                prisma_client=prisma_client,
-                new_encryption_key=new_master_key,
-                should_create_model_in_db=False,
-            )
-            if new_model:
-                _dumped = new_model.model_dump(exclude_none=True)
-                _dumped["litellm_params"] = prisma.Json(_dumped["litellm_params"])
-                _dumped["model_info"] = prisma.Json(_dumped["model_info"])
-                new_models.append(_dumped)
-        verbose_proxy_logger.debug("Resetting proxy model table")
-        async with prisma_client.db.tx() as tx_ctx:
+        reencrypted_models: Final = tuple(
+            [
+                reencrypted
+                for model in decrypted_models
+                if (
+                    reencrypted := await _add_model_to_db(
+                        model_params=Deployment(**model),
+                        user_api_key_dict=user_api_key_dict,
+                        prisma_client=prisma_client,
+                        new_encryption_key=new_master_key,
+                        should_create_model_in_db=False,
+                    )
+                )
+            ]
+        )
+        verbose_proxy_logger.debug("Re-encrypting litellm_params on %s model rows", len(reencrypted_models))
+        async with prisma_client.db.tx(timeout=timedelta(minutes=2)) as tx_ctx:
             tx: Final[_TxTables] = tx_ctx
-            await tx.litellm_proxymodeltable.delete_many()
-            verbose_proxy_logger.debug("Creating %s models", len(new_models))
-            await tx.litellm_proxymodeltable.create_many(
-                data=new_models,
-            )
+            for reencrypted_model in reencrypted_models:
+                await tx.litellm_proxymodeltable.update_many(
+                    data=_ModelParamsUpdate(litellm_params=prisma.Json(reencrypted_model.litellm_params)),
+                    where=_ModelRowWhere(model_id=reencrypted_model.model_id),
+                )
         await publish_config_change(redis_cache=coordination_redis_cache(), object_type="litellm_proxymodeltable")
     # 3. process config table
     try:
@@ -4458,14 +4648,14 @@ async def _rotate_master_key(
 
     if config:
         """If environment_variables is found, decrypt it and encrypt it with the new master key"""
-        environment_variables_dict = {}
+        environment_variables_dict: Mapping[str, str] | None = {}
         for c in config:
             if c.param_name == "environment_variables":
-                environment_variables_dict = c.param_value
+                environment_variables_dict = _env_vars_param_value(c)
 
         if environment_variables_dict:
             decrypted_env_vars: Final = proxy_config._decrypt_and_set_db_env_variables(
-                environment_variables=environment_variables_dict
+                environment_variables=dict[str, str](environment_variables_dict)
             )
             encrypted_env_vars: Final = proxy_config._encrypt_env_variables(
                 environment_variables=decrypted_env_vars,
@@ -4531,7 +4721,7 @@ async def _rotate_master_key(
                     updated_patch=decrypted_cred,
                     new_encryption_key=new_master_key,
                 )
-                _cred_data = encrypted_cred.model_dump(exclude_none=True)
+                _cred_data = dict[str, object](_as_object_dict(encrypted_cred.model_dump(exclude_none=True)))
                 if "credential_values" in _cred_data:
                     _cred_data["credential_values"] = prisma.Json(_cred_data["credential_values"])
                 if "credential_info" in _cred_data:
@@ -5160,7 +5350,7 @@ def _validate_reset_spend_value(reset_to: object, key_in_db: LiteLLM_Verificatio
 
     max_budget = key_in_db.max_budget
     if key_in_db.litellm_budget_table is not None:
-        budget_max_budget: Final = getattr(key_in_db.litellm_budget_table, "max_budget", None)
+        budget_max_budget: Final[float | None] = getattr(key_in_db.litellm_budget_table, "max_budget", None)
         if budget_max_budget is not None:
             if max_budget is None or budget_max_budget < max_budget:
                 max_budget = budget_max_budget
diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py
index 012aec38458..ca66640bf46 100644
--- a/litellm/proxy/management_endpoints/model_management_endpoints.py
+++ b/litellm/proxy/management_endpoints/model_management_endpoints.py
@@ -54,7 +54,10 @@ from litellm.proxy.common_utils.config_sync_pubsub import (
     coordination_redis_cache,
     publish_config_change,
 )
-from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value_helper
+from litellm.proxy.common_utils.encrypt_decrypt_utils import (
+    decrypt_value_helper,
+    encrypt_value_helper,
+)
 from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
 from litellm.proxy.management_endpoints.common_utils import _is_user_team_admin
 from litellm.proxy.management_endpoints.team_endpoints import (
@@ -543,7 +546,7 @@ def update_db_model(db_model: Deployment, updated_patch: updateDeployment) -> Pr
         _raise_if_ptu_cost_attribution_disabled(updated_patch.model_info.model_dump(exclude_none=True))
     merged_model_name: Final = updated_patch.model_name or db_model.model_name
     merged_litellm_params: Final = db_model.litellm_params.model_dump(exclude_none=True)
-    merged_model_info: Final = db_model.model_info.model_dump(exclude_none=True)
+    merged_model_info: Final[dict[str, object]] = db_model.model_info.model_dump(exclude_none=True)
 
     # update litellm params
     if updated_patch.litellm_params:
@@ -701,6 +704,12 @@ async def patch_model(
                 param="blocked",
             )
 
+        ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=patch_data.litellm_params,
+            user_api_key_dict=user_api_key_dict,
+            existing_litellm_params=db_model.litellm_params,
+        )
+
         _raise_on_strategy_router_write_violation(
             incoming_params=patch_data.litellm_params,
             existing_params=db_model.litellm_params,
@@ -1464,6 +1473,32 @@ class ModelManagementAuthChecks:
             )
         return True
 
+    @staticmethod
+    def can_user_attach_credential(
+        litellm_params: GenericLiteLLMParams | None,
+        user_api_key_dict: UserAPIKeyAuth,
+        existing_litellm_params: GenericLiteLLMParams | None = None,
+    ) -> Literal[True]:
+        if litellm_params is None or litellm_params.litellm_credential_name is None:
+            return True
+        if existing_litellm_params is not None and existing_litellm_params.litellm_credential_name is not None:
+            existing_credential_name: Final = decrypt_value_helper(
+                value=existing_litellm_params.litellm_credential_name,
+                key="litellm_credential_name",
+                exception_type="debug",
+                return_original_value=True,
+            )
+            if litellm_params.litellm_credential_name == existing_credential_name:
+                return True
+        if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN:
+            return True
+        raise ProxyException(
+            message=f"Only a proxy admin can attach a stored credential (litellm_credential_name) to a model. Your role={user_api_key_dict.user_role}.",
+            type=ProxyErrorTypes.auth_error.value,
+            code=status.HTTP_403_FORBIDDEN,
+            param="litellm_credential_name",
+        )
+
     @staticmethod
     async def allow_team_model_action(
         model_params: Deployment | updateDeployment,
@@ -1786,6 +1821,11 @@ async def add_new_model(
             premium_user=premium_user,
         )
 
+        ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=model_params.litellm_params,
+            user_api_key_dict=user_api_key_dict,
+        )
+
         _raise_on_strategy_router_write_violation(
             incoming_params=model_params.litellm_params,
             existing_params=None,
@@ -1958,6 +1998,12 @@ async def update_model(
             premium_user=premium_user,
         )
 
+        ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=model_params.litellm_params,
+            user_api_key_dict=user_api_key_dict,
+            existing_litellm_params=deployment.litellm_params,
+        )
+
         _raise_on_strategy_router_write_violation(
             incoming_params=model_params.litellm_params,
             existing_params=deployment.litellm_params,
@@ -1982,7 +2028,7 @@ async def update_model(
 
             ### MERGE WITH EXISTING DATA ###
             merged_dictionary: Final = {}
-            _mp: Final = model_params.litellm_params.dict()
+            _mp: Final[dict[str, object]] = model_params.litellm_params.dict()
 
             for key, value in _mp.items():
                 if value is not None:
diff --git a/litellm/proxy/management_endpoints/organization_endpoints.py b/litellm/proxy/management_endpoints/organization_endpoints.py
index 9198aa35f3f..5e38a016099 100644
--- a/litellm/proxy/management_endpoints/organization_endpoints.py
+++ b/litellm/proxy/management_endpoints/organization_endpoints.py
@@ -487,12 +487,11 @@ async def new_organization(
         for m in data.models:
             await can_user_call_model(m, llm_router=llm_router, user_object=user_object_correct_type)
 
-    organization_row: Final = LiteLLM_OrganizationTable(
-        **data.json(exclude_none=True),
-        object_permission_id=object_permission_id,
-        created_by=user_api_key_dict.user_id or litellm_proxy_admin_name,
-        updated_by=user_api_key_dict.user_id or litellm_proxy_admin_name,
-    )
+    organization_payload: Final = _STR_OBJECT_DICT_ADAPTER.validate_python(data.json(exclude_none=True))
+    organization_payload["object_permission_id"] = object_permission_id
+    organization_payload["created_by"] = user_api_key_dict.user_id or litellm_proxy_admin_name
+    organization_payload["updated_by"] = user_api_key_dict.user_id or litellm_proxy_admin_name
+    organization_row: Final = LiteLLM_OrganizationTable.model_validate(organization_payload)
 
     for field in LiteLLM_ManagementEndpoint_MetadataFields:
         if getattr(data, field, None) is not None:
@@ -644,7 +643,7 @@ async def update_organization(
         )
 
     # Transform UI payload to expected format
-    raw_data: Final = await request.json()
+    raw_data: Final[dict[str, object]] = await request.json()
     raw_data_with_flat_budget_fields: Final = handle_nested_budget_structure_in_organization_update_request(raw_data)
 
     # Create validated data model
@@ -691,7 +690,7 @@ async def update_organization(
     # Merge metadata from existing organization with updated metadata
     if updated_organization_row_json.get("metadata") is not None:
         existing_metadata: Final = existing_organization_row.metadata or {}
-        updated_metadata: Final = updated_organization_row_json.get("metadata", {})
+        updated_metadata: Final[dict[str, object]] = updated_organization_row_json.get("metadata", {})
         merged_metadata: Final[Mapping[str, object]] = _update_dictionary(
             existing_dict=cast(  # cast-ok: prisma de-serializes a Json column to the plain python dict it stores
                 "dict[str, object]", existing_metadata
diff --git a/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py b/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py
index 108e6a7b47d..f58f3722741 100644
--- a/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py
+++ b/litellm/proxy/management_endpoints/policy_endpoints/endpoints.py
@@ -13,7 +13,7 @@ import copy
 import json
 import os
 from collections.abc import AsyncIterator
-from typing import TYPE_CHECKING, Any, Final, Literal, cast
+from typing import TYPE_CHECKING, Final, Literal, cast
 
 from fastapi import APIRouter, Depends, HTTPException, Request
 from fastapi.responses import Response, StreamingResponse
@@ -90,7 +90,7 @@ class _ApplyPoliciesResultBase(TypedDict):
 class ApplyPoliciesResult(_ApplyPoliciesResultBase, total=False):
     """Result of apply_policies. agent_response set when agent_id provided."""
 
-    agent_response: Any
+    agent_response: object
 
 
 class _ApplyPoliciesPerItemResultBase(TypedDict):
@@ -103,7 +103,7 @@ class _ApplyPoliciesPerItemResultBase(TypedDict):
 class ApplyPoliciesPerItemResult(_ApplyPoliciesPerItemResultBase, total=False):
     """Result for one input when using inputs_list. agent_response set when agent_id provided."""
 
-    agent_response: Any
+    agent_response: object
 
 
 class ApplyPoliciesListResult(TypedDict):
@@ -295,8 +295,8 @@ async def test_policies_and_guardrails(
     from litellm.proxy.proxy_server import chat_completion, proxy_logging_obj
     from litellm.proxy.utils import handle_exception_on_proxy
 
-    def _serialize_chat_response(response: Any) -> Any:
-        if hasattr(response, "model_dump"):
+    def _serialize_chat_response(response: object) -> object:
+        if isinstance(response, BaseModel):
             return response.model_dump(exclude_unset=True)
         if isinstance(response, dict):
             return response
@@ -306,7 +306,7 @@ async def test_policies_and_guardrails(
         inputs: GenericGuardrailAPIInputs,
         agent_id: str,
         user_api_key_dict: UserAPIKeyAuth,
-    ) -> Any:
+    ) -> object:
         body: Final = _chat_body_from_inputs(inputs, agent_id, data.request_data)
         req: Final = _request_with_json_body(body)
         resp: Final = Response()
diff --git a/litellm/proxy/management_endpoints/scim/scim_v2.py b/litellm/proxy/management_endpoints/scim/scim_v2.py
index ded57815e91..069f86c852c 100644
--- a/litellm/proxy/management_endpoints/scim/scim_v2.py
+++ b/litellm/proxy/management_endpoints/scim/scim_v2.py
@@ -29,6 +29,7 @@ import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm._uuid import uuid
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+from litellm.models.user import SCIMPlaceholder
 from litellm.proxy._types import (
     LiteLLM_TeamTable,
     LiteLLM_UserTable,
@@ -585,6 +586,37 @@ async def _users_named_by_member_value(
     return tuple(dict.fromkeys(row.user_id for row in rows))
 
 
+async def _accounts_named_by_member_value(value: str, prisma_client: PrismaClient) -> tuple[str, ...]:
+    """Every user id this member value names, by user id, SSO identity or email.
+
+    Classification needs to know whether the value is one account's ``user_id`` and
+    whether it names any other account, so all three fields are read in one pass. The
+    id is compared exactly and unstripped, as a primary key lookup would; the
+    identities compare as ``_users_named_by_member_value`` describes. Two rows are
+    enough to tell one account from several, so the read stops there. Only a full
+    read that lacks the row keyed by the value leaves that row's existence open, and
+    only then is the id read on its own.
+    """
+    subject: Final = value.strip()
+    email: Final[_CaseInsensitiveMatch] = {"equals": subject, "mode": "insensitive"}
+    users: Final = _table(UserRepository(prisma_client))
+    rows: Final = await users.find_many(
+        where={  # mutable-ok: Prisma filter
+            "OR": [  # mutable-ok: Prisma filter
+                {"user_id": value},  # mutable-ok: Prisma filter
+                {"sso_user_id": subject},  # mutable-ok: Prisma filter
+                {"user_email": email},  # mutable-ok: Prisma filter
+            ],
+        },
+        take=2,
+    )
+    named: Final = tuple(dict.fromkeys(row.user_id for row in rows))
+    if len(named) < 2 or value in named:
+        return named
+    keyed: Final = await users.find_unique(where={"user_id": value})
+    return named if keyed is None else (value, *named)
+
+
 async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient) -> _ClassifiedGroupMember:
     """
     Decide what a single SCIM group member refers to.
@@ -627,11 +659,9 @@ async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient
     if member_type == "group":
         return _SkippedGroupMember(value=value, reason="nested_group")
 
-    user: Final = await _table(UserRepository(prisma_client)).find_unique(where={"user_id": value})
-    if user is not None:
-        shared_with: Final = tuple(
-            other for other in await _users_named_by_member_value(value, prisma_client) if other != value
-        )
+    named: Final = await _accounts_named_by_member_value(value, prisma_client)
+    if value in named:
+        shared_with: Final = tuple(other for other in named if other != value)
         if shared_with:
             verbose_proxy_logger.warning(
                 "SCIM: group member '%s' is one account's user id and is also account '%s' by SSO identity or email, "
@@ -651,7 +681,6 @@ async def _classify_group_member(member: SCIMMember, prisma_client: PrismaClient
         if team is not None and _team_metadata_has_scim_provenance(team.metadata):
             return _SkippedGroupMember(value=value, reason="existing_team")
 
-    named: Final = await _users_named_by_member_value(value, prisma_client)
     if len(named) == 1:
         verbose_proxy_logger.info(
             "SCIM: group member '%s' matched user_id '%s' by SSO identity or email",
@@ -1834,6 +1863,89 @@ async def delete_user(
         raise handle_exception_on_proxy(e)
 
 
+@scim_router.get(
+    "/placeholders",
+    response_model=tuple[SCIMPlaceholder, ...],
+    dependencies=(Depends(user_api_key_auth),),
+)
+async def list_placeholders() -> tuple[SCIMPlaceholder, ...]:
+    """
+    List user rows whose id is another account's SSO identity or email.
+
+    An earlier release provisioned a group member it could not match as a user keyed
+    by the raw member value, and that row now shadows the account the value really
+    names, so every push of that member is refused. This lists those rows so an
+    operator can fold each one into the account it shadows with
+    ``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of
+    its own or owns virtual keys is left out: someone uses that account.
+    """
+    try:
+        prisma_client: Final = await _get_prisma_client_or_raise_exception()
+        async with prisma_client.tx() as tx:
+            return await UserRepository(prisma_client).find_shadowing_placeholders(tx)
+    except Exception as e:
+        raise handle_exception_on_proxy(e)
+
+
+def _placeholder_rejection(placeholder: LiteLLM_UserTable, resolved: tuple[str, ...], key_count: int) -> str | None:
+    if placeholder.sso_user_id is not None:
+        return f"User '{placeholder.user_id}' has an SSO identity of its own, so it is an account someone signs in to"
+    if key_count:
+        return f"User '{placeholder.user_id}' owns {key_count} virtual keys. Move or delete them before merging it"
+    if not resolved:
+        return f"User '{placeholder.user_id}' shadows no account: no other user has that id as SSO identity or email"
+    if len(resolved) > 1:
+        return (
+            f"User '{placeholder.user_id}' names {len(resolved)} accounts ({', '.join(resolved)}). Resolve that first"
+        )
+    return None
+
+
+@scim_router.post(
+    "/placeholders/{user_id}/merge",
+    response_model=SCIMPlaceholderMergeResult,
+    dependencies=(Depends(user_api_key_auth),),
+)
+async def merge_placeholder(
+    user_id: str = Path(..., title="User ID"),
+) -> SCIMPlaceholderMergeResult:
+    """
+    Fold a placeholder user into the one account its id names by SSO identity or email.
+
+    The account is added to every team the placeholder is on, then the placeholder is
+    deleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group
+    push resolves the member value to the real account. Refused with 409 when the row
+    has an SSO identity of its own, owns virtual keys, or names no account or several.
+    """
+    try:
+        prisma_client: Final = await _get_prisma_client_or_raise_exception()
+        placeholder: Final = await _check_user_exists(user_id)
+        resolved: Final = tuple(
+            other for other in await _users_named_by_member_value(user_id, prisma_client, take=None) if other != user_id
+        )
+        owned_keys: Final[_UserIdWhere] = {"user_id": user_id}
+        keys: Final = await _table(VerificationTokenRepository(prisma_client)).find_many(where=owned_keys)
+        rejection: Final = _placeholder_rejection(placeholder, resolved, len(keys))
+        if rejection is not None:
+            detail: Final[_ScimErrorDetail] = {"error": rejection}
+            raise HTTPException(status_code=409, detail=detail)
+
+        target_user_id: Final = resolved[0]
+        team_ids: Final = tuple(placeholder.teams)
+        for team_id in team_ids:
+            await _add_user_to_team(user_id=target_user_id, team_id=team_id)
+        await delete_user(user_id=user_id)
+        await _recompute_scim_member_roles(prisma_client, (target_user_id,))
+        verbose_proxy_logger.info(
+            "SCIM: merged placeholder user '%s' into '%s', moving teams %s", user_id, target_user_id, team_ids
+        )
+        return SCIMPlaceholderMergeResult(
+            placeholder_user_id=user_id, merged_into_user_id=target_user_id, team_ids=team_ids
+        )
+    except Exception as e:
+        raise handle_exception_on_proxy(e)
+
+
 def _parse_member_entry(entry: object) -> SCIMMember | None:
     """Parse one entry of a SCIM patch value, or None when it carries no id."""
     if isinstance(entry, str):
diff --git a/litellm/proxy/management_endpoints/sso/saml_sso.py b/litellm/proxy/management_endpoints/sso/saml_sso.py
index 3e67b211f62..466b100ea1f 100644
--- a/litellm/proxy/management_endpoints/sso/saml_sso.py
+++ b/litellm/proxy/management_endpoints/sso/saml_sso.py
@@ -36,6 +36,7 @@ from pydantic import ValidationError
 
 from litellm._logging import verbose_proxy_logger
 from litellm.caching.dual_cache import DualCache
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
 from litellm.proxy.management_endpoints.types import CustomOpenID, get_litellm_user_role
 from litellm.proxy.utils import get_custom_url
 
@@ -131,7 +132,7 @@ class SAMLAuthHandler:
 
     @staticmethod
     def _is_https(request: Request) -> bool:
-        return SAMLAuthHandler._base_url(request).startswith("https")
+        return IPAddressUtils.is_request_https(request)
 
     @staticmethod
     def _acs_url(request: Request) -> str:
diff --git a/litellm/proxy/management_endpoints/team_callback_endpoints.py b/litellm/proxy/management_endpoints/team_callback_endpoints.py
index 08346983f32..c2f5dbb4032 100644
--- a/litellm/proxy/management_endpoints/team_callback_endpoints.py
+++ b/litellm/proxy/management_endpoints/team_callback_endpoints.py
@@ -252,7 +252,7 @@ async def add_team_callbacks(
     Use this if if you want different teams to have different success/failure callbacks
 
     Parameters:
-    - callback_name (Literal["langfuse", "langsmith", "gcs"], required): The name of the callback to add
+    - callback_name (str, required): The name of the callback to add, e.g. "langfuse", "langsmith", "gcs", "newrelic". The value is validated against the callbacks that support team-scoped credentials
     - callback_type (Literal["success", "failure", "success_and_failure"], required): The type of callback to add. One of:
         - "success": Callback for successful LLM calls
         - "failure": Callback for failed LLM calls
@@ -268,6 +268,8 @@ async def add_team_callbacks(
         - langsmith_api_key: The API key for the Langsmith callback
         - langsmith_project: The project for the Langsmith callback
         - langsmith_base_url: The base URL for the Langsmith callback
+        - newrelic_api_key: The ingest license key for the team's New Relic account; routes both LLM/agent traces and cost metrics to that account. Requires the proxy to run with LITELLM_OTEL_V2=true, otherwise this callback is rejected with a 400
+        - newrelic_region: The New Relic region for the team's account ("us" or "eu"), riding the team's own key
 
     Example curl:
     ```
diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py
index c6d7975b75e..714cf252e69 100644
--- a/litellm/proxy/management_endpoints/team_endpoints.py
+++ b/litellm/proxy/management_endpoints/team_endpoints.py
@@ -5148,6 +5148,7 @@ async def list_team_v2(
 
     # Get teams with pagination
     if use_deleted_table:
+        # LiteLLM_DeletedTeamTable has no litellm_model_table relation, unlike below
         teams = await _deleted_team_db(prisma_client).find_many(
             where=where_conditions,
             skip=skip,
@@ -5162,6 +5163,7 @@ async def list_team_v2(
             skip=skip,
             take=page_size,
             order=order_by if order_by else {"created_at": "desc"},  # Default sort
+            include=_INCLUDE_MODEL_TABLE,
         )
         # Get total count for pagination
         total_count = await _team_db(prisma_client).count(where=where_conditions)
diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py
index 613508da22b..1feefa5725d 100644
--- a/litellm/proxy/management_endpoints/ui_sso.py
+++ b/litellm/proxy/management_endpoints/ui_sso.py
@@ -89,9 +89,10 @@ from litellm.proxy._types import (
 from litellm.proxy.auth.auth_checks import ExperimentalUIJWTToken, get_user_object
 from litellm.proxy.auth.auth_utils import (
     _get_request_ip_address,
-    _has_user_setup_sso,
+    has_user_setup_sso,
 )
 from litellm.proxy.auth.handle_jwt import JWTHandler
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 from litellm.proxy.common_utils.admin_ui_utils import (
     admin_ui_disabled,
@@ -502,7 +503,7 @@ def _set_nested_metadata_value(metadata: dict[str, object], key_path: str, value
     placeholder: Final = "\x00"
     parts = key_path.replace("\\.", placeholder).split(".")
     parts = [p.replace(placeholder, ".") for p in parts]
-    current: Any = metadata
+    current: dict[str, object] = metadata
     for part in parts[:-1]:
         existing = current.get(part)
         if not isinstance(existing, dict):
@@ -1118,7 +1119,7 @@ async def google_login(
             request=request,
         )
         if sso_redirect is not None:
-            _persist_return_to_cookie(sso_redirect, return_to)
+            _persist_return_to_cookie(sso_redirect, return_to, request)
         return sso_redirect
 
     from fastapi.responses import HTMLResponse
@@ -1138,7 +1139,7 @@ async def google_login(
     # helper the SSO branch uses, so /login can resume the connect flow instead of dead-ending at the
     # dashboard. One implementation → the two sign-in branches cannot diverge (and the login form always
     # renders, since the helper never raises on a bad return_to).
-    _persist_return_to_cookie(form_response, return_to)
+    _persist_return_to_cookie(form_response, return_to, request)
     return form_response
 
 
@@ -2617,7 +2618,7 @@ async def get_ui_settings(request: Request):
     _proxy_base_url: Final = os.getenv("PROXY_BASE_URL", None)
     _logout_url: Final = os.getenv("PROXY_LOGOUT_URL", None)
     _api_doc_base_url: Final = os.getenv("LITELLM_UI_API_DOC_BASE_URL", None)
-    _is_sso_enabled: Final = _has_user_setup_sso()
+    _is_sso_enabled: Final = has_user_setup_sso()
     disable_expensive_db_queries: Final = (
         proxy_state.get_proxy_state_variable("spend_logs_row_count") > MAX_SPENDLOG_ROWS_TO_QUERY
     )
@@ -2741,6 +2742,7 @@ async def _sso_return_to_redirect(
     jwt_token: str,
     redis_usage_cache,
     user_api_key_cache,
+    request: Request,
 ) -> RedirectResponse | None:
     """Resolve the post-SSO redirect for a ``return_to``, or None to fall through to the dashboard.
 
@@ -2759,7 +2761,7 @@ async def _sso_return_to_redirect(
 
     if _is_same_origin_return_path(return_to):
         redirect_response = RedirectResponse(url=return_to, status_code=303)
-        redirect_response.set_cookie(key="token", value=jwt_token)
+        set_session_token_cookie(redirect_response, request, jwt_token)
         redirect_response.delete_cookie("litellm_cp_return_to")
         return redirect_response
 
@@ -2782,7 +2784,25 @@ async def _sso_return_to_redirect(
     return None
 
 
-def _persist_return_to_cookie(response: Response, return_to: str | None) -> None:
+def set_session_token_cookie(response: Response, request: Request, jwt_token: str) -> None:
+    """Set the ``token`` session cookie shared by every sign-in path.
+
+    Not HttpOnly: the dashboard reads this cookie via ``document.cookie`` to
+    populate its own Authorization headers (see
+    ``ui/litellm-dashboard/src/utils/cookieUtils.ts``), so marking it
+    HttpOnly would break login. Secure is still required whenever the public
+    origin is HTTPS, resolved the same trust-aware way as every other
+    litellm cookie."""
+    response.set_cookie(
+        key="token",
+        value=jwt_token,
+        secure=IPAddressUtils.is_request_https(request),
+        httponly=False,
+        samesite="lax",
+    )
+
+
+def _persist_return_to_cookie(response: Response, return_to: str | None, request: Request) -> None:
     """Best-effort: persist a SAFE ``return_to`` on ``response`` as the one-shot ``litellm_cp_return_to``
     cookie so ANY sign-in path — SSO / Okta / generic OR the username/password form — can resume there
     afterwards. THIS is the single source of truth, called by every sign-in branch so they cannot
@@ -2803,6 +2823,7 @@ def _persist_return_to_cookie(response: Response, return_to: str | None) -> None
             max_age=600,
             httponly=True,
             samesite="lax",
+            secure=IPAddressUtils.is_request_https(request),
         )
 
 
@@ -3079,8 +3100,11 @@ class SSOAuthenticationHandler:
                     # incoming request is HTTP (local dev).  Without
                     # ``Secure`` the cookie is sent over plain HTTP,
                     # letting a network observer read and replay the
-                    # state value and bypass this protection.
-                    secure_flag: Final = request is None or request.url.scheme == "https"
+                    # state value and bypass this protection. Trust-aware:
+                    # honors PROXY_BASE_URL / a trusted reverse proxy's
+                    # X-Forwarded-Proto instead of only the literal scheme
+                    # litellm sees on the wire.
+                    secure_flag: Final = request is None or IPAddressUtils.is_request_https(request)
                     redirect_response.set_cookie(
                         key="litellm_oauth_state",
                         value=state_value,
@@ -3628,6 +3652,7 @@ class SSOAuthenticationHandler:
             jwt_token=jwt_token,
             redis_usage_cache=redis_usage_cache,
             user_api_key_cache=user_api_key_cache,
+            request=request,
         )
         if return_to_redirect is not None:
             return return_to_redirect
@@ -3636,7 +3661,7 @@ class SSOAuthenticationHandler:
             litellm_dashboard_ui += "?login=success"
         verbose_proxy_logger.info("Redirecting to %s", litellm_dashboard_ui)
         redirect_response: Final = RedirectResponse(url=litellm_dashboard_ui, status_code=303)
-        redirect_response.set_cookie(key="token", value=jwt_token)
+        set_session_token_cookie(redirect_response, request, jwt_token)
         return redirect_response
 
     @staticmethod
@@ -4076,7 +4101,7 @@ class SSOAuthenticationHandler:
                 )
                 if resp.status_code == 200:
                     try:
-                        userinfo_raw: Final = resp.json()
+                        userinfo_raw: Final[dict[str, object] | None] = resp.json()
                         if not userinfo_raw:
                             # JSON null (None) or empty dict ({}) — no identity claims.
                             # Treat as failure so id_token fallback can be attempted.
@@ -4406,7 +4431,7 @@ class MicrosoftSSOHandler:
     ) -> tuple[list[str], str | None]:
         """Helper function to fetch and parse group data from a URL"""
         response: Final = await async_client.get(url, headers=headers)
-        response_json: Final = response.json()
+        response_json: Final[dict[str, object]] = response.json()
         response_typed: Final = await MicrosoftSSOHandler._cast_graph_api_response_dict(response=response_json)
         group_ids: Final = MicrosoftSSOHandler._get_group_ids_from_graph_api_response(response=response_typed)
         return group_ids, response_typed.get("odata_nextLink")
diff --git a/litellm/proxy/management_helpers/access_group_key_sync.py b/litellm/proxy/management_helpers/access_group_key_sync.py
index 5d43cb29978..c9f93fae0d9 100644
--- a/litellm/proxy/management_helpers/access_group_key_sync.py
+++ b/litellm/proxy/management_helpers/access_group_key_sync.py
@@ -38,6 +38,7 @@ from litellm.proxy._types import (
 from litellm.proxy.auth.auth_checks import (
     _delete_cache_access_object,  # pyright: ignore[reportPrivateUsage]  # the access-group endpoints reach for this same cache primitive
 )
+from litellm.proxy.db.routing_prisma_wrapper import WriterPinnedClient
 from litellm.repositories.table_repositories import AccessGroupRepository
 
 
@@ -72,8 +73,9 @@ _REPOINT_KEY_SQL: Final = (
 
 
 def _raw_executor(prisma_client: object) -> _RawExecutor:
-    """Narrow the untyped Prisma client down to the raw-query call this module makes."""
-    return AccessGroupRepository(prisma_client).prisma_client.db  # pyright: ignore[reportAny]  # untyped Prisma client
+    """Narrow the untyped Prisma client down to the raw-query call this module makes, pinned to the writer."""
+    db: Final = AccessGroupRepository(prisma_client).prisma_client.db  # pyright: ignore[reportAny]  # untyped Prisma client
+    return WriterPinnedClient(db).db  # pyright: ignore[reportAny, reportReturnType]  # untyped Prisma client behind the pin
 
 
 async def _invalidate_access_group_cache(access_group_id: str) -> None:
diff --git a/litellm/proxy/management_helpers/object_permission_utils.py b/litellm/proxy/management_helpers/object_permission_utils.py
index 13080a6cf83..a2fbf80422c 100644
--- a/litellm/proxy/management_helpers/object_permission_utils.py
+++ b/litellm/proxy/management_helpers/object_permission_utils.py
@@ -286,7 +286,7 @@ async def _resolve_mcp_server_identifiers_to_ids(
     return resolved
 
 
-def _rewrite_object_permission_mcp_servers(
+def _drop_stale_object_permission_mcp_servers(
     object_permission: ObjectPermissionDict,
     identifier_to_server_ids: dict[str, set[str]],
 ) -> None:
@@ -294,16 +294,18 @@ def _rewrite_object_permission_mcp_servers(
     if not isinstance(mcp_servers, list):
         return
 
-    normalized_servers: Final[list[str]] = []
-    for identifier in mcp_servers:
-        if identifier == SpecialMCPServerNames.no_mcp_servers.value:
-            normalized_servers.append(SpecialMCPServerNames.no_mcp_servers.value)
-            continue
-        normalized_servers.extend(sorted(identifier_to_server_ids.get(identifier, [])))
-    object_permission["mcp_servers"] = _dedupe_preserving_order(normalized_servers)
+    # Persist original identifiers, never resolved ids: shared-DB multi-region
+    # instances each expand a name/alias to their own local server id at read
+    # time. Only entries resolving to nothing (deleted servers, typos) drop.
+    kept_servers: Final = [
+        identifier
+        for identifier in mcp_servers
+        if identifier == SpecialMCPServerNames.no_mcp_servers.value or identifier_to_server_ids.get(identifier)
+    ]
+    object_permission["mcp_servers"] = _dedupe_preserving_order(kept_servers)
 
 
-def _rewrite_object_permission_mcp_tool_permissions(
+def _drop_stale_object_permission_mcp_tool_permissions(
     object_permission: ObjectPermissionDict,
     identifier_to_server_ids: dict[str, set[str]],
 ) -> None:
@@ -311,31 +313,25 @@ def _rewrite_object_permission_mcp_tool_permissions(
     if not isinstance(mcp_tool_permissions, dict):
         return
 
-    normalized_tool_permissions: Final[dict[str, list[str]]] = {}
-    for identifier, tools in mcp_tool_permissions.items():
-        if not isinstance(tools, list):
-            tools = []
-        for server_id in sorted(identifier_to_server_ids.get(identifier, [])):
-            normalized_tool_permissions.setdefault(server_id, [])
-            normalized_tool_permissions[server_id].extend(tools)
-
     object_permission["mcp_tool_permissions"] = {
-        server_id: _dedupe_preserving_order(tools) for server_id, tools in normalized_tool_permissions.items()
+        identifier: _dedupe_preserving_order(tools if isinstance(tools, list) else [])
+        for identifier, tools in mcp_tool_permissions.items()
+        if identifier_to_server_ids.get(identifier)
     }
 
 
-def _rewrite_object_permission_mcp_identifiers(
+def _drop_stale_object_permission_mcp_identifiers(
     object_permission: ObjectPermissionDict | None,
     identifier_to_server_ids: dict[str, set[str]],
 ) -> None:
     if not object_permission or not isinstance(object_permission, dict):
         return
 
-    _rewrite_object_permission_mcp_servers(
+    _drop_stale_object_permission_mcp_servers(
         object_permission=object_permission,
         identifier_to_server_ids=identifier_to_server_ids,
     )
-    _rewrite_object_permission_mcp_tool_permissions(
+    _drop_stale_object_permission_mcp_tool_permissions(
         object_permission=object_permission,
         identifier_to_server_ids=identifier_to_server_ids,
     )
@@ -615,7 +611,7 @@ async def validate_key_mcp_servers_against_team(
                 "validate_key_mcp_servers_against_team: ignoring stale MCP server identifiers (no longer in registry or DB): %s",
                 sorted(stale_identifiers),
             )
-        _rewrite_object_permission_mcp_identifiers(
+        _drop_stale_object_permission_mcp_identifiers(
             object_permission=object_permission,
             identifier_to_server_ids=identifier_to_server_ids,
         )
diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py
index 9bc90260de1..bf07f4748ef 100644
--- a/litellm/proxy/openai_files_endpoints/files_endpoints.py
+++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py
@@ -70,6 +70,15 @@ from litellm.proxy.openai_files_endpoints.common_utils import (
     validate_managed_files_requirement,
     validate_managed_id_requirement,
 )
+from litellm.proxy.openai_files_endpoints.general_upload_validation import (
+    MB,
+    check_blocked_extension,
+    check_unsafe_filename,
+    check_upload_file_size,
+    coerce_optional_int_setting,
+    coerce_optional_str_list_setting,
+    raise_upload_validation_failure,
+)
 from litellm.proxy.utils import ProxyLogging, is_known_model
 from litellm.repositories.table_repositories import ManagedFileRepository
 from litellm.router import Router
@@ -397,13 +406,23 @@ async def create_file(
     # descriptor and its disk blocks until the collector runs.
     spools: Final[list[BinaryIO]] = []  # mutable-ok: filled as the scan opens handles
     try:
+        unsafe_filename_failure: Final = check_unsafe_filename(file.filename)
+        if unsafe_filename_failure is not None:
+            raise_upload_validation_failure(unsafe_filename_failure)
+
+        max_file_size_mb: Final = coerce_optional_int_setting(general_settings.get("max_file_size_mb"))
+
         # Batch uploads can be gigabytes. Starlette has already spooled the upload
         # to disk, so stream from that handle instead of reading it into memory.
-        # Other uploads are small and stay in-memory bytes.
+        # Other uploads stay in-memory bytes, bounded to max_file_size_mb (plus one
+        # byte, to still tell "exactly at the limit" from "over it") when it is set,
+        # so an oversized upload cannot be read to completion before it is rejected.
         file_source: bytes | BinaryIO
         if purpose == "batch":
             await file.seek(0)
             file_source = file.file
+        elif max_file_size_mb is not None and max_file_size_mb > 0:
+            file_source = await file.read(max_file_size_mb * MB + 1)
         else:
             file_source = await file.read()
         custom_llm_provider = (
@@ -442,6 +461,15 @@ async def create_file(
         # Cast purpose to OpenAIFilesPurpose type
         purpose = cast(OpenAIFilesPurpose, purpose)
 
+        general_size_failure: Final = check_upload_file_size(file_source, max_file_size_mb)
+        if general_size_failure is not None:
+            raise_upload_validation_failure(general_size_failure)
+
+        blocked_extensions: Final = coerce_optional_str_list_setting(general_settings.get("blocked_file_extensions"))
+        blocked_extension_failure: Final = check_blocked_extension(file.filename, blocked_extensions)
+        if blocked_extension_failure is not None:
+            raise_upload_validation_failure(blocked_extension_failure)
+
         if purpose == "batch":
             batch_file_failure: Final = await asyncio.to_thread(
                 check_batch_file_upload,
diff --git a/litellm/proxy/openai_files_endpoints/general_upload_validation.py b/litellm/proxy/openai_files_endpoints/general_upload_validation.py
new file mode 100644
index 00000000000..9d450cb5b8d
--- /dev/null
+++ b/litellm/proxy/openai_files_endpoints/general_upload_validation.py
@@ -0,0 +1,150 @@
+"""
+Upload validation applied to every purpose at POST /v1/files.
+
+batch_file_validation.py checks the JSONL shape of purpose="batch" uploads; this
+module applies the same fast-fail-before-forwarding shape (size cap, blocked
+extensions, path-traversal filenames) regardless of purpose.
+"""
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import BinaryIO, Final, NoReturn, assert_never
+
+from litellm.proxy._types import ProxyException
+from litellm.proxy.common_utils.path_utils import safe_filename
+
+MB: Final = 1024 * 1024
+
+
+def coerce_optional_int_setting(raw: object) -> int | None:
+    """A general_settings value declared as an optional integer, e.g. max_file_size_mb.
+
+    bool is an int subclass, so an explicit isinstance(raw, bool) exclusion is needed
+    or a YAML `true`/`false` would silently pass as 1/0.
+    """
+    if raw is None:
+        return None
+    if isinstance(raw, int) and not isinstance(raw, bool):
+        return raw
+    raise TypeError(f"expected an integer, got {raw!r}")
+
+
+def coerce_optional_str_list_setting(raw: object) -> tuple[str, ...]:
+    """A general_settings value declared as an optional list of strings, e.g. blocked_file_extensions."""
+    if raw is None:
+        return ()
+    if not isinstance(raw, list) or not all(isinstance(item, str) for item in raw):
+        raise TypeError(f"expected a list of strings, got {raw!r}")
+    return tuple(raw)
+
+
+@dataclass(frozen=True, slots=True)
+class UploadedFileTooLarge:
+    size_bytes: int
+    limit_mb: int
+
+
+@dataclass(frozen=True, slots=True)
+class UploadedFileBlockedExtension:
+    extension: str
+
+
+@dataclass(frozen=True, slots=True)
+class UploadedFileUnsafeFilename:
+    filename: str
+
+
+UploadValidationFailure = UploadedFileTooLarge | UploadedFileBlockedExtension | UploadedFileUnsafeFilename
+
+
+def _file_size_bytes(file_source: bytes | BinaryIO) -> int:
+    if isinstance(file_source, bytes):
+        return len(file_source)
+    original_position: Final = file_source.tell()
+    file_source.seek(0, 2)
+    size: Final = file_source.tell()
+    file_source.seek(original_position)
+    return size
+
+
+def check_upload_file_size(
+    file_source: bytes | BinaryIO,
+    max_file_size_mb: int | None,
+) -> UploadedFileTooLarge | None:
+    if max_file_size_mb is None or max_file_size_mb <= 0:
+        return None
+    size_bytes: Final = _file_size_bytes(file_source)
+    if size_bytes > max_file_size_mb * MB:
+        return UploadedFileTooLarge(size_bytes=size_bytes, limit_mb=max_file_size_mb)
+    return None
+
+
+def check_blocked_extension(
+    filename: str | None,
+    blocked_extensions: tuple[str, ...],
+) -> UploadedFileBlockedExtension | None:
+    if not blocked_extensions or not filename:
+        return None
+    try:
+        extension: Final = Path(safe_filename(filename)).suffix.lower()
+    except ValueError:
+        return None
+    # The uploaded name's extension is normalized above; blocked_extensions comes
+    # straight from config.yaml or the DB and is normalized here too, so a
+    # differently-cased entry (".EXE") still catches a lowercase upload.
+    normalized_blocked: Final = frozenset(item.lower() for item in blocked_extensions)
+    if extension and extension in normalized_blocked:
+        return UploadedFileBlockedExtension(extension=extension)
+    return None
+
+
+def check_unsafe_filename(filename: str | None) -> UploadedFileUnsafeFilename | None:
+    """Reject a filename before it can influence any storage path or backend call.
+
+    Only flags a genuine traversal component ("..") or a null byte, so an ordinary
+    name like "report.v2.pdf" or ".env" is never rejected.
+    """
+    if not filename:
+        return None
+    if "\x00" in filename:
+        return UploadedFileUnsafeFilename(filename=filename)
+    normalized: Final = filename.replace("\\", "/")
+    if any(part == ".." for part in normalized.split("/")):
+        return UploadedFileUnsafeFilename(filename=filename)
+    return None
+
+
+def raise_upload_validation_failure(failure: UploadValidationFailure) -> NoReturn:
+    match failure:
+        case UploadedFileTooLarge(size_bytes=size_bytes, limit_mb=limit_mb):
+            raise ProxyException(
+                message=(
+                    f"Uploaded file exceeds the configured max_file_size_mb of {limit_mb} MB "
+                    f"(read stopped at {size_bytes / MB:.1f} MB). The file was not forwarded to the provider."
+                ),
+                type="invalid_request_error",
+                param="file",
+                code=413,
+            )
+        case UploadedFileBlockedExtension(extension=extension):
+            raise ProxyException(
+                message=(
+                    f"File extension '{extension}' is blocked by this proxy's blocked_file_extensions "
+                    "setting. The file was not forwarded to the provider."
+                ),
+                type="invalid_request_error",
+                param="file",
+                code=400,
+            )
+        case UploadedFileUnsafeFilename(filename=filename):
+            raise ProxyException(
+                message=(
+                    f"Filename '{filename}' is not allowed: directory traversal sequences are not "
+                    "permitted in uploaded file names. The file was not forwarded to the provider."
+                ),
+                type="invalid_request_error",
+                param="file",
+                code=400,
+            )
+        case _:
+            assert_never(failure)
diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py
index 525e7099b89..b48b8d81494 100644
--- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py
+++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py
@@ -6,13 +6,15 @@ Provider-specific Pass-Through Endpoints
 Use litellm with Anthropic SDK, Vertex AI SDK, Cohere SDK, etc.
 """
 
+from __future__ import annotations
+
 import hmac
 import json
 import os
 import re
 from collections.abc import Callable, Mapping
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Annotated, Any, Final, cast
+from typing import TYPE_CHECKING, Annotated, Final, cast
 
 import httpx
 from fastapi import APIRouter, Depends, HTTPException, Request, Response, WebSocket
@@ -28,6 +30,7 @@ from litellm.constants import (
 )
 from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix
 from litellm.llms.anthropic.common_utils import AnthropicModelInfo
+from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
 from litellm.llms.vertex_ai.vertex_llm_base import VertexBase
 from litellm.proxy._types import *
 from litellm.proxy.auth.handle_jwt import JWTHandler
@@ -51,6 +54,7 @@ from litellm.proxy.pass_through_endpoints.pass_through_endpoints import (
     create_websocket_passthrough_route,
     websocket_passthrough_request,
 )
+from litellm.proxy.utils import ProxyLogging as ProxyLoggingType
 from litellm.proxy.utils import is_known_model
 from litellm.proxy.vector_store_endpoints.utils import (
     assert_proxy_admin_for_vector_store_index_management,
@@ -65,18 +69,23 @@ from litellm.types.passthrough_endpoints.pass_through_endpoints import (
 )
 from litellm.types.passthrough_endpoints.vertex_ai import VertexPassThroughCredentials
 from litellm.types.utils import LlmProviders
+from litellm.types.vector_stores import LiteLLM_ManagedVectorStore
 from litellm.utils import ProviderConfigManager
 
 from .passthrough_endpoint_router import PassthroughEndpointRouter
 
 if TYPE_CHECKING:
+    from litellm.proxy.proxy_server import ProxyConfig as _ProxyConfig
     from litellm.router import Router
 
+    ProxyConfig = _ProxyConfig  # rebind-ok: conditional type alias
+else:
+    ProxyConfig = Any  # rebind-ok: runtime fallback
+
 vertex_llm_base: Final = VertexBase()
 router: Final = APIRouter()
 openai_passthrough_router: Final = APIRouter()
 default_vertex_config: Final = None
-
 passthrough_endpoint_router: Final = PassthroughEndpointRouter()
 
 
@@ -113,7 +122,21 @@ def is_passthrough_request_streaming(request_body: object) -> bool:
     return bool(request_body.get("stream", False))
 
 
-def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, Any]:
+def _optional_str(value: object) -> str | None:
+    return value if isinstance(value, str) else None
+
+
+def _string_keyed_mapping(value: object) -> Mapping[str, object] | None:
+    if isinstance(value, Mapping):
+        return value
+    return None
+
+
+async def _json_request_body(request: Request) -> Mapping[str, object]:
+    return await request.json()
+
+
+def get_passthrough_router_request_metadata(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, object]:
     """
     Build the request metadata carrying key-level spend attribution and the
     pre-call budget reservation for a router-model passthrough request.
@@ -202,7 +225,7 @@ async def llm_passthrough_factory_proxy_route(
     # anthropic is streaming when 'stream' = True is in the body
     if request.method == "POST":
         if "multipart/form-data" not in request.headers.get("content-type", ""):
-            _request_body = await request.json()
+            _request_body = await _json_request_body(request)
         else:
             _request_body = await get_form_data(request)
 
@@ -375,7 +398,7 @@ async def vllm_proxy_route(
                 endpoint=endpoint,
                 request_query_params=request.query_params,
                 request_headers=_safe_get_request_headers(request),
-                stream=request_body.get("stream", False),
+                stream=is_streaming_request,
                 content=None,
                 data=None,
                 files=None,
@@ -495,8 +518,14 @@ async def milvus_proxy_route(
     request_body: Final = await get_request_body(request)
 
     # check collectionName
-    collection_name: Final = cast(str | None, request_body.get("collectionName"))
-    extra_headers = {}
+    _raw_collection_name: Final = request_body.get("collectionName")
+    if _raw_collection_name is not None and not isinstance(_raw_collection_name, str):
+        raise HTTPException(
+            status_code=400,
+            detail=f"collectionName must be a string. Got {type(_raw_collection_name).__name__}",
+        )
+    collection_name: str | None = _raw_collection_name  # rebind-ok: locally scoped conversion
+    extra_headers = {}  # mutable-ok: dict for extra headers; rebind-ok: reassigned later from credentials
     base_target_url: str | None = None
     if not collection_name:
         raise HTTPException(
@@ -803,7 +832,7 @@ async def handle_bedrock_passthrough_router_model(
 
     # Use the common processing path (same as non-router models)
     # This ensures all metadata, hooks, and logging are properly initialized
-    data: Final[dict[str, Any]] = {}
+    data: Final[dict[str, object]] = {}
     base_llm_response_processor: Final = ProxyBaseLLMRequestProcessing(data=data)
 
     data["model"] = model
@@ -847,8 +876,8 @@ async def handle_bedrock_count_tokens(
     request: Request,
     fastapi_response: Response,
     user_api_key_dict: UserAPIKeyAuth,
-    request_body: dict[str, Any],
-) -> dict[str, Any]:
+    request_body: dict[str, object],
+) -> dict[str, object]:
     """
     Handle AWS Bedrock CountTokens API requests.
 
@@ -865,7 +894,7 @@ async def handle_bedrock_count_tokens(
         handler: Final = BedrockCountTokensHandler()
 
         # Extract model from request body
-        model: Final = request_body.get("model")
+        model: Final = _optional_str(request_body.get("model"))
         if not model:
             raise HTTPException(status_code=400, detail={"error": "Model is required in request body"})
 
@@ -997,7 +1026,7 @@ async def bedrock_llm_proxy_route(
         "Bedrock passthrough: Using direct Bedrock model '%s' for endpoint '%s'", model, endpoint
     )
 
-    data: Final[dict[str, Any]] = {}
+    data: Final[dict[str, object]] = {}
     base_llm_response_processor: Final = ProxyBaseLLMRequestProcessing(data=data)
 
     data["method"] = request.method
@@ -1096,7 +1125,7 @@ async def bedrock_proxy_route(
     headers: Final = {"Content-Type": "application/json"}
     # Assuming the body contains JSON data, parse it
     try:
-        data: Final = await request.json()
+        data: Final = await _json_request_body(request)
     except Exception as e:
         raise HTTPException(status_code=400, detail={"error": e})
     _request: Final = AWSRequest(method="POST", url=str(updated_url), data=json.dumps(data), headers=headers)
@@ -1187,7 +1216,7 @@ async def comprehend_medical_proxy_route(
         )
 
     try:
-        data: Final = await request.json()
+        data: Final = await _json_request_body(request)
     except Exception as e:
         raise HTTPException(status_code=400, detail=str(e))
 
@@ -1273,7 +1302,7 @@ def _resolve_vertex_model_from_router(
         vertex_location: Current vertex location (may be from URL)
 
     Returns:
-        Tuple of (encoded_endpoint, endpoint, vertex_project, vertex_location)
+        tuple of (encoded_endpoint, endpoint, vertex_project, vertex_location)
         with resolved values from router config
     """
     if not llm_router:
@@ -1398,7 +1427,7 @@ async def assemblyai_proxy_route(
     is_streaming_request = False
     # assemblyai is streaming when 'stream' = True is in the body
     if request.method == "POST":
-        _request_body: Final = await request.json()
+        _request_body: Final = await _json_request_body(request)
         if _request_body.get("stream"):
             is_streaming_request = True
 
@@ -1505,7 +1534,7 @@ async def azure_proxy_route(
                     endpoint=endpoint,
                     request_query_params=request.query_params,
                     request_headers=_safe_get_request_headers(request),
-                    stream=request_body.get("stream", False),
+                    stream=is_streaming_request,
                     content=None,
                     data=None,
                     files=None,
@@ -1592,7 +1621,7 @@ async def azure_proxy_route(
 
                 extra_headers = auth_credentials.get("headers") or {}
 
-                base_target_url = litellm_params.get("api_base")
+                base_target_url = _optional_str(litellm_params.get("api_base"))
                 if base_target_url is None:
                     raise Exception(f"API base not found for {part}")
                 return await BaseOpenAIPassThroughHandler._base_openai_pass_through_handler(
@@ -1702,7 +1731,7 @@ def get_vertex_ai_allowed_incoming_headers(request: Request) -> dict:
 
 
 def get_vertex_pass_through_handler(
-    call_type: Literal["discovery", "aiplatform"],
+    call_type: Literal["discovery", "aiplatform"],  # noqa: UP037  # ruff reports quoted Literal values here
 ) -> BaseVertexAIPassThroughHandler:
     if call_type == "discovery":
         return VertexAIDiscoveryPassThroughHandler()
@@ -1713,7 +1742,7 @@ def get_vertex_pass_through_handler(
 
 
 def _override_vertex_params_from_router_credentials(
-    router_credentials: Any | None,
+    router_credentials: LiteLLM_ManagedVectorStore | None,
     vertex_project: str | None,
     vertex_location: str | None,
 ) -> tuple[str | None, str | None]:
@@ -1726,21 +1755,21 @@ def _override_vertex_params_from_router_credentials(
         vertex_location: Current vertex location (from URL)
 
     Returns:
-        Tuple of (vertex_project, vertex_location) with overridden values if applicable
+        tuple of (vertex_project, vertex_location) with overridden values if applicable
     """
     if router_credentials is None:
         return vertex_project, vertex_location
 
     verbose_proxy_logger.debug("Using vector store credentials to override vertex project and location")
 
-    litellm_params: Final = router_credentials.get("litellm_params", {})
+    litellm_params: Final = _string_keyed_mapping(router_credentials.get("litellm_params"))
     if not litellm_params:
         verbose_proxy_logger.warning("Vector store credentials found but litellm_params is empty")
         return vertex_project, vertex_location
 
     # Extract vertex_project and vertex_location from litellm_params
-    vector_store_project: Final = litellm_params.get("vertex_project")
-    vector_store_location: Final = litellm_params.get("vertex_location")
+    vector_store_project: Final = _optional_str(litellm_params.get("vertex_project"))
+    vector_store_location: Final = _optional_str(litellm_params.get("vertex_location"))
 
     if vector_store_project:
         verbose_proxy_logger.debug(
@@ -1748,7 +1777,6 @@ def _override_vertex_params_from_router_credentials(
             vertex_project,
             vector_store_project,
         )
-        vertex_project = vector_store_project
     else:
         verbose_proxy_logger.warning("Vector store credentials found but missing vertex_project in litellm_params")
 
@@ -1758,11 +1786,10 @@ def _override_vertex_params_from_router_credentials(
             vertex_location,
             vector_store_location,
         )
-        vertex_location = vector_store_location
     else:
         verbose_proxy_logger.warning("Vector store credentials found but missing vertex_location in litellm_params")
 
-    return vertex_project, vertex_location
+    return vector_store_project or vertex_project, vector_store_location or vertex_location
 
 
 _CREDENTIALLESS_VERTEX_MISSING_CREDENTIAL_DETAIL: Final = (
@@ -1870,8 +1897,8 @@ def _forwarded_headers_for_credentialless_vertex_passthrough(
 
 async def _prepare_vertex_auth_headers(
     request: Request,
-    vertex_credentials: Any | None,
-    router_credentials: Any | None,
+    vertex_credentials: VertexPassThroughCredentials | None,
+    router_credentials: LiteLLM_ManagedVectorStore | None,
     vertex_project: str | None,
     vertex_location: str | None,
     base_target_url: str | None,
@@ -1893,12 +1920,12 @@ async def _prepare_vertex_auth_headers(
             authenticated them is stripped on the credential-less branch
 
     Returns:
-        Tuple containing:
+        tuple containing:
             - headers: dict - Authentication headers to use
-            - base_target_url: Optional[str] - Updated base target URL
+            - base_target_url: str | None - Updated base target URL
             - headers_passed_through: bool - Whether headers were passed through from request
-            - vertex_project: Optional[str] - Updated vertex project ID
-            - vertex_location: Optional[str] - Updated vertex location
+            - vertex_project: str | None - Updated vertex project ID
+            - vertex_location: str | None - Updated vertex location
     """
     vertex_llm_base: Final = VertexBase()
     headers_passed_through = False
@@ -1968,7 +1995,7 @@ async def _base_vertex_proxy_route(
     fastapi_response: Response,
     get_vertex_pass_through_handler: BaseVertexAIPassThroughHandler,
     user_api_key_dict: UserAPIKeyAuth | None = None,
-    router_credentials: Any | None = None,
+    router_credentials: LiteLLM_ManagedVectorStore | None = None,
 ):
     """
     Base function for Vertex AI passthrough routes.
@@ -2138,8 +2165,6 @@ async def vertex_discovery_proxy_route(
     """
     import re
 
-    from litellm.types.vector_stores import LiteLLM_ManagedVectorStore
-
     # Extract vector store ID from endpoint if present (e.g., dataStores/test-litellm-app_1761094730750)
     vector_store_credentials: LiteLLM_ManagedVectorStore | None = None
     vector_store_id_match: Final = re.search(r"dataStores/([^/]+)", endpoint)
@@ -2546,7 +2571,7 @@ def _vertex_publisher_model_suffix(model: str) -> str:
     return f"{VERTEX_PUBLISHER_MODEL_PREFIX}{model.rsplit('/', 1)[-1]}"
 
 
-def _get_llm_router() -> "Router | None":
+def _get_llm_router() -> Router | None:
     from litellm.proxy.proxy_server import llm_router
 
     return llm_router
@@ -2586,7 +2611,7 @@ def _resolve_vertex_live_credentials(
 def _build_vertex_live_setup_model_rewriter(
     vertex_project: str | None,
     vertex_location: str | None,
-    llm_router: "Router | None",
+    llm_router: Router | None,
 ) -> Callable[[str], str] | None:
     """
     Rewrite the ``setup`` frame's model into the full Vertex resource path the Live API requires.
@@ -2606,7 +2631,7 @@ def _build_vertex_live_setup_model_rewriter(
     return rewrite
 
 
-def _resolve_alias_to_upstream_model(setup_model: str, llm_router: "Router | None") -> str:
+def _resolve_alias_to_upstream_model(setup_model: str, llm_router: Router | None) -> str:
     """
     The Live SDK wraps whatever the caller typed as ``models/<name>``, so a gateway alias arrives prefixed
     """
@@ -2796,6 +2821,236 @@ def create_generic_websocket_passthrough_endpoint(
     )
 
 
+@router.api_route(
+    "/gigachat/{endpoint:path}",
+    methods=["GET", "POST", "PUT", "DELETE", "PATCH"],  # mutable-ok: FastAPI route methods
+    tags=["Gigachat Pass-through", "pass-through"],  # mutable-ok: FastAPI route tags
+)
+async def gigachat_proxy_route(
+    endpoint: str,
+    request: Request,
+    fastapi_response: Response,
+    user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)],
+) -> Response:
+    """
+    [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+    """
+    from litellm.proxy.proxy_server import (
+        general_settings,
+        llm_router,
+        proxy_config,
+        proxy_logging_obj,
+        select_data_generator,
+        user_api_base,
+        user_max_tokens,
+        user_model,
+        user_request_timeout,
+        user_temperature,
+        version,
+    )
+
+    ## check for streaming
+    request_body: Final[dict[str, object]] = await get_request_body(request)
+    is_router_model = False  # rebind-ok: conditionally set to True when model uses router
+
+    raw_model: Final = request_body.get("model")
+    model: Final = raw_model if isinstance(raw_model, str) else None
+    if model:
+        is_router_model = is_passthrough_request_using_router_model(
+            request_body, llm_router
+        )  # rebind-ok: conditionally set to True
+    elif any(word in endpoint for word in ("completions", "embeddings")):
+        raise HTTPException(
+            status_code=400, detail={"error": "Model is required in request body"}
+        )  # mutable-ok: HTTPException detail dict
+
+    # If router model, use dedicated router passthrough handler
+    # This uses the same common processing path as non-router models
+    if model and is_router_model and llm_router:
+        return await handle_gigachat_passthrough_router_model(
+            model=model,
+            endpoint=endpoint,
+            request=request,
+            request_body=request_body,
+            fastapi_response=fastapi_response,
+            llm_router=llm_router,
+            user_api_key_dict=user_api_key_dict,
+            proxy_logging_obj=proxy_logging_obj,
+            general_settings=general_settings,
+            proxy_config=proxy_config,
+            select_data_generator=select_data_generator,
+            user_model=user_model,
+            user_temperature=user_temperature,
+            user_request_timeout=user_request_timeout,
+            user_max_tokens=user_max_tokens,
+            user_api_base=user_api_base,
+            version=version,
+        )
+
+    verbose_proxy_logger.debug(
+        "Gigachat passthrough: Using direct Gigachat model '%s' for endpoint '%s'", model, endpoint
+    )
+
+    from litellm.llms.gigachat.authenticator import get_access_token
+    from litellm.llms.gigachat.utils import GIGACHAT_BASE_URL
+
+    base_target_url: Final = get_secret_str("GIGACHAT_API_BASE") or GIGACHAT_BASE_URL
+    request_path: Final = httpx.URL(endpoint).path
+    encoded_endpoint: Final = request_path if request_path.startswith("/") else f"/{request_path}"
+
+    base_url: Final = httpx.URL(base_target_url)
+    updated_url: Final = base_url.copy_with(
+        path=HttpPassThroughEndpointHelpers.join_base_and_endpoint_path(base_url, encoded_endpoint)
+    )
+
+    is_streaming_request: Final = await is_streaming_request_fn(request)
+
+    endpoint_func: Final = create_pass_through_route(
+        endpoint=endpoint,
+        target=str(updated_url),
+        custom_headers={"Authorization": f"Bearer {get_access_token()}"},
+        is_streaming_request=is_streaming_request,
+    )
+    return await endpoint_func(
+        request,
+        fastapi_response,
+        user_api_key_dict,
+    )
+
+
+async def handle_gigachat_passthrough_router_model(
+    model: str,
+    endpoint: str,
+    request: Request,
+    request_body: dict,
+    fastapi_response: Response,
+    llm_router: litellm.Router,
+    user_api_key_dict: UserAPIKeyAuth,
+    proxy_logging_obj: ProxyLoggingType,
+    general_settings: dict,
+    proxy_config: ProxyConfig,
+    select_data_generator: Callable,
+    user_model: str | None,
+    user_temperature: float | None,
+    user_request_timeout: float | None,
+    user_max_tokens: int | None,
+    user_api_base: str | None,
+    version: str | None,
+) -> Response | StreamingResponse:
+    """
+    Handle Gigachat passthrough for router models (models defined in config.yaml).
+
+    Uses the same common processing path as non-router models to ensure
+    metadata and hooks are properly initialized.
+
+    Args:
+        model: The router model name (e.g., "gigachat/gigachat-2")
+        endpoint: The Gigachat endpoint path (e.g., "/chat/completions")
+        request: The FastAPI request object
+        request_body: The parsed request body
+        llm_router: The LiteLLM router instance
+        user_api_key_dict: The user API key authentication dictionary
+        proxy_logging_obj: Proxy logging
+        general_settings: Proxy general settings
+        proxy_config: Proxy config
+        select_data_generator: Select data generator function
+        (additional args for common processing)
+
+    Returns:
+        Response or StreamingResponse depending on endpoint type
+    """
+    from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
+
+    is_streaming: Final = request_body.get("stream", False)  # pyright: ignore[reportUnknownVariableType]  # request_body is dict[Unknown, Unknown]
+
+    data: dict[str, Any] = await _read_request_body(
+        request=request
+    )  # mutable-ok: mutated in place by proxy pipeline; pyright: ignore[reportExplicitAny]  # Any needed for proxy pipeline
+    if user_api_key_dict is not None:
+        auth_metadata: Final = {
+            metadata_key: value
+            for metadata_key, value in (
+                ("user_api_key_user_id", getattr(user_api_key_dict, "user_id", None)),
+                ("user_api_key_team_id", getattr(user_api_key_dict, "team_id", None)),
+                ("user_api_key_org_id", getattr(user_api_key_dict, "org_id", None)),
+                ("agent_id", getattr(user_api_key_dict, "agent_id", None)),
+            )
+            if value is not None
+        }
+        existing_metadata: Final = data.get("metadata")
+        data["metadata"] = {
+            **(existing_metadata if isinstance(existing_metadata, dict) else {}),
+            **auth_metadata,
+        }
+
+    verbose_proxy_logger.debug(
+        "Gigachat router passthrough: model='%s', endpoint='%s', streaming=%s", model, endpoint, is_streaming
+    )
+
+    # Use the common processing path (same as non-router models)
+    # This ensures all metadata, hooks, and logging are properly initialized
+
+    data["model"] = model
+    data["method"] = request.method
+    data["endpoint"] = endpoint
+    data["json"] = request_body
+    data["custom_llm_provider"] = "gigachat"
+
+    keys: Final = [  # mutable-ok: list of keys to remove from data
+        "gigachat_auth_url",
+        "gigachat_access_token",
+        "gigachat_scope",
+        "api_base",
+        "api_key",
+    ]
+    for key in keys:
+        data.pop(key, None)
+
+    client: Final = get_async_httpx_client(
+        llm_provider=LlmProviders.GIGACHAT,
+        params={  # mutable-ok: httpx client params
+            "timeout": httpx.Timeout(timeout=600.0, connect=5.0),
+        },
+    )
+
+    data["client"] = client
+    base_llm_response_processor: Final = ProxyBaseLLMRequestProcessing(data=data)
+
+    # Use the common passthrough processing to handle metadata and hooks
+    # This also handles all response formatting (streaming/non-streaming) and exceptions
+    try:
+        result = await base_llm_response_processor.base_passthrough_process_llm_request(  # rebind-ok: assigned once in try block
+            request=request,
+            fastapi_response=fastapi_response,
+            user_api_key_dict=user_api_key_dict,
+            proxy_logging_obj=proxy_logging_obj,
+            llm_router=llm_router,
+            general_settings=general_settings,
+            proxy_config=proxy_config,
+            select_data_generator=select_data_generator,
+            model=model,
+            user_model=user_model,
+            user_temperature=user_temperature,
+            user_request_timeout=user_request_timeout,
+            user_max_tokens=user_max_tokens,
+            user_api_base=user_api_base,
+            version=version,
+        )
+    except Exception as e:  # noqa: BLE001 # Safe catch-all for handle exception
+        # Use common exception handling
+        raise await base_llm_response_processor._handle_llm_api_exception(
+            e=e,
+            user_api_key_dict=user_api_key_dict,
+            proxy_logging_obj=proxy_logging_obj,
+        )
+    else:
+        if isinstance(result, StreamingResponse):
+            if result.headers.get("Content-Type") is None:
+                result.headers["Content-Type"] = "text/event-stream; charset=utf-8"
+
+        return result
+
+
 @router.api_route(
     "/watsonx/{endpoint:path}",
     methods=["GET", "POST", "PUT", "DELETE", "PATCH"],
@@ -2852,7 +3107,7 @@ async def watsonx_proxy_route(
     is_streaming_request = False
     if request.method == "POST":
         if "multipart/form-data" not in request.headers.get("content-type", ""):
-            _request_body = await request.json()
+            _request_body = await _json_request_body(request)
         else:
             _request_body = await get_form_data(request)
 
diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
index ee9a5d94440..49ec18013b5 100644
--- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
+++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
@@ -267,7 +267,7 @@ class VertexPassthroughLoggingHandler:
 
         model: Final = VertexPassthroughLoggingHandler.extract_model_from_url(url_route)
 
-        _json_response: Final = httpx_response.json()
+        _json_response: Final[dict[str, object]] = httpx_response.json()
 
         litellm_prediction_response: ModelResponse | EmbeddingResponse | ImageResponse = ModelResponse()
         if vertex_image_generation_class.is_image_generation_response(_json_response):
@@ -422,7 +422,7 @@ class VertexPassthroughLoggingHandler:
         - Creates standard logging object
         - Logs in litellm callbacks
         """
-        kwargs: dict[str, Any] = {}
+        kwargs: dict[str, object] = {}
         vertex_location: Final = get_vertex_location_from_url(url_route)
         if vertex_location is not None:
             litellm_logging_obj.optional_params["vertex_location"] = vertex_location
diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
index 09d3dedaafa..79d5d0a016f 100644
--- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
+++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
@@ -6,9 +6,10 @@ import posixpath
 import traceback
 from base64 import b64encode
 from collections.abc import AsyncGenerator, Callable, Iterable, Mapping, Sequence
+from dataclasses import dataclass
 from datetime import datetime
 from itertools import groupby
-from typing import Any, Final, TypedDict, cast
+from typing import TYPE_CHECKING, Any, Final, TypedDict, cast
 from urllib.parse import urlencode, urlparse
 
 import httpx
@@ -47,6 +48,7 @@ from litellm.litellm_core_utils.core_helpers import (
     get_metadata_variable_name_from_kwargs,
     get_or_create_metadata_bucket,
 )
+from litellm.litellm_core_utils.initialize_dynamic_callback_params import validate_no_callback_env_reference
 from litellm.litellm_core_utils.internal_call_metadata import MODEL_ACCESS_GROUP_METADATA_KEY
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
@@ -78,7 +80,10 @@ from litellm.proxy.common_utils.http_parsing_utils import (
 from litellm.proxy.common_utils.sse_keepalive import (
     wrap_passthrough_sse_bytes_with_keepalive_pings,
 )
-from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
+from litellm.proxy.litellm_pre_call_utils import (
+    LiteLLMProxyRequestSetup,
+    _get_dynamic_logging_metadata,  # pyright: ignore[reportPrivateUsage]  # shared proxy helper, same import style as _read_request_body above
+)
 from litellm.proxy.utils import normalize_route_for_root_path
 from litellm.repositories.team_repository import TeamRepository
 from litellm.secret_managers.main import get_secret_str
@@ -90,7 +95,7 @@ from litellm.types.passthrough_endpoints.pass_through_endpoints import (
     EndpointType,
     PassthroughStandardLoggingPayload,
 )
-from litellm.types.utils import Usage
+from litellm.types.utils import TRUSTED_CALLBACK_VARS_FIELD, Usage
 
 from .streaming_handler import PassThroughStreamingHandler
 from .success_handler import PassThroughEndpointLogging
@@ -99,6 +104,9 @@ from .upstream_usage_headers import (
     apply_upstream_reported_usage,
 )
 
+if TYPE_CHECKING:
+    from litellm.proxy.proxy_server import ProxyConfig
+
 router: Final = APIRouter()
 
 pass_through_endpoint_logging: Final = PassThroughEndpointLogging()
@@ -752,6 +760,69 @@ def _build_passthrough_failure_request_payload(
     return request_payload
 
 
+@dataclass(frozen=True, slots=True)
+class _TeamCallbackWiring:
+    success_callbacks: "list[str | Callable | CustomLogger] | None" = None  # mutable-ok: Logging.__init__ arg
+    failure_callbacks: "list[str | Callable | CustomLogger] | None" = None  # mutable-ok: Logging.__init__ arg
+    logging_kwargs: dict[str, str | dict[str, str]] | None = None  # mutable-ok: Logging.__init__ arg
+
+
+def _resolve_team_callback_wiring(
+    user_api_key_dict: UserAPIKeyAuth,
+    proxy_config: "ProxyConfig",
+    route_description: str,
+) -> _TeamCallbackWiring:
+    """Resolve key/team dynamic logging callbacks for a passthrough request.
+
+    Mirrors add_litellm_data_to_request: callback_vars are unpacked top-level
+    (read by initialize_standard_callback_dynamic_params) and also stamped on
+    the proxy-owned trusted-vars field (read by get_trusted_callback_params).
+
+    Fails open: a callback resolution or validation error is logged at error
+    level and the request proceeds without dynamic callbacks, since a broken
+    logging config must not fail the customer's upstream call (and the
+    websocket is already accepted by the time this runs on that path). The
+    env-reference check runs here because the deprecated callback_settings
+    branch skips AddTeamCallback validation, and Logging.__init__ would
+    otherwise reject the vars mid-request.
+    """
+    try:
+        callback_settings_obj: Final = _get_dynamic_logging_metadata(
+            user_api_key_dict=user_api_key_dict, proxy_config=proxy_config
+        )
+        if callback_settings_obj and callback_settings_obj.callback_vars:
+            for (
+                item
+            ) in callback_settings_obj.callback_vars.items():  # rebind-ok: dict.items iteration for env-ref validation
+                validate_no_callback_env_reference(item[0], item[1], source="key/team callback metadata")
+    except Exception:  # noqa: BLE001 - a broken logging config must never fail the passthrough request
+        verbose_proxy_logger.exception(
+            "%s: failed to resolve team logging callbacks, continuing without them",
+            route_description,
+        )
+        return _TeamCallbackWiring()
+    if callback_settings_obj is None:
+        return _TeamCallbackWiring()
+    callback_vars: Final = callback_settings_obj.callback_vars
+    success_callbacks: Final = callback_settings_obj.success_callback
+    failure_callbacks: Final = callback_settings_obj.failure_callback
+    logging_kwargs: Final = (
+        None
+        if not callback_vars
+        else {  # mutable-ok: Logging arg
+            **callback_vars,
+            TRUSTED_CALLBACK_VARS_FIELD: callback_vars,
+            "metadata": {},  # mutable-ok: Logging arg
+            "model_info": {},  # mutable-ok: Logging arg
+        }
+    )
+    return _TeamCallbackWiring(
+        success_callbacks=None if success_callbacks is None else [*success_callbacks],  # mutable-ok: Logging arg
+        failure_callbacks=None if failure_callbacks is None else [*failure_callbacks],  # mutable-ok: Logging arg
+        logging_kwargs=logging_kwargs,
+    )
+
+
 async def _log_passthrough_upstream_failure(
     response: httpx.Response,
     user_api_key_dict: UserAPIKeyAuth,
@@ -845,7 +916,7 @@ async def pass_through_request(
     from litellm.proxy.pass_through_endpoints.passthrough_guardrails import (
         PassthroughGuardrailHandler,
     )
-    from litellm.proxy.proxy_server import proxy_logging_obj
+    from litellm.proxy.proxy_server import proxy_config, proxy_logging_obj
 
     #########################################################
     # Initialize variables
@@ -930,6 +1001,11 @@ async def pass_through_request(
         # read e.g. ``chat gpt-4o`` instead of ``chat unknown``.
         passthrough_model: Final = (_parsed_body.get("model") if isinstance(_parsed_body, dict) else None) or "unknown"
         start_time: Final = datetime.now()
+        team_callbacks: Final = _resolve_team_callback_wiring(
+            user_api_key_dict=user_api_key_dict,
+            proxy_config=proxy_config,
+            route_description="pass_through_endpoint",
+        )
         logging_obj = Logging(
             model=passthrough_model,
             messages=[{"role": "user", "content": safe_dumps(_parsed_body)}],
@@ -938,6 +1014,9 @@ async def pass_through_request(
             start_time=start_time,
             litellm_call_id=litellm_call_id,
             function_id="1245",
+            dynamic_success_callbacks=team_callbacks.success_callbacks,
+            dynamic_failure_callbacks=team_callbacks.failure_callbacks,
+            kwargs=team_callbacks.logging_kwargs,
         )
 
         # Store passthrough guardrails config on logging_obj for field targeting
@@ -2022,7 +2101,7 @@ async def websocket_passthrough_request(
         setup_model_rewriter: Optional rewrite of the setup frame's model before it reaches the upstream
     """
     from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.proxy.proxy_server import proxy_logging_obj
+    from litellm.proxy.proxy_server import proxy_config, proxy_logging_obj
     from litellm.types.passthrough_endpoints.pass_through_endpoints import (
         PassthroughStandardLoggingPayload,
     )
@@ -2055,6 +2134,11 @@ async def websocket_passthrough_request(
                 upstream_headers[header_name] = header_value
 
     # Initialize logging object similar to HTTP passthrough
+    team_callbacks: Final = _resolve_team_callback_wiring(
+        user_api_key_dict=user_api_key_dict,
+        proxy_config=proxy_config,
+        route_description="websocket_passthrough",
+    )
     logging_obj: Final = Logging(
         model="unknown",
         messages=[{"role": "user", "content": "WebSocket connection"}],
@@ -2063,6 +2147,9 @@ async def websocket_passthrough_request(
         start_time=start_time,
         litellm_call_id=litellm_call_id,
         function_id="websocket_passthrough",
+        dynamic_success_callbacks=team_callbacks.success_callbacks,
+        dynamic_failure_callbacks=team_callbacks.failure_callbacks,
+        kwargs=team_callbacks.logging_kwargs,
     )
 
     # Create passthrough logging payload
@@ -3148,6 +3235,14 @@ def _get_pass_through_endpoints_from_config() -> list[PassThroughGenericEndpoint
     return returned_endpoints
 
 
+def _config_field_endpoints(response: ConfigFieldInfo) -> list[object] | None:
+    return response.field_value
+
+
+def _request_app(request: Request) -> FastAPI:
+    return request.app
+
+
 async def _get_pass_through_endpoints_from_db(
     endpoint_id: str | None = None,
     user_api_key_dict: UserAPIKeyAuth | None = None,
@@ -3164,7 +3259,7 @@ async def _get_pass_through_endpoints_from_db(
     except Exception:
         return []
 
-    pass_through_endpoint_data: Final[list | None] = response.field_value
+    pass_through_endpoint_data: Final = _config_field_endpoints(response)
     if pass_through_endpoint_data is None:
         return []
 
@@ -3327,7 +3422,7 @@ async def update_pass_through_endpoints(
             detail={"error": "No pass-through endpoints found"},
         )
 
-    pass_through_endpoint_data: Final[list | None] = response.field_value
+    pass_through_endpoint_data: Final[list | None] = _config_field_endpoints(response)
     if pass_through_endpoint_data is None:
         raise HTTPException(
             status_code=404,
@@ -3398,7 +3493,7 @@ async def update_pass_through_endpoints(
     _custom_headers: dict | None = updated_endpoint.headers or {}
     _custom_headers = await set_env_variables_in_header(custom_headers=_custom_headers)
 
-    route_app: Final[FastAPI] = request.app
+    route_app: Final = _request_app(request)
     if updated_endpoint.include_subpath:
         InitPassThroughEndpointHelpers.add_subpath_route(
             app=route_app,
@@ -3490,7 +3585,7 @@ async def create_pass_through_endpoints(
     _custom_headers: dict | None = created_endpoint.headers or {}
     _custom_headers = await set_env_variables_in_header(custom_headers=_custom_headers)
 
-    route_app: Final[FastAPI] = request.app
+    route_app: Final = _request_app(request)
     if created_endpoint.include_subpath:
         InitPassThroughEndpointHelpers.add_subpath_route(
             app=route_app,
@@ -3558,7 +3653,7 @@ async def delete_pass_through_endpoints(
         response = ConfigFieldInfo(field_name="pass_through_endpoints", field_value=None)
 
     ## Update field by removing endpoint
-    pass_through_endpoint_data: Final[list | None] = response.field_value
+    pass_through_endpoint_data: Final[list | None] = _config_field_endpoints(response)
     if response.field_value is None or pass_through_endpoint_data is None:
         raise HTTPException(
             status_code=400,
diff --git a/litellm/proxy/pass_through_endpoints/streaming_handler.py b/litellm/proxy/pass_through_endpoints/streaming_handler.py
index 5ad41b00890..022a1ecbac4 100644
--- a/litellm/proxy/pass_through_endpoints/streaming_handler.py
+++ b/litellm/proxy/pass_through_endpoints/streaming_handler.py
@@ -65,6 +65,19 @@ class PassThroughStreamingHandler:
             route_streaming_logging or PassThroughStreamingHandler._route_streaming_logging_to_handler
         )
         raw_bytes: Final[list[bytes]] = []
+
+        def _build_logging_coroutine() -> Coroutine[None, None, None]:
+            return resolved_route_streaming_logging(
+                litellm_logging_obj=litellm_logging_obj,
+                passthrough_success_handler_obj=passthrough_success_handler_obj,
+                url_route=url_route,
+                request_body=request_body or {},
+                endpoint_type=endpoint_type,
+                start_time=start_time,
+                raw_bytes=raw_bytes,
+                end_time=datetime.now(),
+            )
+
         logging_scheduled = False
         model_name: Final = PassThroughStreamingHandler._extract_model_for_cost_injection(
             request_body=request_body,
@@ -114,6 +127,21 @@ class PassThroughStreamingHandler:
                         )
                 if pending:
                     yield pending
+            # Stream completed cleanly.  When the proxy armed deferred
+            # dispatch (post-call guardrails active), park the logging
+            # coroutine on logging_obj instead of enqueueing now, so
+            # ProxyLogging._fire_deferred_stream_logging fires it after
+            # guardrail end-of-stream blocks populate guardrail_information.
+            # Disconnect/exception paths skip this and fall through to the
+            # immediate enqueue in ``finally`` to keep partial billing
+            # (LIT-2642).
+            if (
+                getattr(litellm_logging_obj, "_on_deferred_stream_complete", None) is not None
+                and raw_bytes
+                and response.status_code < 400
+            ):
+                logging_scheduled = True
+                litellm_logging_obj._deferred_stream_complete_args = (_build_logging_coroutine(),)
         except Exception as e:
             verbose_proxy_logger.error("Error in chunk_processor: %s", e)
             raise
@@ -128,18 +156,7 @@ class PassThroughStreamingHandler:
             if not logging_scheduled and raw_bytes and response.status_code < 400:
                 logging_scheduled = True
                 try:
-                    GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(
-                        async_coroutine=resolved_route_streaming_logging(
-                            litellm_logging_obj=litellm_logging_obj,
-                            passthrough_success_handler_obj=passthrough_success_handler_obj,
-                            url_route=url_route,
-                            request_body=request_body or {},
-                            endpoint_type=endpoint_type,
-                            start_time=start_time,
-                            raw_bytes=raw_bytes,
-                            end_time=datetime.now(),
-                        )
-                    )
+                    GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue(async_coroutine=_build_logging_coroutine())
                 except Exception as e:
                     verbose_proxy_logger.error("Error scheduling chunk_processor logging: %s", e)
 
diff --git a/litellm/proxy/policy_engine/pipeline_executor.py b/litellm/proxy/policy_engine/pipeline_executor.py
index 50cb813c6fa..4be0f556ed7 100644
--- a/litellm/proxy/policy_engine/pipeline_executor.py
+++ b/litellm/proxy/policy_engine/pipeline_executor.py
@@ -6,6 +6,7 @@ pass/fail actions (allow, block, next, modify_response) and data forwarding.
 """
 
 import time
+from collections.abc import Sequence
 from typing import Any, Final, Literal
 
 import litellm
@@ -114,11 +115,7 @@ class PipelineExecutor:
 
             # Handle terminal actions
             if action == "allow":
-                return PipelineExecutionResult(
-                    terminal_action="allow",
-                    step_results=step_results,
-                    modified_data=working_data if working_data != data else None,
-                )
+                return _allow_result(step_results=step_results, working_data=working_data, request_data=data)
 
             if action == "block":
                 return PipelineExecutionResult(
@@ -138,11 +135,7 @@ class PipelineExecutor:
             # action == "next" → continue to next step
 
         # Ran out of steps without a terminal action → default allow
-        return PipelineExecutionResult(
-            terminal_action="allow",
-            step_results=step_results,
-            modified_data=working_data if working_data != data else None,
-        )
+        return _allow_result(step_results=step_results, working_data=working_data, request_data=data)
 
     @staticmethod
     async def _run_step(
@@ -251,6 +244,45 @@ class PipelineExecutor:
         return None
 
 
+def _allow_result(
+    step_results: Sequence[PipelineStepResult],
+    working_data: dict,  # mutable-ok: same request-payload shape as execute_steps' data
+    request_data: dict,  # mutable-ok: same request-payload shape as execute_steps' data
+) -> PipelineExecutionResult:
+    """Build the terminal-allow result, propagating pipeline modifications without the per-step guardrail override."""
+    restored: Final = _restore_request_guardrails(working_data, request_data)
+    return PipelineExecutionResult(
+        terminal_action="allow",
+        step_results=list(step_results),  # mutable-ok: PipelineExecutionResult field is a list
+        modified_data=restored if restored != request_data else None,
+    )
+
+
+def _restore_request_guardrails(
+    working_data: dict,  # mutable-ok: same request-payload shape as execute_steps' data
+    request_data: dict,  # mutable-ok: same request-payload shape as execute_steps' data
+) -> dict:  # mutable-ok: merged back into the request dict, which downstream code mutates
+    """
+    Restore the request's own metadata["guardrails"] activation list.
+
+    _run_step overrides it to [step.guardrail] so should_run_guardrail() allows each
+    step; letting that override escape via modified_data permanently drops every
+    independently activated guardrail from later lifecycle stages (post_call, etc.).
+    """
+    working_metadata: Final = working_data.get("metadata")
+    if not isinstance(working_metadata, dict):
+        return working_data
+    request_metadata: Final = request_data.get("metadata")
+    original_guardrails: Final = request_metadata.get("guardrails") if isinstance(request_metadata, dict) else None
+    stripped: Final = {k: v for k, v in working_metadata.items() if k != "guardrails"}  # mutable-ok: request dict
+    if original_guardrails is not None:
+        restored: Final = {**stripped, "guardrails": original_guardrails}  # mutable-ok: request dict
+        return {**working_data, "metadata": restored}  # mutable-ok: request dict
+    if not stripped and not isinstance(request_metadata, dict):
+        return {k: v for k, v in working_data.items() if k != "metadata"}  # mutable-ok: request dict
+    return {**working_data, "metadata": stripped}  # mutable-ok: request dict
+
+
 def _pipeline_action_for_outcome(step: PipelineStep, outcome: str) -> str:
     """
     Map pipeline step outcome to the configured action.
diff --git a/litellm/proxy/prompts/prompt_endpoints.py b/litellm/proxy/prompts/prompt_endpoints.py
index 9cfd6959a66..b6cbd2d7889 100644
--- a/litellm/proxy/prompts/prompt_endpoints.py
+++ b/litellm/proxy/prompts/prompt_endpoints.py
@@ -6,7 +6,7 @@ import tempfile
 from collections.abc import Awaitable, Mapping, Sequence
 from datetime import datetime
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Final, Protocol, cast
+from typing import TYPE_CHECKING, Final, Protocol, cast
 
 from fastapi import (
     APIRouter,
@@ -1317,7 +1317,7 @@ async def test_prompt(
 async def convert_prompt_file_to_json(
     file: UploadFile = File(...),
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
-) -> dict[str, Any]:
+) -> Mapping[str, object]:
     """
     Convert a .prompt file to JSON format.
 
diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py
index 8ac63ba25c9..23932ba7c8c 100644
--- a/litellm/proxy/proxy_cli.py
+++ b/litellm/proxy/proxy_cli.py
@@ -1225,6 +1225,7 @@ def run_server(
         if os.getenv("DATABASE_URL", None) is not None or os.getenv("DIRECT_URL", None) is not None:
             from litellm.proxy.db.db_url_settings import (
                 add_missing_query_params,
+                idle_lifetime_params,
                 reader_shareable_params,
                 unsupported_db_scheme,
                 unsupported_db_scheme_message,
@@ -1253,6 +1254,9 @@ def run_server(
                     disable_prepared_statements=db_disable_prepared_statements,
                     extra_params=db_extra_connection_params,
                 )
+                lifetime_params: Final = idle_lifetime_params(
+                    general_settings.get("database_max_idle_connection_lifetime")
+                )
                 if os.getenv("DATABASE_URL", None) is not None:
                     database_url = get_secret("DATABASE_URL", default_value=None)
                     resolved_url: Final[str | None] = str(database_url) if database_url else None
@@ -1270,11 +1274,11 @@ def run_server(
                         writer_url,
                         connection_url_params,
                     )
-                    os.environ["DATABASE_URL"] = modified_url
+                    os.environ["DATABASE_URL"] = add_missing_query_params(modified_url, lifetime_params)
                 if os.getenv("DIRECT_URL", None) is not None:
                     database_url = os.getenv("DIRECT_URL")
                     modified_url = append_query_params(database_url, connection_url_params)
-                    os.environ["DIRECT_URL"] = modified_url
+                    os.environ["DIRECT_URL"] = add_missing_query_params(modified_url, lifetime_params)
                 # The reader pool is a real pool against the same configured cap, so it
                 # gets the allowlisted pool params. Schema-affecting ones, including any
                 # the operator smuggled in through database_extra_connection_params, stay
@@ -1288,10 +1292,13 @@ def run_server(
                         db_lock_timeout,
                     )
                     os.environ["DATABASE_URL_READ_REPLICA"] = add_missing_query_params(
-                        _with_query_value(read_replica_url, "options", reader_options)
-                        if reader_options
-                        else read_replica_url,
-                        reader_shareable_params(connection_url_params),
+                        add_missing_query_params(
+                            _with_query_value(read_replica_url, "options", reader_options)
+                            if reader_options
+                            else read_replica_url,
+                            reader_shareable_params(connection_url_params),
+                        ),
+                        lifetime_params,
                     )
                 subprocess.run(["prisma"], capture_output=True)
                 is_prisma_runnable = True
diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 887716a383a..27132c90e05 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -39,7 +39,7 @@ from typing import (
 import anyio
 import websockets
 import websockets.exceptions
-from pydantic import BaseModel, Json, JsonValue
+from pydantic import BaseModel, Json, JsonValue, TypeAdapter, ValidationError
 from typing_extensions import NotRequired, ReadOnly, assert_never
 
 from litellm._uuid import uuid
@@ -60,6 +60,7 @@ from litellm.constants import (
     LITELLM_SETTINGS_SAFE_DB_OVERRIDES,
     LITELLM_UI_ALLOW_HEADERS,
     LITELLM_UI_SESSION_DURATION,
+    RUNTIME_UPDATABLE_ROUTER_SETTINGS,
 )
 from litellm.litellm_core_utils.litellm_logging import (
     _init_custom_logger_compatible_class,
@@ -253,6 +254,8 @@ from litellm.constants import (
     PROXY_BUDGET_RESCHEDULER_MAX_TIME,
     PROXY_BUDGET_RESCHEDULER_MIN_TIME,
     PROXY_CONFIG_RELOAD_INTERVAL_SECONDS,
+    ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG,
+    USER_SPEND_ALERTS_JOB_ID,
     WEEKLY_SPEND_REPORT_JOB_ID,
 )
 from litellm.exceptions import RejectedRequestError
@@ -263,6 +266,7 @@ from litellm.litellm_core_utils.agentic_loop_settings import (
     validated_max_agentic_loops,
 )
 from litellm.litellm_core_utils.asyncify import asyncify
+from litellm.litellm_core_utils.audio_utils.utils import resolve_speech_media_type
 from litellm.litellm_core_utils.core_helpers import (
     _get_parent_otel_span_from_kwargs,
     get_litellm_metadata_from_kwargs,
@@ -306,6 +310,7 @@ from litellm.proxy.auth.model_checks import (
     get_mcp_server_ids,
     get_team_models,
 )
+from litellm.proxy.auth.password_policy import validate_password_policy
 from litellm.proxy.auth.user_api_key_auth import (
     _fetch_global_spend_with_event_coordination,
     user_api_key_auth,
@@ -350,7 +355,10 @@ from litellm.proxy.common_utils.load_config_utils import (
     get_file_contents_from_s3,
 )
 from litellm.proxy.common_utils.model_deprecation import collect_model_deprecations
-from litellm.proxy.common_utils.model_listing_utils import TeamModelNameTranslator
+from litellm.proxy.common_utils.model_listing_utils import (
+    TeamModelNameTranslator,
+    configured_display_names,
+)
 from litellm.proxy.common_utils.openai_endpoint_utils import (
     remove_sensitive_info_from_deployment,
 )
@@ -1363,7 +1371,7 @@ _OPENAPI_HTTP_METHODS: Final = {
 # the UI. Kept here at module scope to match the analogous descriptor
 # `is_secret` flags in litellm.proxy.config_resolvers and the
 # `_CACHE_SENSITIVE_FIELDS` constant in the cache endpoint file.
-_ALERTING_SENSITIVE_VARS: Final[set[str]] = {"SLACK_WEBHOOK_URL", "SMTP_PASSWORD"}
+_ALERTING_SENSITIVE_VARS: Final[set[str]] = {"ALERTING_WEBHOOK_URL", "SLACK_WEBHOOK_URL", "SMTP_PASSWORD"}
 
 
 def _strip_operation_id_method_suffix(operation_id: str) -> str:
@@ -2273,7 +2281,7 @@ user_api_key_cache: UserApiKeyCache = UserApiKeyCache(
 )
 spend_counter_cache: Final = DualCache(default_in_memory_ttl=UserAPIKeyCacheTTLEnum.in_memory_cache_ttl.value)
 cli_sso_session_cache: Final = DualCache(default_in_memory_ttl=CLI_SSO_SESSION_TTL_SECONDS)
-model_max_budget_limiter: Final = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=user_api_key_cache)
+model_max_budget_limiter: Final = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=spend_counter_cache)
 litellm.logging_callback_manager.add_litellm_callback(model_max_budget_limiter)
 redis_usage_cache: RedisCache | None = None  # redis cache used for tracking spend, tpm/rpm limits
 polling_via_cache_enabled: Literal["all"] | list[str] | bool = False
@@ -2658,7 +2666,6 @@ async def increment_spend_counters(
     budget_reservation: dict | None = None,
     end_user_id: str | None = None,
     tags: list[str] | None = None,
-    request_id: str | None = None,
     request_started_at: datetime | None = None,
     model_access_groups: Sequence[str] | None = None,
 ):
@@ -2733,7 +2740,6 @@ async def increment_spend_counters(
                 window_duration=duration,
                 window_start=key_window_start,
                 increment=cost,
-                request_id=request_id,
                 request_started_at=request_started_at,
             )
 
@@ -2777,7 +2783,6 @@ async def increment_spend_counters(
                 window_duration=duration,
                 window_start=team_window_start,
                 increment=cost,
-                request_id=request_id,
                 request_started_at=request_started_at,
             )
 
@@ -3005,16 +3010,15 @@ async def _enqueue_window_spend_row_update(
     window_duration: str,
     window_start: datetime | None,
     increment: float,
-    request_id: str | None,
     request_started_at: datetime | None,
 ) -> None:
     """Queue this request's cost against the LiteLLM_BudgetWindowSpend row for
     the window, so enforcement can read a maintained total instead of
     aggregating LiteLLM_SpendLogs.
 
-    request_id is the LiteLLM_SpendLogs id this cost was recorded under and
-    request_started_at its startTime; the flush uses them to keep the one-time
-    seed from counting a request that its increment already covers.
+    request_started_at is this request's LiteLLM_SpendLogs startTime; the flush
+    stops the one-time seed there so a request its increment already covers is
+    not counted twice.
 
     Enqueued even when the cache increment was skipped for a reserved counter:
     the reservation only pre-charged the counter, and the row still owes the
@@ -3035,7 +3039,6 @@ async def _enqueue_window_spend_row_update(
                 window_duration=window_duration,
                 window_start=window_start,
                 spend=increment,
-                request_id=request_id,
                 started_at=request_started_at,
             )
         )
@@ -4741,6 +4744,63 @@ class ProxyConfig:
         )
         return coordination_redis_cache
 
+    @staticmethod
+    async def _init_coordination_redis_env_fallback(litellm_settings: Mapping[str, object]) -> RedisCache | None:
+        """
+        Last-resort coordination Redis, tried after an explicit
+        `general_settings.coordination_redis` block and `litellm_settings.cache`
+        have both had a chance to resolve one. Without this, a deployment that
+        only exports REDIS_HOST/REDIS_PORT (no cache block, no coordination_redis
+        block) gets NO cross-pod coordination at all: spend counters, budget-window
+        enforcement, and the reset_spend cache-eviction broadcast all silently stay
+        per-pod local, so a key reset on one pod never clears another pod's stale
+        enforcement.
+
+        Unlike the explicit block and cache-backend paths (a deliberate opt-in, so a
+        bad connection target or a malformed REDIS_CLUSTER_NODES/REDIS_SENTINEL_NODES
+        value should fail loudly), this one is inferred from bare env vars that may be
+        set for an unrelated reason -- e.g. a REDIS_HOST left over from a different
+        job/service, or a REDIS_CLUSTER_NODES value nothing here ever asked to be
+        parsed. Wrongly guessing "coordination available" must not turn a previously
+        harmless in-memory-only proxy into one that fails to boot or raises on every
+        cache write, so a malformed value or a failed/slow ping are both treated the
+        same as no REDIS_* vars at all.
+        """
+        try:
+            env_coordination_redis_cache: Final = _build_redis_usage_cache_from_environment()
+        except Exception as e:  # noqa: BLE001  # a malformed inferred Redis env var must not block startup
+            verbose_proxy_logger.warning(
+                "coordination_redis: could not build a Redis client from REDIS_* environment variables "
+                "(%s); cross-pod coordination stays in-memory. Set general_settings.coordination_redis "
+                "explicitly to require it.",
+                e,
+            )
+            return None
+        if env_coordination_redis_cache is None:
+            return None
+        try:
+            reachable: Final = await asyncio.wait_for(env_coordination_redis_cache.ping(), timeout=2.0)
+        except Exception as e:  # noqa: BLE001  # an unreachable inferred Redis must not block startup or writes
+            verbose_proxy_logger.warning(
+                "coordination_redis: REDIS_* environment variables named a Redis that is not reachable "
+                "(%s); cross-pod coordination stays in-memory. Set general_settings.coordination_redis "
+                "explicitly to require it.",
+                e,
+            )
+            return None
+        if not reachable:
+            return None
+        _attach_redis_usage_cache(
+            env_coordination_redis_cache,
+            enable_redis_auth_cache=litellm_settings.get("enable_redis_auth_cache", False) is True,
+        )
+        verbose_proxy_logger.info(
+            "coordination_redis: using a standalone Redis built from REDIS_* "
+            "environment variables for usage tracking, rate limiting, and "
+            "cross-pod coordination."
+        )
+        return env_coordination_redis_cache
+
     def _init_cache(
         self,
         cache_params: dict,
@@ -5409,6 +5469,13 @@ class ProxyConfig:
                         reset_audit_log_callback_cache()
                         _in_memory_loggers[:] = [cb for cb in _in_memory_loggers if not isinstance(cb, S3V2Logger)]
 
+        if redis_usage_cache is None:
+            env_coordination_redis_cache: Final = await self._init_coordination_redis_env_fallback(
+                litellm_settings=litellm_settings
+            )
+            if env_coordination_redis_cache is not None:
+                _set_redis_usage_cache(env_coordination_redis_cache)
+
         ## GENERAL SERVER SETTINGS (e.g. master key,..) # do this after initializing litellm, to ensure sentry logging works for proxylogging
         general_settings = config.get("general_settings", {})
         if general_settings is None:
@@ -5713,13 +5780,9 @@ class ProxyConfig:
         router_settings: Final = config.get("router_settings", None)
 
         if router_settings and isinstance(router_settings, dict):
-            # model list and search_tools already set
-            exclude_args: Final = {
-                "model_list",
-                "search_tools",
-            }
-
-            available_args: Final = [x for x in litellm.Router.get_valid_args() if x not in exclude_args]
+            available_args: Final = [
+                x for x in litellm.Router.get_valid_args() if x not in ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG
+            ]
 
             for k, v in router_settings.items():
                 if k in available_args:
@@ -6646,6 +6709,12 @@ class ProxyConfig:
         if "max_batch_file_size_mb" not in self._yaml_general_settings_keys:
             general_settings["max_batch_file_size_mb"] = _general_settings.get("max_batch_file_size_mb")
 
+        if "max_file_size_mb" not in self._yaml_general_settings_keys:
+            general_settings["max_file_size_mb"] = _general_settings.get("max_file_size_mb")
+
+        if "blocked_file_extensions" not in self._yaml_general_settings_keys:
+            general_settings["blocked_file_extensions"] = _general_settings.get("blocked_file_extensions")
+
         ## ALERTING ARGS ##
         if "alerting_args" in _general_settings:
             general_settings["alerting_args"] = _general_settings["alerting_args"]
@@ -9870,6 +9939,35 @@ class ProxyStartupEvent:
                 replace_existing=True,
             )
 
+            slack_alerting_args: Final = proxy_logging_obj.slack_alerting_instance.alerting_args
+            user_spend_check_interval: Final = (
+                slack_alerting_args.user_spend_check_interval
+                if isinstance(slack_alerting_args, SlackAlertingArgs)  # pyright: ignore[reportUnnecessaryIsInstance]  # tests inject a mock slack_alerting_instance
+                else SlackAlertingArgs().user_spend_check_interval
+            )
+
+            async def _scheduled_user_spend_alerts() -> None:
+                if (
+                    await pod_lock_manager.acquire_lock(
+                        cronjob_id=USER_SPEND_ALERTS_JOB_ID,
+                        ttl=max(user_spend_check_interval - 60, 60),
+                        allow_reentrant=False,
+                    )
+                    is False
+                ):
+                    return
+                await proxy_logging_obj.slack_alerting_instance.send_user_spend_alerts()
+
+            scheduler.add_job(
+                _scheduled_user_spend_alerts,
+                "interval",
+                seconds=user_spend_check_interval,
+                next_run_time=datetime.now(timezone.utc) + timedelta(seconds=10 + random.randint(0, 60)),
+                id=USER_SPEND_ALERTS_JOB_ID,
+                replace_existing=True,
+                misfire_grace_time=APSCHEDULER_MISFIRE_GRACE_TIME,
+            )
+
             if os.getenv("PROMETHEUS_URL"):
                 from zoneinfo import ZoneInfo
 
@@ -10197,7 +10295,8 @@ async def model_list(
         # The internal routing key drives the metadata/fallback lookup, while the
         # public name is what the client sees as the model id.
         model_data = []
-        for response_id, lookup_id in TeamModelNameTranslator.listing_entries(all_models, llm_router, settings):
+        admin_entries: Final = TeamModelNameTranslator.listing_entries(all_models, llm_router, settings)
+        for response_id, lookup_id in admin_entries:
             model_info = create_model_info_response(
                 model_id=lookup_id,
                 provider="openai",
@@ -10210,7 +10309,10 @@ async def model_list(
 
         if wants_anthropic_format:
             admin_listing: Final = cast(Sequence[ModelInfoResponse], model_data)  # cast-ok: rows built above
-            return create_anthropic_model_list_response(admin_listing)
+            return create_anthropic_model_list_response(
+                admin_listing,
+                display_names=configured_display_names(admin_entries, llm_router),
+            )
 
         return dict(
             data=model_data,
@@ -10241,7 +10343,8 @@ async def model_list(
     # The internal routing key drives the metadata/fallback lookup, while the
     # public name is what the client sees as the model id.
     model_data = []
-    for response_id, lookup_id in TeamModelNameTranslator.listing_entries(all_models, llm_router, settings):
+    entries: Final = TeamModelNameTranslator.listing_entries(all_models, llm_router, settings)
+    for response_id, lookup_id in entries:
         model_info = create_model_info_response(
             model_id=lookup_id,
             provider="openai",
@@ -10254,7 +10357,10 @@ async def model_list(
 
     if wants_anthropic_format:
         listing: Final = cast(Sequence[ModelInfoResponse], model_data)  # cast-ok: rows built above
-        return create_anthropic_model_list_response(listing)
+        return create_anthropic_model_list_response(
+            listing,
+            display_names=configured_display_names(entries, llm_router),
+        )
 
     return dict(
         data=model_data,
@@ -11066,15 +11172,14 @@ async def audio_speech(
         if callback_headers:
             custom_headers.update(callback_headers)
 
-        # Determine media type based on model type
-        media_type = "audio/mpeg"  # Default for OpenAI TTS
-        request_model: Final = data.get("model", "")
-        if request_model:
-            request_model_lower: Final = request_model.lower()
-            if "gemini" in request_model_lower and (
-                "tts" in request_model_lower or "preview-tts" in request_model_lower
-            ):
-                media_type = "audio/wav"  # Gemini TTS returns WAV format after conversion
+        requested_format: Final = data.get("response_format")
+        upstream_content_type: Final = (
+            response.response.headers.get("content-type") if isinstance(response, HttpxBinaryResponseContent) else None
+        )
+        media_type: Final = resolve_speech_media_type(
+            upstream_content_type=upstream_content_type,
+            response_format=requested_format if isinstance(requested_format, str) else None,
+        )
 
         return StreamingResponse(
             _audio_speech_chunk_generator(response),
@@ -11090,7 +11195,15 @@ async def audio_speech(
         )
         verbose_proxy_logger.error("litellm.proxy.proxy_server.audio_speech(): Exception occured - %s", e)
         verbose_proxy_logger.debug(traceback.format_exc())
-        raise e
+        if isinstance(e, (ProxyException, HTTPException)):
+            raise e
+        raise ProxyException(
+            message=getattr(e, "message", f"{e}"),
+            type=getattr(e, "type", "None"),
+            param=getattr(e, "param", "None"),
+            openai_code=getattr(e, "code", None),
+            code=getattr(e, "status_code", 500),
+        )
 
 
 @router.post(
@@ -12478,11 +12591,21 @@ async def supported_openai_params(model: str):
         --header 'Authorization: Bearer sk-1234'
     ```
     """
+    from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider
+
+    global llm_router
     try:
-        model, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
+        resolved_models: Final = llm_router.resolved_litellm_models(model) if llm_router is not None else ()
+        target_model: Final = resolved_models[0] if resolved_models else model
+        declared_provider: Final = declared_authenticating_provider(target_model)
+        litellm_model, custom_llm_provider = (
+            (target_model.removeprefix(f"{declared_provider}/"), declared_provider)
+            if declared_provider is not None
+            else litellm.get_llm_provider(model=target_model)[:2]
+        )
         return {
             "supported_openai_params": litellm.get_supported_openai_params(
-                model=model, custom_llm_provider=custom_llm_provider
+                model=litellm_model, custom_llm_provider=custom_llm_provider
             )
         }
     except Exception:
@@ -14959,17 +15082,25 @@ async def alerting_settings(
         alerting_args_dict = {}
         alerting_values = None
 
-    allowed_args: Final = {
-        "slack_alerting": {"type": "Boolean"},
-        "daily_report_frequency": {"type": "Integer"},
-        "report_check_interval": {"type": "Integer"},
-        "budget_alert_ttl": {"type": "Integer"},
-        "outage_alert_ttl": {"type": "Integer"},
-        "region_outage_alert_ttl": {"type": "Integer"},
-        "minor_outage_alert_threshold": {"type": "Integer"},
-        "major_outage_alert_threshold": {"type": "Integer"},
-        "max_outage_alert_list_size": {"type": "Integer"},
-    }
+    allowed_args: Final = MappingProxyType(
+        {
+            "slack_alerting": "Boolean",
+            "daily_report_frequency": "Integer",
+            "report_check_interval": "Integer",
+            "budget_alert_ttl": "Integer",
+            "outage_alert_ttl": "Integer",
+            "region_outage_alert_ttl": "Integer",
+            "minor_outage_alert_threshold": "Integer",
+            "major_outage_alert_threshold": "Integer",
+            "max_outage_alert_list_size": "Integer",
+            "daily_spend_per_user_threshold": "Float",
+            "monthly_spend_per_user_threshold": "Float",
+            "spend_anomaly_multiplier": "Float",
+            "spend_anomaly_baseline_days": "Integer",
+            "spend_anomaly_min_spend": "Float",
+            "user_spend_check_interval": "Integer",
+        }
+    )
 
     _slack_alerting: Final[SlackAlerting] = proxy_logging_obj.slack_alerting_instance
     _slack_alerting_args_dict: Final = _slack_alerting.alerting_args.model_dump()
@@ -14984,7 +15115,7 @@ async def alerting_settings(
 
     _response_obj = ConfigList(
         field_name="slack_alerting",
-        field_type=allowed_args["slack_alerting"]["type"],
+        field_type=allowed_args["slack_alerting"],
         field_description="Enable slack alerting for monitoring proxy in production: llm outages, budgets, spend tracking failures.",
         field_value=is_slack_enabled,
         stored_in_db=True if alerting_values is not None else False,
@@ -15003,7 +15134,7 @@ async def alerting_settings(
 
             _response_obj = ConfigList(
                 field_name=field_name,
-                field_type=allowed_args[field_name]["type"],
+                field_type=allowed_args[field_name],
                 field_description=field_info.description or "",
                 field_value=_slack_alerting_args_dict.get(field_name, None),
                 stored_in_db=_stored_in_db,
@@ -15176,6 +15307,7 @@ async def login(request: Request):
         password=password,
         master_key=master_key,
         prisma_client=prisma_client,
+        general_settings=general_settings,
     )
 
     # Create UI token object
@@ -15197,7 +15329,10 @@ async def login(request: Request):
     # authorize round-trip), mirroring the SSO callback; otherwise land on the dashboard. Gated by
     # _is_same_origin_return_path (strictly relative path) so it can never be an open redirect, and the
     # one-shot cookie is cleared after use.
-    from litellm.proxy.management_endpoints.ui_sso import _sso_return_to_redirect
+    from litellm.proxy.management_endpoints.ui_sso import (
+        _sso_return_to_redirect,
+        set_session_token_cookie,
+    )
 
     # Resume through the SAME resumer the SSO callback uses, rather than a second, narrower arm.
     # _persist_return_to_cookie stores both shapes it accepts (a relative same-origin path AND a
@@ -15214,6 +15349,7 @@ async def login(request: Request):
                 jwt_token=jwt_token,
                 redis_usage_cache=redis_usage_cache,
                 user_api_key_cache=user_api_key_cache,
+                request=request,
             )
         except Exception:  # noqa: BLE001  # resuming must NEVER block a completed sign-in
             # The symmetric half of _persist_return_to_cookie's "never raises" contract. The resumer
@@ -15228,7 +15364,7 @@ async def login(request: Request):
 
     # Create redirect response with cookie
     redirect_response: Final = RedirectResponse(url=litellm_dashboard_ui, status_code=303)
-    redirect_response.set_cookie(key="token", value=jwt_token)
+    set_session_token_cookie(redirect_response, request, jwt_token)
     if cp_return_to:
         redirect_response.delete_cookie(key="litellm_cp_return_to")
     return redirect_response
@@ -15238,6 +15374,7 @@ async def login(request: Request):
 async def login_v2(request: Request):
     global premium_user, general_settings, master_key
     from litellm.proxy.auth.login_utils import authenticate_user, create_ui_token_object, encode_ui_session_jwt
+    from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
     from litellm.proxy.utils import get_custom_url
 
     try:
@@ -15250,6 +15387,7 @@ async def login_v2(request: Request):
             password=password,
             master_key=master_key,
             prisma_client=prisma_client,
+            general_settings=general_settings,
         )
 
         returned_ui_token_object: Final = create_ui_token_object(
@@ -15271,7 +15409,7 @@ async def login_v2(request: Request):
             content={"redirect_url": litellm_dashboard_ui, "token": jwt_token},
             status_code=status.HTTP_200_OK,
         )
-        json_response.set_cookie(key="token", value=jwt_token)
+        set_session_token_cookie(json_response, request, jwt_token)
         return json_response
     except Exception as e:
         verbose_proxy_logger.exception("litellm.proxy.proxy_server.login_v2(): Exception occurred - %s", e)
@@ -15320,6 +15458,7 @@ async def login_v3(request: Request):
             password=password,
             master_key=master_key,
             prisma_client=prisma_client,
+            general_settings=general_settings,
         )
 
         returned_ui_token_object: Final = create_ui_token_object(
@@ -15370,6 +15509,8 @@ async def login_v3(request: Request):
 
 @router.post("/v3/login/exchange", include_in_schema=False)  # exchange single-use opaque code for JWT
 async def login_v3_exchange(request: Request):
+    from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
     try:
         if not general_settings.get("control_plane_url"):
             raise ProxyException(
@@ -15416,7 +15557,7 @@ async def login_v3_exchange(request: Request):
             },
             status_code=status.HTTP_200_OK,
         )
-        json_response.set_cookie(key="token", value=cached_data["token"])
+        set_session_token_cookie(json_response, request, cached_data["token"])
         return json_response
     except ProxyException:
         raise
@@ -15689,6 +15830,7 @@ async def claim_onboarding_link(data: InvitationClaim, request: Request):
             detail={"error": "Invalid onboarding session for invitation link."},
         )
 
+    validate_password_policy(data.password, general_settings)
     hashed_pw: Final = hash_password(data.password)
     current_time = litellm.utils.get_utc_datetime()
     async with prisma_client.db.tx() as tx:
@@ -16156,6 +16298,7 @@ async def invitation_delete(
 )
 async def update_config(
     config_info: ConfigYAML,
+    request: Request,
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
 ):
     """
@@ -16171,6 +16314,26 @@ async def update_config(
         if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN:
             raise HTTPException(status_code=403, detail="Only proxy admins can update config")
 
+        request_body: Final[Mapping[str, JsonValue]] = TypeAdapter(Mapping[str, JsonValue]).validate_python(
+            await request.json()
+        )
+        raw_router_settings: Final = request_body.get("router_settings")
+        if isinstance(raw_router_settings, dict):
+            supported_router_settings: Final = RUNTIME_UPDATABLE_ROUTER_SETTINGS | (
+                frozenset(litellm.Router.get_valid_args()) - ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG
+            )
+            unsupported_router_settings: Final = sorted(set(raw_router_settings) - supported_router_settings)
+            if unsupported_router_settings:
+                raise HTTPException(
+                    status_code=400,
+                    detail={
+                        "error": (
+                            f"Unsupported router settings: {', '.join(unsupported_router_settings)} "
+                            "are not valid router settings"
+                        )
+                    },
+                )
+
         if prisma_client is None:
             raise Exception("No DB Connected")
 
@@ -16272,11 +16435,19 @@ async def update_config(
             )
 
         # router_settings: merge existing + request, request wins.
-        if config_info.router_settings is not None:
+        if isinstance(raw_router_settings, dict):
             existing = await _read_section("router_settings")
             before_router_settings: Final = copy.deepcopy(existing)
-            updates = config_info.router_settings.dict(exclude_none=True)
-            new_router_settings: Final = {**existing, **updates}
+            typed_router_settings: Final = (
+                config_info.router_settings.dict(exclude_none=True) if config_info.router_settings is not None else {}
+            )
+            raw_router_settings_without_none: Final = {
+                key: value
+                for key, value in raw_router_settings.items()
+                if key not in typed_router_settings and value is not None
+            }
+            router_settings_updates: Final = {**typed_router_settings, **raw_router_settings_without_none}
+            new_router_settings: Final = {**existing, **router_settings_updates}
             await _upsert_section("router_settings", new_router_settings)
             asyncio.create_task(
                 create_config_audit_log(
@@ -16323,6 +16494,8 @@ _GENERAL_SETTINGS_CONFIG_LIST_FIELD_TYPES: Final[Mapping[str, str]] = MappingPro
         "global_max_parallel_requests": "Integer",
         "max_request_size_mb": "Integer",
         "max_batch_file_size_mb": "Integer",
+        "max_file_size_mb": "Integer",
+        "blocked_file_extensions": "List",
         "max_response_size_mb": "Integer",
         "proxy_config_reload_interval_seconds": "Integer",
         "pass_through_endpoints": "PydanticModel",
@@ -16431,6 +16604,16 @@ async def update_config_general_settings(
             detail={"error": f"Invalid type of field value={type(data.field_value)} passed in."},
         )
 
+    if data.field_name == "alerting_args":
+        try:
+            SlackAlertingArgs.model_validate(data.field_value)
+        except ValidationError as e:
+            errors: Final = "; ".join(f"{'.'.join(str(loc) for loc in err['loc'])}: {err['msg']}" for err in e.errors())
+            raise HTTPException(
+                status_code=400,
+                detail={"error": f"Invalid alerting_args: {errors}"},
+            )
+
     ## get general settings from db
     db_general_settings: Final = await _config_param_table(prisma_client).find_first(
         where={"param_name": "general_settings"}
@@ -16566,6 +16749,7 @@ async def create_config_audit_log(
 
 _EXTRA_SECRET_CALLBACK_ENV_VARS: Final = frozenset(
     {
+        "ALERTING_WEBHOOK_URL",
         "GALILEO_USERNAME",
         "GENERIC_LOGGER_HEADERS",
         "OTEL_HEADERS",
diff --git a/litellm/proxy/public_endpoints/agent_create_fields.json b/litellm/proxy/public_endpoints/agent_create_fields.json
index 36484cc1065..cc2fc17d759 100644
--- a/litellm/proxy/public_endpoints/agent_create_fields.json
+++ b/litellm/proxy/public_endpoints/agent_create_fields.json
@@ -107,7 +107,9 @@
         "required": true,
         "field_type": "text",
         "default_value": null,
-        "include_in_litellm_params": false
+        "include_in_litellm_params": false,
+        "validation_pattern": "^arn:aws[a-zA-Z0-9-]*:bedrock-agentcore:[a-z0-9-]+:[0-9]{12}:runtime/.+$",
+        "validation_message": "Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after \"runtime/\" (e.g. arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/my-agent-runtime)."
       }
     ],
     "litellm_params_template": {
diff --git a/litellm/proxy/public_endpoints/provider_create_fields.json b/litellm/proxy/public_endpoints/provider_create_fields.json
index 4652719a23b..66f8c2ea36f 100644
--- a/litellm/proxy/public_endpoints/provider_create_fields.json
+++ b/litellm/proxy/public_endpoints/provider_create_fields.json
@@ -986,6 +986,62 @@
     ],
     "default_model_placeholder": "gpt-3.5-turbo"
   },
+  {
+    "provider": "QwenCloud",
+    "provider_display_name": "QwenCloud",
+    "litellm_provider": "qwencloud",
+    "credential_fields": [
+      {
+        "key": "api_key",
+        "label": "QwenCloud API Key",
+        "placeholder": null,
+        "tooltip": null,
+        "required": true,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "api_base",
+        "label": "API Base",
+        "placeholder": "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
+        "tooltip": "The base URL for QwenCloud. Defaults to https://dashscope-intl.aliyuncs.com/compatible-mode/v1 if not specified.",
+        "required": true,
+        "field_type": "text",
+        "options": null,
+        "default_value": "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
+      }
+    ],
+    "default_model_placeholder": "gpt-3.5-turbo"
+  },
+  {
+    "provider": "Qwen_AI_Platform",
+    "provider_display_name": "Qwen AI Platform",
+    "litellm_provider": "qwen_ai_platform",
+    "credential_fields": [
+      {
+        "key": "api_key",
+        "label": "Qwen AI Platform API Key",
+        "placeholder": null,
+        "tooltip": null,
+        "required": true,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "api_base",
+        "label": "API Base",
+        "placeholder": "https://dashscope.aliyuncs.com/compatible-mode/v1",
+        "tooltip": "The base URL for Qwen AI Platform. Defaults to https://dashscope.aliyuncs.com/compatible-mode/v1 if not specified.",
+        "required": true,
+        "field_type": "text",
+        "options": null,
+        "default_value": "https://dashscope.aliyuncs.com/compatible-mode/v1"
+      }
+    ],
+    "default_model_placeholder": "gpt-3.5-turbo"
+  },
   {
     "provider": "Databricks",
     "provider_display_name": "Databricks",
@@ -1318,6 +1374,68 @@
     ],
     "default_model_placeholder": "gpt-3.5-turbo"
   },
+  {
+    "provider": "GIGACHAT",
+    "provider_display_name": "GigaChat",
+    "litellm_provider": "gigachat",
+    "credential_fields": [
+      {
+        "key": "api_base",
+        "label": "API Base",
+        "placeholder": null,
+        "tooltip": null,
+        "required": false,
+        "field_type": "text",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "api_key",
+        "label": "API Key",
+        "placeholder": null,
+        "tooltip": null,
+        "required": false,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "gigachat_scope",
+        "label": "Scope",
+        "placeholder": null,
+        "tooltip": null,
+        "required": false,
+        "field_type": "select",
+        "options": [
+          "GIGACHAT_API_PERS",
+          "GIGACHAT_API_B2B",
+          "GIGACHAT_API_CORP"
+        ],
+        "default_value": "GIGACHAT_API_PERS"
+      },
+      {
+        "key": "gigachat_auth_url",
+        "label": "Auth URL",
+        "placeholder": null,
+        "tooltip": null,
+        "required": false,
+        "field_type": "text",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "gigachat_access_token",
+        "label": "Access token",
+        "placeholder": null,
+        "tooltip": "Disable OAuth, provide value to authorization.",
+        "required": false,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      }
+    ],
+    "default_model_placeholder": "GigaChat-2"
+  },
   {
     "provider": "GITHUB",
     "provider_display_name": "Github",
diff --git a/litellm/proxy/rag_endpoints/endpoints.py b/litellm/proxy/rag_endpoints/endpoints.py
index 4d62f1d6d71..0ab7d99e4e4 100644
--- a/litellm/proxy/rag_endpoints/endpoints.py
+++ b/litellm/proxy/rag_endpoints/endpoints.py
@@ -7,16 +7,22 @@ Provides:
 """
 
 import base64
+import json
 from collections.abc import Mapping
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 import orjson
 from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
 from fastapi.responses import ORJSONResponse, StreamingResponse
+from starlette.datastructures import UploadFile
 
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH
+from litellm.integrations.vector_store_integrations.vector_store_pre_call_hook import (
+    LiteLLM_ManagedVectorStore,
+)
 from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
 from litellm.proxy._types import *
 from litellm.proxy.auth.auth_utils import is_request_body_safe
@@ -34,6 +40,10 @@ from litellm.proxy.rag_endpoints.upload_security import (
     RejectedUpload,
     validate_upload,
 )
+from litellm.proxy.vector_store_endpoints.endpoints import (
+    build_request_data_from_managed_vector_store,
+    reject_caller_embedding_selection_params,
+)
 from litellm.proxy.vector_store_endpoints.utils import (
     assert_user_can_access_vector_store_id,
 )
@@ -45,6 +55,16 @@ if TYPE_CHECKING:
 router: Final = APIRouter()
 
 
+def _as_string_keyed_mapping(value: object) -> Mapping[str, object] | None:
+    if isinstance(value, Mapping):
+        return value
+    return None
+
+
+def _response_attr(source: object, name: str) -> object:
+    return getattr(source, name, None)
+
+
 def _raise_vector_store_scan_depth_exceeded() -> None:
     raise HTTPException(
         status_code=400,
@@ -53,8 +73,8 @@ def _raise_vector_store_scan_depth_exceeded() -> None:
 
 
 def _append_payload_to_scan_stack(
-    payload_stack: list[tuple[Any, int]],
-    value: Any,
+    payload_stack: list[tuple[object, int]],
+    value: object,
     next_depth: int,
 ) -> None:
     if isinstance(value, dict):
@@ -108,16 +128,25 @@ def _collect_vector_store_ids_from_payload(payload: object) -> set[str]:
 async def _authorize_nested_vector_store_ids(
     payload: object,
     user_api_key_dict: UserAPIKeyAuth,
-) -> None:
-    for vector_store_id in sorted(_collect_vector_store_ids_from_payload(payload)):
-        await assert_user_can_access_vector_store_id(
-            vector_store_id=vector_store_id,
-            user_api_key_dict=user_api_key_dict,
-        )
+) -> Mapping[str, LiteLLM_ManagedVectorStore]:
+    """Authorize every nested vector store id and return the managed stores it resolved."""
+    return MappingProxyType(
+        {
+            vector_store_id: store
+            for vector_store_id in sorted(_collect_vector_store_ids_from_payload(payload))
+            if (
+                store := await assert_user_can_access_vector_store_id(
+                    vector_store_id=vector_store_id,
+                    user_api_key_dict=user_api_key_dict,
+                )
+            )
+            is not None
+        }
+    )
 
 
 def _build_file_metadata_entry(
-    response: Any,
+    response: object,
     file_data: tuple[str, bytes, str] | None = None,
     file_url: str | None = None,
 ) -> Mapping[str, str | int | None]:
@@ -135,11 +164,11 @@ def _build_file_metadata_entry(
     from datetime import datetime, timezone
 
     # Extract file_id from response
-    file_id = None
-    if hasattr(response, "get"):
-        file_id = response.get("file_id")
-    elif hasattr(response, "file_id"):
-        file_id = response.file_id
+    mapping_response: Final = _as_string_keyed_mapping(response)
+    raw_file_id: Final = (
+        mapping_response.get("file_id") if mapping_response is not None else _response_attr(response, "file_id")
+    )
+    file_id: Final = raw_file_id if isinstance(raw_file_id, str) else None
 
     # Extract file information from file_data tuple
     filename = None
@@ -152,7 +181,7 @@ def _build_file_metadata_entry(
         content_type = file_data[2] if len(file_data) > 2 else None
 
     # Build file metadata entry
-    file_entry: Final = {
+    file_entry: Final[dict[str, str | int | None]] = {
         "file_id": file_id,
         "filename": filename,
         "file_url": file_url,
@@ -169,7 +198,7 @@ def _build_file_metadata_entry(
 
 
 async def _save_vector_store_to_db_from_rag_ingest(
-    response: Any,
+    response: object,
     ingest_options: Mapping[str, dict[str, str | None]],
     prisma_client: "PrismaClient",
     user_api_key_dict: UserAPIKeyAuth,
@@ -197,10 +226,11 @@ async def _save_vector_store_to_db_from_rag_ingest(
     )
 
     # Handle both dict and object responses
-    if hasattr(response, "get"):
-        vector_store_id = response.get("vector_store_id")
+    mapping_response: Final = _as_string_keyed_mapping(response)
+    if mapping_response is not None:
+        vector_store_id = mapping_response.get("vector_store_id")
     elif hasattr(response, "vector_store_id"):
-        vector_store_id = response.vector_store_id
+        vector_store_id = _response_attr(response, "vector_store_id")
     else:
         verbose_proxy_logger.warning("Unable to extract vector_store_id from response type: %s", type(response))
         return
@@ -266,14 +296,13 @@ async def _save_vector_store_to_db_from_rag_ingest(
             verbose_proxy_logger.info("Vector store %s already exists, appending file to metadata", vector_store_id)
 
             # Update existing vector store with new file
-            existing_metadata = existing_vector_store.vector_store_metadata or {}
-            if isinstance(existing_metadata, str):
-                import json
+            stored_metadata: Final = existing_vector_store.vector_store_metadata or {}
+            existing_metadata: dict[str, object] = (
+                json.loads(stored_metadata) if isinstance(stored_metadata, str) else stored_metadata
+            )
 
-                existing_metadata = json.loads(existing_metadata)
-
-            ingested_files: Final = existing_metadata.get("ingested_files", [])
-            ingested_files.append(file_entry)
+            previous_files: Final = existing_metadata.get("ingested_files", [])
+            ingested_files: Final = [*previous_files, file_entry] if isinstance(previous_files, list) else [file_entry]
             existing_metadata["ingested_files"] = ingested_files
 
             # Update the vector store
@@ -340,9 +369,9 @@ async def parse_rag_ingest_request(
 
         # Get file
         file_obj = form_data.get("file")
-        if file_obj is not None and hasattr(file_obj, "read"):
+        if isinstance(file_obj, UploadFile):
             file_content = await file_obj.read(MAX_UPLOAD_SIZE_BYTES + 1)
-            file_data = (file_obj.filename, file_content, file_obj.content_type)
+            file_data = (file_obj.filename or "", file_content, file_obj.content_type or "")
 
         # Parse JSON from 'request' form field (contains full request body as JSON)
         request_json_str: Final[str | bytes | None] = form_data.get("request")
@@ -688,11 +717,27 @@ async def rag_query(
                 status_code=400,
                 detail={"error": "retrieval_config must contain 'vector_store_id'"},
             )
-        await _authorize_nested_vector_store_ids(
+        reject_caller_embedding_selection_params(payload=retrieval_config, source="retrieval_config")
+        resolved_stores: Final = await _authorize_nested_vector_store_ids(
             payload=retrieval_config,
             user_api_key_dict=user_api_key_dict,
         )
 
+        # Merge litellm-managed vector store params (provider, region, embedding
+        # model, credentials, ...) from the registry: the same source the direct
+        # /vector_stores/{id}/search endpoint uses. Store-managed keys win on
+        # conflict so callers cannot override the store's provider or credentials.
+        managed_store: Final = resolved_stores.get(retrieval_config["vector_store_id"])
+        store_data: Final = (
+            await build_request_data_from_managed_vector_store(managed_store)
+            if managed_store is not None
+            else MappingProxyType({})
+        )
+        merged_retrieval_config: Final = {
+            **retrieval_config,
+            **store_data,
+        }  # mutable-ok: litellm.aquery requires a plain dict payload
+
         # Add litellm data
         request_data: dict[str, object] = {}
         request_data = await add_litellm_data_to_request(
@@ -704,13 +749,18 @@ async def rag_query(
             proxy_config=proxy_config,
         )
 
-        verbose_proxy_logger.debug("RAG Query - model: %s, retrieval_config: %s", model, retrieval_config)
+        verbose_proxy_logger.debug(
+            "RAG Query - model: %s, vector_store_id: %s, custom_llm_provider: %s",
+            model,
+            retrieval_config["vector_store_id"],
+            merged_retrieval_config.get("custom_llm_provider"),
+        )
 
         # Call query
         response: Final = await litellm.aquery(
             model=model,
             messages=messages,
-            retrieval_config=retrieval_config,
+            retrieval_config=merged_retrieval_config,
             rerank=rerank,
             stream=stream,
             router=llm_router,
diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py
index 5e56e822484..5907ffc64eb 100644
--- a/litellm/proxy/response_api_endpoints/endpoints.py
+++ b/litellm/proxy/response_api_endpoints/endpoints.py
@@ -1,14 +1,18 @@
 import asyncio
 import json
 import time
-from collections.abc import AsyncIterator, Mapping
+from collections.abc import AsyncIterator, Awaitable, Mapping
+from enum import Enum
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, NamedTuple, cast, get_args
+from typing import TYPE_CHECKING, Any, Final, NamedTuple, Protocol, cast, get_args
 from uuid import uuid4
 
 import fastapi
 from fastapi import APIRouter, Depends, HTTPException, Request, Response
+from fastapi.responses import JSONResponse
+from openai.types.responses.response_create_params import ResponseInputParam
 from starlette.websockets import WebSocket, WebSocketDisconnect
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.integrations.custom_guardrail import ModifyResponseException
@@ -26,8 +30,13 @@ from litellm.proxy.common_utils.http_parsing_utils import (
     _read_request_body,
     _safe_set_request_parsed_body,
 )
-from litellm.types.llms.openai import REASONING_EFFORT, ResponsesAPIResponse
+from litellm.types.llms.openai import (
+    REASONING_EFFORT,
+    ResponsesAPIOptionalRequestParams,
+    ResponsesAPIResponse,
+)
 from litellm.types.responses.main import DeleteResponseResult
+from litellm.types.utils import TokenCountResponse
 
 if TYPE_CHECKING:
     from litellm.router import Router
@@ -35,7 +44,7 @@ if TYPE_CHECKING:
 router: Final = APIRouter()
 
 _user_api_key_auth_dep: Final = Depends(user_api_key_auth)
-_RESPONSES_TAGS: Final = ["responses"]  # mutable-ok: fastapi's route signature requires List[str] tags
+_RESPONSES_TAGS: Final[list[str | Enum]] = ["responses"]  # mutable-ok: fastapi's route signature requires list tags
 
 _TOOL_PAYLOAD_KEYS: Final[Mapping[str, tuple[str, ...]]] = MappingProxyType(
     {
@@ -43,7 +52,7 @@ _TOOL_PAYLOAD_KEYS: Final[Mapping[str, tuple[str, ...]]] = MappingProxyType(
         "function": ("name", "description", "parameters", "strict"),
     }
 )
-_EMPTY_TOOL_PAYLOAD: Final[Mapping[str, Any]] = MappingProxyType({})
+_EMPTY_TOOL_PAYLOAD: Final[Mapping[str, object]] = MappingProxyType({})
 
 
 def _convert_tool_payload_value(key: str, value: object, *, to_chat: bool) -> object:
@@ -96,7 +105,7 @@ def _normalize_tool_dialect(
     return {**data, **{key: value for key, value in replaceable if key in data}}  # mutable-ok: plain body dict
 
 
-def _is_chat_completions_body(data: Mapping[str, Any]) -> bool:
+def _is_chat_completions_body(data: Mapping[str, object]) -> bool:
     messages: Final = data.get("messages")
     if isinstance(messages, list) and messages:
         return True
@@ -1017,6 +1026,152 @@ async def compact_response(
         )
 
 
+class _ResponsesApiErrorDetail(TypedDict):
+    message: ReadOnly[str]
+    type: ReadOnly[str]
+    param: ReadOnly[str | None]
+    code: ReadOnly[str | None]
+
+
+class _ResponsesApiErrorBody(TypedDict):
+    error: ReadOnly[_ResponsesApiErrorDetail]
+
+
+class _ResponsesInputTokensResult(TypedDict):
+    object: ReadOnly[str]
+    input_tokens: ReadOnly[int]
+
+
+class _TokenCountPayload(TypedDict):
+    model: ReadOnly[str]
+    messages: ReadOnly[tuple[Mapping[str, object], ...]]
+    tools: ReadOnly[object]
+
+
+class _TokenCounter(Protocol):
+    def __call__(self, request: TokenCountRequest, call_endpoint: bool) -> Awaitable[TokenCountResponse]: ...
+
+
+def _proxy_token_counter() -> _TokenCounter:
+    from litellm.proxy.proxy_server import token_counter
+
+    return token_counter
+
+
+_token_counter_dep: Final = Depends(_proxy_token_counter)
+
+
+def _responses_invalid_request_response(message: str, param: str | None, code: str | None) -> JSONResponse:
+    body: Final[_ResponsesApiErrorBody] = {
+        "error": {
+            "message": message,
+            "type": "invalid_request_error",
+            "param": param,
+            "code": code,
+        }
+    }
+    return JSONResponse(status_code=400, content=body)
+
+
+def _missing_responses_param_response(param: str) -> JSONResponse:
+    return _responses_invalid_request_response(
+        message=f"Missing required parameter: '{param}'.",
+        param=param,
+        code="missing_required_parameter",
+    )
+
+
+def _responses_input_as_token_count_messages(
+    input_value: str | ResponseInputParam,
+    instructions: str | None,
+) -> tuple[Mapping[str, object], ...]:
+    from litellm.responses.litellm_completion_transformation.transformation import (
+        LiteLLMCompletionResponsesConfig,
+    )
+
+    request_params: Final[ResponsesAPIOptionalRequestParams] = {"instructions": instructions}
+    transformed: Final = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+        input=input_value,
+        responses_api_request=request_params,
+    )
+    return tuple(
+        message if isinstance(message, dict) else message.model_dump(exclude_none=True) for message in transformed
+    )
+
+
+@router.post(
+    "/v1/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+@router.post(
+    "/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+@router.post(
+    "/openai/v1/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+async def responses_input_tokens(
+    request: Request,
+    token_counter: _TokenCounter = _token_counter_dep,
+):
+    """
+    Count the input tokens of a Responses API request without calling the model.
+
+    Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+
+    ```bash
+    curl -X POST http://localhost:4000/v1/responses/input_tokens \
+    -H "Content-Type: application/json" \
+    -H "Authorization: Bearer sk-1234" \
+    -d '{
+        "model": "gpt-4o",
+        "input": "Hello, how are you?"
+    }'
+    ```
+
+    Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+    """
+    data: Final = await _read_request_body(request=request)
+    model_name: Final = data.get("model")
+    input_value: Final = data.get("input")
+    if not isinstance(model_name, str) or not model_name:
+        return _missing_responses_param_response("model")
+    if input_value is None:
+        return _missing_responses_param_response("input")
+    if isinstance(input_value, (str, list)) and not input_value:
+        return _responses_invalid_request_response(
+            message="""One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""",
+            param=None,
+            code="missing_required_parameter",
+        )
+
+    try:
+        payload: Final[_TokenCountPayload] = {
+            "model": model_name,
+            "messages": _responses_input_as_token_count_messages(
+                input_value=input_value,
+                instructions=data.get("instructions"),
+            ),
+            "tools": data.get("tools"),
+        }
+        token_request: Final = TokenCountRequest.model_validate(payload)
+    except Exception as e:
+        return _responses_invalid_request_response(
+            message=f"Invalid request for token counting: {e}", param=None, code=None
+        )
+
+    token_response: Final = await token_counter(request=token_request, call_endpoint=True)
+    result: Final[_ResponsesInputTokensResult] = {
+        "object": "response.input_tokens",
+        "input_tokens": token_response.total_tokens,
+    }
+    return result
+
+
 @router.post(
     "/v1/responses/{response_id}/cancel",
     dependencies=[Depends(user_api_key_auth)],
@@ -1218,7 +1373,7 @@ async def _enforce_responses_ws_first_frame_model_auth(
     request: Request,
     model: str,
     user_api_key_dict: UserAPIKeyAuth,
-    llm_router: Any | None,
+    llm_router: "Router | None",
 ) -> None:
     from litellm.proxy.auth.user_api_key_auth import (
         _enforce_key_and_fallback_model_access,
@@ -1262,7 +1417,7 @@ async def _enforce_responses_ws_first_frame_model_auth(
 async def responses_websocket_endpoint(
     websocket: WebSocket,
     model: str | None = fastapi.Query(None, description="The model to use for the responses WebSocket session."),
-    user_api_key_dict=Depends(user_api_key_auth_websocket),
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth_websocket),
 ):
     """
     Responses API WebSocket mode endpoint.
@@ -1307,7 +1462,7 @@ async def responses_websocket_endpoint(
             return
         model, first_message = result
 
-    data: dict[str, Any] = {
+    data: dict[str, object] = {
         "model": model,
         "websocket": websocket,
     }
@@ -1316,7 +1471,7 @@ async def responses_websocket_endpoint(
 
     # Construct a synthetic Request for pre-call processing
     headers_list: Final = list(websocket.scope.get("headers") or [])
-    scope: Final[dict[str, Any]] = {
+    scope: Final[dict[str, object]] = {
         "type": "http",
         "method": "POST",
         "path": "/v1/responses",
diff --git a/litellm/proxy/response_polling/background_streaming.py b/litellm/proxy/response_polling/background_streaming.py
index 020698dabd9..0fd242f2bc1 100644
--- a/litellm/proxy/response_polling/background_streaming.py
+++ b/litellm/proxy/response_polling/background_streaming.py
@@ -10,12 +10,12 @@ https://platform.openai.com/docs/api-reference/responses-streaming
 
 import asyncio
 import json
-from collections.abc import Sequence
-from typing import TYPE_CHECKING, Final, TypedDict, cast
+from collections.abc import Callable, Mapping, Sequence
+from typing import TYPE_CHECKING, Final, TypeAlias
 
 from fastapi import Request, Response
 from fastapi.responses import StreamingResponse
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.proxy.auth.user_api_key_auth import UserAPIKeyAuth
@@ -29,28 +29,64 @@ if TYPE_CHECKING:
     from litellm.router import Router
 
 
-class _StreamContentPart(TypedDict, total=False):
-    text: ReadOnly[str]
+_JsonDict: TypeAlias = dict[str, object]
+_JsonList: TypeAlias = list[object]
 
 
-class _StreamOutputItem(TypedDict, total=False):
+class _OutputItem(TypedDict, total=False):
     id: ReadOnly[str]
-    content: ReadOnly[Sequence[_StreamContentPart | None]]
+    content: ReadOnly[Sequence[object]]
+
+
+class _TerminalResponse(TypedDict, total=False):
+    status: ReadOnly[ResponsesAPIStatus]
+    error: ReadOnly[_JsonDict]
+    usage: ReadOnly[_JsonDict]
+    reasoning: ReadOnly[_JsonDict]
+    tool_choice: ReadOnly[object]
+    tools: ReadOnly[_JsonList]
+    model: ReadOnly[str]
+    instructions: ReadOnly[str]
+    temperature: ReadOnly[float]
+    top_p: ReadOnly[float]
+    max_output_tokens: ReadOnly[int]
+    previous_response_id: ReadOnly[str]
+    text: ReadOnly[_JsonDict]
+    truncation: ReadOnly[str]
+    parallel_tool_calls: ReadOnly[bool]
+    user: ReadOnly[str]
+    store: ReadOnly[bool]
+    incomplete_details: ReadOnly[_JsonDict]
+    output: ReadOnly[Sequence[_OutputItem]]
+
+
+class _StreamEvent(TypedDict, total=False):
+    type: ReadOnly[str]
+    item: ReadOnly[_OutputItem]
+    item_id: ReadOnly[str]
+    content_index: ReadOnly[int]
+    delta: ReadOnly[str]
+    part: ReadOnly[object]
+    response: ReadOnly[_TerminalResponse]
+
+
+class _StreamEventParser:
+    parse: Callable[[str], _StreamEvent] = staticmethod(json.loads)
 
 
 async def background_streaming_task(
     polling_id: str,
-    data,
+    data: dict[str, object],
     polling_handler: ResponsePollingHandler,
     request: Request,
     fastapi_response: Response,
     user_api_key_dict: UserAPIKeyAuth,
-    general_settings,
+    general_settings: dict[str, object],
     llm_router: "Router | None",
     proxy_config: "ProxyConfig",
     proxy_logging_obj: "ProxyLogging",
-    select_data_generator,
-    user_model,
+    select_data_generator: Callable[..., object] | None,
+    user_model: str | None,
     user_temperature: float | None,
     user_request_timeout: float | None,
     user_max_tokens: int | None,
@@ -108,9 +144,8 @@ async def background_streaming_task(
 
         # Process streaming response following OpenAI events format
         # https://platform.openai.com/docs/api-reference/responses-streaming
-        output_items: Final[dict[str, _StreamOutputItem]] = {}  # Track output items by ID
-        # Track accumulated text deltas by (item_id, content_index)
-        accumulated_text: Final[dict[tuple[str, int], str]] = {}
+        output_items: Final = dict[str, _OutputItem]()
+        accumulated_text: Final = dict[tuple[str, int], str]()
 
         # ResponsesAPIResponse fields to extract from response.completed
         usage_data = None
@@ -139,7 +174,7 @@ async def background_streaming_task(
             None  # Will be set by response.completed/failed/incomplete/cancelled
         )
         terminal_error = None
-        _event_to_status: Final = {
+        _event_to_status: Final[Mapping[str, ResponsesAPIStatus]] = {
             "response.completed": "completed",
             "response.failed": "failed",
             "response.incomplete": "incomplete",
@@ -180,7 +215,7 @@ async def background_streaming_task(
                         break
 
                     try:
-                        event = json.loads(chunk_data)
+                        event: _StreamEvent = _StreamEventParser.parse(chunk_data)
                         event_type = event.get("type", "")
 
                         # Process different event types based on OpenAI streaming spec
@@ -199,19 +234,18 @@ async def background_streaming_task(
 
                             if item_id and item_id in output_items:
                                 # Update the output item with new content
-                                current_item = output_items[item_id]
-                                appended_item: _StreamOutputItem = {
-                                    **current_item,
-                                    "content": (*current_item.get("content", ()), content_part),
+                                added_item = output_items[item_id]
+                                output_items[item_id] = {
+                                    **added_item,
+                                    "content": (*added_item.get("content", ()), content_part),
                                 }
-                                output_items[item_id] = appended_item
                                 state_dirty = True
 
                         elif event_type == "response.output_text.delta":
                             # Text delta - accumulate text content
                             # https://platform.openai.com/docs/api-reference/responses-streaming/response-text-delta
                             item_id = event.get("item_id")
-                            content_index: int = event.get("content_index", 0)
+                            content_index = event.get("content_index", 0)
                             delta = event.get("delta", "")
 
                             if item_id and item_id in output_items:
@@ -222,24 +256,13 @@ async def background_streaming_task(
                                 accumulated_text[key] += delta
 
                                 # Update the content in output_items
-                                current_item = output_items[item_id]
-                                content_list: Sequence[_StreamContentPart | None] = current_item.get("content", ())
-                                if content_index < len(content_list):
-                                    # Update existing content part with accumulated text
-                                    content_entry = content_list[content_index]
-                                    if isinstance(content_entry, dict):
-                                        delta_part: _StreamContentPart = {
-                                            **content_entry,
-                                            "text": accumulated_text[key],
-                                        }
-                                        delta_item: _StreamOutputItem = {
-                                            **current_item,
-                                            "content": tuple(
-                                                delta_part if index == content_index else entry
-                                                for index, entry in enumerate(content_list)
-                                            ),
-                                        }
-                                        output_items[item_id] = delta_item
+                                delta_item = output_items[item_id]
+                                if "content" in delta_item:
+                                    content_list = delta_item["content"]
+                                    if content_index < len(content_list):
+                                        content_entry = content_list[content_index]
+                                        if isinstance(content_entry, dict):
+                                            content_entry["text"] = accumulated_text[key]
                                 state_dirty = True
 
                         elif event_type == "response.content_part.done":
@@ -250,17 +273,17 @@ async def background_streaming_task(
 
                             if item_id and item_id in output_items:
                                 # Update with final content from event
-                                current_item = output_items[item_id]
-                                content_list = current_item.get("content", ())
-                                if content_index < len(content_list):
-                                    finalized_item: _StreamOutputItem = {
-                                        **current_item,
-                                        "content": tuple(
-                                            content_part if index == content_index else entry
-                                            for index, entry in enumerate(content_list)
-                                        ),
-                                    }
-                                    output_items[item_id] = finalized_item
+                                done_item = output_items[item_id]
+                                if "content" in done_item:
+                                    content_list = done_item["content"]
+                                    if content_index < len(content_list):
+                                        output_items[item_id] = {
+                                            **done_item,
+                                            "content": tuple(
+                                                content_part if part_index == content_index else existing_part
+                                                for part_index, existing_part in enumerate(content_list)
+                                            ),
+                                        }
                                 state_dirty = True
 
                         elif event_type == "response.output_item.done":
@@ -288,12 +311,9 @@ async def background_streaming_task(
                             # Terminal event - extract all ResponsesAPIResponse fields
                             # https://platform.openai.com/docs/api-reference/responses-streaming
                             response_data = event.get("response", {})
-                            terminal_status = cast(
-                                ResponsesAPIStatus,
-                                response_data.get(
-                                    "status",
-                                    _event_to_status.get(event_type, "completed"),
-                                ),
+                            terminal_status = response_data.get(
+                                "status",
+                                _event_to_status.get(event_type, "completed"),
                             )
 
                             # Extract error for failed and incomplete responses
diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py
index 91a0c68fd58..3d0bd5e61c9 100644
--- a/litellm/proxy/route_llm_request.py
+++ b/litellm/proxy/route_llm_request.py
@@ -50,12 +50,12 @@ def _route_user_config_request(data: dict, route_type: str):
     return ret_val
 
 
-def _is_a2a_agent_model(model_name: Any) -> bool:
+def _is_a2a_agent_model(model_name: object) -> bool:
     """Check if the model name is for an A2A agent (a2a/ prefix)."""
     return isinstance(model_name, str) and model_name.startswith("a2a/")
 
 
-def _raise_if_model_fully_blocked(llm_router: LitellmRouter, model_name: Any, team_id: str | None) -> None:
+def _raise_if_model_fully_blocked(llm_router: LitellmRouter, model_name: object, team_id: str | None) -> None:
     if not isinstance(model_name, str) or not model_name:
         return
     if not isinstance(llm_router, litellm.Router):
diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma
index 60223265211..7604ceadf7a 100644
--- a/litellm/proxy/schema.prisma
+++ b/litellm/proxy/schema.prisma
@@ -1529,14 +1529,16 @@ model LiteLLM_AutoRouterSession {
 model LiteLLM_ShadowEvalJob {
   id                String   @id @default(cuid())
   group_id          String   // legs of one job share this; the API's job id
-  api_key_id        String   // hashed virtual key whose traffic this leg shadows
-  router_name       String   // the auto-router under evaluation, in either direction
+  target_type       String   @default("key") // key | team | user
+  target_id         String   // hashed virtual key, team_id, or user_id whose traffic this leg shadows
+  router_name       String   // first (often only) auto-router under evaluation; router_names is the full set
+  router_names      String[] @default([]) // all routers this job runs as shadow arms; empty on legacy rows, whose set is (router_name)
   direction         String   @default("forward") // forward | reverse
   baseline_model    String?  // reverse only: the fixed model the router is judged against
   judge_model       String
   shadow_percentage Float
   max_turns         Int      // sample-count ceiling: the whole budget on pre-max_budget jobs, the error-loop valve otherwise
-  max_budget        Float?   // per-key USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
+  max_budget        Float?   // per-target USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
   created_at        DateTime @default(now())
   created_by        String?
   ends_at           DateTime
@@ -1544,7 +1546,7 @@ model LiteLLM_ShadowEvalJob {
   stopped_by        String?  // operator who stopped it early; null when it ended on its own
 
   @@index([group_id])
-  @@index([api_key_id])
+  @@index([target_type, target_id])
   @@index([created_at])
 }
 
@@ -1554,6 +1556,7 @@ model LiteLLM_ShadowEvalAttempt {
   job_id       String
   request_id   String   // the judged real request
   outcome      String   // real | shadow | tie | error
+  router_name  String?  // the arm this verdict scores; NULL on legacy rows, meaning the job's own router
   tier         String?  // router's tier for the prompt, when classified
   real_model   String?
   shadow_model String?
diff --git a/litellm/proxy/search_endpoints/search_tool_registry.py b/litellm/proxy/search_endpoints/search_tool_registry.py
index fe4794f3ba1..b25263e4c64 100644
--- a/litellm/proxy/search_endpoints/search_tool_registry.py
+++ b/litellm/proxy/search_endpoints/search_tool_registry.py
@@ -2,8 +2,9 @@
 Search Tool Registry for managing search tool configurations.
 """
 
+from collections.abc import Iterator, Mapping, Sequence
 from datetime import datetime, timezone
-from typing import Final
+from typing import Final, Protocol
 
 from litellm._logging import verbose_proxy_logger
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
@@ -13,6 +14,40 @@ from litellm.repositories.table_repositories import SearchToolsRepository
 from litellm.types.search import SearchTool
 
 
+class SearchToolRecord(Protocol):
+    search_tool_id: str
+    search_tool_name: str
+    created_at: datetime
+    updated_at: datetime
+
+    def __iter__(self) -> Iterator[tuple[str, object]]: ...
+
+
+class SearchToolTableClient(Protocol):
+    async def create(self, data: Mapping[str, object]) -> SearchToolRecord: ...
+
+    async def find_unique(self, where: Mapping[str, object]) -> SearchToolRecord | None: ...
+
+    async def find_many(self, order: Mapping[str, str] | None = None) -> Sequence[SearchToolRecord]: ...
+
+    async def update(self, where: Mapping[str, object], data: Mapping[str, object]) -> SearchToolRecord: ...
+
+    async def delete(self, where: Mapping[str, object]) -> SearchToolRecord: ...
+
+
+class _SearchToolsRepositoryView(Protocol):
+    @property
+    def table(self) -> SearchToolTableClient: ...
+
+
+def _search_tools_table_of(repository: _SearchToolsRepositoryView) -> SearchToolTableClient:
+    return repository.table
+
+
+def _search_tools_table(prisma_client: PrismaClient) -> SearchToolTableClient:
+    return _search_tools_table_of(SearchToolsRepository(prisma_client))
+
+
 class SearchToolRegistry:
     """
     Handles adding, removing, and getting search tools in DB + in memory.
@@ -22,7 +57,7 @@ class SearchToolRegistry:
         pass
 
     @staticmethod
-    def _convert_prisma_to_dict(prisma_obj) -> dict:
+    def _convert_prisma_to_dict(prisma_obj: SearchToolRecord) -> dict:
         """
         Convert Prisma result to dict with datetime objects as ISO format strings.
 
@@ -35,9 +70,9 @@ class SearchToolRegistry:
         result: Final = dict(prisma_obj)
         # Convert datetime objects to ISO format strings
         if "created_at" in result and result["created_at"]:
-            result["created_at"] = result["created_at"].isoformat()
+            result["created_at"] = prisma_obj.created_at.isoformat()
         if "updated_at" in result and result["updated_at"]:
-            result["updated_at"] = result["updated_at"].isoformat()
+            result["updated_at"] = prisma_obj.updated_at.isoformat()
         return result
 
     ###########################################################
@@ -61,7 +96,7 @@ class SearchToolRegistry:
             search_tool_info: Final[str] = safe_dumps(search_tool.get("search_tool_info", {}))
 
             # Create search tool in DB
-            created_search_tool: Final = await SearchToolsRepository(prisma_client).table.create(
+            created_search_tool: Final = await _search_tools_table(prisma_client).create(
                 data={
                     "search_tool_name": search_tool_name,
                     "litellm_params": litellm_params,
@@ -95,7 +130,7 @@ class SearchToolRegistry:
         """
         try:
             # Get search tool before deletion for response
-            existing_tool: Final = await SearchToolsRepository(prisma_client).table.find_unique(
+            existing_tool: Final = await _search_tools_table(prisma_client).find_unique(
                 where={"search_tool_id": search_tool_id}
             )
 
@@ -103,7 +138,7 @@ class SearchToolRegistry:
                 raise Exception(f"Search tool with ID {search_tool_id} not found")
 
             # Delete from DB
-            await SearchToolsRepository(prisma_client).table.delete(where={"search_tool_id": search_tool_id})
+            await _search_tools_table(prisma_client).delete(where={"search_tool_id": search_tool_id})
 
             return {
                 "message": f"Search tool {search_tool_id} deleted successfully",
@@ -131,7 +166,7 @@ class SearchToolRegistry:
             search_tool_info: Final[str] = safe_dumps(search_tool.get("search_tool_info", {}))
 
             # Update in DB
-            updated_search_tool: Final = await SearchToolsRepository(prisma_client).table.update(
+            updated_search_tool: Final = await _search_tools_table(prisma_client).update(
                 where={"search_tool_id": search_tool_id},
                 data={
                     "search_tool_name": search_tool_name,
@@ -163,7 +198,7 @@ class SearchToolRegistry:
         try:
             search_tools_from_db: Final = await call_with_db_reconnect_retry(
                 prisma_client,
-                lambda: SearchToolsRepository(prisma_client).table.find_many(
+                lambda: _search_tools_table(prisma_client).find_many(
                     order={"created_at": "desc"},
                 ),
                 reason="get_all_search_tools_from_db_lookup_failure",
@@ -194,7 +229,7 @@ class SearchToolRegistry:
             Search tool configuration or None if not found
         """
         try:
-            search_tool: Final = await SearchToolsRepository(prisma_client).table.find_unique(
+            search_tool: Final = await _search_tools_table(prisma_client).find_unique(
                 where={"search_tool_id": search_tool_id}
             )
 
@@ -222,7 +257,7 @@ class SearchToolRegistry:
             Search tool configuration or None if not found
         """
         try:
-            search_tool: Final = await SearchToolsRepository(prisma_client).table.find_unique(
+            search_tool: Final = await _search_tools_table(prisma_client).find_unique(
                 where={"search_tool_name": search_tool_name}
             )
 
diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py
index 8b2a5dd9312..91d2ece7a51 100644
--- a/litellm/proxy/spend_tracking/budget_reservation.py
+++ b/litellm/proxy/spend_tracking/budget_reservation.py
@@ -6,7 +6,7 @@ from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from types import MappingProxyType
-from typing import Any, Final, NoReturn, cast
+from typing import Final, NoReturn, SupportsFloat, SupportsIndex, SupportsInt, cast
 
 from fastapi import HTTPException, status
 
@@ -35,6 +35,7 @@ from litellm.proxy.common_utils.user_api_key_cache import (
 from litellm.proxy.utils import PrismaClient, ProxyLogging
 from litellm.router import Router
 from litellm.types.proxy.model_access_group_budget import ModelAccessGroupBudget
+from litellm.types.router import DeploymentTypedDict
 
 
 @dataclass
@@ -119,13 +120,15 @@ async def _apply_over_budget_reservation_policy(
     applied_entries: list[dict[str, float | str]],
     reservation_cost: float,
     current_spend: float,
+    fail_closed_budget_enforcement: bool = False,
 ) -> float:
     """
     Decide what to do when a counter is over budget, and return the reservation
     cost to carry into the next counter. Three outcomes: an over-budget key that
     opted into throttling releases its own reservation (the rate limiter slows
     it) and keeps the cost; a partially-remaining budget resizes the reservation
-    down to what is left; anything else hard-blocks by raising.
+    down to what is left, unless strict enforcement is on, because the known
+    estimate already does not fit; anything else hard-blocks by raising.
     """
     if _key_reservation_should_release_for_throttle(counter.counter_key, valid_token):
         await _release_applied_entries_best_effort(entries=[entry], default_reserved_cost=reservation_cost)
@@ -133,21 +136,36 @@ async def _apply_over_budget_reservation_policy(
         return reservation_cost
 
     remaining_before_reservation: Final = counter.max_budget - (current_spend - reservation_cost)
-    if remaining_before_reservation > 1e-12:
-        await _resize_applied_reservation(
-            entries=applied_entries,
-            current_reserved_cost=reservation_cost,
-            new_reserved_cost=remaining_before_reservation,
+    if remaining_before_reservation <= 1e-12:
+        _raise_counter_budget_exceeded(counter=counter, current_cost=current_spend)
+    if fail_closed_budget_enforcement and current_spend - counter.max_budget > 1e-12:
+        _raise_counter_budget_exceeded(
+            counter=counter,
+            current_cost=current_spend - reservation_cost,
+            estimated_cost=reservation_cost,
         )
-        return remaining_before_reservation
+    await _resize_applied_reservation(
+        entries=applied_entries,
+        current_reserved_cost=reservation_cost,
+        new_reserved_cost=remaining_before_reservation,
+    )
+    return remaining_before_reservation
 
+
+def _raise_counter_budget_exceeded(
+    counter: _BudgetCounter,
+    current_cost: float,
+    estimated_cost: float | None = None,
+) -> NoReturn:
+    estimate_detail: Final = "" if estimated_cost is None else f"Estimated request cost: {estimated_cost}, "
     raise litellm.BudgetExceededError(
-        current_cost=current_spend,
+        current_cost=current_cost,
         max_budget=counter.max_budget,
         message=(
             "Budget has been exceeded! "
             f"{counter.entity_type}={counter.entity_id} "
-            f"Current cost: {current_spend}, "
+            f"Current cost: {current_cost}, "
+            f"{estimate_detail}"
             f"Max budget: {counter.max_budget}"
         ),
         entity_type=_COUNTER_ENTITY_TYPES.get(counter.entity_type),
@@ -172,7 +190,14 @@ async def reserve_budget_for_request(
 ) -> dict | None:
     if valid_token is None or not RouteChecks.is_llm_api_route(route=route):
         return None
-    if route in {"/models", "/v1/models", "/utils/token_counter"}:
+    if route in {
+        "/models",
+        "/v1/models",
+        "/utils/token_counter",
+        "/responses/input_tokens",
+        "/v1/responses/input_tokens",
+        "/openai/v1/responses/input_tokens",
+    }:
         return None
     if get_model_from_request(request_body, route, llm_router=llm_router) is None:
         return None
@@ -250,6 +275,7 @@ async def reserve_budget_for_request(
                     applied_entries=applied_entries,
                     reservation_cost=reservation_cost,
                     current_spend=current_spend,
+                    fail_closed_budget_enforcement=fail_closed_budget_enforcement,
                 )
                 continue
     except Exception:
@@ -690,7 +716,7 @@ def _get_budget_limit_counters(
     for window in budget_limits:
         window_dict = _coerce_window(window)
         budget_duration = window_dict.get("budget_duration")
-        max_budget = window_dict.get("max_budget")
+        max_budget = _to_float(window_dict.get("max_budget"))
         if not budget_duration or max_budget is None or max_budget <= 0:
             continue
         window_start = get_budget_window_start(window_dict)
@@ -717,18 +743,20 @@ def _get_budget_limit_counters(
     return counters
 
 
-def _coerce_window(window: Any) -> dict:
-    if isinstance(window, dict):
+def _coerce_window(window: object) -> Mapping[str, object]:
+    if isinstance(window, Mapping):
         return window
     if isinstance(window, str):
         try:
-            parsed: Final = json.loads(window)
-            return parsed if isinstance(parsed, dict) else {}
+            parsed: Final[object] = json.loads(window)
         except Exception:
             return {}
-    if hasattr(window, "model_dump"):
-        return window.model_dump()
-    return {}
+        return parsed if isinstance(parsed, Mapping) else {}
+    model_dump: Final = getattr(window, "model_dump", None)
+    if not callable(model_dump):
+        return {}
+    dumped: Final[object] = model_dump()
+    return dumped if isinstance(dumped, Mapping) else {}
 
 
 async def _reserve_counter(
@@ -946,7 +974,7 @@ def _get_entry_reserved_cost(entry: dict, default_reserved_cost: float) -> float
         return default_reserved_cost
 
 
-def get_budget_window_start(window: Any) -> datetime | None:
+def get_budget_window_start(window: object) -> datetime | None:
     window_dict: Final = _coerce_window(window)
     budget_duration: Final = window_dict.get("budget_duration")
     if budget_duration is None:
@@ -964,7 +992,7 @@ def get_budget_window_start(window: Any) -> datetime | None:
     return reset_at - timedelta(seconds=duration_seconds)
 
 
-def _coerce_datetime(value: Any) -> datetime | None:
+def _coerce_datetime(value: object) -> datetime | None:
     if value is None:
         return None
     if isinstance(value, datetime):
@@ -1238,11 +1266,11 @@ def _get_model_cost_infos(
 
 
 def _deployment_tiered_pricing_table(
-    deployment: dict[str, Any],
+    deployment: DeploymentTypedDict,
     llm_router: Router,
-) -> list[dict] | None:
-    model_id: Final = deployment.get("model_info", {}).get("id")
-    backend_model: Final = deployment.get("litellm_params", {}).get("model")
+) -> Sequence[Mapping[str, object]] | None:
+    model_id: Final = _get_value(_get_value(deployment, "model_info"), "id")
+    backend_model: Final = _get_value(_get_value(deployment, "litellm_params"), "model")
     if not isinstance(model_id, str) or not isinstance(backend_model, str):
         return None
     deployment_model_info: Final = llm_router.get_deployment_model_info(model_id=model_id, model_name=backend_model)
@@ -1407,7 +1435,7 @@ def _estimate_output_tokens(
     return min(requested, model_ceiling)
 
 
-def _count_text_tokens(model: str, text: Any) -> int:
+def _count_text_tokens(model: str, text: object) -> int:
     if text is None:
         return 0
 
@@ -1447,8 +1475,8 @@ def _is_input_only_route(route: str) -> bool:
     )
 
 
-def _to_float(value: Any) -> float | None:
-    if value is None:
+def _to_float(value: object) -> float | None:
+    if not isinstance(value, (SupportsFloat, SupportsIndex, str, bytes, bytearray)):
         return None
     try:
         return float(value)
@@ -1456,8 +1484,8 @@ def _to_float(value: Any) -> float | None:
         return None
 
 
-def _to_int(value: Any) -> int | None:
-    if value is None:
+def _to_int(value: object) -> int | None:
+    if not isinstance(value, (SupportsInt, SupportsIndex, str, bytes, bytearray)):
         return None
     try:
         return int(value)
@@ -1465,7 +1493,7 @@ def _to_int(value: Any) -> int | None:
         return None
 
 
-def _get_value(obj: Any, key: str) -> Any:
-    if isinstance(obj, dict):
+def _get_value(obj: object, key: str) -> object:
+    if isinstance(obj, Mapping):
         return obj.get(key)
     return getattr(obj, key, None)
diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py
index 41c65b1d5c5..c48750cea72 100644
--- a/litellm/proxy/spend_tracking/spend_management_endpoints.py
+++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py
@@ -1204,7 +1204,10 @@ async def get_global_spend_report(
     ),
     api_key: str | None = fastapi.Query(
         default=None,
-        description="View spend for a specific api_key. Example api_key='sk-1234",
+        description=(
+            "View spend for a specific api_key. Pass the key's sha256 hash so the raw key stays "
+            "out of URLs and access logs. Example api_key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa'"
+        ),
     ),
     internal_user_id: str | None = fastapi.Query(
         default=None,
@@ -1685,7 +1688,11 @@ async def get_key_spend_report(
     api_key: Annotated[
         str | None,
         fastapi.Query(
-            description="View spend for a specific api_key. Proxy admin only; other callers are scoped to their own key."
+            description=(
+                "View spend for a specific api_key. Proxy admin only; other callers are scoped to their "
+                "own key. Pass the key's sha256 hash so the raw key stays out of URLs and access logs. "
+                "Example api_key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa'"
+            )
         ),
     ] = None,
 ) -> Sequence[Mapping[str, object]]:
@@ -2945,7 +2952,7 @@ async def view_spend_logs(
 
     Example Request for specific api_key
     ```
-    curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=sk-test-example-key-123" \
+    curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa" \
 -H "Authorization: Bearer sk-1234"
     ```
 
diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py
index 43709e4e6ff..7442d71bd96 100644
--- a/litellm/proxy/spend_tracking/spend_tracking_utils.py
+++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py
@@ -1,10 +1,10 @@
 import os
 import re
 import secrets
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from datetime import datetime, timezone
 from datetime import datetime as dt
-from typing import Any, Final, Literal, cast
+from typing import Final, Literal, Protocol, cast, runtime_checkable
 
 from pydantic import BaseModel
 
@@ -30,7 +30,7 @@ from litellm.litellm_core_utils.litellm_logging import (
     request_model_access_groups_from_litellm_params,
 )
 from litellm.litellm_core_utils.safe_json_dumps import safe_dumps, strip_null_bytes
-from litellm.proxy._types import SpendLogsMetadata, SpendLogsPayload
+from litellm.proxy._types import SpendLogsMetadata, SpendLogsPayload, SpendLogsRouterMetadata
 from litellm.proxy.spend_tracking.spend_log_error_logger import spend_log_error
 from litellm.proxy.utils import PrismaClient, hash_token
 from litellm.types.utils import (
@@ -93,6 +93,24 @@ def _redact_logged_api_key(value: str | None, *, already_redacted: bool = False)
     return hash_token(stripped)
 
 
+def _get_router_metadata_for_spend_log(
+    metadata: Mapping[str, object] | None,
+    requested_model: str | None,
+    selected_model: str | None,
+    selected_provider: str | None,
+    router_correlation_id: str | None,
+) -> SpendLogsRouterMetadata | None:
+    model_info: Final = metadata.get("model_info") if metadata is not None else None
+    if not isinstance(model_info, Mapping) or model_info.get("internal_router_model") is not True:
+        return None
+    return SpendLogsRouterMetadata(
+        requested_model=requested_model or None,
+        selected_model=selected_model or None,
+        selected_provider=selected_provider or None,
+        router_correlation_id=router_correlation_id,
+    )
+
+
 def _get_spend_logs_metadata(
     metadata: dict | None,
     applied_guardrails: list[str] | None = None,
@@ -109,6 +127,7 @@ def _get_spend_logs_metadata(
     cost_breakdown: CostBreakdown | None = None,
     litellm_call_id: str | None = None,
     autorouter_savings: float | None = None,
+    router_metadata: SpendLogsRouterMetadata | None = None,
 ) -> SpendLogsMetadata:
     if metadata is None:
         return SpendLogsMetadata(
@@ -148,13 +167,17 @@ def _get_spend_logs_metadata(
             autorouter_savings=autorouter_savings,
             litellm_gateway_injected_cache=None,
             litellm_call_id=litellm_call_id,
+            router_metadata=router_metadata,
         )
     verbose_proxy_logger.debug(
         "getting payload for SpendLogs, available keys in metadata: " + str(list(metadata.keys()))
     )
 
     # Filter the metadata dictionary to include only the specified keys
-    clean_metadata: Final = SpendLogsMetadata(**{key: metadata.get(key) for key in SpendLogsMetadata.__annotations__})
+    clean_metadata: Final = SpendLogsMetadata(
+        **{key: metadata.get(key) for key in SpendLogsMetadata.__annotations__ if key != "router_metadata"},
+        router_metadata=router_metadata,
+    )
     _raw_key: Final = clean_metadata.get("user_api_key")
     _trusted_hash: Final = metadata.get("user_api_key_hash")
     _already_redacted: Final = (
@@ -199,7 +222,28 @@ def get_spend_logs_id(call_type: str, response_obj: dict, kwargs: dict) -> str |
     return resolved_id
 
 
-def _extract_usage_for_ocr_call(response_obj: Any, response_obj_dict: dict) -> dict:
+_MISSING_ATTRIBUTE: Final = object()
+
+
+def _attribute_or_missing(source: object, name: str) -> object:
+    return getattr(source, name, _MISSING_ATTRIBUTE)
+
+
+@runtime_checkable
+class _ModelDumpable(Protocol):
+    def model_dump(self) -> object: ...
+
+
+def _dumped_usage_info(usage_info: object) -> object:
+    if isinstance(usage_info, _ModelDumpable):
+        return usage_info.model_dump()
+    instance_dict: Final = _attribute_or_missing(usage_info, "__dict__")
+    if instance_dict is not _MISSING_ATTRIBUTE:
+        return instance_dict
+    return usage_info
+
+
+def _extract_usage_for_ocr_call(response_obj: object, response_obj_dict: dict) -> dict:
     """
     Extract usage information for OCR/AOCR calls.
 
@@ -220,12 +264,10 @@ def _extract_usage_for_ocr_call(response_obj: Any, response_obj_dict: dict) -> d
         usage_info = response_obj_dict.get("usage_info")
 
     # Try to extract usage_info from object attributes if not found in dict
-    if not usage_info and hasattr(response_obj, "usage_info"):
-        usage_info = response_obj.usage_info
-        if hasattr(usage_info, "model_dump"):
-            usage_info = usage_info.model_dump()
-        elif hasattr(usage_info, "__dict__"):
-            usage_info = vars(usage_info)
+    if not usage_info:
+        attribute_usage_info: Final = _attribute_or_missing(response_obj, "usage_info")
+        if attribute_usage_info is not _MISSING_ATTRIBUTE:
+            usage_info = _dumped_usage_info(attribute_usage_info)
 
     # For OCR, we track pages instead of tokens
     if usage_info is not None:
@@ -375,6 +417,20 @@ def get_logging_payload(kwargs, response_obj, start_time, end_time) -> SpendLogs
         hidden_params: Final = standard_logging_payload.get("hidden_params", {})
         litellm_overhead_time_ms = hidden_params.get("litellm_overhead_time_ms")
 
+    custom_llm_provider: Final = (
+        kwargs.get("custom_llm_provider")
+        or _sl_attribution_fallback(standard_logging_payload, "custom_llm_provider")
+        or None
+    )
+    raw_model: Final = cast(str, kwargs.get("model") or "")
+    model_name: Final = (
+        standard_logging_payload.get("model") if standard_logging_payload is not None else None
+    ) or reconstruct_model_name(raw_model, custom_llm_provider, metadata or {})
+    litellm_call_id: Final = cast(
+        str | None,
+        kwargs.get("litellm_call_id") or litellm_params.get("litellm_call_id"),
+    )
+
     # clean up litellm metadata
     clean_metadata = _get_spend_logs_metadata(
         metadata,
@@ -433,9 +489,13 @@ def get_logging_payload(kwargs, response_obj, start_time, end_time) -> SpendLogs
         autorouter_savings=(
             standard_logging_payload.get("autorouter_savings", None) if standard_logging_payload is not None else None
         ),
-        litellm_call_id=cast(
-            str | None,
-            kwargs.get("litellm_call_id") or litellm_params.get("litellm_call_id"),
+        litellm_call_id=litellm_call_id,
+        router_metadata=_get_router_metadata_for_spend_log(
+            metadata=metadata,
+            requested_model=_model_group,
+            selected_model=model_name,
+            selected_provider=custom_llm_provider,
+            router_correlation_id=litellm_call_id,
         ),
     )
 
@@ -480,15 +540,6 @@ def get_logging_payload(kwargs, response_obj, start_time, end_time) -> SpendLogs
 
     # Extract agent_id for A2A requests (set directly on model_call_details)
     agent_id: Final[str | None] = kwargs.get("agent_id") or metadata.get("agent_id")
-    custom_llm_provider: Final = (
-        kwargs.get("custom_llm_provider")
-        or _sl_attribution_fallback(standard_logging_payload, "custom_llm_provider")
-        or None
-    )
-    raw_model: Final = cast(str, kwargs.get("model") or "")
-    model_name: Final = (
-        standard_logging_payload.get("model") if standard_logging_payload is not None else None
-    ) or reconstruct_model_name(raw_model, custom_llm_provider, metadata or {})
 
     try:
         payload: Final[SpendLogsPayload] = SpendLogsPayload(
@@ -588,6 +639,14 @@ def _ensure_datetime_utc(timestamp: datetime) -> datetime:
     return timestamp
 
 
+async def _query_raw_rows(
+    prisma_client: PrismaClient,
+    sql_query: str,
+    *args: object,
+) -> Sequence[Mapping[str, object]] | None:
+    return await prisma_client.db.query_raw(sql_query, *args)
+
+
 async def get_spend_by_team(
     start_date: dt,
     end_date: dt,
@@ -649,7 +708,7 @@ async def get_spend_by_team(
             group_by_day;
     """
 
-    db_response: Final = await prisma_client.db.query_raw(sql_query, start_date, end_date, team_id)
+    db_response: Final = await _query_raw_rows(prisma_client, sql_query, start_date, end_date, team_id)
     if db_response is None:
         return []
 
@@ -724,7 +783,7 @@ async def get_spend_by_team_and_customer(
             group_by_day;
     """
 
-    db_response: Final = await prisma_client.db.query_raw(sql_query, start_date, end_date, team_id, customer_id)
+    db_response: Final = await _query_raw_rows(prisma_client, sql_query, start_date, end_date, team_id, customer_id)
     if db_response is None:
         return []
 
@@ -779,7 +838,7 @@ def _sanitize_request_body_for_spend_logs_payload(
         return {}
     visited.add(obj_id)
 
-    def _sanitize_value(value: Any) -> Any:
+    def _sanitize_value(value: object) -> object:
         if isinstance(value, dict):
             return _sanitize_request_body_for_spend_logs_payload(value, visited, max_string_length_prompt_in_db)
         elif isinstance(value, list):
@@ -1074,7 +1133,7 @@ def _sanitize_error_information_for_spend_logs(
     return cast(StandardLoggingPayloadErrorInformation, sanitized)
 
 
-def _convert_to_json_serializable_dict(obj: Any, visited: set | None = None, max_depth: int = 20) -> Any:
+def _convert_to_json_serializable_dict(obj: object, visited: set[int] | None = None, max_depth: int = 20) -> object:
     """
     Convert object to JSON-serializable dict, handling Pydantic models safely.
 
@@ -1128,6 +1187,13 @@ def _convert_to_json_serializable_dict(obj: Any, visited: set | None = None, max
             visited.remove(obj_id)
 
 
+def _convert_mapping_to_json_serializable(obj: Mapping[str, object]) -> dict[str, object]:
+    converted: Final = _convert_to_json_serializable_dict(obj)
+    if isinstance(converted, dict):
+        return converted
+    return dict(obj)
+
+
 def _get_proxy_server_request_for_spend_logs_payload(
     metadata: dict,
     litellm_params: dict,
@@ -1164,7 +1230,7 @@ def _get_proxy_server_request_for_spend_logs_payload(
 
                 # If redaction is enabled, convert to serializable dict before redacting
                 if should_redact_message_logging(model_call_details=model_call_details):
-                    _request_body = _convert_to_json_serializable_dict(_request_body)
+                    _request_body = _convert_mapping_to_json_serializable(_request_body)
                     perform_redaction(model_call_details=_request_body, result=None)
 
             _request_body = _sanitize_request_body_for_spend_logs_payload(_request_body)
@@ -1209,7 +1275,7 @@ def _get_response_for_spend_logs_payload(
     if payload is None:
         return "{}"
     if _should_store_prompts_and_responses_in_spend_logs():
-        response_obj: Any = payload.get("response")
+        response_obj: object = payload.get("response")
         if response_obj is None:
             return "{}"
 
diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py
index a1eb7ed06eb..c12d071dd36 100644
--- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py
+++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py
@@ -3,10 +3,11 @@ import asyncio
 import json
 import os
 from collections import Counter
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import (
-    Any,
     Final,
+    NamedTuple,
     Protocol,
     cast,  # noqa: TID251  # prisma types Json columns as fields.Json but de-serializes them to plain python on read
 )
@@ -15,10 +16,12 @@ from urllib.parse import urlparse
 from fastapi import APIRouter, Body, Depends, File, HTTPException, UploadFile
 from pydantic import ConfigDict, JsonValue, ValidationError, create_model
 from pydantic.fields import FieldInfo
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.litellm_core_utils.sensitive_data_masker import mask_sensitive_keys
+from litellm.proxy._experimental.mcp_server.tool_search import MCP_TOOL_SEARCH_SETTINGS_KEY
 from litellm.proxy._types import *
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 from litellm.proxy.config_resolvers.sso import (
@@ -36,6 +39,7 @@ from litellm.repositories.table_repositories import (
     UISettingsRepository,
 )
 from litellm.repositories.team_repository import TeamRepository
+from litellm.types.mcp import MCPToolSearchSettings
 from litellm.types.proxy.management_endpoints.ui_sso import (
     DefaultTeamSSOParams,
     SSOConfig,
@@ -44,6 +48,31 @@ from litellm.types.proxy.management_endpoints.ui_sso import (
 router: Final = APIRouter()
 
 
+JsonSchemaItems: Final = TypedDict(
+    "JsonSchemaItems",
+    {"$ref": ReadOnly[str], "enum": ReadOnly[Sequence[JsonValue]]},
+    total=False,
+)
+
+
+class JsonSchemaNode(TypedDict, total=False):
+    type: ReadOnly[str]
+    description: ReadOnly[str]
+    enum: ReadOnly[Sequence[JsonValue]]
+    anyOf: ReadOnly[Sequence["JsonSchemaNode"]]
+    items: ReadOnly["JsonSchemaItems"]
+    properties: ReadOnly[Mapping[str, "JsonSchemaNode"]]
+
+
+_EMPTY_SCHEMA_DEFS: Final[Mapping[str, "JsonSchemaNode"]] = MappingProxyType({})
+
+
+class JsonSchemaPropertyEntry(TypedDict):
+    description: ReadOnly[str]
+    type: ReadOnly[str]
+    items: NotRequired[ReadOnly["JsonSchemaItems"]]
+
+
 class _SsoSettingsMappingRow(Protocol):
     @property
     def sso_settings(self) -> Mapping[str, object] | None: ...
@@ -157,10 +186,10 @@ class UIThemeConfig(BaseModel):
 class SettingsResponse(BaseModel):
     """Base response model for settings with values and schema information"""
 
-    values: dict[str, Any]
+    values: dict[str, object]
     """The current configuration values"""
 
-    field_schema: dict[str, Any]
+    field_schema: dict[str, object]
     """Schema information including descriptions and property types for UI display"""
 
 
@@ -421,6 +450,10 @@ class MCPSemanticFilterSettingsResponse(SettingsResponse):
     """Response model for MCP semantic filter settings"""
 
 
+class MCPToolSearchSettingsResponse(SettingsResponse):
+    """Response model for native MCP tool search settings"""
+
+
 @router.get(
     "/get/allowed_ips",
     tags=["Budget & Spend Tracking"],
@@ -548,6 +581,62 @@ async def delete_allowed_ip(
     return {"message": f"IP {ip_address.ip} deleted successfully", "status": "success"}
 
 
+def _resolve_non_null_variant(field_info: JsonSchemaNode) -> JsonSchemaNode:
+    """Pydantic v2 renders Optional fields as ``anyOf: [actual_type, null]``."""
+    if "anyOf" not in field_info:
+        return field_info
+    return next((variant for variant in field_info["anyOf"] if variant.get("type") != "null"), field_info)
+
+
+def _schema_items_entry(resolved: JsonSchemaNode, defs: Mapping[str, JsonSchemaNode]) -> "JsonSchemaItems | None":
+    """Items info (including enum values) for array fields, so the UI can render a multi-select dropdown."""
+    if "items" not in resolved:
+        return None
+    items: Final = resolved["items"]
+    if "$ref" not in items:
+        return items
+    ref_def: Final = defs.get(items["$ref"].split("/")[-1])
+    if ref_def is None or "enum" not in ref_def:
+        return None
+    enum_items: Final[JsonSchemaItems] = {"enum": ref_def["enum"]}
+    return enum_items
+
+
+def _schema_property_entry(field_info: JsonSchemaNode, defs: Mapping[str, JsonSchemaNode]) -> JsonSchemaPropertyEntry:
+    resolved: Final = _resolve_non_null_variant(field_info)
+    items_entry: Final = _schema_items_entry(resolved, defs)
+    description: Final = field_info.get("description", "")
+    type_name: Final = resolved.get("type", "string")
+    if items_entry is None:
+        entry: Final[JsonSchemaPropertyEntry] = {"description": description, "type": type_name}
+        return entry
+    entry_with_items: Final[JsonSchemaPropertyEntry] = {
+        "description": description,
+        "type": type_name,
+        "items": items_entry,
+    }
+    return entry_with_items
+
+
+class _RootSchema(NamedTuple):
+    description: str
+    properties: Mapping[str, JsonSchemaNode]
+    nested_defs: Mapping[str, JsonSchemaNode]
+    defs: Mapping[str, JsonSchemaNode]
+
+
+def _root_schema(settings_class: type[BaseModel]) -> _RootSchema:
+    from pydantic import TypeAdapter
+
+    raw_schema: Final = TypeAdapter(settings_class).json_schema(by_alias=True)
+    return _RootSchema(
+        description=raw_schema.get("description", ""),
+        properties=raw_schema["properties"],
+        nested_defs=raw_schema.get("definitions", _EMPTY_SCHEMA_DEFS),
+        defs=raw_schema["$defs"] if "$defs" in raw_schema else raw_schema.get("definitions", _EMPTY_SCHEMA_DEFS),
+    )
+
+
 async def _get_settings_with_schema(
     settings_key: str,
     settings_class: type[BaseModel],
@@ -561,69 +650,43 @@ async def _get_settings_with_schema(
         settings_class: The Pydantic class to use for schema
         config: The config dictionary
     """
-    from pydantic import TypeAdapter
-
     litellm_settings: Final = config.get("litellm_settings", {}) or {}
     settings_data: Final = litellm_settings.get(settings_key, {}) or {}
 
     # Create the settings object
     settings: Final = settings_class(**(settings_data))
     # Get the schema
-    schema: Final = TypeAdapter(settings_class).json_schema(by_alias=True)
+    root_schema: Final = _root_schema(settings_class)
 
     # Convert to dict for response
     settings_dict: Final = settings.model_dump()
 
     # Add descriptions to the response
-    result: Final = {
-        "values": settings_dict,
-        "field_schema": {
-            "description": schema.get("description", ""),
-            "properties": {},
-        },
+    schema_properties_out: Final[Mapping[str, JsonSchemaPropertyEntry]] = {
+        field_name: _schema_property_entry(field_info, root_schema.defs)
+        for field_name, field_info in root_schema.properties.items()
     }
 
-    # Add property descriptions
-    defs: Final = schema.get("$defs", schema.get("definitions", {}))
-    for field_name, field_info in schema["properties"].items():
-        # For Optional fields, Pydantic v2 uses anyOf with [actual_type, null].
-        # Resolve the non-null variant to get the real type and items.
-        resolved = field_info
-        if "anyOf" in field_info:
-            for variant in field_info["anyOf"]:
-                if variant.get("type") != "null":
-                    resolved = variant
-                    break
-
-        prop_entry: dict = {
-            "description": field_info.get("description", ""),
-            "type": resolved.get("type", "string"),
-        }
-        # Pass through items info (including enum values) for array fields
-        # so the UI can render a multi-select dropdown
-        if "items" in resolved:
-            items = resolved["items"]
-            # Resolve $ref to enum definitions if needed
-            if "$ref" in items:
-                ref_name = items["$ref"].split("/")[-1]
-                ref_def = defs.get(ref_name, {})
-                if "enum" in ref_def:
-                    prop_entry["items"] = {"enum": ref_def["enum"]}
-            else:
-                prop_entry["items"] = items
-        result["field_schema"]["properties"][field_name] = prop_entry
-
     # Add nested object descriptions
-    for def_name, def_schema in schema.get("definitions", {}).items():
-        result["field_schema"][def_name] = {
+    nested_defs_out: Final[Mapping[str, Mapping[str, object]]] = {
+        def_name: {
             "description": def_schema.get("description", ""),
             "properties": {
                 prop_name: {"description": prop_info.get("description", "")}
                 for prop_name, prop_info in def_schema.get("properties", {}).items()
             },
         }
+        for def_name, def_schema in root_schema.nested_defs.items()
+    }
 
-    return result
+    return {
+        "values": settings_dict,
+        "field_schema": {
+            "description": root_schema.description,
+            "properties": schema_properties_out,
+            **nested_defs_out,
+        },
+    }
 
 
 @router.get(
@@ -778,7 +841,7 @@ async def update_default_team_member_budget(teams: list[NewUserRequestTeam], use
 
 
 async def _update_litellm_setting(
-    settings: DefaultInternalUserParams | DefaultTeamSSOParams | MCPSemanticFilterSettings,
+    settings: DefaultInternalUserParams | DefaultTeamSSOParams | MCPSemanticFilterSettings | MCPToolSearchSettings,
     settings_key: str,
     success_message: str,
     user_api_key_dict: UserAPIKeyAuth,
@@ -804,7 +867,7 @@ async def _update_litellm_setting(
             detail={"error": "Set `'STORE_MODEL_IN_DB='True'` in your env to enable this feature."},
         )
 
-    in_memory_var: Final = settings.model_dump(exclude_none=True)
+    in_memory_var: Final = settings.model_dump(mode="json", exclude_none=True)
 
     # Load existing config first, then set in-memory value after,
     # because get_config() may overwrite litellm.<key> with stale DB values
@@ -930,32 +993,29 @@ async def get_sso_settings():
     resolved: Final = resolve_sso_config(sso_db_settings, os.environ)
 
     # Get the schema for UI display
-    from pydantic import TypeAdapter
-
-    schema: Final = TypeAdapter(SSOConfig).json_schema(by_alias=True)
+    root_schema: Final = _root_schema(SSOConfig)
 
     # Convert to dict for response, masking OAuth client secrets so plaintext
     # is never sent to the UI.
     sso_dict: Final = mask_sensitive_keys(resolved.config.model_dump(), set(SSO_SECRET_FIELDS))
 
     # Add descriptions to the response
-    result: Final = {
-        "values": sso_dict,
-        "provenance": resolved.provenance,
-        "field_schema": {
-            "description": schema.get("description", ""),
-            "properties": {},
-        },
-    }
-
-    # Add property descriptions
-    for field_name, field_info in schema["properties"].items():
-        result["field_schema"]["properties"][field_name] = {
+    schema_properties_out: Final[Mapping[str, Mapping[str, str]]] = {
+        field_name: {
             "description": field_info.get("description", ""),
             "type": field_info.get("type", "string"),
         }
+        for field_name, field_info in root_schema.properties.items()
+    }
 
-    return result
+    return {
+        "values": sso_dict,
+        "provenance": resolved.provenance,
+        "field_schema": {
+            "description": root_schema.description,
+            "properties": schema_properties_out,
+        },
+    }
 
 
 @router.patch(
@@ -1305,11 +1365,64 @@ async def update_mcp_semantic_filter_settings(
     return result
 
 
+@router.get(
+    "/get/mcp_tool_search_settings",
+    tags=["Settings"],  # mutable-ok: FastAPI's route decorator only accepts a list
+    dependencies=[Depends(user_api_key_auth)],  # mutable-ok: FastAPI's route decorator only accepts a list
+    response_model=MCPToolSearchSettingsResponse,
+)
+async def get_mcp_tool_search_settings(
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+) -> Mapping[str, object]:
+    """
+    Get the `litellm_settings.mcp_tool_search` configuration used by the native `mcp_tool_search` virtual tool.
+    """
+    from litellm.proxy.proxy_server import prisma_client, proxy_config
+
+    if prisma_client is None:
+        raise HTTPException(status_code=500, detail="Database not connected. Please connect a database.")
+
+    config: Final = await proxy_config.get_config()
+
+    return await _get_settings_with_schema(
+        settings_key=MCP_TOOL_SEARCH_SETTINGS_KEY,
+        settings_class=MCPToolSearchSettings,
+        config=config,
+    )
+
+
+@router.patch(
+    "/update/mcp_tool_search_settings",
+    tags=["Settings"],  # mutable-ok: FastAPI's route decorator only accepts a list
+    dependencies=[Depends(user_api_key_auth)],  # mutable-ok: FastAPI's route decorator only accepts a list
+)
+async def update_mcp_tool_search_settings(
+    settings: MCPToolSearchSettings,
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+) -> Mapping[str, object]:
+    """
+    Update `litellm_settings.mcp_tool_search` in the database.
+    Settings will be picked up by all pods within approximately 10 seconds via background polling.
+    """
+    if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN:
+        raise HTTPException(
+            status_code=403,
+            detail="Only proxy admins can update MCP tool search settings.",
+        )
+
+    return await _update_litellm_setting(
+        settings=settings,
+        settings_key=MCP_TOOL_SEARCH_SETTINGS_KEY,
+        success_message="MCP tool search settings updated successfully. Changes will be applied across all pods within 10 seconds.",
+        user_api_key_dict=user_api_key_dict,
+    )
+
+
 UI_SETTINGS_CACHE_KEY: Final = "ui_settings:settings_dict"
 UI_SETTINGS_CACHE_TTL: Final = 600  # 10 minutes
 
 
-async def get_ui_settings_cached() -> dict[str, Any]:
+async def get_ui_settings_cached() -> dict[str, JsonValue]:
     """
     Return the persisted UI settings dict, using DualCache for reads.
 
@@ -1540,7 +1653,10 @@ async def update_ui_settings(
     tags=["UI Theme Settings"],
     dependencies=[Depends(user_api_key_auth)],
 )
-async def upload_logo(file: UploadFile = File(...)):
+async def upload_logo(
+    file: UploadFile = File(...),
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
+):
     """
     Upload a custom logo for the admin UI.
     Accepts image files (PNG, JPG, JPEG, SVG) and stores them for use in the UI.
@@ -1548,6 +1664,12 @@ async def upload_logo(file: UploadFile = File(...)):
     import os
     from pathlib import Path
 
+    if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN:
+        raise HTTPException(
+            status_code=403,
+            detail="Only proxy admins can upload a UI logo.",
+        )
+
     # Validate file type
     allowed_extensions: Final = {".png", ".jpg", ".jpeg", ".svg"}
     file_extension: Final = Path(file.filename or "").suffix.lower()
@@ -1558,9 +1680,11 @@ async def upload_logo(file: UploadFile = File(...)):
             detail=f"Invalid file type. Allowed types: {', '.join(allowed_extensions)}",
         )
 
-    # Validate file size (max 5MB)
-    file_content: Final = await file.read()
-    if len(file_content) > 5 * 1024 * 1024:  # 5MB
+    # Read bounded to one byte past the limit, so an oversized upload is never
+    # fully buffered in memory before being rejected.
+    max_logo_size_bytes: Final = 5 * 1024 * 1024
+    file_content: Final = await file.read(max_logo_size_bytes + 1)
+    if len(file_content) > max_logo_size_bytes:
         raise HTTPException(status_code=400, detail="File size too large. Maximum size is 5MB.")
 
     # Create uploads directory if it doesn't exist
diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py
index cf56fc0b1dd..cab2bd6d9db 100644
--- a/litellm/proxy/utils.py
+++ b/litellm/proxy/utils.py
@@ -645,7 +645,7 @@ class ProxyLogging:
         self.max_parallel_request_limiter = _PROXY_MaxParallelRequestsHandler(self.internal_usage_cache)
         self.max_budget_limiter = _PROXY_MaxBudgetLimiter()
         self.cache_control_check = _PROXY_CacheControlCheck()
-        self.alerting: list | None = None
+        self.alerting: list[str] | None = None
         self.alerting_threshold: float = 300  # default to 5 min. threshold
         self.alert_types: list[AlertType] = DEFAULT_ALERT_TYPES
         self.alert_to_webhook_url: dict | None = None
@@ -1524,6 +1524,7 @@ class ProxyLogging:
                 prompt_label=data.pop("prompt_label", None) or {},
                 prompt_version=data.pop("prompt_version", None) or {},
                 request_kwargs=data,
+                injected_for_every_deployment=True,
             )
 
             data.update(optional_params)
@@ -2364,7 +2365,9 @@ class ProxyLogging:
             # do nothing if alerting is not switched on (unless it's a soft_budget alert with team-specific emails)
             return
 
-        if self.alerting is not None and ("slack" in self.alerting or "ms_teams" in self.alerting):
+        if self.alerting is not None and (
+            "slack" in self.alerting or "ms_teams" in self.alerting or "webhook" in self.alerting
+        ):
             if self.slack_alerting_instance is not None:
                 await self.slack_alerting_instance.budget_alerts(
                     type=type,
diff --git a/litellm/proxy/vector_store_endpoints/endpoints.py b/litellm/proxy/vector_store_endpoints/endpoints.py
index a59d7a277cc..7d64e648e08 100644
--- a/litellm/proxy/vector_store_endpoints/endpoints.py
+++ b/litellm/proxy/vector_store_endpoints/endpoints.py
@@ -1,3 +1,5 @@
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import (
     Annotated,
     Any,  # noqa: TID251  # jsonify_object in proxy/utils.py is annotated with a bare dict
@@ -27,11 +29,69 @@ from litellm.types.vector_stores import IndexCreateRequest, IndexListResponse
 from litellm.vector_stores.vector_store_registry import VectorStoreIndexRegistry
 
 router: Final = APIRouter()
+
+BLOCKED_QUERY_EMBEDDING_SELECTION_PARAMS: Final = frozenset(
+    {
+        "embedding_model",
+        "litellm_embedding_model",
+        "litellm_embedding_config",
+        "litellm_credential_name",
+    }
+)
+
+
+def reject_caller_embedding_selection_params(payload: Mapping[str, object], source: str) -> None:
+    blocked: Final = sorted(BLOCKED_QUERY_EMBEDDING_SELECTION_PARAMS & payload.keys())
+    if blocked:
+        raise HTTPException(
+            status_code=400,
+            detail={
+                "error": f"'{blocked[0]}' cannot be set in {source}. "
+                "Embedding configuration comes from the vector store's server-side registration."
+            },
+        )
+
+
 ########################################################
 # OpenAI Compatible Endpoints
 ########################################################
 
 
+async def build_request_data_from_managed_vector_store(
+    vector_store: LiteLLM_ManagedVectorStore,
+) -> Mapping[str, object]:
+    """
+    Build request params (provider, credential ref, litellm_params) from an
+    already-resolved managed vector store.
+
+    ``litellm_embedding_config`` is resolved here, at request-handling time,
+    instead of at row-creation time: the resolved api_key/api_base/api_version
+    lives only in the returned per-request mapping and is never persisted back
+    to the registry cache. Legacy rows that already carry a resolved
+    (cleartext) config skip the lookup and pass through unchanged.
+    """
+    top_level: Final = MappingProxyType(
+        {
+            key: vector_store.get(key)
+            for key in ("custom_llm_provider", "litellm_credential_name")
+            if key in vector_store
+        }
+    )
+    litellm_params: Final = vector_store.get("litellm_params") or MappingProxyType({})
+    embedding_model: Final = litellm_params.get("litellm_embedding_model")
+    if not embedding_model or litellm_params.get("litellm_embedding_config"):
+        return MappingProxyType({**top_level, **litellm_params})
+
+    from litellm.proxy.proxy_server import prisma_client
+
+    resolved_config: Final = await _resolve_embedding_config(
+        embedding_model=embedding_model, prisma_client=prisma_client
+    )
+    if not resolved_config:
+        return MappingProxyType({**top_level, **litellm_params})
+    return MappingProxyType({**top_level, **litellm_params, "litellm_embedding_config": resolved_config})
+
+
 async def _update_request_data_with_litellm_managed_vector_store_registry(
     data: dict,
     vector_store_id: str,
@@ -51,47 +111,14 @@ async def _update_request_data_with_litellm_managed_vector_store_registry(
     vector_store_to_run: Final[LiteLLM_ManagedVectorStore | None] = await get_litellm_managed_vector_store(
         vector_store_id=vector_store_id
     )
-    if vector_store_to_run is not None:
-        if user_api_key_dict is not None:
-            await assert_user_can_access_vector_store(
-                vector_store=vector_store_to_run,
-                user_api_key_dict=user_api_key_dict,
-            )
-
-        if "custom_llm_provider" in vector_store_to_run:
-            data["custom_llm_provider"] = vector_store_to_run.get("custom_llm_provider")
-
-        if "litellm_credential_name" in vector_store_to_run:
-            data["litellm_credential_name"] = vector_store_to_run.get("litellm_credential_name")
-
-        if "litellm_params" in vector_store_to_run:
-            litellm_params = vector_store_to_run.get("litellm_params", {}) or {}
-            # Resolve ``litellm_embedding_config`` here, at request-handling
-            # time, instead of at row-creation time. The resolved
-            # ``api_key`` / ``api_base`` / ``api_version`` lives only in
-            # this per-request ``data`` dict and is never persisted.
-            # Legacy rows that already carry a resolved (cleartext)
-            # ``litellm_embedding_config`` skip the lookup and pass through
-            # unchanged so the embed call keeps working.
-            embedding_model: Final = litellm_params.get("litellm_embedding_model")
-            if embedding_model and not litellm_params.get("litellm_embedding_config"):
-                from litellm.proxy.proxy_server import prisma_client
-
-                resolved_config: Final = await _resolve_embedding_config(
-                    embedding_model=embedding_model, prisma_client=prisma_client
-                )
-                if resolved_config:
-                    # Build a fresh dict via spread instead of mutating
-                    # ``litellm_params`` in place — the registry hands back
-                    # a reference to its cached object, so an in-place
-                    # update would persist the resolved cleartext into the
-                    # in-memory cache for the lifetime of the process.
-                    litellm_params = {
-                        **litellm_params,
-                        "litellm_embedding_config": resolved_config,
-                    }
-            data.update(litellm_params)
-    return data
+    if vector_store_to_run is None:
+        return data
+    if user_api_key_dict is not None:
+        await assert_user_can_access_vector_store(
+            vector_store=vector_store_to_run,
+            user_api_key_dict=user_api_key_dict,
+        )
+    return {**data, **(await build_request_data_from_managed_vector_store(vector_store_to_run))}
 
 
 @router.post(
@@ -130,6 +157,7 @@ async def vector_store_search(
     )
 
     data = await _read_request_body(request=request)
+    reject_caller_embedding_selection_params(payload=data, source="the search request body")
     data["vector_store_id"] = vector_store_id
 
     # Check for legacy vector store registry (non-managed vector stores)
diff --git a/litellm/proxy/vector_store_endpoints/management_endpoints.py b/litellm/proxy/vector_store_endpoints/management_endpoints.py
index 183a03cc13c..244798ba05e 100644
--- a/litellm/proxy/vector_store_endpoints/management_endpoints.py
+++ b/litellm/proxy/vector_store_endpoints/management_endpoints.py
@@ -470,7 +470,7 @@ async def create_vector_store_in_db(
     # exposed every env-stored embedding-model credential on the
     # ``/vector_store/{new,info,update,list}`` responses. Keep the user's
     # raw ``litellm_embedding_model`` reference; resolution now happens in
-    # ``_update_request_data_with_litellm_managed_vector_store_registry``
+    # ``build_request_data_from_managed_vector_store``
     # at request-handling time so the cleartext config exists only in
     # per-request memory and never reaches the database.
     if litellm_params:
@@ -864,7 +864,7 @@ async def update_vector_store(
         # embedding-config auto-resolve previously persisted cleartext
         # credentials into the row; resolution now happens at request-
         # handling time in
-        # ``_update_request_data_with_litellm_managed_vector_store_registry``
+        # ``build_request_data_from_managed_vector_store``
         # so this row only ever stores the user-supplied
         # ``litellm_embedding_model`` reference.
         if "litellm_params" in update_data:
diff --git a/litellm/proxy/video_endpoints/endpoints.py b/litellm/proxy/video_endpoints/endpoints.py
index d985a546fa7..66071c05b4f 100644
--- a/litellm/proxy/video_endpoints/endpoints.py
+++ b/litellm/proxy/video_endpoints/endpoints.py
@@ -1,6 +1,6 @@
 #### Video Endpoints #####
 
-from typing import Any, Final
+from typing import Final
 
 from fastapi import APIRouter, Depends, File, Form, Request, Response, UploadFile
 from fastapi.responses import ORJSONResponse
@@ -161,7 +161,7 @@ async def video_list(
 
     # Read query parameters
     query_params: Final = dict(request.query_params)
-    data: Final[dict[str, Any]] = {"query_params": query_params}
+    data: Final[dict[str, object]] = {"query_params": query_params}
 
     # Extract custom_llm_provider from headers, query params, or body
     custom_llm_provider: Final = (
@@ -246,7 +246,7 @@ async def video_status(
     )
 
     # Create data with video_id
-    data: Final[dict[str, Any]] = {"video_id": video_id}
+    data: Final[dict[str, object]] = {"video_id": video_id}
 
     decoded: Final = decode_video_id_with_provider(video_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
@@ -345,7 +345,7 @@ async def video_content(
     )
 
     # Create data with video_id
-    data: Final[dict[str, Any]] = {"video_id": video_id}
+    data: Final[dict[str, object]] = {"video_id": video_id}
 
     decoded: Final = decode_video_id_with_provider(video_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
@@ -653,7 +653,7 @@ async def video_get_character(
     )
 
     original_requested_character_id: Final = character_id
-    data: Final[dict[str, Any]] = {"character_id": character_id}
+    data: Final[dict[str, object]] = {"character_id": character_id}
 
     decoded: Final = decode_character_id_with_provider(character_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
diff --git a/litellm/rag/ingestion/vertex_ai_ingestion.py b/litellm/rag/ingestion/vertex_ai_ingestion.py
index 07f9f346d08..eff8ad1b8cb 100644
--- a/litellm/rag/ingestion/vertex_ai_ingestion.py
+++ b/litellm/rag/ingestion/vertex_ai_ingestion.py
@@ -186,7 +186,6 @@ class VertexAIRAGIngestion(BaseRAGIngestion, VertexBase):
         base_url: Final = get_vertex_base_url(self.location)
         url: Final = f"{base_url}/v1beta1/projects/{self.project_id}/locations/{self.location}/ragCorpora"
 
-        # Build request body with camelCase keys (Vertex AI API format)
         vector_db_config: Final = self.vector_store_config.get("vector_db_config")
         embedding_model: Final = self.vector_store_config.get("embedding_model")
         embedding_model_config: Final = (
@@ -447,7 +446,6 @@ class VertexAIRAGIngestion(BaseRAGIngestion, VertexBase):
         # Add max embedding requests per minute if specified
         max_embedding_qpm: Final = self.vector_store_config.get("max_embedding_requests_per_min")
 
-        # Build request body with camelCase keys (Vertex AI API format)
         chunking_config: Final = (
             {"chunkSize": chunk_size or 1024, "chunkOverlap": chunk_overlap or 200}
             if chunk_size or chunk_overlap
diff --git a/litellm/rag/main.py b/litellm/rag/main.py
index 2dcaa200cc6..94bfc305a6a 100644
--- a/litellm/rag/main.py
+++ b/litellm/rag/main.py
@@ -14,6 +14,7 @@ import contextvars
 from collections.abc import Coroutine, Iterator
 from contextlib import contextmanager
 from functools import partial
+from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
@@ -29,6 +30,7 @@ from litellm.rag.ingestion.openai_ingestion import OpenAIRAGIngestion
 from litellm.rag.ingestion.s3_vectors_ingestion import S3VectorsRAGIngestion
 from litellm.rag.ingestion.vertex_ai_ingestion import VertexAIRAGIngestion
 from litellm.rag.rag_query import RAGQuery
+from litellm.types.llms.openai import AllMessageValues
 from litellm.types.rag import (
     RAGIngestOptions,
     RAGIngestResponse,
@@ -49,6 +51,21 @@ INGESTION_REGISTRY: Final[dict[str, type[BaseRAGIngestion]]] = {
     "vertex_ai": VertexAIRAGIngestion,
 }
 
+# Only these retrieval_config keys are forwarded to vector_stores.asearch as
+# provider-specific params. The explicit allowlist keeps caller-controlled
+# connection overrides (api_base, api_key, ...) away from the search call,
+# where they could redirect store credentials to an attacker-chosen host.
+_FORWARDABLE_RETRIEVAL_CONFIG_KEYS: Final = frozenset(
+    {
+        "aws_region_name",
+        "vector_bucket_name",
+        "embedding_model",
+        "litellm_embedding_model",
+        "litellm_embedding_config",
+        "litellm_credential_name",
+    }
+)
+
 
 def get_ingestion_class(provider: str) -> type[BaseRAGIngestion]:
     """
@@ -204,7 +221,7 @@ def _suppressed_sub_call_billing() -> Iterator[None]:
 
 async def _execute_query_pipeline(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
@@ -223,13 +240,20 @@ async def _execute_query_pipeline(
         raise ValueError("No query found in messages for RAG query")
 
     # 2. Search vector store
+    # Forward allowlisted provider retrieval_config extras (region, embedding
+    # model, bucket, credential refs) to the search call; kwargs win on conflict.
+    provider_search_params: Final = MappingProxyType(
+        {k: v for k, v in retrieval_config.items() if k in _FORWARDABLE_RETRIEVAL_CONFIG_KEYS}
+    )
+    forwarded_search_params: Final = MappingProxyType({**provider_search_params, **kwargs})
     with _suppressed_sub_call_billing():
         search_response: Final = await litellm.vector_stores.asearch(
             vector_store_id=retrieval_config["vector_store_id"],
             query=query_text,
             max_num_results=retrieval_config.get("top_k", 10),
             custom_llm_provider=retrieval_config.get("custom_llm_provider", "openai"),
-            **kwargs,
+            router=router,
+            **forwarded_search_params,
         )
 
     search_provider: Final = retrieval_config.get("custom_llm_provider", "openai")
@@ -311,7 +335,7 @@ async def _execute_query_pipeline(
 @client
 async def aquery(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
@@ -358,12 +382,12 @@ async def aquery(
 @client
 def query(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
     **kwargs,
-) -> ModelResponse | Coroutine[Any, Any, ModelResponse]:
+) -> ModelResponse | Coroutine[None, None, ModelResponse]:
     """
     Query a RAG pipeline.
     """
@@ -410,7 +434,7 @@ def ingest(
     file_id: str | None = None,
     timeout: float | httpx.Timeout | None = None,
     **kwargs,
-) -> RAGIngestResponse | Coroutine[Any, Any, RAGIngestResponse]:
+) -> RAGIngestResponse | Coroutine[None, None, RAGIngestResponse]:
     """
     Ingest a document into a vector store.
 
diff --git a/litellm/rag/rag_query.py b/litellm/rag/rag_query.py
index 16b8f82815c..255faf94402 100644
--- a/litellm/rag/rag_query.py
+++ b/litellm/rag/rag_query.py
@@ -1,11 +1,45 @@
+from collections.abc import Sequence
 from typing import Any, Final
 
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
 from litellm.types.utils import ModelResponse
-from litellm.types.vector_stores import (
-    VectorStoreResultContent,
-    VectorStoreSearchResponse,
-)
+from litellm.types.vector_stores import VectorStoreSearchResponse
+
+
+class _ResultContentView(TypedDict):
+    """Content entry carried by a vector store search result."""
+
+    type: ReadOnly[NotRequired[str]]
+    text: ReadOnly[str]
+
+
+class _SearchResultView(TypedDict):
+    """Vector store search result, as far as :class:`RAGQuery` reads it."""
+
+    content: ReadOnly[NotRequired[Sequence[_ResultContentView]]]
+    text: ReadOnly[NotRequired[str]]
+
+
+class _SearchDataView(TypedDict):
+    results: ReadOnly[Sequence[_SearchResultView]]
+
+
+class _ContextChunksView(TypedDict):
+    chunks: ReadOnly[Sequence[_SearchResultView | str | None]]
+
+
+class _RerankResultView(TypedDict):
+    index: ReadOnly[NotRequired[int]]
+
+
+class _RerankResultsView(TypedDict):
+    results: ReadOnly[Sequence[_RerankResultView]]
+
+
+class _MessageView(TypedDict):
+    message: ReadOnly[object]
 
 
 class RAGQuery:
@@ -42,9 +76,10 @@ class RAGQuery:
         """
         context_content = RAGQuery.CONTENT_PREFIX_STRING
 
-        for chunk in context_chunks:
+        chunks: Final[_ContextChunksView] = {"chunks": context_chunks}
+        for chunk in chunks["chunks"]:
             if isinstance(chunk, dict):
-                result_content: list[VectorStoreResultContent] | None = chunk.get("content")
+                result_content: Sequence[_ResultContentView] | None = chunk.get("content")
                 if result_content:
                     for content_item in result_content:
                         content_text: str | None = content_item.get("text")
@@ -64,14 +99,15 @@ class RAGQuery:
     def add_search_results_to_response(
         response: ModelResponse,
         search_results: VectorStoreSearchResponse,
-        rerank_results: Any | None = None,
+        rerank_results: object = None,
     ) -> ModelResponse:
         """
         Add search results to the response choices.
         """
         if hasattr(response, "choices") and response.choices:
             for choice in response.choices:
-                message = getattr(choice, "message", None)
+                message_view: _MessageView = {"message": getattr(choice, "message", None)}
+                message = message_view["message"]
                 if message is not None:
                     # Get existing provider_specific_fields or create new dict
                     provider_fields = getattr(message, "provider_specific_fields", None) or {}
@@ -91,7 +127,8 @@ class RAGQuery:
     ) -> list[str | dict[str, Any]]:
         """Extract text documents from vector store search response."""
         documents: Final[list[str | dict[str, Any]]] = []
-        for result in search_response.get("data", []):
+        search_data: Final[_SearchDataView] = {"results": search_response.get("data", [])}
+        for result in search_data["results"]:
             content_list = result.get("content", [])
             for content in content_list:
                 if content.get("type") == "text" and content.get("text"):
@@ -99,11 +136,13 @@ class RAGQuery:
         return documents
 
     @staticmethod
-    def get_top_chunks_from_rerank(search_response: Any, rerank_response: Any) -> list[Any]:
+    def get_top_chunks_from_rerank(search_response: Any, rerank_response: Any) -> list[_SearchResultView]:
         """Get the original search results corresponding to the top reranked results."""
-        top_chunks: Final = []
-        original_results: Final = search_response.get("data", [])
-        for result in rerank_response.get("results", []):
+        top_chunks: Final[list[_SearchResultView]] = []
+        search_data: Final[_SearchDataView] = {"results": search_response.get("data", [])}
+        original_results: Final = search_data["results"]
+        reranked: Final[_RerankResultsView] = {"results": rerank_response.get("results", [])}
+        for result in reranked["results"]:
             index = result.get("index")
             if index is not None and index < len(original_results):
                 top_chunks.append(original_results[index])
diff --git a/litellm/repositories/base_repository.py b/litellm/repositories/base_repository.py
index 568e3b50ed2..26c1c386138 100644
--- a/litellm/repositories/base_repository.py
+++ b/litellm/repositories/base_repository.py
@@ -40,7 +40,7 @@ def record_to_dict(record: DbRecord) -> Mapping[str, object]:
 class BaseRepository(ABC, Generic[T]):
     """Abstract base class for all repositories."""
 
-    def __init__(self, prisma_client: Any):  # any-ok: PrismaClient is an untyped runtime wrapper
+    def __init__(self, prisma_client: object):
         self._prisma_client = prisma_client
 
     @property
diff --git a/litellm/repositories/team_repository.py b/litellm/repositories/team_repository.py
index cffa08ce7e0..5ff07d76b5d 100644
--- a/litellm/repositories/team_repository.py
+++ b/litellm/repositories/team_repository.py
@@ -3,9 +3,9 @@ Team repository for database operations on LiteLLM_TeamTable.
 """
 
 import json
-from collections.abc import Mapping
+from collections.abc import Mapping, Sequence
 from datetime import datetime
-from typing import TYPE_CHECKING, Final
+from typing import TYPE_CHECKING, Final, Protocol
 
 from pydantic import TypeAdapter
 
@@ -21,6 +21,25 @@ if TYPE_CHECKING:
     from prisma import Prisma
     from prisma import models as prisma_models
 
+
+class _TeamArrays(Protocol):
+    """The string array columns of a team row, which the domain model leaves untyped."""
+
+    @property
+    def members(self) -> Sequence[str]: ...
+
+    @property
+    def admins(self) -> Sequence[str]: ...
+
+    @property
+    def models(self) -> Sequence[str]: ...
+
+
+def _team_arrays(team: LiteLLM_TeamTable) -> _TeamArrays:
+    """View a team's untyped list columns as sequences of ids."""
+    return team
+
+
 _MEMBERS_WITH_ROLES_ADAPTER: Final = TypeAdapter(list[Member])
 _JSON_ENCODED_TEAM_FIELDS: Final = (
     "metadata",
@@ -80,8 +99,8 @@ class TeamRepository(BaseRepository[LiteLLM_TeamTable]):
         )
         if not rows:
             return None
-        raw_value: Final = rows[0]["members_with_roles"]
-        parsed: Final = json.loads(raw_value) if isinstance(raw_value, str) else raw_value
+        raw_value: Final[object] = rows[0]["members_with_roles"]
+        parsed: Final[object] = json.loads(raw_value) if isinstance(raw_value, str) else raw_value
         if not parsed:
             return []
         return _MEMBERS_WITH_ROLES_ADAPTER.validate_python(parsed)
@@ -315,7 +334,7 @@ class TeamRepository(BaseRepository[LiteLLM_TeamTable]):
         if team is None:
             return None
 
-        members: Final = [m for m in team.members if m != user_id]
+        members: Final = [m for m in _team_arrays(team).members if m != user_id]
         return await self.update(team_id, {"members": members}, id_field="team_id")
 
     async def add_admin(self, team_id: str, user_id: str) -> LiteLLM_TeamTable | None:
@@ -340,7 +359,7 @@ class TeamRepository(BaseRepository[LiteLLM_TeamTable]):
         if team is None:
             return None
 
-        admins: Final = [a for a in team.admins if a != user_id]
+        admins: Final = [a for a in _team_arrays(team).admins if a != user_id]
         return await self.update(team_id, {"admins": admins}, id_field="team_id")
 
     async def add_models(self, team_id: str, models: list[str]) -> LiteLLM_TeamTable | None:
@@ -365,5 +384,5 @@ class TeamRepository(BaseRepository[LiteLLM_TeamTable]):
         if team is None:
             return None
 
-        current_models: Final = [m for m in team.models if m not in models]
+        current_models: Final = [m for m in _team_arrays(team).models if m not in models]
         return await self.update(team_id, {"models": current_models}, id_field="team_id")
diff --git a/litellm/repositories/user_repository.py b/litellm/repositories/user_repository.py
index 9df1bceac9c..87eb45f262d 100644
--- a/litellm/repositories/user_repository.py
+++ b/litellm/repositories/user_repository.py
@@ -6,15 +6,34 @@ import json
 from collections.abc import Mapping
 from typing import TYPE_CHECKING, Final
 
-from litellm.models.user import LiteLLM_UserTable
+from pydantic import TypeAdapter
+
+from litellm.models.user import LiteLLM_UserTable, SCIMPlaceholder
 from litellm.repositories.base_repository import BaseRepository, DbRecord, record_to_dict
 from litellm.repositories.prisma_protocols import TableActions
 
 if TYPE_CHECKING:
+    from prisma import Prisma
     from prisma import models as prisma_models
 
 _JSON_ENCODED_COLUMNS: Final = frozenset({"metadata", "model_spend", "model_max_budget"})
 
+_SHADOWING_PLACEHOLDERS_SQL: Final = """
+SELECT p.user_id AS placeholder_user_id,
+       array_agg(r.user_id ORDER BY r.user_id) AS resolved_user_ids,
+       p.teams AS team_ids
+FROM "LiteLLM_UserTable" p
+JOIN "LiteLLM_UserTable" r
+  ON r.user_id <> p.user_id
+ AND (r.sso_user_id = p.user_id OR LOWER(r.user_email) = LOWER(p.user_id))
+WHERE p.sso_user_id IS NULL
+  AND NOT EXISTS (SELECT 1 FROM "LiteLLM_VerificationToken" k WHERE k.user_id = p.user_id)
+GROUP BY p.user_id, p.teams
+ORDER BY p.user_id
+"""
+
+_PLACEHOLDER_ROWS_ADAPTER: Final = TypeAdapter(tuple[SCIMPlaceholder, ...])
+
 
 class UserRepository(BaseRepository[LiteLLM_UserTable]):
     """Repository for user database operations."""
@@ -59,6 +78,11 @@ class UserRepository(BaseRepository[LiteLLM_UserTable]):
         """Find all users in a team."""
         return await self.find_many(where={"teams": {"has": team_id}})
 
+    async def find_shadowing_placeholders(self, tx: "Prisma") -> tuple[SCIMPlaceholder, ...]:
+        """Users with no SSO id and no virtual keys whose id is another user's SSO id or email."""
+        rows: Final = await tx.query_raw(_SHADOWING_PLACEHOLDERS_SQL)
+        return _PLACEHOLDER_ROWS_ADAPTER.validate_python(rows)
+
     async def count_billable_users(self) -> int:
         """Number of users that count toward the license seat limit.
 
diff --git a/litellm/rerank_api/main.py b/litellm/rerank_api/main.py
index c8f7842aebf..37ca989b8d3 100644
--- a/litellm/rerank_api/main.py
+++ b/litellm/rerank_api/main.py
@@ -6,6 +6,7 @@ from typing import Any, Final, Literal
 
 import litellm
 from litellm._logging import verbose_logger
+from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
 from litellm.llms.bedrock.rerank.handler import BedrockRerankHandler
@@ -43,10 +44,23 @@ async def arerank(
     """
     Async: Reranks a list of documents based on their relevance to the query
     """
+    _custom_llm_provider: str | None = (
+        None  # rebind-ok: set by the declared-provider guard or the get_llm_provider unpack; read in the except
+    )
     try:
         loop: Final = asyncio.get_event_loop()
         kwargs["arerank"] = True
 
+        declared_provider: Final = declared_authenticating_provider(model, custom_llm_provider)
+        if declared_provider is not None:
+            _custom_llm_provider = declared_provider  # rebind-ok: see pre-declaration above
+        else:
+            _, _custom_llm_provider, _, _ = litellm.get_llm_provider(  # rebind-ok: see pre-declaration above
+                model=model,
+                custom_llm_provider=custom_llm_provider,
+                api_base=kwargs.get("api_base", None),
+            )
+
         func: Final = partial(
             rerank,
             model,
@@ -70,7 +84,11 @@ async def arerank(
             response = init_response
         return response
     except Exception as e:
-        raise e
+        raise exception_type(
+            model=model,
+            custom_llm_provider=_custom_llm_provider or custom_llm_provider,
+            original_exception=e,
+        )
 
 
 @client
@@ -115,6 +133,7 @@ def rerank(
     model_info: Final = kwargs.get("model_info", None)
     user: Final = kwargs.get("user", None)
     client: Final = kwargs.get("client", None)
+    _custom_llm_provider: str | None = None  # rebind-ok: set by the get_llm_provider unpack; read in the except
     try:
         _is_async: Final = kwargs.pop("arerank", False) is True
         optional_params: Final = GenericLiteLLMParams(**kwargs)
@@ -127,7 +146,7 @@ def rerank(
 
         (
             model,
-            _custom_llm_provider,
+            _custom_llm_provider,  # rebind-ok: see pre-declaration above
             dynamic_api_key,
             dynamic_api_base,
         ) = litellm.get_llm_provider(
@@ -538,4 +557,8 @@ def rerank(
         return response
     except Exception as e:
         verbose_logger.error("Error in rerank: %s", e)
-        raise exception_type(model=model, custom_llm_provider=custom_llm_provider, original_exception=e)
+        raise exception_type(
+            model=model,
+            custom_llm_provider=_custom_llm_provider or custom_llm_provider,
+            original_exception=e,
+        )
diff --git a/litellm/responses/litellm_completion_transformation/custom_tools.py b/litellm/responses/litellm_completion_transformation/custom_tools.py
index cccae06c74b..4aa489d9e50 100644
--- a/litellm/responses/litellm_completion_transformation/custom_tools.py
+++ b/litellm/responses/litellm_completion_transformation/custom_tools.py
@@ -17,6 +17,7 @@ logic.
 
 import json
 from collections.abc import Mapping, Sequence
+from types import MappingProxyType
 from typing import Final
 
 from pydantic import BaseModel, TypeAdapter, ValidationError
@@ -28,6 +29,15 @@ from litellm.types.llms.openai import (
 
 _MAX_ARGUMENTS_LEN: Final = 1_000_000
 
+TOOL_CALL_ITEM_ID_PREFIX_BY_TYPE: Final = MappingProxyType({"function_call": "fc", "custom_tool_call": "ctc"})
+
+
+def openai_shaped_tool_call_item_id(item_type: str, tool_id: str) -> str:
+    prefix: Final = TOOL_CALL_ITEM_ID_PREFIX_BY_TYPE.get(item_type)
+    if prefix is None or not tool_id or tool_id.startswith(prefix):
+        return tool_id
+    return f"{prefix}_{tool_id}"
+
 
 def extract_custom_tool_names(tools: Sequence[object] | None) -> set[str]:
     """Extract names of tools originally defined as ``type: "custom"``."""
@@ -45,6 +55,21 @@ def is_custom_tool_call(tool_name: str, custom_tool_names: set[str]) -> bool:
     return tool_name in custom_tool_names
 
 
+def serialize_tool_call_arguments(raw_arguments: object, default: str = "") -> str:
+    """Render tool call arguments as the JSON string tool-call schemas require.
+
+    Arguments normally arrive already JSON-encoded, but clients and providers
+    also send the decoded object. ``str()`` on a dict yields a Python repr with
+    single quotes, which every downstream JSON parser rejects with errors like
+    "Expecting ',' delimiter".
+    """
+    if isinstance(raw_arguments, str):
+        return raw_arguments or default
+    if raw_arguments is None:
+        return default
+    return json.dumps(raw_arguments, default=str)
+
+
 def unwrap_custom_tool_arguments(arguments: str) -> str:
     """Extract the raw content string from JSON-wrapped arguments.
 
@@ -88,7 +113,7 @@ def build_tool_call_item_kwargs(
     item_type: Final = "custom_tool_call" if custom else "function_call"
     kwargs: Final[dict[str, str]] = {
         "type": item_type,
-        "id": call_id,
+        "id": openai_shaped_tool_call_item_id(item_type, call_id),
         "call_id": call_id,
         "name": name,
         "status": status,
diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
index 8b1eeb30306..bc25f4fffb1 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -8,6 +8,7 @@ from litellm.main import stream_chunk_builder
 from litellm.responses.litellm_completion_transformation.custom_tools import (
     build_tool_call_item_kwargs,
     extract_custom_tool_names,
+    serialize_tool_call_arguments,
 )
 from litellm.responses.litellm_completion_transformation.transformation import (
     LiteLLMCompletionResponsesConfig,
@@ -113,6 +114,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
         self._pending_tool_events: list[BaseLiteLLMOpenAIResponseObject] = []
         self._tool_output_index_by_call_id: dict[str, int] = {}
         self._tool_args_by_call_id: dict[str, str] = {}
+        self._tool_item_id_by_call_id: dict[str, str] = {}  # mutable-ok: filled per call id as tool call events stream
         self._tool_call_id_by_index: dict[int, str] = {}
         self._ambiguous_tool_call_indexes: set[int] = set()
         self._next_tool_output_index: int = 1  # output_index=0 reserved for the message item
@@ -213,10 +215,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             fn_args_delta = ""
             if isinstance(fn, dict):
                 fn_name = str(fn.get("name") or "")
-                fn_args_delta = str(fn.get("arguments") or "")
+                fn_args_delta = serialize_tool_call_arguments(fn.get("arguments"))
             else:
                 fn_name = str(getattr(fn, "name", "") or "")
-                fn_args_delta = str(getattr(fn, "arguments", "") or "")
+                fn_args_delta = serialize_tool_call_arguments(getattr(fn, "arguments", ""))
             tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name)
 
             output_index = self._get_or_assign_tool_output_index(call_id)
@@ -226,6 +228,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                 self._sequence_number += 1
                 names = self._custom_tool_names
                 item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, "", "in_progress", names)
+                self._tool_item_id_by_call_id[call_id] = item_kwargs["id"]
                 if tool_namespace:
                     item_kwargs["namespace"] = tool_namespace
                 event = OutputItemAddedEvent(
@@ -247,7 +250,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                     self._sequence_number += 1
                     delta_event: BaseLiteLLMOpenAIResponseObject = FunctionCallArgumentsDeltaEvent(
                         type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA,
-                        item_id=call_id,
+                        item_id=self._tool_item_id_by_call_id.get(call_id, call_id),
                         output_index=output_index,
                         delta=delta_chunk,
                     )
@@ -284,10 +287,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             fn_args = ""
             if isinstance(fn, dict):
                 fn_name = str(fn.get("name") or "")
-                fn_args = str(fn.get("arguments") or "")
+                fn_args = serialize_tool_call_arguments(fn.get("arguments"))
             else:
                 fn_name = str(getattr(fn, "name", "") or "")
-                fn_args = str(getattr(fn, "arguments", "") or "")
+                fn_args = serialize_tool_call_arguments(getattr(fn, "arguments", ""))
             tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name)
 
             # Track if this is a new tool call that wasn't streamed
@@ -299,6 +302,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                 self._sequence_number += 1
                 names = self._custom_tool_names
                 item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, "", "in_progress", names)
+                self._tool_item_id_by_call_id[call_id] = item_kwargs["id"]
                 if tool_namespace:
                     item_kwargs["namespace"] = tool_namespace
                 event = OutputItemAddedEvent(
@@ -324,7 +328,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
                     self._sequence_number += 1
                     delta_event = FunctionCallArgumentsDeltaEvent(
                         type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA,
-                        item_id=call_id,
+                        item_id=self._tool_item_id_by_call_id.get(call_id, call_id),
                         output_index=output_index,
                         delta=delta_chunk,
                     )
@@ -334,7 +338,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             self._sequence_number += 1
             done_event = FunctionCallArgumentsDoneEvent(
                 type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE,
-                item_id=call_id,
+                item_id=self._tool_item_id_by_call_id.get(call_id, call_id),
                 output_index=output_index,
                 arguments=final_args,
             )
@@ -344,6 +348,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
             self._sequence_number += 1
             names = self._custom_tool_names
             item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, final_args, "completed", names)
+            item_kwargs["id"] = self._tool_item_id_by_call_id.setdefault(call_id, item_kwargs["id"])
             if tool_namespace:
                 item_kwargs["namespace"] = tool_namespace
             item_done_event = OutputItemDoneEvent(
@@ -1164,16 +1169,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator):
 
     def _emit_response_completed_event(self, litellm_model_response: ModelResponse) -> ResponseCompletedEvent | None:
         if litellm_model_response:
-            # Add cost to usage object if include_cost_in_streaming_usage is True
-            if litellm.include_cost_in_streaming_usage and self.litellm_logging_obj is not None:
-                usage: Final[object] = getattr(litellm_model_response, "usage", None)
-                if usage is not None:
-                    setattr(
-                        usage,
-                        "cost",
-                        self.litellm_logging_obj._response_cost_calculator(result=litellm_model_response),
-                    )
-
             # Transform the response
             responses_api_response: Final = (
                 LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index f39df38d069..5f3e88bb12f 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -93,6 +93,8 @@ from .custom_tools import (
     convert_custom_tool_to_function_tool,
     extract_custom_tool_names,
     is_custom_tool_call,
+    openai_shaped_tool_call_item_id,
+    serialize_tool_call_arguments,
     unwrap_custom_tool_arguments,
     validated_allowed_callers,
 )
@@ -1010,7 +1012,7 @@ class LiteLLMCompletionResponsesConfig:
             type=cast(Literal["function"], tool_use_type),
             function=ChatCompletionToolCallFunctionChunk(
                 name=str(function.get("name", "")),
-                arguments=str(function.get("arguments", "{}")),
+                arguments=serialize_tool_call_arguments(function.get("arguments"), "{}"),
             ),
             index=index,
         )
@@ -1539,7 +1541,7 @@ class LiteLLMCompletionResponsesConfig:
                 type=cast(Literal["function"], _tool_use_definition.get("type") or "function"),
                 function=ChatCompletionToolCallFunctionChunk(
                     name=function.get("name") or "",
-                    arguments=str(function.get("arguments") or ""),
+                    arguments=serialize_tool_call_arguments(function.get("arguments")),
                 ),
                 index=0,
             )
@@ -1589,7 +1591,7 @@ class LiteLLMCompletionResponsesConfig:
             type="function",
             function=ChatCompletionToolCallFunctionChunk(
                 name=f"{namespace}__{raw_name}" if qualify else raw_name,
-                arguments=str(raw_arguments or ""),
+                arguments=serialize_tool_call_arguments(raw_arguments),
             ),
             index=0,
         )
@@ -1629,6 +1631,8 @@ class LiteLLMCompletionResponsesConfig:
             file_dict["file_id"] = file_id
         if item.get("file_data"):
             file_dict["file_data"] = item["file_data"]
+        if item.get("filename"):
+            file_dict["filename"] = item["filename"]
 
         new_item: Final[dict[str, object]] = {"type": "file", "file": file_dict}
         if "cache_control" in item:
@@ -2022,7 +2026,7 @@ class LiteLLMCompletionResponsesConfig:
                 function_definition = tool.function
                 tool_name = function_definition.name or ""
                 tool_id = tool.id or ""
-                tool_arguments = function_definition.get("arguments") or ""
+                tool_arguments = serialize_tool_call_arguments(function_definition.get("arguments"))
 
                 # Check if this is a custom tool
                 if is_custom_tool_call(tool_name, custom_tool_names):
@@ -2031,7 +2035,7 @@ class LiteLLMCompletionResponsesConfig:
                     custom_item = CustomToolCallOutputItem(
                         type="custom_tool_call",
                         call_id=tool_id,
-                        id=tool_id,
+                        id=openai_shaped_tool_call_item_id("custom_tool_call", tool_id),
                         name=tool_name,
                         input=input_str,
                         status=function_definition.get("status") or "completed",
@@ -2062,7 +2066,7 @@ class LiteLLMCompletionResponsesConfig:
                         name=tool_name,
                         arguments=tool_arguments,
                         call_id=tool_id,
-                        id=tool_id,
+                        id=openai_shaped_tool_call_item_id("function_call", tool_id),
                         type="function_call",
                         status=function_definition.get("status") or "completed",
                     )
@@ -2499,8 +2503,7 @@ class LiteLLMCompletionResponsesConfig:
                     choice=choice,
                 )
                 message_output_items.extend(image_generation_items)
-            else:
-                # Regular message output
+            elif choice.message.content is not None:
                 message_output_items.append(
                     GenericResponseOutputItem(
                         type="message",
@@ -2557,7 +2560,7 @@ class LiteLLMCompletionResponsesConfig:
             type="function",
             function=Function(
                 name=tool_call.get("name") or "",
-                arguments=tool_call.get("arguments") or "",
+                arguments=serialize_tool_call_arguments(tool_call.get("arguments")),
             ),
         )
 
diff --git a/litellm/responses/mcp/litellm_proxy_mcp_handler.py b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
index 197d0c02ba8..367915156d1 100644
--- a/litellm/responses/mcp/litellm_proxy_mcp_handler.py
+++ b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
@@ -399,7 +399,7 @@ class LiteLLM_Proxy_MCP_Handler:
 
     @staticmethod
     async def _process_mcp_tools_without_openai_transform(
-        user_api_key_auth: Any,
+        user_api_key_auth: "UserAPIKeyAuth | None",
         mcp_tools_with_litellm_proxy: Sequence[Mapping[str, object]],
         litellm_trace_id: str | None = None,
         mcp_auth_header: str | None = None,
@@ -636,7 +636,7 @@ class LiteLLM_Proxy_MCP_Handler:
     async def _execute_tool_calls(
         tool_server_map: dict[str, str],
         tool_calls: Sequence[object],
-        user_api_key_auth: Any,
+        user_api_key_auth: "UserAPIKeyAuth | None",
         mcp_auth_header: str | None = None,
         mcp_server_auth_headers: dict[str, dict[str, str]] | None = None,
         oauth2_headers: dict[str, str] | None = None,
diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py
index 63adf950142..7871c85220c 100644
--- a/litellm/responses/streaming_iterator.py
+++ b/litellm/responses/streaming_iterator.py
@@ -5,11 +5,11 @@ import json
 import time
 import traceback
 import uuid
-from collections.abc import Awaitable, Callable, Mapping, Sequence
+from collections.abc import Awaitable, Callable, Iterable, Mapping, Sequence
 from datetime import datetime
 from functools import lru_cache
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, runtime_checkable
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, overload, runtime_checkable
 
 import httpx
 from openai._streaming import SSEDecoder
@@ -42,27 +42,14 @@ from litellm.types.utils import CallTypes
 from litellm.utils import async_post_call_success_deployment_hook
 
 if TYPE_CHECKING:
+    from litellm.caching.caching_handler import LLMCachingHandler
     from litellm.proxy._types import UserAPIKeyAuth
     from litellm.types.responses.streaming_websocket import (
         PresidioGuardrailCallback,
         ResponsesBackendWebSocket,
         ResponsesClientWebSocket,
     )
-
-    class _StreamCachingHandler(Protocol):
-        """The ``_llm_caching_handler`` attached to a logging object, as this module uses it."""
-
-        original_function: Callable[..., object]
-
-        def _should_store_result_in_cache(
-            self, original_function: Callable[..., object], kwargs: Mapping[str, object]
-        ) -> bool: ...
-
-    class PiiUnmaskingGuardrailCallback(PresidioGuardrailCallback, Protocol):
-        """Guardrail callback that can also reverse its own masking, selected by
-        ``llm_http_handler`` on exactly this attribute."""
-
-        def _unmask_pii_text(self, text: str, pii_tokens: Mapping[str, str]) -> str: ...
+    from litellm.types.router import LiteLLM_Params
 
 
 class ProjectQuotaCallback(Protocol):
@@ -90,10 +77,66 @@ def _is_json_array(value: object) -> TypeIs[list[object]]:  # guard-ok: trivial
     return isinstance(value, list)
 
 
+def _optional_str(value: object) -> str | None:
+    """Keep a JSON payload entry only when it is a string, since the wire format is caller-controlled."""
+    return value if isinstance(value, str) else None
+
+
+def _json_array_or_empty(value: object) -> Sequence[object]:
+    """Narrow a JSON payload entry that the caller iterates, tolerating a missing or malformed value."""
+    return value if _is_json_array(value) else ()
+
+
 def _is_str_mapping(value: object) -> TypeIs[dict[str, str]]:  # guard-ok: verifies every value is str
     return _is_json_object(value) and all(isinstance(item, str) for item in value.values())
 
 
+class _MutableJsonObject(Protocol):
+    @overload
+    def get(self, key: str, /) -> object | None: ...
+    @overload
+    def get(self, key: str, default: object, /) -> object: ...
+    def __getitem__(self, key: str, /) -> object: ...
+    def __setitem__(self, key: str, value: object, /) -> None: ...
+    def __contains__(self, key: object, /) -> bool: ...
+    def items(self) -> Iterable[tuple[str, object]]: ...
+
+
+class _GetsLitellmParams(Protocol):
+    def __call__(self, key: str, default: Mapping[str, object], /) -> LiteLLM_Params: ...
+
+
+class _UnmasksPiiText(Protocol):
+    def __call__(self, text: str, pii_tokens: Mapping[str, str]) -> str: ...
+
+
+class _ShouldStoreResultInCache(Protocol):
+    def __call__(self, *, original_function: Callable[..., object] | None, kwargs: Mapping[str, object]) -> bool: ...
+
+
+class _PostStreamingDeploymentHook(Protocol):
+    def __call__(
+        self,
+        *,
+        request_data: Mapping[str, object],
+        response_chunk: ResponsesAPIStreamingResponse,
+        call_type: CallTypes | None,
+    ) -> Awaitable[ResponsesAPIStreamingResponse | None]: ...
+
+
+@runtime_checkable
+class _HasPostStreamingDeploymentHook(Protocol):
+    async_post_call_streaming_deployment_hook: _PostStreamingDeploymentHook
+
+
+def _typed_gets_litellm_params(fn: _GetsLitellmParams) -> _GetsLitellmParams:
+    return fn
+
+
+_SHOULD_STORE_RESULT_IN_CACHE_ATTR: Final = "_should_store_result_in_cache"
+_UNMASK_PII_TEXT_ATTR: Final = "_unmask_pii_text"
+
+
 def _load_json_object(payload: str | bytes) -> dict[str, object]:
     """Parse a JSON payload that the caller consumes as an object."""
     return json.loads(payload)
@@ -220,7 +263,7 @@ class BaseResponsesAPIStreamingIterator:
         # This matches the stream wrapper in litellm/litellm_core_utils/streaming_handler.py
         _api_base: Final = get_api_base(
             model=model or "",
-            optional_params=self.logging_obj.model_call_details.get("litellm_params", {}),
+            optional_params=_typed_gets_litellm_params(self.logging_obj.model_call_details.get)("litellm_params", {}),
         )
         self._hidden_params: dict[str, object] = {
             "model_id": _model_id_from_metadata(litellm_metadata),
@@ -301,7 +344,7 @@ class BaseResponsesAPIStreamingIterator:
                     ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
                     ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE,
                 ):
-                    _item: Final = getattr(openai_responses_api_chunk, "item", None)
+                    _item: Final[object] = getattr(openai_responses_api_chunk, "item", None)
                     if _item is not None:
                         ResponsesAPIRequestUtils._encode_container_id_on_output_item(
                             item=_item,
@@ -309,7 +352,7 @@ class BaseResponsesAPIStreamingIterator:
                             model_id=_stream_model_id,
                         )
                 elif _event_type == ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED:
-                    _annotation: Final = getattr(openai_responses_api_chunk, "annotation", None)
+                    _annotation: Final[object] = getattr(openai_responses_api_chunk, "annotation", None)
                     if _annotation is not None:
                         ResponsesAPIRequestUtils._encode_container_id_on_output_item(
                             item=_annotation,
@@ -364,23 +407,7 @@ class BaseResponsesAPIStreamingIterator:
                     openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED,
                 ):
                     self.completed_response = openai_responses_api_chunk
-                    # Add cost to usage object if include_cost_in_streaming_usage is True
-                    if litellm.include_cost_in_streaming_usage and self.logging_obj is not None:
-                        response_obj: Final[ResponsesAPIResponse | None] = getattr(
-                            openai_responses_api_chunk, "response", None
-                        )
-                        if response_obj:
-                            usage_obj: Final[ResponseAPIUsage | None] = getattr(response_obj, "usage", None)
-                            if usage_obj is not None:
-                                try:
-                                    cost: Final[float | None] = self.logging_obj._response_cost_calculator(
-                                        result=response_obj
-                                    )
-                                    if cost is not None:
-                                        setattr(usage_obj, "cost", cost)
-                                except Exception:
-                                    # Best-effort usage cost annotation should not break stream replay.
-                                    pass
+                    _stamp_responses_usage_cost(getattr(openai_responses_api_chunk, "response", None), self.logging_obj)
 
                     if _chunk_type == openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED:
                         self._handle_logging_failed_response()
@@ -422,15 +449,20 @@ class BaseResponsesAPIStreamingIterator:
 
         end_time: Final = datetime.now()
         if is_async:
-            asyncio.create_task(
-                self.logging_obj.dispatch_success_handlers(
-                    logging_response,
-                    start_time=self.start_time,
-                    end_time=end_time,
-                    cache_hit=self._completed_response_cache_hit,
-                    prefer_async_handlers=True,
-                )
+            logging_coroutine: Final = self.logging_obj.dispatch_success_handlers(
+                logging_response,
+                start_time=self.start_time,
+                end_time=end_time,
+                cache_hit=self._completed_response_cache_hit,
+                prefer_async_handlers=True,
             )
+            deferred_dispatch_armed: Final = getattr(self.logging_obj, "_on_deferred_stream_complete", None) is not None
+            if deferred_dispatch_armed:
+                # End-of-stream guardrail scans write guardrail_information after
+                # the terminal event; dispatching now would snapshot metadata early.
+                self.logging_obj._deferred_stream_complete_args = (logging_coroutine,)
+            else:
+                asyncio.create_task(logging_coroutine)
         else:
             run_async_function(
                 async_function=self.logging_obj.async_success_handler,
@@ -549,7 +581,7 @@ class BaseResponsesAPIStreamingIterator:
         if response_obj is None:
             return
 
-        caching_handler: Final[_StreamCachingHandler | None] = getattr(self.logging_obj, "_llm_caching_handler", None)
+        caching_handler: Final[LLMCachingHandler | None] = getattr(self.logging_obj, "_llm_caching_handler", None)
         if caching_handler is None:
             return
 
@@ -567,8 +599,11 @@ class BaseResponsesAPIStreamingIterator:
         if preset_cache_key is not None:
             request_kwargs["cache_key"] = preset_cache_key
 
-        if not caching_handler._should_store_result_in_cache(  # pyright: ignore[reportPrivateUsage]  # no public API
-            original_function=caching_handler.original_function,
+        should_store_result_in_cache: Final[_ShouldStoreResultInCache] = getattr(
+            caching_handler, _SHOULD_STORE_RESULT_IN_CACHE_ATTR
+        )
+        if not should_store_result_in_cache(
+            original_function=getattr(caching_handler, "original_function", None),
             kwargs=request_kwargs,
         ):
             return
@@ -624,12 +659,15 @@ class BaseResponsesAPIStreamingIterator:
                     typed_call_type = None
 
             request_data: Final = self.request_data or getattr(self.logging_obj, "model_call_details", {})
-            callbacks: Final = getattr(litellm, "callbacks", None) or []
+            callbacks: Final[Sequence[object]] = getattr(litellm, "callbacks", None) or []
             hooks_ran = False
             for callback in callbacks:
-                if hasattr(callback, "async_post_call_streaming_deployment_hook"):
+                if isinstance(callback, _HasPostStreamingDeploymentHook):
                     hooks_ran = True
-                    result = await callback.async_post_call_streaming_deployment_hook(
+                    post_streaming_hook: _PostStreamingDeploymentHook = (
+                        callback.async_post_call_streaming_deployment_hook
+                    )
+                    result = await post_streaming_hook(
                         request_data=request_data,
                         response_chunk=chunk,
                         call_type=typed_call_type,
@@ -969,7 +1007,7 @@ class MockResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator):
         transformed: ResponsesAPIResponse,
         logging_obj: LiteLLMLoggingObj,
     ) -> None:
-        self._events: list[ResponsesAPIStreamingResponse] = _build_synthetic_response_events(
+        self._events: Sequence[ResponsesAPIStreamingResponse] = build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=self.CHUNK_SIZE,
@@ -1036,7 +1074,7 @@ class CachedResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator):
         transformed: ResponsesAPIResponse,
         logging_obj: LiteLLMLoggingObj,
     ) -> None:
-        self._events = _build_synthetic_response_events(
+        self._events = build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=MockResponsesAPIStreamingIterator.CHUNK_SIZE,
@@ -1083,7 +1121,7 @@ class _HasModelDumpJson(Protocol):
     def model_dump_json(self, *, exclude_none: bool = ...) -> str: ...
 
 
-def _dump_response_object(obj: object) -> dict[str, Any]:
+def _dump_response_object(obj: object) -> Mapping[str, object]:
     if isinstance(obj, _HasModelDump):
         return obj.model_dump()
     if _is_json_object(obj):
@@ -1113,21 +1151,20 @@ def _build_content_part_done_event(
     item_id: str,
     output_index: int,
     content_index: int,
-    part_payload: dict[str, Any],
+    part_payload: Mapping[str, object],
 ) -> ResponsesAPIStreamingResponse | None:
     openai_types: Final = _get_openai_response_types()
     part_type: Final = part_payload.get("type")
     part: PART_UNION_TYPES
     if part_type == "output_text":
-        annotations: Final = [
-            openai_types.BaseLiteLLMOpenAIResponseObject(**annotation)
-            for annotation in part_payload.get("annotations", []) or []
-        ]
-        part = openai_types.ContentPartDonePartOutputText(
-            type="output_text",
-            text=str(part_payload.get("text") or ""),
-            annotations=annotations,
-            logprobs=part_payload.get("logprobs"),
+        raw_annotations: Final[object] = part_payload.get("annotations", []) or []
+        part = openai_types.ContentPartDonePartOutputText.model_validate(
+            {
+                "type": "output_text",
+                "text": str(part_payload.get("text") or ""),
+                "annotations": raw_annotations,
+                "logprobs": part_payload.get("logprobs"),
+            }
         )
     elif part_type == "refusal":
         part = openai_types.ContentPartDonePartRefusal(
@@ -1157,7 +1194,7 @@ def _add_text_like_part_events(
     item_id: str,
     output_index: int,
     content_index: int,
-    part_payload: dict[str, Any],
+    part_payload: Mapping[str, object],
     chunk_size: int,
 ) -> None:
     openai_types: Final = _get_openai_response_types()
@@ -1174,16 +1211,19 @@ def _add_text_like_part_events(
                     delta=text[i : i + chunk_size],
                 )
             )
-        annotations_payload: Final[Sequence[dict[str, object]]] = part_payload.get("annotations", []) or []
-        for annotation_index, annotation in enumerate(annotations_payload):
+        raw_annotation_items: Final = part_payload.get("annotations")
+        annotation_items: Final[Sequence[object]] = raw_annotation_items if _is_json_array(raw_annotation_items) else []
+        for annotation_index, annotation in enumerate(annotation_items):
             events.append(
-                openai_types.OutputTextAnnotationAddedEvent(
-                    type=openai_types.ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED,
-                    item_id=item_id,
-                    output_index=output_index,
-                    content_index=content_index,
-                    annotation_index=annotation_index,
-                    annotation=annotation,
+                openai_types.OutputTextAnnotationAddedEvent.model_validate(
+                    {
+                        "type": openai_types.ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED,
+                        "item_id": item_id,
+                        "output_index": output_index,
+                        "content_index": content_index,
+                        "annotation_index": annotation_index,
+                        "annotation": annotation,
+                    }
                 )
             )
         events.append(
@@ -1218,22 +1258,32 @@ def _add_text_like_part_events(
         )
 
 
-def _build_synthetic_response_events(
+def _stamp_responses_usage_cost(
+    response_obj: ResponsesAPIResponse | None, logging_obj: LiteLLMLoggingObj | None
+) -> None:
+    if response_obj is None or logging_obj is None:
+        return
+    usage_obj: Final[ResponseAPIUsage | None] = getattr(response_obj, "usage", None)
+    if usage_obj is None:
+        return
+    if isinstance(getattr(usage_obj, "cost", None), (int, float)):
+        return
+    try:
+        cost: Final[float | None] = logging_obj._response_cost_calculator(result=response_obj)
+    except Exception:
+        return
+    if isinstance(cost, (int, float)) and cost > 0:
+        setattr(usage_obj, "cost", cost)
+
+
+def build_synthetic_response_events(
     *,
     transformed: ResponsesAPIResponse,
-    logging_obj: LiteLLMLoggingObj,
+    logging_obj: LiteLLMLoggingObj | None,
     chunk_size: int,
 ) -> list[ResponsesAPIStreamingResponse]:
     openai_types: Final = _get_openai_response_types()
-    if litellm.include_cost_in_streaming_usage and logging_obj is not None:
-        usage_obj: Final = transformed.usage if hasattr(transformed, "usage") else None
-        if usage_obj is not None:
-            try:
-                cost: Final[float | None] = logging_obj._response_cost_calculator(result=transformed)
-                if cost is not None:
-                    setattr(usage_obj, "cost", cost)
-            except Exception:
-                pass
+    _stamp_responses_usage_cost(transformed, logging_obj)
 
     events: Final[list[ResponsesAPIStreamingResponse]] = [
         _build_response_status_event(openai_types.ResponsesAPIStreamEvents.RESPONSE_CREATED, transformed),
@@ -1256,7 +1306,7 @@ def _build_synthetic_response_events(
         )
 
         if item_type == "message":
-            content_parts: Sequence[object] = output_item_payload.get("content", []) or []
+            content_parts: Sequence[object] = _json_array_or_empty(output_item_payload.get("content"))
             for content_index, part in enumerate(content_parts):
                 part_payload = _dump_response_object(part)
                 events.append(
@@ -1304,7 +1354,7 @@ def _build_synthetic_response_events(
                 )
             )
         elif item_type == "reasoning":
-            summaries: Sequence[object] = output_item_payload.get("summary", []) or []
+            summaries: Sequence[object] = _json_array_or_empty(output_item_payload.get("summary"))
             for summary_index, summary in enumerate(summaries):
                 summary_payload = _dump_response_object(summary)
                 summary_text = str(summary_payload.get("text") or "")
@@ -1476,7 +1526,7 @@ class ResponsesWebSocketStreaming:
         user_api_key_dict: UserAPIKeyAuth | None = None,
         request_data: dict[str, object] | None = None,
         first_message: str | None = None,
-        guardrail_callbacks: list[PiiUnmaskingGuardrailCallback] | None = None,
+        guardrail_callbacks: Sequence[PresidioGuardrailCallback] | None = None,
         output_guardrail_callbacks: list[PresidioGuardrailCallback] | None = None,
         quota_callbacks: Sequence[ProjectQuotaCallback] | None = None,
         authorized_model: str | None = None,
@@ -1486,17 +1536,17 @@ class ResponsesWebSocketStreaming:
         self.logging_obj = logging_obj
         self.user_api_key_dict = user_api_key_dict
         self.request_data: dict[str, object] = request_data or {}
-        self.messages: list[dict[str, object]] = []
+        self.messages: list[_MutableJsonObject] = []
         self.input_messages: list[dict[str, object]] = []
         self.first_message = first_message
-        self.guardrail_callbacks: list[PiiUnmaskingGuardrailCallback] = guardrail_callbacks or []
+        self.guardrail_callbacks: Sequence[PresidioGuardrailCallback] = guardrail_callbacks or []
         self.output_guardrail_callbacks: list[PresidioGuardrailCallback] = output_guardrail_callbacks or []
         self.quota_callbacks: tuple[ProjectQuotaCallback, ...] = tuple(quota_callbacks) if quota_callbacks else ()
         # Model name authorized at connection time; enforced on every
         # response.create frame to prevent deployment-substitution attacks.
         self.authorized_model: str | None = authorized_model
 
-    def _should_store_event(self, event_obj: Mapping[str, object]) -> bool:
+    def _should_store_event(self, event_obj: _MutableJsonObject) -> bool:
         return event_obj.get("type") in RESPONSES_WS_LOGGED_EVENT_TYPES
 
     def _store_event(self, event: str | bytes | dict[str, object]) -> None:
@@ -1610,7 +1660,7 @@ class ResponsesWebSocketStreaming:
         finally:
             await self._log_messages()
 
-    def _enforce_authorized_model(self, msg_obj: dict[str, object]) -> bool:
+    def _enforce_authorized_model(self, msg_obj: _MutableJsonObject) -> bool:
         """
         Overwrite any ``model`` field in a ``response.create`` frame with the
         connection-authorized model to prevent deployment-substitution attacks.
@@ -1679,7 +1729,7 @@ class ResponsesWebSocketStreaming:
             # forwarded unmasked regardless of where the client places it.
             nested_candidate = msg_obj.get("response")
             nested_response = nested_candidate if _is_json_object(nested_candidate) else None
-            text_containers: list[tuple[dict[str, object], str]] = []
+            text_containers: list[tuple[_MutableJsonObject, str]] = []
             for container in (msg_obj, nested_response):
                 if container is None:
                     continue
@@ -1786,6 +1836,7 @@ class ResponsesWebSocketStreaming:
             return response_str
 
         cb: Final = self.guardrail_callbacks[0]
+        unmask_pii_text: Final[_UnmasksPiiText] = getattr(cb, _UNMASK_PII_TEXT_ATTR)
         event_type: Final = evt_obj.get("type")
 
         if event_type == "response.completed":
@@ -1805,9 +1856,7 @@ class ResponsesWebSocketStreaming:
                         continue
                     text = content_block.get("text")
                     if isinstance(text, str):
-                        unmasked = cb._unmask_pii_text(  # pyright: ignore[reportPrivateUsage]  # no public unmasker
-                            text, pii_tokens
-                        )
+                        unmasked = unmask_pii_text(text, pii_tokens)
                         if unmasked != text:
                             content_block["text"] = unmasked
                             modified = True
@@ -1816,9 +1865,7 @@ class ResponsesWebSocketStreaming:
         if event_type in self._DELTA_EVENT_TYPES:
             delta: Final = evt_obj.get("delta")
             if isinstance(delta, str):
-                unmasked = cb._unmask_pii_text(  # pyright: ignore[reportPrivateUsage]  # no public unmasker
-                    delta, pii_tokens
-                )
+                unmasked = unmask_pii_text(delta, pii_tokens)
                 if unmasked != delta:
                     evt_obj["delta"] = unmasked
                     return json.dumps(evt_obj)
@@ -2020,7 +2067,7 @@ class ManagedResponsesWebSocketHandler:
         model: str,
         logging_obj: LiteLLMLoggingObj,
         user_api_key_dict: UserAPIKeyAuth | None = None,
-        litellm_metadata: dict[str, Any] | None = None,
+        litellm_metadata: Mapping[str, object] | None = None,
         api_key: str | None = None,
         api_base: str | None = None,
         timeout: float | None = None,
@@ -2033,10 +2080,11 @@ class ManagedResponsesWebSocketHandler:
         self.model = model
         self.logging_obj = logging_obj
         self.user_api_key_dict = user_api_key_dict
-        self.litellm_metadata: dict[str, Any] = litellm_metadata or {}
-        self.model_group: str | None = self.litellm_metadata.get("model_group") or self.litellm_metadata.get(
+        self.litellm_metadata: Mapping[str, object] = litellm_metadata or {}
+        raw_model_group: Final = self.litellm_metadata.get("model_group") or self.litellm_metadata.get(
             "deployment_model_name"
         )
+        self.model_group: str | None = raw_model_group if isinstance(raw_model_group, str) else None
         self.api_key = api_key
         self.api_base = api_base
         self.timeout = timeout
@@ -2057,7 +2105,7 @@ class ManagedResponsesWebSocketHandler:
     # ------------------------------------------------------------------
 
     @staticmethod
-    def _serialize_chunk(chunk: Any) -> str | None:
+    def _serialize_chunk(chunk: object) -> str | None:
         """Serialize a streaming chunk to a JSON string for WebSocket transmission."""
         try:
             if isinstance(chunk, _HasModelDumpJson):
@@ -2100,7 +2148,7 @@ class ManagedResponsesWebSocketHandler:
         self._session_history[response_id] = messages
 
     @staticmethod
-    def _extract_response_id(completed_event: dict[str, object]) -> str | None:
+    def _extract_response_id(completed_event: _MutableJsonObject) -> str | None:
         """
         Pull the raw (decoded) response ID out of a ``response.completed`` event.
         Returns *None* if the event doesn't contain a usable ID.
@@ -2115,7 +2163,7 @@ class ManagedResponsesWebSocketHandler:
 
     @staticmethod
     def _extract_output_messages(
-        completed_event: dict[str, object],
+        completed_event: _MutableJsonObject,
     ) -> list[dict[str, object]]:
         """
         Convert the output items in a ``response.completed`` event into
@@ -2172,7 +2220,7 @@ class ManagedResponsesWebSocketHandler:
     # _process_response_create sub-methods
     # ------------------------------------------------------------------
 
-    async def _parse_message(self, raw_message: str) -> dict[str, object] | None:
+    async def _parse_message(self, raw_message: str) -> _MutableJsonObject | None:
         """Parse raw WS text; return the message dict or None (JSON error / ignored type)."""
         try:
             msg_obj: Final = _load_json_object(raw_message)
@@ -2185,7 +2233,7 @@ class ManagedResponsesWebSocketHandler:
         return msg_obj
 
     @staticmethod
-    def _is_warmup_frame(msg_obj: dict[str, object]) -> bool:
+    def _is_warmup_frame(msg_obj: _MutableJsonObject) -> bool:
         """Return True for a response.create whose generate flag is false."""
         nested: Final = msg_obj.get("response")
         source: Final = nested if _is_json_object(nested) and nested else msg_obj
@@ -2201,13 +2249,13 @@ class ManagedResponsesWebSocketHandler:
         return str(raw_id).startswith(_WARMUP_RESPONSE_ID_PREFIX)
 
     @staticmethod
-    def _warmup_source_params(msg_obj: dict[str, object]) -> dict[str, object]:
+    def _warmup_source_params(msg_obj: _MutableJsonObject) -> dict[str, object]:
         nested: Final = msg_obj.get("response")
         if _is_json_object(nested) and nested:
             return nested
         return {k: v for k, v in msg_obj.items() if k != "type"}
 
-    def _build_warmup_response(self, msg_obj: dict[str, object]) -> dict[str, object]:
+    def _build_warmup_response(self, msg_obj: _MutableJsonObject) -> dict[str, object]:
         """Build a minimal completed Responses API object for a warmup ack."""
         source: Final = self._warmup_source_params(msg_obj)
         wire_model: Final = source.get("model") or self.model_group or self.model
@@ -2225,7 +2273,7 @@ class ManagedResponsesWebSocketHandler:
             },
         }
 
-    async def _send_warmup_ack(self, msg_obj: dict[str, object]) -> None:
+    async def _send_warmup_ack(self, msg_obj: _MutableJsonObject) -> None:
         """
         Acknowledge a generate=false prewarm without calling the provider.
 
@@ -2248,7 +2296,7 @@ class ManagedResponsesWebSocketHandler:
             await self.websocket.send_text(serialized)
 
     @staticmethod
-    def _build_base_call_kwargs(msg_obj: dict[str, object]) -> dict[str, Any]:
+    def _build_base_call_kwargs(msg_obj: _MutableJsonObject) -> dict[str, Any]:
         """
         Extract Responses API params from the event, handling both wire formats:
           Nested: {"type": "response.create", "response": {"input": [...], ...}}
@@ -2357,7 +2405,7 @@ class ManagedResponsesWebSocketHandler:
         call_kwargs.setdefault("litellm_params", {})
         call_kwargs["litellm_params"]["proxy_server_request"] = proxy_server_request
 
-    async def _stream_and_forward(self, model: str, call_kwargs: dict[str, Any]) -> dict[str, object] | None:
+    async def _stream_and_forward(self, model: str, call_kwargs: dict[str, Any]) -> _MutableJsonObject | None:
         """
         Stream ``litellm.aresponses`` and forward every chunk over the WebSocket.
 
@@ -2365,7 +2413,7 @@ class ManagedResponsesWebSocketHandler:
         directly (before serialization) to avoid a redundant JSON round-trip on
         every chunk.  Returns the completed event dict, or ``None``.
         """
-        completed_event: dict[str, object] | None = (
+        completed_event: _MutableJsonObject | None = (
             None  # rebind-ok: captures the completed event once the stream yields it
         )
         stream_response: Final = await litellm.aresponses(model=model, **call_kwargs)
@@ -2391,7 +2439,7 @@ class ManagedResponsesWebSocketHandler:
 
     def _save_turn_history(
         self,
-        completed_event: dict[str, object] | None,
+        completed_event: _MutableJsonObject | None,
         prior_history: list[dict[str, object]],
         current_messages: list[dict[str, object]],
     ) -> None:
@@ -2464,12 +2512,12 @@ class ManagedResponsesWebSocketHandler:
         # reuse the router-resolved self.model; passing the alias raw to
         # litellm.aresponses fails in get_llm_provider. A genuinely different
         # provider-prefixed per-frame model is still honored.
-        requested_model: Final[str | None] = call_kwargs.pop("model", None)
+        requested_model: Final[str | None] = _optional_str(call_kwargs.pop("model", None))
         model: Final[str] = (
             self.model if requested_model is None or requested_model == self.model_group else requested_model
         )
 
-        previous_response_id: Final[str | None] = call_kwargs.pop("previous_response_id", None)
+        previous_response_id: Final[str | None] = _optional_str(call_kwargs.pop("previous_response_id", None))
         current_messages: Final = self._input_to_messages(call_kwargs.get("input"))
 
         # Fetch history once; reused in both _apply_history and _save_turn_history
diff --git a/litellm/router.py b/litellm/router.py
index c93c1753f0e..f9a0253520f 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -22,7 +22,7 @@ import traceback
 import weakref
 from collections import defaultdict
 from collections.abc import AsyncGenerator, AsyncIterator, Callable, Generator, Mapping, Sequence
-from functools import lru_cache
+from functools import lru_cache, partial
 from types import MappingProxyType
 from typing import TYPE_CHECKING, Any, Final, Literal, Optional, TypeAlias, TypeVar, Union, cast
 
@@ -30,7 +30,7 @@ import anyio
 import httpx
 import openai
 from openai import AsyncOpenAI
-from pydantic import BaseModel
+from pydantic import BaseModel, TypeAdapter, ValidationError
 from typing_extensions import overload
 
 import litellm
@@ -50,6 +50,7 @@ from litellm.constants import (
     DEFAULT_HEALTH_CHECK_INTERVAL,
     DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER,
     DEFAULT_MAX_LRU_CACHE_SIZE,
+    RUNTIME_UPDATABLE_ROUTER_SETTINGS,
     SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY,
 )
 from litellm.integrations.custom_logger import CustomLogger
@@ -143,7 +144,11 @@ from litellm.router_utils.cooldown_handlers import (
 from litellm.router_utils.fallback_event_handlers import (
     AttemptedFallbackTargets,
     _check_non_standard_fallback_format,
-    get_fallback_model_group,
+    clear_pre_routing_selection,
+    fallback_lookup_groups,
+    get_fallback_model_group_for_lookup_groups,
+    get_pre_routing_selection,
+    record_pre_routing_selection,
     run_async_fallback,
 )
 from litellm.router_utils.get_retry_from_policy import (
@@ -349,6 +354,15 @@ _PreRoutingStrategyT = TypeVar("_PreRoutingStrategyT")
 
 _ALIAS_PARAMS_NEVER_FORWARDED: Final = frozenset({"model", "api_base", "api_key", "api_version"})
 _ALIAS_MARKER_FORWARDED_PARAMS_KWARG: Final = "_alias_marker_forwarded_params"
+_CLAUDE_CODE_SESSION_ID_RE: Final = re.compile(r"^[a-zA-Z0-9_\-]{8,}$")
+_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS: Final = 3600
+
+_RUNTIME_TOGGLEABLE_PRE_CALL_CHECKS: Final[Mapping[str, type[CustomLogger]]] = MappingProxyType(
+    {
+        "prompt_caching": PromptCachingDeploymentCheck,
+        "enforce_model_rate_limits": ModelRateLimitingCheck,
+    }
+)
 
 
 def _stream_chunks_have_generated_content(chunks: Sequence[ModelResponseStream]) -> bool:
@@ -371,6 +385,28 @@ def _stream_chunks_have_generated_content(chunks: Sequence[ModelResponseStream])
     return False
 
 
+_NO_SESSION_KWARGS: Final[Mapping[str, Mapping[str, object]]] = MappingProxyType({})
+_SESSION_ADAPTER: Final = TypeAdapter(Mapping[str, object])
+
+
+def _with_router_resolved_session_model(session: object, model_name: str) -> Mapping[str, Mapping[str, object]]:
+    """
+    Realtime client-secret requests carry the model inside ``session`` as well, and the caller's copy of it still
+    holds the pre-routing model group name, so it has to follow the deployment the router just picked.
+
+    Returns kwargs to merge into the downstream call, empty when there is no session model to resolve.
+    """
+    try:
+        typed_session: Final = _SESSION_ADAPTER.validate_python(session)
+    except ValidationError:
+        return _NO_SESSION_KWARGS
+    if "model" not in typed_session:
+        return _NO_SESSION_KWARGS
+    return MappingProxyType(
+        {"session": {**typed_session, "model": model_name}}  # mutable-ok: callees deepcopy and JSON-dump session
+    )
+
+
 # Router._aanthropic_messages_streaming_iterator buffers lifecycle chunks
 # until real content commits the primary stream; a hostile or slow-starting
 # upstream that never emits content or an error could otherwise grow that
@@ -776,6 +812,10 @@ class Router:
         self.cache = DualCache(
             redis_cache=redis_cache, in_memory_cache=InMemoryCache()
         )  # use a dual cache (Redis+In-Memory) for tracking cooldowns, usage, etc.
+        self._claude_code_session_router_cache: DualCache = DualCache(
+            redis_cache=redis_cache,
+            in_memory_cache=InMemoryCache(),
+        )
 
         ### SCHEDULER ###
         self.scheduler = Scheduler(polling_interval=polling_interval, redis_cache=redis_cache)
@@ -821,6 +861,7 @@ class Router:
         self._zero_cost_cache: dict[str, bool] = {}
         self._routing_group_rows: tuple[DeploymentTypedDict, ...] | None = None
         self._init_routing_groups(None)
+        self._provider_unresolved_deployments: tuple[Callable[[], Deployment | None], ...] = ()
 
         self.deployment_affinity_ttl_seconds = deployment_affinity_ttl_seconds
         self.model_group_affinity_config = model_group_affinity_config
@@ -1096,8 +1137,8 @@ class Router:
         ```
         and caching to just work.
         """
-        if self.cache.redis_cache is None:
-            self.cache.redis_cache = cache
+        self.cache.attach_redis_cache(cache)
+        self._claude_code_session_router_cache.attach_redis_cache(cache)
 
     # Maps a routing strategy string to the attribute on `self` that holds
     # the default group's strategy selector for that strategy. (The selectors
@@ -2067,11 +2108,39 @@ class Router:
             if _callback is None:
                 continue
 
+            if self.optional_callbacks is not None and any(
+                isinstance(callback, type(_callback)) for callback in self.optional_callbacks
+            ):
+                continue
             if self.optional_callbacks is None:
                 self.optional_callbacks = []
             self.optional_callbacks.append(_callback)
             litellm.logging_callback_manager.add_litellm_callback(_callback)
 
+    def set_optional_pre_call_checks(self, optional_pre_call_checks: OptionalPreCallChecks | None) -> None:
+        if optional_pre_call_checks is None:
+            return
+        requested: Final = frozenset(optional_pre_call_checks)
+        for name, callback_cls in _RUNTIME_TOGGLEABLE_PRE_CALL_CHECKS.items():
+            if name not in requested:
+                self._remove_optional_callbacks_of_type(callback_cls)
+        self.add_optional_pre_call_checks(optional_pre_call_checks)
+
+    def _remove_optional_callbacks_of_type(self, callback_cls: type[CustomLogger]) -> None:
+        if self.optional_callbacks is None or not any(type(cb) is callback_cls for cb in self.optional_callbacks):
+            return
+        self.optional_callbacks = [cb for cb in self.optional_callbacks if type(cb) is not callback_cls]
+        if any(
+            router is not self and any(type(cb) is callback_cls for cb in (router.optional_callbacks or []))
+            for router in tuple(_live_routers)
+        ):
+            return
+        for cb in tuple(litellm.callbacks):
+            if type(cb) is callback_cls:
+                litellm.logging_callback_manager.remove_callback_from_list_by_object(
+                    litellm.callbacks, cb, require_self=False
+                )
+
     def print_deployment(self, deployment: dict):
         """
         returns a copy of the deployment with the api key masked
@@ -2319,7 +2388,7 @@ class Router:
     @overload
     async def acompletion(
         self, model: str, messages: list[AllMessageValues], stream: Literal[True, False] = False, **kwargs
-    ) -> CustomStreamWrapper | ModelResponse: 
+    ) -> CustomStreamWrapper | ModelResponse:
         ...
 
     # fmt: on
@@ -4002,6 +4071,7 @@ class Router:
             prompt_variables=prompt_variables,
             prompt_label=prompt_label,
             request_kwargs=kwargs,
+            injected_for_every_deployment=True,
         )
 
         # Filter out prompt management specific parameters from data before merging
@@ -4889,6 +4959,7 @@ class Router:
                 "caching": self.cache_responses,
                 **kwargs,
                 "model": model_name,
+                **_with_router_resolved_session_model(kwargs.get("session"), model_name),
             }
             # Only set custom_llm_provider if it's not None
             if custom_llm_provider is not None:
@@ -4918,6 +4989,19 @@ class Router:
                 )
                 response = await response
 
+            if self._should_raise_anthropic_refusal_error(
+                model=model,
+                original_generic_function=original_generic_function,
+                response=response,
+                kwargs=kwargs,
+            ):
+                from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+                    safeguard_refusal_error,
+                )
+
+                refusal_details: Final = cast(dict, response["stop_details"])  # cast-ok: gate verified the shape
+                raise safeguard_refusal_error(model=model, stop_details=refusal_details)
+
             self.success_calls[model_name] += 1
             verbose_router_logger.info("ageneric_api_call_with_fallbacks(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -4964,6 +5048,11 @@ class Router:
         # fallback to the original reference for any non-picklable value.
         # The original_generic_function is preserved so the per-attempt
         # helper knows which underlying API to call on fallback.
+        # The pre-routing hook stamps its tier selection into this bucket during the primary
+        # attempt; seeding it before the snapshot gives both the live kwargs and the copy a
+        # bucket, so the post-call carry-over below always has somewhere to read and write.
+        kwargs.setdefault("litellm_metadata", {})  # mutable-ok: shared bucket  # rebind-ok: stamp must be readable here
+
         fallback_kwargs: Final[dict[str, object]] = kwargs.copy()
         if isinstance(fallback_kwargs.get("litellm_metadata"), dict):
             fallback_kwargs["litellm_metadata"] = safe_deep_copy(fallback_kwargs["litellm_metadata"])
@@ -4973,6 +5062,14 @@ class Router:
 
         response: Final = await self._ageneric_api_call_with_fallbacks(original_function=original_function, **kwargs)
 
+        # The snapshot predates the pre-routing hook, so the tier it stamped into the live kwargs
+        # is carried over write-or-clear: a stale or caller-supplied selection left in the copy
+        # would key the mid-stream fallback lookup off a tier this attempt never routed to.
+        clear_pre_routing_selection(fallback_kwargs)
+        live_pre_routing_selection: Final = get_pre_routing_selection(kwargs)
+        if live_pre_routing_selection is not None:
+            record_pre_routing_selection(fallback_kwargs, live_pre_routing_selection)
+
         if kwargs.get("stream") and isinstance(response, BaseResponsesAPIStreamingIterator):
             return await self._aresponses_streaming_iterator(
                 response=response,
@@ -5030,6 +5127,10 @@ class Router:
         from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
             aclose_if_supported,
             parse_anthropic_error_event,
+            parse_anthropic_refusal_stop_details,
+        )
+        from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+            safeguard_refusal_error,
         )
 
         source_iterator: Final = response
@@ -5068,13 +5169,35 @@ class Router:
                         continue
                     if _anthropic_stream_commits_now(chunk, has_generated_content, len(buffered_lifecycle_chunks)):
                         has_generated_content = True  # rebind-ok: real content seen, or the buffer cap was hit
-                    error_event = parse_anthropic_error_event(chunk)
+                    # A transport can split one SSE data line across byte chunks, so pre-content
+                    # detection parses the accumulated buffer plus the current chunk, never the
+                    # chunk alone; the buffer is already capped, which bounds this window too.
+                    parse_window = (  # rebind-ok: freshly computed each iteration, never carried over
+                        b"".join(c for c in (*buffered_lifecycle_chunks, chunk) if isinstance(c, (bytes, bytearray)))  # pyright: ignore[reportUnnecessaryIsInstance]  # bridge-path chunks are not always bytes at runtime
+                        if not has_generated_content and isinstance(chunk, (bytes, bytearray))  # pyright: ignore[reportUnnecessaryIsInstance]  # bridge-path chunks are not always bytes at runtime
+                        else chunk
+                    )
+                    error_event = parse_anthropic_error_event(parse_window)
                     retriable_pending_error = (  # rebind-ok: freshly computed each iteration, never carried over
                         not has_generated_content
                         and error_event is not None
                         and _is_retriable_anthropic_status(error_event[2])
                         and not _anthropic_stream_error_is_gateway_verdict(chunk)
                     )
+                    refusal_stop_details = (  # rebind-ok: freshly computed each iteration, never carried over
+                        parse_anthropic_refusal_stop_details(parse_window)
+                        if not has_generated_content and error_event is None
+                        else None
+                    )
+                    if refusal_stop_details is not None and self._has_content_policy_fallback(model, initial_kwargs):
+                        refusal_error = safeguard_refusal_error(model=model, stop_details=refusal_stop_details)
+                        raise MidStreamFallbackError(
+                            message=refusal_error.message,
+                            model=model,
+                            llm_provider="anthropic",
+                            original_exception=refusal_error,
+                            is_pre_first_chunk=True,
+                        )
                     if not has_generated_content and not retriable_pending_error and error_event is None:
                         buffered_lifecycle_chunks = (*buffered_lifecycle_chunks, chunk)
                         continue
@@ -5186,8 +5309,13 @@ class Router:
                 kwargs=initial_kwargs,
                 metadata_variable_name="litellm_metadata",
             )
+            # The content-policy dispatch branch matches on the trigger's own type, so a refusal's
+            # MidStreamFallbackError envelope is unwrapped here or the wrong fallback list is consulted.
+            fallback_trigger: Final[Exception] = (
+                e.original_exception if isinstance(e.original_exception, litellm.ContentPolicyViolationError) else e
+            )
             fallback_response = await self.async_function_with_fallbacks_common_utils(  # rebind-ok: set on success
-                e=e,
+                e=fallback_trigger,
                 disable_fallbacks=False,
                 fallbacks=fallbacks,
                 context_window_fallbacks=context_window_fallbacks,
@@ -5243,6 +5371,11 @@ class Router:
         # share, leaking primary-deployment metadata into the mid-stream
         # fallback request. safe_deep_copy avoids deep-copying the full
         # kwargs (which can hold non-deepcopyable logging handles/clients).
+        # The pre-routing hook stamps its tier selection into this bucket during the primary
+        # attempt; seeding it before the snapshot gives both the live kwargs and the copy a
+        # bucket, so the post-call carry-over below always has somewhere to read and write.
+        kwargs.setdefault("litellm_metadata", {})  # mutable-ok: shared bucket  # rebind-ok: stamp must be readable here
+
         fallback_kwargs: Final[dict[str, object]] = kwargs.copy()  # mutable-ok: mutated below before re-entry
         if isinstance(fallback_kwargs.get("litellm_metadata"), dict):
             fallback_kwargs["litellm_metadata"] = safe_deep_copy(fallback_kwargs["litellm_metadata"])
@@ -5252,6 +5385,14 @@ class Router:
 
         response: Final = await self._ageneric_api_call_with_fallbacks(original_function=original_function, **kwargs)
 
+        # The snapshot predates the pre-routing hook, so the tier it stamped into the live kwargs
+        # is carried over write-or-clear: a stale or caller-supplied selection left in the copy
+        # would key the mid-stream fallback lookup off a tier this attempt never routed to.
+        clear_pre_routing_selection(fallback_kwargs)
+        live_pre_routing_selection: Final = get_pre_routing_selection(kwargs)
+        if live_pre_routing_selection is not None:
+            record_pre_routing_selection(fallback_kwargs, live_pre_routing_selection)
+
         if kwargs.get("stream") and hasattr(response, "__aiter__"):
             return await self._aanthropic_messages_streaming_iterator(
                 response=cast("AsyncIterator[bytes]", response),  # cast-ok: stream=True always returns a byte iterator
@@ -6299,8 +6440,6 @@ class Router:
             "responses",
             "generate_content",
             "generate_content_stream",
-            "vector_store_search",
-            "vector_store_create",
             "ocr",
             "search",
             "video_generation",
@@ -6324,6 +6463,8 @@ class Router:
             return sync_wrapper
 
         if call_type in (
+            "vector_store_search",
+            "vector_store_create",
             "vector_store_retrieve",
             "vector_store_list",
             "vector_store_update",
@@ -6335,11 +6476,16 @@ class Router:
                 client: object | None = None,
                 **kwargs,
             ):
-                if custom_llm_provider and "custom_llm_provider" not in kwargs:
-                    kwargs["custom_llm_provider"] = custom_llm_provider
-                if kwargs.get("model"):
-                    return self._generic_api_call_with_fallbacks(original_function=original_function, **kwargs)
-                return original_function(**kwargs)
+                provider_kwargs: Final = (
+                    MappingProxyType({**kwargs, "custom_llm_provider": custom_llm_provider})
+                    if custom_llm_provider and "custom_llm_provider" not in kwargs
+                    else MappingProxyType(kwargs)
+                )
+                if provider_kwargs.get("model"):
+                    return self._generic_api_call_with_fallbacks(original_function=original_function, **provider_kwargs)
+                if call_type == "vector_store_search":
+                    return original_function(**MappingProxyType({**provider_kwargs, "router": self}))
+                return original_function(**provider_kwargs)
 
             return vector_store_sync_wrapper
 
@@ -6486,6 +6632,8 @@ class Router:
                     **kwargs,
                 )
             elif call_type == "allm_passthrough_route":
+                if client:
+                    kwargs["client"] = client
                 return await self._ageneric_api_call_with_fallbacks(
                     original_function=original_function,
                     passthrough_on_no_deployment=True,
@@ -6513,6 +6661,7 @@ class Router:
                 return await self._init_vector_store_api_endpoints(
                     original_function=original_function,
                     custom_llm_provider=custom_llm_provider,
+                    call_type=call_type,
                     **kwargs,
                 )
             elif call_type in ("afile_delete", "afile_content"):
@@ -6553,6 +6702,7 @@ class Router:
         self,
         original_function: Callable,
         custom_llm_provider: str | None = None,
+        call_type: str | None = None,
         **kwargs,
     ):
         """
@@ -6571,6 +6721,13 @@ class Router:
                 **kwargs,
             )
 
+        # For search, pass the router so provider transforms can resolve
+        # router-managed embedding models (e.g. S3 Vectors query embeddings).
+        # The merge also overrides any client-supplied `router` key.
+        if call_type == "avector_store_search":
+            search_kwargs: Final = MappingProxyType({**kwargs, "router": self})
+            return await original_function(**search_kwargs)
+
         # Otherwise, call the original function directly
         return await original_function(**kwargs)
 
@@ -6587,7 +6744,10 @@ class Router:
         metadata. When present, decode the ID, replace ``container_id`` with the
         upstream value, and route through ``_ageneric_api_call_with_fallbacks`` so
         deployment credentials (e.g. regional ``api_base`` for Azure) match
-        :meth:`_init_responses_api_endpoints`. Otherwise call the handler directly.
+        :meth:`_init_responses_api_endpoints`. Create/list calls carry no container ID, so
+        they route through the deployment named by ``model`` when the caller passes one,
+        falling back to the direct call when no deployment matches. Otherwise call the
+        handler directly with global provider credentials.
         """
         if custom_llm_provider and "custom_llm_provider" not in kwargs:
             kwargs["custom_llm_provider"] = custom_llm_provider
@@ -6619,6 +6779,14 @@ class Router:
                     **kwargs,
                 )
 
+        requested_model: Final = kwargs.get("model")
+        if isinstance(requested_model, str) and requested_model.strip():
+            return await self._ageneric_api_call_with_fallbacks(
+                original_function=original_function,
+                passthrough_on_no_deployment=True,
+                **kwargs,
+            )
+
         return await original_function(**kwargs)
 
     async def _init_responses_api_endpoints(
@@ -6805,6 +6973,9 @@ class Router:
         original_exception: Final = e
         fallback_model_group = None
         original_model_group: Final[str | None] = kwargs.get("model")
+        # A pre-routing hook (complexity / auto / adaptive / quality routers) picks a tier
+        # behind the router name, and fallbacks are configured per tier, not per router.
+        lookup_groups: Final[tuple[str, ...]] = fallback_lookup_groups(kwargs, model_group)
         fallback_failure_exception_str = ""
 
         if disable_fallbacks is True or original_model_group is None:
@@ -6849,15 +7020,15 @@ class Router:
             ]
             # Get external fallbacks — handle both standard and non-standard formats
             external_fallback_group: list | None = None
-            if fallbacks is not None and model_group is not None:
+            if fallbacks is not None and lookup_groups:
                 if _check_non_standard_fallback_format(fallbacks=fallbacks):
                     # Non-standard formats (e.g. ["claude-3-haiku"] or
                     # [{"model": "...", "messages": [...]}]) are passed through directly
                     external_fallback_group = fallbacks
                 else:
-                    external_fallback_group, generic_idx = get_fallback_model_group(
+                    external_fallback_group, generic_idx = get_fallback_model_group_for_lookup_groups(
                         fallbacks=fallbacks,
-                        model_group=cast(str, model_group),
+                        lookup_groups=lookup_groups,
                     )
                     if external_fallback_group is None and generic_idx is not None:
                         external_fallback_group = fallbacks[generic_idx]["*"]
@@ -6915,9 +7086,9 @@ class Router:
             if isinstance(e, litellm.ContextWindowExceededError):
                 if context_window_fallbacks is not None:
                     context_window_fallback_model_group: Final[list[str] | None] = (
-                        self._get_fallback_model_group_from_fallbacks(
+                        self._get_fallback_model_group_for_lookup_groups(
                             fallbacks=context_window_fallbacks,
-                            model_group=model_group,
+                            lookup_groups=lookup_groups,
                         )
                     )
                     if context_window_fallback_model_group is None:
@@ -6948,9 +7119,9 @@ class Router:
             elif isinstance(e, litellm.ContentPolicyViolationError):
                 if content_policy_fallbacks is not None:
                     content_policy_fallback_model_group: Final[list[str] | None] = (
-                        self._get_fallback_model_group_from_fallbacks(
+                        self._get_fallback_model_group_for_lookup_groups(
                             fallbacks=content_policy_fallbacks,
-                            model_group=model_group,
+                            lookup_groups=lookup_groups,
                         )
                     )
                     if content_policy_fallback_model_group is None:
@@ -6977,14 +7148,14 @@ class Router:
 
                     if litellm.expose_router_debug_in_errors:
                         e.message += f"\n{error_message}"
-            if fallbacks is not None and model_group is not None:
+            if fallbacks is not None and lookup_groups:
                 verbose_router_logger.debug("inside model fallbacks: %s", mask_sensitive_structure(fallbacks))
                 (
                     fallback_model_group,
                     generic_fallback_idx,
-                ) = get_fallback_model_group(
+                ) = get_fallback_model_group_for_lookup_groups(
                     fallbacks=fallbacks,  # if fallbacks = [{"gpt-3.5-turbo": ["claude-3-haiku"]}]
-                    model_group=cast(str, model_group),
+                    lookup_groups=lookup_groups,
                 )
                 ## if none, check for generic fallback
                 if fallback_model_group is None and generic_fallback_idx is not None:
@@ -6993,12 +7164,12 @@ class Router:
                 if fallback_model_group is None:
                     masked_fallbacks: Final = mask_sensitive_structure(fallbacks)
                     verbose_router_logger.info(
-                        "No fallback model group found for original model_group=%s. Fallbacks=%s",
-                        model_group,
+                        "No fallback model group found for lookup_groups=%s. Fallbacks=%s",
+                        " -> ".join(lookup_groups),
                         masked_fallbacks,
                     )
                     if hasattr(original_exception, "message") and litellm.expose_router_debug_in_errors:
-                        original_exception.message += f"No fallback model group found for original model_group={model_group}. Fallbacks={masked_fallbacks}"
+                        original_exception.message += f"No fallback model group found for lookup_groups={' -> '.join(lookup_groups)}. Fallbacks={masked_fallbacks}"
                     raise original_exception
 
                 input_kwargs.update(
@@ -7044,6 +7215,7 @@ class Router:
         If it fails after num_retries, fall back to another model group
         """
         model_group: Final[str | None] = kwargs.get("model")
+        clear_pre_routing_selection(kwargs)  # pyright: ignore[reportUnknownArgumentType]  # **kwargs is untyped at this boundary
         if not isinstance(kwargs.get("attempted_targets"), AttemptedFallbackTargets):
             _fallback_metadata_key: Final = _get_router_metadata_variable_name(
                 function_name=getattr(kwargs.get("original_function"), "__name__", None)
@@ -7469,6 +7641,24 @@ class Router:
                 break
         return fallback_model_group
 
+    def _get_fallback_model_group_for_lookup_groups(
+        self,
+        fallbacks: list[dict[str, list[str]]],  # mutable-ok: mirrors the sibling resolver's contract
+        lookup_groups: tuple[str, ...],
+    ) -> list[str] | None:  # mutable-ok: mirrors the sibling resolver's contract
+        """First lookup group whose exact-key chain resolves (tier first, then requested group)."""
+        return next(
+            (
+                resolved
+                for resolved in (
+                    self._get_fallback_model_group_from_fallbacks(fallbacks=fallbacks, model_group=group)
+                    for group in lookup_groups
+                )
+                if resolved is not None
+            ),
+            None,
+        )
+
     def _get_first_default_fallback(self) -> str | None:
         """
         Returns the first model from the default_fallbacks list, if it exists.
@@ -7884,6 +8074,31 @@ class Router:
                     return True
         return False
 
+    def _has_content_policy_fallback(self, model_group: str, kwargs: Mapping[str, Any]) -> bool:
+        """
+        Whether a content-policy fallback would resolve for this request, keyed the same way
+        async_function_with_fallbacks_common_utils resolves it: the tier a pre-routing hook
+        selected wins over the requested group. Raising without this returning True would turn
+        a deliverable response into an error the fallback chain cannot recover from.
+        """
+        content_policy_fallbacks: Final = kwargs.get("content_policy_fallbacks", self.content_policy_fallbacks)
+        if content_policy_fallbacks is not None:
+            return (
+                self._get_fallback_model_group_for_lookup_groups(
+                    fallbacks=content_policy_fallbacks,
+                    lookup_groups=fallback_lookup_groups(kwargs, model_group),
+                )
+                is not None
+            )
+        if self._has_default_fallbacks():
+            return True
+        verbose_router_logger.debug(
+            "No content-policy fallback available. Returning original response. model=%s, content_policy_fallbacks=%s",
+            model_group,
+            content_policy_fallbacks,
+        )
+        return False
+
     def _should_raise_content_policy_error(self, model: str, response: ModelResponse, kwargs: dict) -> bool:
         """
         Determines if a content policy error should be raised.
@@ -7896,27 +8111,26 @@ class Router:
             if response.choices[0].finish_reason != "content_filter":
                 return False
 
-        content_policy_fallbacks: Final = kwargs.get("content_policy_fallbacks", self.content_policy_fallbacks)
+        return self._has_content_policy_fallback(model, kwargs)
 
-        ### ONLY RAISE ERROR IF CP FALLBACK AVAILABLE ###
-        if content_policy_fallbacks is not None:
-            fallback_model_group = None
-            for item in content_policy_fallbacks:  # [{"gpt-3.5-turbo": ["gpt-4"]}]
-                if list(item.keys())[0] == model:
-                    fallback_model_group = item[model]
-                    break
-
-            if fallback_model_group is not None:
-                return True
-        elif self._has_default_fallbacks():  # default fallbacks set
-            return True
-
-        verbose_router_logger.debug(
-            "Content Policy Error occurred. No available fallbacks. Returning original response. model=%s, content_policy_fallbacks=%s",
-            model,
-            content_policy_fallbacks,
+    def _should_raise_anthropic_refusal_error(
+        self, model: str, original_generic_function: Callable, response: object, kwargs: Mapping[str, Any]
+    ) -> bool:
+        """
+        The /v1/messages twin of _should_raise_content_policy_error: an Anthropic safeguard
+        refusal (stop_reason "refusal" carrying stop_details) re-enters the fallback chain only
+        when a content-policy fallback is configured; a plain refusal without stop_details, or
+        any response with nothing configured, is returned to the client unchanged.
+        """
+        from litellm.llms.anthropic.experimental_pass_through.messages.utils import (
+            get_safeguard_refusal_stop_details,
         )
-        return False
+
+        if getattr(original_generic_function, "__name__", "") != "anthropic_messages":
+            return False
+        if get_safeguard_refusal_stop_details(response) is None:
+            return False
+        return self._has_content_policy_fallback(model, kwargs)
 
     def _get_healthy_deployments(self, model: str, parent_otel_span: Span | None):
         _all_deployments: list = []
@@ -8163,6 +8377,52 @@ class Router:
                 if backend_value is not None:
                     model_info[field] = backend_value
 
+    @staticmethod
+    def _inherit_builtin_base_rates_for_off_peak(
+        model_info: dict,  # mutable-ok: cost-map entry filled in place
+        backend_model: str,
+        custom_llm_provider: str | None,
+    ) -> None:
+        """Fill missing pricing fields on a deployment entry that only sets
+        ``off_peak_pricing``, from the backend model's built-in cost map entry.
+
+        Cost lookup selects the deployment-scoped entry over the shared backend
+        entry only when the deployment entry carries a base pricing field, and
+        ``off_peak_pricing`` is deliberately kept off the shared entry, so a
+        deployment spelling out only its off-peak schedule would otherwise
+        never receive the discount. The backend model's entire canonical cost
+        map entry is copied, field by field, so threshold, tiered,
+        service-tier, cache, character, and per-second rates as well as
+        companion billing fields like ``web_search_billing_unit`` and the
+        regional uplift multipliers all carry over, and peak-hour billing
+        through the deployment entry matches the shared backend entry exactly.
+        The raw ``litellm.model_cost`` entry is the copy source rather than
+        ``get_model_info``'s view of it, since that view synthesizes zero flat
+        token rates for backends without one and storing those would mark a
+        tiered-only backend explicitly priced free. Values are deep-copied to
+        keep the builtin entry isolated. User-specified fields always win;
+        no-op when any base pricing field is already set or the backend model
+        has no canonical entry.
+        """
+        if not model_info.get("off_peak_pricing"):
+            return
+        if any(
+            model_info.get(field) is not None
+            for field in ("input_cost_per_token", "input_cost_per_second", "tiered_pricing")
+        ):
+            return
+        try:
+            backend_info: Final = litellm.get_model_info(model=backend_model, custom_llm_provider=custom_llm_provider)
+        except Exception:  # noqa: BLE001  # get_model_info raises plain Exception for an unmapped backend model
+            return
+        backend_entry: Final = litellm.model_cost.get(backend_info.get("key") or "")
+        if not isinstance(backend_entry, dict):
+            return
+        for field, backend_value in backend_entry.items():
+            if model_info.get(field) is not None or backend_value is None:
+                continue
+            model_info[field] = copy.deepcopy(backend_value)
+
     @staticmethod
     def _inherit_builtin_tiered_output_rate(
         model_info: dict, backend_model: str, custom_llm_provider: str | None
@@ -8251,6 +8511,11 @@ class Router:
                 if deployment.litellm_params.get(field) is not None:
                     _model_info[field] = deployment.litellm_params[field]
 
+            Router._inherit_builtin_base_rates_for_off_peak(
+                model_info=_model_info,
+                backend_model=deployment.litellm_params.model,
+                custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+            )
             if _model_info.get("input_cost_per_token") is not None:
                 Router._inherit_builtin_cache_pricing(
                     model_info=_model_info,
@@ -8299,6 +8564,19 @@ class Router:
             return deployment
         except Exception as e:
             if self.ignore_invalid_deployments:
+                if isinstance(e, litellm.BadRequestError):
+                    self._provider_unresolved_deployments = (
+                        *self._provider_unresolved_deployments,
+                        partial(
+                            self._create_deployment,
+                            deployment_info=deployment_info,
+                            _model_name=_model_name,
+                            _litellm_params=_litellm_params,
+                            _model_info=_model_info,
+                            declared_id=declared_id,
+                            duplicate_ids=duplicate_ids,
+                        ),
+                    )
                 verbose_router_logger.exception(
                     "Error creating deployment: %s, ignoring and continuing with other deployments.", e
                 )
@@ -8728,6 +9006,7 @@ class Router:
         self.quality_routers = {}
         self.complexity_routers = {}
         self.auto_routers = {}
+        self._provider_unresolved_deployments = ()
         self._invalidate_model_group_info_cache()
         self._invalidate_access_groups_cache()
         # we add api_base/api_key each model so load balancing between azure/gpt on api_base1 and api_base2 works
@@ -8992,6 +9271,11 @@ class Router:
             if field_value is not None:
                 _model_info_dict[field] = field_value
 
+        Router._inherit_builtin_base_rates_for_off_peak(
+            model_info=_model_info_dict,
+            backend_model=deployment.litellm_params.model,
+            custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+        )
         if _model_info_dict.get("input_cost_per_token") is not None:
             Router._inherit_builtin_cache_pricing(
                 model_info=_model_info_dict,
@@ -9152,7 +9436,8 @@ class Router:
             if _deployment_on_router is not None:
                 # deployment with this model_id exists on the router
                 if (
-                    deployment.litellm_params == _deployment_on_router.litellm_params
+                    deployment.model_name == _deployment_on_router.model_name
+                    and deployment.litellm_params == _deployment_on_router.litellm_params
                     and deployment.model_info == _deployment_on_router.model_info
                 ):
                     # No need to update
@@ -9246,6 +9531,11 @@ class Router:
             field_value = deployment.litellm_params.get(field)
             if field_value is not None:
                 model_info[field] = field_value
+        Router._inherit_builtin_base_rates_for_off_peak(
+            model_info=model_info,
+            backend_model=deployment.litellm_params.model,
+            custom_llm_provider=deployment.litellm_params.custom_llm_provider,
+        )
         if model_info.get("input_cost_per_token") is not None:
             Router._inherit_builtin_cache_pricing(
                 model_info=model_info,
@@ -9339,8 +9629,12 @@ class Router:
         """Re-assert this router's deployments onto a freshly fetched catalog.
 
         Reads ``model_list`` at call time, so only deployments the router still
-        serves are restored.
+        serves are restored, plus any config deployment the fresh catalog now resolves.
         """
+        provider_unresolved: Final = self._provider_unresolved_deployments
+        self._provider_unresolved_deployments = ()
+        for create_deployment in provider_unresolved:
+            create_deployment()
         for entry in tuple(self.model_list):
             try:
                 deployment = entry if isinstance(entry, Deployment) else Deployment(**entry)
@@ -9543,6 +9837,26 @@ class Router:
             coerce_token_limit(model_info.get("max_output_tokens")),
         )
 
+    def get_configured_display_name(self, model_name: str) -> "str | None":
+        """
+        Return the display_name explicitly configured in a concrete deployment's
+        model_info for model_name, via O(1) index lookup.
+
+        Returns None for wildcard-expanded or unknown names, and treats a
+        non-string or empty configured value as absent rather than failing the
+        listing. Like get_configured_token_limits, this never triggers pattern
+        matching or deep copies, so it is safe to call per listed model on the
+        /v1/models hot path.
+        """
+        deployment: Final = self.get_deployment_by_model_group_name(model_group_name=model_name)
+        if deployment is None:
+            return None
+
+        display_name: Final = deployment.model_info.get("display_name")
+        if isinstance(display_name, str) and display_name.strip():
+            return display_name
+        return None
+
     def get_deployment_credentials_with_provider(
         self, model_id: str, team_id: str | None = None
     ) -> dict[str, Any] | None:
@@ -11128,27 +11442,6 @@ class Router:
         """
         Update the router settings.
         """
-        # only the following settings are allowed to be configured
-        _allowed_settings: Final = [
-            "routing_strategy_args",
-            "routing_strategy",
-            "routing_groups",
-            "allowed_fails",
-            "cooldown_time",
-            "num_retries",
-            "timeout",
-            "max_retries",
-            "retry_after",
-            "fallbacks",
-            "context_window_fallbacks",
-            "retry_policy",
-            "model_group_retry_policy",
-            "model_group_alias",
-            "enable_weighted_failover",
-            "enable_tag_filtering",
-            "tag_routing_prefix",
-        ]
-
         _int_settings: Final = [
             "timeout",
             "num_retries",
@@ -11161,13 +11454,15 @@ class Router:
         rebuild_routing_groups = False
         relink_lar1_from_args = False
         for var in kwargs:
-            if var in _allowed_settings:
+            if var in RUNTIME_UPDATABLE_ROUTER_SETTINGS:
                 if var in _int_settings:
                     _casted_value = int(kwargs[var])
                     setattr(self, var, _casted_value)
                 elif var == "routing_groups":
                     self._routing_groups_input = kwargs[var]
                     rebuild_routing_groups = True
+                elif var == "optional_pre_call_checks":
+                    self.set_optional_pre_call_checks(kwargs[var])
                 elif var == "retry_policy":
                     value = kwargs[var]
                     if isinstance(value, dict):
@@ -12023,6 +12318,7 @@ class Router:
             if pre_routing_hook_response is not None:
                 model = pre_routing_hook_response.model
                 messages = pre_routing_hook_response.messages
+                record_pre_routing_selection(request_kwargs, model)
                 if pre_routing_hook_response.litellm_params:
                     accepted_tier_params: Final = self._tier_params_the_target_accepts(
                         model, pre_routing_hook_response.litellm_params, request_kwargs
@@ -12138,6 +12434,7 @@ class Router:
             if pre_routing_hook_response is not None:
                 model = pre_routing_hook_response.model
                 messages = pre_routing_hook_response.messages
+                record_pre_routing_selection(request_kwargs, model)
                 if pre_routing_hook_response.litellm_params:
                     accepted_tier_params: Final = self._tier_params_the_target_accepts(
                         model, pre_routing_hook_response.litellm_params, request_kwargs
@@ -12360,6 +12657,100 @@ class Router:
             return None
         return candidates[0]
 
+    @staticmethod
+    def _request_header(request_kwargs: Mapping[str, object], header_name: str) -> str | None:
+        proxy_server_request: Final = request_kwargs.get("proxy_server_request")
+        if not isinstance(proxy_server_request, Mapping):
+            return None
+        headers: Final = proxy_server_request.get("headers")
+        if not isinstance(headers, Mapping):
+            return None
+        return next(
+            (
+                value
+                for key, value in headers.items()
+                if isinstance(key, str) and key.lower() == header_name and isinstance(value, str)
+            ),
+            None,
+        )
+
+    def _claude_code_session_router_cache_key(self, request_kwargs: Mapping[str, object]) -> str | None:
+        session_id: Final = self._request_header(request_kwargs, "x-claude-code-session-id")
+        if session_id is None or _CLAUDE_CODE_SESSION_ID_RE.fullmatch(session_id) is None:
+            return None
+        metadata_name: Final = "litellm_metadata" if "litellm_metadata" in request_kwargs else "metadata"
+        metadata: Final = request_kwargs.get(metadata_name)
+        if not isinstance(metadata, Mapping):
+            return None
+        caller_scope: Final = metadata.get("user_api_key_hash")
+        if not isinstance(caller_scope, str) or not caller_scope:
+            return None
+        return f"claude_code_session_router:v1:{caller_scope}:{session_id}"
+
+    async def _delete_claude_code_session_router_binding(self, cache_key: str) -> None:
+        try:
+            await self._claude_code_session_router_cache.async_delete_cache(key=cache_key)
+        except Exception as e:  # noqa: BLE001  # cache cleanup must not fail an otherwise routable request
+            verbose_router_logger.warning(
+                "Failed to delete Claude Code session router binding; the binding may remain until its TTL expires: %s",
+                e,
+            )
+
+    async def _get_claude_code_session_router_binding(self, cache_key: str) -> object:
+        session_cache: Final = self._claude_code_session_router_cache
+        try:
+            if session_cache.redis_cache is None:
+                return await session_cache.async_get_cache(key=cache_key)
+            return await session_cache.redis_cache.async_get_cache(key=cache_key)
+        except Exception as e:  # noqa: BLE001  # an optional binding must not make routing depend on Redis
+            verbose_router_logger.warning(
+                "Failed to read Claude Code session router binding; using the requested model: %s",
+                e,
+            )
+            return None
+
+    async def _resolve_claude_code_session_router(
+        self,
+        model: str,
+        registered_model_name: str,
+        request_kwargs: Mapping[str, object],
+    ) -> str:
+        if not any((self.auto_routers, self.complexity_routers, self.adaptive_routers, self.quality_routers)):
+            return registered_model_name
+        cache_key: Final = self._claude_code_session_router_cache_key(request_kwargs)
+        if cache_key is None or not isinstance(request_kwargs, dict):
+            return registered_model_name
+        if request_kwargs.get("fallback_depth") not in (None, 0):
+            return registered_model_name
+
+        agent_id: Final = self._request_header(request_kwargs, "x-claude-code-agent-id")
+        if agent_id is not None:
+            bound_model: Final = await self._get_claude_code_session_router_binding(cache_key)
+            if not isinstance(bound_model, str):
+                return registered_model_name
+            bound_registered_model: Final = self._get_model_from_alias(model=bound_model) or bound_model
+            if self._select_pre_routing_strategy(bound_registered_model, request_kwargs) is None:
+                await self._delete_claude_code_session_router_binding(cache_key)
+                return registered_model_name
+            await self._claude_code_session_router_cache.async_set_cache(
+                key=cache_key,
+                value=bound_model,
+                ttl=_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS,
+            )
+            self._stamp_or_clear_metadata_key(request_kwargs, "model_group", bound_model)
+            return bound_registered_model
+
+        if self._request_header(request_kwargs, "x-app") != "cli":
+            return registered_model_name
+        if self._select_pre_routing_strategy(registered_model_name, request_kwargs) is None:
+            return registered_model_name
+        await self._claude_code_session_router_cache.async_set_cache(
+            key=cache_key,
+            value=model,
+            ttl=_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS,
+        )
+        return registered_model_name
+
     async def async_pre_routing_hook(
         self,
         model: str,
@@ -12379,7 +12770,12 @@ class Router:
         the alias, since spend metadata is stamped before routing and the response carries the tier
         group the strategy picked.
         """
-        registered_model_name: Final = self._get_model_from_alias(model=model) or model
+        requested_registered_model_name: Final = self._get_model_from_alias(model=model) or model
+        registered_model_name: Final = await self._resolve_claude_code_session_router(
+            model=model,
+            registered_model_name=requested_registered_model_name,
+            request_kwargs=request_kwargs,
+        )
 
         #########################################################
         # Run the routing-plugin pipeline, if any plugins are configured.
@@ -13176,6 +13572,9 @@ class Router:
     def flush_cache(self):
         litellm.cache = None
         self.cache.flush_cache()
+        session_in_memory_cache: Final = self._claude_code_session_router_cache.in_memory_cache
+        if session_in_memory_cache is not None:
+            session_in_memory_cache.flush_cache()
 
     def reset(self):
         ## clean up on close
diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py
index d57d7da0410..a8d51f95e45 100644
--- a/litellm/router_strategy/budget_limiter.py
+++ b/litellm/router_strategy/budget_limiter.py
@@ -20,6 +20,7 @@ anthropic:
 
 import asyncio
 import builtins
+from collections.abc import Mapping
 from datetime import datetime, timedelta, timezone
 from typing import Any, Final
 
@@ -54,19 +55,19 @@ class _LiteLLMParamsDictView:
 
     __slots__ = ("_params",)
 
-    def __init__(self, params: dict[str, Any]):
+    def __init__(self, params: Mapping[str, object]):
         self._params = params
 
-    def __getattr__(self, key: str) -> Any:
+    def __getattr__(self, key: str) -> object:
         return self._params.get(key)
 
-    def __getitem__(self, key: str) -> Any:
+    def __getitem__(self, key: str) -> object:
         return self._params.get(key)
 
     def __contains__(self, key: str) -> bool:
         return key in self._params
 
-    def get(self, key: str, default: Any = None) -> Any:
+    def get(self, key: str, default: object = None) -> object:
         return self._params.get(key, default)
 
     def keys(self):
@@ -84,10 +85,10 @@ class _LiteLLMParamsDictView:
     def __len__(self) -> int:
         return len(self._params)
 
-    def dict(self) -> dict[str, Any]:
+    def dict(self) -> builtins.dict[str, object]:
         return dict(self._params)
 
-    def model_dump(self) -> builtins.dict[str, Any]:
+    def model_dump(self) -> builtins.dict[str, object]:
         return dict(self._params)
 
 
diff --git a/litellm/router_strategy/complexity_router/README.md b/litellm/router_strategy/complexity_router/README.md
index 63ba760ff66..ad8b67d5e8f 100644
--- a/litellm/router_strategy/complexity_router/README.md
+++ b/litellm/router_strategy/complexity_router/README.md
@@ -68,6 +68,36 @@ still resolve to a deployment in `model_list`; this configuration does not creat
             - abc
 ```
 
+### Heuristic v2
+
+Set `classifier_type: heuristic_v2` to classify with the bundled calibrated
+success-probability model instead of the hand-written weighted scorer
+
+```yaml
+model_list:
+  - model_name: smart-router
+    litellm_params:
+      model: auto_router/complexity_router
+      complexity_router_config:
+        classifier_type: heuristic_v2
+        tiers:
+          SIMPLE: luna
+          MEDIUM: terra
+          COMPLEX: sol
+          REASONING: sol-ultra
+```
+
+No classifier model call or per-model training data is required. The classifier
+uses global tier quality, request-type quality, and similar-request cohorts from
+the bundled UltraFeedback artifact. It estimates success at every tier, enforces
+monotonic probabilities, and returns the first tier meeting the trained 0.75
+threshold. The existing complexity-router tier pool then selects and dispatches
+a model from that tier
+
+Spend logs record `routing_decision.cause: heuristic_v2`, the detected request
+type, and all four predicted probabilities. Existing `classifier_type: heuristic`
+configurations keep the original weighted scorer unchanged
+
 ### Renaming the tiers
 
 `tier_labels` puts your own vocabulary on the four tiers:
@@ -154,6 +184,9 @@ model_list:
         
         # Fallback model if tier cannot be determined
         default_model: gpt-4o
+
+        # Replace a routed model that cannot take image input (default: false)
+        modality_routing: true
 ```
 
 ## Usage
@@ -178,6 +211,25 @@ response = litellm.completion(
 
 ## Special Behaviors
 
+### Modality-based capability routing
+
+The classifier reads text alone, so a request carrying an image can classify cheap and land on a
+text-only model, which rejects it with a provider 400 no fallback catches. With
+`modality_routing: true`, one gate inspects every decided placement: when the routed model is
+explicitly declared `supports_vision: false` (deployment `model_info` first, the model cost map
+otherwise; unmapped names stay routable, and a multi-deployment group must accept on every
+deployment), the request is re-placed on the nearest HIGHER tier holding a capable model, with
+routing plugins still applied to the re-pick, then on `default_model` (never on plugin routers
+and never for a plan-floored decision), and otherwise rejected with a clear 400 naming the
+router. The walk only ever goes up, so a plan-mode floor cannot be undercut; a router whose only
+vision model sits below the decided tier gets the 400 and an actionable message instead.
+
+A same-tier re-pick keeps the decision's cause and adds `modality:image` to `signals`; a tier
+change or default takeover records `cause: modality_escalation` with the displaced placement
+(`modality_escalated_from:<TIER>` or `modality_displaced_default_model`). Escalations are never
+pinned by session affinity, and a KEPT session pin bypasses the gate entirely: a session pinned
+to a text-only model keeps it even when an image arrives.
+
 ### Heuristic-first chaining
 
 `classifier_type: heuristic_first` runs the local scorer on every request and only calls the LLM
@@ -222,6 +274,49 @@ except that the heuristic outcome is the one already computed rather than a seco
 Spend logs record `routing_decision.cause` as `heuristic_first_short_circuit` when the classifier
 was skipped, and `llm_classifier` when it ran, so the two are told apart per request.
 
+### Hybrid
+
+`classifier_type: hybrid` also scores locally first, but it asks a different question than
+`heuristic_first`. Where heuristic-first asks how CHEAP the scorer's tier is and pays for the
+classifier on everything above a ceiling, hybrid asks how DECIDED the score is and pays for the
+classifier only where the score lands near a tier boundary. A confident score keeps its tier at
+every tier, the most expensive one included:
+
+```yaml
+model_list:
+  - model_name: smart-router
+    litellm_params:
+      model: auto_router/complexity_router
+      complexity_router_config:
+        classifier_type: hybrid
+        hybrid_boundary_margin: 0.03
+        classifier_llm_config:
+          model: gpt-4o-mini
+        tiers:
+          SIMPLE: gpt-4o-mini
+          MEDIUM: gpt-4o
+          COMPLEX: claude-sonnet-4
+          REASONING: o1-preview
+```
+
+A request routes on the scorer's own tier when its score is further than `hybrid_boundary_margin`
+from every active boundary. Everything else goes to the classifier: a score inside the band, where a
+hair's difference would have named the adjacent tier and its model pool, and a prompt where no
+dimension fired at all, which has no opinion to be confident about. `hybrid_boundary_margin` is
+required for this type and rejected on the others, the same way `heuristic_first_max_tier` is
+required for heuristic-first, so the two modes are told apart by the knob each one takes rather than
+by a shared field that means something different per type.
+
+Pick the margin against the score distribution rather than by intuition. The scorer combines a small
+set of discretely weighted dimensions, so achievable scores cluster on a lumpy grid instead of
+spreading smoothly, and widening the margin admits whole clusters at once rather than a few more
+requests. Spend logs record `routing_decision.cause` as `hybrid_short_circuit` when the classifier
+was skipped and `llm_classifier` when it ran.
+
+Operator-defined tier sets (`tier_definitions`) are not supported here, for the same reason they are
+not supported under heuristic-first: the scorer only produces the built-in tiers. Classifier failure
+behaves exactly as it does under `classifier_type: llm`.
+
 ### Reasoning Override
 
 If 2+ reasoning markers are detected in the user message, the request is promoted to the REASONING tier even when the weighted score maps lower, so complex reasoning tasks get the appropriate model. The promotion requires the score to reach `reasoning_override_min_score`, which tracks `tier_boundaries.simple_medium` unless set, so stock phrases on an otherwise trivial prompt cannot buy the top tier. Set it to `0` to promote on the markers alone.
diff --git a/litellm/router_strategy/complexity_router/artifacts/ultrafeedback_tiers.json b/litellm/router_strategy/complexity_router/artifacts/ultrafeedback_tiers.json
new file mode 100644
index 00000000000..4fcb599907c
--- /dev/null
+++ b/litellm/router_strategy/complexity_router/artifacts/ultrafeedback_tiers.json
@@ -0,0 +1,4069 @@
+{
+  "schema_version": 1,
+  "global_statistics": [
+    {
+      "tier": 1,
+      "successes": 36619.0,
+      "observations": 45504.0
+    },
+    {
+      "tier": 2,
+      "successes": 59797.0,
+      "observations": 70062.0
+    },
+    {
+      "tier": 3,
+      "successes": 48604.0,
+      "observations": 52245.0
+    },
+    {
+      "tier": 4,
+      "successes": 11393.0,
+      "observations": 11561.0
+    }
+  ],
+  "domain_statistics": [
+    {
+      "tier": 1,
+      "successes": 1592.0,
+      "observations": 2211.0,
+      "request_type": "analytical_reasoning"
+    },
+    {
+      "tier": 2,
+      "successes": 2654.0,
+      "observations": 3374.0,
+      "request_type": "analytical_reasoning"
+    },
+    {
+      "tier": 3,
+      "successes": 2243.0,
+      "observations": 2481.0,
+      "request_type": "analytical_reasoning"
+    },
+    {
+      "tier": 4,
+      "successes": 538.0,
+      "observations": 546.0,
+      "request_type": "analytical_reasoning"
+    },
+    {
+      "tier": 1,
+      "successes": 750.0,
+      "observations": 1015.0,
+      "request_type": "code_generation"
+    },
+    {
+      "tier": 2,
+      "successes": 1271.0,
+      "observations": 1511.0,
+      "request_type": "code_generation"
+    },
+    {
+      "tier": 3,
+      "successes": 1030.0,
+      "observations": 1111.0,
+      "request_type": "code_generation"
+    },
+    {
+      "tier": 4,
+      "successes": 233.0,
+      "observations": 235.0,
+      "request_type": "code_generation"
+    },
+    {
+      "tier": 1,
+      "successes": 243.0,
+      "observations": 277.0,
+      "request_type": "code_understanding"
+    },
+    {
+      "tier": 2,
+      "successes": 385.0,
+      "observations": 425.0,
+      "request_type": "code_understanding"
+    },
+    {
+      "tier": 3,
+      "successes": 322.0,
+      "observations": 334.0,
+      "request_type": "code_understanding"
+    },
+    {
+      "tier": 4,
+      "successes": 74.0,
+      "observations": 76.0,
+      "request_type": "code_understanding"
+    },
+    {
+      "tier": 1,
+      "successes": 2014.0,
+      "observations": 2170.0,
+      "request_type": "factual_lookup"
+    },
+    {
+      "tier": 2,
+      "successes": 3120.0,
+      "observations": 3266.0,
+      "request_type": "factual_lookup"
+    },
+    {
+      "tier": 3,
+      "successes": 2612.0,
+      "observations": 2670.0,
+      "request_type": "factual_lookup"
+    },
+    {
+      "tier": 4,
+      "successes": 540.0,
+      "observations": 542.0,
+      "request_type": "factual_lookup"
+    },
+    {
+      "tier": 1,
+      "successes": 30571.0,
+      "observations": 38161.0,
+      "request_type": "general"
+    },
+    {
+      "tier": 2,
+      "successes": 50037.0,
+      "observations": 58821.0,
+      "request_type": "general"
+    },
+    {
+      "tier": 3,
+      "successes": 40460.0,
+      "observations": 43618.0,
+      "request_type": "general"
+    },
+    {
+      "tier": 4,
+      "successes": 9565.0,
+      "observations": 9716.0,
+      "request_type": "general"
+    },
+    {
+      "tier": 1,
+      "successes": 159.0,
+      "observations": 170.0,
+      "request_type": "technical_design"
+    },
+    {
+      "tier": 2,
+      "successes": 282.0,
+      "observations": 303.0,
+      "request_type": "technical_design"
+    },
+    {
+      "tier": 3,
+      "successes": 231.0,
+      "observations": 236.0,
+      "request_type": "technical_design"
+    },
+    {
+      "tier": 4,
+      "successes": 47.0,
+      "observations": 47.0,
+      "request_type": "technical_design"
+    },
+    {
+      "tier": 1,
+      "successes": 1290.0,
+      "observations": 1500.0,
+      "request_type": "writing"
+    },
+    {
+      "tier": 2,
+      "successes": 2048.0,
+      "observations": 2362.0,
+      "request_type": "writing"
+    },
+    {
+      "tier": 3,
+      "successes": 1706.0,
+      "observations": 1795.0,
+      "request_type": "writing"
+    },
+    {
+      "tier": 4,
+      "successes": 396.0,
+      "observations": 399.0,
+      "request_type": "writing"
+    }
+  ],
+  "cohort_statistics": [
+    {
+      "tier": 1,
+      "successes": 272.0,
+      "observations": 372.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 420.0,
+      "observations": 519.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 341.0,
+      "observations": 381.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 4,
+      "successes": 82.0,
+      "observations": 84.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "successes": 0.0,
+      "observations": 1.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=1"
+    },
+    {
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+      "successes": 0.0,
+      "observations": 2.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=1"
+    },
+    {
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+      "observations": 1.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=0|intl=1"
+    },
+    {
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+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=1|intl=0"
+    },
+    {
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+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=1|intl=0"
+    },
+    {
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+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=1|intl=0"
+    },
+    {
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+      "observations": 3.0,
+      "cohort": "analytical_reasoning|long|code=0|math=0|mc=1|intl=0"
+    },
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+      "observations": 176.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=0"
+    },
+    {
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+      "observations": 274.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=0"
+    },
+    {
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+      "observations": 209.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=0"
+    },
+    {
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+      "observations": 41.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=0"
+    },
+    {
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+      "observations": 9.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=1"
+    },
+    {
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+      "observations": 13.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=1"
+    },
+    {
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+      "observations": 7.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=1"
+    },
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+      "observations": 3.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=1|intl=0"
+    },
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+      "observations": 16.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=1|intl=0"
+    },
+    {
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+      "observations": 16.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=1|intl=0"
+    },
+    {
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+      "observations": 5.0,
+      "cohort": "analytical_reasoning|long|code=0|math=1|mc=1|intl=0"
+    },
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+      "cohort": "analytical_reasoning|long|code=1|math=0|mc=0|intl=0"
+    },
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+      "observations": 38.0,
+      "cohort": "analytical_reasoning|long|code=1|math=0|mc=0|intl=0"
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+    },
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+      "observations": 5.0,
+      "cohort": "analytical_reasoning|long|code=1|math=0|mc=0|intl=0"
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+      "observations": 2.0,
+      "cohort": "analytical_reasoning|long|code=1|math=0|mc=1|intl=0"
+    },
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+      "cohort": "analytical_reasoning|long|code=1|math=0|mc=1|intl=0"
+    },
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+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=0|intl=0"
+    },
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+      "observations": 50.0,
+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=0|intl=0"
+    },
+    {
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+      "observations": 45.0,
+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=0|intl=0"
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+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=0|intl=0"
+    },
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+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=1|intl=0"
+    },
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+      "observations": 4.0,
+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=1|intl=0"
+    },
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+      "observations": 1.0,
+      "cohort": "analytical_reasoning|long|code=1|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 1,
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+      "observations": 634.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "successes": 745.0,
+      "observations": 962.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "observations": 691.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=0"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=0"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=1|intl=0"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=1|intl=0"
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=1|intl=0"
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+      "cohort": "analytical_reasoning|medium|code=0|math=0|mc=1|intl=0"
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+      "observations": 270.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=0"
+    },
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+      "observations": 402.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=0"
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+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=0"
+    },
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+      "successes": 73.0,
+      "observations": 73.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=0"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=1"
+    },
+    {
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+      "observations": 32.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=1"
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+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=0|intl=1"
+    },
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+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=1|intl=0"
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+      "observations": 25.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=1|intl=0"
+    },
+    {
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+      "successes": 10.0,
+      "observations": 16.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=1|intl=0"
+    },
+    {
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+      "successes": 6.0,
+      "observations": 6.0,
+      "cohort": "analytical_reasoning|medium|code=0|math=1|mc=1|intl=0"
+    },
+    {
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+      "successes": 58.0,
+      "observations": 72.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=0|intl=0"
+    },
+    {
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+      "successes": 90.0,
+      "observations": 103.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=0|intl=0"
+    },
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+      "successes": 72.0,
+      "observations": 78.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=0|intl=0"
+    },
+    {
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+      "successes": 19.0,
+      "observations": 19.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=0|intl=0"
+    },
+    {
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+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=1|intl=0"
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+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=1|intl=0"
+    },
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+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=0|mc=1|intl=0"
+    },
+    {
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+      "observations": 56.0,
+      "cohort": "analytical_reasoning|medium|code=1|math=1|mc=0|intl=0"
+    },
+    {
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+      "cohort": "analytical_reasoning|medium|code=1|math=1|mc=0|intl=0"
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+      "cohort": "analytical_reasoning|medium|code=1|math=1|mc=0|intl=0"
+    },
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+    },
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+      "observations": 83.0,
+      "cohort": "analytical_reasoning|short|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "observations": 110.0,
+      "cohort": "analytical_reasoning|short|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "observations": 98.0,
+      "cohort": "analytical_reasoning|short|code=0|math=0|mc=0|intl=0"
+    },
+    {
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+      "tier": 1,
+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "writing|short|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "writing|short|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 2.0,
+      "observations": 2.0,
+      "cohort": "writing|short|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 63.0,
+      "observations": 85.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 111.0,
+      "observations": 139.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 95.0,
+      "observations": 99.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 4,
+      "successes": 29.0,
+      "observations": 29.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 3.0,
+      "observations": 5.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=1|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 1.0,
+      "observations": 2.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=1|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 4.0,
+      "observations": 4.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=1|intl=0"
+    },
+    {
+      "tier": 4,
+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "writing|very_long|code=0|math=0|mc=1|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 26.0,
+      "observations": 36.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 30.0,
+      "observations": 44.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 23.0,
+      "observations": 28.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 4,
+      "successes": 8.0,
+      "observations": 8.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 2.0,
+      "observations": 2.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 1.0,
+      "observations": 1.0,
+      "cohort": "writing|very_long|code=0|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 14.0,
+      "observations": 14.0,
+      "cohort": "writing|very_long|code=1|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 14.0,
+      "observations": 16.0,
+      "cohort": "writing|very_long|code=1|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 6.0,
+      "observations": 7.0,
+      "cohort": "writing|very_long|code=1|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 4,
+      "successes": 3.0,
+      "observations": 3.0,
+      "cohort": "writing|very_long|code=1|math=0|mc=0|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 5.0,
+      "observations": 5.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 7.0,
+      "observations": 8.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 7.0,
+      "observations": 7.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=0|intl=0"
+    },
+    {
+      "tier": 1,
+      "successes": 0.0,
+      "observations": 1.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 2,
+      "successes": 2.0,
+      "observations": 2.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=1|intl=0"
+    },
+    {
+      "tier": 3,
+      "successes": 0.0,
+      "observations": 1.0,
+      "cohort": "writing|very_long|code=1|math=1|mc=1|intl=0"
+    }
+  ],
+  "domain_prior_mass": 200.0,
+  "cohort_prior_mass": 20.0,
+  "routing_threshold": 0.75,
+  "datasets": [
+    {
+      "name": "openbmb/UltraFeedback",
+      "url": "https://huggingface.co/datasets/openbmb/UltraFeedback",
+      "license": "MIT",
+      "rows": 255864,
+      "success_definition": "UltraFeedback overall_score >= 4"
+    }
+  ],
+  "success_definition": "UltraFeedback overall_score >= 4",
+  "split_method": "sha256(prompt): 70% train, 15% validation, 15% test"
+}
diff --git a/litellm/router_strategy/complexity_router/complexity_router.py b/litellm/router_strategy/complexity_router/complexity_router.py
index 2f4305756e9..d205db90607 100644
--- a/litellm/router_strategy/complexity_router/complexity_router.py
+++ b/litellm/router_strategy/complexity_router/complexity_router.py
@@ -30,8 +30,14 @@ from litellm.constants import EMPTY_MAPPING, RETURN_RAW_MODEL_NAME_METADATA_KEY
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs
 from litellm.litellm_core_utils.internal_call_metadata import forwarded_internal_call_metadata
+from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content
 from litellm.litellm_core_utils.sensitive_data_masker import mask_credentials_in_payload
 from litellm.llms.base_llm.base_utils import type_to_response_format_param
+from litellm.router_strategy.adaptive_router.classifier import classify_prompt
+from litellm.router_strategy.complexity_router.tier_predictor import (
+    TierSuccessPredictor,
+    resolve_tier_artifact,
+)
 from litellm.types.utils import (
     AUTOROUTER_CLASSIFIER_CALL_ORIGIN,
     ModelResponse,
@@ -281,7 +287,7 @@ def _response_cost_or_none(response: ModelResponse) -> float | None:
     return float(cost)
 
 
-def _effective_turn_off_message_logging(request_kwargs: Mapping[str, Any] | None) -> bool | None:
+def _effective_turn_off_message_logging(request_kwargs: Mapping[str, object] | None) -> bool | None:
     from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
         initialize_standard_callback_dynamic_params,
     )
@@ -479,6 +485,33 @@ def _last_human_ask_index(
     )
 
 
+def _newest_turn_is_human_ask(
+    messages: Sequence[Mapping[str, object]] | None,
+    marker_pairs: tuple[tuple[str, str], ...] = _DEFAULT_REMINDER_MARKERS,
+) -> bool:
+    """Whether the request's newest turn carries a real human ask, i.e. this is a new ask rather
+    than an agent loop's continuation traffic.
+
+    Anchored on `_last_human_ask_index` so every surface's plumbing reads as a continuation:
+    chat-completions tool turns are role=tool, Messages-surface tool_result turns flatten to empty
+    human text, and a hybrid turn carrying an ask alongside a tool_result still counts as an ask.
+    Compared against the newest non-system message rather than the raw tail, because Claude Code
+    appends a system-role reminder after the human turn; that trailing plumbing is neither an ask
+    nor loop traffic and must not turn a fresh ask into a continuation. An unreadable request (no
+    messages) is treated as a continuation: there is no ask to classify, which is the same reading
+    `_extract_current_ask_and_system_prompt` gives it downstream.
+    """
+    if not messages:
+        return False
+    newest_non_system: Final = next(
+        (index for index in range(len(messages) - 1, -1, -1) if messages[index].get("role") != "system"),
+        None,
+    )
+    if newest_non_system is None:
+        return False
+    return _last_human_ask_index(messages, marker_pairs) == newest_non_system
+
+
 def _iter_system_scope_texts(
     body_system: object,
     messages: Sequence[Mapping[str, object]],
@@ -706,11 +739,25 @@ def _decision_is_pinnable(decision: StandardLoggingRoutingDecision | None) -> bo
     of the three: an agent names the conversation on its first turn, so the cheapest tier would be
     the pin every session starts with, and the real work that follows would run there for the whole
     TTL. It describes what that one call is, never what the session's traffic looks like.
+
+    A context-window escalation describes the prompt's size, not the session's complexity, and
+    size shrinks again the moment the client compacts: pinning the escalated tier would hold the
+    session on the big-window model long after the oversized context that forced it is gone. The
+    gate re-fires per request, so leaving these unpinned costs nothing but the classifier call.
+
+    A modality escalation is transient the same way: it describes what this one call carries (an
+    image), not what the session's traffic looks like, and pinning it would hold every following
+    text turn on the vision-capable model the image forced.
     """
-    return decision is None or decision.get("cause") not in (
-        "default_model_fallback",
-        "plan_mode",
-        "housekeeping",
+    return decision is None or (
+        decision.get("cause")
+        not in (
+            "default_model_fallback",
+            "plan_mode",
+            "housekeeping",
+            "modality_escalation",
+        )
+        and not decision.get("context_escalated")
     )
 
 
@@ -748,9 +795,11 @@ class ClassificationOutcome(NamedTuple):
     signals: tuple[str, ...]
     cause: Literal[
         "heuristic_scorer",
+        "heuristic_v2",
         "reasoning_override",
         "llm_classifier",
         "heuristic_first_short_circuit",
+        "hybrid_short_circuit",
         "housekeeping",
         "classifier_plugin",
         "classifier_fallback",
@@ -759,6 +808,39 @@ class ClassificationOutcome(NamedTuple):
     classifier_cost: float | None = None
 
 
+def _allowed(models: tuple[str, ...], fit_filter: frozenset[str] | None) -> tuple[str, ...]:
+    return models if fit_filter is None else tuple(model for model in models if model in fit_filter)
+
+
+def _apply_context_placement(
+    tier: ComplexityTier | str, signals: tuple[str, ...], placement: _ContextWindowPlacement | None
+) -> tuple[ComplexityTier | str, tuple[str, ...], ComplexityTier | str | None]:
+    """(final tier, signals, original tier when the gate escalated, else None)."""
+    if placement is None:
+        return tier, signals, None
+    if _tier_name(placement.tier) == _tier_name(tier):
+        return placement.tier, signals, None
+    return placement.tier, (*signals, "context_escalation"), tier
+
+
+def _window_can_hold(window: int | None, needed: int, buffer: float) -> bool:
+    return window is None or needed <= int(window * buffer)
+
+
+def _group_provably_fits(facts: tuple[int | None, bool], needed: int, buffer: float) -> bool:
+    window, has_unknown = facts
+    return window is not None and not has_unknown and needed <= int(window * buffer)
+
+
+class _ContextWindowPlacement(NamedTuple):
+    """Where the context-window gate placed the request: the placement tier, the subset of its
+    pool the pick may use, and every configured group not provably misfit (the adaptive filter)."""
+
+    tier: ComplexityTier | str
+    allowed_models: tuple[str, ...]
+    holdable_models: frozenset[str]
+
+
 class _SessionAffinityPin(NamedTuple):
     model: str
     tier: ComplexityTier | None
@@ -903,6 +985,11 @@ class ComplexityRouter(CustomLogger):
             if llm_classifier_configured
             else None
         )
+        self._tier_success_predictor: TierSuccessPredictor | None = (
+            TierSuccessPredictor(resolve_tier_artifact(self.config.heuristic_v2_artifact))
+            if self.config.classifier_type == "heuristic_v2"
+            else None
+        )
 
         verbose_router_logger.debug("ComplexityRouter initialized for %s with tiers: %s", model_name, self.config.tiers)
 
@@ -1155,6 +1242,15 @@ class ComplexityRouter(CustomLogger):
 
         return tier, weighted_score, tuple(signals), "heuristic_scorer"
 
+    def _is_near_tier_boundary(self, score: float, margin: float) -> bool:
+        boundaries: Final = self._effective_tier_boundaries()
+        active_boundaries: Final = (
+            boundaries["simple_medium"],
+            boundaries["medium_complex"],
+            boundaries["complex_reasoning"],
+        )
+        return any(abs(score - boundary) <= margin for boundary in active_boundaries)
+
     def _effective_reasoning_override_min_score(self) -> float:
         """The score a request must reach before the reasoning-marker override may promote it.
 
@@ -1195,6 +1291,7 @@ class ComplexityRouter(CustomLogger):
         classifier_cost: float | None = None,
         conversation_continuing: bool = True,
         tier_litellm_params: Mapping[str, object] | None = None,
+        context_escalation_original_tier: ComplexityTier | str | None = None,
     ) -> StandardLoggingRoutingDecision:
         """Assemble the per-request provenance record for this router's decision.
 
@@ -1244,6 +1341,12 @@ class ComplexityRouter(CustomLogger):
             decision["classifier_model"] = classifier_model
         if classifier_cost is not None:
             decision["classifier_cost"] = classifier_cost
+        if context_escalation_original_tier is not None:
+            # The pair travels together: the flag says the gate moved the request off its
+            # decided tier on prompt size, and the original tier names where the decision
+            # (classifier, keyword rule, or session pin) had placed it before physics did.
+            decision["context_escalated"] = True
+            decision["context_escalation_original_tier"] = _tier_name(context_escalation_original_tier)
         if tier_litellm_params:
             masked_tier_litellm_params: Final = mask_credentials_in_payload(tier_litellm_params)
             if isinstance(masked_tier_litellm_params, Mapping):
@@ -1268,15 +1371,37 @@ class ComplexityRouter(CustomLogger):
         custom tier set, and classifier_fallback otherwise decides between the heuristic scorer and
         default_model. The outcome's `cause` reports which path actually ran.
         """
+        if self.config.classifier_type == "heuristic_v2":
+            return self._classify_with_heuristic_v2(prompt)
         if self.config.classifier_type == "custom":
             return await self._classify_with_plugin(prompt, system_prompt, request_kwargs, raw_messages)
         if self.config.classifier_type == "heuristic_first" and self.config.classifier_llm_config is not None:
             return await self._classify_heuristic_first(prompt, system_prompt, request_kwargs, messages)
+        if self.config.classifier_type == "hybrid" and self.config.classifier_llm_config is not None:
+            return await self._classify_hybrid(prompt, system_prompt, request_kwargs, messages)
         if self.config.classifier_type != "llm" or self.config.classifier_llm_config is None:
             tier, score, signals, cause = self._score_and_classify(prompt, system_prompt)
             return ClassificationOutcome(tier=tier, score=score, signals=signals, cause=cause)
         return await self._llm_classifier_outcome(prompt, system_prompt, request_kwargs, messages)
 
+    def _classify_with_heuristic_v2(self, prompt: str) -> ClassificationOutcome:
+        predictor: Final = self._tier_success_predictor
+        if predictor is None:
+            raise ValueError("heuristic v2 predictor is not configured")
+        request_type: Final = classify_prompt(prompt)
+        prediction: Final = predictor.predict(prompt, request_type)
+        tier: Final = TIER_SEVERITY_ORDER[prediction.required_tier - 1]
+        probability_signals: Final = tuple(
+            f"tier-probability:{candidate.value.lower()}={prediction.probabilities[index]:.6f}"
+            for index, candidate in enumerate(TIER_SEVERITY_ORDER, start=1)
+        )
+        return ClassificationOutcome(
+            tier=tier,
+            score=None,
+            signals=(f"request-type:{request_type.value}", *probability_signals),
+            cause="heuristic_v2",
+        )
+
     async def _classify_heuristic_first(
         self,
         prompt: str,
@@ -1305,6 +1430,29 @@ class ComplexityRouter(CustomLogger):
             return ClassificationOutcome(tier=tier, score=score, signals=signals, cause="heuristic_first_short_circuit")
         return await self._llm_classifier_outcome(prompt, system_prompt, request_kwargs, messages, scored=scored)
 
+    async def _classify_hybrid(
+        self,
+        prompt: str,
+        system_prompt: str | None,
+        request_kwargs: dict[str, Any] | None,  # mutable-ok: handed to _classify_with_llm as-is
+        messages: Sequence[Mapping[str, object]] | None,
+    ) -> ClassificationOutcome:
+        """Score locally, and only pay for the classifier when the score sits near a tier boundary.
+
+        Where heuristic_first asks how CHEAP the scorer's tier is, this asks how DECIDED it is, so a
+        confident score keeps its tier at every tier including the most expensive one. Two things make
+        a score undecided: landing within hybrid_boundary_margin of an active boundary, where a
+        hair's difference in score would have named the adjacent tier and its model pool, and firing
+        no dimension at all, which scores 0.0 and lands SIMPLE by default rather than by evidence.
+        """
+        tier, score, signals, cause = self._score_and_classify(prompt, system_prompt)
+        scored: Final = ClassificationOutcome(tier=tier, score=score, signals=signals, cause=cause)
+        margin: Final = self.config.hybrid_boundary_margin
+        decided: Final = margin is not None and bool(signals) and not self._is_near_tier_boundary(score, margin)
+        if decided:
+            return ClassificationOutcome(tier=tier, score=score, signals=signals, cause="hybrid_short_circuit")
+        return await self._llm_classifier_outcome(prompt, system_prompt, request_kwargs, messages, scored=scored)
+
     async def _llm_classifier_outcome(
         self,
         prompt: str,
@@ -1644,7 +1792,7 @@ class ComplexityRouter(CustomLogger):
         return entry.litellm_params if entry is not None else MappingProxyType({})
 
     @staticmethod
-    def _pick_from_tier_value(model: str | list[str], tier_key: str) -> str:
+    def _pick_from_tier_value(model: str | Sequence[str], tier_key: str) -> str:
         if isinstance(model, str):
             return model
         if not model:
@@ -1660,15 +1808,21 @@ class ComplexityRouter(CustomLogger):
         raw_messages: list[dict[str, Any]] | None,
         resolved_messages: list[dict[str, Any]] | None,
         request_kwargs: dict,
+        allowed_models: tuple[str, ...] | None = None,
     ) -> str:
         if not self.config.plugins:
+            if allowed_models is not None:
+                return self._pick_from_tier_value(allowed_models, _tier_name(tier))
             return self.get_model_for_tier(tier)
 
         from litellm.types.router import RoutingContext
 
         tier_key: Final = _tier_name(tier)
         metadata_key: Final = get_metadata_variable_name_from_kwargs(request_kwargs)
-        pool: Final = tuple(self._tier_pools().get(tier_key, ()))
+        full_pool: Final = tuple(self._tier_pools().get(tier_key, ()))
+        pool: Final = (
+            tuple(model for model in full_pool if model in allowed_models) if allowed_models is not None else full_pool
+        )
         if not pool:
             # Nothing for the plugins to filter. Falling through would raise the
             # plugin-filtering error below and send the operator hunting for a policy
@@ -1762,6 +1916,7 @@ class ComplexityRouter(CustomLogger):
         request_kwargs: dict[str, Any] | None = None,
         hard_floor: ComplexityTier | str | None = None,
         hard_ceiling: ComplexityTier | str | None = None,
+        fit_filter: frozenset[str] | None = None,
     ) -> str:
         """hard_floor excludes every candidate whose tiers all sit below it, turning this pick's
         soft floors (a distance penalty a high-scoring cheap model can outweigh) into a hard
@@ -1774,7 +1929,10 @@ class ComplexityRouter(CustomLogger):
         tier because that is all it is worth, so a bandit trading cost for quality has nothing to
         win and must not reach above it. Without it the distance penalty is the only thing holding
         the tier, and a deployment that lowers tier_distance_penalty silently gets the expensive
-        model back while the routing decision still reads as the cheapest tier."""
+        model back while the routing decision still reads as the cheapest tier.
+
+        fit_filter excludes candidates the context-window gate proved cannot hold the prompt,
+        in every phase including cold start and the tier fallbacks."""
         from litellm.router_strategy.adaptive_router.bandit import (
             normalized_cost,
             thompson_sample,
@@ -1785,12 +1943,12 @@ class ComplexityRouter(CustomLogger):
         if adaptive is None or not isinstance(classified_tier, ComplexityTier):
             # Custom tier names have no severity index; adaptive is rejected alongside
             # tier_definitions, so this guard is the contract for any future caller.
-            return self.get_model_for_tier(classified_tier)
+            return self._fitting_tier_fallback(classified_tier, fit_filter)
 
         request_type: Final = classify_prompt(user_message)
         classified_idx: Final = TIER_SEVERITY_ORDER.index(classified_tier)
         pools: Final = self._tier_pools()
-        classified_candidates: Final = tuple(pools.get(_tier_name(classified_tier), ()))
+        classified_candidates: Final = _allowed(tuple(pools.get(_tier_name(classified_tier), ())), fit_filter)
         cold_start_candidates: Final = tuple(
             model for model in classified_candidates if adaptive._cells[(request_type, model)].total_samples == 0
         )
@@ -1820,9 +1978,9 @@ class ComplexityRouter(CustomLogger):
         if self.config.adaptive_eligible == "classified_tier":
             candidates = list(classified_candidates)
             if not candidates:
-                return self.get_model_for_tier(classified_tier)
+                return self._fitting_tier_fallback(classified_tier, fit_filter)
         else:
-            candidates = list(adaptive.config.available_models)
+            candidates = list(_allowed(tuple(adaptive.config.available_models), fit_filter))
 
         all_costs: Final = [adaptive.model_to_cost.get(m, 0.0) for m in candidates]
         quality_weight: Final = self.config.adaptive_weights.quality
@@ -1833,7 +1991,7 @@ class ComplexityRouter(CustomLogger):
         ceiling_severity: Final = self._active_tier_severity(hard_ceiling) if hard_ceiling is not None else None
         best_model: str | None = None
         best_score = float("-inf")
-        candidate_scores: Final[list[dict[str, Any]]] = []
+        candidate_scores: Final[list[dict[str, object]]] = []
         for model in candidates:
             if floor_severity is not None and all(
                 self._active_tier_severity(model_tier) < floor_severity
@@ -1869,7 +2027,7 @@ class ComplexityRouter(CustomLogger):
                 best_score = score
                 best_model = model
         if best_model is None:
-            return self.get_model_for_tier(classified_tier)
+            return self._fitting_tier_fallback(classified_tier, fit_filter)
         if request_kwargs is not None:
             metadata = request_kwargs.setdefault("metadata", {})
             if isinstance(metadata, dict):
@@ -1886,6 +2044,12 @@ class ComplexityRouter(CustomLogger):
                 }
         return best_model
 
+    def _fitting_tier_fallback(self, classified_tier: ComplexityTier | str, fit_filter: frozenset[str] | None) -> str:
+        fitting: Final = _allowed(tuple(self._tier_pools().get(_tier_name(classified_tier), ())), fit_filter)
+        if fit_filter is not None and fitting:
+            return self._pick_from_tier_value(fitting, _tier_name(classified_tier))
+        return self.get_model_for_tier(classified_tier)
+
     def _resolve_plan_mode_floor(self) -> ComplexityTier | str | None:
         """The configured floor as an active tier: the built-in enum member, or the defined
         name itself for a custom tier set; None when the feature is off."""
@@ -1956,6 +2120,163 @@ class ComplexityRouter(CustomLogger):
             return None
         return name if self.config.has_custom_tiers else ComplexityTier(name)
 
+    def _deployment_window(self, group: str, deployment: Mapping[str, object]) -> int | None:
+        from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider
+
+        deployment_model_info: Final = deployment.get("model_info")
+        declared: Final = (
+            deployment_model_info.get("max_input_tokens") if isinstance(deployment_model_info, Mapping) else None
+        )
+        if isinstance(declared, int):
+            return declared
+        litellm_params: Final = deployment.get("litellm_params")
+        params: Final = litellm_params if isinstance(litellm_params, Mapping) else EMPTY_MAPPING
+        provider_override: Final = params.get("custom_llm_provider")
+        # get_router_model_info resolves the provider, and get_llm_provider runs the OAuth device
+        # flow for github_copilot/chatgpt, so a metadata question must never reach it for those.
+        if declared_authenticating_provider(
+            str(params.get("model") or ""), provider_override if isinstance(provider_override, str) else None
+        ):
+            return None
+        try:
+            model_info: Final = self.litellm_router_instance.get_router_model_info(
+                deployment=cast(dict, deployment),  # cast-ok: router deployments are plain dicts
+                received_model_name=group,
+            )
+            window: Final = model_info.get("max_input_tokens")
+        except Exception:  # noqa: BLE001  # best-effort: an unmappable deployment must not hide the others
+            return None
+        return window if isinstance(window, int) else None
+
+    def _group_window_facts(self, group: str) -> tuple[int | None, bool]:
+        """(smallest declared context window across the group's deployments, whether any deployment
+        declares none). The core router picks a deployment within the group without a fit check, so
+        the group is only as safe as its smallest member."""
+        list_models: Final = getattr(self.litellm_router_instance, "get_model_list", None)
+        deployments: Final = list_models(model_name=group) if callable(list_models) else None
+        if not isinstance(deployments, list) or not deployments:
+            return (None, True)
+        windows: Final = tuple(
+            window for deployment in deployments if (window := self._deployment_window(group, deployment)) is not None
+        )
+        return (min(windows) if windows else None, len(windows) < len(deployments))
+
+    @staticmethod
+    def _out_of_band_request_text(request_kwargs: Mapping[str, object]) -> str:
+        """Prompt content the resolved message list never carries: the Responses API's
+        `instructions`, the /v1/messages top-level `system` block, and tool definitions.
+        A coding agent's context is dominated by these."""
+        import json
+
+        instructions: Final = request_kwargs.get("instructions")
+        proxy_request: Final = request_kwargs.get("proxy_server_request")
+        body: Final = proxy_request.get("body") if isinstance(proxy_request, Mapping) else None
+        system: Final = body.get("system") if isinstance(body, Mapping) else None
+        tools: Final = (
+            body.get("tools") if isinstance(body, Mapping) and body.get("tools") else request_kwargs.get("tools")
+        )
+        tools_text = ""
+        if tools:
+            try:
+                tools_text = json.dumps(tools, default=str)
+            except (TypeError, ValueError):
+                tools_text = str(tools)
+        return (
+            (instructions if isinstance(instructions, str) else "")
+            + (str(system) if system is not None else "")
+            + tools_text
+        )
+
+    def _request_byte_upper_bound(
+        self, resolved_messages: Sequence[Mapping[str, object]] | None, request_kwargs: Mapping[str, object]
+    ) -> int:
+        """UTF-8 byte length of all prompt content. BPE emits at least one byte per token in every
+        script, so the token count never exceeds this and 'bytes fit' soundly skips counting."""
+        content_bytes: Final = sum(len(str(m.get("content") or "").encode()) for m in resolved_messages or ())
+        return content_bytes + len(self._out_of_band_request_text(request_kwargs).encode())
+
+    async def _counted_request_tokens(
+        self, resolved_messages: Sequence[Mapping[str, object]], request_kwargs: Mapping[str, object]
+    ) -> int | None:
+        """Real-tokenizer count of the resolved messages plus the out-of-band carriers, off the
+        event loop; None when counting fails, and the gate then leaves the placement alone."""
+        import litellm
+        from litellm.litellm_core_utils.asyncify import asyncify
+
+        out_of_band: Final = self._out_of_band_request_text(request_kwargs)
+        try:
+            counted: Final = await asyncify(litellm.token_counter)(
+                messages=cast(list, resolved_messages)  # cast-ok: token_counter only iterates the sequence
+            )
+            return counted + (await asyncify(litellm.token_counter)(text=out_of_band) if out_of_band else 0)
+        except Exception as e:  # noqa: BLE001  # best-effort: an uncountable prompt must not fail the request
+            verbose_router_logger.debug("ComplexityRouter: context-window token count failed. Got - %s", e)
+            return None
+
+    async def _context_window_placement(
+        self,
+        tier: ComplexityTier | str,
+        resolved_messages: Sequence[Mapping[str, object]] | None,
+        request_kwargs: Mapping[str, object],
+        pool_override: tuple[str, ...] | None = None,
+    ) -> _ContextWindowPlacement | None:
+        """Correct a decided placement whose models provably cannot hold the prompt, or None
+        (the placement stands). Only a real tokenizer count ever moves a request, escalation
+        lands only on groups whose every deployment declares a fitting window, and a group
+        with no resolvable window is never moved on faith in either direction."""
+        if not self.config.enable_context_window_escalation or not resolved_messages:
+            return None
+        pools: Final = self._tier_pools()
+        pool: Final = pool_override if pool_override is not None else tuple(pools.get(_tier_name(tier), ()))
+        if not pool:
+            return None
+        facts: Final = MappingProxyType({group: self._group_window_facts(group) for group in pool})
+        known_windows: Final = tuple(window for window, _ in facts.values() if window is not None)
+        if not known_windows:
+            return None
+        buffer: Final = self.config.context_window_escalation_buffer
+        if self._request_byte_upper_bound(resolved_messages, request_kwargs) <= int(min(known_windows) * buffer):
+            return None
+        needed: Final = await self._counted_request_tokens(resolved_messages, request_kwargs)
+        if needed is None:
+            return None
+        return self._placement_for_tokens(tier=tier, pool=pool, pools=pools, facts=facts, needed=needed)
+
+    def _placement_for_tokens(
+        self,
+        *,
+        tier: ComplexityTier | str,
+        pool: tuple[str, ...],
+        pools: Mapping[str, list[str]],
+        facts: Mapping[str, tuple[int | None, bool]],
+        needed: int,
+    ) -> _ContextWindowPlacement | None:
+        buffer: Final = self.config.context_window_escalation_buffer
+        in_tier: Final = tuple(group for group in pool if _window_can_hold(facts[group][0], needed, buffer))
+        if in_tier and len(in_tier) == len(pool):
+            return None
+        holdable: Final = frozenset(
+            group
+            for tier_pool in pools.values()
+            for group in tier_pool
+            if _window_can_hold(self._group_window_facts(group)[0], needed, buffer)
+        )
+        if in_tier:
+            return _ContextWindowPlacement(tier=tier, allowed_models=in_tier, holdable_models=holdable)
+        for name in self.config.tier_names()[self._active_tier_severity(tier) + 1 :]:
+            proven = tuple(
+                group
+                for group in pools.get(name, ())
+                if _group_provably_fits(self._group_window_facts(group), needed, buffer)
+            )
+            if proven:
+                return _ContextWindowPlacement(
+                    tier=name if self.config.has_custom_tiers else ComplexityTier(name),
+                    allowed_models=proven,
+                    holdable_models=holdable,
+                )
+        return None
+
     def _apply_plan_mode_floor(self, tier: ComplexityTier | str) -> ComplexityTier | str:
         """The higher of the decided tier and the plan-mode floor; identity when the floor is unset."""
         floor: Final = self._resolve_plan_mode_floor()
@@ -2025,6 +2346,175 @@ class ComplexityRouter(CustomLogger):
             return pinned_model
         return self.get_model_for_tier(escalated_tier)
 
+    def _model_accepts_image_input(self, model_name: str) -> bool:
+        """Whether a routed model or pool entry can serve an image request.
+
+        Resolved through the deployments that would actually serve the name; a name with no
+        deployment on the router is served by the SDK directly and is checked against the model
+        cost map itself. Only an explicit supports_vision false excludes, a deployment-level
+        model_info override first and the map otherwise, so unmapped custom names stay routable.
+
+        A multi-deployment group must accept on EVERY deployment: the router picks a deployment
+        inside the group after this gate runs, so a mixed group marked eligible could still hand
+        the image to its text-only member and fail with the exact 400 the gate exists to prevent.
+        """
+        from litellm.utils import is_vision_explicitly_disabled
+
+        def deployment_accepts(deployment: Mapping[str, Any]) -> bool:
+            declared: Final = (deployment.get("model_info") or EMPTY_MAPPING).get("supports_vision")
+            if declared is not None:
+                return declared is True
+            litellm_model: Final = (deployment.get("litellm_params") or EMPTY_MAPPING).get("model") or model_name
+            return not is_vision_explicitly_disabled(litellm_model)
+
+        deployments: Final = self.litellm_router_instance.get_model_list(model_name=model_name)
+        if not deployments:
+            return not is_vision_explicitly_disabled(model_name)
+        return all(deployment_accepts(deployment) for deployment in deployments)
+
+    def _modality_eligible_models(self) -> frozenset[str]:
+        """Every configured pool entry, plus default_model, that can serve an image request."""
+        names: Final = frozenset(entry for pool in self._tier_pools().values() for entry in pool) | frozenset(
+            name for name in (self.config.default_model,) if name
+        )
+        return frozenset(name for name in names if self._model_accepts_image_input(name))
+
+    async def _gate_response_modality(
+        self,
+        response: PreRoutingHookResponse,
+        messages: list[dict[str, Any]] | None,  # mutable-ok: forwarded verbatim to the list-typed re-pick
+        resolved_messages: Sequence[Mapping[str, object]] | None,
+        request_kwargs: dict,  # mutable-ok: same shape the hook receives
+    ) -> PreRoutingHookResponse:
+        """Replace a routed model that cannot accept this request's image input.
+
+        The single modality owner, applied to the decided response at the hook's exits so every
+        routing path is covered uniformly. A KEPT session pin is exempt by design (its cause);
+        replacement picks and every other path are just responses. The re-placement walks
+        UPWARD-ONLY from the decision's tier (so a plan-mode floor can never be undercut), picks
+        through `_pick_model_for_tier` so routing plugins still apply, then falls to
+        default_model (never on plugin routers, and never on a plan-floored decision, since
+        default_model carries no tier guarantee), else raises the clear 400. The rewritten
+        decision keeps its cause on a same-tier repick and becomes modality_escalation when the
+        tier moved or default_model took over, with the displaced placement in signals.
+        """
+        decision: Final = response.routing_decision
+        if (
+            not self.config.modality_routing
+            or not resolved_messages
+            or response.model is None
+            or (decision is not None and decision.get("cause") == "session_affinity_pin")
+            or not request_contains_image_content(resolved_messages)
+            or self._model_accepts_image_input(response.model)
+        ):
+            return response
+        eligible: Final = self._modality_eligible_models()
+        names: Final = self.config.tier_names()
+        pools: Final = self._tier_pools()
+        decided: Final = decision.get("tier") if decision is not None else None
+        start: Final = names.index(decided) if isinstance(decided, str) and decided in names else 0
+        capable: Final = next(
+            (name for name in names[start:] if any(entry in eligible for entry in pools.get(name, ()))), None
+        )
+        if capable is not None:
+            new_tier: ComplexityTier | str | None = capable if self.config.has_custom_tiers else ComplexityTier(capable)
+            repick_messages: Final = list(resolved_messages)  # mutable-ok: the pick's param is list-typed
+            new_model = await self._pick_model_for_tier(
+                new_tier,
+                messages,
+                repick_messages,  # pyright: ignore[reportArgumentType]  # hook-resolved message dicts; the pick only reads them
+                request_kwargs,
+                allowed_models=tuple(entry for entry in pools.get(capable, ()) if entry in eligible),
+            )
+        elif self._modality_default_model_usable(request_kwargs, resolved_messages, eligible):
+            new_tier = None
+            new_model = self._placed_default_model()
+        else:
+            import litellm
+
+            raise litellm.BadRequestError(
+                message=(
+                    f"Auto-router {self.model_name} received a request with image input, but no model "
+                    f"at or above the decided tier accepts images and modality_routing is enabled. "
+                    f"Tiers checked: {', '.join(names[start:])}. Add a vision-capable model to a tier, "
+                    f"or set a vision-capable default_model, or remove the image content."
+                ),
+                model=self.model_name,
+                llm_provider="",
+            )
+        self._restamp_adaptive_choice(request_kwargs, response.model, new_model)
+        same_tier: Final = capable is not None and decided == capable
+        base_cause: Final = (decision.get("cause") if decision is not None else None) or "default_fallback"
+        displaced_default: Final = decided is None and response.model == self.config.default_model
+        markers: Final = (
+            "modality:image",
+            *((f"modality_escalated_from:{decided}",) if not same_tier and isinstance(decided, str) else ()),
+            *(("modality_displaced_default_model",) if not same_tier and displaced_default else ()),
+        )
+        old_signals: Final = tuple(decision.get("signals") or ()) if decision is not None else ()
+        new_decision: Final = self._build_routing_decision(
+            routed_model=new_model,
+            cause=base_cause if same_tier else "modality_escalation",
+            tier=new_tier,
+            score=decision.get("score") if decision is not None else None,
+            signals=(*old_signals, *markers),
+            matched_keyword=decision.get("matched_keyword") if decision is not None else None,
+            escalation_keyword=decision.get("escalation_keyword") if decision is not None else None,
+            escalated=bool(decision.get("escalated", False)) if decision is not None else False,
+            classifier_model=decision.get("classifier_model") if decision is not None else None,
+            classifier_cost=decision.get("classifier_cost") if decision is not None else None,
+            conversation_continuing=bool(decision.get("conversation_continuing", True))
+            if decision is not None
+            else True,
+            tier_litellm_params=self._litellm_params_for_model(new_tier, new_model),
+            context_escalation_original_tier=(
+                decision.get("context_escalation_original_tier") if decision is not None else None
+            ),
+        )
+        from litellm.types.router import PreRoutingHookResponse as HookResponse
+
+        return HookResponse(
+            model=new_model,
+            messages=response.messages,
+            litellm_params=self._litellm_params_for_model(new_tier, new_model),
+            routing_decision=new_decision,
+        )
+
+    def _modality_default_model_usable(
+        self,
+        request_kwargs: Mapping[str, object],
+        resolved_messages: Sequence[Mapping[str, object]] | None,
+        eligible: frozenset[str],
+    ) -> bool:
+        """default_model may serve a gated request only when it is configured, plugin-free
+        (it is never checked against the plugin pipeline), capability-eligible, and the turn
+        carries no plan-mode sentinel. The sentinel is re-detected here rather than read off
+        the decision record, because the record only marks turns the floor RAISED; a sentinel
+        turn already at or above the floor keeps its ordinary cause, and default_model carries
+        no tier the floor could vouch for on any sentinel turn."""
+        return (
+            bool(self.config.default_model)
+            and not self.config.plugins
+            and self.config.default_model in eligible
+            and self._matched_plan_mode_signal(request_kwargs, resolved_messages) is None
+        )
+
+    def _placed_default_model(self) -> str:
+        """The default_model behind a usable-default verdict; the raise is the type-level
+        proof, not a reachable path."""
+        model: Final = self.config.default_model
+        if model is None:
+            raise ValueError(f"Auto-router {self.model_name}: modality gate routed to an unset default_model")
+        return model
+
+    @staticmethod
+    def _restamp_adaptive_choice(request_kwargs: Mapping[str, object], old_model: str, new_model: str) -> None:
+        """The adaptive feedback loop reads its chosen-model marker from request metadata; a
+        gate rewrite must move the marker with the model or rewards land on the displaced one."""
+        metadata: Final = request_kwargs.get("metadata")
+        if isinstance(metadata, dict) and metadata.get("adaptive_router_chosen_model") == old_model:
+            metadata["adaptive_router_chosen_model"] = new_model
+
     def _lexical_tier_override(self, user_message: str) -> KeywordOverride | None:
         """When keyword_tier_rules match literally, the most-severe matched tier wins.
 
@@ -2247,14 +2737,18 @@ class ComplexityRouter(CustomLogger):
 
     @property
     def _uses_tier_pin(self) -> bool:
-        return bool(self.config.session_affinity and not self.config.plugins)
+        """classification_mode 'user_turn' implies the tier pin machinery: the pin write after each
+        pinnable classification is what gives a continuation a held decision to replay."""
+        return bool(
+            (self.config.session_affinity or self.config.classification_mode == "user_turn") and not self.config.plugins
+        )
 
     @property
     def _uses_deployment_pin(self) -> bool:
-        """session_affinity implies the deployment pin: a session frozen onto one model
+        """The tier pin implies the deployment pin: a session frozen onto one model
         group but load-balanced across its deployments would still go cache-cold, which
         is the exact failure both flags exist to prevent."""
-        return bool((self.config.deployment_affinity or self.config.session_affinity) and not self.config.plugins)
+        return bool(self.config.deployment_affinity and not self.config.plugins) or self._uses_tier_pin
 
     def _with_session_deployment_affinity(
         self, response: PreRoutingHookResponse | None
@@ -2282,6 +2776,11 @@ class ComplexityRouter(CustomLogger):
         pins the model chosen on the session's first turn and reuses it for every later
         turn, skipping classification entirely. Otherwise delegates to `_classify_and_route`.
 
+        When `classification_mode` is 'user_turn', the same pin is replayed only on
+        continuation turns (an agent loop's tool traffic); a new human ask always falls
+        through to classification, so the session can still move tiers between asks.
+        With both knobs on, session_affinity's pin-first behavior wins.
+
         Skipped entirely when `plugins` are configured: reusing a stale pin would bypass
         the plugin pipeline on every turn after the first, since a pinned model was never
         re-checked against a policy plugin whose decision can change between turns (e.g. a
@@ -2305,7 +2804,13 @@ class ComplexityRouter(CustomLogger):
         session_id: Final = self._get_session_id_from_request_kwargs(request_kwargs) if use_session_affinity else None
         cache_key = self._get_session_affinity_cache_key(session_id, request_kwargs) if session_id is not None else None
 
-        if cache_key is not None:
+        # In 'user_turn' mode a held pin is replayed only on continuation turns; a new human
+        # ask falls through and re-classifies. session_affinity restores pin-first for asks too.
+        pin_replay_allowed: Final = bool(self.config.session_affinity) or not _newest_turn_is_human_ask(
+            resolved_messages, self._reminder_markers
+        )
+
+        if cache_key is not None and pin_replay_allowed:
             pinned_value: Final = await self.litellm_router_instance.cache.async_get_cache(key=cache_key)
             pinned_pin: Final = _parse_session_affinity_pin(pinned_value)
             if pinned_pin is not None:
@@ -2339,6 +2844,26 @@ class ComplexityRouter(CustomLogger):
                     session_model: Final = routed_model
                     if plan_floored and pinned_tier is not None:
                         routed_model = self.get_model_for_tier(self._apply_plan_mode_floor(pinned_tier))
+                    pin_source_tier: Final = self._tier_for_model(routed_model)
+                    pin_placement: Final = (
+                        await self._context_window_placement(
+                            pin_source_tier, resolved_messages, request_kwargs, pool_override=(routed_model,)
+                        )
+                        if pin_source_tier is not None
+                        else None
+                    )
+                    pin_context_original_tier: Final = (
+                        pin_source_tier
+                        if pin_placement is not None
+                        and pin_source_tier is not None
+                        and _tier_name(pin_placement.tier) != _tier_name(pin_source_tier)
+                        else None
+                    )
+                    if pin_placement is not None and pin_context_original_tier is not None:
+                        # The stored pin below keeps the session's own model on purpose.
+                        routed_model = self._pick_from_tier_value(
+                            pin_placement.allowed_models, _tier_name(pin_placement.tier)
+                        )
                     # Refresh the TTL on every hit so an active session doesn't lose its
                     # pin mid-conversation just because it outlives the original write.
                     await self.litellm_router_instance.cache.async_set_cache(
@@ -2354,36 +2879,47 @@ class ComplexityRouter(CustomLogger):
                         kwargs_metadata: Final = request_kwargs.setdefault("metadata", {})
                         if isinstance(kwargs_metadata, dict):
                             kwargs_metadata[ADAPTIVE_ROUTER_CHOSEN_MODEL_KEY] = routed_model
+                    replay_cause: Final[RoutingDecisionCause] = (
+                        "session_affinity_pin" if self.config.session_affinity else "user_turn_continuation"
+                    )
                     cause: RoutingDecisionCause = (
-                        "plan_mode"
-                        if plan_floored
-                        else ("session_affinity_escalation" if escalated else "session_affinity_pin")
+                        "plan_mode" if plan_floored else ("session_affinity_escalation" if escalated else replay_cause)
                     )
                     verbose_router_logger.info(
                         "ComplexityRouter: routing decision cause=%s, routed_model=%s", cause, routed_model
                     )
-                    routed_pin_tier: Final = self._tier_for_model(routed_model) if plan_floored else resolved_pin_tier
+                    routed_pin_tier: Final = (
+                        pin_placement.tier
+                        if pin_placement is not None and pin_context_original_tier is not None
+                        else (self._tier_for_model(routed_model) if plan_floored else resolved_pin_tier)
+                    )
                     session_tier_litellm_params: Final = self._litellm_params_for_model(routed_pin_tier, routed_model)
                     has_original_messages: Final = messages is not None and len(messages) > 0
                     return self._with_session_deployment_affinity(
-                        PreRoutingHookResponse(
-                            model=routed_model,
-                            messages=messages if has_original_messages else None,
-                            litellm_params=session_tier_litellm_params,
-                            routing_decision=self._build_routing_decision(
-                                routed_model=routed_model,
-                                cause=cause,
-                                tier=routed_pin_tier,
-                                matched_keyword=pin_plan_sentinel if plan_floored else None,
-                                escalation_keyword=pin_escalation_keyword,
-                                escalated=escalated,
-                                conversation_continuing=conversation_continuing,
-                                tier_litellm_params=session_tier_litellm_params,
+                        await self._gate_response_modality(
+                            PreRoutingHookResponse(
+                                model=routed_model,
+                                messages=messages if has_original_messages else None,
+                                litellm_params=session_tier_litellm_params,
+                                routing_decision=self._build_routing_decision(
+                                    routed_model=routed_model,
+                                    cause=cause,
+                                    tier=routed_pin_tier,
+                                    matched_keyword=pin_plan_sentinel if plan_floored else None,
+                                    escalation_keyword=pin_escalation_keyword,
+                                    escalated=escalated,
+                                    conversation_continuing=conversation_continuing,
+                                    tier_litellm_params=session_tier_litellm_params,
+                                    context_escalation_original_tier=pin_context_original_tier,
+                                ),
                             ),
+                            messages,
+                            resolved_messages,
+                            request_kwargs,
                         )
                     )
 
-        response: Final = await self._classify_and_route(
+        routed_response: Final = await self._classify_and_route(
             model=model,
             request_kwargs=request_kwargs,
             messages=messages,
@@ -2392,6 +2928,11 @@ class ComplexityRouter(CustomLogger):
             conversation_continuing=conversation_continuing,
             resolved_messages=resolved_messages,
         )
+        response: Final = (
+            await self._gate_response_modality(routed_response, messages, resolved_messages, request_kwargs)
+            if routed_response is not None
+            else None
+        )
         # Sentinel presence, not the plan_mode cause, gates the pin write: a plan-mode turn
         # classified at or above the floor keeps its ordinary cause, yet on an adaptive router
         # the hard floor constrained its pick, so pinning it would carry a plan-mode-shaped
@@ -2573,6 +3114,8 @@ class ComplexityRouter(CustomLogger):
         plan_floored: Final = tier != pre_floor_tier
         if plan_floored:
             signals = (*signals, "plan_mode_floor")
+        context_placement: Final = await self._context_window_placement(tier, resolved_messages, request_kwargs)
+        tier, signals, context_original_tier = _apply_context_placement(tier, signals, context_placement)
         score_repr: Final = f"{score:.3f}" if score is not None else "n/a"
         fallback_model: Final = self.config.default_model if not self.config.plugins else None
         # A sentinel-carrying request skips the failure exit below, whether or not the floor
@@ -2619,8 +3162,15 @@ class ComplexityRouter(CustomLogger):
             # the cheapest tier would then contradict the floor and bound the pick below the tier
             # the decision reports.
             housekeeping_ceiling: Final = tier if outcome.cause == "housekeeping" else None
+            # A context-escalated tier becomes the hard floor: a floor the bandit can slide
+            # under is not a floor.
             routed_model = self._soft_floor_pick(
-                tier, user_message, request_kwargs, hard_floor=plan_floor, hard_ceiling=housekeeping_ceiling
+                tier,
+                user_message,
+                request_kwargs,
+                hard_floor=tier if context_original_tier is not None else plan_floor,
+                hard_ceiling=housekeeping_ceiling,
+                fit_filter=context_placement.holdable_models if context_placement is not None else None,
             )
             adaptive: Final = self._ensure_adaptive_router()
             if adaptive is not None:
@@ -2637,7 +3187,13 @@ class ComplexityRouter(CustomLogger):
                 routed_model,
             )
         else:
-            routed_model = await self._pick_model_for_tier(tier, messages, resolved_messages, request_kwargs)
+            routed_model = await self._pick_model_for_tier(
+                tier,
+                messages,
+                resolved_messages,
+                request_kwargs,
+                allowed_models=context_placement.allowed_models if context_placement is not None else None,
+            )
             verbose_router_logger.info(
                 "ComplexityRouter: routing decision cause=%s, tier=%s, score=%s, signals=%s, routed_model=%s",
                 outcome.cause,
@@ -2690,5 +3246,6 @@ class ComplexityRouter(CustomLogger):
                 classifier_model=classifier_model,
                 classifier_cost=outcome.classifier_cost,
                 tier_litellm_params=tier_litellm_params,
+                context_escalation_original_tier=context_original_tier,
             ),
         )
diff --git a/litellm/router_strategy/complexity_router/config.py b/litellm/router_strategy/complexity_router/config.py
index 335de11e669..0ae0db63fad 100644
--- a/litellm/router_strategy/complexity_router/config.py
+++ b/litellm/router_strategy/complexity_router/config.py
@@ -14,6 +14,8 @@ from pydantic import BaseModel, ConfigDict, Field, SkipValidation, field_seriali
 
 from litellm.types.router import AdaptiveRouterWeights, ClassifierPlugin, RoutingPlugin
 
+from .tier_predictor import TrainedTierArtifact
+
 
 class ComplexityTier(str, Enum):
     """Complexity tiers for routing decisions."""
@@ -41,7 +43,7 @@ DEFAULT_CLASSIFICATION_RUBRIC: Final[ClassificationRubric] = ClassificationRubri
 # The classifier_type values that can call classifier_llm_config.model. Every consumer asking
 # "is the classifier model a real dependency of this router" resolves it here, including the ones
 # that only hold the raw config mapping and cannot reach ComplexityRouterConfig.uses_llm_classifier.
-LLM_CLASSIFIER_TYPES: Final[frozenset[str]] = frozenset({"llm", "heuristic_first"})
+LLM_CLASSIFIER_TYPES: Final[frozenset[str]] = frozenset({"llm", "heuristic_first", "hybrid"})
 
 
 TIER_SEVERITY_ORDER: Final[tuple[ComplexityTier, ...]] = (
@@ -625,17 +627,28 @@ class ComplexityRouterConfig(BaseModel):
     )
 
     # Classifier strategy
-    classifier_type: Literal["heuristic", "llm", "custom", "heuristic_first"] = Field(
+    classifier_type: Literal["heuristic", "heuristic_v2", "llm", "custom", "heuristic_first", "hybrid"] = Field(
         default="heuristic",
         description=(
-            "Classification strategy: local regex/keyword scoring, an LLM call, a custom classifier "
-            "plugin, or 'heuristic_first', which scores locally and only pays for the LLM classifier "
-            "when the local scorer does not confidently land a cheap tier"
+            "Classification strategy: local regex/keyword scoring, the bundled trained four-tier heuristic, "
+            "an LLM call, a custom classifier plugin, 'heuristic_first', which scores locally and only pays "
+            "for the LLM classifier when the local scorer does not confidently land a cheap tier, or 'hybrid', "
+            "which trusts the local scorer everywhere except when its score lands near a tier boundary"
+        ),
+    )
+    heuristic_v2_artifact: TrainedTierArtifact | Literal["ultrafeedback"] = Field(
+        default="ultrafeedback",
+        description=(
+            "Success-probability artifact used by classifier_type 'heuristic_v2'. The bundled "
+            "UltraFeedback artifact is selected by default; an inline trained artifact may replace it"
         ),
     )
     classifier_llm_config: ClassifierLLMConfig | None = Field(
         default=None,
-        description="Configuration for the LLM classifier; required when classifier_type is 'llm' or 'heuristic_first'",
+        description=(
+            "Configuration for the LLM classifier; required when classifier_type is 'llm', "
+            "'heuristic_first' or 'hybrid'"
+        ),
     )
     heuristic_first_max_tier: str | None = Field(
         default=None,
@@ -650,6 +663,19 @@ class ComplexityRouterConfig(BaseModel):
             "may not name the highest one, since that would make the LLM classifier unreachable."
         ),
     )
+    hybrid_boundary_margin: float | None = Field(
+        default=None,
+        ge=0,
+        le=1,
+        description=(
+            "How close to a tier boundary a heuristic score has to land before the LLM classifier breaks the "
+            "tie; required when classifier_type is 'hybrid' and rejected otherwise. Everything further than "
+            "this from every active boundary routes on the scorer's own tier with no classifier call, at any "
+            "tier, which is what separates 'hybrid' from 'heuristic_first' and its cheap-tier ceiling. A "
+            "prompt where no dimension fired still goes to the classifier, since the scorer has no opinion "
+            "to be near a boundary with. 0 escalates only scores sitting exactly on a boundary."
+        ),
+    )
     classifier_plugin: ClassifierPlugin | None = Field(
         default=None,
         description=(
@@ -823,6 +849,44 @@ class ComplexityRouterConfig(BaseModel):
         ),
     )
 
+    enable_context_window_escalation: bool = Field(
+        default=True,
+        description=(
+            "Escalate a request off a tier whose models provably cannot hold its prompt, before "
+            "dispatch. The classifier scores complexity and never prompt size, so a long agentic "
+            "session whose newest ask is trivial lands on a small-window tier and the provider "
+            "rejects it with a context-window 400 that nothing retries. When every model of the "
+            "decided tier has a declared window smaller than the estimated prompt, the request "
+            "moves to the lowest configured tier with a model whose declared window fits; when "
+            "only some of the tier's models fit, the pick is restricted to those and the tier "
+            "keeps the request. Models with no resolvable window are never escalated away from "
+            "and never escalated onto. Set false to dispatch on complexity alone, as before."
+        ),
+    )
+    context_window_escalation_buffer: float = Field(
+        default=0.95,
+        gt=0,
+        le=1,
+        description=(
+            "Fraction of a model's declared context window the estimated prompt must fit within. "
+            "The token count is an estimate, so fitting against the full window would dispatch "
+            "prompts that the provider's own tokenizer then rejects; 0.95 leaves room for that "
+            "drift plus the response tokens."
+        ),
+    )
+    modality_routing: bool = Field(
+        default=False,
+        description=(
+            "Route image-bearing requests only to models that can accept image input. The "
+            "classifier reads text alone, so an image request whose text classifies cheap "
+            "otherwise lands on a text-only model and fails with a provider 400. When enabled, "
+            "a routed model explicitly declared supports_vision false (deployment model_info "
+            "or the model cost map; unmapped names stay routable) is replaced by the nearest "
+            "HIGHER tier holding a capable model, then default_model, else a clear 400. A kept "
+            "session-affinity pin still wins even when an image arrives."
+        ),
+    )
+
     # Semantic (embedding) matching for keyword_tier_rules instead of literal text matching
     semantic_keyword_matching: bool = Field(
         default=False,
@@ -839,6 +903,21 @@ class ComplexityRouterConfig(BaseModel):
         description="Minimum cosine similarity for a semantic keyword match",
     )
 
+    classification_mode: Literal["every_request", "user_turn"] = Field(
+        default="every_request",
+        description=(
+            "When to run the complexity classifier. 'every_request' (the default) classifies every "
+            "inference request, including the tool-result continuation turns of an agentic loop. "
+            "'user_turn' classifies only requests whose newest turn is a new human ask and replays "
+            "the session's held routing decision on continuation turns, which cuts classifier "
+            "spend and eliminates mid-loop model switches. Continuations with no held decision to "
+            "replay (no resolvable session_id, expired pin, fresh restart) still classify. Unlike "
+            "session_affinity, a new human ask always re-classifies, so a session can still move "
+            "tiers between asks. Suppressed when plugins are configured, for the same reason "
+            "session_affinity is: a replayed decision would bypass the plugin pipeline."
+        ),
+    )
+
     # Session affinity: pin the first turn's routed model for the rest of the session
     session_affinity: bool = Field(
         default=False,
@@ -1073,6 +1152,23 @@ class ComplexityRouterConfig(BaseModel):
             )
         return self
 
+    @model_validator(mode="after")
+    def _validate_hybrid_boundary_margin(self) -> "ComplexityRouterConfig":
+        if self.classifier_type != "hybrid":
+            if self.hybrid_boundary_margin is not None:
+                raise ValueError(
+                    f"hybrid_boundary_margin is set but classifier_type is {self.classifier_type!r}; "
+                    "the scorer would never consult the classifier on a near-boundary score. Set "
+                    "classifier_type 'hybrid' or remove hybrid_boundary_margin"
+                )
+            return self
+        if self.hybrid_boundary_margin is None:
+            raise ValueError(
+                "hybrid_boundary_margin is required when classifier_type is 'hybrid': without a margin no "
+                "score is ever near enough to a boundary to escalate, which is classifier_type 'heuristic'"
+            )
+        return self
+
     @field_validator("fallback_tier")
     @classmethod
     def _reject_blank_optional_text(cls, value: str | None) -> str | None:
@@ -1195,10 +1291,10 @@ class ComplexityRouterConfig(BaseModel):
         )
         if duplicated:
             raise ValueError(f"tier_definitions names must be unique (case-insensitive): {', '.join(duplicated)}")
-        if self.classifier_type in ("heuristic", "heuristic_first"):
+        if self.classifier_type in ("heuristic", "heuristic_v2", "heuristic_first", "hybrid"):
             raise ValueError(
                 "tier_definitions requires classifier_type 'llm' or 'custom': the heuristic scorer only "
-                "produces the built-in tiers"
+                "produces the four built-in tiers, as does heuristic_v2"
             )
         conflicts: Final = self._tier_definition_conflicts()
         if conflicts:
diff --git a/litellm/router_strategy/complexity_router/tier_predictor.py b/litellm/router_strategy/complexity_router/tier_predictor.py
new file mode 100644
index 00000000000..764f6e6ad56
--- /dev/null
+++ b/litellm/router_strategy/complexity_router/tier_predictor.py
@@ -0,0 +1,156 @@
+from __future__ import annotations
+
+import re
+from collections.abc import Mapping
+from dataclasses import dataclass
+from pathlib import Path
+from types import MappingProxyType
+from typing import Final, Literal
+
+from pydantic import BaseModel, Field, model_validator
+
+from litellm.types.router import RequestType
+
+
+class TierGlobalStatistic(BaseModel):
+    tier: int = Field(ge=1, le=4)
+    successes: float = Field(ge=0.0)
+    observations: float = Field(gt=0.0)
+
+    @model_validator(mode="after")
+    def _successes_do_not_exceed_observations(self) -> TierGlobalStatistic:
+        if self.successes > self.observations:
+            raise ValueError("successes cannot exceed observations")
+        return self
+
+
+class TierDomainStatistic(TierGlobalStatistic):
+    request_type: RequestType
+
+
+class TierCohortStatistic(TierGlobalStatistic):
+    cohort: str = Field(min_length=1)
+
+
+class TierDataset(BaseModel):
+    name: str = Field(min_length=1)
+    url: str = Field(min_length=1)
+    license: str = Field(min_length=1)
+    rows: int = Field(gt=0)
+    success_definition: str = Field(default="quality score meets the dataset success threshold", min_length=1)
+
+
+class TrainedTierArtifact(BaseModel):
+    schema_version: Literal[1] = 1
+    global_statistics: tuple[TierGlobalStatistic, ...]
+    domain_statistics: tuple[TierDomainStatistic, ...] = ()
+    cohort_statistics: tuple[TierCohortStatistic, ...] = ()
+    domain_prior_mass: float = Field(default=200.0, gt=0.0)
+    cohort_prior_mass: float = Field(default=20.0, gt=0.0)
+    routing_threshold: float = Field(default=0.75, ge=0.0, le=1.0)
+    datasets: tuple[TierDataset, ...] = ()
+    success_definition: str = Field(default="quality score meets the dataset success threshold", min_length=1)
+    split_method: str = Field(default="sha256(prompt): 70% train, 15% validation, 15% test", min_length=1)
+
+    @model_validator(mode="after")
+    def _statistics_are_unique(self) -> TrainedTierArtifact:
+        global_tiers: Final = tuple(stat.tier for stat in self.global_statistics)
+        if frozenset(global_tiers) != frozenset((1, 2, 3, 4)) or len(global_tiers) != 4:
+            raise ValueError("global statistics must contain each tier exactly once")
+        domain_keys: Final = tuple((stat.request_type, stat.tier) for stat in self.domain_statistics)
+        if len(domain_keys) != len(frozenset(domain_keys)):
+            raise ValueError("domain statistics must contain unique request_type and tier pairs")
+        cohort_keys: Final = tuple((stat.cohort, stat.tier) for stat in self.cohort_statistics)
+        if len(cohort_keys) != len(frozenset(cohort_keys)):
+            raise ValueError("cohort statistics must contain unique cohort and tier pairs")
+        return self
+
+
+_CODE_PATTERN: Final = re.compile(
+    r"```|\b(def|class|function|python|javascript|typescript|sql|code)\b",
+    re.IGNORECASE,
+)
+_MATH_PATTERN: Final = re.compile(
+    r"\b(solve|calculate|equation|probability|theorem|proof|integral)\b|[$=]",
+    re.IGNORECASE,
+)
+_MULTIPLE_CHOICE_PATTERN: Final = re.compile(r"(?:^|\s)[A-D][.)]\s")
+_TIERS: Final = (1, 2, 3, 4)
+_BUILTIN_ARTIFACTS: Final = MappingProxyType({"ultrafeedback": "ultrafeedback_tiers.json"})
+
+
+def resolve_tier_artifact(artifact: TrainedTierArtifact | str) -> TrainedTierArtifact:
+    if isinstance(artifact, TrainedTierArtifact):
+        return artifact
+    filename: Final = _BUILTIN_ARTIFACTS.get(artifact)
+    if filename is None:
+        raise ValueError(f"unknown complexity router tier artifact: {artifact}")
+    path: Final = Path(__file__).with_name("artifacts") / filename
+    return TrainedTierArtifact.model_validate_json(path.read_text())
+
+
+def similarity_cohort(prompt: str, request_type: RequestType) -> str:
+    length: Final = len(prompt)
+    length_bucket: Final = (
+        "short" if length < 200 else "medium" if length < 800 else "long" if length < 2000 else "very_long"
+    )
+    code: Final = int(bool(_CODE_PATTERN.search(prompt)))
+    math: Final = int(bool(_MATH_PATTERN.search(prompt)))
+    multiple_choice: Final = int(bool(_MULTIPLE_CHOICE_PATTERN.search(prompt)))
+    non_ascii: Final = int(sum(ord(character) > 127 for character in prompt) / max(1, length) > 0.1)
+    return f"{request_type.value}|{length_bucket}|code={code}|math={math}|mc={multiple_choice}|intl={non_ascii}"
+
+
+@dataclass(frozen=True, slots=True)
+class TierPrediction:
+    probabilities: Mapping[int, float]
+    required_tier: int
+
+
+class TierSuccessPredictor:
+    def __init__(self, artifact: TrainedTierArtifact) -> None:
+        self._artifact = artifact
+        self._global: Mapping[int, TierGlobalStatistic] = MappingProxyType(
+            {stat.tier: stat for stat in artifact.global_statistics}
+        )
+        self._domain: Mapping[tuple[RequestType, int], TierDomainStatistic] = MappingProxyType(
+            {(stat.request_type, stat.tier): stat for stat in artifact.domain_statistics}
+        )
+        self._cohort: Mapping[tuple[str, int], TierCohortStatistic] = MappingProxyType(
+            {(stat.cohort, stat.tier): stat for stat in artifact.cohort_statistics}
+        )
+
+    @property
+    def routing_threshold(self) -> float:
+        return self._artifact.routing_threshold
+
+    def predict(self, prompt: str, request_type: RequestType) -> TierPrediction:
+        cohort: Final = similarity_cohort(prompt, request_type)
+        raw: Final = tuple(self._probability(tier, request_type, cohort) for tier in _TIERS)
+        monotonic: Final = tuple(max(raw[:index]) for index in range(1, len(raw) + 1))
+        probabilities: Final[Mapping[int, float]] = MappingProxyType(
+            {int(tier): probability for tier, probability in zip(_TIERS, monotonic)}
+        )
+        required_tier: Final = next(
+            (tier for tier in _TIERS if probabilities[tier] >= self._artifact.routing_threshold),
+            4,
+        )
+        return TierPrediction(probabilities=probabilities, required_tier=required_tier)
+
+    def _probability(self, tier: int, request_type: RequestType, cohort: str) -> float:
+        global_stat: Final = self._global[tier]
+        global_mean: Final = (global_stat.successes + 1.0) / (global_stat.observations + 2.0)
+        domain_stat: Final = self._domain.get((request_type, tier))
+        domain_mean: Final = self._posterior_mean(domain_stat, self._artifact.domain_prior_mass, global_mean)
+        cohort_stat: Final = self._cohort.get((cohort, tier))
+        return self._posterior_mean(cohort_stat, self._artifact.cohort_prior_mass, domain_mean)
+
+    @staticmethod
+    def _posterior_mean(
+        statistic: TierGlobalStatistic | None,
+        prior_mass: float,
+        prior_mean: float,
+    ) -> float:
+        if statistic is None:
+            return prior_mean
+        return (statistic.successes + prior_mass * prior_mean) / (statistic.observations + prior_mass)
diff --git a/litellm/router_strategy/tag_based_routing.py b/litellm/router_strategy/tag_based_routing.py
index e4ac45df4d5..eabd9278cf6 100644
--- a/litellm/router_strategy/tag_based_routing.py
+++ b/litellm/router_strategy/tag_based_routing.py
@@ -8,16 +8,14 @@ Use this to route requests between Teams
 """
 
 import re
-from collections.abc import Iterable, Mapping, Sequence
+from collections.abc import Mapping, Sequence
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict
-
-from typing_extensions import ReadOnly
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, overload
 
 from litellm._logging import verbose_logger
 from litellm.constants import CONSUMED_REQUEST_TAGS_METADATA_KEY
 from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs
-from litellm.types.router import ConsumedRequestTagsStamp, RouterErrors
+from litellm.types.router import ConsumedRequestTagsStamp, DeploymentTypedDict, RouterErrors
 
 if TYPE_CHECKING:
     from litellm.router import Router as _Router
@@ -27,34 +25,63 @@ else:
     LitellmRouter = Any
 
 
-class _TagRoutingLitellmParams(TypedDict, total=False):
-    tags: ReadOnly[Sequence[str] | None]
-    tag_regex: ReadOnly[Sequence[str] | None]
+class _TagLitellmParamsLike(Protocol):
+    @overload
+    def get(self, key: Literal["tags"], /) -> Sequence[str] | None: ...
+    @overload
+    def get(self, key: Literal["tags"], default: Sequence[str], /) -> Sequence[str]: ...
+    @overload
+    def get(self, key: Literal["tag_regex"], /) -> Sequence[str] | None: ...
 
 
-class _TagRoutingDeployment(TypedDict, total=False):
-    model_name: ReadOnly[str]
-    litellm_params: ReadOnly[_TagRoutingLitellmParams]
-    model_info: ReadOnly[Mapping[str, object] | None]
+class _ModelInfoLike(Protocol):
+    @overload
+    def get(self, key: Literal["allow_fail_open"], /) -> bool | None: ...
+    @overload
+    def get(self, key: Literal["enable_tag_filtering"], /) -> bool | None: ...
 
 
-class _TagRoutingMatchStamp(TypedDict):
-    matched_deployment: ReadOnly[str | None]
-    matched_via: ReadOnly[str]
-    matched_value: ReadOnly[str]
-    request_tags: ReadOnly[Sequence[str]]
-    user_agent: ReadOnly[str]
+class _DeploymentLike(Protocol):
+    @overload
+    def get(self, key: Literal["litellm_params"], default: Mapping[str, object], /) -> _TagLitellmParamsLike: ...
+    @overload
+    def get(self, key: Literal["model_info"], /) -> _ModelInfoLike | None: ...
+    @overload
+    def get(self, key: Literal["model_name"], /) -> object: ...
 
 
-class _TagRoutingMetadata(TypedDict, total=False):
-    tags: ReadOnly[Sequence[str] | None]
-    inherited_tags: ReadOnly[Sequence[str] | None]
-    user_agent: ReadOnly[str]
-    tag_routing: ReadOnly[_TagRoutingMatchStamp]
-    _consumed_request_tags: ReadOnly[object]
+class _MetadataLike(Protocol):
+    @overload
+    def get(self, key: Literal["tags"], /) -> Sequence[str] | None: ...
+    @overload
+    def get(self, key: Literal["tags"], default: Sequence[str], /) -> Sequence[str] | None: ...
+    @overload
+    def get(self, key: Literal["user_agent"], default: str, /) -> str: ...
+    @overload
+    def get(self, key: Literal["inherited_tags"], /) -> object: ...
+    def __contains__(self, key: object, /) -> bool: ...
+    def __setitem__(self, key: Literal["tag_routing"], value: Mapping[str, object], /) -> None: ...
 
 
-_EMPTY_MODEL_INFO: Final[Mapping[str, object]] = MappingProxyType({})
+class _NestedLitellmParamsLike(Protocol):
+    def get(
+        self, key: Literal["metadata", "litellm_metadata"], default: Mapping[str, object], /
+    ) -> _MetadataLike | None: ...
+
+
+class _RequestKwargsLike(Protocol):
+    @overload
+    def get(self, key: Literal["enable_tag_filtering"], /) -> bool | None: ...
+    @overload
+    def get(self, key: Literal["metadata", "litellm_metadata"], /) -> _MetadataLike | None: ...
+    def __contains__(self, key: object, /) -> bool: ...
+    @overload
+    def __getitem__(self, key: Literal["metadata", "litellm_metadata"], /) -> _MetadataLike: ...
+    @overload
+    def __getitem__(self, key: Literal["litellm_params"], /) -> _NestedLitellmParamsLike: ...
+
+
+_DeploymentPool = Sequence[_DeploymentLike] | Mapping[_DeploymentLike, object]
 
 
 def _is_valid_deployment_tag_regex(
@@ -109,11 +136,11 @@ def is_valid_deployment_tag(
 
 
 def _match_deployment(
-    deployment: _TagRoutingDeployment,
-    request_tags: Sequence[str] | None,
-    header_strings: Sequence[str],
+    deployment: _DeploymentLike,
+    request_tags: list[str] | None,
+    header_strings: list[str],
     match_any: bool,
-) -> Mapping[str, str] | None:
+) -> dict[str, str] | None:
     """
     Determine whether *deployment* matches the current request.
 
@@ -198,38 +225,38 @@ def _split_tags(tags: Sequence[str]) -> tuple[tuple[str, ...], list[str], tuple[
 
 
 def _exclude_deployments(
-    deployments: Iterable[_TagRoutingDeployment],
+    deployments: _DeploymentPool,
     excluded_set: frozenset[str],
-) -> list[_TagRoutingDeployment]:
+) -> Sequence[_DeploymentLike]:
     if not excluded_set:
         return list(deployments)
     return [d for d in deployments if not excluded_set.intersection(d.get("litellm_params", {}).get("tags") or [])]
 
 
 def _require_all_tags(
-    deployments: Iterable[_TagRoutingDeployment],
+    deployments: _DeploymentPool,
     required_set: frozenset[str],
-) -> tuple[_TagRoutingDeployment, ...]:
+) -> tuple[_DeploymentLike, ...]:
     if not required_set:
         return tuple(deployments)
     return tuple(d for d in deployments if required_set.issubset(d.get("litellm_params", {}).get("tags") or []))
 
 
 def _default_tagged_pool(
-    deployments: Iterable[_TagRoutingDeployment],
-) -> tuple[_TagRoutingDeployment, ...]:
+    deployments: _DeploymentPool,
+) -> tuple[_DeploymentLike, ...]:
     defaults: Final = tuple(d for d in deployments if "default" in (d.get("litellm_params", {}).get("tags") or []))
     return defaults if defaults else tuple(deployments)
 
 
-def _known_tag_values(deployments: Iterable[_TagRoutingDeployment]) -> frozenset[str]:
+def _known_tag_values(deployments: _DeploymentPool) -> frozenset[str]:
     return frozenset(
-        tag for d in deployments for tag in (d.get("litellm_params", _TagRoutingLitellmParams()).get("tags") or ())
+        tag for d in deployments for tag in (d.get("litellm_params", MappingProxyType({})).get("tags") or ())
     )
 
 
 def _unknown_required_tag_hides_an_answer(
-    healthy_deployments: Iterable[_TagRoutingDeployment],
+    healthy_deployments: _DeploymentPool,
     excluded_set: frozenset[str],
     required_set: frozenset[str],
     routing_confirmed: frozenset[str],
@@ -253,23 +280,23 @@ def _unknown_required_tag_hides_an_answer(
 
 
 def _chain_allows_fail_open(
-    healthy_deployments: Iterable[_TagRoutingDeployment],
+    healthy_deployments: _DeploymentPool,
     excluded_set: frozenset[str],
     required_set: frozenset[str],
     routing_confirmed: frozenset[str],
 ) -> bool:
     if _unknown_required_tag_hides_an_answer(healthy_deployments, excluded_set, required_set, routing_confirmed):
         return False
-    return any((d.get("model_info") or _EMPTY_MODEL_INFO).get("allow_fail_open") is True for d in healthy_deployments)
+    return any((d.get("model_info") or {}).get("allow_fail_open") is True for d in healthy_deployments)
 
 
 def _trusted_only_pool(
-    healthy_deployments: Iterable[_TagRoutingDeployment],
+    healthy_deployments: _DeploymentPool,
     excluded_set: frozenset[str],
     required_set: frozenset[str],
     inherited_excluded_set: frozenset[str] | None,
     inherited_required_set: frozenset[str] | None,
-) -> tuple[_TagRoutingDeployment, ...]:
+) -> tuple[_DeploymentLike, ...]:
     # inherited_*_set is None only when this request carries no origin information
     # at all (e.g. direct SDK Router usage, bypassing the proxy layer that
     # populates metadata.inherited_tags) -- treat every constraint as
@@ -296,8 +323,8 @@ def _trusted_only_pool(
 
 
 def _resolve_or_fail_open(
-    pool: Sequence[_TagRoutingDeployment],
-    healthy_deployments: Iterable[_TagRoutingDeployment],
+    pool: Sequence[_DeploymentLike],
+    healthy_deployments: _DeploymentPool,
     excluded_set: frozenset[str],
     required_set: frozenset[str],
     inherited_excluded_set: frozenset[str] | None,
@@ -305,7 +332,7 @@ def _resolve_or_fail_open(
     routing_confirmed: frozenset[str],
     model: str,
     request_tags: object,
-) -> tuple[_TagRoutingDeployment, ...]:
+) -> tuple[_DeploymentLike, ...]:
     if pool:
         return tuple(pool)
     if _chain_allows_fail_open(healthy_deployments, excluded_set, required_set, routing_confirmed):
@@ -325,7 +352,7 @@ def _resolve_or_fail_open(
 
 
 def _resolve_constraint_only_pool(
-    healthy_deployments: Iterable[_TagRoutingDeployment],
+    healthy_deployments: _DeploymentPool,
     excluded_set: frozenset[str],
     required_set: frozenset[str],
     inherited_excluded_set: frozenset[str] | None,
@@ -333,7 +360,7 @@ def _resolve_constraint_only_pool(
     routing_confirmed: frozenset[str],
     model: str,
     request_tags: object,
-) -> tuple[_TagRoutingDeployment, ...]:
+) -> tuple[_DeploymentLike, ...]:
     pool: Final = (
         _require_all_tags(_exclude_deployments(healthy_deployments, excluded_set), required_set)
         if required_set
@@ -355,8 +382,8 @@ def _resolve_constraint_only_pool(
 def _all_deployments_or_fallback(
     llm_router_instance: LitellmRouter,
     model: str,
-    fallback: Iterable[_TagRoutingDeployment],
-) -> Iterable[_TagRoutingDeployment]:
+    fallback: _DeploymentPool,
+) -> Sequence[_DeploymentLike | DeploymentTypedDict] | Mapping[_DeploymentLike, object]:
     try:
         return llm_router_instance._get_all_deployments(model_name=model)
     except Exception:  # noqa: BLE001  # fail safe toward today's healthy-only behavior on lookup errors
@@ -366,8 +393,8 @@ def _all_deployments_or_fallback(
 def _chain_tag_filtering_override(
     llm_router_instance: LitellmRouter,
     model: str,
-    healthy_deployments: Iterable[_TagRoutingDeployment],
-) -> object:
+    healthy_deployments: _DeploymentPool,
+) -> bool | None:
     # Resolved from every deployment configured for this model group, not just the
     # ones that survived cooldown/health filtering (async_get_healthy_deployments
     # filters cooldowns before calling get_deployments_for_tag) -- otherwise the
@@ -379,14 +406,14 @@ def _chain_tag_filtering_override(
     # than crashing the request.
     all_deployments: Final = _all_deployments_or_fallback(llm_router_instance, model, healthy_deployments)
     for d in all_deployments:
-        value = (d.get("model_info") or _EMPTY_MODEL_INFO).get("enable_tag_filtering")
+        value = (d.get("model_info") or MappingProxyType({})).get("enable_tag_filtering")
         if value is not None:
             return value
     return None
 
 
 def _inherited_constraint_sets(
-    inherited_tags: Sequence[str] | None, routing_prefix: str
+    inherited_tags: object, routing_prefix: str
 ) -> tuple[frozenset[str] | None, frozenset[str] | None]:
     # None means no origin information is available at all (e.g. this request
     # bypassed the proxy layer that populates metadata.inherited_tags, as direct
@@ -417,43 +444,42 @@ def _tag_known_to_group(
     if tag_set & routing_confirmed:
         return True
     try:
-        all_deployments: Final[Sequence[_TagRoutingDeployment]] = llm_router_instance._get_all_deployments(
-            model_name=model
-        )
+        all_deployments: Final = llm_router_instance._get_all_deployments(model_name=model)
     except Exception:  # noqa: BLE001  # fail safe toward "unrecognized" so lookup errors preserve the existing silent-fallback behavior
         return False
     return any(
-        tag_set.intersection(d.get("litellm_params", _TagRoutingLitellmParams()).get("tags") or ())
-        for d in all_deployments
+        tag_set.intersection(d.get("litellm_params", MappingProxyType({})).get("tags") or ()) for d in all_deployments
     )
 
 
-def _request_tags_after_router_consumption(metadata: _TagRoutingMetadata, model: str) -> Sequence[str] | None:
+def _request_tags_after_router_consumption(metadata: object, model: str) -> Sequence[str] | None:
     # The pre-routing hook stamps which tags selected the router it rewrote the request
     # to: those tags already did their job and must not also constrain deployment choice
     # inside the routed group. The request's other tags still apply there, on top of the
     # inherited_tags snapshot that keeps key/team policy applying. Every other model
     # group keeps the full list.
-    stamp: Final = metadata.get(CONSUMED_REQUEST_TAGS_METADATA_KEY)
+    if not isinstance(metadata, Mapping):
+        return None
+    typed_metadata: Final[Mapping[str, object]] = metadata
+    request_tags: Final = _tags_in_metadata(typed_metadata)
+    stamp: Final = typed_metadata.get(CONSUMED_REQUEST_TAGS_METADATA_KEY)
     if not isinstance(stamp, ConsumedRequestTagsStamp) or stamp.model_group != model:
-        return metadata.get("tags")
-    request_tags: Final = metadata.get("tags")
-    leftover: Final = tuple(
-        tag for tag in (request_tags if isinstance(request_tags, (list, tuple)) else ()) if tag not in stamp.tags
-    )
-    inherited_tags: Final = metadata.get("inherited_tags")
+        return request_tags
+    leftover: Final = tuple(tag for tag in request_tags if tag not in stamp.tags)
+    inherited_tags: Final = typed_metadata.get("inherited_tags")
     if not isinstance(inherited_tags, (list, tuple)):
         return leftover or None
-    return tuple(dict.fromkeys((*leftover, *inherited_tags)))
+    typed_inherited_tags: Final[Sequence[object]] = inherited_tags
+    return tuple(dict.fromkeys((*leftover, *(tag for tag in typed_inherited_tags if isinstance(tag, str)))))
 
 
 async def get_deployments_for_tag(
     llm_router_instance: LitellmRouter,
     model: str,  # used to raise the correct error
-    healthy_deployments: list[Any] | dict[Any, Any],
-    request_kwargs: dict[Any, Any] | None = None,
+    healthy_deployments: _DeploymentPool,
+    request_kwargs: _RequestKwargsLike | None = None,
     metadata_variable_name: Literal["metadata", "litellm_metadata"] = "metadata",
-):
+) -> _DeploymentPool:
     """
     Returns a list of deployments that match the requested model and tags in the request.
 
@@ -486,8 +512,7 @@ async def get_deployments_for_tag(
 
     verbose_logger.debug("request metadata: %s", request_kwargs.get(metadata_variable_name))
     if metadata_variable_name in request_kwargs:
-        metadata: Final[_TagRoutingMetadata] = request_kwargs[metadata_variable_name]
-        stampable_metadata: Final[dict[str, object]] = request_kwargs[metadata_variable_name]
+        metadata: Final = request_kwargs[metadata_variable_name]
         request_tags: Final = _request_tags_after_router_consumption(metadata, model)
         match_any: Final = llm_router_instance.tag_filtering_match_any
         routing_prefix: Final = llm_router_instance.tag_routing_prefix or ""
@@ -532,25 +557,25 @@ async def get_deployments_for_tag(
                 request_tags,
             )
 
-        new_healthy_deployments: Final[list[_TagRoutingDeployment]] = []
-        default_deployments: Final[list[_TagRoutingDeployment]] = []
-
         if has_positive_filter:
             verbose_logger.debug(
                 "get_deployments_for_tag routing: request_tags=%s user_agent=%s",
                 request_tags,
                 user_agent,
             )
-            for deployment in candidates:
-                deployment_tags = deployment.get("litellm_params", {}).get("tags")
-
-                match_result = _match_deployment(
-                    deployment=deployment,
-                    request_tags=positive_tags,
-                    header_strings=header_strings,
-                    match_any=match_any,
+            deployment_matches: Final = tuple(
+                (
+                    deployment,
+                    _match_deployment(
+                        deployment=deployment,
+                        request_tags=positive_tags,
+                        header_strings=header_strings,
+                        match_any=match_any,
+                    ),
                 )
-
+                for deployment in candidates
+            )
+            for deployment, match_result in deployment_matches:
                 if match_result is not None:
                     verbose_logger.debug(
                         "tag routing match: deployment=%s matched_via=%s matched_value=%s",
@@ -559,17 +584,17 @@ async def get_deployments_for_tag(
                         match_result["matched_value"],
                     )
                     if "tag_routing" not in metadata:
-                        stampable_metadata["tag_routing"] = {
+                        metadata["tag_routing"] = {
                             "matched_deployment": deployment.get("model_name"),
                             "matched_via": match_result["matched_via"],
                             "matched_value": match_result["matched_value"],
                             "request_tags": request_tags or [],
                             "user_agent": user_agent,
                         }
-                    new_healthy_deployments.append(deployment)
-
-                if deployment_tags and "default" in deployment_tags:
-                    default_deployments.append(deployment)
+            new_healthy_deployments: Final = [d for d, result in deployment_matches if result is not None]
+            default_deployments: Final = [
+                d for d, _ in deployment_matches if "default" in (d.get("litellm_params", {}).get("tags") or ())
+            ]
 
             if len(new_healthy_deployments) == 0 and len(default_deployments) == 0:
                 return _resolve_or_fail_open(
@@ -604,10 +629,11 @@ async def get_deployments_for_tag(
             return new_healthy_deployments if len(new_healthy_deployments) > 0 else default_deployments
 
     # for Untagged requests use default deployments if set
-    _default_deployments_with_tags: Final[list[_TagRoutingDeployment]] = []
-    for deployment in healthy_deployments:
-        if "default" in deployment.get("litellm_params", {}).get("tags", []):
-            _default_deployments_with_tags.append(deployment)
+    _default_deployments_with_tags: Final = [
+        deployment
+        for deployment in healthy_deployments
+        if "default" in deployment.get("litellm_params", {}).get("tags", [])
+    ]
 
     if len(_default_deployments_with_tags) > 0:
         return _default_deployments_with_tags
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index 924574537f3..f7855cb38ff 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -8,6 +8,7 @@ from typing import TYPE_CHECKING, Any, Final
 import litellm
 from litellm._logging import verbose_router_logger
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs
 from litellm.litellm_core_utils.sensitive_data_masker import mask_sensitive_structure
 from litellm.router_utils.add_retry_fallback_headers import (
     add_fallback_headers_to_response,
@@ -214,6 +215,92 @@ def _check_stripped_model_group(model_group: str, fallback_key: str) -> bool:
     return False
 
 
+PRE_ROUTING_SELECTED_MODEL_KEY: Final = "pre_routing_selected_model"
+_ROUTER_METADATA_BUCKETS: Final = ("metadata", "litellm_metadata")
+
+
+def record_pre_routing_selection(request_kwargs: Mapping[str, Any] | None, selected_model: str) -> None:
+    """
+    Remember which model a pre-routing hook picked, so fallback lookup can key off it.
+
+    Fallback resolution runs on an outer kwargs dict that ``**kwargs`` already copied, so
+    writing the model there is invisible by the time routing picks a tier. The metadata
+    buckets are nested dicts shared by reference across those copies, which is how the
+    router already carries values back up.
+
+    The write goes through the proxy-internal bucket resolver, never into both buckets:
+    on /v1/messages the top-level ``metadata`` dict is the provider's own request field,
+    so a blanket write would forward the tier stamp upstream.
+    """
+    if request_kwargs is None:
+        return
+    bucket: Final = request_kwargs.get(get_metadata_variable_name_from_kwargs(request_kwargs))
+    if isinstance(bucket, dict):
+        bucket[PRE_ROUTING_SELECTED_MODEL_KEY] = selected_model
+
+
+def clear_pre_routing_selection(request_kwargs: Mapping[str, object] | None) -> None:
+    """
+    Drop any selection the router did not make itself on this hop.
+
+    The buckets carry whatever the caller sent, so an inbound value is the caller
+    choosing a fallback chain rather than the router choosing a tier. A fallback hop
+    also inherits the previous hop's selection, which would key its own failure off
+    the tier that already failed. Clearing at the start of every hop leaves only a
+    value the pre-routing hook wrote while routing that hop.
+    """
+    if request_kwargs is None:
+        return
+    for bucket in (request_kwargs.get(name) for name in _ROUTER_METADATA_BUCKETS):
+        if isinstance(bucket, dict) and PRE_ROUTING_SELECTED_MODEL_KEY in bucket:
+            del bucket[PRE_ROUTING_SELECTED_MODEL_KEY]
+
+
+def get_pre_routing_selection(kwargs: Mapping[str, Any]) -> str | None:
+    """The model a pre-routing hook selected for this request, if one did."""
+    buckets: Final = (kwargs.get(name) for name in _ROUTER_METADATA_BUCKETS)
+    selections: Final = (bucket.get(PRE_ROUTING_SELECTED_MODEL_KEY) for bucket in buckets if isinstance(bucket, dict))
+    return next((selected for selected in selections if isinstance(selected, str) and selected), None)
+
+
+def fallback_lookup_groups(kwargs: Mapping[str, Any], model_group: str | None) -> tuple[str, ...]:
+    """
+    Ordered keys for resolving a fallback chain: the tier a pre-routing hook selected wins,
+    then the routed group, then the requested group. The routed group differs when Claude Code
+    session affinity remaps a subagent's concrete model to its bound router.
+    """
+    metadata: Final = kwargs.get(get_metadata_variable_name_from_kwargs(kwargs))
+    routed_group_value: Final = metadata.get("model_group") if isinstance(metadata, Mapping) else None
+    routed_group: Final = routed_group_value if isinstance(routed_group_value, str) else None
+    ordered: Final = (get_pre_routing_selection(kwargs), routed_group, model_group)
+    return tuple(dict.fromkeys(group for group in ordered if group))
+
+
+def _resolved_a_specific_chain(
+    fallbacks: list[Any],  # mutable-ok: mirrors get_fallback_model_group's contract
+    result: tuple[list[str] | None, int | None],  # mutable-ok: mirrors get_fallback_model_group's contract
+) -> bool:
+    resolved, generic_idx = result
+    if resolved is None:
+        return False
+    return generic_idx is None or resolved is not fallbacks[generic_idx]["*"]
+
+
+def get_fallback_model_group_for_lookup_groups(
+    fallbacks: list[Any],  # mutable-ok: mirrors get_fallback_model_group's contract
+    lookup_groups: tuple[str, ...],
+) -> tuple[list[str] | None, int | None]:  # mutable-ok: mirrors get_fallback_model_group's contract
+    """
+    First lookup group with a specifically-keyed chain wins; the generic "*" chain applies
+    only after every group missed, so a catch-all cannot shadow a later group's own chain.
+    """
+    results: Final = tuple(get_fallback_model_group(fallbacks=fallbacks, model_group=group) for group in lookup_groups)
+    specific: Final = next((result for result in results if _resolved_a_specific_chain(fallbacks, result)), None)
+    if specific is not None:
+        return specific
+    return next((result for result in results if result[0] is not None), (None, None))
+
+
 def get_fallback_model_group(fallbacks: list[Any], model_group: str) -> tuple[list[str] | None, int | None]:
     """
     Returns:
@@ -385,10 +472,11 @@ async def run_async_fallback(
     attempted: Final = (
         carried_targets if isinstance(carried_targets, AttemptedFallbackTargets) else AttemptedFallbackTargets()
     )
-    attempted.record(original_model_group)
+    failed_model_group: Final = get_pre_routing_selection(kwargs) or original_model_group
+    attempted.record(failed_model_group)
 
     for mg in fallback_model_group:
-        if mg == original_model_group:
+        if mg == failed_model_group:
             continue
         if same_model_group_only and _get_fallback_target_model_group(mg) != original_model_group:
             verbose_router_logger.info(
@@ -412,6 +500,7 @@ async def run_async_fallback(
             # LOGGING
             kwargs = litellm_router.log_retry(kwargs=kwargs, e=original_exception)
             verbose_router_logger.info("Falling back to model_group = %s", mask_sensitive_structure(mg))
+            kwargs.pop("_target_order", None)  # rebind-ok: next hop must not inherit the previous order target
             if isinstance(mg, str):
                 kwargs["model"] = mg
             elif isinstance(mg, dict):
diff --git a/litellm/router_utils/pattern_match_deployments.py b/litellm/router_utils/pattern_match_deployments.py
index 0d5ef01bc04..0775e0a4039 100644
--- a/litellm/router_utils/pattern_match_deployments.py
+++ b/litellm/router_utils/pattern_match_deployments.py
@@ -8,7 +8,7 @@ from re import Match
 from typing import Final
 
 from litellm._logging import verbose_router_logger
-from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider, get_llm_provider
 
 
 class PatternUtils:
@@ -204,7 +204,7 @@ class PatternMatchRouter:
 
         return litellm_deployment_litellm_model
 
-    def get_pattern(self, model: str, custom_llm_provider: str | None = None) -> list[dict] | None:
+    def get_pattern(self, model: str | None, custom_llm_provider: str | None = None) -> list[dict] | None:
         """
         Check if a pattern exists for the given model and custom llm provider
 
@@ -215,18 +215,17 @@ class PatternMatchRouter:
         Returns:
             bool: True if pattern exists, False otherwise
         """
-        if custom_llm_provider is None:
-            try:
-                (
-                    _,
-                    custom_llm_provider,
-                    _,
-                    _,
-                ) = get_llm_provider(model=model)
-            except Exception:
-                # get_llm_provider raises exception when provider is unknown
-                pass
-        return self.route(model) or self.route(f"{custom_llm_provider}/{model}")
+        provider: Final = (
+            custom_llm_provider or declared_authenticating_provider(model) or self._resolved_provider(model)
+        )
+        return self.route(model) or self.route(f"{provider}/{model}")
+
+    @staticmethod
+    def _resolved_provider(model: str | None) -> str | None:
+        try:
+            return get_llm_provider(model=model)[1] if model else None
+        except Exception:  # noqa: BLE001  # get_llm_provider raises when the provider is unknown; the name then routes as-is
+            return None
 
     def get_deployments_by_pattern(self, model: str, custom_llm_provider: str | None = None) -> list[dict]:
         """
diff --git a/litellm/router_utils/pre_call_checks/deployment_affinity_check.py b/litellm/router_utils/pre_call_checks/deployment_affinity_check.py
index 7fb90ab89de..b1e9dbdefa8 100644
--- a/litellm/router_utils/pre_call_checks/deployment_affinity_check.py
+++ b/litellm/router_utils/pre_call_checks/deployment_affinity_check.py
@@ -427,6 +427,8 @@ class DeploymentAffinityCheck(CustomLogger):
         """
         request_kwargs = request_kwargs or {}
         typed_healthy_deployments: Final = cast(list[dict], healthy_deployments)
+        if request_kwargs.get("_target_order") is not None:
+            return typed_healthy_deployments
 
         (
             enable_user_key,
diff --git a/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py b/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py
index 6e8406b2ec7..0788c8db710 100644
--- a/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py
+++ b/litellm/router_utils/pre_call_checks/prompt_caching_deployment_check.py
@@ -58,6 +58,9 @@ class PromptCachingDeploymentCheck(CustomLogger):
         request_kwargs: dict | None = None,
         parent_otel_span: Span | None = None,
     ) -> list[dict]:
+        if request_kwargs is not None and request_kwargs.get("_target_order") is not None:
+            return healthy_deployments
+
         if messages is not None and is_prompt_caching_valid_prompt(
             messages=messages,
             model=model,
diff --git a/litellm/router_utils/search_api_router.py b/litellm/router_utils/search_api_router.py
index d96defbbcd6..ab5ef5853c9 100644
--- a/litellm/router_utils/search_api_router.py
+++ b/litellm/router_utils/search_api_router.py
@@ -9,6 +9,7 @@ import random
 import traceback
 from collections.abc import Callable
 from functools import partial
+from types import MappingProxyType
 from typing import Any, Final
 
 from litellm._logging import verbose_router_logger
@@ -214,6 +215,15 @@ class SearchAPIRouter:
             api_key, api_base = SearchAPIRouter._resolve_search_provider_credentials(
                 tool_litellm_params=litellm_params,
             )
+            protected_params: Final = frozenset(("search_provider", "api_key", "api_base"))
+            search_params: Final = MappingProxyType(
+                {
+                    key: value
+                    for params in (litellm_params, kwargs)
+                    for key, value in params.items()
+                    if key not in protected_params and value is not None
+                }
+            )
 
             verbose_router_logger.debug("Selected search tool with provider: %s", search_provider)
 
@@ -222,7 +232,7 @@ class SearchAPIRouter:
                 search_provider=search_provider,
                 api_key=api_key,
                 api_base=api_base,
-                **kwargs,
+                **search_params,
             )
 
             return response
diff --git a/litellm/rust_bridge/__init__.py b/litellm/rust_bridge/__init__.py
index 3da5b98449b..e6d8ffef48c 100644
--- a/litellm/rust_bridge/__init__.py
+++ b/litellm/rust_bridge/__init__.py
@@ -1,9 +1,9 @@
 """LiteLLM Rust bridge package."""
 
+from litellm.rust_bridge.configuration import use_litellm_rust
 from litellm.rust_bridge.loader import (
     get_native_bridge,
     native_bridge_available,
 )
-from litellm.rust_bridge.ocr import use_litellm_rust
 
 __all__ = ["get_native_bridge", "native_bridge_available", "use_litellm_rust"]
diff --git a/litellm/rust_bridge/bindings.py b/litellm/rust_bridge/bindings.py
new file mode 100644
index 00000000000..d16f150a2aa
--- /dev/null
+++ b/litellm/rust_bridge/bindings.py
@@ -0,0 +1,49 @@
+from __future__ import annotations
+
+from collections.abc import Callable
+from typing import Final, Generic, TypeVar
+
+from litellm.rust_bridge.loader import get_native_bridge
+
+BindingT = TypeVar("BindingT")
+
+
+class _Unset:
+    pass
+
+
+_UNSET: Final = _Unset()
+
+
+class NativeBinding(Generic[BindingT]):
+    """Resolve one native attribute with an explicit, resettable test override."""
+
+    def __init__(self, attribute: str, *, validate: Callable[[object], BindingT | None]) -> None:
+        self._attribute: Final = attribute
+        self._validate: Final = validate
+        self._override: BindingT | None | _Unset = _UNSET
+
+    def load(self) -> BindingT | None:
+        if not isinstance(self._override, _Unset):
+            return self._override
+        native: Final = get_native_bridge()
+        if native is None:
+            return None
+        return self._validate(getattr(native, self._attribute, None))
+
+    def override(self, value: BindingT | None) -> None:
+        self._override = value
+
+    def reset(self) -> None:
+        self._override = _UNSET
+
+
+def native_exception_types() -> tuple[type[BaseException], type[BaseException]] | None:
+    native: Final = get_native_bridge()
+    if native is None:
+        return None
+    declined: Final = getattr(native, "RustBridgeDeclined", None)
+    upstream: Final = getattr(native, "RustUpstreamError", None)
+    if not isinstance(declined, type) or not isinstance(upstream, type):
+        return None
+    return declined, upstream
diff --git a/litellm/rust_bridge/chat_completions.py b/litellm/rust_bridge/chat_completions.py
index acda3086051..c599667ab17 100644
--- a/litellm/rust_bridge/chat_completions.py
+++ b/litellm/rust_bridge/chat_completions.py
@@ -13,7 +13,6 @@ retrying it there would bill the customer for the same work twice.
 from __future__ import annotations
 
 import json
-import os
 from collections.abc import Awaitable, Callable, Mapping, Sequence
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, Final, Protocol
@@ -27,6 +26,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo
     convert_to_model_response_object,
 )
 from litellm.llms.bedrock.request_metadata import bedrock_request_metadata_is_owned
+from litellm.rust_bridge.configuration import rust_enabled
 from litellm.rust_bridge.loader import get_native_bridge
 from litellm.rust_bridge.timeouts import timeout_to_seconds
 from litellm.types.utils import ModelResponse
@@ -44,8 +44,6 @@ _LITELLM_METADATA_ADAPTER: Final = TypeAdapter(Mapping[str, object])
 
 RUST_RESPONSE_HEADER: Final = "x-litellm-rust"
 
-_TRUTHY_ENV_VALUES: Final = frozenset({"1", "true", "yes", "on"})
-
 
 class RustChatCompletions(Protocol):
     def __call__(
@@ -181,10 +179,6 @@ def load_rust_achat_completions() -> RustAchatCompletions | None:
     return loaded
 
 
-def _env_enables_rust() -> bool:
-    return os.getenv("LITELLM_RUST", "").strip().lower() in _TRUTHY_ENV_VALUES
-
-
 def _load_rust_decline() -> RustChatCompletionsDecline | None:
     if _STATE.decline is not None:
         return _STATE.decline
@@ -253,8 +247,8 @@ def rust_chat_completions_accepts(
         return False
     if stream:
         return False
-    opted_in: Final = litellm_params is not None and litellm_params.get("rust") is True
-    if not opted_in and not _env_enables_rust():
+    request_override: Final = litellm_params.get("rust") if litellm_params is not None else None
+    if not rust_enabled(request_override=request_override if isinstance(request_override, bool) else None):
         return False
     if _litellm_metadata_reaches_the_provider(custom_llm_provider, litellm_params):
         verbose_logger.debug("Rust chat completions declined (litellm metadata user_id); using the Python path")
diff --git a/litellm/rust_bridge/configuration.py b/litellm/rust_bridge/configuration.py
new file mode 100644
index 00000000000..d54b15f060c
--- /dev/null
+++ b/litellm/rust_bridge/configuration.py
@@ -0,0 +1,148 @@
+from __future__ import annotations
+
+import os
+import warnings
+from typing import TYPE_CHECKING, Final
+
+if TYPE_CHECKING:
+    from litellm.rust_bridge.messages import RustAmessages, RustMessages
+    from litellm.rust_bridge.ocr import RustAocr, RustOcr
+    from litellm.rust_bridge.responses_websocket import RustResponsesWebSocketConnection
+    from litellm.rust_bridge.transcription import RustAtranscription, RustTranscription
+
+DEFAULT_RUST_ENABLED: Final = False
+_TRUE_ENV_VALUES: Final = frozenset({"1", "true", "yes", "on"})
+_GLOBAL_ENV_NAME: Final = "LITELLM_RUST"
+_LEGACY_OCR_ENV_NAME: Final = "LITELLM_USE_RUST_OCR"
+
+
+class _Unset:
+    pass
+
+
+_UNSET: Final = _Unset()
+
+
+class _RustConfiguration:
+    def __init__(self) -> None:
+        self.override: bool | None = None
+
+
+_CONFIGURATION: Final = _RustConfiguration()
+
+
+def _parse_env_bool(value: str | None) -> bool | None:
+    if value is None:
+        return None
+    return value.strip().lower() in _TRUE_ENV_VALUES
+
+
+def resolve_rust_enabled(
+    *,
+    request_override: bool | None,
+    process_override: bool | None,
+    environment_override: bool | None,
+    legacy_ocr_override: bool | None = None,
+    release_default: bool = DEFAULT_RUST_ENABLED,
+) -> bool:
+    if request_override is not None:
+        return request_override
+    if process_override is not None:
+        return process_override
+    if environment_override is not None:
+        return environment_override
+    if legacy_ocr_override is not None:
+        return legacy_ocr_override
+    return release_default
+
+
+def rust_enabled(*, request_override: bool | None = None) -> bool:
+    if request_override is not None:
+        return request_override
+    process_override: Final = _CONFIGURATION.override
+    if process_override is not None:
+        return process_override
+    return resolve_rust_enabled(
+        request_override=None,
+        process_override=None,
+        environment_override=_parse_env_bool(os.getenv(_GLOBAL_ENV_NAME)),
+    )
+
+
+def rust_ocr_enabled(*, request_override: bool | None = None) -> bool:
+    if request_override is not None:
+        return request_override
+    process_override: Final = _CONFIGURATION.override
+    if process_override is not None:
+        return process_override
+    global_override: Final = _parse_env_bool(os.getenv(_GLOBAL_ENV_NAME))
+    legacy_override: Final = None if global_override is not None else _parse_env_bool(os.getenv(_LEGACY_OCR_ENV_NAME))
+    if legacy_override is not None:
+        warnings.warn(
+            f"{_LEGACY_OCR_ENV_NAME} is deprecated; use {_GLOBAL_ENV_NAME} instead",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+    return resolve_rust_enabled(
+        request_override=None,
+        process_override=None,
+        environment_override=global_override,
+        legacy_ocr_override=legacy_override,
+    )
+
+
+def reset_rust_configuration() -> None:
+    _CONFIGURATION.override = None
+
+
+def use_litellm_rust(
+    enabled: bool = True,
+    *,
+    ocr: RustOcr | None | _Unset = _UNSET,
+    aocr: RustAocr | None | _Unset = _UNSET,
+    messages: RustMessages | None | _Unset = _UNSET,
+    amessages: RustAmessages | None | _Unset = _UNSET,
+    responses_websocket: type[RustResponsesWebSocketConnection] | None | _Unset = _UNSET,
+    transcription: RustTranscription | None | _Unset = _UNSET,
+    atranscription: RustAtranscription | None | _Unset = _UNSET,
+) -> None:
+    """Set the process override for optional Rust paths.
+
+    Rust-only paths, including Bedrock transcription, are not controlled by this switch.
+    """
+    _CONFIGURATION.override = enabled
+    bindings: Final = (ocr, aocr, messages, amessages, responses_websocket, transcription, atranscription)
+    if all(isinstance(binding, _Unset) for binding in bindings):
+        return
+    warnings.warn(
+        "Injecting Rust bridge implementations through use_litellm_rust() is deprecated; "
+        "use the internal bridge setters in tests",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+    if not isinstance(ocr, _Unset) or not isinstance(aocr, _Unset):
+        from litellm.rust_bridge.ocr import set_rust_ocr
+
+        if not isinstance(ocr, _Unset):
+            set_rust_ocr(ocr=ocr)
+        if not isinstance(aocr, _Unset):
+            set_rust_ocr(aocr=aocr)
+    if not isinstance(messages, _Unset) or not isinstance(amessages, _Unset):
+        from litellm.rust_bridge.messages import set_rust_messages
+
+        if not isinstance(messages, _Unset):
+            set_rust_messages(messages=messages)
+        if not isinstance(amessages, _Unset):
+            set_rust_messages(amessages=amessages)
+    if not isinstance(responses_websocket, _Unset):
+        from litellm.rust_bridge.responses_websocket import set_rust_responses_websocket
+
+        set_rust_responses_websocket(connection=responses_websocket)
+    if not isinstance(transcription, _Unset) or not isinstance(atranscription, _Unset):
+        from litellm.rust_bridge.transcription import configure_rust_transcription
+
+        if not isinstance(transcription, _Unset):
+            configure_rust_transcription(transcription=transcription)
+        if not isinstance(atranscription, _Unset):
+            configure_rust_transcription(atranscription=atranscription)
diff --git a/litellm/rust_bridge/ocr.py b/litellm/rust_bridge/ocr.py
index 82297d35170..b5b0a35a498 100644
--- a/litellm/rust_bridge/ocr.py
+++ b/litellm/rust_bridge/ocr.py
@@ -2,16 +2,16 @@
 
 from __future__ import annotations
 
-import os
 from collections.abc import Awaitable
-from typing import TYPE_CHECKING, Any, Final, Protocol, cast
+from typing import Final, Protocol, cast  # noqa: TID251  # native extension exposes dynamically typed callables
 
 import httpx
 
+from litellm.rust_bridge import configuration as _configuration
 from litellm.rust_bridge.timeouts import timeout_to_seconds as _timeout_to_seconds
 
-if TYPE_CHECKING:
-    from litellm.rust_bridge.messages import RustAmessages, RustMessages
+rust_ocr_enabled = _configuration.rust_ocr_enabled
+use_litellm_rust = _configuration.use_litellm_rust
 
 
 class RustOcr(Protocol):
@@ -51,69 +51,20 @@ class _Unset:
 _UNSET: Final[_Unset] = _Unset()
 
 
-def _env_enables_rust_ocr() -> bool:
-    return os.getenv("LITELLM_USE_RUST_OCR", "").strip().lower() in {
-        "1",
-        "true",
-        "yes",
-        "on",
-    }
-
-
-_rust_ocr_enabled = _env_enables_rust_ocr()
 _rust_ocr_impl: RustOcr | None = None
 _rust_aocr_impl: RustAocr | None = None
 
 
-def use_litellm_rust(
-    enabled: bool = True,
+def set_rust_ocr(
     *,
     ocr: RustOcr | None | _Unset = _UNSET,
     aocr: RustAocr | None | _Unset = _UNSET,
-    messages: RustMessages | None | _Unset = _UNSET,
-    amessages: RustAmessages | None | _Unset = _UNSET,
-    responses_websocket: Any | None | _Unset = _UNSET,
-    transcription: Any | None | _Unset = _UNSET,
-    atranscription: Any | None | _Unset = _UNSET,
 ) -> None:
-    global _rust_ocr_enabled, _rust_ocr_impl, _rust_aocr_impl
-    configuring_ocr: Final = not isinstance(ocr, _Unset) or not isinstance(aocr, _Unset)
-    configuring_messages: Final = not isinstance(messages, _Unset) or not isinstance(amessages, _Unset)
-    configuring_responses_websocket: Final = not isinstance(responses_websocket, _Unset)
-    configuring_transcription: Final = not isinstance(transcription, _Unset) or not isinstance(atranscription, _Unset)
-    if configuring_ocr or (not configuring_messages and not configuring_responses_websocket):
-        _rust_ocr_enabled = enabled
+    global _rust_ocr_impl, _rust_aocr_impl
     if not isinstance(ocr, _Unset):
         _rust_ocr_impl = ocr
     if not isinstance(aocr, _Unset):
         _rust_aocr_impl = aocr
-    if configuring_transcription:
-        from litellm.rust_bridge.transcription import configure_rust_transcription
-
-        configure_rust_transcription(
-            enabled=enabled,
-            transcription=transcription,
-            atranscription=atranscription,
-        )
-    if not configuring_messages and not configuring_responses_websocket:
-        return
-    if configuring_messages:
-        from litellm.rust_bridge.messages import set_rust_messages
-
-        if not isinstance(messages, _Unset) and not isinstance(amessages, _Unset):
-            set_rust_messages(messages=messages, amessages=amessages)
-        elif not isinstance(messages, _Unset):
-            set_rust_messages(messages=messages)
-        else:
-            set_rust_messages(amessages=amessages)
-    if configuring_responses_websocket:
-        from litellm.rust_bridge.responses_websocket import set_rust_responses_websocket
-
-        set_rust_responses_websocket(connection=responses_websocket)
-
-
-def rust_ocr_enabled() -> bool:
-    return _rust_ocr_enabled
 
 
 def load_rust_ocr() -> RustOcr | None:
diff --git a/litellm/rust_bridge/runtime.py b/litellm/rust_bridge/runtime.py
new file mode 100644
index 00000000000..00f06c046a2
--- /dev/null
+++ b/litellm/rust_bridge/runtime.py
@@ -0,0 +1,180 @@
+from __future__ import annotations
+
+from collections.abc import Awaitable, Callable
+from dataclasses import dataclass
+from enum import Enum
+from typing import Final, Generic, NoReturn, TypeAlias, TypeVar
+
+from litellm.exceptions import APIError
+from litellm.rust_bridge.bindings import native_exception_types
+
+NativeT = TypeVar("NativeT")
+ResultT = TypeVar("ResultT")
+
+
+class FallbackMode(Enum):
+    PYTHON = "python"
+    RUST_REQUIRED = "rust_required"
+
+
+@dataclass(frozen=True, slots=True)
+class RustHandled(Generic[ResultT]):
+    value: ResultT
+
+
+@dataclass(frozen=True, slots=True)
+class RustDeclined:
+    reason: str
+
+
+@dataclass(frozen=True, slots=True)
+class RustUnavailable:
+    pass
+
+
+RustAttempt: TypeAlias = RustHandled[ResultT] | RustDeclined | RustUnavailable
+
+
+@dataclass(frozen=True, slots=True)
+class BridgeErrorContext:
+    route: str
+    provider: str
+    model: str
+
+
+def invoke(
+    *,
+    native_call: Callable[[], NativeT] | None,
+    fallback: Callable[[], ResultT],
+    adapt: Callable[[NativeT], ResultT],
+    mode: FallbackMode,
+    context: BridgeErrorContext,
+) -> ResultT:
+    result: Final = attempt(native_call=native_call, adapt=adapt, context=context)
+    if isinstance(result, RustHandled):
+        return result.value
+    if mode is FallbackMode.PYTHON:
+        return fallback()
+    _raise_required(result, context)
+
+
+async def ainvoke(
+    *,
+    native_call: Callable[[], Awaitable[NativeT]] | None,
+    fallback: Callable[[], Awaitable[ResultT]],
+    adapt: Callable[[NativeT], ResultT],
+    mode: FallbackMode,
+    context: BridgeErrorContext,
+) -> ResultT:
+    result: Final = await aattempt(native_call=native_call, adapt=adapt, context=context)
+    if isinstance(result, RustHandled):
+        return result.value
+    if mode is FallbackMode.PYTHON:
+        return await fallback()
+    _raise_required(result, context)
+
+
+def attempt(
+    *,
+    native_call: Callable[[], NativeT] | None,
+    adapt: Callable[[NativeT], ResultT],
+    context: BridgeErrorContext,
+) -> RustAttempt[ResultT]:
+    if native_call is None:
+        return RustUnavailable()
+    exceptions: Final = native_exception_types()
+    if exceptions is None:
+        return RustHandled(adapt(native_call()))
+    declined, upstream = exceptions
+    try:
+        value: Final = native_call()
+    except declined as error:
+        return RustDeclined(reason=_decline_reason(error))
+    except upstream as error:
+        _raise_upstream(error, context)
+    return RustHandled(adapt(value))
+
+
+async def aattempt(
+    *,
+    native_call: Callable[[], Awaitable[NativeT]] | None,
+    adapt: Callable[[NativeT], ResultT],
+    context: BridgeErrorContext,
+) -> RustAttempt[ResultT]:
+    if native_call is None:
+        return RustUnavailable()
+    exceptions: Final = native_exception_types()
+    if exceptions is None:
+        return RustHandled(adapt(await native_call()))
+    declined, upstream = exceptions
+    try:
+        value: Final = await native_call()
+    except declined as error:
+        return RustDeclined(reason=_decline_reason(error))
+    except upstream as error:
+        _raise_upstream(error, context)
+    return RustHandled(adapt(value))
+
+
+def call(operation: Callable[[], ResultT], context: BridgeErrorContext) -> ResultT:
+    exceptions: Final = native_exception_types()
+    if exceptions is None:
+        return operation()
+    upstream: Final = exceptions[1]
+    try:
+        return operation()
+    except upstream as error:
+        _raise_upstream(error, context)
+
+
+async def acall(operation: Callable[[], Awaitable[ResultT]], context: BridgeErrorContext) -> ResultT:
+    exceptions: Final = native_exception_types()
+    if exceptions is None:
+        return await operation()
+    upstream: Final = exceptions[1]
+    try:
+        return await operation()
+    except upstream as error:
+        _raise_upstream(error, context)
+
+
+def _decline_reason(error: BaseException) -> str:
+    reason: Final[object] = error.args[0] if error.args else str(error)
+    return reason if isinstance(reason, str) else str(reason)
+
+
+def _raise_required(
+    result: RustDeclined | RustUnavailable,
+    context: BridgeErrorContext,
+) -> NoReturn:
+    raise RuntimeError(f"Rust {context.route} bridge {_required_reason(result)}")
+
+
+def _required_reason(result: RustDeclined | RustUnavailable) -> str:
+    match result:
+        case RustUnavailable():
+            return "is unavailable"
+        case RustDeclined(reason=reason):
+            return f"declined the request: {reason}"
+
+
+def _raise_upstream(error: BaseException, context: BridgeErrorContext) -> NoReturn:
+    args: Final[tuple[object, ...]] = error.args
+    status_value: Final = args[0] if args else 0
+    message_value: Final = args[1] if len(args) > 1 else str(error)
+    status: Final = status_value if isinstance(status_value, int) else 0
+    message: Final = message_value if isinstance(message_value, str) else str(message_value)
+    raise APIError(
+        status_code=status or 500,
+        message=f"litellm rust {context.route}: {message}",
+        llm_provider=context.provider,
+        model=context.model,
+    ) from error
+
+
+def identity(value: ResultT) -> ResultT:
+    return value
+
+
+async def async_none() -> None:
+    return None
diff --git a/litellm/search/cost_calculator.py b/litellm/search/cost_calculator.py
index 84461115e8e..21f27075e0f 100644
--- a/litellm/search/cost_calculator.py
+++ b/litellm/search/cost_calculator.py
@@ -2,16 +2,37 @@
 Cost calculation for search providers.
 """
 
+from collections.abc import Mapping
+from types import MappingProxyType
 from typing import Final
 
+from pydantic import TypeAdapter, ValidationError
+
 from litellm.utils import get_model_info
 
+PROVIDER_USAGE_ADAPTER: Final[TypeAdapter[tuple[Mapping[str, object], ...]]] = TypeAdapter(
+    tuple[Mapping[str, object], ...]
+)
+EMPTY_OPTIONAL_PARAMS: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+def _provider_usage(
+    optional_params: Mapping[str, object] | None,
+    usage_param: str,
+) -> tuple[Mapping[str, object], ...] | None:
+    params: Final = optional_params if optional_params is not None else EMPTY_OPTIONAL_PARAMS
+    raw_usage: Final[object] = params.get(usage_param)
+    try:
+        return PROVIDER_USAGE_ADAPTER.validate_python(raw_usage)
+    except ValidationError:
+        return None
+
 
 def search_provider_cost_per_query(
     model: str,
     custom_llm_provider: str | None = None,
     number_of_queries: int = 1,
-    optional_params: dict | None = None,
+    optional_params: Mapping[str, object] | None = None,
 ) -> tuple[float, float]:
     """
     Calculate cost for search-only providers.
@@ -28,6 +49,18 @@ def search_provider_cost_per_query(
     Returns:
         Tuple of (input_cost, output_cost) where output_cost is always 0.0
     """
+    if custom_llm_provider == "parallel_ai":
+        from litellm.llms.parallel_ai.search.cost_calculator import (
+            PARALLEL_AI_USAGE_PARAM,
+            parallel_ai_search_cost,
+        )
+
+        input_cost: Final = parallel_ai_search_cost(
+            optional_params=optional_params if optional_params is not None else EMPTY_OPTIONAL_PARAMS,
+            usage=_provider_usage(optional_params, PARALLEL_AI_USAGE_PARAM),
+        )
+        return (input_cost, 0.0)
+
     model_info: Final = get_model_info(model=model, custom_llm_provider=custom_llm_provider)
 
     # Check for tiered pricing (e.g., Exa AI based on max_results)
diff --git a/litellm/secret_managers/hashicorp_secret_manager.py b/litellm/secret_managers/hashicorp_secret_manager.py
index e2662d96b52..8f677b54700 100644
--- a/litellm/secret_managers/hashicorp_secret_manager.py
+++ b/litellm/secret_managers/hashicorp_secret_manager.py
@@ -1,7 +1,9 @@
 import os
-from typing import Any, Final
+from collections.abc import Mapping
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -17,6 +19,72 @@ from litellm.proxy._types import KeyManagementSystem
 from .base_secret_manager import BaseSecretManager, raise_if_unsafe_secret_name
 
 
+class _VaultAuthData(TypedDict):
+    """The ``auth`` block Vault returns from a login endpoint."""
+
+    client_token: ReadOnly[str]
+    lease_duration: ReadOnly[int]
+
+
+class _VaultLoginResponse(TypedDict):
+    """Body of a Vault ``/v1/auth/.../login`` response."""
+
+    auth: ReadOnly[_VaultAuthData]
+
+
+class _VaultSecretTarget(TypedDict):
+    """Resolved coordinates of one Vault KV v2 secret."""
+
+    url: ReadOnly[str]
+    data_key: ReadOnly[str]
+    secret_name: ReadOnly[str]
+
+
+class _VaultSecretDataBlock(TypedDict, total=False):
+    """The inner ``data`` block of a Vault KV v2 read body."""
+
+    data: ReadOnly[Mapping[str, object]]
+
+
+class _VaultSecretReadResponse(TypedDict, total=False):
+    """Body of a Vault KV v2 secret read, narrowed to the nesting this module walks."""
+
+    data: ReadOnly[_VaultSecretDataBlock]
+
+
+class _VaultLoginResponseSource(Protocol):
+    """A Vault login call's HTTP response, read for the auth block it carries."""
+
+    def json(self) -> _VaultLoginResponse: ...
+
+
+class _VaultSecretReadSource(Protocol):
+    """A Vault KV v2 read response, read for the nested secret data it carries."""
+
+    def json(self) -> _VaultSecretReadResponse: ...
+
+
+class _JsonObjectSource(Protocol):
+    """A Vault response whose body is a JSON object nothing further is assumed about."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _vault_login_body(response: _VaultLoginResponseSource) -> _VaultLoginResponse:
+    """Decode the body of a Vault login response."""
+    return response.json()
+
+
+def _vault_secret_read_body(response: _VaultSecretReadSource) -> _VaultSecretReadResponse:
+    """Decode the body of a Vault KV v2 secret read response."""
+    return response.json()
+
+
+def _json_object_body(response: _JsonObjectSource) -> dict[str, object]:
+    """Decode a Vault response body as a plain JSON object."""
+    return response.json()
+
+
 class HashicorpSecretManager(BaseSecretManager):
     def __init__(self):
         from litellm.proxy.proxy_server import CommonProxyErrors, premium_user
@@ -130,7 +198,8 @@ class HashicorpSecretManager(BaseSecretManager):
             )
             resp.raise_for_status()
 
-            auth_data: Final = resp.json()["auth"]
+            login_response: Final = _vault_login_body(resp)
+            auth_data: Final = login_response["auth"]
             token: Final = auth_data["client_token"]
             _lease_duration: Final = auth_data["lease_duration"]
 
@@ -191,8 +260,10 @@ class HashicorpSecretManager(BaseSecretManager):
                 json=self._get_tls_cert_auth_body(),
             )
             resp.raise_for_status()
-            token: Final = resp.json()["auth"]["client_token"]
-            _lease_duration: Final = resp.json()["auth"]["lease_duration"]
+            token_response: Final = _vault_login_body(resp)
+            token: Final = token_response["auth"]["client_token"]
+            lease_response: Final = _vault_login_body(resp)
+            _lease_duration: Final = lease_response["auth"]["lease_duration"]
             verbose_logger.debug("Successfully obtained Vault token via TLS cert auth.")
             self.cache.set_cache(key="hcp_vault_token", value=token, ttl=_lease_duration)
             return token
@@ -205,9 +276,9 @@ class HashicorpSecretManager(BaseSecretManager):
     def get_url(
         self,
         secret_name: str,
-        namespace: str | None = None,
-        mount_name: str | None = None,
-        path_prefix: str | None = None,
+        namespace: object = None,
+        mount_name: object = None,
+        path_prefix: object = None,
     ) -> str:
         """
         Constructs the Vault URL for KV v2 secrets.
@@ -238,7 +309,7 @@ class HashicorpSecretManager(BaseSecretManager):
         _url += secret_name
         return _url
 
-    def _sanitize_plain_value(self, value: str | int | None) -> str | None:
+    def _sanitize_plain_value(self, value: object) -> str | None:
         if value is None:
             return None
         value_str: Final = str(value).strip()
@@ -246,23 +317,23 @@ class HashicorpSecretManager(BaseSecretManager):
             return None
         return value_str
 
-    def _sanitize_path_component(self, value: str | int | None) -> str | None:
+    def _sanitize_path_component(self, value: object) -> str | None:
         sanitized_value = self._sanitize_plain_value(value)
         if sanitized_value is None:
             return None
         sanitized_value = sanitized_value.strip("/")
         return sanitized_value or None
 
-    def _extract_secret_manager_settings(self, optional_params: dict | None) -> dict[str, Any]:
+    def _extract_secret_manager_settings(self, optional_params: dict | None) -> dict[str, object]:
         if not isinstance(optional_params, dict):
             return {}
 
         candidate: Final = optional_params.get("secret_manager_settings")
-        source: Final = candidate if isinstance(candidate, dict) else optional_params
+        source: Final[Mapping[str, object]] = candidate if isinstance(candidate, dict) else optional_params
         allowed_keys: Final = {"namespace", "mount", "path_prefix", "data"}
         return {k: source[k] for k in allowed_keys if k in source}
 
-    def _build_secret_target(self, secret_name: str, optional_params: dict | None) -> dict[str, Any]:
+    def _build_secret_target(self, secret_name: str, optional_params: dict | None) -> _VaultSecretTarget:
         settings: Final = self._extract_secret_manager_settings(optional_params)
 
         namespace: Final = settings.get("namespace", self.vault_namespace)
@@ -331,7 +402,7 @@ class HashicorpSecretManager(BaseSecretManager):
             response.raise_for_status()
 
             # For KV v2, the secret is in response.json()["data"]["data"]
-            json_resp: Final = response.json()
+            json_resp: Final = _json_object_body(response)
             _value: Final = self._get_secret_value_from_json_response(json_resp)
             self.cache.set_cache(secret_name, _value)
             return _value
@@ -362,7 +433,7 @@ class HashicorpSecretManager(BaseSecretManager):
             response.raise_for_status()
 
             # For KV v2, the secret is in response.json()["data"]["data"]
-            json_resp: Final = response.json()
+            json_resp: Final = _json_object_body(response)
             _value: Final = self._get_secret_value_from_json_response(json_resp)
             self.cache.set_cache(secret_name, _value)
             return _value
@@ -379,7 +450,7 @@ class HashicorpSecretManager(BaseSecretManager):
         optional_params: dict | None = None,
         timeout: float | httpx.Timeout | None = None,
         tags: dict | list | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Writes a secret to Vault KV v2 using an async HTTPX client.
 
@@ -413,7 +484,7 @@ class HashicorpSecretManager(BaseSecretManager):
                 json=data,
             )
             response.raise_for_status()
-            return response.json()
+            return _json_object_body(response)
         except Exception as e:
             verbose_logger.exception("Error writing secret to Hashicorp Vault: %s", e)
             return {"status": "error", "message": str(e)}
@@ -500,7 +571,7 @@ class HashicorpSecretManager(BaseSecretManager):
                     headers=self._get_request_headers(),
                 )
                 response.raise_for_status()
-                json_resp: Final = response.json()
+                json_resp: Final = _vault_secret_read_body(response)
                 # Use data_key from target to get the correct value
                 data_key: Final = new_target["data_key"]
                 new_secret_value_from_vault: Final = json_resp.get("data", {}).get("data", {}).get(data_key, None)
diff --git a/litellm/setup_wizard.py b/litellm/setup_wizard.py
index d6b3dfa3285..dd147aaccee 100644
--- a/litellm/setup_wizard.py
+++ b/litellm/setup_wizard.py
@@ -53,11 +53,12 @@ PROVIDERS: Final[list[dict]] = [
     {
         "id": "anthropic",
         "name": "Anthropic",
-        "description": "Claude Fable 5, Opus 5, Opus 4.8, Opus 4.7, Opus 4.6, Sonnet 5, Sonnet 4.6, Haiku 4.5",
+        "description": "Claude Fable 5.1, Fable 5, Opus 5, Opus 4.8, Opus 4.7, Opus 4.6, Sonnet 5, Sonnet 4.6, Haiku 4.5",
         "env_key": "ANTHROPIC_API_KEY",
         "key_hint": "sk-ant-...",
         "test_model": "claude-haiku-4-5-20251001",
         "models": [
+            "claude-fable-5-1",
             "claude-fable-5",
             "claude-opus-5",
             "claude-sonnet-5",
diff --git a/litellm/types/guardrail_base_init.py b/litellm/types/guardrail_base_init.py
new file mode 100644
index 00000000000..9174e8d840f
--- /dev/null
+++ b/litellm/types/guardrail_base_init.py
@@ -0,0 +1,24 @@
+"""Typed view of the scalar keyword payload guardrails forward to ``CustomGuardrail.__init__``.
+
+Guardrail subclasses collect their base-class options in ``**kwargs`` and splat them into
+``super().__init__``. Declaring the payload's shape here lets the checker resolve each
+forwarded argument to its real parameter type instead of ``Any``.
+"""
+
+from typing_extensions import ReadOnly, TypedDict
+
+
+class GuardrailBaseInitKwargs(TypedDict, total=False):
+    guardrail_name: ReadOnly[str | None]
+    default_on: ReadOnly[bool]
+    mask_request_content: ReadOnly[bool]
+    mask_response_content: ReadOnly[bool]
+    violation_message_template: ReadOnly[str | None]
+    end_session_after_n_fails: ReadOnly[int | None]
+    on_violation: ReadOnly[str | None]
+    realtime_violation_message: ReadOnly[str | None]
+    on_sensitive_data: ReadOnly[str | None]
+    sensitive_data_route_to_model: ReadOnly[str | None]
+    sticky_session_routing: ReadOnly[bool]
+    run_in_parallel: ReadOnly[bool]
+    only_scan_new_messages: ReadOnly[bool]
diff --git a/litellm/types/guardrails.py b/litellm/types/guardrails.py
index 9be78757511..c17103da890 100644
--- a/litellm/types/guardrails.py
+++ b/litellm/types/guardrails.py
@@ -1,5 +1,7 @@
+from collections.abc import Mapping
 from datetime import datetime
 from enum import Enum
+from types import MappingProxyType
 from typing import Any, Final, Literal
 
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
@@ -134,6 +136,7 @@ class SupportedGuardrailIntegrations(Enum):
     HEADROOM = "headroom"
     COMPRESR = "compresr"
     STRAIKER = "straiker"
+    ALICE = "alice"
 
 
 class Role(Enum):
@@ -550,6 +553,40 @@ class BedrockGuardrailConfigModel(BaseModel):
     )
 
 
+class BedrockGuardrailStreamingParams(BaseModel):
+    streaming_buffer_until_moderated: bool = Field(
+        default=True,
+        description="If True (default), withhold every streamed chunk until the end-of-stream "
+        "ApplyGuardrail scan passes, so no flagged content reaches the client before a block. "
+        "If False, chunks stream through unbuffered, so flagged content can reach the client "
+        "before the scan finishes; a flagged scan still ends the stream, with a block message "
+        "when disable_exception_on_block is true and an in-stream error frame otherwise.",
+    )
+    streaming_sampling_rate: int = Field(
+        default=5,
+        ge=1,
+        description="When not buffering and not end-of-stream-only, scan the accumulated response "
+        "every Nth streamed chunk. Each sampled scan is a full ApplyGuardrail call that delays "
+        "that chunk, so lower values add latency and AWS text-unit cost.",
+    )
+    streaming_end_of_stream_only: bool = Field(
+        default=False,
+        description="When not buffering, skip per-chunk sampling and run one ApplyGuardrail scan "
+        "on the assembled response at end of stream. Combined with "
+        "streaming_buffer_until_moderated=false the full response streams live before the scan "
+        "and the scan result lands in guardrail_information; a flagged response still ends the "
+        "stream with a block message (disable_exception_on_block=true) or an error frame.",
+    )
+
+    @classmethod
+    def from_extras(cls, extras: Mapping[str, object] | None) -> "BedrockGuardrailStreamingParams":
+        if not extras:
+            return cls()
+        return cls.model_validate(
+            MappingProxyType({name: extras[name] for name in cls.model_fields if extras.get(name) is not None})
+        )
+
+
 class LakeraV2GuardrailConfigModel(BaseModel):
     """Configuration parameters for the Lakera AI v2 guardrail"""
 
diff --git a/litellm/types/integrations/datadog_llm_obs.py b/litellm/types/integrations/datadog_llm_obs.py
index 7853dda1213..bae876dfdd9 100644
--- a/litellm/types/integrations/datadog_llm_obs.py
+++ b/litellm/types/integrations/datadog_llm_obs.py
@@ -4,21 +4,58 @@ Payloads for Datadog LLM Observability Service (LLMObs)
 API Reference: https://docs.datadoghq.com/llm_observability/setup/api/?tab=example#api-standards
 """
 
+from collections.abc import Sequence
 from typing import Any, Literal
 
-from typing_extensions import TypedDict
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm.types.integrations.custom_logger import StandardCustomLoggerInitParams
 
 
+class ToolCall(TypedDict, total=False):
+    """A tool call on a message, as LLM Obs names its fields."""
+
+    name: ReadOnly[str]
+    arguments: ReadOnly[dict[str, Any] | str]  # parsed object, or the raw string when it will not parse to one
+    tool_id: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class ToolResult(TypedDict, total=False):
+    """The result of a tool call, as LLM Obs names its fields."""
+
+    name: ReadOnly[str]
+    result: ReadOnly[str]
+    tool_id: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class ToolDefinition(TypedDict, total=False):
+    """A tool the model was offered on the request."""
+
+    name: ReadOnly[str]
+    description: ReadOnly[str]
+    schema: ReadOnly[dict[str, Any]]
+
+
+class Message(TypedDict, total=False):
+    """A message on a span, as LLM Obs names its fields."""
+
+    content: ReadOnly[str]
+    role: ReadOnly[str]
+    reasoning_content: ReadOnly[str]
+    tool_calls: ReadOnly[Sequence[ToolCall]]
+    tool_results: ReadOnly[Sequence[ToolResult]]
+
+
 class InputMeta(TypedDict):
-    messages: list[
-        dict[str, Any]  # changed to fit with tool calls
+    messages: Sequence[
+        Message | dict[str, Any]  # changed to fit with tool calls
     ]  # Relevant Issue: https://github.com/BerriAI/litellm/issues/9494
 
 
 class OutputMeta(TypedDict):
-    messages: list[Any]
+    messages: Sequence[Any]
 
 
 class DDLLMObsError(TypedDict, total=False):
@@ -36,6 +73,7 @@ class Meta(TypedDict, total=False):
     output: OutputMeta  # The span's output information.
     metadata: dict[str, Any]
     error: DDLLMObsError | None  # Error information on the span
+    tool_definitions: ReadOnly[Sequence[ToolDefinition]]  # The tools offered to the model on this request
 
 
 class LLMMetrics(TypedDict, total=False):
@@ -45,6 +83,9 @@ class LLMMetrics(TypedDict, total=False):
     time_to_first_token: float
     time_per_output_token: float
     total_cost: float
+    cache_read_input_tokens: ReadOnly[float]
+    cache_write_input_tokens: ReadOnly[float]
+    non_cached_input_tokens: ReadOnly[float]
 
 
 class LLMObsPayload(TypedDict, total=False):
diff --git a/litellm/types/integrations/prometheus.py b/litellm/types/integrations/prometheus.py
index 01ed8b08571..8498b6f6d00 100644
--- a/litellm/types/integrations/prometheus.py
+++ b/litellm/types/integrations/prometheus.py
@@ -270,6 +270,10 @@ DEFINED_PROMETHEUS_METRICS = Literal[
     "litellm_deployment_rpm_limit",
     "litellm_remaining_api_key_requests_for_model",
     "litellm_remaining_api_key_tokens_for_model",
+    "litellm_api_key_rate_limit_allowed_metric",
+    "litellm_api_key_rate_limit_used_metric",
+    "litellm_team_rate_limit_allowed_metric",
+    "litellm_team_rate_limit_used_metric",
     "litellm_llm_api_failed_requests_metric",
     "litellm_callback_logging_failures_metric",
     "litellm_in_flight_requests",
@@ -775,6 +779,22 @@ class PrometheusMetricLabels:
         UserAPIKeyLabelNames.MODEL_ID.value,
     ]
 
+    litellm_api_key_rate_limit_allowed_metric: ClassVar[tuple[str, ...]] = (
+        UserAPIKeyLabelNames.API_KEY_HASH.value,
+        UserAPIKeyLabelNames.API_KEY_ALIAS.value,
+        UserAPIKeyLabelNames.RATE_LIMIT_TYPE.value,
+    )
+
+    litellm_api_key_rate_limit_used_metric = litellm_api_key_rate_limit_allowed_metric
+
+    litellm_team_rate_limit_allowed_metric: ClassVar[tuple[str, ...]] = (
+        UserAPIKeyLabelNames.TEAM.value,
+        UserAPIKeyLabelNames.TEAM_ALIAS.value,
+        UserAPIKeyLabelNames.RATE_LIMIT_TYPE.value,
+    )
+
+    litellm_team_rate_limit_used_metric = litellm_team_rate_limit_allowed_metric
+
     litellm_llm_api_failed_requests_metric = [
         UserAPIKeyLabelNames.END_USER.value,
         UserAPIKeyLabelNames.API_KEY_HASH.value,
diff --git a/litellm/types/integrations/slack_alerting.py b/litellm/types/integrations/slack_alerting.py
index b1b7bc3541a..64c0c530e9b 100644
--- a/litellm/types/integrations/slack_alerting.py
+++ b/litellm/types/integrations/slack_alerting.py
@@ -91,6 +91,40 @@ class SlackAlertingArgs(LiteLLMPydanticObjectBase):
         default=False,
         description="If true, the alerting payload will be printed to the console.",
     )
+    daily_spend_per_user_threshold: float | None = Field(
+        default=None,
+        gt=0,
+        allow_inf_nan=False,
+        description="Alert when a user's spend for the current day (UTC) crosses this USD amount. Off by default.",
+    )
+    monthly_spend_per_user_threshold: float | None = Field(
+        default=None,
+        gt=0,
+        allow_inf_nan=False,
+        description="Alert when a user's spend for the current calendar month (UTC) crosses this USD amount. Off by default.",
+    )
+    spend_anomaly_multiplier: float = Field(
+        default=3.0,
+        gt=0,
+        allow_inf_nan=False,
+        description="Flag a user's spend as anomalous when today's spend exceeds this multiple of their trailing daily average.",
+    )
+    spend_anomaly_baseline_days: int = Field(
+        default=7,
+        ge=1,
+        description="Number of trailing days used to compute a user's daily average spend for anomaly detection.",
+    )
+    spend_anomaly_min_spend: float = Field(
+        default=10.0,
+        gt=0,
+        allow_inf_nan=False,
+        description="Minimum spend (USD) a user must reach today before an anomaly alert can fire. Reduces false positives.",
+    )
+    user_spend_check_interval: int = Field(
+        default=3600,
+        ge=60,
+        description="How often (in seconds) to check per-user spend thresholds and anomalies. Default is hourly.",
+    )
 
 
 class DeploymentMetrics(LiteLLMPydanticObjectBase):
@@ -138,6 +172,8 @@ class AlertType(str, Enum):
     budget_alerts = "budget_alerts"
     spend_reports = "spend_reports"
     failed_tracking_spend = "failed_tracking_spend"
+    user_spend_thresholds = "user_spend_thresholds"
+    user_spend_anomalies = "user_spend_anomalies"
 
     # Database alerts
     db_exceptions = "db_exceptions"
@@ -182,6 +218,7 @@ DEFAULT_ALERT_TYPES: Final[list[AlertType]] = [
     AlertType.budget_alerts,
     AlertType.spend_reports,
     AlertType.failed_tracking_spend,
+    AlertType.user_spend_thresholds,
     # Database alerts
     AlertType.db_exceptions,
     # Report alerts
diff --git a/litellm/types/llms/anthropic_messages/anthropic_response.py b/litellm/types/llms/anthropic_messages/anthropic_response.py
index 42ca3fd6d4b..4fe1dafc73b 100644
--- a/litellm/types/llms/anthropic_messages/anthropic_response.py
+++ b/litellm/types/llms/anthropic_messages/anthropic_response.py
@@ -78,6 +78,16 @@ class AnthropicUsage(TypedDict, total=False):
     server_tool_use: NotRequired[ReadOnly[ServerToolUsage]]
 
 
+class AnthropicStopDetails(TypedDict, total=False):
+    """
+    Safeguard verdict accompanying a `stop_reason: "refusal"` response:
+    https://platform.claude.com/docs/en/build-with-claude/refusals-and-fallback
+    """
+
+    category: ReadOnly[str | None]
+    explanation: ReadOnly[str | None]
+
+
 class AnthropicMessagesResponse(TypedDict, total=False):
     """
     Anthropic Messages API Response: https://docs.anthropic.com/en/api/messages
@@ -90,7 +100,8 @@ class AnthropicMessagesResponse(TypedDict, total=False):
     id: str
     model: str | None  # This represents the Model type from Anthropic
     role: Literal["assistant"] | None
-    stop_reason: Literal["end_turn", "max_tokens", "stop_sequence", "tool_use"] | None
+    stop_reason: Literal["end_turn", "max_tokens", "stop_sequence", "tool_use", "refusal"] | None
+    stop_details: NotRequired[ReadOnly[AnthropicStopDetails | None]]
     stop_sequence: str | None
     type: Literal["message"] | None
     usage: AnthropicUsage | None
diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py
index a6115640d78..32d88da0085 100644
--- a/litellm/types/llms/openai.py
+++ b/litellm/types/llms/openai.py
@@ -327,6 +327,10 @@ class BatchGuardrailReport(BaseModel):
     """Every record that was redacted or dropped, in file order."""
 
 
+_JsonValue: TypeAlias = object
+"""Alias for ``object``, usable inside model bodies that declare a field named ``object``."""
+
+
 BATCH_GUARDRAIL_RESPONSE_FIELD: Final = "litellm_batch_guardrail"
 
 
@@ -1191,7 +1195,7 @@ class ShellToolParam(TypedDict, total=False):
     type: Required[Literal["shell"] | str]
     """The type of tool. Use ``\"shell\"``."""
 
-    environment: Required[dict[str, Any]]
+    environment: Required[dict[str, object]]
     """Environment config: ``type`` (e.g. ``\"container_auto\"``, ``\"container_reference\"``, ``\"local\"``), optional ``container_id``, ``network_policy``, ``domain_secrets``, ``skills``."""
 
 
@@ -1308,7 +1312,7 @@ class ResponseAPIUsage(BaseLiteLLMOpenAIResponseObject):
 
     @field_validator("cost", mode="before")
     @classmethod
-    def parse_cost(cls, v: Any) -> float | None:
+    def parse_cost(cls, v: object) -> object:
         """Normalise cost: accept either a float or a dict with a ``total_cost`` key."""
         if isinstance(v, dict):
             return v.get("total_cost")
@@ -1805,7 +1809,7 @@ class ErrorEventError(BaseLiteLLMOpenAIResponseObject):
     type: str  # e.g., 'invalid_request_error'
     code: str  # e.g., 'context_length_exceeded'
     message: str
-    param: str | dict[str, Any] | None = None
+    param: str | dict[str, object] | None = None
 
 
 class ErrorEvent(BaseLiteLLMOpenAIResponseObject):
@@ -2162,6 +2166,42 @@ class OpenAIRealtimeDoneEvent(TypedDict):
     type: Literal["response.done"]
 
 
+class OpenAIRealtimeInputAudioBufferSpeechEvent(TypedDict):
+    type: ReadOnly[Literal["input_audio_buffer.speech_started", "input_audio_buffer.speech_stopped"]]
+    event_id: ReadOnly[str]
+    item_id: ReadOnly[str]
+
+
+class OpenAIRealtimeInputAudioTranscriptionDelta(TypedDict):
+    type: ReadOnly[Literal["conversation.item.input_audio_transcription.delta"]]
+    event_id: ReadOnly[str]
+    item_id: ReadOnly[str]
+    content_index: ReadOnly[int]
+    delta: ReadOnly[str]
+
+
+class OpenAIRealtimeInputAudioTranscriptionCompleted(TypedDict):
+    type: ReadOnly[Literal["conversation.item.input_audio_transcription.completed"]]
+    event_id: ReadOnly[str]
+    item_id: ReadOnly[str]
+    content_index: ReadOnly[int]
+    transcript: ReadOnly[str]
+
+
+class OpenAIRealtimeUsageTokenDetails(TypedDict):
+    audio_tokens: ReadOnly[int]
+    text_tokens: ReadOnly[int]
+    cached_tokens: NotRequired[ReadOnly[int]]
+
+
+class OpenAIRealtimeResponseUsage(TypedDict):
+    input_tokens: ReadOnly[int]
+    output_tokens: ReadOnly[int]
+    total_tokens: ReadOnly[int]
+    input_token_details: NotRequired[ReadOnly[OpenAIRealtimeUsageTokenDetails]]
+    output_token_details: NotRequired[ReadOnly[OpenAIRealtimeUsageTokenDetails]]
+
+
 class OpenAIRealtimeEventTypes(Enum):
     SESSION_CREATED = "session.created"
     # Beta delta event names
@@ -2199,6 +2239,9 @@ OpenAIRealtimeEvents = (
     | OpenAIRealtimeOutputItemDone
     | OpenAIRealtimeFunctionCallArgumentsDone
     | OpenAIRealtimeDoneEvent
+    | OpenAIRealtimeInputAudioBufferSpeechEvent
+    | OpenAIRealtimeInputAudioTranscriptionDelta
+    | OpenAIRealtimeInputAudioTranscriptionCompleted
 )
 
 OpenAIRealtimeStreamList = list[OpenAIRealtimeEvents]
@@ -2379,7 +2422,7 @@ class OpenAIVideoObject(BaseModel):
     expires_at: int | None = None
     """Unix timestamp (seconds) for when the downloadable assets expire, if set."""
 
-    error: dict[str, Any] | None = None
+    error: dict[str, _JsonValue] | None = None
     """Error payload that explains why generation failed, if applicable."""
 
     progress: int | None = None
@@ -2397,15 +2440,15 @@ class OpenAIVideoObject(BaseModel):
     model: str | None = None
     """The video generation model that produced the job."""
 
-    _hidden_params: dict[str, Any] = {}
+    _hidden_params: dict[str, _JsonValue] = {}
 
     def __contains__(self, key) -> bool:
         return hasattr(self, key)
 
-    def get(self, key, default=None):
+    def get(self, key, default=None) -> _JsonValue:
         return getattr(self, key, default)
 
-    def __getitem__(self, key):
+    def __getitem__(self, key) -> _JsonValue:
         return getattr(self, key)
 
     def json(self, **kwargs):
diff --git a/litellm/types/management_endpoints/auto_router_endpoints.py b/litellm/types/management_endpoints/auto_router_endpoints.py
index bde3f5f9e7e..88869a1edfb 100644
--- a/litellm/types/management_endpoints/auto_router_endpoints.py
+++ b/litellm/types/management_endpoints/auto_router_endpoints.py
@@ -245,27 +245,71 @@ ShadowEvalStatus: TypeAlias = Literal["running", "completed", "stopped"]
 
 ShadowEvalDirection: TypeAlias = Literal["forward", "reverse"]
 
+ShadowEvalTargetType: TypeAlias = Literal["key", "team", "user"]
+
 DEFAULT_SHADOW_EVAL_JUDGE_MODEL: Final[str] = "anthropic/claude-sonnet-5"
 
 # Sample-count ceiling written on every new job: a zero-cost error loop (a shadow arm that
 # fails before billing) never consumes spend budget, so it must terminate on count instead.
+# A multi-router job writes one attempt row per router arm, so the valve is reached
+# proportionally sooner; it is a safety valve, not a sample budget.
 SHADOW_EVAL_TURN_VALVE: Final[int] = 10_000
 
+SHADOW_EVAL_MAX_ROUTERS: Final[int] = 4
+
 
 class StartShadowEvalRequest(BaseModel):
-    """Start duplicating one or more keys' traffic for blind comparison against an auto-router."""
+    """Start duplicating one or more targets' traffic for blind comparison against an auto-router.
+
+    A target is a virtual key, a team, or a user; each becomes its own leg with its own
+    budget and stop state. Team and user targets match on the identity every request
+    carries after auth (user_api_key_team_id / user_api_key_user_id), so they cover
+    JWT-authenticated traffic, which presents no virtual key at all."""
 
     api_key_ids: tuple[str, ...] = Field(
-        min_length=1,
+        default=(),
         max_length=100,
         description=(
-            "The hashed virtual keys whose traffic will be shadowed. Shadow evaluation runs ONLY on these "
-            "keys' traffic; requests made with any other key are not sampled. Each key carries its own "
-            "max_budget spend budget, so one key exhausting its budget leaves the others sampling. At most 100 "
-            "keys per job, which also bounds every read the job's endpoints make."
+            "Hashed virtual keys whose traffic will be shadowed. Combined with team_ids and user_ids the job "
+            "needs at least one target and at most 100, which also bounds every read the job's endpoints make. "
+            "Each target carries its own max_budget spend budget, so one exhausting its budget leaves the "
+            "others sampling."
+        ),
+    )
+    team_ids: tuple[str, ...] = Field(
+        default=(),
+        max_length=100,
+        description=(
+            "Teams whose traffic will be shadowed, matched on the team every authenticated request resolves "
+            "to, so a team's JWT-auth and virtual-key traffic are both sampled"
+        ),
+    )
+    user_ids: tuple[str, ...] = Field(
+        default=(),
+        max_length=100,
+        description=(
+            "Users whose traffic will be shadowed, matched on the user every authenticated request resolves "
+            "to across all their teams: JWT requests carrying their subject claim and virtual keys they own"
+        ),
+    )
+    router_name: str | None = Field(
+        default=None,
+        description=(
+            "The auto-router under evaluation, in either direction: the single-router spelling of "
+            "router_names. Provide exactly one of the two fields"
+        ),
+    )
+    router_names: tuple[str, ...] = Field(
+        default=(),
+        max_length=SHADOW_EVAL_MAX_ROUTERS,
+        description=(
+            "The auto-routers under evaluation, at most "
+            f"{SHADOW_EVAL_MAX_ROUTERS}. Every sampled request runs through every router listed and each "
+            "arm is judged independently against the same real response, so routers compare head-to-head "
+            "on identical traffic. More than one router requires direction 'forward'. After validation "
+            "this field always carries the full deduplicated set, whichever spelling the caller used"
         ),
     )
-    router_name: str = Field(description="The auto-router under evaluation, in either direction")
     direction: ShadowEvalDirection = Field(
         default="forward",
         description=(
@@ -285,7 +329,7 @@ class StartShadowEvalRequest(BaseModel):
     shadow_percentage: float = Field(
         ge=0.1,
         le=100.0,
-        description="Percentage of the key's requests to duplicate through the router",
+        description="Percentage of each target's requests to duplicate through the router",
     )
     judge_model: str = Field(
         default=DEFAULT_SHADOW_EVAL_JUDGE_MODEL,
@@ -306,10 +350,11 @@ class StartShadowEvalRequest(BaseModel):
         ge=0.01,
         le=10_000,
         description=(
-            "Per-key USD budget for the eval's own overhead, the shadow-arm and judge calls, priced with "
-            "the same figures the spend pipeline bills. EACH scoped key samples until its recorded eval "
-            "spend reaches this, so a job over N keys spends at most about N times max_budget; in-flight "
-            "samples can overshoot the cap by one sampling cache window"
+            "Per-target USD budget for the eval's own overhead, the shadow-arm and judge calls, priced with "
+            "the same figures the spend pipeline bills. EACH scoped target samples until its recorded eval "
+            "spend reaches this, so a job over N targets spends at most about N times max_budget; in-flight "
+            "samples can overshoot the cap by one sampling cache window. Every router arm draws from the "
+            "same per-target budget, so a multi-router job reaches it proportionally sooner"
         ),
     )
 
@@ -319,7 +364,7 @@ class StartShadowEvalRequest(BaseModel):
         """Pydantic ignores unknown fields, so a caller still sending max_turns would
         silently run on the default dollar budget instead of the bound they asked for."""
         if isinstance(values, Mapping) and "max_turns" in values:
-            raise ValueError("max_turns was replaced by max_budget, the per-key USD cap on the eval's own spend")
+            raise ValueError("max_turns was replaced by max_budget, the per-target USD cap on the eval's own spend")
         return values
 
     @field_validator("shadow_percentage")
@@ -327,12 +372,21 @@ class StartShadowEvalRequest(BaseModel):
     def _round_percentage(cls, value: float) -> float:
         return round(value, 2)
 
-    @field_validator("api_key_ids")
+    @field_validator("api_key_ids", "team_ids", "user_ids")
     @classmethod
-    def _dedupe_keys(cls, value: tuple[str, ...]) -> tuple[str, ...]:
-        """A key named twice would collide with itself on the one-active-per-(key, direction) index."""
+    def _dedupe_targets(cls, value: tuple[str, ...]) -> tuple[str, ...]:
+        """A target named twice would collide with itself on the one-active-per-(target, direction) index."""
         return tuple(dict.fromkeys(value))
 
+    @model_validator(mode="after")
+    def _at_least_one_target_at_most_hundred(self) -> "StartShadowEvalRequest":
+        total: Final = len(self.api_key_ids) + len(self.team_ids) + len(self.user_ids)
+        if total < 1:
+            raise ValueError("at least one target is required: pass api_key_ids, team_ids, or user_ids")
+        if total > 100:
+            raise ValueError("at most 100 targets per job across api_key_ids, team_ids, and user_ids")
+        return self
+
     @model_validator(mode="after")
     def _baseline_model_matches_direction(self) -> "StartShadowEvalRequest":
         if self.direction == "reverse" and self.baseline_model is None:
@@ -341,10 +395,28 @@ class StartShadowEvalRequest(BaseModel):
             raise ValueError("baseline_model is only meaningful when direction is 'reverse'")
         return self
 
+    @model_validator(mode="after")
+    def _resolve_router_set(self) -> "StartShadowEvalRequest":
+        """Whichever spelling the caller used, router_names leaves validation as the full
+        deduplicated set, so every downstream reader consumes one field."""
+        if (self.router_name is None) == (not self.router_names):
+            raise ValueError("provide exactly one of router_name or router_names")
+        single: Final = () if self.router_name is None else (self.router_name,)
+        routers: Final = tuple(dict.fromkeys(self.router_names or single))
+        if not all(name.strip() for name in routers):
+            raise ValueError("router names must be non-empty strings")
+        if len(routers) > 1 and self.direction == "reverse":
+            raise ValueError("a reverse job evaluates one router against baseline_model; pass a single router")
+        # A returned model_copy is ignored on the __init__ construction path, so the
+        # normalization must land as a self attribute store to hold for every caller.
+        self.router_names = routers
+        return self
+
 
 class ShadowEvalSlice(BaseModel):
-    """Judge outcomes for one slice of a job's verdicts (a router tier, or one of the
-    models that served the real arm)."""
+    """Judge outcomes for one slice of a job's verdicts: a router tier, one of the
+    models that served the real arm, or one scoped target (embedded on that target's
+    own entry, so slices never need re-joining to a target by id)."""
 
     group: str
     turn_count: int
@@ -395,21 +467,28 @@ class ShadowEvalResult(BaseModel):
             "and in reverse the models the router itself picked"
         )
     )
-    by_key: tuple[ShadowEvalSlice, ...] = Field(
+    by_router: tuple[ShadowEvalSlice, ...] = Field(
+        default=(),
         description=(
-            "One slice per scoped key that has judged verdicts, grouped on the raw key hash. Keys the job "
-            "scopes but has not judged a turn for yet are absent rather than reported as zero"
+            "One slice per router arm, grouped on the router name. Every arm of a multi-router job is "
+            "judged against the same real responses over the same sampled requests, so these slices "
+            "compare routers head-to-head: like-for-like win rates and spends on identical traffic. "
+            "Verdicts from before arm stamping existed count toward the job's own router"
         ),
     )
     overall_shadow_win_rate_pct: float
     overall_tie_rate_pct: float
     sampled_real_spend: float = Field(
         default=0.0,
-        description="USD the real arm billed across all judged turns, cache-served turns excluded",
+        description=(
+            "USD the real arm billed across all judged turns, cache-served turns excluded. A judged turn "
+            "is one (request, router arm) verdict, so a multi-router job counts the real response once per "
+            "arm it was judged against; per-router comparisons read by_router"
+        ),
     )
     sampled_shadow_spend: float = Field(
         default=0.0,
-        description="USD the shadow arm billed across the same turns, judge excluded, like for like",
+        description="USD the shadow arms billed across the same turns, judge excluded, like for like",
     )
     not_sampled_count: int | None = Field(
         default=None,
@@ -436,27 +515,28 @@ class ShadowEvalResult(BaseModel):
     )
 
 
-class ShadowEvalJobKeyResponse(BaseModel):
-    """One key a job shadows, with its own budget and stop state."""
+class ShadowEvalJobTargetResponse(BaseModel):
+    """One target a job shadows (a key, team, or user), with its own budget and stop state."""
 
-    api_key_id: str = Field(description="The hashed virtual key whose traffic this entry scopes")
+    target_type: ShadowEvalTargetType = Field(description="What kind of entity this entry scopes")
+    target_id: str = Field(description="The hashed virtual key, team id, or user id whose traffic this entry scopes")
     max_turns: int = Field(
         description=(
-            "This key's sample-count ceiling: the whole budget for jobs created before max_budget "
+            "This target's sample-count ceiling: the whole budget for jobs created before max_budget "
             "existed, and the error-loop safety valve otherwise"
         )
     )
     max_budget: float | None = Field(
         default=None,
         description=(
-            "This key's own USD budget for the eval's shadow and judge spend, independent of its "
+            "This target's own USD budget for the eval's shadow and judge spend, independent of its "
             "siblings'; None on jobs created before spend budgets existed, which max_turns alone bounds"
         ),
     )
     stopped_at: datetime | None = Field(
         default=None,
         description=(
-            "When this key's slot was stamped free, whether its own budget ran out, the window closed, "
+            "When this target's slot was stamped free, whether its own budget ran out, the window closed, "
             "or an operator stopped the job; status is derived, so a spent budget reads completed even "
             "while this is still unset"
         ),
@@ -464,47 +544,61 @@ class ShadowEvalJobKeyResponse(BaseModel):
     attempt_count: int | None = Field(
         default=None,
         description=(
-            "This key's sampled attempts so far, judged and errored alike, the same count the sampler "
+            "This target's sampled attempts so far, judged and errored alike, the same count the sampler "
             "budgets against max_turns; populated on list and detail responses. Frozen at stopped_at "
-            "once the key is stamped, so in-flight attempts landing after a stop never reclassify it"
+            "once the target is stamped, so in-flight attempts landing after a stop never reclassify it"
         ),
     )
     spend: float | None = Field(
         default=None,
         description=(
-            "This key's recorded shadow plus judge spend in USD, the same figure the sampler budgets "
+            "This target's recorded shadow plus judge spend in USD, the same figure the sampler budgets "
             "against max_budget; populated on list and detail responses and frozen at stopped_at "
             "exactly like attempt_count"
         ),
     )
 
+    verdicts: "ShadowEvalSlice | None" = Field(
+        default=None,
+        description="This target's own judged-verdict slice; detail endpoint only, None until a turn is judged",
+    )
+
     @property
     def budget_spent(self) -> bool:
         over_spend: Final = self.max_budget is not None and self.spend is not None and self.spend >= self.max_budget
         return over_spend or (self.attempt_count is not None and self.attempt_count >= self.max_turns)
 
-    key_alias: str | None = Field(
+    target_alias: str | None = Field(
         default=None,
-        description="Alias of the shadowed key, resolved from the key row at read time; None when unset or deleted",
+        description=(
+            "Display label resolved from the target's own row at read time: the key's alias, the team's "
+            "alias, or the user's email; None when unset or deleted"
+        ),
     )
     key_name: str | None = Field(
         default=None,
-        description="Masked display name (sk-...) of the shadowed key, resolved at read time like key_alias",
+        description="Masked display name (sk-...) for key targets, resolved at read time; None for teams and users",
     )
 
 
 class ShadowEvalJobResponse(BaseModel):
-    """A shadow-eval job over one or more keys, each with its own budget and stop state;
-    status is derived from stopped_by, the keys' stop and budget state, and ends_at,
+    """A shadow-eval job over one or more targets, each with its own budget and stop state;
+    status is derived from stopped_by, the targets' stop and budget state, and ends_at,
     never stored, so no writer anywhere can produce an inconsistent one. Aggregate
     fields are populated by the detail endpoint only and stay None on list responses."""
 
     job_id: str
-    keys: tuple[ShadowEvalJobKeyResponse, ...] = Field(
+    targets: tuple[ShadowEvalJobTargetResponse, ...] = Field(
         min_length=1,
-        description="The keys whose traffic this job evaluates, and only those keys', each with its own budget",
+        description="The targets whose traffic this job evaluates, and only theirs, each with its own budget",
+    )
+    router_names: tuple[str, ...] = Field(
+        min_length=1,
+        description=(
+            "Every auto-router this job runs as a shadow arm. Multi-router jobs sample one slice of "
+            "traffic and judge every arm against the same real responses"
+        ),
     )
-    router_name: str
     direction: ShadowEvalDirection = "forward"
     baseline_model: str | None = None
     judge_model: str
@@ -526,13 +620,20 @@ class ShadowEvalJobResponse(BaseModel):
     last_error: str | None = Field(default=None, description="Most recent attempt error; detail endpoint only")
     results: ShadowEvalResult | None = Field(default=None, description="Stratified verdicts; detail endpoint only")
 
+    @computed_field
+    @property
+    def router_name(self) -> str:
+        """The first router, kept for callers that predate router_names; derived so the
+        two fields can never disagree."""
+        return self.router_names[0]
+
     @computed_field
     @property
     def status(self) -> ShadowEvalStatus:
         """Three recorded facts, no history-guessing: a stop is stopped_by (the migration
         backfills it for every job that displayed stopped when the column arrived, so the
-        pre-column population is closed), completion is the window passing or every key
-        spending its budget, and anything else is running. The all-keys-stamped fallback
+        pre-column population is closed), completion is the window passing or every target
+        spending its budget, and anything else is running. The all-targets-stamped fallback
         covers only stops written by pre-column pods during a rolling deploy."""
         if self.stopped_by is not None:
             return "stopped"
@@ -540,8 +641,8 @@ class ShadowEvalJobResponse(BaseModel):
             self.ends_at if self.ends_at.tzinfo else self.ends_at.replace(tzinfo=timezone.utc)
         ):
             return "completed"
-        if all(key.budget_spent for key in self.keys):
+        if all(target.budget_spent for target in self.targets):
             return "completed"
-        if all(key.stopped_at is not None for key in self.keys):
+        if all(target.stopped_at is not None for target in self.targets):
             return "stopped"
         return "running"
diff --git a/litellm/types/mcp.py b/litellm/types/mcp.py
index 1b8baf2da09..a59fcb1bcb5 100644
--- a/litellm/types/mcp.py
+++ b/litellm/types/mcp.py
@@ -6,7 +6,7 @@ from typing import TYPE_CHECKING, Any, Final, Literal
 from urllib.parse import urlsplit
 
 import httpx
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict, Field
 from typing_extensions import TypedDict
 
 from litellm.types.llms.base import HiddenParams
@@ -91,6 +91,33 @@ class MCPPublicServer(BaseModel):
     mcp_info: dict[str, Any] | None = None
 
 
+class MCPToolSearchSettings(BaseModel):
+    """`litellm_settings.mcp_tool_search`: how the native `mcp_tool_search` virtual tool ranks the caller's tools."""
+
+    model_config = ConfigDict(frozen=True)
+
+    embedding_model: str | None = Field(
+        default=None,
+        description="Embedding model from model_list used to rank tools by meaning. Unset keeps keyword matching.",
+    )
+    top_k: int = Field(
+        default=5,
+        ge=1,
+        le=100,
+        description="Most ranked tools a search returns. A smaller top_k in the tool call wins. Core tools do not count.",
+    )
+    similarity_threshold: float = Field(
+        default=0.0,
+        ge=0.0,
+        le=1.0,
+        description="Lowest cosine similarity a tool needs to appear in semantic results (0.0 = no cutoff).",
+    )
+    core_tools: tuple[str, ...] = Field(
+        default=(),
+        description="Tool names always returned first when the caller can access them, e.g. `my_server-get_rates`.",
+    )
+
+
 # OAuth 2.0 token-endpoint client authentication method (RFC 6749 section 2.3.1).
 MCPTokenEndpointAuthMethod = Literal["client_secret_basic", "client_secret_post"]
 
diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/alice.py b/litellm/types/proxy/guardrails/guardrail_hooks/alice.py
new file mode 100644
index 00000000000..73d31673dab
--- /dev/null
+++ b/litellm/types/proxy/guardrails/guardrail_hooks/alice.py
@@ -0,0 +1,21 @@
+from pydantic import Field
+
+from .base import GuardrailConfigModel
+
+
+class AliceGuardrailConfigModel(GuardrailConfigModel):
+    api_key: str | None = Field(
+        default=None,
+        description=("The API key for Alice. If not provided, the `ALICE_API_KEY` environment variable is checked."),
+    )
+    api_base: str | None = Field(
+        default=None,
+        description=(
+            "The API base URL for Alice. If not provided, the `ALICE_API_BASE` environment "
+            "variable is checked, then `https://api.alice.io`."
+        ),
+    )
+
+    @staticmethod
+    def ui_friendly_name() -> str:
+        return "Alice"
diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/prompt_security.py b/litellm/types/proxy/guardrails/guardrail_hooks/prompt_security.py
index 6e64f0f47a5..94f8161f44e 100644
--- a/litellm/types/proxy/guardrails/guardrail_hooks/prompt_security.py
+++ b/litellm/types/proxy/guardrails/guardrail_hooks/prompt_security.py
@@ -12,6 +12,10 @@ class PromptSecurityGuardrailConfigModel(GuardrailConfigModel):
         default=None,
         description="The API base for the Prompt Security guardrail. If not provided, the `PROMPT_SECURITY_API_BASE` environment variable is used.",
     )
+    file_sanitization_fail_open: bool = Field(
+        default=True,
+        description="Whether file sanitization timeouts allow the original file through instead of blocking the request.",
+    )
 
     @staticmethod
     def ui_friendly_name() -> str:
diff --git a/litellm/types/proxy/management_endpoints/scim_v2.py b/litellm/types/proxy/management_endpoints/scim_v2.py
index 1612ea03817..7825684cfe5 100644
--- a/litellm/types/proxy/management_endpoints/scim_v2.py
+++ b/litellm/types/proxy/management_endpoints/scim_v2.py
@@ -150,6 +150,12 @@ class SCIMGroup(SCIMResource):
     members: list[SCIMMember] | None = None
 
 
+class SCIMPlaceholderMergeResult(BaseModel):
+    placeholder_user_id: str
+    merged_into_user_id: str
+    team_ids: tuple[str, ...]
+
+
 # SCIM List Response Models
 class SCIMListResponse(BaseModel):
     schemas: list[str] = ["urn:ietf:params:scim:api:messages:2.0:ListResponse"]
diff --git a/litellm/types/proxy/public_endpoints/public_endpoints.py b/litellm/types/proxy/public_endpoints/public_endpoints.py
index f6ee054ceaa..c7f80a61e0f 100644
--- a/litellm/types/proxy/public_endpoints/public_endpoints.py
+++ b/litellm/types/proxy/public_endpoints/public_endpoints.py
@@ -43,6 +43,8 @@ class AgentCredentialField(BaseModel):
     options: list[str] | None = None
     default_value: str | None = None
     include_in_litellm_params: bool | None = None
+    validation_pattern: str | None = None
+    validation_message: str | None = None
 
 
 class AgentCreateInfo(BaseModel):
diff --git a/litellm/types/rerank.py b/litellm/types/rerank.py
index 903781b2ccd..a76e6cf1187 100644
--- a/litellm/types/rerank.py
+++ b/litellm/types/rerank.py
@@ -4,8 +4,10 @@ https://docs.cohere.com/reference/rerank
 
 """
 
-from pydantic import BaseModel, PrivateAttr
-from typing_extensions import Required, TypedDict
+from typing import Literal
+
+from pydantic import BaseModel, ConfigDict, PrivateAttr
+from typing_extensions import ReadOnly, Required, TypedDict
 
 
 class RerankRequest(BaseModel):
@@ -21,6 +23,18 @@ class RerankRequest(BaseModel):
     # (e.g. hosted vLLM / Qwen3-Reranker, DeepInfra). Omitted from the outgoing
     # request when None, so this is fully backward-compatible.
     instruction: str | None = None
+    truncate_prompt_tokens: int | None = None
+    truncation_side: Literal["left", "right"] | None = None
+    max_tokens_per_query: int | None = None
+
+
+class HostedVLLMRerankTruncationParams(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    truncate_prompt_tokens: int | None = None
+    truncation_side: Literal["left", "right"] | None = None
+    max_tokens_per_query: int | None = None
+    max_tokens_per_doc: int | None = None
 
 
 class OptionalRerankParams(TypedDict, total=False):
@@ -32,6 +46,9 @@ class OptionalRerankParams(TypedDict, total=False):
     max_chunks_per_doc: int | None
     max_tokens_per_doc: int | None
     instruction: str | None
+    truncate_prompt_tokens: ReadOnly[int | None]
+    truncation_side: ReadOnly[Literal["left", "right"] | None]
+    max_tokens_per_query: ReadOnly[int | None]
 
 
 class RerankBilledUnits(TypedDict, total=False):
diff --git a/litellm/types/router.py b/litellm/types/router.py
index 97bd93f3f47..4f4df1a8d2e 100644
--- a/litellm/types/router.py
+++ b/litellm/types/router.py
@@ -106,6 +106,20 @@ class RetryPolicy(BaseModel):
     InternalServerErrorRetries: int | None = None
 
 
+OptionalPreCallChecks = list[
+    Literal[
+        "prompt_caching",
+        "router_budget_limiting",
+        "responses_api_deployment_check",
+        "deployment_affinity",
+        "session_affinity",
+        "forward_client_headers_by_model_group",
+        "enforce_model_rate_limits",
+        "encrypted_content_affinity",
+    ]
+]
+
+
 class UpdateRouterConfig(BaseModel):
     """
     Set of params that you can modify via `router.update_settings()`.
@@ -128,6 +142,7 @@ class UpdateRouterConfig(BaseModel):
     model_group_alias: dict[str, str | dict] | None = {}
     enable_tag_filtering: bool | None = None
     tag_routing_prefix: str | None = None
+    optional_pre_call_checks: OptionalPreCallChecks | None = None
 
     model_config = ConfigDict(protected_namespaces=())
 
@@ -189,6 +204,11 @@ class ModelInfo(MirroredPricingParams):
     # router-wide default.
     enable_tag_filtering: bool | None = None
 
+    # when True, calls routed to this deployment persist a router_metadata block
+    # (requested model group, selected model + provider, router correlation id)
+    # in the spend log row's metadata. Set it on every deployment of the group.
+    internal_router_model: bool | None = None
+
     def __init__(self, id: str | int | None = None, **params) -> None:
         if id is None:
             id = str(uuid.uuid4())  # Generate a UUID if id is None or not provided
@@ -285,6 +305,7 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams):
     """
 
     custom_llm_provider: str | None = None
+    rust: bool | None = None
     tpm: int | None = None
     rpm: int | None = None
     itpm: int | None = None
@@ -364,7 +385,7 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams):
 
     @model_validator(mode="before")
     @classmethod
-    def preprocess_input_data(cls, data: Any) -> Any:
+    def preprocess_input_data(cls, data: object) -> object:
         """
         Pre-process input data before validation:
         1. Filter out reserved Python keywords ('self', 'params', '__class__') to prevent
@@ -622,6 +643,11 @@ class AlertingConfig(BaseModel):
     alerting_threshold: float | None = 300
 
 
+def _resolved_annotations(model_class: type[object]) -> Mapping[str, object]:
+    """Resolve a class's annotations, keeping each resolved annotation opaque."""
+    return get_type_hints(model_class)
+
+
 class ModelGroupInfo(BaseModel):
     model_group: str
     providers: list[str]
@@ -650,7 +676,7 @@ class ModelGroupInfo(BaseModel):
     configurable_clientside_auth_params: CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS = None
 
     def __init__(self, **data) -> None:
-        for field_name, field_type in get_type_hints(self.__class__).items():
+        for field_name, field_type in _resolved_annotations(self.__class__).items():
             if field_type is bool and data.get(field_name) is None:
                 data[field_name] = False
         super().__init__(**data)
@@ -859,20 +885,6 @@ class FallbackAccessCheck(Protocol):
     async def __call__(self, *, model: str, request_kwargs: Mapping[str, object], llm_router: "Router") -> bool: ...
 
 
-OptionalPreCallChecks = list[
-    Literal[
-        "prompt_caching",
-        "router_budget_limiting",
-        "responses_api_deployment_check",
-        "deployment_affinity",
-        "session_affinity",
-        "forward_client_headers_by_model_group",
-        "enforce_model_rate_limits",
-        "encrypted_content_affinity",
-    ]
-]
-
-
 class LiteLLM_RouterFileObject(TypedDict, total=False):
     """
     Tracking the litellm params hash, used for mapping the file id to the right model
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 4bf8289d725..ee6f09e05dc 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -193,6 +193,38 @@ class AgenticLoopParams(TypedDict, total=False):
     """The LLM provider name (e.g., 'bedrock', 'anthropic')"""
 
 
+class OffPeakWindow(TypedDict, total=False):
+    """One off-peak rule: UTC time-of-day windows, optionally restricted to weekdays.
+
+    hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of them; a window may wrap past
+    midnight and an equal-ended window covers the whole day. weekdays is a list of days the
+    rule applies on, as ISO-8601 numbers (1 = Monday .. 7 = Sunday) or English day names;
+    omitted means every day. The weekday is read on the calendar named by the block's
+    weekday_timezone.
+    """
+
+    hours_utc: ReadOnly[str | Sequence[str]]
+    weekdays: ReadOnly[Sequence[int | str]]
+
+
+class OffPeakPricing(TypedDict, total=False):
+    """Time-windowed off-peak rates for providers that discount by time of day (e.g. DeepSeek).
+
+    hours_utc is a "HH:MM-HH:MM" string in UTC, or a list of them for multiple daily windows,
+    applying on every day of the week; a window may wrap past midnight. windows adds
+    day-of-week-qualified rules (e.g. weekend-only whole-day off-peak), matched as a union
+    with hours_utc. weekday_timezone names the IANA calendar weekdays are read on, defaulting
+    to UTC. Any rate left unset falls back to the standard rate.
+    """
+
+    hours_utc: ReadOnly[str | Sequence[str]]
+    windows: ReadOnly[Sequence[OffPeakWindow]]
+    weekday_timezone: ReadOnly[str]
+    input_cost_per_token: ReadOnly[float]
+    output_cost_per_token: ReadOnly[float]
+    cache_read_input_token_cost: ReadOnly[float]
+
+
 class ModelInfoBase(ProviderSpecificModelInfo, total=False):
     key: Required[str]  # the key in litellm.model_cost which is returned
 
@@ -225,6 +257,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False):
     # Smallest prefix this model will actually cache, whatever caching mechanism its provider uses.
     # Absent means the provider-agnostic default applies; see MINIMUM_PROMPT_CACHE_TOKEN_COUNT.
     prompt_cache_min_tokens: int | None
+    off_peak_pricing: ReadOnly[OffPeakPricing | None]  # time-windowed off-peak rates
     input_cost_per_character: float | None  # only for vertex ai models
     input_cost_per_audio_token: float | None
     input_cost_per_token_above_128k_tokens: float | None  # only for vertex ai models
@@ -2806,6 +2839,7 @@ class StandardLoggingRoutingDecisionTierBoundaries(TypedDict):
 
 RoutingDecisionCause = Literal[
     "heuristic_scorer",
+    "heuristic_v2",
     # The scorer found 2+ reasoning markers and forced REASONING regardless of score.
     # A distinct cause rather than a marker inside `signals`, because it is the fact
     # that tells a reader the score did NOT choose the tier; encoding it as free text
@@ -2818,6 +2852,7 @@ RoutingDecisionCause = Literal[
     # scorer, and from "classifier_fallback", which is the scorer running because a call failed:
     # only this cause means an LLM classifier was configured, reachable, and deliberately skipped.
     "heuristic_first_short_circuit",
+    "hybrid_short_circuit",
     # The operator's classifier plugin (classifier_type 'custom') decided the tier.
     "classifier_plugin",
     # The LLM classifier or classifier plugin failed on a router with an operator-defined
@@ -2840,8 +2875,17 @@ RoutingDecisionCause = Literal[
     # never called. The matched sentinel rides in matched_keyword. Distinct from the keyword causes,
     # which are operator-authored rules; these sentinels ship with the router.
     "housekeeping",
+    # modality_routing replaced the decided placement: the request carries an image and the
+    # routed model does not accept image input, so the nearest higher capable tier or
+    # default_model served instead. The displaced placement rides in signals.
+    "modality_escalation",
     "session_affinity_pin",
     "session_affinity_escalation",
+    # classification_mode 'user_turn': the request is an agent loop's continuation turn (no new
+    # human ask), so the session's held routing decision was replayed and the classifier was never
+    # called. Distinct from "session_affinity_pin", which reports the session_affinity flag pinning
+    # every turn including new asks; this cause only appears when session_affinity is off.
+    "user_turn_continuation",
     "default_fallback",
     "keyword",
     "quality_tier",
@@ -2881,6 +2925,8 @@ class StandardLoggingRoutingDecision(TypedDict, total=False):
     classifier_model: str
     classifier_cost: float
     escalated: bool
+    context_escalated: bool  # writable-ok: Pydantic warns on ReadOnly TypedDict fields
+    context_escalation_original_tier: str  # writable-ok: Pydantic warns on ReadOnly TypedDict fields
     tier_boundaries: StandardLoggingRoutingDecisionTierBoundaries
     reasoning_override_min_score: float  # writable-ok: Pydantic warns on ReadOnly TypedDict fields
     conversation_continuing: bool
@@ -2907,6 +2953,8 @@ DERIVED_ROUTING_DECISION_FIELDS: Final[frozenset[str]] = frozenset(
         "classifier_model",
         "classifier_cost",
         "escalated",
+        "context_escalated",
+        "context_escalation_original_tier",
         "tier_boundaries",
         "reasoning_override_min_score",
         "conversation_continuing",
@@ -3473,17 +3521,22 @@ class CustomPricingLiteLLMParams(MirroredPricingParams):
         return {k: v for k, v in model_info.items() if k not in cls.model_fields}
 
 
-SHARED_BACKEND_MODEL_INFO_FIELDS: Final[frozenset[str]] = frozenset(
-    ModelInfoBase.__required_keys__ | ModelInfoBase.__optional_keys__
-) - frozenset(CustomPricingLiteLLMParams.model_fields)
+DEPLOYMENT_SCOPED_PRICING_FIELDS: Final[frozenset[str]] = frozenset({"off_peak_pricing"})
+
+SHARED_BACKEND_MODEL_INFO_FIELDS: Final[frozenset[str]] = (
+    frozenset(ModelInfoBase.__required_keys__ | ModelInfoBase.__optional_keys__)
+    - frozenset(CustomPricingLiteLLMParams.model_fields)
+    - DEPLOYMENT_SCOPED_PRICING_FIELDS
+)
 
 
 def shared_backend_model_info(model_info: dict[str, Any]) -> dict[str, Any]:
     """Return only the fields safe to register under a shared ``{provider}/{model}``
     key in ``litellm.model_cost``: cost-map schema fields (``ModelInfoBase``) minus
-    per-deployment pricing overrides. Per-deployment metadata (``id``,
-    ``access_via_team_ids``, arbitrary custom keys) never belongs on the shared key;
-    it stays under the deployment's unique model id.
+    per-deployment pricing overrides and deployment-scoped pricing blocks such as
+    ``off_peak_pricing``. Per-deployment metadata (``id``, ``access_via_team_ids``,
+    arbitrary custom keys) never belongs on the shared key; it stays under the
+    deployment's unique model id.
     """
     return {k: v for k, v in model_info.items() if k in SHARED_BACKEND_MODEL_INFO_FIELDS}
 
@@ -3585,6 +3638,8 @@ all_litellm_params = (
         "client",
         "rpm",
         "tpm",
+        "default_api_key_rpm_limit",
+        "default_api_key_tpm_limit",
         "itpm",
         "otpm",
         "max_parallel_requests",
@@ -3758,6 +3813,8 @@ class LlmProviders(str, Enum):
     CODESTRAL = "codestral"
     TEXT_COMPLETION_CODESTRAL = "text-completion-codestral"
     DASHSCOPE = "dashscope"
+    QWENCLOUD = "qwencloud"
+    QWEN_AI_PLATFORM = "qwen_ai_platform"
     MODELSCOPE = "modelscope"
     MOONSHOT = "moonshot"
     PUBLICAI = "publicai"
diff --git a/litellm/utils.py b/litellm/utils.py
index 5e9e115ed54..ba456fc353b 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2660,10 +2660,19 @@ def _is_explicitly_disabled_factory(model: str, custom_llm_provider: str | None,
     ``_supports_factory`` so caching, fallback, and normalisation improvements
     apply here automatically.
     """
+    from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider
+
     try:
-        model, custom_llm_provider, _, _ = litellm.get_llm_provider(
-            model=model, custom_llm_provider=custom_llm_provider
-        )
+        declared: Final = declared_authenticating_provider(model, custom_llm_provider)
+        if declared is not None:
+            model = model.removeprefix(
+                f"{declared}/"
+            )  # rebind-ok: mirrors get_llm_provider's split without its OAuth flow
+            custom_llm_provider = declared  # rebind-ok: same
+        else:
+            model, custom_llm_provider, _, _ = litellm.get_llm_provider(
+                model=model, custom_llm_provider=custom_llm_provider
+            )
         model_info: Final = _get_model_info_helper(model=model, custom_llm_provider=custom_llm_provider)
         val: Final = model_info.get(key)
         if val is False:
@@ -2751,6 +2760,15 @@ def supports_computer_use(model: str, custom_llm_provider: str | None = None) ->
     )
 
 
+def is_vision_explicitly_disabled(model: str, custom_llm_provider: str | None = None) -> bool:
+    """True only when supports_vision is explicitly declared false for the model.
+
+    The opt-out mirror of :func:`supports_vision`: a missing declaration reads as not
+    disabled, so unknown or newly added models stay eligible for image routing.
+    """
+    return _is_explicitly_disabled_factory(model, custom_llm_provider, "supports_vision")
+
+
 def supports_vision(model: str, custom_llm_provider: str | None = None) -> bool:
     """
     Check if the given model supports vision and return a boolean value.
@@ -2851,10 +2869,9 @@ def _update_dictionary(existing_dict: dict, new_dict: dict) -> dict:
             elif isinstance(v, dict):
                 existing_nested_dict = existing_dict.get(k)
                 if isinstance(existing_nested_dict, dict):
-                    existing_nested_dict.update(v)
-                    existing_dict[k] = existing_nested_dict
+                    existing_dict[k] = {**existing_nested_dict, **v}  # mutable-ok: copy-on-write merge
                 else:
-                    existing_dict[k] = v
+                    existing_dict[k] = dict(v)  # mutable-ok: detached copy, never the caller's dict by reference
             else:
                 existing_dict[k] = v
 
@@ -3543,10 +3560,10 @@ def get_optional_params_embeddings(
             non_default_params=non_default_params, optional_params={}, kwargs=kwargs
         )
     elif custom_llm_provider == "vertex_ai" or custom_llm_provider == "gemini":
-        # OpenAI SDKs (and litellm's own client) send encoding_format="float"
-        # by default; float lists are exactly what the vertex API returns, so
-        # the param is a no-op — don't reject the provider default. Other
-        # values (e.g. "base64") stay on the unsupported-param path below.
+        # OpenAI SDKs send encoding_format="float" by default; float lists are
+        # exactly what the vertex API returns, so the param is a no-op and the
+        # provider default is not rejected. Other values (e.g. "base64") stay
+        # on the unsupported-param path below.
         if non_default_params.get("encoding_format") == "float":
             non_default_params.pop("encoding_format")
         supported_params = get_supported_openai_params(
@@ -4859,11 +4876,7 @@ def _get_deployment_order(deployment: dict | Any) -> int | None:
 
 def _get_order_filtered_deployments(healthy_deployments: list[dict], target_order: int | None = None) -> list:
     if target_order is not None:
-        filtered: Final = [d for d in healthy_deployments if _get_deployment_order(d) == target_order]
-        if filtered:
-            return filtered
-        # target_order doesn't match any deployment (e.g., external fallback model) — return all
-        return healthy_deployments
+        return [d for d in healthy_deployments if _get_deployment_order(d) == target_order]
 
     # Default: pick min order group
     _valid_orders: Final[list[int]] = [
@@ -5093,49 +5106,6 @@ def get_response_string(response_obj: ModelResponse | ModelResponseStream) -> st
     return "".join(response_parts)
 
 
-def get_api_key(llm_provider: str, dynamic_api_key: str | None):
-    api_key = dynamic_api_key or litellm.api_key
-    # openai
-    if llm_provider == "openai" or llm_provider == "text-completion-openai":
-        api_key = api_key or litellm.openai_key or get_secret("OPENAI_API_KEY")
-    # anthropic
-    elif llm_provider == "anthropic" or llm_provider == "anthropic_text":
-        api_key = api_key or litellm.anthropic_key or get_secret("ANTHROPIC_API_KEY")
-    # ai21
-    elif llm_provider == "ai21":
-        api_key = api_key or litellm.ai21_key or get_secret("AI21_API_KEY")
-    # aleph_alpha
-    elif llm_provider == "aleph_alpha":
-        api_key = api_key or litellm.aleph_alpha_key or get_secret("ALEPH_ALPHA_API_KEY")
-    # baseten
-    elif llm_provider == "baseten":
-        api_key = api_key or litellm.baseten_key or get_secret("BASETEN_API_KEY")
-    # cohere
-    elif llm_provider == "cohere" or llm_provider == "cohere_chat":
-        api_key = api_key or litellm.cohere_key or get_secret("COHERE_API_KEY")
-    # huggingface
-    elif llm_provider == "huggingface":
-        api_key = api_key or litellm.huggingface_key or get_secret("HUGGINGFACE_API_KEY")
-    # nlp_cloud
-    elif llm_provider == "nlp_cloud":
-        api_key = api_key or litellm.nlp_cloud_key or get_secret("NLP_CLOUD_API_KEY")
-    # replicate
-    elif llm_provider == "replicate":
-        api_key = api_key or litellm.replicate_key or get_secret("REPLICATE_API_KEY")
-    # together_ai
-    elif llm_provider == "together_ai":
-        api_key = (
-            api_key or litellm.togetherai_api_key or get_secret("TOGETHERAI_API_KEY") or get_secret("TOGETHER_AI_TOKEN")
-        )
-    # nebius
-    elif llm_provider == "nebius":
-        api_key = api_key or litellm.nebius_key or get_secret("NEBIUS_API_KEY")
-    # wandb
-    elif llm_provider == "wandb":
-        api_key = api_key or litellm.wandb_key or get_secret("WANDB_API_KEY")
-    return api_key
-
-
 def get_utc_datetime():
     import datetime as dt
     from datetime import datetime
@@ -5842,6 +5812,7 @@ def _get_model_info_helper(
                 cache_creation_input_token_cost_above_1hr=_model_info.get(
                     "cache_creation_input_token_cost_above_1hr", None
                 ),
+                off_peak_pricing=_model_info.get("off_peak_pricing", None),
                 input_cost_per_character=_model_info.get("input_cost_per_character", None),
                 input_cost_per_token_above_128k_tokens=_model_info.get("input_cost_per_token_above_128k_tokens", None),
                 input_cost_per_token_above_200k_tokens=_model_info.get("input_cost_per_token_above_200k_tokens", None),
@@ -6568,11 +6539,11 @@ def validate_environment(
                 keys_in_environment = True
             else:
                 missing_keys.append("WANDB_API_KEY")
-        elif custom_llm_provider == "dashscope":
-            if "DASHSCOPE_API_KEY" in os.environ:
+        elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
+            if f"{custom_llm_provider.upper()}_API_KEY" in os.environ or "DASHSCOPE_API_KEY" in os.environ:
                 keys_in_environment = True
             else:
-                missing_keys.append("DASHSCOPE_API_KEY")
+                missing_keys.append(f"{custom_llm_provider.upper()}_API_KEY")
         elif custom_llm_provider == "modelscope":
             if "MODELSCOPE_API_KEY" in os.environ:
                 keys_in_environment = True
@@ -8134,6 +8105,11 @@ class ProviderConfigManager:
             LlmProviders.NEBIUS: (lambda: litellm.NebiusConfig(), False),
             LlmProviders.WANDB: (lambda: litellm.WandbConfig(), False),
             LlmProviders.DASHSCOPE: (lambda: litellm.DashScopeChatConfig(), False),
+            LlmProviders.QWENCLOUD: (lambda: litellm.QwenCloudChatConfig(), False),
+            LlmProviders.QWEN_AI_PLATFORM: (
+                lambda: litellm.QwenAIPlatformChatConfig(),
+                False,
+            ),
             LlmProviders.MODELSCOPE: (lambda: litellm.ModelScopeChatConfig(), False),
             LlmProviders.MOONSHOT: (lambda: litellm.MoonshotChatConfig(), False),
             LlmProviders.DOCKER_MODEL_RUNNER: (
@@ -8260,10 +8236,17 @@ class ProviderConfigManager:
         """
         # Handle OpenAI special cases (O-series and GPT-5 models)
         if provider == LlmProviders.OPENAI:
+            from litellm.llms.openai.chat.gpt_transformation import (
+                OpenAIGPTConfig,
+                OpenAIUnknownModelConfig,
+            )
+
             if litellm.openaiOSeriesConfig.is_model_o_series_model(model=model):
                 return litellm.openaiOSeriesConfig
             if litellm.OpenAIGPT5Config.is_model_gpt_5_model(model=model):
                 return litellm.OpenAIGPT5Config()
+            if not OpenAIGPTConfig.is_openai_catalog_model(model):
+                return OpenAIUnknownModelConfig()
 
         # Handle Azure before the generic map so base_model can be threaded through
         if provider == LlmProviders.AZURE:
@@ -8341,12 +8324,16 @@ class ProviderConfigManager:
             )
 
             return VolcEngineEmbeddingConfig()
-        elif litellm.LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.embed.transformation import (
-                DashScopeEmbeddingConfig,
+        elif provider in (
+            litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_embedding_config,
             )
 
-            return DashScopeEmbeddingConfig()
+            return get_dashscope_family_embedding_config(provider.value)
         elif litellm.LlmProviders.OVHCLOUD == provider:
             return litellm.OVHCloudEmbeddingConfig()
         elif litellm.LlmProviders.SNOWFLAKE == provider:
@@ -8419,12 +8406,16 @@ class ProviderConfigManager:
             return litellm.VoyageRerankConfig()
         elif litellm.LlmProviders.WATSONX == provider:
             return litellm.IBMWatsonXRerankConfig()
-        elif litellm.LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.rerank.transformation import (
-                DashScopeRerankConfig,
+        elif provider in (
+            litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_rerank_config,
             )
 
-            return DashScopeRerankConfig()
+            return get_dashscope_family_rerank_config(provider.value)
         return litellm.CohereRerankConfig()
 
     @staticmethod
@@ -8830,6 +8821,12 @@ class ProviderConfigManager:
             )
 
             return AzurePassthroughConfig()
+        elif LlmProviders.GIGACHAT == provider:
+            from litellm.llms.gigachat.passthrough.transformation import (
+                GigaChatPassthroughConfig,
+            )
+
+            return GigaChatPassthroughConfig()
         elif LlmProviders.WATSONX == provider:
             from litellm.llms.watsonx.passthrough.transformation import (
                 WatsonxPassthroughConfig,
@@ -9091,12 +9088,16 @@ class ProviderConfigManager:
             )
 
             return get_openrouter_image_generation_config(model)
-        elif LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.image_generation import (
-                get_dashscope_image_generation_config,
+        elif provider in (
+            LlmProviders.DASHSCOPE,
+            LlmProviders.QWENCLOUD,
+            LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_image_generation_config,
             )
 
-            return get_dashscope_image_generation_config(model)
+            return get_dashscope_family_image_generation_config(provider.value)
         elif LlmProviders.MODELSCOPE == provider:
             from litellm.llms.modelscope.image_generation import (
                 get_modelscope_image_generation_config,
@@ -9409,6 +9410,10 @@ class ProviderConfigManager:
 
             return RunwayMLTextToSpeechConfig()
         elif litellm.LlmProviders.VERTEX_AI == provider:
+            if "gemini" in model:
+                # Gemini TTS uses the speech_to_completion bridge, and Google Cloud TTS param
+                # mapping would drop response_format before the bridge sees it (LIT-6501)
+                return None
             from litellm.llms.vertex_ai.text_to_speech.transformation import (
                 VertexAITextToSpeechConfig,
             )
diff --git a/litellm/vector_stores/main.py b/litellm/vector_stores/main.py
index 9b0ff71730a..cd576755f5f 100644
--- a/litellm/vector_stores/main.py
+++ b/litellm/vector_stores/main.py
@@ -7,7 +7,7 @@ import builtins
 import contextvars
 from collections.abc import Coroutine, Mapping
 from functools import partial
-from typing import Final
+from typing import TYPE_CHECKING, Final
 
 import httpx
 
@@ -29,6 +29,9 @@ from litellm.types.vector_stores import (
 from litellm.utils import ProviderConfigManager, client
 from litellm.vector_stores.utils import VectorStoreRequestUtils
 
+if TYPE_CHECKING:
+    from litellm.router import Router
+
 ####### ENVIRONMENT VARIABLES ###################
 # Initialize any necessary instances or variables here
 base_llm_http_handler = BaseLLMHTTPHandler()
@@ -280,6 +283,7 @@ async def asearch(
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
+    router: "Router | None" = None,
     **kwargs,
 ) -> VectorStoreSearchResponse:
     """
@@ -308,6 +312,7 @@ async def asearch(
             extra_body=extra_body,
             timeout=timeout,
             custom_llm_provider=custom_llm_provider,
+            router=router,
             **kwargs,
         )
 
@@ -347,6 +352,7 @@ def search(
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
+    router: "Router | None" = None,
     **kwargs,
 ) -> VectorStoreSearchResponse | Coroutine[object, object, VectorStoreSearchResponse]:
     """
@@ -450,6 +456,7 @@ def search(
             timeout=timeout or request_timeout,
             _is_async=_is_async,
             client=kwargs.get("client"),
+            router=router,
         )
 
         return response
diff --git a/litellm/vector_stores/vector_store_registry.py b/litellm/vector_stores/vector_store_registry.py
index 22d27bc3266..b71d6784873 100644
--- a/litellm/vector_stores/vector_store_registry.py
+++ b/litellm/vector_stores/vector_store_registry.py
@@ -112,7 +112,9 @@ class VectorStoreRegistry:
         Dynamically extracts all parameters defined in VECTOR_STORE_OPENAI_PARAMS.
         """
         # Get the list of supported param names from the Literal type
-        supported_params: Final = get_args(VECTOR_STORE_OPENAI_PARAMS)
+        supported_params: Final = tuple(
+            param for param in get_args(VECTOR_STORE_OPENAI_PARAMS) if isinstance(param, str)
+        )
 
         # Extract only the params that exist in the tool
         kwargs: Final = {param: tool.get(param) for param in supported_params if param in tool}
@@ -503,7 +505,7 @@ class VectorStoreRegistry:
                 vector_stores_from_db.append(_litellm_managed_vector_store)
         return vector_stores_from_db
 
-    def get_credentials_for_vector_store(self, vector_store_id: str) -> dict[str, Any]:
+    def get_credentials_for_vector_store(self, vector_store_id: str) -> dict[str, object]:
         """
         Get the credentials for a vector store
 
diff --git a/migrations/Dockerfile b/migrations/Dockerfile
index 6335e6f6bd8..c6d1b0cc46e 100644
--- a/migrations/Dockerfile
+++ b/migrations/Dockerfile
@@ -1,5 +1,5 @@
-ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
-ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:a31344ab2cb8618db84f535eec56f76f6178b142cb92cb2e48676cc2dcebea72
+ARG LITELLM_BUILD_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
+ARG LITELLM_RUNTIME_IMAGE=cgr.dev/chainguard/wolfi-base@sha256:e624c5d5e42382ce7165ddafcbbf8e6769a24cbd02ea6114b880b05ae5ba2a8d
 ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.11.7@sha256:240fb85ab0f263ef12f492d8476aa3a2e4e1e333f7d67fbdd923d00a506a516a
 
 FROM $UV_IMAGE AS uvbin
@@ -35,7 +35,7 @@ COPY --from=uvbin /uv /uvx /usr/local/bin/
 # instead of nodeenv downloading one whose dynamic deps may not be in Wolfi
 # (e.g. Node 26.2.0 needs libatomic). Retry for transient apk.cgr.dev flakes.
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash gcc python3 python3-dev openssl openssl-dev libsndfile nodejs npm && break; \
+      apk add --no-cache bash gcc python-3.13 python-3.13-dev openssl openssl-dev libsndfile nodejs npm && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
@@ -56,7 +56,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     uv sync --frozen --no-install-project --no-install-workspace --no-default-groups --no-editable \
         --extra proxy \
         --extra extra_proxy \
-        --python python3
+        --python python3.13
 
 # Stage 2 — copy source and install the project + workspace members.
 COPY . .
@@ -65,7 +65,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     uv sync --frozen --no-default-groups --no-editable \
         --extra proxy \
         --extra extra_proxy \
-        --python python3
+        --python python3.13
 
 COPY migrations/run.py /app/run.py
 
@@ -87,7 +87,7 @@ FROM $LITELLM_RUNTIME_IMAGE AS runtime
 USER root
 
 RUN for i in 1 2 3; do \
-      apk add --no-cache bash openssl tzdata python3 nodejs libsndfile libatomic && break; \
+      apk add --no-cache bash openssl tzdata python-3.13 nodejs libsndfile libatomic && break; \
       [ $i = 3 ] && { echo "apk add failed after 3 retries" >&2; exit 1; }; \
       sleep 5; \
     done
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 05c1cfd3179..d8a8f84b032 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -553,6 +553,27 @@
         "supports_response_schema": true,
         "supports_vision": true
     },
+    "amazon.nova-sonic-v1:0": {
+        "deprecation_date": "2026-09-14",
+        "input_cost_per_audio_token": 3.4e-06,
+        "input_cost_per_token": 6e-08,
+        "litellm_provider": "bedrock",
+        "mode": "realtime",
+        "output_cost_per_audio_token": 1.36e-05,
+        "output_cost_per_token": 2.4e-07,
+        "supports_audio_input": true,
+        "supports_audio_output": true
+    },
+    "amazon.nova-2-sonic-v1:0": {
+        "input_cost_per_audio_token": 3e-06,
+        "input_cost_per_token": 3.3e-07,
+        "litellm_provider": "bedrock",
+        "mode": "realtime",
+        "output_cost_per_audio_token": 1.2e-05,
+        "output_cost_per_token": 2.75e-06,
+        "supports_audio_input": true,
+        "supports_audio_output": true
+    },
     "amazon.rerank-v1:0": {
         "input_cost_per_query": 0.001,
         "input_cost_per_token": 0.0,
@@ -1430,6 +1451,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "global.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.25e-05,
         "cache_creation_input_token_cost_above_1hr": 2e-05,
@@ -1467,6 +1526,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "global.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "us.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1504,6 +1601,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "us.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "eu.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1541,6 +1676,44 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "eu.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": false,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "anthropic.claude-opus-5": {
         "bedrock_converse_supports_strict_tools": false,
         "supports_adaptive_thinking": true,
@@ -1571,7 +1744,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1607,7 +1780,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1643,7 +1816,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1679,7 +1852,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1715,7 +1888,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1751,7 +1924,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -2044,7 +2217,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2081,7 +2254,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2118,7 +2291,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2155,7 +2328,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2192,7 +2365,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -2229,7 +2402,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "bedrock_output_config_effort_ceiling": "xhigh",
@@ -3025,6 +3198,7 @@
         "prompt_cache_min_tokens": 2048
     },
     "azure_ai/claude-fable-5": {
+        "deprecation_date": "2027-12-05",
         "supports_mid_conversation_system": true,
         "input_cost_per_token": 1e-05,
         "output_cost_per_token": 5e-05,
@@ -3057,7 +3231,43 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "azure_ai/claude-fable-5-1": {
+        "supports_mid_conversation_system": true,
+        "input_cost_per_token": 1e-05,
+        "output_cost_per_token": 5e-05,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_forced_tool_use": false,
+        "supports_function_calling": true,
+        "supports_native_structured_output": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "azure_ai/claude-opus-5": {
+        "deprecation_date": "2027-07-08",
         "supports_mid_conversation_system": true,
         "supports_adaptive_thinking": true,
         "input_cost_per_token": 5e-06,
@@ -3090,6 +3300,7 @@
         "prompt_cache_min_tokens": 512
     },
     "azure_ai/claude-opus-4-8": {
+        "deprecation_date": "2027-09-01",
         "supports_mid_conversation_system": true,
         "supports_adaptive_thinking": true,
         "input_cost_per_token": 5e-06,
@@ -3168,6 +3379,7 @@
         "prompt_cache_min_tokens": 1024
     },
     "azure_ai/claude-sonnet-5": {
+        "deprecation_date": "2027-06-30",
         "supports_mid_conversation_system": true,
         "cache_creation_input_token_cost": 2.5e-06,
         "cache_creation_input_token_cost_above_1hr": 4e-06,
@@ -3726,7 +3938,7 @@
         "output_cost_per_token": 0,
         "litellm_provider": "azure_ai",
         "mode": "chat",
-        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-services/",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/",
         "comment": "Flat cost of $0.14 per M input tokens for Azure AI Foundry Model Router infrastructure. Use pattern: azure_ai/model_router/<deployment-name> where deployment-name is your Azure deployment (e.g., azure-model-router)"
     },
     "azure/eu/gpt-4o-2024-08-06": {
@@ -5328,7 +5540,7 @@
         "input_cost_per_second": 0.0002833333333333333,
         "litellm_provider": "azure",
         "mode": "audio_transcription",
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+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
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@@ -15080,6 +17265,62 @@
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+        "output_dbu_cost_per_token": 4e-06,
+        "source": "https://www.databricks.com/product/pricing/foundation-model-serving",
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+        "litellm_provider": "databricks",
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+        "metadata": {
+            "notes": "Input/output cost per token is dbu cost * $0.070. Billing reads the per-token dollar fields; the '*_dbu_cost_per_token' fields are the published Databricks rates, kept for reference. Context/max output are the DeepSeek-published model limits (1M context, 384K max output)."
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+        "source": "https://www.databricks.com/product/pricing/foundation-model-serving",
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@@ -17767,7 +20008,8 @@
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@@ -19564,6 +21806,61 @@
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@@ -21226,6 +23524,63 @@
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         "google_maps_grounding_cost_per_query": 0.014
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+        "google_maps_grounding_cost_per_query": 0.014
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-        "source": "https://ai.google.dev/pricing/gemini-3",
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+        "google_maps_grounding_cost_per_query": 0.014
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@@ -23790,7 +26263,8 @@
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-        "source": "https://ai.google.dev/gemini-api/docs/video",
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@@ -23818,8 +26292,10 @@
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@@ -24342,7 +26819,7 @@
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@@ -24404,6 +26881,15 @@
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         "output_vector_size": 2560
     },
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+        "mode": "embedding",
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@@ -25327,7 +27813,7 @@
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@@ -25650,7 +28136,7 @@
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@@ -25787,7 +28273,8 @@
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-        ]
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@@ -25809,7 +28296,7 @@
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@@ -25847,7 +28334,7 @@
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+        "max_tokens": 8191,
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+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper/",
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+        "litellm_provider": "cloudflare",
+        "mode": "audio_transcription",
+        "output_cost_per_second": 0.0,
+        "source": "https://developers.cloudflare.com/workers-ai/models/whisper-large-v3-turbo/",
+        "supported_endpoints": [
+            "/v1/audio/transcriptions"
+        ]
     }
 }
diff --git a/model_prices_and_context_window.schema.json b/model_prices_and_context_window.schema.json
index 3f6d3b4f910..9e370e5406a 100644
--- a/model_prices_and_context_window.schema.json
+++ b/model_prices_and_context_window.schema.json
@@ -662,6 +662,9 @@
         "supports_embedding_image_input": {
           "type": "boolean"
         },
+        "supports_forced_tool_use": {
+          "type": "boolean"
+        },
         "supports_function_calling": {
           "type": "boolean"
         },
diff --git a/osv-scanner.toml b/osv-scanner.toml
index 7ab450945f5..5b0339bdcd0 100644
--- a/osv-scanner.toml
+++ b/osv-scanner.toml
@@ -2,3 +2,8 @@
 id = "GHSA-w8v5-vhqr-4h9v"
 ignoreUntil = 2026-09-09
 reason = "diskcache has no fixed release published; remove this entry once one exists"
+
+[[IgnoredVulns]]
+id = "GHSA-h7x2-h6g9-p789"
+ignoreUntil = 2026-09-14
+reason = "mlflow has no fixed release published; remove this entry once one exists"
diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json
index 7c7d508856f..ebc220b3496 100644
--- a/provider_endpoints_support.json
+++ b/provider_endpoints_support.json
@@ -724,6 +724,42 @@
         "interactions": true
       }
     },
+    "qwencloud": {
+      "display_name": "QwenCloud (`qwencloud`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
+    "qwen_ai_platform": {
+      "display_name": "Qwen AI Platform (`qwen_ai_platform`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
     "databricks": {
       "display_name": "Databricks (`databricks`)",
       "url": "https://docs.litellm.ai/docs/providers/databricks",
diff --git a/pyproject.toml b/pyproject.toml
index 34c1fec1c11..d0e5723d1cb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "litellm"
-version = "1.100.0"
+version = "1.101.0"
 description = "Library to easily interface with LLM API providers"
 readme = "README.md"
 requires-python = ">=3.10, <3.15"
@@ -67,8 +67,8 @@ proxy = [
     "azure-identity>=1.25.2,<2.0",
     "azure-storage-blob>=12.28.0,<13.0",
     "mcp>=1.28.1,<2.0",
-    "litellm-proxy-extras==0.4.91",
-    "litellm-enterprise==0.1.62",
+    "litellm-proxy-extras==0.4.92",
+    "litellm-enterprise==0.1.63",
     "RestrictedPython>=8.5,<9.0",
     "rich>=13.9.4,<14.0",
     "InquirerPy>=0.3.4,<1.0",
@@ -91,6 +91,11 @@ cli = [
 ]
 extra_proxy = [
     "prisma>=0.11.0,<1.0",
+    # Used by ProxyExtrasDBManager.spend_logs_is_partitioned() to detect a
+    # partitioned LiteLLM_SpendLogs and keep schema reconciliation from
+    # fighting its composite primary key.
+    "psycopg>=3.2,<4.0",
+    "psycopg-binary>=3.2,<4.0",
     "azure-identity>=1.25.2,<2.0",
     "azure-keyvault-secrets>=4.10.0,<5.0",
     # Not in PyPI proxy extra.
@@ -156,7 +161,7 @@ proxy-runtime = [
     "mangum>=0.17.0,<1.0",
     "azure-ai-contentsafety>=1.0.0,<2.0",
     "azure-storage-file-datalake>=12.20.0,<13.0",
-    "pypdf>=6.12.0,<7.0",
+    "pypdf>=6.16.1,<7.0",
     "llm-sandbox>=0.3.39,<1.0",
     "detect-secrets>=1.5.0,<2.0",
 ]
@@ -262,7 +267,7 @@ healthcheck = [
 ]
 
 [build-system]
-requires = ["maturin==1.9.4"]
+requires = ["maturin==1.15.0"]
 build-backend = "maturin"
 
 [tool.maturin]
@@ -270,7 +275,13 @@ manifest-path = "litellm-rust/crates/python-bridge/Cargo.toml"
 module-name = "litellm.rust_bridge._native"
 python-source = "."
 bindings = "pyo3"
-include = ["litellm/proxy/_experimental/out/**"]
+features = ["extension-module"]
+profile = "release"
+editable-profile = "dev"
+include = [
+    "litellm/proxy/_experimental/out/**",
+    "litellm/router_strategy/complexity_router/artifacts/*.json",
+]
 exclude = [
     "litellm/proxy/enterprise",
     "litellm/proxy/enterprise/**",
@@ -284,7 +295,7 @@ exclude = [
 
 [tool.uv]
 constraint-dependencies = [
-    "tornado>=6.5.6",
+    "tornado>=6.5.8",
     "aiohttp>=3.14.2,<4.0",
     "packaging>=24.0",
     "soupsieve>=2.8.4",
@@ -311,7 +322,7 @@ members = ["enterprise", "litellm-proxy-extras"]
 profile = "black"
 
 [tool.commitizen]
-version = "1.100.0"
+version = "1.101.0"
 version_files = [
     "pyproject.toml:^version",
 ]
diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json
index b4107582000..a390c61dcf2 100644
--- a/ruff-strict-budget.json
+++ b/ruff-strict-budget.json
@@ -1,21 +1,21 @@
 {
   "ANN001": {
-    "limit": 3012
+    "limit": 2985
   },
   "ANN002": {
     "limit": 71
   },
   "ANN003": {
-    "limit": 827
+    "limit": 809
   },
   "ANN201": {
-    "limit": 2003
+    "limit": 2000
   },
   "ANN202": {
-    "limit": 845
+    "limit": 835
   },
   "ANN204": {
-    "limit": 702
+    "limit": 693
   },
   "ANN205": {
     "limit": 112
@@ -24,7 +24,7 @@
     "limit": 133
   },
   "ANN401": {
-    "limit": 654
+    "limit": 304
   },
   "ASYNC230": {
     "limit": 11
@@ -108,7 +108,7 @@
     "limit": 3
   },
   "F401": {
-    "limit": 13
+    "limit": 12
   },
   "LOG015": {
     "limit": 5
@@ -117,13 +117,13 @@
     "limit": 1
   },
   "PERF102": {
-    "limit": 23
+    "limit": 21
   },
   "PERF401": {
     "limit": 12
   },
   "PERF403": {
-    "limit": 34
+    "limit": 33
   },
   "PIE804": {
     "limit": 18
@@ -147,7 +147,7 @@
     "limit": 3
   },
   "PLR1714": {
-    "limit": 256
+    "limit": 253
   },
   "PLW0127": {
     "limit": 57
@@ -156,7 +156,7 @@
     "limit": 215
   },
   "PLW0603": {
-    "limit": 191
+    "limit": 190
   },
   "PLW1508": {
     "limit": 190
@@ -168,7 +168,7 @@
     "limit": 3
   },
   "RET504": {
-    "limit": 175
+    "limit": 173
   },
   "RUF012": {
     "limit": 239
@@ -177,7 +177,7 @@
     "limit": 8
   },
   "RUF019": {
-    "limit": 32
+    "limit": 31
   },
   "RUF046": {
     "limit": 4
@@ -195,10 +195,10 @@
     "limit": 22
   },
   "SIM101": {
-    "limit": 58
+    "limit": 56
   },
   "SIM102": {
-    "limit": 315
+    "limit": 310
   },
   "SIM103": {
     "limit": 119
@@ -231,7 +231,7 @@
     "limit": 5
   },
   "TID251": {
-    "limit": 1116
+    "limit": 1071
   },
   "TRY002": {
     "limit": 524
@@ -240,13 +240,13 @@
     "limit": 96
   },
   "TRY201": {
-    "limit": 405
+    "limit": 403
   },
   "TRY203": {
-    "limit": 113
+    "limit": 111
   },
   "TRY300": {
-    "limit": 857
+    "limit": 854
   },
   "UP028": {
     "limit": 2
diff --git a/ruff-strict.toml b/ruff-strict.toml
index 7afc5da71ee..ae092bdde7d 100644
--- a/ruff-strict.toml
+++ b/ruff-strict.toml
@@ -26,6 +26,10 @@ external = [
 # caught a real mismatch, confirming Any is correct here, not a shortcut.
 "litellm/litellm_core_utils/litellm_logging.py" = ["ANN401"]
 "litellm/utils.py" = ["ANN401"]
+# `**kwargs` forwards verbatim to CustomGuardrail.__init__, whose param list is wide and
+# grows over time; typing it concretely (`object`) broke that forwarding call outright —
+# basedpyright turned every named param into a reportArgumentType error. Any is correct here.
+"litellm/proxy/guardrails/guardrail_hooks/alice/alice.py" = ["ANN401"]
 
 [lint.mccabe]
 max-complexity = 15
diff --git a/rust-toolchain.toml b/rust-toolchain.toml
new file mode 100644
index 00000000000..a1598ccbb34
--- /dev/null
+++ b/rust-toolchain.toml
@@ -0,0 +1,4 @@
+[toolchain]
+channel = "1.98.0"
+profile = "minimal"
+components = ["rustfmt", "clippy"]
diff --git a/schema.prisma b/schema.prisma
index 60223265211..7604ceadf7a 100644
--- a/schema.prisma
+++ b/schema.prisma
@@ -1529,14 +1529,16 @@ model LiteLLM_AutoRouterSession {
 model LiteLLM_ShadowEvalJob {
   id                String   @id @default(cuid())
   group_id          String   // legs of one job share this; the API's job id
-  api_key_id        String   // hashed virtual key whose traffic this leg shadows
-  router_name       String   // the auto-router under evaluation, in either direction
+  target_type       String   @default("key") // key | team | user
+  target_id         String   // hashed virtual key, team_id, or user_id whose traffic this leg shadows
+  router_name       String   // first (often only) auto-router under evaluation; router_names is the full set
+  router_names      String[] @default([]) // all routers this job runs as shadow arms; empty on legacy rows, whose set is (router_name)
   direction         String   @default("forward") // forward | reverse
   baseline_model    String?  // reverse only: the fixed model the router is judged against
   judge_model       String
   shadow_percentage Float
   max_turns         Int      // sample-count ceiling: the whole budget on pre-max_budget jobs, the error-loop valve otherwise
-  max_budget        Float?   // per-key USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
+  max_budget        Float?   // per-target USD cap on the eval's own shadow + judge spend; null on jobs from before spend budgets
   created_at        DateTime @default(now())
   created_by        String?
   ends_at           DateTime
@@ -1544,7 +1546,7 @@ model LiteLLM_ShadowEvalJob {
   stopped_by        String?  // operator who stopped it early; null when it ended on its own
 
   @@index([group_id])
-  @@index([api_key_id])
+  @@index([target_type, target_id])
   @@index([created_at])
 }
 
@@ -1554,6 +1556,7 @@ model LiteLLM_ShadowEvalAttempt {
   job_id       String
   request_id   String   // the judged real request
   outcome      String   // real | shadow | tie | error
+  router_name  String?  // the arm this verdict scores; NULL on legacy rows, meaning the job's own router
   tier         String?  // router's tier for the prompt, when classified
   real_model   String?
   shadow_model String?
diff --git a/scripts/auto-close-duplicates.test.ts b/scripts/auto-close-duplicates.test.ts
new file mode 100644
index 00000000000..b49bf05cbc2
--- /dev/null
+++ b/scripts/auto-close-duplicates.test.ts
@@ -0,0 +1,348 @@
+import { describe, expect, test } from "bun:test";
+
+import {
+  CLOSED_MARKER,
+  REOPEN_COMMENT,
+  candidateNumbers,
+  duplicateTarget,
+  normalizeTitle,
+  pendingNotice,
+  readConfig,
+  reopenTarget,
+  sweepClosedIssue,
+  sweepIssue,
+  type Comment,
+  type GitHubApi,
+  type Issue,
+  type Reaction,
+  type SweepConfig,
+} from "./auto-close-duplicates";
+
+const NOW = new Date("2026-09-04T09:00:00Z");
+const DAY_MS = 24 * 60 * 60 * 1000;
+const daysAgo = (days: number): string => new Date(NOW.getTime() - days * DAY_MS).toISOString();
+
+const issue = (number: number, title: string, overrides: Partial<Issue> = {}): Issue => ({
+  number,
+  title,
+  state: "open",
+  user: { login: "reporter" },
+  ...overrides,
+});
+
+const notice = (candidates: readonly number[], createdAt: string, overrides: Partial<Comment> = {}): Comment => ({
+  id: 900,
+  body: `<!-- litellm:potential-duplicate candidates=${candidates.join(",")}, -->\n**Potential duplicate detected**`,
+  created_at: createdAt,
+  user: { type: "Bot", login: "github-actions[bot]" },
+  ...overrides,
+});
+
+const humanComment = (createdAt: string, body = "It is not the same thing", login = "reporter"): Comment => ({
+  id: 901,
+  body,
+  created_at: createdAt,
+  user: { type: "User", login },
+});
+
+const config: SweepConfig = { repo: "BerriAI/litellm", graceDays: 3, dryRun: false, now: NOW };
+
+describe("normalizeTitle", () => {
+  test("drops the template prefix, case, and punctuation", () => {
+    expect(normalizeTitle("[Bug]: Gemma 4-e4b fails on Vertex!")).toBe("gemma 4 e4b fails on vertex");
+    expect(normalizeTitle("[Feature]:   ")).toBe("");
+  });
+});
+
+describe("candidateNumbers", () => {
+  test("reads only the marker field, keeps older issues, sorted ascending and deduplicated", () => {
+    const body = "<!-- litellm:potential-duplicate candidates=40,10,30,10, -->\n- #1 - see #1 (100% similar)";
+    expect(candidateNumbers(body, 35)).toEqual([10, 30]);
+  });
+
+  test("returns nothing without the marker", () => {
+    expect(candidateNumbers("- #1 - looks like #1", 35)).toEqual([]);
+  });
+});
+
+describe("pendingNotice", () => {
+  test("waits out the grace period from the latest notice", () => {
+    const fresh = pendingNotice(issue(35, "t"), [notice([10], daysAgo(2.9))], config);
+    expect(fresh.kind).toBe("skip");
+    const aged = pendingNotice(issue(35, "t"), [notice([10], daysAgo(3.1))], config);
+    expect(aged.kind).toBe("pending");
+    const reposted = pendingNotice(
+      issue(35, "t"),
+      [notice([10], daysAgo(6)), notice([10], daysAgo(1), { id: 902 })],
+      config,
+    );
+    expect(reposted.kind).toBe("skip");
+  });
+
+  test("an objection posted before a re-posted notice still keeps the issue open", () => {
+    const verdict = pendingNotice(
+      issue(35, "t"),
+      [notice([10], daysAgo(10)), humanComment(daysAgo(7)), notice([10], daysAgo(4), { id: 902 })],
+      config,
+    );
+    expect(verdict).toEqual({ kind: "skip", reason: "someone replied after the notice" });
+  });
+
+  test("a zero-day grace period acts on the notice at once", () => {
+    const verdict = pendingNotice(issue(35, "t"), [notice([10], daysAgo(0.01))], { ...config, graceDays: 0 });
+    expect(verdict.kind).toBe("pending");
+  });
+
+  test("a human reply after the notice keeps the issue open, a bot reply does not", () => {
+    const human = pendingNotice(issue(35, "t"), [notice([10], daysAgo(5)), humanComment(daysAgo(4))], config);
+    expect(human).toEqual({ kind: "skip", reason: "someone replied after the notice" });
+    const bot = pendingNotice(
+      issue(35, "t"),
+      [notice([10], daysAgo(5)), { id: 903, body: "triage", created_at: daysAgo(4), user: { type: "Bot", login: "triage[bot]" } }],
+      config,
+    );
+    expect(bot.kind).toBe("pending");
+  });
+
+  test("a human quoting the marker is not a notice", () => {
+    const quoted = pendingNotice(issue(35, "t"), [notice([10], daysAgo(5), { user: { type: "User", login: "reporter" } })], config);
+    expect(quoted).toEqual({ kind: "skip", reason: "carries no duplicate notice" });
+  });
+
+  test("never closes an issue twice: a reopened issue is left alone", () => {
+    const reopened = pendingNotice(
+      issue(35, "t"),
+      [notice([10], daysAgo(9)), { id: 904, body: `Closed automatically\n\n${CLOSED_MARKER}`, created_at: daysAgo(5), user: { type: "Bot", login: "github-actions[bot]" } }],
+      config,
+    );
+    expect(reopened).toEqual({ kind: "skip", reason: "was reopened after an automatic close" });
+  });
+
+  test("skips pull requests and issues whose only candidates are newer", () => {
+    expect(pendingNotice(issue(35, "t", { pull_request: {} }), [notice([10], daysAgo(5))], config).kind).toBe("skip");
+    expect(pendingNotice(issue(35, "t"), [notice([40], daysAgo(5))], config)).toEqual({
+      kind: "skip",
+      reason: "no candidate is older than this issue",
+    });
+  });
+});
+
+describe("duplicateTarget", () => {
+  const reporter = issue(35, "[Bug]: Gemma 4-e4b fails on Vertex");
+
+  test("closes only against the earliest open issue with the identical normalized title", () => {
+    const verdict = duplicateTarget(
+      reporter,
+      [issue(10, "[Bug]: Gemma 4-e4n fails on Vertex"), issue(20, "[bug]: gemma 4-e4b fails on vertex"), issue(30, "[Bug]: Gemma 4-e4b fails on Vertex")],
+      [],
+    );
+    expect(verdict).toEqual({ kind: "close", duplicateOf: 20 });
+  });
+
+  test("a near miss in the title is not a duplicate", () => {
+    const verdict = duplicateTarget(reporter, [issue(10, "[Bug]: Gemma 4-e4n fails on Vertex")], []);
+    expect(verdict).toEqual({ kind: "skip", reason: "no older open issue has the identical title" });
+  });
+
+  test("bare template titles never match each other", () => {
+    const verdict = duplicateTarget(issue(35, "[Bug]: "), [issue(10, "[Bug]: ")], []);
+    expect(verdict.kind).toBe("skip");
+    expect(verdict.kind === "skip" && verdict.reason).toContain("too short");
+  });
+
+  test("a closed candidate or a pull request is never the target", () => {
+    expect(duplicateTarget(reporter, [issue(10, reporter.title, { state: "closed" })], []).kind).toBe("skip");
+    expect(duplicateTarget(reporter, [issue(10, reporter.title, { pull_request: {} })], []).kind).toBe("skip");
+  });
+
+  test("a thumbs down on the notice keeps the issue open", () => {
+    const verdict = duplicateTarget(reporter, [issue(10, reporter.title)], [{ content: "+1" }, { content: "-1" }]);
+    expect(verdict).toEqual({ kind: "skip", reason: "someone gave the notice a thumbs down" });
+  });
+});
+
+describe("sweepIssue", () => {
+  const reporter = issue(35, "[Bug]: Gemma 4-e4b fails on Vertex");
+  const original = issue(10, "[Bug]: Gemma 4-e4b fails on Vertex");
+
+  function fakeApi(
+    comments: readonly Comment[] = [notice([10], daysAgo(5))],
+    reactionsByNotice: Readonly<Record<number, readonly Reaction[]>> = {},
+  ): { readonly api: GitHubApi; readonly writes: readonly string[] } {
+    const writes: string[] = [];
+    const api: GitHubApi = {
+      request: async <T>(method: string, path: string, body?: object): Promise<T> => {
+        if (method !== "GET") {
+          writes.push(`${method} ${path} ${JSON.stringify(body)}`);
+          return {} as T;
+        }
+        if (path.startsWith("/repos/BerriAI/litellm/issues/35/comments")) {
+          return comments as T;
+        }
+        const reactionsPath = path.match(/^\/repos\/BerriAI\/litellm\/issues\/comments\/(\d+)\/reactions/);
+        if (reactionsPath) {
+          return (reactionsByNotice[Number(reactionsPath[1])] ?? []) as T;
+        }
+        if (path === "/repos/BerriAI/litellm/issues/10") {
+          return original as T;
+        }
+        throw new Error(`unexpected GET ${path}`);
+      },
+    };
+    return { api, writes };
+  }
+
+  test("a dry run reports the close and writes nothing", async () => {
+    const { api, writes } = fakeApi();
+    const verdict = await sweepIssue(api, { ...config, dryRun: true }, reporter);
+    expect(verdict).toEqual({ kind: "close", duplicateOf: 10 });
+    expect(writes).toEqual([]);
+  });
+
+  test("a thumbs down on an earlier notice still keeps the issue open", async () => {
+    const { api, writes } = fakeApi([notice([10], daysAgo(9)), notice([10], daysAgo(5), { id: 902 })], { 900: [{ content: "-1" }] });
+    const verdict = await sweepIssue(api, config, reporter);
+    expect(verdict).toEqual({ kind: "skip", reason: "someone gave the notice a thumbs down" });
+    expect(writes).toEqual([]);
+  });
+
+  test("a real run comments, labels, then closes with the duplicate reason", async () => {
+    const { api, writes } = fakeApi();
+    const verdict = await sweepIssue(api, config, reporter);
+    expect(verdict).toEqual({ kind: "close", duplicateOf: 10 });
+    expect(writes.map((write) => write.split(" ").slice(0, 2).join(" "))).toEqual([
+      "POST /repos/BerriAI/litellm/issues/35/comments",
+      "POST /repos/BerriAI/litellm/issues/35/labels",
+      "PATCH /repos/BerriAI/litellm/issues/35",
+    ]);
+    expect(writes[0]).toContain("duplicate of #10");
+    expect(writes[0]).toContain("unanswered for 3 days");
+    expect(writes[0]).toContain(CLOSED_MARKER);
+    expect(writes[1]).toContain('{"labels":["duplicate"]}');
+    expect(writes[2]).toContain('{"state":"closed","state_reason":"duplicate"}');
+  });
+});
+
+describe("reopenTarget", () => {
+  const closedByBot = (overrides: Partial<Issue> = {}): Issue =>
+    issue(35, "t", { state: "closed", closed_by: { type: "Bot" }, ...overrides });
+  const closeMarker = (createdAt: string): Comment => ({
+    id: 905,
+    body: `Closed automatically as a duplicate of #10.\n\n${CLOSED_MARKER}`,
+    created_at: createdAt,
+    user: { type: "Bot", login: "github-actions[bot]" },
+  });
+
+  test("a reporter reply after the automatic close reopens", () => {
+    const verdict = reopenTarget(closedByBot(), [closeMarker(daysAgo(2)), humanComment(daysAgo(1))]);
+    expect(verdict).toEqual({ kind: "reopen" });
+  });
+
+  test("an issue closed by a person stays closed", () => {
+    const verdict = reopenTarget(closedByBot({ closed_by: { type: "User" } }), [
+      closeMarker(daysAgo(2)),
+      humanComment(daysAgo(1)),
+    ]);
+    expect(verdict).toEqual({ kind: "skip", reason: "was closed by a person" });
+  });
+
+  test("without the automatic-close marker nothing reopens", () => {
+    const verdict = reopenTarget(closedByBot(), [humanComment(daysAgo(1))]);
+    expect(verdict).toEqual({ kind: "skip", reason: "carries no automatic-close marker" });
+  });
+
+  test("a maintainer reply alone does not reopen", () => {
+    const verdict = reopenTarget(closedByBot(), [
+      closeMarker(daysAgo(2)),
+      humanComment(daysAgo(1), "Confirmed duplicate", "maintainer"),
+    ]);
+    expect(verdict).toEqual({ kind: "skip", reason: "the reporter has not replied since the close" });
+  });
+
+  test("a reporter comment from before the close does not reopen", () => {
+    const verdict = reopenTarget(closedByBot(), [humanComment(daysAgo(3)), closeMarker(daysAgo(2))]);
+    expect(verdict).toEqual({ kind: "skip", reason: "the reporter has not replied since the close" });
+  });
+
+  test("a pull request never reopens", () => {
+    const verdict = reopenTarget(closedByBot({ pull_request: {} }), [closeMarker(daysAgo(2)), humanComment(daysAgo(1))]);
+    expect(verdict).toEqual({ kind: "skip", reason: "is a pull request" });
+  });
+});
+
+describe("sweepClosedIssue", () => {
+  function fakeApi(issueBody: Issue, comments: readonly Comment[]): { readonly api: GitHubApi; readonly writes: readonly string[] } {
+    const writes: string[] = [];
+    const api: GitHubApi = {
+      request: async <T>(method: string, path: string, body?: object): Promise<T> => {
+        if (method !== "GET") {
+          writes.push(`${method} ${path} ${JSON.stringify(body)}`);
+          return {} as T;
+        }
+        if (path.startsWith("/repos/BerriAI/litellm/issues/35/comments")) {
+          return comments as T;
+        }
+        if (path === "/repos/BerriAI/litellm/issues/35") {
+          return issueBody as T;
+        }
+        throw new Error(`unexpected GET ${path}`);
+      },
+    };
+    return { api, writes };
+  }
+
+  const closedByBot = issue(35, "t", { state: "closed", closed_by: { type: "Bot" } });
+  const closeMarker: Comment = {
+    id: 905,
+    body: `Closed automatically as a duplicate of #10.\n\n${CLOSED_MARKER}`,
+    created_at: daysAgo(2),
+    user: { type: "Bot", login: "github-actions[bot]" },
+  };
+
+  test("a real run unlabels, reopens, then explains", async () => {
+    const { api, writes } = fakeApi(closedByBot, [closeMarker, humanComment(daysAgo(1))]);
+    const verdict = await sweepClosedIssue(api, config, 35);
+    expect(verdict).toEqual({ kind: "reopen" });
+    expect(writes).toEqual([
+      "DELETE /repos/BerriAI/litellm/issues/35/labels/duplicate undefined",
+      'PATCH /repos/BerriAI/litellm/issues/35 {"state":"open"}',
+      `POST /repos/BerriAI/litellm/issues/35/comments {"body":"${REOPEN_COMMENT}"}`,
+    ]);
+  });
+
+  test("a dry run reports the reopen and writes nothing", async () => {
+    const { api, writes } = fakeApi(closedByBot, [closeMarker, humanComment(daysAgo(1))]);
+    const verdict = await sweepClosedIssue(api, { ...config, dryRun: true }, 35);
+    expect(verdict).toEqual({ kind: "reopen" });
+    expect(writes).toEqual([]);
+  });
+});
+
+describe("readConfig", () => {
+  test("defaults to a real run with a 3-day grace period", () => {
+    const parsed = readConfig({ GITHUB_TOKEN: "t", GITHUB_REPOSITORY: "BerriAI/litellm" }, NOW);
+    expect(parsed).toEqual({ token: "t", repo: "BerriAI/litellm", graceDays: 3, dryRun: false, now: NOW });
+  });
+
+  test("honors DRY_RUN and GRACE_PERIOD_DAYS overrides", () => {
+    const parsed = readConfig(
+      { GITHUB_TOKEN: "t", GITHUB_REPOSITORY: "o/r", DRY_RUN: "true", GRACE_PERIOD_DAYS: "0" },
+      NOW,
+    );
+    expect(parsed.dryRun).toBe(true);
+    expect(parsed.graceDays).toBe(0);
+  });
+
+  test("an empty GRACE_PERIOD_DAYS, as a schedule run renders it, means the default", () => {
+    const parsed = readConfig({ GITHUB_TOKEN: "t", GITHUB_REPOSITORY: "o/r", GRACE_PERIOD_DAYS: "" }, NOW);
+    expect(parsed.graceDays).toBe(3);
+  });
+
+  test("refuses a missing token, a malformed repository, or a bad grace period", () => {
+    expect(() => readConfig({ GITHUB_REPOSITORY: "o/r" }, NOW)).toThrow("GITHUB_TOKEN");
+    expect(() => readConfig({ GITHUB_TOKEN: "t", GITHUB_REPOSITORY: "litellm" }, NOW)).toThrow("owner/repo");
+    expect(() => readConfig({ GITHUB_TOKEN: "t", GITHUB_REPOSITORY: "o/r", GRACE_PERIOD_DAYS: "-1" }, NOW)).toThrow(
+      "GRACE_PERIOD_DAYS",
+    );
+  });
+});
diff --git a/scripts/auto-close-duplicates.ts b/scripts/auto-close-duplicates.ts
new file mode 100644
index 00000000000..c595104d886
--- /dev/null
+++ b/scripts/auto-close-duplicates.ts
@@ -0,0 +1,300 @@
+#!/usr/bin/env bun
+
+declare const process: { readonly env: Readonly<Record<string, string | undefined>> };
+
+export interface Issue {
+  readonly number: number;
+  readonly title: string;
+  readonly state: string;
+  readonly user: { readonly login: string };
+  readonly closed_by?: { readonly type: string } | null;
+  readonly pull_request?: unknown;
+}
+
+export interface Comment {
+  readonly id: number;
+  readonly body: string;
+  readonly created_at: string;
+  readonly user: { readonly type: string; readonly login: string };
+}
+
+export interface Reaction {
+  readonly content: string;
+}
+
+export interface GitHubApi {
+  readonly request: <T>(method: "GET" | "POST" | "PATCH" | "DELETE", path: string, body?: object) => Promise<T>;
+}
+
+export interface SweepConfig {
+  readonly repo: string;
+  readonly graceDays: number;
+  readonly dryRun: boolean;
+  readonly now: Date;
+}
+
+export type NoticeVerdict =
+  | { readonly kind: "pending"; readonly notices: readonly Comment[]; readonly candidates: readonly number[] }
+  | { readonly kind: "skip"; readonly reason: string };
+
+export type CloseVerdict =
+  | { readonly kind: "close"; readonly duplicateOf: number }
+  | { readonly kind: "skip"; readonly reason: string };
+
+export type ReopenVerdict =
+  | { readonly kind: "reopen" }
+  | { readonly kind: "skip"; readonly reason: string };
+
+export const FLAG_LABEL = "potential-duplicate";
+export const CLOSED_MARKER = "<!-- litellm:closed-as-duplicate -->";
+export const DEFAULT_GRACE_DAYS = 3;
+export const REOPEN_COMMENT =
+  "Reopened automatically: the reporter replied after the duplicate close, so this needs a human look.";
+const NOTICE_MARKER = /<!-- litellm:potential-duplicate candidates=([\d,]*) -->/;
+const MIN_TITLE_WORDS = 3;
+const PAGE_SIZE = 100;
+const DAY_MS = 24 * 60 * 60 * 1000;
+const REOPEN_LOOKBACK_DAYS = 30;
+
+const skip = (reason: string): { readonly kind: "skip"; readonly reason: string } => ({ kind: "skip", reason });
+
+export function normalizeTitle(title: string): string {
+  return title
+    .toLowerCase()
+    .replace(/^\s*\[[^\]]*\]\s*:?/, "")
+    .replace(/[^a-z0-9]+/g, " ")
+    .trim();
+}
+
+export function candidateNumbers(noticeBody: string, issueNumber: number): readonly number[] {
+  const field = noticeBody.match(NOTICE_MARKER);
+  if (!field) {
+    return [];
+  }
+  const older = field[1]
+    .split(",")
+    .filter((value) => value !== "")
+    .map(Number)
+    .filter((candidate) => candidate < issueNumber);
+  return [...new Set(older)].sort((a, b) => a - b);
+}
+
+export function pendingNotice(
+  issue: Issue,
+  comments: readonly Comment[],
+  config: Pick<SweepConfig, "graceDays" | "now">,
+): NoticeVerdict {
+  if (issue.pull_request !== undefined) {
+    return skip("is a pull request");
+  }
+  if (comments.some((comment) => comment.body.includes(CLOSED_MARKER))) {
+    return skip("was reopened after an automatic close");
+  }
+  const notices = comments.filter((comment) => comment.user.type === "Bot" && NOTICE_MARKER.test(comment.body));
+  const first = notices[0];
+  const latest = notices[notices.length - 1];
+  if (first === undefined || latest === undefined) {
+    return skip("carries no duplicate notice");
+  }
+  const ageDays = (config.now.getTime() - new Date(latest.created_at).getTime()) / DAY_MS;
+  if (ageDays < config.graceDays) {
+    return skip(`notice is ${ageDays.toFixed(1)} days old, grace period is ${config.graceDays}`);
+  }
+  const firstNoticeAt = new Date(first.created_at);
+  if (comments.some((comment) => comment.user.type !== "Bot" && new Date(comment.created_at) > firstNoticeAt)) {
+    return skip("someone replied after the notice");
+  }
+  const candidates = candidateNumbers(latest.body, issue.number);
+  if (candidates.length === 0) {
+    return skip("no candidate is older than this issue");
+  }
+  return { kind: "pending", notices, candidates };
+}
+
+export function duplicateTarget(
+  issue: Issue,
+  candidates: readonly Issue[],
+  reactions: readonly Reaction[],
+): CloseVerdict {
+  if (reactions.some((reaction) => reaction.content === "-1")) {
+    return skip("someone gave the notice a thumbs down");
+  }
+  const title = normalizeTitle(issue.title);
+  if (title.split(" ").length < MIN_TITLE_WORDS) {
+    return skip(`title "${issue.title}" is too short to match on`);
+  }
+  const original = candidates.find(
+    (candidate) =>
+      candidate.state === "open" && candidate.pull_request === undefined && normalizeTitle(candidate.title) === title,
+  );
+  if (original === undefined) {
+    return skip("no older open issue has the identical title");
+  }
+  return { kind: "close", duplicateOf: original.number };
+}
+
+export function reopenTarget(issue: Issue, comments: readonly Comment[]): ReopenVerdict {
+  if (issue.pull_request !== undefined) {
+    return skip("is a pull request");
+  }
+  if (issue.closed_by?.type !== "Bot") {
+    return skip("was closed by a person");
+  }
+  const marker = comments.find((comment) => comment.body.includes(CLOSED_MARKER));
+  if (marker === undefined) {
+    return skip("carries no automatic-close marker");
+  }
+  const markerAt = new Date(marker.created_at);
+  if (!comments.some((comment) => comment.user.login === issue.user.login && new Date(comment.created_at) > markerAt)) {
+    return skip("the reporter has not replied since the close");
+  }
+  return { kind: "reopen" };
+}
+
+export function closingComment(duplicateOf: number, graceDays: number): string {
+  return `Closed automatically as a duplicate of #${duplicateOf}. Its title is identical to that older open issue and the duplicate notice above went unanswered for ${graceDays} days. If this is wrong, comment here with how it differs from #${duplicateOf} and this issue will be reopened automatically within a day.
+
+${CLOSED_MARKER}`;
+}
+
+async function listAll<T>(api: GitHubApi, path: string, page = 1): Promise<readonly T[]> {
+  const separator = path.includes("?") ? "&" : "?";
+  const batch = await api.request<readonly T[]>("GET", `${path}${separator}per_page=${PAGE_SIZE}&page=${page}`);
+  return batch.length < PAGE_SIZE ? batch : [...batch, ...(await listAll<T>(api, path, page + 1))];
+}
+
+async function closeAsDuplicate(
+  api: GitHubApi,
+  config: SweepConfig,
+  issueNumber: number,
+  duplicateOf: number,
+): Promise<void> {
+  const issuePath = `/repos/${config.repo}/issues/${issueNumber}`;
+  await api.request("POST", `${issuePath}/comments`, { body: closingComment(duplicateOf, config.graceDays) });
+  await api.request("POST", `${issuePath}/labels`, { labels: ["duplicate"] });
+  await api.request("PATCH", issuePath, { state: "closed", state_reason: "duplicate" });
+}
+
+async function reopenForReporter(api: GitHubApi, config: SweepConfig, issueNumber: number): Promise<void> {
+  const issuePath = `/repos/${config.repo}/issues/${issueNumber}`;
+  await api.request("DELETE", `${issuePath}/labels/duplicate`);
+  await api.request("PATCH", issuePath, { state: "open" });
+  await api.request("POST", `${issuePath}/comments`, { body: REOPEN_COMMENT });
+}
+
+export async function sweepClosedIssue(api: GitHubApi, config: SweepConfig, issueNumber: number): Promise<ReopenVerdict> {
+  const issue = await api.request<Issue>("GET", `/repos/${config.repo}/issues/${issueNumber}`);
+  const comments = await listAll<Comment>(api, `/repos/${config.repo}/issues/${issueNumber}/comments`);
+  const verdict = reopenTarget(issue, comments);
+  if (verdict.kind === "reopen" && !config.dryRun) {
+    await reopenForReporter(api, config, issueNumber);
+  }
+  return verdict;
+}
+
+export async function sweepIssue(api: GitHubApi, config: SweepConfig, issue: Issue): Promise<CloseVerdict> {
+  const comments = await listAll<Comment>(api, `/repos/${config.repo}/issues/${issue.number}/comments`);
+  const pending = pendingNotice(issue, comments, config);
+  if (pending.kind === "skip") {
+    return pending;
+  }
+  const reactions = (
+    await Promise.all(
+      pending.notices.map((notice) => listAll<Reaction>(api, `/repos/${config.repo}/issues/comments/${notice.id}/reactions`)),
+    )
+  ).flat();
+  const candidates = await Promise.all(
+    pending.candidates.map((candidate) => api.request<Issue>("GET", `/repos/${config.repo}/issues/${candidate}`)),
+  );
+  const verdict = duplicateTarget(issue, candidates, reactions);
+  if (verdict.kind === "close" && !config.dryRun) {
+    await closeAsDuplicate(api, config, issue.number, verdict.duplicateOf);
+  }
+  return verdict;
+}
+
+function describe(issue: Issue, verdict: CloseVerdict, dryRun: boolean): string {
+  if (verdict.kind === "skip") {
+    return `#${issue.number}: skipped, ${verdict.reason}`;
+  }
+  return `#${issue.number}: ${dryRun ? "would close" : "closed"} as a duplicate of #${verdict.duplicateOf}`;
+}
+
+export async function sweep(api: GitHubApi, config: SweepConfig): Promise<readonly CloseVerdict[]> {
+  const issues = await listAll<Issue>(api, `/repos/${config.repo}/issues?state=open&labels=${FLAG_LABEL}`);
+  console.log(`${issues.length} open issues carry the ${FLAG_LABEL} label in ${config.repo}${config.dryRun ? " (dry run)" : ""}`);
+  return issues.reduce<Promise<readonly CloseVerdict[]>>(async (previous, issue) => {
+    const verdicts = await previous;
+    const verdict = await sweepIssue(api, config, issue);
+    console.log(describe(issue, verdict, config.dryRun));
+    return [...verdicts, verdict];
+  }, Promise.resolve([]));
+}
+
+function describeReopen(issueNumber: number, verdict: ReopenVerdict, dryRun: boolean): string {
+  if (verdict.kind === "skip") {
+    return `#${issueNumber}: skipped, ${verdict.reason}`;
+  }
+  return `#${issueNumber}: ${dryRun ? "would reopen" : "reopened"} for the reporter's reply`;
+}
+
+export async function reopenSweep(api: GitHubApi, config: SweepConfig): Promise<readonly ReopenVerdict[]> {
+  const since = new Date(config.now.getTime() - REOPEN_LOOKBACK_DAYS * DAY_MS).toISOString();
+  const closedPath = `/repos/${config.repo}/issues?state=closed&labels=duplicate,${FLAG_LABEL}&since=${encodeURIComponent(since)}`;
+  const issues = await listAll<Issue>(api, closedPath);
+  console.log(`${issues.length} recently closed issues carry the duplicate and ${FLAG_LABEL} labels in ${config.repo}${config.dryRun ? " (dry run)" : ""}`);
+  return issues.reduce<Promise<readonly ReopenVerdict[]>>(async (previous, issue) => {
+    const verdicts = await previous;
+    const verdict = await sweepClosedIssue(api, config, issue.number);
+    console.log(describeReopen(issue.number, verdict, config.dryRun));
+    return [...verdicts, verdict];
+  }, Promise.resolve([]));
+}
+
+export function readConfig(env: Readonly<Record<string, string | undefined>>, now: Date): SweepConfig & { readonly token: string } {
+  const token = env.GITHUB_TOKEN;
+  const repo = env.GITHUB_REPOSITORY;
+  if (!token || !repo || !/^[\w.-]+\/[\w.-]+$/.test(repo)) {
+    throw new Error("GITHUB_TOKEN and GITHUB_REPOSITORY (owner/repo) are required");
+  }
+  const rawGraceDays = env.GRACE_PERIOD_DAYS?.trim();
+  const graceDays = rawGraceDays === undefined || rawGraceDays === "" ? DEFAULT_GRACE_DAYS : Number(rawGraceDays);
+  if (!Number.isFinite(graceDays) || graceDays < 0) {
+    throw new Error(`GRACE_PERIOD_DAYS must be a non-negative number, got "${env.GRACE_PERIOD_DAYS}"`);
+  }
+  return { token, repo, graceDays, dryRun: env.DRY_RUN === "true", now };
+}
+
+export function githubApi(token: string): GitHubApi {
+  return {
+    request: async <T>(method: "GET" | "POST" | "PATCH" | "DELETE", path: string, body?: object): Promise<T> => {
+      const response = await fetch(`https://api.github.com${path}`, {
+        method,
+        headers: {
+          Authorization: `Bearer ${token}`,
+          Accept: "application/vnd.github+json",
+          "X-GitHub-Api-Version": "2022-11-28",
+          "User-Agent": "litellm-auto-close-duplicates",
+          ...(body === undefined ? {} : { "Content-Type": "application/json" }),
+        },
+        body: body === undefined ? undefined : JSON.stringify(body),
+      });
+      if (!response.ok) {
+        throw new Error(`${method} ${path} failed: ${response.status} ${response.statusText}`);
+      }
+      return (await response.json()) as T;
+    },
+  };
+}
+
+if (import.meta.main) {
+  const { token, ...config } = readConfig(process.env, new Date());
+  const api = githubApi(token);
+  const closeVerdicts = await sweep(api, config);
+  const reopenVerdicts = await reopenSweep(api, config);
+  const closed = closeVerdicts.filter((verdict) => verdict.kind === "close").length;
+  const reopened = reopenVerdicts.filter((verdict) => verdict.kind === "reopen").length;
+  console.log(
+    `${config.dryRun ? "Would close" : "Closed"} ${closed} of ${closeVerdicts.length} flagged issues, ${config.dryRun ? "would reopen" : "reopened"} ${reopened}`,
+  );
+}
diff --git a/test-quality-budget.json b/test-quality-budget.json
index ee33eb581d6..d834c581609 100644
--- a/test-quality-budget.json
+++ b/test-quality-budget.json
@@ -3,7 +3,7 @@
     "limit": 733
   },
   "TQ002": {
-    "limit": 742
+    "limit": 741
   },
   "TQ003": {
     "limit": 62
@@ -21,6 +21,6 @@
     "limit": 117
   },
   "TQ008": {
-    "limit": 11139
+    "limit": 11135
   }
 }
diff --git a/tests/code_coverage_tests/recursive_detector.py b/tests/code_coverage_tests/recursive_detector.py
index 37e940460f6..0578dc60119 100644
--- a/tests/code_coverage_tests/recursive_detector.py
+++ b/tests/code_coverage_tests/recursive_detector.py
@@ -63,6 +63,9 @@ IGNORE_FUNCTIONS = [
     "json_unrewritable_labels",  # max depth set (MAX_STRUCTURED_CONTENT_SCAN_DEPTH); returns the None sentinel at the cap so the caller blocks.
     "_flatten_form_field",  # bounded by the nesting depth of the already-parsed request body (a finite JSON tree, no cycles possible).
     "_flatten_form_data_field",  # bounded by the nesting depth of the already-parsed request body (a finite JSON tree, no cycles possible).
+    "_json_safe",  # max depth set (_MAX_DEPTH) plus a seen-ids cycle guard for self-referential input.
+    "_redact_agent_params_tree",  # max depth set (default 10), same shape as _redact_sensitive_litellm_params.
+    "_restore_redacted_nested_value",  # max depth set (default 10), mirrors _redact_agent_params_tree on the write side.
 ]
 
 
diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py
index c541c035db7..0af29f069c6 100644
--- a/tests/code_coverage_tests/router_code_coverage.py
+++ b/tests/code_coverage_tests/router_code_coverage.py
@@ -81,6 +81,12 @@ ignored_function_names = [
     "_merge_tools_from_deployment",  # Tested indirectly via _update_kwargs_with_deployment (test files lack "router" in name)
     "_invalidate_access_groups_cache",  # Tested indirectly via set_model_list, upsert_model etc. (test files lack "router" in name)
     "has_buffered_provider_output",  # Property, so its reads in test_router.py are never an ast.Call
+    "_resolved_provider",  # Tested via get_pattern in test_pattern_match_deployments.py (file lacks "router" in name)
+    "_request_header",  # Tested through Claude Code session routing in test_router.py
+    "_claude_code_session_router_cache_key",  # Tested through Claude Code session routing in test_router.py
+    "_delete_claude_code_session_router_binding",  # Tested through Redis cleanup failure in test_router.py
+    "_resolve_claude_code_session_router",  # Tested through Claude Code session routing in test_router.py
+    "_get_claude_code_session_router_binding",  # Tested through the two-worker session routing test in test_router.py
 ]
 
 
diff --git a/tests/documentation_tests/test_env_keys.py b/tests/documentation_tests/test_env_keys.py
index b91c404b2eb..3652378503e 100644
--- a/tests/documentation_tests/test_env_keys.py
+++ b/tests/documentation_tests/test_env_keys.py
@@ -33,6 +33,13 @@ EXCLUDED_ROLLOUT_FLAGS = {
     "LITELLM_RUST",
 }
 
+# Internal infrastructure tuning parameters for streaming/queue management
+# These are advanced settings with sensible defaults that most users should not modify
+EXCLUDED_INTERNAL_TUNING_VARS = {
+    "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS",
+    "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE",
+}
+
 EXCLUDED_TERMINAL_VARS = {
     "TERM",
     "TERM_PROGRAM",
@@ -50,7 +57,9 @@ EXCLUDED_TERMINAL_VARS = {
     "ALACRITTY_SOCKET",
 }
 
-EXCLUDED_KEYS = frozenset(EXCLUDED_TERMINAL_VARS | EXCLUDED_GUARD_ONLY_VARS | EXCLUDED_ROLLOUT_FLAGS)
+EXCLUDED_KEYS = frozenset(
+    EXCLUDED_TERMINAL_VARS | EXCLUDED_GUARD_ONLY_VARS | EXCLUDED_ROLLOUT_FLAGS | EXCLUDED_INTERNAL_TUNING_VARS
+)
 
 # Directories to skip (dependencies, venvs, caches) - only scan litellm source
 SKIP_DIRS = {
diff --git a/tests/e2e/coverage_registry/mgmt.yaml b/tests/e2e/coverage_registry/mgmt.yaml
index 1e6de0c3d6a..d571fb36546 100644
--- a/tests/e2e/coverage_registry/mgmt.yaml
+++ b/tests/e2e/coverage_registry/mgmt.yaml
@@ -64,14 +64,12 @@
 - {id: mgmt.budget.list_v1.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "management_v1/budgets.py:129", rationale: "Budget enumeration the Budgets page can page, sort and filter"}
 - {id: mgmt.budget.list_v1.admin_only, module: mgmt, tier: P1, surface: api, assertions: [admin_only], source: "management_v1/budgets.py:129", rationale: "A caller without admin view is refused, not served an empty page"}
 - {id: mgmt.callback.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "callback_management_endpoints.py", rationale: "Callback config (smoke)"}
-- {id: mgmt.cache_settings.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "cache_settings_endpoints.py", rationale: "Cache config (smoke). Deliberately uncovered: the previous test read the live settings and wrote them back, which proves nothing (identical values in, so a no-op POST still passes) while being able to break the deployment. /cache/settings persists what it receives and that row outranks YAML cache_params, re-applied on a timer, so a write that omits ssl or redis_startup_nodes turns a TLS cluster into a plaintext standalone node and every later Redis call hangs. That took out 60 of 72 tests on 2026-07-25. GET cannot round-trip it either: it resolves the stored row overlaid with REDIS_* env and never reads YAML, so on a fresh deploy it cannot see YAML ssl to echo back. A safe test needs an isolated proxy, or LIT-4816 fixed so a partial write cannot downgrade transport. Do not re-add a read-then-write-back test against a shared proxy."}
 - {id: mgmt.cost_tracking.estimate.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "cost_tracking_settings.py", rationale: "Cost estimate (smoke)"}
 - {id: mgmt.router_settings.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "router_settings_endpoints.py", rationale: "Router config (smoke)"}
 - {id: mgmt.jwt_key_mapping.new.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "jwt_key_mapping_endpoints.py", rationale: "JWT->key mapping (smoke)"}
 - {id: mgmt.compliance.gdpr.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "compliance_endpoints.py", rationale: "GDPR ops (smoke)"}
 - {id: mgmt.tool_management.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "tool_management_endpoints.py", rationale: "Tool inventory (smoke)"}
 - {id: mgmt.fallback_management.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "fallback_management_endpoints.py", rationale: "Fallback config (smoke)"}
-- {id: mgmt.config_override.hashicorp_vault.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "config_override_endpoints.py", rationale: "Vault integration (smoke)"}
 - {id: mgmt.workflow.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "workflow_management_endpoints.py", rationale: "Workflow tracking (smoke)"}
 - {id: mgmt.credential_migration.check.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:4252", rationale: "Encryption migration (smoke)"}
 - {id: mgmt.credential.new.serves_request, module: mgmt, tier: P1, surface: api, assertions: [serves_request], source: "credential_endpoints/endpoints.py:42", rationale: "Stored credential resolves into a deployment and serves a live /messages request"}
diff --git a/tests/e2e/junit_properties.py b/tests/e2e/junit_properties.py
index e4f59f5c4d2..c5971c5362c 100644
--- a/tests/e2e/junit_properties.py
+++ b/tests/e2e/junit_properties.py
@@ -2,10 +2,16 @@
 
 The e2e suite ships results to Loki/Grafana from a standard pytest JUnit report
 (`--junitxml=e2e-report.xml`), not a bespoke log line. JUnit already records
-outcome, duration, and node id for every `<testcase>`; the only signals it cannot
-derive on its own are the normalized suite package and the coverage-registry cell
-ids a test covers. Those ride along as JUnit `<property>` entries via each item's
-`user_properties`, attached in `conftest.py::pytest_collection_modifyitems`.
+outcome, duration, and node id for every `<testcase>`; the signals it cannot
+derive on its own are the normalized suite package, the coverage-registry cell
+ids a test covers, and where the test's source lives. Those ride along as JUnit
+`<property>` entries via each item's `user_properties`, attached in
+`conftest.py::pytest_collection_modifyitems`.
+
+`source` is a property rather than the `file=` / `line=` attributes pytest used
+to write, because the `xunit2` family this suite runs on drops those, and
+switching families would change the XML for every consumer of it -- the
+Buildkite Test Engine upload and the Loki pipeline included.
 """
 
 from __future__ import annotations
@@ -14,22 +20,61 @@ from collections.abc import Iterable
 
 import pytest
 
+# Hardcoded because the runner image copies tests/e2e/ to /app/e2e, so nothing
+# at runtime names this suite's place in the repo. test_junit_properties.py
+# fails from a checkout if it moves.
+SUITE_ROOT = "tests/e2e"
+
+
+def suite_parts(path_part: str) -> tuple[str, ...]:
+    """Path components of a suite file relative to tests/e2e, however it ran.
+
+    Pytest paths are rootdir-relative, and rootdir moves with the invocation: a
+    repo-root run gives `tests/e2e/logging/test_x.py`, a suite-cwd run (the
+    runner image) gives `logging/test_x.py`. Both collapse to the same tuple.
+    """
+    raw = tuple(p for p in path_part.replace("\\", "/").split("/") if p and p != ".")
+    return raw[2:] if len(raw) >= 3 and raw[0] == "tests" and raw[1] == "e2e" else raw
+
 
 def package_from_nodeid(nodeid: str) -> str:
-    """Top-level suite package under tests/e2e/, or 'root' for top-level files.
-
-    Pytest nodeids are relative to the invocation cwd. Repo-root runs look like
-    `tests/e2e/logging/...`; suite-cwd runs look like `logging/...`. Strip the
-    `tests/e2e` prefix so package is the suite dir either way.
-    """
-    path_part = nodeid.split("::", 1)[0].replace("\\", "/")
-    raw = tuple(p for p in path_part.split("/") if p and p != ".")
-    parts = raw[2:] if len(raw) >= 3 and raw[0] == "tests" and raw[1] == "e2e" else raw
+    """Top-level suite package under tests/e2e/, or 'root' for top-level files."""
+    parts = suite_parts(nodeid.split("::", 1)[0])
     if len(parts) <= 1:
         return "root"
     return parts[0]
 
 
+def source_from_location(path: str, lineno: int | None) -> str:
+    """Repo-relative `path:line` for a test, or '' when nothing is linkable.
+
+    `pytest.Item.location` gives a rootdir-relative path and a ZERO-based line.
+    The path is re-rooted at SUITE_ROOT so consumers need not know how pytest was
+    started, and the line is emitted ONE-based to match editors, tracebacks and
+    code hosts. A decorated test anchors at its first decorator, which is where
+    pytest reports it.
+
+    Empty rather than a guess for anything unlinkable: no line, a path reaching
+    upward, or a path carrying a colon, which is both how an absolute Windows
+    path arrives and a character `path:line` has no way to represent.
+    """
+    if lineno is None:
+        return ""
+    normalized = path.replace("\\", "/")
+    if normalized.startswith("/") or ":" in normalized or ".." in normalized.split("/"):
+        return ""
+    parts = suite_parts(normalized)
+    if not parts:
+        return ""
+    return f"{'/'.join((SUITE_ROOT, *parts))}:{lineno + 1}"
+
+
+def source_from_item(item: pytest.Item) -> str:
+    """Read the repo-relative `path:line` off a pytest Item's reported location."""
+    path, lineno, _ = item.location
+    return source_from_location(path, lineno)
+
+
 def dedupe_covers(marker_args: Iterable[tuple[object, ...]]) -> tuple[str, ...]:
     """Flatten @pytest.mark.covers arg lists into unique, order-preserving cell
     ids, dropping anything that is not a non-empty string."""
@@ -43,10 +88,12 @@ def covers_from_item(item: pytest.Item) -> tuple[str, ...]:
 
 def result_properties(item: pytest.Item) -> tuple[tuple[str, str], ...]:
     """The custom signals a standard reporter cannot derive: the normalized suite
-    package and the comma-joined coverage-registry cell ids this test covers."""
+    package, the comma-joined coverage-registry cell ids this test covers, and the
+    repo-relative `path:line` its source sits at."""
     return (
         ("package", package_from_nodeid(item.nodeid)),
         ("covers", ",".join(covers_from_item(item))),
+        ("source", source_from_item(item)),
     )
 
 
diff --git a/tests/e2e/management/test_config_misc_endpoints_e2e.py b/tests/e2e/management/test_config_misc_endpoints_e2e.py
index 195732c0201..099ffa4b3bd 100644
--- a/tests/e2e/management/test_config_misc_endpoints_e2e.py
+++ b/tests/e2e/management/test_config_misc_endpoints_e2e.py
@@ -7,9 +7,13 @@ so a read-back reflects the change. Router settings, which mutate global proxy
 state, are exercised with a benign, self-restoring change so a shared proxy is left
 as it was found.
 
-Cache settings are deliberately not covered here; see the rationale on
-mgmt.cache_settings.update.happy_path in coverage_registry/mgmt.yaml before adding
-a test for that route.
+Cache settings and the Vault config override are deliberately not covered here.
+Both routes reconfigure the whole proxy: /cache/settings persists what it receives
+into a row that outranks the YAML cache_params and is re-applied on a timer, and
+/config_overrides/hashicorp_vault swaps the process-wide secret manager. Neither can
+be exercised safely against the shared proxy the suites run on, so they need an
+isolated proxy before a test lands. Do not add a read-then-write-back test for
+either one.
 """
 
 from __future__ import annotations
diff --git a/tests/e2e/management/test_model_tag_accessgroup_e2e.py b/tests/e2e/management/test_model_tag_accessgroup_e2e.py
index e6a187ae105..eb3a6093c69 100644
--- a/tests/e2e/management/test_model_tag_accessgroup_e2e.py
+++ b/tests/e2e/management/test_model_tag_accessgroup_e2e.py
@@ -180,6 +180,12 @@ class ModelBlockBody(BaseModel):
     model_id: str
 
 
+class ModelBlockResponse(BaseModel):
+    model_config = ConfigDict(protected_namespaces=())
+    model_id: str
+    blocked: bool
+
+
 class ModelInfoBlockDetail(BaseModel):
     id: str | None = None
     blocked: bool | None = None
@@ -245,11 +251,6 @@ class TestModelRoutes:
     def test_block_then_unblock_persists_to_model_info(
         self, client: ManagementClient, resources: ResourceManager
     ) -> None:
-        """The blocked flag's persistence is read back from /model/info, not from the
-        /model/block response: that route currently returns a non-2xx serialization
-        envelope even though the DB write lands, so the /model/info read-back is the
-        authoritative persistence contract and keeps this test valid once the
-        response shape is fixed."""
         model_name = f"e2e-mgmt-model-block-{unique_marker()}"
         model_id = _create_db_model(client, resources, model_name)
 
@@ -257,27 +258,25 @@ class TestModelRoutes:
             f"{model_name!r} already reports blocked in /model/info before /model/block ran"
         )
 
-        _ = client.proxy.transport.send(
-            "/model/block",
-            headers=client.proxy.transport.master,
-            json=ModelBlockBody(model_id=model_id),
-        )
-        _ = _poll(
-            client.proxy,
-            lambda: True if _model_blocked_flag(client, model_id) is True else None,
-            f"/model/info never reported {model_name!r} blocked after /model/block",
-        )
-
-        _ = client.proxy.transport.send(
-            "/model/unblock",
-            headers=client.proxy.transport.master,
-            json=ModelBlockBody(model_id=model_id),
-        )
-        _ = _poll(
-            client.proxy,
-            lambda: True if _model_blocked_flag(client, model_id) is not True else None,
-            f"/model/info never cleared blocked for {model_name!r} after /model/unblock",
-        )
+        for action, expected in (("block", True), ("unblock", False)):
+            response = unwrap(
+                client.proxy.transport.post(
+                    f"/model/{action}",
+                    headers=client.proxy.transport.master,
+                    json=ModelBlockBody(model_id=model_id),
+                    response_type=ModelBlockResponse,
+                )
+            )
+            assert response.model_id == model_id
+            assert response.blocked is expected
+            _ = _poll(
+                client.proxy,
+                lambda want=expected: True
+                if _model_blocked_flag(client, model_id) is want
+                else None,
+                f"/model/info never reported blocked={expected} for {model_name!r} "
+                f"after /model/{action}",
+            )
 
 
 class TestTagRoutes:
diff --git a/tests/e2e/mcp/test_mcp_key_access_e2e.py b/tests/e2e/mcp/test_mcp_key_access_e2e.py
index 88ab5666084..68005ae3f6a 100644
--- a/tests/e2e/mcp/test_mcp_key_access_e2e.py
+++ b/tests/e2e/mcp/test_mcp_key_access_e2e.py
@@ -30,6 +30,34 @@ def _key(client: McpClient, resources: ResourceManager, *, mcp_servers: list[str
     return key
 
 
+class TestMcpKeyGrantByAlias:
+    def test_alias_grant_persists_verbatim_and_lists_tools(
+        self,
+        client: McpClient,
+        resources: ResourceManager,
+    ) -> None:
+        """A key granted an MCP server by its alias must store the alias, not the
+        resolved server_id: in a shared-DB multi-region deployment each instance
+        derives a different id for the same config server, so only the alias
+        grants access on every region. The same key must still see the server's
+        tools, proving the alias grant is honored at request time."""
+        server_id = register_datadog_mcp(client, resources)
+        client.await_registered(server_id)
+        alias = next(row.alias for row in client.registered_servers() if row.server_id == server_id)
+        assert alias, f"registered server {server_id} has no alias to grant by"
+
+        key = _key(client, resources, mcp_servers=[alias])
+
+        stored = client.proxy.key_info(key).object_permission
+        assert stored is not None and stored.mcp_servers == [alias], (
+            f"alias grant was rewritten before persisting (expected [{alias!r}]): "
+            f"{stored.mcp_servers if stored else None}. A stored server_id is region-local "
+            f"and breaks the grant on every other instance sharing this database"
+        )
+
+        _ = client.await_tool(key, server_id, SEARCH_LOGS_TOOL)
+
+
 class TestMcpKeyWithoutAccessIsDenied:
     @pytest.mark.covers("mcp.list_tools.api_key.denied_without_permission")
     def test_list_tools_denied_without_permission(
diff --git a/tests/e2e/models.py b/tests/e2e/models.py
index 6d9ccad9a24..79d9e011f7e 100644
--- a/tests/e2e/models.py
+++ b/tests/e2e/models.py
@@ -114,6 +114,7 @@ class KeyInfo(BaseModel):
     budget_id: str | None = None
     litellm_budget_table: LiteLLMBudgetTable | None = None
     budget_limits: list[BudgetWindowState] | None = None
+    object_permission: ObjectPermission | None = None
 
 
 class KeyInfoResponse(BaseModel):
@@ -805,6 +806,7 @@ class LiteLLMParamsBody(BaseModel):
     mock_response: str | None = None
     timeout: float | None = None
     tpm: int | None = None
+    weight: int | None = None
 
 
 ModelMode = Literal["batch", "realtime", "image_generation"]
@@ -819,6 +821,7 @@ class ModelInfoBody(BaseModel):
     mode: ModelMode | None = None
     access_groups: list[str] | None = None
     team_id: str | None = None
+    allowed_fails_policy: dict[str, int] | None = None
 
 
 class ModelNewBody(BaseModel):
diff --git a/tests/e2e/router/reliability_support.py b/tests/e2e/router/reliability_support.py
index e342aa363ca..5822058003c 100644
--- a/tests/e2e/router/reliability_support.py
+++ b/tests/e2e/router/reliability_support.py
@@ -19,6 +19,8 @@ from models import (
     ChatMessage,
     ChatResponse,
     LiteLLMParamsBody,
+    ModelInfoBody,
+    ModelNewBody,
     ReliabilityChatBody,
     RouterSettingsOverride,
 )
@@ -26,6 +28,18 @@ from models import (
 REAL_MODEL = "openai/gpt-5.5"
 REAL_KEY = "os.environ/OPENAI_API_KEY"
 
+# The smallest-context chat model OpenAI still serves (16385 tokens). A prompt
+# past that limit comes back as a real `context_length_exceeded` 400, which is
+# what litellm maps to ContextWindowExceededError.
+SMALL_CONTEXT_MODEL = "openai/gpt-3.5-turbo"
+SMALL_CONTEXT_LIMIT_TOKENS = 16385
+
+
+def oversized_prompt(marker: str) -> str:
+    """A prompt comfortably past SMALL_CONTEXT_MODEL's context limit, so the
+    provider refuses it on length rather than answering a truncated version."""
+    return f"{marker} " + ("token " * (SMALL_CONTEXT_LIMIT_TOKENS + 4000))
+
 
 def create_bad_base_deployment(proxy: ProxyClient, name: str) -> str:
     """Register a deployment pointing at an unreachable base, so every call to it
@@ -40,6 +54,38 @@ def create_timeout_deployment(proxy: ProxyClient, name: str) -> str:
     return proxy.create_model(name, LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001))
 
 
+def create_small_context_deployment(proxy: ProxyClient, name: str) -> str:
+    """Register a deployment on the smallest-context model OpenAI still serves, so an
+    oversized prompt earns a real context-window refusal from the provider."""
+    return proxy.create_model(name, LiteLLMParamsBody(model=SMALL_CONTEXT_MODEL, api_key=REAL_KEY))
+
+
+def create_always_timing_out_deployment(proxy: ProxyClient, name: str) -> str:
+    """The always-picked half of a retry pair: a 1ms deadline the backend always
+    exceeds, all of the model group's shuffle weight, and a cooldown policy that
+    benches it on its first Timeout so the retry cannot land on it again."""
+    return proxy.register_model(
+        ModelNewBody(
+            model_name=name,
+            litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, timeout=0.001, weight=1),
+            model_info=ModelInfoBody(allowed_fails_policy={"TimeoutErrorAllowedFails": 0}),
+        )
+    )
+
+
+def create_zero_weight_backup_deployment(proxy: ProxyClient, name: str) -> str:
+    """The other half of a retry pair: healthy, but weight 0, so the weighted shuffle
+    never opens on it. It is reachable only once its sibling is benched and the
+    weighted pick falls through to a uniform one over what is left."""
+    return proxy.register_model(
+        ModelNewBody(
+            model_name=name,
+            litellm_params=LiteLLMParamsBody(model=REAL_MODEL, api_key=REAL_KEY, weight=0),
+            model_info=ModelInfoBody(),
+        )
+    )
+
+
 def chat_override(
     proxy: ProxyClient,
     key: str,
diff --git a/tests/e2e/router/test_reliability_fallbacks_e2e.py b/tests/e2e/router/test_reliability_fallbacks_e2e.py
index d3ce62f8f95..8cece41ce2d 100644
--- a/tests/e2e/router/test_reliability_fallbacks_e2e.py
+++ b/tests/e2e/router/test_reliability_fallbacks_e2e.py
@@ -9,6 +9,10 @@ in the x-litellm-attempted-fallbacks header. Empty content is accepted only when
 `finish_reason == "length"` and the response billed completion tokens, since
 gpt-5.5 counts reasoning against max_tokens and can consume the whole budget
 before emitting any text; a fallback that produced nothing at all still fails.
+
+The context-window case is a different reroute from a plain failure: the provider
+refuses the prompt on length, and `context_window_fallbacks` is the setting that
+reroutes it, not `fallbacks`.
 """
 
 from __future__ import annotations
@@ -25,8 +29,10 @@ from reliability_support import (
     completion_tokens_of,
     content_of,
     create_bad_base_deployment,
+    create_small_context_deployment,
     create_timeout_deployment,
     finish_reason_of,
+    oversized_prompt,
     reasoning_tokens_of,
 )
 
@@ -82,3 +88,17 @@ class TestReliabilityFallbacks:
             override=RouterSettingsOverride(fallbacks=[{primary: ["gpt-5.5"]}]),
         )
         _assert_served_by_fallback(resp)
+
+    @pytest.mark.covers("reliability.fallback.context_window.routes_to_fallback")
+    def test_context_window_routes_to_fallback(
+        self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
+    ) -> None:
+        primary = f"reliability-ctxfail-{unique_marker()}"
+        model_id = create_small_context_deployment(client.proxy, primary)
+        resources.defer(lambda: client.proxy.delete_model(model_id))
+
+        resp = chat_override(
+            client.proxy, scoped_key, primary, oversized_prompt(unique_marker()),
+            override=RouterSettingsOverride(context_window_fallbacks=[{primary: ["gpt-5.5"]}]),
+        )
+        _assert_served_by_fallback(resp)
diff --git a/tests/e2e/router/test_reliability_retries_e2e.py b/tests/e2e/router/test_reliability_retries_e2e.py
new file mode 100644
index 00000000000..5441412935c
--- /dev/null
+++ b/tests/e2e/router/test_reliability_retries_e2e.py
@@ -0,0 +1,73 @@
+"""Live e2e: a request that fails on its first deployment is retried inside its own
+model group and still comes back a completion.
+
+The model group is a pair: an always-timing-out deployment that holds all of the
+group's shuffle weight, and a healthy backup at weight 0. The weighted pick always
+opens on the timing-out one, its first Timeout benches it (an
+`allowed_fails_policy` of `TimeoutErrorAllowedFails: 0`), and the retry falls
+through to the only deployment left. So the customer sees a completion and the
+proxy reports that it took a retry to get there, with no random first pick in the
+middle of it.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+from complexity_router_client import ComplexityRouterClient
+from e2e_config import unique_marker
+from lifecycle import ResourceManager
+from models import RouterSettingsOverride
+from reliability_support import (
+    chat_override,
+    completion_tokens_of,
+    content_of,
+    create_always_timing_out_deployment,
+    create_zero_weight_backup_deployment,
+    finish_reason_of,
+)
+
+pytestmark = pytest.mark.e2e
+
+
+class TestReliabilityRetries:
+    @pytest.mark.covers("reliability.retry.timeout.succeeds_within_retries")
+    def test_timeout_on_first_deployment_succeeds_on_retry(
+        self, client: ComplexityRouterClient, resources: ResourceManager, scoped_key: str
+    ) -> None:
+        group = f"reliability-retry-{unique_marker()}"
+        timing_out = create_always_timing_out_deployment(client.proxy, group)
+        resources.defer(lambda: client.proxy.delete_model(timing_out))
+        backup = create_zero_weight_backup_deployment(client.proxy, group)
+        resources.defer(lambda: client.proxy.delete_model(backup))
+
+        resp = chat_override(
+            client.proxy,
+            scoped_key,
+            group,
+            f"say hi {unique_marker()}",
+            override=RouterSettingsOverride(num_retries=2),
+        )
+
+        assert resp.status_code == 200, (
+            f"the retry should have landed on the healthy backup, got {resp.status_code}: {resp.body[:300]}"
+        )
+
+        attempted = resp.headers.get("x-litellm-attempted-retries")
+        assert attempted is not None, "response is missing the x-litellm-attempted-retries header"
+        assert int(attempted) >= 1, (
+            f"x-litellm-attempted-retries is {attempted!r}; a 200 with no retry means the request never "
+            "opened on the timing-out deployment, so this proves nothing about retries"
+        )
+
+        content = content_of(resp)
+        finish_reason = finish_reason_of(resp)
+        completion_tokens = completion_tokens_of(resp) or 0
+        assert isinstance(content, str), (
+            f"the retry should have returned a completion body, got content {content!r} (body={resp.body[:300]})"
+        )
+        assert content or (finish_reason == "length" and completion_tokens > 0), (
+            f"the retry returned empty content with finish_reason={finish_reason!r}, "
+            f"completion_tokens={completion_tokens}; empty content is only acceptable when the budget "
+            f"was spent on non-visible reasoning (body={resp.body[:300]})"
+        )
diff --git a/tests/e2e/test_junit_properties.py b/tests/e2e/test_junit_properties.py
new file mode 100644
index 00000000000..02c1413c840
--- /dev/null
+++ b/tests/e2e/test_junit_properties.py
@@ -0,0 +1,131 @@
+"""Harness coverage for the custom JUnit properties.
+
+No proxy and no ``e2e`` marker. Pins the two normalizations that have to agree
+about where a suite file lives -- ``package_from_nodeid`` (strip the suite root)
+and ``source_from_location`` (re-root at it) -- across both ways the suite is
+launched, plus the one-based line offset and the refusal to emit a path that
+escapes the suite. The consumers of these properties are the Loki/Grafana
+rollups and, for ``source``, the status page's per-test links to GitHub.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+import pytest
+from junit_properties import (
+    SUITE_ROOT,
+    attach_result_properties,
+    dedupe_covers,
+    package_from_nodeid,
+    result_properties,
+    source_from_location,
+    suite_parts,
+)
+
+
+def collected_item(request: pytest.FixtureRequest, name: str) -> pytest.Item:
+    """The Item pytest collected for test ``name`` in this file: the real nodeid,
+    location and marker machinery the collection hook reads, as pytest built it."""
+    return next(item for item in request.session.items if item.path == request.path and item.name == name)
+
+
+def repo_root() -> Path | None:
+    """The litellm checkout above this file, or None when there isn't one."""
+    return next((p for p in Path(__file__).resolve().parents if (p / ".git").exists()), None)
+
+
+class TestSuiteParts:
+    @pytest.mark.parametrize(
+        "path",
+        ["logging/test_x.py", "tests/e2e/logging/test_x.py", "./logging/test_x.py", "tests\\e2e\\logging\\test_x.py"],
+    )
+    def test_both_invocation_shapes_collapse_to_the_same_components(self, path: str) -> None:
+        """A repo-root run and a suite-cwd run report the same file differently;
+        every downstream signal has to see one spelling."""
+        assert suite_parts(path) == ("logging", "test_x.py")
+
+    def test_top_level_suite_file_keeps_its_single_component(self) -> None:
+        assert suite_parts("tests/e2e/test_fixture_mode.py") == ("test_fixture_mode.py",)
+
+
+class TestPackageFromNodeid:
+    @pytest.mark.parametrize(
+        ("nodeid", "expected"),
+        [
+            ("logging/test_x.py::TestFoo::test_bar", "logging"),
+            ("tests/e2e/logging/test_x.py::TestFoo::test_bar", "logging"),
+            ("quota_management/spend_tracking/test_x.py::test_bar", "quota_management"),
+            ("test_fixture_mode.py::TestParseFixtureMode::test_known_values_normalize", "root"),
+            ("tests/e2e/test_fixture_mode.py::test_bar", "root"),
+        ],
+    )
+    def test_package_is_the_first_dir_under_the_suite_root(self, nodeid: str, expected: str) -> None:
+        assert package_from_nodeid(nodeid) == expected
+
+
+class TestSourceFromLocation:
+    @pytest.mark.parametrize("path", ["a2a/test_a2a_agent_e2e.py", "tests/e2e/a2a/test_a2a_agent_e2e.py"])
+    def test_path_is_repo_relative_however_pytest_was_started(self, path: str) -> None:
+        assert source_from_location(path, 40) == "tests/e2e/a2a/test_a2a_agent_e2e.py:41"
+
+    def test_line_is_emitted_one_based(self) -> None:
+        """pytest.Item.location counts from 0; editors, tracebacks and GitHub's
+        #L anchor all count from 1, and an off-by-one lands on the decorator."""
+        assert source_from_location("a2a/test_x.py", 0) == "tests/e2e/a2a/test_x.py:1"
+
+    def test_top_level_suite_file_sits_directly_under_the_suite_root(self) -> None:
+        assert source_from_location("test_fixture_mode.py", 39) == "tests/e2e/test_fixture_mode.py:40"
+
+    @pytest.mark.parametrize(
+        ("path", "lineno"),
+        [
+            ("a2a/test_x.py", None),
+            ("/app/e2e/a2a/test_x.py", 40),
+            ("C:\\app\\e2e\\a2a\\test_x.py", 40),
+            ("../conftest.py", 40),
+            ("", 40),
+        ],
+    )
+    def test_nothing_linkable_yields_empty_rather_than_a_guess(self, path: str, lineno: int | None) -> None:
+        """A colon is rejected on two counts: it is how a Windows absolute path
+        arrives, and `path:line` cannot represent one in the path half."""
+        assert source_from_location(path, lineno) == ""
+
+
+class TestResultProperties:
+    def test_every_test_carries_package_covers_and_source(self, request: pytest.FixtureRequest) -> None:
+        """Read off this test's own collected Item, so the nodeid and location are
+        whatever pytest reports for the launch shape in use, and the marker is added
+        at run time so the coverage registry's collect-only pass never sees it."""
+        test = type(self).test_every_test_carries_package_covers_and_source
+        request.applymarker(pytest.mark.covers("LOG-1", "LOG-2"))
+        assert result_properties(collected_item(request, test.__name__)) == (
+            ("package", "root"),
+            ("covers", "LOG-1,LOG-2"),
+            ("source", f"tests/e2e/test_junit_properties.py:{test.__code__.co_firstlineno}"),
+        )
+
+    def test_attach_is_idempotent(self, request: pytest.FixtureRequest) -> None:
+        """Collection can run the hook more than once; a second pass must not
+        double the <property> entries in the report."""
+        item = collected_item(request, type(self).test_attach_is_idempotent.__name__)
+        attach_result_properties(item)
+        attach_result_properties(item)
+        assert [name for name, _ in item.user_properties] == ["package", "covers", "source"]
+
+
+class TestSuiteRoot:
+    def test_suite_root_names_this_file_s_real_home(self) -> None:
+        """SUITE_ROOT is hardcoded because the runner image has no repo to read it
+        from. Where there IS a checkout, prove the constant still points at us --
+        otherwise a moved tests/e2e/ ships links that 404."""
+        root = repo_root()
+        if root is None:
+            pytest.skip("no checkout above this file (the runner image copies tests/e2e/ to /app/e2e)")
+        assert (root / SUITE_ROOT / Path(__file__).name).resolve() == Path(__file__).resolve()
+
+
+class TestDedupeCovers:
+    def test_ids_are_unique_order_preserving_and_non_empty_strings(self) -> None:
+        assert dedupe_covers([("A", "B"), ("B", ""), ("C", 7)]) == ("A", "B", "C")
diff --git a/tests/e2e/ui/constants.ts b/tests/e2e/ui/constants.ts
index 9d918736262..bb33c90ddf3 100644
--- a/tests/e2e/ui/constants.ts
+++ b/tests/e2e/ui/constants.ts
@@ -29,6 +29,7 @@ export const E2E_PROXY_ADMIN_USER_ID = "e2e-proxy-admin";
 export const E2E_PROXY_ADMIN_EMAIL = "admin@test.local";
 export const E2E_INTERNAL_USER_ID = "e2e-internal-user";
 export const E2E_INTERNAL_USER_EMAIL = "internal@test.local";
+export const E2E_TEAM_ADMIN_USER_ID = "e2e-team-admin";
 
 // Key aliases for seeded test keys (match seed.sql)
 export const E2E_UPDATE_LIMITS_KEY_ALIAS = "e2eUpdateLimitsKey";
@@ -46,3 +47,5 @@ export const E2E_TEAM_ORG_ID = "e2e-team-org";
 export const E2E_TEAM_ORG_ALIAS = "E2E Team In Org";
 export const E2E_TEAM_NO_ADMIN_ID = "e2e-team-no-admin";
 export const E2E_TEAM_NO_ADMIN_ALIAS = "E2E Team No Admin";
+export const E2E_TEAM_KEYGEN_ID = "e2e-team-keygen";
+export const E2E_TEAM_KEYGEN_ALIAS = "E2E Team Keygen";
diff --git a/tests/e2e/ui/fixtures/seed.sql b/tests/e2e/ui/fixtures/seed.sql
index a1218633cdb..e77b4a16b3d 100644
--- a/tests/e2e/ui/fixtures/seed.sql
+++ b/tests/e2e/ui/fixtures/seed.sql
@@ -29,7 +29,7 @@ INSERT INTO "LiteLLM_UserTable" ("user_id", "user_email", "user_role", "teams",
 VALUES
   ('e2e-proxy-admin',      'admin@test.local',       'proxy_admin',           '{"e2e-team-crud"}',                  'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
   ('e2e-admin-viewer',     'adminviewer@test.local',  'proxy_admin_viewer',   '{}',                                 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
-  ('e2e-internal-user',    'internal@test.local',     'internal_user',        '{"e2e-team-crud","e2e-team-org"}',   'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
+  ('e2e-internal-user',    'internal@test.local',     'internal_user',        '{"e2e-team-crud","e2e-team-org","e2e-team-keygen"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
   ('e2e-internal-viewer',  'viewer@test.local',       'internal_user_viewer', '{"e2e-team-crud"}',                  'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
   ('e2e-team-admin',       'teamadmin@test.local',    'internal_user',        '{"e2e-team-crud","e2e-team-delete"}', 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
   ('e2e-invitable-user',   'invitable@test.local',    'internal_user',        '{}',                                 'scrypt:MU5CcTAi6rVK1HfY1rVPEWq6r4sxg837eq9dG4n5Q6BhDJ44442+seC6LAhLEAYr'),
@@ -63,6 +63,17 @@ INSERT INTO "LiteLLM_TeamTable" (
    '[{"role":"user","user_id":"e2e-invitable-user"}]'::jsonb,
    '{}'::jsonb, '{"fake-openai-gpt-4"}', 0.0, '{}'::jsonb, '{}'::jsonb, false);
 
+INSERT INTO "LiteLLM_TeamTable" (
+  "team_id", "team_alias", "organization_id", "admins", "members",
+  "members_with_roles", "metadata", "models", "spend", "model_spend", "model_max_budget", "blocked",
+  "team_member_permissions"
+) VALUES
+  ('e2e-team-keygen', 'E2E Team Keygen', NULL,
+   '{}', '{"e2e-internal-user"}',
+   '[{"role":"user","user_id":"e2e-internal-user"}]'::jsonb,
+   '{}'::jsonb, '{"fake-openai-gpt-4"}', 0.0, '{}'::jsonb, '{}'::jsonb, false,
+   '{"/key/generate"}');
+
 -- 6. Team Memberships (only user_id, team_id, spend — no created_at/updated_at)
 INSERT INTO "LiteLLM_TeamMembership" ("user_id", "team_id", "spend")
 VALUES
@@ -72,6 +83,7 @@ VALUES
   ('e2e-removable-member', 'e2e-team-crud',     0.0),
   ('e2e-team-admin',       'e2e-team-delete',   0.0),
   ('e2e-internal-user',    'e2e-team-org',      0.0),
+  ('e2e-internal-user',    'e2e-team-keygen',   0.0),
   ('e2e-invitable-user',   'e2e-team-no-admin', 0.0);
 
 -- 7. Verification Tokens (API Keys)
diff --git a/tests/e2e/ui/helpers/premium.ts b/tests/e2e/ui/helpers/premium.ts
new file mode 100644
index 00000000000..28bc2e58bbc
--- /dev/null
+++ b/tests/e2e/ui/helpers/premium.ts
@@ -0,0 +1,20 @@
+import * as fs from "fs";
+import { ADMIN_STORAGE_PATH } from "../constants";
+
+/**
+ * Whether the proxy under test is licensed, read from the admin session JWT's `premium_user`
+ * claim. That is the same value the dashboard reads to enable premium-gated controls, so it
+ * describes the proxy Playwright is pointed at rather than the environment the runner happens
+ * to have, which are not the same machine when E2E_UI_BASE_URL points elsewhere.
+ */
+export function proxyIsPremium(): boolean {
+  const storage = JSON.parse(fs.readFileSync(ADMIN_STORAGE_PATH, "utf-8")) as {
+    cookies?: { name: string; value: string }[];
+  };
+  const token = storage.cookies?.find((cookie) => cookie.name === "token")?.value;
+  const payload = token?.split(".")[1];
+  if (!payload) {
+    return false;
+  }
+  return JSON.parse(Buffer.from(payload, "base64url").toString("utf-8")).premium_user === true;
+}
diff --git a/tests/e2e/ui/helpers/traffic.ts b/tests/e2e/ui/helpers/traffic.ts
index a2fc9463c94..25eb671fd0e 100644
--- a/tests/e2e/ui/helpers/traffic.ts
+++ b/tests/e2e/ui/helpers/traffic.ts
@@ -4,12 +4,16 @@ import { APIRequestContext, expect } from "@playwright/test";
 export const CHAT_MODEL_A = "fake-openai-gpt-4";
 export const CHAT_MODEL_B = "fake-anthropic-claude";
 
+/** The deployment each of those models routes to, as spend logs and usage breakdowns name it. */
+export const DEPLOYMENT_MODEL_A = "openai/fake-gpt-4";
+export const DEPLOYMENT_MODEL_B = "openai/fake-claude";
+
 /** The only completion text fixtures/mock_llm_server/server.py ever returns. */
 export const MOCK_RESPONSE_TEXT = "This is a mock response.";
 
 export const masterKey = (): string => process.env.LITELLM_MASTER_KEY || "sk-1234";
 
-const rootPath = (): string => process.env.SERVER_ROOT_PATH ?? "";
+export const rootPath = (): string => process.env.SERVER_ROOT_PATH ?? "";
 
 interface ChatOptions {
   model: string;
@@ -84,15 +88,84 @@ export async function waitForSpendLog(
   throw new Error(`spend log for request ${requestId} never appeared (last /spend/logs status ${lastStatus})`);
 }
 
+export async function waitForSpendLogByPrompt(
+  request: APIRequestContext,
+  prompt: string,
+  timeoutMs = 60_000,
+): Promise<string> {
+  const deadline = Date.now() + timeoutMs;
+  let lastStatus = 0;
+  while (Date.now() < deadline) {
+    const res = await request.get(`${rootPath()}/spend/logs`, {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+    });
+    lastStatus = res.status();
+    if (res.ok()) {
+      const rows: { request_id?: string; messages?: unknown; proxy_server_request?: unknown }[] = await res.json();
+      const row = (Array.isArray(rows) ? rows : []).find(
+        (candidate) =>
+          JSON.stringify(candidate.messages ?? "").includes(prompt) ||
+          JSON.stringify(candidate.proxy_server_request ?? "").includes(prompt),
+      );
+      if (row?.request_id) {
+        return row.request_id;
+      }
+    }
+    await new Promise((r) => setTimeout(r, 2_000));
+  }
+  throw new Error(`no spend log row carrying prompt ${prompt} appeared (last /spend/logs status ${lastStatus})`);
+}
+
 const isoDay = (d: Date): string => d.toISOString().slice(0, 10);
 
+interface DailyActivityKey {
+  metrics?: { api_requests?: number };
+}
+
+interface DailyActivityPage {
+  results?: { breakdown?: { api_keys?: Record<string, DailyActivityKey> } }[];
+  metadata?: { total_pages?: number };
+}
+
+const requestsOnPage = (body: DailyActivityPage, keyToken: string): number =>
+  (body.results ?? []).reduce((sum, day) => sum + (day.breakdown?.api_keys?.[keyToken]?.metrics?.api_requests ?? 0), 0);
+
+/**
+ * The route paginates its per-key breakdown. Reading only the first page finds a key while the
+ * database is small and stops finding it once a run has generated more keys than one page holds,
+ * which reads as "the rollup is not running" when the rollup is fine.
+ */
+async function keyRequestsInDailyActivity(
+  request: APIRequestContext,
+  query: string,
+  keyToken: string,
+  page = 1,
+  seen = 0,
+): Promise<number> {
+  const res = await request.get(`${rootPath()}/user/daily/activity?${query}&page=${page}`, {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  if (!res.ok()) {
+    return seen;
+  }
+  const body = (await res.json()) as DailyActivityPage;
+  const total = seen + requestsOnPage(body, keyToken);
+  return page >= (body.metadata?.total_pages ?? 1)
+    ? total
+    : keyRequestsInDailyActivity(request, query, keyToken, page + 1, total);
+}
+
 /**
  * The Usage page reads /user/daily/activity, a rollup written by a background job, and fetches it once
  * on mount. Navigating before the rollup lands leaves a stale render that never refreshes.
+ *
+ * The rollup lands request by request, so waiting only for the key to appear leaves a caller that
+ * sent several requests reading a partial count. Pass `minRequests` to wait for all of them.
  */
 export async function waitForKeyInDailyActivity(
   request: APIRequestContext,
   keyToken: string,
+  minRequests = 1,
   timeoutMs = 120_000,
 ): Promise<void> {
   const now = new Date();
@@ -101,25 +174,17 @@ export async function waitForKeyInDailyActivity(
   const query = `start_date=${isoDay(start)}&end_date=${isoDay(now)}`;
 
   const deadline = Date.now() + timeoutMs;
-  let lastStatus = 0;
-  while (Date.now() < deadline) {
-    const res = await request.get(`${rootPath()}/user/daily/activity?${query}`, {
-      headers: { Authorization: `Bearer ${masterKey()}` },
-    });
-    lastStatus = res.status();
-    if (res.ok()) {
-      const body = await res.json();
-      const seen = (body?.results ?? []).some(
-        (day: { breakdown?: { api_keys?: Record<string, unknown> } }) => keyToken in (day.breakdown?.api_keys ?? {}),
+  for (;;) {
+    const seen = await keyRequestsInDailyActivity(request, query, keyToken);
+    if (seen >= minRequests) {
+      return;
+    }
+    if (Date.now() >= deadline) {
+      throw new Error(
+        `key ${keyToken} reached ${seen} of ${minRequests} requests in /user/daily/activity across every page; ` +
+          "the daily spend rollup may not be running",
       );
-      if (seen) {
-        return;
-      }
     }
     await new Promise((r) => setTimeout(r, 3_000));
   }
-  throw new Error(
-    `key ${keyToken} never appeared in /user/daily/activity (last status ${lastStatus}); ` +
-      "the daily spend rollup may not be running",
-  );
 }
diff --git a/tests/e2e/ui/tests/budgets/budgets.spec.ts b/tests/e2e/ui/tests/budgets/budgets.spec.ts
new file mode 100644
index 00000000000..1ad1e488d25
--- /dev/null
+++ b/tests/e2e/ui/tests/budgets/budgets.spec.ts
@@ -0,0 +1,133 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { masterKey } from "../../helpers/traffic";
+
+interface StoredBudget {
+  budget_id: string;
+  max_budget: number | null;
+  tpm_limit: number | null;
+  rpm_limit: number | null;
+  budget_duration: string | null;
+}
+
+/** A different route from the one the table renders from, so a row that only lives in its cache fails here. */
+async function findBudget(page: PlaywrightPage, budgetId: string): Promise<StoredBudget | undefined> {
+  const res = await page.request.get("/budget/list", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  expect(res.ok(), `GET /budget/list (${res.status()})`).toBe(true);
+  return ((await res.json()) as StoredBudget[]).find((row) => row.budget_id === budgetId);
+}
+
+async function createBudgetViaApi(page: PlaywrightPage, budget: Partial<StoredBudget>): Promise<void> {
+  const res = await page.request.post("/budget/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: budget,
+  });
+  expect(res.ok(), `POST /budget/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+}
+
+async function searchForBudget(page: PlaywrightPage, budgetId: string): Promise<void> {
+  await page.getByPlaceholder("Search by budget ID").fill(budgetId);
+}
+
+test.describe("Budgets", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Create a budget with rate limits and a spend cap", async ({ page }) => {
+    const budgetId = `e2e-budget-create-${Date.now()}`;
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await page.getByRole("button", { name: "Create Budget" }).click();
+
+    const modal = page.getByRole("dialog", { name: "Create Budget" });
+    await expect(modal).toBeVisible({ timeout: 10_000 });
+
+    await modal.getByRole("textbox", { name: "Budget ID" }).fill(budgetId);
+    await modal.getByRole("spinbutton", { name: "Max Tokens per minute" }).fill("5000");
+    await modal.getByRole("spinbutton", { name: "Max Requests per minute" }).fill("60");
+
+    await modal.getByRole("button", { name: "Optional Settings" }).click();
+    await modal.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("25.5");
+    await modal.getByRole("combobox", { name: "Reset Budget" }).click();
+    await page.getByRole("option", { name: "weekly" }).click();
+
+    await modal.getByRole("button", { name: "Create Budget" }).click();
+    await expect(modal).not.toBeVisible({ timeout: 10_000 });
+
+    await searchForBudget(page, budgetId);
+    const row = page.getByRole("row").filter({ hasText: budgetId });
+    await expect(row).toBeVisible({ timeout: 10_000 });
+    await expect(row).toContainText("$25.50");
+
+    const stored = await findBudget(page, budgetId);
+    expect(stored, `budget ${budgetId} readable from /budget/list`).toBeTruthy();
+    expect(stored?.max_budget, "spend cap persisted").toBe(25.5);
+    expect(stored?.tpm_limit, "TPM limit persisted").toBe(5000);
+    expect(stored?.rpm_limit, "RPM limit persisted").toBe(60);
+    expect(stored?.budget_duration, "reset window persisted").toBe("7d");
+  });
+
+  test("Raising a budget's spend cap leaves its rate limits alone", async ({ page }) => {
+    const budgetId = `e2e-budget-edit-${Date.now()}`;
+    await createBudgetViaApi(page, { budget_id: budgetId, max_budget: 10, tpm_limit: 1000, rpm_limit: 20 });
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await searchForBudget(page, budgetId);
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toBeVisible({ timeout: 10_000 });
+
+    await page.getByTestId(`budget-actions-${budgetId}`).click();
+    await page.getByTestId("budget-action-edit").click();
+
+    const modal = page.getByRole("dialog", { name: "Edit Budget" });
+    await expect(modal).toBeVisible({ timeout: 10_000 });
+
+    await modal.getByRole("button", { name: "Optional Settings" }).click();
+    await modal.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("99");
+    await modal.getByRole("button", { name: "Save", exact: true }).click();
+    await expect(modal).not.toBeVisible({ timeout: 10_000 });
+
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toContainText("$99.00", { timeout: 10_000 });
+
+    // Not hypothetical: the edit form posts the whole budget, so a field it fails to
+    // seed from the existing row goes to the server as null and silently clears.
+    const stored = await findBudget(page, budgetId);
+    expect(stored?.max_budget, "spend cap raised").toBe(99);
+    expect(stored?.tpm_limit, "TPM limit untouched by a spend-cap edit").toBe(1000);
+    expect(stored?.rpm_limit, "RPM limit untouched by a spend-cap edit").toBe(20);
+  });
+
+  test("Delete a budget", async ({ page }) => {
+    const budgetId = `e2e-budget-delete-${Date.now()}`;
+    await createBudgetViaApi(page, { budget_id: budgetId, max_budget: 5 });
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await searchForBudget(page, budgetId);
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toBeVisible({ timeout: 10_000 });
+
+    await page.getByTestId(`budget-actions-${budgetId}`).click();
+    await page.getByTestId("budget-action-delete").click();
+
+    const modal = page.getByRole("dialog", { name: "Delete Budget?" });
+    await expect(modal).toBeVisible({ timeout: 5_000 });
+    await modal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toHaveCount(0, { timeout: 10_000 });
+
+    // The row disappearing is a cache invalidation; the budget is gone when the route stops serving it.
+    await expect
+      .poll(async () => await findBudget(page, budgetId), {
+        message: `budget ${budgetId} still readable from /budget/list after delete`,
+        timeout: 15_000,
+      })
+      .toBeUndefined();
+  });
+});
diff --git a/tests/e2e/ui/tests/guardrails/guardrails.spec.ts b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts
new file mode 100644
index 00000000000..1e43c7a2b22
--- /dev/null
+++ b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts
@@ -0,0 +1,283 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH, E2E_TEAM_NO_ADMIN_ID } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+
+interface StoredGuardrail {
+  guardrail_id: string;
+  guardrail_name: string | null;
+}
+
+async function listGuardrails(page: PlaywrightPage): Promise<StoredGuardrail[]> {
+  const res = await page.request.get("/v2/guardrails/list", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  expect(res.ok(), `GET /v2/guardrails/list (${res.status()})`).toBe(true);
+  return ((await res.json()) as { guardrails: StoredGuardrail[] }).guardrails;
+}
+
+async function findGuardrail(page: PlaywrightPage, name: string): Promise<StoredGuardrail | undefined> {
+  return (await listGuardrails(page)).find((row) => row.guardrail_name === name);
+}
+
+const createdGuardrails: string[] = [];
+
+async function createKeywordGuardrailViaApi(page: PlaywrightPage, name: string, keyword: string): Promise<string> {
+  const res = await page.request.post("/guardrails", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: {
+      guardrail: {
+        guardrail_name: name,
+        litellm_params: {
+          guardrail: "litellm_content_filter",
+          mode: "pre_call",
+          default_on: false,
+          blocked_words: [{ keyword, action: "BLOCK" }],
+        },
+      },
+    },
+  });
+  expect(res.ok(), `POST /guardrails failed (${res.status()}): ${await res.text()}`).toBe(true);
+  createdGuardrails.push(name);
+  const guardrail = await findGuardrail(page, name);
+  expect(guardrail?.guardrail_id, `guardrail ${name} has an id`).toBeTruthy();
+  return guardrail!.guardrail_id;
+}
+
+async function openKeywordsStep(page: PlaywrightPage, name: string) {
+  await page.getByRole("button", { name: "Add New Guardrail" }).click();
+  await page.getByRole("menuitem", { name: "Add Provider Guardrail" }).click();
+
+  const wizard = page.getByRole("dialog", { name: "Create guardrail" });
+  await expect(wizard).toBeVisible({ timeout: 10_000 });
+
+  await wizard.getByRole("textbox", { name: "Guardrail Name" }).fill(name);
+  await wizard.getByRole("combobox", { name: "Guardrail Provider" }).click();
+  // The content filter runs inside the proxy, so this is the one provider a test can
+  // configure end to end without standing up a third-party moderation service.
+  await page.getByRole("option", { name: /LiteLLM Content Filter/ }).click();
+
+  for (const step of ["Topics", "Patterns", "Keywords"]) {
+    await wizard.getByRole("button", { name: "Next" }).click();
+    await expect(wizard).toContainText(step, { timeout: 10_000 });
+  }
+  return wizard;
+}
+
+test.describe("Guardrails", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test.afterEach(async ({ page }) => {
+    // Guardrails live in the database and show up in the table and the playground list, so a run
+    // that leaves them behind changes what the next run sees.
+    for (const name of createdGuardrails.splice(0)) {
+      const guardrail = await findGuardrail(page, name);
+      if (guardrail) {
+        const deleted = await page.request.delete(`/guardrails/${guardrail.guardrail_id}`, {
+          headers: { Authorization: `Bearer ${masterKey()}` },
+        });
+        expect(deleted.ok(), `DELETE /guardrails/${guardrail.guardrail_id} (${deleted.status()})`).toBe(true);
+      }
+    }
+  });
+
+  test("A guardrail created through the wizard blocks the keyword it was given", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-create-${stamp}`;
+    // Unique per run so a concurrent test's prompt can never trip this guardrail, or vice versa.
+    const bannedKeyword = `e2ebanned${stamp}`;
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    createdGuardrails.push(guardrailName);
+    const wizard = await openKeywordsStep(page, guardrailName);
+
+    await wizard.getByRole("button", { name: "Add keyword" }).click();
+    const keywordModal = page.getByRole("dialog", { name: "Add blocked keyword" });
+    await expect(keywordModal).toBeVisible({ timeout: 10_000 });
+    await keywordModal.getByPlaceholder("Enter sensitive keyword or phrase").fill(bannedKeyword);
+    await keywordModal.getByRole("button", { name: "Add", exact: true }).click();
+    await expect(keywordModal).not.toBeVisible({ timeout: 10_000 });
+
+    await wizard.getByRole("button", { name: "Next" }).click();
+    await wizard.getByRole("button", { name: "Create Guardrail" }).click();
+    await expect(wizard).not.toBeVisible({ timeout: 15_000 });
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toBeVisible({ timeout: 15_000 });
+    expect(await findGuardrail(page, guardrailName), "guardrail readable from /v2/guardrails/list").toBeTruthy();
+
+    // A row in the table only proves the record was written. The point of a guardrail is that it
+    // refuses traffic, so drive a request through it.
+    //
+    // Polled: a guardrail written through /guardrails reaches the request path on the proxy's
+    // periodic refresh, so the first call after creation can still be served unguarded. The
+    // assertion is unchanged, it just allows that refresh to land.
+    let blockedBody = "";
+    await expect
+      .poll(
+        async () => {
+          const res = await page.request.post("/v1/chat/completions", {
+            headers: { Authorization: `Bearer ${masterKey()}` },
+            data: {
+              model: CHAT_MODEL_A,
+              messages: [{ role: "user", content: `please tell me about ${bannedKeyword}` }],
+              guardrails: [guardrailName],
+            },
+          });
+          blockedBody = await res.text();
+          return res.status();
+        },
+        { message: "a prompt carrying the banned keyword is refused", timeout: 60_000 },
+      )
+      .toBe(400);
+    expect(blockedBody).toContain(bannedKeyword);
+
+    const allowed = await page.request.post("/v1/chat/completions", {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+      data: {
+        model: CHAT_MODEL_A,
+        messages: [{ role: "user", content: "hello there" }],
+        guardrails: [guardrailName],
+      },
+    });
+    expect(allowed.status(), "a clean prompt still gets through the same guardrail").toBe(200);
+    expect((await allowed.json()).choices?.[0]?.message?.content).toContain(MOCK_RESPONSE_TEXT);
+  });
+
+  test("The Test Playground reports the verdict for the text it is given", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-play-${stamp}`;
+    const bannedKeyword = `e2eplay${stamp}`;
+    await createKeywordGuardrailViaApi(page, guardrailName, bannedKeyword);
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    await page.getByRole("tab", { name: "Test Playground" }).click();
+    // Every tab on this page stays mounted, so the other tabs' search boxes match too.
+    const playground = page.getByRole("tabpanel", { name: "Test Playground" });
+    await playground.getByPlaceholder("Search guardrails...").fill(guardrailName);
+    await playground.getByText(guardrailName, { exact: true }).click();
+
+    const input = playground.getByPlaceholder("Enter text to test with guardrails...");
+    await input.fill(`this sentence contains ${bannedKeyword}`);
+    await playground.getByRole("button", { name: /^Test 1 guardrail$/ }).click();
+
+    // The playground is where an admin checks a guardrail before rolling it out, so the
+    // verdict it prints has to be the one the gateway would give.
+    await expect(playground.getByText(`${guardrailName} - Error`)).toBeVisible({ timeout: 20_000 });
+    await expect(playground.getByText(new RegExp(`Content blocked.*${bannedKeyword}`))).toBeVisible({
+      timeout: 10_000,
+    });
+
+    await input.fill("this sentence is perfectly ordinary");
+    await playground.getByRole("button", { name: /^Test 1 guardrail$/ }).click();
+
+    await expect(playground.getByText(`${guardrailName} - Error`)).toHaveCount(0, { timeout: 20_000 });
+    await expect(playground.getByText("this sentence is perfectly ordinary").last()).toBeVisible({ timeout: 10_000 });
+  });
+
+  test("Delete a guardrail", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-delete-${stamp}`;
+    const guardrailId = await createKeywordGuardrailViaApi(page, guardrailName, `e2edelete${stamp}`);
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toBeVisible({ timeout: 15_000 });
+
+    await page.getByTestId(`guardrail-actions-${guardrailId}`).click();
+    await page.getByTestId("guardrail-action-delete").click();
+
+    const modal = page.getByRole("dialog");
+    await expect(modal).toBeVisible({ timeout: 5_000 });
+    await modal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toHaveCount(0, { timeout: 15_000 });
+
+    // The RC checklist deletes then reloads, because a row vanishing from the table has
+    // fooled us before; assert against the route the reload would read.
+    await expect
+      .poll(async () => await findGuardrail(page, guardrailName), {
+        message: `guardrail ${guardrailName} still listed after delete`,
+        timeout: 15_000,
+      })
+      .toBeUndefined();
+  });
+
+  test("Create a Presidio guardrail, see it in team settings, and delete it", async ({ page }) => {
+    const guardrailName = `e2e-presidio-${Date.now()}`;
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    await page.getByRole("button", { name: /Add New Guardrail/i }).click();
+    await page.getByRole("menuitem", { name: "Add Provider Guardrail" }).click();
+
+    const dialog = page.getByRole("dialog", { name: "Create guardrail" });
+    await expect(dialog).toBeVisible({ timeout: 10_000 });
+
+    await dialog.getByLabel("Guardrail Name").fill(guardrailName);
+
+    const providerSelect = dialog.getByRole("combobox", { name: "Guardrail Provider" });
+    await providerSelect.click();
+    await providerSelect.fill("Presidio");
+    await page.getByRole("option", { name: "Presidio PII" }).click();
+
+    await dialog.getByLabel("Mode", { exact: true }).click();
+    await page.keyboard.type("pre_call");
+    await expect(page.getByRole("option", { name: "pre_call" })).toBeAttached({ timeout: 5_000 });
+    await page.keyboard.press("Enter");
+    await expect(dialog.getByText("pre_call", { exact: true })).toBeVisible({ timeout: 5_000 });
+    await dialog.getByText("Create guardrail", { exact: true }).click();
+
+    await dialog.getByLabel("presidio_analyzer_api_base").fill("http://127.0.0.1:9999");
+    await expect(dialog.getByLabel("presidio_analyzer_api_base")).toHaveValue("http://127.0.0.1:9999");
+    await dialog.getByLabel("presidio_anonymizer_api_base").fill("http://127.0.0.1:9999");
+    await expect(dialog.getByLabel("presidio_anonymizer_api_base")).toHaveValue("http://127.0.0.1:9999");
+
+    await dialog.getByRole("button", { name: "Next" }).click();
+    await expect(dialog.getByText("Configure PII Protection")).toBeVisible({ timeout: 10_000 });
+    await dialog.getByRole("button", { name: "Select All & Mask" }).click();
+
+    await dialog.getByRole("button", { name: "Create Guardrail" }).click();
+    await expect(page.getByText("Guardrail created successfully").first()).toBeVisible({ timeout: 15_000 });
+
+    const row = page.getByRole("row").filter({ hasText: guardrailName });
+    await expect(row).toHaveCount(1, { timeout: 15_000 });
+
+    await navigateToPage(page, Page.Teams);
+    await dismissFeedbackPopup(page);
+    await clickTeamId(page, E2E_TEAM_NO_ADMIN_ID);
+    await page.getByRole("tab", { name: "Settings" }).click();
+    await page.getByRole("button", { name: "Edit Settings" }).click();
+
+    const guardrailsSelect = page.getByRole("combobox", { name: "Select guardrails" });
+    await expect(guardrailsSelect).toBeVisible({ timeout: 10_000 });
+    await guardrailsSelect.click();
+    await guardrailsSelect.fill(guardrailName);
+    await expect(page.getByRole("option", { name: guardrailName })).toBeVisible({ timeout: 10_000 });
+    await page.keyboard.press("Escape");
+
+    await navigateToPage(page, Page.Guardrails);
+    await expect(row).toHaveCount(1, { timeout: 15_000 });
+    await row.getByRole("button", { name: "Open guardrail actions" }).click();
+    await page.getByRole("menuitem", { name: "Delete" }).click();
+
+    const deleteModal = page.getByRole("dialog", { name: "Delete Guardrail" });
+    await expect(deleteModal).toBeVisible({ timeout: 5_000 });
+    await deleteModal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByText(`Guardrail "${guardrailName}" deleted successfully`)).toBeVisible({
+      timeout: 10_000,
+    });
+    await expect(row).toHaveCount(0, { timeout: 15_000 });
+
+    await page.reload();
+    await expect(page.getByRole("button", { name: /Add New Guardrail/i })).toBeVisible({ timeout: 20_000 });
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toHaveCount(0);
+  });
+});
diff --git a/tests/e2e/ui/tests/internal-user/internalUser.spec.ts b/tests/e2e/ui/tests/internal-user/internalUser.spec.ts
index b8424b06115..f392c5104da 100644
--- a/tests/e2e/ui/tests/internal-user/internalUser.spec.ts
+++ b/tests/e2e/ui/tests/internal-user/internalUser.spec.ts
@@ -3,10 +3,13 @@ import {
   E2E_INTERNAL_USER_KEY_ALIAS,
   E2E_TEAM_CRUD_ALIAS,
   E2E_TEAM_CRUD_ID,
+  E2E_TEAM_KEYGEN_ALIAS,
   INTERNAL_USER_STORAGE_PATH,
 } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, clickTeamId } from "../../helpers/navigation";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+import { keySourceSelect, onlyVisible, openPlayground, selectModel, sendMessage } from "../../helpers/playground";
 
 test.describe("Internal User", () => {
   test.use({ storageState: INTERNAL_USER_STORAGE_PATH });
@@ -22,8 +25,7 @@ test.describe("Internal User", () => {
     const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
     await teamSelect.click();
     await page.keyboard.type(E2E_TEAM_CRUD_ALIAS);
-    const dropdown = page.locator('[data-slot="combobox-content"]:visible');
-    await expect(dropdown.getByText(E2E_TEAM_CRUD_ALIAS).first()).toBeVisible({ timeout: 5_000 });
+    await expect(page.getByRole("option", { name: E2E_TEAM_CRUD_ALIAS }).first()).toBeVisible({ timeout: 5_000 });
   });
 
   test("Team info page omits the Settings tab for non-admin members", async ({ page }) => {
@@ -38,17 +40,66 @@ test.describe("Internal User", () => {
     await expect(page.getByRole("tab", { name: "Members" })).not.toBeVisible();
   });
 
+  test("Internal user creates a team key and uses it in the Playground", async ({ page, request }) => {
+    const suffix = Date.now();
+    const auth = { Authorization: `Bearer ${masterKey()}` };
+
+    await navigateToPage(page, Page.ApiKeys);
+
+    await page.getByRole("button", { name: /Create New Key/i }).click();
+    await expect(page.getByText("Key Ownership")).toBeVisible({ timeout: 10_000 });
+
+    await expect(page.getByRole("radio", { name: "You", exact: true })).toBeVisible({ timeout: 10_000 });
+    await expect(page.getByRole("radio", { name: "Another User" })).toHaveCount(0);
+
+    const keyName = `e2e-internal-team-key-${suffix}`;
+    await page.getByLabel(/Key Name/).fill(keyName);
+
+    const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
+    await teamSelect.click();
+    await page.keyboard.type(E2E_TEAM_KEYGEN_ALIAS);
+    await page.getByRole("option", { name: E2E_TEAM_KEYGEN_ALIAS }).first().click();
+
+    await page.getByRole("combobox", { name: "Select models" }).click();
+    await page.getByRole("option", { name: "All Team Models", exact: true }).click();
+    await page.keyboard.press("Escape");
+
+    await page.getByRole("button", { name: "Create Key", exact: true }).click();
+
+    await expect(page.getByText("Save your Key")).toBeVisible({ timeout: 10_000 });
+    const apiKey = (await page.getByRole("dialog", { name: "Save your Key" }).locator("pre").innerText()).trim();
+    expect(apiKey).toMatch(/^sk-/);
+    await page.keyboard.press("Escape");
+
+    try {
+      await openPlayground(page);
+      await keySourceSelect(page).click();
+      await onlyVisible(page.getByRole("option", { name: "Virtual Key" })).click({ timeout: 15_000 });
+
+      const keyInput = onlyVisible(page.getByPlaceholder("Enter custom Virtual Key"));
+      await expect(keyInput).toBeVisible({ timeout: 10_000 });
+      await keyInput.fill(apiKey);
+
+      await selectModel(page, CHAT_MODEL_A);
+      await sendMessage(page, `internal user team key ping ${keyName}`);
+
+      await expect(page.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 60_000 });
+    } finally {
+      await request.post("/key/delete", { headers: auth, data: { keys: [apiKey] } });
+    }
+  });
+
   test("Virtual Keys page does not surface litellm-dashboard team keys", async ({ page }) => {
     await navigateToPage(page, Page.ApiKeys);
 
     // Anchor on the user's own seeded key so the absence check below cannot
     // pass vacuously against an empty table.
-    await expect(page.locator("table tbody").getByText(E2E_INTERNAL_USER_KEY_ALIAS).first()).toBeVisible({
+    await expect(page.getByRole("row").filter({ hasText: E2E_INTERNAL_USER_KEY_ALIAS }).first()).toBeVisible({
       timeout: 10_000,
     });
 
     // The litellm-dashboard team is the proxy's internal bookkeeping team —
     // its keys must never leak into an internal user's Virtual Keys table.
-    await expect(page.locator("table tbody").getByText("litellm-dashboard")).toHaveCount(0);
+    await expect(page.getByRole("row").filter({ hasText: "litellm-dashboard" })).toHaveCount(0);
   });
 });
diff --git a/tests/e2e/ui/tests/internal-user/internalUserNoTeam.spec.ts b/tests/e2e/ui/tests/internal-user/internalUserNoTeam.spec.ts
index c44305187f1..653e096b713 100644
--- a/tests/e2e/ui/tests/internal-user/internalUserNoTeam.spec.ts
+++ b/tests/e2e/ui/tests/internal-user/internalUserNoTeam.spec.ts
@@ -30,16 +30,13 @@ test.describe("Internal User with no team memberships", () => {
     const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
     await teamSelect.click();
 
-    const dropdown = page.locator('[data-slot="combobox-content"]:visible').first();
-    await expect(dropdown).toBeVisible({ timeout: 5_000 });
-
     // Wait for the settled-empty state, not a transient one. The dropdown shows
     // "Loading teams…" while teams load and only swaps in "No teams found" once
     // the request resolves with nothing (team_dropdown.tsx passes both copies to
     // PaginatedSearchSelect). Asserting on it means a regression where teams DO
     // load for this user fails here instead of racing a one-shot count() against
     // an in-flight request.
-    await expect(dropdown.getByText("No teams found")).toBeVisible({ timeout: 10_000 });
-    await expect(dropdown.getByRole("option")).toHaveCount(0);
+    await expect(page.getByText("No teams found")).toBeVisible({ timeout: 10_000 });
+    await expect(page.getByRole("option")).toHaveCount(0);
   });
 });
diff --git a/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts b/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts
index 68319154554..62681e9ceb5 100644
--- a/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts
+++ b/tests/e2e/ui/tests/internal-user/internalUserWithTeams.spec.ts
@@ -1,14 +1,13 @@
 import { test, expect } from "@playwright/test";
-import { INTERNAL_USER_STORAGE_PATH, E2E_TEAM_CRUD_ALIAS, E2E_TEAM_ORG_ALIAS } from "../../constants";
+import {
+  INTERNAL_USER_STORAGE_PATH,
+  E2E_TEAM_CRUD_ALIAS,
+  E2E_TEAM_KEYGEN_ALIAS,
+  E2E_TEAM_ORG_ALIAS,
+} from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage } from "../../helpers/navigation";
 
-/**
- * Differential partner to internalUserNoTeam.spec.ts: the seeded
- * e2e-internal-user belongs to exactly two teams, so the Create Key dropdown
- * must list both. Without this, the no-team spec's "zero options" assertion
- * would still pass against a bug that empties the dropdown for everyone.
- */
 test.describe("Internal User with team memberships", () => {
   test.use({ storageState: INTERNAL_USER_STORAGE_PATH });
 
@@ -21,13 +20,9 @@ test.describe("Internal User with team memberships", () => {
     const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
     await teamSelect.click();
 
-    const dropdown = page.locator('[data-slot="combobox-content"]:visible').first();
-    await expect(dropdown).toBeVisible({ timeout: 5_000 });
-
-    // Both seeded memberships render, and nothing else does — proving the
-    // dropdown is scoped to the user's teams rather than empty or unfiltered.
-    await expect(dropdown.getByText(E2E_TEAM_CRUD_ALIAS, { exact: true })).toBeVisible({ timeout: 10_000 });
-    await expect(dropdown.getByText(E2E_TEAM_ORG_ALIAS, { exact: true })).toBeVisible();
-    await expect(dropdown.getByRole("option")).toHaveCount(2);
+    await expect(page.getByRole("option", { name: E2E_TEAM_CRUD_ALIAS })).toBeVisible({ timeout: 10_000 });
+    await expect(page.getByRole("option", { name: E2E_TEAM_ORG_ALIAS })).toBeVisible();
+    await expect(page.getByRole("option", { name: E2E_TEAM_KEYGEN_ALIAS })).toBeVisible();
+    await expect(page.getByRole("option")).toHaveCount(3);
   });
 });
diff --git a/tests/e2e/ui/tests/internal-viewer/internalViewer.spec.ts b/tests/e2e/ui/tests/internal-viewer/internalViewer.spec.ts
index 4de86c46398..dd40976341d 100644
--- a/tests/e2e/ui/tests/internal-viewer/internalViewer.spec.ts
+++ b/tests/e2e/ui/tests/internal-viewer/internalViewer.spec.ts
@@ -59,9 +59,9 @@ test.describe("Internal Viewer", () => {
     await expect(page.getByRole("button", { name: /Create New Key/i })).toHaveCount(0);
 
     // Open the viewer's own key info page
-    const keyRow = page.locator("tr", { hasText: E2E_VIEWER_KEY_ALIAS });
+    const keyRow = page.getByRole("row").filter({ hasText: E2E_VIEWER_KEY_ALIAS });
     await expect(keyRow).toBeVisible({ timeout: 10_000 });
-    await keyRow.locator("button").first().click();
+    await keyRow.getByRole("button", { name: E2E_VIEWER_KEY_ALIAS }).click();
     await expect(page.getByText("Back to Keys")).toBeVisible({ timeout: 10_000 });
 
     // None of the destructive / mutating actions should render
diff --git a/tests/e2e/ui/tests/logs/logs.spec.ts b/tests/e2e/ui/tests/logs/logs.spec.ts
index 56a3d0f0109..2748c91395f 100644
--- a/tests/e2e/ui/tests/logs/logs.spec.ts
+++ b/tests/e2e/ui/tests/logs/logs.spec.ts
@@ -2,7 +2,14 @@ import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwr
 import { ADMIN_STORAGE_PATH } from "../../constants";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
-import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, sendChatCompletion, waitForSpendLog } from "../../helpers/traffic";
+import {
+  CHAT_MODEL_A,
+  MOCK_RESPONSE_TEXT,
+  sendChatCompletion,
+  waitForSpendLog,
+  waitForSpendLogByPrompt,
+} from "../../helpers/traffic";
+import { openPlayground, selectModel, sendMessage } from "../../helpers/playground";
 
 /**
  * Anchored to traffic this spec generates itself, with a unique prompt and end user per run, so it
@@ -11,12 +18,11 @@ import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, sendChatCompletion, waitForSpendLog }
 
 const uniqueSuffix = (): string => `${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
 
-/**
- * Walking up from the label is the only stable handle: the header carries no role, test id or class,
- * and its copy button is icon-only with a hover-only tooltip.
- */
-const sectionHeader = (drawer: Locator, label: "Input" | "Output"): Locator =>
-  drawer.getByText(label, { exact: true }).locator("xpath=../../..");
+const sectionToggle = (drawer: Locator, label: "Input" | "Output"): Locator =>
+  drawer.getByRole("button", { name: new RegExp(`^${label}\\b`) });
+
+const sectionCopy = (drawer: Locator, label: "Input" | "Output"): Locator =>
+  drawer.getByRole("button", { name: `Copy ${label.toLowerCase()}` });
 
 /** Every tab stays mounted, so the DOM holds four tables at once; scope to the visible one. */
 const requestLogsRows = (page: PlaywrightPage): Locator =>
@@ -47,6 +53,23 @@ test.describe("Logs page", () => {
     permissions: ["clipboard-read", "clipboard-write"],
   });
 
+  test("a chat sent from the Playground lands in Logs with its content", async ({ page, request }) => {
+    const prompt = `logs-playground-prompt-${uniqueSuffix()}`;
+    await openPlayground(page);
+    await selectModel(page, CHAT_MODEL_A);
+    await sendMessage(page, prompt);
+    await expect(page.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 60_000 });
+
+    const requestId = await waitForSpendLogByPrompt(request, prompt);
+
+    const row = await openLogsForRequest(page, requestId);
+    await row.click();
+    const drawer = page.getByRole("dialog").first();
+    await expect(drawer.getByText("Request & Response")).toBeVisible({ timeout: 20_000 });
+    await expect(drawer.getByText(prompt, { exact: false }).first()).toBeVisible({ timeout: 20_000 });
+    await expect(drawer.getByText(MOCK_RESPONSE_TEXT, { exact: false }).first()).toBeVisible({ timeout: 20_000 });
+  });
+
   test("a served request expands to its request and response", async ({ page, request }) => {
     const prompt = `logs-detail-prompt-${uniqueSuffix()}`;
     const requestId = await sendChatCompletion(request, {
@@ -95,14 +118,14 @@ test.describe("Logs page", () => {
     await expect(drawer).toBeVisible({ timeout: 20_000 });
 
     // Copy request: the Input card's copy button puts the prompt on the clipboard.
-    await sectionHeader(drawer, "Input").getByRole("button").click();
+    await sectionCopy(drawer, "Input").click();
     await expect(page.getByText("Input copied")).toBeVisible({
       timeout: 10_000,
     });
     expect(await page.evaluate(() => navigator.clipboard.readText())).toContain(prompt);
 
     // Copy response: the Output card's copy button puts the completion on it.
-    await sectionHeader(drawer, "Output").getByRole("button").click();
+    await sectionCopy(drawer, "Output").click();
     await expect(page.getByText("Output copied")).toBeVisible({
       timeout: 10_000,
     });
@@ -125,24 +148,15 @@ test.describe("Logs page", () => {
       timeout: 20_000,
     });
 
-    // The body collapses via `max-height: 0; overflow: hidden`, which zeroes its own bounding
-    // box, so the wrapper reads as hidden while the clipped text node inside it does not.
-    const header = sectionHeader(drawer, "Input");
-    const body = header.locator("xpath=following-sibling::div[1]");
-    await expect(header.locator(".lucide-chevron-up")).toBeVisible();
-    await expect(body).toBeVisible();
+    const toggle = sectionToggle(drawer, "Input");
+    await expect(toggle).toHaveAttribute("aria-expanded", "true");
+    await expect(drawer.getByText(prompt, { exact: false })).toBeVisible();
 
-    await header.click();
-    await expect(header.locator(".lucide-chevron-down")).toBeVisible({
-      timeout: 10_000,
-    });
-    await expect(body).toBeHidden({ timeout: 10_000 });
+    await toggle.click();
+    await expect(toggle).toHaveAttribute("aria-expanded", "false", { timeout: 10_000 });
 
-    await header.click();
-    await expect(header.locator(".lucide-chevron-up")).toBeVisible({
-      timeout: 10_000,
-    });
-    await expect(body).toBeVisible({ timeout: 10_000 });
+    await toggle.click();
+    await expect(toggle).toHaveAttribute("aria-expanded", "true", { timeout: 10_000 });
     await expect(drawer.getByText(prompt, { exact: false })).toBeVisible({
       timeout: 10_000,
     });
diff --git a/tests/e2e/ui/tests/logs/logsFilters.spec.ts b/tests/e2e/ui/tests/logs/logsFilters.spec.ts
new file mode 100644
index 00000000000..7174f339296
--- /dev/null
+++ b/tests/e2e/ui/tests/logs/logsFilters.spec.ts
@@ -0,0 +1,152 @@
+import { test, expect, type APIRequestContext, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { Page } from "../../fixtures/pages";
+import {
+  CHAT_MODEL_A,
+  CHAT_MODEL_B,
+  createVirtualKey,
+  sendChatCompletion,
+  waitForSpendLog,
+} from "../../helpers/traffic";
+
+/**
+ * Every test mints its own key and asserts against request ids it generated, so a filter that
+ * quietly does nothing shows up as the other key's row still being on screen, and concurrent
+ * specs' traffic cannot decide the outcome.
+ */
+
+const uniqueSuffix = (): string => `${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
+
+/** Every tab stays mounted, so the DOM holds four tables at once; scope to the visible one. */
+const requestLogsRows = (page: PlaywrightPage): Locator =>
+  page.locator("table").filter({ visible: true }).first().locator("tbody tr");
+
+const visibleTestId = (page: PlaywrightPage, id: string): Locator => page.getByTestId(id).filter({ visible: true });
+
+async function openLogs(page: PlaywrightPage): Promise<void> {
+  await navigateToPage(page, Page.Logs);
+  await dismissFeedbackPopup(page);
+  await expect(visibleTestId(page, "datatable-search")).toBeVisible({ timeout: 20_000 });
+}
+
+async function openFilterDrawer(page: PlaywrightPage): Promise<Locator> {
+  await visibleTestId(page, "datatable-filters-trigger").click();
+  const drawer = page.getByRole("dialog", { name: "Filters" });
+  await expect(drawer).toBeVisible({ timeout: 10_000 });
+  return drawer;
+}
+
+/** Picks a value in one of the drawer's searchable comboboxes and applies the filter. */
+async function applyComboboxFilter(
+  page: PlaywrightPage,
+  drawer: Locator,
+  comboboxLabel: string,
+  value: string,
+): Promise<void> {
+  await drawer.getByRole("combobox", { name: comboboxLabel }).click();
+  await page.keyboard.type(value);
+  await page.getByRole("option", { name: value, exact: true }).first().click();
+  await drawer.getByRole("button", { name: "Apply Filters" }).click();
+  await expect(drawer).not.toBeVisible({ timeout: 10_000 });
+}
+
+/** A request the key is not entitled to make, so the proxy refuses it and logs the refusal. */
+async function sendDeniedCompletion(request: APIRequestContext, apiKey: string): Promise<void> {
+  const res = await request.post("/v1/chat/completions", {
+    headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
+    data: { model: CHAT_MODEL_B, messages: [{ role: "user", content: "denied" }] },
+  });
+  expect(res.status(), "a model outside the key's allow-list is refused").toBe(403);
+}
+
+test.describe("Logs page filters", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("the Key Alias filter narrows the table to that key's requests", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const mine = await createVirtualKey(request, { key_alias: `e2e-logs-mine-${suffix}` });
+    const theirs = await createVirtualKey(request, { key_alias: `e2e-logs-theirs-${suffix}` });
+
+    const myRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-mine-${suffix}`,
+      apiKey: mine.key,
+    });
+    const theirRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-theirs-${suffix}`,
+      apiKey: theirs.key,
+    });
+    await waitForSpendLog(request, myRequestId);
+    await waitForSpendLog(request, theirRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await applyComboboxFilter(page, drawer, "Search a key alias", mine.alias!);
+
+    await expect(requestLogsRows(page).filter({ hasText: myRequestId })).toHaveCount(1, { timeout: 30_000 });
+    // The filter is only doing its job if the other key's request is gone, not merely if ours is present.
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(0, { timeout: 10_000 });
+  });
+
+  test("the Status filter narrows the table to the refused request", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const alias = `e2e-logs-status-${suffix}`;
+    const scoped = await createVirtualKey(request, { key_alias: alias, models: [CHAT_MODEL_A] });
+
+    const servedRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-served-${suffix}`,
+      apiKey: scoped.key,
+    });
+    await sendDeniedCompletion(request, scoped.key);
+    await waitForSpendLog(request, servedRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await drawer.getByRole("combobox", { name: "Search a key alias" }).click();
+    await page.keyboard.type(alias);
+    await page.getByRole("option", { name: alias, exact: true }).first().click();
+    // The Status field labels its group, not the trigger, so it is addressed by the value it shows.
+    await drawer.getByRole("combobox").filter({ hasText: "All Statuses" }).click();
+    await page.getByRole("option", { name: "Failure", exact: true }).click();
+    await drawer.getByRole("button", { name: "Apply Filters" }).click();
+    await expect(drawer).not.toBeVisible({ timeout: 10_000 });
+
+    // Both requests were made by this key, so a Status filter that does nothing leaves the served one on screen.
+    await expect(requestLogsRows(page)).toHaveCount(1, { timeout: 30_000 });
+    await expect(requestLogsRows(page)).toContainText("Failure");
+    await expect(requestLogsRows(page).filter({ hasText: servedRequestId })).toHaveCount(0);
+  });
+
+  test("Reset Filters brings back the rows a filter hid", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const mine = await createVirtualKey(request, { key_alias: `e2e-logs-reset-mine-${suffix}` });
+    const theirs = await createVirtualKey(request, { key_alias: `e2e-logs-reset-theirs-${suffix}` });
+
+    const myRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-reset-mine-${suffix}`,
+      apiKey: mine.key,
+    });
+    const theirRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-reset-theirs-${suffix}`,
+      apiKey: theirs.key,
+    });
+    await waitForSpendLog(request, myRequestId);
+    await waitForSpendLog(request, theirRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await applyComboboxFilter(page, drawer, "Search a key alias", mine.alias!);
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(0, { timeout: 30_000 });
+
+    // A filter you cannot clear is a page that looks empty forever, which is how it reads to a user.
+    await page.getByRole("button", { name: "Reset Filters" }).filter({ visible: true }).click();
+
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(1, { timeout: 30_000 });
+    await expect(requestLogsRows(page).filter({ hasText: myRequestId })).toHaveCount(1, { timeout: 10_000 });
+  });
+});
diff --git a/tests/e2e/ui/tests/mcp/mcpServerEdit.spec.ts b/tests/e2e/ui/tests/mcp/mcpServerEdit.spec.ts
index 46799c8a18f..aa7cdf82498 100644
--- a/tests/e2e/ui/tests/mcp/mcpServerEdit.spec.ts
+++ b/tests/e2e/ui/tests/mcp/mcpServerEdit.spec.ts
@@ -73,7 +73,7 @@ test.describe("MCP Servers - edit and delete", () => {
   test("Deleting a server removes it", async ({ page }) => {
     expect(await findServerByName(page, serverName), `created server ${serverName} exists`).toBeTruthy();
 
-    const card = page.getByTestId("mcp-servers-grid").locator("div").filter({ hasText: serverName }).first();
+    const card = page.getByTestId("mcp-servers-grid").getByRole("button", { name: serverName });
     await card.getByRole("button", { name: "Server actions" }).click();
     await page.getByRole("menuitem", { name: "Delete" }).click();
 
diff --git a/tests/e2e/ui/tests/migration/migratedPages.spec.ts b/tests/e2e/ui/tests/migration/migratedPages.spec.ts
index 3ad4b217d08..547330190bd 100644
--- a/tests/e2e/ui/tests/migration/migratedPages.spec.ts
+++ b/tests/e2e/ui/tests/migration/migratedPages.spec.ts
@@ -35,17 +35,12 @@ async function expectRendered(page: Page) {
  */
 async function clickSidebar(page: Page, segment: string) {
   const link = sidebar(page).locator(`a[href$="/ui/${segment}"]`).first();
+  const collapsedGroups = sidebar(page).getByRole("button", { expanded: false });
   for (let i = 0; i < 8 && !(await link.isVisible().catch(() => false)); i++) {
-    // A collapsed group is a menu item with a group-toggle button but no
-    // rendered submenu yet; clicking the toggle expands it.
-    const collapsedGroup = sidebar(page)
-      .locator(
-        '[data-slot="sidebar-menu-item"]:has(> [data-slot="sidebar-menu-button"]):not(:has(> [data-slot="sidebar-menu-sub"])) > [data-slot="sidebar-menu-button"]',
-      )
-      .first();
-    if (!(await collapsedGroup.isVisible().catch(() => false))) break;
-    await collapsedGroup.click();
-    await page.waitForTimeout(250);
+    const stillCollapsed = await collapsedGroups.count();
+    if (stillCollapsed === 0) break;
+    await collapsedGroups.first().click();
+    await expect(collapsedGroups).toHaveCount(stillCollapsed - 1);
   }
   await link.click();
 }
diff --git a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts
index 16ec94c1dc8..6877fc9c48d 100644
--- a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts
+++ b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts
@@ -1,7 +1,8 @@
-import { test, expect } from "@playwright/test";
+import { test, expect, type APIRequestContext } from "@playwright/test";
 import { ADMIN_STORAGE_PATH } from "../../constants";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
+import { masterKey } from "../../helpers/traffic";
 
 test.describe("AI Hub (internal admin view)", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
@@ -77,4 +78,89 @@ test.describe("Public model hub (/ui/model_hub_table)", () => {
     // agents/MCP servers exist, so we don't assert on them in a fresh CI run.
     await expect(page.getByRole("tab", { name: "Model Hub" })).toBeVisible({ timeout: 10_000 });
   });
+
+  test("Agent Hub and MCP Hub tabs render their public entries", async ({ page, request }) => {
+    const suffix = `${Date.now()}`;
+    const agentName = `e2e-public-agent-${suffix}`;
+    const mcpServerName = `e2e_public_mcp_${suffix}`;
+    const auth = { Authorization: `Bearer ${masterKey()}` };
+
+    const publicMcpServerIds = async (api: APIRequestContext): Promise<string[]> => {
+      const res = await api.get("/public/mcp_hub");
+      expect(res.ok(), `public mcp_hub read failed (${res.status()}): ${await res.text()}`).toBe(true);
+      const servers: { server_id: string }[] = await res.json();
+      return servers.map((server) => server.server_id);
+    };
+
+    const seedPublicEntries = async (
+      api: APIRequestContext,
+      priorMcpIds: string[],
+    ): Promise<{ agentId: string; serverId: string }> => {
+      const agentRes = await api.post("/v1/agents", {
+        headers: auth,
+        data: {
+          agent_name: agentName,
+          agent_card_params: {
+            name: agentName,
+            description: "E2E public agent",
+            version: "1.0.0",
+            url: "http://127.0.0.1:9999/",
+            capabilities: {},
+            skills: [],
+            defaultInputModes: ["text"],
+            defaultOutputModes: ["text"],
+          },
+        },
+      });
+      expect(agentRes.ok(), `agent create failed (${agentRes.status()}): ${await agentRes.text()}`).toBe(true);
+      const agentId = (await agentRes.json()).agent_id as string;
+
+      const serverRes = await api.post("/v1/mcp/server", {
+        headers: auth,
+        data: {
+          server_name: mcpServerName,
+          url: "http://127.0.0.1:9999/mcp",
+          transport: "http",
+          description: "E2E public MCP server",
+        },
+      });
+      expect(serverRes.ok(), `mcp server create failed (${serverRes.status()}): ${await serverRes.text()}`).toBe(true);
+      const serverId = (await serverRes.json()).server_id as string;
+
+      const agentPublicRes = await api.post(`/v1/agents/${agentId}/make_public`, { headers: auth });
+      expect(agentPublicRes.ok(), `agent make_public failed: ${await agentPublicRes.text()}`).toBe(true);
+      const mcpPublicRes = await api.post("/v1/mcp/make_public", {
+        headers: auth,
+        data: { mcp_server_ids: [...priorMcpIds, serverId] },
+      });
+      expect(mcpPublicRes.ok(), `mcp make_public failed: ${await mcpPublicRes.text()}`).toBe(true);
+
+      return { agentId, serverId };
+    };
+
+    const priorMcpIds = await publicMcpServerIds(request);
+    const { agentId, serverId } = await seedPublicEntries(request, priorMcpIds);
+    try {
+      await page.goto(`/ui/model_hub_table?key=${masterKey()}`);
+      await dismissFeedbackPopup(page);
+
+      const agentHubTab = page.getByRole("tab", { name: "Agent Hub" });
+      await expect(agentHubTab).toBeVisible({ timeout: 15_000 });
+      await agentHubTab.click();
+      await expect(page.getByText("Available Agents")).toBeVisible({ timeout: 10_000 });
+      await expect(page.getByRole("row").filter({ hasText: agentName })).toHaveCount(1, { timeout: 10_000 });
+      await expect(page.getByText("E2E public agent").first()).toBeVisible();
+
+      const mcpHubTab = page.getByRole("tab", { name: "MCP Hub" });
+      await expect(mcpHubTab).toBeVisible();
+      await mcpHubTab.click();
+      await expect(page.getByText("Available MCP Servers")).toBeVisible({ timeout: 10_000 });
+      await expect(page.getByRole("row").filter({ hasText: mcpServerName })).toHaveCount(1, { timeout: 10_000 });
+      await expect(page.getByText("E2E public MCP server").first()).toBeVisible();
+    } finally {
+      await request.post("/v1/mcp/make_public", { headers: auth, data: { mcp_server_ids: priorMcpIds } });
+      await request.delete(`/v1/agents/${agentId}`, { headers: auth });
+      await request.delete(`/v1/mcp/server/${serverId}`, { headers: auth });
+    }
+  });
 });
diff --git a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
index dad716b4c83..de25ec1aac5 100644
--- a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
+++ b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
@@ -5,6 +5,11 @@ import { navigateToPage } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
 import { captureRequestBody, readBack } from "../../helpers/roundTrip";
 import { sendChatCompletion } from "../../helpers/traffic";
+import { proxyIsPremium } from "../../helpers/premium";
+
+/** Four probes 13s apart span 39s, one PROXY_CONFIG_RELOAD_INTERVAL_SECONDS (30s) plus margin. */
+const CREDENTIAL_PROBE_SUCCESSES = 4;
+const CREDENTIAL_PROBE_SPACING_MS = 13_000;
 
 /** The mock LLM as the proxy reaches it: same host locally, a sidecar in the deployed stack. */
 const MOCK_LLM_BASE = `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`;
@@ -35,7 +40,10 @@ async function selectProvider(page: PlaywrightPage, providerName: string) {
   const providerDropdown = page.getByRole("combobox", { name: "Provider", exact: true });
   await providerDropdown.click();
   await providerDropdown.fill(providerName);
-  await page.getByRole("option").filter({ hasText: exactly(providerName) }).click();
+  await page
+    .getByRole("option")
+    .filter({ hasText: exactly(providerName) })
+    .click();
   await expect(providerDropdown).toHaveValue(providerName);
 }
 
@@ -78,6 +86,9 @@ test.describe("Add Model", () => {
   });
 
   test("Edit team model TPM and RPM limits", async ({ page }) => {
+    // /model/new refuses a team-scoped deployment on an unlicensed proxy, so there this fails in
+    // setup on a product gate rather than on a regression in the edit it covers.
+    test.skip(!proxyIsPremium(), "proxy under test is unlicensed — team-scoped models are premium");
     const masterKey = users[Role.ProxyAdmin].password;
     const modelName = `e2e-team-model-${Date.now()}`;
 
@@ -188,7 +199,7 @@ test.describe("Add Model", () => {
     await expect(resultsModal).toBeHidden({ timeout: 5_000 });
 
     const created = await captureRequestBody(page, { method: "POST", urlIncludes: "/model/new" }, async () => {
-      await page.getByRole("button", { name: "Add Model" }).last().click();
+      await page.getByTestId("add-model-btn").click();
     });
     expect(created.model_name, "the model is created under the name that was typed").toBe(publicName);
     expect(created.litellm_params?.api_base, "the api base survives the form").toBe(MOCK_LLM_BASE);
@@ -212,6 +223,120 @@ test.describe("Add Model", () => {
       .toBe(true);
   });
 
+  test("Add a model with a stored credential, pass Test Connect, and serve traffic", async ({ page, request }) => {
+    const masterKey = users[Role.ProxyAdmin].password;
+    const auth = { Authorization: `Bearer ${masterKey}` };
+    const credentialName = `e2e-cred-reuse-${Date.now()}`;
+    const createCred = await page.request.post("/credentials", {
+      headers: auth,
+      data: {
+        credential_name: credentialName,
+        credential_values: { api_key: "fake-key", api_base: MOCK_LLM_BASE },
+        credential_info: { custom_llm_provider: "openai" },
+      },
+    });
+    expect(createCred.ok(), `POST /credentials failed (${createCred.status()}): ${await createCred.text()}`).toBe(true);
+
+    // The proxy's periodic credential refresh prunes its in-memory list against a database snapshot
+    // it took before this credential landed, so a credential that resolves right after POST
+    // /credentials can stop resolving until the refresh after that. Successes spanning a whole
+    // PROXY_CONFIG_RELOAD_INTERVAL_SECONDS prove it survived a refresh, after which it stays.
+    // Resolution fails open onto the ambient key, so losing it reads as a confusing upstream 404.
+    let consecutiveProbeSuccesses = 0;
+    await expect
+      .poll(
+        async () => {
+          const probe = await page.request.post("/health/test_connection", {
+            headers: auth,
+            data: {
+              litellm_params: {
+                model: "openai/fake-gpt-4",
+                custom_llm_provider: "openai",
+                litellm_credential_name: credentialName,
+              },
+              model_info: {},
+              mode: "chat",
+            },
+          });
+          const healthy = probe.ok() && (await probe.json()).status === "success";
+          consecutiveProbeSuccesses = healthy ? consecutiveProbeSuccesses + 1 : 0;
+          return consecutiveProbeSuccesses;
+        },
+        {
+          message: `stored credential ${credentialName} never stayed usable across a config reload`,
+          intervals: [0, CREDENTIAL_PROBE_SPACING_MS],
+          timeout: 110_000,
+        },
+      )
+      .toBeGreaterThanOrEqual(CREDENTIAL_PROBE_SUCCESSES);
+
+    try {
+      await navigateToPage(page, Page.Models);
+      await page.getByRole("tab", { name: "Add Model" }).click();
+
+      await selectProvider(page, "OpenAI-Compatible Endpoints (Together AI, etc.)");
+
+      const publicName = `e2e-cred-model-${Date.now()}`;
+      uiAddedModelName = publicName;
+
+      await page.getByRole("combobox", { name: "Select models" }).click();
+      await page.getByRole("option", { name: "Custom Model Name (Enter below)" }).click();
+      await page.keyboard.press("Escape");
+      await page.getByPlaceholder("Enter custom model name").fill(publicName);
+
+      const credentialSelect = page.getByRole("combobox", { name: "Existing Credentials" });
+      await credentialSelect.click();
+      await credentialSelect.fill(credentialName);
+      await page.getByRole("option", { name: credentialName, exact: true }).click();
+
+      await expect(page.locator("#api_key")).toHaveCount(0);
+      await expect(page.locator("#api_base")).toHaveCount(0);
+
+      await page.getByRole("button", { name: "Test Connect" }).click();
+      await expect(page.getByText("Connection Test Results")).toBeVisible({ timeout: 10_000 });
+      await expect(page.getByTestId("connection-success-msg")).toBeVisible({ timeout: 30_000 });
+
+      const resultsModal = page.getByRole("dialog", { name: "Connection Test Results" });
+      await resultsModal.locator('[data-slot="dialog-footer"]').getByRole("button", { name: "Close" }).click();
+      await expect(resultsModal).toBeHidden({ timeout: 5_000 });
+
+      const created = await captureRequestBody(page, { method: "POST", urlIncludes: "/model/new" }, async () => {
+        await page.getByRole("button", { name: "Add Model" }).last().click();
+      });
+      expect(created.litellm_params?.litellm_credential_name, "the picked credential goes on the wire").toBe(
+        credentialName,
+      );
+      expect(created.litellm_params?.api_key, "no raw api key goes on the wire").toBeUndefined();
+
+      await expect(page.getByText("created successfully")).toBeVisible({ timeout: 15_000 });
+
+      await expect
+        .poll(
+          async () => {
+            try {
+              await sendChatCompletion(request, { model: publicName, prompt: `hello via ${credentialName}` });
+              return true;
+            } catch {
+              return false;
+            }
+          },
+          {
+            message: `model ${publicName} added with a stored credential never served a request`,
+            timeout: 30_000,
+          },
+        )
+        .toBe(true);
+    } finally {
+      const stored = uiAddedModelName ? await findDeploymentByName(page, uiAddedModelName) : undefined;
+      const id = stored?.model_info?.id;
+      if (id) {
+        await page.request.post("/model/delete", { headers: auth, data: { id } });
+        uiAddedModelName = "";
+      }
+      await page.request.delete(`/credentials/${credentialName}`, { headers: auth });
+    }
+  });
+
   test("Test connection with bad credentials shows failure", async ({ page }) => {
     await navigateToPage(page, Page.Models);
     await page.getByRole("tab", { name: "Add Model" }).click();
@@ -254,7 +379,7 @@ test.describe("Add Model", () => {
 
     // Click Add Model button by its text
     const created = await captureRequestBody(page, { method: "POST", urlIncludes: "/model/new" }, async () => {
-      await page.getByRole("button", { name: "Add Model" }).last().click();
+      await page.getByTestId("add-model-btn").click();
     });
     // The form sends custom_llm_provider separately from the name, so both halves have to arrive.
     expect(created.model_name, "the selected model is what goes on the wire").toBe("claude-haiku-4-5");
@@ -267,11 +392,9 @@ test.describe("Add Model", () => {
     // Navigate to All Models tab
     await page.getByRole("tab", { name: "All Models" }).click();
     await page.waitForLoadState("networkidle");
-    await page.waitForTimeout(2000);
 
     // Search for the model we just added
     await page.getByPlaceholder("Search model names").fill("claude-haiku-4-5");
-    await page.waitForTimeout(1000);
 
     // Verify the model appears in the results count (not "Showing 0 results")
     await expect(page.getByTestId("pagination-range")).toHaveText(/Showing \d+-\d+ of \d+/, {
@@ -279,8 +402,9 @@ test.describe("Add Model", () => {
     });
 
     // Verify the model name appears in the table body
-    const tableBody = page.locator("table tbody");
-    await expect(tableBody.getByText("claude-haiku-4-5").first()).toBeVisible({ timeout: 15_000 });
+    await expect(page.getByRole("row").filter({ hasText: "claude-haiku-4-5" })).not.toHaveCount(0, {
+      timeout: 15_000,
+    });
 
     // A row proves the name is there, not what the deployment routes to.
     const stored = await findDeploymentByName(page, "claude-haiku-4-5");
@@ -333,11 +457,11 @@ test.describe("Add Model", () => {
       const teamDropdown = page.getByTestId("team-dropdown").getByRole("combobox");
       await expect(teamDropdown).toBeVisible({ timeout: 5_000 });
       await teamDropdown.click();
-      const teamOption = page.locator('[data-slot="combobox-content"]:visible').getByText(E2E_TEAM_CRUD_ID).first();
+      const teamOption = page.getByRole("option", { name: E2E_TEAM_CRUD_ID }).first();
       await expect(teamOption).toBeVisible({ timeout: 5_000 });
       await teamOption.click();
 
-      await page.getByRole("button", { name: "Add Model" }).last().click();
+      await page.getByTestId("add-model-btn").click();
 
       // Scope to the toast container so a stale toast can't satisfy this.
       await expect(page.locator("[data-sonner-toast]").getByText("created successfully").last()).toBeVisible({
@@ -347,11 +471,8 @@ test.describe("Add Model", () => {
       // The Models table renders team-scoped models with the team id in the row.
       await page.getByRole("tab", { name: "All Models" }).click();
       await page.waitForLoadState("networkidle");
-      // networkidle fires before the table finishes re-rendering.
-      await page.waitForTimeout(2000);
 
       await page.getByPlaceholder("Search model names").fill("cohere");
-      await page.waitForTimeout(1000);
 
       // Clearer failure than timing out on a row assertion when the table is empty.
       await expect(page.getByTestId("pagination-range")).toHaveText(/Showing \d+-\d+ of \d+/, {
@@ -360,10 +481,7 @@ test.describe("Add Model", () => {
 
       // Pin to one row carrying both the name and the team, so the sibling test's
       // team-less cohere row can't satisfy it.
-      const teamCohereRow = page
-        .locator("table tbody tr")
-        .filter({ hasText: "cohere/" })
-        .filter({ hasText: E2E_TEAM_CRUD_ID });
+      const teamCohereRow = page.getByRole("row").filter({ hasText: "cohere/" }).filter({ hasText: E2E_TEAM_CRUD_ID });
       await expect(teamCohereRow).toHaveCount(1, { timeout: 15_000 });
     } finally {
       await deleteTeamScopedCohereModels();
@@ -387,7 +505,7 @@ test.describe("Add Model", () => {
 
     // Click Add Model button by its text
     const created = await captureRequestBody(page, { method: "POST", urlIncludes: "/model/new" }, async () => {
-      await page.getByRole("button", { name: "Add Model" }).last().click();
+      await page.getByTestId("add-model-btn").click();
     });
     // A wildcard with the star stripped becomes a plain "cohere" deployment that matches nothing.
     expect(created.model_name, "the wildcard route goes on the wire intact").toBe("cohere/*");
@@ -398,11 +516,9 @@ test.describe("Add Model", () => {
     // Navigate to All Models tab
     await page.getByRole("tab", { name: "All Models" }).click();
     await page.waitForLoadState("networkidle");
-    await page.waitForTimeout(2000);
 
     // Search for the wildcard model
     await page.getByPlaceholder("Search model names").fill("cohere");
-    await page.waitForTimeout(1000);
 
     // Verify the model appears in the results count (not "Showing 0 results")
     await expect(page.getByTestId("pagination-range")).toHaveText(/Showing \d+-\d+ of \d+/, {
@@ -410,8 +526,7 @@ test.describe("Add Model", () => {
     });
 
     // Verify the wildcard model appears in the table body (wildcard models show as "cohere/*")
-    const tableBody = page.locator("table tbody");
-    await expect(tableBody.getByText("cohere/").first()).toBeVisible({ timeout: 15_000 });
+    await expect(page.getByRole("row").filter({ hasText: "cohere/" })).not.toHaveCount(0, { timeout: 15_000 });
 
     // "cohere/" in the table also matches a plain cohere deployment; require the wildcard exactly.
     const stored = await findDeploymentByName(page, "cohere/*");
diff --git a/tests/e2e/ui/tests/modelsPage/autoRouterTemplateSelect.spec.ts b/tests/e2e/ui/tests/modelsPage/autoRouterTemplateSelect.spec.ts
index 1d080ec82b8..51df50a2e68 100644
--- a/tests/e2e/ui/tests/modelsPage/autoRouterTemplateSelect.spec.ts
+++ b/tests/e2e/ui/tests/modelsPage/autoRouterTemplateSelect.spec.ts
@@ -17,49 +17,54 @@ async function openTemplateSelect(page: PlaywrightPage) {
   return trigger;
 }
 
-function pollPixelsBelowTrigger(trigger: Locator, popup: Locator) {
+async function boxes(trigger: Locator, options: Locator) {
+  const triggerBox = await trigger.boundingBox();
+  const optionsBox = await options.boundingBox();
+  return triggerBox && optionsBox ? { triggerBox, optionsBox } : null;
+}
+
+const clippedPopup = (page: PlaywrightPage) => page.locator('[data-slot="select-content"]');
+
+function pollOptionsOpenBelowTrigger(trigger: Locator, options: Locator) {
   return expect.poll(async () => {
-    const triggerBox = await trigger.boundingBox();
-    const popupBox = await popup.boundingBox();
-    if (!triggerBox || !popupBox) return null;
-    return popupBox.y - (triggerBox.y + triggerBox.height);
+    const box = await boxes(trigger, options);
+    return box && box.optionsBox.y >= box.triggerBox.y + box.triggerBox.height;
   });
 }
 
-function pollPopupOverlapsTrigger(trigger: Locator, popup: Locator) {
+function pollOptionsCoverTrigger(trigger: Locator, options: Locator) {
   return expect.poll(async () => {
-    const triggerBox = await trigger.boundingBox();
-    const popupBox = await popup.boundingBox();
-    if (!triggerBox || !popupBox) return null;
-    return popupBox.y < triggerBox.y + triggerBox.height && popupBox.y + popupBox.height > triggerBox.y;
+    const box = await boxes(trigger, options);
+    return (
+      box &&
+      box.optionsBox.y < box.triggerBox.y + box.triggerBox.height &&
+      box.optionsBox.y + box.optionsBox.height > box.triggerBox.y
+    );
   });
 }
 
 test.describe("Auto Router template select anchoring", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
-  test("opens the options below the trigger rather than over it", async ({ page }) => {
+  test("opens the options below the trigger when there is room below it", async ({ page }) => {
     await page.setViewportSize({ width: 1280, height: 900 });
     const trigger = await openTemplateSelect(page);
+    await trigger.scrollIntoViewIfNeeded();
 
     await trigger.click();
-    const popup = page.locator('[data-slot="select-content"]');
-    await expect(popup).toBeVisible();
+    await expect(page.getByRole("listbox")).toBeVisible();
 
-    // Item-aligned mode reports "none" and puts the active item over the trigger.
-    await expect(popup).toHaveAttribute("data-side", "bottom");
-    await pollPixelsBelowTrigger(trigger, popup).toBeGreaterThanOrEqual(0);
+    await pollOptionsOpenBelowTrigger(trigger, clippedPopup(page)).toBe(true);
   });
 
-  test("flips above the trigger instead of covering it when there is no room below", async ({ page }) => {
+  test("keeps the trigger uncovered when the options open with no room below it", async ({ page }) => {
     await page.setViewportSize({ width: 1280, height: 560 });
     const trigger = await openTemplateSelect(page);
     await trigger.scrollIntoViewIfNeeded();
 
     await trigger.click();
-    const popup = page.locator('[data-slot="select-content"]');
-    await expect(popup).toBeVisible();
+    await expect(page.getByRole("listbox")).toBeVisible();
 
-    await pollPopupOverlapsTrigger(trigger, popup).toBe(false);
+    await pollOptionsCoverTrigger(trigger, clippedPopup(page)).toBe(false);
   });
 });
diff --git a/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts b/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts
new file mode 100644
index 00000000000..96abd9833c0
--- /dev/null
+++ b/tests/e2e/ui/tests/modelsPage/deleteTeamModel.spec.ts
@@ -0,0 +1,72 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH, E2E_TEAM_CRUD_ID } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage } from "../../helpers/navigation";
+import { readBack } from "../../helpers/roundTrip";
+import { masterKey } from "../../helpers/traffic";
+
+type DeploymentRow = { model_name?: string };
+
+async function findDeploymentByName(page: PlaywrightPage, modelName: string): Promise<DeploymentRow | undefined> {
+  const body = await readBack<{ data: DeploymentRow[] }>(page, "/v2/model/info");
+  return body.data.find((row) => row.model_name === modelName);
+}
+
+test.describe("Delete team model", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Delete a team-scoped model and verify it leaves the team's model list", async ({ page }) => {
+    const modelName = `e2e-team-model-delete-${Date.now()}`;
+    const createResponse = await page.request.post("/model/new", {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+      data: {
+        model_name: modelName,
+        litellm_params: {
+          model: "openai/fake-gpt-4",
+          api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`,
+          api_key: "fake-key",
+        },
+        model_info: { team_id: E2E_TEAM_CRUD_ID },
+      },
+    });
+    expect(createResponse.ok(), `/model/new failed: ${createResponse.status()} ${await createResponse.text()}`).toBe(
+      true,
+    );
+
+    await expect
+      .poll(async () => (await findDeploymentByName(page, modelName)) !== undefined, {
+        message: `deployment ${modelName} never appeared in /v2/model/info after create`,
+        timeout: 30_000,
+      })
+      .toBe(true);
+
+    await navigateToPage(page, Page.Models);
+    await page.getByPlaceholder("Search model names").fill(modelName);
+
+    const row = page.getByRole("row").filter({ hasText: modelName });
+    await expect(row).toHaveCount(1, { timeout: 15_000 });
+    await expect(row.getByText(E2E_TEAM_CRUD_ID)).toBeVisible({ timeout: 10_000 });
+
+    await row.getByRole("button", { name: "Delete model" }).click();
+
+    const modal = page.getByRole("dialog", { name: "Delete Model" });
+    await expect(modal).toBeVisible({ timeout: 5_000 });
+    await expect(modal.getByText(modelName).first()).toBeVisible();
+    await modal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByText("Model deleted successfully").first()).toBeVisible({ timeout: 10_000 });
+    await expect(row).toHaveCount(0, { timeout: 15_000 });
+
+    await expect
+      .poll(async () => await findDeploymentByName(page, modelName), {
+        message: `deployment ${modelName} still readable from /v2/model/info after delete`,
+        timeout: 15_000,
+      })
+      .toBeUndefined();
+
+    await page.reload();
+    await page.getByPlaceholder("Search model names").fill(modelName);
+    await expect(page.getByText("No models found").first()).toBeVisible({ timeout: 15_000 });
+    await expect(page.getByRole("row").filter({ hasText: modelName })).toHaveCount(0);
+  });
+});
diff --git a/tests/e2e/ui/tests/modelsPage/responsiveHeader.spec.ts b/tests/e2e/ui/tests/modelsPage/responsiveHeader.spec.ts
index 6ad1ccb8451..aabdf18d427 100644
--- a/tests/e2e/ui/tests/modelsPage/responsiveHeader.spec.ts
+++ b/tests/e2e/ui/tests/modelsPage/responsiveHeader.spec.ts
@@ -7,9 +7,7 @@ test.describe("Models and Endpoints responsive header", () => {
     viewport: { width: 900, height: 720 },
   });
 
-  test("keeps the refresh action on the same row as the tabs", async ({
-    page,
-  }) => {
+  test("keeps the refresh action on the same row as the tabs", async ({ page }) => {
     await page.goto("/ui");
     await page
       .getByRole("complementary")
@@ -26,8 +24,8 @@ test.describe("Models and Endpoints responsive header", () => {
     expect(tabsBox).not.toBeNull();
     expect(refreshBox).not.toBeNull();
 
-    const tabsCenterY = tabsBox!.y + tabsBox!.height / 2;
     const refreshCenterY = refreshBox!.y + refreshBox!.height / 2;
-    expect(Math.abs(tabsCenterY - refreshCenterY)).toBeLessThanOrEqual(2);
+    const sharesARow = refreshCenterY > tabsBox!.y && refreshCenterY < tabsBox!.y + tabsBox!.height;
+    expect(sharesARow, "refresh wrapped onto its own row below the tabs").toBe(true);
   });
 });
diff --git a/tests/e2e/ui/tests/proxy-admin/keys.spec.ts b/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
index 0c38641dcc7..deb7ae70d07 100644
--- a/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
+++ b/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
@@ -1,15 +1,17 @@
 import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
 import {
   ADMIN_STORAGE_PATH,
-  E2E_DELETE_KEY_ALIAS,
   E2E_REGENERATE_KEY_ALIAS,
   E2E_UPDATE_LIMITS_KEY_ALIAS,
   E2E_INTERNAL_USER_KEY_ALIAS,
   E2E_TEAM_CRUD_ALIAS,
+  E2E_TEAM_CRUD_ID,
 } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { captureRequestBody, readBack } from "../../helpers/roundTrip";
+import { masterKey } from "../../helpers/traffic";
+import { proxyIsPremium } from "../../helpers/premium";
 
 /**
  * Looks a key up by alias, undefined when none carries it. `return_full_object=true` is what makes
@@ -23,6 +25,17 @@ async function findKeyByAlias(page: PlaywrightPage, alias: string): Promise<Reco
   return body.keys.find((row) => row.key_alias === alias);
 }
 
+/** A key this test owns, so deleting it costs the suite nothing on a retry or a second run. */
+async function createDeletableKey(page: PlaywrightPage): Promise<string> {
+  const alias = `e2e-delete-key-${Date.now()}`;
+  const res = await page.request.post("/key/generate", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { key_alias: alias, team_id: E2E_TEAM_CRUD_ID },
+  });
+  expect(res.ok(), `POST /key/generate failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return alias;
+}
+
 test.describe("Proxy Admin - Keys", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
@@ -43,7 +56,7 @@ test.describe("Proxy Admin - Keys", () => {
     const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
     await teamSelect.click();
     await page.keyboard.type(E2E_TEAM_CRUD_ALIAS);
-    await page.locator('[data-slot="combobox-content"]:visible').getByText(E2E_TEAM_CRUD_ALIAS).first().click();
+    await page.getByRole("option", { name: E2E_TEAM_CRUD_ALIAS }).first().click();
 
     // Select models — the popup is portaled to the body, so scope options to the page.
     await page.getByRole("combobox", { name: "Select models" }).click();
@@ -67,6 +80,9 @@ test.describe("Proxy Admin - Keys", () => {
   });
 
   test("Regenerate key", async ({ page }) => {
+    // The Regenerate Key button renders disabled when the proxy is unlicensed, so without one this
+    // fails on a product gate rather than on a regression.
+    test.skip(!proxyIsPremium(), "proxy under test is unlicensed — Regenerate Key is premium-gated");
     await navigateToPage(page, Page.ApiKeys);
     await dismissFeedbackPopup(page);
 
@@ -74,10 +90,9 @@ test.describe("Proxy Admin - Keys", () => {
     const before = await findKeyByAlias(page, E2E_REGENERATE_KEY_ALIAS);
     expect(before?.token, `seeded key ${E2E_REGENERATE_KEY_ALIAS} has a token`).toBeTruthy();
 
-    // Key IDs are rendered as buttons in the table
-    const keyRow = page.locator("tr", { hasText: E2E_REGENERATE_KEY_ALIAS });
+    const keyRow = page.getByRole("row").filter({ hasText: E2E_REGENERATE_KEY_ALIAS });
     await expect(keyRow).toBeVisible({ timeout: 10_000 });
-    await keyRow.locator("button").first().click();
+    await keyRow.getByRole("button", { name: E2E_REGENERATE_KEY_ALIAS }).click();
 
     await expect(page.getByText("Back to Keys")).toBeVisible({ timeout: 10_000 });
 
@@ -109,9 +124,9 @@ test.describe("Proxy Admin - Keys", () => {
     const before = await findKeyByAlias(page, E2E_UPDATE_LIMITS_KEY_ALIAS);
     expect(before, `seeded key ${E2E_UPDATE_LIMITS_KEY_ALIAS} exists`).toBeTruthy();
 
-    const keyRow = page.locator("tr", { hasText: E2E_UPDATE_LIMITS_KEY_ALIAS });
+    const keyRow = page.getByRole("row").filter({ hasText: E2E_UPDATE_LIMITS_KEY_ALIAS });
     await expect(keyRow).toBeVisible({ timeout: 10_000 });
-    await keyRow.locator("button").first().click();
+    await keyRow.getByRole("button", { name: E2E_UPDATE_LIMITS_KEY_ALIAS }).click();
 
     await expect(page.getByText("Back to Keys")).toBeVisible({ timeout: 10_000 });
 
@@ -144,12 +159,16 @@ test.describe("Proxy Admin - Keys", () => {
   });
 
   test("Delete key", async ({ page }) => {
+    // Deleting the seeded key leaves nothing for the next attempt, so the retries CI runs with are
+    // guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const alias = await createDeletableKey(page);
+
     await navigateToPage(page, Page.ApiKeys);
     await dismissFeedbackPopup(page);
 
-    const keyRow = page.locator("tr", { hasText: E2E_DELETE_KEY_ALIAS });
+    const keyRow = page.getByRole("row").filter({ hasText: alias });
     await expect(keyRow).toBeVisible({ timeout: 10_000 });
-    await keyRow.locator("button").first().click();
+    await keyRow.getByRole("button", { name: alias }).click();
 
     await expect(page.getByText("Back to Keys")).toBeVisible({ timeout: 10_000 });
 
@@ -158,7 +177,7 @@ test.describe("Proxy Admin - Keys", () => {
 
     const modal = page.getByRole("dialog", { name: "Delete Key" });
     await expect(modal).toBeVisible({ timeout: 5_000 });
-    await modal.locator("input").fill(E2E_DELETE_KEY_ALIAS);
+    await modal.locator("input").fill(alias);
 
     const deleteButton = modal.getByRole("button", { name: "Delete", exact: true });
     await expect(deleteButton).toBeEnabled();
@@ -168,8 +187,8 @@ test.describe("Proxy Admin - Keys", () => {
 
     // The key is gone when the management API stops returning it, not when the toast says so.
     await expect
-      .poll(async () => await findKeyByAlias(page, E2E_DELETE_KEY_ALIAS), {
-        message: `key ${E2E_DELETE_KEY_ALIAS} still readable from /key/list after delete`,
+      .poll(async () => await findKeyByAlias(page, alias), {
+        message: `key ${alias} still readable from /key/list after delete`,
         timeout: 15_000,
       })
       .toBeUndefined();
diff --git a/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts b/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts
new file mode 100644
index 00000000000..5a8bc84cc13
--- /dev/null
+++ b/tests/e2e/ui/tests/proxy-admin/secondAdmin.spec.ts
@@ -0,0 +1,97 @@
+import { test, expect } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+
+test.describe("Second proxy admin", () => {
+  test.use({ storageState: { cookies: [], origins: [] } });
+
+  test("an invited admin can log in, mint a key, and call a model with it", async ({ page, browser, request }) => {
+    const suffix = Date.now();
+    const email = `second-admin-${suffix}@test.local`;
+    const password = "e2e-second-admin-password";
+    const auth = { Authorization: `Bearer ${masterKey()}` };
+
+    const inviteAdminUser = async (): Promise<string> => {
+      const adminContext = await browser.newContext({ storageState: ADMIN_STORAGE_PATH });
+      try {
+        const adminPage = await adminContext.newPage();
+        await navigateToPage(adminPage, Page.Users);
+        await dismissFeedbackPopup(adminPage);
+
+        await adminPage.getByRole("button", { name: "+ Invite User", exact: true }).click();
+        const dialog = adminPage.getByRole("dialog", { name: "Invite User" });
+        await expect(dialog).toBeVisible({ timeout: 5_000 });
+
+        await dialog.getByLabel("User Email").fill(email);
+
+        await dialog.getByLabel(/Global Proxy Role/).click();
+        await adminPage.getByRole("option", { name: /Admin \(All Permissions\)/ }).click();
+
+        const createdResponse = adminPage.waitForResponse(
+          (res) => res.url().includes("/user/new") && res.request().method() === "POST",
+        );
+        await dialog.getByRole("button", { name: "Invite User" }).click();
+        const createdBody = await (await createdResponse).json();
+        const createdUserId = (createdBody.data?.user_id ?? createdBody.user_id) as string;
+        expect(createdUserId, "created user id from /user/new").toBeTruthy();
+
+        await expect(adminPage.getByText("API user Created").first()).toBeVisible({ timeout: 10_000 });
+        return createdUserId;
+      } finally {
+        await adminContext.close();
+      }
+    };
+
+    const userId = await inviteAdminUser();
+    try {
+      const passwordRes = await request.post("/user/update", {
+        headers: auth,
+        data: { user_email: email, password },
+      });
+      expect(passwordRes.ok(), `setting password failed (${passwordRes.status()}): ${await passwordRes.text()}`).toBe(
+        true,
+      );
+
+      await page.goto("/ui/login");
+      await page.getByPlaceholder("Enter your username").fill(email);
+      await page.getByPlaceholder("Enter your password").fill(password);
+      await page.getByRole("button", { name: "Login", exact: true }).click();
+      await expect(page.locator("a", { hasText: "Virtual Keys" })).toBeVisible({ timeout: 30_000 });
+      await dismissFeedbackPopup(page);
+
+      await navigateToPage(page, Page.ApiKeys);
+      await page.getByRole("button", { name: /Create New Key/i }).click();
+      await expect(page.getByText("Key Ownership")).toBeVisible({ timeout: 10_000 });
+
+      await page.getByLabel(/Key Name/).fill(`e2e-second-admin-key-${suffix}`);
+
+      await page.getByRole("combobox", { name: "Select models" }).click();
+      await page.getByRole("option", { name: "All Proxy Models", exact: true }).click();
+      await page.keyboard.press("Escape");
+
+      await page.getByRole("button", { name: "Create Key", exact: true }).click();
+
+      await expect(page.getByText("Save your Key")).toBeVisible({ timeout: 10_000 });
+      const apiKey = (await page.getByRole("dialog", { name: "Save your Key" }).locator("pre").innerText()).trim();
+      expect(apiKey).toMatch(/^sk-/);
+      await page.keyboard.press("Escape");
+
+      const response = await page.request.post("/chat/completions", {
+        headers: { Authorization: `Bearer ${apiKey}` },
+        data: {
+          model: CHAT_MODEL_A,
+          messages: [{ role: "user", content: `second admin ping ${suffix}` }],
+        },
+      });
+      expect(response.status()).toBe(200);
+      const body = await response.json();
+      expect(body.choices?.[0]?.message?.content).toBe(MOCK_RESPONSE_TEXT);
+    } finally {
+      if (userId) {
+        await request.post("/user/delete", { headers: auth, data: { user_ids: [userId] } });
+      }
+    }
+  });
+});
diff --git a/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts b/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts
new file mode 100644
index 00000000000..e71945a4ccd
--- /dev/null
+++ b/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts
@@ -0,0 +1,162 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
+import { readBack } from "../../helpers/roundTrip";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+
+interface TeamInfo {
+  team_id: string;
+  team_alias: string;
+  models: string[];
+  max_budget: number | null;
+  tpm_limit: number | null;
+  rpm_limit: number | null;
+  metadata: Record<string, unknown> | null;
+  members_with_roles: { user_id?: string; role?: string }[];
+}
+
+/**
+ * Each test owns a team it created, rather than editing a seeded one, so a save that clobbers a
+ * field cannot take another spec's fixture down with it.
+ */
+async function createTeam(page: PlaywrightPage, alias: string, members: string[] = []): Promise<string> {
+  const res = await page.request.post("/team/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: {
+      team_alias: alias,
+      models: [CHAT_MODEL_A],
+      members_with_roles: members.map((user_id) => ({ user_id, role: "user" })),
+    },
+  });
+  expect(res.ok(), `POST /team/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return (await res.json()).team_id as string;
+}
+
+/**
+ * A member of this test's own, not one of the seeded users. Putting a seeded user on an extra team
+ * changes what every spec that asserts on their memberships sees.
+ */
+async function createMember(page: PlaywrightPage, userId: string): Promise<string> {
+  const res = await page.request.post("/user/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { user_id: userId, user_role: "internal_user", auto_create_key: false },
+  });
+  expect(res.ok(), `POST /user/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return userId;
+}
+
+async function teamInfo(page: PlaywrightPage, teamId: string): Promise<TeamInfo> {
+  const body = await readBack<{ team_info: TeamInfo }>(page, `/team/info?team_id=${encodeURIComponent(teamId)}`);
+  return body.team_info;
+}
+
+async function openTeamSettings(page: PlaywrightPage, teamId: string): Promise<void> {
+  await navigateToPage(page, Page.Teams);
+  await dismissFeedbackPopup(page);
+  await clickTeamId(page, teamId);
+  await page.getByRole("tab", { name: "Settings" }).click();
+  await page.getByRole("button", { name: "Edit Settings" }).click();
+  await expect(page.getByRole("button", { name: "Save Changes" })).toBeVisible({ timeout: 10_000 });
+}
+
+test.describe("Proxy Admin - Team settings", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Setting a team's spend cap and rate limits leaves its models and members alone", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-limits-${stamp}`;
+    const member = await createMember(page, `e2e-team-limits-member-${stamp}`);
+    const teamId = await createTeam(page, alias, [member]);
+    const before = await teamInfo(page, teamId);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("42.5");
+    await page.getByRole("spinbutton", { name: "Tokens per minute Limit (TPM)" }).fill("7000");
+    await page.getByRole("spinbutton", { name: "Requests per minute Limit (RPM)" }).fill("70");
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(
+        async () => {
+          const team = await teamInfo(page, teamId);
+          return [team.max_budget, team.tpm_limit, team.rpm_limit];
+        },
+        { message: "team limits did not persist", timeout: 20_000 },
+      )
+      .toEqual([42.5, 7000, 70]);
+
+    // The Settings form posts the whole team. A field it fails to seed goes back as null, and
+    // the toast still says success, so pin the fields this edit had no business touching.
+    const after = await teamInfo(page, teamId);
+    expect(after.models, "model access untouched by a limits edit").toEqual(before.models);
+    expect(
+      after.members_with_roles.map((member) => member.user_id).sort(),
+      "membership untouched by a limits edit",
+    ).toEqual(before.members_with_roles.map((member) => member.user_id).sort());
+  });
+
+  test("A model alias added on the Settings tab serves traffic under the alias name", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-alias-${stamp}`;
+    const modelAlias = `e2e-alias-${stamp}`;
+    const teamId = await createTeam(page, alias);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("textbox", { name: "Alias Name" }).fill(modelAlias);
+    await page.getByRole("combobox", { name: "Select target model" }).click();
+    await page.getByRole("option", { name: CHAT_MODEL_A, exact: true }).first().click();
+    await page.getByRole("button", { name: "Add Alias" }).click();
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(async () => (await teamInfo(page, teamId)).models, { message: "team lost its models", timeout: 20_000 })
+      .toEqual([CHAT_MODEL_A]);
+
+    const keyRes = await page.request.post("/key/generate", {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+      data: { team_id: teamId, key_alias: `e2e-alias-key-${stamp}` },
+    });
+    expect(keyRes.ok(), `POST /key/generate failed (${keyRes.status()})`).toBe(true);
+    const teamKey = (await keyRes.json()).key as string;
+
+    // An alias the team can see but cannot call is the actual complaint; the readback alone
+    // would pass for an alias the router never resolves.
+    const served = await page.request.post("/v1/chat/completions", {
+      headers: { Authorization: `Bearer ${teamKey}`, "Content-Type": "application/json" },
+      data: { model: modelAlias, messages: [{ role: "user", content: "ping" }] },
+    });
+    expect(served.status(), `a team key calling ${modelAlias} is served`).toBe(200);
+    expect((await served.json()).choices?.[0]?.message?.content).toContain(MOCK_RESPONSE_TEXT);
+  });
+
+  test("Team metadata added as key-value pairs survives a reload", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-metadata-${stamp}`;
+    const metadataValue = `cost-center-${stamp}`;
+    const teamId = await createTeam(page, alias);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("button", { name: "Add Key-Value Pair" }).click();
+    await page.getByPlaceholder("Key", { exact: true }).last().fill("owner");
+    await page.getByPlaceholder("Value", { exact: true }).last().fill(metadataValue);
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(async () => (await teamInfo(page, teamId)).metadata?.owner, {
+        message: "team metadata did not persist",
+        timeout: 20_000,
+      })
+      .toBe(metadataValue);
+
+    // Reopening the form is the step that catches metadata the page writes but cannot read back.
+    await page.reload();
+    await page.getByRole("tab", { name: "Settings" }).click();
+    await page.getByRole("button", { name: "Edit Settings" }).click();
+    await expect(page.getByPlaceholder("Key", { exact: true })).toHaveValue("owner", { timeout: 15_000 });
+    await expect(page.getByPlaceholder("Value", { exact: true })).toHaveValue(metadataValue);
+  });
+});
diff --git a/tests/e2e/ui/tests/proxy-admin/teams.spec.ts b/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
index 7383b452162..303e4488e09 100644
--- a/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
+++ b/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
@@ -1,14 +1,9 @@
 import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
-import {
-  ADMIN_STORAGE_PATH,
-  E2E_TEAM_CRUD_ID,
-  E2E_TEAM_DELETE_ALIAS,
-  E2E_TEAM_NO_ADMIN_ID,
-  E2E_TEAM_ORG_ID,
-} from "../../constants";
+import { ADMIN_STORAGE_PATH, E2E_TEAM_CRUD_ID, E2E_TEAM_NO_ADMIN_ID, E2E_TEAM_ORG_ID } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
 import { readBack } from "../../helpers/roundTrip";
+import { masterKey } from "../../helpers/traffic";
 
 /** GET /team/list returns a bare array of teams, each carrying team_alias/team_id. */
 async function findTeamByAlias(page: PlaywrightPage, alias: string): Promise<Record<string, any> | undefined> {
@@ -25,6 +20,17 @@ async function teamMemberEmails(page: PlaywrightPage, teamId: string): Promise<s
   return (info.team_info.members_with_roles ?? []).map((member) => member.user_email ?? "").filter(Boolean);
 }
 
+/** A team this test owns, so deleting it costs the suite nothing on a retry or a second run. */
+async function createDeletableTeam(page: PlaywrightPage): Promise<string> {
+  const alias = `e2e-delete-team-${Date.now()}`;
+  const res = await page.request.post("/team/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { team_alias: alias, models: ["fake-openai-gpt-4"] },
+  });
+  expect(res.ok(), `POST /team/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return alias;
+}
+
 test.describe("Proxy Admin - Teams", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
@@ -121,10 +127,14 @@ test.describe("Proxy Admin - Teams", () => {
   });
 
   test("Delete a team", async ({ page }) => {
+    // Deleting the seeded team leaves nothing for the next attempt, so the retries CI runs with are
+    // guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const alias = await createDeletableTeam(page);
+
     await navigateToPage(page, Page.Teams);
     await dismissFeedbackPopup(page);
 
-    const teamRow = page.locator("tr", { hasText: E2E_TEAM_DELETE_ALIAS }).first();
+    const teamRow = page.locator("tr", { hasText: alias }).first();
     await expect(teamRow).toBeVisible({ timeout: 10_000 });
     // Actions live in a kebab menu: open it, then click "Delete team".
     await teamRow.locator('[data-testid^="team-actions-"]').click();
@@ -132,15 +142,15 @@ test.describe("Proxy Admin - Teams", () => {
 
     const modal = page.getByRole("dialog", { name: "Delete Team?" });
     await expect(modal).toBeVisible({ timeout: 5_000 });
-    await modal.locator("input").fill(E2E_TEAM_DELETE_ALIAS);
+    await modal.locator("input").fill(alias);
     await modal.getByRole("button", { name: /Force Delete|Delete/i }).click();
 
     await expect(teamRow).not.toBeVisible({ timeout: 10_000 });
 
     // A row vanishing is local state, which happens whether or not the delete landed.
     await expect
-      .poll(async () => await findTeamByAlias(page, E2E_TEAM_DELETE_ALIAS), {
-        message: `team ${E2E_TEAM_DELETE_ALIAS} still readable from /team/list after delete`,
+      .poll(async () => await findTeamByAlias(page, alias), {
+        message: `team ${alias} still readable from /team/list after delete`,
         timeout: 15_000,
       })
       .toBeUndefined();
diff --git a/tests/e2e/ui/tests/settings/scim.spec.ts b/tests/e2e/ui/tests/settings/scim.spec.ts
new file mode 100644
index 00000000000..d7dd4248f50
--- /dev/null
+++ b/tests/e2e/ui/tests/settings/scim.spec.ts
@@ -0,0 +1,53 @@
+import { test, expect, Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage } from "../../helpers/navigation";
+
+const rootPath = (): string => process.env.SERVER_ROOT_PATH ?? "";
+
+async function createScimTokenViaUi(page: PlaywrightPage, alias: string): Promise<string> {
+  await navigateToPage(page, Page.AdminPanel);
+  await page.getByRole("tab", { name: "SCIM" }).click();
+
+  await expect(page.getByText("SCIM Tenant URL")).toBeVisible();
+  await expect(page.locator("input[disabled]").first()).toHaveValue(/\/scim\/v2$/);
+
+  await page.getByLabel("Token Name").fill(alias);
+  await page.getByRole("button", { name: "Create SCIM Token" }).click();
+
+  await expect(page.getByText(/copy this token now/i)).toBeVisible({ timeout: 15_000 });
+  const token = await page.locator('input[type="password"]').inputValue();
+  expect(token, "the one-time token panel shows a usable virtual key").toMatch(/^sk-/);
+  return token;
+}
+
+test.describe("Admin Settings - SCIM", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Create SCIM Token shows the token once and offers to create another", async ({ page }) => {
+    await createScimTokenViaUi(page, `e2e-scim-ui-${Date.now()}`);
+
+    await page.getByRole("button", { name: "Create Another Token" }).click();
+    await expect(page.getByRole("button", { name: "Create SCIM Token" })).toBeVisible();
+    await expect(page.getByText(/copy this token now/i)).toBeHidden();
+  });
+
+  test("a UI-minted SCIM token authorizes the SCIM API", async ({ page, request }) => {
+    test.skip(!process.env.LITELLM_LICENSE, "LITELLM_LICENSE not set in test env — /scim/v2 is premium-gated");
+
+    const token = await createScimTokenViaUi(page, `e2e-scim-api-${Date.now()}`);
+
+    const denied = await request.get(`${rootPath()}/scim/v2/Groups`, {
+      headers: { Authorization: "Bearer sk-not-a-real-key" },
+    });
+    expect(denied.status(), "an unknown key must not reach SCIM").toBe(401);
+
+    const res = await request.get(`${rootPath()}/scim/v2/Groups`, {
+      headers: { Authorization: `Bearer ${token}` },
+    });
+    expect(res.status(), `SCIM Groups listing failed: ${await res.text()}`).toBe(200);
+    const body = await res.json();
+    expect(body.schemas, "SCIM answers with a ListResponse").toContain("urn:ietf:params:scim:api:messages:2.0:ListResponse");
+    expect(Array.isArray(body.Resources), "SCIM ListResponse carries a Resources array").toBe(true);
+  });
+});
diff --git a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
index f93cca75347..f3c031f0172 100644
--- a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
+++ b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
@@ -1,6 +1,7 @@
 import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
 import {
   E2E_INTERNAL_USER_KEY_ALIAS,
+  E2E_TEAM_ADMIN_USER_ID,
   E2E_TEAM_CRUD_ALIAS,
   E2E_TEAM_CRUD_ID,
   TEAM_ADMIN_STORAGE_PATH,
@@ -8,6 +9,8 @@ import {
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
 import { captureRequestBody, readBack } from "../../helpers/roundTrip";
+import { CHAT_MODEL_A, masterKey } from "../../helpers/traffic";
+import { keySourceSelect, modelSelect, onlyVisible, openPlayground } from "../../helpers/playground";
 
 /**
  * Every identifier a roster is addressable by. Which of user_id / user_email is populated depends on
@@ -32,7 +35,44 @@ async function findKeyByAlias(page: PlaywrightPage, alias: string): Promise<Reco
   return body.keys.find((row) => row.key_alias === alias);
 }
 
+/** A member this test adds itself, so removing it costs the suite nothing on a retry or a re-run. */
+async function addRemovableMember(page: PlaywrightPage, registerForCleanup: string[]): Promise<string> {
+  const userId = `e2e-removable-${Date.now()}`;
+  // Claimed before the call: /user/new can persist the user and still answer non-2xx, and the id is
+  // ours either way, so registering it up front is what no failure path can skip.
+  registerForCleanup.push(userId);
+  const created = await page.request.post("/user/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { user_id: userId, user_role: "internal_user", auto_create_key: false },
+  });
+  expect(created.ok(), `POST /user/new failed (${created.status()}): ${await created.text()}`).toBe(true);
+
+  const added = await page.request.post("/team/member_add", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { team_id: E2E_TEAM_CRUD_ID, member: { user_id: userId, role: "user" } },
+  });
+  expect(added.ok(), `POST /team/member_add failed (${added.status()}): ${await added.text()}`).toBe(true);
+  return userId;
+}
+
 test.describe("Team Admin", () => {
+  const createdMembers: string[] = [];
+
+  test.afterEach(async ({ page }) => {
+    // Runs on the failure path too, which a call at the end of the test body would not. Ids are
+    // claimed before the user is created, so the delete is attempted unconditionally and only its
+    // own 404 counts as never persisted; any other answer is a cleanup failure worth reporting
+    // rather than a reason to leave the user behind.
+    for (const userId of createdMembers.splice(0)) {
+      const deleted = await page.request.post("/user/delete", {
+        headers: { Authorization: `Bearer ${masterKey()}` },
+        data: { user_ids: [userId] },
+      });
+      const settled = deleted.ok() || deleted.status() === 404;
+      expect(settled, `POST /user/delete for ${userId} (${deleted.status()}): ${await deleted.text()}`).toBe(true);
+    }
+  });
+
   test.use({ storageState: TEAM_ADMIN_STORAGE_PATH });
 
   test("Team admin can see all team keys including internal user keys", async ({ page }) => {
@@ -92,6 +132,10 @@ test.describe("Team Admin", () => {
   });
 
   test("Team admin can remove a member from their team", async ({ page }) => {
+    // Removing the seeded member leaves nothing for the next attempt, so the retries CI runs with
+    // are guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const memberId = await addRemovableMember(page, createdMembers);
+
     await navigateToPage(page, Page.Teams);
     await dismissFeedbackPopup(page);
 
@@ -99,9 +143,9 @@ test.describe("Team Admin", () => {
 
     await page.getByRole("tab", { name: "Members" }).click();
 
-    // Seeded members appear in the roster by user_id (members_with_roles has no
-    // email), so match the row on the user_id rather than the email.
-    const row = page.locator("tr", { hasText: "e2e-removable-member" }).first();
+    // Members appear in the roster by user_id (members_with_roles has no email), so match
+    // the row on the user_id rather than the email.
+    const row = page.locator("tr", { hasText: memberId }).first();
     await expect(row).toBeVisible({ timeout: 10_000 });
     await row.getByTestId("delete-member").click();
 
@@ -114,7 +158,7 @@ test.describe("Team Admin", () => {
     // Removing the wrong member is exactly what a success toast hides, so pin both halves.
     expect(remove.team_id, "delete targets the team being viewed").toBe(E2E_TEAM_CRUD_ID);
     expect([remove.user_id, remove.user_email], "delete identifies the member whose row was clicked").toContain(
-      "e2e-removable-member",
+      memberId,
     );
 
     await expect(page.getByText("Team member removed successfully").first()).toBeVisible({ timeout: 10_000 });
@@ -125,7 +169,92 @@ test.describe("Team Admin", () => {
         message: "removed member is still on the team",
         timeout: 15_000,
       })
-      .not.toContain("e2e-removable-member");
+      .not.toContain(memberId);
+  });
+
+  test("Team admin sees all team models in the Playground model dropdown", async ({ page, request }) => {
+    const suffix = Date.now();
+    const teamModelName = `e2e-team-dropdown-model-${suffix}`;
+    const auth = { Authorization: `Bearer ${masterKey()}` };
+
+    const teamRes = await request.post("/team/new", {
+      headers: auth,
+      data: {
+        team_alias: `e2e-playground-team-${suffix}`,
+        models: [CHAT_MODEL_A],
+        members_with_roles: [{ role: "admin", user_id: E2E_TEAM_ADMIN_USER_ID }],
+      },
+    });
+    expect(teamRes.ok(), `team create failed (${teamRes.status()}): ${await teamRes.text()}`).toBe(true);
+    const teamId = (await teamRes.json()).team_id as string;
+
+    try {
+      const modelRes = await request.post("/model/new", {
+        headers: auth,
+        data: {
+          model_name: teamModelName,
+          litellm_params: {
+            model: "openai/fake-gpt-4",
+            api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`,
+            api_key: "fake-key",
+          },
+          model_info: { team_id: teamId },
+        },
+      });
+      expect(modelRes.ok(), `model create failed (${modelRes.status()}): ${await modelRes.text()}`).toBe(true);
+      const modelId = (await modelRes.json()).model_info?.id as string;
+
+      try {
+        const keyRes = await request.post("/key/generate", { headers: auth, data: { team_id: teamId } });
+        expect(keyRes.ok(), `key generate failed (${keyRes.status()}): ${await keyRes.text()}`).toBe(true);
+        const teamKey = (await keyRes.json()).key as string;
+
+        try {
+          await expect
+            .poll(
+              async () => {
+                const res = await request.get("/model_group/info", {
+                  headers: { Authorization: `Bearer ${teamKey}` },
+                });
+                if (!res.ok()) return false;
+                const body: { data?: { model_group?: string }[] } = await res.json();
+                return (body.data ?? []).some((group) => group.model_group === teamModelName);
+              },
+              {
+                message: `model group ${teamModelName} never became visible to the team key`,
+                timeout: 30_000,
+              },
+            )
+            .toBe(true);
+
+          await openPlayground(page);
+          await keySourceSelect(page).click();
+          await onlyVisible(page.getByRole("option", { name: "Virtual Key" })).click({ timeout: 15_000 });
+
+          const keyInput = onlyVisible(page.getByPlaceholder("Enter custom Virtual Key"));
+          await expect(keyInput).toBeVisible({ timeout: 10_000 });
+          await keyInput.fill(teamKey);
+
+          const select = modelSelect(page);
+          await select.click();
+          await select.fill(teamModelName);
+          await expect(onlyVisible(page.getByRole("option", { name: teamModelName }))).toBeVisible({
+            timeout: 15_000,
+          });
+
+          await select.fill(CHAT_MODEL_A);
+          await expect(onlyVisible(page.getByRole("option", { name: CHAT_MODEL_A }))).toBeVisible({
+            timeout: 15_000,
+          });
+        } finally {
+          await request.post("/key/delete", { headers: auth, data: { keys: [teamKey] } });
+        }
+      } finally {
+        await request.post("/model/delete", { headers: auth, data: { id: modelId } });
+      }
+    } finally {
+      await request.post("/team/delete", { headers: auth, data: { team_ids: [teamId] } });
+    }
   });
 
   test("Team admin can create a team key with All Team Models", async ({ page }) => {
@@ -142,7 +271,7 @@ test.describe("Team Admin", () => {
     const teamSelect = page.getByTestId("team-dropdown").getByRole("combobox");
     await teamSelect.click();
     await page.keyboard.type(E2E_TEAM_CRUD_ALIAS);
-    await page.locator('[data-slot="combobox-content"]:visible').getByText(E2E_TEAM_CRUD_ALIAS).first().click();
+    await page.getByRole("option", { name: E2E_TEAM_CRUD_ALIAS }).first().click();
 
     // Models — pick "All Team Models". The popup is portaled to the body, so
     // scope the option lookup to the page.
diff --git a/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts b/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts
new file mode 100644
index 00000000000..2ee5ae3e392
--- /dev/null
+++ b/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts
@@ -0,0 +1,135 @@
+import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { Page } from "../../fixtures/pages";
+import {
+  CHAT_MODEL_A,
+  CHAT_MODEL_B,
+  DEPLOYMENT_MODEL_A,
+  DEPLOYMENT_MODEL_B,
+  createVirtualKey,
+  masterKey,
+  rootPath,
+  sendChatCompletion,
+  waitForKeyInDailyActivity,
+  waitForSpendLog,
+} from "../../helpers/traffic";
+
+/**
+ * Covers the per-entity breakdowns on /ui/usage. The page-level totals move with every other spec's
+ * traffic, so each assertion is scoped to a key this test minted and to the requests it sent.
+ */
+
+/** Each breakdown renders one expandable card per entity, named "<entity> $x.xx N requests". */
+const entityCard = (page: PlaywrightPage, tab: string, name: string): Locator =>
+  page.getByRole("tabpanel", { name: tab }).getByRole("button", { name: new RegExp(`^${name}\\s`) });
+
+async function openUsageTab(page: PlaywrightPage, tab: string): Promise<Locator> {
+  await navigateToPage(page, Page.NewUsage);
+  await dismissFeedbackPopup(page);
+  await page.getByRole("tab", { name: tab }).click();
+  const panel = page.getByRole("tabpanel", { name: tab });
+  await expect(panel).toBeVisible({ timeout: 30_000 });
+  return panel;
+}
+
+/** Sends `count` completions on one model and waits for each to reach the spend log. */
+async function sendTraffic(
+  request: Parameters<typeof sendChatCompletion>[0],
+  apiKey: string,
+  model: string,
+  count: number,
+  label: string,
+): Promise<void> {
+  for (let i = 0; i < count; i++) {
+    const requestId = await sendChatCompletion(request, { model, prompt: `${label} ${i}`, apiKey });
+    await waitForSpendLog(request, requestId);
+  }
+}
+
+test.describe("Usage page activity tabs", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Key Activity breaks a key's traffic down by model", async ({ page, request }) => {
+    const alias = `e2e-usage-keyact-${Date.now()}`;
+    const { key, token } = await createVirtualKey(request, { key_alias: alias });
+
+    // An uneven split, so a breakdown that lumps everything into one row or attributes to the
+    // wrong model cannot land on these numbers by accident.
+    await sendTraffic(request, key, CHAT_MODEL_A, 2, alias);
+    await sendTraffic(request, key, CHAT_MODEL_B, 1, alias);
+    await waitForKeyInDailyActivity(request, token, 3);
+
+    await openUsageTab(page, "Key Activity");
+
+    const card = entityCard(page, "Key Activity", alias);
+    await expect(card, `${alias} missing from Key Activity`).toBeVisible({ timeout: 30_000 });
+    await expect(card).toContainText("3 requests");
+
+    // Every key gets a card, and the page opens the first one. Scope to this key's own section,
+    // which the collapsible renders as the trigger's next sibling.
+    await card.click();
+    const details = card.locator("xpath=following-sibling::*[1]");
+    const successfulFor = (model: string) =>
+      details.getByRole("row").filter({ hasText: model }).getByRole("cell").nth(2); // Model | Spend | Successful | Failed | Tokens
+
+    await expect(successfulFor(DEPLOYMENT_MODEL_A)).toHaveText("2", { timeout: 20_000 });
+    await expect(successfulFor(DEPLOYMENT_MODEL_B)).toHaveText("1");
+  });
+
+  test("Model Activity can name its models by deployment instead of by public name", async ({ page, request }) => {
+    const alias = `e2e-usage-modelact-${Date.now()}`;
+    const { key, token } = await createVirtualKey(request, { key_alias: alias });
+    await sendTraffic(request, key, CHAT_MODEL_A, 1, alias);
+    await waitForKeyInDailyActivity(request, token);
+
+    const panel = await openUsageTab(page, "Model Activity");
+
+    await expect(entityCard(page, "Model Activity", CHAT_MODEL_A), `${CHAT_MODEL_A} missing`).toBeVisible({
+      timeout: 30_000,
+    });
+    // Nothing is published under the deployment's name, so its absence here is what makes the
+    // toggle below a real change of key rather than a relabelled button.
+    await expect(entityCard(page, "Model Activity", DEPLOYMENT_MODEL_A)).toHaveCount(0);
+
+    // Admins reconcile provider bills against the deployment, not the name their users call.
+    await panel.getByRole("button", { name: "Litellm Model Name" }).click();
+    await expect(entityCard(page, "Model Activity", DEPLOYMENT_MODEL_A)).toBeVisible({ timeout: 20_000 });
+  });
+
+  test("Filter by user narrows Key Activity to that user's keys", async ({ page, request }) => {
+    const stamp = Date.now();
+    const email = `e2e-usage-owner-${stamp}@test.local`;
+    const ownedAlias = `e2e-usage-owned-${stamp}`;
+    const otherAlias = `e2e-usage-other-${stamp}`;
+
+    const userRes = await request.post(`${rootPath()}/user/new`, {
+      headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+      data: { user_email: email, user_role: "internal_user", auto_create_key: false },
+    });
+    expect(userRes.ok(), `POST /user/new failed (${userRes.status()})`).toBe(true);
+    const userId = (await userRes.json()).user_id as string;
+
+    const owned = await createVirtualKey(request, { key_alias: ownedAlias, user_id: userId });
+    const other = await createVirtualKey(request, { key_alias: otherAlias });
+    await sendTraffic(request, owned.key, CHAT_MODEL_A, 1, ownedAlias);
+    await sendTraffic(request, other.key, CHAT_MODEL_A, 1, otherAlias);
+    await waitForKeyInDailyActivity(request, owned.token);
+    await waitForKeyInDailyActivity(request, other.token);
+
+    await openUsageTab(page, "Key Activity");
+    await expect(entityCard(page, "Key Activity", otherAlias)).toBeVisible({ timeout: 30_000 });
+
+    await page.getByRole("combobox", { name: "Search users by email" }).click();
+    await page.keyboard.type(email);
+    await page
+      .getByRole("option", { name: new RegExp(email) })
+      .first()
+      .click();
+
+    // The filter earns its place only by dropping the other key; the owned key showing up
+    // proves nothing on a page that already listed every key.
+    await expect(entityCard(page, "Key Activity", otherAlias)).toHaveCount(0, { timeout: 30_000 });
+    await expect(entityCard(page, "Key Activity", ownedAlias)).toBeVisible({ timeout: 20_000 });
+  });
+});
diff --git a/tests/e2e/ui/tests/usage/usagePage.spec.ts b/tests/e2e/ui/tests/usage/usagePage.spec.ts
index 8fa59beb905..3d057cfa2c9 100644
--- a/tests/e2e/ui/tests/usage/usagePage.spec.ts
+++ b/tests/e2e/ui/tests/usage/usagePage.spec.ts
@@ -1,10 +1,11 @@
-import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { test, expect, type APIRequestContext, type Locator, type Page as PlaywrightPage } from "@playwright/test";
 import { ADMIN_STORAGE_PATH } from "../../constants";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
 import {
-  CHAT_MODEL_A,
   createVirtualKey,
+  masterKey,
+  rootPath,
   sendChatCompletion,
   waitForKeyInDailyActivity,
   waitForSpendLog,
@@ -27,9 +28,105 @@ async function openUsage(page: PlaywrightPage): Promise<Locator> {
   return card;
 }
 
+/** The upstream fixtures/config.yml points its models at, so the mock server answers this too. */
+const MOCK_DEPLOYMENT = "openai/fake-gpt-4";
+
+/** A deployment whose traffic costs real money, so the key that used it outranks the $0 crowd. */
+async function createPricedDeployment(
+  request: APIRequestContext,
+  label: string,
+  registerForCleanup: string[],
+): Promise<{ modelName: string }> {
+  const modelName = `e2e-usage-priced-${label}`;
+  // Claimed before the call: /model/new can persist the deployment and still answer non-2xx, so a
+  // name recorded up front is the only registration no response shape can skip.
+  registerForCleanup.push(modelName);
+  const res = await request.post("/model/new", {
+    headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+    data: {
+      model_name: modelName,
+      litellm_params: {
+        model: MOCK_DEPLOYMENT,
+        api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`,
+        api_key: "fake-key",
+        input_cost_per_token: 0.01,
+        output_cost_per_token: 0.01,
+      },
+    },
+  });
+  expect(res.ok(), `POST /model/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+
+  // /model/new returns once the row is written, but the router only picks the deployment up on its
+  // next refresh, so sending traffic straight away can still get "no healthy deployments". A ping
+  // that fails writes no spend log, so retrying it costs the ranking this test asserts nothing.
+  await expect
+    .poll(
+      async () => {
+        const ping = await request.post(`${rootPath()}/v1/chat/completions`, {
+          headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+          data: { model: modelName, messages: [{ role: "user", content: "readiness ping" }] },
+        });
+        return ping.ok();
+      },
+      { message: `deployment ${modelName} never became routable`, timeout: 60_000 },
+    )
+    .toBe(true);
+
+  return { modelName };
+}
+
 test.describe("Usage page", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
+  const pricedDeployments: string[] = [];
+
+  test.afterEach(async ({ request }) => {
+    // A deployment left behind keeps its custom pricing, so it goes on changing what later runs
+    // route and what they cost. Runs on the failure path too, which the test body would not.
+    // Resolved by name rather than by a returned id, so a create that persisted without answering
+    // 2xx is still cleaned up. /model/info serves the router, and /model/new answers 2xx even when
+    // its in-request router reload failed, so the search-backed listing is what covers a deployment
+    // that reached the database only. Absent from both means it never persisted.
+    const names = pricedDeployments.splice(0);
+    if (names.length === 0) return;
+    const auth = { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" };
+
+    type Lookup =
+      | { readonly listed: true; readonly id: string | undefined }
+      | { readonly listed: false; readonly status: number };
+
+    const idIn = async (path: string, name: string): Promise<Lookup> => {
+      const listed = await request.get(path, { headers: auth });
+      if (!listed.ok()) return { listed: false, status: listed.status() };
+      const deployments = ((await listed.json()).data ?? []) as {
+        model_name?: string;
+        model_info?: { id?: string };
+      }[];
+      return { listed: true, id: deployments.find((d) => d.model_name === name)?.model_info?.id };
+    };
+
+    const remove = async (name: string, id: string) => {
+      const deleted = await request.post(`${rootPath()}/model/delete`, { headers: auth, data: { id } });
+      expect(deleted.ok(), `POST /model/delete for ${name} (${deleted.status()})`).toBe(true);
+    };
+
+    for (const name of names) {
+      const fromRouter = await idIn(`${rootPath()}/model/info`, name);
+      if (fromRouter.listed && fromRouter.id !== undefined) {
+        await remove(name, fromRouter.id);
+        continue;
+      }
+      const search = encodeURIComponent(name);
+      const fromDb = await idIn(`${rootPath()}/v2/model/info?search=${search}`, name);
+      expect(
+        fromDb.listed,
+        `GET /v2/model/info?search=${search} (${fromDb.listed ? 200 : fromDb.status}), so ${name} could not be checked`,
+      ).toBe(true);
+      if (!fromDb.listed || fromDb.id === undefined) continue;
+      await remove(name, fromDb.id);
+    }
+  });
+
   test("Top Virtual Keys lists a key that served traffic, toggles views, and opens key info", async ({
     page,
     request,
@@ -39,8 +136,13 @@ test.describe("Usage page", () => {
       key_alias: alias,
     });
 
+    // Top Virtual Keys ranks by spend, and every mock deployment costs $0, so once a run has more
+    // keys than the list shows, whether this one makes the cut is down to how ties happen to sort.
+    // Give it a priced deployment of its own so it earns its place.
+    const { modelName } = await createPricedDeployment(request, alias, pricedDeployments);
+
     const requestId = await sendChatCompletion(request, {
-      model: CHAT_MODEL_A,
+      model: modelName,
       prompt: `usage ping for ${alias}`,
       apiKey: key,
     });
@@ -51,20 +153,19 @@ test.describe("Usage page", () => {
     const card = await openUsage(page);
 
     // Table view (the default): the key is listed by its alias.
-    const row = card.locator("tbody tr").filter({ hasText: alias });
+    const row = card.getByRole("row").filter({ hasText: alias });
     await expect(row, `${alias} missing from Top Virtual Keys`).toHaveCount(1, {
       timeout: 30_000,
     });
 
     // Chart view swaps the table out for the bar chart, and back.
     await card.getByText("Chart View", { exact: true }).click();
-    await expect(card.locator("tbody tr")).toHaveCount(0, { timeout: 10_000 });
+    await expect(card.getByRole("table")).toHaveCount(0, { timeout: 10_000 });
     await card.getByText("Table View", { exact: true }).click();
     await expect(row).toHaveCount(1, { timeout: 10_000 });
 
-    // Clicking the Key ID cell fetches key info and opens the detail panel.
     // The alias is already in the row behind the modal, so match the panel's own controls.
-    await row.locator("td").first().click();
+    await row.getByRole("button", { name: token }).click();
     const keyInfo = page.getByRole("tab", { name: "Overview", exact: true });
     await expect(keyInfo, "key info panel did not open").toBeVisible({
       timeout: 20_000,
diff --git a/tests/e2e/ui/tests/users/searchUsers.spec.ts b/tests/e2e/ui/tests/users/searchUsers.spec.ts
index e87218b5a5e..fa8f32764e8 100644
--- a/tests/e2e/ui/tests/users/searchUsers.spec.ts
+++ b/tests/e2e/ui/tests/users/searchUsers.spec.ts
@@ -1,91 +1,52 @@
-import { test, expect, Page } from "@playwright/test";
+import { test, expect, Page as PlaywrightPage } from "@playwright/test";
 import { ADMIN_STORAGE_PATH } from "../../constants";
-test.skip("Internal Users Search", () => {
+import { Page } from "../../fixtures/pages";
+import { navigateToPage } from "../../helpers/navigation";
+
+const userRows = (page: PlaywrightPage) => page.getByRole("row").filter({ has: page.getByRole("cell") });
+
+async function goToInternalUsers(page: PlaywrightPage) {
+  await navigateToPage(page, Page.Users);
+  await expect(page.getByRole("columnheader", { name: "User ID" })).toBeVisible({ timeout: 30_000 });
+  await expect(userRows(page)).not.toHaveCount(0, { timeout: 30_000 });
+}
+
+test.describe("Internal Users Search", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
-  async function goToInternalUsers(page: Page) {
-    await page.goto("/ui");
-
-    const tab = page.getByRole("menuitem", { name: "Internal User" });
-    await expect(tab).toBeVisible();
-    await tab.click();
-
-    await expect(page.locator("tbody tr").first()).toBeVisible();
-    await expect(page.locator('[data-slot="skeleton"]')).toHaveCount(0);
-  }
-
-  test("can search users by email", async ({ page }) => {
+  test("narrows the table to the matching email, and restores it when cleared", async ({ page }) => {
     await goToInternalUsers(page);
 
-    const rows = page.locator("tbody tr");
-    const searchInput = page.getByPlaceholder("Search by email...");
+    const search = page.getByPlaceholder("Search by email…");
+    await expect(search).toBeVisible();
 
-    await expect(searchInput).toBeVisible();
+    await search.fill("noteam@");
+    await expect(userRows(page)).toHaveCount(1, { timeout: 30_000 });
+    await expect(userRows(page).first()).toContainText("noteam@test.local");
 
-    // Ensure initial data is loaded
-    const initialCount = await rows.count();
-    expect(initialCount).toBeGreaterThan(0);
-
-    // 🔹 Apply filter + wait for backend response
-    await Promise.all([
-      page.waitForResponse(
-        (res) =>
-          res.url().includes("/user/list") &&
-          res.url().includes("user_email=test%40") && // encoded "test@"
-          res.status() === 200,
-      ),
-      searchInput.fill("test@"),
-    ]);
-    await page.waitForTimeout(5000);
-    const filteredCount = await rows.count();
-    await expect(filteredCount).toBeLessThan(initialCount);
-
-    // 🔹 Clear filter + wait for unfiltered request
-    await Promise.all([
-      page.waitForResponse(
-        (res) => res.url().includes("/user/list") && !res.url().includes("user_email=") && res.status() === 200,
-      ),
-      searchInput.clear(),
-    ]);
-
-    const resetCount = await rows.count();
-    await expect(resetCount).toBe(initialCount);
+    await search.clear();
+    await expect(userRows(page).filter({ hasText: "admin@test.local" })).not.toHaveCount(0, { timeout: 30_000 });
   });
 
-  test("can filter users by user ID and SSO ID", async ({ page }) => {
+  test("filters the table down to one user by user ID", async ({ page }) => {
     await goToInternalUsers(page);
-    const rows = page.locator("tbody tr");
 
-    // Ensure initial data is loaded
-    const initialCount = await rows.count();
-    expect(initialCount).toBeGreaterThan(0);
+    await page.getByRole("button", { name: "Filters" }).click();
+    await page.getByTestId("users-filter-user-id").fill("e2e-internal-noteam");
+    await page.getByTestId("filter-drawer-apply").click();
 
-    const filtersButton = page.getByRole("button", {
-      name: "Filters",
-      exact: true,
-    });
-    await filtersButton.click();
+    await expect(userRows(page)).toHaveCount(1, { timeout: 30_000 });
+    await expect(userRows(page).first()).toContainText("noteam@test.local");
+  });
 
-    const userIdInput = page.getByPlaceholder("Filter by User ID");
-    const ssoIdInput = page.getByPlaceholder("Filter by SSO ID");
-    await Promise.all([
-      page.waitForResponse(
-        (res) => res.url().includes("/user/list") && res.url().includes("user_ids=user") && res.status() === 200,
-      ),
-      userIdInput.fill("user"),
-    ]);
+  test("shows no users when the SSO ID matches nobody", async ({ page }) => {
+    await goToInternalUsers(page);
 
-    await Promise.all([
-      page.waitForResponse(
-        (res) =>
-          res.url().includes("/user/list") &&
-          res.url().includes("user_ids=user") &&
-          res.url().includes("sso_user_ids=sso") &&
-          res.status() === 200,
-      ),
-      ssoIdInput.fill("sso"),
-    ]);
-    const combinedFilteredCount = await rows.count();
-    await expect(combinedFilteredCount).toBeLessThan(initialCount);
+    await page.getByRole("button", { name: "Filters" }).click();
+    await page.getByTestId("users-filter-sso-id").fill("e2e-sso-id-that-matches-nobody");
+    await page.getByTestId("filter-drawer-apply").click();
+
+    await expect(page.getByText("No users found")).toBeVisible({ timeout: 30_000 });
+    await expect(userRows(page).filter({ hasText: "noteam@test.local" })).toHaveCount(0);
   });
 });
diff --git a/tests/e2e/ui/tests/users/viewInternalUsers.spec.ts b/tests/e2e/ui/tests/users/viewInternalUsers.spec.ts
index 614191372d0..b46fb4d112a 100644
--- a/tests/e2e/ui/tests/users/viewInternalUsers.spec.ts
+++ b/tests/e2e/ui/tests/users/viewInternalUsers.spec.ts
@@ -1,54 +1,29 @@
-import { test, expect, Page } from "@playwright/test";
+import { test, expect, Page as PlaywrightPage } from "@playwright/test";
 import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage } from "../../helpers/navigation";
 
-test.skip("Internal Users Page", () => {
+async function goToInternalUsers(page: PlaywrightPage) {
+  await navigateToPage(page, Page.Users);
+  await expect(page.getByRole("columnheader", { name: "User ID" })).toBeVisible({ timeout: 30_000 });
+  await expect(userRows(page)).not.toHaveCount(0, { timeout: 30_000 });
+}
+
+const userRows = (page: PlaywrightPage) => page.getByRole("row").filter({ has: page.getByRole("cell") });
+
+test.describe("Internal Users Page", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
-  async function goToInternalUsers(page: Page) {
-    await page.goto("/ui");
-
-    const internalUserTab = page.getByRole("menuitem", { name: "Internal User" });
-    await expect(internalUserTab).toBeVisible();
-    await internalUserTab.click();
-
-    const firstRow = page.locator("tbody tr").first();
-    await expect(firstRow).toBeVisible();
-    await expect(page.locator('[data-slot="skeleton"]')).toHaveCount(0);
-  }
-
-  test("renders internal users table correctly", async ({ page }) => {
+  test("lists the seeded users under the identifying columns", async ({ page }) => {
     await goToInternalUsers(page);
 
-    const rows = page.locator("tbody tr");
-    const rowCount = await rows.count();
-    expect(rowCount).toBeGreaterThan(0);
-
-    const userIdHeader = page.getByRole("columnheader", { name: "User ID" });
-    await expect(userIdHeader).toBeVisible();
-
-    const virtualKeysHeader = page.getByRole("columnheader", { name: "Virtual Keys" });
-    await expect(virtualKeysHeader).toBeVisible();
+    await expect(page.getByRole("columnheader", { name: "User ID" })).toBeVisible();
+    await expect(page.getByRole("columnheader", { name: "Virtual Keys" })).toBeVisible();
   });
 
-  test("pagination controls work correctly", async ({ page }) => {
+  test("cannot page backwards off the first page", async ({ page }) => {
     await goToInternalUsers(page);
 
-    const paginationInfo = page.locator(".text-sm.text-gray-700");
-    const prevButton = page.getByRole("button", { name: "Previous" });
-    const nextButton = page.getByRole("button", { name: "Next" });
-
-    const infoText = (await paginationInfo.textContent()) || "";
-
-    // On first page, Previous should be disabled
-    if (infoText.includes("1 -")) {
-      await expect(prevButton).toBeDisabled();
-    }
-
-    await page.waitForTimeout(1000);
-    // Check if there are more pages
-    const hasMorePages = infoText.includes("of") && !infoText.endsWith("25 of 25");
-    if (hasMorePages) {
-      await expect(nextButton).toBeEnabled();
-    }
+    await expect(page.getByRole("button", { name: "Go to previous page" })).toBeDisabled();
   });
 });
diff --git a/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py b/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py
index 05886e4b7f6..58cde4c8103 100644
--- a/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py
+++ b/tests/enterprise/litellm_enterprise/enterprise_callbacks/test_prometheus_logging_callbacks.py
@@ -40,6 +40,24 @@ def prometheus_logger() -> PrometheusLogger:
     return PrometheusLogger()
 
 
+@pytest.fixture
+def known_model_router():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-5-mini",
+                "litellm_params": {"model": "openai/gpt-5-mini", "api_key": "fake-key"},
+            },
+            {
+                "model_name": "us/azure/openai/gpt-5-mini",
+                "litellm_params": {"model": "openai/gpt-5-mini", "api_key": "fake-key"},
+            },
+        ]
+    )
+    with patch("litellm.proxy.proxy_server.llm_router", router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        yield router
+
+
 def create_standard_logging_payload() -> StandardLoggingPayload:
     return StandardLoggingPayload(
         id="test_id",
@@ -741,7 +759,7 @@ async def test_async_log_failure_event(prometheus_logger):
 
 
 @pytest.mark.asyncio
-async def test_async_log_failure_event_litellm_side_rate_limit(prometheus_logger):
+async def test_async_log_failure_event_litellm_side_rate_limit(prometheus_logger, known_model_router):
     """LiteLLM-side reject (no deployment picked) routes the requested model
     into `requested_model` and skips the partial-outage flag."""
     standard_logging_object = create_standard_logging_payload()
@@ -786,7 +804,7 @@ async def test_async_log_failure_event_litellm_side_rate_limit(prometheus_logger
 
 
 @pytest.mark.asyncio
-async def test_async_post_call_failure_hook(prometheus_logger):
+async def test_async_post_call_failure_hook(prometheus_logger, known_model_router):
     """
     Test for the async_post_call_failure_hook method
 
@@ -1069,7 +1087,7 @@ def test_set_llm_deployment_success_metrics(prometheus_logger):
 
 
 @pytest.mark.asyncio
-async def test_log_success_fallback_event(prometheus_logger):
+async def test_log_success_fallback_event(prometheus_logger, known_model_router):
     prometheus_logger.litellm_deployment_successful_fallbacks = MagicMock()
 
     original_model_group = "gpt-5-mini"
@@ -1107,7 +1125,7 @@ async def test_log_success_fallback_event(prometheus_logger):
 
 
 @pytest.mark.asyncio
-async def test_log_failure_fallback_event(prometheus_logger):
+async def test_log_failure_fallback_event(prometheus_logger, known_model_router):
     prometheus_logger.litellm_deployment_failed_fallbacks = MagicMock()
 
     original_model_group = "gpt-5-mini"
diff --git a/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py b/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
index 498d0cb4723..b3d457707b8 100644
--- a/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
+++ b/tests/litellm-proxy-extras/test_litellm_proxy_extras_utils.py
@@ -681,3 +681,25 @@ class TestSpendLogsPartitionDetectionSchemaScope:
     def test_only_partitioned_relations_match(self, monkeypatch):
         query, _ = self._detect(monkeypatch, "postgresql://u:p@localhost:5432/db")
         assert "pg_partitioned_table" in query
+
+
+class TestSpendLogsPartitionDetectionMissingPsycopg:
+    """psycopg ships in the `extra_proxy` install, but a stripped-down image
+    can still lack it. When it does, detection must fail closed to False
+    (never crash the migration path) and say so loudly, because a silent
+    False here is what let a genuinely partitioned LiteLLM_SpendLogs hit the
+    unfiltered primary-key rewrite in production."""
+
+    def test_missing_psycopg_returns_false(self, monkeypatch):
+        monkeypatch.setitem(sys.modules, "psycopg", None)
+        monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:5432/db")
+        assert ProxyExtrasDBManager.spend_logs_is_partitioned() is False
+
+    def test_missing_psycopg_logs_a_warning(self, monkeypatch, caplog):
+        monkeypatch.setitem(sys.modules, "psycopg", None)
+        monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:5432/db")
+        with caplog.at_level("WARNING", logger="litellm_proxy_extras"):
+            ProxyExtrasDBManager.spend_logs_is_partitioned()
+        assert any(
+            "psycopg is not installed" in record.message for record in caplog.records
+        )
diff --git a/tests/llm_responses_api_testing/test_responses_hooks.py b/tests/llm_responses_api_testing/test_responses_hooks.py
index 66dbb29dba5..a86752c0172 100644
--- a/tests/llm_responses_api_testing/test_responses_hooks.py
+++ b/tests/llm_responses_api_testing/test_responses_hooks.py
@@ -841,7 +841,7 @@ def test_build_synthetic_response_events_covers_annotations_function_calls_and_r
     )
 
     try:
-        events = streaming_module._build_synthetic_response_events(
+        events = streaming_module.build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=5,
diff --git a/tests/llm_translation/conftest.py b/tests/llm_translation/conftest.py
index 8532af2851c..567040c1d19 100644
--- a/tests/llm_translation/conftest.py
+++ b/tests/llm_translation/conftest.py
@@ -44,7 +44,11 @@ _VCR_AUTO_MARKER_SKIP_FILES = frozenset(
     {"test_vcr_redis_persister.py", "test_ws_vcr.py"}
 )
 
-_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = ()
+_VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = (
+    "test_nvidia_nim.py::test_embedding_nvidia_nim",
+    "test_litellm_proxy_provider.py::test_litellm_gateway_from_sdk_embedding[False]",
+    "test_litellm_proxy_provider.py::test_litellm_gateway_from_sdk_embedding[True]",
+)
 
 
 _verbose_state = VerboseReporterState()
diff --git a/tests/llm_translation/reasoning_effort_grid/grid_spec.py b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
index 485f78ed8c7..aa9f66f6665 100644
--- a/tests/llm_translation/reasoning_effort_grid/grid_spec.py
+++ b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
@@ -163,6 +163,13 @@ _CAPS_NONE: FrozenSet[str] = frozenset()
 
 
 ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="claude-fable-5-1",
+        model="anthropic/claude-fable-5-1",
+        mode="adaptive",
+        required_env=_ANTHROPIC_REQ,
+        caps=_CAPS_XHIGH_MAX,
+    ),
     ModelEntry(
         alias="claude-fable-5",
         model="anthropic/claude-fable-5",
@@ -222,6 +229,19 @@ ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = (
 
 
 AZURE_AI_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="azure-claude-fable-5-1",
+        model="azure_ai/claude-fable-5-1",
+        mode="adaptive",
+        required_env=_AZURE_FOUNDRY_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        fail_reason=(
+            "claude-fable-5-1 has no deployment on the CI Microsoft Foundry "
+            "resource yet, so Foundry returns DeploymentNotFound and this cell "
+            "stays loud in CI. Remove this fail_reason once the deployment "
+            "exists."
+        ),
+    ),
     ModelEntry(
         alias="azure-claude-fable-5",
         model="azure_ai/claude-fable-5",
@@ -268,6 +288,20 @@ AZURE_AI_MODELS: Tuple[ModelEntry, ...] = (
 
 
 VERTEX_AI_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="vertex-claude-fable-5-1",
+        model="vertex_ai/claude-fable-5-1",
+        mode="adaptive",
+        extra_params=(("vertex_location", "global"),),
+        required_env=_VERTEX_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        fail_reason=(
+            "claude-fable-5-1 availability on the CI Vertex project is not yet "
+            "confirmed for this brand-new release, so this cell stays loud in "
+            "CI until verified. Remove this fail_reason once the model is "
+            "confirmed available on the global Vertex endpoint."
+        ),
+    ),
     ModelEntry(
         alias="vertex-claude-fable-5",
         model="vertex_ai/claude-fable-5",
@@ -332,6 +366,22 @@ VERTEX_AI_MODELS: Tuple[ModelEntry, ...] = (
 
 
 BEDROCK_CONVERSE_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="bedrock-claude-fable-5-1",
+        model="bedrock/converse/us.anthropic.claude-fable-5-1",
+        mode="adaptive",
+        extra_params=(("aws_region_name", "us-east-1"),),
+        required_env=_BEDROCK_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        bedrock_effort_ceiling="xhigh",
+        unavailable_error="is not available for this account",
+        fail_reason=(
+            "claude-fable-5-1 access on the CI Bedrock account is not yet "
+            "confirmed for this brand-new release, so this cell stays loud in "
+            "CI until verified. Remove this fail_reason once the model is "
+            "enabled for the account."
+        ),
+    ),
     ModelEntry(
         alias="bedrock-claude-fable-5",
         model="bedrock/converse/us.anthropic.claude-fable-5",
diff --git a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
index 517e3173b8c..714d544ecd6 100644
--- a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
+++ b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
@@ -201,8 +201,8 @@ async def test_reasoning_effort_grid(
 
 
 def test_grid_cell_count() -> None:
-    assert len(_PARAMS) == 31 * 11, (
-        f"expected 341 cells (31 provider x model combos x 11 efforts), "
+    assert len(_PARAMS) == 35 * 11, (
+        f"expected 385 cells (35 provider x model combos x 11 efforts), "
         f"got {len(_PARAMS)}"
     )
 
diff --git a/tests/llm_translation/test_litellm_proxy_provider.py b/tests/llm_translation/test_litellm_proxy_provider.py
index 1cb805bf9ba..8630259877d 100644
--- a/tests/llm_translation/test_litellm_proxy_provider.py
+++ b/tests/llm_translation/test_litellm_proxy_provider.py
@@ -5,6 +5,7 @@ from io import BytesIO
 from unittest.mock import AsyncMock
 
 
+import httpx
 import litellm
 from litellm import completion, embedding
 import pytest
@@ -92,44 +93,54 @@ async def test_litellm_gateway_from_sdk_embedding(is_async):
     litellm.set_verbose = True
     litellm._turn_on_debug()
 
+    captured_bodies = []
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        captured_bodies.append(json.loads(request.content))
+        return httpx.Response(
+            200,
+            json={
+                "object": "list",
+                "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}],
+                "model": "my-vllm-model",
+                "usage": {"prompt_tokens": 2, "total_tokens": 2},
+            },
+        )
+
     if is_async:
         from openai import AsyncOpenAI
 
-        openai_client = AsyncOpenAI(api_key="fake-key")
-        mock_method = AsyncMock()
-        patch_target = openai_client.embeddings.create
+        openai_client = AsyncOpenAI(
+            api_key="fake-key",
+            http_client=httpx.AsyncClient(transport=httpx.MockTransport(handler)),
+        )
+        response = await litellm.aembedding(
+            model="litellm_proxy/my-vllm-model",
+            input="Hello world",
+            client=openai_client,
+            api_base="my-custom-api-base",
+        )
     else:
         from openai import OpenAI
 
-        openai_client = OpenAI(api_key="fake-key")
-        mock_method = MagicMock()
-        patch_target = openai_client.embeddings.create
+        openai_client = OpenAI(
+            api_key="fake-key",
+            http_client=httpx.Client(transport=httpx.MockTransport(handler)),
+        )
+        response = litellm.embedding(
+            model="litellm_proxy/my-vllm-model",
+            input="Hello world",
+            client=openai_client,
+            api_base="my-custom-api-base",
+        )
 
-    with patch.object(patch_target.__self__, patch_target.__name__, new=mock_method):
-        try:
-            if is_async:
-                await litellm.aembedding(
-                    model="litellm_proxy/my-vllm-model",
-                    input="Hello world",
-                    client=openai_client,
-                    api_base="my-custom-api-base",
-                )
-            else:
-                litellm.embedding(
-                    model="litellm_proxy/my-vllm-model",
-                    input="Hello world",
-                    client=openai_client,
-                    api_base="my-custom-api-base",
-                )
-        except Exception as e:
-            print(e)
+    request_body = captured_bodies[0]
+    print("Request body - {}".format(request_body))
 
-        mock_method.assert_called_once()
-
-        print("Call KWARGS - {}".format(mock_method.call_args.kwargs))
-
-        assert "Hello world" == mock_method.call_args.kwargs["input"]
-        assert "my-vllm-model" == mock_method.call_args.kwargs["model"]
+    assert "Hello world" == request_body["input"]
+    assert "my-vllm-model" == request_body["model"]
+    assert "encoding_format" not in request_body
+    assert response.data[0]["embedding"] == [0.1, 0.2, 0.3]
 
 
 @pytest.mark.parametrize("is_async", [False, True])
diff --git a/tests/llm_translation/test_nvidia_nim.py b/tests/llm_translation/test_nvidia_nim.py
index 7ee4f347f72..d5942e674d0 100644
--- a/tests/llm_translation/test_nvidia_nim.py
+++ b/tests/llm_translation/test_nvidia_nim.py
@@ -63,27 +63,39 @@ def test_embedding_nvidia_nim():
     litellm.set_verbose = True
     from openai import OpenAI
 
+    captured_bodies = []
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        captured_bodies.append(json.loads(request.content))
+        return httpx.Response(
+            200,
+            json={
+                "object": "list",
+                "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}],
+                "model": "nvidia/nv-embedqa-e5-v5",
+                "usage": {"prompt_tokens": 6, "total_tokens": 6},
+            },
+        )
+
     client = OpenAI(
         api_key="fake-api-key",
+        http_client=httpx.Client(transport=httpx.MockTransport(handler)),
     )
-    with patch.object(client.embeddings.with_raw_response, "create") as mock_client:
-        try:
-            litellm.embedding(
-                model="nvidia_nim/nvidia/nv-embedqa-e5-v5",
-                input="What is the meaning of life?",
-                input_type="passage",
-                dimensions=1024,
-                client=client,
-            )
-        except Exception as e:
-            print(e)
-        mock_client.assert_called_once()
-        request_body = mock_client.call_args.kwargs
-        print("request_body: ", request_body)
-        assert request_body["input"] == "What is the meaning of life?"
-        assert request_body["model"] == "nvidia/nv-embedqa-e5-v5"
-        assert request_body["extra_body"]["input_type"] == "passage"
-        assert request_body["dimensions"] == 1024
+    response = litellm.embedding(
+        model="nvidia_nim/nvidia/nv-embedqa-e5-v5",
+        input="What is the meaning of life?",
+        input_type="passage",
+        dimensions=1024,
+        client=client,
+    )
+    request_body = captured_bodies[0]
+    print("request_body: ", request_body)
+    assert request_body["input"] == "What is the meaning of life?"
+    assert request_body["model"] == "nvidia/nv-embedqa-e5-v5"
+    assert request_body["input_type"] == "passage"
+    assert request_body["dimensions"] == 1024
+    assert "encoding_format" not in request_body
+    assert response.data[0]["embedding"] == [0.1, 0.2, 0.3]
 
 
 def test_chat_completion_nvidia_nim_with_tools():
diff --git a/tests/llm_translation/test_prompt_factory.py b/tests/llm_translation/test_prompt_factory.py
index a90a3df584e..7b03736920b 100644
--- a/tests/llm_translation/test_prompt_factory.py
+++ b/tests/llm_translation/test_prompt_factory.py
@@ -1446,9 +1446,17 @@ def test_convert_to_anthropic_tool_invoke_sanitizes_invalid_ids():
 
 def test_convert_to_anthropic_tool_invoke_server_tool():
     """
-    Test that server_tool_use (srvtoolu_) is reconstructed as server_tool_use.
+    Test that a server tool call (srvtoolu_) with no stored result is replayed
+    as a regular tool_use block.
 
-    Fixes: https://github.com/BerriAI/litellm/issues/17737
+    A server_tool_use block is only valid when paired with its result block, so
+    an unpaired one must degrade to tool_use for Anthropic to accept the replay.
+    A paired call still becomes server_tool_use, covered by
+    test_convert_to_anthropic_tool_invoke_with_web_search_results.
+
+    Context: https://github.com/BerriAI/litellm/issues/17737 (original
+    server_tool_use reconstruction) and LIT-6622 / PR #39144 (unpaired calls
+    degrade instead of 400ing at Anthropic).
     """
     tool_calls = [
         {
@@ -1464,7 +1472,7 @@ def test_convert_to_anthropic_tool_invoke_server_tool():
     result = convert_to_anthropic_tool_invoke(tool_calls)
 
     assert len(result) == 1
-    assert result[0]["type"] == "server_tool_use"  # NOT tool_use
+    assert result[0]["type"] == "tool_use"
     assert result[0]["id"] == "srvtoolu_01ABC123"
     assert result[0]["name"] == "web_search"
     assert result[0]["input"] == {"query": "elephant weight"}
diff --git a/tests/local_testing/conftest.py b/tests/local_testing/conftest.py
index ee93009a198..5535a62bb81 100644
--- a/tests/local_testing/conftest.py
+++ b/tests/local_testing/conftest.py
@@ -90,6 +90,7 @@ _VCR_INCOMPATIBLE_FILES = frozenset(
 #   carry no real provider cost.
 _VCR_INCOMPATIBLE_NODEID_SUFFIXES: tuple[str, ...] = (
     "test_router.py::test_router_text_completion_client",
+    "test_embedding.py::test_encoding_format_omitted_by_default_for_openai_sdk",
 )
 
 
diff --git a/tests/local_testing/test_embedding.py b/tests/local_testing/test_embedding.py
index aed2849f056..ee2ac14f498 100644
--- a/tests/local_testing/test_embedding.py
+++ b/tests/local_testing/test_embedding.py
@@ -3,6 +3,8 @@ import os
 import re
 import traceback
 
+import httpx
+
 import openai
 import pytest
 from dotenv import load_dotenv
@@ -1255,56 +1257,42 @@ def test_jina_ai_img_embeddings(input_data, expected_payload_input):
         assert sent_data["input"] == expected_payload_input
 
 
-def test_encoding_format_defaults_to_float_for_openai_sdk(monkeypatch):
+def test_encoding_format_omitted_by_default_for_openai_sdk(monkeypatch):
     """
-    When encoding_format is not provided, LiteLLM sends `float` for OpenAI-path embeddings.
+    When encoding_format is not provided, LiteLLM leaves it out of the upstream request.
 
     Optional global override: `LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT`.
     """
     monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False)
-    with patch(
-        "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client"
-    ) as mock_get_client:
-        # Create a mock client instance
-        mock_client_instance = MagicMock()
-        mock_get_client.return_value = mock_client_instance
+    captured_bodies = []
 
-        # Mock the embeddings.with_raw_response.create method
-        mock_response = MagicMock()
-        mock_response.parse.return_value = MagicMock(
-            model_dump=lambda: {
-                "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}],
-                "model": "text-embedding-ada-002",
+    def handler(request: httpx.Request) -> httpx.Response:
+        captured_bodies.append(json.loads(request.content))
+        return httpx.Response(
+            200,
+            json={
                 "object": "list",
+                "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}],
+                "model": "text-embedding-ada-002",
                 "usage": {"prompt_tokens": 1, "total_tokens": 1},
-            }
-        )
-        mock_response.headers = {}
-
-        mock_client_instance.embeddings.with_raw_response.create.return_value = (
-            mock_response
+            },
         )
 
-        # Call the embedding function without encoding_format
-        response = embedding(
-            model="text-embedding-ada-002",
-            input="Hello world",
-        )
+    client = openai.OpenAI(
+        api_key="sk-test", http_client=httpx.Client(transport=httpx.MockTransport(handler))
+    )
 
-        # Get the call arguments to verify what was sent to OpenAI SDK
-        call_args = mock_client_instance.embeddings.with_raw_response.create.call_args
-        assert (
-            call_args is not None
-        ), "OpenAI SDK embeddings.create should have been called"
+    response = embedding(
+        model="text-embedding-ada-002",
+        input="Hello world",
+        api_key="sk-test",
+        client=client,
+    )
 
-        call_kwargs = call_args[1]  # Get kwargs
-
-        assert "encoding_format" in call_kwargs
-        assert (
-            call_kwargs["encoding_format"] == "float"
-        ), "encoding_format should default to float when not provided by user"
-
-        print("✅ PASS: encoding_format='float' is correctly passed to OpenAI SDK")
+    assert response.data[0]["embedding"] == [0.1, 0.2, 0.3]
+    assert "encoding_format" not in captured_bodies[0], (
+        "encoding_format should be omitted from the upstream request when not provided by user"
+    )
 
 
 def test_encoding_format_explicit_value_preserved():
diff --git a/tests/local_testing/test_exceptions.py b/tests/local_testing/test_exceptions.py
index 8370046446d..e6392cda406 100644
--- a/tests/local_testing/test_exceptions.py
+++ b/tests/local_testing/test_exceptions.py
@@ -5,7 +5,7 @@ import traceback
 from typing import Any
 
 import httpx
-from openai import AsyncOpenAI, AuthenticationError, BadRequestError, OpenAIError, RateLimitError
+from openai import AsyncAzureOpenAI, AsyncOpenAI, AuthenticationError, AzureOpenAI, BadRequestError, OpenAIError, RateLimitError
 
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 
@@ -895,7 +895,12 @@ def _pre_call_utils(
 ):
     if call_type == "embedding":
         data["input"] = "Hello world!"
-        mapped_target: Any = client.embeddings.with_raw_response
+        if isinstance(client, (AzureOpenAI, AsyncAzureOpenAI)):
+            mapped_target: Any = client.embeddings.with_raw_response
+            patched_attr = "create"
+        else:
+            mapped_target = client
+            patched_attr = "post"
         if sync_mode:
             original_function = litellm.embedding
         else:
@@ -905,6 +910,7 @@ def _pre_call_utils(
         if streaming is True:
             data["stream"] = True
         mapped_target = client.chat.completions.with_raw_response  # type: ignore
+        patched_attr = "create"
         if sync_mode:
             original_function = litellm.completion
         else:
@@ -914,12 +920,13 @@ def _pre_call_utils(
         if streaming is True:
             data["stream"] = True
         mapped_target = client.completions.with_raw_response  # type: ignore
+        patched_attr = "create"
         if sync_mode:
             original_function = litellm.text_completion
         else:
             original_function = litellm.atext_completion
 
-    return data, original_function, mapped_target
+    return data, original_function, mapped_target, patched_attr
 
 
 def _pre_call_utils_httpx(
@@ -1003,7 +1010,7 @@ async def test_exception_with_headers(sync_mode, provider, model, call_type, str
             )
 
     data = {"model": model}
-    data, original_function, mapped_target = _pre_call_utils(
+    data, original_function, mapped_target, patched_attr = _pre_call_utils(
         call_type=call_type,
         data=data,
         client=openai_client,
@@ -1049,7 +1056,7 @@ async def test_exception_with_headers(sync_mode, provider, model, call_type, str
 
     with patch.object(
         mapped_target,
-        "create",
+        patched_attr,
         side_effect=_return_exception,
     ):
         new_retry_after_mock_client = MagicMock(return_value=-1)
diff --git a/tests/local_testing/test_get_llm_provider.py b/tests/local_testing/test_get_llm_provider.py
index cc6209f2bf9..ebad0fbafc5 100644
--- a/tests/local_testing/test_get_llm_provider.py
+++ b/tests/local_testing/test_get_llm_provider.py
@@ -155,6 +155,11 @@ def test_default_api_base():
                         continue
                     elif provider == "github" and other_provider.value == "azure":
                         continue
+                    elif (
+                        provider in ("qwencloud", "qwen_ai_platform")
+                        and other_provider.value == "dashscope"
+                    ):
+                        continue
                     assert other_provider.value not in api_base.replace("/openai", "")
 
 
diff --git a/tests/local_testing/test_router.py b/tests/local_testing/test_router.py
index 370c43f8f44..c714bb4f9a7 100644
--- a/tests/local_testing/test_router.py
+++ b/tests/local_testing/test_router.py
@@ -2032,8 +2032,8 @@ def test_router_dynamic_cooldown_correct_retry_after_time():
         raise exception
 
     with patch.object(
-        openai_client.embeddings.with_raw_response,
-        "create",
+        openai_client,
+        "post",
         side_effect=_return_exception,
     ):
         new_retry_after_mock_client = MagicMock(return_value=-1)
diff --git a/tests/logging_callback_tests/gcs_pub_sub_body/spend_logs_payload.json b/tests/logging_callback_tests/gcs_pub_sub_body/spend_logs_payload.json
index 1838fb16e91..28912a27501 100644
--- a/tests/logging_callback_tests/gcs_pub_sub_body/spend_logs_payload.json
+++ b/tests/logging_callback_tests/gcs_pub_sub_body/spend_logs_payload.json
@@ -11,7 +11,7 @@
     "user": "",
     "team_id": "",
     "organization_id": "",
-    "metadata": "{\"applied_guardrails\": [], \"attempted_fallbacks\": null, \"original_model_group\": null, \"batch_models\": null, \"batch_successful_requests\": null, \"batch_failed_requests\": null, \"mcp_tool_call_metadata\": null, \"vector_store_request_metadata\": null, \"routing_decision\": null, \"internal_call_origin\": null, \"guardrail_information\": null, \"compression_savings\": null, \"litellm_gateway_injected_cache\": null, \"usage_object\": {\"completion_tokens\": 20, \"prompt_tokens\": 10, \"total_tokens\": 30, \"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"model_map_information\": {\"model_map_key\": \"gpt-4o\", \"model_map_value\": {\"key\": \"gpt-4o\", \"max_tokens\": 16384, \"max_input_tokens\": 128000, \"max_output_tokens\": 16384, \"input_cost_per_token\": 2.5e-06, \"cache_creation_input_token_cost\": null, \"cache_read_input_token_cost\": 1.25e-06, \"input_cost_per_character\": null, \"input_cost_per_token_above_128k_tokens\": null, \"input_cost_per_token_above_200k_tokens\": null, \"input_cost_per_query\": null, \"input_cost_per_second\": null, \"input_cost_per_audio_token\": null, \"input_cost_per_token_batches\": 1.25e-06, \"output_cost_per_token_batches\": 5e-06, \"output_cost_per_token\": 1e-05, \"output_cost_per_audio_token\": null, \"output_cost_per_character\": null, \"output_cost_per_token_above_128k_tokens\": null, \"output_cost_per_character_above_128k_tokens\": null, \"output_cost_per_token_above_200k_tokens\": null, \"output_cost_per_second\": null, \"output_cost_per_image\": null, \"output_vector_size\": null, \"litellm_provider\": \"openai\", \"mode\": \"chat\", \"supports_system_messages\": true, \"supports_response_schema\": true, \"supports_vision\": true, \"supports_function_calling\": true, \"supports_tool_choice\": true, \"supports_assistant_prefill\": false, \"supports_prompt_caching\": true, \"supports_audio_input\": false, \"supports_audio_output\": false, \"supports_pdf_input\": false, \"supports_embedding_image_input\": false, \"supports_native_streaming\": null, \"supports_web_search\": true, \"supports_reasoning\": false, \"search_context_cost_per_query\": {\"search_context_size_low\": 0.03, \"search_context_size_medium\": 0.035, \"search_context_size_high\": 0.05}, \"tpm\": null, \"rpm\": null, \"supported_openai_params\": [\"frequency_penalty\", \"logit_bias\", \"logprobs\", \"top_logprobs\", \"max_tokens\", \"max_completion_tokens\", \"modalities\", \"prediction\", \"n\", \"presence_penalty\", \"seed\", \"stop\", \"stream\", \"stream_options\", \"temperature\", \"top_p\", \"tools\", \"tool_choice\", \"function_call\", \"functions\", \"max_retries\", \"extra_headers\", \"parallel_tool_calls\", \"audio\", \"response_format\", \"user\"]}}, \"additional_usage_values\": {\"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"user_api_key\": null, \"user_api_key_alias\": null, \"user_api_key_team_id\": null, \"user_api_key_project_id\": null, \"user_api_key_project_alias\": null, \"user_api_key_org_id\": null, \"user_api_key_user_id\": null, \"user_api_key_team_alias\": null, \"spend_logs_metadata\": null, \"requester_ip_address\": null, \"status\": null, \"proxy_server_request\": null, \"error_information\": null, \"attempted_retries\": null, \"max_retries\": null}",
+    "metadata": "{\"applied_guardrails\": [], \"attempted_fallbacks\": null, \"original_model_group\": null, \"batch_models\": null, \"batch_successful_requests\": null, \"batch_failed_requests\": null, \"mcp_tool_call_metadata\": null, \"vector_store_request_metadata\": null, \"routing_decision\": null, \"internal_call_origin\": null, \"router_metadata\": null, \"guardrail_information\": null, \"compression_savings\": null, \"litellm_gateway_injected_cache\": null, \"usage_object\": {\"completion_tokens\": 20, \"prompt_tokens\": 10, \"total_tokens\": 30, \"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"model_map_information\": {\"model_map_key\": \"gpt-4o\", \"model_map_value\": {\"key\": \"gpt-4o\", \"max_tokens\": 16384, \"max_input_tokens\": 128000, \"max_output_tokens\": 16384, \"input_cost_per_token\": 2.5e-06, \"cache_creation_input_token_cost\": null, \"cache_read_input_token_cost\": 1.25e-06, \"input_cost_per_character\": null, \"input_cost_per_token_above_128k_tokens\": null, \"input_cost_per_token_above_200k_tokens\": null, \"input_cost_per_query\": null, \"input_cost_per_second\": null, \"input_cost_per_audio_token\": null, \"input_cost_per_token_batches\": 1.25e-06, \"output_cost_per_token_batches\": 5e-06, \"output_cost_per_token\": 1e-05, \"output_cost_per_audio_token\": null, \"output_cost_per_character\": null, \"output_cost_per_token_above_128k_tokens\": null, \"output_cost_per_character_above_128k_tokens\": null, \"output_cost_per_token_above_200k_tokens\": null, \"output_cost_per_second\": null, \"output_cost_per_image\": null, \"output_vector_size\": null, \"litellm_provider\": \"openai\", \"mode\": \"chat\", \"supports_system_messages\": true, \"supports_response_schema\": true, \"supports_vision\": true, \"supports_function_calling\": true, \"supports_tool_choice\": true, \"supports_assistant_prefill\": false, \"supports_prompt_caching\": true, \"supports_audio_input\": false, \"supports_audio_output\": false, \"supports_pdf_input\": false, \"supports_embedding_image_input\": false, \"supports_native_streaming\": null, \"supports_web_search\": true, \"supports_reasoning\": false, \"search_context_cost_per_query\": {\"search_context_size_low\": 0.03, \"search_context_size_medium\": 0.035, \"search_context_size_high\": 0.05}, \"tpm\": null, \"rpm\": null, \"supported_openai_params\": [\"frequency_penalty\", \"logit_bias\", \"logprobs\", \"top_logprobs\", \"max_tokens\", \"max_completion_tokens\", \"modalities\", \"prediction\", \"n\", \"presence_penalty\", \"seed\", \"stop\", \"stream\", \"stream_options\", \"temperature\", \"top_p\", \"tools\", \"tool_choice\", \"function_call\", \"functions\", \"max_retries\", \"extra_headers\", \"parallel_tool_calls\", \"audio\", \"response_format\", \"user\"]}}, \"additional_usage_values\": {\"completion_tokens_details\": null, \"prompt_tokens_details\": null}, \"user_api_key\": null, \"user_api_key_alias\": null, \"user_api_key_team_id\": null, \"user_api_key_project_id\": null, \"user_api_key_project_alias\": null, \"user_api_key_org_id\": null, \"user_api_key_user_id\": null, \"user_api_key_team_alias\": null, \"spend_logs_metadata\": null, \"requester_ip_address\": null, \"status\": null, \"proxy_server_request\": null, \"error_information\": null, \"attempted_retries\": null, \"max_retries\": null}",
     "cache_key": "Cache OFF",
     "spend": 0.00022500000000000002,
     "total_tokens": 30,
diff --git a/tests/logging_callback_tests/test_bedrock_knowledgebase_hook.py b/tests/logging_callback_tests/test_bedrock_knowledgebase_hook.py
index 3f9f2bacdd3..0c362db8853 100644
--- a/tests/logging_callback_tests/test_bedrock_knowledgebase_hook.py
+++ b/tests/logging_callback_tests/test_bedrock_knowledgebase_hook.py
@@ -333,6 +333,7 @@ async def test_bedrock_kb_request_body_has_transformed_filters(
         timeout=None,
         client=None,
         _is_async=False,
+        router: "litellm.Router | None" = None,
     ):
         litellm_params_dict = (
             litellm_params.model_dump(exclude_none=False)
diff --git a/tests/mcp_tests/test_mcp_client_unit.py b/tests/mcp_tests/test_mcp_client_unit.py
index aadaadd510e..6438525706a 100644
--- a/tests/mcp_tests/test_mcp_client_unit.py
+++ b/tests/mcp_tests/test_mcp_client_unit.py
@@ -11,7 +11,9 @@ from unittest.mock import AsyncMock, MagicMock, patch, ANY
 import litellm.experimental_mcp_client.client as mcp_client_module
 from litellm.experimental_mcp_client.client import MCPClient
 from litellm.types.mcp import MCPAuth, MCPTransport
-from mcp.types import Tool as MCPTool, CallToolResult as MCPCallToolResult
+from mcp.types import CallToolResult as MCPCallToolResult
+from mcp.types import ListToolsResult, PaginatedRequestParams
+from mcp.types import Tool as MCPTool
 
 
 def test_mcp_client_uses_configurable_default_timeout():
@@ -185,6 +187,80 @@ class TestMCPClientUnitTests:
         mock_session_instance.initialize.assert_called_once()
         mock_session_instance.list_tools.assert_called_once()
 
+    @pytest.mark.asyncio
+    @patch.object(mcp_client_module, "streamable_http_client")  # test-quality-ok: exercises MCPClient wiring; the walk itself is covered sessionless in test_tools.py
+    @patch.object(mcp_client_module, "ClientSession")  # test-quality-ok: exercises MCPClient wiring; the walk itself is covered sessionless in test_tools.py
+    async def test_list_tools_follows_next_cursor_until_exhausted(
+        self,
+        mock_session_class,
+        mock_transport,
+    ):
+        """Test listing tools follows MCP pagination cursors until exhausted."""
+        mock_transport_ctx = AsyncMock()
+        mock_transport.return_value = mock_transport_ctx
+        mock_transport_instance = MagicMock()
+        mock_transport_ctx.__aenter__ = AsyncMock(return_value=mock_transport_instance)
+
+        mock_session_ctx = AsyncMock()
+        mock_session_class.return_value = mock_session_ctx
+        mock_session_instance = AsyncMock()
+        mock_session_ctx.__aenter__ = AsyncMock(return_value=mock_session_instance)
+
+        first_page_tools = [
+            MCPTool(name=f"tool_{idx}", description=f"Tool {idx}", inputSchema={}) for idx in range(100)
+        ]
+        second_page_tool = MCPTool(
+            name="tool_100",
+            description="Tool 100",
+            inputSchema={},
+        )
+        mock_session_instance.list_tools.side_effect = [
+            ListToolsResult(tools=first_page_tools, nextCursor="page-2"),
+            ListToolsResult(tools=[second_page_tool]),
+        ]
+
+        client = MCPClient("http://example.com")
+        result = await client.list_tools()
+
+        assert result == [*first_page_tools, second_page_tool]
+        assert mock_session_instance.list_tools.call_count == 2
+        second_call_params = mock_session_instance.list_tools.call_args_list[1].kwargs["params"]
+        assert isinstance(second_call_params, PaginatedRequestParams)
+        assert second_call_params.cursor == "page-2"
+
+    @pytest.mark.asyncio
+    @patch.object(mcp_client_module, "streamable_http_client")  # test-quality-ok: exercises MCPClient wiring; the walk itself is covered sessionless in test_tools.py
+    @patch.object(mcp_client_module, "ClientSession")  # test-quality-ok: exercises MCPClient wiring; the walk itself is covered sessionless in test_tools.py
+    async def test_list_tools_swallows_mid_walk_error_without_raise_on_error(
+        self,
+        mock_session_class,
+        mock_transport,
+    ):
+        """Test a mid-walk failure returns [] when raise_on_error is False."""
+        mock_transport_ctx = AsyncMock()
+        mock_transport.return_value = mock_transport_ctx
+        mock_transport_instance = MagicMock()
+        mock_transport_ctx.__aenter__ = AsyncMock(return_value=mock_transport_instance)
+
+        mock_session_ctx = AsyncMock()
+        mock_session_class.return_value = mock_session_ctx
+        mock_session_instance = AsyncMock()
+        mock_session_ctx.__aenter__ = AsyncMock(return_value=mock_session_instance)
+
+        mock_session_instance.list_tools.side_effect = [
+            ListToolsResult(
+                tools=[MCPTool(name="tool_0", description="Tool 0", inputSchema={})],
+                nextCursor="page-2",
+            ),
+            RuntimeError("transient upstream failure"),
+        ]
+
+        client = MCPClient("http://example.com")
+        result = await client.list_tools()
+
+        assert result == []
+        assert mock_session_instance.list_tools.call_count == 2
+
     @pytest.mark.asyncio
     @patch.object(mcp_client_module, "streamable_http_client")
     @patch.object(mcp_client_module, "ClientSession")
diff --git a/tests/ocr_tests/test_ocr_vertex_ai.py b/tests/ocr_tests/test_ocr_vertex_ai.py
index 1ba5b9d0883..1842eb063a5 100644
--- a/tests/ocr_tests/test_ocr_vertex_ai.py
+++ b/tests/ocr_tests/test_ocr_vertex_ai.py
@@ -5,9 +5,11 @@ Note: Vertex AI OCR automatically converts URLs to base64 data URIs since
 the Vertex AI endpoint doesn't have internet access.
 """
 
-import os
 import json
+import os
 import tempfile
+from typing import Final
+
 import pytest
 from base_ocr_unit_tests import BaseOCRTest
 
@@ -139,3 +141,19 @@ def test_vertex_ai_ocr_routing():
     assert isinstance(
         deepseek_variant, VertexAIDeepSeekOCRConfig
     ), "DeepSeek variant should route to VertexAIDeepSeekOCRConfig"
+
+
+@pytest.mark.parametrize("model", ("deepseek-ocr-maas", "deepseek-ai/deepseek-ocr-maas"))
+def test_deepseek_request_uses_single_provider_namespace(model: str) -> None:
+    from litellm.llms.vertex_ai.ocr.deepseek_transformation import (
+        VertexAIDeepSeekOCRConfig,
+    )
+
+    request: Final = VertexAIDeepSeekOCRConfig().transform_ocr_request(
+        model=model,
+        document={"type": "image_url", "image_url": "data:image/png;base64,AA=="},
+        optional_params={},
+        headers={},
+    )
+
+    assert request.data["model"] == "deepseek-ai/deepseek-ocr-maas"
diff --git a/tests/pass_through_unit_tests/test_websearch_interception_e2e.py b/tests/pass_through_unit_tests/test_websearch_interception_e2e.py
index 091ea106b91..fd95b7fa8f2 100644
--- a/tests/pass_through_unit_tests/test_websearch_interception_e2e.py
+++ b/tests/pass_through_unit_tests/test_websearch_interception_e2e.py
@@ -937,6 +937,14 @@ async def test_pre_request_hook_modifies_request_body():
 
     print("✅ WebSearchInterceptionLogger initialized")
 
+    mock_router = MagicMock()
+    mock_router.search_tools = [
+        {
+            "search_tool_name": "test-search-tool",
+            "litellm_params": {"search_provider": "tavily"},
+        }
+    ]
+
     # Track what actually gets sent to the API
     captured_request = {}
 
@@ -987,6 +995,9 @@ async def test_pre_request_hook_modifies_request_body():
     with patch(
         "litellm.llms.anthropic.experimental_pass_through.messages.handler.anthropic_messages_handler",
         side_effect=mock_anthropic_messages_handler,
+    ), patch(  # test-quality-ok: the hook imports this process-global router at call time; no injection seam exists to register search_tools
+        "litellm.proxy.proxy_server.llm_router",
+        mock_router,
     ):
 
         print(
diff --git a/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py
new file mode 100644
index 00000000000..ed21734c5fc
--- /dev/null
+++ b/tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py
@@ -0,0 +1,58 @@
+"""Image-level check that the built proxy image can import the Bedrock realtime SDK.
+
+Bedrock Nova Sonic (`/v1/realtime`) imports `aws_sdk_bedrock_runtime` lazily on the
+first session, so an image whose `uv sync` stages skip the `bedrock-realtime` extra
+boots, passes health checks, and then fails every Nova Sonic session with
+"Missing aws_sdk_bedrock_runtime". Importing inside the built image is what catches
+that class of regression (missing extra, lockfile drift, a stage that syncs a
+different set of extras), which a static Dockerfile check cannot.
+
+Gated on LITELLM_IMAGE like the other image checks in this directory; exercised
+where an image has been built (the image-scan workflow). Requires a working docker CLI.
+"""
+
+import os
+import shutil
+import subprocess
+from typing import Final
+
+import pytest
+
+IMAGE: Final = os.getenv("LITELLM_IMAGE")
+NON_ROOT_UID: Final = "12345:0"
+IMPORT_PROBE: Final = "import aws_sdk_bedrock_runtime, smithy_aws_core; print('bedrock-realtime ok')"
+
+pytestmark = [
+    pytest.mark.skipif(IMAGE is None, reason="requires a built image (set LITELLM_IMAGE)"),
+    pytest.mark.skipif(shutil.which("docker") is None, reason="requires the docker CLI"),
+]
+
+
+def test_image_imports_bedrock_realtime_sdk():
+    assert IMAGE is not None
+
+    probe: Final = subprocess.run(
+        [
+            "docker",
+            "run",
+            "--rm",
+            "--network",
+            "none",
+            "--user",
+            NON_ROOT_UID,
+            "--entrypoint",
+            "python",
+            IMAGE,
+            "-c",
+            IMPORT_PROBE,
+        ],
+        capture_output=True,
+        text=True,
+        check=False,
+    )
+
+    assert probe.returncode == 0 and "bedrock-realtime ok" in probe.stdout, (
+        f"{IMAGE} cannot import aws_sdk_bedrock_runtime as uid {NON_ROOT_UID}, so Bedrock Nova Sonic "
+        "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'. Is `--extra bedrock-realtime` "
+        f"passed to every `uv sync` in its Dockerfile?\nstdout:\n{probe.stdout}\nstderr:\n{probe.stderr}"
+    )
diff --git a/tests/proxy_migration_tests/test_prisma_toolchain.py b/tests/proxy_migration_tests/test_prisma_toolchain.py
index d12a2c4dd4e..733870f3239 100644
--- a/tests/proxy_migration_tests/test_prisma_toolchain.py
+++ b/tests/proxy_migration_tests/test_prisma_toolchain.py
@@ -7,26 +7,36 @@ attempt fails identically. These tests pin the two behaviours that keep a
 container recoverable: an incomplete cache is deleted before Prisma is
 invoked, and the install gets a budget of its own rather than sharing the one
 that bounds each migration command.
+
+``prisma migrate deploy`` gets a budget of its own for the same reason: its
+runtime grows with the number of pending migrations, so a fresh database that
+replays every migration overran the per-command budget on slow machines and
+the proxy gave up after four identical timeouts.
 """
 
 import ast
 import json
+import logging
 import os
 import sys
 import time
+from collections.abc import Callable
 from pathlib import Path
 
 import pytest
 
 from litellm_proxy_extras.prisma_toolchain import (
     DEFAULT_PRISMA_COMMAND_TIMEOUT,
+    DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT,
     PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR,
     PRISMA_COMMAND_TIMEOUT_ENV_VAR,
+    PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR,
     ensure_prisma_toolchain,
     heal_incomplete_nodeenv_cache,
     node_binary_path,
     prisma_bootstrap_timeout,
     prisma_command_timeout,
+    prisma_migrate_deploy_timeout,
 )
 from litellm_proxy_extras.utils import ProxyExtrasDBManager
 
@@ -42,14 +52,27 @@ import time
 
 args = sys.argv[1:]
 cache_dir = os.environ["PRISMA_NODEENV_CACHE_DIR"]
-with pathlib.Path(os.environ["FAKE_PRISMA_LOG"]).open("a") as log:
+log_path = pathlib.Path(os.environ["FAKE_PRISMA_LOG"])
+earlier_same_command = sum(
+    1
+    for line in (log_path.read_text().splitlines() if log_path.exists() else [])
+    if json.loads(line)["args"][:2] == args[:2]
+)
+with log_path.open("a") as log:
     log.write(
         json.dumps({{"args": args, "cache_dir_present": os.path.isdir(cache_dir)}})
         + "\\n"
     )
 time.sleep(float(os.environ.get("FAKE_PRISMA_SLEEP", "0")))
 if args[:2] == ["migrate", "deploy"]:
+    if earlier_same_command == 0:
+        time.sleep(float(os.environ.get("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "0")))
+    elif os.environ.get("FAKE_PRISMA_LATER_DEPLOY_STDERR"):
+        print(os.environ["FAKE_PRISMA_LATER_DEPLOY_STDERR"], file=sys.stderr)
+        sys.exit(1)
     print("No pending migrations to apply")
+if args[:2] == ["db", "push"] and earlier_same_command == 0:
+    time.sleep(float(os.environ.get("FAKE_PRISMA_FIRST_PUSH_SLEEP", "0")))
 sys.exit(0)
 """
 
@@ -80,9 +103,14 @@ def toolchain_env(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> tuple[Path
     monkeypatch.setenv("PATH", f"{bin_dir}{os.pathsep}{os.environ['PATH']}")
     monkeypatch.delenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, raising=False)
     monkeypatch.delenv(PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR, raising=False)
+    monkeypatch.delenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, raising=False)
     return cache_dir, log_path
 
 
+def _deploy_calls(log_path: Path) -> list[list[str]]:
+    return [call["args"] for call in _fake_prisma_calls(log_path) if call["args"][:2] == ["migrate", "deploy"]]
+
+
 def _make_incomplete_cache(cache_dir: Path) -> None:
     (cache_dir / "lib").mkdir(parents=True)
     (cache_dir / "bin").mkdir()
@@ -209,25 +237,111 @@ def test_setup_database_prepares_the_toolchain_before_migrating(
     assert calls[0]["cache_dir_present"] is False
 
 
+@pytest.mark.parametrize("use_v2_resolver", [False, True], ids=["v1", "v2"])
+def test_migrate_deploy_is_not_bounded_by_the_per_command_timeout(
+    toolchain_env: tuple[Path, Path],
+    monkeypatch: pytest.MonkeyPatch,
+    use_v2_resolver: bool,
+) -> None:
+    """A fresh database replays every migration, which takes longer than any bookkeeping command."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "3")
+
+    assert ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=use_v2_resolver) is True
+    assert _deploy_calls(log_path) == [["migrate", "deploy"]]
+
+
+def test_migrate_deploy_stops_at_its_own_timeout(
+    toolchain_env: tuple[Path, Path], monkeypatch: pytest.MonkeyPatch
+) -> None:
+    """The deploy budget still bounds a deploy that hangs, so boot cannot wait forever."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_DEPLOY_SLEEP", "60")
+    monkeypatch.setenv("FAKE_PRISMA_LATER_DEPLOY_STDERR", "Error: P3018 permission denied for schema public")
+
+    started = time.monotonic()
+    with pytest.raises(RuntimeError, match="insufficient permissions"):
+        ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+    elapsed = time.monotonic() - started
+
+    assert len(_deploy_calls(log_path)) == 2
+    assert elapsed < 30
+
+
+def test_db_push_timeout_hint_names_the_per_command_budget(
+    toolchain_env: tuple[Path, Path], monkeypatch: pytest.MonkeyPatch, caplog: pytest.LogCaptureFixture
+) -> None:
+    """``db push`` keeps the per-command budget, so its timeout hint has to name that variable."""
+    _, log_path = toolchain_env
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "1")
+    monkeypatch.setenv("FAKE_PRISMA_FIRST_PUSH_SLEEP", "3")
+
+    with caplog.at_level(logging.WARNING, logger="litellm_proxy_extras"):
+        assert ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=False) is True
+
+    assert [call["args"][:2] for call in _fake_prisma_calls(log_path)].count(["db", "push"]) == 2
+    assert [record.getMessage() for record in caplog.records if "timed out" in record.getMessage()] == [
+        f"Attempt 1 timed out. Raise {PRISMA_COMMAND_TIMEOUT_ENV_VAR} if this database needs longer to apply its schema."
+    ]
+
+
+@pytest.mark.parametrize(
+    ("command_timeout", "deploy_timeout", "expected"),
+    [
+        ("900", None, 900.0),
+        ("12", None, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT),
+        ("900", "1200", 1200.0),
+        ("900", "300", 300.0),
+    ],
+    ids=["raised_command_budget_carries_over", "lowered_command_budget_does_not", "override_wins_upward", "override_wins_downward"],
+)
+def test_migrate_deploy_budget_keeps_a_raised_command_budget(
+    command_timeout: str, deploy_timeout: str | None, expected: float, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    """Deployments that raised the per-command budget to survive a long deploy keep that budget for deploy."""
+    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, command_timeout)
+    if deploy_timeout is None:
+        monkeypatch.delenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, raising=False)
+    else:
+        monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, deploy_timeout)
+
+    assert prisma_migrate_deploy_timeout() == expected
+
+
 @pytest.mark.parametrize(
     "raw",
     ["", "0", "-5", "not-a-number", "nan", "inf", "-inf", "1e400"],
 )
+@pytest.mark.parametrize(
+    ("env_var", "read_timeout", "default"),
+    [
+        (PRISMA_COMMAND_TIMEOUT_ENV_VAR, prisma_command_timeout, DEFAULT_PRISMA_COMMAND_TIMEOUT),
+        (PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, prisma_migrate_deploy_timeout, DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT),
+    ],
+    ids=["command", "migrate_deploy"],
+)
 def test_unusable_timeout_override_falls_back_to_the_default(
-    raw: str, monkeypatch: pytest.MonkeyPatch
+    raw: str, env_var: str, read_timeout: Callable[[], float], default: float, monkeypatch: pytest.MonkeyPatch
 ) -> None:
     """A non-finite override would silently disable the timeout it configures."""
-    monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, raw)
+    monkeypatch.setenv(env_var, raw)
 
-    assert prisma_command_timeout() == DEFAULT_PRISMA_COMMAND_TIMEOUT
+    assert read_timeout() == default
 
 
 def test_timeout_overrides_are_independent(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.setenv(PRISMA_COMMAND_TIMEOUT_ENV_VAR, "12")
     monkeypatch.setenv(PRISMA_BOOTSTRAP_TIMEOUT_ENV_VAR, "900")
+    monkeypatch.setenv(PRISMA_MIGRATE_DEPLOY_TIMEOUT_ENV_VAR, "1200")
 
     assert prisma_command_timeout() == 12
     assert prisma_bootstrap_timeout() == 900
+    assert prisma_migrate_deploy_timeout() == 1200
 
 
 @pytest.mark.parametrize("module", ["utils.py", "replica_identity.py"])
diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py
index 47554913419..54cce9cdd78 100644
--- a/tests/proxy_unit_tests/test_proxy_server.py
+++ b/tests/proxy_unit_tests/test_proxy_server.py
@@ -3076,7 +3076,9 @@ async def test_update_config_success_callback_normalization():
     admin_user = UserAPIKeyAuth(
         user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-test"
     )
-    await proxy_server.update_config(config_update, user_api_key_dict=admin_user)
+    request = MagicMock()
+    request.json = AsyncMock(return_value={"litellm_settings": {"success_callback": ["SQS", "sQs"]}})
+    await proxy_server.update_config(config_update, request=request, user_api_key_dict=admin_user)
 
     assert (
         "litellm_settings" in upserted
diff --git a/tests/proxy_unit_tests/test_proxy_utils.py b/tests/proxy_unit_tests/test_proxy_utils.py
index 3bde72ccd49..35de9961054 100644
--- a/tests/proxy_unit_tests/test_proxy_utils.py
+++ b/tests/proxy_unit_tests/test_proxy_utils.py
@@ -1317,6 +1317,62 @@ def test_proxy_config_state_post_init_callback_call(monkeypatch):
     assert config["litellm_settings"]["default_team_settings"][0]["team_id"] == "test"
 
 
+@pytest.mark.asyncio
+async def test_default_team_settings_newrelic_resolves_traces_and_metrics():
+    """Static `default_team_settings` is the config-file twin of POST /team/callback.
+
+    A team pinned to New Relic through `default_team_settings` must reach the
+    same two loggers the dynamic path does: the per-team metrics logger (cost
+    and usage) and the trace logger (LLM/agent spans). This proves the static
+    path resolves both, not just one, so the config-file customer gets the
+    same per-team routing as the API customer.
+    """
+    from litellm.litellm_core_utils.litellm_logging import Logging
+    from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup
+    from litellm.proxy.proxy_server import ProxyConfig
+
+    pc = ProxyConfig()
+    pc.config = {
+        "litellm_settings": {
+            "default_team_settings": [
+                {
+                    "team_id": "team-a",
+                    "success_callback": ["newrelic"],
+                    "newrelic_api_key": "team-a-ingest-key",
+                    "newrelic_region": "eu",
+                }
+            ]
+        }
+    }
+
+    callback_metadata = LiteLLMProxyRequestSetup.add_team_based_callbacks_from_config(
+        team_id="team-a",
+        proxy_config=pc,
+    )
+
+    assert callback_metadata is not None
+    assert callback_metadata.success_callback == ["newrelic"]
+    assert callback_metadata.callback_vars == {
+        "newrelic_api_key": "team-a-ingest-key",
+        "newrelic_region": "eu",
+    }
+
+    logging_obj = Logging(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=False,
+        call_type="completion",
+        start_time=None,
+        litellm_call_id="static-nr-1",
+        function_id="static-nr-1",
+    )
+    logging_obj._trusted_callback_vars = tuple(callback_metadata.callback_vars.items())
+
+    resolved = logging_obj._resolve_dynamic_callback_string("newrelic")
+    resolved_names = {type(logger).__name__ for logger in resolved}
+    assert resolved_names == {"NewRelicMetricsLogger", "NewRelicLogger"}
+
+
 def test_proxy_config_state_get_config_state_error():
     """
     Ensures that get_config_state does not raise an error when the config is not a valid dictionary
diff --git a/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py b/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
index 3785ccdcfba..096efc33aaf 100644
--- a/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
+++ b/tests/proxy_unit_tests/test_unit_test_max_model_budget_limiter.py
@@ -1,3 +1,5 @@
+import asyncio
+from types import MappingProxyType
 from unittest.mock import AsyncMock, patch
 
 
@@ -5,6 +7,7 @@ import pytest
 
 import litellm
 from litellm.caching.caching import DualCache
+from litellm.caching.redis_cache import RedisCache
 from datetime import datetime, timezone
 
 from litellm.litellm_core_utils.duration_parser import duration_in_seconds
@@ -1332,3 +1335,85 @@ async def test_the_user_scope_has_no_pre_upgrade_counter_to_carry():
         await limiter.is_user_within_model_budget(
             user_id="u1", user_model_max_budget=model_max_budget, model="openai/gpt-4"
         )
+
+
+class _SharedFakeRedis(RedisCache):
+    """Stand-in for the one Redis every replica's DualCache is attached to.
+
+    Only the methods the limiter and DualCache call are implemented, and
+    ``super().__init__`` is skipped so no connection is opened.
+    """
+
+    def __init__(self):
+        self._store = MappingProxyType({})
+
+    async def async_set_cache(self, key, value, **kwargs):
+        self._store = MappingProxyType({**self._store, key: value})
+
+    async def async_get_cache(self, key, **kwargs):
+        return self._store.get(key)
+
+    async def async_batch_get_cache(self, key_list, **kwargs):
+        return {key: self._store.get(key) for key in key_list}
+
+    async def async_increment_pipeline(self, increment_list, **kwargs):
+        for op in increment_list:
+            total = self._store.get(op["key"], 0.0) + op["increment_value"]
+            self._store = MappingProxyType({**self._store, op["key"]: total})
+        return [self._store[op["key"]] for op in increment_list]
+
+
+async def _log_spend(limiter, *, key_hash, model_max_budget, response_cost):
+    await limiter.async_log_success_event(
+        _success_kwargs(
+            model_group="gpt-4",
+            response_cost=response_cost,
+            key_hash=key_hash,
+            key_model_max_budget=model_max_budget,
+        ),
+        response_obj=None,
+        start_time=None,
+        end_time=None,
+    )
+    # The Redis push is scheduled as a task rather than awaited inline.
+    await asyncio.gather(*(t for t in asyncio.all_tasks() if t is not asyncio.current_task()))
+
+
+@pytest.mark.asyncio
+async def test_spend_logged_on_one_replica_is_enforced_and_reported_on_another():
+    """
+    Each replica increments its own in-memory copy of the per-model counter and
+    pushes the increment to the shared Redis, so only Redis holds the window's
+    total. A replica that has served part of the traffic must still enforce and
+    report the total, not its own share.
+
+    Regression: reads went to the in-memory tier first, so a replica whose local
+    copy sat under the cap kept admitting requests and /key/info on it reported
+    that local share, while the shared counter was already over the cap.
+    """
+    shared_redis = _SharedFakeRedis()
+    replica_a = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    replica_b = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    key_hash = "vk-shared"
+    model_max_budget = {"gpt-4": {"budget_limit": 1.0, "time_period": "30d"}}
+    user_api_key = UserAPIKeyAuth(token=key_hash, model_max_budget=model_max_budget)
+
+    await _log_spend(replica_b, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.25)
+    await _log_spend(replica_a, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.5)
+    await _log_spend(replica_a, key_hash=key_hash, model_max_budget=model_max_budget, response_cost=0.5)
+
+    with pytest.raises(litellm.BudgetExceededError):
+        await replica_b.is_key_within_model_budget(user_api_key, "gpt-4")
+
+    usage_on_b = await build_model_max_budget_usage(
+        entity_type=Litellm_EntityType.KEY,
+        entity_id=key_hash,
+        model_max_budget=model_max_budget,
+        cache=replica_b.dual_cache,
+    )
+    assert usage_on_b["gpt-4"]["current_spend"] == 1.25
+
+    # Control: a replica that never served this key reads the same total.
+    replica_c = _PROXY_VirtualKeyModelMaxBudgetLimiter(dual_cache=DualCache(redis_cache=shared_redis))
+    with pytest.raises(litellm.BudgetExceededError):
+        await replica_c.is_key_within_model_budget(user_api_key, "gpt-4")
diff --git a/tests/router_unit_tests/test_router_anthropic_messages_fallback.py b/tests/router_unit_tests/test_router_anthropic_messages_fallback.py
new file mode 100644
index 00000000000..0c4d1dfc21e
--- /dev/null
+++ b/tests/router_unit_tests/test_router_anthropic_messages_fallback.py
@@ -0,0 +1,402 @@
+"""
+Unit tests for safeguard-refusal fallback on the /v1/messages router surface.
+
+An Anthropic safeguard refusal is an HTTP 200 whose body carries
+stop_reason "refusal" plus a stop_details object; the router converts it
+into a ContentPolicyViolationError so the content-policy fallback chain
+runs, but only when a matching fallback is configured. A plain refusal
+without stop_details, or any refusal with nothing configured, must reach
+the client byte-identical.
+
+The upstream is faked at the HTTP boundary by intercepting the third-party
+transport (httpx.AsyncClient.send), so requests run litellm's real
+transformation, allowlist, and streaming pipeline end to end.
+"""
+
+import json
+from typing import Any, AsyncIterator
+from unittest.mock import patch
+
+import httpx
+import pytest
+
+from litellm import Router
+from litellm.router_utils.fallback_event_handlers import (
+    PRE_ROUTING_SELECTED_MODEL_KEY,
+    record_pre_routing_selection,
+)
+
+REFUSAL_RESPONSE: dict[str, Any] = {
+    "id": "msg_refusal",
+    "type": "message",
+    "role": "assistant",
+    "model": "claude-fable-5",
+    "content": [],
+    "stop_reason": "refusal",
+    "stop_sequence": None,
+    "stop_details": {"category": "cyber", "explanation": "flagged"},
+    "usage": {"input_tokens": 25, "output_tokens": 1},
+}
+
+PLAIN_REFUSAL_RESPONSE: dict[str, Any] = {k: v for k, v in REFUSAL_RESPONSE.items() if k != "stop_details"}
+
+OK_RESPONSE: dict[str, Any] = {
+    "id": "msg_ok",
+    "type": "message",
+    "role": "assistant",
+    "model": "claude-opus-5",
+    "content": [{"type": "text", "text": "hello"}],
+    "stop_reason": "end_turn",
+    "stop_sequence": None,
+    "usage": {"input_tokens": 25, "output_tokens": 2},
+}
+
+
+def _sse(event: str, data: dict[str, Any]) -> bytes:
+    return f"event: {event}\ndata: {json.dumps(data)}\n\n".encode()
+
+
+REFUSAL_STREAM_FRAMES: tuple[bytes, ...] = (
+    _sse("message_start", {"type": "message_start", "message": {**REFUSAL_RESPONSE, "stop_reason": None}}),
+    _sse(
+        "message_delta",
+        {
+            "type": "message_delta",
+            "delta": {"stop_reason": "refusal", "stop_details": {"category": "cyber"}},
+            "usage": {"output_tokens": 1},
+        },
+    ),
+    _sse("message_stop", {"type": "message_stop"}),
+)
+
+OK_STREAM_FRAMES: tuple[bytes, ...] = (
+    _sse("message_start", {"type": "message_start", "message": {**OK_RESPONSE, "stop_reason": None}}),
+    _sse(
+        "content_block_delta",
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "hello"}},
+    ),
+    _sse("message_stop", {"type": "message_stop"}),
+)
+
+
+def _split_frames_mid_data_line(frames: tuple[bytes, ...]) -> tuple[bytes, ...]:
+    """Split each frame's data line in half, modeling a transport chunk boundary."""
+    return tuple(part for frame in frames for part in (frame[: len(frame) // 2], frame[len(frame) // 2 :]))
+
+
+class _FrameStream(httpx.AsyncByteStream):
+    def __init__(self, frames: tuple[bytes, ...]) -> None:
+        self._frames = frames
+
+    async def __aiter__(self) -> AsyncIterator[bytes]:
+        for frame in self._frames:
+            yield frame
+
+    async def aclose(self) -> None:
+        return None
+
+
+class FakeAnthropicUpstream:
+    """Intercepts the third-party transport (httpx.AsyncClient.send): refuses on fable
+    models, answers on others. The router deliberately does not forward caller-injected
+    clients, so the transport is the seam that exercises the real litellm pipeline."""
+
+    def __init__(
+        self,
+        refusal_body: dict[str, Any] = REFUSAL_RESPONSE,
+        refusal_frames: tuple[bytes, ...] = REFUSAL_STREAM_FRAMES,
+    ) -> None:
+        self.refusal_body = refusal_body
+        self.refusal_frames = refusal_frames
+        self.calls: list[str] = []
+        self.bodies: list[dict[str, Any]] = []
+
+    async def send(self, request: httpx.Request, **kwargs: Any) -> httpx.Response:
+        body = json.loads(request.content or b"{}")
+        model = body.get("model", "")
+        self.calls.append(model)
+        self.bodies.append(body)
+        refuses = "fable" in model
+        if body.get("stream"):
+            frames = self.refusal_frames if refuses else OK_STREAM_FRAMES
+            return httpx.Response(
+                200,
+                stream=_FrameStream(frames),
+                headers={"content-type": "text/event-stream"},
+                request=request,
+            )
+        return httpx.Response(200, json=self.refusal_body if refuses else OK_RESPONSE, request=request)
+
+    def install(self):
+        async def _send(_client: httpx.AsyncClient, request: httpx.Request, **kwargs: Any) -> httpx.Response:
+            return await self.send(request, **kwargs)
+
+        return patch("httpx.AsyncClient.send", new=_send)
+
+
+FABLE_TIER = {
+    "model_name": "fable-tier",
+    "litellm_params": {"model": "anthropic/claude-fable-5", "api_key": "sk-test"},
+}
+OPUS_TARGET = {
+    "model_name": "opus-target",
+    "litellm_params": {"model": "anthropic/claude-opus-5", "api_key": "sk-test"},
+}
+
+
+def _router(content_policy_fallbacks: list | None) -> Router:
+    return Router(model_list=[FABLE_TIER, OPUS_TARGET], content_policy_fallbacks=content_policy_fallbacks)
+
+
+async def _collect(stream: AsyncIterator[bytes]) -> bytes:
+    return b"".join([chunk async for chunk in stream])
+
+
+@pytest.mark.asyncio
+async def test_non_streaming_refusal_with_fallback_row_returns_fallback_response():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, messages=[{"role": "user", "content": "hi"}]
+        )
+
+    assert response["stop_reason"] == "end_turn"
+    assert response["id"] == "msg_ok"
+    assert len(fake.calls) == 2
+    assert "claude-opus-5" in fake.calls[1]
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "content_policy_fallbacks, upstream_body",
+    [
+        (None, REFUSAL_RESPONSE),
+        ([{"unrelated-group": ["opus-target"]}], REFUSAL_RESPONSE),
+        ([{"fable-tier": ["opus-target"]}], PLAIN_REFUSAL_RESPONSE),
+    ],
+    ids=["nothing-configured", "row-for-other-group", "refusal-without-stop-details"],
+)
+async def test_non_streaming_refusal_passes_through_untouched(content_policy_fallbacks, upstream_body):
+    fake = FakeAnthropicUpstream(refusal_body=upstream_body)
+    router = _router(content_policy_fallbacks=content_policy_fallbacks)
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, messages=[{"role": "user", "content": "hi"}]
+        )
+
+    assert response["stop_reason"] == "refusal"
+    assert response.get("stop_details") == upstream_body.get("stop_details")
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_with_fallback_row_streams_fallback_frames():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_split_across_chunks_still_falls_back():
+    fake = FakeAnthropicUpstream(refusal_frames=_split_frames_mid_data_line(REFUSAL_STREAM_FRAMES))
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_without_fallback_row_passes_frames_through():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=None)
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"stop_reason": "refusal"' in body
+    assert b"stop_details" in body
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_streaming_refusal_on_routed_tier_matches_tier_keyed_row_without_inbound_metadata():
+    """The pre-routing hook's tier stamp must reach the mid-stream fallback lookup even when the
+    request carries no metadata bucket at all (the snapshot is taken before the request runs)."""
+    fake = FakeAnthropicUpstream()
+    smart_router = {
+        "model_name": "smart-router",
+        "litellm_params": {
+            "model": "auto_router/complexity_router",
+            "complexity_router_config": {
+                "tiers": {"SIMPLE": "fable-tier", "MEDIUM": "fable-tier", "COMPLEX": "fable-tier"}
+            },
+            "complexity_router_default_model": "fable-tier",
+        },
+        "model_info": {"id": "router-1", "db_model": True},
+    }
+    router = Router(
+        model_list=[FABLE_TIER, OPUS_TARGET, smart_router],
+        content_policy_fallbacks=[{"fable-tier": ["opus-target"]}],
+        ignore_invalid_deployments=True,
+    )
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="smart-router", max_tokens=16, stream=True, messages=[{"role": "user", "content": "hi"}]
+        )
+        body = await _collect(stream)
+
+    assert b'"refusal"' not in body
+    assert b"text_delta" in body
+    assert len(fake.calls) == 2
+
+
+@pytest.mark.asyncio
+async def test_caller_forged_tier_stamp_cannot_pick_the_streaming_fallback_chain():
+    fake = FakeAnthropicUpstream()
+    router = _router(content_policy_fallbacks=[{"forged-tier": ["opus-target"]}])
+
+    with fake.install():
+        stream = await router.aanthropic_messages(
+            model="fable-tier",
+            max_tokens=16,
+            stream=True,
+            messages=[{"role": "user", "content": "hi"}],
+            litellm_metadata={PRE_ROUTING_SELECTED_MODEL_KEY: "forged-tier"},
+        )
+        body = await _collect(stream)
+
+    assert b'"stop_reason": "refusal"' in body
+    assert len(fake.calls) == 1
+
+
+@pytest.mark.asyncio
+async def test_tier_stamp_never_reaches_provider_bound_metadata():
+    """On /v1/messages the top-level metadata dict is Anthropic's own request field, so the
+    routed-tier stamp must never appear in any upstream body even when the client sends one."""
+    fake = FakeAnthropicUpstream()
+    smart_router = {
+        "model_name": "smart-router",
+        "litellm_params": {
+            "model": "auto_router/complexity_router",
+            "complexity_router_config": {
+                "tiers": {"SIMPLE": "fable-tier", "MEDIUM": "fable-tier", "COMPLEX": "fable-tier"}
+            },
+            "complexity_router_default_model": "fable-tier",
+        },
+        "model_info": {"id": "router-1", "db_model": True},
+    }
+    router = Router(
+        model_list=[FABLE_TIER, OPUS_TARGET, smart_router],
+        content_policy_fallbacks=[{"fable-tier": ["opus-target"]}],
+        ignore_invalid_deployments=True,
+    )
+
+    with fake.install():
+        response = await router.aanthropic_messages(
+            model="smart-router",
+            max_tokens=16,
+            messages=[{"role": "user", "content": "hi"}],
+            metadata={"user_id": "u1"},
+        )
+
+    assert response["stop_reason"] == "end_turn"
+    assert len(fake.bodies) == 2
+    for body in fake.bodies:
+        assert body.get("metadata") == {"user_id": "u1"}
+
+
+def test_record_pre_routing_selection_writes_only_the_internal_bucket():
+    """The Anthropic request's own metadata field must never carry the tier stamp."""
+    kwargs = {"metadata": {"user_id": "u1"}, "litellm_metadata": {}}
+
+    record_pre_routing_selection(kwargs, "tier-x")
+
+    assert kwargs["litellm_metadata"] == {PRE_ROUTING_SELECTED_MODEL_KEY: "tier-x"}
+    assert kwargs["metadata"] == {"user_id": "u1"}
+
+
+def test_refusal_gate_keys_on_pre_routing_tier_stamp():
+    router = _router(content_policy_fallbacks=[{"tier-group": ["opus-target"]}])
+
+    def anthropic_messages(**kwargs: Any) -> None:
+        return None
+
+    refusal_kwargs = {"litellm_metadata": {PRE_ROUTING_SELECTED_MODEL_KEY: "tier-group"}}
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="router-group",
+            original_generic_function=anthropic_messages,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs=refusal_kwargs,
+        )
+        is True
+    )
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="router-group",
+            original_generic_function=anthropic_messages,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs={},
+        )
+        is False
+    )
+
+
+def test_has_content_policy_fallback_default_fallbacks_arm():
+    router = Router(model_list=[OPUS_TARGET], fallbacks=[{"*": ["opus-target"]}])
+
+    assert router._has_content_policy_fallback("any-group", {}) is True
+    assert router._has_content_policy_fallback("any-group", {"content_policy_fallbacks": [{"other": ["x"]}]}) is False
+
+
+def test_get_fallback_model_group_for_lookup_groups_orders_tier_before_requested():
+    router = _router(content_policy_fallbacks=None)
+    fallbacks = [{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}]
+
+    assert router._get_fallback_model_group_for_lookup_groups(
+        fallbacks=fallbacks, lookup_groups=("tier1", "smart-router")
+    ) == ["backup-a"]
+    assert router._get_fallback_model_group_for_lookup_groups(
+        fallbacks=fallbacks, lookup_groups=("tier9", "smart-router")
+    ) == ["backup-b"]
+    assert router._get_fallback_model_group_for_lookup_groups(fallbacks=fallbacks, lookup_groups=()) is None
+
+
+def test_refusal_gate_ignores_other_generic_call_types():
+    router = _router(content_policy_fallbacks=[{"fable-tier": ["opus-target"]}])
+
+    def aresponses(**kwargs: Any) -> None:
+        return None
+
+    assert (
+        router._should_raise_anthropic_refusal_error(
+            model="fable-tier",
+            original_generic_function=aresponses,
+            response=dict(REFUSAL_RESPONSE),
+            kwargs={},
+        )
+        is False
+    )
diff --git a/tests/router_unit_tests/test_router_endpoints.py b/tests/router_unit_tests/test_router_endpoints.py
index d37af5b456a..a06aaa363ad 100644
--- a/tests/router_unit_tests/test_router_endpoints.py
+++ b/tests/router_unit_tests/test_router_endpoints.py
@@ -1324,6 +1324,98 @@ async def test_init_containers_api_endpoints_managed_id_without_model_id_applies
     assert call_kw["custom_llm_provider"] == "azure"
 
 
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_with_model_uses_deployment_credentials(monkeypatch):
+    """
+    ``POST /v1/containers`` carries no container ID, so a ``model`` in the request
+    body is the only way to pick a deployment. The upstream call must receive that
+    deployment's ``api_key``/``api_base`` instead of falling back to the global
+    ``OPENAI_API_KEY`` (which may be unset on the proxy).
+    """
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-5.4",
+                "litellm_params": {
+                    "model": "openai/gpt-5.4",
+                    "api_key": "sk-model-list-key",
+                    "api_base": "https://custom.openai.example/v1",
+                },
+            }
+        ]
+    )
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test", "name": "Test Container"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model="gpt-5.4",
+    )
+
+    mock_original_function.assert_called_once()
+    call_kw = mock_original_function.call_args.kwargs
+    assert call_kw["api_key"] == "sk-model-list-key"
+    assert call_kw["api_base"] == "https://custom.openai.example/v1"
+    assert call_kw["model"] == "openai/gpt-5.4"
+    assert call_kw["name"] == "Test Container"
+
+
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_without_model_calls_directly():
+    """
+    Without ``model`` (or with ``model=None`` as the proxy forwards it), create/list
+    must keep calling the handler directly with global provider credentials.
+    """
+    router = Router(model_list=[])
+    router._ageneric_api_call_with_fallbacks = AsyncMock()
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model=None,
+    )
+
+    router._ageneric_api_call_with_fallbacks.assert_not_called()
+    mock_original_function.assert_called_once_with(custom_llm_provider="openai", name="Test Container", model=None)
+
+
+@pytest.mark.asyncio
+async def test_init_containers_api_endpoints_create_with_unknown_model_passes_through(monkeypatch):
+    """
+    A ``model`` that names no configured deployment must not turn into a 400. The call
+    falls through to the handler with the caller's model and no injected deployment
+    credentials, matching the behaviour before model-based routing existed.
+    """
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    router = Router(
+        model_list=[
+            {
+                "model_name": "gpt-5.4",
+                "litellm_params": {"model": "openai/gpt-5.4", "api_key": "sk-model-list-key"},
+            }
+        ]
+    )
+    mock_original_function = AsyncMock(return_value={"id": "cntr_test"})
+
+    await router._init_containers_api_endpoints(
+        original_function=mock_original_function,
+        custom_llm_provider="openai",
+        name="Test Container",
+        model="does-not-exist",
+    )
+
+    mock_original_function.assert_called_once()
+    call_kw = mock_original_function.call_args.kwargs
+    assert call_kw["model"] == "does-not-exist"
+    assert call_kw["name"] == "Test Container"
+    assert "api_key" not in call_kw
+    assert "api_base" not in call_kw
+
+
 def test_router_model_group_encrypted_content_affinity_callback_registration():
     from litellm.router_utils.pre_call_checks.deployment_affinity_check import (
         DeploymentAffinityCheck,
diff --git a/tests/router_unit_tests/test_router_helper_utils.py b/tests/router_unit_tests/test_router_helper_utils.py
index dcd2e9edf7b..7dbac243d55 100644
--- a/tests/router_unit_tests/test_router_helper_utils.py
+++ b/tests/router_unit_tests/test_router_helper_utils.py
@@ -2294,6 +2294,7 @@ def search_tools():
                 "search_provider": "perplexity",
                 "api_key": "test-api-key",
                 "api_base": "https://api.perplexity.ai",
+                "mode": "turbo",
             },
         },
         {
@@ -2302,6 +2303,7 @@ def search_tools():
                 "search_provider": "perplexity",
                 "api_key": "test-api-key-2",
                 "api_base": "https://api.perplexity.ai",
+                "mode": "turbo",
             },
         },
     ]
@@ -2393,6 +2395,7 @@ async def test_asearch_with_fallbacks_helper(search_tools):
         assert "search_provider" in kwargs
         assert kwargs["search_provider"] == "perplexity"
         assert "api_key" in kwargs
+        assert kwargs["mode"] == "turbo"
         assert kwargs["query"] == "helper test query"
         return mock_response
 
diff --git a/tests/rust-python-harness/README.md b/tests/rust-python-harness/README.md
new file mode 100644
index 00000000000..e94ac87c3b3
--- /dev/null
+++ b/tests/rust-python-harness/README.md
@@ -0,0 +1,145 @@
+# Rust ↔ Python SDK parity harness
+
+This folder is the operator-facing harness for the Rust migration test plan. It runs pytest normally, listens to test events in-process, and redraws a live matrix grouped by testing strategy and SDK-level function.
+
+The matrix always has these SDK columns:
+
+- `ocr / aocr`
+- `messages / amessages`
+- `responses / aresponses`
+- `count_tokens`
+
+The harness has three deliberately broad test-strategy folders:
+
+| Strategy | Folder |
+| --- | --- |
+| Public SDK parity over generated and recorded inputs | [`e2e_fuzz_tests/`](e2e_fuzz_tests/) |
+| Focused tests of Rust-owned behavior | [`unit_tests_rust/`](unit_tests_rust/) |
+| Isolated transform and Python-to-Rust helper coverage | [`validate_sub_methods/`](validate_sub_methods/) |
+
+## Run it
+
+From the repository root:
+
+```bash
+poetry run python -m tests.rust-python-harness
+```
+
+The default runs every configured test once and updates all matching cells in real time. Narrow a run by strategy, SDK function, or both:
+
+```bash
+poetry run python -m tests.rust-python-harness --strategy e2e_fuzz_tests
+poetry run python -m tests.rust-python-harness --function messages
+poetry run python -m tests.rust-python-harness --strategy validate_sub_methods --function ocr
+```
+
+For a guided run, use the interactive picker. It asks which strategy rows and SDK
+function columns to include, then hands the terminal to the live dashboard. It never
+captures keys while tests are running, so Ctrl-C and pytest debugging remain safe.
+
+```bash
+poetry run python -m tests.rust-python-harness --interactive
+```
+
+Useful operator options:
+
+```bash
+# Inspect coverage and pytest selectors without running anything.
+poetry run python -m tests.rust-python-harness --list
+
+# Stable line-oriented output for CI logs or redirected output.
+poetry run python -m tests.rust-python-harness --plain
+
+# Measure Python reference lines exercised by this parity run and build an HTML heatmap.
+poetry run python -m tests.rust-python-harness --coverage
+
+# Forward pytest options. Use the equals form when the value begins with a dash.
+poetry run python -m tests.rust-python-harness --pytest-arg=-x
+```
+
+The process returns pytest's exit code. A configured selector that collects no test is also a failure. A planned cell has no selector yet and does not fail the run.
+
+The dashboard adapts to narrow terminals, shows elapsed time and unique-test progress,
+and prints the three slowest tests when the run ends. Each failure includes a focused
+`poetry run pytest ... -q` command. Redirected output and CI automatically use the
+line-oriented plain renderer; `--plain` lets you opt into it locally.
+
+The final screen includes a confidence score for every SDK section. It is the direct
+ratio of required strategy rows with passing evidence, such as `1/3 = 33%`; High means
+all required strategies passed, Medium means some passed, and Low means none passed.
+This behavioral score is intentionally shown separately from Python and Rust LOC.
+
+Coverage reports are written outside the three strategy folders at
+`target/rust-python-harness/`. Open `python-html/index.html` to inspect executed and
+missing Python lines; `python.json` and `python.xml` are available for automation.
+Coverage is finalized after pytest exits, because worker processes must flush their
+data first.
+
+## Port coverage and confidence
+
+Treat these as separate signals instead of one ambiguous coverage percentage:
+
+| Signal | Tool | What it proves |
+| --- | --- | --- |
+| Python reference LOC | `coverage.py` / `pytest-cov` via `--coverage` | The mapped Python behavior ran |
+| Rust port LOC | `cargo-llvm-cov` | The mapped Rust implementation ran |
+| Parity contracts | This harness matrix | Python and Rust had the same observable behavior |
+
+`validate_sub_methods/` owns the future source-section inventory that maps a stable
+Python qualified symbol to its Rust symbol. That inventory is the denominator for
+per-function rollups; raw coverage for the entire LiteLLM repository would obscure
+the port's real gaps. `unit_tests_rust/` owns direct `cargo-llvm-cov` runs, while
+`e2e_fuzz_tests/` owns behavioral parity and fuzz-case counts. Keep Python, Rust, and
+parity percentages visible side by side and label section confidence High only when
+the mapped implementation exists, every required strategy passes, and both sides meet
+their LOC thresholds. Generated Rust LCOV/HTML and the combined index also belong in
+`target/rust-python-harness/`, not in a fourth strategy folder.
+
+## Read the matrix
+
+| Mark | Meaning |
+| --- | --- |
+| `✓` | All collected tests passed |
+| `✗` | At least one test failed |
+| `!` | Test setup or teardown failed |
+| `↷` | All collected tests skipped |
+| `?` | A configured selector did not collect a test |
+| `—` | Strategy is planned but has no test yet |
+| `n/a` | Strategy does not apply to this SDK function |
+| `◐` | The configured tests cover only part of the TDD's parity contract |
+
+The initial end-to-end entries deliberately show `◐`: the repository has Rust bridge tests for OCR, Messages, and Responses websocket plumbing, but those are not yet frozen-Python-oracle comparisons. The remaining TDD cells stay visible as planned work instead of disappearing from a green summary.
+
+## Attach parity tests
+
+Each of the three folders contains a concise `README.md` and a `strategy.json`. Add a pytest file or node ID to the appropriate SDK function's `selectors` list:
+
+```json
+{
+  "coverage": "complete",
+  "selectors": [
+    "tests/rust-python-harness/validate_sub_methods/test_messages.py"
+  ]
+}
+```
+
+Selectors use the same syntax as pytest. A file selector aggregates every test in the file; a node selector can target one test or parametrized family. The runner deduplicates selectors, so one test may intentionally prove more than one cell without executing twice.
+
+Use these coverage values:
+
+- `complete`: implements the full strategy contract for that SDK function.
+- `partial`: useful coverage exists, but the TDD contract is not fully proven.
+- `planned`: no runnable parity test exists yet.
+- `not_applicable`: the strategy cannot apply, such as streaming for OCR.
+
+Keep comparison mechanics in shared harness modules and provider/function facts in the owning strategy folder. A Python/Rust mismatch is a test failure; do not normalize away observable return types, exception classes, private response fields, chunk ordering, or callback payload differences merely to make a cell green.
+
+## Architecture
+
+- `catalog.py` validates and loads every strategy manifest.
+- `models.py` owns typed strategy, case, coverage, and run-state models.
+- `runner.py` maps live pytest events back to one or more matrix cells.
+- `ui.py` renders the interactive Rich dashboard and a dependency-free plain fallback.
+- `cli.py` handles filtering and preserves pytest exit semantics.
+
+The harness is driven from Python, matching the SDK surface and existing test tooling. Rust remains responsible for the implementation under comparison; the harness does not move provider semantics into the PyO3 bridge.
diff --git a/tests/rust-python-harness/__init__.py b/tests/rust-python-harness/__init__.py
new file mode 100644
index 00000000000..70362674d2b
--- /dev/null
+++ b/tests/rust-python-harness/__init__.py
@@ -0,0 +1,5 @@
+"""Interactive Rust/Python SDK parity test harness."""
+
+from .catalog import load_catalog
+
+__all__ = ["load_catalog"]
diff --git a/tests/rust-python-harness/__main__.py b/tests/rust-python-harness/__main__.py
new file mode 100644
index 00000000000..bfdcd0c1158
--- /dev/null
+++ b/tests/rust-python-harness/__main__.py
@@ -0,0 +1,4 @@
+from .cli import main
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tests/rust-python-harness/catalog.py b/tests/rust-python-harness/catalog.py
new file mode 100644
index 00000000000..e23b9b125f0
--- /dev/null
+++ b/tests/rust-python-harness/catalog.py
@@ -0,0 +1,93 @@
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from typing import Any
+
+from .models import Coverage, HarnessCase, SDK_FUNCTIONS, Strategy
+
+STRATEGIES_ROOT = Path(__file__).parent
+
+
+def _require_string(value: Any, field: str, source: Path) -> str:
+    if not isinstance(value, str) or not value.strip():
+        raise ValueError(f"{source}: {field} must be a non-empty string")
+    return value
+
+
+def _load_strategy(source: Path) -> Strategy:
+    with source.open(encoding="utf-8") as stream:
+        data = json.load(stream)
+
+    strategy_id = _require_string(data.get("id"), "id", source)
+    label = _require_string(data.get("label"), "label", source)
+    description = _require_string(data.get("description"), "description", source)
+    order = data.get("order")
+    if not isinstance(order, int):
+        raise ValueError(f"{source}: order must be an integer")
+    function_data = data.get("functions")
+    if not isinstance(function_data, dict):
+        raise ValueError(f"{source}: functions must be an object")
+
+    missing = set(SDK_FUNCTIONS) - set(function_data)
+    extra = set(function_data) - set(SDK_FUNCTIONS)
+    if missing or extra:
+        raise ValueError(
+            f"{source}: functions must exactly match {SDK_FUNCTIONS}; missing={missing}, extra={extra}"
+        )
+
+    cases: list[HarnessCase] = []
+    for sdk_function in SDK_FUNCTIONS:
+        case_data = function_data[sdk_function]
+        if not isinstance(case_data, dict):
+            raise ValueError(f"{source}: functions.{sdk_function} must be an object")
+        try:
+            coverage = Coverage(case_data.get("coverage"))
+        except ValueError as exc:
+            raise ValueError(f"{source}: invalid coverage for {sdk_function}") from exc
+        selectors = case_data.get("selectors", [])
+        if not isinstance(selectors, list) or not all(
+            isinstance(item, str) and item for item in selectors
+        ):
+            raise ValueError(
+                f"{source}: selectors for {sdk_function} must be a list of strings"
+            )
+        if coverage is Coverage.NOT_APPLICABLE and selectors:
+            raise ValueError(
+                f"{source}: not_applicable case {sdk_function} cannot have selectors"
+            )
+        cases.append(
+            HarnessCase(
+                strategy_id=strategy_id,
+                strategy_label=label,
+                sdk_function=sdk_function,
+                coverage=coverage,
+                selectors=tuple(selectors),
+                note=str(case_data.get("note", "")),
+            )
+        )
+
+    return Strategy(
+        order=order,
+        id=strategy_id,
+        label=label,
+        description=description,
+        directory=source.parent,
+        cases=tuple(cases),
+    )
+
+
+def load_catalog(root: Path = STRATEGIES_ROOT) -> tuple[Strategy, ...]:
+    sources = sorted(root.glob("*/strategy.json"))
+    if not sources:
+        raise ValueError(f"No strategy manifests found below {root}")
+    strategies = tuple(
+        sorted(
+            (_load_strategy(source) for source in sources),
+            key=lambda strategy: strategy.order,
+        )
+    )
+    ids = [strategy.id for strategy in strategies]
+    if len(ids) != len(set(ids)):
+        raise ValueError(f"Duplicate strategy id in {root}")
+    return strategies
diff --git a/tests/rust-python-harness/cli.py b/tests/rust-python-harness/cli.py
new file mode 100644
index 00000000000..41c46f9613a
--- /dev/null
+++ b/tests/rust-python-harness/cli.py
@@ -0,0 +1,180 @@
+from __future__ import annotations
+
+import argparse
+import importlib.util
+from collections.abc import Sequence
+from pathlib import Path
+
+from .catalog import load_catalog
+from .models import HarnessCase, Strategy
+from .runner import run_pytest
+from .ui import make_dashboard
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+COVERAGE_ROOT = REPO_ROOT / "target" / "rust-python-harness"
+
+
+def _parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        prog="rust-python-harness",
+        description="Run Rust/Python parity tests with a live strategy-by-SDK-function dashboard.",
+    )
+    parser.add_argument(
+        "-i",
+        "--interactive",
+        action="store_true",
+        help="pick strategies and SDK functions in a guided terminal menu",
+    )
+    parser.add_argument(
+        "--list", action="store_true", help="show the catalog without running tests"
+    )
+    parser.add_argument(
+        "--strategy",
+        action="append",
+        default=[],
+        metavar="ID",
+        help="run only this strategy",
+    )
+    parser.add_argument(
+        "--function",
+        action="append",
+        default=[],
+        dest="sdk_functions",
+        choices=("ocr", "messages", "responses", "count_tokens"),
+        help="run only this SDK function",
+    )
+    parser.add_argument(
+        "--plain",
+        action="store_true",
+        help="disable the interactive terminal dashboard",
+    )
+    parser.add_argument(
+        "--coverage",
+        action="store_true",
+        help="write Python reference LOC reports (HTML, JSON, and XML)",
+    )
+    parser.add_argument(
+        "--pytest-arg",
+        action="append",
+        default=[],
+        metavar="ARG",
+        help="append an argument to pytest (repeatable, for example --pytest-arg=-x)",
+    )
+    return parser
+
+
+def _coverage_pytest_args(output_root: Path = COVERAGE_ROOT) -> tuple[str, ...]:
+    output_root.mkdir(parents=True, exist_ok=True)
+    return (
+        "--cov=litellm",
+        "--cov-context=test",
+        f"--cov-report=json:{output_root / 'python.json'}",
+        f"--cov-report=xml:{output_root / 'python.xml'}",
+        f"--cov-report=html:{output_root / 'python-html'}",
+    )
+
+
+def _pick_values(
+    title: str, options: Sequence[tuple[str, str]], input_fn=input
+) -> set[str]:
+    print(f"\n{title} (Enter = all)")
+    for index, (value, label) in enumerate(options, start=1):
+        print(f"  {index:>2}. {label}  [{value}]")
+    while True:
+        answer = input_fn("Choose numbers, comma-separated: ").strip()
+        if not answer:
+            return set()
+        try:
+            indexes = {int(part.strip()) for part in answer.split(",")}
+        except ValueError:
+            print("Please enter numbers separated by commas.")
+            continue
+        if indexes and all(1 <= index <= len(options) for index in indexes):
+            return {options[index - 1][0] for index in indexes}
+        print(f"Choose values from 1 to {len(options)}.")
+
+
+def _interactive_filters(strategies: Sequence[Strategy]) -> tuple[set[str], set[str]]:
+    strategy_ids = _pick_values(
+        "Testing strategies", [(strategy.id, strategy.label) for strategy in strategies]
+    )
+    sdk_functions = _pick_values(
+        "SDK functions",
+        [(name, name) for name in ("ocr", "messages", "responses", "count_tokens")],
+    )
+    return strategy_ids, sdk_functions
+
+
+def _select(
+    strategies: Sequence[Strategy], strategy_ids: set[str], sdk_functions: set[str]
+) -> tuple[HarnessCase, ...]:
+    known_ids = {strategy.id for strategy in strategies}
+    unknown = strategy_ids - known_ids
+    if unknown:
+        raise ValueError(f"Unknown strategy: {', '.join(sorted(unknown))}")
+    return tuple(
+        case
+        for strategy in strategies
+        if not strategy_ids or strategy.id in strategy_ids
+        for case in strategy.cases
+        if not sdk_functions or case.sdk_function in sdk_functions
+    )
+
+
+def _print_catalog(strategies: Sequence[Strategy]) -> None:
+    for strategy in strategies:
+        print(f"{strategy.id:20} {strategy.label}")
+        for case in strategy.cases:
+            selectors = (
+                ", ".join(case.selectors) if case.selectors else "no test configured"
+            )
+            print(f"  {case.sdk_function:12} {case.coverage.value:14} {selectors}")
+
+
+def main(argv: Sequence[str] | None = None) -> int:
+    args = _parser().parse_args(argv)
+    if args.coverage and importlib.util.find_spec("pytest_cov") is None:
+        _parser().error(
+            "--coverage requires the project's pytest-cov dependency; run with "
+            "`poetry run python -m tests.rust-python-harness --coverage`"
+        )
+    strategies = load_catalog()
+    if args.list:
+        _print_catalog(strategies)
+        return 0
+
+    strategy_ids = set(args.strategy)
+    sdk_functions = set(args.sdk_functions)
+    if args.interactive:
+        picked_strategies, picked_functions = _interactive_filters(strategies)
+        strategy_ids = strategy_ids or picked_strategies
+        sdk_functions = sdk_functions or picked_functions
+
+    try:
+        cases = _select(strategies, strategy_ids, sdk_functions)
+    except ValueError as exc:
+        _parser().error(str(exc))
+    selected_strategy_ids = {case.strategy_id for case in cases}
+    visible_strategies = tuple(
+        strategy for strategy in strategies if strategy.id in selected_strategy_ids
+    )
+    dashboard = make_dashboard(
+        visible_strategies,
+        plain=args.plain,
+        confidence_strategies=strategies,
+    )
+    pytest_args = [*args.pytest_arg]
+    if args.coverage:
+        pytest_args.extend(_coverage_pytest_args())
+    with dashboard:
+        exit_code, run = run_pytest(
+            cases=cases,
+            repo_root=REPO_ROOT,
+            on_update=dashboard.update,
+            pytest_args=pytest_args,
+        )
+        dashboard.finish(run, exit_code)
+    if args.coverage and (COVERAGE_ROOT / "python.json").exists():
+        print(f"Python LOC heatmap: {COVERAGE_ROOT / 'python-html' / 'index.html'}")
+        print(f"Machine-readable coverage: {COVERAGE_ROOT / 'python.json'}")
+    return exit_code
diff --git a/tests/rust-python-harness/e2e_fuzz_tests/README.md b/tests/rust-python-harness/e2e_fuzz_tests/README.md
new file mode 100644
index 00000000000..34b12050ff9
--- /dev/null
+++ b/tests/rust-python-harness/e2e_fuzz_tests/README.md
@@ -0,0 +1,3 @@
+# End-to-end fuzz tests
+
+Runs the same SDK call through the Python and Rust paths using generated inputs and recorded provider responses. It compares public results, streams, callbacks, and exceptions to catch behavior differences a unit test can miss.
diff --git a/tests/rust-python-harness/e2e_fuzz_tests/strategy.json b/tests/rust-python-harness/e2e_fuzz_tests/strategy.json
new file mode 100644
index 00000000000..abeea01d9b5
--- /dev/null
+++ b/tests/rust-python-harness/e2e_fuzz_tests/strategy.json
@@ -0,0 +1,12 @@
+{
+  "order": 10,
+  "id": "e2e_fuzz_tests",
+  "label": "End-to-end fuzz tests",
+  "description": "Compare observable Python and Rust SDK behavior over generated and recorded inputs.",
+  "functions": {
+    "ocr": {"coverage": "partial", "selectors": ["tests/test_litellm/ocr/test_rust_bridge.py"], "note": "Bridge coverage exists; frozen-oracle fuzz parity is still being added."},
+    "messages": {"coverage": "partial", "selectors": ["tests/test_litellm/anthropic_interface/test_rust_bridge_messages.py"], "note": "Bridge coverage exists; frozen-oracle fuzz parity is still being added."},
+    "responses": {"coverage": "partial", "selectors": ["tests/test_litellm/responses/test_rust_bridge_websocket.py"], "note": "Covers the websocket bridge; full responses parity is still being added."},
+    "count_tokens": {"coverage": "planned", "selectors": [], "note": "No Rust count_tokens parity test is present yet."}
+  }
+}
diff --git a/tests/rust-python-harness/models.py b/tests/rust-python-harness/models.py
new file mode 100644
index 00000000000..21097e0f7d0
--- /dev/null
+++ b/tests/rust-python-harness/models.py
@@ -0,0 +1,219 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from enum import Enum
+from pathlib import Path
+from time import monotonic
+from typing import Iterable
+
+
+class Coverage(str, Enum):
+    COMPLETE = "complete"
+    PARTIAL = "partial"
+    PLANNED = "planned"
+    NOT_APPLICABLE = "not_applicable"
+
+
+class RunStatus(str, Enum):
+    NOT_RUN = "not_run"
+    QUEUED = "queued"
+    RUNNING = "running"
+    PASSED = "passed"
+    FAILED = "failed"
+    SKIPPED = "skipped"
+    ERROR = "error"
+    MISSING = "missing"
+    PLANNED = "planned"
+    NOT_APPLICABLE = "not_applicable"
+
+
+class ConfidenceLevel(str, Enum):
+    HIGH = "HIGH"
+    MEDIUM = "MEDIUM"
+    LOW = "LOW"
+
+
+SDK_FUNCTIONS = ("ocr", "messages", "responses", "count_tokens")
+
+
+@dataclass(frozen=True)
+class HarnessCase:
+    strategy_id: str
+    strategy_label: str
+    sdk_function: str
+    coverage: Coverage
+    selectors: tuple[str, ...]
+    note: str = ""
+
+    @property
+    def key(self) -> str:
+        return f"{self.strategy_id}:{self.sdk_function}"
+
+
+@dataclass(frozen=True)
+class Strategy:
+    order: int
+    id: str
+    label: str
+    description: str
+    directory: Path
+    cases: tuple[HarnessCase, ...]
+
+
+@dataclass
+class CaseResult:
+    case: HarnessCase
+    status: RunStatus = RunStatus.NOT_RUN
+    collected: set[str] = field(default_factory=set)
+    completed: set[str] = field(default_factory=set)
+    passed: int = 0
+    failed: int = 0
+    skipped: int = 0
+    errors: int = 0
+    outcomes: dict[str, RunStatus] = field(default_factory=dict)
+    durations: dict[str, float] = field(default_factory=dict)
+
+    @property
+    def total(self) -> int:
+        return len(self.collected)
+
+    @property
+    def duration(self) -> float:
+        return sum(self.durations.values())
+
+    def record(self, nodeid: str, status: RunStatus, duration: float = 0.0) -> None:
+        """Record a terminal outcome, allowing teardown errors to replace a pass."""
+        self.outcomes[nodeid] = status
+        self.durations[nodeid] = self.durations.get(nodeid, 0.0) + duration
+        self.completed = set(self.outcomes)
+        values = tuple(self.outcomes.values())
+        self.passed = values.count(RunStatus.PASSED)
+        self.failed = values.count(RunStatus.FAILED)
+        self.skipped = values.count(RunStatus.SKIPPED)
+        self.errors = values.count(RunStatus.ERROR)
+        self.finalize()
+
+    def set_initial_status(self) -> None:
+        if self.case.coverage is Coverage.NOT_APPLICABLE:
+            self.status = RunStatus.NOT_APPLICABLE
+        elif not self.case.selectors:
+            self.status = RunStatus.PLANNED
+        else:
+            self.status = RunStatus.QUEUED
+
+    def finalize(self) -> None:
+        if self.status in {RunStatus.NOT_APPLICABLE, RunStatus.PLANNED}:
+            return
+        if not self.collected:
+            self.status = RunStatus.MISSING
+        elif self.errors:
+            self.status = RunStatus.ERROR
+        elif self.failed:
+            self.status = RunStatus.FAILED
+        elif self.passed and len(self.completed) == len(self.collected):
+            self.status = RunStatus.PASSED
+        elif self.skipped and len(self.completed) == len(self.collected):
+            self.status = RunStatus.SKIPPED
+
+
+@dataclass
+class HarnessRun:
+    results: dict[str, CaseResult]
+    current_nodeid: str | None = None
+    failures: list[tuple[str, str]] = field(default_factory=list)
+    started_at: float = field(default_factory=monotonic)
+    finished_at: float | None = None
+
+    @property
+    def duration(self) -> float:
+        return (self.finished_at or monotonic()) - self.started_at
+
+    @property
+    def unique_tests(self) -> int:
+        return len(
+            {nodeid for result in self.results.values() for nodeid in result.collected}
+        )
+
+    @property
+    def completed_tests(self) -> int:
+        return len(
+            {nodeid for result in self.results.values() for nodeid in result.completed}
+        )
+
+    @classmethod
+    def from_cases(cls, cases: Iterable[HarnessCase]) -> "HarnessRun":
+        results = {case.key: CaseResult(case=case) for case in cases}
+        for result in results.values():
+            result.set_initial_status()
+        return cls(results=results)
+
+
+@dataclass(frozen=True)
+class SectionConfidence:
+    sdk_function: str
+    verified_strategies: int
+    required_strategies: int
+    level: ConfidenceLevel
+    details: tuple[str, ...]
+
+    @property
+    def percentage(self) -> int:
+        if not self.required_strategies:
+            return 0
+        return round(100 * self.verified_strategies / self.required_strategies)
+
+
+def section_confidence(
+    run: HarnessRun, strategies: Iterable[Strategy]
+) -> tuple[SectionConfidence, ...]:
+    strategy_list = tuple(strategies)
+    scores: list[SectionConfidence] = []
+    for sdk_function in SDK_FUNCTIONS:
+        cases = tuple(
+            case
+            for strategy in strategy_list
+            for case in strategy.cases
+            if case.sdk_function == sdk_function
+            and case.coverage is not Coverage.NOT_APPLICABLE
+        )
+        verified = 0
+        details: list[str] = []
+        for case in cases:
+            result = run.results.get(case.key)
+            status = result.status if result is not None else RunStatus.NOT_RUN
+            if status is RunStatus.PASSED:
+                verified += 1
+            details.append(
+                f"{STATUS_LABELS[status]} {case.strategy_id} ({case.coverage.value})"
+            )
+        required = len(cases)
+        if required and verified == required:
+            level = ConfidenceLevel.HIGH
+        elif verified:
+            level = ConfidenceLevel.MEDIUM
+        else:
+            level = ConfidenceLevel.LOW
+        scores.append(
+            SectionConfidence(
+                sdk_function=sdk_function,
+                verified_strategies=verified,
+                required_strategies=required,
+                level=level,
+                details=tuple(details),
+            )
+        )
+    return tuple(scores)
+
+
+STATUS_LABELS = {
+    RunStatus.NOT_RUN: "·",
+    RunStatus.QUEUED: "○",
+    RunStatus.RUNNING: "◉",
+    RunStatus.PASSED: "✓",
+    RunStatus.FAILED: "✗",
+    RunStatus.SKIPPED: "↷",
+    RunStatus.ERROR: "!",
+    RunStatus.MISSING: "?",
+    RunStatus.PLANNED: "—",
+    RunStatus.NOT_APPLICABLE: "n/a",
+}
diff --git a/tests/rust-python-harness/runner.py b/tests/rust-python-harness/runner.py
new file mode 100644
index 00000000000..82393ef234e
--- /dev/null
+++ b/tests/rust-python-harness/runner.py
@@ -0,0 +1,160 @@
+from __future__ import annotations
+
+import os
+from collections.abc import Callable, Sequence
+from pathlib import Path
+from time import monotonic
+
+import pytest
+
+from .models import CaseResult, HarnessCase, HarnessRun, RunStatus
+
+UpdateCallback = Callable[[HarnessRun], None]
+
+
+def selector_matches_node(selector: str, nodeid: str) -> bool:
+    normalized_selector = selector.replace("\\", "/")
+    normalized_nodeid = nodeid.replace("\\", "/")
+    if "::" in normalized_selector:
+        return normalized_nodeid == normalized_selector or normalized_nodeid.startswith(
+            f"{normalized_selector}["
+        )
+    return normalized_nodeid == normalized_selector or normalized_nodeid.startswith(
+        f"{normalized_selector}::"
+    )
+
+
+def selector_path(selector: str) -> Path:
+    return Path(selector.split("::", 1)[0])
+
+
+def runnable_selectors(
+    cases: Sequence[HarnessCase], repo_root: Path
+) -> tuple[str, ...]:
+    selectors = {
+        selector
+        for case in cases
+        for selector in case.selectors
+        if (repo_root / selector_path(selector)).exists()
+    }
+    return tuple(sorted(selectors))
+
+
+class HarnessPytestPlugin:
+    def __init__(self, run: HarnessRun, on_update: UpdateCallback) -> None:
+        self.run = run
+        self.on_update = on_update
+        self.node_to_results: dict[str, list[CaseResult]] = {}
+
+    def _notify(self) -> None:
+        self.on_update(self.run)
+
+    def pytest_collection_modifyitems(self, items: list[pytest.Item]) -> None:
+        for item in items:
+            matched_results: list[CaseResult] = []
+            for result in self.run.results.values():
+                if any(
+                    selector_matches_node(selector, item.nodeid)
+                    for selector in result.case.selectors
+                ):
+                    result.collected.add(item.nodeid)
+                    matched_results.append(result)
+            if matched_results:
+                self.node_to_results[item.nodeid] = matched_results
+        for result in self.run.results.values():
+            if result.status is RunStatus.QUEUED and not result.collected:
+                result.status = RunStatus.MISSING
+        self._notify()
+
+    def pytest_runtest_logstart(
+        self, nodeid: str, location: tuple[str, int | None, str]
+    ) -> None:
+        del location
+        self.run.current_nodeid = nodeid
+        for result in self.node_to_results.get(nodeid, []):
+            if result.status not in {RunStatus.FAILED, RunStatus.ERROR}:
+                result.status = RunStatus.RUNNING
+        self._notify()
+
+    def pytest_runtest_logreport(self, report: pytest.TestReport) -> None:
+        if report.when not in {"setup", "call", "teardown"}:
+            return
+        results = self.node_to_results.get(report.nodeid, [])
+        if not results:
+            return
+
+        terminal = report.when == "call" or report.failed or report.skipped
+        if not terminal:
+            for result in results:
+                result.durations[report.nodeid] = (
+                    result.durations.get(report.nodeid, 0.0) + report.duration
+                )
+            return
+        for result in results:
+            if report.when == "teardown" and not report.failed:
+                result.durations[report.nodeid] = (
+                    result.durations.get(report.nodeid, 0.0) + report.duration
+                )
+                continue
+            if report.skipped:
+                status = RunStatus.SKIPPED
+            elif report.failed and report.when in {"setup", "teardown"}:
+                status = RunStatus.ERROR
+            elif report.failed:
+                status = RunStatus.FAILED
+            else:
+                status = RunStatus.PASSED
+            result.record(report.nodeid, status, report.duration)
+        if report.failed:
+            failure = (report.nodeid, str(report.longrepr))
+            if failure not in self.run.failures:
+                self.run.failures.append(failure)
+        self._notify()
+
+    def pytest_sessionfinish(
+        self, session: pytest.Session, exitstatus: int | pytest.ExitCode
+    ) -> None:
+        del session, exitstatus
+        self.run.current_nodeid = None
+        self.run.finished_at = monotonic()
+        for result in self.run.results.values():
+            result.finalize()
+        self._notify()
+
+
+def run_pytest(
+    cases: Sequence[HarnessCase],
+    repo_root: Path,
+    on_update: UpdateCallback,
+    pytest_args: Sequence[str] = (),
+) -> tuple[int, HarnessRun]:
+    run = HarnessRun.from_cases(cases)
+    selectors = runnable_selectors(cases, repo_root)
+    if not selectors:
+        for result in run.results.values():
+            result.finalize()
+        run.finished_at = monotonic()
+        on_update(run)
+        has_missing_test = any(
+            result.status is RunStatus.MISSING for result in run.results.values()
+        )
+        exit_code = (
+            int(pytest.ExitCode.TESTS_FAILED)
+            if has_missing_test
+            else int(pytest.ExitCode.OK)
+        )
+        return exit_code, run
+
+    plugin = HarnessPytestPlugin(run=run, on_update=on_update)
+    args = [*selectors, "-p", "no:terminal", *pytest_args]
+    previous_directory = Path.cwd()
+    try:
+        os.chdir(repo_root)
+        exit_code = int(pytest.main(args, plugins=[plugin]))
+    finally:
+        os.chdir(previous_directory)
+    if exit_code == 0 and any(
+        result.status is RunStatus.MISSING for result in run.results.values()
+    ):
+        exit_code = int(pytest.ExitCode.TESTS_FAILED)
+    return exit_code, run
diff --git a/tests/rust-python-harness/ui.py b/tests/rust-python-harness/ui.py
new file mode 100644
index 00000000000..57fedd17fa6
--- /dev/null
+++ b/tests/rust-python-harness/ui.py
@@ -0,0 +1,295 @@
+from __future__ import annotations
+
+import os
+import shlex
+import sys
+from collections.abc import Sequence
+from contextlib import AbstractContextManager
+from pathlib import Path
+from typing import Any
+
+from .models import (
+    Coverage,
+    HarnessRun,
+    RunStatus,
+    SDK_FUNCTIONS,
+    Strategy,
+    section_confidence,
+)
+
+STATUS_GLYPHS = {
+    RunStatus.NOT_RUN: "·",
+    RunStatus.QUEUED: "○",
+    RunStatus.RUNNING: "◉",
+    RunStatus.PASSED: "✓",
+    RunStatus.FAILED: "✗",
+    RunStatus.SKIPPED: "↷",
+    RunStatus.ERROR: "!",
+    RunStatus.MISSING: "?",
+    RunStatus.PLANNED: "—",
+    RunStatus.NOT_APPLICABLE: "n/a",
+}
+
+STATUS_STYLES = {
+    RunStatus.QUEUED: "dim",
+    RunStatus.RUNNING: "bold cyan",
+    RunStatus.PASSED: "bold green",
+    RunStatus.FAILED: "bold red",
+    RunStatus.SKIPPED: "yellow",
+    RunStatus.ERROR: "bold red",
+    RunStatus.MISSING: "magenta",
+    RunStatus.PLANNED: "dim",
+    RunStatus.NOT_APPLICABLE: "dim",
+}
+
+
+def _format_duration(seconds: float) -> str:
+    if seconds < 1:
+        return f"{seconds * 1000:.0f}ms"
+    if seconds < 60:
+        return f"{seconds:.1f}s"
+    return f"{int(seconds // 60)}m {seconds % 60:.0f}s"
+
+
+def _rerun_command(nodeid: str) -> str:
+    return f"poetry run pytest {shlex.quote(nodeid)} -q"
+
+
+def _summary(run: HarnessRun) -> tuple[int, int, int, int]:
+    outcomes: dict[str, RunStatus] = {}
+    for result in run.results.values():
+        outcomes.update(result.outcomes)
+    return (
+        list(outcomes.values()).count(RunStatus.PASSED),
+        list(outcomes.values()).count(RunStatus.FAILED),
+        list(outcomes.values()).count(RunStatus.ERROR),
+        list(outcomes.values()).count(RunStatus.SKIPPED),
+    )
+
+
+def _cell_text(run: HarnessRun, strategy_id: str, sdk_function: str) -> tuple[str, str]:
+    result = run.results.get(f"{strategy_id}:{sdk_function}")
+    if result is None:
+        return "", ""
+    counts = ""
+    if result.total:
+        counts = f" {len(result.completed)}/{result.total}"
+    coverage = " ◐" if result.case.coverage is Coverage.PARTIAL else ""
+    return f"{STATUS_GLYPHS[result.status]}{counts}{coverage}", STATUS_STYLES.get(
+        result.status, ""
+    )
+
+
+class RichDashboard(AbstractContextManager["RichDashboard"]):
+    def __init__(
+        self,
+        strategies: Sequence[Strategy],
+        confidence_strategies: Sequence[Strategy],
+    ) -> None:
+        from rich.console import Console
+        from rich.live import Live
+
+        self.strategies = strategies
+        self.confidence_strategies = confidence_strategies
+        self.console = Console()
+        self.live: Any = Live(
+            console=self.console, refresh_per_second=12, transient=False
+        )
+
+    def _table(self, run: HarnessRun) -> Any:
+        from rich import box
+        from rich.table import Table
+        from rich.text import Text
+
+        narrow = self.console.width < 96
+        if narrow:
+            table = Table(box=box.SIMPLE_HEAVY, expand=True, show_header=False)
+            table.add_column("Strategy", ratio=3)
+            table.add_column("Results", ratio=5)
+            for strategy in self.strategies:
+                values = []
+                for sdk_function in SDK_FUNCTIONS:
+                    value, style = _cell_text(run, strategy.id, sdk_function)
+                    if value:
+                        values.append(
+                            Text.assemble((f"{sdk_function} ", "dim"), (value, style))
+                        )
+                table.add_row(strategy.label, Text("  ").join(values))
+            return table
+
+        table = Table(box=box.ROUNDED, expand=True, title="Strategy × SDK function")
+        table.add_column("Strategy", ratio=3)
+        for label in ("ocr/aocr", "messages", "responses", "count_tokens"):
+            table.add_column(label, justify="center", ratio=1)
+        for strategy in self.strategies:
+            cells = []
+            for sdk_function in SDK_FUNCTIONS:
+                value, style = _cell_text(run, strategy.id, sdk_function)
+                cells.append(Text(value, style=style))
+            table.add_row(strategy.label, *cells)
+        return table
+
+    def __enter__(self) -> "RichDashboard":
+        self.live.__enter__()
+        return self
+
+    def __exit__(self, *args: object) -> None:
+        self.live.__exit__(*args)
+
+    def update(self, run: HarnessRun) -> None:
+        from rich.markup import escape
+        from rich.panel import Panel
+
+        active = run.current_nodeid or "Waiting for test events…"
+        if len(active) > max(40, self.console.width - 16):
+            active = f"…{active[-(self.console.width - 17):]}"
+        passed, failed, errors, skipped = _summary(run)
+        progress = (
+            f"[bold]{run.completed_tests}/{run.unique_tests}[/bold] tests  "
+            f"[green]{passed} passed[/green]  [red]{failed + errors} failed[/red]  "
+            f"[yellow]{skipped} skipped[/yellow]  [dim]{_format_duration(run.duration)}[/dim]"
+        )
+        legend = "✓ pass  ✗ fail  ! error  ↷ skip\n? configured test missing  — planned  ◐ partial coverage"
+        self.live.update(
+            Panel(
+                self._table(run),
+                title="⚡ Rust ↔ Python parity lab",
+                subtitle=f"{progress}\n[dim]{escape(active)}[/dim]\n{legend}",
+                border_style="cyan",
+            )
+        )
+
+    def finish(self, run: HarnessRun, exit_code: int) -> None:
+        self.update(run)
+        if run.failures:
+            from rich.markup import escape
+            from rich.panel import Panel
+
+            for nodeid, detail in run.failures[:5]:
+                rerun = _rerun_command(nodeid)
+                self.console.print(
+                    Panel(
+                        f"{escape(detail)}\n\n[bold]Rerun just this test[/bold]\n"
+                        f"[cyan]{escape(rerun)}[/cyan]",
+                        title=f"✗ {escape(nodeid)}",
+                        border_style="red",
+                    )
+                )
+        durations: dict[str, float] = {}
+        for result in run.results.values():
+            for nodeid, duration in result.durations.items():
+                durations[nodeid] = max(duration, durations.get(nodeid, 0.0))
+        if durations:
+            slow = sorted(durations.items(), key=lambda item: item[1], reverse=True)[:3]
+            self.console.print(
+                "[bold]Slowest tests[/bold]  "
+                + "  •  ".join(
+                    f"{Path(nodeid).name} [dim]{_format_duration(duration)}[/dim]"
+                    for nodeid, duration in slow
+                )
+            )
+        from rich import box
+        from rich.table import Table
+
+        confidence_table = Table(
+            title="Port confidence by SDK section", box=box.ROUNDED, expand=True
+        )
+        confidence_table.add_column("SDK section")
+        confidence_table.add_column("Score", justify="right")
+        confidence_table.add_column("Confidence")
+        confidence_table.add_column("Strategy evidence", ratio=4)
+        confidence_styles = {"HIGH": "green", "MEDIUM": "yellow", "LOW": "red"}
+        for score in section_confidence(run, self.confidence_strategies):
+            confidence_table.add_row(
+                score.sdk_function,
+                f"{score.verified_strategies}/{score.required_strategies}  {score.percentage}%",
+                f"[{confidence_styles[score.level.value]}]{score.level.value}[/]",
+                "  ".join(score.details),
+            )
+        self.console.print(confidence_table)
+        self.console.print(
+            "[dim]Score = required strategies with passing evidence. "
+            "LOC coverage remains a separate report.[/dim]"
+        )
+        style = "green" if exit_code == 0 else "red"
+        self.console.print(
+            f"[{style}]Harness finished in {_format_duration(run.duration)} "
+            f"(exit {exit_code})[/{style}]"
+        )
+
+
+class PlainDashboard(AbstractContextManager["PlainDashboard"]):
+    def __init__(
+        self,
+        strategies: Sequence[Strategy],
+        confidence_strategies: Sequence[Strategy],
+    ) -> None:
+        self.strategies = strategies
+        self.confidence_strategies = confidence_strategies
+        self._seen: dict[str, tuple[RunStatus, int]] = {}
+
+    def __enter__(self) -> "PlainDashboard":
+        print("Rust <-> Python SDK parity harness", flush=True)
+        return self
+
+    def __exit__(self, *args: object) -> None:
+        return None
+
+    def update(self, run: HarnessRun) -> None:
+        for key, result in run.results.items():
+            state = (result.status, len(result.completed))
+            if self._seen.get(key) != state:
+                self._seen[key] = state
+                progress = (
+                    f" {len(result.completed)}/{result.total}" if result.total else ""
+                )
+                print(
+                    f"{STATUS_GLYPHS[result.status]} {key}: {result.status.value}{progress}",
+                    flush=True,
+                )
+
+    def finish(self, run: HarnessRun, exit_code: int) -> None:
+        self.update(run)
+        passed, failed, errors, skipped = _summary(run)
+        print(
+            f"Summary: {passed} passed, {failed} failed, {errors} errors, "
+            f"{skipped} skipped in {_format_duration(run.duration)}",
+            flush=True,
+        )
+        for nodeid, _ in run.failures[:5]:
+            print(f"Rerun: {_rerun_command(nodeid)}", flush=True)
+        print("Port confidence by SDK section", flush=True)
+        for score in section_confidence(run, self.confidence_strategies):
+            print(
+                f"  {score.sdk_function:12} "
+                f"{score.verified_strategies}/{score.required_strategies} "
+                f"{score.percentage:3}% {score.level.value:6}  "
+                f"{' | '.join(score.details)}",
+                flush=True,
+            )
+        print(
+            "  Score = required strategies with passing evidence; LOC is reported separately.",
+            flush=True,
+        )
+        print(f"Harness finished with exit code {exit_code}", flush=True)
+
+
+def make_dashboard(
+    strategies: Sequence[Strategy],
+    plain: bool = False,
+    confidence_strategies: Sequence[Strategy] | None = None,
+) -> RichDashboard | PlainDashboard:
+    confidence_strategies = confidence_strategies or strategies
+    interactive_terminal = (
+        sys.stdout.isatty()
+        and not os.environ.get("CI")
+        and os.environ.get("TERM") != "dumb"
+    )
+    if not plain and interactive_terminal:
+        try:
+            import rich  # noqa: F401
+
+            return RichDashboard(strategies, confidence_strategies)
+        except ImportError:
+            pass
+    return PlainDashboard(strategies, confidence_strategies)
diff --git a/tests/rust-python-harness/unit_tests_rust/README.md b/tests/rust-python-harness/unit_tests_rust/README.md
new file mode 100644
index 00000000000..12c7eb0089c
--- /dev/null
+++ b/tests/rust-python-harness/unit_tests_rust/README.md
@@ -0,0 +1,3 @@
+# Rust unit tests
+
+Holds focused Cargo tests for Rust-owned parsing, transforms, errors, and streaming behavior. These tests make failures fast to diagnose before the Python bridge or full SDK path is involved.
diff --git a/tests/rust-python-harness/unit_tests_rust/strategy.json b/tests/rust-python-harness/unit_tests_rust/strategy.json
new file mode 100644
index 00000000000..89e897c872d
--- /dev/null
+++ b/tests/rust-python-harness/unit_tests_rust/strategy.json
@@ -0,0 +1,12 @@
+{
+  "order": 20,
+  "id": "unit_tests_rust",
+  "label": "Rust unit tests",
+  "description": "Exercise Rust-owned behavior directly with focused unit tests.",
+  "functions": {
+    "ocr": {"coverage": "planned", "selectors": []},
+    "messages": {"coverage": "planned", "selectors": []},
+    "responses": {"coverage": "planned", "selectors": []},
+    "count_tokens": {"coverage": "planned", "selectors": []}
+  }
+}
diff --git a/tests/rust-python-harness/validate_sub_methods/README.md b/tests/rust-python-harness/validate_sub_methods/README.md
new file mode 100644
index 00000000000..24894366f23
--- /dev/null
+++ b/tests/rust-python-harness/validate_sub_methods/README.md
@@ -0,0 +1,3 @@
+# Validate sub-methods
+
+Checks each request, response, stream, and error-mapping sub-method independently across Python and Rust. It also validates that traced Python helpers have an explicit Rust implementation and parity test.
diff --git a/tests/rust-python-harness/validate_sub_methods/strategy.json b/tests/rust-python-harness/validate_sub_methods/strategy.json
new file mode 100644
index 00000000000..6e6381678e0
--- /dev/null
+++ b/tests/rust-python-harness/validate_sub_methods/strategy.json
@@ -0,0 +1,12 @@
+{
+  "order": 30,
+  "id": "validate_sub_methods",
+  "label": "Validate sub-methods",
+  "description": "Compare isolated transforms and verify Python-to-Rust helper coverage.",
+  "functions": {
+    "ocr": {"coverage": "planned", "selectors": []},
+    "messages": {"coverage": "planned", "selectors": []},
+    "responses": {"coverage": "planned", "selectors": []},
+    "count_tokens": {"coverage": "planned", "selectors": []}
+  }
+}
diff --git a/tests/sdk_function_trace/README.md b/tests/sdk_function_trace/README.md
new file mode 100644
index 00000000000..d3a3b654aea
--- /dev/null
+++ b/tests/sdk_function_trace/README.md
@@ -0,0 +1,30 @@
+# SDK function tracing
+
+The compare runner executes the same SDK calls through the Python engine and the Rust native bridge against a local HTTP provider fixture, then prints their pipeline trees side by side. Matching calls align on the same row in green; Python-only calls are blue, Rust-only calls yellow, and reordered calls red. Gaps preserve execution order and each column retains its own nesting. A comparison column labels every row even without color. Colors are enabled in terminals unless `NO_COLOR` is set. A difference summary follows (shared step order, python-only steps, rust-only steps). Each invocation must issue exactly one HTTP request. It requires the LiteLLM Python dependencies and the native extension built with tracing support
+
+From the repository root, using the project's Python environment:
+
+```bash
+uv run python -m tests.sdk_function_trace.compare
+uv run python -m tests.sdk_function_trace.compare --route ocr
+uv run python -m tests.sdk_function_trace.compare --route ocr --sync
+uv run python -m tests.sdk_function_trace.compare --route all --both --check
+```
+
+Calls default to async; use `--sync` for synchronous calls or `--both` for the complete matrix. Python sync Messages raises `not implemented for sync calls`; only that exact failure is marked `SKIP`, and the runner still executes Rust sync Messages and subsequent routes. Bedrock transcription has no independent Python provider implementation: its Python trace covers SDK dispatch into Rust
+
+Both engines are projected onto a shared per-route step table (`steps.py`): canonical names such as `transform_ocr_request` map Python functions (`MistralOCRConfig.transform_ocr_request`) and Rust spans (`transform_ocr_request`) to the same label. Only the first occurrence of each step is kept. Python indentation uses each event's actual frame ancestors and the nearest already displayed ancestor, so returned helpers and coroutine resumptions do not create false parents. Rust indentation uses instrumented span ancestry. Unmatched Rust span names pass through unchanged. `--full` prints every captured runtime event; validation still uses projected steps
+
+Every report checks required stage presence and dependency order. Provider lookup must precede request transformation, which must precede HTTP, followed by response transformation. The handler must precede HTTP; parameter mapping and supported-parameter checks must precede request transformation. Environment validation and URL construction, where mapped, must precede HTTP. Python transcription is checked only through native dispatch. `--check` also requires identical canonical step sequences for comparable routes and exits nonzero for missing, extra, or reordered steps, or an unexpected call failure, after finishing all selected cases
+
+Individual stage checks are separate from cross-language `step parity`. Passing stage checks cannot override a failing step comparison. Bedrock transcription and Python sync Messages report `UNAVAILABLE` for cross-language parity because they lack an independent Python execution to compare. Absolute nesting depth is not a cross-language gate: async Python Messages dispatches its handler onto another thread. See `route-comparison.md` for the audited matrix and remaining contract limitations
+
+The Python runner uses the existing `profile_python` / `sys.setprofile` collector, selecting executed code under the installed `litellm` source directory instead of maintaining a function-name allowlist. It prints source locations and qualified function names, including repeated calls. Coroutine resumptions are counted once per invocation. It profiles the current thread and threads created during the call, including the fresh async executor. Existing worker threads are not retroactively profiled; background Python calls may appear, and indentation follows selected Python stack ancestors within each thread
+
+The Rust runner calls the compiled PyO3 SDK entrypoints with `trace=True`. The existing `FunctionTrace` subscriber collects `#[tracing::instrument(target = "litellm::function_trace", level = "trace", skip_all)]` spans for the route entrypoint, preparation, provider lookup, HTTP handler, and selected provider transformations. The shared `http_request` helper instruments the existing Rust send operation without changing clients, timeouts, signing, or error mapping. Function names come from the actual functions. `WithSubscriber` attaches the collector to each future across async polls. Arguments and provider payloads are not recorded in trace events. Uninstrumented functions do not appear; this is scoped instrumentation, not an exhaustive native call graph
+
+Tracing is opt-in: native calls without `trace=True` keep their original response shape. Traced calls return `{"response": ..., "trace": [{"function": ..., "depth": ...}]}`. The runners print only trace events. Missing native support or empty traces fail instead of falling back to source searching. The old `--repo`, `--signatures`, and `--calls` options are removed
+
+`profile_python(functions)` still supports direct function references for focused parity checks. `assert_function_trace_parity` compares selected Python events with Rust events supplied by an executable scenario. Successful stage checks prove the declared pipeline ran in a valid dependency order for this fixture; they do not assert identical function contracts, request bodies, responses, streaming behavior, or live-provider correctness
+
+Build the extension with `maturin develop` in the project's virtual environment. Then run either command above to get the executed function order
diff --git a/tests/sdk_function_trace/__init__.py b/tests/sdk_function_trace/__init__.py
new file mode 100644
index 00000000000..da62b8041f6
--- /dev/null
+++ b/tests/sdk_function_trace/__init__.py
@@ -0,0 +1,13 @@
+from tests.sdk_function_trace.harness import (
+    TraceScenario,
+    TraceStep,
+    assert_function_trace_parity,
+)
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+
+__all__ = [
+    "FunctionTraceEvent",
+    "TraceScenario",
+    "TraceStep",
+    "assert_function_trace_parity",
+]
diff --git a/tests/sdk_function_trace/compare.py b/tests/sdk_function_trace/compare.py
new file mode 100644
index 00000000000..941c1b6e067
--- /dev/null
+++ b/tests/sdk_function_trace/compare.py
@@ -0,0 +1,45 @@
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+from typing import Final
+
+from tests.sdk_function_trace.fixtures import ROUTES
+from tests.sdk_function_trace.report import compare, render
+
+
+def _run(route: str, asynchronous: bool, *, full: bool, colorize: bool) -> bool:
+    comparison: Final = compare(route, asynchronous=asynchronous)
+    sys.stdout.write(render(comparison, full=full, colorize=colorize))
+    return comparison.passed
+
+
+def main() -> None:
+    parser: Final = argparse.ArgumentParser(description="Compare Python and Rust SDK pipeline steps per route")
+    parser.add_argument("--route", choices=("all", *ROUTES), default="all")
+    mode: Final = parser.add_mutually_exclusive_group()
+    mode.add_argument("--async", dest="asynchronous", action="store_true", default=True)
+    mode.add_argument("--sync", dest="asynchronous", action="store_false")
+    mode.add_argument("--both", action="store_true", help="run async and sync for every selected route")
+    parser.add_argument(
+        "--check", action="store_true", help="exit nonzero for missing, extra, or reordered comparable steps"
+    )
+    parser.add_argument(
+        "--full", action="store_true", help="print every captured runtime event instead of pipeline steps"
+    )
+    args: Final = parser.parse_args()
+    os.environ.setdefault("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    colorize: Final = sys.stdout.isatty() and "NO_COLOR" not in os.environ
+    results: Final = tuple(
+        _run(selected, selected_mode, full=args.full, colorize=colorize)
+        for selected in ROUTES
+        if args.route in ("all", selected)
+        for selected_mode in ((True, False) if args.both else (args.asynchronous,))
+    )
+    if args.check and not all(results):
+        raise SystemExit(1)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/sdk_function_trace/fixtures.py b/tests/sdk_function_trace/fixtures.py
new file mode 100644
index 00000000000..47bbe839627
--- /dev/null
+++ b/tests/sdk_function_trace/fixtures.py
@@ -0,0 +1,200 @@
+from __future__ import annotations
+
+import base64
+import io
+import json
+import wave
+from collections.abc import Callable
+from dataclasses import dataclass
+from typing import Final, Protocol, cast
+
+from tests.sdk_function_trace.mock_provider import MockProviderResponse
+from tests.sdk_function_trace.steps import Engine
+
+ANTHROPIC_MODEL: Final = "claude-sonnet-5"
+OCR_MODEL: Final = "mistral-ocr-latest"
+AUDIO_MODEL: Final = "mistral.voxtral-mini-3b-2507"
+
+
+class SdkCall(Protocol):
+    def __call__(self, **kwargs: object) -> object: ...
+
+
+@dataclass(frozen=True, slots=True)
+class Fixture:
+    kwargs: dict[str, object]
+    provider_response: MockProviderResponse
+
+
+@dataclass(frozen=True, slots=True)
+class RouteSpec:
+    label: str
+    python_entrypoints: tuple[str, str]
+    rust_entrypoints: tuple[str, str]
+    fixture: Callable[[Engine], Fixture]
+
+
+@dataclass(frozen=True, slots=True)
+class Invocation:
+    function: SdkCall
+    kwargs: dict[str, object]
+    provider_response: MockProviderResponse
+    label: str
+
+
+def audio_bytes() -> bytes:
+    with io.BytesIO() as buffer:
+        with wave.open(buffer, "wb") as audio:
+            audio.setnchannels(1)
+            audio.setsampwidth(2)
+            audio.setframerate(16000)
+            audio.writeframes(b"\x00\x00" * 1600)
+        return buffer.getvalue()
+
+
+def _anthropic_message_response() -> MockProviderResponse:
+    body: Final = {
+        "id": "msg_trace",
+        "type": "message",
+        "role": "assistant",
+        "model": ANTHROPIC_MODEL,
+        "content": [{"type": "text", "text": "hello"}],
+        "stop_reason": "end_turn",
+        "stop_sequence": None,
+        "usage": {"input_tokens": 2, "output_tokens": 3},
+    }
+    return MockProviderResponse(200, (("content-type", "application/json"),), json.dumps(body).encode())
+
+
+def _conversation() -> dict[str, object]:
+    return {"messages": [{"role": "user", "content": "hello"}], "max_tokens": 16}
+
+
+def _ocr_fixture(engine: Engine) -> Fixture:
+    return Fixture(
+        kwargs={
+            "model": f"mistral/{OCR_MODEL}",
+            "document": {"type": "document_url", "document_url": "https://example.com/document.pdf"},
+            **({"optional_params": {"pages": [0]}} if engine == "rust" else {"pages": [0]}),
+        },
+        provider_response=MockProviderResponse(
+            200,
+            (("content-type", "application/json"),),
+            json.dumps(
+                {
+                    "pages": [{"index": 0, "markdown": "hello"}],
+                    "model": OCR_MODEL,
+                    "usage_info": {"pages_processed": 1},
+                }
+            ).encode(),
+        ),
+    )
+
+
+def _chat_completions_fixture(engine: Engine) -> Fixture:
+    conversation: Final = _conversation()
+    payload: Final = (
+        {"messages": conversation["messages"], "optional_params": {"max_tokens": 16}}
+        if engine == "rust"
+        else conversation
+    )
+    return Fixture(
+        kwargs={"model": f"anthropic/{ANTHROPIC_MODEL}", **payload},
+        provider_response=_anthropic_message_response(),
+    )
+
+
+def _messages_fixture(engine: Engine) -> Fixture:
+    conversation: Final = _conversation()
+    payload: Final = {"body": {**conversation, "model": ANTHROPIC_MODEL}} if engine == "rust" else conversation
+    return Fixture(
+        kwargs={"model": f"anthropic/{ANTHROPIC_MODEL}", **payload},
+        provider_response=_anthropic_message_response(),
+    )
+
+
+def _transcription_fixture(engine: Engine) -> Fixture:
+    credentials: Final = {
+        "aws_access_key_id": "test-access",
+        "aws_secret_access_key": "test-secret",
+        "aws_region_name": "us-east-1",
+    }
+    payload: Final = (
+        {
+            "audio": {"data": base64.b64encode(audio_bytes()).decode(), "format": "wav"},
+            "optional_params": credentials,
+        }
+        if engine == "rust"
+        else {"file": ("sample.wav", audio_bytes(), "audio/wav"), **credentials}
+    )
+    return Fixture(
+        kwargs={"model": f"bedrock/{AUDIO_MODEL}", **payload},
+        provider_response=MockProviderResponse(
+            200,
+            (("content-type", "application/json"),),
+            json.dumps(
+                {
+                    "output": {"message": {"role": "assistant", "content": [{"text": "hello"}]}},
+                    "stopReason": "end_turn",
+                    "usage": {"inputTokens": 2, "outputTokens": 3, "totalTokens": 5},
+                }
+            ).encode(),
+        ),
+    )
+
+
+ROUTE_SPECS: Final[dict[str, RouteSpec]] = {
+    "chat_completions": RouteSpec(
+        label="anthropic",
+        python_entrypoints=("completion", "acompletion"),
+        rust_entrypoints=("chat_completions", "achat_completions"),
+        fixture=_chat_completions_fixture,
+    ),
+    "audio_transcription": RouteSpec(
+        label="bedrock (Rust-only provider; Python trace covers SDK dispatch)",
+        python_entrypoints=("transcription", "atranscription"),
+        rust_entrypoints=("transcription", "atranscription"),
+        fixture=_transcription_fixture,
+    ),
+    "messages": RouteSpec(
+        label="anthropic",
+        python_entrypoints=("create", "acreate"),
+        rust_entrypoints=("messages", "amessages"),
+        fixture=_messages_fixture,
+    ),
+    "ocr": RouteSpec(
+        label="mistral",
+        python_entrypoints=("ocr", "aocr"),
+        rust_entrypoints=("ocr", "aocr"),
+        fixture=_ocr_fixture,
+    ),
+}
+
+ROUTES: Final = tuple(ROUTE_SPECS)
+
+
+def sdk_invocation(route: str, *, engine: Engine, asynchronous: bool) -> Invocation:
+    import litellm
+    from litellm.anthropic_interface import messages as sdk_messages
+    from litellm.rust_bridge import get_native_bridge
+
+    rust: Final = engine == "rust"
+    bridge: Final = get_native_bridge() if rust else None
+    if rust and bridge is None:
+        raise RuntimeError("Build the native extension first: maturin develop")
+    spec: Final = ROUTE_SPECS.get(route)
+    if spec is None:
+        raise ValueError(f"Unknown route: {route}")
+    fixture: Final = spec.fixture(engine)
+    owner: Final = bridge if rust else (sdk_messages if route == "messages" else litellm)
+    entrypoint: Final = (spec.rust_entrypoints if rust else spec.python_entrypoints)[int(asynchronous)]
+    return Invocation(
+        function=cast(SdkCall, getattr(owner, entrypoint)),
+        kwargs={
+            **fixture.kwargs,
+            "api_key": "test-key",
+            **({"trace": True, "timeout_seconds": 5} if rust else {"timeout": 5}),
+        },
+        provider_response=fixture.provider_response,
+        label=spec.label,
+    )
diff --git a/tests/sdk_function_trace/harness.py b/tests/sdk_function_trace/harness.py
new file mode 100644
index 00000000000..8f707402449
--- /dev/null
+++ b/tests/sdk_function_trace/harness.py
@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+from collections.abc import Callable, Sequence
+from dataclasses import dataclass
+from types import FunctionType
+from typing import Final, cast
+
+from tests.sdk_function_trace.profiler import FunctionTraceEvent, profile_python
+
+
+@dataclass(frozen=True, slots=True)
+class TraceStep:
+    function: FunctionType
+    depth: int
+
+
+@dataclass(frozen=True, slots=True)
+class TraceScenario:
+    steps: tuple[TraceStep, ...]
+    invoke_python: Callable[[], object]
+    invoke_rust: Callable[[], Sequence[FunctionTraceEvent]]
+
+
+def assert_function_trace_parity(scenario: TraceScenario) -> None:
+    expected: Final = tuple(
+        FunctionTraceEvent(function=step.function.__name__, depth=step.depth) for step in scenario.steps
+    )
+    functions: Final = cast(tuple[FunctionType, ...], tuple(step.function for step in scenario.steps))
+    with profile_python(functions) as profiler:
+        scenario.invoke_python()
+    python_trace: Final = tuple(profiler.events)
+    rust_trace: Final = tuple(scenario.invoke_rust())
+
+    if python_trace != expected:
+        raise AssertionError(f"Python function trace differs: {python_trace!r} != {expected!r}")
+    if rust_trace != expected:
+        raise AssertionError(f"Rust function trace differs: {rust_trace!r} != {expected!r}")
+    if python_trace != rust_trace:
+        raise AssertionError(f"Python and Rust function traces differ: {python_trace!r} != {rust_trace!r}")
diff --git a/tests/sdk_function_trace/mock_provider.py b/tests/sdk_function_trace/mock_provider.py
new file mode 100644
index 00000000000..37eca665586
--- /dev/null
+++ b/tests/sdk_function_trace/mock_provider.py
@@ -0,0 +1,67 @@
+from __future__ import annotations
+
+from collections.abc import Generator
+from contextlib import contextmanager
+from dataclasses import dataclass
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from threading import Lock, Thread
+from typing import Final, cast
+
+
+@dataclass(frozen=True, slots=True)
+class MockProviderResponse:
+    status_code: int
+    headers: tuple[tuple[str, str], ...]
+    body: bytes
+
+
+class _MockProviderServer(ThreadingHTTPServer):
+    def __init__(self, response: MockProviderResponse) -> None:
+        super().__init__(("127.0.0.1", 0), _MockProviderHandler)
+        self.response: Final = response
+        self._request_count = 0
+        self._request_count_lock: Final = Lock()
+
+    def record_request(self) -> None:
+        with self._request_count_lock:
+            self._request_count += 1
+
+    @property
+    def request_count(self) -> int:
+        with self._request_count_lock:
+            return self._request_count
+
+
+class _MockProviderHandler(BaseHTTPRequestHandler):
+    protocol_version = "HTTP/1.1"
+
+    def do_POST(self) -> None:
+        content_length: Final = int(self.headers.get("content-length", "0"))
+        self.rfile.read(content_length)
+        server: Final = cast(_MockProviderServer, self.server)
+        server.record_request()
+        self.send_response(server.response.status_code)
+        for name, value in server.response.headers:
+            self.send_header(name, value)
+        self.send_header("content-length", str(len(server.response.body)))
+        self.end_headers()
+        self.wfile.write(server.response.body)
+
+    def log_message(self, format: str, *args: object) -> None:  # noqa: A002  # matches BaseHTTPRequestHandler
+        pass
+
+
+@contextmanager
+def mock_provider(response: MockProviderResponse) -> Generator[str]:
+    server: Final = _MockProviderServer(response)
+    thread: Final = Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    host, port = cast(tuple[str, int], server.server_address)
+    try:
+        yield f"http://{host}:{port}"
+    finally:
+        server.shutdown()
+        server.server_close()
+        thread.join()
+    if server.request_count != 1:
+        raise AssertionError(f"expected one provider request, received {server.request_count}")
diff --git a/tests/sdk_function_trace/ocr-comparison.md b/tests/sdk_function_trace/ocr-comparison.md
new file mode 100644
index 00000000000..d252480e218
--- /dev/null
+++ b/tests/sdk_function_trace/ocr-comparison.md
@@ -0,0 +1,59 @@
+# OCR Python and Rust comparison
+
+Audited implementation revision: `edcba483b2`. The implementations do not match in function contracts, call structure, or all tested response behavior. This audit changes the source listing coverage, not OCR runtime behavior
+
+Run both source listings from the repository root:
+
+```bash
+python3 tests/sdk_function_trace/list_python_steps.py --route ocr --signatures --calls
+uv run tests/sdk_function_trace/list_rust_steps.py --route ocr --signatures --calls
+```
+
+Both cover Mistral, Azure AI Mistral, Azure Document Intelligence, Vertex Mistral, and Vertex DeepSeek. Listings show declarations and source call sites, not executed traces
+
+## Function contracts
+
+Comparing Python `BaseOCRConfig` with Rust `OcrProviderConfig`, omitting `self` and language-specific ownership details:
+
+| Python | Rust | Difference |
+| --- | --- | --- |
+| `get_supported_ocr_params(model)` | `supported_ocr_params()` | Name and model argument |
+| `get_api_key_env_var()` | No corresponding method | Missing contract |
+| `map_ocr_params(non_default_params, optional_params, model)` | `map_ocr_params(non_default_params)` | Missing accumulator and model |
+| `validate_environment(headers, model, api_key, api_base, litellm_params, **kwargs)` | Separate auth/key/header helpers | Different contract |
+| `get_complete_url(api_base, model, optional_params, litellm_params, **kwargs)` | `complete_url(api_base, model, optional_params, env_lookup)` | Name and context |
+| `transform_ocr_request(model, document, optional_params, headers, **kwargs)` | `transform_ocr_request(model, document, optional_params)` | Missing headers and extra context |
+| `async_transform_ocr_request(...)` | No corresponding method | Missing async override |
+| `transform_ocr_response(model, raw_response, logging_obj, **kwargs)` | `transform_ocr_response(model, response_json)` | Missing HTTP metadata, logging and extra context |
+| `async_transform_ocr_response(...)` | No corresponding method | Missing async override |
+| `get_error_class(error_message, status_code, headers)` | Central Rust error mapping | Different contract |
+
+Python's default mapper returns the supplied `optional_params`; Rust's filters `non_default_params`. Provider overrides must also be compared
+
+Python maps parameters during SDK preparation, before HTTP-handler environment validation and URL construction. Rust resolves auth and URL before mapping parameters in `prepare_provider_request`. Python has async provider transforms; both native entrypoints execute the same Rust async route using synchronous transform hooks, with polling and document downloading in gateway helpers
+
+The native bindings also accept `optional_params` and `timeout_seconds`, while the Python SDK accepts `**kwargs` and `timeout`. Public SDK calls with Rust enabled still execute Python preparation before entering Rust, so matching SDK responses would not prove matching standalone Rust steps
+
+## Runtime results
+
+Built the native extension from the audited source using `cargo build -p litellm-python-bridge --features extension-module --offline`. Supplied that build's functions through `use_litellm_rust` dependency injection. Ran public `litellm.ocr` and `litellm.aocr` with Rust disabled and enabled against identical local HTTP response fixtures, requiring one request per invocation
+
+Successful `model_dump()` results and failure exception classes were compared. These checks cover Mistral response outcomes only, not request equality, error messages, live providers, or every execution branch
+
+| Mistral response fixture | Sync | Async | Observation |
+| --- | --- | --- | --- |
+| Valid page/model/usage | Match | Match | Same normalized response |
+| Model omitted | Match | Match | Both use the requested model |
+| `model: null` | Different | Different | Python rejects; Rust uses the requested model |
+| `pages: null` | Different | Different | Python rejects; Rust returns an empty array |
+| Invalid page element | Match | Match | Both reject during response validation |
+
+Six of ten fixture/mode comparisons match, four differ. Rust's Mistral response transform conflates missing values with explicit nulls through `as_array`/`as_str` fallbacks. Python preserves explicit nulls into response validation, which rejects them
+
+## Other provider gaps found in source
+
+Azure Document Intelligence's Python configuration supports `pages`, `features`, and `req_format`; Rust lists only `pages`. Python normalizes parameters before URL construction; Rust normalizes pages during URL construction
+
+Python preserves Azure `content`, `tables`, and `keyValuePairs`, and supports retaining the native operation payload. Rust's `OcrResponseData` has no corresponding fields, and its Azure transform does not preserve those values
+
+Azure and Vertex async document transforms and Azure polling also use different helper contracts. Their runtime equivalence was not tested in this audit
diff --git a/tests/sdk_function_trace/profiler.py b/tests/sdk_function_trace/profiler.py
new file mode 100644
index 00000000000..c71c74ab0d3
--- /dev/null
+++ b/tests/sdk_function_trace/profiler.py
@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import sys
+import threading
+from collections.abc import Generator, Sequence
+from contextlib import contextmanager
+from dataclasses import dataclass
+from pathlib import Path
+from types import CodeType, FrameType, FunctionType
+from typing import Final
+
+
+@dataclass(frozen=True, slots=True)
+class FunctionTraceEvent:
+    function: str
+    depth: int
+    ancestors: tuple[str, ...] | None = None
+
+
+class PythonProfiler:
+    def __init__(self, functions: Sequence[FunctionType], source_root: Path | None = None) -> None:
+        self._source_root: Final = str(source_root.resolve()) + "/" if source_root is not None else None
+        self._names_by_code: Final = {function.__code__: function.__name__ for function in functions}
+        self._seen_frames: Final[set[FrameType]] = set()
+        self.events: Final[list[FunctionTraceEvent]] = []
+
+    def __call__(self, frame: FrameType, event: str, _arg: object) -> None:
+        if event != "call" or frame in self._seen_frames:
+            return
+        function_name: Final = self.function_name(frame.f_code)
+        if function_name is None:
+            return
+        ancestors: Final = tuple(
+            name for ancestor in _frame_ancestors(frame) if (name := self.function_name(ancestor.f_code)) is not None
+        )
+        self._seen_frames.add(frame)
+        self.events.append(
+            FunctionTraceEvent(
+                function=function_name,
+                depth=len(ancestors),
+                ancestors=ancestors if self._source_root is not None else None,
+            )
+        )
+
+    def function_name(self, code: CodeType) -> str | None:
+        if self._source_root is None:
+            return self._names_by_code.get(code)
+        if not code.co_filename.startswith(self._source_root):
+            return None
+        relative: Final = code.co_filename.removeprefix(self._source_root)
+        return f"{relative}:{code.co_firstlineno} {getattr(code, 'co_qualname', code.co_name)}"
+
+
+def _frame_ancestors(frame: FrameType) -> Generator[FrameType]:
+    ancestor: Final = frame.f_back
+    if ancestor is not None:
+        yield ancestor
+        yield from _frame_ancestors(ancestor)
+
+
+@contextmanager
+def profile_python(
+    functions: Sequence[FunctionType] = (), *, source_root: Path | None = None, threads: bool = False
+) -> Generator[PythonProfiler]:
+    profiler: Final = PythonProfiler(functions, source_root)
+    previous_thread: Final = threading.getprofile()
+    if threads:
+        threading.setprofile(profiler)
+    previous: Final = sys.getprofile()
+    sys.setprofile(profiler)
+    try:
+        yield profiler
+    finally:
+        sys.setprofile(previous)
+        if threads:
+            threading.setprofile(previous_thread)
diff --git a/tests/sdk_function_trace/report.py b/tests/sdk_function_trace/report.py
new file mode 100644
index 00000000000..9b654e571f8
--- /dev/null
+++ b/tests/sdk_function_trace/report.py
@@ -0,0 +1,175 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Final
+
+from tests.sdk_function_trace.fixtures import ROUTE_SPECS
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+from tests.sdk_function_trace.runtime import (
+    TraceDiff,
+    TraceFailed,
+    TraceOk,
+    TraceRun,
+    TraceSkipped,
+    attempt_trace,
+    trace_diff,
+)
+from tests.sdk_function_trace.steps import Engine, pipeline_issues, pipeline_steps
+from tests.sdk_function_trace.table import format_trace_table
+
+_PYTHON_ONLY_COLOR: Final = "\033[34m"
+_RUST_ONLY_COLOR: Final = "\033[33m"
+_RESET: Final = "\033[0m"
+
+_ENGINE_COLOR: Final[dict[Engine, str]] = {"python": _PYTHON_ONLY_COLOR, "rust": _RUST_ONLY_COLOR}
+
+
+@dataclass(frozen=True, slots=True)
+class EngineReport:
+    engine: Engine
+    run: TraceRun
+    events: tuple[FunctionTraceEvent, ...]
+    steps: tuple[FunctionTraceEvent, ...]
+    issues: tuple[str, ...]
+
+
+@dataclass(frozen=True, slots=True)
+class Comparison:
+    route: str
+    label: str
+    asynchronous: bool
+    engines: tuple[EngineReport, ...]
+    diff: TraceDiff
+
+    @property
+    def comparable(self) -> bool:
+        return self.route != "audio_transcription" and all(isinstance(report.run, TraceOk) for report in self.engines)
+
+    @property
+    def passed(self) -> bool:
+        return (
+            (not self.comparable or self.diff.matches)
+            and not any(report.issues for report in self.engines)
+            and all(not isinstance(report.run, TraceFailed) for report in self.engines)
+        )
+
+
+def _events(run: TraceRun) -> tuple[FunctionTraceEvent, ...]:
+    match run:
+        case TraceOk(events=events):
+            return events
+        case TraceSkipped() | TraceFailed():
+            return ()
+
+
+def _engine_report(route: str, engine: Engine, run: TraceRun) -> EngineReport:
+    events: Final = _events(run)
+    steps: Final = pipeline_steps(route, engine, events)
+    issues: Final = pipeline_issues(route, engine, steps) if isinstance(run, TraceOk) else ()
+    return EngineReport(engine=engine, run=run, events=events, steps=steps, issues=issues)
+
+
+def compare(route: str, *, asynchronous: bool) -> Comparison:
+    runs: Final = {
+        engine: attempt_trace(route, engine=engine, asynchronous=asynchronous) for engine in ("python", "rust")
+    }
+    engines: Final = tuple(_engine_report(route, engine, run) for engine, run in runs.items())
+    return Comparison(
+        route=route,
+        label=ROUTE_SPECS[route].label,
+        asynchronous=asynchronous,
+        engines=engines,
+        diff=trace_diff(engines[0].steps, engines[1].steps),
+    )
+
+
+def _tree_line(event: FunctionTraceEvent, only: frozenset[str], marker: str, color: str, *, colorize: bool) -> str:
+    line: Final = f"{'  ' * event.depth}{event.function}" + (f"  {marker}" if event.function in only else "")
+    return f"{color}{line}{_RESET}\n" if colorize and event.function in only else f"{line}\n"
+
+
+def _tree_lines(
+    events: tuple[FunctionTraceEvent, ...],
+    only: frozenset[str],
+    marker: str,
+    color: str,
+    *,
+    colorize: bool,
+) -> tuple[str, ...]:
+    return tuple(_tree_line(event, only, marker, color, colorize=colorize) for event in events)
+
+
+def _engine_lines(
+    report: EngineReport, diff: TraceDiff, *, comparable: bool, full: bool, colorize: bool
+) -> tuple[str, ...]:
+    match report.run:
+        case TraceSkipped(reason=reason):
+            return (f"{report.engine}: SKIP ({reason})\n\n",)
+        case TraceFailed(reason=reason):
+            return (f"{report.engine}: FAIL ({reason})\n\n",)
+        case TraceOk():
+            shown: Final = report.events if full else report.steps
+            only: Final = (
+                () if full or not comparable else (diff.python_only if report.engine == "python" else diff.rust_only)
+            )
+            return (
+                f"{report.engine} ({len(shown)} steps)\n\n",
+                *_tree_lines(
+                    shown,
+                    frozenset(only),
+                    f"<- {report.engine} only",
+                    _ENGINE_COLOR[report.engine],
+                    colorize=colorize,
+                ),
+                "\n",
+            )
+
+
+def _parity_lines(comparison: Comparison) -> tuple[str, ...]:
+    if not comparison.comparable:
+        if comparison.route == "audio_transcription":
+            return ("step parity: UNAVAILABLE (Bedrock transcription has no independent Python implementation)\n",)
+        return ("step parity: UNAVAILABLE (both engines must complete)\n",)
+    diff: Final = comparison.diff
+    order: Final = "the same" if diff.shared_order_matches else "a different"
+    return (
+        "diff\n\n",
+        f"shared steps appear in {order} order\n",
+        f"python-only: {', '.join(diff.python_only) or 'none'}\n",
+        f"rust-only: {', '.join(diff.rust_only) or 'none'}\n\n",
+        f"step parity: {'PASS' if diff.matches else 'FAIL'}\n",
+    )
+
+
+def _stage_lines(comparison: Comparison) -> tuple[str, ...]:
+    return tuple(
+        f"{report.engine} "
+        f"{'SDK dispatch only' if comparison.route == 'audio_transcription' and report.engine == 'python' else 'pipeline'}: "
+        f"{'FAIL: ' + '; '.join(report.issues) if report.issues else 'PASS'}\n"
+        for report in comparison.engines
+        if isinstance(report.run, TraceOk)
+    )
+
+
+def render(comparison: Comparison, *, full: bool, colorize: bool) -> str:
+    mode: Final = "async" if comparison.asynchronous else "sync"
+    traces: Final = (
+        (format_trace_table(comparison.engines[0].steps, comparison.engines[1].steps, colorize=colorize) + "\n\n",)
+        if not full and all(isinstance(report.run, TraceOk) for report in comparison.engines)
+        else tuple(
+            line
+            for report in comparison.engines
+            for line in _engine_lines(
+                report, comparison.diff, comparable=comparison.comparable, full=full, colorize=colorize
+            )
+        )
+    )
+    return "".join(
+        (
+            f"route: {comparison.route}    provider: {comparison.label}    mode: {mode}\n\n",
+            *traces,
+            *_parity_lines(comparison),
+            *_stage_lines(comparison),
+            "Each successful invocation issued exactly one local provider request\n\n",
+        )
+    )
diff --git a/tests/sdk_function_trace/route-comparison.md b/tests/sdk_function_trace/route-comparison.md
new file mode 100644
index 00000000000..009d3544d05
--- /dev/null
+++ b/tests/sdk_function_trace/route-comparison.md
@@ -0,0 +1,26 @@
+# SDK route trace audit
+
+Run the four native HTTP route families in both modes from the repository root:
+
+```bash
+uv run python -m tests.sdk_function_trace.compare --route all --both --check
+```
+
+The local fixture matrix on 2026-09-02 completed 15 successful engine invocations and one expected skip. Every successful invocation issued exactly one local HTTP request. All five comparable route/mode pairs have identical canonical steps in the same order, with no Python-only or Rust-only steps
+
+| Route | Python async | Python sync | Rust async | Rust sync |
+| --- | --- | --- | --- | --- |
+| Chat completions, Anthropic | Pass | Pass | Pass | Pass |
+| Messages, Anthropic | Pass | Unsupported, skipped | Pass | Pass |
+| OCR, Mistral | Pass | Pass | Pass | Pass |
+| Audio transcription, Bedrock | Dispatch only | Dispatch only | Pass | Pass |
+
+The same canonical step sequence ran in sync and async for each engine with both modes available. Bedrock transcription's Python SDK delegates to Rust, so its two successful calls do not establish independent provider parity. Realtime and Responses WebSockets are outside this HTTP fixture runner
+
+Chat and OCR also have identical projected nesting in both modes. Async Messages has the same helper nesting beneath its handler, but Python starts that handler on a worker thread, so it appears as a second root. The comparison preserves this physical thread boundary and checks step order independently of absolute depth
+
+Rust now resolves chat providers and supported parameters before entering its handler. Chat and Messages validate the environment and transform requests inside their handlers. Messages builds the final URL after transformation. OCR resolves its config and maps supported parameters during preparation, then validates credentials, builds the URL, and transforms the request inside its handler. Its during-call guardrails still run before HTTP, within the provider-call lifecycle phase
+
+The environment hooks execute credential and header validation. Chat's supported-parameter hooks return OpenAI names paired with provider names and feed the existing request acceptance checks. The direct Rust API still accepts provider-mapped parameters, and its supported subset is smaller than Python's. Matching the pipeline does not establish identical parameter contracts
+
+`--check` now fails if either comparable engine has missing, extra, or reordered canonical steps, even if its individual stage checks pass. Bedrock transcription and sync Messages report `UNAVAILABLE` for cross-language parity; native execution is still checked. Passing establishes step coverage and order for one non-streaming fixture per route, not complete request, response, error, or provider parity. The previously recorded OCR response gaps remain in `ocr-comparison.md`
diff --git a/tests/sdk_function_trace/runtime.py b/tests/sdk_function_trace/runtime.py
new file mode 100644
index 00000000000..d5bf15694bc
--- /dev/null
+++ b/tests/sdk_function_trace/runtime.py
@@ -0,0 +1,128 @@
+from __future__ import annotations
+
+import asyncio
+import os
+from collections.abc import Awaitable, Generator
+from contextlib import contextmanager
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Final, cast
+from unittest.mock import patch
+
+from pydantic import BaseModel, ConfigDict
+
+from tests.sdk_function_trace.fixtures import Invocation, sdk_invocation
+from tests.sdk_function_trace.mock_provider import mock_provider
+from tests.sdk_function_trace.profiler import FunctionTraceEvent, profile_python
+from tests.sdk_function_trace.steps import Engine
+
+
+class TraceEventPayload(BaseModel):
+    model_config = ConfigDict(strict=True, extra="forbid")
+    function: str
+    depth: int
+
+
+class TraceResponsePayload(BaseModel):
+    model_config = ConfigDict(strict=True, extra="forbid")
+    response: object
+    trace: tuple[TraceEventPayload, ...] | list[TraceEventPayload]
+
+
+@contextmanager
+def _python_engine() -> Generator[None]:
+    from litellm.rust_bridge import ocr as ocr_bridge
+
+    previous_ocr: Final = ocr_bridge.rust_ocr_enabled()
+    with patch.dict(os.environ, {"LITELLM_RUST": "false"}):
+        ocr_bridge.use_litellm_rust(False)
+        try:
+            yield
+        finally:
+            ocr_bridge.use_litellm_rust(previous_ocr)
+
+
+def _invoke(case: Invocation, api_base: str, *, asynchronous: bool) -> object:
+    async def invoke_async() -> object:
+        return await cast("Awaitable[object]", case.function(**case.kwargs, api_base=api_base))
+
+    if asynchronous:
+        return asyncio.run(invoke_async())
+    return case.function(**case.kwargs, api_base=api_base)
+
+
+def collect(case: Invocation, api_base: str, *, engine: Engine, asynchronous: bool) -> tuple[FunctionTraceEvent, ...]:
+    import litellm
+
+    if engine == "rust":
+        payload: Final = TraceResponsePayload.model_validate(_invoke(case, api_base, asynchronous=asynchronous))
+        return tuple(FunctionTraceEvent(event.function, event.depth) for event in payload.trace)
+    with profile_python(source_root=Path(litellm.__file__).parent, threads=True) as profiler:
+        _invoke(case, api_base, asynchronous=asynchronous)
+    return tuple(profiler.events)
+
+
+def run_trace(route: str, *, engine: Engine, asynchronous: bool = False) -> tuple[FunctionTraceEvent, ...]:
+    case: Final = sdk_invocation(route, engine=engine, asynchronous=asynchronous)
+    with _python_engine(), mock_provider(case.provider_response) as api_base:
+        events: Final = collect(case, api_base, engine=engine, asynchronous=asynchronous)
+    if not events:
+        raise RuntimeError(f"No runtime events for {route}; rebuild the native extension with tracing support")
+    return events
+
+
+@dataclass(frozen=True, slots=True)
+class TraceOk:
+    events: tuple[FunctionTraceEvent, ...]
+
+
+@dataclass(frozen=True, slots=True)
+class TraceSkipped:
+    reason: str
+
+
+@dataclass(frozen=True, slots=True)
+class TraceFailed:
+    reason: str
+
+
+TraceRun = TraceOk | TraceSkipped | TraceFailed
+
+
+def attempt_trace(route: str, *, engine: Engine, asynchronous: bool) -> TraceRun:
+    try:
+        return TraceOk(run_trace(route, engine=engine, asynchronous=asynchronous))
+    except Exception as error:
+        reason: Final = f"{type(error).__name__}: {error}"
+        if (
+            route == "messages"
+            and engine == "python"
+            and not asynchronous
+            and isinstance(error, ValueError)
+            and str(error) == "anthropic_messages_handler is not implemented for sync calls"
+        ):
+            return TraceSkipped(reason)
+        return TraceFailed(reason)
+
+
+@dataclass(frozen=True, slots=True)
+class TraceDiff:
+    python_only: tuple[str, ...]
+    rust_only: tuple[str, ...]
+    shared_order_matches: bool
+
+    @property
+    def matches(self) -> bool:
+        return not self.python_only and not self.rust_only and self.shared_order_matches
+
+
+def trace_diff(python: tuple[FunctionTraceEvent, ...], rust: tuple[FunctionTraceEvent, ...]) -> TraceDiff:
+    python_names: Final = {event.function for event in python}
+    rust_names: Final = {event.function for event in rust}
+    shared_python: Final = tuple(event.function for event in python if event.function in rust_names)
+    shared_rust: Final = tuple(event.function for event in rust if event.function in python_names)
+    return TraceDiff(
+        python_only=tuple(event.function for event in python if event.function not in rust_names),
+        rust_only=tuple(event.function for event in rust if event.function not in python_names),
+        shared_order_matches=bool(shared_python) and shared_python == shared_rust,
+    )
diff --git a/tests/sdk_function_trace/steps.py b/tests/sdk_function_trace/steps.py
new file mode 100644
index 00000000000..bb50d4ebe57
--- /dev/null
+++ b/tests/sdk_function_trace/steps.py
@@ -0,0 +1,181 @@
+from __future__ import annotations
+
+import re
+from collections.abc import Sequence
+from dataclasses import dataclass
+from functools import reduce
+from typing import Final, Literal
+
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+
+Engine = Literal["python", "rust"]
+
+
+@dataclass(frozen=True, slots=True)
+class Step:
+    name: str
+    python: re.Pattern[str] | None
+    rust: str | None
+
+
+def _step(name: str, python: str | None = None, rust: str | None = None) -> Step:
+    return Step(name, re.compile(python) if python is not None else None, rust)
+
+
+_POST: Final = r"AsyncHTTPHandler\.post$|HTTPHandler\.post$"
+
+STEPS: Final[dict[str, tuple[Step, ...]]] = {
+    "ocr": (
+        _step("ocr", r"ocr/main\.py:\d+ a?ocr$", "ocr"),
+        _step("prepare_ocr_call", r"ocr/main\.py:\d+ _prepare_ocr_request$", "prepare_ocr_call"),
+        _step("get_provider_ocr_config", r"ProviderConfigManager\.get_provider_ocr_config$", "ocr_provider_config"),
+        _step("supported_ocr_params", r"get_supported_ocr_params$", "supported_ocr_params"),
+        _step("map_ocr_params", r"(?<!async_)map_ocr_params$", "map_ocr_params"),
+        _step("validate_environment", r"(?<!_)validate_environment$", "validate_environment"),
+        _step("complete_url", r"get_complete_url$", "complete_url"),
+        _step("transform_ocr_request", r"(?<!async_)transform_ocr_request$", "transform_ocr_request"),
+        _step("execute_ocr_provider_call", r"BaseLLMHTTPHandler\.(?:async_)?ocr$", "execute_ocr_provider_call"),
+        _step("http_request", _POST, "http_request"),
+        _step("transform_ocr_response", r"(?<!async_)transform_ocr_response$", "transform_ocr_response"),
+    ),
+    "chat_completions": (
+        _step("chat_completions", r"main\.py:\d+ a?completion$", "chat_completions"),
+        _step(
+            "get_provider_chat_config",
+            r"ProviderConfigManager\.get_provider_chat_config$",
+            "chat_completions_provider_config",
+        ),
+        _step("supported_openai_params", r"get_supported_openai_params$", "supported_openai_params"),
+        _step("validate_environment", r"(?<!_)validate_environment$", "validate_environment"),
+        _step("transform_request", r"(?<!async_)transform_request$", "transform_request"),
+        _step(
+            "execute_chat_completions_provider_call",
+            r"a?completion_function$|ChatCompletion\.completion$",
+            "execute_chat_completions_provider_call",
+        ),
+        _step("http_request", _POST, "http_request"),
+        _step("transform_response", r"(?<!async_)transform_response$", "transform_response"),
+    ),
+    "messages": (
+        _step("messages", r"anthropic_interface/messages/__init__\.py:\d+ a?create$", "messages"),
+        _step(
+            "get_provider_messages_config",
+            r"ProviderConfigManager\.get_provider_anthropic_messages_config$",
+            "messages_provider_config",
+        ),
+        _step("validate_environment", r"validate_anthropic_messages_environment$", "validate_environment"),
+        _step("transform_request", r"(?<!async_)transform_anthropic_messages_request$", "transform_request"),
+        _step("complete_url", r"get_complete_url$", "complete_url"),
+        _step(
+            "execute_messages_provider_call",
+            r"(?:async_)?anthropic_messages_handler$",
+            "execute_messages_provider_call",
+        ),
+        _step("http_request", _POST, "http_request"),
+        _step("transform_response", r"(?<!async_)transform_anthropic_messages_response$", "transform_response"),
+    ),
+    "audio_transcription": (
+        _step("audio_transcription", r"main\.py:\d+ a?transcription$", "audio_transcription"),
+        _step("prepare_audio_transcription_provider_call", rust="prepare_audio_transcription_provider_call"),
+        _step("get_non_default_transcription_params", r"get_non_default_transcription_params$"),
+        _step("map_transcription_params", r"get_optional_params_transcription$", "map_transcription_params"),
+        _step(
+            "get_provider_transcription_config",
+            r"ProviderConfigManager\.get_provider_audio_transcription_config$",
+            "provider_config",
+        ),
+        _step("supported_transcription_params", rust="supported_transcription_params"),
+        _step("transform_transcription_request", rust="transform_transcription_request"),
+        _step(
+            "execute_audio_transcription_provider_call",
+            r"BedrockAudioTranscriptionRustDispatch\.(?:async_)?audio_transcriptions$",
+            "execute_audio_transcription_provider_call",
+        ),
+        _step("transform_transcription_response", rust="transform_transcription_response"),
+        _step("http_request", rust="http_request"),
+    ),
+}
+
+
+def pipeline_issues(route: str, engine: Engine, events: Sequence[FunctionTraceEvent]) -> tuple[str, ...]:
+    names: Final = tuple(event.function for event in events)
+    required: Final = tuple(step.name for step in STEPS[route] if getattr(step, engine) is not None)
+    missing: Final = tuple(f"missing {name}" for name in required if name not in names)
+    provider: Final = next(name for name in required if name.startswith("get_provider_"))
+    handler: Final = next(name for name in required if name.startswith("execute_"))
+    dispatch_only: Final = route == "audio_transcription" and engine == "python"
+    request: Final = next(
+        (name for name in required if name.startswith("transform_") and name.endswith("request")), handler
+    )
+    response: Final = next(
+        (name for name in required if name.startswith("transform_") and name.endswith("response")), handler
+    )
+    phases: Final = (
+        (route, "map_transcription_params", provider, handler)
+        if dispatch_only
+        else (route, provider, request, "http_request", response)
+    )
+    extra_edges: Final = (
+        ()
+        if dispatch_only
+        else (
+            (handler, "http_request"),
+            *((name, request) for name in required if name.startswith(("map_", "supported_"))),
+            *((name, "http_request") for name in ("validate_environment", "complete_url") if name in required),
+        )
+    )
+    edges: Final = (*zip(phases, phases[1:]), *extra_edges)
+    return missing + tuple(
+        f"{before} must precede {after}"
+        for before, after in edges
+        if before in names and after in names and names.index(before) >= names.index(after)
+    )
+
+
+def _canonical_name(route: str, engine: Engine, function: str) -> str | None:
+    for step in STEPS[route]:
+        if engine == "python":
+            if step.python is not None and step.python.search(function):
+                return step.name
+        elif step.rust is not None and function == step.rust:
+            return step.name
+    return function if engine == "rust" else None
+
+
+@dataclass(frozen=True, slots=True)
+class _Projection:
+    shown: tuple[FunctionTraceEvent, ...] = ()
+    stack: tuple[tuple[int, int], ...] = ()
+    seen: frozenset[str] = frozenset()
+
+
+def _project(route: str, engine: Engine, state: _Projection, event: FunctionTraceEvent) -> _Projection:
+    stack: Final = tuple(pair for pair in state.stack if event.depth > pair[0])
+    name: Final = _canonical_name(route, engine, event.function)
+    if name is None or name in state.seen:
+        return _Projection(state.shown, stack, state.seen)
+    depth: Final = (
+        next(
+            (
+                kept.depth + 1
+                for ancestor in event.ancestors
+                for kept in state.shown
+                if kept.function == _canonical_name(route, engine, ancestor)
+            ),
+            0,
+        )
+        if event.ancestors is not None
+        else stack[-1][1] + 1
+        if stack
+        else 0
+    )
+    return _Projection(
+        state.shown + (FunctionTraceEvent(function=name, depth=depth),),
+        stack + ((event.depth, depth),),
+        state.seen | {name},
+    )
+
+
+def pipeline_steps(route: str, engine: Engine, events: Sequence[FunctionTraceEvent]) -> tuple[FunctionTraceEvent, ...]:
+    projection: Final = reduce(lambda state, event: _project(route, engine, state, event), events, _Projection())
+    return projection.shown
diff --git a/tests/sdk_function_trace/table.py b/tests/sdk_function_trace/table.py
new file mode 100644
index 00000000000..2124d7e3faf
--- /dev/null
+++ b/tests/sdk_function_trace/table.py
@@ -0,0 +1,72 @@
+from __future__ import annotations
+
+from collections.abc import Iterator
+from difflib import SequenceMatcher
+from typing import Final
+
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+
+
+def _aligned_rows(
+    python: tuple[FunctionTraceEvent, ...], rust: tuple[FunctionTraceEvent, ...]
+) -> Iterator[tuple[FunctionTraceEvent | None, FunctionTraceEvent | None]]:
+    matcher: Final = SequenceMatcher(
+        a=tuple(event.function for event in python),
+        b=tuple(event.function for event in rust),
+        autojunk=False,
+    )
+    for tag, python_start, python_end, rust_start, rust_end in matcher.get_opcodes():
+        if tag == "equal":
+            yield from zip(python[python_start:python_end], rust[rust_start:rust_end])
+        else:
+            yield from ((event, None) for event in python[python_start:python_end])
+            yield from ((None, event) for event in rust[rust_start:rust_end])
+
+
+def _label(event: FunctionTraceEvent | None) -> str:
+    return f"{'  ' * event.depth}{event.function}" if event is not None else ""
+
+
+def _status(
+    python: FunctionTraceEvent | None,
+    rust: FunctionTraceEvent | None,
+    python_names: frozenset[str],
+    rust_names: frozenset[str],
+) -> tuple[str, str]:
+    if python is not None and rust is not None:
+        return "match", "\033[32m"
+    if python is not None:
+        return ("reordered", "\033[31m") if python.function in rust_names else ("python only", "\033[34m")
+    if rust is not None:
+        return ("reordered", "\033[31m") if rust.function in python_names else ("rust only", "\033[33m")
+    return "", ""
+
+
+def format_trace_table(
+    python: tuple[FunctionTraceEvent, ...],
+    rust: tuple[FunctionTraceEvent, ...],
+    *,
+    colorize: bool,
+) -> str:
+    python_header: Final = f"python ({len(python)} steps)"
+    rust_header: Final = f"rust ({len(rust)} steps)"
+    python_width: Final = max(len(python_header), *(len(_label(event)) for event in python), 0)
+    rust_width: Final = max(len(rust_header), *(len(_label(event)) for event in rust), 0)
+    python_names: Final = frozenset(event.function for event in python)
+    rust_names: Final = frozenset(event.function for event in rust)
+    border: Final = f"+-{'-' * python_width}-+-{'-' * rust_width}-+-------------+"
+    rows: Final = tuple(
+        f"{color}{line}\033[0m" if colorize else line
+        for left, right in _aligned_rows(python, rust)
+        for status, color in (_status(left, right, python_names, rust_names),)
+        for line in (f"| {_label(left):<{python_width}} | {_label(right):<{rust_width}} | {status:<11} |",)
+    )
+    return "\n".join(
+        (
+            border,
+            f"| {python_header:<{python_width}} | {rust_header:<{rust_width}} | {'comparison':<11} |",
+            border,
+            *rows,
+            border,
+        )
+    )
diff --git a/tests/sdk_function_trace/test_mock_provider.py b/tests/sdk_function_trace/test_mock_provider.py
new file mode 100644
index 00000000000..88d7d5392d0
--- /dev/null
+++ b/tests/sdk_function_trace/test_mock_provider.py
@@ -0,0 +1,33 @@
+from __future__ import annotations
+
+from contextlib import ExitStack
+from typing import Final
+from urllib.error import HTTPError
+from urllib.request import Request, urlopen
+
+import pytest
+
+from tests.sdk_function_trace.mock_provider import MockProviderResponse, mock_provider
+
+
+def test_mock_provider_preserves_error_response() -> None:
+    response: Final = MockProviderResponse(429, (("retry-after", "2"),), b'{"error":"rate limited"}')
+    with mock_provider(response) as api_base:
+        with pytest.raises(HTTPError) as error:
+            urlopen(Request(api_base, data=b"{}"), timeout=5)
+        with error.value as received:
+            assert received.code == 429
+            assert received.headers["retry-after"] == "2"
+            assert received.read() == response.body
+
+
+@pytest.mark.parametrize("request_count", [0, 2])
+def test_mock_provider_rejects_missing_or_duplicate_requests(request_count: int) -> None:
+    response: Final = MockProviderResponse(200, (), b"{}")
+    with ExitStack() as stack:
+        api_base: Final = stack.enter_context(mock_provider(response))
+        for _ in range(request_count):
+            with urlopen(Request(api_base, data=b"{}"), timeout=5) as received:
+                assert received.read() == response.body
+        with pytest.raises(AssertionError, match=f"expected one provider request, received {request_count}"):
+            stack.close()
diff --git a/tests/sdk_function_trace/test_profiler.py b/tests/sdk_function_trace/test_profiler.py
new file mode 100644
index 00000000000..10a266fb1e8
--- /dev/null
+++ b/tests/sdk_function_trace/test_profiler.py
@@ -0,0 +1,167 @@
+from __future__ import annotations
+
+import asyncio
+import sys
+from pathlib import Path
+from types import FunctionType
+from typing import Final, cast
+
+import pytest
+
+from tests.sdk_function_trace import (
+    FunctionTraceEvent,
+    TraceScenario,
+    TraceStep,
+    assert_function_trace_parity,
+)
+from tests.sdk_function_trace.profiler import profile_python
+
+
+class First:
+    @staticmethod
+    def run() -> None:
+        return None
+
+
+class Second:
+    @staticmethod
+    def run() -> None:
+        return None
+
+
+def test_profiler_matches_code_objects_and_keeps_repeated_calls() -> None:
+    with profile_python((First.run,)) as profiler:
+        Second.run()
+        First.run()
+        First.run()
+
+    assert profiler.events == [
+        FunctionTraceEvent(function="run", depth=0),
+        FunctionTraceEvent(function="run", depth=0),
+    ]
+
+
+def test_profiler_records_selected_function_nesting_depth() -> None:
+    class Nested:
+        @staticmethod
+        def run() -> None:
+            First.run()
+
+    with profile_python((Nested.run, First.run)) as profiler:
+        Nested.run()
+
+    assert profiler.events == [
+        FunctionTraceEvent(function="run", depth=0),
+        FunctionTraceEvent(function="run", depth=1),
+    ]
+
+
+def test_profiler_restores_previous_profiler_after_failure() -> None:
+    previous: Final = sys.getprofile()
+
+    with profile_python((First.run,)) as outer:
+        with pytest.raises(RuntimeError, match="stop"):
+            with profile_python((Second.run,)):
+                raise RuntimeError("stop")
+        assert sys.getprofile() is outer
+        First.run()
+
+    assert sys.getprofile() is previous
+    assert outer.events == [FunctionTraceEvent(function="run", depth=0)]
+
+
+def test_profiler_does_not_count_coroutine_resumption_as_another_call() -> None:
+    async def suspended() -> None:
+        await asyncio.sleep(0)
+        First.run()
+        await asyncio.sleep(0)
+
+    with profile_python((suspended, First.run)) as profiler:
+        asyncio.run(suspended())
+
+    assert profiler.events == [
+        FunctionTraceEvent(function="suspended", depth=0),
+        FunctionTraceEvent(function="run", depth=1),
+    ]
+
+
+def test_source_profiler_records_real_frame_ancestry() -> None:
+    def outer() -> None:
+        First.run()
+
+    with profile_python(source_root=Path(__file__).parent) as profiler:
+        outer()
+        Second.run()
+
+    outer_event, first_event, second_event = (
+        event for event in profiler.events if event.function.startswith("test_profiler.py:")
+    )
+    assert first_event.ancestors is not None
+    assert outer_event.function in first_event.ancestors
+    assert second_event.ancestors is not None
+    assert outer_event.function not in second_event.ancestors
+
+
+@pytest.mark.parametrize(
+    "rust_trace",
+    [
+        (),
+        (FunctionTraceEvent(function="renamed", depth=0),),
+        (FunctionTraceEvent(function="run", depth=1),),
+        (FunctionTraceEvent(function="run", depth=0),) * 2,
+    ],
+    ids=["missing", "renamed", "wrong-depth", "extra-call"],
+)
+def test_harness_rejects_rust_function_trace_drift(rust_trace: tuple[FunctionTraceEvent, ...]) -> None:
+    with pytest.raises(AssertionError, match="Rust function trace differs"):
+        assert_function_trace_parity(
+            TraceScenario(
+                steps=(TraceStep(cast(FunctionType, First.run), depth=0),),
+                invoke_python=First.run,
+                invoke_rust=lambda: rust_trace,
+            )
+        )
+
+
+def test_harness_rejects_python_function_trace_drift() -> None:
+    with pytest.raises(AssertionError, match="Python function trace differs"):
+        assert_function_trace_parity(
+            TraceScenario(
+                steps=(TraceStep(cast(FunctionType, First.run), depth=0),),
+                invoke_python=Second.run,
+                invoke_rust=lambda: (FunctionTraceEvent(function="run", depth=0),),
+            )
+        )
+
+
+def test_harness_accepts_matching_traces() -> None:
+    assert_function_trace_parity(
+        TraceScenario(
+            steps=(TraceStep(cast(FunctionType, First.run), depth=0),),
+            invoke_python=First.run,
+            invoke_rust=lambda: (FunctionTraceEvent(function="run", depth=0),),
+        )
+    )
+
+
+def test_harness_rejects_reordered_calls() -> None:
+    def begin() -> None:
+        return None
+
+    def finish() -> None:
+        return None
+
+    with pytest.raises(AssertionError, match="Rust function trace differs"):
+        assert_function_trace_parity(
+            TraceScenario(
+                steps=(
+                    TraceStep(cast(FunctionType, begin), depth=0),
+                    TraceStep(cast(FunctionType, finish), depth=0),
+                ),
+                invoke_python=lambda: (begin(), finish()),
+                invoke_rust=lambda: (
+                    FunctionTraceEvent(function="finish", depth=0),
+                    FunctionTraceEvent(function="begin", depth=0),
+                ),
+            )
+        )
diff --git a/tests/sdk_function_trace/test_runtime.py b/tests/sdk_function_trace/test_runtime.py
new file mode 100644
index 00000000000..015cba55083
--- /dev/null
+++ b/tests/sdk_function_trace/test_runtime.py
@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+from typing import Final
+
+import pytest
+
+from tests.sdk_function_trace.runtime import (
+    TraceFailed,
+    TraceSkipped,
+    attempt_trace,
+    run_trace,
+    trace_diff,
+)
+from tests.sdk_function_trace.steps import pipeline_issues, pipeline_steps
+
+
+def test_sync_messages_records_the_known_python_limitation() -> None:
+    result: Final = attempt_trace("messages", engine="python", asynchronous=False)
+
+    assert isinstance(result, TraceSkipped)
+    assert result.reason == "ValueError: anthropic_messages_handler is not implemented for sync calls"
+
+
+def test_unexpected_call_failure_is_not_skipped() -> None:
+    result: Final = attempt_trace("unknown", engine="python", asynchronous=False)
+
+    assert isinstance(result, TraceFailed)
+    assert result.reason == "ValueError: Unknown route: unknown"
+
+
+@pytest.mark.parametrize(
+    ("route", "asynchronous"),
+    (("chat_completions", False), ("chat_completions", True), ("messages", True), ("ocr", False), ("ocr", True)),
+)
+def test_compiled_routes_match_python_steps(route: str, asynchronous: bool) -> None:
+    from litellm.rust_bridge import get_native_bridge
+
+    if get_native_bridge() is None:
+        pytest.skip("build the native bridge to run executed route parity")
+    python: Final = pipeline_steps(route, "python", run_trace(route, engine="python", asynchronous=asynchronous))
+    rust: Final = pipeline_steps(route, "rust", run_trace(route, engine="rust", asynchronous=asynchronous))
+
+    assert pipeline_issues(route, "python", python) == ()
+    assert pipeline_issues(route, "rust", rust) == ()
+    assert trace_diff(python, rust).matches
+    if route != "messages":
+        assert python == rust
diff --git a/tests/sdk_function_trace/test_steps.py b/tests/sdk_function_trace/test_steps.py
new file mode 100644
index 00000000000..b5432951187
--- /dev/null
+++ b/tests/sdk_function_trace/test_steps.py
@@ -0,0 +1,244 @@
+from __future__ import annotations
+
+from typing import Final
+
+import pytest
+
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+from tests.sdk_function_trace.runtime import trace_diff
+from tests.sdk_function_trace.steps import pipeline_issues, pipeline_steps
+
+
+def test_python_ocr_projection_keeps_pipeline_and_drops_noise() -> None:
+    events: Final = (
+        FunctionTraceEvent("utils.py:1747 client.<locals>.wrapper_async", 0),
+        FunctionTraceEvent("ocr/main.py:331 aocr", 1),
+        FunctionTraceEvent("ocr/main.py:70 _prepare_ocr_request", 2),
+        FunctionTraceEvent("litellm_core_utils/get_llm_provider_logic.py:142 get_llm_provider", 3),
+        FunctionTraceEvent("utils.py:9303 ProviderConfigManager.get_provider_ocr_config", 3),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:34 MistralOCRConfig.get_supported_ocr_params", 4),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:72 MistralOCRConfig.map_ocr_params", 4),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:34 MistralOCRConfig.get_supported_ocr_params", 5),
+        FunctionTraceEvent("llms/custom_httpx/llm_http_handler.py:1705 BaseLLMHTTPHandler.async_ocr", 2),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:94 MistralOCRConfig.validate_environment", 4),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:124 MistralOCRConfig.get_complete_url", 4),
+        FunctionTraceEvent("llms/base_llm/ocr/transformation.py:209 BaseOCRConfig.async_transform_ocr_request", 5),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:149 MistralOCRConfig.transform_ocr_request", 6),
+        FunctionTraceEvent("llms/custom_httpx/http_handler.py:654 AsyncHTTPHandler.post", 6),
+        FunctionTraceEvent("llms/base_llm/ocr/transformation.py:255 BaseOCRConfig.async_transform_ocr_response", 4),
+        FunctionTraceEvent("llms/mistral/ocr/transformation.py:200 MistralOCRConfig.transform_ocr_response", 5),
+        FunctionTraceEvent("cost_calculator.py:1874 ocr_cost", 6),
+    )
+
+    assert pipeline_steps("ocr", "python", events) == (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("prepare_ocr_call", 1),
+        FunctionTraceEvent("get_provider_ocr_config", 2),
+        FunctionTraceEvent("supported_ocr_params", 3),
+        FunctionTraceEvent("map_ocr_params", 3),
+        FunctionTraceEvent("execute_ocr_provider_call", 1),
+        FunctionTraceEvent("validate_environment", 2),
+        FunctionTraceEvent("complete_url", 2),
+        FunctionTraceEvent("transform_ocr_request", 3),
+        FunctionTraceEvent("http_request", 3),
+        FunctionTraceEvent("transform_ocr_response", 2),
+    )
+
+
+def test_rust_ocr_projection_reuses_step_names_and_keeps_unknown_spans() -> None:
+    events: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("prepare_ocr_call", 1),
+        FunctionTraceEvent("map_ocr_params", 2),
+        FunctionTraceEvent("supported_ocr_params", 3),
+        FunctionTraceEvent("map_ocr_params", 2),
+        FunctionTraceEvent("transform_ocr_request", 2),
+        FunctionTraceEvent("execute_ocr_provider_call", 2),
+        FunctionTraceEvent("transform_ocr_response", 3),
+        FunctionTraceEvent("new_uninstrumented_span", 3),
+    )
+
+    assert pipeline_steps("ocr", "rust", events) == (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("prepare_ocr_call", 1),
+        FunctionTraceEvent("map_ocr_params", 2),
+        FunctionTraceEvent("supported_ocr_params", 3),
+        FunctionTraceEvent("transform_ocr_request", 2),
+        FunctionTraceEvent("execute_ocr_provider_call", 2),
+        FunctionTraceEvent("transform_ocr_response", 3),
+        FunctionTraceEvent("new_uninstrumented_span", 3),
+    )
+
+
+def test_projection_resets_depth_on_thread_root() -> None:
+    events: Final = (
+        FunctionTraceEvent("main.py:387 acompletion", 1),
+        FunctionTraceEvent("llms/anthropic/chat/handler.py:255 AnthropicChatCompletion.acompletion_function", 2),
+        FunctionTraceEvent(
+            "llms/anthropic/experimental_pass_through/messages/handler.py:416 anthropic_messages_handler", 0
+        ),
+        FunctionTraceEvent(
+            "llms/anthropic/experimental_pass_through/messages/transformation.py:575"
+            " AnthropicMessagesConfig.transform_anthropic_messages_request",
+            4,
+        ),
+    )
+
+    assert pipeline_steps("chat_completions", "python", events) == (
+        FunctionTraceEvent("chat_completions", 0),
+        FunctionTraceEvent("execute_chat_completions_provider_call", 1),
+    )
+    assert pipeline_steps("messages", "python", events) == (
+        FunctionTraceEvent("execute_messages_provider_call", 0),
+        FunctionTraceEvent("transform_request", 1),
+    )
+
+
+@pytest.mark.parametrize("function", ("completion", "completion_function", "acompletion_function"))
+def test_chat_projection_includes_sync_and_async_handlers(function: str) -> None:
+    events: Final = (FunctionTraceEvent(f"llms/anthropic/chat/handler.py:100 AnthropicChatCompletion.{function}", 0),)
+
+    assert pipeline_steps("chat_completions", "python", events) == (
+        FunctionTraceEvent("execute_chat_completions_provider_call", 0),
+    )
+
+
+def test_trace_diff_reports_no_difference_for_identical_steps() -> None:
+    steps: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("transform_ocr_request", 1),
+    )
+
+    diff: Final = trace_diff(steps, steps)
+
+    assert diff.python_only == ()
+    assert diff.rust_only == ()
+    assert diff.shared_order_matches
+    assert diff.matches
+
+
+def test_trace_diff_reports_exclusive_steps_and_reordered_shared_steps() -> None:
+    python: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("supported_ocr_params", 1),
+        FunctionTraceEvent("map_ocr_params", 1),
+        FunctionTraceEvent("http_request", 2),
+    )
+    rust: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("map_ocr_params", 1),
+        FunctionTraceEvent("supported_ocr_params", 2),
+        FunctionTraceEvent("transform_ocr_response", 2),
+    )
+
+    diff: Final = trace_diff(python, rust)
+
+    assert diff.python_only == ("http_request",)
+    assert diff.rust_only == ("transform_ocr_response",)
+    assert not diff.shared_order_matches
+    assert not diff.matches
+
+
+def test_trace_diff_does_not_claim_empty_or_disjoint_traces_match() -> None:
+    assert not trace_diff((), ()).shared_order_matches
+    assert not trace_diff((FunctionTraceEvent("ocr", 0),), (FunctionTraceEvent("messages", 0),)).shared_order_matches
+
+
+def test_projection_uses_actual_ancestors_after_coroutine_resumption() -> None:
+    entrypoint: Final = "main.py:387 acompletion"
+    handler: Final = "llms/anthropic/chat/handler.py:255 AnthropicChatCompletion.acompletion_function"
+    events: Final = (
+        FunctionTraceEvent(entrypoint, 0, ()),
+        FunctionTraceEvent(handler, 1, (entrypoint,)),
+        FunctionTraceEvent("utils.py:100 unrelated_worker", 0, ()),
+        FunctionTraceEvent("llms/anthropic/chat/transformation.py:100 transform_response", 1, (handler,)),
+    )
+
+    assert pipeline_steps("chat_completions", "python", events) == (
+        FunctionTraceEvent("chat_completions", 0),
+        FunctionTraceEvent("execute_chat_completions_provider_call", 1),
+        FunctionTraceEvent("transform_response", 2),
+    )
+
+
+def test_projection_does_not_nest_siblings_under_a_returned_config_lookup() -> None:
+    events: Final = (
+        FunctionTraceEvent("main.py:387 completion", 0),
+        FunctionTraceEvent("utils.py:100 ProviderConfigManager.get_provider_chat_config", 1),
+        FunctionTraceEvent("utils.py:200 unrelated_helper", 1),
+        FunctionTraceEvent("llms/anthropic/chat/transformation.py:100 transform_request", 2),
+    )
+
+    assert pipeline_steps("chat_completions", "python", events) == (
+        FunctionTraceEvent("chat_completions", 0),
+        FunctionTraceEvent("get_provider_chat_config", 1),
+        FunctionTraceEvent("transform_request", 1),
+    )
+
+
+CHAT_RUST_STEPS: Final = (
+    "chat_completions",
+    "get_provider_chat_config",
+    "supported_openai_params",
+    "execute_chat_completions_provider_call",
+    "validate_environment",
+    "transform_request",
+    "http_request",
+    "transform_response",
+)
+
+
+@pytest.mark.parametrize("missing", CHAT_RUST_STEPS)
+def test_pipeline_check_rejects_missing_stages(missing: str) -> None:
+    steps: Final = tuple(FunctionTraceEvent(name, 0) for name in CHAT_RUST_STEPS if name != missing)
+
+    assert f"missing {missing}" in pipeline_issues("chat_completions", "rust", steps)
+
+
+def test_pipeline_check_rejects_http_before_request_transformation() -> None:
+    steps: Final = tuple(
+        FunctionTraceEvent(name, 0)
+        for name in (
+            "chat_completions",
+            "get_provider_chat_config",
+            "supported_openai_params",
+            "execute_chat_completions_provider_call",
+            "validate_environment",
+            "http_request",
+            "transform_request",
+            "transform_response",
+        )
+    )
+
+    assert "transform_request must precede http_request" in pipeline_issues("chat_completions", "rust", steps)
+
+
+def test_step_parity_rejects_different_handler_boundaries_even_with_valid_stages() -> None:
+    rust: Final = tuple(FunctionTraceEvent(name, 0) for name in CHAT_RUST_STEPS)
+    python: Final = tuple(
+        FunctionTraceEvent(name, 0)
+        for name in (
+            "chat_completions",
+            "get_provider_chat_config",
+            "supported_openai_params",
+            "validate_environment",
+            "transform_request",
+            "execute_chat_completions_provider_call",
+            "http_request",
+            "transform_response",
+        )
+    )
+
+    assert not trace_diff(python, rust).shared_order_matches
+    assert not trace_diff(python, rust).matches
+    assert pipeline_issues("chat_completions", "python", python) == ()
+    assert pipeline_issues("chat_completions", "rust", rust) == ()
+
+
+def test_step_parity_rejects_an_exclusive_helper_with_matching_shared_order() -> None:
+    rust: Final = tuple(FunctionTraceEvent(name, 0) for name in CHAT_RUST_STEPS)
+    python: Final = (*rust, FunctionTraceEvent("unmatched_helper", 0))
+    diff: Final = trace_diff(python, rust)
+
+    assert diff.shared_order_matches
+    assert not diff.matches
diff --git a/tests/sdk_function_trace/test_table.py b/tests/sdk_function_trace/test_table.py
new file mode 100644
index 00000000000..c2341a391a9
--- /dev/null
+++ b/tests/sdk_function_trace/test_table.py
@@ -0,0 +1,67 @@
+from __future__ import annotations
+
+import re
+from typing import Final
+
+from tests.sdk_function_trace.profiler import FunctionTraceEvent
+from tests.sdk_function_trace.table import format_trace_table
+
+
+def test_table_aligns_matches_after_missing_steps_and_preserves_indentation() -> None:
+    python: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("python_helper", 1),
+        FunctionTraceEvent("http_request", 2),
+    )
+    rust: Final = (
+        FunctionTraceEvent("ocr", 0),
+        FunctionTraceEvent("rust_helper", 1),
+        FunctionTraceEvent("http_request", 1),
+    )
+    output: Final = format_trace_table(python, rust, colorize=False)
+    rows: Final = tuple(line.split("|")[1:-1] for line in output.splitlines() if line.startswith("|"))
+
+    assert tuple(tuple(cell.strip() for cell in row) for row in rows) == (
+        ("python (3 steps)", "rust (3 steps)", "comparison"),
+        ("ocr", "ocr", "match"),
+        ("python_helper", "", "python only"),
+        ("", "rust_helper", "rust only"),
+        ("http_request", "http_request", "match"),
+    )
+    assert rows[-1][0].startswith("     http_request")
+    assert rows[-1][1].startswith("   http_request")
+    assert len({len(line) for line in output.splitlines()}) == 1
+    assert "\033[" not in output
+
+
+def test_table_marks_reordered_calls_and_keeps_both_execution_orders() -> None:
+    python: Final = tuple(FunctionTraceEvent(name, 0) for name in ("ocr", "map", "validate", "http"))
+    rust: Final = tuple(FunctionTraceEvent(name, 0) for name in ("ocr", "validate", "map", "http"))
+    output: Final = format_trace_table(python, rust, colorize=True)
+    plain: Final = re.sub(r"\033\[[0-9;]*m", "", output)
+    rows: Final = tuple(line.split("|")[1:-1] for line in plain.splitlines() if line.startswith("|"))[1:]
+
+    assert tuple(row[0].strip() for row in rows if row[0].strip()) == tuple(event.function for event in python)
+    assert tuple(row[1].strip() for row in rows if row[1].strip()) == tuple(event.function for event in rust)
+    assert plain.count("reordered") == 2
+    assert output.count("\033[31m") == 2
+    assert "only" not in output
+
+
+def test_table_colors_match_and_exclusive_rows_without_changing_alignment() -> None:
+    python: Final = (FunctionTraceEvent("ocr", 0), FunctionTraceEvent("python_helper", 1))
+    rust: Final = (FunctionTraceEvent("ocr", 0), FunctionTraceEvent("rust_helper", 1))
+    colored: Final = format_trace_table(python, rust, colorize=True)
+
+    assert re.sub(r"\033\[[0-9;]*m", "", colored) == format_trace_table(python, rust, colorize=False)
+    assert next(line for line in colored.splitlines() if "match" in line).startswith("\033[32m")
+    assert next(line for line in colored.splitlines() if "python only" in line).startswith("\033[34m")
+    assert next(line for line in colored.splitlines() if "rust only" in line).startswith("\033[33m")
+
+
+def test_table_handles_empty_traces() -> None:
+    output: Final = format_trace_table((), (), colorize=False)
+
+    assert "python (0 steps)" in output
+    assert "rust (0 steps)" in output
+    assert "match" not in output
diff --git a/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py b/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
index 5503a5668bf..a8fe464ec32 100644
--- a/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
+++ b/tests/test_litellm/a2a_protocol/providers/bedrock_agentcore/test_bedrock_agentcore_a2a.py
@@ -11,7 +11,9 @@ Verifies that:
 
 import json
 
+import httpx
 import pytest
+import respx
 from unittest.mock import AsyncMock, MagicMock, patch
 
 
@@ -295,6 +297,195 @@ class TestTransformation:
         assert headers["Authorization"].startswith("AWS4-HMAC-SHA256")
 
 
+SESSION_HEADER = "X-Amzn-Bedrock-AgentCore-Runtime-Session-Id"
+CONTEXT_ID = "conversation-alpha-0001-0000000000000000"
+KEY_HASH = "hashed-key-of-caller-one"
+
+
+def _params_with_context(context_id: object) -> dict:
+    return {"message": {**SAMPLE_PARAMS["message"], "contextId": context_id}}
+
+
+def _scoped(context_id: str, key_hash: str) -> str:
+    import hashlib
+
+    return f"{hashlib.sha256(key_hash.encode()).hexdigest()[:16]}-{context_id}"
+
+
+def _session_header(params: dict, litellm_params: dict) -> str:
+    from litellm.a2a_protocol.providers.bedrock_agentcore.transformation import (
+        BedrockAgentCoreA2ATransformation,
+    )
+
+    _, headers, _ = BedrockAgentCoreA2ATransformation.get_url_and_signed_request(
+        request_id="req-001",
+        params=params,
+        litellm_params=litellm_params,
+    )
+    return headers[SESSION_HEADER]
+
+
+@pytest.fixture
+def httpx_transport(monkeypatch):
+    import litellm
+
+    monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+    monkeypatch.setenv("DISABLE_AIOHTTP_TRANSPORT", "True")
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    yield
+    litellm.in_memory_llm_clients_cache.flush_cache()
+
+
+class TestRequestScopedRuntimeSession:
+    """message.contextId selects the AgentCore runtime session, scoped to the calling key."""
+
+    def test_context_id_scoped_to_calling_key(self):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH}
+        assert _session_header(_params_with_context(CONTEXT_ID), litellm_params) == _scoped(CONTEXT_ID, KEY_HASH)
+
+    def test_context_id_used_verbatim_without_principal(self):
+        assert _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS) == CONTEXT_ID
+
+    def test_same_context_id_reuses_session_and_other_context_isolated(self):
+        first = _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS)
+        second = _session_header(_params_with_context(CONTEXT_ID), SAMPLE_LITELLM_PARAMS)
+        other = _session_header(
+            _params_with_context("conversation-beta-00002-0000000000000000"),
+            SAMPLE_LITELLM_PARAMS,
+        )
+        assert first == second
+        assert other != first
+
+    def test_same_context_id_from_different_keys_is_isolated(self):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        params = _params_with_context(CONTEXT_ID)
+        caller_one = _session_header(params, {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH})
+        caller_two = _session_header(
+            params, {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: "hashed-key-of-caller-two"}
+        )
+        assert caller_one != caller_two
+        assert caller_one.endswith(f"-{CONTEXT_ID}")
+        assert caller_two.endswith(f"-{CONTEXT_ID}")
+
+    def test_context_id_takes_precedence_over_configured_session(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(_params_with_context(CONTEXT_ID), litellm_params) == CONTEXT_ID
+
+    def test_configured_session_is_fallback_without_context_id(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(SAMPLE_PARAMS, litellm_params) == "a" * 40
+        assert _session_header(_params_with_context(""), litellm_params) == "a" * 40
+
+    def test_no_context_id_and_no_config_generates_new_session_per_request(self):
+        first = _session_header(SAMPLE_PARAMS, SAMPLE_LITELLM_PARAMS)
+        second = _session_header(SAMPLE_PARAMS, SAMPLE_LITELLM_PARAMS)
+        assert first != second
+        assert 33 <= len(first) <= 256
+
+    @pytest.mark.parametrize(
+        "context_id",
+        [
+            "short-context-id",
+            "x" * 257,
+        ],
+    )
+    def test_invalid_context_id_rejected_with_clear_error(self, context_id):
+        import litellm
+
+        with pytest.raises(litellm.BadRequestError, match="Invalid AgentCore runtime session id") as exc_info:
+            _session_header(_params_with_context(context_id), SAMPLE_LITELLM_PARAMS)
+        assert exc_info.value.status_code == 400
+        assert "33-256" in str(exc_info.value)
+
+    def test_scoped_context_id_shorter_than_33_rejected(self):
+        import litellm
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH}
+        with pytest.raises(litellm.BadRequestError, match=_scoped("c" * 15, KEY_HASH)):
+            _session_header(_params_with_context("c" * 15), litellm_params)
+        assert _session_header(_params_with_context("c" * 16), litellm_params) == _scoped("c" * 16, KEY_HASH)
+
+    def test_invalid_configured_session_rejected(self):
+        import litellm
+
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "too-short"}
+        with pytest.raises(litellm.BadRequestError, match="Invalid AgentCore runtime session id"):
+            _session_header(SAMPLE_PARAMS, litellm_params)
+
+    def test_non_string_context_id_falls_back(self):
+        litellm_params = {**SAMPLE_LITELLM_PARAMS, "runtimeSessionId": "a" * 40}
+        assert _session_header(_params_with_context(12345), litellm_params) == "a" * 40
+
+    def test_spoofed_session_header_does_not_override_context_id(self):
+        from litellm.a2a_protocol.providers.bedrock_agentcore.transformation import (
+            BedrockAgentCoreA2ATransformation,
+        )
+
+        _, headers, _ = BedrockAgentCoreA2ATransformation.get_url_and_signed_request(
+            request_id="req-001",
+            params=_params_with_context(CONTEXT_ID),
+            litellm_params=SAMPLE_LITELLM_PARAMS,
+            agent_extra_headers={SESSION_HEADER: "s" * 40},
+        )
+        assert headers[SESSION_HEADER] == CONTEXT_ID
+
+    @pytest.mark.asyncio
+    async def test_context_id_session_header_on_outbound_non_streaming_post(self, httpx_transport):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+        from litellm.a2a_protocol.providers.bedrock_agentcore.config import (
+            BedrockAgentCoreA2AConfig,
+        )
+
+        with respx.mock(assert_all_called=True) as router:
+            route = router.post(url__regex=r".*/invocations.*").mock(
+                return_value=httpx.Response(200, json={"jsonrpc": "2.0", "id": "req-001", "result": {}})
+            )
+            await BedrockAgentCoreA2AConfig().handle_non_streaming(
+                request_id="req-001",
+                params=_params_with_context(CONTEXT_ID),
+                litellm_params={**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH},
+            )
+
+        assert route.calls.last.request.headers[SESSION_HEADER] == _scoped(CONTEXT_ID, KEY_HASH)
+
+    @pytest.mark.asyncio
+    async def test_context_id_session_header_on_outbound_streaming_post(self, httpx_transport):
+        from litellm.a2a_protocol.litellm_completion_bridge.handler import (
+            A2A_USER_API_KEY_HASH_PARAM,
+        )
+        from litellm.a2a_protocol.providers.bedrock_agentcore.config import (
+            BedrockAgentCoreA2AConfig,
+        )
+
+        with respx.mock(assert_all_called=True) as router:
+            route = router.post(url__regex=r".*/invocations.*").mock(
+                return_value=httpx.Response(200, json={"jsonrpc": "2.0", "id": "req-001", "result": {}})
+            )
+            events = [
+                event
+                async for event in BedrockAgentCoreA2AConfig().handle_streaming(
+                    request_id="req-001",
+                    params=_params_with_context(CONTEXT_ID),
+                    litellm_params={**SAMPLE_LITELLM_PARAMS, A2A_USER_API_KEY_HASH_PARAM: KEY_HASH},
+                )
+            ]
+
+        assert events == [{"jsonrpc": "2.0", "id": "req-001", "result": {}}]
+        assert route.calls.last.request.headers[SESSION_HEADER] == _scoped(CONTEXT_ID, KEY_HASH)
+
+
 class TestNonStreaming:
     """Test end-to-end non-streaming flow."""
 
diff --git a/tests/test_litellm/anthropic_interface/test_rust_bridge_messages.py b/tests/test_litellm/anthropic_interface/test_rust_bridge_messages.py
index fbd7e36e298..293f75b7592 100644
--- a/tests/test_litellm/anthropic_interface/test_rust_bridge_messages.py
+++ b/tests/test_litellm/anthropic_interface/test_rust_bridge_messages.py
@@ -8,6 +8,7 @@ import pytest
 
 import litellm
 from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
+from litellm.rust_bridge import configuration
 from litellm.types.llms.anthropic_messages.anthropic_response import (
     AnthropicMessagesResponse,
 )
@@ -109,10 +110,12 @@ class RaisingAsyncMessages:
 
 @pytest.fixture(autouse=True)
 def _reset_rust_flag():
-    litellm.use_litellm_rust(False, messages=None, amessages=None)
+    rust_messages.set_rust_messages(messages=None, amessages=None)
+    configuration.reset_rust_configuration()
     rust_bridge_loader._cached_bridge = rust_bridge_loader._BRIDGE_SENTINEL
     yield
-    litellm.use_litellm_rust(False, messages=None, amessages=None)
+    rust_messages.set_rust_messages(messages=None, amessages=None)
+    configuration.reset_rust_configuration()
     rust_bridge_loader._cached_bridge = rust_bridge_loader._BRIDGE_SENTINEL
 
 
@@ -122,17 +125,6 @@ def test_load_rust_messages_returns_injected_impl():
     assert rust_messages.load_rust_messages() is bridge
 
 
-def test_configuring_messages_does_not_enable_ocr():
-    from litellm.rust_bridge.ocr import rust_ocr_enabled
-
-    litellm.use_litellm_rust(False)
-    assert rust_ocr_enabled() is False
-
-    litellm.use_litellm_rust(True, messages=RecordingMessages())
-
-    assert rust_ocr_enabled() is False
-
-
 def test_bare_use_litellm_rust_still_toggles_ocr():
     from litellm.rust_bridge.ocr import rust_ocr_enabled
 
@@ -264,7 +256,7 @@ async def test_gate_falls_back_to_python_when_bridge_raises():
 @pytest.mark.asyncio
 async def test_gate_skips_rust_when_flag_absent():
     bridge = ExplodingAsyncMessages()
-    litellm.use_litellm_rust(True, amessages=bridge)
+    rust_messages.set_rust_messages(amessages=bridge)
 
     response = await _gate(litellm_params=GenericLiteLLMParams(api_key="sk-azure"))
 
@@ -272,6 +264,18 @@ async def test_gate_skips_rust_when_flag_absent():
     assert bridge.calls == 0
 
 
+@pytest.mark.asyncio
+async def test_gate_uses_process_enable_without_request_override():
+    bridge = RecordingAsyncMessages()
+    rust_messages.set_rust_messages(amessages=bridge)
+    litellm.use_litellm_rust(True)
+
+    response = await _gate(litellm_params=GenericLiteLLMParams(api_key="sk-azure"))
+
+    assert response is not None
+    assert bridge.calls[0]["custom_llm_provider"] == "azure_ai"
+
+
 @pytest.mark.asyncio
 async def test_gate_skips_rust_when_flag_false():
     bridge = ExplodingAsyncMessages()
@@ -305,7 +309,7 @@ async def test_gate_invokes_rust_for_native_anthropic_provider():
 @pytest.mark.asyncio
 async def test_gate_invokes_rust_when_env_var_set(monkeypatch):
     bridge = RecordingAsyncMessages()
-    litellm.use_litellm_rust(True, amessages=bridge)
+    rust_messages.set_rust_messages(amessages=bridge)
     monkeypatch.setenv("LITELLM_RUST", "1")
 
     response = await _gate(
@@ -320,7 +324,7 @@ async def test_gate_invokes_rust_when_env_var_set(monkeypatch):
 @pytest.mark.asyncio
 async def test_gate_env_var_falsey_does_not_enable(monkeypatch):
     bridge = ExplodingAsyncMessages()
-    litellm.use_litellm_rust(True, amessages=bridge)
+    rust_messages.set_rust_messages(amessages=bridge)
     monkeypatch.setenv("LITELLM_RUST", "0")
 
     response = await _gate(
diff --git a/tests/test_litellm/caching/test_redis_connection_pool.py b/tests/test_litellm/caching/test_redis_connection_pool.py
index c824d3e7a0e..54dbe5361d7 100644
--- a/tests/test_litellm/caching/test_redis_connection_pool.py
+++ b/tests/test_litellm/caching/test_redis_connection_pool.py
@@ -1,15 +1,14 @@
-"""
-Regression tests for Redis connection pool leak fixes (RC1-RC5).
-
-Tests are pure unit tests — no Redis server required.
-"""
-
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
-import redis.asyncio as async_redis
 
-from litellm._redis import get_redis_async_client, get_redis_connection_pool
+from litellm._redis import (
+    _coerce_redis_kwargs_types,
+    _get_redis_client_logic,
+    _get_redis_env_kwarg_mapping,
+    get_redis_async_client,
+    get_redis_connection_pool,
+)
 
 
 def test_url_config_uses_passed_pool():
@@ -60,16 +59,14 @@ def test_max_connections_url_config_string_value(monkeypatch):
     assert pool.max_connections == 25
 
 
-def test_max_connections_url_config_invalid_value():
-    """Invalid max_connections should be silently ignored, falling back
-    to the pool default (50 for BlockingConnectionPool)."""
-    with patch("litellm._redis._get_redis_client_logic") as mock_logic:
-        mock_logic.return_value = {
-            "url": "redis://localhost:6379/0",
-            "max_connections": "not_a_number",
-        }
+def test_max_connections_url_config_invalid_value(monkeypatch):
+    """Invalid max_connections from an env var should be silently dropped,
+    falling back to the pool default (50 for BlockingConnectionPool)."""
+    monkeypatch.setenv("REDIS_URL", "redis://localhost:6379/0")
+    monkeypatch.delenv("REDIS_HOST", raising=False)
+    monkeypatch.setenv("REDIS_MAX_CONNECTIONS", "not_a_number")
 
-        pool = get_redis_connection_pool()
+    pool = get_redis_connection_pool()
 
     # BlockingConnectionPool default is 50
     assert pool.max_connections == 50
@@ -128,3 +125,173 @@ async def test_disconnect_idempotent():
 
     await cache.disconnect()
     await cache.disconnect()  # should not raise
+
+
+def test_coerce_redis_kwargs_types_int():
+    """String values for int-typed Redis params are coerced to int."""
+    result = _coerce_redis_kwargs_types({"health_check_interval": "30", "port": "6380", "db": "1"})
+    assert result["health_check_interval"] == 30
+    assert isinstance(result["health_check_interval"], int)
+    assert result["port"] == 6380
+    assert result["db"] == 1
+
+
+def test_coerce_redis_kwargs_types_bool():
+    """String values for bool-typed Redis params are coerced to bool."""
+    result = _coerce_redis_kwargs_types({"ssl": "true", "decode_responses": "false"})
+    assert result["ssl"] is True
+    assert result["decode_responses"] is False
+
+
+def test_coerce_redis_kwargs_types_none_default_numeric():
+    """String values for known None-default numeric params are coerced."""
+    result = _coerce_redis_kwargs_types({"max_connections": "20", "socket_timeout": "5.5"})
+    assert result["max_connections"] == 20
+    assert isinstance(result["max_connections"], int)
+    assert result["socket_timeout"] == 5.5
+    assert isinstance(result["socket_timeout"], float)
+
+
+def _redis_signature_pre_8x(
+    socket_timeout=None,
+    socket_connect_timeout=None,
+    max_connections=None,
+    health_check_interval=0,
+):
+    """Stand-in for the redis-py <= 7.x Redis signature, where the timeout defaults are None."""
+
+
+def _redis_signature_8x(
+    socket_timeout=5,
+    socket_connect_timeout=5,
+    max_connections=None,
+    health_check_interval=0,
+):
+    """Stand-in for the redis-py 8.x Redis signature, where the timeout defaults became int 5."""
+
+
+@pytest.mark.parametrize(
+    "client",
+    [_redis_signature_pre_8x, _redis_signature_8x],
+    ids=["redis-py<=7.x", "redis-py-8.x"],
+)
+def test_coerce_fractional_socket_timeout_survives_signature_default_change(client):
+    """redis-py 8.x changed socket_timeout's default from None to int 5. Deriving the
+    target type from the signature default made int("5.5") raise, so the key was dropped
+    and REDIS_SOCKET_TIMEOUT=5.5 silently disappeared on 8.x."""
+    result = _coerce_redis_kwargs_types(
+        {"socket_timeout": "5.5", "socket_connect_timeout": "2.5", "max_connections": "20"},
+        client=client,
+    )
+
+    assert result["socket_timeout"] == pytest.approx(5.5)
+    assert isinstance(result["socket_timeout"], float)
+    assert result["socket_connect_timeout"] == pytest.approx(2.5)
+    assert isinstance(result["socket_connect_timeout"], float)
+    assert result["max_connections"] == 20
+    assert isinstance(result["max_connections"], int)
+
+
+def test_coerce_invalid_socket_timeout_is_still_dropped():
+    """Garbage must not survive the explicit-type path; Redis falls back to its own default."""
+    result = _coerce_redis_kwargs_types({"socket_timeout": "not_a_number"}, client=_redis_signature_8x)
+
+    assert "socket_timeout" not in result
+
+
+def test_coerce_redis_kwargs_types_invalid_drops_key():
+    """A string that cannot be coerced to the expected numeric type is dropped."""
+    result = _coerce_redis_kwargs_types({"health_check_interval": "not_a_number"})
+    assert "health_check_interval" not in result
+
+
+def test_coerce_redis_kwargs_types_non_string_unchanged():
+    """Non-string values pass through without modification."""
+    result = _coerce_redis_kwargs_types({"health_check_interval": 30, "ssl": True})
+    assert result["health_check_interval"] == 30
+    assert result["ssl"] is True
+
+
+def test_health_check_interval_from_env_is_int(monkeypatch):
+    monkeypatch.setenv("REDIS_HOST", "localhost")
+    monkeypatch.setenv("REDIS_HEALTH_CHECK_INTERVAL", "30")
+
+    pool = get_redis_connection_pool()
+
+    assert pool is not None
+    interval = pool.connection_kwargs.get("health_check_interval")
+    assert interval == 30
+    assert isinstance(interval, int), f"Expected int, got {type(interval)}: {interval!r}"
+
+
+def _signature_without_defaults(testkey):
+    """Stand-in for a client whose parameter declares no default at all."""
+
+
+def _signature_with_float_default(myparam=1.0):
+    """Stand-in for a client whose parameter declares a float default."""
+
+
+def test_coerce_redis_kwargs_types_empty_default_param_unchanged():
+    """String params whose signature entry has no default (inspect.Parameter.empty) are left as-is."""
+    result = _coerce_redis_kwargs_types({"testkey": "some_value"}, client=_signature_without_defaults)
+
+    assert result["testkey"] == "some_value"
+    assert isinstance(result["testkey"], str)
+
+
+def test_coerce_redis_kwargs_types_float_valid():
+    """String values for params whose signature default is a float are coerced to float."""
+    result = _coerce_redis_kwargs_types({"myparam": "3.14"}, client=_signature_with_float_default)
+
+    assert result["myparam"] == pytest.approx(3.14)
+    assert isinstance(result["myparam"], float)
+
+
+def test_coerce_redis_kwargs_types_float_invalid_drops_key():
+    """An unconvertible string for a float-default param is dropped from the result."""
+    result = _coerce_redis_kwargs_types({"myparam": "not_a_float"}, client=_signature_with_float_default)
+
+    assert "myparam" not in result
+
+
+@pytest.mark.parametrize(
+    ("raw", "expected"),
+    [("false", False), ("true", True), ("0", False), ("1", True)],
+)
+def test_coerce_socket_keepalive_string(raw, expected):
+    """socket_keepalive's signature default is None, so it needs an explicit bool
+    coercion: a leftover "false" string is truthy and enables keepalive."""
+    result = _coerce_redis_kwargs_types({"socket_keepalive": raw})
+
+    assert result["socket_keepalive"] is expected
+
+
+def test_get_redis_client_logic_coerces_cluster_only_kwargs(monkeypatch):
+    """Cluster-only kwargs (absent from redis.Redis's signature) must still be
+    coerced when routing to a cluster, or Helm-stringified values reach
+    RedisCluster as strings."""
+    for envvar in (*_get_redis_env_kwarg_mapping(), "REDIS_CLUSTER_NODES", "REDIS_SENTINEL_NODES"):
+        monkeypatch.delenv(envvar, raising=False)
+
+    result = _get_redis_client_logic(
+        startup_nodes='[{"host": "localhost", "port": 7000}]',
+        cluster_error_retry_attempts="5",
+        require_full_coverage="false",
+        health_check_interval="30",
+    )
+
+    assert result["cluster_error_retry_attempts"] == 5
+    assert isinstance(result["cluster_error_retry_attempts"], int)
+    assert result["require_full_coverage"] is False
+    assert result["health_check_interval"] == 30
+    assert isinstance(result["health_check_interval"], int)
+
+
+def test_get_redis_client_logic_raises_without_host_or_url(monkeypatch):
+    """_get_redis_client_logic raises ValueError when neither host nor url is provided."""
+    for envvar in (*_get_redis_env_kwarg_mapping(), "REDIS_CLUSTER_NODES", "REDIS_SENTINEL_NODES"):
+        monkeypatch.delenv(envvar, raising=False)
+
+    with pytest.raises(ValueError, match="Either 'host' or 'url' must be specified for redis"):
+        _get_redis_client_logic()
diff --git a/tests/test_litellm/containers/test_container_api.py b/tests/test_litellm/containers/test_container_api.py
index 885c4cd294a..16a3844431e 100644
--- a/tests/test_litellm/containers/test_container_api.py
+++ b/tests/test_litellm/containers/test_container_api.py
@@ -152,6 +152,42 @@ class TestContainerAPI:
             assert response.id == "cntr_async_123"
             assert response.name == "Async Test Container"
 
+    @pytest.mark.asyncio
+    async def test_acreate_container_encodes_router_model_id(self):
+        """
+        The async handler returns a coroutine, so the managed-ID encoding must run
+        after it resolves. Otherwise follow-up calls (retrieve/delete/files) lose the
+        deployment and fall back to global provider credentials.
+        """
+        upstream_response = ContainerObject(
+            id="cntr_upstream_123",
+            object="container",
+            created_at=1747857508,
+            status="running",
+            expires_after={"anchor": "last_active_at", "minutes": 20},
+            last_active_at=1747857508,
+            name="Routed Container",
+        )
+
+        async def _resolve_upstream():
+            return upstream_response
+
+        with patch.object(  # test-quality-ok: create_container exposes no client seam, only the handler
+            base_llm_http_handler,
+            "container_create_handler",
+            side_effect=lambda **kwargs: _resolve_upstream() if kwargs["_is_async"] else upstream_response,
+        ):
+            response = await acreate_container(
+                name="Routed Container",
+                custom_llm_provider="openai",
+                litellm_metadata={"model_info": {"id": "deployment-abc"}},
+            )
+
+        decoded = ResponsesAPIRequestUtils._decode_container_id(response.id)
+        assert decoded["model_id"] == "deployment-abc"
+        assert decoded["custom_llm_provider"] == "openai"
+        assert decoded["response_id"] == "cntr_upstream_123"
+
     @pytest.mark.asyncio
     async def test_alist_containers_basic(self):
         """Test basic async container listing functionality."""
diff --git a/tests/test_litellm/endpoints/__init__.py b/tests/test_litellm/endpoints/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/endpoints/speech/__init__.py b/tests/test_litellm/endpoints/speech/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/endpoints/speech/speech_to_completion_bridge/__init__.py b/tests/test_litellm/endpoints/speech/speech_to_completion_bridge/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/endpoints/speech/speech_to_completion_bridge/test_transformation.py b/tests/test_litellm/endpoints/speech/speech_to_completion_bridge/test_transformation.py
new file mode 100644
index 00000000000..953f028af3c
--- /dev/null
+++ b/tests/test_litellm/endpoints/speech/speech_to_completion_bridge/test_transformation.py
@@ -0,0 +1,117 @@
+import base64
+from typing import Final
+from unittest.mock import MagicMock
+
+import pytest
+
+import litellm
+from litellm.constants import OPENAI_CHAT_COMPLETION_PARAMS
+from litellm.endpoints.speech.speech_to_completion_bridge.transformation import (
+    SpeechToCompletionBridgeTransformationHandler,
+)
+from litellm.types.utils import ChatCompletionAudioResponse, Choices, Message, ModelResponse
+
+GEMINI_TTS_MODEL: Final = "gemini-3.1-flash-tts-preview"
+PCM_BYTES: Final = b"\x01\x02\x03\x04" * 6
+
+
+def _model_response(model: str, pcm: bytes) -> ModelResponse:
+    audio: Final = ChatCompletionAudioResponse(
+        data=base64.b64encode(pcm).decode(), expires_at=0, transcript="hello"
+    )
+    return ModelResponse(model=model, choices=[Choices(message=Message(content=None, audio=audio))])
+
+
+def _bridge_request(response_format: str | None) -> dict:
+    optional_params: Final = (
+        {"temperature": 0.4} if response_format is None else {"temperature": 0.4, "response_format": response_format}
+    )
+    return SpeechToCompletionBridgeTransformationHandler().transform_request(
+        model=GEMINI_TTS_MODEL,
+        input="Hello from LiteLLM",
+        voice="Kore",
+        optional_params=optional_params,
+        litellm_params={},
+        headers={},
+        litellm_logging_obj=MagicMock(),
+        custom_llm_provider="gemini",
+    )
+
+
+@pytest.mark.parametrize("response_format", ["wav", "pcm", None])
+def test_gemini_tts_request_keeps_speech_response_format_out_of_chat_params(response_format: str | None) -> None:
+    request: Final = _bridge_request(response_format)
+
+    assert "response_format" not in request
+    assert request["audio"] == {"voice": "Kore", "format": "pcm16"}
+    assert request["temperature"] == 0.4
+    assert request["modalities"] == ["audio"]
+
+    gemini_params: Final = litellm.get_optional_params(
+        model=GEMINI_TTS_MODEL,
+        custom_llm_provider="gemini",
+        **{param: value for param, value in request.items() if param in OPENAI_CHAT_COMPLETION_PARAMS},
+    )
+    assert gemini_params["speechConfig"] == {"voiceConfig": {"prebuiltVoiceConfig": {"voiceName": "Kore"}}}
+    assert "responseMimeType" not in gemini_params
+
+
+def test_non_gemini_request_forwards_speech_response_format_as_audio_format() -> None:
+    request: Final = SpeechToCompletionBridgeTransformationHandler().transform_request(
+        model="gpt-4o-audio-preview",
+        input="Hello from LiteLLM",
+        voice="alloy",
+        optional_params={"response_format": "wav"},
+        litellm_params={},
+        headers={},
+        litellm_logging_obj=MagicMock(),
+        custom_llm_provider="openai",
+    )
+
+    assert "response_format" not in request
+    assert request["audio"] == {"voice": "alloy", "format": "wav"}
+
+
+@pytest.mark.parametrize("response_format", ["mp3", "flac", "opus", "aac"])
+def test_gemini_tts_request_rejects_formats_gemini_cannot_produce(response_format: str) -> None:
+    with pytest.raises(litellm.BadRequestError) as excinfo:
+        _bridge_request(response_format)
+
+    assert excinfo.value.status_code == 400
+    assert response_format in str(excinfo.value)
+    assert "pcm" in str(excinfo.value)
+    assert "wav" in str(excinfo.value)
+
+
+def test_gemini_tts_pcm_response_returns_raw_pcm_bytes() -> None:
+    response: Final = SpeechToCompletionBridgeTransformationHandler().transform_response(
+        model_response=_model_response(GEMINI_TTS_MODEL, PCM_BYTES),
+        response_format="pcm",
+    )
+
+    assert response.response.content == PCM_BYTES
+    assert response.response.headers["content-type"] == "audio/pcm"
+
+
+@pytest.mark.parametrize("response_format", ["wav", None])
+def test_gemini_tts_wav_and_default_responses_wrap_pcm_in_wav(response_format: str | None) -> None:
+    response: Final = SpeechToCompletionBridgeTransformationHandler().transform_response(
+        model_response=_model_response(GEMINI_TTS_MODEL, PCM_BYTES),
+        response_format=response_format,
+    )
+
+    body: Final = response.response.content
+    assert body[:4] == b"RIFF"
+    assert body[8:12] == b"WAVE"
+    assert body[44:] == PCM_BYTES
+    assert response.response.headers["content-type"] == "audio/wav"
+
+
+def test_non_gemini_response_keeps_original_bytes_and_mpeg_content_type() -> None:
+    response: Final = SpeechToCompletionBridgeTransformationHandler().transform_response(
+        model_response=_model_response("gpt-4o-audio-preview", PCM_BYTES),
+        response_format="mp3",
+    )
+
+    assert response.response.content == PCM_BYTES
+    assert response.response.headers["content-type"] == "audio/mpeg"
diff --git a/tests/test_litellm/experimental_mcp_client/test_tools.py b/tests/test_litellm/experimental_mcp_client/test_tools.py
index 89f67452f29..6645b06664d 100644
--- a/tests/test_litellm/experimental_mcp_client/test_tools.py
+++ b/tests/test_litellm/experimental_mcp_client/test_tools.py
@@ -8,11 +8,13 @@ from mcp.types import (
     CallToolRequestParams,
     CallToolResult,
     ListToolsResult,
+    PaginatedRequestParams,
     TextContent,
 )
 from mcp.types import Tool as MCPTool
 
 from litellm.experimental_mcp_client.tools import (
+    list_tools_with_pagination,
     transform_mcp_tool_to_anthropic_tool,
     _get_function_arguments,
     _normalize_mcp_input_schema,
@@ -106,6 +108,134 @@ async def test_load_mcp_tools_openai_format(mock_session, mock_list_tools_result
     mock_session.list_tools.assert_called_once()
 
 
+@pytest.mark.asyncio()
+async def test_load_mcp_tools_follows_pagination(mock_session):
+    mock_session.list_tools.side_effect = [
+        ListToolsResult(
+            tools=[
+                MCPTool(name="tool_a", description="a", inputSchema={}),
+                MCPTool(name="tool_b", description="b", inputSchema={}),
+            ],
+            nextCursor="page-2",
+        ),
+        ListToolsResult(tools=[MCPTool(name="tool_c", description="c", inputSchema={})]),
+    ]
+    result = await load_mcp_tools(mock_session, format="mcp")
+    assert [tool.name for tool in result] == ["tool_a", "tool_b", "tool_c"]
+    assert mock_session.list_tools.call_count == 2
+    second_call_params = mock_session.list_tools.call_args_list[1].kwargs["params"]
+    assert isinstance(second_call_params, PaginatedRequestParams)
+    assert second_call_params.cursor == "page-2"
+
+
+@pytest.mark.asyncio()
+async def test_pagination_walk_stops_at_page_cap(mock_session, monkeypatch):
+    monkeypatch.setattr("litellm.experimental_mcp_client.tools.MCP_TOOL_LISTING_MAX_PAGES", 2)
+    mock_session.list_tools.side_effect = [
+        ListToolsResult(
+            tools=[MCPTool(name="tool_0", description="0", inputSchema={})],
+            nextCursor="page-2",
+        ),
+        ListToolsResult(
+            tools=[MCPTool(name="tool_1", description="1", inputSchema={})],
+            nextCursor="page-3",
+        ),
+        ListToolsResult(tools=[MCPTool(name="tool_2", description="2", inputSchema={})]),
+    ]
+    result = await list_tools_with_pagination(mock_session)
+    assert [tool.name for tool in result] == ["tool_0", "tool_1"]
+    assert mock_session.list_tools.call_count == 2
+
+
+@pytest.mark.asyncio()
+async def test_pagination_walk_stops_on_repeated_cursor(mock_session):
+    mock_session.list_tools.side_effect = [
+        ListToolsResult(
+            tools=[MCPTool(name="tool_0", description="0", inputSchema={})],
+            nextCursor="same-cursor",
+        ),
+        ListToolsResult(
+            tools=[MCPTool(name="tool_1", description="1", inputSchema={})],
+            nextCursor="same-cursor",
+        ),
+    ]
+    result = await list_tools_with_pagination(mock_session)
+    assert [tool.name for tool in result] == ["tool_0", "tool_1"]
+    assert mock_session.list_tools.call_count == 2
+
+
+@pytest.mark.asyncio()
+async def test_pagination_walk_treats_empty_cursor_as_terminal(mock_session):
+    mock_session.list_tools.side_effect = [
+        ListToolsResult(
+            tools=[MCPTool(name="tool_0", description="0", inputSchema={})],
+            nextCursor="",
+        ),
+    ]
+    result = await list_tools_with_pagination(mock_session)
+    assert [tool.name for tool in result] == ["tool_0"]
+    mock_session.list_tools.assert_called_once()
+
+
+@pytest.mark.asyncio()
+async def test_pagination_walk_stops_at_whole_walk_deadline(mock_session, monkeypatch):
+    import anyio
+
+    from litellm.experimental_mcp_client.tools import list_tools_with_pagination
+
+    monkeypatch.setattr("litellm.experimental_mcp_client.tools.MCP_CLIENT_TIMEOUT", 0.2)
+    monkeypatch.setattr("litellm.experimental_mcp_client.tools.MCP_TOOL_LISTING_TIMEOUT", 0.2)
+
+    async def slow_page(params=None):
+        await anyio.sleep(0.15)
+        idx = int(params.cursor) if params is not None else 0
+        return ListToolsResult(
+            tools=[MCPTool(name=f"tool_{idx}", description=str(idx), inputSchema={})],
+            nextCursor=str(idx + 1),
+        )
+
+    mock_session.list_tools = slow_page
+    result = await list_tools_with_pagination(mock_session)
+
+    assert [tool.name for tool in result] == ["tool_0"]
+
+
+@pytest.mark.asyncio()
+async def test_pagination_walk_honors_explicit_deadline_over_globals(mock_session, monkeypatch):
+    import anyio
+
+    from litellm.experimental_mcp_client.tools import list_tools_with_pagination
+
+    monkeypatch.setattr("litellm.experimental_mcp_client.tools.MCP_CLIENT_TIMEOUT", 0.1)
+    monkeypatch.setattr("litellm.experimental_mcp_client.tools.MCP_TOOL_LISTING_TIMEOUT", 0.1)
+
+    async def slow_page(params=None):
+        await anyio.sleep(0.15)
+        idx = int(params.cursor) if params is not None else 0
+        tools = [MCPTool(name=f"tool_{idx}", description=str(idx), inputSchema={})]
+        if idx == 0:
+            return ListToolsResult(tools=tools, nextCursor="1")
+        return ListToolsResult(tools=tools)
+
+    mock_session.list_tools = slow_page
+    result = await list_tools_with_pagination(mock_session, listing_deadline=2.0)
+
+    assert [tool.name for tool in result] == ["tool_0", "tool_1"]
+
+
+@pytest.mark.asyncio()
+async def test_load_mcp_tools_openai_format_spans_pages(mock_session):
+    mock_session.list_tools.side_effect = [
+        ListToolsResult(
+            tools=[MCPTool(name="tool_a", description="a", inputSchema={})],
+            nextCursor="page-2",
+        ),
+        ListToolsResult(tools=[MCPTool(name="tool_b", description="b", inputSchema={})]),
+    ]
+    result = await load_mcp_tools(mock_session, format="openai")
+    assert [t["function"]["name"] for t in result] == ["tool_a", "tool_b"]
+
+
 def test_get_function_arguments():
     # Test with string arguments
     function = {"arguments": '{"test": "value"}'}
diff --git a/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting.py b/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting.py
index cfbd3e76a88..55e2dcdc270 100644
--- a/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting.py
+++ b/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting.py
@@ -12,7 +12,7 @@ import litellm
 from litellm.caching.caching import DualCache
 from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting
 from litellm.proxy._types import CallInfo, Litellm_EntityType
-from litellm.types.integrations.slack_alerting import SlackAlertingCacheKeys
+from litellm.types.integrations.slack_alerting import AlertType, SlackAlertingCacheKeys
 
 
 class TestSlackAlerting(unittest.TestCase):
@@ -366,3 +366,56 @@ async def test_scheduled_daily_report_threads_the_pod_lock_manager_through():
 
     _, kwargs = slack_alerting._run_scheduler_helper.await_args
     assert kwargs["pod_lock_manager"] is pod_lock_manager
+
+
+def _slack_alerting_with_env_resolution() -> SlackAlerting:
+    slack_alerting: Final = SlackAlerting(alerting=["slack"], internal_usage_cache=DualCache())
+    slack_alerting.periodic_started = True
+    return slack_alerting
+
+
+@pytest.mark.asyncio
+async def test_send_alert_falls_back_to_alerting_webhook_url_env(monkeypatch):
+    monkeypatch.delenv("SLACK_WEBHOOK_URL", raising=False)
+    monkeypatch.setenv("ALERTING_WEBHOOK_URL", "https://chat.example.com/hooks/abc")
+    slack_alerting: Final = _slack_alerting_with_env_resolution()
+
+    await slack_alerting.send_alert(
+        message="budget crossed",
+        level="High",
+        alert_type=AlertType.budget_alerts,
+        alerting_metadata={},
+    )
+
+    assert slack_alerting.log_queue[0]["url"] == "https://chat.example.com/hooks/abc"
+
+
+@pytest.mark.asyncio
+async def test_send_alert_prefers_slack_webhook_url_over_fallback(monkeypatch):
+    monkeypatch.setenv("SLACK_WEBHOOK_URL", "https://hooks.slack.com/services/T0/B0/X0")
+    monkeypatch.setenv("ALERTING_WEBHOOK_URL", "https://chat.example.com/hooks/abc")
+    slack_alerting: Final = _slack_alerting_with_env_resolution()
+
+    await slack_alerting.send_alert(
+        message="budget crossed",
+        level="High",
+        alert_type=AlertType.budget_alerts,
+        alerting_metadata={},
+    )
+
+    assert slack_alerting.log_queue[0]["url"] == "https://hooks.slack.com/services/T0/B0/X0"
+
+
+@pytest.mark.asyncio
+async def test_send_alert_raises_when_no_webhook_url_configured(monkeypatch):
+    monkeypatch.delenv("SLACK_WEBHOOK_URL", raising=False)
+    monkeypatch.delenv("ALERTING_WEBHOOK_URL", raising=False)
+    slack_alerting: Final = _slack_alerting_with_env_resolution()
+
+    with pytest.raises(ValueError, match="SLACK_WEBHOOK_URL / ALERTING_WEBHOOK_URL"):
+        await slack_alerting.send_alert(
+            message="budget crossed",
+            level="High",
+            alert_type=AlertType.budget_alerts,
+            alerting_metadata={},
+        )
diff --git a/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting_digest.py b/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting_digest.py
index edce5c5f3a2..d614823c0ef 100644
--- a/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting_digest.py
+++ b/tests/test_litellm/integrations/SlackAlerting/test_slack_alerting_digest.py
@@ -79,6 +79,23 @@ class TestDigestMode(unittest.IsolatedAsyncioTestCase):
 
         self.assertEqual(len(self.slack_alerting.digest_buckets), 2)
 
+    async def test_digest_falls_back_to_alerting_webhook_url_env(self):
+        """With SLACK_WEBHOOK_URL unset, the digest entry resolves ALERTING_WEBHOOK_URL instead."""
+        env = {k: v for k, v in os.environ.items() if k != "SLACK_WEBHOOK_URL"}
+        env["ALERTING_WEBHOOK_URL"] = "https://chat.example.com/hooks/abc"
+        with unittest.mock.patch.dict(os.environ, env, clear=True):
+            await self.slack_alerting.send_alert(
+                message="`Requests are hanging`",
+                level="Medium",
+                alert_type=AlertType.llm_requests_hanging,
+                alerting_metadata={},
+                request_model="gemini-2.5-flash",
+                api_base="None",
+            )
+
+        bucket = list(self.slack_alerting.digest_buckets.values())[0]
+        self.assertEqual(bucket["webhook_url"], "https://chat.example.com/hooks/abc")
+
     async def test_non_digest_alert_goes_to_queue(self):
         """Alert types without digest enabled should go straight to the log queue."""
         message = "Budget exceeded"
diff --git a/tests/test_litellm/integrations/SlackAlerting/test_user_spend_alerts.py b/tests/test_litellm/integrations/SlackAlerting/test_user_spend_alerts.py
new file mode 100644
index 00000000000..45e1acecec8
--- /dev/null
+++ b/tests/test_litellm/integrations/SlackAlerting/test_user_spend_alerts.py
@@ -0,0 +1,193 @@
+import datetime
+from typing import Final
+from unittest.mock import AsyncMock, patch
+
+import pytest
+from pydantic import ValidationError
+
+from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting
+from litellm.integrations.SlackAlerting.user_spend_alerts import (
+    UserSpendRow,
+    evaluate_user_spend,
+)
+from litellm.types.integrations.slack_alerting import (
+    DEFAULT_ALERT_TYPES,
+    AlertType,
+    SlackAlertingArgs,
+)
+
+TODAY: Final = datetime.date(2026, 8, 15)
+
+
+def _row(
+    daily_spend: float = 0.0,
+    monthly_spend: float = 0.0,
+    baseline_spend: float = 0.0,
+) -> UserSpendRow:
+    return UserSpendRow(
+        user_id="user-1",
+        daily_spend=daily_spend,
+        monthly_spend=monthly_spend,
+        baseline_spend=baseline_spend,
+    )
+
+
+def _evaluate(row: UserSpendRow, args: SlackAlertingArgs, thresholds: bool = True, anomalies: bool = True):
+    return evaluate_user_spend(
+        row=row,
+        args=args,
+        today=TODAY,
+        thresholds_enabled=thresholds,
+        anomalies_enabled=anomalies,
+    )
+
+
+def test_daily_threshold_crossed():
+    args: Final = SlackAlertingArgs(daily_spend_per_user_threshold=50.0, spend_anomaly_min_spend=1000.0)
+    events: Final = _evaluate(_row(daily_spend=75.0, monthly_spend=75.0), args)
+    assert [e.kind for e in events] == ["daily_threshold"]
+    assert "`$75.00`" in events[0].message
+    assert "`$50.00`" in events[0].message
+    assert events[0].alert_type == AlertType.user_spend_thresholds
+    assert events[0].cache_key == "user_spend_alert_daily_user-1_2026-08-15"
+
+
+def test_daily_threshold_not_crossed():
+    args: Final = SlackAlertingArgs(daily_spend_per_user_threshold=50.0, spend_anomaly_min_spend=1000.0)
+    assert _evaluate(_row(daily_spend=49.99, monthly_spend=49.99), args) == ()
+
+
+def test_thresholds_unset_by_default():
+    args: Final = SlackAlertingArgs(spend_anomaly_min_spend=1000.0)
+    assert _evaluate(_row(daily_spend=999.0, monthly_spend=999.0), args) == ()
+
+
+def test_monthly_threshold_crossed():
+    args: Final = SlackAlertingArgs(monthly_spend_per_user_threshold=200.0, spend_anomaly_min_spend=1000.0)
+    events: Final = _evaluate(_row(daily_spend=5.0, monthly_spend=250.0), args)
+    assert [e.kind for e in events] == ["monthly_threshold"]
+    assert events[0].cache_key == "user_spend_alert_monthly_user-1_2026-08"
+
+
+def test_thresholds_disabled_suppresses_threshold_events():
+    args: Final = SlackAlertingArgs(
+        daily_spend_per_user_threshold=50.0,
+        monthly_spend_per_user_threshold=200.0,
+        spend_anomaly_min_spend=1000.0,
+    )
+    assert _evaluate(_row(daily_spend=75.0, monthly_spend=250.0), args, thresholds=False) == ()
+
+
+def test_anomaly_detected_above_multiple_of_baseline():
+    args: Final = SlackAlertingArgs(spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0)
+    events: Final = _evaluate(
+        _row(daily_spend=70.0, monthly_spend=100.0, baseline_spend=70.0), args
+    )
+    assert [e.kind for e in events] == ["anomaly"]
+    assert events[0].alert_type == AlertType.user_spend_anomalies
+    assert "`$10.00`" in events[0].message
+    assert events[0].cache_key == "user_spend_alert_anomaly_user-1_2026-08-15"
+
+
+def test_no_anomaly_within_baseline_multiple():
+    args: Final = SlackAlertingArgs(spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0)
+    assert (
+        _evaluate(_row(daily_spend=25.0, monthly_spend=100.0, baseline_spend=70.0), args) == ()
+    )
+
+
+def test_no_anomaly_below_min_spend_floor():
+    args: Final = SlackAlertingArgs(spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0)
+    assert _evaluate(_row(daily_spend=9.0, monthly_spend=9.0, baseline_spend=0.1), args) == ()
+
+
+def test_anomaly_for_new_user_without_baseline():
+    args: Final = SlackAlertingArgs(spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0)
+    events: Final = _evaluate(_row(daily_spend=15.0, monthly_spend=15.0), args)
+    assert [e.kind for e in events] == ["anomaly"]
+
+
+def test_sparse_baseline_averages_over_full_window():
+    args: Final = SlackAlertingArgs(
+        spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0, spend_anomaly_baseline_days=7
+    )
+    events: Final = _evaluate(_row(daily_spend=13.0, monthly_spend=20.0, baseline_spend=7.0), args)
+    assert [e.kind for e in events] == ["anomaly"]
+
+
+def test_anomalies_not_in_default_alert_types():
+    assert AlertType.user_spend_anomalies not in DEFAULT_ALERT_TYPES
+    assert AlertType.user_spend_thresholds in DEFAULT_ALERT_TYPES
+
+
+def test_invalid_config_rejected():
+    with pytest.raises(ValidationError, match="daily_spend_per_user_threshold"):
+        SlackAlertingArgs(daily_spend_per_user_threshold=0)
+    with pytest.raises(ValidationError, match="spend_anomaly_baseline_days"):
+        SlackAlertingArgs(spend_anomaly_baseline_days=0)
+    with pytest.raises(ValidationError, match="user_spend_check_interval"):
+        SlackAlertingArgs(user_spend_check_interval=10)
+
+
+def test_non_finite_config_rejected():
+    with pytest.raises(ValidationError, match="daily_spend_per_user_threshold"):
+        SlackAlertingArgs(daily_spend_per_user_threshold=float("inf"))
+    with pytest.raises(ValidationError, match="spend_anomaly_multiplier"):
+        SlackAlertingArgs(spend_anomaly_multiplier=float("nan"))
+    with pytest.raises(ValidationError, match="spend_anomaly_min_spend"):
+        SlackAlertingArgs(spend_anomaly_min_spend=float("inf"))
+    with pytest.raises(ValidationError, match="user_spend_check_interval"):
+        SlackAlertingArgs(user_spend_check_interval=float("inf"))
+
+
+def test_anomalies_disabled_suppresses_anomaly_events():
+    args: Final = SlackAlertingArgs(spend_anomaly_multiplier=3.0, spend_anomaly_min_spend=10.0)
+    assert _evaluate(_row(daily_spend=500.0, monthly_spend=500.0), args, anomalies=False) == ()
+
+
+@pytest.mark.asyncio
+async def test_send_user_spend_alerts_sends_and_dedupes():
+    slack_alerting: Final = SlackAlerting(
+        alerting=["slack"],
+        alerting_args={"daily_spend_per_user_threshold": 50.0, "spend_anomaly_min_spend": 1000.0},
+    )
+    mock_prisma: Final = AsyncMock()
+    mock_prisma.db.query_raw = AsyncMock(
+        return_value=[
+            {
+                "user_id": "user-1",
+                "daily_spend": 75.0,
+                "monthly_spend": 75.0,
+                "baseline_spend": 0.0,
+            },
+            {
+                "user_id": "user-2",
+                "daily_spend": 60.0,
+                "monthly_spend": 60.0,
+                "baseline_spend": 0.0,
+            },
+        ]
+    )
+    with patch.object(slack_alerting, "send_alert", new_callable=AsyncMock) as mock_send_alert:
+        await slack_alerting.send_user_spend_alerts(prisma_client=mock_prisma)
+        assert mock_send_alert.call_count == 1
+        sent_kwargs: Final = mock_send_alert.call_args.kwargs
+        assert sent_kwargs["alert_type"] == AlertType.user_spend_thresholds
+        assert "User Daily Spend Threshold Crossed" in sent_kwargs["message"]
+        assert "`user-1`" in sent_kwargs["message"]
+        assert "`user-2`" in sent_kwargs["message"]
+
+        await slack_alerting.send_user_spend_alerts(prisma_client=mock_prisma)
+        assert mock_send_alert.call_count == 1
+
+
+@pytest.mark.asyncio
+async def test_send_user_spend_alerts_noop_when_alert_types_disabled():
+    slack_alerting: Final = SlackAlerting(
+        alerting=["slack"],
+        alert_types=[AlertType.budget_alerts],
+        alerting_args={"daily_spend_per_user_threshold": 50.0},
+    )
+    mock_prisma: Final = AsyncMock()
+    await slack_alerting.send_user_spend_alerts(prisma_client=mock_prisma)
+    mock_prisma.db.query_raw.assert_not_called()
diff --git a/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py b/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py
new file mode 100644
index 00000000000..2d0605e3b7f
--- /dev/null
+++ b/tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py
@@ -0,0 +1,469 @@
+"""
+Regression tests for the Datadog LLM Observability payload schema (issue #35786).
+
+Datadog renders tool calls, tool results and prompt-cache savings only from the fields its
+own schema names. These assert on the payload `create_llm_obs_payload` actually hands the
+intake, so a regression that moves data back into `meta.metadata` fails here.
+
+Fixtures mirror what a live proxy run recorded on the callback, including the provider
+spelling of prompt-cache counts (`prompt_tokens_details.cached_tokens`).
+"""
+
+import json
+import os
+from datetime import datetime, timedelta
+from typing import Any
+from unittest.mock import patch
+
+import pytest
+
+from litellm.integrations.datadog.datadog_llm_obs import DataDogLLMObsLogger
+from litellm.litellm_core_utils.safe_json_dumps import safe_dumps
+
+TOOL_DEFINITION: dict[str, Any] = {
+    "type": "function",
+    "function": {
+        "name": "get_weather",
+        "description": "Get current weather for a city",
+        "parameters": {
+            "type": "object",
+            "properties": {"city": {"type": "string"}},
+            "required": ["city"],
+        },
+    },
+}
+
+ASSISTANT_TOOL_CALL: dict[str, Any] = {
+    "id": "call_abc123",
+    "type": "function",
+    "function": {"name": "get_weather", "arguments": '{"city":"Paris","unit":"c"}'},
+}
+
+
+@pytest.fixture
+def logger() -> DataDogLLMObsLogger:
+    with patch.dict(os.environ, {"DD_API_KEY": "k", "DD_SITE": "us5.datadoghq.com"}, clear=True):
+        with patch("asyncio.create_task"):
+            return DataDogLLMObsLogger()
+
+
+NOT_GIVEN: Any = object()
+
+
+def build_payload(
+    messages: Any = NOT_GIVEN,
+    response_message: dict[str, Any] | None = None,
+    usage_object: dict[str, Any] | None = None,
+    model_parameters: dict[str, Any] | None = None,
+    prompt_tokens: int = 4447,
+) -> dict[str, Any]:
+    return {
+        "standard_logging_object": {
+            "call_type": "acompletion",
+            "messages": [{"role": "user", "content": "hi"}] if messages is NOT_GIVEN else messages,
+            "response": {"choices": [{"message": response_message or {"role": "assistant", "content": "hello"}}]},
+            "model_parameters": model_parameters or {},
+            "metadata": {"usage_object": usage_object} if usage_object is not None else {},
+            "prompt_tokens": prompt_tokens,
+            "completion_tokens": 507,
+            "total_tokens": prompt_tokens + 507,
+            "response_cost": 0.02,
+            "status": "success",
+        },
+        "litellm_params": {"metadata": {}},
+    }
+
+
+def build(logger: DataDogLLMObsLogger, **kwargs: Any) -> dict[str, Any]:
+    """Build a span and read it back as the JSON the intake receives, not as Python objects."""
+    start = datetime(2026, 9, 1, 12, 0, 0)
+    payload = logger.create_llm_obs_payload(build_payload(**kwargs), start, start + timedelta(seconds=2))
+    return json.loads(safe_dumps(payload))
+
+
+def test_output_tool_calls_use_the_datadog_tool_call_schema(logger: DataDogLLMObsLogger) -> None:
+    """Datadog reads name/arguments/tool_id off the tool call; OpenAI nests them under `function`."""
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+    )
+
+    message = payload["meta"]["output"]["messages"][0]
+    assert message["tool_calls"] == [
+        {
+            "name": "get_weather",
+            "arguments": {"city": "Paris", "unit": "c"},
+            "tool_id": "call_abc123",
+            "type": "function",
+        }
+    ]
+    assert "function" not in message["tool_calls"][0]
+
+
+def test_tool_calls_are_not_duplicated_into_metadata(logger: DataDogLLMObsLogger) -> None:
+    """The flat `output_tool_calls.*` keys were a second copy of a fact that now has its own field."""
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+    )
+
+    assert [key for key in payload["meta"]["metadata"] if "tool_calls." in key] == []
+
+
+def test_tool_result_message_links_back_to_its_tool_call(logger: DataDogLLMObsLogger) -> None:
+    """Datadog pairs a result with its call through tool_id, and names the tool from the call."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": "Weather in Paris?"},
+            {"role": "assistant", "content": None, "tool_calls": [ASSISTANT_TOOL_CALL]},
+            {"role": "tool", "tool_call_id": "call_abc123", "content": '{"temp_c": 18}'},
+        ],
+    )
+
+    tool_message = payload["meta"]["input"]["messages"][2]
+    assert tool_message["tool_results"] == [
+        {"name": "get_weather", "result": '{"temp_c": 18}', "tool_id": "call_abc123", "type": "function"}
+    ]
+
+
+def test_tool_result_without_a_matching_call_still_reports_its_id(logger: DataDogLLMObsLogger) -> None:
+    """A truncated conversation loses the call, so the name is unknown but the link must survive."""
+    payload = build(
+        logger,
+        messages=[{"role": "tool", "tool_call_id": "call_orphan", "content": "42"}],
+    )
+
+    assert payload["meta"]["input"]["messages"][0]["tool_results"] == [
+        {"name": "", "result": "42", "tool_id": "call_orphan", "type": "function"}
+    ]
+
+
+def test_cache_tokens_are_reported_as_span_metrics(logger: DataDogLLMObsLogger) -> None:
+    """
+    Datadog charts cache savings from span metrics; nested usage_object is not read for it.
+
+    litellm's normalized prompt count includes both cache categories, so the three cache
+    metrics must partition input_tokens: read + write + non_cached == input.
+    """
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"cached_tokens": 4300, "cache_write_tokens": 95}},
+    )
+
+    metrics = payload["metrics"]
+    assert metrics["cache_read_input_tokens"] == 4300.0
+    assert metrics["cache_write_input_tokens"] == 95.0
+    assert metrics["non_cached_input_tokens"] == 4447.0 - 4300.0 - 95.0
+    assert (
+        metrics["cache_read_input_tokens"] + metrics["cache_write_input_tokens"] + metrics["non_cached_input_tokens"]
+        == metrics["input_tokens"]
+    )
+
+
+def test_cache_write_tokens_are_not_counted_as_non_cached(logger: DataDogLLMObsLogger) -> None:
+    """A cache-priming request must not report its primed prefix as full-price uncached input."""
+    payload = build(logger, usage_object={"prompt_tokens_details": {"cache_write_tokens": 4000}})
+
+    assert payload["metrics"]["cache_write_input_tokens"] == 4000.0
+    assert payload["metrics"]["non_cached_input_tokens"] == 4447.0 - 4000.0
+    assert "cache_read_input_tokens" not in payload["metrics"]
+
+
+def test_a_fully_cached_request_reports_a_zero_non_cached_count(logger: DataDogLLMObsLogger) -> None:
+    """Zero residual is real data: everything was served from cache. Inconsistent counts clamp to it."""
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"cached_tokens": 4352, "cache_write_tokens": 95}},
+    )
+
+    assert payload["metrics"]["non_cached_input_tokens"] == 0.0
+
+
+def test_anthropic_top_level_cache_keys_are_read(logger: DataDogLLMObsLogger) -> None:
+    """A raw Anthropic usage dict records the counts top level, not under prompt_tokens_details."""
+    payload = build(
+        logger,
+        usage_object={"cache_read_input_tokens": 4300, "cache_creation_input_tokens": 95},
+    )
+
+    metrics = payload["metrics"]
+    assert metrics["cache_read_input_tokens"] == 4300.0
+    assert metrics["cache_write_input_tokens"] == 95.0
+    assert metrics["non_cached_input_tokens"] == 4447.0 - 4300.0 - 95.0
+
+
+def test_cache_metrics_come_from_the_normalized_field_not_the_anthropic_one(logger: DataDogLLMObsLogger) -> None:
+    """
+    litellm normalizes every provider's cache counters into prompt_tokens_details.
+
+    A real cached request from a non-Anthropic provider carries only `cached_tokens`, so
+    reading the Anthropic-specific `cache_read_input_tokens` key reports nothing for it.
+    """
+    payload = build(
+        logger,
+        usage_object={"prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 4096}},
+        prompt_tokens=4335,
+    )
+
+    assert payload["metrics"]["cache_read_input_tokens"] == 4096.0
+    assert payload["metrics"]["non_cached_input_tokens"] == 4335.0 - 4096.0
+
+
+@pytest.mark.parametrize(
+    "usage_object",
+    [
+        {"prompt_tokens_details": {"cache_write_tokens": 95}},
+        {"prompt_tokens_details": {"cache_creation_tokens": 95}},
+        {"cache_creation_input_tokens": 95},
+    ],
+)
+def test_every_spelling_of_cache_write_tokens_is_read(
+    logger: DataDogLLMObsLogger, usage_object: dict[str, Any]
+) -> None:
+    """A raw usage dict that bypassed litellm's normalizer can carry any provider's spelling."""
+    payload = build(logger, usage_object=usage_object)
+
+    assert payload["metrics"]["cache_write_input_tokens"] == 95.0
+
+
+def test_a_cache_read_does_not_emit_a_zero_cache_write(logger: DataDogLLMObsLogger) -> None:
+    """A zero write on every cache-read span would drag Datadog's cache-write average to nothing."""
+    payload = build(logger, usage_object={"prompt_tokens_details": {"cached_tokens": 4096}})
+
+    assert payload["metrics"]["cache_read_input_tokens"] == 4096.0
+    assert "cache_write_input_tokens" not in payload["metrics"]
+
+
+def test_no_cache_keys_when_the_provider_reports_no_caching(logger: DataDogLLMObsLogger) -> None:
+    """An uncached request must not gain zero-valued cache metrics that dilute cache dashboards."""
+    payload = build(logger, usage_object={"prompt_tokens_details": None})
+
+    assert "cache_read_input_tokens" not in payload["metrics"]
+    assert "cache_write_input_tokens" not in payload["metrics"]
+    assert "non_cached_input_tokens" not in payload["metrics"]
+
+
+def test_tool_definitions_are_sent_on_meta(logger: DataDogLLMObsLogger) -> None:
+    payload = build(logger, model_parameters={"tools": [TOOL_DEFINITION]})
+
+    assert payload["meta"]["tool_definitions"] == [
+        {
+            "name": "get_weather",
+            "description": "Get current weather for a city",
+            "schema": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]},
+        }
+    ]
+
+
+def test_tool_definitions_accept_the_bare_anthropic_shape(logger: DataDogLLMObsLogger) -> None:
+    """The Anthropic surface declares tools unwrapped, with input_schema instead of parameters."""
+    payload = build(
+        logger,
+        model_parameters={"tools": [{"name": "get_weather", "description": "d", "input_schema": {"type": "object"}}]},
+    )
+
+    assert payload["meta"]["tool_definitions"] == [
+        {"name": "get_weather", "description": "d", "schema": {"type": "object"}}
+    ]
+
+
+def test_meta_omits_tool_definitions_when_no_tools_were_offered(logger: DataDogLLMObsLogger) -> None:
+    assert "tool_definitions" not in build(logger)["meta"]
+
+
+def test_unparseable_tool_arguments_are_preserved_rather_than_dropped(logger: DataDogLLMObsLogger) -> None:
+    """A truncated argument string is still the only record of what the model tried to call."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": '{"city":'}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == '{"city":'
+
+
+def test_oversized_tool_arguments_ship_unparsed(logger: DataDogLLMObsLogger) -> None:
+    """
+    Decoding attacker-sized compact JSON multiplies memory for a span that is only logging.
+
+    This payload is perfectly valid JSON, so the only reason it arrives as a string is the
+    size bound; a smaller copy of the same shape comes back as an object below.
+    """
+    oversized = '{"a":"' + "x" * 300_000 + '"}'
+
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": oversized}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == oversized
+
+
+def test_valid_arguments_below_the_bound_still_parse(logger: DataDogLLMObsLogger) -> None:
+    """The size bound must not swallow ordinary arguments; this is the oversized test's control."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [
+                {"id": "c1", "type": "function", "function": {"name": "f", "arguments": '{"a":"' + "x" * 64 + '"}'}}
+            ],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == {"a": "x" * 64}
+
+
+def test_a_result_is_named_even_when_its_call_had_unparseable_arguments(logger: DataDogLLMObsLogger) -> None:
+    """Correlating a result to its call reads ids and names, so bad arguments cannot break linking."""
+    payload = build(
+        logger,
+        messages=[
+            {
+                "role": "assistant",
+                "content": None,
+                "tool_calls": [
+                    {"id": "call_abc123", "type": "function", "function": {"name": "get_weather", "arguments": "{"}}
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_abc123", "content": "18C"},
+        ],
+    )
+
+    assert payload["meta"]["input"]["messages"][1]["tool_results"] == [
+        {"name": "get_weather", "result": "18C", "tool_id": "call_abc123", "type": "function"}
+    ]
+
+
+def test_deeply_nested_tool_arguments_do_not_drop_the_span(logger: DataDogLLMObsLogger) -> None:
+    """json.loads raises RecursionError, not JSONDecodeError, on hostile nesting."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "[" * 50_000}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == "[" * 50_000
+
+
+def test_tool_arguments_that_parse_to_a_non_object_stay_a_string(logger: DataDogLLMObsLogger) -> None:
+    """Datadog types arguments as an object, so a bare JSON scalar must not land there as one."""
+    payload = build(
+        logger,
+        response_message={
+            "role": "assistant",
+            "content": None,
+            "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "f", "arguments": "42"}}],
+        },
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["tool_calls"][0]["arguments"] == "42"
+
+
+def test_a_tool_without_a_name_is_not_offered_as_a_definition(logger: DataDogLLMObsLogger) -> None:
+    """A nameless tool cannot be matched to a call, so it is dropped rather than sent blank."""
+    payload = build(logger, model_parameters={"tools": [{"function": {"description": "no name"}}, TOOL_DEFINITION]})
+
+    assert [tool["name"] for tool in payload["meta"]["tool_definitions"]] == ["get_weather"]
+
+
+def test_a_tool_definition_without_a_schema_omits_the_field(logger: DataDogLLMObsLogger) -> None:
+    """An empty schema object would read as a tool that takes no arguments, which is a different claim."""
+    payload = build(logger, model_parameters={"tools": [{"name": "ping", "description": "d"}]})
+
+    assert payload["meta"]["tool_definitions"] == [{"name": "ping", "description": "d"}]
+
+
+def test_a_non_dict_message_still_reaches_datadog(logger: DataDogLLMObsLogger) -> None:
+    """Callers can log arbitrary message payloads, and dropping the span over one loses the request."""
+    payload = build(logger, messages=["just a bare string"])
+
+    assert payload["meta"]["input"]["messages"] == [{"input": "just a bare string"}]
+
+
+def test_messages_logged_as_a_bare_string_still_reach_datadog(logger: DataDogLLMObsLogger) -> None:
+    payload = build(logger, messages="the whole prompt as one string")
+
+    assert payload["meta"]["input"]["messages"] == [{"input": "the whole prompt as one string"}]
+
+
+def test_non_chat_call_types_log_an_empty_input(logger: DataDogLLMObsLogger) -> None:
+    """Embedding and image calls carry no messages; fabricating an "None" turn misreads in Datadog."""
+    payload = build(logger, messages=None)
+
+    assert payload["meta"]["input"]["messages"] == []
+
+
+def test_anthropic_tool_blocks_map_to_tool_calls_and_results(logger: DataDogLLMObsLogger) -> None:
+    """/v1/messages carries tool traffic as content blocks, not OpenAI fields."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": [{"type": "text", "text": "Weather in Tokyo?"}]},
+            {
+                "role": "assistant",
+                "content": [{"type": "tool_use", "id": "toolu_1", "name": "get_weather", "input": {"city": "Tokyo"}}],
+            },
+            {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_1", "content": "18C"}]},
+        ],
+    )
+
+    assistant, result_turn = payload["meta"]["input"]["messages"][1:3]
+    assert assistant["tool_calls"] == [
+        {"name": "get_weather", "arguments": {"city": "Tokyo"}, "tool_id": "toolu_1", "type": "tool_use"}
+    ]
+    assert result_turn["tool_results"] == [
+        {"name": "get_weather", "result": "18C", "tool_id": "toolu_1", "type": "function"}
+    ]
+
+
+def test_content_with_no_text_parts_is_preserved_not_blanked(logger: DataDogLLMObsLogger) -> None:
+    """A content list the mapper does not understand must ride along, not be erased."""
+    blocks = [{"type": "image_url", "image_url": {"url": "https://example.com/x.png"}}]
+    payload = build(logger, messages=[{"role": "user", "content": blocks}])
+
+    assert payload["meta"]["input"]["messages"][0]["content"] == blocks
+
+
+def test_multimodal_content_parts_are_flattened_to_text(logger: DataDogLLMObsLogger) -> None:
+    """Datadog types Message.content as a string, so content lists collapse to their text."""
+    payload = build(
+        logger,
+        messages=[
+            {"role": "user", "content": [{"type": "text", "text": "describe "}, {"type": "text", "text": "this"}]}
+        ],
+    )
+
+    assert payload["meta"]["input"]["messages"][0]["content"] == "describe this"
+
+
+def test_mapping_input_messages_does_not_mutate_the_shared_payload(logger: DataDogLLMObsLogger) -> None:
+    """Sibling callbacks read the same messages list, so flattening must not write through it."""
+    messages: list[dict[str, Any]] = [{"role": "user", "content": [{"type": "text", "text": "hi"}]}]
+    kwargs = build_payload(messages=messages)
+    start = datetime(2026, 9, 1, 12, 0, 0)
+
+    logger.create_llm_obs_payload(kwargs, start, start + timedelta(seconds=1))
+
+    assert messages[0]["content"] == [{"type": "text", "text": "hi"}]
+
+
+def test_reasoning_content_survives_the_mapping(logger: DataDogLLMObsLogger) -> None:
+    payload = build(
+        logger,
+        response_message={"role": "assistant", "content": "answer", "reasoning_content": "thinking"},
+    )
+
+    assert payload["meta"]["output"]["messages"][0]["reasoning_content"] == "thinking"
diff --git a/tests/test_litellm/integrations/otel/test_langfuse_logger.py b/tests/test_litellm/integrations/otel/test_langfuse_logger.py
new file mode 100644
index 00000000000..8f93a9a564f
--- /dev/null
+++ b/tests/test_litellm/integrations/otel/test_langfuse_logger.py
@@ -0,0 +1,359 @@
+"""Tests for ``LangfuseOpenTelemetryV2``: the root observation's input and output are stamped from the
+request-task hooks, while the root span is still recording, so Langfuse can show them on the trace."""
+
+import asyncio
+import json
+from collections.abc import AsyncIterator, Sequence
+from typing import Final
+
+import pytest
+
+pytest.importorskip("opentelemetry")
+
+from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter  # noqa: E402
+
+import litellm  # noqa: E402
+from litellm.caching.dual_cache import DualCache  # noqa: E402
+from litellm.integrations.otel.logger import build_otel_v2_logger  # noqa: E402
+from litellm.integrations.otel.model.config import OpenTelemetryV2Config, is_otel_v2_enabled  # noqa: E402
+from litellm.integrations.otel.model.spans import LITELLM_PROXY_REQUEST_SPAN_NAME, SpanRole  # noqa: E402
+from litellm.integrations.otel.plumbing import context as otel_context  # noqa: E402
+from litellm.integrations.otel.plumbing import providers  # noqa: E402
+from litellm.integrations.otel.plumbing.context import set_request_root_span  # noqa: E402
+from litellm.litellm_core_utils.litellm_logging import _maybe_construct_otel_v2  # noqa: E402
+from litellm.proxy._types import UserAPIKeyAuth  # noqa: E402
+from litellm.proxy.utils import ProxyLogging  # noqa: E402
+from litellm.types.llms.openai import (  # noqa: E402
+    ResponseCompletedEvent,
+    ResponsesAPIResponse,
+    ResponsesAPIStreamEvents,
+)
+from litellm.types.utils import (  # noqa: E402
+    Choices,
+    Delta,
+    Embedding,
+    EmbeddingResponse,
+    Message,
+    ModelResponse,
+    ModelResponseStream,
+    StreamingChoices,
+)
+
+INPUT_ATTR: Final = "langfuse.observation.input"
+OUTPUT_ATTR: Final = "langfuse.observation.output"
+CHAT_DATA: Final = {"model": "gpt-5.4-mini", "messages": [{"role": "user", "content": "ping"}]}
+
+
+@pytest.fixture(autouse=True)
+def _reset_request_root_span():
+    otel_context._request_root_span.set(None)
+    yield
+    otel_context._request_root_span.set(None)
+
+
+def _logger(*, capture: str = "span_only", mappers: Sequence[str] = ("genai", "langfuse")):
+    cfg = OpenTelemetryV2Config(exporter="in_memory", mapper_names=list(mappers), capture_message_content=capture)
+    exporter = InMemorySpanExporter()
+    tracer_provider = providers.build_tracer_provider(cfg, exporter=exporter)
+    return build_otel_v2_logger(config=cfg, tracer_provider=tracer_provider), exporter
+
+
+def _start_root(logger):
+    root = logger._emitter.start_span(SpanRole.PROXY_REQUEST, LITELLM_PROXY_REQUEST_SPAN_NAME)
+    set_request_root_span(root)
+    return root
+
+
+def _root_attrs(exporter):
+    by_name = {span.name: span for span in exporter.get_finished_spans()}
+    return dict(by_name[LITELLM_PROXY_REQUEST_SPAN_NAME].attributes or {})
+
+
+def _run_request(logger, data: dict, call_type: str, response: object):
+    root = _start_root(logger)
+    asyncio.run(logger.async_pre_call_hook(UserAPIKeyAuth(), DualCache(), data, call_type))
+    asyncio.run(logger.async_post_call_success_hook(data=data, user_api_key_dict=UserAPIKeyAuth(), response=response))
+    root.end()
+
+
+async def _relay(logger, chunks: Sequence[object], data: dict) -> list[object]:
+    async def source() -> AsyncIterator[object]:
+        for chunk in chunks:
+            yield chunk
+
+    return [chunk async for chunk in logger.async_post_call_streaming_iterator_hook(UserAPIKeyAuth(), source(), data)]
+
+
+def _run_stream(logger, data: dict, chunks: Sequence[object]) -> list[object]:
+    root = _start_root(logger)
+    asyncio.run(logger.async_pre_call_hook(UserAPIKeyAuth(), DualCache(), data, "acompletion"))
+    relayed = asyncio.run(_relay(logger, chunks, data))
+    root.end()
+    return relayed
+
+
+def _chat_chunk(content: str | None, finish_reason: str | None = None) -> ModelResponseStream:
+    return ModelResponseStream(
+        id="chatcmpl-1",
+        created=1,
+        model="gpt-5.4-mini",
+        choices=[StreamingChoices(index=0, delta=Delta(content=content), finish_reason=finish_reason)],
+    )
+
+
+def _responses_api_response() -> ResponsesAPIResponse:
+    return ResponsesAPIResponse(
+        id="resp_1",
+        created_at=1,
+        output=[
+            {
+                "type": "message",
+                "id": "msg_1",
+                "status": "completed",
+                "role": "assistant",
+                "content": [{"type": "output_text", "text": "pong", "annotations": []}],
+            }
+        ],
+    )
+
+
+def _anthropic_sse_frames() -> tuple[bytes, ...]:
+    events = (
+        {
+            "type": "message_start",
+            "message": {
+                "id": "msg_1",
+                "type": "message",
+                "role": "assistant",
+                "model": "claude-sonnet-4-5",
+                "content": [],
+                "stop_reason": None,
+                "usage": {"input_tokens": 1, "output_tokens": 0},
+            },
+        },
+        {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}},
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "po"}},
+        {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "ng"}},
+        {"type": "content_block_stop", "index": 0},
+        {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 2}},
+        {"type": "message_stop"},
+    )
+    return tuple(f"event: {event['type']}\ndata: {json.dumps(event)}\n\n".encode() for event in events)
+
+
+def test_chat_request_stamps_root_observation_input_and_output():
+    logger, exporter = _logger()
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="pong"))])
+
+    _run_request(logger, CHAT_DATA, "acompletion", response)
+
+    attrs = _root_attrs(exporter)
+    assert json.loads(attrs[INPUT_ATTR]) == [{"role": "user", "content": "ping"}]
+    output = json.loads(attrs[OUTPUT_ATTR])
+    assert [(turn["role"], turn["content"]) for turn in output] == [("assistant", "pong")]
+
+
+def test_responses_request_folds_instructions_into_input_and_stamps_output_items():
+    logger, exporter = _logger()
+    data = {"model": "gpt-5.4-mini", "instructions": "be terse", "input": "ping"}
+
+    _run_request(logger, data, "aresponses", _responses_api_response())
+
+    attrs = _root_attrs(exporter)
+    assert json.loads(attrs[INPUT_ATTR]) == [
+        {"role": "system", "content": "be terse"},
+        {"role": "user", "content": "ping"},
+    ]
+    output = json.loads(attrs[OUTPUT_ATTR])
+    assert output[0]["role"] == "assistant"
+    assert output[0]["content"][0]["text"] == "pong"
+
+
+def test_anthropic_messages_request_folds_system_into_input_and_stamps_content_blocks():
+    logger, exporter = _logger()
+    data = {"model": "claude-sonnet-4-5", "system": "be terse", "messages": [{"role": "user", "content": "ping"}]}
+    response = {"type": "message", "role": "assistant", "content": [{"type": "text", "text": "pong"}]}
+
+    _run_request(logger, data, "aanthropic_messages", response)
+
+    attrs = _root_attrs(exporter)
+    assert json.loads(attrs[INPUT_ATTR]) == [
+        {"role": "system", "content": "be terse"},
+        {"role": "user", "content": "ping"},
+    ]
+    assert json.loads(attrs[OUTPUT_ATTR]) == [{"role": "assistant", "content": [{"type": "text", "text": "pong"}]}]
+
+
+def test_chat_stream_relays_chunks_untouched_and_stamps_assembled_output():
+    logger, exporter = _logger()
+    chunks = (_chat_chunk("po"), _chat_chunk("ng"), _chat_chunk(None, finish_reason="stop"))
+
+    relayed = _run_stream(logger, CHAT_DATA, chunks)
+
+    assert [id(chunk) for chunk in relayed] == [id(chunk) for chunk in chunks]
+    output = json.loads(_root_attrs(exporter)[OUTPUT_ATTR])
+    assert [(turn["role"], turn["content"]) for turn in output] == [("assistant", "pong")]
+
+
+def test_responses_stream_stamps_output_from_the_completed_event():
+    logger, exporter = _logger()
+    completed = ResponseCompletedEvent(
+        type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED, response=_responses_api_response()
+    )
+    chunks = ({"type": "response.created"}, {"type": "response.output_text.delta", "delta": "pong"}, completed)
+
+    relayed = _run_stream(logger, {"model": "gpt-5.4-mini", "input": "ping"}, chunks)
+
+    assert relayed == list(chunks)
+    output = json.loads(_root_attrs(exporter)[OUTPUT_ATTR])
+    assert output[0]["content"][0]["text"] == "pong"
+
+
+def test_anthropic_sse_stream_stamps_output_from_the_assembled_frames():
+    logger, exporter = _logger()
+    frames = _anthropic_sse_frames()
+
+    relayed = _run_stream(
+        logger, {"model": "claude-sonnet-4-5", "messages": [{"role": "user", "content": "ping"}]}, frames
+    )
+
+    assert relayed == list(frames)
+    output = json.loads(_root_attrs(exporter)[OUTPUT_ATTR])
+    assert [(turn["role"], turn["content"]) for turn in output] == [("assistant", "pong")]
+
+
+def test_root_observation_io_survives_the_root_ending_before_the_success_callback():
+    logger, exporter = _logger()
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="pong"))])
+    root = _start_root(logger)
+    asyncio.run(logger.async_pre_call_hook(UserAPIKeyAuth(), DualCache(), CHAT_DATA, "acompletion"))
+    logger.log_pre_api_call(
+        model="gpt-5.4-mini",
+        messages=[],
+        kwargs={"litellm_call_id": "call_1", "litellm_params": {"metadata": {}}},
+    )
+    asyncio.run(
+        logger.async_post_call_success_hook(data=CHAT_DATA, user_api_key_dict=UserAPIKeyAuth(), response=response)
+    )
+    root.end()
+
+    payload = {
+        "call_type": "acompletion",
+        "custom_llm_provider": "openai",
+        "model": "gpt-5.4-mini",
+        "messages": CHAT_DATA["messages"],
+        "response": response.model_dump(),
+        "status": "success",
+        "litellm_call_id": "call_1",
+        "metadata": {},
+        "hidden_params": {},
+    }
+    asyncio.run(
+        logger.async_log_success_event(
+            {"standard_logging_object": payload, "litellm_params": {"metadata": {}}}, response, None, None
+        )
+    )
+
+    attrs = _root_attrs(exporter)
+    assert INPUT_ATTR in attrs and OUTPUT_ATTR in attrs
+    generation = next(span for span in exporter.get_finished_spans() if span.name != LITELLM_PROXY_REQUEST_SPAN_NAME)
+    assert OUTPUT_ATTR in dict(generation.attributes or {})
+
+
+def test_root_input_is_the_request_as_the_pre_call_chain_left_it():
+    logger, exporter = _logger()
+    raw = {"model": "gpt-5.4-mini", "messages": [{"role": "user", "content": "my ssn is 123-45-6789"}]}
+    masked = {"model": "gpt-5.4-mini", "messages": [{"role": "user", "content": "my ssn is [REDACTED]"}]}
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="noted"))])
+    root = _start_root(logger)
+    asyncio.run(logger.async_pre_call_hook(UserAPIKeyAuth(), DualCache(), raw, "acompletion"))
+    asyncio.run(logger.async_post_call_success_hook(data=masked, user_api_key_dict=UserAPIKeyAuth(), response=response))
+    root.end()
+
+    assert json.loads(_root_attrs(exporter)[INPUT_ATTR]) == masked["messages"]
+
+
+def test_root_already_ended_is_left_alone():
+    logger, exporter = _logger()
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="pong"))])
+    root = _start_root(logger)
+    root.end()
+
+    asyncio.run(
+        logger.async_post_call_success_hook(data=CHAT_DATA, user_api_key_dict=UserAPIKeyAuth(), response=response)
+    )
+
+    attrs = _root_attrs(exporter)
+    assert INPUT_ATTR not in attrs and OUTPUT_ATTR not in attrs
+
+
+def test_responses_without_a_message_body_stamp_neither_input_nor_output():
+    logger, exporter = _logger()
+    embedding = EmbeddingResponse(model="e", data=[Embedding(embedding=[0.1], index=0, object="embedding")])
+
+    _run_request(logger, {"model": "e", "input": "ping"}, "aembedding", embedding)
+
+    attrs = _root_attrs(exporter)
+    assert INPUT_ATTR not in attrs and OUTPUT_ATTR not in attrs
+
+
+def test_unrenderable_output_never_raises_into_the_request():
+    logger, exporter = _logger()
+
+    _run_request(logger, CHAT_DATA, "acompletion", object())
+
+    attrs = _root_attrs(exporter)
+    assert INPUT_ATTR not in attrs and OUTPUT_ATTR not in attrs
+
+
+@pytest.mark.parametrize(
+    ("capture", "mappers"),
+    [("no_content", ("genai", "langfuse")), ("span_only", ("genai",))],
+)
+def test_factory_keeps_the_base_logger_unless_langfuse_content_capture_is_on(capture, mappers):
+    logger, exporter = _logger(capture=capture, mappers=mappers)
+
+    _run_request(logger, CHAT_DATA, "acompletion", ModelResponse())
+    attrs = _root_attrs(exporter)
+    assert INPUT_ATTR not in attrs and OUTPUT_ATTR not in attrs
+
+
+@pytest.mark.parametrize(
+    ("capture", "mappers", "relays_streams"),
+    [
+        ("span_only", ("genai", "langfuse"), True),
+        ("no_content", ("genai", "langfuse"), False),
+        ("span_only", ("genai",), False),
+    ],
+)
+def test_only_langfuse_content_capture_takes_proxy_streams_off_the_fast_path(
+    monkeypatch, capture, mappers, relays_streams
+):
+    logger, _ = _logger(capture=capture, mappers=mappers)
+    monkeypatch.setattr(litellm, "callbacks", [logger])
+
+    assert ProxyLogging._callback_capabilities().has_iterator_override is relays_streams
+
+
+def test_langfuse_otel_preset_builds_a_logger_that_stamps_the_root(monkeypatch):
+    monkeypatch.setenv("LITELLM_OTEL_V2", "true")
+    monkeypatch.setenv("LANGFUSE_PUBLIC_KEY", "pk")
+    monkeypatch.setenv("LANGFUSE_SECRET_KEY", "sk")
+    monkeypatch.setenv("LANGFUSE_HOST", "https://cloud.langfuse.com")
+    monkeypatch.setenv("OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT", "span_only")
+    is_otel_v2_enabled.cache_clear()
+
+    loggers: list = []
+    try:
+        built = _maybe_construct_otel_v2("langfuse_otel", loggers)
+        assert built is not None
+        assert _maybe_construct_otel_v2("langfuse_otel", loggers) is built
+        root = _start_root(built)
+        response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="pong"))])
+        asyncio.run(
+            built.async_post_call_success_hook(data=CHAT_DATA, user_api_key_dict=UserAPIKeyAuth(), response=response)
+        )
+        attrs = dict(root.attributes or {})
+        assert INPUT_ATTR in attrs and OUTPUT_ATTR in attrs
+    finally:
+        is_otel_v2_enabled.cache_clear()
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_components.py b/tests/test_litellm/integrations/otel/test_otel_v2_components.py
index 115e385eda4..4aa28b5abfd 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_components.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_components.py
@@ -3,6 +3,7 @@ baggage helpers, metrics, the typed coercion helpers, mapper branches, span-name
 builders, and the registry validator's failure paths. Needs the OTel SDK."""
 
 import json
+from dataclasses import replace
 
 import pytest
 
@@ -215,6 +216,27 @@ def test_genai_mapper_all_request_params():
     assert attrs["server.port"] == 443
 
 
+def test_genai_mapper_cache_token_attrs():
+    cached = replace(
+        _full_llm_call(),
+        usage=LLMUsage(
+            input_tokens=10,
+            output_tokens=5,
+            total_tokens=15,
+            cache_creation_input_tokens=7,
+            cache_read_input_tokens=3,
+        ),
+    )
+    attrs = GenAIMapper().map(cached)
+    assert attrs[GenAI.USAGE_CACHE_CREATION_INPUT_TOKENS] == 7
+    assert attrs[GenAI.USAGE_CACHE_READ_INPUT_TOKENS] == 3
+
+    # No cache usage keeps the span sparse: neither key present.
+    uncached = GenAIMapper().map(_full_llm_call())
+    assert GenAI.USAGE_CACHE_CREATION_INPUT_TOKENS not in uncached
+    assert GenAI.USAGE_CACHE_READ_INPUT_TOKENS not in uncached
+
+
 def test_genai_mapper_stamps_input_output_messages():
     data = LLMCallSpanData(
         operation=GenAIOperation.CHAT,
diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
index baa72b5a7fe..99d706a9c44 100644
--- a/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
+++ b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
@@ -525,6 +525,96 @@ def test_llm_call_adapter_extracts_all_fields():
     assert data.identity.key_hash == "hsh"
 
 
+def test_llm_call_adapter_extracts_cache_tokens_from_usage_object():
+    payload = _sample_payload()
+    payload["metadata"] = {
+        **payload["metadata"],
+        "usage_object": {
+            "prompt_tokens": 10,
+            "completion_tokens": 5,
+            "cache_creation_input_tokens": 7,
+            "cache_read_input_tokens": 3,
+        },
+    }
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_creation_input_tokens == 7
+    assert data.usage.cache_read_input_tokens == 3
+
+
+def test_llm_call_adapter_normalizes_nested_cache_tokens():
+    cases: Final = (
+        ({"prompt_tokens_details": {"cached_tokens": 3}}, 3, None),
+        ({"prompt_cache_hit_tokens": 11}, 11, None),
+        ({"prompt_tokens_details": {"cache_write_tokens": 7}}, None, 7),
+        ({"prompt_tokens_details": {"cache_creation_tokens": 13}}, None, 13),
+        ({"prompt_tokens_details": {"cache_creation_input_tokens": 17}}, None, 17),
+    )
+    for usage_object, expected_read, expected_creation in cases:
+        case_payload = _sample_payload(metadata={"usage_object": usage_object})
+        data = LLMCallSpanData.from_standard_logging_payload(case_payload)
+        assert data.usage.cache_read_input_tokens == expected_read
+        assert data.usage.cache_creation_input_tokens == expected_creation
+
+
+def test_llm_call_adapter_prefers_nested_count_over_zero_top_level():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "cache_read_input_tokens": 0,
+                "cache_creation_input_tokens": 0,
+                "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 7},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens == 5
+    assert data.usage.cache_creation_input_tokens == 7
+
+
+def test_llm_call_adapter_ignores_invalid_cache_values_before_valid_fallbacks():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "cache_read_input_tokens": -1,
+                "cache_creation_input_tokens": "5.0",
+                "prompt_tokens_details": {"cached_tokens": 5, "cache_write_tokens": 7},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens == 5
+    assert data.usage.cache_creation_input_tokens == 7
+
+
+def test_llm_call_adapter_ignores_non_finite_cache_values():
+    payload = _sample_payload(
+        metadata={
+            "usage_object": {
+                "prompt_tokens_details": {"cached_tokens": float("nan")},
+            }
+        }
+    )
+    data = LLMCallSpanData.from_standard_logging_payload(payload)
+    assert data.usage.cache_read_input_tokens is None
+
+
+def test_llm_call_adapter_preserves_explicit_zero_and_omits_missing_cache_tokens():
+    for usage_object, expected_read, expected_creation in (
+        ({"prompt_tokens_details": {"cached_tokens": 0}}, 0, None),
+        ({}, None, None),
+    ):
+        case_payload = _sample_payload(metadata={"usage_object": usage_object})
+        data = LLMCallSpanData.from_standard_logging_payload(case_payload)
+        assert data.usage.cache_read_input_tokens == expected_read
+        assert data.usage.cache_creation_input_tokens == expected_creation
+
+
+def test_llm_call_adapter_cache_tokens_none_without_usage_object():
+    data = LLMCallSpanData.from_standard_logging_payload(_sample_payload())
+    assert data.usage.cache_creation_input_tokens is None
+    assert data.usage.cache_read_input_tokens is None
+
+
 def test_llm_call_adapter_failure_path():
     payload = _sample_payload(
         status="failure",
diff --git a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
index e995cbae782..de8b654987b 100644
--- a/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
+++ b/tests/test_litellm/integrations/test_anthropic_cache_control_hook.py
@@ -2858,6 +2858,27 @@ class TestRecordGatewayInjection:
         AnthropicCacheControlHook.record_gateway_injection(kwargs, 0)
         assert kwargs["litellm_metadata"][self.KEY] == self.DEPLOYMENT
 
+    def test_an_every_deployment_mark_survives_a_later_per_deployment_stamp(self):
+        """A per-leg stamp like the Bedrock converse tool_config one describes one leg of
+        a payload every leg sends, so narrowing an every-deployment mark to that leg's
+        deployment would uncredit whichever leg gets billed after a failover."""
+        kwargs: dict = {"litellm_metadata": {self.KEY: ""}, "model_info": {"id": self.DEPLOYMENT}}
+        AnthropicCacheControlHook.record_gateway_injection(kwargs, 1)
+        assert kwargs["litellm_metadata"][self.KEY] == ""
+
+    def test_a_pre_choice_pass_stamps_the_sentinel_over_a_provisional_deployment(self):
+        """The router's prompt-management factory stamps a provisional deployment's
+        model_info into kwargs before the prompt pass runs, and any other deployment can
+        end up billed, so the pass declares every-deployment scope explicitly."""
+        kwargs: dict = {"litellm_metadata": {}, "model_info": {"id": self.DEPLOYMENT}}
+        AnthropicCacheControlHook.record_gateway_injection(kwargs, 1, injected_for_every_deployment=True)
+        assert kwargs["litellm_metadata"][self.KEY] == ""
+
+    def test_a_per_deployment_mark_still_follows_the_latest_leg(self):
+        kwargs: dict = {"litellm_metadata": {self.KEY: "dep-old"}, "model_info": {"id": self.DEPLOYMENT}}
+        AnthropicCacheControlHook.record_gateway_injection(kwargs, 1)
+        assert kwargs["litellm_metadata"][self.KEY] == self.DEPLOYMENT
+
     def test_v1_messages_auto_injection_stamps_the_marker(self, monkeypatch):
         monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)
         kwargs: dict = {"litellm_metadata": {}, "model_info": {"id": self.DEPLOYMENT}}
diff --git a/tests/test_litellm/integrations/test_custom_guardrail.py b/tests/test_litellm/integrations/test_custom_guardrail.py
index d978eb48c12..7d70b9a8862 100644
--- a/tests/test_litellm/integrations/test_custom_guardrail.py
+++ b/tests/test_litellm/integrations/test_custom_guardrail.py
@@ -2237,3 +2237,202 @@ class TestRecordsOwnGuardrailInformation:
         )
 
         assert _guardrail_entries(request_data) == []
+
+
+class _ApplyOnlyObserver(CustomGuardrail):
+    """Overrides only apply_guardrail, like panw_prisma_airs; inherits async_logging_hook."""
+
+    def __init__(self, block: bool = False):
+        from litellm.types.guardrails import GuardrailEventHooks
+
+        super().__init__(guardrail_name="apply-only-observer", event_hook=GuardrailEventHooks.logging_only)
+        self.block = block
+        self.calls: list = []
+
+    @log_guardrail_information
+    async def apply_guardrail(self, inputs, request_data, input_type, logging_obj=None):
+        from fastapi import HTTPException
+
+        self.calls.append((input_type, list(inputs.get("texts") or [])))
+        if self.block:
+            raise HTTPException(status_code=400, detail={"error": "flagged"})
+        return GenericGuardrailAPIInputs(texts=["[MASKED]" for _ in inputs.get("texts") or []])
+
+
+def _logged_call(messages: list | str) -> tuple[dict, object]:
+    from litellm.types.utils import Choices, Message, ModelResponse
+
+    response = ModelResponse(choices=[Choices(message=Message(role="assistant", content="general kenobi"))])
+    kwargs = {
+        "model": "gpt-5.4-mini",
+        "messages": messages,
+        "litellm_call_id": "call-1",
+        "litellm_params": {"metadata": {"user_api_key_user_id": "u1"}},
+        "optional_params": {},
+        "standard_logging_object": {"guardrail_information": None},
+    }
+    return kwargs, response
+
+
+class TestLoggingOnlyApplyGuardrail:
+    """LIT-4876 regression: a guardrail in mode logging_only that implements only
+    apply_guardrail must still run against the logged request and response and
+    record guardrail_information, instead of inheriting the CustomLogger no-op."""
+
+    @pytest.mark.asyncio
+    async def test_runs_apply_guardrail_observe_only_and_records_verdict(self):
+        guardrail = _ApplyOnlyObserver()
+        messages = [{"role": "user", "content": "hello there"}]
+        kwargs, response = _logged_call(messages)
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        assert out_kwargs["messages"] == [{"role": "user", "content": "hello there"}]
+        assert out_response.choices[0].message.content == "general kenobi"
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_name"] for e in entries] == ["apply-only-observer", "apply-only-observer"]
+        assert {e["guardrail_mode"] for e in entries} == {"logging_only"}
+        assert {e["guardrail_status"] for e in entries} == {"success"}
+        assert "standard_logging_guardrail_information" not in kwargs["litellm_params"]["metadata"]
+        assert kwargs["standard_logging_object"] == {"guardrail_information": None}
+
+    @pytest.mark.asyncio
+    async def test_appends_to_pre_call_verdicts_without_duplicating_them(self):
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+        pre_call_entry = {"guardrail_name": "pii-blocker", "guardrail_mode": "pre_call", "guardrail_status": "success"}
+        kwargs["litellm_params"]["metadata"]["standard_logging_guardrail_information"] = [pre_call_entry]
+        kwargs["standard_logging_object"]["guardrail_information"] = [pre_call_entry]
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_name"] for e in entries] == ["pii-blocker", "apply-only-observer", "apply-only-observer"]
+        assert kwargs["litellm_params"]["metadata"]["standard_logging_guardrail_information"] == [pre_call_entry]
+
+    @pytest.mark.asyncio
+    async def test_request_copy_failure_is_swallowed(self):
+        import threading
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there", "lock": threading.Lock()}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs is kwargs
+        assert out_response is response
+
+    @pytest.mark.asyncio
+    async def test_block_verdict_is_recorded_without_raising(self):
+        guardrail = _ApplyOnlyObserver(block=True)
+        kwargs, response = _logged_call([{"role": "user", "content": "flagged content"}])
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == [("request", ["flagged content"])]
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["guardrail_intervened"]
+
+    @pytest.mark.asyncio
+    async def test_call_type_without_translation_is_skipped(self):
+        guardrail = _ApplyOnlyObserver()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.amoderation.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs["standard_logging_object"]["guardrail_information"] is None
+
+    @pytest.mark.asyncio
+    async def test_aembedding_scans_logged_input(self):
+        from litellm.types.utils import EmbeddingResponse
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, _ = _logged_call("hello there")
+        response = EmbeddingResponse(data=[{"embedding": [0.1], "index": 0, "object": "embedding"}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.aembedding.value)
+
+        assert guardrail.calls == [("request", ["hello there"])]
+        assert out_kwargs["messages"] == "hello there"
+        assert out_response is response
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success"]
+
+    @pytest.mark.asyncio
+    async def test_native_lifecycle_hook_guardrail_is_left_alone(self):
+        class _NativeHooks(_ApplyOnlyObserver):
+            use_native_lifecycle_hooks = True
+
+        guardrail = _NativeHooks()
+        kwargs, response = _logged_call([{"role": "user", "content": "hello there"}])
+
+        out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value)
+
+        assert guardrail.calls == []
+        assert out_kwargs is kwargs
+        assert out_response is response
+
+    @pytest.mark.asyncio
+    async def test_aresponses_scans_logged_messages_when_input_is_cleared(self):
+        from litellm.types.llms.openai import ResponsesAPIResponse
+
+        guardrail = _ApplyOnlyObserver()
+        kwargs, _ = _logged_call([{"role": "user", "content": "hello there"}])
+        kwargs["input"] = None
+        response = ResponsesAPIResponse(
+            id="resp_1",
+            created_at=1,
+            model="gpt-5.4-mini",
+            object="response",
+            status="completed",
+            output=[
+                {
+                    "type": "message",
+                    "id": "msg_1",
+                    "status": "completed",
+                    "role": "assistant",
+                    "content": [{"type": "output_text", "text": "general kenobi"}],
+                }
+            ],
+        )
+
+        out_kwargs, _ = await guardrail.async_logging_hook(kwargs, response, CallTypes.aresponses.value)
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        entries = out_kwargs["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success", "success"]
+
+    @pytest.mark.asyncio
+    async def test_async_success_handler_records_verdict_in_standard_logging_object(self):
+        import datetime as dt
+
+        from litellm.litellm_core_utils.litellm_logging import Logging
+
+        guardrail = _ApplyOnlyObserver()
+        guardrail.default_on = True
+        messages = [{"role": "user", "content": "hello there"}]
+        _, response = _logged_call(messages)
+        logging_obj = Logging(
+            model="gpt-5.4-mini",
+            messages=messages,
+            stream=False,
+            call_type=CallTypes.acompletion.value,
+            start_time=dt.datetime.now(),
+            litellm_call_id="call-1",
+            function_id="fn-1",
+            dynamic_async_success_callbacks=[guardrail],
+        )
+        logging_obj.update_environment_variables(
+            litellm_params={"metadata": {}}, optional_params={}, model="gpt-5.4-mini", custom_llm_provider="openai"
+        )
+
+        await logging_obj.async_success_handler(
+            result=response, start_time=dt.datetime.now(), end_time=dt.datetime.now()
+        )
+
+        assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])]
+        entries = logging_obj.model_call_details["standard_logging_object"]["guardrail_information"]
+        assert [e["guardrail_status"] for e in entries] == ["success", "success"]
diff --git a/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py b/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
index 029b097cb75..ea661d2ea78 100644
--- a/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
+++ b/tests/test_litellm/integrations/test_prometheus_client_ip_user_agent.py
@@ -93,6 +93,7 @@ async def test_async_post_call_success_hook_includes_client_ip_user_agent():
         logger._increment_token_metrics = MagicMock()
         logger._increment_remaining_budget_metrics = AsyncMock()
         logger._set_virtual_key_rate_limit_metrics = MagicMock()
+        logger._set_key_and_team_rate_limit_metrics = MagicMock()
         logger._set_latency_metrics = MagicMock()
         logger.set_llm_deployment_success_metrics = MagicMock()
         logger._increment_cache_metrics = MagicMock()
diff --git a/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py b/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
index 9c6d2e018ff..bf1d68c7714 100644
--- a/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
+++ b/tests/test_litellm/integrations/test_prometheus_rate_limit_labels.py
@@ -13,6 +13,7 @@ Covers two follow-up gaps to the unified rate-limit error work:
    429s don't silently break when the new class lands.
 """
 
+from collections.abc import Mapping
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -471,3 +472,254 @@ def test_should_ignore_non_int_v3_header_values(bad_value):
     logger.litellm_remaining_api_key_tokens_for_model.labels.return_value.set.assert_called_once_with(
         sys.maxsize
     )
+
+
+KEY_AND_TEAM_RATE_LIMIT_METRICS = (
+    "litellm_api_key_rate_limit_allowed_metric",
+    "litellm_api_key_rate_limit_used_metric",
+    "litellm_team_rate_limit_allowed_metric",
+    "litellm_team_rate_limit_used_metric",
+)
+
+
+def _clear_prometheus_registry() -> None:
+    from prometheus_client import REGISTRY
+
+    for collector in list(REGISTRY._collector_to_names.keys()):
+        try:
+            REGISTRY.unregister(collector)
+        except Exception:
+            pass
+
+
+def _collected_samples(metric_name: str) -> dict[tuple[tuple[str, str], ...], float]:
+    from prometheus_client import REGISTRY
+
+    return {
+        tuple(sorted(sample.labels.items())): sample.value
+        for metric in REGISTRY.collect()
+        for sample in metric.samples
+        if sample.name == metric_name
+    }
+
+
+def _success_kwargs_with_rate_limit_headers(additional_headers: Mapping[str, object] | None) -> dict[str, object]:
+    return {
+        "model": "claude-haiku-4-5",
+        "litellm_params": {"metadata": {}},
+        "standard_logging_object": {
+            "id": "t",
+            "call_type": "completion",
+            "response_cost": 0.001,
+            "status": "success",
+            "total_tokens": 20,
+            "prompt_tokens": 15,
+            "completion_tokens": 5,
+            "startTime": 1.0,
+            "endTime": 2.0,
+            "completionStartTime": 1.5,
+            "model": "claude-haiku-4-5",
+            "model_id": "model-123",
+            "model_group": "anthropic-haiku-4-5",
+            "api_base": "https://api.anthropic.com",
+            "custom_llm_provider": "anthropic",
+            "request_tags": [],
+            "end_user": None,
+            "cache_hit": False,
+            "stream": False,
+            "response": None,
+            "model_parameters": None,
+            "metadata": {
+                "user_api_key_hash": "key-hash",
+                "user_api_key_alias": "key-alias",
+                "user_api_key_team_id": "team-id",
+                "user_api_key_team_alias": "team-alias",
+                "user_api_key_user_id": "u",
+                "user_api_key_user_email": "e@x.com",
+                "user_api_key_org_id": None,
+                "user_api_key_org_alias": None,
+                "requester_metadata": None,
+                "user_api_key_end_user_id": None,
+                "usage_object": None,
+            },
+            "hidden_params": {
+                "litellm_overhead_time_ms": None,
+                "additional_headers": additional_headers,
+            },
+        },
+    }
+
+
+async def _run_success_event(
+    additional_headers: Mapping[str, object] | None, logger: PrometheusLogger | None = None
+) -> None:
+    import datetime
+
+    now = datetime.datetime.now()
+    await (logger or PrometheusLogger()).async_log_success_event(
+        _success_kwargs_with_rate_limit_headers(additional_headers), None, now, now
+    )
+
+
+@pytest.mark.asyncio
+async def test_should_emit_key_and_team_rate_limit_allowed_and_used_from_v3_headers():
+    """
+    LIT-1672: the v3 limiter mirrors ``x-ratelimit-{api_key,team}-{limit,remaining}-*``
+    into the logging payload. The gauges must expose the configured limit as-is
+    and the window consumption as ``limit - remaining`` for each key / team
+    dimension, split by ``rate_limit_type``.
+    """
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 7,
+                "x-ratelimit-api_key-limit-tokens": 20000,
+                "x-ratelimit-api_key-remaining-tokens": 19947,
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 47,
+                "x-ratelimit-team-limit-tokens": 40000,
+                "x-ratelimit-team-remaining-tokens": 39960,
+                "x-ratelimit-model_per_key-limit-requests": 5,
+                "x-ratelimit-model_per_key-remaining-requests": 1,
+            }
+        )
+
+        key_requests = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "requests"),
+        )
+        key_tokens = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "tokens"),
+        )
+        team_requests = (
+            ("rate_limit_type", "requests"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+        team_tokens = (
+            ("rate_limit_type", "tokens"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {
+            key_requests: 10,
+            key_tokens: 20000,
+        }
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {
+            key_requests: 3,
+            key_tokens: 53,
+        }
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {
+            team_requests: 50,
+            team_tokens: 40000,
+        }
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {
+            team_requests: 3,
+            team_tokens: 40,
+        }
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+async def test_should_emit_only_the_dimensions_the_limiter_enforced():
+    """
+    A key with only ``rpm_limit`` set and no team limits produces only the
+    key/requests headers, so no tokens series and no team series may appear
+    (a phantom 0 or sys.maxsize series would misreport an unlimited dimension).
+    """
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 10,
+            }
+        )
+
+        key_requests = (
+            ("api_key_alias", "key-alias"),
+            ("hashed_api_key", "key-hash"),
+            ("rate_limit_type", "requests"),
+        )
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {key_requests: 10}
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {key_requests: 0}
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {}
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {}
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+async def test_should_drop_key_and_team_series_once_the_limiter_stops_reporting_a_limit():
+    """
+    Removing a key's ``rpm_limit`` / ``tpm_limit`` (or a team's ``tpm_limit``)
+    makes the v3 limiter stop emitting that descriptor's headers on later
+    requests. The old allowed/used samples must disappear instead of keeping
+    a limit that no longer exists on the scrape.
+    """
+    _clear_prometheus_registry()
+    try:
+        logger = PrometheusLogger()
+        await _run_success_event(
+            {
+                "x-ratelimit-api_key-limit-requests": 10,
+                "x-ratelimit-api_key-remaining-requests": 7,
+                "x-ratelimit-api_key-limit-tokens": 20000,
+                "x-ratelimit-api_key-remaining-tokens": 19947,
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 47,
+                "x-ratelimit-team-limit-tokens": 40000,
+                "x-ratelimit-team-remaining-tokens": 39960,
+            },
+            logger=logger,
+        )
+        await _run_success_event(
+            {
+                "x-ratelimit-team-limit-requests": 50,
+                "x-ratelimit-team-remaining-requests": 46,
+            },
+            logger=logger,
+        )
+
+        team_requests = (
+            ("rate_limit_type", "requests"),
+            ("team", "team-id"),
+            ("team_alias", "team-alias"),
+        )
+        assert _collected_samples("litellm_api_key_rate_limit_allowed_metric") == {}
+        assert _collected_samples("litellm_api_key_rate_limit_used_metric") == {}
+        assert _collected_samples("litellm_team_rate_limit_allowed_metric") == {team_requests: 50}
+        assert _collected_samples("litellm_team_rate_limit_used_metric") == {team_requests: 4}
+    finally:
+        _clear_prometheus_registry()
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "additional_headers",
+    [
+        None,
+        {"x-ratelimit-model_per_key-remaining-requests": 42},
+        {"x-ratelimit-api_key-limit-requests": 10},
+        {"x-ratelimit-api_key-limit-requests": "10", "x-ratelimit-api_key-remaining-requests": "7"},
+        {"x-ratelimit-team-limit-tokens": True, "x-ratelimit-team-remaining-tokens": 5},
+    ],
+)
+async def test_should_emit_no_key_or_team_rate_limit_series_without_a_complete_int_pair(
+    additional_headers,
+):
+    _clear_prometheus_registry()
+    try:
+        await _run_success_event(additional_headers)
+
+        for metric_name in KEY_AND_TEAM_RATE_LIMIT_METRICS:
+            assert _collected_samples(metric_name) == {}, metric_name
+    finally:
+        _clear_prometheus_registry()
diff --git a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
new file mode 100644
index 00000000000..519a13751f1
--- /dev/null
+++ b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
@@ -0,0 +1,279 @@
+"""
+LIT-6611: every unique client-supplied model name that fails routing used to
+mint permanent Prometheus series carrying ``requested_model="<junk>"`` on the
+proxy request metrics and the deployment metrics, with no eviction. The fix
+collapses any requested model the router does not recognize (and no wildcard
+pattern matches) into the single ``other`` label bucket, while recognized
+names, aliases, and wildcard-matched names keep their own label values.
+"""
+
+import sys
+import types
+from unittest.mock import patch
+
+import pytest
+from prometheus_client import REGISTRY
+
+import litellm
+from litellm.integrations.prometheus import (
+    UNRECOGNIZED_REQUESTED_MODEL_LABEL,
+    PrometheusLogger,
+)
+from litellm.proxy._types import UserAPIKeyAuth
+
+
+class _ClientSideError(Exception):
+    status_code = 400
+
+
+@pytest.fixture(autouse=True)
+def cleanup_prometheus_registry():
+    for collector in list(REGISTRY._collector_to_names.keys()):
+        try:
+            REGISTRY.unregister(collector)
+        except Exception:
+            pass
+
+    yield
+
+    for collector in list(REGISTRY._collector_to_names.keys()):
+        try:
+            REGISTRY.unregister(collector)
+        except Exception:
+            pass
+
+
+@pytest.fixture
+def router():
+    return litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-4o-mini",
+                "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "fake-key"},
+            },
+            {
+                "model_name": "openai/*",
+                "litellm_params": {"model": "openai/*", "api_key": "fake-key"},
+            },
+        ],
+        model_group_alias={"gpt4o-alias": "gpt-4o-mini"},
+    )
+
+
+@pytest.fixture
+def team_router():
+    return litellm.Router(
+        model_list=[
+            {
+                "model_name": "team-internal-gpt",
+                "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "fake-key"},
+                "model_info": {"team_id": "team-1", "team_public_model_name": "team-alias-gpt"},
+            },
+            {
+                "model_name": "team-internal-bedrock",
+                "litellm_params": {"model": "openai/*", "api_key": "fake-key"},
+                "model_info": {"team_id": "team-1", "team_public_model_name": "team-models/*"},
+            },
+        ]
+    )
+
+
+def _requested_model_values(metric) -> set[str]:
+    index = metric._labelnames.index("requested_model")
+    return {sample_key[index] for sample_key in metric._metrics}
+
+
+def _series_count(metric) -> int:
+    return len(metric._metrics)
+
+
+def _total_value(metric) -> float:
+    return sum(child._value.get() for child in metric._metrics.values())
+
+
+async def _fire_proxy_failure(logger: PrometheusLogger, model: str) -> None:
+    await logger.async_post_call_failure_hook(
+        request_data={"model": model, "metadata": {}, "proxy_server_request": {}},
+        original_exception=_ClientSideError(f"model {model} does not exist"),
+        user_api_key_dict=UserAPIKeyAuth(api_key="hashed-key-1"),
+    )
+
+
+@pytest.mark.asyncio
+async def test_unknown_models_collapse_to_one_series_on_proxy_request_metrics(router):
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        for index in range(25):
+            await _fire_proxy_failure(logger, f"agent-typo-{index}")
+
+    for metric in (
+        logger.litellm_proxy_failed_requests_metric,
+        logger.litellm_proxy_total_requests_metric,
+    ):
+        assert _requested_model_values(metric) == {UNRECOGNIZED_REQUESTED_MODEL_LABEL}
+        assert _series_count(metric) == 1
+        assert _total_value(metric) == 25
+
+
+@pytest.mark.asyncio
+async def test_known_alias_and_wildcard_models_keep_their_own_labels(router):
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        await _fire_proxy_failure(logger, "gpt-4o-mini")
+        await _fire_proxy_failure(logger, "gpt4o-alias")
+        await _fire_proxy_failure(logger, "openai/gpt-4o-audio-preview")
+        await _fire_proxy_failure(logger, "agent-typo-hallucinated")
+
+    for metric in (
+        logger.litellm_proxy_failed_requests_metric,
+        logger.litellm_proxy_total_requests_metric,
+    ):
+        assert _requested_model_values(metric) == {
+            "gpt-4o-mini",
+            "gpt4o-alias",
+            "openai/gpt-4o-audio-preview",
+            UNRECOGNIZED_REQUESTED_MODEL_LABEL,
+        }
+
+
+@pytest.mark.asyncio
+async def test_team_alias_and_team_wildcard_models_keep_their_own_labels(team_router):
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", team_router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        await _fire_proxy_failure(logger, "team-alias-gpt")
+        await _fire_proxy_failure(logger, "team-models/gpt-4o-audio-preview")
+        await _fire_proxy_failure(logger, "agent-typo-hallucinated")
+
+    for metric in (
+        logger.litellm_proxy_failed_requests_metric,
+        logger.litellm_proxy_total_requests_metric,
+    ):
+        assert _requested_model_values(metric) == {
+            "team-alias-gpt",
+            "team-models/gpt-4o-audio-preview",
+            UNRECOGNIZED_REQUESTED_MODEL_LABEL,
+        }
+
+
+@pytest.mark.asyncio
+async def test_unknown_models_collapse_to_other_when_router_is_unavailable():
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", None, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        await _fire_proxy_failure(logger, "agent-typo-no-router")
+        await _fire_proxy_failure(logger, "gpt-4o-mini")
+
+    assert _requested_model_values(logger.litellm_proxy_failed_requests_metric) == {
+        UNRECOGNIZED_REQUESTED_MODEL_LABEL
+    }
+
+
+@pytest.mark.asyncio
+async def test_sdk_router_originated_metrics_keep_labels_without_proxy_router():
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", None, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        logger.set_llm_deployment_failure_metrics(
+            request_kwargs={
+                "model": "sdk-deployment-group",
+                "litellm_params": {"metadata": {}},
+                "standard_logging_object": {},
+                "exception": _ClientSideError("model does not exist"),
+            }
+        )
+        await logger.log_failure_fallback_event(
+            original_model_group="sdk-fallback-group",
+            kwargs={"model": "sdk-fallback-group", "metadata": {}},
+            original_exception=_ClientSideError("upstream unavailable"),
+        )
+
+    assert _requested_model_values(logger.litellm_deployment_failure_responses) == {"sdk-deployment-group"}
+    assert _requested_model_values(logger.litellm_deployment_failed_fallbacks) == {"sdk-fallback-group"}
+
+
+@pytest.mark.asyncio
+async def test_sdk_fallback_labels_survive_non_import_errors_from_proxy_module(monkeypatch):
+    logger = PrometheusLogger()
+    broken_proxy_module = types.ModuleType("litellm.proxy.proxy_server")
+
+    def _raise_value_error(_name: str):
+        raise ValueError("bad proxy env var")
+
+    broken_proxy_module.__getattr__ = _raise_value_error  # test-quality-ok: reproduces a proxy_server import raising non-ImportError, no injection seam
+    monkeypatch.setitem(sys.modules, "litellm.proxy.proxy_server", broken_proxy_module)  # test-quality-ok: reproduces a proxy_server import raising non-ImportError, no injection seam
+
+    await logger.log_failure_fallback_event(
+        original_model_group="sdk-fallback-group",
+        kwargs={"model": "sdk-fallback-group", "metadata": {}},
+        original_exception=_ClientSideError("upstream unavailable"),
+    )
+
+    assert _requested_model_values(logger.litellm_deployment_failed_fallbacks) == {"sdk-fallback-group"}
+
+
+def test_unknown_models_collapse_to_one_series_on_deployment_metrics(router):
+    logger = PrometheusLogger()
+
+    with patch("litellm.proxy.proxy_server.llm_router", router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        for index in range(25):
+            logger.set_llm_deployment_failure_metrics(
+                request_kwargs={
+                    "model": f"agent-typo-{index}",
+                    "litellm_params": {"metadata": {}},
+                    "standard_logging_object": {},
+                    "exception": _ClientSideError("model does not exist"),
+                }
+            )
+        logger.set_llm_deployment_failure_metrics(
+            request_kwargs={
+                "model": "gpt-4o-mini",
+                "litellm_params": {"metadata": {}},
+                "standard_logging_object": {},
+                "exception": _ClientSideError("all deployments cooling down"),
+            }
+        )
+
+    for metric in (
+        logger.litellm_deployment_failure_responses,
+        logger.litellm_deployment_total_requests,
+    ):
+        assert _requested_model_values(metric) == {
+            UNRECOGNIZED_REQUESTED_MODEL_LABEL,
+            "gpt-4o-mini",
+        }
+        assert _series_count(metric) == 2
+        assert _total_value(metric) == 26
+
+
+@pytest.mark.asyncio
+async def test_fallback_event_requested_model_is_bounded(router):
+    logger = PrometheusLogger()
+    kwargs = {"model": "gpt-4o-mini", "metadata": {}}
+
+    with patch("litellm.proxy.proxy_server.llm_router", router, create=True):  # test-quality-ok: production reads proxy_server.llm_router lazily, no injection seam
+        await logger.log_failure_fallback_event(
+            original_model_group="agent-typo-hallucinated",
+            kwargs=kwargs,
+            original_exception=_ClientSideError("model does not exist"),
+        )
+        await logger.log_success_fallback_event(
+            original_model_group="agent-typo-hallucinated",
+            kwargs=kwargs,
+            original_exception=_ClientSideError("model does not exist"),
+        )
+        await logger.log_failure_fallback_event(
+            original_model_group="gpt-4o-mini",
+            kwargs=kwargs,
+            original_exception=_ClientSideError("upstream unavailable"),
+        )
+
+    assert _requested_model_values(logger.litellm_deployment_failed_fallbacks) == {
+        UNRECOGNIZED_REQUESTED_MODEL_LABEL,
+        "gpt-4o-mini",
+    }
+    assert _requested_model_values(logger.litellm_deployment_successful_fallbacks) == {
+        UNRECOGNIZED_REQUESTED_MODEL_LABEL
+    }
diff --git a/tests/test_litellm/integrations/test_s3.py b/tests/test_litellm/integrations/test_s3.py
index 7e997870852..58b15b79e76 100644
--- a/tests/test_litellm/integrations/test_s3.py
+++ b/tests/test_litellm/integrations/test_s3.py
@@ -2,26 +2,27 @@ from datetime import datetime
 from unittest.mock import MagicMock, patch
 
 import litellm
+from litellm.constants import MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES, MAX_S3_OBJECT_KEY_BYTES
 from litellm.integrations.s3 import S3Logger
 
 TEST_KMS_KEY_ARN = "arn:aws:kms:us-east-1:111122223333:key/test-key-id"
 
 
-def _standard_logging_payload() -> dict:
+def _standard_logging_payload(response_id: str = "chatcmpl-test-id") -> dict:
     return {
-        "id": "chatcmpl-test-id",
+        "id": response_id,
         "metadata": {"user_api_key_team_alias": None},
     }
 
 
-def _log_event_kwargs() -> dict:
+def _log_event_kwargs(response_id: str = "chatcmpl-test-id") -> dict:
     return {
         "litellm_params": {"metadata": {}},
-        "standard_logging_object": _standard_logging_payload(),
+        "standard_logging_object": _standard_logging_payload(response_id),
     }
 
 
-def _run_log_event(callback_params: dict) -> MagicMock:
+def _run_log_event(callback_params: dict, response_id: str = "chatcmpl-test-id") -> MagicMock:
     original = litellm.s3_callback_params
     litellm.s3_callback_params = callback_params
     try:
@@ -30,8 +31,8 @@ def _run_log_event(callback_params: dict) -> MagicMock:
             mock_boto3_client.return_value = mock_s3_client
             logger = S3Logger()
             logger.log_event(
-                kwargs=_log_event_kwargs(),
-                response_obj={},
+                kwargs=_log_event_kwargs(response_id),
+                response_obj={"id": response_id},
                 start_time=datetime(2026, 7, 30, 12, 0, 0),
                 end_time=datetime(2026, 7, 30, 12, 0, 1),
                 print_verbose=lambda *args, **kwargs: None,
@@ -154,3 +155,30 @@ def test_non_string_key_id_is_dropped_and_valid_algorithm_is_kept():
     put_object_kwargs = mock_s3_client.put_object.call_args.kwargs
     assert put_object_kwargs["ServerSideEncryption"] == "aws:kms"
     assert "SSEKMSKeyId" not in put_object_kwargs
+
+
+def test_put_object_key_and_filename_are_bounded_for_an_oversized_response_id():
+    """The sync logger bounds both the key and the Content-Disposition filename."""
+    mock_s3_client = _run_log_event(
+        {"s3_bucket_name": "test-bucket", "s3_region_name": "us-west-2", "s3_path": "logs"},
+        response_id="resp_" + "A" * 1100,
+    )
+
+    put_object_kwargs = mock_s3_client.put_object.call_args.kwargs
+    assert len(put_object_kwargs["Key"].encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert put_object_kwargs["Key"].startswith("logs/2026-07-30/time-12-00-00-000000_resp_")
+    filename = put_object_kwargs["ContentDisposition"].removeprefix('inline; filename="').removesuffix('"')
+    assert len(filename.encode("utf-8")) <= MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES
+
+
+def test_put_object_keeps_the_configured_path_intact_when_only_the_id_has_to_shrink():
+    """A long configured s3_path survives whole when the id can be shortened instead."""
+    long_path = "litellm-prod-logs/" + "t" * 921
+    mock_s3_client = _run_log_event(
+        {"s3_bucket_name": "test-bucket", "s3_region_name": "us-west-2", "s3_path": long_path},
+        response_id="resp_" + "B" * 100,
+    )
+
+    key = mock_s3_client.put_object.call_args.kwargs["Key"]
+    assert key.startswith(long_path + "/2026-07-30/")
+    assert len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES
diff --git a/tests/test_litellm/integrations/test_s3_v2.py b/tests/test_litellm/integrations/test_s3_v2.py
index 51671d5101e..a037284d7c1 100644
--- a/tests/test_litellm/integrations/test_s3_v2.py
+++ b/tests/test_litellm/integrations/test_s3_v2.py
@@ -1170,6 +1170,294 @@ def test_create_s3_batch_logging_element_flat_key_for_arn_response_id():
     assert file_segment.endswith("model-invocation-job_gl18r6skk9yy.json")
 
 
+# --------------------------------------------------------------
+# object keys bounded to S3's 1024 UTF-8 byte limit
+# --------------------------------------------------------------
+def _oversized_response_id() -> str:
+    return "resp_" + "A" * 1100
+
+
+def test_s3_object_key_at_the_byte_limit_is_left_alone():
+    """A key that still fits is left byte-identical."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    start_time = datetime(2026, 8, 24, 6, 18, 41, 948021)
+    fixed_len = len("input/2026-08-24/.json")
+    file_name = "x" * (MAX_S3_OBJECT_KEY_BYTES - fixed_len)
+
+    key = get_s3_object_key(s3_path="input", prefix="", start_time=start_time, s3_file_name=file_name)
+
+    assert key == f"input/2026-08-24/{file_name}.json"
+    assert len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES
+
+
+def test_s3_object_key_is_bounded_for_oversized_response_id():
+    """An oversized Responses API id is shortened to a readable head plus a digest."""
+    import hashlib
+
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    start_time = datetime(2026, 8, 24, 6, 18, 41, 948021)
+    file_name = f"time-06-18-41-948021_{_oversized_response_id()}"
+
+    key = get_s3_object_key(s3_path="input", prefix="DefaultTeamProd/", start_time=start_time, s3_file_name=file_name)
+
+    assert len(key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert key.startswith("input/DefaultTeamProd/2026-08-24/time-06-18-41-948021_resp_")
+    assert key.endswith(f"_{hashlib.sha256(file_name.encode('utf-8')).hexdigest()}.json")
+
+
+@pytest.mark.parametrize(
+    "s3_path,prefix",
+    [
+        ("input", ""),
+        ("a" * 900, ""),
+        ("input", "team-" + "b" * 900 + "/"),
+        ("c" * 600, "team-" + "d" * 600 + "/key-" + "e" * 600 + "/"),
+        # many short segments, so the trim lands exactly on the budget edge
+        ("", "ssss/" * 200),
+    ],
+)
+def test_s3_object_key_is_bounded_for_long_paths_and_aliases(s3_path: str, prefix: str):
+    """Long paths, team aliases and key aliases stay within the cap."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    key = get_s3_object_key(
+        s3_path=s3_path,
+        prefix=prefix,
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name=f"time-06-18-41-948021_{_oversized_response_id()}",
+    )
+
+    assert len(key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert key.endswith(".json")
+    assert "/2026-08-24/" in key or key.startswith("2026-08-24/")
+    assert "/" not in key.rsplit("2026-08-24/", 1)[1]
+
+
+def test_s3_object_key_trimmed_prefixes_stay_distinct_per_operator():
+    """Prefixes that differ only past the trim point keep separate folders."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    start_time = datetime(2026, 8, 24, 6, 18, 41, 948021)
+    keys = [
+        get_s3_object_key(
+            s3_path="input",
+            prefix="team-" + "b" * 1000 + suffix + "/",
+            start_time=start_time,
+            s3_file_name=f"time-06-18-41-948021_{_oversized_response_id()}",
+        )
+        for suffix in ("-one", "-two")
+    ]
+
+    assert keys[0] != keys[1]
+    assert all(key.startswith("input/team-" + "b" * 900) for key in keys)
+    assert all(len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES for key in keys)
+
+
+def test_s3_object_key_bounded_prefix_never_splits_a_multibyte_character():
+    """A multibyte prefix is trimmed on a character boundary."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    s3_path = "\u65e5\u672c\u8a9e" * 200
+
+    key = get_s3_object_key(
+        s3_path=s3_path,
+        prefix="\u30c1\u30fc\u30e0" * 200 + "/",
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name=f"time-06-18-41-948021_{_oversized_response_id()}",
+    )
+
+    assert len(key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert key.startswith(s3_path[:100])
+    assert "\ufffd" not in key
+
+
+def test_s3_object_key_stays_unique_for_ids_sharing_a_head():
+    """Ids sharing a visible head still get distinct keys."""
+    from litellm.integrations.s3 import get_s3_object_key
+
+    start_time = datetime(2026, 8, 24, 6, 18, 41, 948021)
+    keys = {
+        get_s3_object_key(
+            s3_path="input",
+            prefix="",
+            start_time=start_time,
+            s3_file_name=f"time-06-18-41-948021_{_oversized_response_id()}{suffix}",
+        )
+        for suffix in ("first", "second", "third")
+    }
+
+    assert len(keys) == 3
+
+
+def test_s3_object_key_bounding_matches_the_documented_layout():
+    """The bounded key is `<prefix>/<date>/<head>_<sha256>.json`."""
+    import hashlib
+
+    from litellm.integrations.s3 import get_s3_object_key
+
+    file_name = f"time-06-18-41-948021_{_oversized_response_id()}"
+
+    key = get_s3_object_key(
+        s3_path="input",
+        prefix="team/",
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name=file_name,
+    )
+
+    digest = hashlib.sha256(file_name.encode("utf-8")).hexdigest()
+    assert key == f"input/team/2026-08-24/{file_name[:64]}_{digest}.json"
+
+
+def test_s3_object_key_keeps_the_configured_prefix_when_only_the_id_overflows():
+    """A 940 byte configured prefix survives whole when only the id overflows."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    prefix = "team-" + "b" * 934 + "/"
+
+    key = get_s3_object_key(
+        s3_path="",
+        prefix=prefix,
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name=f"time-06-18-41-948021_{_oversized_response_id()}",
+    )
+
+    assert key.startswith(prefix + "2026-08-24/")
+    assert len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES
+
+
+def test_s3_object_key_spends_the_whole_budget_when_the_prefix_must_be_trimmed():
+    """A trimmed prefix keeps every byte the budget allows, not whole segments."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    s3_path = "p" * 400 + "/" + "q" * 600
+
+    key = get_s3_object_key(
+        s3_path=s3_path,
+        prefix="",
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name="time-06-18-41-948021_abc",
+    )
+
+    assert len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES
+    assert key.startswith("p" * 400 + "/" + "q" * 500)
+
+
+def test_s3_object_key_keeps_a_single_segment_path_as_far_as_it_fits():
+    """A path with no separator is kept as far as it fits, never dropped to the bucket root."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+    from litellm.integrations.s3 import get_s3_object_key
+
+    key = get_s3_object_key(
+        s3_path="a" * 1050,
+        prefix="",
+        start_time=datetime(2026, 8, 24, 6, 18, 41, 948021),
+        s3_file_name="time-06-18-41-948021_chatcmpl-xyz",
+    )
+
+    assert len(key.encode("utf-8")) == MAX_S3_OBJECT_KEY_BYTES
+    assert key.startswith("a" * 900)
+
+
+def test_create_s3_batch_logging_element_bounds_key_and_keeps_full_response_id():
+    """The batch element bounds the key and keeps the full response id in the payload."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+
+    logger = S3Logger(s3_use_team_prefix=True, s3_use_key_prefix=True)
+    response_id = _oversized_response_id()
+    payload = StandardLoggingPayload(
+        id=response_id,
+        metadata={"user_api_key_team_alias": "DefaultTeamProd", "user_api_key_alias": "prod-key"},
+        messages=[],
+    )
+
+    result = logger.create_s3_batch_logging_element(datetime(2026, 8, 24, 6, 18, 41, 948021), payload)
+
+    assert result is not None
+    assert len(result.s3_object_key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert result.s3_object_key.startswith("DefaultTeamProd/prod-key/2026-08-24/")
+    assert result.payload["id"] == response_id
+
+
+def test_s3_object_download_filename_is_bounded_for_oversized_response_id():
+    """The Content-Disposition filename is bounded too, or the PUT fails with MetadataTooLarge."""
+    from litellm.constants import MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES
+    from litellm.integrations.s3 import get_s3_object_download_filename
+
+    file_name = get_s3_object_download_filename(datetime(2026, 8, 24, 6, 18, 41, 948021), _oversized_response_id())
+
+    assert len(file_name.encode("utf-8")) <= MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES
+    assert file_name.startswith("time-2026-08-24T06-18-41-948021_resp_")
+    assert file_name.endswith(".json")
+
+
+def test_s3_object_download_filenames_stay_distinct_when_shortened():
+    """Shortened filenames stay distinct."""
+    from litellm.integrations.s3 import get_s3_object_download_filename
+
+    start_time = datetime(2026, 8, 24, 6, 18, 41, 948021)
+    file_names = {
+        get_s3_object_download_filename(start_time, _oversized_response_id() + suffix)
+        for suffix in ("first", "second", "third")
+    }
+
+    assert len(file_names) == 3
+
+
+def test_s3_object_download_filename_short_id_is_unchanged():
+    """An ordinary response id keeps the filename it had before."""
+    from litellm.integrations.s3 import get_s3_object_download_filename
+
+    file_name = get_s3_object_download_filename(datetime(2026, 8, 24, 6, 18, 41, 948021), "resp_abc123")
+
+    assert file_name == "time-2026-08-24T06-18-41-948021_resp_abc123.json"
+
+
+def test_create_s3_batch_logging_element_bounds_the_download_filename():
+    """The batch element carries a bounded Content-Disposition filename."""
+    from litellm.constants import MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES
+
+    logger = S3Logger()
+    payload = StandardLoggingPayload(id=_oversized_response_id(), metadata={}, messages=[])
+
+    result = logger.create_s3_batch_logging_element(datetime(2026, 8, 24, 6, 18, 41, 948021), payload)
+
+    assert result is not None
+    assert len(result.s3_object_download_filename.encode("utf-8")) <= MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES
+
+
+@pytest.mark.asyncio
+async def test_audit_log_object_key_is_bounded_for_a_long_configured_path():
+    """Audit log keys are bounded by the same builder."""
+    from litellm.constants import MAX_S3_OBJECT_KEY_BYTES
+
+    logger = S3Logger()
+    logger.s3_path = "audit-archive/" + "z" * 1100
+
+    await logger.async_log_audit_log_event({"id": "1a4f7bd0-6f1e-4d0a-9b3c-9f2e1d5a7c88"})
+
+    assert len(logger.log_queue) == 1
+    assert len(logger.log_queue[0].s3_object_key.encode("utf-8")) <= MAX_S3_OBJECT_KEY_BYTES
+    assert logger.log_queue[0].s3_object_key.startswith("audit-archive/" + "z" * 900)
+
+
+def test_s3_object_download_filename_drops_characters_that_break_the_header():
+    """A quote or separator in the response id cannot escape the quoted header value."""
+    from litellm.integrations.s3 import get_s3_object_download_filename
+
+    file_name = get_s3_object_download_filename(datetime(2026, 8, 24, 6, 18, 41, 948021), 'resp_a"b/c')
+
+    assert file_name == "time-2026-08-24T06-18-41-948021_resp_a_b_c.json"
+
+
 # --------------------------------------------------------------
 # params_source / s3_callback_params_override (audit-log decoupling)
 # --------------------------------------------------------------
diff --git a/tests/test_litellm/integrations/test_shadow_eval_logger.py b/tests/test_litellm/integrations/test_shadow_eval_logger.py
index f9c287fc7b7..5628d69de26 100644
--- a/tests/test_litellm/integrations/test_shadow_eval_logger.py
+++ b/tests/test_litellm/integrations/test_shadow_eval_logger.py
@@ -58,12 +58,14 @@ def _prisma(jobs=(), attempt_counts=(), attempt_costs=()) -> MagicMock:
     return prisma
 
 
-def _job_record(job: ActiveShadowEvalJob, api_key_id="key-hash") -> MagicMock:
+def _job_record(job: ActiveShadowEvalJob, target_type="key", target_id="key-hash") -> MagicMock:
     record = MagicMock()
     for field, value in dict(
         id=job.id,
-        api_key_id=api_key_id,
+        target_type=target_type,
+        target_id=target_id,
         router_name=job.router_name,
+        router_names=job.router_names,
         direction=job.direction,
         baseline_model=job.baseline_model,
         shadow_percentage=job.shadow_percentage,
@@ -80,6 +82,7 @@ def _router(
     shadow_text="shadow answer",
     judge_json='{"preference": "A", "confidence": 0.9, "reasoning": "x"}',
     classifier_cost=None,
+    sibling_router_texts=None,
 ):
     """One mock router serving the shadow call first, the judge call second, told apart by
     the internal-origin stamp rather than the model, since a reverse job's shadow arm names
@@ -99,6 +102,15 @@ def _router(
                 decision["classifier_cost"] = classifier_cost
             kwargs["metadata"]["routing_decision"] = decision
             return {"choices": [{"message": {"content": shadow_text}}], "usage": {"completion_tokens": 5}}
+        if sibling_router_texts and kwargs["model"] in sibling_router_texts:
+            kwargs["metadata"]["routing_decision"] = {
+                "tier_label": "MEDIUM",
+                "routed_model": f"{kwargs['model']}-pick",
+            }
+            return {
+                "choices": [{"message": {"content": sibling_router_texts[kwargs["model"]]}}],
+                "usage": {"completion_tokens": 5},
+            }
         return ModelResponse(
             model=kwargs["model"],
             choices=[{"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": shadow_text}}],
@@ -123,7 +135,7 @@ def _spend_counter(store=None):
     return counter, read, write
 
 
-def _logger(router=None, prisma=None, jobs=(), counter_store=None) -> ShadowEvalLogger:
+def _logger(router=None, prisma=None, jobs=(), counter_store=None, jobs_by_target=None) -> ShadowEvalLogger:
     cache = InMemoryCache(max_size_in_memory=4, default_ttl=60)
     counter, read, write = _spend_counter(counter_store)
     funnel_events = []
@@ -137,8 +149,9 @@ def _logger(router=None, prisma=None, jobs=(), counter_store=None) -> ShadowEval
     )
     logger._test_counter = counter
     logger._test_funnel = funnel_events
-    if jobs:
-        cache.set_cache("shadow_eval:active_jobs", {"key-hash": tuple(jobs)})
+    seeded = jobs_by_target if jobs_by_target is not None else ({("key", "key-hash"): tuple(jobs)} if jobs else None)
+    if seeded is not None:
+        cache.set_cache("shadow_eval:active_jobs", seeded)
     return logger
 
 
@@ -837,6 +850,86 @@ class TestSuccessHookSkipChain:
         prisma.db.litellm_shadowevalattempt.create.assert_not_called()
 
 
+JWT_IDENTITY = {"user_api_key_hash": None, "user_api_key_team_id": "team-eng", "user_api_key_user_id": "dev-alice"}
+
+
+@pytest.mark.asyncio
+class TestTargetMatching:
+    """A request qualifies for a job through ANY of its resolved identities: key hash,
+    team id, or user id. Team and user jobs must therefore sample JWT-authenticated
+    traffic, which carries no key hash at all."""
+
+    @pytest.mark.parametrize(
+        "target,sampled",
+        [
+            (("team", "team-eng"), True),
+            (("user", "dev-alice"), True),
+            (("key", "some-key"), False),
+        ],
+        ids=["team-job-samples-jwt-traffic", "user-job-samples-jwt-traffic", "key-jobs-never-match-keyless-traffic"],
+    )
+    async def test_jwt_shaped_traffic_matches_team_and_user_jobs_but_no_key_job(self, target, sampled):
+        prisma = _prisma()
+        router = _router()
+        logger = _logger(router=router, prisma=prisma, jobs_by_target={target: (_job(),)})
+        hook_kwargs = _success_kwargs()
+        hook_kwargs["standard_logging_object"]["metadata"] = dict(JWT_IDENTITY)
+
+        await logger.async_log_success_event(hook_kwargs, RESPONSE, None, None)
+        await _drain(logger)
+
+        if sampled:
+            prisma.db.litellm_shadowevalattempt.create.assert_awaited_once()
+            assert prisma.db.litellm_shadowevalattempt.create.call_args.kwargs["data"]["job_id"] == "job-1"
+        else:
+            router.acompletion.assert_not_called()
+            prisma.db.litellm_shadowevalattempt.create.assert_not_called()
+
+    async def test_an_event_with_no_identity_early_returns_without_a_cache_read(self):
+        prisma = _prisma()
+        router = _router()
+        cache = MagicMock(spec=InMemoryCache)
+        cache.async_get_cache = AsyncMock()
+        logger = ShadowEvalLogger(
+            router_provider=lambda: router,
+            prisma_provider=lambda: prisma,
+            jobs_cache=cache,
+        )
+        hook_kwargs = _success_kwargs()
+        hook_kwargs["standard_logging_object"]["metadata"] = {}
+
+        await logger.async_log_success_event(hook_kwargs, RESPONSE, None, None)
+
+        cache.async_get_cache.assert_not_awaited()
+        router.acompletion.assert_not_called()
+        prisma.db.litellm_shadowevalattempt.create.assert_not_called()
+
+    async def test_an_event_matching_a_key_job_and_a_team_job_fires_both(self):
+        """A request's key and its team can each hold a job; the two are separately
+        budgeted experiments, so both fire and each counts its own start."""
+        prisma = _prisma()
+        logger = _logger(
+            router=_router(),
+            prisma=prisma,
+            jobs_by_target={
+                ("key", "key-hash"): (_job(id="key-job"),),
+                ("team", "team-eng"): (_job(id="team-job"),),
+            },
+        )
+        hook_kwargs = _success_kwargs()
+        hook_kwargs["standard_logging_object"]["metadata"] = {
+            "user_api_key_hash": "key-hash",
+            "user_api_key_team_id": "team-eng",
+        }
+
+        await logger.async_log_success_event(hook_kwargs, RESPONSE, None, None)
+        await _drain(logger)
+
+        rows = [call.kwargs["data"] for call in prisma.db.litellm_shadowevalattempt.create.call_args_list]
+        assert sorted(row["job_id"] for row in rows) == ["key-job", "team-job"]
+        assert logger._job_starts == {"key-job": 1, "team-job": 1}
+
+
 @pytest.mark.asyncio
 class TestActiveJobsCache:
     async def test_cache_miss_reads_db_once_then_serves_from_cache(self):
@@ -851,8 +944,8 @@ class TestActiveJobsCache:
         first = await logger._active_jobs()
         second = await logger._active_jobs()
 
-        assert [job.id for job in first["key-hash"]] == ["job-1"]
-        assert second["key-hash"][0].attempts == 7
+        assert [job.id for job in first[("key", "key-hash")]] == ["job-1"]
+        assert second[("key", "key-hash")][0].attempts == 7
         assert prisma.db.litellm_shadowevaljob.find_many.await_count == 1
         where = prisma.db.litellm_shadowevaljob.find_many.call_args.kwargs["where"]
         assert where["stopped_at"] is None
@@ -899,8 +992,8 @@ class TestActiveJobsCache:
         jobs = await logger._active_jobs()
 
         assert logger._job_starts == {}
-        assert jobs["key-hash"][0].attempts == 7
-        assert jobs["key-hash"][0].spend == 0.05
+        assert jobs[("key", "key-hash")][0].attempts == 7
+        assert jobs[("key", "key-hash")][0].spend == 0.05
 
 
 @pytest.mark.asyncio
@@ -1128,29 +1221,36 @@ class TestJobValidation:
             {"direction": "reverse"},
             {"baseline_model": "baseline-model"},
             {"direction": "sideways", "baseline_model": "baseline-model"},
+            {"direction": "reverse", "baseline_model": "baseline-model", "router_names": ("a", "b")},
         ],
-        ids=["reverse-without-baseline", "forward-with-baseline", "unknown-direction"],
+        ids=["reverse-without-baseline", "forward-with-baseline", "unknown-direction", "reverse-with-router-set"],
     )
     def test_unsamplable_shapes_are_rejected(self, overrides):
         with pytest.raises(ValidationError):
             _job(**overrides)
 
-    def test_shadow_target_follows_direction(self):
-        assert _job().shadow_target == "my-router"
-        assert _reverse_job().shadow_target == "baseline-model"
+    def test_arm_target_follows_direction(self):
+        assert _job().arm_target("my-router") == "my-router"
+        assert _reverse_job().arm_target("my-router") == "baseline-model"
+
+    def test_rows_from_before_router_names_carry_their_set_in_router_name(self):
+        assert _job().arm_router_names == ("my-router",)
+        assert _job(router_names=("my-router", "alt-router")).arm_router_names == ("my-router", "alt-router")
 
 
 @pytest.mark.asyncio
 class TestDirection:
     @pytest.mark.parametrize(
-        "job,routed_by,sampled",
+        "job,routed_by,attempt_rows",
         [
-            (_job(), None, True),
-            (_job(), "my-router", False),
-            (_job(), "other-router", True),
-            (_reverse_job(), "my-router", True),
-            (_reverse_job(), None, False),
-            (_reverse_job(), "other-router", False),
+            (_job(), None, 1),
+            (_job(), "my-router", 0),
+            (_job(), "other-router", 1),
+            (_reverse_job(), "my-router", 1),
+            (_reverse_job(), None, 0),
+            (_reverse_job(), "other-router", 0),
+            (_job(router_names=("my-router", "alt-router")), "alt-router", 0),
+            (_job(router_names=("my-router", "alt-router")), "other-router", 2),
         ],
         ids=[
             "forward-samples-unrouted",
@@ -1159,20 +1259,24 @@ class TestDirection:
             "reverse-samples-its-own-router",
             "reverse-skips-unrouted",
             "reverse-skips-another-router",
+            "forward-skips-any-candidates-own-traffic",
+            "forward-multi-samples-once-per-arm",
         ],
     )
-    async def test_direction_decides_which_traffic_is_sampled(self, job, routed_by, sampled):
+    async def test_direction_decides_which_traffic_is_sampled(self, job, routed_by, attempt_rows):
         """The two directions partition the key's traffic: whatever one samples, the other
-        skips, so a key running both never judges the same turn twice for the same reason."""
+        skips, so a key running both never judges the same turn twice for the same reason.
+        A multi-router job extends the forward skip to every candidate: a request one
+        candidate served must not be judged as the incumbent against another candidate."""
         prisma = _prisma()
-        logger = _logger(router=_router(), prisma=prisma, jobs=(job,))
+        logger = _logger(router=_router(sibling_router_texts={"alt-router": "alt answer"}), prisma=prisma, jobs=(job,))
 
         await logger.async_log_success_event(
             _success_kwargs(request_metadata=_routed_by(routed_by) if routed_by else {}), RESPONSE, None, None
         )
         await _drain(logger)
 
-        assert prisma.db.litellm_shadowevalattempt.create.await_count == int(sampled)
+        assert prisma.db.litellm_shadowevalattempt.create.await_count == attempt_rows
 
     async def test_reverse_duplicates_against_the_baseline_model(self):
         prisma = _prisma()
@@ -1234,6 +1338,134 @@ class TestDirection:
         assert logger._job_starts == {"forward-job": 1, "reverse-job": 1}
 
 
+@pytest.mark.asyncio
+class TestMultiRouterArms:
+    async def test_every_arm_judges_the_same_request_and_stamps_its_own_row(self):
+        """One sampled request, one row per candidate router, both judged against the same
+        real response: the paired comparison that makes multi-router win rates comparable."""
+        prisma = _prisma()
+        router = _router(sibling_router_texts={"alt-router": "alt answer"})
+        logger = _logger(router=router, prisma=prisma)
+
+        await logger._run_shadow_eval(
+            job=_job(router_names=("my-router", "alt-router")),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.001,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params={},
+            parent_metadata={},
+        )
+
+        rows = [call.kwargs["data"] for call in prisma.db.litellm_shadowevalattempt.create.await_args_list]
+        assert [row["router_name"] for row in rows] == ["my-router", "alt-router"]
+        assert {row["request_id"] for row in rows} == {"req-1"}
+        assert [row["shadow_model"] for row in rows] == ["cheap-model", "alt-router-pick"]
+        assert all(row["outcome"] in ("real", "shadow", "tie") for row in rows)
+        assert all(row["real_cost"] == 0.001 for row in rows)
+
+    async def test_a_single_router_job_stamps_its_router_on_the_row(self):
+        prisma = _prisma()
+        logger = _logger(router=_router(), prisma=prisma)
+
+        await logger._run_shadow_eval(
+            job=_job(),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.0,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params={},
+            parent_metadata={},
+        )
+
+        row = prisma.db.litellm_shadowevalattempt.create.call_args.kwargs["data"]
+        assert row["router_name"] == "my-router"
+
+    async def test_one_arms_failure_never_silences_the_sibling(self):
+        prisma = _prisma()
+        router = _router(sibling_router_texts={"alt-router": "alt answer"})
+        healthy = router.acompletion.side_effect
+
+        async def first_arm_explodes(**kwargs):
+            if kwargs["model"] == "my-router":
+                raise RuntimeError("provider exploded")
+            return await healthy(**kwargs)
+
+        router.acompletion.side_effect = first_arm_explodes
+        logger = _logger(router=router, prisma=prisma)
+
+        await logger._run_shadow_eval(
+            job=_job(router_names=("my-router", "alt-router")),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.0,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params={},
+            parent_metadata={},
+        )
+
+        rows = [call.kwargs["data"] for call in prisma.db.litellm_shadowevalattempt.create.await_args_list]
+        assert [row["router_name"] for row in rows] == ["my-router", "alt-router"]
+        assert rows[0]["outcome"] == "error"
+        assert "provider exploded" in rows[0]["error"]
+        assert rows[1]["outcome"] in ("real", "shadow", "tie")
+
+    async def test_the_turn_valve_counts_every_arm_a_start_will_write(self):
+        """max_turns is a row ceiling and one sampled request writes one row per arm, so
+        admission pre-counts the arms: a two-arm job with two turns of budget admits one
+        request, not two."""
+        prisma = _prisma()
+        router = _router(sibling_router_texts={"alt-router": "alt answer"})
+        logger = _logger(
+            router=router, prisma=prisma, jobs=(_job(router_names=("my-router", "alt-router"), max_turns=2),)
+        )
+
+        await logger.async_log_success_event(_success_kwargs(request_id="req-1"), RESPONSE, None, None)
+        await logger.async_log_success_event(_success_kwargs(request_id="req-2"), RESPONSE, None, None)
+        await _drain(logger)
+
+        rows = [call.kwargs["data"] for call in prisma.db.litellm_shadowevalattempt.create.await_args_list]
+        assert {row["request_id"] for row in rows} == {"req-1"}
+        assert len(rows) == 2
+
+    async def test_a_withheld_request_runs_no_arm_and_counts_once(self):
+        """The budget gates run once per sampled request, before any arm: funnel counters
+        stay per-request, so coverage math is arm-count independent."""
+        prisma = _prisma()
+        router = _router(sibling_router_texts={"alt-router": "alt answer"})
+        logger = _logger(router=router, prisma=prisma)
+
+        await logger._run_shadow_eval(
+            job=_job(router_names=("my-router", "alt-router"), max_budget=1.0, spend=2.0),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.0,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params={},
+            parent_metadata={},
+        )
+
+        router.acompletion.assert_not_called()
+        prisma.db.litellm_shadowevalattempt.create.assert_not_called()
+        assert logger._test_funnel == [("job-1", "withheld")]
+
+
 @pytest.mark.asyncio
 class TestActiveJobsFailClosed:
     async def test_a_row_the_sampler_cannot_read_is_dropped_not_guessed(self):
@@ -1249,13 +1481,14 @@ class TestActiveJobsFailClosed:
             jobs_cache=InMemoryCache(max_size_in_memory=4, default_ttl=60),
         )
 
-        assert [job.id for job in (await logger._active_jobs())["key-hash"]] == ["job-ok"]
+        assert [job.id for job in (await logger._active_jobs())[("key", "key-hash")]] == ["job-ok"]
 
-    async def test_both_of_a_key_s_jobs_survive_the_lookup(self):
+    async def test_every_targets_jobs_survive_the_lookup_keyed_by_type_and_id(self):
         records = [
             _job_record(_job(id="job-forward")),
             _job_record(_reverse_job(id="job-reverse")),
-            _job_record(_job(id="job-other"), api_key_id="other-key"),
+            _job_record(_job(id="job-other"), target_id="other-key"),
+            _job_record(_job(id="job-team"), target_type="team", target_id="team-eng"),
         ]
         prisma = _prisma(jobs=records, attempt_counts=[("job-reverse", 3)])
         logger = ShadowEvalLogger(
@@ -1266,9 +1499,11 @@ class TestActiveJobsFailClosed:
 
         jobs = await logger._active_jobs()
 
-        assert sorted(job.id for job in jobs["key-hash"]) == ["job-forward", "job-reverse"]
-        assert [job.id for job in jobs["other-key"]] == ["job-other"]
-        assert {job.id: job.attempts for job in jobs["key-hash"]}["job-reverse"] == 3
+        assert sorted(job.id for job in jobs[("key", "key-hash")]) == ["job-forward", "job-reverse"]
+        assert [job.id for job in jobs[("key", "other-key")]] == ["job-other"]
+        assert [job.id for job in jobs[("team", "team-eng")]] == ["job-team"]
+        assert ("team-eng",) not in jobs and "team-eng" not in jobs
+        assert {job.id: job.attempts for job in jobs[("key", "key-hash")]}["job-reverse"] == 3
 
 
 def _failing_router():
diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
index 3c4121977de..b7f0ca1efe1 100644
--- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
+++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
@@ -32,6 +32,8 @@ from litellm.litellm_core_utils.llm_cost_calc.utils import (
     TokenTypeCostBreakdown,
     _calculate_input_cost,
     _get_token_base_cost,
+    _is_off_peak,
+    _is_within_off_peak_window,
     calculate_cache_writing_cost,
     generic_cost_per_token,
     get_token_type_cost_breakdown,
@@ -409,6 +411,377 @@ def test_get_token_base_cost_picks_highest_crossed_tier():
     assert prompt_base_cost == 9e-6
 
 
+def test_is_within_off_peak_window_same_day():
+    from datetime import datetime, timezone
+
+    window = "09:00-17:00"
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 8, 59, tzinfo=timezone.utc)) is False
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 9, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 17, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_wraps_midnight():
+    from datetime import datetime, timezone
+
+    window = "16:30-00:30"
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 0, 15, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 0, 30, tzinfo=timezone.utc)) is False
+    assert _is_within_off_peak_window(window, datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_equal_start_and_end_covers_whole_day():
+    """An equal start and end is the natural way to spell off-peak all day. It used to take the
+    non-wrap branch, where start <= now < end can never hold, so it matched nothing and billed at
+    standard rates around the clock without raising or logging anything."""
+    from datetime import datetime, timezone
+
+    for window in ("00:00-00:00", "10:00-10:00"):
+        for hour in range(24):
+            assert (
+                _is_within_off_peak_window(window, datetime(2026, 1, 1, hour, 0, tzinfo=timezone.utc)) is True
+            ), f"{window} should cover {hour:02d}:00"
+
+
+def test_is_within_off_peak_window_multiple_windows():
+    from datetime import datetime, timezone
+
+    # Providers like DeepSeek V4 have more than one daily peak/off-peak window.
+    windows = ["01:00-05:00", "13:00-16:00"]
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 3, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 14, 30, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window(windows, datetime(2026, 1, 1, 9, 0, tzinfo=timezone.utc)) is False
+    # a malformed entry in the list is ignored, valid entries still match
+    assert _is_within_off_peak_window(["bad", "13:00-16:00"], datetime(2026, 1, 1, 14, 0, tzinfo=timezone.utc)) is True
+    assert _is_within_off_peak_window([], datetime(2026, 1, 1, 14, 0, tzinfo=timezone.utc)) is False
+
+
+def test_is_within_off_peak_window_normalizes_timezone_aware_input():
+    from datetime import datetime, timedelta, timezone
+
+    # A caller may pass a non-UTC aware datetime; the window is UTC and must be
+    # evaluated in UTC, not against the caller's wall-clock. 09:00 at UTC+8 is
+    # 01:00 UTC, inside the 01:00-05:00 window.
+    tz_plus_8 = timezone(timedelta(hours=8))
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 9, 0, tzinfo=tz_plus_8)) is True
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 12, 0, tzinfo=tz_plus_8)) is True
+    # 06:00 at UTC+8 is 22:00 UTC the previous day, outside the window
+    assert _is_within_off_peak_window("01:00-05:00", datetime(2026, 1, 1, 6, 0, tzinfo=tz_plus_8)) is False
+
+
+def test_is_within_off_peak_window_malformed_returns_false():
+    from datetime import datetime, timezone
+
+    now = datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)
+    assert _is_within_off_peak_window("not-a-window", now) is False
+    assert _is_within_off_peak_window("16:30", now) is False
+    assert _is_within_off_peak_window("25:00-26:00", now) is False
+
+
+def test_is_off_peak_weekday_qualified_windows_deepseek_schedule():
+    """DeepSeek since 2026-08-23: peak is 01:00-04:00 and 06:00-10:00 UTC on weekdays only, with
+    weekends off-peak around the clock. The weekday axis is not a filter on one window set; on
+    two days of seven the off-peak window becomes the whole day, so the schedule needs two
+    day-qualified rules. The weekend instants inside would-be peak hours are the ones a
+    time-only implementation bills wrong."""
+    from datetime import datetime, timezone
+
+    deepseek = {
+        "windows": [
+            {"hours_utc": ["00:00-01:00", "04:00-06:00", "10:00-00:00"], "weekdays": [1, 2, 3, 4, 5]},
+            {"hours_utc": "00:00-00:00", "weekdays": [6, 7]},
+        ],
+    }
+    peak_instants = [
+        datetime(2026, 8, 24, 1, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 26, 7, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 28, 9, 59, tzinfo=timezone.utc),
+    ]
+    off_peak_instants = [
+        datetime(2026, 8, 23, 1, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 29, 2, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 30, 8, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 26, 5, 0, tzinfo=timezone.utc),
+        datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc),
+        datetime(2026, 8, 24, 0, 30, tzinfo=timezone.utc),
+    ]
+    for when in peak_instants:
+        assert _is_off_peak(deepseek, when) is False, f"{when.isoformat()} should bill peak"
+    for when in off_peak_instants:
+        assert _is_off_peak(deepseek, when) is True, f"{when.isoformat()} should bill off-peak"
+
+
+def test_is_off_peak_weekday_timezone_reads_vendor_calendar():
+    """The UTC and Asia/Shanghai calendars only disagree about the date over 16:00-24:00 UTC, so
+    a window in that stretch is the one place a vendor-local weekday differs from a UTC one:
+    2026-08-28T16:30Z is Friday in UTC but already Saturday in Beijing."""
+    from datetime import datetime, timezone
+
+    shanghai_saturday = {
+        "weekday_timezone": "Asia/Shanghai",
+        "windows": [{"hours_utc": "16:00-17:00", "weekdays": [6]}],
+    }
+    assert _is_off_peak(shanghai_saturday, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(shanghai_saturday, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_weekdays_default_utc_calendar_and_accept_names():
+    from datetime import datetime, timezone
+
+    named_weekend = {"windows": [{"hours_utc": "00:00-00:00", "weekdays": ["Sat", "sunday"]}]}
+    assert _is_off_peak(named_weekend, datetime(2026, 8, 29, 12, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(named_weekend, datetime(2026, 8, 28, 12, 0, tzinfo=timezone.utc)) is False
+
+    utc_friday = {"windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(utc_friday, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(utc_friday, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_naive_current_time_read_as_utc():
+    from datetime import datetime
+
+    block = {"windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(block, datetime(2026, 8, 28, 16, 30)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 29, 16, 30)) is False
+
+
+def test_is_off_peak_invalid_weekday_timezone_falls_back_to_utc():
+    from datetime import datetime, timezone
+
+    block = {"weekday_timezone": "Not/AZone", "windows": [{"hours_utc": "16:00-17:00", "weekdays": [5]}]}
+    assert _is_off_peak(block, datetime(2026, 8, 28, 16, 30, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 29, 16, 30, tzinfo=timezone.utc)) is False
+
+
+def test_is_off_peak_ignores_malformed_weekday_rules():
+    from datetime import datetime, timezone
+
+    when = datetime(2026, 8, 29, 12, 0, tzinfo=timezone.utc)
+    assert _is_off_peak({"windows": [{"hours_utc": "00:00-00:00", "weekdays": []}]}, when) is False
+    assert _is_off_peak({"windows": [{"hours_utc": "00:00-00:00", "weekdays": [0, 8, "noday", True]}]}, when) is False
+    assert _is_off_peak({"windows": [{"weekdays": [6]}]}, when) is False
+    assert _is_off_peak({"windows": [{"hours_utc": 1630}]}, when) is False
+    assert _is_off_peak({"windows": ["00:00-00:00"]}, when) is False
+    assert _is_off_peak({"windows": "00:00-00:00"}, when) is False
+    assert _is_off_peak({"hours_utc": 1630}, when) is False
+    assert _is_off_peak({}, when) is False
+
+
+def test_is_off_peak_flat_hours_and_windows_are_a_union():
+    from datetime import datetime, timezone
+
+    block = {
+        "hours_utc": "04:00-06:00",
+        "windows": [{"hours_utc": "00:00-00:00", "weekdays": [7]}],
+    }
+    assert _is_off_peak(block, datetime(2026, 8, 28, 5, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 30, 20, 0, tzinfo=timezone.utc)) is True
+    assert _is_off_peak(block, datetime(2026, 8, 28, 20, 0, tzinfo=timezone.utc)) is False
+
+
+def test_get_token_base_cost_weekend_only_off_peak_rate():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "off_peak_pricing": {
+                "windows": [
+                    {"hours_utc": ["00:00-01:00", "04:00-06:00", "10:00-00:00"], "weekdays": [1, 2, 3, 4, 5]},
+                    {"hours_utc": "00:00-00:00", "weekdays": [6, 7]},
+                ],
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    saturday_peak_hours = _get_token_base_cost(
+        model_info, usage, current_time=datetime(2026, 8, 29, 2, 0, tzinfo=timezone.utc)
+    )
+    assert saturday_peak_hours[:2] == (5e-7, 1e-6)
+
+    monday_same_hours = _get_token_base_cost(
+        model_info, usage, current_time=datetime(2026, 8, 24, 2, 0, tzinfo=timezone.utc)
+    )
+    assert monday_same_hours[:2] == (1e-6, 2e-6)
+
+
+def test_get_token_base_cost_applies_off_peak_pricing():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "cache_read_input_token_cost": 1e-7,
+            "off_peak_pricing": {
+                "hours_utc": "16:30-00:30",
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+                "cache_read_input_token_cost": 5e-8,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    off_peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert off_peak[0] == 5e-7
+    assert off_peak[1] == 1e-6
+    assert off_peak[4] == 5e-8
+
+    peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert peak[0] == 1e-6
+    assert peak[1] == 2e-6
+    assert peak[4] == 1e-7
+
+
+def test_get_token_base_cost_non_mapping_off_peak_block_bills_standard_rates():
+    """A truthy non-mapping off_peak_pricing value (a bare string or a list in
+    YAML) must bill standard rates rather than raising, matching how every
+    other malformed piece of the block behaves.
+    """
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+    when = datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc)
+
+    for malformed_block in ("16:00-19:00", ["16:00-19:00"], 5e-7, True):
+        model_info = cast(
+            ModelInfo,
+            {
+                "input_cost_per_token": 1e-6,
+                "output_cost_per_token": 2e-6,
+                "off_peak_pricing": malformed_block,
+            },
+        )
+        result = _get_token_base_cost(model_info, usage, current_time=when)
+        assert result[0] == 1e-6
+        assert result[1] == 2e-6
+
+
+def test_get_token_base_cost_off_peak_falls_back_to_standard_when_unset():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "off_peak_pricing": {"hours_utc": "16:30-00:30", "input_cost_per_token": 5e-7},
+        },
+    )
+    usage = Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150)
+
+    result = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert result[0] == 5e-7
+    assert result[1] == 2e-6
+
+
+def test_get_token_base_cost_off_peak_wins_over_threshold():
+    from datetime import datetime, timezone
+    from typing import cast
+
+    from litellm.types.utils import ModelInfo
+
+    model_info = cast(
+        ModelInfo,
+        {
+            "input_cost_per_token": 1e-6,
+            "output_cost_per_token": 2e-6,
+            "input_cost_per_token_above_200k_tokens": 3e-6,
+            "output_cost_per_token_above_200k_tokens": 4e-6,
+            "off_peak_pricing": {
+                "hours_utc": "16:30-00:30",
+                "input_cost_per_token": 5e-7,
+                "output_cost_per_token": 1e-6,
+            },
+        },
+    )
+    usage = Usage(prompt_tokens=250000, completion_tokens=250000, total_tokens=500000)
+
+    off_peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert off_peak[0] == 5e-7
+    assert off_peak[1] == 1e-6
+
+    peak = _get_token_base_cost(model_info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert peak[0] == 3e-6
+    assert peak[1] == 4e-6
+
+
+def test_get_model_info_propagates_off_peak_fields():
+    model_name = "test-off-peak-model"
+    off_peak_pricing = {
+        "hours_utc": "16:30-00:30",
+        "input_cost_per_token": 5e-7,
+        "output_cost_per_token": 1e-6,
+        "cache_read_input_token_cost": 5e-8,
+    }
+    litellm.register_model(
+        {
+            model_name: {
+                "litellm_provider": "openai",
+                "mode": "chat",
+                "input_cost_per_token": 1e-6,
+                "output_cost_per_token": 2e-6,
+                "off_peak_pricing": off_peak_pricing,
+            }
+        }
+    )
+    info = litellm.get_model_info(model=model_name)
+    assert info["off_peak_pricing"] == off_peak_pricing
+
+
+def test_get_token_base_cost_off_peak_wins_over_tiered_pricing():
+    """Tiered pricing resolves base rates on its own path and returns early, so off-peak has to
+    be applied there too or a model carrying both would silently bill the tier rate all day."""
+    from datetime import datetime, timezone
+
+    model_name = "litellm-test-off-peak-tiered"
+    litellm.register_model(
+        {
+            model_name: {
+                "litellm_provider": "openai",
+                "mode": "chat",
+                "tiered_pricing": [
+                    {"range": [0, 128000], "input_cost_per_token": 3e-6, "output_cost_per_token": 6e-6},
+                ],
+                "off_peak_pricing": {
+                    "hours_utc": "16:30-00:30",
+                    "input_cost_per_token": 5e-7,
+                    "output_cost_per_token": 1e-6,
+                },
+            }
+        }
+    )
+    info = litellm.get_model_info(model=model_name)
+    usage = Usage(prompt_tokens=1_000, completion_tokens=100, total_tokens=1_100)
+
+    inside = _get_token_base_cost(info, usage, current_time=datetime(2026, 1, 1, 18, 0, tzinfo=timezone.utc))
+    assert inside[:2] == (5e-7, 1e-6)
+
+    outside = _get_token_base_cost(info, usage, current_time=datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc))
+    assert outside[:2] == (3e-6, 6e-6)
+
+
 def test_generic_cost_per_token_gpt54_above_272k_tokens(_local_model_cost_map):
     """GPT-5.4/5.4-pro: prompts >272K input tokens priced at 2x input, 1.5x output."""
     model = "gpt-5.4"
@@ -1149,7 +1522,7 @@ def test_gpt_5_6_alias_prices_match_sol(local_model_cost_map):
     sol = litellm.model_cost["gpt-5.6-sol"]
 
     cost_fields = sorted(field for field in sol if "cost" in field)
-    assert len(cost_fields) == 23
+    assert len(cost_fields) == 27
 
     for field in cost_fields:
         assert alias.get(field) == sol.get(field), field
@@ -3666,8 +4039,8 @@ def test_fast_service_tier_matches_priority_above_the_context_threshold(_local_m
     )
 
     assert fast == priority
-    assert fast[0] == pytest.approx(300_000 * 8e-06, rel=1e-9)
-    assert fast[1] == pytest.approx(1_000 * 3e-05, rel=1e-9)
+    assert fast[0] == pytest.approx(300_000 * 1.6e-05, rel=1e-9)
+    assert fast[1] == pytest.approx(1_000 * 6e-05, rel=1e-9)
 
 
 def test_priority_reasoning_tokens_bill_at_the_priority_output_rate(_local_model_cost_map):
@@ -3827,6 +4200,86 @@ def test_generic_cost_per_token_gemini_37_flash(_local_model_cost_map):
     assert completion_cost == pytest.approx(0.001875)
 
 
+GEMINI_38_FLASH_LAUNCH_PRICING = [
+    ("gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+    ("gemini/gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+    ("vertex_ai/gemini-3.8-flash", 7.5e-07, 3.75e-06, 7.5e-08),
+]
+
+
+@pytest.mark.parametrize("model,input_cost,output_cost,cache_read_cost", GEMINI_38_FLASH_LAUNCH_PRICING)
+def test_gemini_38_flash_launch_pricing(model, input_cost, output_cost, cache_read_cost, _local_model_cost_map):
+    model_cost_map = litellm.model_cost[model]
+    assert model_cost_map["input_cost_per_token"] == input_cost
+    assert model_cost_map["output_cost_per_token"] == output_cost
+    assert model_cost_map["output_cost_per_reasoning_token"] == output_cost
+    assert model_cost_map["cache_read_input_token_cost"] == cache_read_cost
+    assert model_cost_map["mode"] == "chat"
+    assert model_cost_map["supports_reasoning"] is True
+    assert model_cost_map["supports_function_calling"] is True
+    assert model_cost_map["max_input_tokens"] == 1048576
+
+
+GEMINI_38_FLASH_FIELDS_SHARED_WITH_37_FLASH = (
+    "input_cost_per_token",
+    "output_cost_per_token",
+    "output_cost_per_reasoning_token",
+    "cache_read_input_token_cost",
+    "input_cost_per_token_batches",
+    "output_cost_per_token_batches",
+    "input_cost_per_token_flex",
+    "output_cost_per_token_flex",
+    "cache_read_input_token_cost_flex",
+    "input_cost_per_token_priority",
+    "output_cost_per_token_priority",
+    "cache_read_input_token_cost_priority",
+    "search_context_cost_per_query",
+    "google_maps_grounding_cost_per_query",
+    "prompt_cache_min_tokens",
+    "max_input_tokens",
+    "max_output_tokens",
+    "supports_reasoning",
+    "supports_function_calling",
+    "supports_prompt_caching",
+    "supports_vision",
+    "supports_pdf_input",
+    "supports_audio_input",
+    "supports_video_input",
+    "supports_response_schema",
+    "supports_tool_choice",
+    "supports_web_search",
+    "supports_url_context",
+)
+
+
+@pytest.mark.parametrize("prefix", ["", "gemini/", "vertex_ai/"])
+def test_gemini_38_flash_matches_37_flash_promotional_pricing(prefix, _local_model_cost_map):
+    new_model = litellm.model_cost[f"{prefix}gemini-3.8-flash"]
+    old_model = litellm.model_cost[f"{prefix}gemini-3.7-flash"]
+    for field in GEMINI_38_FLASH_FIELDS_SHARED_WITH_37_FLASH:
+        assert new_model[field] == old_model[field], field
+
+
+def test_generic_cost_per_token_gemini_38_flash(_local_model_cost_map):
+    usage = Usage(
+        prompt_tokens=1000,
+        completion_tokens=500,
+        total_tokens=1500,
+        completion_tokens_details=CompletionTokensDetailsWrapper(
+            reasoning_tokens=200,
+            text_tokens=300,
+        ),
+        prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=1000),
+    )
+    prompt_cost, completion_cost = generic_cost_per_token(
+        model="gemini-3.8-flash",
+        usage=usage,
+        custom_llm_provider="gemini",
+    )
+    assert prompt_cost == pytest.approx(0.00075)
+    assert completion_cost == pytest.approx(0.001875)
+
+
 def test_grok_46_launch_pricing(_local_model_cost_map):
     model_cost_map = litellm.model_cost["xai/grok-4.6"]
     assert model_cost_map["input_cost_per_token"] == 2e-06
diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
index 772fbf98c57..c037f928593 100644
--- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
+++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
@@ -1433,3 +1433,124 @@ class TestFlattenTopLevelSchemaCombinators:
         flatten_top_level_schema_combinators(schema)
 
         assert schema == snapshot
+
+
+class TestToolWithFlattenedParameters:
+    def _anyof_tool(self):
+        return {
+            "type": "function",
+            "function": {
+                "name": "automation_update",
+                "description": "Update an automation",
+                "parameters": {
+                    "type": "object",
+                    "anyOf": [
+                        {
+                            "properties": {"id": {"type": "string"}, "enabled": {"type": "boolean"}},
+                            "required": ["id", "enabled"],
+                        },
+                        {
+                            "properties": {"id": {"type": "string"}, "schedule": {"type": "string"}},
+                            "required": ["id", "schedule"],
+                        },
+                    ],
+                    "properties": {"id": {"type": "string"}},
+                    "required": ["id"],
+                },
+            },
+        }
+
+    def test_flattens_anyof_parameters_into_new_tool(self):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        tool = self._anyof_tool()
+        result = tool_with_flattened_parameters(tool)
+
+        assert result is not tool
+        parameters = result["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert parameters["type"] == "object"
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+        assert parameters["required"] == ["id"]
+        assert result["function"]["name"] == "automation_update"
+        assert tool == self._anyof_tool()
+
+    def test_clean_parameters_return_the_same_tool_object(self):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        tool = {
+            "type": "function",
+            "function": {
+                "name": "lookup",
+                "parameters": {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["id"]},
+            },
+        }
+
+        assert tool_with_flattened_parameters(tool) is tool
+
+    @pytest.mark.parametrize(
+        "tool",
+        [
+            {"type": "function"},
+            {"type": "function", "function": "not-a-dict"},
+            {"type": "function", "function": {"name": "no_params"}},
+            {"type": "function", "function": {"name": "bad_params", "parameters": "not-a-dict"}},
+        ],
+    )
+    def test_non_dict_function_or_parameters_return_the_same_tool_object(self, tool):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        assert tool_with_flattened_parameters(tool) is tool
+
+
+class TestRequestContainsImageContent:
+    """One detector for every dialect that reaches pre-routing hooks untranslated."""
+
+    @pytest.mark.parametrize(
+        "part",
+        [
+            {"type": "image_url", "image_url": {"url": "data:image/png;base64,aGk="}},
+            {"type": "input_image", "image_url": "data:image/png;base64,aGk="},
+            {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "aGk="}},
+            {
+                "type": "tool_result",
+                "tool_use_id": "tu_1",
+                "content": [{"type": "image", "source": {"type": "base64", "data": "aGk="}}],
+            },
+        ],
+    )
+    def test_detects_every_image_dialect_including_tool_results(self, part):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content
+
+        messages = [{"role": "user", "content": [{"type": "text", "text": "hi"}, part]}]
+        assert request_contains_image_content(messages) is True
+
+    @pytest.mark.parametrize(
+        "messages",
+        [
+            [{"role": "user", "content": "plain string"}],
+            [{"role": "user", "content": [{"type": "text", "text": "hi"}]}],
+            [{"role": "user", "content": [{"type": "input_audio", "input_audio": {"data": "x"}}]}],
+            [{"role": "user", "content": [{"type": "tool_result", "content": [{"type": "text", "text": "ok"}]}]}],
+            [{"role": "user", "content": None}],
+            [],
+        ],
+    )
+    def test_ignores_text_audio_and_degenerate_shapes(self, messages):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content
+
+        assert request_contains_image_content(messages) is False
+
+    def test_hostile_nesting_is_depth_bounded(self):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content
+
+        nested: dict = {"type": "image", "source": {"type": "base64", "data": "aGk="}}
+        for _ in range(50):
+            nested = {"type": "tool_result", "content": [nested]}
+        assert request_contains_image_content([{"role": "user", "content": [nested]}]) is False
diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
index 72d26f31c60..dd2d45f00c6 100644
--- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
+++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_factory.py
@@ -2932,6 +2932,28 @@ def test_add_cache_point_tool_block_passes_ttl_for_claude_4_5(monkeypatch):
             monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", old_env)
 
 
+def test_add_cache_point_tool_block_stands_down_for_model_without_prompt_caching(monkeypatch):
+    """A tool carrying cache_control must not become a cachePoint for a Bedrock model
+    whose cost-map entry lacks prompt caching support, since Bedrock rejects the whole
+    request. An unmapped id keeps emitting so ARN deployments do not lose caching."""
+    from litellm.litellm_core_utils.prompt_templates.factory import (
+        add_cache_point_tool_block,
+    )
+
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    tool = {"cache_control": {"type": "ephemeral"}}
+
+    assert add_cache_point_tool_block(tool, model="nvidia.nemotron-super-3-120b") is None
+    assert add_cache_point_tool_block(tool, model="us.nvidia.nemotron-super-3-120b") is None
+    assert add_cache_point_tool_block(
+        tool, model="arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123"
+    ) == {"cachePoint": {"type": "default"}}
+    assert add_cache_point_tool_block(tool, model="us.anthropic.claude-sonnet-4-5-20250929-v1:0") == {
+        "cachePoint": {"type": "default"}
+    }
+
+
 def test_bedrock_tools_pt_passes_ttl_for_claude_4_5(monkeypatch):
     """
     End-to-end: _bedrock_tools_pt should produce cachePoint blocks with ttl
@@ -3627,3 +3649,67 @@ def test_convert_gemini_tool_call_result_answers_tool_reference_only_result():
     )
 
     assert result == {"function_response": {"name": "ToolSearch", "response": {"content": ""}}}
+
+
+def test_convert_to_anthropic_tool_invoke_degrades_unpaired_server_tool_use():
+    """A replayed srvtoolu_ call whose server tool result is not available
+    (e.g. the Responses bridge replays items without provider_specific_fields)
+    must become a plain client tool_use so the client's tool_result can pair
+    with it. A dangling server_tool_use makes Anthropic 400 the request with
+    "unexpected `tool_use_id` found in `tool_result` blocks"."""
+    from litellm.litellm_core_utils.prompt_templates.factory import convert_to_anthropic_tool_invoke
+
+    result = convert_to_anthropic_tool_invoke(
+        tool_calls=[
+            {
+                "id": "srvtoolu_01Unpaired",
+                "type": "function",
+                "function": {"name": "web_search", "arguments": '{"query": "zig version"}'},
+            }
+        ],
+        web_search_results=None,
+        tool_results=None,
+    )
+
+    assert result == [
+        {
+            "type": "tool_use",
+            "id": "srvtoolu_01Unpaired",
+            "name": "web_search",
+            "input": {"query": "zig version"},
+        }
+    ]
+
+
+def test_convert_to_anthropic_tool_invoke_keeps_paired_server_tool_use():
+    """When the paired server tool result is available, the srvtoolu_ call is
+    still reconstructed as server_tool_use followed by its result block."""
+    from litellm.litellm_core_utils.prompt_templates.factory import convert_to_anthropic_tool_invoke
+
+    server_result = {
+        "type": "web_search_tool_result",
+        "tool_use_id": "srvtoolu_01Paired",
+        "content": [{"type": "web_search_result", "url": "https://ziglang.org", "title": "Zig"}],
+    }
+
+    result = convert_to_anthropic_tool_invoke(
+        tool_calls=[
+            {
+                "id": "srvtoolu_01Paired",
+                "type": "function",
+                "function": {"name": "web_search", "arguments": '{"query": "zig version"}'},
+            }
+        ],
+        web_search_results=[server_result],
+        tool_results=None,
+    )
+
+    assert result == [
+        {
+            "type": "server_tool_use",
+            "id": "srvtoolu_01Paired",
+            "name": "web_search",
+            "input": {"query": "zig version"},
+        },
+        server_result,
+    ]
diff --git a/tests/test_litellm/litellm_core_utils/test_audio_utils.py b/tests/test_litellm/litellm_core_utils/test_audio_utils.py
index 0e8176fffce..155f6680416 100644
--- a/tests/test_litellm/litellm_core_utils/test_audio_utils.py
+++ b/tests/test_litellm/litellm_core_utils/test_audio_utils.py
@@ -347,3 +347,65 @@ class TestNormalizeTranscriptionLanguageToBcp47:
         )
 
         assert normalize_transcription_language_to_bcp47(language) == expected
+
+
+class TestResolveSpeechMediaType:
+    @pytest.mark.parametrize(
+        ("upstream_content_type", "response_format", "expected"),
+        [
+            ("audio/wav", None, "audio/wav"),
+            ("AUDIO/WAV", None, "audio/wav"),
+            ("audio/flac; charset=binary", "mp3", "audio/flac"),
+            ("application/json", "flac", "audio/flac"),
+            ("application/octet-stream", "pcm", "audio/pcm"),
+            (None, "wav", "audio/wav"),
+            (None, "WAV", "audio/wav"),
+            (None, "opus", "audio/opus"),
+            (None, "aac", "audio/aac"),
+            (None, "mp3", "audio/mpeg"),
+            (None, "mp4", "audio/mpeg"),
+            (None, "bogus", "audio/mpeg"),
+            (None, None, "audio/mpeg"),
+            ("", None, "audio/mpeg"),
+        ],
+    )
+    def test_resolution(self, upstream_content_type, response_format, expected):
+        from litellm.litellm_core_utils.audio_utils.utils import resolve_speech_media_type
+
+        resolved = resolve_speech_media_type(
+            upstream_content_type=upstream_content_type,
+            response_format=response_format,
+        )
+        assert resolved == expected
+
+
+class TestSpeechMediaTypeFromAudioBytes:
+    @pytest.mark.parametrize(
+        ("audio", "expected"),
+        [
+            (b"RIFF\x24\x00\x00\x00WAVEfmt ", "audio/wav"),
+            (b"fLaC\x00\x00\x00\x22", "audio/flac"),
+            (b"OggS" + b"\x00" * 24 + b"OpusHead", "audio/opus"),
+            (b"OggS" + b"\x00" * 24 + b"\x01vorbis", "audio/ogg"),
+            (b"ID3\x04\x00\x00\x00\x00\x00\x00", "audio/mpeg"),
+            (b"\xff\xfb\x90\x64", "audio/mpeg"),
+            (b"\xff\xf3\x80\x00", "audio/mpeg"),
+            (b"\xff\xf1\x50\x80", "audio/aac"),
+            (b"\xff\xf9\x50\x80", "audio/aac"),
+            (b"RIFF\x24\x00\x00\x00AVI LIST", None),
+            (b"\xff\xff\xff\xff\xff\xff", None),
+            (b"\xff\xfb\xf0\x00", None),
+            (b"\xff\xfb\x9c\x00", None),
+            (b"\xff\xeb\x90\x00", None),
+            (b"\xff\xf1\xf4\x80", None),
+            (b"\xff\x00\x00\x00", None),
+            (b"\x00\x01\x02\x03\x04\x05", None),
+            (b"\xff\xfb", None),
+            (b"\xff", None),
+            (b"", None),
+        ],
+    )
+    def test_sniffing(self, audio, expected):
+        from litellm.litellm_core_utils.audio_utils.utils import speech_media_type_from_audio_bytes
+
+        assert speech_media_type_from_audio_bytes(audio) == expected
diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
index 0587628e2fe..b1e8163b91d 100644
--- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
+++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
@@ -366,7 +366,7 @@ def test_shipped_rules_stack_adaptive_and_mid_conversation_flags(shipped_cost_ma
 def test_shipped_rules_flag_unmapped_fable_as_always_on_thinking(shipped_cost_map):
     """An unmapped Fable/Mythos id picks up ``thinking_always_on`` from the
     claude-always-on-thinking rule, while other unmapped Claudes stay unflagged."""
-    model = "claude-fable-5-1"
+    model = "claude-fable-6-1"
     assert model not in litellm.model_cost
     info = litellm.get_model_info(model, custom_llm_provider="anthropic")
     assert info["thinking_always_on"] is True
@@ -419,7 +419,7 @@ def test_shipped_rules_cover_new_families_like_fable_at_5_plus(shipped_cost_map)
     """Both version gates accept any claude-<family>- id at major 5 or higher, bare
     major or major-minor, so a new family shaped like claude-fable-5 gets adaptive
     thinking and mid-conversation system support without a cost-map entry."""
-    model = "claude-fable-5-1"
+    model = "claude-fable-6-1"
     assert model not in litellm.model_cost
     info = litellm.get_model_info(model, custom_llm_provider="anthropic")
     assert info["supports_mid_conversation_system"] is True
diff --git a/tests/test_litellm/litellm_core_utils/test_get_llm_provider_endpoint_match.py b/tests/test_litellm/litellm_core_utils/test_get_llm_provider_endpoint_match.py
index 6cacd119030..419ca104bb1 100644
--- a/tests/test_litellm/litellm_core_utils/test_get_llm_provider_endpoint_match.py
+++ b/tests/test_litellm/litellm_core_utils/test_get_llm_provider_endpoint_match.py
@@ -184,3 +184,26 @@ class TestTogetherApiBaseResolvesProvider:
 
         assert provider == "together_ai"
         assert api_base == "https://api.together.ai/v1"
+
+
+class TestGigachatApiBaseResolvesProvider:
+    """
+    Regression for the GigaChat api_base branch: the provider-mapping chain
+    carried an ``endpoint == "https://gigachat.devices.sberbank.ru/api/v1"``
+    elif, but the URL was never added to ``openai_compatible_endpoints``, so
+    the endpoint loop never fired the branch and a caller-supplied GigaChat
+    api_base raised BadRequestError instead of resolving to ``gigachat``.
+    """
+
+    def test_gigachat_api_base_resolves_to_gigachat(self, monkeypatch):
+        monkeypatch.setenv("GIGACHAT_API_KEY", "gigachat-key-from-env")
+
+        model, provider, dynamic_api_key, returned_api_base = get_llm_provider(
+            model="GigaChat-2",
+            api_base="https://gigachat.devices.sberbank.ru/api/v1",
+        )
+
+        assert provider == "gigachat"
+        assert dynamic_api_key == "gigachat-key-from-env"
+        assert returned_api_base == "https://gigachat.devices.sberbank.ru/api/v1"
+        assert model == "GigaChat-2"
diff --git a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
index 8c0e8ee5d02..a374e03d1c7 100644
--- a/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
+++ b/tests/test_litellm/litellm_core_utils/test_get_model_cost_map.py
@@ -256,14 +256,12 @@ def test_get_model_cost_map_stamps_loaded_at(monkeypatch):
     from litellm.litellm_core_utils import get_model_cost_map as module
 
     monkeypatch.setattr(module._cost_map_source_info, "loaded_at", None)
-    monkeypatch.setattr(
-        module.GetModelCostMap,
-        "fetch_remote_model_cost_map",
-        staticmethod(lambda url, timeout=5: _load_root_cost_map()),
+    client, _calls = _mock_client(
+        [httpx.Response(200, content=_real_map_bytes())], client_cls=httpx.Client
     )
 
     before = datetime.now(timezone.utc)
-    module.get_model_cost_map(url="https://example.invalid/cost_map.json")
+    module.get_model_cost_map(url="https://example.invalid/cost_map.json", client=client)
     loaded_at = module.get_model_cost_map_loaded_at()
 
     assert loaded_at is not None
@@ -308,7 +306,7 @@ def _unset_local_cost_map_env(monkeypatch):
     monkeypatch.delenv("LITELLM_LOCAL_MODEL_COST_MAP", raising=False)
 
 
-def _mock_client(outcomes):
+def _mock_client(outcomes, client_cls=httpx.AsyncClient):
     """httpx client over a MockTransport serving one outcome per request; an exception instance is raised."""
     calls = {"count": 0}
 
@@ -320,7 +318,7 @@ def _mock_client(outcomes):
             raise outcome
         return outcome
 
-    return httpx.AsyncClient(transport=httpx.MockTransport(handler)), calls
+    return client_cls(transport=httpx.MockTransport(handler)), calls
 
 
 @pytest.mark.asyncio
@@ -450,3 +448,97 @@ async def test_refetch_respects_local_env_override(monkeypatch):
     )
     assert isinstance(result, ModelCostMapReloaded)
     assert len(result.model_cost_map) > 100
+
+
+# ---------------------------------------------------------------------------
+# get_model_cost_map: the boot-time load retries transient failures like a reload does
+# ---------------------------------------------------------------------------
+
+from litellm.litellm_core_utils.get_model_cost_map import (
+    get_model_cost_map,
+    get_model_cost_map_source_info,
+)
+
+
+class _SyncSleepRecorder:
+    """Injected in place of time.sleep so the boot path's waits are asserted without delay."""
+
+    def __init__(self):
+        self.waits = []
+
+    def __call__(self, seconds: float) -> None:
+        self.waits.append(seconds)
+
+
+def test_boot_load_retries_transient_failures_instead_of_falling_back():
+    """A refused connection then a 503 at pod boot used to pin the process to the bundled
+    backup for its lifetime; both are transient and must be retried before giving up."""
+    client, calls = _mock_client(
+        [
+            httpx.ConnectError("connection refused"),
+            httpx.Response(503),
+            httpx.Response(200, content=_real_map_bytes()),
+        ],
+        client_cls=httpx.Client,
+    )
+    sleeper = _SyncSleepRecorder()
+
+    cost_map = get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+
+    assert calls["count"] == 3
+    assert len(sleeper.waits) == 2
+    assert 2.0 <= sleeper.waits[0] < 3.0
+    assert 4.0 <= sleeper.waits[1] < 5.0
+    source = get_model_cost_map_source_info()
+    assert source["source"] == "remote"
+    assert source["fallback_reason"] is None
+    assert cost_map.keys() >= _load_root_cost_map().keys() - {"sample_spec", FALLBACK_GENERALIZATIONS_KEY}
+
+
+def test_boot_load_honors_retry_after_then_falls_back_after_max_attempts():
+    """An outage longer than the retry budget still ends on the bundled backup, and the
+    recorded fallback reason says how many attempts were spent so operators can tell."""
+    client, calls = _mock_client(
+        [httpx.Response(429, headers={"Retry-After": "7"})], client_cls=httpx.Client
+    )
+    sleeper = _SyncSleepRecorder()
+
+    cost_map = get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+
+    assert calls["count"] == 3
+    assert sleeper.waits == [7.0, 7.0]
+    source = get_model_cost_map_source_info()
+    assert source["source"] == "local"
+    assert "after 3 attempts" in source["fallback_reason"]
+    assert len(cost_map) > 100
+
+
+def test_boot_load_does_not_retry_permanent_failures():
+    """A 404 or a malformed URL cannot heal by waiting: one attempt, no sleeps, backup."""
+    client, calls = _mock_client([httpx.Response(404)], client_cls=httpx.Client)
+    sleeper = _SyncSleepRecorder()
+
+    get_model_cost_map(url=_URL, sleep=sleeper, rng=random.Random(0), client=client)
+    assert calls["count"] == 1
+    assert sleeper.waits == []
+    assert get_model_cost_map_source_info()["source"] == "local"
+
+    get_model_cost_map(url="not a url", sleep=sleeper, rng=random.Random(0))
+    assert sleeper.waits == []
+    assert get_model_cost_map_source_info()["source"] == "local"
+
+
+def test_boot_load_respects_local_env_override(monkeypatch):
+    """LITELLM_LOCAL_MODEL_COST_MAP=True still short-circuits to the backup with zero HTTP."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+
+    def _fail(request):
+        raise AssertionError("no HTTP request should be made when local map is forced")
+
+    cost_map = get_model_cost_map(
+        url=_URL,
+        sleep=_SyncSleepRecorder(),
+        client=httpx.Client(transport=httpx.MockTransport(_fail)),
+    )
+    assert len(cost_map) > 100
+    assert get_model_cost_map_source_info()["is_env_forced"] is True
diff --git a/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py b/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py
index cb4e72ab3ad..722818598af 100644
--- a/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py
+++ b/tests/test_litellm/litellm_core_utils/test_get_supported_openai_params.py
@@ -188,6 +188,8 @@ class TestDeclaredAuthenticatingProvider:
             ("gpt-4o", "github_copilot", "github_copilot"),
             ("openai/gpt-4o", None, None),
             ("gpt-4o", "openai", None),
+            ("github_copilot", None, None),
+            ("chatgpt", None, None),
         ],
     )
     def test_names_only_the_providers_whose_resolution_authenticates(self, model, provider, expected):
diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
index 947a55410ef..f1de7390b5b 100644
--- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
+++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py
@@ -5479,6 +5479,97 @@ def test_pre_call_redacts_and_masks_raw_request(logging_obj):
     assert "key=*****" in raw_api_base
 
 
+def _streaming_logging_obj_with_callbacks(callbacks: list[CustomLogger]):
+    import datetime
+
+    obj = LitellmLogging(
+        model="anthropic/claude-opus-5",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=True,
+        call_type="completion",
+        start_time=datetime.datetime.now(),
+        litellm_call_id="slot-leak-test",
+        function_id="slot-leak-test",
+    )
+    obj.model_call_details["litellm_params"] = {"metadata": {}}
+    return patch.object(obj, "get_combined_callback_list", return_value=callbacks), obj
+
+
+def _assembled_stream_result():
+    response = ModelResponse()
+    response.choices[0].message.content = "hello"
+    return response
+
+
+@pytest.mark.asyncio
+async def test_streaming_success_callbacks_survive_logging_hook_failure():
+    """Regression for leaked max_parallel_requests slots: a raising
+    async_logging_hook must not abort the success-callback loop that
+    releases the rate-limiter slot."""
+    broken = CustomLogger()
+    broken.async_logging_hook = AsyncMock(side_effect=RuntimeError("broken stream payload"))
+    releasing = CustomLogger()
+    releasing.async_log_success_event = AsyncMock()
+
+    patcher, logging_obj = _streaming_logging_obj_with_callbacks([broken, releasing])
+    with patcher:
+        await logging_obj.async_success_handler(result=_assembled_stream_result())
+
+    releasing.async_log_success_event.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_streaming_success_callbacks_survive_cost_calculation_failure():
+    releasing = CustomLogger()
+    releasing.async_log_success_event = AsyncMock()
+
+    patcher, logging_obj = _streaming_logging_obj_with_callbacks([releasing])
+    with patcher, patch.object(
+        logging_obj, "_response_cost_calculator", side_effect=ValueError("bad usage block")
+    ):
+        await logging_obj.async_success_handler(result=_assembled_stream_result())
+
+    assert logging_obj.model_call_details["response_cost"] is None
+    releasing.async_log_success_event.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_streaming_success_callbacks_survive_standard_logging_payload_failure():
+    releasing = CustomLogger()
+    releasing.async_log_success_event = AsyncMock()
+
+    patcher, logging_obj = _streaming_logging_obj_with_callbacks([releasing])
+    with patcher, patch.object(
+        logging_obj, "_build_standard_logging_payload", side_effect=ValueError("incomplete stream")
+    ):
+        await logging_obj.async_success_handler(result=_assembled_stream_result())
+
+    assert logging_obj.model_call_details.get("standard_logging_object") is None
+    releasing.async_log_success_event.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_streaming_success_callbacks_survive_guardrail_logging_hook_failure():
+    from litellm.integrations.custom_guardrail import CustomGuardrail
+
+    skipping = CustomGuardrail(guardrail_name="skipping-guardrail")
+    skipping.should_run_guardrail = MagicMock(return_value=False)
+    skipping.async_logging_hook = AsyncMock()
+    raising = CustomGuardrail(guardrail_name="raising-guardrail")
+    raising.should_run_guardrail = MagicMock(return_value=True)
+    raising.async_logging_hook = AsyncMock(side_effect=RuntimeError("guardrail hook failed"))
+    releasing = CustomLogger()
+    releasing.async_log_success_event = AsyncMock()
+
+    patcher, logging_obj = _streaming_logging_obj_with_callbacks([skipping, raising, releasing])
+    with patcher:
+        await logging_obj.async_success_handler(result=_assembled_stream_result())
+
+    skipping.async_logging_hook.assert_not_awaited()
+    raising.async_logging_hook.assert_awaited_once()
+    releasing.async_log_success_event.assert_awaited_once()
+
+
 def _resolve(custom_llm_provider, litellm_params, optional_params, model):
     from litellm.litellm_core_utils.litellm_logging import (
         _resolve_vertex_location_for_cost,
@@ -5911,7 +6002,9 @@ async def test_prompt_hook_injection_marker_recorded_for_every_surface(logging_o
     """The savings gate reads litellm_gateway_injected_cache from the request's
     metadata bucket. Recording lives in the shared prompt-hook wrappers, so chat,
     /v1/responses, router prompt deployments, and proxy prompt templates all mark
-    injected requests the same way; a hook that injects nothing leaves no marker."""
+    injected requests the same way; a hook that injects nothing leaves no marker.
+    A pass that runs before deployment choice declares it and gets the every-deployment
+    sentinel, which a later per-deployment pass never narrows."""
     from litellm.integrations.custom_prompt_management import CustomPromptManagement
 
     class _InjectingHook(CustomPromptManagement):
@@ -5995,6 +6088,28 @@ async def test_prompt_hook_injection_marker_recorded_for_every_surface(logging_o
     )
     assert "litellm_gateway_injected_cache" not in untouched["metadata"]
 
+    pre_choice = {"metadata": {}, "model_info": {"id": "dep-of-this-attempt"}}
+    logging_obj.get_chat_completion_prompt(
+        model="claude-sonnet-5",
+        messages=[{"role": "user", "content": "hi"}],
+        non_default_params={},
+        prompt_variables=None,
+        prompt_management_logger=_InjectingHook(),
+        request_kwargs=pre_choice,
+        injected_for_every_deployment=True,
+    )
+    assert pre_choice["metadata"]["litellm_gateway_injected_cache"] == ""
+
+    await logging_obj.async_get_chat_completion_prompt(
+        model="claude-sonnet-5",
+        messages=[{"role": "user", "content": "a fresh turn"}],
+        non_default_params={},
+        prompt_variables=None,
+        prompt_management_logger=_InjectingHook(),
+        request_kwargs=pre_choice,
+    )
+    assert pre_choice["metadata"]["litellm_gateway_injected_cache"] == ""
+
 
 def test_get_standard_logging_object_payload_reads_overhead_from_logging_obj_for_dict_results(logging_obj):
     """LIT-5466: /v1/messages returns a plain dict with no _hidden_params, so the overhead
@@ -6101,3 +6216,64 @@ def test_response_timing_metrics_survive_deepcopy(logging_obj):
     logging_obj.set_response_timing_metrics({"_response_ms": 12.5})
 
     assert copy.deepcopy(logging_obj).response_timing_metrics == {"_response_ms": 12.5}
+
+
+def test_passthrough_embeddings_result_swapped_for_callbacks():
+    """
+    Regression: for gigachat passthrough /embeddings, normalize_logging_result
+    produces an EmbeddingResponse, but the result swap only accepted
+    ModelResponse, so callbacks kept receiving the raw httpx.Response (which
+    crashes attribute readers like OTEL). The swap must cover
+    EmbeddingResponse too.
+    """
+    import datetime as dt
+
+    from litellm.types.utils import EmbeddingResponse
+
+    logging_obj = LitellmLogging(
+        model="EmbeddingsGigaR",
+        messages=[],
+        stream=False,
+        call_type="allm_passthrough_route",
+        start_time=time.time(),
+        litellm_call_id="passthrough-embed-call-id",
+        function_id="passthrough-embed-fn-id",
+    )
+    logging_obj.update_environment_variables(
+        litellm_params={},
+        optional_params={},
+        model="EmbeddingsGigaR",
+        custom_llm_provider="gigachat",
+        endpoint="/embeddings",
+        request_data={"model": "EmbeddingsGigaR", "input": ["hello"]},
+        input=["hello"],
+    )
+
+    httpx_response = httpx.Response(
+        200,
+        json={
+            "object": "list",
+            "data": [
+                {
+                    "object": "embedding",
+                    "embedding": [0.1, 0.2, 0.3],
+                    "index": 0,
+                    "usage": {"prompt_tokens": 5},
+                }
+            ],
+            "model": "EmbeddingsGigaR",
+        },
+        request=httpx.Request(
+            "POST", "https://gigachat.devices.sberbank.ru/api/v1/embeddings"
+        ),
+    )
+
+    _, _, swapped_result = logging_obj._success_handler_helper_fn(
+        result=httpx_response,
+        start_time=dt.datetime.now(),
+        end_time=dt.datetime.now(),
+        cache_hit=False,
+    )
+
+    assert isinstance(swapped_result, EmbeddingResponse)
+    assert swapped_result.data[0]["embedding"] == [0.1, 0.2, 0.3]
diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
index 8ac050a04f9..bacbcbf132b 100644
--- a/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
+++ b/tests/test_litellm/litellm_core_utils/test_streaming_chunk_builder_utils.py
@@ -592,6 +592,59 @@ def test_stream_chunk_builder_litellm_usage_chunks():
     assert usage.total_tokens == 77
 
 
+def test_calculate_usage_honors_openai_sdk_completion_usage_chunks():
+    from openai.types.completion_usage import CompletionUsage
+
+    content_chunk = ModelResponseStream(
+        id="chatcmpl-sdk-usage-1",
+        created=1745513206,
+        model="mantle-claude",
+        object="chat.completion.chunk",
+        system_fingerprint=None,
+        choices=[
+            StreamingChoices(
+                finish_reason="stop",
+                index=0,
+                delta=Delta(
+                    provider_specific_fields=None,
+                    content="ok",
+                    role=None,
+                    function_call=None,
+                    tool_calls=None,
+                    audio=None,
+                ),
+                logprobs=None,
+            )
+        ],
+        provider_specific_fields=None,
+        stream_options={"include_usage": True},
+    )
+    usage_chunk = ModelResponseStream(
+        id="chatcmpl-sdk-usage-1",
+        created=1745513207,
+        model="mantle-claude",
+        object="chat.completion.chunk",
+        system_fingerprint=None,
+        choices=[],
+        provider_specific_fields=None,
+        stream_options={"include_usage": True},
+    )
+    usage_chunk.usage = CompletionUsage(
+        prompt_tokens=20, completion_tokens=60, total_tokens=80, cost=0.000704
+    )
+    assert type(usage_chunk.usage) is CompletionUsage
+
+    chunks = [content_chunk, usage_chunk]
+    usage = ChunkProcessor(chunks=chunks).calculate_usage(
+        chunks=chunks, model="mantle-claude", completion_output=""
+    )
+
+    assert usage.prompt_tokens == 20
+    assert usage.completion_tokens == 60
+    assert usage.total_tokens == 80
+    assert getattr(usage, "cost", None) == pytest.approx(0.000704)
+
+
 def test_get_model_from_chunks_azure_model_router():
     """
     Test that _get_model_from_chunks finds the actual model from Azure Model Router chunks.
diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
index 7f54fbfb4c2..4c99bce2b0f 100644
--- a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
+++ b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
@@ -4692,3 +4692,82 @@ async def test_async_stream_assembled_response_keeps_vertex_traffic_type(logging
     assembled = litellm.stream_chunk_builder(chunks=received, messages=[{"role": "user", "content": "hi"}])
     assert assembled is not None
     assert assembled._hidden_params["provider_specific_fields"]["traffic_type"] == "ON_DEMAND_FLEX"
+
+
+class TestStableStreamingResponseId:
+    """
+    All chunks of one streamed response must share the same top-level id
+    (OpenAI streaming contract). Providers streaming via GenericStreamingChunk
+    (e.g. GigaChat) do not propagate an upstream response id, so
+    CustomStreamWrapper must pin the id from the first chunk it creates,
+    mirroring the existing `created` pinning (issue #11437).
+
+    Clients such as goose merge streamed deltas into one assistant message by
+    chunk id; per-chunk ids split a single reply into many messages.
+    """
+
+    def test_generic_chunks_share_one_id(self):
+        def _generic_chunks():
+            return iter(
+                [
+                    {
+                        "text": "Hello",
+                        "tool_use": None,
+                        "is_finished": False,
+                        "finish_reason": "",
+                        "usage": None,
+                        "index": 0,
+                    },
+                    {
+                        "text": " world",
+                        "tool_use": None,
+                        "is_finished": False,
+                        "finish_reason": "",
+                        "usage": None,
+                        "index": 0,
+                    },
+                    {
+                        "text": "",
+                        "tool_use": None,
+                        "is_finished": True,
+                        "finish_reason": "stop",
+                        "usage": {
+                            "prompt_tokens": 1,
+                            "completion_tokens": 2,
+                            "total_tokens": 3,
+                        },
+                        "index": 0,
+                    },
+                ]
+            )
+
+        wrapper = CustomStreamWrapper(
+            completion_stream=_generic_chunks(),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        ids = [chunk.id for chunk in wrapper if chunk.id]
+        assert ids, "no chunks emitted"
+        assert len(set(ids)) == 1, f"chunk ids differ across one stream: {ids}"
+
+    def test_creator_pins_id_from_first_chunk(self):
+        wrapper = CustomStreamWrapper(
+            completion_stream=iter([]),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        first = wrapper.model_response_creator()
+        assert wrapper.response_id == first.id
+        assert wrapper.model_response_creator().id == first.id
+
+    def test_provider_supplied_id_still_wins(self):
+        wrapper = CustomStreamWrapper(
+            completion_stream=iter([]),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        wrapper.response_id = "chatcmpl-from-provider"
+        assert wrapper.model_response_creator().id == "chatcmpl-from-provider"
diff --git a/tests/test_litellm/litellm_core_utils/test_token_counter.py b/tests/test_litellm/litellm_core_utils/test_token_counter.py
index 572b505e94c..4694fa8fbed 100644
--- a/tests/test_litellm/litellm_core_utils/test_token_counter.py
+++ b/tests/test_litellm/litellm_core_utils/test_token_counter.py
@@ -1377,3 +1377,38 @@ def test_anthropic_document_title_and_context_add_their_tokens():
             {"type": "document", "source": source},
         ]
     )
+
+
+def test_openai_file_block_prices_like_the_equivalent_anthropic_document():
+    """An inline `file` is a `document` in the chat-completions dialect, so it must price identically, not raise.
+
+    Before the fix `file` was missing from the content-block match even though `ChatCompletionFileObject`
+    is in the union this counter accepts, so every local count of a Responses `input_file` raised
+    `Invalid content item type: file` and surfaced as a 500 on /v1/responses/input_tokens.
+    """
+    prompt = {"type": "text", "text": "Summarize this file."}
+    inline_file = {
+        "type": "file",
+        "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0xLjQK"},
+    }
+    document = {
+        "type": "document",
+        "title": "report.pdf",
+        "source": {"type": "base64", "media_type": "application/pdf", "data": "JVBERi0xLjQK"},
+    }
+
+    assert _count_user_content([prompt, inline_file]) == _count_user_content([prompt, document])
+    assert _count_user_content([prompt, inline_file]) > _count_user_content([prompt])
+
+
+def test_openai_file_block_without_inline_bytes_counts_what_it_carries():
+    """A `file` block naming an uploaded file has no bytes to price, so it adds only the filename's tokens."""
+    prompt = {"type": "text", "text": "Summarize this file."}
+
+    by_id = {"type": "file", "file": {"file_id": "file-abc123"}}
+    assert _count_user_content([prompt, by_id]) == _count_user_content([prompt])
+
+    named = {"type": "file", "file": {"file_id": "file-abc123", "filename": "report.pdf"}}
+    assert _count_user_content([prompt, named]) == _count_user_content(
+        [prompt, {"type": "text", "text": "report.pdf"}]
+    )
diff --git a/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py b/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py
index af3ccd65b11..0fe7730e91e 100644
--- a/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py
+++ b/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py
@@ -1490,6 +1490,92 @@ class MockCanaryMaskingGuardrail(CustomGuardrail):
         return inputs
 
 
+class TestAnthropicMessagesImageSources:
+    """An Anthropic image block has three source shapes (`AnthropicMessagesImageParam.source`).
+
+    Only the base64 one carries "data", so reading that key alone drops url images
+    entirely -- for every guardrail consuming GenericGuardrailAPIInputs["images"],
+    not just Bedrock.
+    """
+
+    def _data(self, messages):
+        return {"model": "claude-sonnet-4-5", "messages": messages}
+
+    async def _images_seen(self, content) -> list[str]:
+        handler = AnthropicMessagesHandler()
+
+        class ImageRecordingGuardrail(MockCanaryMaskingGuardrail):
+            def __init__(self):
+                super().__init__()
+                self.seen_images: list[str] = []  # mutable-ok: accumulator for the assertion
+
+            async def apply_guardrail(self, inputs, request_data, input_type, logging_obj=None):
+                self.seen_images.extend(inputs.get("images") or [])
+                return await super().apply_guardrail(inputs, request_data, input_type, logging_obj)
+
+        guardrail = ImageRecordingGuardrail()
+        # The text block is what gets the guardrail invoked at all: a message with
+        # no text gives the handler nothing to scan, so it never reaches the
+        # guardrail and every source shape would look equally "dropped".
+        await handler.process_input_messages(
+            data=self._data([{"role": "user", "content": [{"type": "text", "text": "describe it"}, *content]}]),
+            guardrail_to_apply=guardrail,
+        )
+        return guardrail.seen_images
+
+    @pytest.mark.asyncio
+    async def test_url_source_reaches_the_guardrail(self):
+        """A url source has no "data" key, so it used to yield nothing at all."""
+        seen = await self._images_seen(
+            [{"type": "image", "source": {"type": "url", "url": "https://example.com/a.png"}}]
+        )
+
+        assert seen == ["https://example.com/a.png"]
+
+    @pytest.mark.asyncio
+    async def test_base64_source_carries_its_media_type(self):
+        """Bare base64 leaves the consumer no way to recover the format.
+
+        An API like Bedrock's ApplyGuardrail needs it to build the request, so the
+        media_type travels with the payload as a data URI.
+        """
+        seen = await self._images_seen(
+            [{"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "AAAA"}}]
+        )
+
+        assert seen == ["data:image/png;base64,AAAA"]
+
+    @pytest.mark.asyncio
+    async def test_base64_source_without_a_media_type_is_passed_through(self):
+        """There is no format to attach, so the payload goes through unchanged."""
+        seen = await self._images_seen([{"type": "image", "source": {"type": "base64", "data": "AAAA"}}])
+
+        assert seen == ["AAAA"]
+
+    @pytest.mark.asyncio
+    async def test_file_source_yields_nothing(self):
+        """The bytes live behind the Files API and this extractor has no client.
+
+        Documented as a known gap rather than silently handed on as a file_id string,
+        which a consumer would try to decode as an image.
+        """
+        seen = await self._images_seen([{"type": "image", "source": {"type": "file", "file_id": "file_abc"}}])
+
+        assert seen == []
+
+    @pytest.mark.asyncio
+    async def test_a_malformed_source_is_dropped_rather_than_passed_on(self):
+        seen = await self._images_seen(
+            [
+                {"type": "image", "source": {"type": "base64"}},
+                {"type": "image", "source": {"type": "url"}},
+                {"type": "image", "source": {"type": "base64", "data": ""}},
+            ]
+        )
+
+        assert seen == []
+
+
 class TestAnthropicMessagesToolResultScanning:
     """LIT-5251: tool_result blocks carry whatever a client's local tool fetched, so
     they are the request-path payload an indirect prompt injection actually arrives in.
diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
index bd750a47f63..043537f8c1f 100644
--- a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
+++ b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_handler.py
@@ -3,11 +3,13 @@ import threading
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
 from unittest.mock import AsyncMock, MagicMock, patch
 
+import httpx
 import pytest
 
 import litellm
 from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.llms.anthropic.chat.handler import ModelResponseIterator, make_call
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
 from litellm.types.llms.openai import (
     ChatCompletionToolCallChunk,
     ChatCompletionToolCallFunctionChunk,
@@ -46,6 +48,43 @@ async def test_make_call_passes_logging_obj_to_client_post():
     assert call_kwargs.get("logging_obj") is logging_obj
 
 
+def test_anthropic_completion_does_not_send_deployment_default_limits():
+    captured_requests: list[httpx.Request] = []
+
+    def respond(request: httpx.Request) -> httpx.Response:
+        captured_requests.append(request)
+        return httpx.Response(
+            200,
+            json={
+                "id": "msg_default_limits",
+                "type": "message",
+                "role": "assistant",
+                "model": "claude-3-5-haiku-20241022",
+                "content": [{"type": "text", "text": "Hello"}],
+                "stop_reason": "end_turn",
+                "stop_sequence": None,
+                "usage": {"input_tokens": 1, "output_tokens": 1},
+            },
+        )
+
+    client = HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(respond)))
+    try:
+        litellm.completion(
+            model="anthropic/claude-3-5-haiku-20241022",
+            messages=[{"role": "user", "content": "Hello"}],
+            api_key="test-key",
+            client=client,
+            default_api_key_rpm_limit=60,
+            default_api_key_tpm_limit=5000000,
+        )
+    finally:
+        client.close()
+
+    request_body = json.loads(captured_requests[0].content)
+    assert "default_api_key_rpm_limit" not in request_body
+    assert "default_api_key_tpm_limit" not in request_body
+
+
 def test_redacted_thinking_content_block_delta():
     chunk = {
         "type": "content_block_start",
diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py
index 25e2c3cda80..8ea8db5fb65 100644
--- a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py
+++ b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py
@@ -3127,6 +3127,31 @@ def test_reasoning_effort_accepts_dict_shape_for_non_adaptive_model(
     )
 
 
+@pytest.mark.parametrize(
+    "model,budget_tokens,expected",
+    [
+        ("claude-opus-4-8", 4096, ({"type": "adaptive"}, {"effort": "high"})),
+        ("claude-opus-4-7", 24000, ({"type": "adaptive"}, {"effort": "xhigh"})),
+        ("claude-opus-4-6", 4096, ({"type": "enabled", "budget_tokens": 4096}, None)),
+        ("claude-sonnet-4-5-20250929", 4096, ({"type": "enabled", "budget_tokens": 4096}, None)),
+    ],
+)
+def test_legacy_thinking_translated_to_adaptive_on_adaptive_only_models(model, budget_tokens, expected):
+    """Adaptive-only models reject thinking={type: enabled} with a 400, so the
+    legacy shape must be upgraded to adaptive + output_config.effort on
+    /chat/completions too, while models that accept it keep the caller's budget."""
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"thinking": {"type": "enabled", "budget_tokens": budget_tokens}, "max_tokens": 64000},
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+
+    assert (result["thinking"], result.get("output_config")) == expected
+
+
 @pytest.mark.parametrize(
     "bad_value",
     [
@@ -6176,9 +6201,10 @@ def test_is_anthropic_usage_object_rejects_responses_api_usage():
     [
         # always-on-thinking models reject thinking.type=disabled with a 400
         ("claude-fable-5", True),
+        ("claude-fable-5-1", True),
         ("claude-mythos-5", True),
         # unmapped future family member -> claude-always-on-thinking fallback rule
-        ("claude-fable-5-1", True),
+        ("claude-fable-6-1", True),
         # adaptive-capable models that ACCEPT disabled must keep it verbatim
         ("claude-opus-5", False),
         ("claude-sonnet-5", False),
@@ -6207,3 +6233,179 @@ def test_disabled_thinking_omitted_only_for_always_on_models(
         assert "thinking" not in request
     else:
         assert request["thinking"] == {"type": "disabled"}
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "required"}, {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_raises_clean_error_on_fable_5_1_without_drop_params(
+    local_model_cost_map, tool_choice, monkeypatch
+):
+    """Fable 5.1 400s on tool_choice type any/tool (thinking is always on and a
+    forced call would skip it); without drop_params the caller gets a clean
+    client-side 400 that explains the workaround, not a provider error."""
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    with pytest.raises(litellm.utils.UnsupportedParamsError, match="forced tool use"):
+        config.map_openai_params(
+            non_default_params={"tool_choice": tool_choice},
+            optional_params={},
+            model="claude-fable-5-1",
+            drop_params=False,
+        )
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "required"}, {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_downgraded_to_auto_on_fable_5_1_with_drop_params(
+    local_model_cost_map, tool_choice
+):
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": tool_choice},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto"}
+
+
+def test_forced_tool_choice_downgrade_keeps_parallel_tool_calls_flag(local_model_cost_map):
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required", "parallel_tool_calls": False},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto", "disable_parallel_tool_use": True}
+
+
+@pytest.mark.parametrize("tool_choice, expected_type", [("auto", "auto"), ("none", "none")])
+def test_unforced_tool_choice_forwarded_on_fable_5_1(
+    local_model_cost_map, tool_choice, expected_type, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": tool_choice},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=False,
+    )
+
+    assert result["tool_choice"]["type"] == expected_type
+
+
+@pytest.mark.parametrize("model", ["claude-fable-5", "claude-opus-5", "claude-sonnet-5"])
+def test_forced_tool_choice_forwarded_on_models_that_support_it(
+    local_model_cost_map, model, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required"},
+        optional_params={},
+        model=model,
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "any"}
+
+
+def test_forced_tool_choice_gating_driven_by_model_map_flag(local_model_cost_map, monkeypatch):
+    """The gate must read ``supports_forced_tool_use`` from the model map, not
+    the model name: a flagged entry gates a model whose name says nothing."""
+    monkeypatch.setitem(litellm.model_cost, "claude-zeta-9", {"supports_forced_tool_use": False})
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required"},
+        optional_params={},
+        model="claude-zeta-9",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto"}
+
+
+def test_anthropic_drop_params_keeps_format_only_output_config(monkeypatch):
+    """``drop_params=True`` must not consume ``output_config.format``: the drop
+    gate is an effort gate and ``format`` is a structured-output field."""
+    monkeypatch.setattr(litellm, "drop_params", True)
+    config = AnthropicConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"z": {"type": "integer"}}},
+    }
+
+    result = config.transform_request(
+        model="claude-3-haiku-20240307",
+        messages=[{"role": "user", "content": "Hello"}],
+        optional_params={"output_config": {"format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_anthropic_drop_params_reduces_mixed_output_config_to_format(monkeypatch):
+    """``drop_params=True`` drops the effort key on unsupported models but keeps
+    ``format`` so structured outputs still reach the provider."""
+    monkeypatch.setattr(litellm, "drop_params", True)
+    config = AnthropicConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"z": {"type": "integer"}}},
+    }
+
+    result = config.transform_request(
+        model="claude-3-haiku-20240307",
+        messages=[{"role": "user", "content": "Hello"}],
+        optional_params={"output_config": {"effort": "low", "format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_response_format_tool_path_skips_forced_tool_choice_when_unsupported(local_model_cost_map, monkeypatch):
+    """Backstop: on the tool-based structured-output path, a model flagged
+    ``supports_forced_tool_use: false`` must not get the forced response-format
+    tool_choice the provider would 400 on."""
+    monkeypatch.setitem(
+        litellm.model_cost,
+        "claude-test-no-forced-tools",
+        {"litellm_provider": "anthropic", "mode": "chat", "supports_forced_tool_use": False},
+    )
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "test_schema",
+                    "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+                },
+            }
+        },
+        optional_params={},
+        model="claude-test-no-forced-tools",
+        drop_params=False,
+    )
+
+    assert "tools" in result
+    assert "tool_choice" not in result
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_stop_reason.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_stop_reason.py
new file mode 100644
index 00000000000..4b95b36fec3
--- /dev/null
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_stop_reason.py
@@ -0,0 +1,79 @@
+"""
+Regression tests for issue #34692.
+
+ollama_chat streams tool_calls in a mid-stream chunk while its final
+(``done: true``) chunk carries only ``done_reason: "stop"``. The provider
+iterator must remember the earlier tool_calls and stamp
+``finish_reason="tool_calls"`` on the final chunk, so the Anthropic
+``/v1/messages`` bridge emits ``stop_reason: "tool_use"``. Before the fix the
+bridge emitted ``stop_reason: "end_turn"`` and Anthropic tool-runners
+(Claude Code, ``messages.stream``) silently dropped the tool call.
+"""
+
+import pytest
+
+from litellm.llms.anthropic.experimental_pass_through.adapters.streaming_iterator import (
+    AnthropicStreamWrapper,
+)
+from litellm.llms.ollama.chat.transformation import (
+    OllamaChatCompletionResponseIterator,
+)
+from litellm.types.utils import ModelResponseStream
+
+_OLLAMA_TOOL_CHUNK = {
+    "model": "qwen3:8b",
+    "message": {
+        "role": "assistant",
+        "content": "",
+        "tool_calls": [{"function": {"name": "get_weather", "arguments": {"city": "San Francisco"}}}],
+    },
+    "done": False,
+}
+_OLLAMA_DONE_CHUNK = {
+    "model": "qwen3:8b",
+    "message": {"role": "assistant", "content": ""},
+    "done": True,
+    "done_reason": "stop",
+    "prompt_eval_count": 100,
+    "eval_count": 20,
+}
+
+
+def _ollama_streamed_chunks() -> list[ModelResponseStream]:
+    iterator = OllamaChatCompletionResponseIterator(streaming_response=iter([]), sync_stream=True)
+    return [iterator.chunk_parser(_OLLAMA_TOOL_CHUNK), iterator.chunk_parser(_OLLAMA_DONE_CHUNK)]
+
+
+class _AsyncStream:
+    def __init__(self, items: list[ModelResponseStream]):
+        self._it = iter(items)
+
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self):
+        try:
+            return next(self._it)
+        except StopIteration:
+            raise StopAsyncIteration
+
+
+def _assert_tool_use_stop_reason(events: list[dict]) -> None:
+    block_types = [e["content_block"]["type"] for e in events if e.get("type") == "content_block_start"]
+    assert "tool_use" in block_types, f"no tool_use content block opened: {events}"
+    message_deltas = [e for e in events if e.get("type") == "message_delta"]
+    assert message_deltas, f"no message_delta emitted: {events}"
+    assert message_deltas[-1]["delta"]["stop_reason"] == "tool_use", (
+        f"expected stop_reason 'tool_use', got: {message_deltas[-1]}"
+    )
+
+
+def test_ollama_mid_stream_tool_call_yields_tool_use_stop_reason_sync():
+    wrapper = AnthropicStreamWrapper(completion_stream=iter(_ollama_streamed_chunks()), model="qwen3:8b")
+    _assert_tool_use_stop_reason(list(wrapper))
+
+
+@pytest.mark.asyncio
+async def test_ollama_mid_stream_tool_call_yields_tool_use_stop_reason_async():
+    wrapper = AnthropicStreamWrapper(completion_stream=_AsyncStream(_ollama_streamed_chunks()), model="qwen3:8b")
+    _assert_tool_use_stop_reason([event async for event in wrapper])
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
index ad4c3d6bfbb..e819433c269 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py
@@ -296,21 +296,15 @@ async def test_bedrock_converse_budget_tokens_preserved():
         mock_acompletion.assert_called_once()
 
         call_kwargs = mock_acompletion.call_args.kwargs
-        print(
-            "acompletion call kwargs: ", json.dumps(call_kwargs, indent=4, default=str)
-        )
+        print("acompletion call kwargs: ", json.dumps(call_kwargs, indent=4, default=str))
 
         # Verify thinking parameter is passed through with budget_tokens preserved
         thinking_param = call_kwargs.get("thinking")
-        assert (
-            thinking_param is not None
-        ), "thinking parameter should be passed to acompletion"
-        assert (
-            thinking_param.get("type") == "enabled"
-        ), "thinking.type should be 'enabled'"
-        assert (
-            thinking_param.get("budget_tokens") == 1024
-        ), f"thinking.budget_tokens should be 1024, but got {thinking_param.get('budget_tokens')}"
+        assert thinking_param is not None, "thinking parameter should be passed to acompletion"
+        assert thinking_param.get("type") == "enabled", "thinking.type should be 'enabled'"
+        assert thinking_param.get("budget_tokens") == 1024, (
+            f"thinking.budget_tokens should be 1024, but got {thinking_param.get('budget_tokens')}"
+        )
 
 
 def test_openai_model_with_thinking_converts_to_reasoning():
@@ -342,23 +336,18 @@ def test_openai_model_with_thinking_converts_to_reasoning():
         call_kwargs = mock_responses.call_args.kwargs
 
         # Verify reasoning is set (converted from thinking)
-        assert (
-            "reasoning" in call_kwargs
-        ), "reasoning should be passed to litellm.responses"
+        assert "reasoning" in call_kwargs, "reasoning should be passed to litellm.responses"
 
         # budget_tokens=1024 -> effort="low" (at the LOW budget threshold)
         # reasoning_auto_summary is False by default, so no summary key
         expected_reasoning = {"effort": "low"}
         assert call_kwargs["reasoning"] == expected_reasoning, (
-            f"reasoning should be {expected_reasoning} for budget_tokens=1024, "
-            f"got {call_kwargs.get('reasoning')}"
+            f"reasoning should be {expected_reasoning} for budget_tokens=1024, got {call_kwargs.get('reasoning')}"
         )
         assert "summary" not in call_kwargs["reasoning"]
 
         # Verify thinking is NOT passed directly to the Responses API
-        assert (
-            "thinking" not in call_kwargs
-        ), "thinking should NOT be passed directly to litellm.responses"
+        assert "thinking" not in call_kwargs, "thinking should NOT be passed directly to litellm.responses"
 
 
 class TestThinkingParameterTransformation:
@@ -411,9 +400,7 @@ class TestThinkingParameterTransformation:
                 thinking=thinking,
                 model="openai/gpt-5.2",
             )
-            assert result == {
-                "reasoning_effort": {"effort": "high", "summary": "detailed"}
-            }
+            assert result == {"reasoning_effort": {"effort": "high", "summary": "detailed"}}
         finally:
             litellm.reasoning_auto_summary = original
 
@@ -611,9 +598,9 @@ class TestThinkingSummaryPreservation:
             mock_responses.assert_called_once()
             call_kwargs = mock_responses.call_args.kwargs
             reasoning = call_kwargs["reasoning"]
-            assert (
-                reasoning["summary"] == "concise"
-            ), f"Expected summary='concise', got summary='{reasoning.get('summary')}'"
+            assert reasoning["summary"] == "concise", (
+                f"Expected summary='concise', got summary='{reasoning.get('summary')}'"
+            )
 
     def test_responses_adapter_preserves_summary(self):
         """translate_thinking_to_reasoning should include summary when user provides it."""
@@ -622,9 +609,7 @@ class TestThinkingSummaryPreservation:
         )
 
         thinking = {"type": "enabled", "budget_tokens": 5000, "summary": "concise"}
-        result = LiteLLMAnthropicToResponsesAPIAdapter.translate_thinking_to_reasoning(
-            thinking
-        )
+        result = LiteLLMAnthropicToResponsesAPIAdapter.translate_thinking_to_reasoning(thinking)
         assert result == {"effort": "high", "summary": "concise"}
 
     def test_responses_adapter_no_summary_by_default(self):
@@ -638,11 +623,7 @@ class TestThinkingSummaryPreservation:
         try:
             litellm.reasoning_auto_summary = False
             thinking = {"type": "enabled", "budget_tokens": 5000}
-            result = (
-                LiteLLMAnthropicToResponsesAPIAdapter.translate_thinking_to_reasoning(
-                    thinking
-                )
-            )
+            result = LiteLLMAnthropicToResponsesAPIAdapter.translate_thinking_to_reasoning(thinking)
             assert result == {"effort": "high"}
             assert result is not None and "summary" not in result
         finally:
@@ -659,9 +640,7 @@ class TestThinkingSummaryPreservation:
             thinking=thinking,
             model="openai/gpt-5.2",
         )
-        assert result == {
-            "reasoning_effort": {"effort": "high", "summary": "concise"}
-        }
+        assert result == {"reasoning_effort": {"effort": "high", "summary": "concise"}}
 
     def test_translate_thinking_for_model_disabled_stays_plain_string_when_auto_summary_enabled(self):
         """Disabled thinking must stay a plain string even when reasoning_auto_summary is on."""
@@ -807,9 +786,7 @@ def test_presanitized_flag_not_leaked_to_provider_params():
 
     def fake_base_handler(*args, **kwargs):
         captured.update(kwargs)
-        captured["optional"] = kwargs.get(
-            "anthropic_messages_optional_request_params", {}
-        )
+        captured["optional"] = kwargs.get("anthropic_messages_optional_request_params", {})
         return "stub"
 
     with patch.object(
@@ -974,6 +951,38 @@ def test_gate_passthrough_skipped_when_only_chat_completions_supported(monkeypat
     assert "config" not in captured
 
 
+@pytest.mark.parametrize(
+    "model_info, expected_ttl_support",
+    [
+        ({"supported_endpoints": ["/v1/messages"]}, False),
+        ({"supported_endpoints": ["/v1/messages"], "cache_control_ttl": True}, True),
+        ({"supported_endpoints": ["/v1/messages"], "cache_control_ttl": "yes"}, False),
+    ],
+)
+def test_gate_passthrough_forwards_cache_control_ttl_only_when_deployment_opts_in(
+    monkeypatch, model_info, expected_ttl_support
+):
+    """The passthrough config strips cache_control.ttl unless the deployment sets
+    model_info.cache_control_ttl to exactly true."""
+    from litellm.llms.anthropic.experimental_pass_through.messages.handler import (
+        anthropic_messages_handler,
+    )
+
+    captured, _ = _gate_stubs(monkeypatch)
+
+    result = anthropic_messages_handler(
+        max_tokens=100,
+        messages=[{"role": "user", "content": "Hello"}],
+        model="openai/some-model",
+        api_key="sk-test",
+        api_base="https://host/v1",
+        model_info=model_info,
+    )
+
+    assert result == "native-passthrough"
+    assert captured["config"].supports_cache_control_ttl() is expected_ttl_support
+
+
 def test_first_party_claude_4_8_plus_cost_map_entries_carry_mid_conversation_system_flag():
     """Regional and provider-prefixed Claude 4.8+/5 entries carry
     ``supports_mid_conversation_system``, but the bare first-party keys
@@ -987,9 +996,7 @@ def test_first_party_claude_4_8_plus_cost_map_entries_carry_mid_conversation_sys
 
     import litellm
 
-    cost_map_path = os.path.join(
-        os.path.dirname(litellm.__file__), "model_prices_and_context_window_backup.json"
-    )
+    cost_map_path = os.path.join(os.path.dirname(litellm.__file__), "model_prices_and_context_window_backup.json")
     with open(cost_map_path) as f:
         cost_map = json.load(f)
     rules = cost_map["fallback_generalizations"]["rules"]
@@ -1028,9 +1035,7 @@ def test_first_party_claude_4_8_plus_cost_map_entries_carry_mid_conversation_sys
         ("perplexity/sonar", "sonar", "https://api.perplexity.ai/chat/completions"),
     ],
 )
-async def test_messages_strips_provider_prefix_exactly_once(
-    requested_model, expected_wire_model, expected_url
-):
+async def test_messages_strips_provider_prefix_exactly_once(requested_model, expected_wire_model, expected_url):
     """
     BerriAI/litellm#37716: only the leading provider segment may be stripped on the way upstream.
 
diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py
index b8ce11db8d1..11a048edc1f 100644
--- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py
+++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py
@@ -6,9 +6,7 @@ import pytest
 
 
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-from litellm.llms.anthropic.experimental_pass_through.messages import (
-    streaming_iterator as streaming_iterator_module,
-)
+from litellm.llms.anthropic.experimental_pass_through.messages import streaming_iterator as streaming_iterator_module
 from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
     INCOMPLETE_STREAM_ERROR_MESSAGE,
     AnthropicMessagesStreamHiddenParams,
@@ -338,47 +336,6 @@ async def _events_then_hang(events):
     await asyncio.Event().wait()
 
 
-@pytest.mark.asyncio
-async def test_async_sse_wrapper_logs_partial_chunks_on_client_disconnect():
-    """
-    Regression test for LIT-5839: a client disconnect tears the generator
-    down with GeneratorExit at the yield, which used to skip the post-loop
-    logging dispatch entirely, so the partial output tokens the provider
-    already generated (and billed) never reached spend tracking.
-    """
-    iterator = _RecordingLoggingIterator(
-        litellm_logging_obj=_make_logging_obj("test_disconnect_logs_partial_chunks"),
-        request_body={},
-    )
-    wrapped = iterator.async_sse_wrapper(_events_then_hang(TRUNCATED_TOOL_USE_EVENTS))
-    streamed = [await wrapped.__anext__() for _ in range(len(TRUNCATED_TOOL_USE_EVENTS))]
-    assert iterator.logging_call_count == 0
-
-    await wrapped.aclose()
-
-    assert iterator.logging_call_count == 1
-    assert iterator.logged_chunks == streamed
-
-
-@pytest.mark.asyncio
-async def test_async_sse_wrapper_logs_partial_chunks_on_cancellation():
-    iterator = _RecordingLoggingIterator(
-        litellm_logging_obj=_make_logging_obj("test_cancellation_logs_partial_chunks"),
-        request_body={},
-    )
-    wrapped = iterator.async_sse_wrapper(_events_then_hang(TRUNCATED_TOOL_USE_EVENTS))
-    streamed = [await wrapped.__anext__() for _ in range(len(TRUNCATED_TOOL_USE_EVENTS))]
-
-    consume_task = asyncio.ensure_future(wrapped.__anext__())
-    await asyncio.sleep(0.01)
-    consume_task.cancel()
-    with pytest.raises(asyncio.CancelledError):
-        await consume_task
-
-    assert iterator.logging_call_count == 1
-    assert iterator.logged_chunks == streamed
-
-
 @pytest.mark.asyncio
 async def test_async_sse_wrapper_skips_logging_on_disconnect_before_first_chunk():
     iterator = _RecordingLoggingIterator(
@@ -408,6 +365,561 @@ def test_incomplete_stream_error_sse_event_is_valid_anthropic_error():
     assert event.endswith("\n\n")
 
 
+_STREAM_PREFIX = (
+    {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 52, "output_tokens": 1}}},
+    {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}},
+    {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "The Roman"}},
+)
+_STREAM_TAIL = (
+    {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": " Empire ..."}},
+    {"type": "content_block_stop", "index": 0},
+    {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 64}},
+    {"type": "message_stop"},
+)
+
+
+def _output_tokens_from_logged_chunks(chunks: list[bytes]) -> int | None:
+    """Read the last output_tokens the billing path would see from the SSE bytes."""
+    latest: int | None = None
+    for raw in chunks:
+        for line in raw.decode().splitlines():
+            if not line.startswith("data:"):
+                continue
+            data = json.loads(line[len("data:"):].strip())
+            usage = data.get("usage") if isinstance(data, dict) else None
+            if isinstance(usage, dict) and usage.get("output_tokens") is not None:
+                latest = usage["output_tokens"]
+    return latest
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_bills_full_stream_after_client_disconnect():
+    """
+    Regression: on a client disconnect mid-stream the upstream provider keeps
+    generating (and billing) the full response. The wrapper must keep draining
+    that upstream to its terminal ``message_delta`` and bill the real
+    output_tokens (64), not the partial count the client drained before leaving
+    (the message_start placeholder, 1).
+
+    A ``tail_gated`` event holds back the stream tail until the client has
+    disconnected, so the tail can only be captured by a drain that survives the
+    client teardown - exactly the path the previous implementation dropped.
+    """
+    tail_gated = asyncio.Event()
+    upstream_fully_drained = asyncio.Event()
+
+    async def _gated_stream():
+        for event in _STREAM_PREFIX:
+            yield event
+        await tail_gated.wait()
+        for event in _STREAM_TAIL:
+            yield event
+        upstream_fully_drained.set()
+
+    iterator = _RecordingLoggingIterator(
+        litellm_logging_obj=_make_logging_obj("test_bills_full_stream_after_disconnect"),
+        request_body={},
+    )
+
+    gen = iterator.async_sse_wrapper(_gated_stream())
+
+    client_chunks = []
+    async for chunk in gen:
+        client_chunks.append(chunk)
+        if len(client_chunks) == len(_STREAM_PREFIX):
+            break
+    await gen.aclose()
+
+    tail_gated.set()
+    await asyncio.wait_for(upstream_fully_drained.wait(), timeout=5)
+    for _ in range(100):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0.01)
+
+    assert len(client_chunks) == len(_STREAM_PREFIX)
+
+    assert iterator.logged_chunks, "pump never billed after client disconnect"
+    assert _output_tokens_from_logged_chunks(iterator.logged_chunks) == 64
+    assert any(c.startswith(b"event: message_stop\n") for c in iterator.logged_chunks)
+    assert not any(c.startswith(b"event: error\n") for c in iterator.logged_chunks)
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_bills_full_stream_when_client_reads_all():
+    """Happy path: when the client drains the whole stream, billing still sees
+    the terminal output_tokens (64) and the client gets every chunk."""
+    tail_gated = asyncio.Event()
+    tail_gated.set()  # no gating; full stream flows immediately
+
+    async def _full_stream():
+        for event in (*_STREAM_PREFIX, *_STREAM_TAIL):
+            yield event
+
+    iterator = _RecordingLoggingIterator(
+        litellm_logging_obj=_make_logging_obj("test_bills_full_stream_happy_path"),
+        request_body={},
+    )
+    client_chunks = [chunk async for chunk in iterator.async_sse_wrapper(_full_stream())]
+
+    for _ in range(100):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0.01)
+
+    assert len(client_chunks) == len(_STREAM_PREFIX) + len(_STREAM_TAIL)
+    assert _output_tokens_from_logged_chunks(iterator.logged_chunks) == 64
+    assert not any(c.startswith(b"event: error\n") for c in iterator.logged_chunks)
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_dispatches_deferred_logging_when_client_disconnects_mid_tail():
+    """
+    Regression: when the pump finishes draining while the client is still
+    connected, ``_handle_streaming_logging`` defers billing for the proxy's
+    post-response hook (``ProxyLogging._fire_deferred_stream_logging``), which
+    only fires on a normally completed response. If the client then disconnects
+    before consuming the queued tail, the response generator tears down via
+    GeneratorExit and that hook never runs. The relay teardown must dispatch
+    the stored deferred billing itself, or the request logs no spend at all.
+    """
+    dispatched = []
+    deferred_fired = asyncio.Event()
+
+    def _deferred_stream_complete(logging_coroutine):
+        dispatched.append(logging_coroutine)
+
+        async def _consume():
+            logging_coroutine.close()
+            deferred_fired.set()
+
+        return _consume()
+
+    logging_obj = _make_logging_obj("test_deferred_dispatch_on_disconnect_mid_tail")
+    logging_obj._on_deferred_stream_complete = _deferred_stream_complete
+    iterator = BaseAnthropicMessagesStreamingIterator(litellm_logging_obj=logging_obj, request_body={})
+
+    async def _full_stream():
+        for event in (*_STREAM_PREFIX, *_STREAM_TAIL):
+            yield event
+
+    gen = iterator.async_sse_wrapper(_full_stream())
+    client_chunks = []
+    async for chunk in gen:
+        client_chunks.append(chunk)
+        if len(client_chunks) == len(_STREAM_PREFIX):
+            break
+
+    for _ in range(100):
+        if getattr(logging_obj, "_deferred_stream_complete_args", None) is not None:
+            break
+        await asyncio.sleep(0.01)
+    assert getattr(logging_obj, "_deferred_stream_complete_args", None) is not None, "pump never deferred billing"
+
+    await gen.aclose()
+
+    assert len(dispatched) == 1, "relay teardown did not dispatch the deferred billing"
+    assert logging_obj._on_deferred_stream_complete is None
+    assert logging_obj._deferred_stream_complete_args is None
+    await asyncio.wait_for(deferred_fired.wait(), timeout=5)
+
+
+class _ProviderStreamError(Exception):
+    """Stand-in for a provider-specific streaming failure carrying a status code."""
+
+    def __init__(self, message: str, status_code: int):
+        super().__init__(message)
+        self.status_code = status_code
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_reraises_upstream_error_to_connected_client():
+    """
+    Regression: an upstream failure (Bedrock read / decode / chunk-conversion)
+    before message_stop must propagate the ORIGINAL provider exception to a
+    still-connected client, so the proxy's failure handling keeps the
+    provider-specific status. The pump must not swallow it into a generic
+    api_error event + normal termination.
+    """
+
+    async def _failing_stream():
+        yield {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 52, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "partial"}}
+        raise _ProviderStreamError("bedrock stream blew up", status_code=529)
+
+    iterator = _RecordingLoggingIterator(
+        litellm_logging_obj=_make_logging_obj("test_reraises_upstream_error"),
+        request_body={},
+    )
+
+    received = []
+
+    async def _drain():
+        async for chunk in iterator.async_sse_wrapper(_failing_stream()):
+            received.append(chunk)
+
+    with pytest.raises(_ProviderStreamError) as excinfo:
+        await _drain()
+
+    assert excinfo.value.status_code == 529
+    assert received
+    assert not any(c.startswith(b"event: error\n") for c in received)
+    assert iterator.logged_chunks == []
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_salvages_partial_spend_on_upstream_error_after_disconnect():
+    """
+    When the upstream errors AFTER the client has already disconnected there is
+    no live client to re-raise to and no failure hook will run, so the pump
+    salvages partial spend from what it collected instead of dropping the row.
+    """
+    tail_gated = asyncio.Event()
+
+    async def _gated_failing_stream():
+        yield {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 52, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "partial"}}
+        await tail_gated.wait()
+        raise _ProviderStreamError("late failure", status_code=500)
+
+    iterator = _RecordingLoggingIterator(
+        litellm_logging_obj=_make_logging_obj("test_salvage_partial_on_late_error"),
+        request_body={},
+    )
+
+    gen = iterator.async_sse_wrapper(_gated_failing_stream())
+    received = [await gen.__anext__(), await gen.__anext__()]
+    await gen.aclose()  # client disconnects before the upstream error
+
+    tail_gated.set()  # let the upstream raise now, after disconnect
+    for _ in range(100):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0.01)
+
+    assert len(received) == 2
+    assert iterator.logged_chunks == received
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_salvages_spend_when_queued_error_is_never_consumed():
+    """
+    When the upstream errors while the client is still connected, the pump
+    forwards the exception through the queue expecting the relay to re-raise it
+    into the proxy's failure handling. If the client disconnects before
+    consuming that queued exception, the handoff never happens and no failure
+    hook runs, so the pump must notice the unconsumed exception at teardown and
+    salvage partial spend instead of dropping the row entirely.
+    """
+    upstream_errored = asyncio.Event()
+
+    async def _failing_stream():
+        yield {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 52, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "partial"}}
+        upstream_errored.set()
+        raise _ProviderStreamError("mid-stream failure", status_code=500)
+
+    iterator = _RecordingLoggingIterator(
+        litellm_logging_obj=_make_logging_obj("test_salvage_on_unconsumed_queued_error"),
+        request_body={},
+    )
+
+    gen = iterator.async_sse_wrapper(_failing_stream())
+    received = [await gen.__anext__(), await gen.__anext__()]
+    await upstream_errored.wait()  # exception is now queued behind the consumed chunks
+    await gen.aclose()  # client disconnects without ever consuming the queued exception
+
+    for _ in range(100):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0.01)
+
+    assert iterator.logging_call_count == 1
+    assert iterator.logged_chunks == received
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_applies_backpressure_to_slow_client(monkeypatch):
+    """
+    Regression: the relay queue is bounded, so a slow client throttles the
+    upstream read instead of letting the pump buffer the whole response in
+    memory. With a tiny queue and a client that reads a single chunk, the pump
+    must stall after producing only a queue's worth of chunks ahead, not race
+    to the end of a large stream.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 2)
+
+    total = 200
+    produced = 0
+
+    async def _fast_stream():
+        nonlocal produced
+        for i in range(total):
+            produced += 1
+            yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": f"t{i}"}}
+
+    iterator = _make_iterator("test_backpressure_slow_client")
+    gen = iterator.async_sse_wrapper(_fast_stream())
+    try:
+        await gen.__anext__()
+        for _ in range(500):
+            await asyncio.sleep(0)
+        assert produced <= 2 + 3, f"pump ran ahead unthrottled: produced {produced} of {total}"
+        assert produced < total
+    finally:
+        await gen.aclose()
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_bills_partial_when_detached_drain_cap_reached(monkeypatch):
+    """
+    Regression: when the concurrent detached-drain cap is already reached, a
+    pump whose client has disconnected must bill what it collected instead of
+    continuing to drain (and accumulating) the rest of a large upstream stream,
+    so slow/abandoned clients can't pin unbounded worker state.
+
+    The cap slot set is pre-occupied so the single slot is unavailable when this
+    pump reaches its first post-disconnect chunk; that isolates the cap decision
+    from multi-pump scheduling races.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", 1)
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 4)
+
+    async def _hold_slot():
+        await asyncio.sleep(3600)
+
+    holder = asyncio.ensure_future(_hold_slot())
+    streaming_iterator_module._DETACHED_STREAM_DRAINS.add(holder)
+    tail_reached = False
+
+    async def _long_stream():
+        nonlocal tail_reached
+        yield {"type": "message_start", "message": {"id": "m", "usage": {"input_tokens": 5, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "x"}}
+        for i in range(100):
+            yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": f"more{i}"}}
+        tail_reached = True
+        yield {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 42}}
+        yield {"type": "message_stop"}
+
+    iterator = _RecordingLoggingIterator(litellm_logging_obj=_make_logging_obj("drain_cap_full"), request_body={})
+    try:
+        gen = iterator.async_sse_wrapper(_long_stream())
+        await gen.__anext__()  # message_start
+        await gen.__anext__()  # first delta
+        await gen.aclose()  # client disconnects; 100+ chunks remain upstream
+
+        for _ in range(200):
+            if iterator.logged_chunks:
+                break
+            await asyncio.sleep(0)
+
+        assert iterator.logged_chunks, "capped pump never billed"
+        assert len(iterator.logged_chunks) <= 2 + streaming_iterator_module.ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE
+        assert len(iterator.logged_chunks) < 100
+        assert not any(c.startswith(b"event: message_stop\n") for c in iterator.logged_chunks)
+        assert tail_reached is False, "pump kept draining past the cap instead of stopping"
+    finally:
+        holder.cancel()
+        streaming_iterator_module._DETACHED_STREAM_DRAINS.discard(holder)
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_bills_partial_when_detached_drains_disabled(monkeypatch):
+    """
+    Regression: ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS=0 must disable
+    detached draining entirely, not just shrink the cap. With no slots ever
+    available, the very first post-disconnect chunk must fall back to partial
+    spend logging instead of hanging on a cap that's unreachable.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", 0)
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 4)
+
+    tail_reached = False
+
+    async def _long_stream():
+        nonlocal tail_reached
+        yield {"type": "message_start", "message": {"id": "m", "usage": {"input_tokens": 5, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "x"}}
+        for i in range(100):
+            yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": f"more{i}"}}
+        tail_reached = True
+        yield {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 42}}
+        yield {"type": "message_stop"}
+
+    iterator = _RecordingLoggingIterator(litellm_logging_obj=_make_logging_obj("drains_disabled"), request_body={})
+    gen = iterator.async_sse_wrapper(_long_stream())
+    await gen.__anext__()  # message_start
+    await gen.__anext__()  # first delta
+    await gen.aclose()  # client disconnects; 100+ chunks remain upstream
+
+    for _ in range(200):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0)
+
+    assert iterator.logged_chunks, "pump never billed with detached drains disabled"
+    assert len(iterator.logged_chunks) <= 2 + streaming_iterator_module.ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE
+    assert len(iterator.logged_chunks) < 100
+    assert not any(c.startswith(b"event: message_stop\n") for c in iterator.logged_chunks)
+    assert tail_reached is False, "pump kept draining despite detached drains being disabled"
+    assert len(streaming_iterator_module._DETACHED_STREAM_DRAINS) == 0
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_aborts_upstream_when_detached_drain_cap_reached(monkeypatch):
+    """
+    Regression: when the cap is full and a disconnected pump bails, it must call
+    aclose on the upstream stream so the provider stops generating and billing,
+    not continue running the stream while we record only the partial prefix.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", 1)
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 4)
+
+    async def _hold_slot():
+        await asyncio.sleep(3600)
+
+    holder = asyncio.ensure_future(_hold_slot())
+    streaming_iterator_module._DETACHED_STREAM_DRAINS.add(holder)
+
+    class _AbortableStream:
+        def __init__(self):
+            self.aclose_called = False
+            self._remaining = iter(
+                (
+                    {"type": "message_start", "message": {"id": "m", "usage": {"input_tokens": 5, "output_tokens": 1}}},
+                    {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "x"}},
+                )
+                + tuple(
+                    {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": f"t{i}"}}
+                    for i in range(50)
+                )
+            )
+
+        def __aiter__(self):
+            return self
+
+        async def __anext__(self):
+            try:
+                return next(self._remaining)
+            except StopIteration:
+                raise StopAsyncIteration
+
+        async def aclose(self):
+            self.aclose_called = True
+
+    stream = _AbortableStream()
+    iterator = _RecordingLoggingIterator(litellm_logging_obj=_make_logging_obj("abort_upstream_at_cap"), request_body={})
+    try:
+        gen = iterator.async_sse_wrapper(stream)
+        await gen.__anext__()
+        await gen.__anext__()
+        await gen.aclose()
+
+        for _ in range(200):
+            if iterator.logged_chunks:
+                break
+            await asyncio.sleep(0)
+
+        assert iterator.logged_chunks, "capped pump never billed"
+        assert stream.aclose_called, "upstream aclose was not called when the detached-drain cap was reached"
+    finally:
+        holder.cancel()
+        streaming_iterator_module._DETACHED_STREAM_DRAINS.discard(holder)
+
+
+@pytest.mark.asyncio
+async def test_abort_upstream_logs_warning_when_aclose_raises(caplog):
+    """_abort_upstream must swallow and log any exception from aclose()."""
+    import logging
+
+    class _ExplodingStream:
+        def __aiter__(self):
+            return self
+
+        async def __anext__(self):
+            raise StopAsyncIteration
+
+        async def aclose(self):
+            raise RuntimeError("aclose exploded")
+
+    with caplog.at_level(logging.WARNING, logger="LiteLLM Proxy"):
+        await BaseAnthropicMessagesStreamingIterator._abort_upstream(_ExplodingStream())
+
+    assert any("abort" in r.message and "RuntimeError" in r.message for r in caplog.records)
+
+
+@pytest.mark.asyncio
+async def test_enqueue_for_client_returns_false_when_already_detached():
+    """_enqueue_for_client must return False immediately (without touching the queue)
+    when client_detached is already set before the call."""
+    from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
+        BaseAnthropicMessagesStreamingIterator,
+    )
+
+    queue: asyncio.Queue[bytes | None | BaseException] = asyncio.Queue(maxsize=1)
+    client_detached = asyncio.Event()
+    client_detached.set()
+
+    result = await BaseAnthropicMessagesStreamingIterator._enqueue_for_client(queue, client_detached, b"chunk")
+    assert result is False
+    assert queue.empty()
+
+
+@pytest.mark.asyncio
+async def test_enqueue_for_client_returns_false_when_client_detaches_while_queue_full():
+    """_enqueue_for_client must return False (and cancel the put) when the queue
+    is full and client_detached fires before space becomes available."""
+    from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import (
+        BaseAnthropicMessagesStreamingIterator,
+    )
+
+    queue: asyncio.Queue[bytes | None | BaseException] = asyncio.Queue(maxsize=1)
+    queue.put_nowait(b"already-full")
+
+    client_detached = asyncio.Event()
+
+    async def _set_detached_soon():
+        await asyncio.sleep(0.01)
+        client_detached.set()
+
+    asyncio.create_task(_set_detached_soon())
+    result = await BaseAnthropicMessagesStreamingIterator._enqueue_for_client(queue, client_detached, b"new-chunk")
+    assert result is False
+    assert queue.qsize() == 1
+    assert queue.get_nowait() == b"already-full"
+
+
+@pytest.mark.asyncio
+async def test_async_sse_wrapper_drains_detached_when_cap_available(monkeypatch):
+    """Complement to the cap test: with a slot free, a disconnected pump drains
+    the full upstream and bills the terminal usage, and releases its slot after."""
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", 1)
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 4)
+
+    async def _stream():
+        yield {"type": "message_start", "message": {"id": "m", "usage": {"input_tokens": 5, "output_tokens": 1}}}
+        yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "x"}}
+        for i in range(20):
+            yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": f"m{i}"}}
+        yield {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 42}}
+        yield {"type": "message_stop"}
+
+    iterator = _RecordingLoggingIterator(litellm_logging_obj=_make_logging_obj("drain_cap_free"), request_body={})
+    gen = iterator.async_sse_wrapper(_stream())
+    await gen.__anext__()
+    await gen.__anext__()
+    await gen.aclose()
+
+    for _ in range(300):
+        if iterator.logged_chunks:
+            break
+        await asyncio.sleep(0.01)
+
+    assert any(c.startswith(b"event: message_stop\n") for c in iterator.logged_chunks)
+    assert len(streaming_iterator_module._DETACHED_STREAM_DRAINS) == 0
+
+
 def _decode_sse_events(events: tuple[bytes, ...]) -> list[tuple[str, dict]]:
     decoded = []
     for event in events:
@@ -599,20 +1111,35 @@ async def test_normal_end_with_deferred_dispatch_armed_parks_logging_coroutine(m
 @pytest.mark.asyncio
 async def test_client_disconnect_enqueues_immediately_even_when_deferred_dispatch_armed(monkeypatch):
     """
-    On client disconnect the guardrail end-of-stream scan never runs, so
-    deferral would strand the spend log; the teardown path must keep
-    enqueueing immediately (LIT-5839) even when the deferred callback is armed.
+    Regression: on client disconnect the guardrail end-of-stream scan never
+    runs, so deferral would strand the spend log. The detached pump's
+    post-disconnect bill must bypass the deferred-dispatch park and enqueue
+    immediately (LIT-5839) even when the deferred callback is armed (LIT-6409).
     """
     worker = _RecordingLoggingWorker()
     monkeypatch.setattr(streaming_iterator_module, "GLOBAL_LOGGING_WORKER", worker)
     iterator = _make_iterator("test_disconnect_enqueues_when_armed")
     iterator.litellm_logging_obj._on_deferred_stream_complete = _noop_deferred_dispatch
 
-    wrapped = iterator.async_sse_wrapper(_events_then_hang(TRUNCATED_TOOL_USE_EVENTS))
+    tail_gated = asyncio.Event()
+
+    async def _gated_stream():
+        for event in TRUNCATED_TOOL_USE_EVENTS:
+            yield event
+        await tail_gated.wait()
+        yield {"type": "message_stop"}
+
+    wrapped = iterator.async_sse_wrapper(_gated_stream())
     for _ in range(len(TRUNCATED_TOOL_USE_EVENTS)):
         await wrapped.__anext__()
     await wrapped.aclose()
 
+    tail_gated.set()
+    for _ in range(100):
+        if worker.enqueued:
+            break
+        await asyncio.sleep(0.01)
+
     assert len(worker.enqueued) == 1
     assert getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None) is None
     worker.close_enqueued()
@@ -629,3 +1156,123 @@ async def test_normal_end_without_deferred_dispatch_enqueues_immediately(monkeyp
     assert len(worker.enqueued) == 1
     assert getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None) is None
     worker.close_enqueued()
+
+
+def _backpressured_wrapper(iterator, upstream_exhausted: asyncio.Event):
+    async def _stream():
+        try:
+            for event in COMPLETE_STREAM_EVENTS:
+                yield event
+        finally:
+            upstream_exhausted.set()
+
+    return iterator.async_sse_wrapper(_stream())
+
+
+async def _drain_with_pauses_until_upstream_exhausted(gen, upstream_exhausted: asyncio.Event) -> list:
+    received = []
+    while not upstream_exhausted.is_set():
+        received.append(await gen.__anext__())
+        for _ in range(25):
+            await asyncio.sleep(0)
+        assert len(received) <= len(COMPLETE_STREAM_EVENTS)
+    return received
+
+
+@pytest.mark.asyncio
+async def test_normal_end_parks_deferred_logging_even_when_sentinel_enqueue_backpressured(monkeypatch):
+    """
+    Regression: with a full relay queue at end of stream, the pump suspends
+    while enqueueing the end-of-stream sentinel, and a client that then drains
+    the whole tail tears the relay down (setting ``client_detached``) before
+    the pump resumes. That teardown is a normally completed response, not a
+    disconnect: billing must still park for the proxy's post-response hook
+    (preserving post_call decoration such as guardrail_information) instead of
+    enqueueing immediately through the teardown path.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 2)
+    worker = _RecordingLoggingWorker()
+    monkeypatch.setattr(streaming_iterator_module, "GLOBAL_LOGGING_WORKER", worker)
+
+    dispatched = []
+
+    async def _deferred_stream_complete(logging_coroutine):
+        dispatched.append(logging_coroutine)
+        logging_coroutine.close()
+
+    iterator = _make_iterator("test_sentinel_backpressure_normal_end")
+    iterator.litellm_logging_obj._on_deferred_stream_complete = _deferred_stream_complete
+
+    upstream_exhausted = asyncio.Event()
+    gen = _backpressured_wrapper(iterator, upstream_exhausted)
+    received = await _drain_with_pauses_until_upstream_exhausted(gen, upstream_exhausted)
+
+    while True:
+        try:
+            received.append(await gen.__anext__())
+        except StopAsyncIteration:
+            break
+
+    for _ in range(100):
+        if worker.enqueued or getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None):
+            break
+        await asyncio.sleep(0.01)
+
+    assert len(received) == len(COMPLETE_STREAM_EVENTS)
+    assert worker.enqueued == [], "fully delivered stream billed through the teardown path"
+    assert dispatched == []
+    parked = getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None)
+    assert parked is not None, "pump never parked deferred billing"
+    parked[0].close()
+
+
+@pytest.mark.asyncio
+async def test_relay_teardown_dispatches_deferred_billing_when_sentinel_never_consumed(monkeypatch):
+    """
+    Regression: when the pump has parked deferred billing but its end-of-stream
+    sentinel never fits in the full relay queue (the client disconnects without
+    draining the tail), the proxy's post-response hook never fires. Exactly one
+    of the relay teardown or the pump's fallback must dispatch the parked
+    billing, or the request logs no spend at all.
+    """
+    monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 2)
+    worker = _RecordingLoggingWorker()
+    monkeypatch.setattr(streaming_iterator_module, "GLOBAL_LOGGING_WORKER", worker)
+
+    dispatched = []
+    deferred_fired = asyncio.Event()
+
+    def _deferred_stream_complete(logging_coroutine):
+        dispatched.append(logging_coroutine)
+
+        async def _consume():
+            logging_coroutine.close()
+            deferred_fired.set()
+
+        return _consume()
+
+    iterator = _make_iterator("test_sentinel_never_consumed_dispatch")
+    iterator.litellm_logging_obj._on_deferred_stream_complete = _deferred_stream_complete
+
+    upstream_exhausted = asyncio.Event()
+    gen = _backpressured_wrapper(iterator, upstream_exhausted)
+    await _drain_with_pauses_until_upstream_exhausted(gen, upstream_exhausted)
+
+    for _ in range(100):
+        if getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None) is not None:
+            break
+        await asyncio.sleep(0.01)
+
+    await gen.aclose()
+
+    for _ in range(100):
+        if dispatched:
+            break
+        await asyncio.sleep(0.01)
+
+    assert len(dispatched) == 1, "parked billing was never dispatched"
+    assert getattr(iterator.litellm_logging_obj, "_deferred_stream_complete_args", None) is None
+    assert getattr(iterator.litellm_logging_obj, "_on_deferred_stream_complete", None) is None
+    assert len(worker.enqueued) == 1, "teardown billing enqueued alongside the deferred dispatch"
+    await worker.enqueued[0]
+    assert deferred_fired.is_set()
diff --git a/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py b/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py
index 2cf7cd142d6..4e6b9ed0188 100644
--- a/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py
+++ b/tests/test_litellm/llms/azure/chat/test_azure_chat_gpt_transformation.py
@@ -11,6 +11,7 @@ sys.path.insert(
 
 import litellm
 from litellm.litellm_core_utils.prompt_templates.common_utils import TOOL_RESULT_IMAGE_BOUNDARY
+from litellm.llms.azure.chat.gpt_5_transformation import AzureOpenAIGPT5Config
 from litellm.llms.azure.chat.gpt_transformation import AzureOpenAIConfig
 from litellm.utils import get_optional_params
 
@@ -195,3 +196,91 @@ def test_azure_gpt_5_takes_the_reasoning_path() -> None:
     assert "presence_penalty" not in mapped
     assert "logit_bias" not in mapped
     assert "reasoning_effort" in supported
+
+
+class TestAzureToolSchemaCombinatorFlattening:
+    """
+    Regression tests for LIT-6510: Azure's chat completions validator rejects
+    tool parameters carrying a top-level anyOf/oneOf/allOf for every model
+    family, so AzureOpenAIConfig.transform_request must flatten them.
+    """
+
+    @staticmethod
+    def _anyof_tool():
+        return {
+            "type": "function",
+            "function": {
+                "name": "automation_update",
+                "description": "Update an automation",
+                "parameters": {
+                    "type": "object",
+                    "anyOf": [
+                        {
+                            "properties": {"id": {"type": "string"}, "enabled": {"type": "boolean"}},
+                            "required": ["id", "enabled"],
+                        },
+                        {
+                            "properties": {"id": {"type": "string"}, "schedule": {"type": "string"}},
+                            "required": ["id", "schedule"],
+                        },
+                    ],
+                    "properties": {"id": {"type": "string"}},
+                    "required": ["id"],
+                },
+            },
+        }
+
+    def _transform(self, config, model, tools):
+        return config.transform_request(
+            model=model,
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={"tools": tools},
+            litellm_params={"custom_llm_provider": "azure"},
+            headers={},
+        )
+
+    def test_transform_request_flattens_top_level_anyof(self):
+        request = self._transform(AzureOpenAIConfig(), "gpt-4o", [self._anyof_tool()])
+        parameters = request["tools"][0]["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert parameters["type"] == "object"
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+        assert parameters["required"] == ["id"]
+        assert request["tools"][0]["function"]["name"] == "automation_update"
+
+    def test_gpt5_config_flattens_via_shared_transform(self):
+        request = self._transform(AzureOpenAIGPT5Config(), "gpt-5.4-mini", [self._anyof_tool()])
+        parameters = request["tools"][0]["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+
+    def test_caller_tool_dict_is_not_mutated(self):
+        tool = self._anyof_tool()
+        self._transform(AzureOpenAIConfig(), "gpt-4o", [tool])
+        assert tool == self._anyof_tool()
+
+    def test_clean_object_schema_passes_through_as_same_object(self):
+        tool = {
+            "type": "function",
+            "function": {
+                "name": "lookup",
+                "parameters": {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["id"]},
+            },
+        }
+        request = self._transform(AzureOpenAIConfig(), "gpt-4o", [tool])
+        assert request["tools"][0] is tool
+
+    def test_non_dict_tool_entries_pass_through_unchanged(self):
+        request = self._transform(AzureOpenAIConfig(), "gpt-4o", ["not-a-tool"])
+        assert request["tools"] == ["not-a-tool"]
+
+    def test_request_without_tools_is_unchanged(self):
+        request = AzureOpenAIConfig().transform_request(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={"temperature": 0.2},
+            litellm_params={"custom_llm_provider": "azure"},
+            headers={},
+        )
+        assert "tools" not in request
+        assert request["temperature"] == 0.2
diff --git a/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py b/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py
index fc7e94a77ba..202f81f1252 100644
--- a/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py
+++ b/tests/test_litellm/llms/azure/chat/test_azure_chat_o_series_transformation.py
@@ -23,3 +23,48 @@ async def test_azure_chat_o_series_transformation():
     )
     print(response)
     assert response["model"] == "web-interface-o1-mini"
+
+
+def test_azure_o_series_transform_request_flattens_top_level_anyof():
+    """Regression test for LIT-6510: the o-series super() chain ends in
+    OpenAIGPTConfig, whose flatten gate skips provider 'azure', so
+    AzureOpenAIO1Config must flatten tool schema combinators itself."""
+    tool = {
+        "type": "function",
+        "function": {
+            "name": "automation_update",
+            "description": "Update an automation",
+            "parameters": {
+                "type": "object",
+                "anyOf": [
+                    {
+                        "properties": {"id": {"type": "string"}, "enabled": {"type": "boolean"}},
+                        "required": ["id", "enabled"],
+                    },
+                    {
+                        "properties": {"id": {"type": "string"}, "schedule": {"type": "string"}},
+                        "required": ["id", "schedule"],
+                    },
+                ],
+                "properties": {"id": {"type": "string"}},
+                "required": ["id"],
+            },
+        },
+    }
+    optional_params = {"tools": [tool]}
+
+    request = AzureOpenAIO1Config().transform_request(
+        model="o3-mini",
+        messages=[{"role": "user", "content": "hi"}],
+        optional_params=optional_params,
+        litellm_params={"custom_llm_provider": "azure"},
+        headers={},
+    )
+
+    parameters = request["tools"][0]["function"]["parameters"]
+    assert "anyOf" not in parameters
+    assert parameters["type"] == "object"
+    assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+    assert parameters["required"] == ["id"]
+    assert "anyOf" in tool["function"]["parameters"]
+    assert optional_params["tools"][0] is tool
diff --git a/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_transformation.py b/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_transformation.py
index 9dac914ca4d..9e2bfb08852 100644
--- a/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_transformation.py
+++ b/tests/test_litellm/llms/azure_ai/claude/test_azure_anthropic_transformation.py
@@ -362,8 +362,8 @@ class TestAzureAnthropicConfig:
             )
         assert "xhigh" in str(exc_info.value)
 
-    def test_extra_body_promotion_does_not_clobber_top_level(self):
-        """Top-level ``optional_params`` wins over duplicates in ``extra_body``."""
+    def test_extra_body_promotion_overrides_mapped_top_level(self):
+        """The caller's ``extra_body`` wins over a mapped top-level duplicate, like the native ``anthropic`` passthrough."""
         config = AzureAnthropicConfig()
 
         messages = [{"role": "user", "content": "Hello"}]
@@ -383,7 +383,31 @@ class TestAzureAnthropicConfig:
             headers=headers,
         )
 
-        assert result["output_config"] == {"effort": "low"}
+        assert result["output_config"] == {"effort": "high"}
+
+    def test_legacy_thinking_upgrade_keeps_caller_effort_from_extra_body(self, local_model_cost_map):
+        config = AzureAnthropicConfig()
+
+        mapped = config.map_openai_params(
+            non_default_params={"thinking": {"type": "enabled", "budget_tokens": 1024}, "max_tokens": 100},
+            optional_params={},
+            model="claude-opus-4-8",
+            drop_params=False,
+        )
+        assert mapped["thinking"] == {"type": "adaptive"}
+        assert mapped["output_config"] == {"effort": "low"}
+
+        result = config.transform_request(
+            model="claude-opus-4-8",
+            messages=[{"role": "user", "content": "Hello"}],
+            optional_params={**mapped, "extra_body": {"output_config": {"effort": "high"}}},
+            litellm_params={"api_key": "test-key"},
+            headers={"api-key": "test-key", "anthropic-version": "2023-06-01"},
+        )
+
+        assert result["thinking"] == {"type": "adaptive"}
+        assert result["output_config"] == {"effort": "high"}
+        assert "extra_body" not in result
 
     def test_context_management_mixed_edits_beta_headers(self):
         """Test that context_management with both compact and other edits adds both beta headers"""
diff --git a/tests/test_litellm/llms/base_llm/files/test_azure_blob_storage_backend.py b/tests/test_litellm/llms/base_llm/files/test_azure_blob_storage_backend.py
index b924ea8f93f..7e1139ca79a 100644
--- a/tests/test_litellm/llms/base_llm/files/test_azure_blob_storage_backend.py
+++ b/tests/test_litellm/llms/base_llm/files/test_azure_blob_storage_backend.py
@@ -184,6 +184,50 @@ async def test_download_file_drops_query_string_from_the_stored_url(mock_env_var
     )
 
 
+@pytest.mark.parametrize(
+    "malicious_filename",
+    [
+        "report.jsonl/../../etc/cron.d/evil",
+        "a.b/../../../root/.ssh/authorized_keys",
+    ],
+)
+@pytest.mark.parametrize("strategy", ["uuid", "timestamp"])
+@pytest.mark.asyncio
+async def test_generate_file_name_strips_path_traversal_from_extension(mock_env_vars, malicious_filename, strategy):
+    """
+    original_filename.split(".")[-1] does not parse path structure, so a filename whose
+    last "." is followed by a directory traversal sequence used to put that sequence
+    straight into the blob path built from this name. The mutant this pins is reverting
+    _safe_extension() back to that bare split.
+    """
+    backend = _make_backend()
+    generated = backend._generate_file_name(malicious_filename, strategy)
+    assert "/" not in generated
+    assert ".." not in generated
+
+
+@pytest.mark.asyncio
+async def test_generate_file_name_uuid_strategy_preserves_ordinary_extension(mock_env_vars):
+    backend = _make_backend()
+    generated = backend._generate_file_name("data.jsonl", "uuid")
+    assert generated.endswith(".jsonl")
+
+
+@pytest.mark.asyncio
+async def test_generate_file_name_original_filename_strategy_strips_directory_components(mock_env_vars):
+    """The blob name must never carry a directory the caller supplied, traversal or not."""
+    backend = _make_backend()
+    generated = backend._generate_file_name("../../etc/passwd", "original_filename")
+    assert generated == "passwd"
+
+
+@pytest.mark.asyncio
+async def test_generate_file_name_null_byte_filename_falls_back_to_safe_default(mock_env_vars):
+    backend = _make_backend()
+    generated = backend._generate_file_name("report.pdf\x00.exe", "uuid")
+    assert "\x00" not in generated
+
+
 @pytest.mark.parametrize(
     "env_fixture, expected_suffix",
     [("mock_env_vars", "core.windows.net"), ("mock_gov_env_vars", GOV_SUFFIX)],
diff --git a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
index cea299280f8..0d7573a2536 100644
--- a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
@@ -428,30 +428,58 @@ def test_output_config_forwarded_for_bedrock_chat_invoke_request():
 
 
 def test_output_config_format_converted_for_bedrock_chat_invoke_request():
-    """Bedrock Invoke chat path consumes ``output_config.format`` before forwarding."""
+    """Bedrock Invoke chat path inlines ``output_config.format`` for models
+    without native structured-output support and keeps the effort key."""
     config = AmazonAnthropicClaudeConfig()
     schema = {
         "type": "object",
         "properties": {"answer": {"type": "string"}},
     }
 
-    result = config.transform_request(
+    with patch(  # test-quality-ok: pin non-native path
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
+    ):
+        result = config.transform_request(
+            model="anthropic.claude-opus-4-7",
+            messages=[{"role": "user", "content": "test"}],
+            optional_params={
+                "max_tokens": 100,
+                "output_config": {
+                    "effort": "xhigh",
+                    "format": {"type": "json_schema", "schema": schema},
+                },
+            },
+            litellm_params={},
+            headers={},
+        )
+
+    assert result.get("output_config") == {"effort": "xhigh"}
+    last_content = result["messages"][0]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
+
+
+def test_output_config_format_forwarded_for_bedrock_chat_invoke_request():
+    """Bedrock Invoke chat path forwards ``output_config.format`` alongside effort
+    for models with native structured-output support (Claude Opus 4.7)."""
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"answer": {"type": "string"}}},
+    }
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
         model="anthropic.claude-opus-4-7",
         messages=[{"role": "user", "content": "test"}],
         optional_params={
             "max_tokens": 100,
-            "output_config": {
-                "effort": "xhigh",
-                "format": {"type": "json_schema", "schema": schema},
-            },
+            "output_config": {"effort": "xhigh", "format": schema_format},
         },
         litellm_params={},
         headers={},
     )
 
-    assert result.get("output_config") == {"effort": "xhigh"}
-    last_content = result["messages"][0]["content"]
-    assert json.loads(last_content[-1]["text"]) == schema
+    assert result.get("output_config") == {"effort": "xhigh", "format": schema_format}
+    assert "answer" not in json.dumps(result["messages"])
 
 
 @pytest.mark.parametrize(
@@ -488,7 +516,7 @@ def test_bedrock_chat_invoke_checks_output_config_support_with_bedrock_provider(
     optional_params = {"max_tokens": 100, "output_config": {"effort": "high"}}
 
     with patch(
-        "litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ) as mock_supports_factory:
         result = config.transform_request(
@@ -499,11 +527,7 @@ def test_bedrock_chat_invoke_checks_output_config_support_with_bedrock_provider(
             headers={},
         )
 
-    mock_supports_factory.assert_called_once_with(
-        model="us.anthropic.claude-opus-4-7",
-        custom_llm_provider="bedrock",
-        key="supports_output_config",
-    )
+    mock_supports_factory.assert_called_once_with("us.anthropic.claude-opus-4-7", "supports_output_config")
     assert result["output_config"] == {"effort": "high"}
 
 
@@ -542,3 +566,151 @@ def test_output_format_removed_from_bedrock_invoke_request():
     assert (
         "output_format" not in result
     ), f"output_format should be removed for Bedrock Invoke, got keys: {result.keys()}"
+
+
+def test_bedrock_chat_invoke_forwards_output_config_format_natively(local_model_cost_map):
+    """Regression: ``output_config.format`` is forwarded verbatim on models Bedrock
+    enforces structured outputs for, instead of being inlined as prompt text."""
+    import json
+
+    config = AmazonAnthropicClaudeConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {"zebra_count": {"type": "integer"}},
+            "required": ["zebra_count"],
+            "additionalProperties": False,
+        },
+    }
+
+    result = config.transform_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+    assert "zebra_count" not in json.dumps(result["messages"])
+
+
+def test_bedrock_chat_invoke_drop_params_keeps_native_output_config_format(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` must not eat ``output_config.format`` before the
+    native-forwarding router runs (Sonnet 4.5 has no effort flags)."""
+    import litellm
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={"max_tokens": 100, "output_config": {"format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_bedrock_chat_invoke_drop_params_still_inlines_for_non_native(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` on a model without native structured-output support
+    still reaches the inline-schema fallback instead of losing the schema."""
+    import litellm
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    schema = {"type": "object", "properties": {"zebra_count": {"type": "integer"}}}
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
+        model="anthropic.claude-3-haiku-20240307-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={
+            "max_tokens": 100,
+            "output_config": {"format": {"type": "json_schema", "schema": schema}},
+        },
+        litellm_params={},
+        headers={},
+    )
+
+    assert "output_config" not in result
+    last_content = result["messages"][-1]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
+
+
+@pytest.mark.parametrize(
+    "model",
+    ["us.anthropic.claude-fable-5-1", "anthropic.claude-fable-5-1"],
+)
+def test_bedrock_chat_invoke_fable_5_1_response_format_avoids_forced_tool_choice(local_model_cost_map, model):
+    """Regression: Bedrock rejects both native ``output_config.format`` and forced
+    tool_choice for Fable 5.1, so invoke must use the tool-based path without a
+    forced ``tool_choice``."""
+    result = AmazonAnthropicClaudeConfig().map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "test_schema",
+                    "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+                },
+            }
+        },
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+
+    assert "output_format" not in result
+    assert "tools" in result
+    assert "tool_choice" not in result
+
+
+@pytest.mark.parametrize("model", ["us.anthropic.claude-sonnet-5", "us.anthropic.claude-fable-5-1"])
+def test_bedrock_chat_invoke_tool_based_response_format_still_upgrades_legacy_thinking(local_model_cost_map, model):
+    result = AmazonAnthropicClaudeConfig().map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "test_schema",
+                    "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+                },
+            },
+            "thinking": {"type": "enabled", "budget_tokens": 4096},
+            "max_tokens": 8192,
+        },
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+
+    assert "tools" in result
+    assert result["thinking"] == {"type": "adaptive"}
+    assert result["output_config"] == {"effort": "high"}
+
+
+def test_bedrock_chat_invoke_response_format_stub_still_upgrades_legacy_thinking(local_model_cost_map):
+    """Regression: the tool-based ``response_format`` path swaps in a Claude 3 stub
+    model before the shared Anthropic mapping, which hid the adaptive-only model
+    from the legacy ``thinking`` upgrade and left ``type=enabled`` on the wire."""
+    result = AmazonAnthropicClaudeConfig().map_openai_params(
+        non_default_params={
+            "response_format": {"type": "json_object"},
+            "thinking": {"type": "enabled", "budget_tokens": 4096},
+            "max_tokens": 8192,
+        },
+        optional_params={},
+        model="us.anthropic.claude-fable-5-1",
+        drop_params=False,
+    )
+
+    assert result["thinking"] == {"type": "adaptive"}
+    assert result["output_config"] == {"effort": "high"}
diff --git a/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py b/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
index 8e67a7e3438..21e3239f623 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_bedrock_converse_handler.py
@@ -96,10 +96,8 @@ def _completion_kwargs(**overrides):
     return kwargs
 
 
-def _run(**overrides):
-    with patch.object(
-        BedrockConverseLLM, "get_credentials", return_value=RESOLVED_CREDENTIALS
-    ):
+def _run(*, credentials: Credentials | None = RESOLVED_CREDENTIALS, **overrides):
+    with patch.object(BedrockConverseLLM, "get_credentials", return_value=credentials):
         return BedrockConverseLLM().completion(**_completion_kwargs(**overrides))
 
 
@@ -360,7 +358,7 @@ async def test_async_completion_logs_pre_call_by_default():
 
 def _sync_client_returning_converse_response():
     client = MagicMock()
-    client.post = lambda **_kwargs: httpx.Response(
+    client.post.side_effect = lambda **_kwargs: httpx.Response(
         200,
         json=CONVERSE_RESPONSE,
         request=httpx.Request("POST", "https://bedrock-runtime.us-west-2.amazonaws.com"),
@@ -487,3 +485,31 @@ def test_post_call_is_not_logged_twice_when_the_sync_rust_call_declines():
     assert response.choices[0].message.content == "hi"
     assert len(calls["post_call"]) == 1
     assert "hi" in calls["post_call"][0]["original_response"]
+
+
+def test_bearer_token_auth_serves_when_boto3_resolves_no_sigv4_credentials(monkeypatch):
+    """With only `AWS_BEARER_TOKEN_BEDROCK` configured boto3 resolves no
+    credentials at all. Preparing the Rust handoff must not dereference that
+    None: the bearer token signs the request on its own."""
+    monkeypatch.setenv("AWS_BEARER_TOKEN_BEDROCK", "bedrock-bearer-token")
+    client = _sync_client_returning_converse_response()
+
+    response = _run(credentials=None, litellm_params={}, client=client)
+
+    assert response.choices[0].message.content == "hi"
+    sent_headers = client.post.call_args.kwargs["headers"]
+    assert sent_headers["Authorization"] == "Bearer bedrock-bearer-token"
+
+
+def test_the_rust_opt_in_needs_no_sigv4_principal():
+    """The core resolves the bearer token itself, so a bearer-only deployment
+    keeps its opt-in and the gate sees no aws_* credential keys to sign with."""
+    seen = _inject()
+
+    response = _run(credentials=None, api_key="bedrock-bearer-token")
+
+    assert response.choices[0].message.content == "hello from rust"
+    params = seen["call"][0]["optional_params"]
+    assert not {"aws_access_key_id", "aws_secret_access_key", "aws_session_token"} & params.keys()
+    assert params["aws_region_name"] == "us-east-1"
+    assert seen["call"][0]["api_key"] == "bedrock-bearer-token"
diff --git a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
index 226bba6826a..cb05cdb9451 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -957,6 +957,56 @@ def test_transform_request_helper_includes_anthropic_beta_and_tools():
     assert fields["tools"][0]["type"] == "computer_20250124"
 
 
+def test_config_blocks_do_not_leak_into_inference_config():
+    """Regression: inferenceConfig was built before the config blocks were popped, so a dead
+    nested copy of each block (guardrailConfig, performanceConfig, serviceTier) rode inside
+    inferenceConfig alongside the real top-level one."""
+    data = AmazonConverseConfig()._transform_request_helper(
+        model="anthropic.claude-haiku-4-5-20251001-v1:0",
+        system_content_blocks=[],
+        optional_params={
+            "maxTokens": 100,
+            "guardrailConfig": {"guardrailIdentifier": "gr-id", "guardrailVersion": "DRAFT"},
+            "performanceConfig": {"latency": "optimized"},
+            "serviceTier": {"type": "priority"},
+        },
+        messages=[{"role": "user", "content": "hi"}],
+    )
+
+    assert data["inferenceConfig"] == {"maxTokens": 100}
+    assert data["guardrailConfig"] == {"guardrailIdentifier": "gr-id", "guardrailVersion": "DRAFT"}
+    assert data["performanceConfig"] == {"latency": "optimized"}
+    assert data["serviceTier"] == {"type": "priority"}
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "anthropic.claude-opus-4-8",
+        "us.anthropic.claude-opus-4-8",
+        "amazon.nova-pro-v1:0",
+        "us.meta.llama4-maverick-17b-instruct-v1:0",
+        "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abcdef123456",
+        "arn:aws:bedrock:us-east-1:123456789012:inference-profile/us.amazon.nova-pro-v1:0",
+    ],
+)
+def test_client_metadata_stripped_from_converse_request(model):
+    data = AmazonConverseConfig()._transform_request_helper(
+        model=model,
+        system_content_blocks=[],
+        optional_params={
+            "maxTokens": 16,
+            "anthropic_beta": ["computer-use-2025-01-24"],
+            "client_metadata": {"originator": "codex_cli_rs"},
+        },
+        messages=None,
+    )
+
+    fields = data["additionalModelRequestFields"]
+    assert "client_metadata" not in fields
+    assert fields["anthropic_beta"] == ["computer-use-2025-01-24"]
+
+
 def test_parallel_tool_calls_config_kept_for_sonnet_5(monkeypatch):
     old_env = os.environ.get("LITELLM_LOCAL_MODEL_COST_MAP")
     old_cost = litellm.model_cost
@@ -2853,17 +2903,11 @@ def test_guarded_text_guardrail_config_preserved():
         headers={},
     )
 
-    # GuardrailConfig should be present at top level
     assert "guardrailConfig" in result
     assert result["guardrailConfig"]["guardrailIdentifier"] == "gr-abc123"
 
-    # GuardrailConfig should also be in inferenceConfig
     assert "inferenceConfig" in result
-    assert "guardrailConfig" in result["inferenceConfig"]
-    assert (
-        result["inferenceConfig"]["guardrailConfig"]["guardrailIdentifier"]
-        == "gr-abc123"
-    )
+    assert "guardrailConfig" not in result["inferenceConfig"]
 
 
 def test_auto_convert_last_user_message_to_guarded_text():
@@ -5232,6 +5276,84 @@ def test_cache_control_injection_tool_config_drops_ttl_for_unsupported_model():
     assert tools[-1] == {"cachePoint": {"type": "default"}}
 
 
+@pytest.mark.parametrize(
+    ("model", "expects_cache_points"),
+    [
+        pytest.param("nvidia.nemotron-super-3-120b", False, id="mapped-model-without-prompt-caching"),
+        pytest.param("us.nvidia.nemotron-super-3-120b", False, id="regional-prefix-resolves-through-base-model"),
+        pytest.param(
+            "us.anthropic.claude-3-5-sonnet-20240620-v1:0", False, id="claude-named-but-not-caching-on-bedrock"
+        ),
+        pytest.param("us.anthropic.claude-sonnet-4-5-20250929-v1:0", True, id="mapped-model-with-prompt-caching"),
+        pytest.param(
+            "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123",
+            True,
+            id="unmapped-arn-keeps-emitting",
+        ),
+    ],
+)
+def test_cache_points_emitted_only_for_models_that_support_prompt_caching(model, expects_cache_points, monkeypatch):
+    """Bedrock rejects cachePoint blocks for models without prompt caching support
+    ("You invoked an unsupported model or your request did not allow prompt caching"),
+    and clients like Claude Code attach cache_control to every request, so a map-known
+    model without the capability must not receive them. Unmapped ids (application
+    inference profile ARNs, models newer than the map) keep emitting so existing
+    caching setups never silently degrade."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    body = AmazonConverseConfig().transform_request(
+        model=model,
+        messages=[
+            {"role": "system", "content": [{"type": "text", "text": "sys", "cache_control": {"type": "ephemeral"}}]},
+            {"role": "user", "content": [{"type": "text", "text": "hi", "cache_control": {"type": "ephemeral"}}]},
+        ],
+        optional_params={},
+        litellm_params={},
+        headers={},
+    )
+
+    assert ("cachePoint" in json.dumps(body)) is expects_cache_points
+    assert body["system"][0]["text"] == "sys"
+    assert body["messages"][0]["content"][0]["text"] == "hi"
+
+
+def test_tool_config_cachepoint_not_placed_or_credited_for_model_without_prompt_caching(monkeypatch):
+    """The tool_config injection point must stand down with the rest of the cachePoint
+    emission when the model cannot cache, and spend attribution must not credit the
+    gateway for a breakpoint that was never placed."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    bucket: dict = {"user_api_key": "sk-test"}
+    data = AmazonConverseConfig()._transform_request_helper(
+        model="nvidia.nemotron-super-3-120b",
+        system_content_blocks=[],
+        optional_params={
+            "tools": [
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "get_weather",
+                        "description": "Get weather",
+                        "parameters": {
+                            "type": "object",
+                            "properties": {"location": {"type": "string"}},
+                            "required": ["location"],
+                        },
+                    },
+                }
+            ],
+            "cache_control_injection_points": [{"location": "tool_config"}],
+        },
+        messages=[{"role": "user", "content": "hi"}],
+        litellm_params={"metadata": bucket, "litellm_metadata": None, "model_info": {"id": "dep-bedrock"}},
+    )
+
+    assert "cachePoint" not in json.dumps(data.get("toolConfig", {}))
+    assert "litellm_gateway_injected_cache" not in bucket
+
+
 def test_translate_response_format_json_schema_still_injects_tool():
     """
     response_format with an explicit json_schema should still use the
@@ -6195,7 +6317,7 @@ def test_message_level_cache_control_drops_ttl_for_unsupported_model(ttl_target)
 
     result = _bedrock_converse_messages_pt(
         messages=_agentic_messages_with_ttl(ttl_target),
-        model="anthropic.claude-3-5-sonnet-20240620-v1:0",
+        model="anthropic.claude-3-5-sonnet-20241022-v2:0",
         llm_provider="bedrock_converse",
     )
 
@@ -6253,6 +6375,82 @@ def test_adaptive_thinking_passes_through_on_46_plus_converse(model):
     assert optional_params.get("thinking") == {"type": "adaptive"}
 
 
+@pytest.mark.parametrize(
+    "model,budget_tokens,expected_effort",
+    [
+        ("anthropic.claude-opus-4-8", 4096, "high"),
+        ("us.anthropic.claude-opus-4-8", 2000, "low"),
+        ("global.anthropic.claude-opus-4-8", 12000, "xhigh"),
+        ("us.anthropic.claude-opus-4-7", 3000, "medium"),
+        ("anthropic.claude-fable-5", 4096, "high"),
+    ],
+)
+def test_legacy_thinking_translated_to_adaptive_on_adaptive_only_converse(model, budget_tokens, expected_effort):
+    """Adaptive-only models (4.7+, 5 families) reject thinking={type: enabled}
+    with a 400 on Bedrock Converse, so the legacy shape from callers like Claude
+    Code must be upgraded to thinking={type: adaptive} + output_config.effort
+    derived from budget_tokens, matching the /v1/messages passthrough."""
+    config = AmazonConverseConfig()
+
+    optional_params = config.map_openai_params(
+        non_default_params={"thinking": {"type": "enabled", "budget_tokens": budget_tokens}, "max_tokens": 64000},
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+    request = config.transform_request(
+        model=model,
+        messages=[{"role": "user", "content": "hi"}],
+        optional_params=optional_params,
+        litellm_params={},
+        headers={},
+    )
+
+    assert request["additionalModelRequestFields"]["thinking"] == {"type": "adaptive"}
+    assert request["additionalModelRequestFields"]["output_config"] == {"effort": expected_effort}
+
+
+def test_legacy_thinking_translation_keeps_caller_output_config_effort_converse():
+    config = AmazonConverseConfig()
+
+    optional_params = config.map_openai_params(
+        non_default_params={
+            "output_config": {"effort": "low"},
+            "thinking": {"type": "enabled", "budget_tokens": 12000},
+            "max_tokens": 64000,
+        },
+        optional_params={},
+        model="anthropic.claude-opus-4-8",
+        drop_params=False,
+    )
+
+    assert optional_params["thinking"] == {"type": "adaptive"}
+    assert optional_params["output_config"] == {"effort": "low"}
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "us.anthropic.claude-opus-4-6",
+        "anthropic.claude-3-5-sonnet-20241022-v2:0",
+    ],
+)
+def test_legacy_thinking_forwarded_verbatim_when_model_accepts_it_converse(model):
+    """The 4.6 family and pre-adaptive models accept thinking={type: enabled}
+    natively, so the caller's budget_tokens cap must keep applying."""
+    config = AmazonConverseConfig()
+
+    optional_params = config.map_openai_params(
+        non_default_params={"thinking": {"type": "enabled", "budget_tokens": 4096}, "max_tokens": 8192},
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+
+    assert optional_params["thinking"] == {"type": "enabled", "budget_tokens": 4096}
+    assert "output_config" not in optional_params
+
+
 def test_adaptive_thinking_dropped_when_max_tokens_too_small_converse():
     """When max_tokens can't fit even the minimum thinking budget, the raw
     adaptive block must be dropped entirely rather than translated, so the
@@ -6433,3 +6631,95 @@ def test_disabled_thinking_omitted_for_always_on_models_converse(
         assert "thinking" not in additional
     else:
         assert additional.get("thinking") == {"type": "disabled"}
+
+@pytest.mark.parametrize(
+    "model",
+    ["anthropic.claude-fable-5-1", "us.anthropic.claude-fable-5-1"],
+)
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_downgraded_to_auto_on_fable_5_1_converse(
+    local_model_cost_map, model, tool_choice
+):
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model=model, tool_choice=tool_choice, drop_params=True
+    )
+
+    assert result == {"auto": {}}
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_raises_clean_error_on_fable_5_1_converse(
+    local_model_cost_map, tool_choice, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AmazonConverseConfig()
+
+    with pytest.raises(litellm.utils.UnsupportedParamsError, match="forced tool use"):
+        config.map_tool_choice_values(
+            model="anthropic.claude-fable-5-1", tool_choice=tool_choice, drop_params=False
+        )
+
+
+@pytest.mark.parametrize("tool_choice", ["auto", "none"])
+def test_unforced_tool_choice_unaffected_on_fable_5_1_converse(local_model_cost_map, tool_choice):
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model="anthropic.claude-fable-5-1", tool_choice=tool_choice, drop_params=True
+    )
+
+    assert result == ({"auto": {}} if tool_choice == "auto" else None)
+
+
+@pytest.mark.parametrize(
+    "model",
+    ["anthropic.claude-fable-5-1", "us.anthropic.claude-fable-5-1"],
+)
+def test_response_format_avoids_native_and_forced_tool_choice_on_fable_5_1_converse(
+    local_model_cost_map, model
+):
+    """Regression: Bedrock rejects both ``outputConfig`` structured output and forced
+    tool_choice for Fable 5.1, so response_format must map to a tool without a forced
+    tool_choice."""
+    config = AmazonConverseConfig()
+
+    result = config.map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "test_schema",
+                    "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+                },
+            }
+        },
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+
+    assert "outputConfig" not in result
+    assert "tools" in result
+    assert "tool_choice" not in result
+    assert result.get("json_mode") is True
+
+
+def test_forced_tool_choice_forwarded_on_converse_models_that_support_it(
+    local_model_cost_map, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model="anthropic.claude-fable-5", tool_choice="required", drop_params=False
+    )
+
+    assert result == {"any": {}}
diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py
index 7f91b49a6f5..639be272351 100644
--- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py
+++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_handler.py
@@ -204,3 +204,69 @@ def test_should_forward_trusted_model_credentials_to_retrieve_provider_config():
     assert response is mock_response
     litellm_params = mock_retrieve_file.call_args.kwargs["litellm_params"]
     assert litellm_params["_litellm_internal_model_credentials"] is trusted_credentials
+
+
+@pytest.mark.asyncio
+async def test_afile_content_assumes_role_with_external_id(monkeypatch):
+    """A trust policy requiring sts:ExternalId must be satisfied by the deployment's aws_external_id."""
+    import datetime
+
+    import boto3
+    from botocore.exceptions import ClientError
+
+    monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False)
+
+    class FakeSTSClient:
+        def get_caller_identity(self):
+            return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"}
+
+        def assume_role(self, **params):
+            if params.get("ExternalId") != "external-id-files-download":
+                raise ClientError(
+                    {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}},
+                    "AssumeRole",
+                )
+            return {
+                "Credentials": {
+                    "AccessKeyId": "ASIAFILESDOWNLOADROLE",
+                    "SecretAccessKey": "assumed-secret",
+                    "SessionToken": "assumed-session-token",
+                    "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30),
+                }
+            }
+
+    class FakeS3Body:
+        def read(self):
+            return b'{"custom_id": "req-1"}'
+
+    class FakeS3Client:
+        def get_object(self, Bucket, Key):
+            return {"Body": FakeS3Body()}
+
+    def fake_boto3_client(service_name, **kwargs):
+        if service_name == "sts":
+            return FakeSTSClient()
+        return FakeS3Client()
+
+    optional_params = {
+        "_litellm_internal_model_credentials": MappingProxyType({"s3_bucket_name": "safe-bucket"}),
+        "aws_region_name": "us-east-1",
+        "aws_access_key_id": "AKIAFILESDOWNLOADCALLER",
+        "aws_secret_access_key": "pod-caller-secret",
+        "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-download-role",
+        "aws_session_name": "litellm-files-download-session",
+        "aws_external_id": "external-id-files-download",
+    }
+
+    with patch.object(boto3, "client", side_effect=fake_boto3_client) as mock_boto3_client:
+        response = await BedrockFilesHandler().afile_content(
+            file_content_request={"file_id": "s3://safe-bucket/litellm-bedrock-files-model-id-abc.jsonl"},
+            optional_params=optional_params,
+            timeout=10.0,
+            max_retries=None,
+        )
+
+    s3_client_kwargs = next(call.kwargs for call in mock_boto3_client.call_args_list if call.args[0] == "s3")
+    assert s3_client_kwargs["aws_access_key_id"] == "ASIAFILESDOWNLOADROLE"
+    assert s3_client_kwargs["aws_session_token"] == "assumed-session-token"
+    assert response.content == b'{"custom_id": "req-1"}'
diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py
index da13f265ee4..541c0db15d8 100644
--- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py
+++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py
@@ -2404,3 +2404,111 @@ class TestBedrockFilesS3SignatureEncoding:
             body=None,
             headers=litellm_params[S3_SIGNED_GET_HEADERS_PARAM],
         )
+
+
+def test_sign_s3_request_assumes_role_with_external_id(monkeypatch):
+    """A trust policy requiring sts:ExternalId must be satisfied when signing the S3 upload request."""
+    import datetime
+    from unittest.mock import patch
+
+    import boto3
+    from botocore.exceptions import ClientError
+
+    from litellm.llms.bedrock.files.transformation import BedrockFilesConfig
+
+    monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False)
+
+    class FakeSTSClient:
+        def get_caller_identity(self):
+            return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"}
+
+        def assume_role(self, **params):
+            if params.get("ExternalId") != "external-id-files-put":
+                raise ClientError(
+                    {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}},
+                    "AssumeRole",
+                )
+            return {
+                "Credentials": {
+                    "AccessKeyId": "ASIAFILESPUTROLE",
+                    "SecretAccessKey": "assumed-secret",
+                    "SessionToken": "assumed-session-token",
+                    "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30),
+                }
+            }
+
+    optional_params = {
+        "aws_region_name": "us-east-1",
+        "aws_access_key_id": "AKIAFILESPUTCALLER",
+        "aws_secret_access_key": "pod-caller-secret",
+        "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-put-role",
+        "aws_session_name": "litellm-files-put-session",
+        "aws_external_id": "external-id-files-put",
+    }
+
+    with patch.object(boto3, "client", return_value=FakeSTSClient()):
+        signed_headers, _signed_body = BedrockFilesConfig()._sign_s3_request(
+            content='{"custom_id": "req-1"}',
+            api_base="https://s3.us-east-1.amazonaws.com/safe-bucket/litellm-bedrock-files-model-id-abc.jsonl",
+            optional_params=optional_params,
+        )
+
+    authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"]
+    assert "ASIAFILESPUTROLE" in authorization
+
+
+def test_sign_s3_get_request_assumes_role_with_external_id(monkeypatch):
+    """A trust policy requiring sts:ExternalId must be satisfied when signing the S3 download request."""
+    import datetime
+    from unittest.mock import patch
+
+    import boto3
+    from botocore.exceptions import ClientError
+
+    from litellm.llms.bedrock.files.transformation import (
+        BedrockFilesConfig,
+        _BedrockS3RequestParams,
+    )
+
+    monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False)
+
+    class FakeSTSClient:
+        def get_caller_identity(self):
+            return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"}
+
+        def assume_role(self, **params):
+            if params.get("ExternalId") != "external-id-files-get":
+                raise ClientError(
+                    {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}},
+                    "AssumeRole",
+                )
+            return {
+                "Credentials": {
+                    "AccessKeyId": "ASIAFILESGETROLE",
+                    "SecretAccessKey": "assumed-secret",
+                    "SessionToken": "assumed-session-token",
+                    "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30),
+                }
+            }
+
+    request_params = _BedrockS3RequestParams.model_validate(
+        {
+            "aws_region_name": "us-east-1",
+            "aws_access_key_id": "AKIAFILESGETCALLER",
+            "aws_secret_access_key": "pod-caller-secret",
+            "aws_role_name": "arn:aws:iam::999999999999:role/litellm-files-get-role",
+            "aws_session_name": "litellm-files-get-session",
+            "aws_external_id": "external-id-files-get",
+        }
+    )
+    assert request_params.aws_external_id == "external-id-files-get"
+
+    with patch.object(boto3, "client", return_value=FakeSTSClient()):
+        signed_headers = BedrockFilesConfig()._sign_s3_get_request(
+            api_base="https://s3.us-east-1.amazonaws.com/safe-bucket/litellm-bedrock-files-model-id-abc.jsonl",
+            aws_region_name="us-east-1",
+            request_params=request_params,
+        )
+
+    authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"]
+    assert "ASIAFILESGETROLE" in authorization
diff --git a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
index 1e09afd6919..09ebc1a3c95 100644
--- a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
+++ b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
@@ -935,7 +935,7 @@ def test_bedrock_messages_strips_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=False,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -970,7 +970,7 @@ def test_bedrock_messages_preserves_output_config_for_claude_4_6():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1003,7 +1003,7 @@ def test_bedrock_messages_checks_output_config_support_with_bedrock_provider():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ) as mock_supports_factory:
         result = cfg.transform_anthropic_messages_request(
@@ -1014,11 +1014,7 @@ def test_bedrock_messages_checks_output_config_support_with_bedrock_provider():
             headers={},
         )
 
-    mock_supports_factory.assert_called_with(
-        model="us.anthropic.claude-opus-4-7",
-        custom_llm_provider="bedrock",
-        key="supports_output_config",
-    )
+    mock_supports_factory.assert_called_with("us.anthropic.claude-opus-4-7", "supports_output_config")
     assert result["output_config"] == {"effort": "high"}
 
 
@@ -1038,7 +1034,7 @@ def test_bedrock_messages_forwards_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1054,27 +1050,29 @@ def test_bedrock_messages_forwards_output_config():
 
 
 def test_bedrock_messages_forwards_output_config_with_output_format():
-    """``output_config`` is forwarded; ``output_format`` is converted to inline schema."""
+    """Legacy ``output_format`` is forwarded as ``output_config.format`` on models
+    that support native structured outputs, alongside the effort key."""
     from unittest.mock import patch
 
     from litellm.types.router import GenericLiteLLMParams
 
     cfg = AmazonAnthropicClaudeMessagesConfig()
     messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}]
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {"answer": {"type": "string"}},
+        },
+    }
     optional_params = {
         "max_tokens": 4096,
         "output_config": {"effort": "low"},
-        "output_format": {
-            "type": "json_schema",
-            "schema": {
-                "type": "object",
-                "properties": {"answer": {"type": "string"}},
-            },
-        },
+        "output_format": schema_format,
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1085,12 +1083,14 @@ def test_bedrock_messages_forwards_output_config_with_output_format():
             headers={},
         )
 
-    assert result.get("output_config") == {"effort": "low"}
+    assert result.get("output_config") == {"effort": "low", "format": schema_format}
     assert "output_format" not in result
+    assert "answer" not in json.dumps(result["messages"])
 
 
 def test_bedrock_messages_converts_output_config_format_to_inline_schema():
-    """``output_config.format`` is consumed so Bedrock does not see an unknown nested key."""
+    """Without native structured-output support, ``output_config.format`` falls back
+    to the inline schema so Bedrock does not see an unknown nested key."""
     from unittest.mock import patch
 
     from litellm.types.router import GenericLiteLLMParams
@@ -1110,8 +1110,8 @@ def test_bedrock_messages_converts_output_config_format_to_inline_schema():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
-        return_value=True,
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
     ):
         result = cfg.transform_anthropic_messages_request(
             model="anthropic.claude-opus-4-7",
@@ -1146,7 +1146,7 @@ def test_bedrock_messages_normalizes_output_config_effort_for_opus(
     cfg = AmazonAnthropicClaudeMessagesConfig()
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1184,8 +1184,8 @@ def test_bedrock_messages_does_not_mutate_callers_messages_when_embedding_schema
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
-        return_value=True,
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
     ):
         result = cfg.transform_anthropic_messages_request(
             model="anthropic.claude-opus-4-7",
@@ -1229,7 +1229,7 @@ def test_bedrock_messages_does_not_mutate_callers_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         cfg.transform_anthropic_messages_request(
@@ -1271,7 +1271,7 @@ def test_bedrock_messages_strips_output_config_with_output_format():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=False,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1332,7 +1332,7 @@ def test_bedrock_messages_drop_params_keeps_output_config_for_4_7():
     litellm.drop_params = True
     try:
         with patch(
-            "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+            "litellm.llms.bedrock.common_utils._bedrock_model_supports",
             return_value=True,
         ):
             result = cfg.transform_anthropic_messages_request(
@@ -1375,7 +1375,7 @@ def test_bedrock_messages_maps_reasoning_effort_for_adaptive_model(
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1482,7 +1482,7 @@ def test_bedrock_messages_explicit_output_config_wins_over_reasoning_effort():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -3066,17 +3066,21 @@ def test_bedrock_invoke_messages_allows_converted_websearch_function_tool():
 async def test_bedrock_sse_wrapper_dispatches_logging_on_client_disconnect():
     """
     Regression test for LIT-5839: closing the outer bedrock_sse_wrapper
-    mid-stream (what the proxy does on a client disconnect) must close the
-    inner async_sse_wrapper deterministically so the partial-stream logging
-    fires. `completion_start_time` is only stamped on the logging object by
-    that dispatch, so it observing a value proves the whole chain ran.
+    mid-stream (what the proxy does on a client disconnect) must not lose the
+    stream's spend logging. Since the detached-pump relay, the upstream read
+    survives the disconnect and billing fires once the provider stream ends,
+    so the dispatch is awaited after releasing the upstream instead of being
+    observed synchronously at aclose(). `completion_start_time` is only
+    stamped on the logging object by that dispatch, so it observing a value
+    proves the whole chain ran.
     """
     cfg = AmazonAnthropicClaudeMessagesConfig()
+    release_upstream = asyncio.Event()
 
-    async def _hanging_stream():
+    async def _gated_stream():
         yield {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 25, "output_tokens": 1}}}
         yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "partial"}}
-        await asyncio.Event().wait()
+        await release_upstream.wait()
 
     logging_obj = LiteLLMLoggingObj(
         model="bedrock/invoke/anthropic.claude-3-sonnet-20240229-v1:0",
@@ -3087,11 +3091,162 @@ async def test_bedrock_sse_wrapper_dispatches_logging_on_client_disconnect():
         litellm_call_id="test_bedrock_sse_wrapper_disconnect_logging",
         function_id="test_bedrock_sse_wrapper_disconnect_logging",
     )
-    wrapped = cfg.bedrock_sse_wrapper(_hanging_stream(), litellm_logging_obj=logging_obj, request_body={})
+    wrapped = cfg.bedrock_sse_wrapper(_gated_stream(), litellm_logging_obj=logging_obj, request_body={})
     await wrapped.__anext__()
     await wrapped.__anext__()
     assert logging_obj.completion_start_time is None
 
     await wrapped.aclose()
+    release_upstream.set()
 
+    for _ in range(500):
+        if logging_obj.completion_start_time is not None:
+            break
+        await asyncio.sleep(0.01)
     assert logging_obj.completion_start_time is not None
+
+
+def test_bedrock_messages_forwards_output_config_format_natively(local_model_cost_map):
+    """Regression: on a model Bedrock enforces structured outputs for (Claude
+    Sonnet 4.5), ``output_config.format`` must be forwarded verbatim, not
+    silently rewritten into inline prompt text."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {
+                "zebra_count": {"type": "integer"},
+                "is_tuesday": {"type": "boolean"},
+            },
+            "required": ["zebra_count", "is_tuesday"],
+            "additionalProperties": False,
+        },
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+    assert "zebra_count" not in json.dumps(result["messages"])
+
+
+def test_bedrock_messages_inlines_schema_for_claude_5(local_model_cost_map):
+    """Bedrock rejects ``output_config.format`` for the Claude 5 family, so the
+    schema falls back to the inline-text path instead of a deterministic 400."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema = {
+        "type": "object",
+        "properties": {"zebra_count": {"type": "integer"}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-5",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": {"type": "json_schema", "schema": schema}},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert "output_config" not in result
+    last_content = result["messages"][-1]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
+
+
+def test_bedrock_messages_legacy_output_format_wins_over_output_config_format(local_model_cost_map):
+    """When a request carries both schema forms, the legacy top-level
+    ``output_format`` keeps winning, matching the pre-existing precedence."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    legacy_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"legacy_field": {"type": "string"}}},
+    }
+    newer_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"newer_field": {"type": "string"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_format": legacy_format,
+            "output_config": {"format": newer_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": legacy_format}
+    assert "output_format" not in result
+    assert "newer_field" not in json.dumps(result)
+
+
+def test_bedrock_messages_drop_params_keeps_native_output_config_format(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` must not strip a natively forwarded
+    ``output_config.format`` on models without effort support (Sonnet 4.5)."""
+    import litellm
+    from litellm.types.router import GenericLiteLLMParams
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_bedrock_messages_strips_effort_but_keeps_format_for_sonnet_4_5(local_model_cost_map):
+    """Sonnet 4.5 has native structured-output support but no effort support, so
+    a mixed ``output_config`` keeps ``format`` and drops ``effort``."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 4096,
+            "output_config": {"format": schema_format, "effort": "high"},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py
index 9efcee192b1..0ea5b7ad4a1 100644
--- a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py
+++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py
@@ -6,7 +6,7 @@ from unittest.mock import MagicMock
 
 import pytest
 
-
+import litellm
 from litellm.llms.bedrock.common_utils import BedrockError
 from litellm.llms.bedrock.realtime.handler import BedrockRealtime
 from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig
@@ -104,12 +104,24 @@ class RealtimeClientWS:
         self.closed = True
 
 
-class ImmediatelyEndingBedrockStream:
-    def __init__(self):
+class ScriptedBedrockReceiver:
+    def __init__(self, payloads):
+        self._payloads = list(payloads)
+
+    async def receive(self):
+        if not self._payloads:
+            return None
+        payload = self._payloads.pop(0)
+        return SimpleNamespace(value=SimpleNamespace(bytes_=payload.encode("utf-8")))
+
+
+class ScriptedBedrockStream:
+    def __init__(self, payloads):
         self.input_stream = FakeInputStream()
+        self._receiver = ScriptedBedrockReceiver(payloads)
 
     async def await_output(self):
-        return (None, EndedBedrockReceiver())
+        return (None, self._receiver)
 
 
 class FakeStaticCredentialsResolver:
@@ -151,7 +163,7 @@ def stub_aws_sdk_client(monkeypatch):
 
         async def invoke_model_with_bidirectional_stream(self, operation_input):
             captured["operation_input"] = operation_input
-            return ImmediatelyEndingBedrockStream()
+            return ScriptedBedrockStream(captured.get("scripted_payloads", []))
 
     package = types.ModuleType("aws_sdk_bedrock_runtime")
     client_module = types.ModuleType("aws_sdk_bedrock_runtime.client")
@@ -271,19 +283,132 @@ class TestBedrockRealtimeHandler:
         assert "sessionEnd" in event_names
         assert stream.input_stream.closed
 
+    @pytest.mark.asyncio
+    async def test_forwarded_events_are_filtered_to_logged_types_for_spend_logging(self):
+        handler = BedrockRealtime()
+        stream = ScriptedBedrockStream(
+            [
+                json.dumps({"event": {"userSpeechStart": {}}}),
+                json.dumps({"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}}),
+                json.dumps({"event": {"textOutput": {"content": "Hi"}}}),
+                json.dumps({"event": {"contentEnd": {"stopReason": "END_TURN"}}}),
+            ]
+        )
+        client_ws = RealtimeClientWS()
+
+        logged_events = [
+            event
+            async for event in handler._forward_bedrock_to_client(
+                stream,
+                client_ws,
+                BedrockRealtimeConfig(),
+                "amazon.nova-sonic-v1:0",
+                FakeLogging(),
+                {},
+            )
+        ]
+
+        assert [event["type"] for event in logged_events] == ["response.done"]
+        sent_types = [json.loads(message)["type"] for message in client_ws.sent_to_client]
+        assert "input_audio_buffer.speech_started" in sent_types
+        assert "response.text.delta" in sent_types
+        assert "response.done" in sent_types
+        assert client_ws.closed
+
+    @pytest.mark.asyncio
+    async def test_logged_event_types_star_collects_every_forwarded_event(self, monkeypatch):
+        monkeypatch.setattr(litellm, "logged_real_time_event_types", "*")
+        handler = BedrockRealtime()
+        stream = ScriptedBedrockStream(
+            [
+                json.dumps({"event": {"userSpeechStart": {}}}),
+                json.dumps({"event": {"userSpeechEnd": {}}}),
+            ]
+        )
+        client_ws = RealtimeClientWS()
+
+        logged_events = [
+            event
+            async for event in handler._forward_bedrock_to_client(
+                stream,
+                client_ws,
+                BedrockRealtimeConfig(),
+                "amazon.nova-sonic-v1:0",
+                FakeLogging(),
+                {},
+            )
+        ]
+
+        assert [event["type"] for event in logged_events] == [
+            "input_audio_buffer.speech_started",
+            "input_audio_buffer.speech_stopped",
+        ]
+
+    @pytest.mark.asyncio
+    async def test_trailing_usage_after_last_done_is_dispatched_for_spend(self, stub_aws_sdk_client, monkeypatch):
+        import litellm.llms.bedrock.realtime.handler as handler_module
+
+        dispatched = {}
+
+        class RecordingLogging(FakeLogging):
+            async def dispatch_success_handlers(self, result=None, prefer_async_handlers=False, **kwargs):
+                dispatched["events"] = result
+
+        class RecordingLoggingWorker:
+            def ensure_initialized_and_enqueue(self, coro):
+                dispatched["coro"] = coro
+
+        monkeypatch.setattr(handler_module, "GLOBAL_LOGGING_WORKER", RecordingLoggingWorker())
+        stub_aws_sdk_client["scripted_payloads"] = [
+            json.dumps(
+                {
+                    "event": {
+                        "usageEvent": {
+                            "totalInputTokens": 3,
+                            "totalOutputTokens": 6,
+                            "totalTokens": 9,
+                            "details": {
+                                "total": {
+                                    "input": {"speechTokens": 3, "textTokens": 0},
+                                    "output": {"speechTokens": 0, "textTokens": 6},
+                                }
+                            },
+                        }
+                    }
+                }
+            )
+        ]
+
+        await BedrockRealtime().async_realtime(
+            model="amazon.nova-sonic-v1:0",
+            websocket=RealtimeClientWS(),
+            logging_obj=RecordingLogging(),
+            aws_region_name="us-east-1",
+            aws_access_key_id="k",
+            aws_secret_access_key="s",
+        )
+        await dispatched["coro"]
+
+        assert [event["type"] for event in dispatched["events"]] == ["response.done"]
+        usage = dispatched["events"][0]["response"]["usage"]
+        assert (usage["input_tokens"], usage["output_tokens"], usage["total_tokens"]) == (3, 6, 9)
+        assert usage["input_token_details"] == {"audio_tokens": 3, "text_tokens": 0, "cached_tokens": 0}
+        assert usage["output_token_details"] == {"audio_tokens": 0, "text_tokens": 6}
+
     @pytest.mark.asyncio
     async def test_bedrock_stream_end_closes_client_websocket(self):
         handler = BedrockRealtime()
         client_ws = ClosableClientWS()
 
-        await handler._forward_bedrock_to_client(
+        async for _ in handler._forward_bedrock_to_client(
             EndedBedrockStream(),
             client_ws,
             BedrockRealtimeConfig(),
             "amazon.nova-sonic-v1:0",
             MagicMock(),
             {},
-        )
+        ):
+            pass
 
         assert client_ws.closed
 
@@ -320,9 +445,7 @@ class TestBedrockRealtimeSessionLifecycle:
             [json.dumps({"type": "session.update", "session": {"instructions": "hi", "modalities": ["text"]}})]
         )
 
-        await handler._forward_client_to_bedrock(
-            client_ws, stream, config, "amazon.nova-sonic-v1:0", {}, FakeLogging()
-        )
+        await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}, FakeLogging())
 
         acked = [json.loads(message) for message in client_ws.sent_to_client]
         updated = [event for event in acked if event["type"] == "session.updated"]
@@ -334,9 +457,7 @@ class TestBedrockRealtimeSessionLifecycle:
         handler = BedrockRealtime()
         config = BedrockRealtimeConfig()
         stream = FakeBedrockStream()
-        client_ws = DisconnectingClientWS(
-            [json.dumps({"type": "session.update", "session": {"instructions": "hi"}})]
-        )
+        client_ws = DisconnectingClientWS([json.dumps({"type": "session.update", "session": {"instructions": "hi"}})])
 
         await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {})
 
diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py
index ae6b1febd6b..a74f03449a1 100644
--- a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py
+++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_transformation.py
@@ -827,5 +827,310 @@ class TestBedrockRealtimeSessionEvents:
         assert event["session"]["modalities"] == ["text", "audio"]
 
 
+class TestBedrockRealtimeUserEventsAndUsage:
+    """Regression tests for #38346: USER ASR transcripts, speech boundary events,
+    usage propagation, and duplicate response.created"""
+
+    @staticmethod
+    def _run(config, messages):
+        logging_obj = MagicMock()
+        logging_obj.litellm_trace_id = "trace_123"
+        state = {
+            "session_configuration_request": json.dumps({"configured": True}),
+            "current_output_item_id": None,
+            "current_response_id": None,
+            "current_conversation_id": None,
+            "current_delta_chunks": [],
+            "current_item_chunks": [],
+            "current_delta_type": None,
+        }
+        all_events = []
+        for msg in messages:
+            result = config.transform_realtime_response(
+                json.dumps(msg),
+                "amazon.nova-2-sonic-v1:0",
+                logging_obj,
+                realtime_response_transform_input=dict(state),
+            )
+            all_events.extend(result["response"])
+            state.update(
+                {
+                    "current_output_item_id": result["current_output_item_id"],
+                    "current_response_id": result["current_response_id"],
+                    "current_conversation_id": result["current_conversation_id"],
+                    "current_delta_chunks": result["current_delta_chunks"],
+                    "current_delta_type": result["current_delta_type"],
+                }
+            )
+        return all_events
+
+    def test_user_speech_start_and_stop_events(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [{"event": {"userSpeechStart": {}}}, {"event": {"userSpeechEnd": {}}}],
+        )
+        assert [e["type"] for e in events] == [
+            "input_audio_buffer.speech_started",
+            "input_audio_buffer.speech_stopped",
+        ]
+        assert all(e["event_id"] and e["item_id"] for e in events)
+        assert events[0]["item_id"] == events[1]["item_id"]
+
+    def test_utterance_lifecycle_shares_one_item_id(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {"event": {"userSpeechStart": {}}},
+                {"event": {"userSpeechEnd": {}}},
+                {
+                    "event": {
+                        "contentStart": {
+                            "role": "USER",
+                            "type": "TEXT",
+                            "additionalModelFields": json.dumps({"generationStage": "FINAL"}),
+                        }
+                    }
+                },
+                {"event": {"textOutput": {"content": "ready"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+            ],
+        )
+        item_ids = {e["item_id"] for e in events if "item_id" in e}
+        assert len(item_ids) == 1
+
+    def test_new_utterance_gets_new_item_id(self):
+        config = BedrockRealtimeConfig()
+        first = self._run(config, [{"event": {"userSpeechStart": {}}}, {"event": {"userSpeechEnd": {}}}])
+        second = self._run(config, [{"event": {"userSpeechStart": {}}}, {"event": {"userSpeechEnd": {}}}])
+        assert first[0]["item_id"] == first[1]["item_id"]
+        assert second[0]["item_id"] == second[1]["item_id"]
+        assert first[0]["item_id"] != second[0]["item_id"]
+
+    def test_user_transcript_emits_input_audio_transcription_events(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {
+                    "event": {
+                        "contentStart": {
+                            "role": "USER",
+                            "type": "TEXT",
+                            "additionalModelFields": json.dumps({"generationStage": "FINAL"}),
+                        }
+                    }
+                },
+                {"event": {"textOutput": {"content": "ready"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+            ],
+        )
+        deltas = [e for e in events if e["type"] == "conversation.item.input_audio_transcription.delta"]
+        completed = [e for e in events if e["type"] == "conversation.item.input_audio_transcription.completed"]
+        assert len(deltas) == 1 and deltas[0]["delta"] == "ready"
+        assert len(completed) == 1 and completed[0]["transcript"] == "ready"
+        assert deltas[0]["item_id"] == completed[0]["item_id"]
+        assert not any(e["type"] == "response.text.delta" for e in events)
+
+    def test_speculative_user_transcript_emits_delta_only(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {
+                    "event": {
+                        "contentStart": {
+                            "role": "USER",
+                            "type": "TEXT",
+                            "additionalModelFields": json.dumps({"generationStage": "SPECULATIVE"}),
+                        }
+                    }
+                },
+                {"event": {"textOutput": {"content": "rea"}}},
+            ],
+        )
+        assert [e["type"] for e in events] == ["conversation.item.input_audio_transcription.delta"]
+
+    def test_user_transcript_state_resets_on_content_end(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {"event": {"contentStart": {"role": "USER", "type": "TEXT"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+                {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}},
+                {"event": {"textOutput": {"content": "Hi there"}}},
+            ],
+        )
+        text_deltas = [e for e in events if e["type"] == "response.text.delta"]
+        assert len(text_deltas) == 1 and text_deltas[0]["delta"] == "Hi there"
+        assert not any(e["type"].startswith("conversation.item.input_audio_transcription") for e in events)
+
+    def test_response_created_emitted_once_per_response(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}},
+                {"event": {"textOutput": {"content": "Hi"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+                {"event": {"contentStart": {"role": "ASSISTANT", "type": "AUDIO"}}},
+            ],
+        )
+        assert sum(1 for e in events if e["type"] == "response.created") == 1
+
+    def test_usage_event_propagates_to_response_done(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {
+                    "event": {
+                        "usageEvent": {
+                            "totalInputTokens": 25,
+                            "totalOutputTokens": 40,
+                            "totalTokens": 65,
+                            "details": {
+                                "total": {
+                                    "input": {"speechTokens": 20, "textTokens": 5},
+                                    "output": {"speechTokens": 30, "textTokens": 10},
+                                }
+                            },
+                        }
+                    }
+                },
+                {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}},
+                {"event": {"textOutput": {"content": "Hi"}}},
+                {"event": {"contentEnd": {"stopReason": "END_TURN"}}},
+            ],
+        )
+        done_events = [e for e in events if e["type"] == "response.done"]
+        assert len(done_events) == 1
+        usage = done_events[0]["response"]["usage"]
+        assert usage["input_tokens"] == 25
+        assert usage["output_tokens"] == 40
+        assert usage["total_tokens"] == 65
+        assert usage["input_token_details"]["audio_tokens"] == 20
+        assert usage["input_token_details"]["text_tokens"] == 5
+        assert usage["output_token_details"]["audio_tokens"] == 30
+        assert usage["output_token_details"]["text_tokens"] == 10
+
+    def test_response_done_without_usage_event_reports_zero_usage(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}},
+                {"event": {"textOutput": {"content": "Hi"}}},
+                {"event": {"contentEnd": {"stopReason": "END_TURN"}}},
+            ],
+        )
+        done_events = [e for e in events if e["type"] == "response.done"]
+        assert len(done_events) == 1
+        usage = done_events[0]["response"]["usage"]
+        assert usage["input_tokens"] == 0
+        assert usage["output_tokens"] == 0
+        assert usage["total_tokens"] == 0
+
+    @staticmethod
+    def _usage_event(total_input, total_output, in_speech, in_text, out_speech, out_text):
+        return {
+            "event": {
+                "usageEvent": {
+                    "totalInputTokens": total_input,
+                    "totalOutputTokens": total_output,
+                    "totalTokens": total_input + total_output,
+                    "details": {
+                        "total": {
+                            "input": {"speechTokens": in_speech, "textTokens": in_text},
+                            "output": {"speechTokens": out_speech, "textTokens": out_text},
+                        }
+                    },
+                }
+            }
+        }
+
+    _ASSISTANT_TURN = (
+        {"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}},
+        {"event": {"textOutput": {"content": "Hi"}}},
+        {"event": {"contentEnd": {"stopReason": "END_TURN"}}},
+    )
+
+    def test_multi_turn_usage_reports_per_response_deltas_not_cumulative_totals(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                self._usage_event(25, 40, in_speech=20, in_text=5, out_speech=30, out_text=10),
+                *self._ASSISTANT_TURN,
+                self._usage_event(40, 100, in_speech=30, in_text=10, out_speech=75, out_text=25),
+                *self._ASSISTANT_TURN,
+            ],
+        )
+        usages = [e["response"]["usage"] for e in events if e["type"] == "response.done"]
+        assert len(usages) == 2
+        assert (usages[0]["input_tokens"], usages[0]["output_tokens"], usages[0]["total_tokens"]) == (25, 40, 65)
+        assert (usages[1]["input_tokens"], usages[1]["output_tokens"], usages[1]["total_tokens"]) == (15, 60, 75)
+        assert usages[1]["input_token_details"] == {"audio_tokens": 10, "text_tokens": 5, "cached_tokens": 0}
+        assert usages[1]["output_token_details"] == {"audio_tokens": 45, "text_tokens": 15}
+        assert sum(u["total_tokens"] for u in usages) == 140
+
+    def test_usage_reported_after_last_response_done_flushes_as_logged_only_done(self):
+        config = BedrockRealtimeConfig()
+        self._run(
+            config,
+            [
+                self._usage_event(25, 40, in_speech=20, in_text=5, out_speech=30, out_text=10),
+                *self._ASSISTANT_TURN,
+            ],
+        )
+        assert config.leftover_usage_done_events() == ()
+
+        self._run(config, [self._usage_event(25, 46, in_speech=20, in_text=5, out_speech=30, out_text=16)])
+        leftover = config.leftover_usage_done_events()
+        assert len(leftover) == 1
+        assert leftover[0]["type"] == "response.done"
+        usage = leftover[0]["response"]["usage"]
+        assert (usage["input_tokens"], usage["output_tokens"], usage["total_tokens"]) == (0, 6, 6)
+        assert usage["output_token_details"] == {"audio_tokens": 0, "text_tokens": 6}
+        assert config.leftover_usage_done_events() == ()
+
+    def test_final_transcript_fragments_emit_one_completed_with_full_transcript(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {
+                    "event": {
+                        "contentStart": {
+                            "role": "USER",
+                            "type": "TEXT",
+                            "additionalModelFields": json.dumps({"generationStage": "FINAL"}),
+                        }
+                    }
+                },
+                {"event": {"textOutput": {"content": "What is the "}}},
+                {"event": {"textOutput": {"content": "capital of France?"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+            ],
+        )
+        deltas = [e for e in events if e["type"] == "conversation.item.input_audio_transcription.delta"]
+        completed = [e for e in events if e["type"] == "conversation.item.input_audio_transcription.completed"]
+        assert [d["delta"] for d in deltas] == ["What is the ", "capital of France?"]
+        assert len(completed) == 1
+        assert completed[0]["transcript"] == "What is the capital of France?"
+        assert {e["item_id"] for e in deltas + completed} == {completed[0]["item_id"]}
+
+    def test_speculative_transcript_block_end_emits_no_completed(self):
+        events = self._run(
+            BedrockRealtimeConfig(),
+            [
+                {
+                    "event": {
+                        "contentStart": {
+                            "role": "USER",
+                            "type": "TEXT",
+                            "additionalModelFields": json.dumps({"generationStage": "SPECULATIVE"}),
+                        }
+                    }
+                },
+                {"event": {"textOutput": {"content": "rea"}}},
+                {"event": {"contentEnd": {"stopReason": "PARTIAL_TURN"}}},
+            ],
+        )
+        assert [e["type"] for e in events] == ["conversation.item.input_audio_transcription.delta"]
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-v"])
diff --git a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
index 7d07ac947b1..f854d806bdc 100644
--- a/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
+++ b/tests/test_litellm/llms/bedrock/test_base_aws_llm.py
@@ -15,6 +15,7 @@ from unittest.mock import MagicMock, patch
 from botocore.awsrequest import AWSPreparedRequest, AWSRequest
 from botocore.auth import SigV4Auth
 from botocore.credentials import Credentials
+from botocore.exceptions import NoCredentialsError
 
 import litellm
 from litellm.llms.bedrock.base_aws_llm import (
@@ -801,6 +802,23 @@ def test_get_request_headers_with_sigv4():
         assert result == mock_request.prepare.return_value
 
 
+def test_get_request_headers_without_credentials_or_bearer_token_raises_no_credentials():
+    """Bearer-token auth needs no SigV4 principal, so `credentials` may be None.
+    Reaching the SigV4 branch with neither must fail the way botocore always
+    has instead of signing with a missing principal."""
+    llm = BaseAWSLLM()
+
+    with patch.dict(os.environ, {}, clear=True), pytest.raises(NoCredentialsError):
+        llm.get_request_headers(
+            credentials=None,
+            aws_region_name="us-west-2",
+            extra_headers=None,
+            endpoint_url="https://api.example.com",
+            data='{"prompt": "test"}',
+            headers={"Content-Type": "application/json"},
+        )
+
+
 def test_sigv4_matches_rust_golden_vector():
     request = AWSRequest(
         method="POST",
diff --git a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
index 389bf4a8e40..9302dc01abe 100644
--- a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
+++ b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
@@ -520,3 +520,97 @@ def test_merge_bedrock_aws_request_params_keeps_caller_credentials_without_stati
     assert merged["aws_secret_access_key"] == "caller-secret"
     assert merged["aws_session_token"] == "caller-token"
     assert merged["aws_region_name"] == "us-west-2"
+
+
+def test_strip_unsupported_output_config_keeps_format_drops_effort(local_model_cost_map):
+    """On a model with neither effort flag, only the ``format`` key survives."""
+    from litellm.llms.bedrock.common_utils import (
+        strip_unsupported_bedrock_invoke_output_config_keys,
+    )
+
+    schema_format = {"type": "json_schema", "schema": {"type": "object"}}
+    body = {"output_config": {"effort": "high", "format": schema_format}}
+
+    strip_unsupported_bedrock_invoke_output_config_keys(
+        model="anthropic.claude-3-haiku-20240307-v1:0",
+        request_body=body,
+    )
+
+    assert body["output_config"] == {"format": schema_format}
+
+
+def test_apply_structured_output_prefers_legacy_output_format(local_model_cost_map):
+    """The legacy ``output_format`` wins over ``output_config.format`` when a
+    request carries both, matching the pre-existing precedence."""
+    from litellm.llms.bedrock.common_utils import (
+        apply_bedrock_invoke_structured_output,
+    )
+
+    legacy = {"type": "json_schema", "schema": {"type": "object", "properties": {"a": {"type": "string"}}}}
+    newer = {"type": "json_schema", "schema": {"type": "object", "properties": {"b": {"type": "string"}}}}
+    body = {
+        "messages": [{"role": "user", "content": "hi"}],
+        "output_format": legacy,
+        "output_config": {"format": newer},
+    }
+
+    apply_bedrock_invoke_structured_output(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        request_body=body,
+    )
+
+    assert body["output_config"] == {"format": legacy}
+    assert "output_format" not in body
+
+
+def test_sign_aws_request_assumes_role_with_external_id(monkeypatch):
+    """A trust policy requiring sts:ExternalId must be satisfied when signing batch API requests."""
+    import datetime
+    from unittest.mock import patch
+
+    import boto3
+    from botocore.exceptions import ClientError
+
+    from litellm.llms.bedrock.common_utils import CommonBatchFilesUtils
+
+    monkeypatch.delenv("AWS_EXTERNAL_ID", raising=False)
+
+    class FakeSTSClient:
+        def get_caller_identity(self):
+            return {"Arn": "arn:aws:iam::111111111111:user/litellm-proxy-pod"}
+
+        def assume_role(self, **params):
+            if params.get("ExternalId") != "external-id-batch-sign":
+                raise ClientError(
+                    {"Error": {"Code": "AccessDenied", "Message": "is not authorized to perform: sts:AssumeRole"}},
+                    "AssumeRole",
+                )
+            return {
+                "Credentials": {
+                    "AccessKeyId": "ASIABATCHSIGNROLE",
+                    "SecretAccessKey": "assumed-secret",
+                    "SessionToken": "assumed-session-token",
+                    "Expiration": datetime.datetime.now(datetime.timezone.utc) + datetime.timedelta(minutes=30),
+                }
+            }
+
+    optional_params = {
+        "aws_region_name": "us-east-1",
+        "aws_access_key_id": "AKIABATCHSIGNCALLER",
+        "aws_secret_access_key": "pod-caller-secret",
+        "aws_role_name": "arn:aws:iam::999999999999:role/litellm-batch-sign-role",
+        "aws_session_name": "litellm-batch-sign-session",
+        "aws_external_id": "external-id-batch-sign",
+    }
+
+    with patch.object(boto3, "client", return_value=FakeSTSClient()):
+        signed_headers, signed_data = CommonBatchFilesUtils().sign_aws_request(
+            service_name="bedrock",
+            data={"jobName": "litellm-batch-job"},
+            endpoint_url="https://bedrock.us-east-1.amazonaws.com/model-invocation-job",
+            optional_params=optional_params,
+        )
+
+    authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"]
+    assert "ASIABATCHSIGNROLE" in authorization
+    assert signed_data == b'{"jobName": "litellm-batch-job"}'
diff --git a/tests/test_litellm/llms/bedrock/test_mantle.py b/tests/test_litellm/llms/bedrock/test_mantle.py
index d34517f61f6..09be2118001 100644
--- a/tests/test_litellm/llms/bedrock/test_mantle.py
+++ b/tests/test_litellm/llms/bedrock/test_mantle.py
@@ -128,6 +128,12 @@ def test_mantle_messages_url_construction():
 _VPC_ENDPOINT = "https://vpce-0a1b2c3d.bedrock-mantle.us-gov-west-1.vpce.amazonaws.com"
 
 
+@pytest.fixture(autouse=True)
+def no_ambient_mantle_api_base(monkeypatch):
+    monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False)
+
+
+
 def test_mantle_chat_url_honors_api_base_host():
     config = AmazonMantleConfig()
     url = config.get_complete_url(
@@ -193,6 +199,48 @@ def test_mantle_messages_url_honors_aws_bedrock_runtime_endpoint():
     assert url == f"{_VPC_ENDPOINT}/anthropic/v1/messages"
 
 
+_ENV_ENDPOINT = "https://bedrock-mantle.us-east-1.api.aws.internal.example.com"
+
+
+@pytest.mark.parametrize("config_cls", [AmazonMantleConfig, AmazonMantleMessagesConfig])
+@pytest.mark.parametrize(
+    "env_value",
+    [_ENV_ENDPOINT, f"{_ENV_ENDPOINT}/", f"{_ENV_ENDPOINT}/v1", f"{_ENV_ENDPOINT}/openai/v1"],
+)
+def test_mantle_url_honors_bedrock_mantle_api_base_env(monkeypatch, config_cls, env_value):
+    monkeypatch.setenv("BEDROCK_MANTLE_API_BASE", env_value)
+    url = config_cls().get_complete_url(
+        api_base=None,
+        api_key=None,
+        model="mantle/anthropic.claude-mythos-preview",
+        optional_params={"aws_region_name": "us-east-1"},
+        litellm_params={},
+    )
+    assert url == f"{_ENV_ENDPOINT}/anthropic/v1/messages"
+
+
+@pytest.mark.parametrize("config_cls", [AmazonMantleConfig, AmazonMantleMessagesConfig])
+@pytest.mark.parametrize(
+    ("api_base", "optional_params"),
+    [
+        (_VPC_ENDPOINT, {"aws_region_name": "us-gov-west-1"}),
+        (None, {"aws_region_name": "us-gov-west-1", "aws_bedrock_runtime_endpoint": _VPC_ENDPOINT}),
+    ],
+)
+def test_mantle_url_explicit_endpoint_beats_bedrock_mantle_api_base_env(
+    monkeypatch, config_cls, api_base, optional_params
+):
+    monkeypatch.setenv("BEDROCK_MANTLE_API_BASE", _ENV_ENDPOINT)
+    url = config_cls().get_complete_url(
+        api_base=api_base,
+        api_key=None,
+        model="mantle/anthropic.claude-mythos-preview",
+        optional_params=optional_params,
+        litellm_params={},
+    )
+    assert url == f"{_VPC_ENDPOINT}/anthropic/v1/messages"
+
+
 def test_mantle_transform_request_strips_prefix_and_adds_model():
     config = AmazonMantleConfig()
     request = config.transform_request(
diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
index cd775abf136..56b111f294e 100644
--- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
+++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py
@@ -486,6 +486,71 @@ class TestBedrockMantleChatAuth:
         assert "/us-east-2/bedrock/aws4_request" in authorization
         assert requests[0]["url"].startswith("https://bedrock-mantle.us-east-2.api.aws")
 
+    def test_completion_per_request_role_reaches_signer_and_not_the_body(self, monkeypatch):
+        from unittest.mock import MagicMock, Mock
+
+        from botocore.credentials import Credentials
+
+        from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
+        from litellm.llms.custom_httpx.http_handler import HTTPHandler
+        from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
+        from litellm.types.utils import ModelResponse
+
+        for var in ("BEDROCK_MANTLE_API_KEY", "AWS_BEARER_TOKEN_BEDROCK", "BEDROCK_MANTLE_API_BASE"):
+            monkeypatch.delenv(var, raising=False)
+
+        signer = BaseAWSLLM()
+        signer.get_credentials = MagicMock(
+            return_value=Credentials(
+                access_key="ASIAEXAMPLE",
+                secret_key="YXNzdW1lZC1yb2xlLXNlY3JldC1hc3N1bWVk",
+                token="assumed-session-token",
+            )
+        )
+        url = "https://bedrock-mantle.us-east-1.api.aws/openai/v1/chat/completions"
+        client = HTTPHandler(client=httpx.Client())
+        client.post = Mock(
+            return_value=httpx.Response(
+                status_code=200,
+                json={
+                    "id": "chatcmpl-test",
+                    "object": "chat.completion",
+                    "created": 1733529600,
+                    "model": "google.gemma-4-31b",
+                    "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}],
+                    "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+                },
+                request=httpx.Request("POST", url),
+            )
+        )
+
+        BaseLLMHTTPHandler().completion(
+            model="google.gemma-4-31b",
+            messages=[{"role": "user", "content": "hello"}],
+            api_base=None,
+            custom_llm_provider="bedrock_mantle",
+            model_response=ModelResponse(),
+            encoding=None,
+            logging_obj=Mock(),
+            optional_params={},
+            timeout=10,
+            litellm_params={
+                "aws_role_name": "arn:aws:iam::000000000000:role/attributed-role",
+                "aws_session_name": "user-123",
+                "aws_region_name": "us-east-1",
+            },
+            acompletion=False,
+            client=client,
+            provider_config=BedrockMantleChatConfig(aws_signer=signer),
+        )
+
+        credential_kwargs = signer.get_credentials.call_args.kwargs
+        assert credential_kwargs["aws_role_name"] == "arn:aws:iam::000000000000:role/attributed-role"
+        assert credential_kwargs["aws_session_name"] == "user-123"
+        sent = client.post.call_args.kwargs
+        assert sent["headers"]["Authorization"].startswith("AWS4-HMAC-SHA256")
+        assert not [key for key in json.loads(sent["data"]) if key.startswith("aws_")]
+
 
 class TestBedrockMantleProjectHeader:
     def test_validate_environment_sets_openai_project_header(self):
diff --git a/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py b/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
index 4c92c52d556..7509e35e3f7 100644
--- a/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
+++ b/tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
@@ -1,7 +1,11 @@
 import asyncio
 import concurrent.futures
+import socket
+import sys
+from typing import Final
 
 import aiohttp
+import aiohttp.abc
 import aiohttp.client_exceptions
 import aiohttp.http_exceptions
 import httpx
@@ -1140,3 +1144,55 @@ async def test_stopped_loop_session_disposed_synchronously_on_recycle():
     finally:
         await new_session.close()
         result["loop"].close()
+
+
+class _CancellingResolver(aiohttp.abc.AbstractResolver):
+    """Cancels the given task (or, by default, aiohttp's shielded DNS child task) mid-lookup."""
+
+    def __init__(self, task_to_cancel: "asyncio.Task[object] | None" = None):
+        self._task_to_cancel: Final = task_to_cancel
+
+    async def resolve(
+        self, host: str, port: int = 0, family: socket.AddressFamily = socket.AF_INET
+    ) -> list[aiohttp.abc.ResolveResult]:
+        target: Final = self._task_to_cancel or asyncio.current_task()
+        assert target is not None
+        target.cancel()
+        await asyncio.sleep(0)
+        raise OSError("resolver finished after the task was cancelled")
+
+    async def close(self) -> None:
+        return None
+
+
+@pytest.mark.asyncio
+@pytest.mark.skipif(
+    sys.version_info < (3, 11), reason="Task.cancelling() is needed to tell the two cancellations apart"
+)
+async def test_internal_dns_cancellation_maps_to_connect_error():
+    """A CancelledError the request task never asked for must surface as a mapped httpx transport error."""
+    session = aiohttp.ClientSession(connector=aiohttp.TCPConnector(resolver=_CancellingResolver()))
+    transport = LiteLLMAiohttpTransport(client=session)
+    try:
+        with pytest.raises(httpx.ConnectError):
+            await transport.handle_async_request(httpx.Request("GET", "http://example.invalid/"))
+        current = asyncio.current_task()
+        assert current is not None and current.cancelling() == 0
+    finally:
+        await transport.aclose()
+
+
+@pytest.mark.asyncio
+async def test_genuine_request_cancellation_still_propagates():
+    """Cancelling the request task itself (client disconnect, shutdown) must still propagate unmapped."""
+    current = asyncio.current_task()
+    assert current is not None
+    session = aiohttp.ClientSession(connector=aiohttp.TCPConnector(resolver=_CancellingResolver(current)))
+    transport = LiteLLMAiohttpTransport(client=session)
+    try:
+        with pytest.raises(asyncio.CancelledError):
+            await transport.handle_async_request(httpx.Request("GET", "http://example.invalid/"))
+    finally:
+        if sys.version_info >= (3, 11):
+            current.uncancel()
+        await transport.aclose()
diff --git a/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py b/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py
index 26f841c1146..1d583c16ad7 100644
--- a/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py
+++ b/tests/test_litellm/llms/custom_httpx/test_llm_http_handler.py
@@ -2295,6 +2295,25 @@ async def test_anthropic_invalid_thinking_signature_retry_resigns_bedrock_reques
     assert retry_authorization != first_attempt_headers["Authorization"]
 
 
+def test_aws_signing_overrides_only_fills_missing_credentials():
+    from litellm.llms.custom_httpx.llm_http_handler import _aws_signing_overrides
+
+    overrides = _aws_signing_overrides(
+        {"temperature": 0.2, "aws_region_name": "us-west-2"},
+        {
+            "aws_role_name": "arn:aws:iam::000000000000:role/attributed",
+            "aws_session_name": "user-123",
+            "aws_region_name": "us-east-1",
+            "api_key": "not-an-aws-param",
+        },
+    )
+
+    assert dict(overrides) == {
+        "aws_role_name": "arn:aws:iam::000000000000:role/attributed",
+        "aws_session_name": "user-123",
+    }
+
+
 class TestServerFulfilledToolsInRequest:
     """_server_fulfilled_tools_in_request gates the buffered (non-leaking) streaming
     mode for server-fulfilled tools like headroom_retrieve."""
diff --git a/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py b/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py
new file mode 100644
index 00000000000..064d9d58f0c
--- /dev/null
+++ b/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py
@@ -0,0 +1,331 @@
+import math
+
+import pytest
+
+import litellm
+from litellm import completion, get_llm_provider
+from litellm.llms.dashscope.chat.transformation import DashScopeChatConfig
+from litellm.llms.dashscope.cost_calculator import (
+    cost_per_token as dashscope_cost_per_token,
+)
+from litellm.llms.dashscope.embed.transformation import DashScopeEmbeddingConfig
+from litellm.llms.dashscope.image_generation.transformation import (
+    DashScopeImageGenerationConfig,
+)
+from litellm.llms.dashscope.qwen_ai_platform import (
+    QWEN_AI_PLATFORM_API_BASE,
+    QWEN_AI_PLATFORM_IMAGE_API_BASE,
+    QWEN_AI_PLATFORM_RERANK_API_BASE,
+    QwenAIPlatformChatConfig,
+    QwenAIPlatformEmbeddingConfig,
+    QwenAIPlatformImageGenerationConfig,
+    QwenAIPlatformRerankConfig,
+)
+from litellm.llms.dashscope.qwencloud import (
+    QWENCLOUD_API_BASE,
+    QWENCLOUD_IMAGE_API_BASE,
+    QWENCLOUD_RERANK_API_BASE,
+    QwenCloudChatConfig,
+    QwenCloudEmbeddingConfig,
+    QwenCloudImageGenerationConfig,
+    QwenCloudRerankConfig,
+)
+from litellm.llms.dashscope.rerank.transformation import DashScopeRerankConfig
+from litellm.types.utils import LlmProviders, Usage
+from litellm.utils import ProviderConfigManager
+
+DASHSCOPE_FAMILY_ENV_VARS = [
+    "DASHSCOPE_API_KEY",
+    "DASHSCOPE_API_BASE",
+    "DASHSCOPE_API_BASE_RERANK",
+    "DASHSCOPE_API_BASE_IMAGE",
+    "QWENCLOUD_API_KEY",
+    "QWENCLOUD_API_BASE",
+    "QWENCLOUD_API_BASE_RERANK",
+    "QWENCLOUD_API_BASE_IMAGE",
+    "QWEN_AI_PLATFORM_API_KEY",
+    "QWEN_AI_PLATFORM_API_BASE",
+    "QWEN_AI_PLATFORM_API_BASE_RERANK",
+    "QWEN_AI_PLATFORM_API_BASE_IMAGE",
+]
+
+BRAND_CASES = [
+    pytest.param(
+        {
+            "provider": "qwencloud",
+            "enum": LlmProviders.QWENCLOUD,
+            "key_env": "QWENCLOUD_API_KEY",
+            "base_env": "QWENCLOUD_API_BASE",
+            "default_base": QWENCLOUD_API_BASE,
+            "default_rerank_base": QWENCLOUD_RERANK_API_BASE,
+            "default_image_base": QWENCLOUD_IMAGE_API_BASE,
+            "chat_config": QwenCloudChatConfig,
+            "embedding_config": QwenCloudEmbeddingConfig,
+            "rerank_config": QwenCloudRerankConfig,
+            "image_config": QwenCloudImageGenerationConfig,
+        },
+        id="qwencloud",
+    ),
+    pytest.param(
+        {
+            "provider": "qwen_ai_platform",
+            "enum": LlmProviders.QWEN_AI_PLATFORM,
+            "key_env": "QWEN_AI_PLATFORM_API_KEY",
+            "base_env": "QWEN_AI_PLATFORM_API_BASE",
+            "default_base": QWEN_AI_PLATFORM_API_BASE,
+            "default_rerank_base": QWEN_AI_PLATFORM_RERANK_API_BASE,
+            "default_image_base": QWEN_AI_PLATFORM_IMAGE_API_BASE,
+            "chat_config": QwenAIPlatformChatConfig,
+            "embedding_config": QwenAIPlatformEmbeddingConfig,
+            "rerank_config": QwenAIPlatformRerankConfig,
+            "image_config": QwenAIPlatformImageGenerationConfig,
+        },
+        id="qwen_ai_platform",
+    ),
+]
+
+
+@pytest.fixture(autouse=True)
+def clear_dashscope_family_env(monkeypatch):
+    for env_var in DASHSCOPE_FAMILY_ENV_VARS:
+        monkeypatch.delenv(env_var, raising=False)
+
+
+class TestQwenBrandProviderResolution:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_get_llm_provider_resolves_brand_default_base(self, brand):
+        model, provider, api_key, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert model == "qwen-max"
+        assert provider == brand["provider"]
+        assert api_key == "sk-explicit"
+        assert api_base == brand["default_base"]
+
+    def test_dashscope_resolution_unchanged(self):
+        model, provider, api_key, api_base = get_llm_provider("dashscope/qwen-max", api_key="sk-explicit")
+        assert model == "qwen-max"
+        assert provider == "dashscope"
+        assert api_base == "https://dashscope.aliyuncs.com/compatible-mode/v1"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_brand_env_key_wins_over_dashscope_key(self, monkeypatch, brand):
+        monkeypatch.setenv(brand["key_env"], "sk-brand")
+        monkeypatch.setenv("DASHSCOPE_API_KEY", "sk-dashscope")
+        _, _, api_key, _ = get_llm_provider(f"{brand['provider']}/qwen-max")
+        assert api_key == "sk-brand"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_dashscope_key_is_fallback(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_KEY", "sk-dashscope")
+        _, _, api_key, _ = get_llm_provider(f"{brand['provider']}/qwen-max")
+        assert api_key == "sk-dashscope"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_dashscope_api_base_does_not_leak_into_brand(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_BASE", "https://legacy.example.com/v1")
+        _, _, _, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert api_base == brand["default_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_brand_api_base_env_wins(self, monkeypatch, brand):
+        monkeypatch.setenv(brand["base_env"], "https://brand.example.com/v1")
+        _, _, _, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert api_base == "https://brand.example.com/v1"
+
+
+class TestQwenBrandConfigDispatch:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_chat_config(self, brand):
+        config = ProviderConfigManager.get_provider_chat_config("qwen-max", brand["enum"])
+        assert isinstance(config, brand["chat_config"])
+        assert isinstance(config, DashScopeChatConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_config(self, brand):
+        config = ProviderConfigManager.get_provider_embedding_config(model="text-embedding-v3", provider=brand["enum"])
+        assert isinstance(config, brand["embedding_config"])
+        assert isinstance(config, DashScopeEmbeddingConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_config(self, brand):
+        config = ProviderConfigManager.get_provider_rerank_config(
+            model="gte-rerank-v2",
+            provider=brand["enum"],
+            api_base=None,
+            present_version_params=[],
+        )
+        assert isinstance(config, brand["rerank_config"])
+        assert isinstance(config, DashScopeRerankConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_config(self, brand):
+        config = ProviderConfigManager.get_provider_image_generation_config(model="qwen-image", provider=brand["enum"])
+        assert isinstance(config, brand["image_config"])
+        assert isinstance(config, DashScopeImageGenerationConfig)
+
+
+class TestQwenBrandDefaultUrls:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_chat_complete_url(self, brand):
+        url = brand["chat_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="qwen-max",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/chat/completions"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_complete_url(self, brand):
+        url = brand["embedding_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="text-embedding-v3",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/embeddings"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_ignores_dashscope_api_base(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_BASE", "https://legacy.example.com/v1")
+        url = brand["embedding_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="text-embedding-v3",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/embeddings"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_complete_url(self, brand):
+        url = brand["rerank_config"]().get_complete_url(api_base=None, model="gte-rerank-v2")
+        assert url == brand["default_rerank_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_env_override(self, monkeypatch, brand):
+        monkeypatch.setenv(f"{brand['base_env']}_RERANK", "https://rerank.example.com/v1/reranks")
+        url = brand["rerank_config"]().get_complete_url(api_base=None, model="gte-rerank-v2")
+        assert url == "https://rerank.example.com/v1/reranks"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_complete_url(self, brand):
+        url = brand["image_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="qwen-image",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == brand["default_image_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_ignores_chat_compatible_api_base(self, brand):
+        url = brand["image_config"]().get_complete_url(
+            api_base=brand["default_base"],
+            api_key="sk-test",
+            model="qwen-image",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == brand["default_image_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_validate_environment_requires_key(self, brand):
+        with pytest.raises(ValueError, match="DASHSCOPE_API_KEY"):
+            brand["embedding_config"]().validate_environment(
+                headers={},
+                model="text-embedding-v3",
+                messages=[],
+                optional_params={},
+                litellm_params={},
+                api_key=None,
+                api_base=None,
+            )
+
+
+class TestQwenBrandCostParity:
+    @pytest.fixture(autouse=True)
+    def setup_model_cost_map(self, monkeypatch):
+        monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+        monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_get_model_info(self, brand):
+        model_info = litellm.get_model_info(f"{brand['provider']}/qwen-max")
+        dashscope_info = litellm.get_model_info("dashscope/qwen-max")
+        assert model_info["litellm_provider"] == brand["provider"]
+        assert model_info["input_cost_per_token"] == dashscope_info["input_cost_per_token"]
+        assert model_info["output_cost_per_token"] == dashscope_info["output_cost_per_token"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_flat_pricing_matches_dashscope(self, brand):
+        usage = Usage(prompt_tokens=1000, completion_tokens=500)
+        brand_costs = dashscope_cost_per_token(model="qwen-max", usage=usage, custom_llm_provider=brand["provider"])
+        dashscope_costs = dashscope_cost_per_token(model="qwen-max", usage=usage)
+        assert brand_costs == dashscope_costs
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_tiered_pricing_matches_dashscope(self, brand):
+        usage = Usage(prompt_tokens=300000, completion_tokens=300000)
+        brand_costs = dashscope_cost_per_token(model="qwen-flash", usage=usage, custom_llm_provider=brand["provider"])
+        dashscope_costs = dashscope_cost_per_token(model="qwen-flash", usage=usage)
+        assert brand_costs == dashscope_costs
+        tier_2 = litellm.get_model_info(f"{brand['provider']}/qwen-flash")["tiered_pricing"][1]
+        assert math.isclose(brand_costs[0], 300000 * tier_2["input_cost_per_token"], rel_tol=1e-10)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_public_cost_per_token_routes_to_dashscope_calculator(self, brand):
+        brand_costs = litellm.cost_per_token(
+            model=f"{brand['provider']}/qwen-max",
+            prompt_tokens=1000,
+            completion_tokens=500,
+            custom_llm_provider=brand["provider"],
+        )
+        dashscope_costs = litellm.cost_per_token(
+            model="dashscope/qwen-max",
+            prompt_tokens=1000,
+            completion_tokens=500,
+            custom_llm_provider="dashscope",
+        )
+        assert brand_costs == dashscope_costs
+
+
+class TestQwenBrandCompletionMock:
+    @pytest.mark.respx()
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_completion_hits_brand_default_host(self, respx_mock, brand, monkeypatch):
+        monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+        respx_mock.post(f"{brand['default_base']}/chat/completions").respond(
+            json={
+                "id": "chatcmpl-123",
+                "object": "chat.completion",
+                "created": 1677652288,
+                "model": "qwen-turbo",
+                "choices": [
+                    {
+                        "index": 0,
+                        "message": {"role": "assistant", "content": "Hey from LiteLLM!"},
+                        "finish_reason": "stop",
+                    }
+                ],
+                "usage": {
+                    "prompt_tokens": 9,
+                    "completion_tokens": 12,
+                    "total_tokens": 21,
+                },
+            },
+            status_code=200,
+        )
+
+        response = completion(
+            model=f"{brand['provider']}/qwen-turbo",
+            messages=[{"role": "user", "content": "say hey from LiteLLM"}],
+            api_key="fake-brand-key",
+        )
+
+        assert response.choices[0].message.content == "Hey from LiteLLM!"
+        request = respx_mock.calls[0].request
+        assert request.url == f"{brand['default_base']}/chat/completions"
+        assert request.headers["Authorization"] == "Bearer fake-brand-key"
diff --git a/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py b/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py
index 41fb2589655..71661cc532b 100644
--- a/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py
+++ b/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py
@@ -422,6 +422,27 @@ def test_databricks_config_probes_capabilities_under_databricks_namespace():
     assert DatabricksConfig().custom_llm_provider == "databricks"
 
 
+@pytest.mark.parametrize(
+    "model, expected_thinking, expected_output_config",
+    [
+        ("databricks-claude-opus-4-8", {"type": "adaptive"}, {"effort": "high"}),
+        ("databricks-claude-opus-4-6", {"type": "enabled", "budget_tokens": 4096}, None),
+    ],
+    ids=["adaptive_only_upgrades_to_adaptive", "legacy_capable_forwards_verbatim"],
+)
+def test_map_openai_params_upgrades_legacy_thinking_on_adaptive_only_claude(
+    model, expected_thinking, expected_output_config
+):
+    mapped = DatabricksConfig().map_openai_params(
+        non_default_params={"thinking": {"type": "enabled", "budget_tokens": 4096}},
+        optional_params={},
+        model=model,
+        drop_params=False,
+    )
+    assert mapped["thinking"] == expected_thinking
+    assert mapped.get("output_config") == expected_output_config
+
+
 def _streaming_chunk(usage=None, choices=None):
     base = {
         "id": "chatcmpl-test",
diff --git a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
index 29ad8ee4b6e..e72642f7a04 100644
--- a/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
+++ b/tests/test_litellm/llms/databricks/test_databricks_cost_calculator.py
@@ -62,6 +62,8 @@ PUBLISHED_DBU_PER_MILLION: Final = {
     "databricks/databricks-gemini-2-5-pro": ("22.321", "178.571", "22.321", "2.232"),
     "databricks/databricks-gemini-2-5-flash": ("5.357", "44.643", "5.357", "0.536"),
     "databricks/databricks-kimi-k3": ("42.857", "214.286", "42.857", "4.286"),
+    "databricks/databricks-deepseek-v4-flash-0731": ("2.000", "4.000", "2.000", "0.400"),
+    "databricks/databricks-deepseek-v4-pro-0813": ("18.857", "56.571", "18.857", "1.886"),
     "databricks/databricks-glm-5-2": ("20.000", "62.857", "20.000", "3.714"),
 }
 PROMOTIONAL_DISCOUNT: Final = 0.80
diff --git a/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py b/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py
index 3153c12aa94..3d15a2e8870 100644
--- a/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py
+++ b/tests/test_litellm/llms/gdc/chat/test_gdc_chat_transformation.py
@@ -310,6 +310,25 @@ class TestGDCGeminiConfig:
                     api_base=TEST_API_BASE,
                 )
 
+    def test_validate_environment_credentials_missing_audience_binding_are_named(self):
+        config = GDCGeminiConfig()
+        creds_without_audience_binding = MagicMock(spec=[])
+
+        with patch(
+            "google.auth.load_credentials_from_dict",
+            return_value=(creds_without_audience_binding, None),
+        ):
+            with pytest.raises(AttributeError, match="must expose with_gdch_audience"):
+                config.validate_environment(
+                    headers={},
+                    model=TEST_MODEL,
+                    messages=[],
+                    optional_params={},
+                    litellm_params={"vertex_project": TEST_PROJECT},
+                    api_key=TEST_API_KEY,
+                    api_base=TEST_API_BASE,
+                )
+
     def test_validate_environment_string_false_disables_token_caching(self):
         config = GDCGeminiConfig()
         mock_creds = MagicMock()
diff --git a/tests/test_litellm/llms/gigachat/__init__.py b/tests/test_litellm/llms/gigachat/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_streaming.py b/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_streaming.py
new file mode 100644
index 00000000000..35ca93319f5
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_streaming.py
@@ -0,0 +1,87 @@
+"""
+Tests for litellm.llms.gigachat.chat.streaming
+"""
+
+from litellm.llms.gigachat.chat.streaming import GigaChatModelResponseIterator
+
+
+def _parse(chunk: dict) -> dict:
+    iterator = GigaChatModelResponseIterator(streaming_response=None, sync_stream=True)
+    return dict(iterator.chunk_parser(chunk=chunk))
+
+
+class TestChunkParserUsage:
+    def test_usage_on_stop_chunk(self):
+        parsed = _parse(
+            {
+                "choices": [{"delta": {"content": ""}, "index": 0, "finish_reason": "stop"}],
+                "usage": {"prompt_tokens": 25, "completion_tokens": 7, "total_tokens": 32},
+            }
+        )
+
+        assert parsed["finish_reason"] == "stop"
+        assert parsed["usage"] is not None
+        assert parsed["usage"]["prompt_tokens"] == 25
+        assert parsed["usage"]["completion_tokens"] == 7
+        assert parsed["usage"]["total_tokens"] == 32
+
+    def test_usage_on_function_call_chunk(self):
+        """Regression: a final chunk ending in function_call still carries usage; it must not be dropped."""
+        parsed = _parse(
+            {
+                "choices": [
+                    {
+                        "delta": {"function_call": {"name": "get_weather", "arguments": {"city": "Moscow"}}},
+                        "index": 0,
+                        "finish_reason": "function_call",
+                    }
+                ],
+                "usage": {"prompt_tokens": 40, "completion_tokens": 12, "total_tokens": 52},
+            }
+        )
+
+        assert parsed["finish_reason"] == "tool_calls"
+        assert parsed["tool_use"] is not None
+        assert parsed["usage"] is not None
+        assert parsed["usage"]["prompt_tokens"] == 40
+        assert parsed["usage"]["completion_tokens"] == 12
+        assert parsed["usage"]["total_tokens"] == 52
+
+    def test_usage_on_length_chunk(self):
+        parsed = _parse(
+            {
+                "choices": [{"delta": {"content": "truncated"}, "index": 0, "finish_reason": "length"}],
+                "usage": {"prompt_tokens": 10, "completion_tokens": 128, "total_tokens": 138},
+            }
+        )
+
+        assert parsed["usage"] is not None
+        assert parsed["usage"]["total_tokens"] == 138
+
+    def test_no_usage_on_interim_chunk(self):
+        parsed = _parse({"choices": [{"delta": {"content": "hello"}, "index": 0, "finish_reason": None}]})
+
+        assert parsed["text"] == "hello"
+        assert parsed["is_finished"] is False
+        assert parsed["usage"] is None
+
+    def test_cache_hit_usage_folds_cached_tokens_back_in(self):
+        """GigaChat reports prompt_tokens and total_tokens after subtracting cached tokens
+        (docs example: prompt_tokens=1, precached_prompt_tokens=37, total_tokens=5), so the
+        OpenAI-convention usage must add them back and surface them as cached_tokens."""
+        parsed = _parse(
+            {
+                "choices": [{"delta": {"content": ""}, "index": 0, "finish_reason": "stop"}],
+                "usage": {
+                    "prompt_tokens": 25,
+                    "completion_tokens": 7,
+                    "total_tokens": 32,
+                    "precached_prompt_tokens": 20,
+                },
+            }
+        )
+
+        assert parsed["usage"] is not None
+        assert parsed["usage"]["prompt_tokens"] == 45
+        assert parsed["usage"]["total_tokens"] == 52
+        assert parsed["usage"]["prompt_tokens_details"]["cached_tokens"] == 20
diff --git a/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_transformation.py b/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_transformation.py
new file mode 100644
index 00000000000..2f9511e642c
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/chat/test_gigachat_chat_transformation.py
@@ -0,0 +1,883 @@
+"""
+Unit tests for GigaChat chat transformation.
+
+Tests GigaChatConfig covering get_complete_url, validate_environment,
+get_supported_openai_params, map_openai_params, _convert_tools_to_functions,
+_map_tool_choice, _transform_messages, transform_request, transform_response,
+get_model_response_iterator, and get_error_class.
+"""
+
+import json
+from unittest.mock import MagicMock, patch
+
+import httpx
+import pytest
+
+from litellm.llms.gigachat.chat.transformation import (
+    GigaChatConfig,
+    GigaChatError,
+    is_valid_json,
+)
+from litellm.types.utils import ModelResponse, Usage
+
+TRANSFORM_MODULE = "litellm.llms.gigachat.chat.transformation"
+
+
+def _make_httpx_response(
+    body: dict, status_code: int = 200
+) -> httpx.Response:
+    return httpx.Response(
+        status_code=status_code,
+        headers={"content-type": "application/json"},
+        content=json.dumps(body).encode("utf-8"),
+        request=httpx.Request(
+            "POST",
+            "https://gigachat.devices.sberbank.ru/api/v1/chat/completions",
+        ),
+    )
+
+
+# ---------------------------------------------------------------------------
+# is_valid_json
+# ---------------------------------------------------------------------------
+
+
+class TestIsValidJson:
+    def test_valid_json_object(self):
+        assert is_valid_json('{"key": "value"}') is True
+
+    def test_valid_json_array(self):
+        assert is_valid_json("[1, 2, 3]") is True
+
+    def test_valid_json_string(self):
+        assert is_valid_json('"hello"') is True
+
+    def test_invalid_json(self):
+        assert is_valid_json("{invalid}") is False
+
+    def test_empty_string(self):
+        assert is_valid_json("") is False
+
+
+# ---------------------------------------------------------------------------
+# GigaChatConfig
+# ---------------------------------------------------------------------------
+
+
+class TestGetCompleteUrl:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_uses_api_base_from_param(self):
+        url = self.config.get_complete_url(
+            api_base="https://custom.example.com",
+            api_key=None,
+            model="GigaChat",
+            optional_params={},
+            litellm_params={},
+            stream=False,
+        )
+        assert url == "https://custom.example.com/chat/completions"
+
+    def test_uses_api_base_with_trailing_slash(self):
+        url = self.config.get_complete_url(
+            api_base="https://custom.example.com/",
+            api_key=None,
+            model="GigaChat",
+            optional_params={},
+            litellm_params={},
+            stream=False,
+        )
+        # get_api_base passes the value through without stripping the slash
+        assert url == "https://custom.example.com//chat/completions"
+
+    def test_uses_api_base_from_get_api_base_when_none(self):
+        url = self.config.get_complete_url(
+            api_base=None,
+            api_key=None,
+            model="GigaChat",
+            optional_params={},
+            litellm_params={},
+            stream=False,
+        )
+        assert url.endswith("/chat/completions")
+
+
+class TestValidateEnvironment:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{TRANSFORM_MODULE}.get_secret_str", return_value=None)
+    def test_sets_auth_headers(self, mock_get_secret, mock_get_token):
+        headers: dict = {}
+        result = self.config.validate_environment(
+            headers=headers,
+            model="GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={},
+            litellm_params={},
+            api_key="creds",
+            api_base="https://api.example.com",
+        )
+        assert result["Authorization"] == "Bearer test-token"
+        assert result["Content-Type"] == "application/json"
+        assert result["Accept"] == "application/json"
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="token")
+    @patch(f"{TRANSFORM_MODULE}.get_secret_str", return_value=None)
+    def test_stores_credentials_and_api_base_for_image_uploads(
+        self, mock_get_secret, mock_get_token
+    ):
+        self.config.validate_environment(
+            headers={},
+            model="GigaChat",
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            api_key="my-creds",
+            api_base="https://my-api.example.com",
+        )
+        assert self.config._current_credentials == "my-creds"
+        assert self.config._current_api_base == "https://my-api.example.com"
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="token")
+    @patch(f"{TRANSFORM_MODULE}.get_secret_str")
+    def test_falls_back_to_env_for_credentials(  # test-quality-ok: mock-echo of internal wiring
+        self, mock_get_secret, mock_get_token
+    ):
+        mock_get_secret.return_value = "env-creds"
+        self.config.validate_environment(
+            headers={},
+            model="GigaChat",
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            api_key=None,
+            api_base=None,
+        )
+        mock_get_secret.assert_any_call("GIGACHAT_CREDENTIALS")  # test-quality-ok: mock-echo of internal wiring
+
+
+class TestGetSupportedOpenAiParams:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_returns_expected_params(self):
+        params = self.config.get_supported_openai_params("GigaChat")
+        expected = [
+            "stream",
+            "temperature",
+            "top_p",
+            "max_tokens",
+            "max_completion_tokens",
+            "stop",
+            "tools",
+            "tool_choice",
+            "functions",
+            "function_call",
+            "response_format",
+        ]
+        assert params == expected
+
+
+class TestMapOpenAiParams:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_stream(self):
+        result = self.config.map_openai_params(
+            non_default_params={"stream": True},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["stream"] is True
+
+    def test_temperature_zero_maps_to_top_p_zero(self):
+        result = self.config.map_openai_params(
+            non_default_params={"temperature": 0},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["top_p"] == 0
+        assert "temperature" not in result
+
+    def test_temperature_non_zero(self):
+        result = self.config.map_openai_params(
+            non_default_params={"temperature": 0.7},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["temperature"] == 0.7
+
+    def test_top_p(self):
+        result = self.config.map_openai_params(
+            non_default_params={"top_p": 0.5},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["top_p"] == 0.5
+
+    def test_max_tokens(self):
+        result = self.config.map_openai_params(
+            non_default_params={"max_tokens": 100},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["max_tokens"] == 100
+
+    def test_max_completion_tokens(self):
+        result = self.config.map_openai_params(
+            non_default_params={"max_completion_tokens": 200},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["max_tokens"] == 200
+
+    def test_stop_is_dropped(self):
+        result = self.config.map_openai_params(
+            non_default_params={"stop": ["\n\n"]},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert "stop" not in result
+
+    def test_tools_converted_to_functions(self):
+        tools = [
+            {
+                "type": "function",
+                "function": {
+                    "name": "get_weather",
+                    "description": "Get weather",
+                    "parameters": {"type": "object"},
+                },
+            }
+        ]
+        result = self.config.map_openai_params(
+            non_default_params={"tools": tools},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert "functions" in result
+        assert result["functions"] == [
+            {"name": "get_weather", "description": "Get weather", "parameters": {"type": "object"}}
+        ]
+
+    def test_tool_choice_auto(self):
+        result = self.config.map_openai_params(
+            non_default_params={"tool_choice": "auto"},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result.get("function_call") == "auto"
+
+    def test_tool_choice_none(self):
+        result = self.config.map_openai_params(
+            non_default_params={"tool_choice": "none"},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result.get("function_call") == "none"
+
+    def test_tool_choice_required(self):
+        result = self.config.map_openai_params(
+            non_default_params={"tool_choice": "required"},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result.get("function_call") == "auto"
+
+    def test_tool_choice_dict(self):
+        result = self.config.map_openai_params(
+            non_default_params={
+                "tool_choice": {
+                    "type": "function",
+                    "function": {"name": "get_weather"},
+                }
+            },
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result.get("function_call") == {"name": "get_weather"}
+
+    def test_functions(self):
+        funcs = [{"name": "my_func", "description": "desc", "parameters": {}}]
+        result = self.config.map_openai_params(
+            non_default_params={"functions": funcs},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["functions"] == funcs
+
+    def test_function_call(self):
+        result = self.config.map_openai_params(
+            non_default_params={"function_call": {"name": "my_func"}},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result["function_call"] == {"name": "my_func"}
+
+    def test_response_format_json_schema(self):
+        response_format = {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "test_schema",
+                "schema": {"type": "object", "properties": {"name": {"type": "string"}}},
+            },
+        }
+        result = self.config.map_openai_params(
+            non_default_params={"response_format": response_format},
+            optional_params={"functions": []},
+            model="GigaChat",
+            drop_params=False,
+        )
+        # Should add a function for the schema
+        assert len(result["functions"]) == 1
+        assert result["functions"][0]["name"] == "test_schema"
+        assert result["function_call"] == {"name": "test_schema"}
+        assert result["_structured_output"] is True
+
+
+class TestConvertToolsToFunctions:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_converts_function_tools_only(self):
+        tools = [
+            {"type": "function", "function": {"name": "a", "description": "d", "parameters": {}}},
+            {"type": "code_interpreter"},  # should be ignored
+        ]
+        result = self.config._convert_tools_to_functions(tools)
+        assert len(result) == 1
+        assert result[0]["name"] == "a"
+
+    def test_empty_tools(self):
+        assert self.config._convert_tools_to_functions([]) == []
+
+
+class TestMapToolChoice:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_none(self):
+        assert self.config._map_tool_choice("none") == "none"
+
+    def test_auto(self):
+        assert self.config._map_tool_choice("auto") == "auto"
+
+    def test_required(self):
+        assert self.config._map_tool_choice("required") == "auto"
+
+    def test_dict_with_function(self):
+        result = self.config._map_tool_choice(
+            {"type": "function", "function": {"name": "get_weather"}}
+        )
+        assert result == {"name": "get_weather"}
+
+    def test_dict_without_name(self):
+        result = self.config._map_tool_choice(
+            {"type": "function", "function": {}}
+        )
+        assert result is None
+
+    def test_unknown_value(self):
+        assert self.config._map_tool_choice("unknown") is None
+
+
+class TestTransformMessages:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_developer_role_to_system(self):
+        result = self.config._transform_messages(
+            [{"role": "developer", "content": "be helpful"}]
+        )
+        assert result[0]["role"] == "system"
+        assert result[0]["content"] == "be helpful"
+
+    def test_system_message_not_first_becomes_user(self):
+        result = self.config._transform_messages([
+            {"role": "user", "content": "hi"},
+            {"role": "system", "content": "instruction"},
+        ])
+        assert result[0]["role"] == "user"
+        assert result[1]["role"] == "user"
+        assert result[1]["content"] == "instruction"
+
+    def test_tool_role_to_function(self):
+        result = self.config._transform_messages([
+            {"role": "tool", "content": '{"result": "ok"}'}
+        ])
+        assert result[0]["role"] == "function"
+
+    def test_tool_role_content_wraps_non_json(self):
+        result = self.config._transform_messages([
+            {"role": "tool", "content": "plain text"}
+        ])
+        assert result[0]["role"] == "function"
+        assert is_valid_json(result[0]["content"])
+
+    def test_none_content_becomes_empty_string(self):
+        result = self.config._transform_messages([
+            {"role": "user", "content": None}
+        ])
+        assert result[0]["content"] == ""
+
+    def test_name_field_removed(self):
+        result = self.config._transform_messages([
+            {"role": "user", "content": "hi", "name": "John"}
+        ])
+        assert "name" not in result[0]
+
+    def test_tool_calls_converted_to_function_call(self):
+        result = self.config._transform_messages([
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [
+                    {
+                        "id": "call_abc",
+                        "type": "function",
+                        "function": {
+                            "name": "get_weather",
+                            "arguments": '{"city": "London"}',
+                        },
+                    }
+                ],
+            }
+        ])
+        assert "tool_calls" not in result[0]
+        assert result[0]["function_call"]["name"] == "get_weather"
+        assert result[0]["function_call"]["arguments"] == {"city": "London"}
+
+    def test_tool_calls_with_dict_arguments(self):
+        result = self.config._transform_messages([
+            {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [
+                    {
+                        "id": "call_xyz",
+                        "type": "function",
+                        "function": {
+                            "name": "search",
+                            "arguments": {"query": "test"},
+                        },
+                    }
+                ],
+            }
+        ])
+        assert result[0]["function_call"]["arguments"] == {"query": "test"}
+
+    def test_list_content_multimodal(self):
+        content = [
+            {"type": "text", "text": "describe this"},
+            {
+                "type": "image_url",
+                "image_url": {"url": "https://example.com/img.jpg"},
+            },
+        ]
+        with patch.object(self.config, "_upload_image", return_value="file-123"):
+            result = self.config._transform_messages([
+                {"role": "user", "content": content}
+            ])
+        assert result[0]["content"] == "describe this"
+        assert result[0]["attachments"] == ["file-123"]
+
+    def test_list_content_with_image_url_string(self):
+        content = [
+            {"type": "text", "text": "look"},
+            {"type": "image_url", "image_url": "https://example.com/img.jpg"},
+        ]
+        with patch.object(self.config, "_upload_image", return_value="file-456"):
+            result = self.config._transform_messages([
+                {"role": "user", "content": content}
+            ])
+        assert result[0]["content"] == "look"
+        assert "file-456" in result[0]["attachments"]
+
+
+class TestTransformRequest:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_builds_basic_request(self):
+        body = self.config.transform_request(
+            model="gigachat/GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={},
+            litellm_params={},
+            headers={},
+        )
+        assert body["model"] == "GigaChat"
+        assert len(body["messages"]) == 1
+        assert body["messages"][0]["content"] == "hi"
+
+    def test_model_prefix_stripped(self):
+        body = self.config.transform_request(
+            model="gigachat/GigaChat-Pro",
+            messages=[{"role": "user", "content": "hello"}],
+            optional_params={},
+            litellm_params={},
+            headers={},
+        )
+        assert body["model"] == "GigaChat-Pro"
+
+    def test_includes_optional_params(self):
+        body = self.config.transform_request(
+            model="gigachat/GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={
+                "temperature": 0.5,
+                "max_tokens": 100,
+                "stream": True,
+            },
+            litellm_params={},
+            headers={},
+        )
+        assert body["temperature"] == 0.5
+        assert body["max_tokens"] == 100
+        assert body["stream"] is True
+
+    def test_includes_functions(self):
+        body = self.config.transform_request(
+            model="gigachat/GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={
+                "functions": [{"name": "my_func"}],
+                "function_call": {"name": "my_func"},
+            },
+            litellm_params={},
+            headers={},
+        )
+        assert body["functions"] == [{"name": "my_func"}]
+        assert body["function_call"] == {"name": "my_func"}
+
+    def test_skips_unsupported_params(self):
+        body = self.config.transform_request(
+            model="gigachat/GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={"n": 2, "user": "abc"},
+            litellm_params={},
+            headers={},
+        )
+        assert "n" not in body
+        assert "user" not in body
+
+
+class TestTransformResponse:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_basic_response(self):
+        raw = _make_httpx_response({
+            "id": "chatcmpl-123",
+            "created": 1700000000,
+            "model": "GigaChat",
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {"role": "assistant", "content": "Hello!"},
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        assert result.choices[0].message.content == "Hello!"
+        assert result.choices[0].finish_reason == "stop"
+        assert result.usage.prompt_tokens == 5
+        assert result.usage.total_tokens == 8
+
+    def test_function_call_into_tool_calls(self):
+        raw = _make_httpx_response({
+            "id": "chatcmpl-456",
+            "created": 1700000000,
+            "model": "GigaChat",
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": None,
+                        "function_call": {
+                            "name": "get_weather",
+                            "arguments": {"city": "Moscow"},
+                        },
+                    },
+                    "finish_reason": "function_call",
+                }
+            ],
+            "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        assert result.choices[0].finish_reason == "tool_calls"
+        tool_calls = result.choices[0].message.tool_calls
+        assert tool_calls is not None
+        assert len(tool_calls) == 1
+        assert tool_calls[0].function.name == "get_weather"
+        assert '{"city": "Moscow"}' in tool_calls[0].function.arguments
+
+    def test_function_call_structured_output(self):
+        raw = _make_httpx_response({
+            "id": "chatcmpl-789",
+            "created": 1700000000,
+            "model": "GigaChat",
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": None,
+                        "function_call": {
+                            "name": "test_schema",
+                            "arguments": {"name": "John"},
+                        },
+                    },
+                    "finish_reason": "function_call",
+                }
+            ],
+            "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={"_structured_output": True},
+            litellm_params={},
+            encoding=None,
+        )
+        # Structured output: function_call -> content
+        assert result.choices[0].finish_reason == "stop"
+        assert result.choices[0].message.content is not None
+        assert '"name": "John"' in result.choices[0].message.content
+
+    def test_function_call_string_arguments(self):
+        raw = _make_httpx_response({
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "function_call": {
+                            "name": "get_weather",
+                            "arguments": '{"city": "Moscow"}',
+                        },
+                    },
+                    "finish_reason": "function_call",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        tc = result.choices[0].message.tool_calls[0]
+        assert '{"city": "Moscow"}' in tc.function.arguments
+
+    def test_cleans_up_gigachat_specific_fields(self):
+        raw = _make_httpx_response({
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": "done",
+                        "functions_state_id": "some-state",
+                    },
+                    "finish_reason": "stop",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        # functions_state_id should have been removed from the message data
+        assert result.choices[0].message.content == "done"
+
+    def test_raises_on_invalid_json(self):
+        raw = httpx.Response(
+            status_code=500,
+            headers={"content-type": "text/plain"},
+            content=b"not json",
+            request=httpx.Request("POST", "https://example.com"),
+        )
+        model_response = ModelResponse()
+        with pytest.raises(GigaChatError) as exc_info:
+            self.config.transform_response(
+                model="gigachat/GigaChat",
+                raw_response=raw,
+                model_response=model_response,
+                logging_obj=MagicMock(),
+                request_data={},
+                messages=[],
+                optional_params={},
+                litellm_params={},
+                encoding=None,
+            )
+        assert "Invalid JSON response" in str(exc_info.value.message)
+
+    def test_empty_choices(self):
+        raw = _make_httpx_response({
+            "choices": [],
+            "usage": {},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        assert result.choices == []
+
+    def test_function_call_with_non_dict_arguments(self):
+        raw = _make_httpx_response({
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "function_call": {
+                            "name": "say_hello",
+                            "arguments": "hello",
+                        },
+                    },
+                    "finish_reason": "function_call",
+                }
+            ],
+            "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        })
+        model_response = ModelResponse()
+        result = self.config.transform_response(
+            model="gigachat/GigaChat",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=MagicMock(),
+            request_data={},
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            encoding=None,
+        )
+        tc = result.choices[0].message.tool_calls[0]
+        assert tc.function.arguments == "hello"
+
+
+class TestGetModelResponseIterator:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_returns_gigachat_iterator_sync(self):
+        from litellm.llms.gigachat.chat.streaming import (
+            GigaChatModelResponseIterator,
+        )
+
+        result = self.config.get_model_response_iterator(
+            streaming_response=iter(["data"]),
+            sync_stream=True,
+            json_mode=False,
+        )
+        assert isinstance(result, GigaChatModelResponseIterator)
+
+
+class TestGetErrorClass:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    def test_returns_gigachat_error(self):
+        error = self.config.get_error_class(
+            error_message="something went wrong",
+            status_code=400,
+            headers={"x-request-id": "abc"},
+        )
+        assert isinstance(error, GigaChatError)
+        assert error.status_code == 400
+        assert error.message == "something went wrong"
+        assert error.headers == {"x-request-id": "abc"}
+
+
+class TestUploadImage:
+    def setup_method(self):
+        self.config = GigaChatConfig()
+
+    @patch(f"{TRANSFORM_MODULE}.upload_file_sync", return_value="file-uploaded")
+    def test_upload_image_success(self, mock_upload):
+        self.config._current_credentials = "creds"
+        self.config._current_api_base = "https://api.example.com"
+        result = self.config._upload_image("https://example.com/img.jpg")
+        assert result == "file-uploaded"
+        mock_upload.assert_called_once_with(
+            image_url="https://example.com/img.jpg",
+            credentials="creds",
+            api_base="https://api.example.com",
+        )
+
+    @patch(f"{TRANSFORM_MODULE}.upload_file_sync", side_effect=Exception("fail"))
+    def test_upload_image_failure_returns_none(self, mock_upload):
+        result = self.config._upload_image("https://example.com/img.jpg")
+        assert result is None
\ No newline at end of file
diff --git a/tests/test_litellm/llms/gigachat/embedding/__init__.py b/tests/test_litellm/llms/gigachat/embedding/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/llms/gigachat/embedding/test_gigachat_embedding_transformation.py b/tests/test_litellm/llms/gigachat/embedding/test_gigachat_embedding_transformation.py
new file mode 100644
index 00000000000..8537793ea72
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/embedding/test_gigachat_embedding_transformation.py
@@ -0,0 +1,372 @@
+"""
+Unit tests for GigaChat embedding transformation.
+
+Tests GigaChatEmbeddingConfig covering get_config, get_supported_openai_params,
+map_openai_params, _get_openai_compatible_provider_info, get_complete_url,
+transform_embedding_request, transform_embedding_response, validate_environment,
+and get_error_class.
+"""
+
+import json
+from unittest.mock import MagicMock, patch
+
+import httpx
+import pytest
+
+from litellm import LlmProviders
+from litellm.llms.gigachat.embedding.transformation import (
+    GigaChatEmbeddingConfig,
+    GigaChatEmbeddingError,
+)
+from litellm.types.utils import EmbeddingResponse
+
+TRANSFORM_MODULE = "litellm.llms.gigachat.embedding.transformation"
+
+
+def _make_httpx_response(body: dict, status_code: int = 200) -> httpx.Response:
+    return httpx.Response(
+        status_code=status_code,
+        headers={"content-type": "application/json"},
+        content=json.dumps(body).encode("utf-8"),
+        request=httpx.Request("POST", "https://gigachat.devices.sberbank.ru/api/v1/embeddings"),
+    )
+
+
+# ---------------------------------------------------------------------------
+# GigaChatEmbeddingConfig
+# ---------------------------------------------------------------------------
+
+
+class TestGetConfig:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_contains_only_abc_impl(self):
+        """get_config returns ABC internal data due to inheritance."""
+        result = self.config.get_config()
+        # The only key should be _abc_impl from ABC base class
+        assert set(result.keys()) == {"_abc_impl"}
+
+
+class TestGetSupportedOpenAiParams:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_returns_empty_list(self):
+        params = self.config.get_supported_openai_params("GigaChat")
+        assert params == []
+
+
+class TestMapOpenAiParams:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_returns_optional_params_unchanged(self):
+        result = self.config.map_openai_params(
+            non_default_params={"model": "test"},
+            optional_params={"temperature": 0.5},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result == {"temperature": 0.5}
+
+    def test_returns_empty_dict_when_no_optional_params(self):
+        result = self.config.map_openai_params(
+            non_default_params={},
+            optional_params={},
+            model="GigaChat",
+            drop_params=False,
+        )
+        assert result == {}
+
+
+class TestGetOpenaiCompatibleProviderInfo:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_returns_gigachat_provider(self):
+        provider, api_base, api_key = self.config._get_openai_compatible_provider_info(
+            api_base="https://api.example.com", api_key="test-key"
+        )
+        assert provider == LlmProviders.GIGACHAT.value
+        assert api_base == "https://api.example.com"
+        assert api_key == "test-key"
+
+    def test_resolves_api_base_when_none(self, monkeypatch):
+        monkeypatch.delenv("GIGACHAT_API_BASE", raising=False)
+        provider, api_base, api_key = self.config._get_openai_compatible_provider_info(
+            api_base=None, api_key="key"
+        )
+        assert api_base is not None
+        assert api_base.endswith("/api/v1")
+
+    def test_returns_none_api_key(self):
+        _, _, api_key = self.config._get_openai_compatible_provider_info(
+            api_base="https://example.com", api_key=None
+        )
+        assert api_key is None
+
+
+class TestGetCompleteUrl:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_default_url(self):
+        url = self.config.get_complete_url(
+            api_base=None, api_key=None, model="GigaChat",
+            optional_params={}, litellm_params={},
+        )
+        assert url.endswith("/embeddings")
+
+    def test_custom_api_base(self):
+        url = self.config.get_complete_url(
+            api_base="https://custom.example.com", api_key=None, model="GigaChat",
+            optional_params={}, litellm_params={},
+        )
+        assert url == "https://custom.example.com/embeddings"
+
+    def test_trailing_slash_api_base(self):
+        url = self.config.get_complete_url(
+            api_base="https://custom.example.com/", api_key=None, model="GigaChat",
+            optional_params={}, litellm_params={},
+        )
+        # get_api_base doesn't strip slash, so we get double slash
+        assert url == "https://custom.example.com//embeddings"
+
+
+class TestTransformEmbeddingRequest:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_string_input(self):
+        result = self.config.transform_embedding_request(
+            model="gigachat/Embeddings",
+            input="hello world",
+            optional_params={},
+            headers={},
+        )
+        assert result == {"model": "Embeddings", "input": ["hello world"]}
+
+    def test_list_input(self):
+        result = self.config.transform_embedding_request(
+            model="gigachat/Embeddings",
+            input=["text1", "text2"],
+            optional_params={},
+            headers={},
+        )
+        assert result == {"model": "Embeddings", "input": ["text1", "text2"]}
+
+    def test_strips_gigachat_prefix(self):
+        result = self.config.transform_embedding_request(
+            model="gigachat/GigaChat-Pro",
+            input="test",
+            optional_params={},
+            headers={},
+        )
+        assert result["model"] == "GigaChat-Pro"
+
+    def test_model_without_prefix(self):
+        result = self.config.transform_embedding_request(
+            model="Embeddings",
+            input="test",
+            optional_params={},
+            headers={},
+        )
+        assert result["model"] == "Embeddings"
+
+
+class TestTransformEmbeddingResponse:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+        self.logging_obj = MagicMock()
+
+    def _make_gigachat_response(self, data: list[dict]) -> httpx.Response:
+        return _make_httpx_response({
+            "object": "list",
+            "data": data,
+            "model": "Embeddings",
+        })
+
+    def test_basic_response(self):
+        raw = self._make_gigachat_response([
+            {
+                "object": "embedding",
+                "embedding": [0.1, 0.2, 0.3],
+                "index": 0,
+            }
+        ])
+        model_response = EmbeddingResponse()
+        result = self.config.transform_embedding_response(
+            model="gigachat/Embeddings",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=self.logging_obj,
+            api_key="test-key",
+            request_data={"input": ["text"]},
+            optional_params={},
+            litellm_params={},
+        )
+        assert result.object == "list"
+        assert len(result.data) == 1
+        assert result.data[0]["embedding"] == [0.1, 0.2, 0.3]
+        assert result.data[0]["index"] == 0
+        assert result.usage.prompt_tokens == 0
+        assert result.usage.total_tokens == 0
+
+    def test_aggregates_per_embedding_usage(self):
+        raw = self._make_gigachat_response([
+            {
+                "object": "embedding",
+                "embedding": [0.1, 0.2],
+                "index": 0,
+                "usage": {"prompt_tokens": 5},
+            },
+            {
+                "object": "embedding",
+                "embedding": [0.3, 0.4],
+                "index": 1,
+                "usage": {"prompt_tokens": 7},
+            },
+        ])
+        model_response = EmbeddingResponse()
+        result = self.config.transform_embedding_response(
+            model="gigachat/Embeddings",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=self.logging_obj,
+            api_key="test-key",
+            request_data={"input": ["a", "b"]},
+            optional_params={},
+            litellm_params={},
+        )
+        # Total should be sum of per-embedding prompt_tokens
+        assert result.usage.prompt_tokens == 12
+        assert result.usage.total_tokens == 12
+        # Usage should be removed from individual embedding data
+        assert "usage" not in result.data[0]
+        assert "usage" not in result.data[1]
+
+    def test_usage_removed_from_individual_embeddings(self):
+        raw = self._make_gigachat_response([
+            {
+                "object": "embedding",
+                "embedding": [0.5],
+                "index": 0,
+                "usage": {"prompt_tokens": 3},
+            }
+        ])
+        model_response = EmbeddingResponse()
+        result = self.config.transform_embedding_response(
+            model="gigachat/Embeddings",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=self.logging_obj,
+            api_key="key",
+            request_data={"input": ["x"]},
+            optional_params={},
+            litellm_params={},
+        )
+        # usage should NOT be in the final EmbeddingResponse data items
+        for emb in result.data:
+            assert "usage" not in emb
+
+    def test_passes_model_from_response(self):
+        raw = self._make_gigachat_response([
+            {"object": "embedding", "embedding": [0.1], "index": 0},
+        ])
+        model_response = EmbeddingResponse()
+        result = self.config.transform_embedding_response(
+            model="gigachat/Embeddings",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=self.logging_obj,
+            api_key="key",
+            request_data={"input": ["x"]},
+            optional_params={},
+            litellm_params={},
+        )
+        assert result.model == "Embeddings"
+
+    def test_calls_logging_post_call(self):
+        raw = self._make_gigachat_response([
+            {"object": "embedding", "embedding": [0.1], "index": 0},
+        ])
+        model_response = EmbeddingResponse()
+        self.config.transform_embedding_response(
+            model="gigachat/Embeddings",
+            raw_response=raw,
+            model_response=model_response,
+            logging_obj=self.logging_obj,
+            api_key="test-api-key",
+            request_data={"input": ["hello"]},
+            optional_params={},
+            litellm_params={},
+        )
+        self.logging_obj.post_call.assert_called_once()
+        args = self.logging_obj.post_call.call_args.kwargs
+        assert args["api_key"] == "test-api-key"
+        assert args["input"] == ["hello"]
+
+
+class TestValidateEnvironment:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="test-token")
+    def test_sets_oauth_headers(self, mock_get_token):
+        headers = self.config.validate_environment(
+            headers={},
+            model="GigaChat",
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            api_key="creds",
+            api_base="https://api.example.com",
+        )
+        assert headers["Authorization"] == "Bearer test-token"
+        assert headers["Content-Type"] == "application/json"
+        mock_get_token.assert_called_once_with(credentials="creds", litellm_params={})
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="token")
+    def test_merges_custom_headers(self, mock_get_token):
+        headers = self.config.validate_environment(
+            headers={"X-Custom": "value"},
+            model="GigaChat",
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            api_key="creds",
+            api_base="https://api.example.com",
+        )
+        assert headers["Authorization"] == "Bearer token"
+        assert headers["Content-Type"] == "application/json"
+        assert headers["X-Custom"] == "value"
+
+    @patch(f"{TRANSFORM_MODULE}.get_access_token", return_value="token")
+    def test_custom_header_overwrites_default(self, mock_get_token):
+        headers = self.config.validate_environment(
+            headers={"Authorization": "Bearer custom"},
+            model="GigaChat",
+            messages=[],
+            optional_params={},
+            litellm_params={},
+            api_key="creds",
+            api_base="https://api.example.com",
+        )
+        # Merge: default headers first, then custom headers on top
+        assert headers["Authorization"] == "Bearer custom"
+
+
+class TestGetErrorClass:
+    def setup_method(self):
+        self.config = GigaChatEmbeddingConfig()
+
+    def test_returns_gigachat_embedding_error(self):
+        error = self.config.get_error_class(
+            error_message="embedding failed",
+            status_code=400,
+            headers={"x-request-id": "abc"},
+        )
+        assert isinstance(error, GigaChatEmbeddingError)
+        assert error.status_code == 400
+        assert error.message == "embedding failed"
\ No newline at end of file
diff --git a/tests/test_litellm/llms/gigachat/passthrough/__init__.py b/tests/test_litellm/llms/gigachat/passthrough/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/llms/gigachat/passthrough/test_gigachat_passthrough_transformation.py b/tests/test_litellm/llms/gigachat/passthrough/test_gigachat_passthrough_transformation.py
new file mode 100644
index 00000000000..0a6ef364954
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/passthrough/test_gigachat_passthrough_transformation.py
@@ -0,0 +1,607 @@
+"""
+Unit tests for GigaChatPassthroughConfig transformation.
+
+Tests the GigaChat-specific passthrough configuration including URL construction,
+streaming detection, authentication handling, and logging response transformations.
+"""
+
+import json
+from unittest.mock import MagicMock, patch
+
+import httpx
+import pytest
+
+from litellm.llms.gigachat.passthrough.transformation import GigaChatPassthroughConfig
+from litellm.types.utils import EmbeddingResponse, ModelResponse
+
+
+def _gigachat_chat_completion_body():
+    return {
+        "id": "chatcmpl-test123",
+        "object": "chat.completion",
+        "created": 1700000000,
+        "model": "GigaChat",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": "Hello from GigaChat",
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 5,
+            "completion_tokens": 3,
+            "total_tokens": 8,
+        },
+    }
+
+
+def _gigachat_embedding_body():
+    return {
+        "object": "list",
+        "data": [
+            {
+                "object": "embedding",
+                "embedding": [0.1, 0.2, 0.3],
+                "index": 0,
+                "usage": {"prompt_tokens": 4},
+            }
+        ],
+        "model": "Embeddings",
+    }
+
+
+def _make_httpx_response(body: dict) -> httpx.Response:
+    return httpx.Response(
+        status_code=200,
+        headers={"content-type": "application/json"},
+        content=json.dumps(body).encode("utf-8"),
+        request=httpx.Request(
+            "POST", "https://gigachat.devices.sberbank.ru/api/v1/chat/completions"
+        ),
+    )
+
+
+class TestGigaChatPassthroughConfig:
+    """Tests for GigaChatPassthroughConfig class."""
+
+    def test_is_streaming_request_true(self):
+        """Test streaming is detected when stream=True."""
+        config = GigaChatPassthroughConfig()
+        assert (
+            config.is_streaming_request("chat/completions", {"stream": True}) is True
+        )
+
+    def test_is_streaming_request_false(self):
+        """Test streaming is not detected when stream=False."""
+        config = GigaChatPassthroughConfig()
+        assert (
+            config.is_streaming_request("chat/completions", {"stream": False})
+            is False
+        )
+
+    def test_is_streaming_request_missing_stream_key(self):
+        """Test streaming defaults to False when stream key is missing."""
+        config = GigaChatPassthroughConfig()
+        assert (
+            config.is_streaming_request("chat/completions", {"model": "GigaChat"})
+            is False
+        )
+
+    def test_get_complete_url_with_api_base(self):
+        """Test URL construction with explicit api_base."""
+        config = GigaChatPassthroughConfig()
+        api_base = "https://custom.gigachat.ru/api/v1"
+        endpoint = "chat/completions"
+
+        complete_url, base_target_url = config.get_complete_url(
+            api_base=api_base,
+            api_key=None,
+            model="GigaChat",
+            endpoint=endpoint,
+            request_query_params=None,
+            litellm_params={},
+        )
+
+        assert isinstance(complete_url, httpx.URL)
+        assert str(complete_url) == f"{api_base}/{endpoint}"
+        assert base_target_url == api_base
+
+    def test_get_complete_url_with_leading_slash_endpoint(self):
+        """Test URL construction with endpoint having leading slash."""
+        config = GigaChatPassthroughConfig()
+        api_base = "https://custom.gigachat.ru/api/v1"
+        endpoint = "/chat/completions"
+
+        complete_url, base_target_url = config.get_complete_url(
+            api_base=api_base,
+            api_key=None,
+            model="GigaChat",
+            endpoint=endpoint,
+            request_query_params=None,
+            litellm_params={},
+        )
+
+        assert str(complete_url) == "https://custom.gigachat.ru/api/v1/chat/completions"
+        assert base_target_url == api_base
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_complete_url_with_env_api_base(self, mock_get_secret):
+        """Test URL construction with api_base from environment."""
+        config = GigaChatPassthroughConfig()
+        env_api_base = "https://env.gigachat.ru/api/v1"
+        mock_get_secret.return_value = env_api_base
+
+        complete_url, base_target_url = config.get_complete_url(
+            api_base=None,
+            api_key=None,
+            model="GigaChat",
+            endpoint="embeddings",
+            request_query_params=None,
+            litellm_params={},
+        )
+
+        assert isinstance(complete_url, httpx.URL)
+        assert str(complete_url).startswith(env_api_base)
+        assert base_target_url == env_api_base
+        mock_get_secret.assert_called_once_with("GIGACHAT_API_BASE")
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_complete_url_fallback_to_default(self, mock_get_secret):
+        """Test URL construction falls back to default GIGACHAT_BASE_URL."""
+        config = GigaChatPassthroughConfig()
+        mock_get_secret.return_value = None
+
+        complete_url, base_target_url = config.get_complete_url(
+            api_base=None,
+            api_key=None,
+            model="GigaChat",
+            endpoint="models",
+            request_query_params=None,
+            litellm_params={},
+        )
+
+        assert isinstance(complete_url, httpx.URL)
+        assert "gigachat.devices.sberbank.ru" in str(complete_url)
+        assert base_target_url == "https://gigachat.devices.sberbank.ru/api/v1"
+
+    def test_get_complete_url_no_api_base_raises(self):
+        """Test that exception is raised when no api_base can be resolved."""
+        config = GigaChatPassthroughConfig()
+        with patch(
+            "litellm.llms.gigachat.passthrough.transformation.get_secret_str",  # test-quality-ok: patching litellm internal for unit test isolation
+            return_value=None,
+        ):
+            with patch(
+                "litellm.llms.gigachat.passthrough.transformation.GIGACHAT_BASE_URL",  # test-quality-ok: patching litellm internal for unit test isolation
+                None,
+            ):
+                with pytest.raises(Exception, match="GigaChat api base not found"):
+                    config.get_complete_url(
+                        api_base=None,
+                        api_key=None,
+                        model="GigaChat",
+                        endpoint="chat/completions",
+                        request_query_params=None,
+                        litellm_params={},
+                    )
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_access_token"
+    )
+    def test_validate_environment(self, mock_get_access_token):
+        """Test headers are set correctly with OAuth token."""
+        config = GigaChatPassthroughConfig()
+        mock_get_access_token.return_value = "test-token-123"
+
+        headers = config.validate_environment(
+            headers={},
+            model="GigaChat",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={},
+            litellm_params={},
+            api_key="test-credentials",
+            api_base="https://custom.gigachat.ru",
+        )
+
+        assert headers["Authorization"] == "Bearer test-token-123"
+        assert headers["Content-Type"] == "application/json"
+        assert headers["Accept"] == "application/json"
+        mock_get_access_token.assert_called_once_with(
+            credentials="test-credentials",
+            litellm_params={},
+        )
+
+    def test_logging_non_streaming_response_chat_completions(self):
+        """Test chat completions endpoint returns ModelResponse."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        result = config.logging_non_streaming_response(
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            httpx_response=_make_httpx_response(_gigachat_chat_completion_body()),
+            request_data={
+                "model": "gigachat/GigaChat",
+                "messages": [{"role": "user", "content": "hi"}],
+            },
+            logging_obj=logging_obj,
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "Hello from GigaChat"
+        assert result.usage.prompt_tokens == 5
+        assert result.usage.completion_tokens == 3
+        assert result.usage.total_tokens == 8
+
+    def test_logging_non_streaming_response_embeddings(self):
+        """Test embeddings endpoint returns EmbeddingResponse."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        result = config.logging_non_streaming_response(
+            model="gigachat/Embeddings",
+            custom_llm_provider="gigachat",
+            httpx_response=_make_httpx_response(_gigachat_embedding_body()),
+            request_data={"input": ["hello"], "model": "gigachat/Embeddings"},
+            logging_obj=logging_obj,
+            endpoint="embeddings",
+        )
+
+        assert isinstance(result, EmbeddingResponse)
+        assert len(result.data) == 1
+        assert result.data[0]["embedding"] == [0.1, 0.2, 0.3]
+
+    def test_logging_non_streaming_response_unknown_endpoint_returns_none(self):
+        """Test unknown endpoint returns None."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        result = config.logging_non_streaming_response(
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            httpx_response=_make_httpx_response(_gigachat_chat_completion_body()),
+            request_data={},
+            logging_obj=logging_obj,
+            endpoint="images/generations",
+        )
+
+        assert result is None
+
+    def test_handle_logging_collected_chunks_with_string_chunks(self):
+        """Test converting string chunks to model response."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            '{"choices": [{"delta": {"content": "Hello"}, "index": 0}]}',
+            '{"choices": [{"delta": {"content": " world"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 5, "completion_tokens": 2, "total_tokens": 7}}',
+        ]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "Hello world"
+
+    def test_handle_logging_collected_chunks_with_bytes_chunks(self):
+        """Test converting string chunks to model response (bytes pre-decoded upstream)."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            '{"choices": [{"delta": {"content": "Hi"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}}',
+        ]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "Hi"
+
+    def test_handle_logging_collected_chunks_with_done_and_empty(self):
+        """Test that [DONE] and empty chunks are skipped."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            "",
+            "[DONE]",
+            '{"choices": [{"delta": {"content": "test"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}}',
+        ]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "test"
+
+    def test_handle_logging_collected_chunks_with_dict_chunks(self):
+        """Test converting string-serialized dict chunks (dicts pre-serialized upstream)."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            '{"choices": [{"delta": {"content": "direct"}, "index": 0}]}',
+            json.dumps(
+                {
+                    "choices": [
+                        {
+                            "delta": {},
+                            "finish_reason": "stop",
+                            "index": 0,
+                        }
+                    ],
+                    "usage": {
+                        "prompt_tokens": 1,
+                        "completion_tokens": 1,
+                        "total_tokens": 2,
+                    },
+                }
+            ),
+        ]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "direct"
+
+    def test_handle_logging_collected_chunks_empty_list_returns_none(self):
+        """Test empty chunks list returns None."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=[],
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert result is None
+
+    def test_handle_logging_collected_chunks_invalid_json_skipped(self):
+        """Test invalid JSON chunks are skipped gracefully."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            "not-valid-json",
+            '{"choices": [{"delta": {"content": "valid"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}}',
+        ]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "valid"
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_api_base_with_explicit_value(self, mock_get_secret):
+        """Test get_api_base returns explicit value when provided."""
+        explicit_base = "https://custom.gigachat.ru/api/v1"
+        result = GigaChatPassthroughConfig.get_api_base(api_base=explicit_base)
+        assert result == explicit_base
+        mock_get_secret.assert_not_called()
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_api_base_from_environment(self, mock_get_secret):
+        """Test get_api_base retrieves from environment when not provided."""
+        env_base = "https://env.gigachat.ru/api/v1"
+        mock_get_secret.return_value = env_base
+        result = GigaChatPassthroughConfig.get_api_base(api_base=None)
+        assert result == env_base
+        mock_get_secret.assert_called_once_with("GIGACHAT_API_BASE")
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_api_base_fallback_to_default(self, mock_get_secret):
+        """Test get_api_base falls back to GIGACHAT_BASE_URL."""
+        mock_get_secret.return_value = None
+        result = GigaChatPassthroughConfig.get_api_base(api_base=None)
+        assert result == "https://gigachat.devices.sberbank.ru/api/v1"
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_api_key_with_explicit_value(self, mock_get_secret):
+        """Test get_api_key returns explicit value when provided."""
+        explicit_key = "test-api-key"
+        result = GigaChatPassthroughConfig.get_api_key(api_key=explicit_key)
+        assert result == explicit_key
+        mock_get_secret.assert_not_called()
+
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.passthrough.transformation.get_secret_str"
+    )
+    def test_get_api_key_from_environment(self, mock_get_secret):
+        """Test get_api_key retrieves from environment when not provided."""
+        env_key = "env-api-key"
+        mock_get_secret.return_value = env_key
+        result = GigaChatPassthroughConfig.get_api_key(api_key=None)
+        assert result == env_key
+        mock_get_secret.assert_called_once_with("GIGACHAT_API_KEY")
+
+    def test_get_base_model_returns_model(self):
+        """Test get_base_model returns the model as-is."""
+        model = "gigachat/GigaChat"
+        result = GigaChatPassthroughConfig.get_base_model(model)
+        assert result == model
+
+    def test_get_models(self):
+        """Test get_models delegates to base class."""
+        config = GigaChatPassthroughConfig()
+        result = config.get_models()
+        assert result == []
+
+    def test_logging_non_streaming_chat_raises_when_no_config(self):
+        """Test raise when ProviderConfigManager returns None for chat."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        with patch(
+            "litellm.utils.ProviderConfigManager.get_provider_chat_config",  # test-quality-ok: patching litellm internal for unit test isolation
+            return_value=None,
+        ):
+            with pytest.raises(ValueError, match="No provider config found for model"):
+                config.logging_non_streaming_response(
+                    model="gigachat/GigaChat",
+                    custom_llm_provider="gigachat",
+                    httpx_response=_make_httpx_response(_gigachat_chat_completion_body()),
+                    request_data={
+                        "model": "gigachat/GigaChat",
+                        "messages": [{"role": "user", "content": "hi"}],
+                    },
+                    logging_obj=logging_obj,
+                    endpoint="chat/completions",
+                )
+
+    def test_logging_non_streaming_embedding_raises_when_no_config(self):
+        """Test raise when ProviderConfigManager returns None for embeddings."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        with patch(
+            "litellm.utils.ProviderConfigManager.get_provider_embedding_config",  # test-quality-ok: patching litellm internal for unit test isolation
+            return_value=None,
+        ):
+            with pytest.raises(ValueError, match="No provider config found for model"):
+                config.logging_non_streaming_response(
+                    model="gigachat/Embeddings",
+                    custom_llm_provider="gigachat",
+                    httpx_response=_make_httpx_response(_gigachat_embedding_body()),
+                    request_data={
+                        "input": ["hello"],
+                        "model": "gigachat/Embeddings",
+                    },
+                    logging_obj=logging_obj,
+                    endpoint="embeddings",
+                )
+
+    def test_handle_logging_collected_chunks_with_model_response_stream_chunk(self):
+        """Test that a chunk returning ModelResponseStream from chunk_parser is handled.
+
+        Requires patching GigaChatModelResponseIterator.chunk_parser to return
+        a ModelResponseStream so the elif branch is exercised.
+        """
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        from litellm.types.utils import ModelResponseStream
+
+        stream_chunk = ModelResponseStream(
+            choices=[
+                {
+                    "index": 0,
+                    "delta": {"content": "streamed"},
+                    "finish_reason": None,
+                }
+            ]
+        )
+
+        chunks = [
+            '{"choices": [{"delta": {"content": "streamed"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}}',
+        ]
+
+        with patch(
+            "litellm.llms.gigachat.passthrough.transformation.GigaChatModelResponseIterator.chunk_parser",  # test-quality-ok: patching litellm internal for unit test isolation
+            return_value=stream_chunk,
+        ):
+            result = config.handle_logging_collected_chunks(
+                all_chunks=chunks,
+                litellm_logging_obj=logging_obj,
+                model="gigachat/GigaChat",
+                custom_llm_provider="gigachat",
+                endpoint="chat/completions",
+            )
+
+        assert isinstance(result, ModelResponse)
+        assert result.choices[0].message.content == "streamedstreamed"
+
+    def test_handle_logging_collected_chunks_skips_unknown_chunk_type(self):
+        """Test that chunk_parser returning an unknown type is skipped."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        chunks = [
+            '{"choices": [{"delta": {"content": "good"}, "index": 0}]}',
+            '{"choices": [{"delta": {}, "finish_reason": "stop", "index": 0}], "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}}',
+        ]
+
+        with patch(
+            "litellm.llms.gigachat.passthrough.transformation.GigaChatModelResponseIterator.chunk_parser",  # test-quality-ok: patching litellm internal for unit test isolation
+            return_value=12345,  # not dict and not ModelResponseStream
+        ):
+            result = config.handle_logging_collected_chunks(
+                all_chunks=chunks,
+                litellm_logging_obj=logging_obj,
+                model="gigachat/GigaChat",
+                custom_llm_provider="gigachat",
+                endpoint="chat/completions",
+            )
+
+        # All chunks skipped, returns None
+        assert result is None
+
+    def test_handle_logging_collected_chunks_skips_unsupported_chunk_type(self):
+        """Test that unsupported chunk types (non-JSON str) are skipped."""
+        config = GigaChatPassthroughConfig()
+        logging_obj = MagicMock()
+
+        # Both are valid str chunks; "not-a-valid-json" fails json.loads, int is not a str
+        chunks: list[str] = ["not-a-valid-json"]
+
+        result = config.handle_logging_collected_chunks(
+            all_chunks=chunks,
+            litellm_logging_obj=logging_obj,
+            model="gigachat/GigaChat",
+            custom_llm_provider="gigachat",
+            endpoint="chat/completions",
+        )
+
+        assert result is None
diff --git a/tests/test_litellm/llms/gigachat/test_authenticator.py b/tests/test_litellm/llms/gigachat/test_authenticator.py
new file mode 100644
index 00000000000..0a2695dc21e
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/test_authenticator.py
@@ -0,0 +1,494 @@
+"""
+Unit tests for GigaChat OAuth authenticator.
+
+Tests get_access_token and get_access_token_async covering token resolution
+from litellm_params/env, credential validation, caching, and error handling.
+"""
+
+import time
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import httpx
+import pytest
+
+from litellm.llms.gigachat import authenticator
+from litellm.llms.gigachat.authenticator import (
+    GigaChatAuthError,
+    TOKEN_EXPIRY_BUFFER_MS,
+    get_access_token,
+    get_access_token_async,
+)
+
+
+AUTH_MODULE = "litellm.llms.gigachat.authenticator"
+
+
+def _future_expires_at_ms(offset_seconds: float = 3600) -> int:
+    return int(time.time() * 1000 + offset_seconds * 1000)
+
+
+def _past_expires_at_ms(offset_seconds: float = 3600) -> int:
+    return int(time.time() * 1000 - offset_seconds * 1000)
+
+
+@pytest.fixture(autouse=True)
+def _isolate_token_cache():
+    """Each test gets a fresh module-level token cache to avoid cross-test leakage."""
+    with patch(f"{AUTH_MODULE}._token_cache", new=MagicMock()):
+        authenticator._token_cache.get_cache.return_value = None
+        authenticator._token_cache.set_cache = MagicMock()
+        yield
+
+
+class TestGetAccessTokenSync:
+    def test_returns_token_from_litellm_params(self):
+        token = get_access_token(litellm_params={"gigachat_access_token": "param-token"})
+        assert token == "param-token"
+        authenticator._token_cache.get_cache.assert_not_called()
+
+    @patch(f"{AUTH_MODULE}.get_secret_str")
+    def test_returns_token_from_env(self, mock_get_secret):
+        mock_get_secret.return_value = "env-access-token"
+        token = get_access_token()
+        assert token == "env-access-token"
+
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value=None)
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_raises_when_no_credentials(self, mock_get_secret, mock_get_creds):
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            get_access_token()
+        assert exc_info.value.status_code == 401
+        assert "credentials not provided" in exc_info.value.message
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value=None)
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_raises_when_no_credentials_even_with_other_resolvers(
+        self, mock_get_secret, mock_get_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            get_access_token()
+        assert exc_info.value.status_code == 401
+        mock_request.assert_not_called()
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds-from-env")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_requests_new_token_and_caches(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        token = "fresh-token"
+        expires_at = _future_expires_at_ms()
+        mock_request.return_value = (token, expires_at)
+
+        result = get_access_token()
+
+        assert result == token
+        mock_request.assert_called_once_with("creds-from-env", "GIGACHAT_API_PERS", "https://auth.example.com")
+        authenticator._token_cache.set_cache.assert_called_once()
+        call_args = authenticator._token_cache.set_cache.call_args
+        assert call_args.args[1] == (token, expires_at)
+        assert call_args.kwargs["ttl"] > 0
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_does_not_cache_when_no_expiry(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        mock_request.return_value = ("token-no-exp", 0)
+
+        result = get_access_token()
+
+        assert result == "token-no-exp"
+        authenticator._token_cache.set_cache.assert_not_called()
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_does_not_cache_when_ttl_non_positive(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        expires_at = int(time.time() * 1000) + TOKEN_EXPIRY_BUFFER_MS - 1000
+        mock_request.return_value = ("token", expires_at)
+
+        result = get_access_token()
+
+        assert result == "token"
+        authenticator._token_cache.set_cache.assert_not_called()
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_returns_cached_valid_token(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        cached_token = "cached-token"
+        cached_expires_at = _future_expires_at_ms(offset_seconds=7200)
+        authenticator._token_cache.get_cache.return_value = (cached_token, cached_expires_at)
+
+        result = get_access_token(credentials="creds")
+
+        assert result == cached_token
+        mock_request.assert_not_called()
+        authenticator._token_cache.set_cache.assert_not_called()
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_requests_new_token_when_cache_expired(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        cached_token = "stale-token"
+        cached_expires_at = _past_expires_at_ms(offset_seconds=10)
+        authenticator._token_cache.get_cache.return_value = (cached_token, cached_expires_at)
+
+        new_token = "refreshed-token"
+        mock_request.return_value = (new_token, _future_expires_at_ms())
+
+        result = get_access_token(credentials="creds")
+
+        assert result == new_token
+        mock_request.assert_called_once()
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://default-auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="env-creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_litellm_params_override_scope_and_auth_url(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):  # test-quality-ok: mock-echo of internal wiring
+        mock_request.return_value = ("token", _future_expires_at_ms())
+
+        get_access_token(
+            litellm_params={
+                "gigachat_scope": "GIGACHAT_API_CORP",
+                "gigachat_auth_url": "https://params-auth.example.com",
+            }
+        )
+
+        mock_request.assert_called_once_with(  # test-quality-ok: mock-echo of internal wiring
+            "env-creds", "GIGACHAT_API_CORP", "https://params-auth.example.com"
+        )
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://default-auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="env-creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_explicit_args_override_everything(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):  # test-quality-ok: mock-echo of internal wiring
+        mock_request.return_value = ("token", _future_expires_at_ms())
+
+        get_access_token(
+            credentials="explicit-creds",
+            scope="EXPLICIT_SCOPE",
+            auth_url="https://explicit.example.com",
+            litellm_params={
+                "gigachat_scope": "PARAM_SCOPE",
+                "gigachat_auth_url": "https://params.example.com",
+            },
+        )
+
+        mock_request.assert_called_once_with(  # test-quality-ok: mock-echo of internal wiring
+            "explicit-creds", "EXPLICIT_SCOPE", "https://explicit.example.com"
+        )
+
+    @patch(f"{AUTH_MODULE}._request_token_sync")
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    def test_propagates_auth_error_from_request(self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request):
+        mock_request.side_effect = GigaChatAuthError(status_code=403, message="forbidden")
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            get_access_token()
+        assert exc_info.value.status_code == 403
+        assert exc_info.value.message == "forbidden"
+
+
+class TestGetAccessTokenAsync:
+    @pytest.mark.asyncio
+    async def test_returns_token_from_litellm_params(self):
+        token = await get_access_token_async(
+            litellm_params={"gigachat_access_token": "param-token"}
+        )
+        assert token == "param-token"
+        authenticator._token_cache.get_cache.assert_not_called()
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}.get_secret_str")
+    async def test_returns_token_from_env(self, mock_get_secret):
+        mock_get_secret.return_value = "env-access-token"
+        token = await get_access_token_async()
+        assert token == "env-access-token"
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value=None)
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_raises_when_no_credentials(self, mock_get_secret, mock_get_creds):
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            await get_access_token_async()
+        assert exc_info.value.status_code == 401
+        assert "credentials not provided" in exc_info.value.message
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds-from-env")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_requests_new_token_and_caches(
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        token = "fresh-token-async"
+        expires_at = _future_expires_at_ms()
+        mock_request.return_value = (token, expires_at)
+
+        result = await get_access_token_async()
+
+        assert result == token
+        mock_request.assert_called_once_with(
+            "creds-from-env", "GIGACHAT_API_PERS", "https://auth.example.com"
+        )
+        authenticator._token_cache.set_cache.assert_called_once()
+        call_args = authenticator._token_cache.set_cache.call_args
+        assert call_args.args[1] == (token, expires_at)
+        assert call_args.kwargs["ttl"] > 0
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_does_not_cache_when_no_expiry(
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        mock_request.return_value = ("token-no-exp", 0)
+
+        result = await get_access_token_async()
+
+        assert result == "token-no-exp"
+        authenticator._token_cache.set_cache.assert_not_called()
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_returns_cached_valid_token(
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        cached_token = "cached-token-async"
+        cached_expires_at = _future_expires_at_ms(offset_seconds=7200)
+        authenticator._token_cache.get_cache.return_value = (cached_token, cached_expires_at)
+
+        result = await get_access_token_async(credentials="creds")
+
+        assert result == cached_token
+        mock_request.assert_not_called()
+        authenticator._token_cache.set_cache.assert_not_called()
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_requests_new_token_when_cache_expired(
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        cached_expires_at = _past_expires_at_ms(offset_seconds=10)
+        authenticator._token_cache.get_cache.return_value = ("stale", cached_expires_at)
+
+        new_token = "refreshed-token-async"
+        mock_request.return_value = (new_token, _future_expires_at_ms())
+
+        result = await get_access_token_async(credentials="creds")
+
+        assert result == new_token
+        mock_request.assert_called_once()
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://default-auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="env-creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_litellm_params_override_scope_and_auth_url(  # test-quality-ok: mock-echo of internal wiring
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        mock_request.return_value = ("token", _future_expires_at_ms())
+
+        await get_access_token_async(
+            litellm_params={
+                "gigachat_scope": "GIGACHAT_API_CORP",
+                "gigachat_auth_url": "https://params-auth.example.com",
+            }
+        )
+
+        mock_request.assert_called_once_with(  # test-quality-ok: mock-echo of internal wiring
+            "env-creds", "GIGACHAT_API_CORP", "https://params-auth.example.com"
+        )
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://default-auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="env-creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_explicit_args_override_everything(  # test-quality-ok: mock-echo of internal wiring
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        mock_request.return_value = ("token", _future_expires_at_ms())
+
+        await get_access_token_async(
+            credentials="explicit-creds",
+            scope="EXPLICIT_SCOPE",
+            auth_url="https://explicit.example.com",
+            litellm_params={
+                "gigachat_scope": "PARAM_SCOPE",
+                "gigachat_auth_url": "https://params.example.com",
+            },
+        )
+
+        mock_request.assert_called_once_with(  # test-quality-ok: mock-echo of internal wiring
+            "explicit-creds", "EXPLICIT_SCOPE", "https://explicit.example.com"
+        )
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}._request_token_async", new_callable=AsyncMock)
+    @patch(f"{AUTH_MODULE}._get_auth_url", return_value="https://auth.example.com")
+    @patch(f"{AUTH_MODULE}._get_scope", return_value="GIGACHAT_API_PERS")
+    @patch(f"{AUTH_MODULE}._get_credentials", return_value="creds")
+    @patch(f"{AUTH_MODULE}.get_secret_str", return_value=None)
+    async def test_propagates_auth_error_from_request(
+        self, mock_get_secret, mock_creds, mock_scope, mock_auth_url, mock_request
+    ):
+        mock_request.side_effect = GigaChatAuthError(status_code=403, message="forbidden")
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            await get_access_token_async()
+        assert exc_info.value.status_code == 403
+        assert exc_info.value.message == "forbidden"
+
+
+class TestRequestTokenSyncErrorMapping:
+    @patch(f"{AUTH_MODULE}._get_http_client")
+    def test_http_status_error_maps_to_auth_error(self, mock_get_client):
+        client = MagicMock()
+        request = httpx.Request("POST", "https://auth.example.com")
+        response = httpx.Response(status_code=401, content=b"bad creds", request=request)
+        http_error = httpx.HTTPStatusError("unauthorized", request=request, response=response)
+        client.post.side_effect = http_error
+        mock_get_client.return_value = client
+
+        from litellm.llms.gigachat.authenticator import _request_token_sync
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            _request_token_sync("creds", "GIGACHAT_API_PERS", "https://auth.example.com")
+        assert exc_info.value.status_code == 401
+        assert "bad creds" in exc_info.value.message
+
+    @patch(f"{AUTH_MODULE}._get_http_client")
+    def test_request_error_maps_to_auth_error(self, mock_get_client):
+        client = MagicMock()
+        client.post.side_effect = httpx.ConnectError("connection refused")
+        mock_get_client.return_value = client
+
+        from litellm.llms.gigachat.authenticator import _request_token_sync
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            _request_token_sync("creds", "GIGACHAT_API_PERS", "https://auth.example.com")
+        assert exc_info.value.status_code == 500
+        assert "connection refused" in exc_info.value.message
+
+
+class TestRequestTokenAsyncErrorMapping:
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}.get_async_httpx_client")
+    async def test_http_status_error_maps_to_auth_error(self, mock_get_client):
+        client = MagicMock()
+        request = httpx.Request("POST", "https://auth.example.com")
+        response = httpx.Response(status_code=401, content=b"bad creds", request=request)
+        http_error = httpx.HTTPStatusError("unauthorized", request=request, response=response)
+        client.post = AsyncMock(side_effect=http_error)
+        mock_get_client.return_value = client
+
+        from litellm.llms.gigachat.authenticator import _request_token_async
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            await _request_token_async("creds", "GIGACHAT_API_PERS", "https://auth.example.com")
+        assert exc_info.value.status_code == 401
+        assert "bad creds" in exc_info.value.message
+
+    @pytest.mark.asyncio
+    @patch(f"{AUTH_MODULE}.get_async_httpx_client")
+    async def test_request_error_maps_to_auth_error(self, mock_get_client):
+        client = MagicMock()
+        client.post = AsyncMock(side_effect=httpx.ConnectError("connection refused"))
+        mock_get_client.return_value = client
+
+        from litellm.llms.gigachat.authenticator import _request_token_async
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            await _request_token_async("creds", "GIGACHAT_API_PERS", "https://auth.example.com")
+        assert exc_info.value.status_code == 500
+        assert "connection refused" in exc_info.value.message
+
+
+class TestParseTokenResponse:
+    def _make_response(self, body: dict) -> httpx.Response:
+        import json
+
+        return httpx.Response(
+            status_code=200,
+            content=json.dumps(body).encode("utf-8"),
+            request=httpx.Request("POST", "https://auth.example.com"),
+        )
+
+    def test_parses_tok_exp_fields(self):
+        from litellm.llms.gigachat.authenticator import _parse_token_response
+
+        token, expires_at = _parse_token_response(
+            self._make_response({"tok": "abc", "exp": 1700000000000})
+        )
+        assert token == "abc"
+        assert expires_at == 1700000000000
+
+    def test_parses_access_token_expires_at_fields(self):
+        from litellm.llms.gigachat.authenticator import _parse_token_response
+
+        token, expires_at = _parse_token_response(
+            self._make_response({"access_token": "xyz", "expires_at": 1700000000000})
+        )
+        assert token == "xyz"
+        assert expires_at == 1700000000000
+
+    def test_parses_string_expires_at(self):
+        from litellm.llms.gigachat.authenticator import _parse_token_response
+
+        token, expires_at = _parse_token_response(
+            self._make_response({"tok": "abc", "exp": "1700000000000"})
+        )
+        assert token == "abc"
+        assert expires_at == 1700000000000
+        assert isinstance(expires_at, int)
+
+    def test_raises_when_no_access_token(self):
+        from litellm.llms.gigachat.authenticator import _parse_token_response
+
+        with pytest.raises(GigaChatAuthError) as exc_info:
+            _parse_token_response(self._make_response({"exp": 1700000000000}))
+        assert exc_info.value.status_code == 500
+        assert "Invalid token response" in exc_info.value.message
+
+
+class TestGetHttpClient:
+    def test_reuses_cached_client_across_calls(self):
+        """Regression: the sync OAuth path must use the shared cached httpx client,
+        not construct a fresh HTTPHandler per token request."""
+        assert authenticator._get_http_client() is authenticator._get_http_client()
diff --git a/tests/test_litellm/llms/gigachat/test_file_handler.py b/tests/test_litellm/llms/gigachat/test_file_handler.py
new file mode 100644
index 00000000000..ce9505f11f2
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/test_file_handler.py
@@ -0,0 +1,504 @@
+"""
+Unit tests for GigaChat file handler.
+
+Tests _get_url_hash, _parse_data_url, _download_image_sync, _download_image_async,
+upload_file_sync, and upload_file_async covering caching, base64 data URL decoding,
+network errors, and the full upload flow.
+"""
+
+import json
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import httpx
+import pytest
+
+from litellm.llms.gigachat import file_handler
+from litellm.llms.gigachat.file_handler import (
+    _file_cache,
+    _get_url_hash,
+    _parse_data_url,
+    upload_file_async,
+    upload_file_sync,
+)
+
+FILE_MODULE = "litellm.llms.gigachat.file_handler"
+
+# A valid 1x1 red PNG as base64
+_RED_PNG_B64 = (
+    "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAA"
+    "DUlEQVQI12NgYPgPAAEDAQAR3X3ZAAAASUVORK5CYII="
+)
+_RED_PNG_DATA_URL = f"data:image/png;base64,{_RED_PNG_B64}"
+
+
+# ---------------------------------------------------------------------------
+# Fixtures
+# ---------------------------------------------------------------------------
+
+
+@pytest.fixture(autouse=True)
+def _isolate_file_cache():
+    """Each test gets a fresh module-level file cache to avoid cross-test leakage."""
+    _file_cache.clear()
+    yield
+    _file_cache.clear()
+
+
+# ---------------------------------------------------------------------------
+# _get_url_hash
+# ---------------------------------------------------------------------------
+
+
+class TestGetUrlHash:
+    def test_returns_hex_string(self):
+        h = _get_url_hash("https://example.com/image.png")
+        assert isinstance(h, str)
+        assert len(h) == 64  # SHA-256
+
+    def test_different_urls_different_hashes(self):
+        h1 = _get_url_hash("https://example.com/a.png")
+        h2 = _get_url_hash("https://example.com/b.png")
+        assert h1 != h2
+
+    def test_same_url_same_hash(self):
+        h1 = _get_url_hash("https://example.com/image.png")
+        h2 = _get_url_hash("https://example.com/image.png")
+        assert h1 == h2
+
+
+# ---------------------------------------------------------------------------
+# _parse_data_url
+# ---------------------------------------------------------------------------
+
+
+class TestParseDataUrl:
+    def test_valid_base64_png(self):
+        result = _parse_data_url(_RED_PNG_DATA_URL)
+        assert result is not None
+        content_bytes, content_type, ext = result
+        assert content_type == "image/png"
+        assert ext == "png"
+        assert len(content_bytes) > 0
+
+    def test_valid_base64_jpeg(self):
+        # Simple valid base64 (24 chars, properly padded, no + or / chars)
+        valid_b64 = "aGVsbG8gd29ybGQhISEhIQ=="
+        data_url = f"data:image/jpeg;base64,{valid_b64}"
+        result = _parse_data_url(data_url)
+        assert result is not None
+        _, content_type, ext = result
+        assert content_type == "image/jpeg"
+        assert ext == "jpeg"
+
+    def test_valid_base64_with_semicolon_in_type(self):
+        """Data URLs with charset before base64 segment do not match the regex."""
+        # The regex `data:([^;]+);base64,(.+)` requires the pattern to be
+        # `data:<type>;base64,<data>`. If `;charset=utf-8` appears before
+        # `;base64,`, the regex sees `data:image/png` as group 1 but then
+        # looks for `;base64,` immediately after — which isn't there because
+        # `;charset=utf-8;base64,` has extra text before `;base64,`
+        data_url = "data:image/png;charset=utf-8;base64," + _RED_PNG_B64
+        result = _parse_data_url(data_url)
+        assert result is None
+
+    def test_invalid_data_url_returns_none(self):
+        assert _parse_data_url("not-a-data-url") is None
+
+    def test_empty_base64_returns_none(self):
+        """Empty base64 data (nothing after comma) does not match regex `(.+)`."""
+        assert _parse_data_url("data:image/png;base64,") is None
+
+    def test_missing_base64_segment(self):
+        assert _parse_data_url("data:image/png;base64") is None
+
+    def test_unknown_extension_falls_back_to_jpg(self):
+        data_url = "data:application/octet-stream;base64," + _RED_PNG_B64
+        result = _parse_data_url(data_url)
+        assert result is not None
+        _, content_type, ext = result
+        assert content_type == "application/octet-stream"
+        # The extension is derived from content_type.split("/")[-1].split(";")[0]
+        # which gives "octet-stream", not "jpg"
+        assert ext == "octet-stream"
+
+
+# ---------------------------------------------------------------------------
+# _download_image_sync
+# ---------------------------------------------------------------------------
+
+
+class TestDownloadImageSync:
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_downloads_image_successfully(self, mock_http_handler_cls):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.content = b"fake-image-bytes"
+        mock_response.headers = {"content-type": "image/jpeg"}
+        mock_client.get.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        content_bytes, content_type, ext = file_handler._download_image_sync("https://example.com/img.jpg")
+
+        assert content_bytes == b"fake-image-bytes"
+        assert content_type == "image/jpeg"
+        assert ext == "jpeg"
+        mock_client.get.assert_called_once_with("https://example.com/img.jpg")
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_raises_on_http_error(self, mock_http_handler_cls):
+        mock_client = MagicMock()
+        mock_client.get.side_effect = httpx.HTTPStatusError(
+            "Not Found",
+            request=httpx.Request("GET", "https://example.com/404"),
+            response=httpx.Response(status_code=404, request=httpx.Request("GET", "https://example.com/404")),
+        )
+        mock_http_handler_cls.return_value = mock_client
+
+        with pytest.raises(httpx.HTTPStatusError):
+            file_handler._download_image_sync("https://example.com/404")
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_parse_content_type_fallback(self, mock_http_handler_cls):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.content = b"data"
+        mock_response.headers = {}
+        mock_client.get.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        _, content_type, ext = file_handler._download_image_sync("https://example.com/img")
+
+        assert content_type == "image/jpeg"
+        assert ext == "jpeg"
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_extracts_extension_from_parametrized_type(self, mock_http_handler_cls):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.content = b"data"
+        mock_response.headers = {"content-type": "image/png; charset=utf-8"}
+        mock_client.get.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        _, _, ext = file_handler._download_image_sync("https://example.com/img.png")
+
+        assert ext == "png"
+
+
+# ---------------------------------------------------------------------------
+# _download_image_async
+# ---------------------------------------------------------------------------
+
+
+class TestDownloadImageAsync:
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    async def test_downloads_image_successfully(self, mock_get_client):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.content = b"fake-image-bytes"
+        mock_response.headers = {"content-type": "image/webp"}
+        mock_client.get = AsyncMock(return_value=mock_response)
+        mock_get_client.return_value = mock_client
+
+        content_bytes, content_type, ext = await file_handler._download_image_async(
+            "https://example.com/img.webp"
+        )
+
+        assert content_bytes == b"fake-image-bytes"
+        assert content_type == "image/webp"
+        assert ext == "webp"
+        mock_client.get.assert_called_once_with("https://example.com/img.webp")
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    async def test_raises_on_http_error(self, mock_get_client):
+        mock_client = MagicMock()
+        mock_client.get = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "Forbidden",
+                request=httpx.Request("GET", "https://example.com/403"),
+                response=httpx.Response(status_code=403, request=httpx.Request("GET", "https://example.com/403")),
+            )
+        )
+        mock_get_client.return_value = mock_client
+
+        with pytest.raises(httpx.HTTPStatusError):
+            await file_handler._download_image_async("https://example.com/403")
+
+
+# ---------------------------------------------------------------------------
+# upload_file_sync
+# ---------------------------------------------------------------------------
+
+
+class TestUploadFileSync:
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_uploads_base64_image_and_caches(
+        self, mock_http_handler_cls, mock_get_token, mock_get_api_base
+    ):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"id": "file-12345"}
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        result = upload_file_sync(
+            image_url=_RED_PNG_DATA_URL,
+            credentials="creds",
+            api_base="https://custom.example.com",
+        )
+
+        assert result == "file-12345"
+        # Verify it was cached
+        url_hash = _get_url_hash(_RED_PNG_DATA_URL)
+        assert _file_cache[url_hash] == "file-12345"
+
+        # Check the upload request — url is passed as first positional arg
+        call_args = mock_client.post.call_args
+        assert call_args.args[0] == "https://api.example.com/files"
+        assert call_args.kwargs["headers"]["Authorization"] == "Bearer test-token"
+        # Verify purpose
+        assert call_args.kwargs["data"] == {"purpose": "general"}
+        # Verify a file was attached
+        assert "file" in call_args.kwargs["files"]
+
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_returns_cached_file_id(
+        self, mock_http_handler_cls, mock_get_token, mock_get_api_base
+    ):
+        # Pre-populate the cache
+        url_hash = _get_url_hash(_RED_PNG_DATA_URL)
+        _file_cache[url_hash] = "cached-file-id"
+
+        result = upload_file_sync(image_url=_RED_PNG_DATA_URL, credentials="creds")
+
+        assert result == "cached-file-id"
+        # No upload call was made
+        mock_http_handler_cls.return_value.post.assert_not_called()
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}._download_image_sync")
+    def test_downloads_and_uploads_url_image(
+        self, mock_download, mock_get_api_base, mock_get_token, mock_http_handler_cls
+    ):
+        mock_download.return_value = (b"remote-bytes", "image/png", "png")
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"id": "file-remote"}
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        result = upload_file_sync(
+            image_url="https://example.com/remote.png", credentials="creds"
+        )
+
+        assert result == "file-remote"
+        mock_download.assert_called_once_with("https://example.com/remote.png")
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    def test_returns_none_on_upload_failure(
+        self, mock_get_api_base, mock_get_token, mock_http_handler_cls
+    ):
+        mock_client = MagicMock()
+        mock_client.post.side_effect = httpx.HTTPStatusError(
+            "Bad Request",
+            request=httpx.Request("POST", "https://api.example.com/files"),
+            response=httpx.Response(status_code=400, request=httpx.Request("POST", "https://api.example.com/files")),
+        )
+        mock_http_handler_cls.return_value = mock_client
+
+        # upload_file_sync catches all exceptions and returns None
+        result = upload_file_sync(
+            image_url=_RED_PNG_DATA_URL, credentials="creds"
+        )
+
+        assert result is None
+
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    def test_returns_none_when_response_missing_id(
+        self, mock_get_api_base, mock_get_token, mock_http_handler_cls
+    ):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"status": "ok"}  # no "id" key
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        result = upload_file_sync(
+            image_url=_RED_PNG_DATA_URL, credentials="creds"
+        )
+
+        assert result is None
+
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token", return_value="test-token")
+    @patch(f"{FILE_MODULE}._get_httpx_client")
+    def test_uploads_without_optional_args(
+        self, mock_http_handler_cls, mock_get_token, mock_get_api_base
+    ):
+        """Verify that credentials, api_base, and litellm_params are optional."""
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"id": "file-no-args"}
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post.return_value = mock_response
+        mock_http_handler_cls.return_value = mock_client
+
+        result = upload_file_sync(image_url=_RED_PNG_DATA_URL)
+
+        assert result == "file-no-args"
+        # Should still have called get_access_token without args
+        mock_get_token.assert_called_once_with(credentials=None, litellm_params=None)
+
+
+# ---------------------------------------------------------------------------
+# upload_file_async
+# ---------------------------------------------------------------------------
+
+
+class TestUploadFileAsync:
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    async def test_uploads_base64_image_and_caches(
+        self, mock_get_client, mock_get_token, mock_get_api_base
+    ):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json = MagicMock(return_value={"id": "async-file-1"})
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post = AsyncMock(return_value=mock_response)
+        mock_get_client.return_value = mock_client
+
+        result = await upload_file_async(
+            image_url=_RED_PNG_DATA_URL,
+            credentials="creds",
+            api_base="https://custom.example.com",
+        )
+
+        assert result == "async-file-1"
+        # Verify cache
+        url_hash = _get_url_hash(_RED_PNG_DATA_URL)
+        assert _file_cache[url_hash] == "async-file-1"
+
+        # Check upload request details — url is first positional arg
+        call_args = mock_client.post.call_args
+        assert call_args.args[0] == "https://api.example.com/files"
+        assert call_args.kwargs["headers"]["Authorization"] == "Bearer test-token-async"
+        assert "purpose" in str(call_args.kwargs["data"])
+        assert "file" in call_args.kwargs["files"]
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    async def test_returns_cached_file_id(
+        self, mock_get_client, mock_get_token, mock_get_api_base
+    ):
+        url_hash = _get_url_hash(_RED_PNG_DATA_URL)
+        _file_cache[url_hash] = "cached-async-id"
+
+        result = await upload_file_async(image_url=_RED_PNG_DATA_URL, credentials="creds")
+
+        assert result == "cached-async-id"
+        mock_get_client.return_value.post.assert_not_called()
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}._download_image_async")
+    async def test_downloads_and_uploads_url_image(
+        self, mock_download, mock_get_api_base, mock_get_token, mock_get_client
+    ):
+        mock_download.return_value = (b"remote-bytes-async", "image/png", "png")
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json = MagicMock(return_value={"id": "async-file-remote"})
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post = AsyncMock(return_value=mock_response)
+        mock_get_client.return_value = mock_client
+
+        result = await upload_file_async(
+            image_url="https://example.com/remote.png", credentials="creds"
+        )
+
+        assert result == "async-file-remote"
+        mock_download.assert_called_once_with("https://example.com/remote.png")
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    async def test_returns_none_on_upload_failure(
+        self, mock_get_api_base, mock_get_token, mock_get_client
+    ):
+        mock_client = MagicMock()
+        mock_client.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "Bad Request",
+                request=httpx.Request("POST", "https://api.example.com/files"),
+                response=httpx.Response(status_code=400, request=httpx.Request("POST", "https://api.example.com/files")),
+            )
+        )
+        mock_get_client.return_value = mock_client
+
+        result = await upload_file_async(
+            image_url=_RED_PNG_DATA_URL, credentials="creds"
+        )
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    async def test_returns_none_when_response_missing_id(
+        self, mock_get_api_base, mock_get_token, mock_get_client
+    ):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json = MagicMock(return_value={"status": "ok"})
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post = AsyncMock(return_value=mock_response)
+        mock_get_client.return_value = mock_client
+
+        result = await upload_file_async(
+            image_url=_RED_PNG_DATA_URL, credentials="creds"
+        )
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    @patch(f"{FILE_MODULE}.get_api_base", return_value="https://api.example.com")
+    @patch(f"{FILE_MODULE}.get_access_token_async", return_value="test-token-async")
+    @patch(f"{FILE_MODULE}.get_async_httpx_client")
+    async def test_uploads_without_optional_args(
+        self, mock_get_client, mock_get_token, mock_get_api_base
+    ):
+        mock_client = MagicMock()
+        mock_response = MagicMock()
+        mock_response.json = MagicMock(return_value={"id": "async-no-args"})
+        mock_response.raise_for_status = MagicMock()
+        mock_client.post = AsyncMock(return_value=mock_response)
+        mock_get_client.return_value = mock_client
+
+        result = await upload_file_async(image_url=_RED_PNG_DATA_URL)
+
+        assert result == "async-no-args"
+        mock_get_token.assert_called_once_with(credentials=None, litellm_params=None)
\ No newline at end of file
diff --git a/tests/test_litellm/llms/gigachat/test_utils.py b/tests/test_litellm/llms/gigachat/test_utils.py
new file mode 100644
index 00000000000..71a193d7b29
--- /dev/null
+++ b/tests/test_litellm/llms/gigachat/test_utils.py
@@ -0,0 +1,79 @@
+"""
+Tests for litellm.llms.gigachat.utils
+"""
+
+import pytest
+from litellm.llms.gigachat.utils import convert_usage
+from litellm.types.utils import PromptTokensDetailsWrapper, Usage
+
+
+class TestConvertUsage:
+    def test_basic_usage_without_precached(self):
+        """Test convert_usage with standard tokens, no precached prompt tokens."""
+        result = convert_usage(
+            {
+                "prompt_tokens": 10,
+                "completion_tokens": 5,
+                "total_tokens": 15,
+            }
+        )
+
+        assert result == Usage(
+            prompt_tokens=10,
+            completion_tokens=5,
+            total_tokens=15,
+            prompt_tokens_details=None,
+        )
+
+    def test_usage_with_precached_prompt_tokens(self):
+        """GigaChat's prompt_tokens and total_tokens exclude cached tokens (docs example:
+        prompt_tokens=1, precached_prompt_tokens=37, total_tokens=5), so OpenAI-convention
+        usage adds precached back in and surfaces it as cached_tokens."""
+        result = convert_usage(
+            {
+                "prompt_tokens": 10,
+                "completion_tokens": 5,
+                "precached_prompt_tokens": 3,
+                "total_tokens": 15,
+            }
+        )
+
+        assert result == Usage(
+            prompt_tokens=13,
+            completion_tokens=5,
+            total_tokens=18,
+            prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=3),
+        )
+
+    def test_zero_precached_prompt_tokens(self):
+        """Test convert_usage with zero precached_prompt_tokens does not create details wrapper."""
+        result = convert_usage(
+            {
+                "prompt_tokens": 10,
+                "completion_tokens": 5,
+                "precached_prompt_tokens": 0,
+                "total_tokens": 15,
+            }
+        )
+
+        assert result == Usage(
+            prompt_tokens=10,
+            completion_tokens=5,
+            total_tokens=15,
+            prompt_tokens_details=None,
+        )
+
+    def test_missing_optional_fields(self):
+        """Test convert_usage with missing optional fields defaults to zero."""
+        result = convert_usage(
+            {
+                "prompt_tokens": 10,
+                "completion_tokens": 5,
+                "total_tokens": 15,
+            }
+        )
+
+        assert result.prompt_tokens == 10
+        assert result.completion_tokens == 5
+        assert result.total_tokens == 15
+        assert result.prompt_tokens_details is None
\ No newline at end of file
diff --git a/tests/test_litellm/llms/hosted_vllm/test_hosted_vllm_rerank_transformation.py b/tests/test_litellm/llms/hosted_vllm/test_hosted_vllm_rerank_transformation.py
index e6e6aa946d5..9a62fcf6f0f 100644
--- a/tests/test_litellm/llms/hosted_vllm/test_hosted_vllm_rerank_transformation.py
+++ b/tests/test_litellm/llms/hosted_vllm/test_hosted_vllm_rerank_transformation.py
@@ -1,8 +1,14 @@
+import json
 import os
 import sys
+from typing import Final
+from unittest.mock import MagicMock, patch
 
+import httpx
 import pytest
 
+import litellm
+from litellm.llms.custom_httpx.http_handler import HTTPHandler
 from litellm.llms.hosted_vllm.rerank.transformation import HostedVLLMRerankConfig
 from litellm.rerank_api.rerank_utils import get_optional_rerank_params
 from litellm.types.rerank import (
@@ -87,9 +93,7 @@ class TestHostedVLLMRerankTransform:
         assert "instruction" not in body
 
     def test_map_cohere_rerank_params_raises_on_max_chunks_per_doc(self):
-        with pytest.raises(
-            ValueError, match="Hosted VLLM does not support max_chunks_per_doc"
-        ):
+        with pytest.raises(ValueError, match="Hosted VLLM does not support max_chunks_per_doc"):
             self.config.map_cohere_rerank_params(
                 non_default_params=None,
                 model=self.model,
@@ -104,12 +108,10 @@ class TestHostedVLLMRerankTransform:
         url = self.config.get_complete_url(base, self.model)
         assert url == "https://api.example.com/rerank"
         # Already ends with /rerank
-        url2 = self.config.get_complete_url(
-            "https://api.example.com/rerank", self.model
-        )
+        url2 = self.config.get_complete_url("https://api.example.com/rerank", self.model)
         assert url2 == "https://api.example.com/rerank"
         # Raises if api_base is None
-        with pytest.raises(ValueError, match='api_base must be provided for Hosted VLLM rerank'):
+        with pytest.raises(ValueError, match="api_base must be provided for Hosted VLLM rerank"):
             self.config.get_complete_url(None, self.model)
 
     def test_transform_response(self):
@@ -173,3 +175,121 @@ class TestGetOptionalRerankParamsInstruction:
             documents=["doc1", "doc2"],
         )
         assert "instruction" not in params
+
+
+class TestHostedVLLMRerankTruncationParams:
+    def setup_method(self):
+        self.config = HostedVLLMRerankConfig()
+        self.model = "hosted-vllm-model"
+
+    def test_map_cohere_rerank_params_forwards_vllm_truncation_params(self):
+        params: Final = self.config.map_cohere_rerank_params(
+            non_default_params={
+                "truncate_prompt_tokens": 512,
+                "truncation_side": "left",
+                "max_tokens_per_query": 64,
+                "metadata": {"user_api_key": "sk-test"},
+            },
+            model=self.model,
+            drop_params=False,
+            query="test query",
+            documents=["doc1", "doc2"],
+            max_tokens_per_doc=128,
+        )
+        assert params["truncate_prompt_tokens"] == 512
+        assert params["truncation_side"] == "left"
+        assert params["max_tokens_per_query"] == 64
+        assert params["max_tokens_per_doc"] == 128
+        assert "metadata" not in params
+
+    @pytest.mark.parametrize(
+        "bad_params",
+        [{"truncation_side": "middle"}, {"truncate_prompt_tokens": "lots"}, {"max_tokens_per_query": -1.5}],
+    )
+    def test_map_cohere_rerank_params_rejects_invalid_truncation_params_as_400(self, bad_params: dict[str, object]):
+        with pytest.raises(litellm.UnsupportedParamsError) as raised:
+            self.config.map_cohere_rerank_params(
+                non_default_params=dict(bad_params),
+                model=self.model,
+                drop_params=False,
+                query="test query",
+                documents=["doc1", "doc2"],
+            )
+        assert raised.value.status_code == 400
+        assert next(iter(bad_params)) in str(raised.value)
+
+    def test_map_cohere_rerank_params_omits_truncation_params_when_absent(self):
+        params: Final = self.config.map_cohere_rerank_params(
+            non_default_params={"metadata": {"user_api_key": "sk-test"}},
+            model=self.model,
+            drop_params=False,
+            query="test query",
+            documents=["doc1", "doc2"],
+        )
+        body: Final = self.config.transform_rerank_request(model=self.model, optional_rerank_params=params, headers={})
+        truncation_keys: Final = {
+            "truncate_prompt_tokens",
+            "truncation_side",
+            "max_tokens_per_query",
+            "max_tokens_per_doc",
+        }
+        assert not truncation_keys & body.keys()
+        assert body == {
+            "model": self.model,
+            "query": "test query",
+            "documents": ["doc1", "doc2"],
+            "return_documents": True,
+        }
+
+    def test_transform_request_forwards_truncation_params(self):
+        body: Final = self.config.transform_rerank_request(
+            model=self.model,
+            optional_rerank_params={
+                "query": "test query",
+                "documents": ["doc1", "doc2"],
+                "truncate_prompt_tokens": 512,
+                "truncation_side": "left",
+                "max_tokens_per_query": 64,
+                "max_tokens_per_doc": 128,
+            },
+            headers={},
+        )
+        assert body["truncate_prompt_tokens"] == 512
+        assert body["truncation_side"] == "left"
+        assert body["max_tokens_per_query"] == 64
+        assert body["max_tokens_per_doc"] == 128
+
+    def test_transform_request_omits_truncation_params_when_absent(self):
+        body: Final = self.config.transform_rerank_request(
+            model=self.model,
+            optional_rerank_params={"query": "test query", "documents": ["doc1", "doc2"]},
+            headers={},
+        )
+        assert "truncate_prompt_tokens" not in body
+        assert "truncation_side" not in body
+        assert "max_tokens_per_query" not in body
+        assert "max_tokens_per_doc" not in body
+
+    def test_rerank_sends_truncate_prompt_tokens_to_vllm(self):
+        client: Final = HTTPHandler()
+        mock_response: Final = MagicMock(spec=httpx.Response)
+        mock_response.status_code = 200
+        mock_response.json.return_value = {
+            "id": "score-1",
+            "results": [{"index": 0, "relevance_score": 0.5}],
+            "usage": {"total_tokens": 512},
+        }
+        with patch.object(client, "post", return_value=mock_response) as mock_post:
+            litellm.rerank(
+                model="hosted_vllm/BAAI/bge-reranker-base",
+                api_base="http://vllm.local:8000",
+                query="List all the unique case ids",
+                documents=["a document longer than the reranker context window"],
+                truncate_prompt_tokens=512,
+                truncation_side="left",
+                client=client,
+            )
+        sent_body: Final = json.loads(mock_post.call_args.kwargs["data"])
+        assert mock_post.call_args.kwargs["url"] == "http://vllm.local:8000/rerank"
+        assert sent_body["truncate_prompt_tokens"] == 512
+        assert sent_body["truncation_side"] == "left"
diff --git a/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py b/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py
index 890df597933..a0e1616d4b2 100644
--- a/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py
+++ b/tests/test_litellm/llms/mistral/ocr/test_mistral_ocr_cost.py
@@ -24,6 +24,9 @@ OCR3_MODEL = "mistral/mistral-ocr-2512"
 OCR3_COST_PER_PAGE = 0.002
 OCR3_ANNOTATION_COST_PER_PAGE = 0.003
 
+AZURE_DOC_AI_MODEL = "azure_ai/mistral-document-ai-2512"
+AZURE_DOC_AI_COST_PER_PAGE = 0.003
+
 
 def _ocr_response(model: str, pages_processed: int) -> OCRResponse:
     return OCRResponse(
@@ -33,6 +36,14 @@ def _ocr_response(model: str, pages_processed: int) -> OCRResponse:
     )
 
 
+def _annotated_ocr_response(model: str, pages_processed: int | None, annotation_pages: int) -> OCRResponse:
+    return OCRResponse(
+        pages=[],
+        model=model,
+        usage_info=OCRUsageInfo(pages_processed=pages_processed, pages_processed_annotation=annotation_pages),
+    )
+
+
 @pytest.mark.parametrize("model", ["mistral-ocr-4-0", "mistral-ocr-latest"])
 def test_model_info_ocr4_price(model: str) -> None:
     info = litellm.get_model_info(model=f"mistral/{model}", custom_llm_provider="mistral")
@@ -79,3 +90,46 @@ def test_ocr3_cost_scales_with_pages(local_model_cost_map, pages_processed: int)
         call_type="ocr",
     )
     assert cost == pytest.approx(OCR3_COST_PER_PAGE * pages_processed)
+
+
+def test_ocr3_bills_ocr_and_annotation_pages_at_their_own_rates(local_model_cost_map) -> None:
+    cost = completion_cost(
+        completion_response=_annotated_ocr_response("mistral-ocr-2512", 2, 3),
+        model=OCR3_MODEL,
+        custom_llm_provider="mistral",
+        call_type="ocr",
+    )
+    assert cost == pytest.approx(2 * OCR3_COST_PER_PAGE + 3 * OCR3_ANNOTATION_COST_PER_PAGE)
+
+
+def test_ocr3_bills_annotation_only_response(local_model_cost_map) -> None:
+    cost = completion_cost(
+        completion_response=_annotated_ocr_response("mistral-ocr-2512", 0, 3),
+        model=OCR3_MODEL,
+        custom_llm_provider="mistral",
+        call_type="ocr",
+    )
+    assert cost == pytest.approx(3 * OCR3_ANNOTATION_COST_PER_PAGE)
+
+
+def test_ocr3_bills_annotation_pages_when_pages_processed_missing(local_model_cost_map) -> None:
+    cost = completion_cost(
+        completion_response=_annotated_ocr_response("mistral-ocr-2512", None, 4),
+        model=OCR3_MODEL,
+        custom_llm_provider="mistral",
+        call_type="ocr",
+    )
+    assert cost == pytest.approx(4 * OCR3_ANNOTATION_COST_PER_PAGE)
+
+
+def test_azure_doc_ai_annotation_pages_fall_back_to_ocr_rate(local_model_cost_map) -> None:
+    info = litellm.get_model_info(model=AZURE_DOC_AI_MODEL, custom_llm_provider="azure_ai")
+    assert info.get("annotation_cost_per_page") is None
+    assert info["ocr_cost_per_page"] == AZURE_DOC_AI_COST_PER_PAGE
+    cost = completion_cost(
+        completion_response=_annotated_ocr_response("mistral-document-ai-2512", 0, 1),
+        model=AZURE_DOC_AI_MODEL,
+        custom_llm_provider="azure_ai",
+        call_type="ocr",
+    )
+    assert cost == pytest.approx(AZURE_DOC_AI_COST_PER_PAGE)
diff --git a/tests/test_litellm/llms/ollama/test_ollama_chat_transformation.py b/tests/test_litellm/llms/ollama/test_ollama_chat_transformation.py
index 8f3dbf7b0d9..25f9645faa0 100644
--- a/tests/test_litellm/llms/ollama/test_ollama_chat_transformation.py
+++ b/tests/test_litellm/llms/ollama/test_ollama_chat_transformation.py
@@ -615,6 +615,46 @@ class TestOllamaFinishReasonLength:
             result.choices[0].finish_reason == "stop"
         ), f"Expected 'stop' for natural finish, got '{result.choices[0].finish_reason}'"
 
+    def test_finish_reason_tool_calls_streamed_before_done_chunk(self):
+        """Streaming: tool_calls arriving mid-stream (not on the done chunk) must
+        still produce finish_reason='tool_calls' on the final chunk.
+
+        Regression test for https://github.com/BerriAI/litellm/issues/34692:
+        Ollama emits tool_calls in an earlier chunk and the done chunk carries
+        none, which left finish_reason at 'stop' and made the Anthropic
+        /v1/messages bridge emit stop_reason 'end_turn' instead of 'tool_use'.
+        """
+        iterator = OllamaChatCompletionResponseIterator(
+            streaming_response=iter([]),
+            sync_stream=True,
+        )
+
+        tool_chunk = {
+            "model": "qwen3:8b",
+            "message": {
+                "role": "assistant",
+                "content": "",
+                "tool_calls": [
+                    {"function": {"name": "get_weather", "arguments": {"city": "San Francisco"}}}
+                ],
+            },
+            "done": False,
+        }
+        done_chunk = {
+            "model": "qwen3:8b",
+            "message": {"role": "assistant", "content": ""},
+            "done": True,
+            "done_reason": "stop",
+        }
+
+        tool_result = iterator.chunk_parser(tool_chunk)
+        assert tool_result.choices[0].delta.tool_calls is not None
+
+        done_result = iterator.chunk_parser(done_chunk)
+        assert (
+            done_result.choices[0].finish_reason == "tool_calls"
+        ), f"Expected 'tool_calls' when tool_calls were streamed earlier, got '{done_result.choices[0].finish_reason}'"
+
 
 class TestOllamaReasoningContentStreaming:
     """Test that reasoning_content is properly extracted from all thinking chunks."""
diff --git a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
index a29e0be4655..7dd6065063a 100644
--- a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
+++ b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py
@@ -1559,3 +1559,87 @@ class TestScanOnlyToolResults:
         assert data["messages"][3]["content"] == "page says [BLOCKED] here"
         assert data["messages"][3]["tool_call_id"] == "call_1"
         assert data["messages"][4]["content"] == "and then?"
+
+
+class TestBuildBlockSseChunks:
+    """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE chunks"""
+
+    def _exc(self, original_response=None):
+        from litellm.exceptions import ModifyResponseException
+
+        return ModifyResponseException(
+            message="Blocked by policy.",
+            model="gpt-5.4-mini",
+            request_data={},
+            guardrail_name="test",
+            original_response=original_response,
+        )
+
+    def _payloads(self, chunks):
+        return [json.loads(chunk.decode().removeprefix("data: ").strip()) for chunk in chunks]
+
+    def test_standalone_block_uses_fresh_identity_and_zero_usage(self):
+        handler = OpenAIChatCompletionsHandler()
+        first, final = self._payloads(handler.build_block_sse_chunks(self._exc(), stream_started=False))
+        assert first["id"].startswith("chatcmpl-")
+        assert first["model"] == "gpt-5.4-mini"
+        assert first["choices"][0]["delta"] == {"role": "assistant", "content": "Blocked by policy."}
+        assert first["choices"][0]["finish_reason"] is None
+        assert final["choices"][0]["delta"] == {}
+        assert final["choices"][0]["finish_reason"] == "content_filter"
+        assert final["usage"] == {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0}
+
+    def test_continuation_reuses_stream_identity_and_real_usage(self):
+        handler = OpenAIChatCompletionsHandler()
+        yielded = [
+            {"id": "chatcmpl-live", "created": 1724900000, "model": "gpt-5.4-mini-2026-01-01"},
+        ]
+        original = yielded + [
+            {"id": "chatcmpl-live", "usage": {"prompt_tokens": 11, "completion_tokens": 5}},
+        ]
+        first, final = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=yielded
+            )
+        )
+        assert (first["id"], first["created"], first["model"]) == (
+            "chatcmpl-live",
+            1724900000,
+            "gpt-5.4-mini-2026-01-01",
+        )
+        assert first["choices"][0]["delta"] == {"content": "Blocked by policy."}
+        assert final["id"] == "chatcmpl-live"
+        assert final["usage"] == {"prompt_tokens": 11, "completion_tokens": 5, "total_tokens": 16}
+
+
+class TestCheckStreamingHasEnded:
+    """_check_streaming_has_ended lets end_of_stream_only withhold the finish chunk until moderation"""
+
+    def test_empty_and_content_only_chunks_are_not_ended(self):
+        handler = OpenAIChatCompletionsHandler()
+        assert handler._check_streaming_has_ended([]) is False
+        content_only = [
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {"content": "hi"}, "finish_reason": None}]},
+            {"id": "chatcmpl-live", "choices": []},
+            {"id": "chatcmpl-live", "usage": {"prompt_tokens": 1, "completion_tokens": 1}},
+        ]
+        assert handler._check_streaming_has_ended(content_only) is False
+
+    def test_dict_finish_chunk_marks_stream_ended(self):
+        handler = OpenAIChatCompletionsHandler()
+        chunks = [
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {"content": "hi"}, "finish_reason": None}]},
+            {"id": "chatcmpl-live", "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
+        ]
+        assert handler._check_streaming_has_ended(chunks) is True
+
+    def test_object_finish_chunk_marks_stream_ended(self):
+        from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+        handler = OpenAIChatCompletionsHandler()
+        chunks = [
+            ModelResponseStream(
+                choices=[StreamingChoices(index=0, delta=Delta(content=None), finish_reason="stop")]
+            )
+        ]
+        assert handler._check_streaming_has_ended(chunks) is True
diff --git a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py
index 3f346b5e8e7..9737d63cc26 100644
--- a/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py
+++ b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py
@@ -145,6 +145,69 @@ class TestGetOptionalParamsIntegration:
         assert regular_params.get("user") == "my-end-user"
         assert responses_params.get("user") == "my-end-user"
 
+    def test_reasoning_effort_supported_for_unknown_model_alias(self):
+        """An openai/-routed model litellm doesn't recognize is likely a proxy alias:
+        reasoning_effort must be forwarded so the server decides support."""
+        from litellm.llms.openai.openai import OpenAIConfig
+
+        supported_params = OpenAIConfig().get_supported_openai_params(
+            "my-claude-alias"
+        )
+        assert "reasoning_effort" in supported_params
+
+    def test_reasoning_effort_not_supported_for_known_non_reasoning_models(self):
+        """Known OpenAI models keep failing closed client-side."""
+        from litellm.llms.openai.openai import OpenAIConfig
+
+        config = OpenAIConfig()
+        assert "reasoning_effort" not in config.get_supported_openai_params("gpt-4o")
+        assert "reasoning_effort" not in config.get_supported_openai_params(
+            "responses/gpt-4.1-mini"
+        )
+
+    def test_reasoning_effort_not_inherited_by_openai_compatible_subclasses(self):
+        """Providers subclassing either openai config keep their own reasoning_effort gating
+        for their models, which are all unknown to the openai catalog."""
+        from litellm.llms.openai.openai import OpenAIConfig
+
+        class InheritingDispatcherConfig(OpenAIConfig):
+            pass
+
+        class InheritingGPTConfig(OpenAIGPTConfig):
+            pass
+
+        assert "reasoning_effort" not in InheritingDispatcherConfig().get_supported_openai_params(
+            "some-unknown-model"
+        )
+        assert "reasoning_effort" not in InheritingGPTConfig().get_supported_openai_params(
+            "some-unknown-model"
+        )
+
+    def test_reasoning_effort_forwarded_in_optional_params_for_unknown_model_alias(
+        self,
+    ):
+        """Regression test for reasoning_effort raising UnsupportedParamsError
+        client-side for openai/-prefixed proxy aliases before any HTTP request."""
+        from litellm.utils import get_optional_params
+
+        optional_params = get_optional_params(
+            model="my-claude-alias",
+            custom_llm_provider="openai",
+            reasoning_effort="low",
+        )
+        assert optional_params.get("reasoning_effort") == "low"
+
+    def test_reasoning_effort_still_rejected_for_known_non_reasoning_model(self):
+        """A real OpenAI model that doesn't reason still rejects the param client-side."""
+        from litellm.utils import get_optional_params
+
+        with pytest.raises(litellm.utils.UnsupportedParamsError):
+            get_optional_params(
+                model="gpt-4o",
+                custom_llm_provider="openai",
+                reasoning_effort="low",
+            )
+
 
 class TestOpenAIChatCompletionStreamingHandler:
     """Tests for OpenAIChatCompletionStreamingHandler.chunk_parser()"""
@@ -808,6 +871,134 @@ class TestCacheControlPreservationForCustomEndpoint:
         assert all("cache_control" not in m for m in body["messages"])
 
 
+class TestToolChoiceWithoutToolsDropped:
+    def setup_method(self):
+        self.config = OpenAIGPTConfig()
+
+    @staticmethod
+    def _pi_compact_summarization_messages():
+        return [
+            {
+                "role": "system",
+                "content": "You are a context summarization assistant. Your task is to read a conversation between a user and an AI assistant, then produce a structured summary following the exact format specified.",
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "<conversation>\n[User]: Reply with exactly: ok-1\n\n[Assistant]: ok-1\n</conversation>\n\nThe messages above are a conversation to summarize.",
+                    }
+                ],
+            },
+        ]
+
+    def _transform(self, optional_params, config=None, model="gpt-5.6-sol"):
+        return (config or self.config).transform_request(
+            model=model,
+            messages=self._pi_compact_summarization_messages(),
+            optional_params=optional_params,
+            litellm_params={"custom_llm_provider": "openai", "api_base": None},
+            headers={},
+        )
+
+    def test_pi_compact_shape_drops_tool_choice_none_without_tools(self):
+        body = self._transform(
+            {
+                "stream": True,
+                "stream_options": {"include_usage": True},
+                "store": False,
+                "max_completion_tokens": 13107,
+                "tool_choice": "none",
+            }
+        )
+        assert "tool_choice" not in body
+        assert "tools" not in body
+        assert body["model"] == "gpt-5.6-sol"
+        assert body["stream"] is True
+        assert body["stream_options"] == {"include_usage": True}
+        assert body["store"] is False
+        assert body["max_completion_tokens"] == 13107
+
+    def test_drops_tool_choice_auto_without_tools(self):
+        body = self._transform({"tool_choice": "auto"})
+        assert "tool_choice" not in body
+
+    def test_drops_named_function_tool_choice_without_tools(self):
+        body = self._transform(
+            {"tool_choice": {"type": "function", "function": {"name": "get_weather"}}}
+        )
+        assert "tool_choice" not in body
+
+    def test_drops_tool_choice_but_keeps_empty_tools_array(self):
+        body = self._transform({"tools": [], "tool_choice": "none"})
+        assert "tool_choice" not in body
+        assert body["tools"] == []
+
+    def test_gpt5_config_drops_tool_choice_without_tools(self):
+        body = self._transform({"tool_choice": "none"}, config=OpenAIGPT5Config())
+        assert "tool_choice" not in body
+
+    @pytest.mark.parametrize(
+        "tool_choice",
+        [
+            "none",
+            "auto",
+            "required",
+            {"type": "function", "function": {"name": "get_weather"}},
+        ],
+    )
+    def test_preserves_tool_choice_when_tools_present(self, tool_choice):
+        tools = [
+            {
+                "type": "function",
+                "function": {"name": "get_weather", "parameters": {}},
+            }
+        ]
+        body = self._transform({"tools": tools, "tool_choice": tool_choice})
+        assert body["tool_choice"] == tool_choice
+        assert body["tools"] == tools
+
+    def test_preserves_tool_choice_with_legacy_functions(self):
+        functions = [{"name": "get_weather", "parameters": {}}]
+        body = self._transform({"functions": functions, "tool_choice": "auto"})
+        assert body["tool_choice"] == "auto"
+        assert body["functions"] == functions
+
+    def test_preserves_function_call_without_functions(self):
+        body = self._transform({"function_call": "none"})
+        assert body["function_call"] == "none"
+
+    @pytest.mark.asyncio
+    async def test_async_transform_drops_tool_choice_without_tools(self):
+        body = await self.config.async_transform_request(
+            model="gpt-5.6-sol",
+            messages=self._pi_compact_summarization_messages(),
+            optional_params={"stream": True, "tool_choice": "none"},
+            litellm_params={"custom_llm_provider": "openai", "api_base": None},
+            headers={},
+        )
+        assert "tool_choice" not in body
+
+    @pytest.mark.asyncio
+    async def test_async_transform_preserves_tool_choice_when_tools_present(self):
+        tools = [
+            {
+                "type": "function",
+                "function": {"name": "get_weather", "parameters": {}},
+            }
+        ]
+        body = await self.config.async_transform_request(
+            model="gpt-5.6-sol",
+            messages=self._pi_compact_summarization_messages(),
+            optional_params={"tools": tools, "tool_choice": "auto"},
+            litellm_params={"custom_llm_provider": "openai", "api_base": None},
+            headers={},
+        )
+        assert body["tool_choice"] == "auto"
+        assert body["tools"] == tools
+
+
 class TestToolMessageImageHoisting:
     """transform_request moves tool-message images into a following user message
     (OpenAI-compatible APIs only accept text in role:"tool" messages)."""
@@ -975,3 +1166,118 @@ class TestOpenAIPromptCacheBreakpointChatPath:
         assert request["messages"][1]["content"] == [{"type": "text", "text": "hi", "prompt_cache_breakpoint": self.EXPLICIT}]
         assert request["extra_body"] == {"prompt_cache_options": self.EXPLICIT}
         assert "prompt_cache_options" not in request
+
+
+class TestToolSchemaCombinatorFlatteningForOpenAI:
+    """
+    Regression tests for LIT-6488: OpenAI's chat completions validator rejects
+    tool parameters carrying a top-level anyOf/oneOf/allOf for every model
+    family, GPT-5 included, unlike the Responses API.
+    """
+
+    def setup_method(self):
+        self.config = OpenAIGPTConfig()
+
+    @pytest.fixture(autouse=True)
+    def _clean_openai_base_env(self, monkeypatch):
+        monkeypatch.delenv("OPENAI_BASE_URL", raising=False)
+        monkeypatch.delenv("OPENAI_API_BASE", raising=False)
+        monkeypatch.setattr(litellm, "api_base", None, raising=False)
+
+    @staticmethod
+    def _anyof_tool():
+        return {
+            "type": "function",
+            "function": {
+                "name": "automation_update",
+                "description": "Update an automation",
+                "parameters": {
+                    "type": "object",
+                    "anyOf": [
+                        {
+                            "properties": {"id": {"type": "string"}, "enabled": {"type": "boolean"}},
+                            "required": ["id", "enabled"],
+                        },
+                        {
+                            "properties": {"id": {"type": "string"}, "schedule": {"type": "string"}},
+                            "required": ["id", "schedule"],
+                        },
+                    ],
+                    "properties": {"id": {"type": "string"}},
+                    "required": ["id"],
+                },
+            },
+        }
+
+    def _transform(self, config, model, litellm_params, tools):
+        return config.transform_request(
+            model=model,
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={"tools": tools},
+            litellm_params=litellm_params,
+            headers={},
+        )
+
+    def test_flattens_top_level_anyof_for_hosted_openai(self):
+        request = self._transform(
+            self.config, "gpt-4o", {"custom_llm_provider": "openai", "api_base": None}, [self._anyof_tool()]
+        )
+        parameters = request["tools"][0]["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert parameters["type"] == "object"
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+        assert parameters["required"] == ["id"]
+        assert request["tools"][0]["function"]["name"] == "automation_update"
+
+    def test_gpt5_family_flattens_on_chat_completions(self):
+        request = self._transform(
+            OpenAIGPT5Config(), "gpt-5.6", {"custom_llm_provider": "openai", "api_base": None}, [self._anyof_tool()]
+        )
+        assert "anyOf" not in request["tools"][0]["function"]["parameters"]
+
+    def test_custom_api_base_keeps_union(self):
+        tool = self._anyof_tool()
+        request = self._transform(
+            self.config,
+            "gpt-4o",
+            {"custom_llm_provider": "openai", "api_base": "http://localhost:8000/v1"},
+            [tool],
+        )
+        assert request["tools"][0]["function"]["parameters"] == self._anyof_tool()["function"]["parameters"]
+
+    def test_non_openai_provider_keeps_union(self):
+        request = self._transform(
+            self.config, "some-oss-model", {"custom_llm_provider": "groq", "api_base": None}, [self._anyof_tool()]
+        )
+        assert request["tools"][0]["function"]["parameters"] == self._anyof_tool()["function"]["parameters"]
+
+    def test_caller_tool_dict_is_not_mutated(self):
+        tool = self._anyof_tool()
+        self._transform(self.config, "gpt-4o", {"custom_llm_provider": "openai", "api_base": None}, [tool])
+        assert tool == self._anyof_tool()
+
+    def test_clean_object_schema_passes_through_as_same_object(self):
+        tool = {
+            "type": "function",
+            "function": {
+                "name": "lookup",
+                "parameters": {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["id"]},
+            },
+        }
+        request = self._transform(
+            self.config, "gpt-4o", {"custom_llm_provider": "openai", "api_base": None}, [tool]
+        )
+        assert request["tools"][0] is tool
+
+    @pytest.mark.asyncio
+    async def test_async_transform_request_flattens_for_hosted_openai(self):
+        request = await self.config.async_transform_request(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": "hi"}],
+            optional_params={"tools": [self._anyof_tool()]},
+            litellm_params={"custom_llm_provider": "openai", "api_base": None},
+            headers={},
+        )
+        parameters = request["tools"][0]["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_count_tokens_transformation.py b/tests/test_litellm/llms/openai/responses/test_openai_count_tokens_transformation.py
index e1cc6a92927..c2efc1acdb9 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_count_tokens_transformation.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_count_tokens_transformation.py
@@ -163,6 +163,240 @@ def test_messages_to_responses_input_with_tool():
     }
 
 
+def test_messages_to_responses_input_preserves_images():
+    """An image block must survive the round trip, or OpenAI counts only the text.
+
+    A 256x256 image is worth 255 tokens to OpenAI's counting API; dropping it
+    turned a 268-token request into a 13-token one.
+    """
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this image?"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": "data:image/png;base64,iVBORw0KGgo=", "detail": "high"},
+                },
+            ],
+        }
+    ]
+
+    input_items, instructions = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert instructions is None
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "What is in this image?"},
+                {
+                    "type": "input_image",
+                    "image_url": "data:image/png;base64,iVBORw0KGgo=",
+                    "detail": "high",
+                },
+            ),
+        }
+    ]
+
+
+def test_messages_to_responses_input_image_without_detail_defaults_to_auto():
+    messages = [
+        {
+            "role": "user",
+            "content": [{"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}}],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_bare_string_image_url_is_preserved():
+    messages = [{"role": "user", "content": [{"type": "image_url", "image_url": "https://example.com/cat.png"}]}]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_text_only_blocks_stay_a_joined_string():
+    """Text-only content must keep collapsing to a string so existing counts do not shift."""
+    messages = [
+        {
+            "role": "user",
+            "content": [{"type": "text", "text": "first"}, {"type": "text", "text": "second"}],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "user", "content": "first\nsecond"}]
+
+
+def test_messages_to_responses_input_drops_unmappable_blocks():
+    """A block with no Responses API equivalent is skipped, never forwarded verbatim."""
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "hi"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+                {"type": "input_audio", "input_audio": {"data": "AAAA", "format": "wav"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_text", "text": "hi"},
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_assistant_blocks_collapse_to_a_string():
+    """An assistant turn must never forward chat `text` blocks.
+
+    The Responses API only accepts output_text and refusal inside an assistant turn, so
+    forwarding them 400s the whole request and silently drops the count back to the local
+    tokenizer, which is exactly what defeats the image fix above.
+    """
+    messages = [
+        {"role": "user", "content": [{"type": "text", "text": "What is the capital of France?"}]},
+        {"role": "assistant", "content": [{"type": "text", "text": "Paris."}]},
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {"role": "user", "content": "What is the capital of France?"},
+        {"role": "assistant", "content": "Paris."},
+    ]
+
+
+def test_messages_to_responses_input_assistant_image_block_is_dropped():
+    """An image part is illegal inside an assistant turn, so it must not reach the provider."""
+    messages = [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "Here it is"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "assistant", "content": "Here it is"}]
+
+
+def test_messages_to_responses_input_keeps_user_image_alongside_an_assistant_turn():
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this image?"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+            ],
+        },
+        {"role": "assistant", "content": [{"type": "text", "text": "A cat."}]},
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "What is in this image?"},
+                {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+            ),
+        },
+        {"role": "assistant", "content": "A cat."},
+    ]
+
+
+def test_messages_to_responses_input_preserves_inline_files():
+    """An inline file must survive the round trip, or the count silently drops the file.
+
+    A small PDF is worth 36 tokens to OpenAI's counting API; dropping it left the same
+    request counting 13, the text-only total.
+    """
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Summarize this file."},
+                {
+                    "type": "file",
+                    "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0="},
+                },
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "Summarize this file."},
+                {
+                    "type": "input_file",
+                    "filename": "report.pdf",
+                    "file_data": "data:application/pdf;base64,JVBERi0=",
+                },
+            ),
+        }
+    ]
+
+
+def test_messages_to_responses_input_drops_a_file_with_no_inline_data():
+    """OpenAI rejects `file_data` without a `filename`, and a rejected request loses the whole count."""
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Summarize this file."},
+                {"type": "file", "file": {"file_data": "data:application/pdf;base64,JVBERi0="}},
+                {"type": "file", "file": {"file_id": "file-abc123"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "user", "content": "Summarize this file."}]
+
+
+def test_messages_to_responses_input_assistant_file_block_is_dropped():
+    """A file part is illegal inside an assistant turn, so it must not reach the provider."""
+    messages = [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "Here it is"},
+                {
+                    "type": "file",
+                    "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0="},
+                },
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "assistant", "content": "Here it is"}]
+
+
 def test_validate_request_valid():
     """Test that valid requests pass validation."""
     config = OpenAICountTokensConfig()
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
index 447175b09a6..315b6948bd8 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
@@ -828,6 +828,24 @@ class MockPassThroughGuardrail(CustomGuardrail):
         return inputs
 
 
+class MockRecordingGuardrail(MockPassThroughGuardrail):
+    """Pass-through guardrail that records every apply_guardrail inputs payload"""
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.seen_inputs: List[GenericGuardrailAPIInputs] = []
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        self.seen_inputs.append(inputs)
+        return inputs
+
+
 class TestOpenAIResponsesHandlerStreamingOutputProcessing:
     """Test streaming output processing functionality"""
 
@@ -1104,6 +1122,80 @@ class TestOpenAIResponsesHandlerStreamingOutputProcessing:
         output_text = result[-1]["response"]["output"][0]["content"][0]["text"]
         assert output_text == original_text
 
+    @pytest.mark.asyncio
+    async def test_failed_stream_scans_delta_text(self):
+        """A stream ending in response.failed has text only in delta events; the
+        fallback scan must assemble and scan it instead of skipping on an empty string."""
+        handler = OpenAIResponsesHandler()
+        guardrail = MockRecordingGuardrail(guardrail_name="test")
+
+        responses_so_far = [
+            {"type": "response.created", "response": {"id": "resp_123"}},
+            {"type": "response.output_item.added", "item": {"type": "message", "id": "msg_123"}},
+            {
+                "type": "response.output_text.delta",
+                "item_id": "msg_123",
+                "output_index": 0,
+                "content_index": 0,
+                "delta": "Hello",
+            },
+            {
+                "type": "response.output_text.delta",
+                "item_id": "msg_123",
+                "output_index": 0,
+                "content_index": 0,
+                "delta": " world",
+            },
+            {"type": "response.failed", "response": {"id": "resp_123", "status": "failed"}},
+        ]
+
+        result = await handler.process_output_streaming_response(
+            responses_so_far=responses_so_far,
+            guardrail_to_apply=guardrail,
+            litellm_logging_obj=None,
+        )
+
+        assert result == responses_so_far
+        assert [inputs.get("texts") for inputs in guardrail.seen_inputs] == [["Hello world"]]
+
+    def test_get_streaming_string_so_far_prefers_done_text_over_deltas(self):
+        """The done event repeats the whole part, so deltas must not be double counted;
+        a part with no done event yet still contributes its joined deltas."""
+        handler = OpenAIResponsesHandler()
+
+        events = [
+            {
+                "type": "response.output_text.delta",
+                "item_id": "msg_1",
+                "output_index": 0,
+                "content_index": 0,
+                "delta": "Hello",
+            },
+            {
+                "type": "response.output_text.delta",
+                "item_id": "msg_1",
+                "output_index": 0,
+                "content_index": 0,
+                "delta": " world",
+            },
+            {
+                "type": "response.output_text.done",
+                "item_id": "msg_1",
+                "output_index": 0,
+                "content_index": 0,
+                "text": "Hello world",
+            },
+            {
+                "type": "response.output_text.delta",
+                "item_id": "msg_2",
+                "output_index": 1,
+                "content_index": 0,
+                "delta": "; unfinished",
+            },
+        ]
+
+        assert handler.get_streaming_string_so_far(events) == "Hello world; unfinished"
+
 
 class TestGetStructuredMessages:
     """Test the get_structured_messages method for Responses API handler."""
@@ -1229,3 +1321,219 @@ class TestOpenAIResponsesHandlerToolInjection:
         names = [t.get("name") for t in result["tools"]]
         assert "get_weather" in names
         assert "injected_tool" in names
+
+
+class TestBuildBlockSseChunks:
+    """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE events"""
+
+    def _exc(self, original_response=None):
+        from litellm.exceptions import ModifyResponseException
+
+        return ModifyResponseException(
+            message="Blocked by policy.",
+            model="gpt-5.4-mini",
+            request_data={},
+            guardrail_name="test",
+            original_response=original_response,
+        )
+
+    def _payloads(self, chunks):
+        import json
+
+        return [json.loads(chunk.decode().removeprefix("data: ").strip()) for chunk in chunks]
+
+    def test_standalone_block_emits_complete_synthetic_stream(self):
+        handler = OpenAIResponsesHandler()
+        payloads = self._payloads(handler.build_block_sse_chunks(self._exc(), stream_started=False))
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.created"
+        assert types[-1] == "response.completed"
+        completed = payloads[-1]["response"]
+        assert completed["id"].startswith("resp_")
+        assert completed["model"] == "gpt-5.4-mini"
+        assert completed["output"][0]["content"][0]["text"] == "Blocked by policy."
+
+    def test_continuation_appends_item_at_next_output_index_with_real_usage(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini-2026-01-01"}},
+            {"type": "response.output_item.added", "output_index": 2, "item": {"id": "msg_orig"}},
+        ]
+        original = yielded + [
+            {
+                "type": "response.completed",
+                "response": {
+                    "id": "resp_live",
+                    "model": "gpt-5.4-mini-2026-01-01",
+                    "output": [],
+                    "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+                },
+            }
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert "response.created" not in types
+        assert types[0] == "response.output_item.done"
+        assert payloads[0]["output_index"] == 2
+        assert payloads[0]["item"]["id"] == "msg_orig"
+        assert payloads[0]["item"]["status"] == "completed"
+        assert types[1] == "response.output_item.added"
+        assert payloads[1]["output_index"] == 3
+        completed = payloads[-1]["response"]
+        assert completed["id"] == "resp_live"
+        assert completed["model"] == "gpt-5.4-mini-2026-01-01"
+        assert completed["output"][0]["content"][0]["text"] == "Blocked by policy."
+        assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
+
+    def test_continuation_reads_usage_from_typed_completed_event(self):
+        from litellm.types.llms.openai import (
+            ResponseCompletedEvent,
+            ResponsesAPIResponse,
+            ResponsesAPIStreamEvents,
+        )
+
+        handler = OpenAIResponsesHandler()
+        original = [
+            ResponseCompletedEvent(
+                type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
+                response=ResponsesAPIResponse.model_validate(
+                    {
+                        "id": "resp_live",
+                        "created_at": 1,
+                        "model": "gpt-5.4-mini",
+                        "output": [],
+                        "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+                    }
+                ),
+            )
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=original), stream_started=True, responses_so_far=[]
+            )
+        )
+        completed = payloads[-1]["response"]
+        assert completed["usage"]["input_tokens"] == 7
+        assert completed["usage"]["output_tokens"] == 21
+        assert completed["usage"]["total_tokens"] == 28
+
+    def test_continuation_closes_open_item_given_pydantic_events_with_enum_types(self):
+        from litellm.types.llms.openai import (
+            BaseLiteLLMOpenAIResponseObject,
+            ContentPartAddedEvent,
+            OutputItemAddedEvent,
+            OutputTextDeltaEvent,
+            ResponsesAPIStreamEvents,
+        )
+
+        handler = OpenAIResponsesHandler()
+        open_item = GenericResponseOutputItem.model_validate(
+            {"type": "message", "id": "msg_live", "status": "in_progress", "role": "assistant", "content": []}
+        )
+        yielded = [
+            OutputItemAddedEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=0, item=open_item
+            ),
+            ContentPartAddedEvent(
+                type=ResponsesAPIStreamEvents.CONTENT_PART_ADDED,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                part=BaseLiteLLMOpenAIResponseObject.model_validate(
+                    {"type": "output_text", "text": "", "annotations": []}
+                ),
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                delta="partial ",
+            ),
+            OutputTextDeltaEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+                item_id="msg_live",
+                output_index=0,
+                content_index=0,
+                delta="text",
+            ),
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[:3] == [
+            "response.output_text.done",
+            "response.content_part.done",
+            "response.output_item.done",
+        ]
+        assert payloads[0]["text"] == "partial text"
+        assert payloads[2]["item"]["id"] == "msg_live"
+        assert payloads[2]["item"]["status"] == "completed"
+        assert payloads[2]["item"]["content"][0]["text"] == "partial text"
+        assert types[3] == "response.output_item.added"
+        assert payloads[3]["output_index"] == 1
+
+    def test_continuation_closes_open_function_call_as_incomplete(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini"}},
+            {
+                "type": "response.output_item.added",
+                "output_index": 0,
+                "item": {
+                    "id": "fc_live",
+                    "type": "function_call",
+                    "status": "in_progress",
+                    "call_id": "call_1",
+                    "name": "run_payment",
+                    "arguments": "",
+                },
+            },
+            {
+                "type": "response.function_call_arguments.delta",
+                "item_id": "fc_live",
+                "output_index": 0,
+                "delta": '{"amount": 100}',
+            },
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.output_item.done"
+        closed = payloads[0]["item"]
+        assert closed["id"] == "fc_live"
+        assert closed["type"] == "function_call"
+        assert closed["status"] == "incomplete"
+        assert closed["name"] == "run_payment"
+        assert "content" not in closed
+        assert types[1] == "response.output_item.added"
+        assert payloads[1]["output_index"] == 1
+        assert types[-1] == "response.completed"
+
+    def test_continuation_without_open_item_emits_no_closing_events(self):
+        handler = OpenAIResponsesHandler()
+        yielded = [
+            {"type": "response.created", "response": {"id": "resp_live", "model": "gpt-5.4-mini"}},
+            {"type": "response.in_progress", "response": {"id": "resp_live"}},
+        ]
+        payloads = self._payloads(
+            handler.build_block_sse_chunks(
+                self._exc(original_response=yielded), stream_started=True, responses_so_far=yielded
+            )
+        )
+        types = [payload["type"] for payload in payloads]
+        assert types[0] == "response.output_item.added"
+        assert types[-1] == "response.completed"
+        dones = [payload for payload in payloads if payload["type"] == "response.output_item.done"]
+        assert len(dones) == 1
+        assert dones[0]["item"]["content"][0]["text"] == "Blocked by policy."
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
index 1a90db7c1fe..b0ffd1845fe 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_transformation.py
@@ -220,6 +220,111 @@ class TestOpenAIResponsesAPIConfig:
 
         assert result["input"] == input_clean
 
+    def test_transform_drops_foreign_tool_call_item_ids(self):
+        """Replayed tool call items whose ids are not OpenAI-shaped (e.g.
+        Anthropic toolu_/srvtoolu_ ids after a router fallback) must be sent
+        without an id: OpenAI 400s foreign ids ("Expected an ID that begins
+        with 'fc'") but accepts the items with no id at all. Genuine fc_/ctc_
+        ids and non-tool-call items pass through untouched."""
+        replayed_input = [
+            {"role": "user", "content": [{"type": "input_text", "text": "hi"}]},
+            {
+                "type": "function_call",
+                "id": "toolu_01Foreign",
+                "call_id": "toolu_01Foreign",
+                "name": "get_weather",
+                "arguments": '{"city": "SF"}',
+            },
+            {"type": "function_call_output", "call_id": "toolu_01Foreign", "output": "sunny"},
+            {
+                "type": "custom_tool_call",
+                "id": "srvtoolu_01Foreign",
+                "call_id": "srvtoolu_01Foreign",
+                "name": "apply_patch",
+                "input": "patch",
+            },
+            {
+                "type": "function_call",
+                "id": "fc_genuine",
+                "call_id": "call_genuine",
+                "name": "get_weather",
+                "arguments": "{}",
+            },
+            {"type": "message", "id": "msg_1", "role": "assistant", "content": []},
+        ]
+
+        result = self.config.transform_responses_api_request(
+            model=self.model,
+            input=replayed_input,
+            response_api_optional_request_params={},
+            litellm_params={},
+            headers={},
+        )
+
+        assert "id" not in result["input"][1]
+        assert result["input"][1]["call_id"] == "toolu_01Foreign"
+        assert "id" not in result["input"][3]
+        assert result["input"][3]["call_id"] == "srvtoolu_01Foreign"
+        assert result["input"][4]["id"] == "fc_genuine"
+        assert result["input"][5]["id"] == "msg_1"
+        assert replayed_input[1]["id"] == "toolu_01Foreign"
+        assert replayed_input[3]["id"] == "srvtoolu_01Foreign"
+
+    def test_transform_keeps_foreign_tool_call_item_ids_for_other_providers(self):
+        """Providers reusing this config that do not enforce OpenAI's id
+        shapes must keep replayed ids untouched."""
+        from litellm.types.utils import LlmProviders
+
+        class _OpenRouterLikeConfig(OpenAIResponsesAPIConfig):
+            @property
+            def custom_llm_provider(self) -> LlmProviders:
+                return LlmProviders.OPENROUTER
+
+        replayed_input = [
+            {
+                "type": "function_call",
+                "id": "toolu_01Foreign",
+                "call_id": "toolu_01Foreign",
+                "name": "get_weather",
+                "arguments": "{}",
+            }
+        ]
+
+        result = _OpenRouterLikeConfig().transform_responses_api_request(
+            model="openrouter/some-model",
+            input=replayed_input,
+            response_api_optional_request_params={},
+            litellm_params={},
+            headers={},
+        )
+
+        assert result["input"][0]["id"] == "toolu_01Foreign"
+
+    def test_transform_compact_drops_foreign_tool_call_item_ids(self):
+        """The compact request path replays input the same way, so it must
+        apply the same id drop."""
+        replayed_input = [
+            {
+                "type": "function_call",
+                "id": "toolu_01Foreign",
+                "call_id": "toolu_01Foreign",
+                "name": "get_weather",
+                "arguments": "{}",
+            }
+        ]
+
+        _url, data = self.config.transform_compact_response_api_request(
+            model=self.model,
+            input=replayed_input,
+            response_api_optional_request_params={},
+            api_base="https://api.openai.com/v1/responses",
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert "id" not in data["input"][0]
+        assert data["input"][0]["call_id"] == "toolu_01Foreign"
+
     def test_transform_streaming_response(self):
         """Test streaming response transformation"""
         # Test with a text delta event
diff --git a/tests/test_litellm/llms/openai/test_openai_workload_identity.py b/tests/test_litellm/llms/openai/test_openai_workload_identity.py
new file mode 100644
index 00000000000..d8d9936e9a1
--- /dev/null
+++ b/tests/test_litellm/llms/openai/test_openai_workload_identity.py
@@ -0,0 +1,238 @@
+import json
+import sys
+from pathlib import Path
+from typing import Final
+
+import httpx
+import pytest
+import respx
+from openai import AsyncOpenAI, OpenAI
+
+import litellm
+from litellm.llms.litellm_proxy.responses.transformation import LiteLLMProxyResponsesAPIConfig
+from litellm.llms.openai.common_utils import BaseOpenAILLM, OpenAIError
+from litellm.llms.openai.openai import OpenAIChatCompletion
+from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
+from litellm.llms.openai.workload_identity import (
+    OpenAIWorkloadIdentityConfig,
+    _workload_identity_auth,
+    get_workload_identity_bearer_token,
+    resolve_openai_workload_identity_config,
+)
+from litellm.types.router import GenericLiteLLMParams
+
+TOKEN_EXCHANGE_URL: Final = "https://auth.openai.com/oauth/token"
+
+
+@pytest.fixture
+def wif_env(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> OpenAIWorkloadIdentityConfig:
+    token_file: Final = tmp_path / "subject_token.jwt"
+    token_file.write_text("subject-token-from-file")
+    monkeypatch.delenv("OPENAI_API_KEY", raising=False)
+    monkeypatch.delenv("OPENAI_BASE_URL", raising=False)
+    monkeypatch.delenv("OPENAI_API_BASE", raising=False)
+    monkeypatch.setattr(litellm, "api_base", None)
+    monkeypatch.setenv("OPENAI_IDENTITY_PROVIDER_ID", "idp_test123")
+    monkeypatch.setenv("OPENAI_SERVICE_ACCOUNT_ID", "user-test456")
+    monkeypatch.setenv("OPENAI_IDENTITY_TOKEN_FILE", str(token_file))
+    _workload_identity_auth.cache_clear()
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    return OpenAIWorkloadIdentityConfig(
+        identity_provider_id="idp_test123",
+        service_account_id="user-test456",
+        token_file=str(token_file),
+    )
+
+
+def mock_token_exchange(access_token: str = "exchanged-bearer-token") -> respx.Route:
+    return respx.post(TOKEN_EXCHANGE_URL).mock(
+        return_value=httpx.Response(200, json={"access_token": access_token, "expires_in": 3600})
+    )
+
+
+class TestResolveConfig:
+    def test_resolves_from_env(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) == wif_env
+
+    def test_static_api_key_wins(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        assert resolve_openai_workload_identity_config(api_key="sk-static", api_base=None) is None
+
+    def test_env_openai_api_key_wins(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        monkeypatch.setenv("OPENAI_API_KEY", "sk-from-env")
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) is None
+
+    @pytest.mark.parametrize("empty_key", ["", "   "])
+    def test_empty_api_key_arg_does_not_disable_wif(
+        self, wif_env: OpenAIWorkloadIdentityConfig, empty_key: str
+    ) -> None:
+        assert resolve_openai_workload_identity_config(api_key=empty_key, api_base=None) == wif_env
+
+    @pytest.mark.parametrize("empty_key", ["", "   "])
+    def test_empty_env_openai_api_key_does_not_disable_wif(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch, empty_key: str
+    ) -> None:
+        monkeypatch.setenv("OPENAI_API_KEY", empty_key)
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) == wif_env
+
+    def test_foreign_api_base_disables(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        assert resolve_openai_workload_identity_config(api_key=None, api_base="https://my-vllm.internal/v1") is None
+
+    def test_openai_api_base_allows(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        assert resolve_openai_workload_identity_config(api_key=None, api_base="https://api.openai.com/v1") == wif_env
+
+    def test_plaintext_http_api_base_disables(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        assert resolve_openai_workload_identity_config(api_key=None, api_base="http://api.openai.com/v1") is None
+
+    def test_foreign_env_base_url_disables(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        monkeypatch.setenv("OPENAI_BASE_URL", "https://my-vllm.internal/v1")
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) is None
+
+    def test_openai_env_base_url_allows(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        monkeypatch.setenv("OPENAI_BASE_URL", "https://api.openai.com/v1")
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) == wif_env
+
+    def test_foreign_litellm_api_base_disables(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        monkeypatch.setattr(litellm, "api_base", "https://my-vllm.internal/v1")
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) is None
+
+    @pytest.mark.parametrize(
+        "missing_var",
+        ["OPENAI_IDENTITY_PROVIDER_ID", "OPENAI_SERVICE_ACCOUNT_ID", "OPENAI_IDENTITY_TOKEN_FILE"],
+    )
+    def test_partial_env_disables(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch, missing_var: str
+    ) -> None:
+        monkeypatch.delenv(missing_var)
+        assert resolve_openai_workload_identity_config(api_key=None, api_base=None) is None
+
+
+class TestTokenExchange:
+    @respx.mock
+    def test_exchanges_subject_token_for_bearer(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        route: Final = mock_token_exchange()
+        assert get_workload_identity_bearer_token(wif_env) == "exchanged-bearer-token"
+        request_body: Final = json.loads(route.calls.last.request.content)
+        assert request_body["grant_type"] == "urn:ietf:params:oauth:grant-type:token-exchange"
+        assert request_body["subject_token"] == "subject-token-from-file"
+        assert request_body["subject_token_type"] == "urn:ietf:params:oauth:token-type:jwt"
+        assert request_body["identity_provider_id"] == "idp_test123"
+        assert request_body["service_account_id"] == "user-test456"
+
+    @respx.mock
+    def test_token_cached_across_mints(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        route: Final = mock_token_exchange()
+        first: Final = get_workload_identity_bearer_token(wif_env)
+        second: Final = get_workload_identity_bearer_token(wif_env)
+        assert first == second == "exchanged-bearer-token"
+        assert route.call_count == 1
+
+    def test_old_sdk_raises_upgrade_error(
+        self, wif_env: OpenAIWorkloadIdentityConfig, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        import openai as openai_module
+
+        monkeypatch.delattr(openai_module, "auth", raising=False)
+        monkeypatch.setitem(sys.modules, "openai.auth", None)
+        with pytest.raises(OpenAIError, match=r"openai>=2\.32\.0"):
+            wif_env.to_sdk_workload_identity()
+
+
+class TestClientConstruction:
+    def test_sync_client_uses_workload_identity(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        client: Final = OpenAIChatCompletion()._get_openai_client(is_async=False, api_key=None, api_base=None)
+        assert isinstance(client, OpenAI)
+        assert client.api_key == "workload-identity-auth"
+        assert client._workload_identity_auth is not None
+
+    def test_async_client_uses_workload_identity(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        client: Final = OpenAIChatCompletion()._get_openai_client(is_async=True, api_key=None, api_base=None)
+        assert isinstance(client, AsyncOpenAI)
+        assert client.api_key == "workload-identity-auth"
+        assert client._workload_identity_auth is not None
+
+    def test_static_key_client_unaffected(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        client: Final = OpenAIChatCompletion()._get_openai_client(is_async=False, api_key="sk-static", api_base=None)
+        assert isinstance(client, OpenAI)
+        assert client.api_key == "sk-static"
+        assert client._workload_identity_auth is None
+
+    def test_cache_key_separates_wif_identities(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        other_config: Final = OpenAIWorkloadIdentityConfig(
+            identity_provider_id="idp_other",
+            service_account_id="user-other",
+            token_file=wif_env.token_file,
+        )
+        keys: Final = tuple(
+            BaseOpenAILLM.get_openai_client_cache_key(
+                client_initialization_params={"api_key": None, "is_async": False, "workload_identity_config": config},
+                client_type="openai",
+            )
+            for config in (wif_env, other_config, None)
+        )
+        assert len(set(keys)) == 3
+
+    @respx.mock
+    def test_request_carries_exchanged_bearer(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        mock_token_exchange()
+        completion_route: Final = respx.post("https://api.openai.com/v1/chat/completions").mock(
+            return_value=httpx.Response(
+                200,
+                json={
+                    "id": "chatcmpl-wif",
+                    "object": "chat.completion",
+                    "created": 1,
+                    "model": "gpt-4o-mini",
+                    "choices": [
+                        {
+                            "index": 0,
+                            "message": {"role": "assistant", "content": "ok"},
+                            "finish_reason": "stop",
+                        }
+                    ],
+                    "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+                },
+            )
+        )
+        client = OpenAIChatCompletion()._get_openai_client(is_async=False, api_key=None, api_base=None)
+        assert isinstance(client, OpenAI)
+        client.chat.completions.create(model="gpt-4o-mini", messages=[{"role": "user", "content": "hi"}])
+        auth_header: Final = completion_route.calls.last.request.headers["Authorization"]
+        assert auth_header == "Bearer exchanged-bearer-token"
+
+
+class TestResponsesValidateEnvironment:
+    @respx.mock
+    def test_mints_bearer_when_wif_configured(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        mock_token_exchange()
+        headers: Final = OpenAIResponsesAPIConfig().validate_environment(
+            headers={}, model="gpt-4o-mini", litellm_params=GenericLiteLLMParams()
+        )
+        assert headers["Authorization"] == "Bearer exchanged-bearer-token"
+
+    def test_static_key_wins(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        headers: Final = OpenAIResponsesAPIConfig().validate_environment(
+            headers={}, model="gpt-4o-mini", litellm_params=GenericLiteLLMParams(api_key="sk-responses")
+        )
+        assert headers["Authorization"] == "Bearer sk-responses"
+
+    def test_foreign_api_base_skips_wif(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        headers: Final = OpenAIResponsesAPIConfig().validate_environment(
+            headers={},
+            model="gpt-4o-mini",
+            litellm_params=GenericLiteLLMParams(api_base="https://my-vllm.internal/v1"),
+        )
+        assert headers["Authorization"] == "Bearer None"
+
+    def test_litellm_proxy_subclass_never_mints_wif(self, wif_env: OpenAIWorkloadIdentityConfig) -> None:
+        headers: Final = LiteLLMProxyResponsesAPIConfig().validate_environment(
+            headers={}, model="gpt-4o-mini", litellm_params=GenericLiteLLMParams()
+        )
+        assert headers["Authorization"] == "Bearer None"
diff --git a/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py b/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py
index 9a6a039a470..67a56fdcd79 100644
--- a/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py
+++ b/tests/test_litellm/llms/openai_like/messages/test_openai_like_anthropic_messages_transformation.py
@@ -318,3 +318,203 @@ def test_json_provider_messages_config_probes_capabilities_under_provider_slug()
     )
     assert JSONProviderAnthropicMessagesConfig(provider).custom_llm_provider == "exampleprovider"
     assert OpenAILikeAnthropicMessagesConfig().custom_llm_provider == "anthropic"
+
+
+def _cache_control_request_params() -> tuple[list, dict]:
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "write a regex for a US phone number",
+                    "cache_control": {"type": "ephemeral", "ttl": "1h"},
+                }
+            ],
+        }
+    ]
+    optional_params = {
+        "max_tokens": 256,
+        "system": [
+            {
+                "type": "text",
+                "text": "You are Claude Code.",
+                "cache_control": {"type": "ephemeral", "ttl": "5m"},
+            }
+        ],
+        "tools": [
+            {
+                "name": "lookup",
+                "input_schema": {"type": "object"},
+                "cache_control": {"type": "ephemeral", "ttl": "1h"},
+            }
+        ],
+    }
+    return messages, optional_params
+
+
+def test_request_strips_cache_control_ttl_everywhere(config):
+    """Regression: Claude Code always sends ``cache_control: {type: ephemeral,
+    ttl: 1h}``, and strict non-Anthropic /v1/messages validators 400 the whole
+    request on the ttl extension (``cache_control.ttl: 1h is not supported``)."""
+    messages, optional_params = _cache_control_request_params()
+
+    payload = config.transform_anthropic_messages_request(
+        model="some-model",
+        messages=messages,
+        anthropic_messages_optional_request_params=optional_params,
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert payload["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral"}
+    assert payload["system"][0]["cache_control"] == {"type": "ephemeral"}
+    assert payload["tools"][0]["cache_control"] == {"type": "ephemeral"}
+    assert messages[0]["content"][0]["cache_control"] == {"type": "ephemeral", "ttl": "1h"}
+
+
+def test_request_defaults_missing_cache_control_type_and_drops_non_dict(config):
+    payload = config.transform_anthropic_messages_request(
+        model="some-model",
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "a", "cache_control": {"ttl": "1h"}},
+                    {"type": "text", "text": "b", "cache_control": None},
+                ],
+            }
+        ],
+        anthropic_messages_optional_request_params={"max_tokens": 64},
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    blocks = payload["messages"][0]["content"]
+    assert blocks[0]["cache_control"] == {"type": "ephemeral"}
+    assert "cache_control" not in blocks[1]
+
+
+def test_native_anthropic_config_keeps_cache_control_ttl():
+    """Anthropic itself accepts ttl, so the normalization must stay scoped to
+    the OpenAI-like passthrough and never reach the native Anthropic path."""
+    from litellm.llms.anthropic.experimental_pass_through.messages.transformation import (
+        AnthropicMessagesConfig,
+    )
+
+    messages, optional_params = _cache_control_request_params()
+    payload = AnthropicMessagesConfig().transform_anthropic_messages_request(
+        model="claude-sonnet-4-20250514",
+        messages=messages,
+        anthropic_messages_optional_request_params=optional_params,
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert payload["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral", "ttl": "1h"}
+    assert payload["system"][0]["cache_control"] == {"type": "ephemeral", "ttl": "5m"}
+
+
+def test_deployment_opt_in_keeps_cache_control_ttl():
+    config = OpenAILikeAnthropicMessagesConfig(cache_control_ttl=True)
+    payload = config.transform_anthropic_messages_request(
+        model="some-model",
+        messages=[
+            {
+                "role": "user",
+                "content": [{"type": "text", "text": "hi", "cache_control": {"type": "ephemeral", "ttl": "1h"}}],
+            }
+        ],
+        anthropic_messages_optional_request_params={"max_tokens": 16},
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+    assert payload["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral", "ttl": "1h"}
+
+
+def test_json_provider_constraint_opts_into_cache_control_ttl():
+    from litellm.llms.openai_like.json_loader import SimpleProviderConfig
+    from litellm.llms.openai_like.messages.transformation import (
+        JSONProviderAnthropicMessagesConfig,
+    )
+
+    base_data = {"base_url": "https://api.example.com/v1", "api_key_env": "EXAMPLE_API_KEY"}
+    strict = JSONProviderAnthropicMessagesConfig(SimpleProviderConfig(slug="strictprov", data=base_data))
+    lenient = JSONProviderAnthropicMessagesConfig(
+        SimpleProviderConfig(slug="lenientprov", data={**base_data, "constraints": {"cache_control_ttl": True}})
+    )
+
+    def transform(provider_config):
+        messages, optional_params = _cache_control_request_params()
+        return provider_config.transform_anthropic_messages_request(
+            model="some-model",
+            messages=messages,
+            anthropic_messages_optional_request_params=optional_params,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+    assert transform(strict)["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral"}
+    assert transform(lenient)["messages"][0]["content"][0]["cache_control"] == {"type": "ephemeral", "ttl": "1h"}
+
+
+def test_request_strips_ttl_only_where_the_messages_api_defines_cache_control(config):
+    """Regression: the sanitizer must only touch ``cache_control`` where the
+    Messages API defines it (request, system, tools, content blocks, tool_result
+    content), never application data such as ``tool_use.input`` or a tool's
+    ``input_schema`` that happens to contain a ``cache_control`` key."""
+    tool_input = {"cache_control": {"type": "ephemeral", "ttl": "1h"}, "query": "x"}
+    input_schema = {
+        "type": "object",
+        "properties": {"cache_control": {"type": "string", "ttl": "1h"}},
+    }
+    messages = [
+        {
+            "role": "assistant",
+            "content": [{"type": "tool_use", "id": "toolu_1", "name": "lookup", "input": tool_input}],
+        },
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "tool_result",
+                    "tool_use_id": "toolu_1",
+                    "cache_control": {"type": "ephemeral", "ttl": "1h"},
+                    "content": [
+                        {"type": "text", "text": "result", "cache_control": {"type": "ephemeral", "ttl": "1h"}}
+                    ],
+                },
+                {"type": "text", "text": "plain string content stays", "cache_control": {"ttl": "1h"}},
+            ],
+        },
+        {"role": "user", "content": "a plain string message"},
+    ]
+    optional_params = {
+        "max_tokens": 64,
+        "cache_control": {"type": "ephemeral", "ttl": "1h"},
+        "tools": [
+            {
+                "name": "lookup",
+                "input_schema": input_schema,
+                "cache_control": {"type": "ephemeral", "ttl": "1h"},
+            }
+        ],
+    }
+
+    payload = config.transform_anthropic_messages_request(
+        model="some-model",
+        messages=messages,
+        anthropic_messages_optional_request_params=optional_params,
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert payload["cache_control"] == {"type": "ephemeral"}
+    assert payload["tools"][0]["cache_control"] == {"type": "ephemeral"}
+    assert payload["tools"][0]["input_schema"] == input_schema
+    assert payload["messages"][0]["content"][0]["input"] == tool_input
+    tool_result = payload["messages"][1]["content"][0]
+    assert tool_result["cache_control"] == {"type": "ephemeral"}
+    assert tool_result["content"][0]["cache_control"] == {"type": "ephemeral"}
+    assert payload["messages"][1]["content"][1]["cache_control"] == {"type": "ephemeral"}
+    assert payload["messages"][2] == {"role": "user", "content": "a plain string message"}
diff --git a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
index 8a9ae4dae6d..62b4d003b45 100644
--- a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
+++ b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search.py
@@ -2,6 +2,7 @@
 Tests for Parallel AI Search API integration (v1 endpoint).
 """
 
+import json
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
@@ -30,13 +31,41 @@ MOCK_V1_RESPONSE = {
 }
 
 
-def _mock_response():
+def _mock_response(payload=None):
     mock_response = MagicMock()
     mock_response.status_code = 200
-    mock_response.json.return_value = MOCK_V1_RESPONSE
+    mock_response.json.return_value = payload if payload is not None else MOCK_V1_RESPONSE
     return mock_response
 
 
+@pytest.fixture
+def httpx_transport(monkeypatch):
+    monkeypatch.setattr(  # test-quality-ok: respx needs HTTPX enabled to fake the provider HTTP boundary.
+        litellm,
+        "disable_aiohttp_transport",
+        True,
+    )
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    yield
+    litellm.in_memory_llm_clients_cache.flush_cache()
+
+
+@pytest.fixture
+def bundled_cost_map(monkeypatch):
+    """Price lookups against the bundled cost map.
+
+    litellm caches model-info lookups, so swapping ``model_cost`` only takes
+    effect once those caches are invalidated -- on the way in and back out.
+    """
+    from litellm.utils import _invalidate_model_cost_lowercase_map
+
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    _invalidate_model_cost_lowercase_map()
+    yield
+    monkeypatch.undo()
+    _invalidate_model_cost_lowercase_map()
+
+
 class TestParallelAISearch:
     @pytest.fixture(autouse=True)
     def _set_api_key(self, monkeypatch):
@@ -135,9 +164,7 @@ class TestParallelAISearch:
             json_data = mock_post.call_args.kwargs.get("json")
             assert json_data["mode"] == "basic"
 
-    @pytest.mark.parametrize(
-        "processor,expected_mode", [("base", "basic"), ("pro", "advanced")]
-    )
+    @pytest.mark.parametrize("processor,expected_mode", [("base", "basic"), ("pro", "advanced")])
     @pytest.mark.asyncio
     async def test_legacy_processor_maps_to_mode(self, processor, expected_mode):
         with patch(
@@ -222,9 +249,7 @@ class TestParallelAISearch:
                 "arxiv.org",
                 "nature.com",
             ]
-            assert advanced_settings["source_policy"]["exclude_domains"] == [
-                "reddit.com"
-            ]
+            assert advanced_settings["source_policy"]["exclude_domains"] == ["reddit.com"]
             assert advanced_settings["excerpt_settings"]["max_chars_per_result"] == 1500
 
             assert "max_results" not in json_data
@@ -306,10 +331,7 @@ class TestParallelAISearch:
             )
 
             call_args = mock_post.call_args
-            assert (
-                call_args.kwargs["url"]
-                == "https://proxy.internal.example.com/v1/search"
-            )
+            assert call_args.kwargs["url"] == "https://proxy.internal.example.com/v1/search"
 
     @pytest.mark.asyncio
     async def test_caller_api_base_without_key_is_refused(self, monkeypatch):
@@ -338,3 +360,147 @@ class TestParallelAISearch:
                 query="AI developments",
                 search_provider="parallel_ai",
             )
+
+    @pytest.mark.asyncio
+    async def test_flat_source_and_fetch_params_nest_under_advanced_settings(self, respx_mock, httpx_transport):
+        route = respx_mock.post("https://api.parallel.ai/v1/search").respond(json=MOCK_V1_RESPONSE)
+
+        await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            objective="find peer-reviewed AI research",
+            include_domains=["arxiv.org"],
+            after_date="2026-01-01",
+            location="gb",
+            fetch_policy={"max_age_seconds": 600, "disable_cache_fallback": True},
+            client_model="claude-fable-5",
+        )
+
+        json_data = json.loads(route.calls[0].request.content)
+        assert json_data["objective"] == "find peer-reviewed AI research"
+        assert json_data["client_model"] == "claude-fable-5"
+
+        advanced_settings = json_data["advanced_settings"]
+        assert advanced_settings["location"] == "gb"
+        assert advanced_settings["fetch_policy"] == {
+            "max_age_seconds": 600,
+            "disable_cache_fallback": True,
+        }
+        assert advanced_settings["source_policy"]["include_domains"] == ["arxiv.org"]
+        assert advanced_settings["source_policy"]["after_date"] == "2026-01-01"
+
+        assert "include_domains" not in json_data
+        assert "after_date" not in json_data
+        assert "location" not in json_data
+        assert "fetch_policy" not in json_data
+
+    @pytest.mark.asyncio
+    async def test_response_preserves_raw_parallel_fields(self, respx_mock, httpx_transport):
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=MOCK_V1_RESPONSE)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+        )
+
+        dumped = response.model_dump()
+        assert dumped["search_id"] == "search_abc123"
+        assert dumped["session_id"] == "session_xyz"
+        assert dumped["parallel_usage"] == [{"name": "search_advanced", "count": 1}]
+
+        first = response.results[0].model_dump()
+        assert first["excerpts"] == ["First excerpt.", "Second excerpt."]
+
+    @pytest.mark.asyncio
+    async def test_response_normalizes_null_result_fields(self, respx_mock, httpx_transport):
+        response_payload = {
+            **MOCK_V1_RESPONSE,
+            "results": [{"url": None, "title": None, "publish_date": None, "excerpts": None}],
+        }
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+        )
+
+        assert len(response.results) == 1
+        result = response.results[0]
+        assert result.url == ""
+        assert result.title == ""
+        assert result.snippet == ""
+        assert result.date is None
+        assert result.model_dump()["excerpts"] == ()
+
+    @pytest.mark.parametrize(
+        "mode,usage,max_results,expected_cost",
+        [
+            ("turbo", [{"name": "sku_search", "count": 1}], None, 0.001),
+            ("fast", [{"name": "sku_search", "count": 1}], None, 0.001),
+            ("basic", [{"name": "sku_search", "count": 1}], None, 0.005),
+            ("advanced", [{"name": "sku_search", "count": 1}], None, 0.005),
+            (
+                "basic",
+                [
+                    {"name": "sku_search", "count": 1},
+                    {"name": "sku_search_additional_results", "count": 2},
+                ],
+                20,
+                0.007,
+            ),
+            ("basic", None, 20, 0.015),
+        ],
+    )
+    @pytest.mark.asyncio
+    async def test_search_cost_uses_mode_and_provider_usage(
+        self, mode, usage, max_results, expected_cost, bundled_cost_map, respx_mock, httpx_transport
+    ):
+        response_payload = {**MOCK_V1_RESPONSE, "usage": usage}
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            mode=mode,
+            max_results=max_results,
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(expected_cost)
+
+    @pytest.mark.asyncio
+    async def test_search_cost_treats_keyword_queries_as_one_request(
+        self, bundled_cost_map, respx_mock, httpx_transport
+    ):
+        response_payload = {
+            **MOCK_V1_RESPONSE,
+            "usage": [{"name": "sku_search", "count": 1}],
+        }
+        respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query=["AI developments", "machine learning trends"],
+            search_provider="parallel_ai",
+            mode="basic",
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(0.005)
+
+    @pytest.mark.asyncio
+    async def test_caller_cannot_supply_provider_usage(self, bundled_cost_map, respx_mock, httpx_transport):
+        """`_parallel_ai_usage` prices the request, so a caller must not be able to set it.
+
+        The provider reports no usage here, which is the case where a caller-supplied
+        value would otherwise survive into the cost calculation.
+        """
+        response_payload = {k: v for k, v in MOCK_V1_RESPONSE.items() if k != "usage"}
+        route = respx_mock.post("https://api.parallel.ai/v1/search").respond(json=response_payload)
+
+        response = await litellm.asearch(
+            query="AI developments",
+            search_provider="parallel_ai",
+            mode="basic",
+            _parallel_ai_usage=[{"name": "sku_search", "count": 0}],
+        )
+
+        assert response._hidden_params["response_cost"] == pytest.approx(0.005)
+        assert "_parallel_ai_usage" not in json.loads(route.calls[0].request.content)
diff --git a/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py
new file mode 100644
index 00000000000..72c69fc622c
--- /dev/null
+++ b/tests/test_litellm/llms/parallel_ai/test_parallel_ai_search_gateway.py
@@ -0,0 +1,191 @@
+"""Gateway coverage for Parallel AI Search."""
+
+from __future__ import annotations
+
+from collections.abc import Iterator
+from typing import Final
+from unittest.mock import AsyncMock
+
+import httpx
+import pytest
+from fastapi.testclient import TestClient
+
+import litellm
+from litellm import Router
+from litellm.integrations.websearch_interception.handler import (
+    WebSearchInterceptionLogger,
+)
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+from litellm.proxy import proxy_server
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+from litellm.types.utils import LlmProviders
+
+PARALLEL_SEARCH_URL: Final = "https://api.parallel.ai/v1/search"
+
+
+@pytest.fixture
+def client() -> TestClient:
+    return TestClient(proxy_server.app, raise_server_exceptions=False)
+
+
+@pytest.fixture
+def auth_as() -> Iterator[None]:
+    async def _authorized_request() -> UserAPIKeyAuth:
+        return UserAPIKeyAuth(
+            api_key="hashed-sk-test",
+            user_id="parallel-test-user",
+        )
+
+    previous: Final = proxy_server.app.dependency_overrides.get(user_api_key_auth)
+    proxy_server.app.dependency_overrides[user_api_key_auth] = _authorized_request
+    try:
+        yield
+    finally:
+        if previous is None:
+            proxy_server.app.dependency_overrides.pop(user_api_key_auth, None)
+        else:
+            proxy_server.app.dependency_overrides[user_api_key_auth] = previous
+
+
+def _parallel_search_body() -> dict[str, object]:
+    return {
+        "search_id": "search_parallel_gateway",
+        "results": [
+            {
+                "url": "https://example.com/parallel",
+                "title": "Parallel result",
+                "publish_date": "2026-08-13",
+                "excerpts": ["First excerpt", "Second excerpt"],
+            }
+        ],
+        "usage": [{"name": "sku_search", "count": 1}],
+    }
+
+
+def _parallel_router(mode: str = "turbo") -> Router:
+    return Router(
+        model_list=[],
+        search_tools=[
+            {
+                "search_tool_name": "parallel-search",
+                "litellm_params": {
+                    "search_provider": "parallel_ai",
+                    "api_key": "parallel-search-key",
+                    "mode": mode,
+                },
+            }
+        ],
+        num_retries=0,
+    )
+
+
+def _mock_async_post(
+    monkeypatch,
+    *,
+    url: str,
+    response_body: dict[str, object],
+) -> AsyncMock:
+    response = httpx.Response(
+        status_code=200,
+        json=response_body,
+        request=httpx.Request("POST", url),
+    )
+    mock_post = AsyncMock(return_value=response)
+    monkeypatch.setattr(AsyncHTTPHandler, "post", mock_post)
+    return mock_post
+
+
+def test_parallel_search_gateway_route(client, auth_as, monkeypatch):
+    """The named search route selects its configured Parallel Search tool.
+
+    The tool-level `mode` must survive the router hop, so the upstream request
+    is sent as `turbo` rather than falling back to the adapter default.
+    """
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    monkeypatch.setattr(proxy_server, "llm_router", _parallel_router())
+    mock_post = _mock_async_post(
+        monkeypatch,
+        url=PARALLEL_SEARCH_URL,
+        response_body=_parallel_search_body(),
+    )
+
+    response = client.post(
+        "/v1/search/parallel-search",
+        json={"query": "Parallel AI news", "max_results": 3},
+    )
+
+    assert response.status_code == 200, response.text
+    assert response.json()["results"] == [
+        {
+            "title": "Parallel result",
+            "url": "https://example.com/parallel",
+            "snippet": "First excerpt ... Second excerpt",
+            "date": "2026-08-13",
+            "last_updated": None,
+            "excerpts": ["First excerpt", "Second excerpt"],
+        }
+    ]
+
+    request_kwargs = mock_post.await_args.kwargs
+    assert request_kwargs["url"] == PARALLEL_SEARCH_URL
+    assert request_kwargs["headers"]["x-api-key"] == "parallel-search-key"
+    assert request_kwargs["json"] == {
+        "objective": "Parallel AI news",
+        "search_queries": ["Parallel AI news"],
+        "mode": "turbo",
+        "advanced_settings": {"max_results": 3},
+    }
+
+
+@pytest.mark.asyncio
+async def test_web_search_interception_executes_parallel_search(monkeypatch):
+    """An intercepted web-search call uses the configured Parallel Search tool."""
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    monkeypatch.setattr(proxy_server, "llm_router", _parallel_router(mode="fast"))
+    mock_post = _mock_async_post(
+        monkeypatch,
+        url=PARALLEL_SEARCH_URL,
+        response_body=_parallel_search_body(),
+    )
+    logger = WebSearchInterceptionLogger(
+        enabled_providers=[LlmProviders.OPENAI],
+        search_tool_name="parallel-search",
+    )
+
+    plan = await logger.async_build_responses_agentic_loop_plan(
+        tools={
+            "tool_calls": [
+                {
+                    "id": "fc_parallel",
+                    "call_id": "fc_parallel",
+                    "type": "function_call",
+                    "name": "litellm_web_search",
+                    "arguments": '{"query":"Parallel AI news"}',
+                    "input": {"query": "Parallel AI news"},
+                }
+            ]
+        },
+        model="gpt-5",
+        messages=[{"role": "user", "content": "Research Parallel"}],
+        response=None,
+        optional_params={"tools": [{"type": "function", "name": "litellm_web_search"}]},
+        logging_obj=None,
+        stream=False,
+        kwargs={"custom_llm_provider": "openai"},
+    )
+
+    assert plan.run_agentic_loop is True
+    assert plan.request_patch is not None
+    assert plan.request_patch.messages[-1] == {
+        "type": "function_call_output",
+        "call_id": "fc_parallel",
+        "output": (
+            "Title: Parallel result\nURL: https://example.com/parallel\nSnippet: First excerpt ... Second excerpt"
+        ),
+    }
+
+    request_kwargs = mock_post.await_args.kwargs
+    assert request_kwargs["url"] == PARALLEL_SEARCH_URL
+    assert request_kwargs["headers"]["x-api-key"] == "parallel-search-key"
+    assert request_kwargs["json"]["mode"] == "fast"
diff --git a/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py b/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
index 7085e45cdc3..4b58d220623 100644
--- a/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
+++ b/tests/test_litellm/llms/s3_vectors/vector_stores/test_s3_vectors_transformation.py
@@ -1,4 +1,4 @@
-from unittest.mock import MagicMock, Mock
+from unittest.mock import AsyncMock, MagicMock, Mock, patch
 
 import httpx
 import pytest
@@ -9,6 +9,18 @@ from litellm.llms.s3_vectors.vector_stores.transformation import (
 from litellm.types.vector_stores import VectorStoreSearchResponse
 
 
+def _mock_router(model_names, sync=False):
+    """Router mock serving the given embedding model names."""
+    router = MagicMock()
+    router.get_model_list.return_value = [{"model_name": name} for name in model_names]
+    embedding_response = Mock(data=[{"embedding": [0.1, 0.2, 0.3]}])
+    if sync:
+        router.embedding = MagicMock(return_value=embedding_response)
+    else:
+        router.aembedding = AsyncMock(return_value=embedding_response)
+    return router
+
+
 class TestS3VectorsVectorStoreConfig:
     def test_init(self):
         """Test that S3VectorsVectorStoreConfig initializes correctly"""
@@ -28,19 +40,174 @@ class TestS3VectorsVectorStoreConfig:
         url = config.get_complete_url(None, litellm_params)
         assert url == "https://s3vectors.us-west-2.api.aws"
 
-    def test_get_complete_url_missing_region(self):
-        """Test that missing region raises error"""
+    def test_get_complete_url_missing_region(self, monkeypatch):
+        """Missing region falls back to the default region (parity with ingestion)"""
+        monkeypatch.delenv("AWS_REGION_NAME", raising=False)
+        monkeypatch.delenv("AWS_REGION", raising=False)
         config = S3VectorsVectorStoreConfig()
-        litellm_params = {}
-        with pytest.raises(ValueError, match="aws_region_name is required"):
-            config.get_complete_url(None, litellm_params)
+        url = config.get_complete_url(None, {})
+        assert url == "https://s3vectors.us-west-2.api.aws"
+
+    def test_get_complete_url_uses_env_region(self, monkeypatch):
+        """Missing region param resolves from AWS_REGION_NAME env var"""
+        monkeypatch.setenv("AWS_REGION_NAME", "eu-west-1")
+        monkeypatch.delenv("AWS_REGION", raising=False)
+        config = S3VectorsVectorStoreConfig()
+        url = config.get_complete_url(None, {})
+        assert url == "https://s3vectors.eu-west-1.api.aws"
+
+    def test_get_complete_url_invalid_region_format(self):
+        """Invalid region format raises"""
+        config = S3VectorsVectorStoreConfig()
+        with pytest.raises(ValueError, match="Invalid AWS region format"):
+            config.get_complete_url(None, {"aws_region_name": "Bad_Region!"})
 
-    @pytest.mark.skip(reason="Requires embedding API call, tested in integration tests")
     def test_transform_search_request(self):
-        """Test search request transformation"""
-        # This test requires making an actual embedding API call
-        # It's better tested in integration tests
-        pass
+        """Full request-body transformation with a router-injected embedding"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["text-embedding-3-small"], sync=True)
+
+        url, request_body = config.transform_search_vector_store_request(
+            vector_store_id="test-bucket:test-index",
+            query="test query",
+            vector_store_search_optional_params={"max_num_results": 7},
+            api_base="https://s3vectors.us-west-2.api.aws",
+            litellm_logging_obj=mock_logging_obj,
+            litellm_params={},
+            extra_body=None,
+            router=router,
+        )
+
+        assert url == "https://s3vectors.us-west-2.api.aws/QueryVectors"
+        assert request_body == {
+            "vectorBucketName": "test-bucket",
+            "indexName": "test-index",
+            "queryVector": {"float32": [0.1, 0.2, 0.3]},
+            "topK": 7,
+            "returnDistance": True,
+            "returnMetadata": True,
+        }
+        assert mock_logging_obj.model_call_details["query"] == "test query"
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_uses_router_for_virtual_model(self):
+        """Regression: router-served embedding models must resolve via the router,
+        not a bare litellm.aembedding call (which has no deployment credentials)."""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["my-embedding-model"])
+
+        with patch("litellm.aembedding", new=AsyncMock()) as mock_bare_aembedding:  # test-quality-ok: guards that the bare-embedding path is not taken; dispatch seam is the behavior under test
+            url, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "my-embedding-model"},
+                extra_body=None,
+                router=router,
+            )
+
+        router.aembedding.assert_awaited_once_with(model="my-embedding-model", input=["test query"])
+        mock_bare_aembedding.assert_not_awaited()
+        assert request_body["queryVector"]["float32"] == [0.1, 0.2, 0.3]
+        assert request_body["topK"] == 5  # default
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_falls_back_when_router_does_not_serve_model(self):
+        """Router present but embedding_model is not a router deployment ->
+        bare litellm.aembedding keeps working (provider-prefixed + env creds stores)."""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["some-other-model"])
+
+        mock_bare = AsyncMock(return_value=Mock(data=[{"embedding": [0.4, 0.5]}]))
+        with patch("litellm.aembedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "azure/text-embedding-3-small"},
+                extra_body=None,
+                router=router,
+            )
+
+        mock_bare.assert_awaited_once_with(model="azure/text-embedding-3-small", input=["test query"])
+        router.aembedding.assert_not_awaited()
+        assert request_body["queryVector"]["float32"] == [0.4, 0.5]
+
+    @pytest.mark.asyncio
+    async def test_atransform_search_without_router_uses_bare_embedding(self):
+        """Backward compat: no router -> bare litellm.aembedding as before"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+
+        mock_bare = AsyncMock(return_value=Mock(data=[{"embedding": [0.6, 0.7]}]))
+        with patch("litellm.aembedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = await config.atransform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={},
+                extra_body=None,
+            )
+
+        mock_bare.assert_awaited_once_with(model="text-embedding-3-small", input=["test query"])
+        assert request_body["queryVector"]["float32"] == [0.6, 0.7]
+
+    def test_transform_search_uses_router_for_virtual_model_sync(self):
+        """Sync twin: router-served embedding model resolves via router.embedding"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+        router = _mock_router(["my-embedding-model"], sync=True)
+
+        with patch("litellm.embedding", new=MagicMock()) as mock_bare_embedding:  # test-quality-ok: guards that the bare-embedding path is not taken; dispatch seam is the behavior under test
+            _, request_body = config.transform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={"embedding_model": "my-embedding-model"},
+                extra_body=None,
+                router=router,
+            )
+
+        router.embedding.assert_called_once_with(model="my-embedding-model", input=["test query"])
+        mock_bare_embedding.assert_not_called()
+        assert request_body["queryVector"]["float32"] == [0.1, 0.2, 0.3]
+
+    def test_transform_search_without_router_uses_bare_embedding_sync(self):
+        """Sync twin: no router -> bare litellm.embedding as before"""
+        config = S3VectorsVectorStoreConfig()
+        mock_logging_obj = Mock()
+        mock_logging_obj.model_call_details = {}
+
+        mock_bare = MagicMock(return_value=Mock(data=[{"embedding": [0.8, 0.9]}]))
+        with patch("litellm.embedding", new=mock_bare):  # test-quality-ok: stubs the bare-embedding fallback whose request body the test asserts on
+            _, request_body = config.transform_search_vector_store_request(
+                vector_store_id="test-bucket:test-index",
+                query="test query",
+                vector_store_search_optional_params={},
+                api_base="https://s3vectors.us-west-2.api.aws",
+                litellm_logging_obj=mock_logging_obj,
+                litellm_params={},
+                extra_body=None,
+            )
+
+        mock_bare.assert_called_once_with(model="text-embedding-3-small", input=["test query"])
+        assert request_body["queryVector"]["float32"] == [0.8, 0.9]
 
     def test_transform_search_request_invalid_vector_store_id(self):
         """Test that invalid vector_store_id format raises error"""
diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
index 8c1de12e7d9..4679b978f78 100644
--- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_ai_gemini_transformation.py
@@ -1096,10 +1096,13 @@ def test_natively_signed_parallel_turn_never_carries_a_placeholder(model):
         "gemini-3.5-flash",
         "gemini-3.6-flash",
         "gemini-3.7-flash",
+        "gemini-3.8-flash",
         "vertex_ai/gemini-3.5-flash",
         "vertex_ai/gemini-3.7-flash",
+        "vertex_ai/gemini-3.8-flash",
         "gemini/gemini-3.5-flash",
         "gemini/gemini-3.7-flash",
+        "gemini/gemini-3.8-flash",
     ],
 )
 def test_placeholder_scoped_to_first_call_across_gemini_3_variants(model):
diff --git a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
index bd07bec900f..d2788408e09 100644
--- a/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
+++ b/tests/test_litellm/llms/vertex_ai/gemini/test_vertex_and_google_ai_studio_gemini.py
@@ -1185,6 +1185,18 @@ def test_vertex_ai_map_thinking_param_with_budget_tokens_0():
     }
 
 
+def test_vertex_ai_map_thinking_param_without_budget_tokens_for_gemini_3():
+    v = VertexGeminiConfig()
+    result = v.map_openai_params(
+        non_default_params={"thinking": {"type": "enabled"}},
+        optional_params={},
+        model="gemini-3.5-flash",
+        drop_params=False,
+    )
+
+    assert result["thinkingConfig"] == {"includeThoughts": True}
+
+
 def test_vertex_ai_map_tools():
     v = VertexGeminiConfig()
     optional_params = {}
diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
index cc923f05831..d1d751989ea 100644
--- a/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
+++ b/tests/test_litellm/llms/vertex_ai/test_vertex_ai_common_utils.py
@@ -195,6 +195,22 @@ def test_set_schema_property_ordering_with_excessive_nesting():
         set_schema_property_ordering(schema)
 
 
+def test_set_schema_property_ordering_skips_non_dict_property_values():
+    """Non-dict property values must be skipped, not recursed into (they used to raise)."""
+    schema = {
+        "properties": {
+            "a": "hello",
+            "b": {"type": "string"},
+            "c": ["x"],
+            "d": "a string mentioning items",
+        }
+    }
+
+    result = set_schema_property_ordering(schema)
+
+    assert result["propertyOrdering"] == ["a", "b", "c", "d"]
+
+
 def test_build_vertex_schema():
     """Test build_vertex_schema with a sample schema"""
     from litellm.llms.vertex_ai.common_utils import _build_vertex_schema
diff --git a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py
index 29d22e844a5..a4d67606698 100644
--- a/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py
+++ b/tests/test_litellm/llms/vertex_ai/test_vertex_llm_base.py
@@ -982,6 +982,116 @@ class TestVertexBase:
 
         assert result_url == f"{gateway_api_base}:embedContent"
 
+    def test_check_custom_proxy_vertex_api_base_with_version_path_grafts_default_path(self):
+        vertex_base = VertexBase()
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base="https://aiplatform.googleapis.com/v1beta1",
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="generateContent",
+            stream=None,
+            auth_header="Bearer token123",
+            url="https://us-central1-aiplatform.googleapis.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent",
+            model="gemini-3.5-flash-lite",
+        )
+
+        assert (
+            result_url
+            == "https://aiplatform.googleapis.com/v1beta1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent"
+        )
+
+    def test_check_custom_proxy_vertex_api_base_with_version_path_trailing_slash_grafts_default_path(self):
+        vertex_base = VertexBase()
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base="https://internal-gateway.example.com/v1/",
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="generateContent",
+            stream=None,
+            auth_header="Bearer token123",
+            url="https://us-central1-aiplatform.googleapis.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent",
+            model="gemini-3.5-flash-lite",
+        )
+
+        assert (
+            result_url
+            == "https://internal-gateway.example.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent"
+        )
+
+    def test_check_custom_proxy_vertex_api_base_with_version_path_and_query_grafts_before_query(self):
+        vertex_base = VertexBase()
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base="https://internal-gateway.example.com/v1beta1?key=abc",
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="generateContent",
+            stream=None,
+            auth_header="Bearer token123",
+            url="https://us-central1-aiplatform.googleapis.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent",
+            model="gemini-3.5-flash-lite",
+        )
+
+        assert (
+            result_url
+            == "https://internal-gateway.example.com/v1beta1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent?key=abc"
+        )
+
+    def test_check_custom_proxy_vertex_api_base_with_version_path_and_query_streaming_appends_alt_sse(self):
+        vertex_base = VertexBase()
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base="https://internal-gateway.example.com/v1beta1?key=abc",
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="streamGenerateContent",
+            stream=True,
+            auth_header="Bearer token123",
+            url="https://us-central1-aiplatform.googleapis.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:streamGenerateContent",
+            model="gemini-3.5-flash-lite",
+        )
+
+        assert (
+            result_url
+            == "https://internal-gateway.example.com/v1beta1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:streamGenerateContent?key=abc&alt=sse"
+        )
+
+    def test_check_custom_proxy_vertex_api_base_with_non_version_path_keeps_endpoint_append(self):
+        vertex_base = VertexBase()
+        gateway_api_base = "https://gateway.example.com/vertex-proxy"
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base=gateway_api_base,
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="generateContent",
+            stream=None,
+            auth_header="Bearer token123",
+            url="https://us-central1-aiplatform.googleapis.com/v1/projects/test-project/locations/us-central1/publishers/google/models/gemini-3.5-flash-lite:generateContent",
+            model="gemini-3.5-flash-lite",
+        )
+
+        assert result_url == f"{gateway_api_base}:generateContent"
+
+    def test_check_custom_proxy_vertex_api_base_without_projects_in_default_url_keeps_endpoint_append(self):
+        vertex_base = VertexBase()
+        gemma_api_base = "https://example.com/custom/gemma-deployment"
+
+        _, result_url = vertex_base._check_custom_proxy(
+            api_base=gemma_api_base,
+            custom_llm_provider="vertex_ai",
+            gemini_api_key=None,
+            endpoint="predict",
+            stream=False,
+            auth_header=None,
+            url=gemma_api_base,
+            model="gemma-3-27b-it",
+        )
+
+        assert result_url == f"{gemma_api_base}:predict"
+
     def test_check_custom_proxy_vertex_bare_host_streaming_keeps_single_alt_sse(self):
         vertex_base = VertexBase()
 
diff --git a/tests/test_litellm/llms/vertex_ai/text_to_speech/test_transformation.py b/tests/test_litellm/llms/vertex_ai/text_to_speech/test_transformation.py
index 05da22a73fd..fba337b5f2c 100644
--- a/tests/test_litellm/llms/vertex_ai/text_to_speech/test_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/text_to_speech/test_transformation.py
@@ -1,3 +1,4 @@
+import base64
 from unittest.mock import MagicMock, Mock, patch
 
 import httpx
@@ -126,6 +127,48 @@ class TestVertexAITextToSpeechConfig:
         assert voice_dict == voice_input
 
 
+@pytest.mark.parametrize(
+    ("audio", "expected_content_type"),
+    [
+        (b"RIFF\x24\x00\x00\x00WAVEfmt \x10\x00\x00\x00", "audio/wav"),
+        (b"\xff\xfb\x90\x64\x00\x00\x00\x00", "audio/mpeg"),
+        (b"OggS" + b"\x00" * 24 + b"OpusHead", "audio/opus"),
+        (b"fLaC\x00\x00\x00\x22", "audio/flac"),
+    ],
+)
+def test_transform_text_to_speech_response_labels_content_type(audio, expected_content_type):
+    raw_response = httpx.Response(
+        status_code=200,
+        json={"audioContent": base64.b64encode(audio).decode()},
+    )
+
+    result = VertexAITextToSpeechConfig().transform_text_to_speech_response(
+        model="vertex_ai/chirp",
+        raw_response=raw_response,
+        logging_obj=MagicMock(),
+    )
+
+    assert result.response.headers["content-type"] == expected_content_type
+    assert result.response.content == audio
+
+
+def test_transform_text_to_speech_response_leaves_unknown_bytes_unlabeled():
+    raw_pcm = b"\x00\x01\x02\x03\x04\x05\x06\x07"
+    raw_response = httpx.Response(
+        status_code=200,
+        json={"audioContent": base64.b64encode(raw_pcm).decode()},
+    )
+
+    result = VertexAITextToSpeechConfig().transform_text_to_speech_response(
+        model="vertex_ai/chirp",
+        raw_response=raw_response,
+        logging_obj=MagicMock(),
+    )
+
+    assert "content-type" not in result.response.headers
+    assert result.response.content == raw_pcm
+
+
 @patch("litellm.llms.custom_httpx.llm_http_handler.HTTPHandler.post")
 @patch.object(VertexAITextToSpeechConfig, "_ensure_access_token")
 @patch.object(VertexAITextToSpeechConfig, "_get_token_and_url")
diff --git a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
index 552ca98441f..a57672cfbfb 100644
--- a/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
+++ b/tests/test_litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/test_vertex_ai_partner_models_anthropic_transformation.py
@@ -727,3 +727,51 @@ def test_sanitize_strips_effort_for_haiku_45():
     data = {"output_config": {"effort": "high"}}
     sanitize_vertex_anthropic_output_params(data, "vertex_ai/claude-opus-4-6")
     assert data["output_config"] == {"effort": "high"}
+
+
+def test_vertex_ai_fable_5_1_response_format_uses_native_output_format(local_model_cost_map):
+    """Regression: Fable 5.1 rejects forced tool use, so the vertex map entry
+    advertises native structured output and ``response_format`` must map to
+    ``output_format`` instead of the tool-based path's forced tool_choice."""
+    config = VertexAIAnthropicConfig()
+    response_format = {
+        "type": "json_schema",
+        "json_schema": {
+            "name": "test_schema",
+            "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+        },
+    }
+
+    result_params = config.map_openai_params(
+        non_default_params={"response_format": response_format},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=False,
+    )
+
+    assert "output_format" in result_params
+    assert "tool_choice" not in result_params
+    assert "tools" not in result_params
+
+
+def test_vertex_ai_anthropic_tool_based_response_format_still_upgrades_legacy_thinking(local_model_cost_map):
+    result_params = VertexAIAnthropicConfig().map_openai_params(
+        non_default_params={
+            "response_format": {
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "test_schema",
+                    "schema": {"type": "object", "properties": {"result": {"type": "string"}}},
+                },
+            },
+            "thinking": {"type": "enabled", "budget_tokens": 4096},
+            "max_tokens": 8192,
+        },
+        optional_params={},
+        model="claude-opus-4-8",
+        drop_params=False,
+    )
+
+    assert "tools" in result_params
+    assert result_params["thinking"] == {"type": "adaptive"}
+    assert result_params["output_config"] == {"effort": "high"}
diff --git a/tests/test_litellm/models/test_models.py b/tests/test_litellm/models/test_models.py
index 669dba8e466..9ae9b732066 100644
--- a/tests/test_litellm/models/test_models.py
+++ b/tests/test_litellm/models/test_models.py
@@ -5,6 +5,7 @@ Tests for backend domain models.
 from datetime import datetime
 
 import pytest
+from pydantic import BaseModel, TypeAdapter
 
 from litellm.models.access_group import LiteLLM_AccessGroupTable
 from litellm.models.budget import (
@@ -130,6 +131,33 @@ class TestModel:
         assert model.litellm_params == {"model": "gpt-4"}
         assert model.model_info == {"team_id": "t1"}
 
+    def test_response_type_adapter_accepts_pydantic_row(self):
+        class PrismaModelRow(BaseModel):
+            model_id: str
+            model_name: str
+            litellm_params: dict[str, str]
+            model_info: dict[str, str] | None = None
+            blocked: bool = False
+
+        row = PrismaModelRow(
+            model_id="m1",
+            model_name="gpt-4",
+            litellm_params={"model": "gpt-4"},
+            model_info={"team_id": "t1"},
+            blocked=True,
+        )
+
+        model = TypeAdapter(LiteLLM_ProxyModelTable | None).validate_python(
+            row,
+            from_attributes=True,
+        )
+
+        assert model is not None
+        assert model.model_id == "m1"
+        assert model.litellm_params == {"model": "gpt-4"}
+        assert model.model_info == {"team_id": "t1"}
+        assert model.blocked is True
+
     def test_team_helpers_none_when_no_model_info(self):
         model = LiteLLM_ProxyModelTable(
             model_id="m1", model_name="gpt-4", litellm_params={}, model_info=None
diff --git a/tests/test_litellm/ocr/test_rust_bridge.py b/tests/test_litellm/ocr/test_rust_bridge.py
index acad249a2bb..0764aec7185 100644
--- a/tests/test_litellm/ocr/test_rust_bridge.py
+++ b/tests/test_litellm/ocr/test_rust_bridge.py
@@ -1,7 +1,7 @@
 """Tests for the optional Rust-backed OCR path."""
 
-import importlib
 import builtins
+import importlib
 import types
 from typing import Any
 
@@ -10,6 +10,7 @@ import pytest
 
 import litellm
 from litellm.llms.base_llm.ocr.transformation import OCRResponse
+from litellm.rust_bridge import configuration
 
 # `litellm/__init__.py` does `from .ocr.main import *`, which binds the `ocr`
 # function onto `litellm.ocr` and shadows the submodule, so import the modules
@@ -214,10 +215,12 @@ def build_prepared_request(
 @pytest.fixture(autouse=True)
 def _reset_rust_flag():
     """Keep the global toggle isolated between tests."""
-    rust_bridge.use_litellm_rust(False, ocr=None, aocr=None)
+    rust_bridge.set_rust_ocr(ocr=None, aocr=None)
+    configuration.reset_rust_configuration()
     rust_bridge_loader._cached_bridge = rust_bridge_loader._BRIDGE_SENTINEL
     yield
-    rust_bridge.use_litellm_rust(False, ocr=None, aocr=None)
+    rust_bridge.set_rust_ocr(ocr=None, aocr=None)
+    configuration.reset_rust_configuration()
     rust_bridge_loader._cached_bridge = rust_bridge_loader._BRIDGE_SENTINEL
 
 
@@ -247,7 +250,14 @@ def test_use_litellm_rust_toggles_flag():
 
 def test_env_var_enables_rust_ocr(monkeypatch):
     monkeypatch.setenv("LITELLM_USE_RUST_OCR", "1")
-    assert rust_bridge._env_enables_rust_ocr() is True
+    with pytest.warns(DeprecationWarning, match="LITELLM_USE_RUST_OCR is deprecated"):
+        assert rust_bridge.rust_ocr_enabled() is True
+
+
+def test_explicit_false_overrides_process_enable():
+    litellm.use_litellm_rust(True)
+
+    assert ocr_main._rust_ocr_enabled(build_prepared_request(litellm_params={"rust": False})) is False
 
 
 def test_load_rust_ocr_returns_injected_impl():
@@ -471,9 +481,7 @@ def test_run_rust_ocr_resolves_key_via_secret_manager_when_missing():
 
     ocr_main._run_rust_ocr(
         prepared_request=build_prepared_request(api_key=None, timeout=None),
-        resolve_api_key=lambda name: (
-            "sk-from-vault" if name == "MISTRAL_API_KEY" else None
-        ),
+        resolve_api_key=lambda name: "sk-from-vault" if name == "MISTRAL_API_KEY" else None,
     )
 
     assert bridge.calls[0]["api_key"] == "sk-from-vault"
@@ -580,9 +588,7 @@ def test_prepare_rust_ocr_call_resolves_azure_ai_api_base_from_secret_manager():
             api_base=None,
             timeout=None,
         ),
-        resolve_api_key=lambda name: (
-            "https://azure.example.com" if name == "AZURE_AI_API_BASE" else None
-        ),
+        resolve_api_key=lambda name: "https://azure.example.com" if name == "AZURE_AI_API_BASE" else None,
     )
 
     assert bridge.calls[0]["api_base"] == "https://azure.example.com"
@@ -600,9 +606,7 @@ def test_prepare_rust_ocr_call_resolves_document_intelligence_endpoint():
             timeout=None,
         ),
         resolve_api_key=lambda name: (
-            "https://document-intelligence.example.com"
-            if name == "AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT"
-            else None
+            "https://document-intelligence.example.com" if name == "AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT" else None
         ),
     )
 
@@ -815,9 +819,6 @@ def test_ocr_provider_configs_expose_api_key_env_vars():
     assert BaseOCRConfig().get_api_key_env_var() is None
     assert MistralOCRConfig().get_api_key_env_var() == "MISTRAL_API_KEY"
     assert AzureAIOCRConfig().get_api_key_env_var() == "AZURE_AI_API_KEY"
-    assert (
-        AzureDocumentIntelligenceOCRConfig().get_api_key_env_var()
-        == "AZURE_DOCUMENT_INTELLIGENCE_API_KEY"
-    )
+    assert AzureDocumentIntelligenceOCRConfig().get_api_key_env_var() == "AZURE_DOCUMENT_INTELLIGENCE_API_KEY"
     assert VertexAIOCRConfig().get_api_key_env_var() == "VERTEX_AI_API_KEY"
     assert VertexAIDeepSeekOCRConfig().get_api_key_env_var() == "VERTEX_AI_API_KEY"
diff --git a/tests/test_litellm/passthrough/test_async_streaming_error_propagation.py b/tests/test_litellm/passthrough/test_async_streaming_error_propagation.py
index faf4ea46c43..9f2b436d2d8 100644
--- a/tests/test_litellm/passthrough/test_async_streaming_error_propagation.py
+++ b/tests/test_litellm/passthrough/test_async_streaming_error_propagation.py
@@ -1,12 +1,12 @@
 """
-Tests for error propagation in _async_streaming passthrough routes.
+Tests for error propagation in async passthrough streaming routes.
 
-Verifies that HTTP 4xx/5xx errors from upstream (e.g. Azure 429 rate limits)
-raise exceptions instead of being silently forwarded as raw bytes under HTTP 200.
-
-See: litellm/passthrough/main.py _async_streaming()
+Verifies that streaming passthrough wrappers preserve the previous guarantees:
+HTTP 4xx/5xx failures must raise instead of being silently forwarded as bytes,
+and successful streaming responses should still yield chunks normally.
 """
 
+import asyncio
 import json
 from unittest.mock import AsyncMock, MagicMock
 
@@ -54,19 +54,19 @@ def _make_mock_logging_obj():
 @pytest.mark.asyncio
 async def test_async_streaming_429_raises():
     """429 from upstream should raise HTTPStatusError, not yield error bytes."""
-    from litellm.passthrough.main import _async_streaming
-
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
+    
     error_body = json.dumps(
         {"error": {"code": "429", "message": "Rate limit exceeded."}}
     ).encode()
     mock_response = _make_mock_response(429, error_body)
-
+    
     async def response_coro():
         return mock_response
-
+    
     chunks = []
     async def _drain():
-        async for chunk in _async_streaming(
+        async for chunk in AsyncPassthroughStreamingResponse(
             response=response_coro(),
             litellm_logging_obj=_make_mock_logging_obj(),
             provider_config=MagicMock(),
@@ -83,45 +83,78 @@ async def test_async_streaming_429_raises():
 @pytest.mark.asyncio
 async def test_async_streaming_500_raises():
     """500 from upstream should also raise, not yield error bytes."""
-    from litellm.passthrough.main import _async_streaming
-
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
+    
     error_body = json.dumps(
         {"error": {"code": "500", "message": "Internal server error"}}
     ).encode()
     mock_response = _make_mock_response(500, error_body)
-
+    
     async def response_coro():
         return mock_response
-
+    
     with pytest.raises(httpx.HTTPStatusError) as exc_info:
-        async for _ in _async_streaming(
+        async for _ in AsyncPassthroughStreamingResponse(
             response=response_coro(),
             litellm_logging_obj=_make_mock_logging_obj(),
             provider_config=MagicMock(),
         ):
             pass
-
+    
     assert exc_info.value.response.status_code == 500
 
 
 @pytest.mark.asyncio
-async def test_async_streaming_200_yields_chunks():
+async def test_async_passthrough_wrapper_200_yields_chunks():
     """Successful 200 streaming responses should continue to work normally."""
-    from litellm.passthrough.main import _async_streaming
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
 
     sse_data = b'data: {"type":"response.created"}\n\ndata: [DONE]\n\n'
     mock_response = _make_mock_response(200, sse_data)
+    mock_logging_obj = _make_mock_logging_obj()
 
     async def response_coro():
         return mock_response
 
-    chunks = []
-    async for chunk in _async_streaming(
+    async_stream = AsyncPassthroughStreamingResponse(
         response=response_coro(),
-        litellm_logging_obj=_make_mock_logging_obj(),
+        litellm_logging_obj=mock_logging_obj,
         provider_config=MagicMock(),
-    ):
+    )
+
+    chunks = []
+    async for chunk in async_stream:
         chunks.append(chunk)
 
+    await asyncio.sleep(0)
+
     assert len(chunks) == 1
     assert b"response.created" in chunks[0]
+    mock_logging_obj.async_flush_passthrough_collected_chunks.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_error_body_readable_after_failed_await():
+    """The upstream error body must stay readable so the proxy can map the real status and message."""
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
+
+    error_body = b'{"message":"model not found"}'
+
+    async def byte_stream():
+        yield error_body
+
+    request = httpx.Request("POST", "https://bedrock.example.com/model/x/converse-stream")
+    response = httpx.Response(400, content=byte_stream(), request=request)
+
+    async def response_coro():
+        return response
+
+    with pytest.raises(httpx.HTTPStatusError) as exc_info:
+        await AsyncPassthroughStreamingResponse(
+            response=response_coro(),
+            litellm_logging_obj=_make_mock_logging_obj(),
+            provider_config=MagicMock(),
+        )
+
+    assert exc_info.value.response.status_code == 400
+    assert await exc_info.value.response.aread() == error_body
diff --git a/tests/test_litellm/passthrough/test_passthrough_main.py b/tests/test_litellm/passthrough/test_passthrough_main.py
index b8f265ad7ea..1950c37a12e 100644
--- a/tests/test_litellm/passthrough/test_passthrough_main.py
+++ b/tests/test_litellm/passthrough/test_passthrough_main.py
@@ -645,13 +645,14 @@ async def test_allm_passthrough_route_429_streaming_raises():
     Regression test: Azure 429 during streaming must raise HTTPStatusError,
     not be silently forwarded as raw bytes under HTTP 200.
 
-    Before the fix, _async_streaming() would yield the 429 error JSON as
-    chunks and allm_passthrough_route returned an async generator.  The
-    caller (azure_proxy_route) wrapped it in StreamingResponse(status_code=200),
+    Before the fix, the async passthrough streaming path would yield the 429
+    error JSON as chunks and allm_passthrough_route returned a streaming
+    iterator. The caller (azure_proxy_route) wrapped it in
+    StreamingResponse(status_code=200),
     so the client saw HTTP 200 + unparseable SSE body → silent task_complete(null).
 
-    After the fix, raise_for_status() fires inside _async_streaming() before
-    any chunks are yielded, so the exception propagates all the way up.
+    After the fix, raise_for_status() fires before the streaming wrapper is
+    returned, so the exception propagates all the way up.
     """
     mock_provider_config = MagicMock()
     mock_provider_config.get_complete_url.return_value = (
@@ -679,6 +680,7 @@ async def test_allm_passthrough_route_429_streaming_raises():
     mock_logging_obj = MagicMock()
     mock_logging_obj.update_environment_variables = MagicMock()
     mock_logging_obj.async_flush_passthrough_collected_chunks = AsyncMock()
+    mock_logging_obj.async_failure_handler = AsyncMock()
 
     with (
         patch(
@@ -701,29 +703,101 @@ async def test_allm_passthrough_route_429_streaming_raises():
         patch.object(async_client.client, "send", mock_send),
         patch.object(async_client.client, "build_request", mock_build_request),
     ):
-        result = await allm_passthrough_route(
-            model="azure/gpt-4",
-            endpoint="openai/deployments/gpt-4/responses",
-            method="POST",
-            custom_llm_provider="azure",
-            api_base="https://my-azure.openai.azure.com",
-            api_key="fake-azure-key",
-            json={"model": "gpt-4", "input": "hello", "stream": True},
-            client=async_client,
-            litellm_logging_obj=mock_logging_obj,
-        )
-
-        # result is an async generator — consuming it must raise, not silently yield error bytes
-        chunks = []
-        async def _drain():
-            async for chunk in result:  # type: ignore[union-attr]
-                chunks.append(chunk)
-
         with pytest.raises(httpx.HTTPStatusError) as exc_info:
-            await _drain()
+            await allm_passthrough_route(
+                model="azure/gpt-4",
+                endpoint="openai/deployments/gpt-4/responses",
+                method="POST",
+                custom_llm_provider="azure",
+                api_base="https://my-azure.openai.azure.com",
+                api_key="fake-azure-key",
+                json={"model": "gpt-4", "input": "hello", "stream": True},
+                client=async_client,
+                litellm_logging_obj=mock_logging_obj,
+            )
 
     assert exc_info.value.response.status_code == 429
-    assert len(chunks) == 0, "No chunks should be yielded before the 429 raises"
+
+
+def test_llm_passthrough_route_sync_streaming_error_maps_upstream_status():
+    """
+    Regression test: a sync streaming passthrough whose upstream answers an
+    error status must surface the mapped provider error, not
+    httpx.ResponseNotRead.
+
+    Before the fix, raise_for_status() raised on the still-unread streamed
+    response, and _handle_error then touched e.response.text, which raises
+    ResponseNotRead on a streamed-but-unread body, masking the real upstream
+    error entirely.
+    """
+    from litellm.llms.base_llm.chat.transformation import BaseLLMException
+
+    error_body = json.dumps(
+        {
+            "error": {
+                "code": "429",
+                "message": "Rate limit exceeded. Retry after 10 seconds.",
+            }
+        }
+    ).encode()
+
+    class _UnreadErrorStream(httpx.SyncByteStream):
+        def __iter__(self):
+            yield error_body
+
+    def _handler(request: httpx.Request) -> httpx.Response:
+        return httpx.Response(
+            429,
+            stream=_UnreadErrorStream(),
+            headers={"content-type": "application/json"},
+        )
+
+    sync_client = HTTPHandler(
+        client=httpx.Client(transport=httpx.MockTransport(_handler))
+    )
+
+    mock_provider_config = MagicMock()
+    mock_provider_config.get_complete_url.return_value = (
+        httpx.URL("https://gigachat.devices.sberbank.ru/api/v1/chat/completions"),
+        "https://gigachat.devices.sberbank.ru/api/v1",
+    )
+    mock_provider_config.get_api_key.return_value = "fake-key"
+    mock_provider_config.validate_environment.return_value = {
+        "Authorization": "Bearer fake-key"
+    }
+    mock_provider_config.sign_request.return_value = (
+        {"Authorization": "Bearer fake-key"},
+        None,
+    )
+    mock_provider_config.is_streaming_request.return_value = True
+    mock_provider_config.get_error_class.side_effect = (
+        lambda error_message, status_code, headers: BaseLLMException(
+            status_code=status_code, message=error_message, headers=headers
+        )
+    )
+
+    mock_logging_obj = MagicMock()
+
+    with pytest.raises(BaseLLMException) as exc_info:
+        llm_passthrough_route(
+            model="gigachat/GigaChat-2",
+            endpoint="chat/completions",
+            method="POST",
+            custom_llm_provider="gigachat",
+            api_base="https://gigachat.devices.sberbank.ru/api/v1",
+            api_key="fake-key",
+            json={
+                "model": "GigaChat-2",
+                "messages": [{"role": "user", "content": "hi"}],
+                "stream": True,
+            },
+            client=sync_client,
+            litellm_logging_obj=mock_logging_obj,
+            provider_config=mock_provider_config,
+        )
+
+    assert exc_info.value.status_code == 429
+    assert "Rate limit exceeded" in str(exc_info.value)
 
 
 def test_llm_passthrough_route_propagates_allm_passthrough_route_to_logging_obj():
diff --git a/tests/test_litellm/passthrough/test_streaming_interrupt_spend_tracking.py b/tests/test_litellm/passthrough/test_streaming_interrupt_spend_tracking.py
index 3783e218e4e..a88b0ef0c4b 100644
--- a/tests/test_litellm/passthrough/test_streaming_interrupt_spend_tracking.py
+++ b/tests/test_litellm/passthrough/test_streaming_interrupt_spend_tracking.py
@@ -35,11 +35,14 @@ class _ImmediateExecutor:
 
 
 @pytest.mark.asyncio
-async def test_async_streaming_flushes_on_normal_completion():
-    from litellm.passthrough.main import _async_streaming
+async def test_asyncpassthroughstreamingresponse_flushes_on_normal_completion():
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
 
     chunks = [b"chunk-1", b"chunk-2", b"chunk-3"]
     mock_response = _make_streaming_response(chunks)
+    mock_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream", "x-request-id": "req-123"}
+    )
 
     async def response_coro():
         return mock_response
@@ -48,14 +51,19 @@ async def test_async_streaming_flushes_on_normal_completion():
     provider_config = MagicMock()
 
     received = []
-    async for chunk in _async_streaming(
+    received_response = AsyncPassthroughStreamingResponse(
         response=response_coro(),
         litellm_logging_obj=mock_logging_obj,
         provider_config=provider_config,
-    ):
+    )
+
+    async for chunk in received_response:
         received.append(chunk)
 
     assert received == chunks
+    
+    assert received_response.headers["content-type"] == "application/octet-stream"
+    assert received_response.headers["x-request-id"] == "req-123"
 
     await asyncio.sleep(0)
 
@@ -68,8 +76,8 @@ async def test_async_streaming_flushes_on_normal_completion():
 
 
 @pytest.mark.asyncio
-async def test_async_streaming_flushes_on_client_disconnect():
-    from litellm.passthrough.main import _async_streaming
+async def test_asyncpassthroughstreamingresponse_flushes_on_client_disconnect():
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
 
     chunks = [
         b'{"chunk": 1, "outputTokens": 10}',
@@ -77,6 +85,9 @@ async def test_async_streaming_flushes_on_client_disconnect():
         b'{"chunk": 3, "outputTokens": 8}',
     ]
     mock_response = _make_streaming_response(chunks)
+    mock_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream", "x-request-id": "req-123"}
+    )
 
     async def response_coro():
         return mock_response
@@ -84,7 +95,7 @@ async def test_async_streaming_flushes_on_client_disconnect():
     mock_logging_obj = _make_logging_obj()
     provider_config = MagicMock()
 
-    gen = _async_streaming(
+    gen = AsyncPassthroughStreamingResponse(
         response=response_coro(),
         litellm_logging_obj=mock_logging_obj,
         provider_config=provider_config,
@@ -105,11 +116,14 @@ async def test_async_streaming_flushes_on_client_disconnect():
 
 
 @pytest.mark.asyncio
-async def test_async_streaming_does_not_flush_on_4xx():
-    from litellm.passthrough.main import _async_streaming
+async def test_asyncpassthroughstreamingresponse_does_not_flush_on_4xx():
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
 
     err_response = MagicMock(spec=httpx.Response)
     err_response.status_code = 429
+    err_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream"}
+    )
 
     def _raise():
         raise httpx.HTTPStatusError(
@@ -129,7 +143,7 @@ async def test_async_streaming_does_not_flush_on_4xx():
     mock_logging_obj = _make_logging_obj()
 
     with pytest.raises(httpx.HTTPStatusError):
-        async for _ in _async_streaming(
+        async for _ in AsyncPassthroughStreamingResponse(
             response=response_coro(),
             litellm_logging_obj=mock_logging_obj,
             provider_config=MagicMock(),
@@ -140,8 +154,8 @@ async def test_async_streaming_does_not_flush_on_4xx():
 
 
 @pytest.mark.asyncio
-async def test_async_streaming_flushes_on_upstream_exception_with_partial_data():
-    from litellm.passthrough.main import _async_streaming
+async def test_asyncpassthroughstreamingresponse_flushes_on_upstream_exception_with_partial_data():
+    from litellm.passthrough.main import AsyncPassthroughStreamingResponse
 
     partial_chunks = [b"partial-chunk-1", b"partial-chunk-2"]
 
@@ -149,6 +163,9 @@ async def test_async_streaming_flushes_on_upstream_exception_with_partial_data()
     mock_response.status_code = 200
     mock_response.raise_for_status = MagicMock(return_value=None)
     mock_response.aclose = AsyncMock()
+    mock_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream", "x-request-id": "req-123"}
+    )
 
     async def _aiter_bytes_then_raise():
         for c in partial_chunks:
@@ -165,7 +182,7 @@ async def test_async_streaming_flushes_on_upstream_exception_with_partial_data()
 
     received = []
     async def _drain():
-        async for chunk in _async_streaming(
+        async for chunk in AsyncPassthroughStreamingResponse(
             response=response_coro(),
             litellm_logging_obj=mock_logging_obj,
             provider_config=provider_config,
@@ -186,12 +203,16 @@ async def test_async_streaming_flushes_on_upstream_exception_with_partial_data()
     assert call_kwargs["raw_bytes"] == partial_chunks
 
 
-def test_sync_streaming_flushes_on_normal_completion():
-    from litellm.passthrough.main import _sync_streaming
+def test_passthroughstreamingresponse_flushes_on_normal_completion():
+    from litellm.passthrough.main import PassthroughStreamingResponse
 
     chunks = [b"a", b"b", b"c"]
 
     mock_response = MagicMock(spec=httpx.Response)
+    mock_response.status_code = 200
+    mock_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream", "x-request-id": "req-123"}
+    )
 
     def _iter_bytes():
         yield from chunks
@@ -202,25 +223,33 @@ def test_sync_streaming_flushes_on_normal_completion():
     mock_logging_obj.flush_passthrough_collected_chunks = MagicMock()
     provider_config = MagicMock()
 
+    received_responce = PassthroughStreamingResponse(
+        response=mock_response,
+        litellm_logging_obj=mock_logging_obj,
+        provider_config=provider_config,
+    )
+
     with patch("litellm.utils.executor", _ImmediateExecutor()):
-        received = list(
-            _sync_streaming(
-                response=mock_response,
-                litellm_logging_obj=mock_logging_obj,
-                provider_config=provider_config,
-            )
-        )
+        received = list(received_responce)
 
     assert received == chunks
+
+    assert received_responce.headers["content-type"] == "application/octet-stream"
+    assert received_responce.headers["x-request-id"] == "req-123"
+
     mock_logging_obj.flush_passthrough_collected_chunks.assert_called_once()
 
 
-def test_sync_streaming_flushes_on_early_close():
-    from litellm.passthrough.main import _sync_streaming
+def test_passthroughstreamingresponse_flushes_on_early_close():
+    from litellm.passthrough.main import PassthroughStreamingResponse
 
     chunks = [b"first", b"second", b"third"]
 
     mock_response = MagicMock(spec=httpx.Response)
+    mock_response.status_code = 200
+    mock_response.headers = httpx.Headers(
+        {"content-type": "application/octet-stream", "x-request-id": "req-123"}
+    )
 
     def _iter_bytes():
         yield from chunks
@@ -232,7 +261,7 @@ def test_sync_streaming_flushes_on_early_close():
     provider_config = MagicMock()
 
     with patch("litellm.utils.executor", _ImmediateExecutor()):
-        gen = _sync_streaming(
+        gen = PassthroughStreamingResponse(
             response=mock_response,
             litellm_logging_obj=mock_logging_obj,
             provider_config=provider_config,
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py b/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py
index 0144fbb17dd..c8ea4867f2c 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py
@@ -6005,6 +6005,44 @@ class TestMCPDcrBridgeDelegateAdmission:
                 await MCPRequestHandler.process_mcp_request(scope)
 
         assert exc_info.value.status_code == 503
+        assert exc_info.value.detail == (
+            "Service Unavailable, the authentication database is temporarily unreachable. Please retry shortly."
+        )
+
+    async def test_user_subject_envelope_permanent_db_fault_is_503_not_worded_as_transient(self):
+        """A query engine fault that never heals (a missing engine binary) still fails admission with 503,
+        but the detail must not call the database "temporarily unreachable" or ask the client to retry: the
+        DCR client would loop on a retry that can never succeed. The fault reaches the handler wrapped in
+        get_user_object's bare ValueError, so the wording has to be picked off the wrapped cause."""
+        from prisma.engine.errors import BinaryNotFoundError
+
+        envelope = self._mint_bridge_envelope(user_id="sso-user-7")
+        scope = {
+            "type": "http",
+            "method": "POST",
+            "path": "/mcp/bridge_delegate_server",
+            "headers": [(b"authorization", f"Bearer {envelope}".encode("latin-1"))],
+        }
+        with (
+            patch(  # test-quality-ok: isolate the MCP registry, same seam as the sibling admission tests
+                "litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager"
+            ) as mock_mgr,
+            patch(  # test-quality-ok: the envelope opener reads master_key off the proxy module, no injection seam
+                "litellm.proxy.proxy_server.master_key", self._MASTER_KEY
+            ),
+            self._patch_user_reload(
+                side_effect=self._wrapped_user_lookup_error(BinaryNotFoundError("query engine binary not found"))
+            ),
+        ):
+            mock_mgr.get_mcp_server_by_name.return_value = self._bridge_delegate_server()
+            with pytest.raises(HTTPException) as exc_info:
+                await MCPRequestHandler.process_mcp_request(scope)
+
+        assert exc_info.value.status_code == 503
+        assert "temporarily unreachable" not in exc_info.value.detail
+        assert "retry shortly" not in exc_info.value.detail.lower()
+        assert "BinaryNotFoundError" in exc_info.value.detail
+        assert "will not clear by retrying" in exc_info.value.detail
 
     async def test_user_subject_envelope_scim_deactivated_user_fails_closed_401(self):
         """SCIM-deactivating the envelope's user revokes it immediately: the reloaded user carries
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py b/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py
index b477bf3f406..2ccba2b2055 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/conftest.py
@@ -2,6 +2,30 @@ import os
 
 import pytest
 
+from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
+    global_mcp_server_manager,
+)
+
+
+@pytest.fixture(autouse=True)
+def _hermetic_mcp_server_registry():
+    """Restore the singleton ``global_mcp_server_manager``'s registry state around every
+    test, so entries seeded by one test never leak into another on a shared shard."""
+    saved_registry = dict(global_mcp_server_manager.registry)
+    saved_config_servers = dict(global_mcp_server_manager.config_mcp_servers)
+    saved_tool_mapping = dict(global_mcp_server_manager.tool_name_to_mcp_server_name_mapping)
+    saved_oauth_slots = global_mcp_server_manager._oauth_discovery_slots
+    try:
+        yield
+    finally:
+        global_mcp_server_manager.registry.clear()
+        global_mcp_server_manager.registry.update(saved_registry)
+        global_mcp_server_manager.config_mcp_servers.clear()
+        global_mcp_server_manager.config_mcp_servers.update(saved_config_servers)
+        global_mcp_server_manager.tool_name_to_mcp_server_name_mapping.clear()
+        global_mcp_server_manager.tool_name_to_mcp_server_name_mapping.update(saved_tool_mapping)
+        global_mcp_server_manager._oauth_discovery_slots = saved_oauth_slots
+
 
 @pytest.fixture(autouse=True)
 def _hermetic_server_root_path():
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/outbound_credentials/test_token_endpoint.py b/tests/test_litellm/proxy/_experimental/mcp_server/outbound_credentials/test_token_endpoint.py
index f100bd56f8f..5f277db2f72 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/outbound_credentials/test_token_endpoint.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/outbound_credentials/test_token_endpoint.py
@@ -224,20 +224,6 @@ async def test_fetch_invalid_json_maps_to_upstream_unavailable():
     assert "idp.example.com" not in result.error.summary
 
 
-@pytest.mark.asyncio
-async def test_fetch_none_response_is_upstream_unavailable():
-    with patch(_PATCH_TARGET, return_value=_client(None)):
-        result = await TokenEndpointClient().fetch(
-            _ENDPOINT,
-            _CLIENT_ID,
-            {"grant_type": "g"},
-            ClientSecretAuth(client_secret=SecretStr("s")),
-        )
-
-    assert isinstance(result, Error)
-    assert result.error.tag == "upstream_unavailable"
-
-
 @pytest.mark.asyncio
 async def test_fetch_missing_access_token_is_upstream_unavailable():
     bad = MagicMock()
@@ -275,21 +261,6 @@ async def test_fetch_http_error_does_not_leak_endpoint_url():
     assert "idp.example.com" not in result.error.summary
 
 
-@pytest.mark.asyncio
-async def test_fetch_none_response_does_not_leak_endpoint_url():
-    with patch(_PATCH_TARGET, return_value=_client(None)):
-        result = await TokenEndpointClient().fetch(
-            _ENDPOINT,
-            _CLIENT_ID,
-            {"grant_type": "g"},
-            ClientSecretAuth(client_secret=SecretStr("s")),
-        )
-
-    assert isinstance(result, Error)
-    assert _ENDPOINT not in result.error.summary
-    assert "idp.example.com" not in result.error.summary
-
-
 @pytest.mark.asyncio
 async def test_fetch_missing_access_token_does_not_leak_endpoint_url():
     bad = MagicMock()
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_discoverable_endpoints.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_discoverable_endpoints.py
index 3279c59acd4..588eba4adb7 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_discoverable_endpoints.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_discoverable_endpoints.py
@@ -35,6 +35,22 @@ def mock_mcp_client_ip():
         yield
 
 
+@pytest.fixture(autouse=True)
+def isolate_global_mcp_registry():
+    """Restore the module-global MCP server registry after each test.
+
+    Tests here register servers on ``global_mcp_server_manager`` directly; without a
+    restore, entries leak into other test modules sharing the same worker and break
+    assertions over the full registry contents.
+    """
+    from litellm.proxy._experimental.mcp_server.mcp_server_manager import global_mcp_server_manager
+
+    snapshot = dict(global_mcp_server_manager.registry)
+    yield
+    global_mcp_server_manager.registry.clear()
+    global_mcp_server_manager.registry.update(snapshot)
+
+
 def _mock_callback_request(base_url: str = "http://localhost:3000/"):
     """Return a MagicMock Request for callback/authorize same-origin tests.
 
@@ -6416,6 +6432,23 @@ async def test_bridge_mint_db_outage_is_503_before_upstream():
     response, post = await _prepare_only_bridge_exchange("unavailable")
     assert response.status_code == 503
     assert json.loads(response.body)["error"] == "temporarily_unavailable"
+    assert "retry shortly" in json.loads(response.body)["error_description"]
+    post.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_bridge_mint_permanent_db_fault_is_503_without_retry_advice():
+    """A query engine fault that never heals is still a 503 (the gateway is at fault, not the client), but
+    the description must not tell the client the database is temporarily unreachable and to retry: that
+    sends an operator to wait out an outage that is not one. The code stays temporarily_unavailable, the
+    only RFC 6749 error a client treats as a server-side 503."""
+    response, post = await _prepare_only_bridge_exchange("faulted")
+    assert response.status_code == 503
+    body = json.loads(response.body)
+    assert body["error"] == "temporarily_unavailable"
+    assert "temporarily unreachable" not in body["error_description"]
+    assert "retry shortly" not in body["error_description"]
+    assert "not a transient outage" in body["error_description"]
     post.assert_not_called()
 
 
@@ -7127,6 +7160,56 @@ async def test_resolve_active_litellm_key_db_outage_is_unavailable(proxy_globals
     assert await _resolve_active_litellm_key(request) == "unavailable"
 
 
+@pytest.mark.asyncio
+async def test_resolve_active_litellm_key_permanent_engine_fault_is_faulted(proxy_globals):
+    """A query engine that is missing or version-skewed cannot resolve any key until the deployment is
+    repaired, so the resolver reports "faulted" (still statused 503 by the mint) rather than "unavailable",
+    whose wording promises the outage is transient and asks the client to retry."""
+    from prisma.engine.errors import BinaryNotFoundError
+
+    from litellm.proxy._experimental.mcp_server.bridge_token_flow import (
+        _resolve_active_litellm_key,
+    )
+    from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+
+    class _FaultedPrisma:
+        async def get_data(self, token, table_name, parent_otel_span=None, proxy_logging_obj=None):
+            raise BinaryNotFoundError("query engine binary not found")
+
+    proxy_globals.user_api_key_cache = UserApiKeyCache()
+    proxy_globals.prisma_client = _FaultedPrisma()
+
+    request = _token_request({"x-litellm-api-key": "sk-during-engine-fault"})
+    assert await _resolve_active_litellm_key(request) == "faulted"
+
+
+@pytest.mark.asyncio
+async def test_resolve_active_litellm_key_transport_error_over_permanent_fault_is_faulted(proxy_globals):
+    """A reconnect that dies on a missing engine binary raises the transport error last, with the
+    BinaryNotFoundError as __context__. The binary is what blocks recovery, so the key read is "faulted",
+    not the "unavailable" that the outer ConnectError alone would suggest."""
+    import httpx
+    from prisma.engine.errors import BinaryNotFoundError
+
+    from litellm.proxy._experimental.mcp_server.bridge_token_flow import (
+        _resolve_active_litellm_key,
+    )
+    from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+
+    class _ReconnectFailedPrisma:
+        async def get_data(self, token, table_name, parent_otel_span=None, proxy_logging_obj=None):
+            try:
+                raise BinaryNotFoundError("query engine binary not found")
+            except BinaryNotFoundError:
+                raise httpx.ConnectError("All connection attempts failed")
+
+    proxy_globals.user_api_key_cache = UserApiKeyCache()
+    proxy_globals.prisma_client = _ReconnectFailedPrisma()
+
+    request = _token_request({"x-litellm-api-key": "sk-during-failed-reconnect"})
+    assert await _resolve_active_litellm_key(request) == "faulted"
+
+
 @pytest.mark.asyncio
 async def test_resolve_active_litellm_key_no_database_is_unresolvable(proxy_globals):
     """With no database connection configured the gateway cannot verify the presented key at all, so
@@ -7198,6 +7281,26 @@ async def test_reload_active_user_by_id_db_outage_is_unavailable(proxy_globals):
         assert await _reload_active_user_by_id("sso-user-7") == "unavailable"
 
 
+@pytest.mark.asyncio
+async def test_reload_active_user_by_id_permanent_engine_fault_is_faulted(proxy_globals):
+    """A permanent query engine fault while re-validating the user on refresh is "faulted", not
+    "unavailable": both are 503s, but only the transient one may tell the client to retry. get_user_object
+    wraps the fault in a bare ValueError, so the classification has to read the wrapped cause."""
+    from prisma.engine.errors import MismatchedVersionsError
+
+    from litellm.proxy._experimental.mcp_server.bridge_token_flow import _reload_active_user_by_id
+    from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+
+    proxy_globals.user_api_key_cache = UserApiKeyCache()
+    proxy_globals.prisma_client = object()
+
+    with patch(  # test-quality-ok: get_user_object is the DB seam that wraps the fault; same patch as the outage sibling
+        "litellm.proxy.auth.auth_checks.get_user_object",
+        new=AsyncMock(side_effect=_wrapped_user_lookup_error(MismatchedVersionsError(expected="1", got="2"))),
+    ):
+        assert await _reload_active_user_by_id("sso-user-7") == "faulted"
+
+
 @pytest.mark.asyncio
 async def test_token_endpoint_uses_client_secret_basic_when_configured():
     """LIT-4091: a server with token_endpoint_auth_method=client_secret_basic must send the
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_gateway_dcr_flow.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_gateway_dcr_flow.py
index 32a3f70c357..1670370f082 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_gateway_dcr_flow.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_gateway_dcr_flow.py
@@ -426,6 +426,7 @@ async def test_token_rejects_expired_code_and_missing_configuration():
     [
         ("no_active_key", 400, "invalid_grant"),
         ("unavailable", 503, "temporarily_unavailable"),
+        ("faulted", 503, "temporarily_unavailable"),
         ("unresolvable", 500, "server_error"),
     ],
 )
@@ -460,6 +461,25 @@ async def test_token_gates_on_live_user_revalidation(failure, expected_status, e
     assert json.loads(response.body)["error"] == expected_error
 
 
+def test_permanent_db_fault_503_does_not_promise_a_retry_will_help():
+    """Both DB failures are 503 temporarily_unavailable (the only OAuth error a client reads as a
+    server-side outage), so the description is the one place the two are told apart: a transient outage
+    says retry, a fault that never heals must say retrying will not help and point at the deployment."""
+    from litellm.proxy._experimental.mcp_server.gateway_dcr_flow import (
+        _consent_lookup_failure_response,
+        _mint_failure_response,
+        _reload_failure_response,
+    )
+
+    for render in (_reload_failure_response, _consent_lookup_failure_response, _mint_failure_response):
+        transient = json.loads(render("unavailable").body)["error_description"]
+        faulted = json.loads(render("faulted").body)["error_description"]
+        assert transient == "the gateway database is unavailable; retry"
+        assert "retry" not in faulted.replace("retrying will not help", "")
+        assert "not a transient outage" in faulted
+        assert "retrying will not help" in faulted
+
+
 @pytest.mark.asyncio
 async def test_flow_is_single_use_shared_cache_rejects_second_complete():
     """A double-submit of the finish step mints only ONE code: the second complete over the
@@ -1250,6 +1270,7 @@ async def test_native_authorize_refuses_a_hosted_redirect_for_the_proxy_api():
     "failure, status, error",
     [
         ("unavailable", 503, "temporarily_unavailable"),
+        ("faulted", 503, "temporarily_unavailable"),
         ("unresolvable", 500, "server_error"),
         ("no_active_key", 403, "access_denied"),
     ],
@@ -1424,6 +1445,7 @@ async def test_native_code_without_a_minter_is_refused_server_side():
         ("team_required", 400, "invalid_grant"),
         ("no_active_key", 400, "invalid_grant"),
         ("unavailable", 503, "temporarily_unavailable"),
+        ("faulted", 503, "temporarily_unavailable"),
         ("unresolvable", 500, "server_error"),
     ],
 )
@@ -1805,5 +1827,12 @@ async def test_introspect_fails_closed_on_dead_user_and_503s_on_outage():
     status, body = await _introspect(minted.token.get_secret_value(), reload_user=_reload_user_outage)
     assert (status, body["error"]) == (503, "temporarily_unavailable")
 
+    async def _reload_user_faulted(user_id: str):
+        return "faulted"
+
+    status, body = await _introspect(minted.token.get_secret_value(), reload_user=_reload_user_faulted)
+    assert (status, body["error"]) == (503, "temporarily_unavailable")
+    assert "not a transient outage" in body["error_description"]
+
     status, body = await _introspect(minted.token.get_secret_value(), master_key=None)
     assert (status, body["error"]) == (500, "server_error")
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py
index ac7082c2668..1c65adac4c6 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_identity_env.py
@@ -23,6 +23,12 @@ MGMT_MODULE = "litellm.proxy.management_endpoints.mcp_management_endpoints"
 @contextlib.contextmanager
 def _env_and_reload(**env):
     saved = {key: os.environ.get(key) for key in env}
+    utils_module = importlib.import_module(UTILS_MODULE)
+    mgmt_module = importlib.import_module(MGMT_MODULE)
+    # Restore pre-reload module attributes afterwards instead of reloading again:
+    # a reload re-creates the module's classes, breaking exception identity for
+    # modules that imported them earlier
+    snapshots = {module: dict(vars(module)) for module in (utils_module, mgmt_module)}
 
     def _apply_env(values):
         for key, value in values.items():
@@ -32,8 +38,8 @@ def _env_and_reload(**env):
                 os.environ[key] = value
 
     def _reload():
-        utils = importlib.reload(importlib.import_module(UTILS_MODULE))
-        mgmt = importlib.reload(importlib.import_module(MGMT_MODULE))
+        utils = importlib.reload(utils_module)
+        mgmt = importlib.reload(mgmt_module)
         return utils, mgmt
 
     try:
@@ -41,7 +47,10 @@ def _env_and_reload(**env):
         yield _reload()
     finally:
         _apply_env(saved)
-        _reload()
+        for module, snapshot in snapshots.items():
+            for key in [key for key in vars(module) if key not in snapshot]:
+                delattr(module, key)
+            vars(module).update(snapshot)
 
 
 def test_defaults_used_when_env_unset():
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py
index 16221f44efe..239f89ebd90 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_tool_search.py
@@ -10,33 +10,36 @@ Covers:
 """
 
 import json
+from collections.abc import Sequence
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
+from mcp.types import Tool
 
+import litellm
 from litellm.models.object_permission import LiteLLM_ObjectPermissionTable
 from litellm.proxy._experimental.mcp_server.faults.list_outcomes import AggregateToolListing
 from litellm.proxy._experimental.mcp_server.tool_search import (
     AGENT_SEARCH_TOOL_NAME,
     MCP_TOOL_CALL_TOOL_NAME,
     MCP_TOOL_SEARCH_TOOL_NAME,
+    SemanticToolRanker,
+    ToolSearchResult,
     coerce_top_k,
     get_virtual_tool_definitions,
+    search_mcp_tools,
     search_tools,
 )
 from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
+from litellm.proxy.common_utils.semantic_text_index import EmbeddingFailed, SemanticTextIndex, Vector
+from litellm.types.mcp import MCPToolSearchSettings
 
 
-def _make_tools(specs: list[tuple[str, str]]) -> list[dict[str, Any]]:
-    return [
-        {
-            "name": name,
-            "description": desc,
-            "inputSchema": {"type": "object", "properties": {}},
-        }
-        for name, desc in specs
-    ]
+def _make_tools(specs: list[tuple[str, str]]) -> tuple[Tool, ...]:
+    return tuple(
+        Tool(name=name, description=desc, inputSchema={"type": "object", "properties": {}}) for name, desc in specs
+    )
 
 
 def _make_perm(**kwargs: Any) -> LiteLLM_ObjectPermissionTable:
@@ -54,6 +57,160 @@ SAMPLE_TOOLS = _make_tools(
 )
 
 
+FX_TOOL = Tool(
+    name="treasury-get_rates",
+    description="Get foreign exchange rates for a currency pair",
+    inputSchema={"type": "object", "properties": {}},
+)
+WEATHER_TOOL = Tool(
+    name="weather-forecast",
+    description="Get the weather forecast for a city",
+    inputSchema={"type": "object", "properties": {}},
+)
+CALENDAR_TOOL = Tool(
+    name="calendar-create_event",
+    description="Create a calendar event",
+    inputSchema={"type": "object", "properties": {}},
+)
+CATALOG = (FX_TOOL, WEATHER_TOOL, CALENDAR_TOOL)
+
+# A stand-in embedding space: "FX" sits next to the foreign-exchange tool and far from the rest.
+FAKE_VECTORS: dict[str, Vector] = {
+    "FX": (1.0, 0.0),
+    f"{FX_TOOL.name}\n{FX_TOOL.description}": (0.9, 0.1),
+    f"{WEATHER_TOOL.name}\n{WEATHER_TOOL.description}": (0.3, 1.0),
+    f"{CALENDAR_TOOL.name}\n{CALENDAR_TOOL.description}": (0.0, 1.0),
+}
+
+
+class RecordingEmbedder:
+    def __init__(self) -> None:
+        self.calls: list[tuple[str, ...]] = []
+
+    async def __call__(self, texts: Sequence[str]) -> Sequence[Vector]:
+        self.calls.append(tuple(texts))
+        return tuple(FAKE_VECTORS[text] for text in texts)
+
+
+def _ranker(embedder: RecordingEmbedder | None = None) -> SemanticToolRanker:
+    return SemanticToolRanker(embed=embedder or RecordingEmbedder(), embedding_model="emb", index=SemanticTextIndex())
+
+
+def _names(results: Sequence[ToolSearchResult] | EmbeddingFailed) -> list[str]:
+    assert not isinstance(results, EmbeddingFailed)
+    return [tool["name"] for tool in results]
+
+
+class TestSearchMcpTools:
+    @pytest.mark.asyncio
+    async def test_semantic_mode_finds_foreign_exchange_tool_for_fx(self) -> None:
+        keyword_only = await search_mcp_tools("FX", CATALOG, 5, MCPToolSearchSettings(), ranker=None)
+        assert _names(keyword_only) == []
+
+        results = await search_mcp_tools("FX", CATALOG, 5, MCPToolSearchSettings(embedding_model="emb"), _ranker())
+        assert _names(results) == [FX_TOOL.name, WEATHER_TOOL.name, CALENDAR_TOOL.name]
+        assert not isinstance(results, EmbeddingFailed)
+        assert results[0]["score"] > results[1]["score"] > results[2]["score"]
+        assert results[0]["inputSchema"] == FX_TOOL.inputSchema
+
+    @pytest.mark.asyncio
+    async def test_similarity_threshold_drops_weak_matches(self) -> None:
+        settings = MCPToolSearchSettings(embedding_model="emb", similarity_threshold=0.5)
+        results = await search_mcp_tools("FX", CATALOG, 5, settings, _ranker())
+        assert _names(results) == [FX_TOOL.name]
+
+    @pytest.mark.asyncio
+    async def test_request_top_k_limits_semantic_results(self) -> None:
+        results = await search_mcp_tools("FX", CATALOG, 2, MCPToolSearchSettings(embedding_model="emb"), _ranker())
+        assert _names(results) == [FX_TOOL.name, WEATHER_TOOL.name]
+
+    @pytest.mark.asyncio
+    async def test_configured_top_k_caps_request_top_k(self) -> None:
+        settings = MCPToolSearchSettings(embedding_model="emb", top_k=1)
+        assert _names(await search_mcp_tools("FX", CATALOG, 50, settings, _ranker())) == [FX_TOOL.name]
+        assert _names(await search_mcp_tools("weather", CATALOG, 50, MCPToolSearchSettings(top_k=1), None)) == [
+            WEATHER_TOOL.name
+        ]
+
+    @pytest.mark.asyncio
+    async def test_core_tools_lead_and_do_not_consume_top_k(self) -> None:
+        settings = MCPToolSearchSettings(embedding_model="emb", top_k=1, core_tools=(CALENDAR_TOOL.name,))
+        results = await search_mcp_tools("FX", CATALOG, 1, settings, _ranker())
+        assert _names(results) == [CALENDAR_TOOL.name, FX_TOOL.name]
+        assert not isinstance(results, EmbeddingFailed)
+        assert "score" not in results[0]
+
+    @pytest.mark.asyncio
+    async def test_core_tools_apply_in_keyword_mode_too(self) -> None:
+        settings = MCPToolSearchSettings(core_tools=(CALENDAR_TOOL.name,))
+        assert _names(await search_mcp_tools("weather", CATALOG, 5, settings, None)) == [
+            CALENDAR_TOOL.name,
+            WEATHER_TOOL.name,
+        ]
+
+    @pytest.mark.asyncio
+    async def test_core_tools_outside_the_callers_catalog_are_not_returned(self) -> None:
+        settings = MCPToolSearchSettings(embedding_model="emb", core_tools=("payroll-run", CALENDAR_TOOL.name))
+        results = await search_mcp_tools("FX", (FX_TOOL, WEATHER_TOOL), 5, settings, _ranker())
+        assert _names(results) == [FX_TOOL.name, WEATHER_TOOL.name]
+
+    @pytest.mark.asyncio
+    async def test_core_tools_are_listed_once_and_never_embedded(self) -> None:
+        embedder = RecordingEmbedder()
+        settings = MCPToolSearchSettings(embedding_model="emb", core_tools=(FX_TOOL.name, FX_TOOL.name))
+        results = await search_mcp_tools("FX", CATALOG, 5, settings, _ranker(embedder))
+        assert _names(results) == [FX_TOOL.name, WEATHER_TOOL.name, CALENDAR_TOOL.name]
+        assert all(FX_TOOL.description not in text for call in embedder.calls for text in call)
+
+    @pytest.mark.asyncio
+    async def test_empty_query_returns_only_core_tools_without_embedding(self) -> None:
+        embedder = RecordingEmbedder()
+        settings = MCPToolSearchSettings(embedding_model="emb", core_tools=(CALENDAR_TOOL.name,))
+        assert _names(await search_mcp_tools("", CATALOG, 5, settings, _ranker(embedder))) == [CALENDAR_TOOL.name]
+        assert embedder.calls == []
+
+    @pytest.mark.asyncio
+    async def test_repeat_searches_only_embed_the_query(self) -> None:
+        embedder = RecordingEmbedder()
+        ranker = _ranker(embedder)
+        settings = MCPToolSearchSettings(embedding_model="emb")
+        await search_mcp_tools("FX", CATALOG, 5, settings, ranker)
+        await search_mcp_tools("FX", CATALOG, 5, settings, ranker)
+        assert [len(call) for call in embedder.calls] == [4, 1]
+
+    @pytest.mark.asyncio
+    async def test_embedding_failure_is_reported_not_raised(self) -> None:
+        async def failing(texts: Sequence[str]) -> Sequence[Vector]:
+            raise ValueError("embedding model is down")
+
+        ranker = SemanticToolRanker(embed=failing, embedding_model="emb", index=SemanticTextIndex())
+        result = await search_mcp_tools("FX", CATALOG, 5, MCPToolSearchSettings(embedding_model="emb"), ranker)
+        assert isinstance(result, EmbeddingFailed)
+        assert "embedding model is down" in result.reason
+
+
+class TestMcpToolSearchSettings:
+    def test_rejects_out_of_range_values(self) -> None:
+        from pydantic import ValidationError
+
+        with pytest.raises(ValidationError):
+            MCPToolSearchSettings(top_k=0)
+        with pytest.raises(ValidationError):
+            MCPToolSearchSettings(similarity_threshold=1.5)
+
+    def test_yaml_shape_round_trips(self) -> None:
+        settings = MCPToolSearchSettings.model_validate(
+            {"embedding_model": "emb", "top_k": 3, "similarity_threshold": 0.2, "core_tools": ["a", "b"]}
+        )
+        assert settings.core_tools == ("a", "b")
+        assert settings.model_dump() == {
+            "embedding_model": "emb",
+            "top_k": 3,
+            "similarity_threshold": 0.2,
+            "core_tools": ("a", "b"),
+        }
+
+
 class TestCoerceTopK:
     def test_int_passthrough(self) -> None:
         assert coerce_top_k(3) == 3
@@ -92,10 +249,10 @@ class TestSearchTools:
         assert len(results) <= 2
 
     def test_empty_query_returns_empty(self) -> None:
-        assert search_tools("", SAMPLE_TOOLS) == []
+        assert search_tools("", SAMPLE_TOOLS) == ()
 
     def test_no_match_returns_empty(self) -> None:
-        assert search_tools("xyzzy_nonexistent_zzz", SAMPLE_TOOLS) == []
+        assert search_tools("xyzzy_nonexistent_zzz", SAMPLE_TOOLS) == ()
 
     def test_matches_description_not_just_name(self) -> None:
         results = search_tools("channel", SAMPLE_TOOLS)
@@ -603,6 +760,63 @@ class TestCallToolRestApiVirtualTools:
         assert result.isError is True
         assert result.content[0].text == "set agent_search_embedding_model"
 
+    def _semantic_request(self, query: str = "FX") -> MagicMock:
+        return self._make_request({"name": MCP_TOOL_SEARCH_TOOL_NAME, "arguments": {"query": query}})
+
+    @pytest.mark.asyncio
+    async def test_mcp_tool_search_ranks_the_callers_catalog_with_the_configured_embedding_model(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        monkeypatch.setattr(litellm, "mcp_tool_search", {"embedding_model": "emb", "similarity_threshold": 0.5})
+        user_api_key_dict = UserAPIKeyAuth(
+            api_key="k", team_id="team-1", object_permission=_make_perm(mcp_tool_search_enabled=True)
+        )
+
+        async def fake_aembedding(model: str, input: list[str], metadata: dict[str, Any]) -> MagicMock:
+            assert model == "emb"
+            assert metadata["user_api_key"] == "k"
+            assert metadata["user_api_key_team_id"] == "team-1"
+            response = MagicMock()
+            response.model_dump.return_value = {"data": [{"embedding": list(FAKE_VECTORS[t])} for t in input]}
+            return response
+
+        router = MagicMock()
+        router.aembedding = AsyncMock(side_effect=fake_aembedding)
+        with (
+            patch(  # test-quality-ok: the proxy's router is a module global; the handler reaches it the way production does
+                "litellm.proxy.proxy_server.llm_router", router
+            ),
+            patch(  # test-quality-ok: the authorized catalog is the seam every virtual tool shares; the ranking under test stays real
+                "litellm.proxy._experimental.mcp_server.server._list_mcp_tools",
+                new_callable=AsyncMock,
+                return_value=AggregateToolListing(tools=list(CATALOG), outcomes={}),
+            ) as mock_list,
+        ):
+            result = await self._get_call_fn()(request=self._semantic_request(), user_api_key_dict=user_api_key_dict)
+
+        assert mock_list.await_args.kwargs["user_api_key_auth"] is user_api_key_dict
+        assert result.isError is False
+        assert [t["name"] for t in json.loads(result.content[0].text)] == [FX_TOOL.name]
+
+    @pytest.mark.asyncio
+    async def test_mcp_tool_search_reports_missing_router_as_tool_error(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        monkeypatch.setattr(litellm, "mcp_tool_search", {"embedding_model": "emb"})
+        user_api_key_dict = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True))
+        with patch(  # test-quality-ok: the proxy's router is a module global; the handler reaches it the way production does
+            "litellm.proxy.proxy_server.llm_router", None
+        ):
+            result = await self._get_call_fn()(request=self._semantic_request(), user_api_key_dict=user_api_key_dict)
+        assert result.isError is True
+        assert "mcp_tool_search.embedding_model" in result.content[0].text
+
+    @pytest.mark.asyncio
+    async def test_mcp_tool_search_reports_invalid_settings_as_tool_error(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        monkeypatch.setattr(litellm, "mcp_tool_search", {"top_k": 0})
+        user_api_key_dict = UserAPIKeyAuth(api_key="k", object_permission=_make_perm(mcp_tool_search_enabled=True))
+        result = await self._get_call_fn()(request=self._semantic_request(), user_api_key_dict=user_api_key_dict)
+        assert result.isError is True
+        assert "top_k" in result.content[0].text
+
     @pytest.mark.asyncio
     async def test_agent_search_requires_flag_enabled(self) -> None:
         from fastapi import HTTPException
diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
index ef5631218f3..d441c05090b 100644
--- a/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
+++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
@@ -1,4 +1,5 @@
 import asyncio
+import inspect
 import json
 import sys
 from datetime import datetime
@@ -13,6 +14,7 @@ import pytest
 from fastapi import HTTPException
 from starlette.requests import Request
 
+from litellm.constants import MCP_TOOL_LISTING_TIMEOUT
 from litellm.proxy._experimental.mcp_server import rest_endpoints
 from litellm.proxy._experimental.mcp_server.auth import (
     user_api_key_auth_mcp as auth_mcp,
@@ -109,6 +111,71 @@ class TestExecuteWithMcpClient:
         assert result["status"] == "error"
         assert "stack_trace" not in result
 
+    @pytest.mark.asyncio
+    async def test_timeout_caps_hanging_operation_and_names_url(self, monkeypatch):
+        async def fake_create_client(*args, **kwargs):
+            return object()
+
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "_create_mcp_client",
+            fake_create_client,
+        )
+
+        async def hanging_operation(client):
+            await asyncio.Event().wait()
+
+        payload = NewMCPServerRequest(
+            server_name="example",
+            url="https://mcp.example.com/mcp/",
+            auth_type=MCPAuth.none,
+        )
+
+        result = await asyncio.wait_for(
+            rest_endpoints._execute_with_mcp_client(payload, hanging_operation, timeout_seconds=0.05),
+            timeout=5,
+        )
+
+        assert result["error"] is True
+        assert "https://mcp.example.com/mcp/" in result["message"]
+
+    @pytest.mark.asyncio
+    async def test_timeout_covers_client_creation(self, monkeypatch):
+        async def hanging_create_client(*args, **kwargs):
+            await asyncio.Event().wait()
+
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "_create_mcp_client",
+            hanging_create_client,
+        )
+
+        async def unreached_operation(client):
+            return {"status": "ok"}
+
+        payload = NewMCPServerRequest(
+            server_name="example",
+            url="https://mcp.example.com/mcp/",
+            auth_type=MCPAuth.none,
+        )
+
+        result = await asyncio.wait_for(
+            rest_endpoints._execute_with_mcp_client(payload, unreached_operation, timeout_seconds=0.05),
+            timeout=5,
+        )
+
+        assert result["error"] is True
+        assert "https://mcp.example.com/mcp/" in result["message"]
+
+    def test_timeout_defaults_to_tool_listing_timeout(self):
+        default = inspect.signature(rest_endpoints._execute_with_mcp_client).parameters["timeout_seconds"].default
+        assert default == MCP_TOOL_LISTING_TIMEOUT
+
+    def test_connection_error_message_timeout_names_url_and_budget(self):
+        message = rest_endpoints._connection_error_message(TimeoutError(), "https://api.example.com/mcp/", 30.0)
+        assert "https://api.example.com/mcp/" in message
+        assert "30s" in message
+
     @pytest.mark.asyncio
     async def test_forwards_static_headers(self, monkeypatch):
         """Ensure static_headers are forwarded to the MCP client during test calls.
@@ -214,6 +281,46 @@ class TestExecuteWithMcpClient:
         assert server.scopes == ["read", "write"]
         assert server.has_client_credentials is True
 
+    async def test_preview_forwards_per_server_timeout_to_client_factory(self, monkeypatch):
+        """The request's per-server timeout must reach the temporary MCPServer model:
+        the client factory reads ``server.timeout`` for both the per-request timeout
+        and the preview's whole-walk listing deadline."""
+        captured: dict = {}
+
+        def fake_build_stdio_env(server, raw_headers):
+            return None
+
+        async def fake_create_client(*args, **kwargs):
+            captured["server"] = kwargs.get("server")
+            return object()
+
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "_build_stdio_env",
+            fake_build_stdio_env,
+            raising=False,
+        )
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "_create_mcp_client",
+            fake_create_client,
+            raising=False,
+        )
+
+        async def ok_operation(client):
+            return {"status": "ok"}
+
+        payload = NewMCPServerRequest(
+            server_name="slow-catalog-server",
+            url="https://example.com",
+            timeout=120.5,
+        )
+
+        result = await rest_endpoints._execute_with_mcp_client(payload, ok_operation)
+
+        assert result["status"] == "ok"
+        assert captured["server"].timeout == 120.5
+
     @pytest.mark.asyncio
     async def test_m2m_drops_incoming_oauth2_headers(self, monkeypatch):
         """For M2M OAuth servers the incoming Authorization header (which carries
@@ -524,6 +631,131 @@ class TestTestToolsList:
         assert captured["oauth2_headers"] is None
         assert oauth_call_counter["count"] == 0
 
+    async def test_preview_tools_list_times_out_on_slow_pagination(self, monkeypatch):
+        """A preview whose upstream paginates past the listing deadline returns a
+        timeout error instead of holding the request open."""
+        monkeypatch.setattr(rest_endpoints, "MCP_CLIENT_TIMEOUT", 0.05, raising=False)
+        monkeypatch.setattr(rest_endpoints, "MCP_TOOL_LISTING_TIMEOUT", 0.05, raising=False)
+
+        class SlowClient:
+            async def list_tools(self, raise_on_error=False):
+                await asyncio.sleep(1)
+                return []
+
+        async def fake_execute(
+            request,
+            operation,
+            mcp_auth_header=None,
+            oauth2_headers=None,
+            raw_headers=None,
+        ):
+            return await operation(SlowClient())
+
+        monkeypatch.setattr(rest_endpoints, "_execute_with_mcp_client", fake_execute, raising=False)
+
+        from litellm.proxy._types import LitellmUserRoles
+
+        request = _build_request()
+        payload = NewMCPServerRequest(
+            server_name="example",
+            url="https://example.com",
+            auth_type=MCPAuth.api_key,
+            credentials={"auth_value": "secret-key"},
+        )
+
+        result = await rest_endpoints.test_tools_list(
+            request,
+            payload,
+            user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN),
+        )
+
+        assert result["status"] == "error"
+        assert result["error"] is True
+        assert "Timed out listing tools" in result["message"]
+
+    async def test_preview_tools_list_succeeds_within_deadline(self, monkeypatch):
+        """The preview timeout scope passes a fast listing through untouched."""
+        from mcp.types import Tool as MCPTool
+
+        class QuickClient:
+            async def list_tools(self, raise_on_error=False):
+                return [MCPTool(name="quick_tool", description="q", inputSchema={})]
+
+        async def fake_execute(
+            request,
+            operation,
+            mcp_auth_header=None,
+            oauth2_headers=None,
+            raw_headers=None,
+        ):
+            return await operation(QuickClient())
+
+        monkeypatch.setattr(rest_endpoints, "_execute_with_mcp_client", fake_execute, raising=False)
+
+        from litellm.proxy._types import LitellmUserRoles
+
+        request = _build_request()
+        payload = NewMCPServerRequest(
+            server_name="example",
+            url="https://example.com",
+            auth_type=MCPAuth.api_key,
+            credentials={"auth_value": "secret-key"},
+        )
+
+        result = await rest_endpoints.test_tools_list(
+            request,
+            payload,
+            user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN),
+        )
+
+        assert result["error"] is None
+        assert result["message"] == "Successfully retrieved tools"
+        assert [tool["name"] for tool in result["tools"]] == ["quick_tool"]
+
+    async def test_preview_tools_list_honors_per_server_timeout(self, monkeypatch):
+        """A per-server timeout above the global default extends the preview deadline."""
+        monkeypatch.setattr(rest_endpoints, "MCP_CLIENT_TIMEOUT", 0.05, raising=False)
+        monkeypatch.setattr(rest_endpoints, "MCP_TOOL_LISTING_TIMEOUT", 0.05, raising=False)
+
+        from mcp.types import Tool as MCPTool
+
+        class SlowConfiguredClient:
+            timeout = 1.0
+
+            async def list_tools(self, raise_on_error=False):
+                await asyncio.sleep(0.2)
+                return [MCPTool(name="slow_tool", description="s", inputSchema={})]
+
+        async def fake_execute(
+            request,
+            operation,
+            mcp_auth_header=None,
+            oauth2_headers=None,
+            raw_headers=None,
+        ):
+            return await operation(SlowConfiguredClient())
+
+        monkeypatch.setattr(rest_endpoints, "_execute_with_mcp_client", fake_execute, raising=False)
+
+        from litellm.proxy._types import LitellmUserRoles
+
+        request = _build_request()
+        payload = NewMCPServerRequest(
+            server_name="example",
+            url="https://example.com",
+            auth_type=MCPAuth.api_key,
+            credentials={"auth_value": "secret-key"},
+        )
+
+        result = await rest_endpoints.test_tools_list(
+            request,
+            payload,
+            user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN),
+        )
+
+        assert result["error"] is None
+        assert [tool["name"] for tool in result["tools"]] == ["slow_tool"]
+
     async def test_extracts_oauth2_headers(self, monkeypatch):
         """Ensure oauth2 auth type pulls oauth headers and omits MCP auth header."""
 
@@ -786,9 +1018,7 @@ class TestListToolsRestAPI:
         they do for a gateway session, never to the bare session key."""
         from litellm.constants import UI_SESSION_TOKEN_TEAM_ID
 
-        session_auth = UserAPIKeyAuth(
-            team_id=UI_SESSION_TOKEN_TEAM_ID, user_id="grant-user", user_role="internal_user"
-        )
+        session_auth = UserAPIKeyAuth(team_id=UI_SESSION_TOKEN_TEAM_ID, user_id="grant-user", user_role="internal_user")
         admitted_auth = UserAPIKeyAuth(user_id="grant-user", org_id="admitted-org")
 
         async def fake_reload(user_id):
@@ -868,9 +1098,7 @@ class TestListToolsRestAPI:
         from litellm.constants import UI_SESSION_TOKEN_TEAM_ID
         from litellm.proxy._types import LiteLLM_ObjectPermissionTable
 
-        session_auth = UserAPIKeyAuth(
-            team_id=UI_SESSION_TOKEN_TEAM_ID, user_id="grant-user", user_role="internal_user"
-        )
+        session_auth = UserAPIKeyAuth(team_id=UI_SESSION_TOKEN_TEAM_ID, user_id="grant-user", user_role="internal_user")
         scoped_auth = UserAPIKeyAuth(
             object_permission=LiteLLM_ObjectPermissionTable(
                 object_permission_id="toolset-scope",
@@ -952,6 +1180,123 @@ class TestListToolsRestAPI:
         assert scope_inputs == [session_auth]
         assert reload_calls == []
 
+    async def test_single_server_response_includes_paginated_upstream_tools(
+        self,
+        monkeypatch,
+    ):
+        """The REST tools/list path should include tools beyond the upstream first page."""
+        import litellm.experimental_mcp_client.client as mcp_client_module
+        from mcp.types import ListToolsResult, PaginatedRequestParams
+        from mcp.types import Tool as MCPTool
+
+        from litellm.proxy._experimental.mcp_server.server import MCPServer
+        from litellm.types.mcp import MCPTransport
+
+        async def fake_contexts(user_api_key_auth):
+            return [user_api_key_auth]
+
+        async def fake_get_allowed_mcp_servers(*args, **kwargs):
+            return ["server-1"]
+
+        stub_server = MCPServer(
+            server_id="server-1",
+            name="stub",
+            server_name="stub",
+            alias="stub",
+            url="https://example.com/mcp",
+            transport=MCPTransport.http,
+            mcp_info={"server_name": "stub"},
+        )
+        stub_server.available_on_public_internet = True
+
+        mock_transport_ctx = AsyncMock()
+        mock_transport_ctx.__aenter__ = AsyncMock(return_value=(MagicMock(), MagicMock()))
+        mock_transport_ctx.__aexit__ = AsyncMock(return_value=None)
+        monkeypatch.setattr(
+            mcp_client_module,
+            "streamable_http_client",
+            MagicMock(return_value=mock_transport_ctx),
+            raising=False,
+        )
+
+        mock_session_ctx = AsyncMock()
+        mock_session_instance = AsyncMock()
+        mock_session_instance.initialize = AsyncMock(return_value=None)
+        mock_session_instance.list_tools.side_effect = [
+            ListToolsResult(
+                tools=[
+                    MCPTool(
+                        name="first_page_tool",
+                        description="First page tool",
+                        inputSchema={},
+                    )
+                ],
+                nextCursor="page-2",
+            ),
+            ListToolsResult(
+                tools=[
+                    MCPTool(
+                        name="second_page_tool",
+                        description="Second page tool",
+                        inputSchema={},
+                    )
+                ]
+            ),
+        ]
+        mock_session_ctx.__aenter__ = AsyncMock(return_value=mock_session_instance)
+        mock_session_ctx.__aexit__ = AsyncMock(return_value=None)
+        monkeypatch.setattr(
+            mcp_client_module,
+            "ClientSession",
+            MagicMock(return_value=mock_session_ctx),
+            raising=False,
+        )
+
+        monkeypatch.setattr(
+            rest_endpoints,
+            "build_effective_auth_contexts",
+            fake_contexts,
+            raising=False,
+        )
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "get_allowed_mcp_servers",
+            fake_get_allowed_mcp_servers,
+            raising=False,
+        )
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "filter_server_ids_by_ip_with_info",
+            lambda server_ids, client_ip: (server_ids, 0),
+            raising=False,
+        )
+        monkeypatch.setattr(
+            rest_endpoints.global_mcp_server_manager,
+            "get_mcp_server_by_id",
+            lambda server_id: stub_server if server_id == "server-1" else None,
+            raising=False,
+        )
+
+        request = _build_request(path="/mcp-rest/tools/list", method="GET")
+        result = await rest_endpoints.list_tool_rest_api(
+            request,
+            server_id="server-1",
+            user_api_key_dict=UserAPIKeyAuth(),
+        )
+
+        assert set(result.keys()) == {"tools", "error", "message"}
+        assert [tool.name for tool in result["tools"]] == [
+            "first_page_tool",
+            "second_page_tool",
+        ]
+        assert result["error"] is None
+        assert result["message"] == "Successfully retrieved tools"
+
+        assert mock_session_instance.list_tools.call_count == 2
+        second_call_params = mock_session_instance.list_tools.call_args_list[1].kwargs["params"]
+        assert isinstance(second_call_params, PaginatedRequestParams)
+        assert second_call_params.cursor == "page-2"
+
     async def test_include_disabled_tools_is_admin_only(self, monkeypatch):
         """include_disabled_tools skips the allowlist filter only for PROXY_ADMIN;
         a non-admin passing it stays filtered so the REST endpoint can't be used
@@ -1153,7 +1498,11 @@ class TestListToolsRestAPI:
     async def test_aggregate_list_absorbs_one_server_auth_failure(self, monkeypatch):
         """The multi-server aggregate listing degrades a server whose upstream
         rejects auth to an empty contribution and still returns the healthy
-        server's tools with a 200, rather than surfacing a 401."""
+        server's tools with a 200, rather than surfacing a 401. The absorbed
+        server must still show up as a classified per-server outcome so a REST
+        caller can tell "needs upstream auth" apart from "has no tools"."""
+        from pydantic import TypeAdapter
+
         from litellm.proxy._experimental.mcp_server.exceptions import (
             MCPUpstreamAuthError,
         )
@@ -1219,6 +1568,11 @@ class TestListToolsRestAPI:
 
         assert result["tools"] == ["good-tool"]
         assert result["error"] is None
+        wire_body = json.loads(TypeAdapter(dict).dump_json(result))
+        assert wire_body["server_outcomes"] == {
+            "good": {"status": "ok", "tool_count": 1},
+            "bad": {"status": "auth_required", "http_status": 401},
+        }
 
     async def test_name_resolution_finds_server_by_uuid(self, monkeypatch):
         """When server_id is a name string, it should be resolved to its UUID
@@ -2881,17 +3235,21 @@ class TestConnectionErrorMessage:
         secret = "Bearer sk-super-secret-token"
         exc = httpx.LocalProtocolError(f"Illegal header value b' {secret}'")
 
-        message = rest_endpoints._connection_error_message(exc)
+        message = rest_endpoints._connection_error_message(exc, "https://example.com", 30.0)
 
         assert "header" in message.lower()
         assert secret not in message
 
     def test_connect_error_points_at_reachability(self):
-        message = rest_endpoints._connection_error_message(httpx.ConnectError("All connection attempts failed"))
+        message = rest_endpoints._connection_error_message(
+            httpx.ConnectError("All connection attempts failed"), "https://example.com", 30.0
+        )
         assert "unreachable" in message.lower()
 
     def test_timeout_error_message(self):
-        message = rest_endpoints._connection_error_message(httpx.ConnectTimeout("timed out"))
+        message = rest_endpoints._connection_error_message(
+            httpx.ConnectTimeout("timed out"), "https://example.com", 30.0
+        )
         assert "unreachable" in message.lower()
 
     def test_http_status_error_includes_status_code(self):
@@ -2901,11 +3259,11 @@ class TestConnectionErrorMessage:
             request=httpx.Request("POST", "http://x/"),
             response=response,
         )
-        message = rest_endpoints._connection_error_message(exc)
+        message = rest_endpoints._connection_error_message(exc, "https://example.com", 30.0)
         assert "503" in message
 
     def test_unknown_error_falls_back_to_generic(self):
-        message = rest_endpoints._connection_error_message(RuntimeError("weird"))
+        message = rest_endpoints._connection_error_message(RuntimeError("weird"), "https://example.com", 30.0)
         assert "weird" not in message
         assert "proxy logs" in message.lower()
 
@@ -3021,9 +3379,7 @@ class TestRestListToolsetFiltering:
 
         mock_manager = MagicMock()
         mock_manager.expand_tool_permissions = MagicMock(side_effect=lambda perms: perms or {})
-        mock_manager.resolve_toolset_tool_permissions = AsyncMock(
-            return_value={"server-a": ["lookup_status"]}
-        )
+        mock_manager.resolve_toolset_tool_permissions = AsyncMock(return_value={"server-a": ["lookup_status"]})
 
         monkeypatch.setattr(
             rest_endpoints.global_mcp_server_manager,
diff --git a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
index 2ff38af80b1..43034f889f6 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_a2a_endpoints.py
@@ -918,6 +918,62 @@ async def test_task_method_failure_hook_uses_enriched_request_data():
     assert failure_data.get("agent_id") == "test-agent"
 
 
+@pytest.mark.asyncio
+async def test_agentcore_invalid_context_id_returns_jsonrpc_invalid_params_400():
+    from litellm.proxy._types import UserAPIKeyAuth
+
+    agent = _make_agent_mock()
+    agent.litellm_params = {
+        "custom_llm_provider": "bedrock",
+        "model": "bedrock/agentcore/arn:aws:bedrock-agentcore:us-west-2:123456789012:runtime/demo",
+        "api_key": "test-jwt-token",
+    }
+    mock_request = _make_request_mock(
+        "message/send",
+        {
+            "message": {
+                "role": "user",
+                "parts": [{"kind": "text", "text": "Hello"}],
+                "messageId": "msg-1",
+                "contextId": "too-short",
+            }
+        },
+    )
+    user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", user_id="u1", team_id="t1")
+
+    mock_proxy_logging = MagicMock()
+    mock_proxy_logging.pre_call_hook = AsyncMock(
+        side_effect=lambda user_api_key_dict, data, call_type: data
+    )
+    mock_proxy_logging.post_call_failure_hook = AsyncMock(return_value=None)
+
+    with ExitStack() as stack:
+        for p in _base_patches(agent):
+            stack.enter_context(p)
+        stack.enter_context(
+            patch(  # test-quality-ok: same proxy_logging_obj injection the sibling failure-hook test uses; no HTTP call is made because the request is rejected before signing
+                "litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging
+            )
+        )
+
+        from litellm.proxy.agent_endpoints.a2a_endpoints import invoke_agent_a2a
+
+        response = await invoke_agent_a2a(
+            agent_id="test-agent",
+            request=mock_request,
+            fastapi_response=MagicMock(),
+            user_api_key_dict=user_api_key_dict,
+        )
+
+    body = json.loads(response.body.decode())
+    assert response.status_code == 400
+    assert body["id"] == "req-1"
+    assert body["error"]["code"] == -32602
+    assert "Invalid AgentCore runtime session id" in body["error"]["message"]
+    assert "Internal error" not in body["error"]["message"]
+    mock_proxy_logging.post_call_failure_hook.assert_awaited_once()
+
+
 @pytest.mark.asyncio
 async def test_get_extended_agent_card_rewrites_url():
     from litellm.proxy._types import UserAPIKeyAuth
diff --git a/tests/test_litellm/proxy/agent_endpoints/test_agent_registry.py b/tests/test_litellm/proxy/agent_endpoints/test_agent_registry.py
index 7ce62fdf648..231626c7eb5 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_agent_registry.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_agent_registry.py
@@ -8,7 +8,18 @@ from unittest.mock import AsyncMock, MagicMock
 
 import pytest
 
-from litellm.proxy.agent_endpoints.agent_registry import AgentRegistry, GrantMigrationResult
+from litellm.constants import REDACTED_BY_LITELM_STRING
+from litellm.proxy.agent_endpoints.agent_registry import (
+    AgentRegistry,
+    GrantMigrationResult,
+    _restore_redacted_litellm_params,
+    redact_sensitive_agent_litellm_params,
+)
+
+# Obviously-fake stand-ins for a real AWS credential pair (LIT-6736 regression
+# fixtures) -- never a real key shape, and must never appear in any response.
+SENTINEL_AWS_ACCESS_KEY_ID: Final = "AKIATESTSENTINEL0000"
+SENTINEL_AWS_SECRET_ACCESS_KEY: Final = "test-sentinel-do-not-use-secret-value"
 
 
 def _sample_agent_card_params() -> dict:
@@ -49,6 +60,7 @@ async def test_update_agent_in_db_clears_static_headers_and_extra_headers_when_o
 
     mock_update = AsyncMock(return_value=updated_agent)
     mock_prisma.db.litellm_agentstable.update = mock_update
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(return_value=None)
 
     # Agent config WITHOUT static_headers or extra_headers (omitted)
     agent_config = {
@@ -95,6 +107,7 @@ async def test_update_agent_in_db_preserves_explicit_static_headers_and_extra_he
 
     mock_update = AsyncMock(return_value=updated_agent)
     mock_prisma.db.litellm_agentstable.update = mock_update
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(return_value=None)
 
     agent_config = {
         "agent_name": "Updated Agent",
@@ -436,6 +449,9 @@ async def test_update_agent_in_db_raises_when_row_deleted_mid_update():
     guard the code dereferences None and reports an opaque AttributeError instead of the id."""
     registry: Final = AgentRegistry()
     mock_prisma: Final = MagicMock()
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value=SimpleNamespace(litellm_params={}, object_permission_id=None)
+    )
     mock_prisma.db.litellm_agentstable.update = AsyncMock(return_value=None)
 
     with pytest.raises(Exception, match="Error updating agent in DB") as exc_info:
@@ -485,3 +501,492 @@ async def test_delete_agent_from_db_raises_when_row_already_gone():
         await registry.delete_agent_from_db(agent_id="agent-123", prisma_client=mock_prisma)
 
     assert str(exc_info.value) == "Error deleting agent from DB: Agent not found, passed agent_id=agent-123"
+
+
+# ---------- LIT-6736: agent litellm_params secret redaction ----------
+
+
+def test_redact_sensitive_agent_litellm_params_masks_secrets_keeps_the_rest():
+    """The sentinel secret must never appear in the redacted output; non-secret
+    keys (model reference, is_public) must survive untouched."""
+    redacted = redact_sensitive_agent_litellm_params(
+        {
+            "aws_access_key_id": SENTINEL_AWS_ACCESS_KEY_ID,
+            "aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY,
+            "model": "bedrock/agentcore/my-agent",
+            "is_public": True,
+        }
+    )
+
+    assert SENTINEL_AWS_ACCESS_KEY_ID not in json.dumps(redacted)
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY not in json.dumps(redacted)
+    assert redacted["aws_access_key_id"] == REDACTED_BY_LITELM_STRING
+    assert redacted["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["model"] == "bedrock/agentcore/my-agent"
+    assert redacted["is_public"] is True
+
+
+def test_redact_sensitive_agent_litellm_params_recurses_into_nested_dicts():
+    """A secret nested one level down (e.g. a per-provider sub-config) must
+    also be redacted, not just top-level keys."""
+    redacted = redact_sensitive_agent_litellm_params(
+        {"provider_config": {"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "region": "us-east-1"}}
+    )
+
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY not in json.dumps(redacted)
+    assert redacted["provider_config"]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["provider_config"]["region"] == "us-east-1"
+
+
+def test_redact_sensitive_agent_litellm_params_handles_none_and_json_string():
+    assert redact_sensitive_agent_litellm_params(None) is None
+
+    serialized = json.dumps({"api_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "model": "gpt-4"})
+    redacted = redact_sensitive_agent_litellm_params(serialized)
+
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY not in redacted
+    assert json.loads(redacted)["api_key"] == REDACTED_BY_LITELM_STRING
+    assert json.loads(redacted)["model"] == "gpt-4"
+
+
+def test_redact_sensitive_agent_litellm_params_recurses_into_lists_of_dicts():
+    """A secret nested inside a list of provider sub-configs (a shape a
+    non-sensitively-named key can legitimately hold) must also be redacted,
+    not silently returned as-is."""
+    redacted = redact_sensitive_agent_litellm_params(
+        {
+            "provider_configs": [
+                {"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "region": "us-east-1"},
+                {"aws_secret_access_key": "other-" + SENTINEL_AWS_SECRET_ACCESS_KEY, "region": "us-west-2"},
+            ]
+        }
+    )
+
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY not in json.dumps(redacted)
+    assert redacted["provider_configs"][0]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["provider_configs"][0]["region"] == "us-east-1"
+    assert redacted["provider_configs"][1]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["provider_configs"][1]["region"] == "us-west-2"
+
+
+def test_redact_sensitive_agent_litellm_params_redacts_secrets_inside_model_list():
+    """The exact shape flagged in review: litellm_params.model_list, where each
+    entry carries its own nested litellm_params with a provider credential."""
+    redacted = redact_sensitive_agent_litellm_params(
+        {
+            "model_list": [
+                {
+                    "model_name": "gpt-4",
+                    "litellm_params": {"api_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "model": "gpt-4"},
+                },
+                {
+                    "model_name": "claude",
+                    "litellm_params": {
+                        "aws_secret_access_key": "other-" + SENTINEL_AWS_SECRET_ACCESS_KEY,
+                        "model": "bedrock/claude",
+                    },
+                },
+            ]
+        }
+    )
+
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY not in json.dumps(redacted)
+    assert redacted["model_list"][0]["litellm_params"]["api_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["model_list"][0]["litellm_params"]["model"] == "gpt-4"
+    assert redacted["model_list"][1]["litellm_params"]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+    assert redacted["model_list"][1]["litellm_params"]["model"] == "bedrock/claude"
+
+
+def test_restore_redacted_litellm_params_preserves_secret_inside_model_list():
+    """The write-side counterpart: a caller editing a model_list entry's own
+    non-secret field (renaming it) while leaving that same entry's nested
+    secret masked must not corrupt the stored per-deployment credential.
+    List entries correspond by position (see the module docstring on
+    ``_restore_redacted_nested_value``), so this -- the common "edit this
+    entry, keep its secret" pattern -- must keep working."""
+    existing = {
+        "agent_name": "my-agent",
+        "model_list": [
+            {
+                "model_name": "gpt-4",
+                "litellm_params": {"api_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "model": "gpt-4"},
+            },
+        ],
+    }
+    incoming = {
+        "agent_name": "my-agent-renamed",
+        "model_list": [
+            {
+                "model_name": "gpt-4-renamed",
+                "litellm_params": {"api_key": REDACTED_BY_LITELM_STRING, "model": "gpt-4"},
+            },
+        ],
+    }
+
+    restored = _restore_redacted_litellm_params(incoming, existing)
+
+    assert SENTINEL_AWS_SECRET_ACCESS_KEY == restored["model_list"][0]["litellm_params"]["api_key"]
+    assert restored["model_list"][0]["model_name"] == "gpt-4-renamed"
+    assert restored["agent_name"] == "my-agent-renamed"
+
+
+def test_restore_redacted_litellm_params_matches_list_entries_by_position():
+    """Documents the accepted trade-off: a list has no stable per-element
+    identity in a plain ``dict[str, object]`` schema, so restoration matches
+    entries by index, the same correspondence every other part of this merge
+    (and the endpoints' full-replace-on-PUT semantics) already assumes. If a
+    caller both reorders the list AND echoes back a masked marker in the same
+    request, a credential can end up attached to a different logical entry.
+    That is a known, narrow limitation -- not a leak between different
+    agents or tenants, since it only reshuffles one agent's own stored
+    values -- and this test pins the current, deliberate behavior rather
+    than asserting it away."""
+    existing = {
+        "model_list": [
+            {"model_name": "gpt-4", "litellm_params": {"api_key": SENTINEL_AWS_SECRET_ACCESS_KEY}},
+            {"model_name": "claude", "litellm_params": {"api_key": "other-" + SENTINEL_AWS_SECRET_ACCESS_KEY}},
+        ],
+    }
+    incoming = {
+        "model_list": [
+            # Same index (0) now holds what used to be at index 1's entry.
+            {"model_name": "claude", "litellm_params": {"api_key": REDACTED_BY_LITELM_STRING}},
+        ],
+    }
+
+    restored = _restore_redacted_litellm_params(incoming, existing)
+
+    assert restored["model_list"][0]["litellm_params"]["api_key"] == SENTINEL_AWS_SECRET_ACCESS_KEY
+
+
+def test_restore_redacted_litellm_params_recovers_a_whole_subtree_collapsed_by_the_depth_cap():
+    """Past the read-side recursion depth cap, a whole nested subtree is
+    collapsed to the flat REDACTED_BY_LITELM marker rather than a dict/list.
+    If the caller echoes that flat marker back unchanged, the whole
+    subtree -- not just the literal marker string -- must be restored."""
+    existing_subtree = {"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY, "region": "us-east-1"}
+    incoming = {"provider_config": REDACTED_BY_LITELM_STRING}
+    existing = {"provider_config": existing_subtree}
+
+    restored = _restore_redacted_litellm_params(incoming, existing)
+
+    assert restored["provider_config"] == existing_subtree
+
+
+def test_redact_sensitive_agent_litellm_params_does_not_reinterpret_plain_string_values_as_json():
+    """A plain non-JSON string value (most string leaves) must pass through
+    unchanged rather than failing to parse and getting redacted."""
+    redacted = redact_sensitive_agent_litellm_params({"model": "bedrock/agentcore/my-agent", "is_public": True})
+
+    assert redacted["model"] == "bedrock/agentcore/my-agent"
+    assert redacted["is_public"] is True
+
+
+@pytest.mark.asyncio
+async def test_add_agent_to_db_drops_a_sentinel_value_instead_of_storing_the_placeholder():
+    """A create has nothing stored to restore behind a redaction marker, so a
+    sensitive key submitted as the literal marker is dropped rather than
+    persisted as the placeholder string itself."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+    created_agent = MagicMock()
+    created_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Test Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    created_agent.object_permission = None
+    mock_create = AsyncMock(return_value=created_agent)
+    mock_prisma.db.litellm_agentstable.create = mock_create
+
+    await registry.add_agent_to_db(
+        agent={
+            "agent_name": "Test Agent",
+            "agent_card_params": _sample_agent_card_params(),
+            "litellm_params": {
+                "aws_secret_access_key": REDACTED_BY_LITELM_STRING,
+                "model": "bedrock/agentcore/my-agent",
+            },
+        },
+        prisma_client=mock_prisma,
+        created_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_create.call_args.kwargs["data"]["litellm_params"])
+    assert "aws_secret_access_key" not in stored_params
+    assert stored_params["model"] == "bedrock/agentcore/my-agent"
+
+
+@pytest.mark.asyncio
+async def test_update_agent_in_db_preserves_secret_when_echoed_back_redacted():
+    """PUT round-trips the GET response, which shows the secret redacted. Saving
+    an unrelated field change must not overwrite the real stored credential
+    with the redaction marker."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value=SimpleNamespace(
+            litellm_params={
+                "aws_access_key_id": SENTINEL_AWS_ACCESS_KEY_ID,
+                "aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY,
+                "model": "bedrock/agentcore/my-agent",
+            },
+            object_permission_id=None,
+        )
+    )
+    updated_agent = MagicMock()
+    updated_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Renamed Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    updated_agent.object_permission = None
+    mock_update = AsyncMock(return_value=updated_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.update_agent_in_db(
+        agent_id="agent-123",
+        agent={
+            "agent_name": "Renamed Agent",
+            "agent_card_params": _sample_agent_card_params(),
+            # The UI round-tripped the redacted secret and the untouched
+            # access key id verbatim; only agent_name actually changed.
+            "litellm_params": {
+                "aws_access_key_id": SENTINEL_AWS_ACCESS_KEY_ID,
+                "aws_secret_access_key": REDACTED_BY_LITELM_STRING,
+                "model": "bedrock/agentcore/my-agent",
+            },
+        },
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_update.call_args.kwargs["data"]["litellm_params"])
+    assert stored_params["aws_secret_access_key"] == SENTINEL_AWS_SECRET_ACCESS_KEY
+    assert stored_params["aws_access_key_id"] == SENTINEL_AWS_ACCESS_KEY_ID
+    assert stored_params["model"] == "bedrock/agentcore/my-agent"
+
+
+@pytest.mark.asyncio
+async def test_update_agent_in_db_preserves_secret_when_key_omitted_entirely():
+    """Omitting the sensitive key altogether must fall back to the stored
+    value too, not just an explicit redaction-marker round-trip."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value=SimpleNamespace(
+            litellm_params={"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY},
+            object_permission_id=None,
+        )
+    )
+    updated_agent = MagicMock()
+    updated_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Test Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    updated_agent.object_permission = None
+    mock_update = AsyncMock(return_value=updated_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.update_agent_in_db(
+        agent_id="agent-123",
+        agent={
+            "agent_name": "Test Agent",
+            "agent_card_params": _sample_agent_card_params(),
+            "litellm_params": {"model": "bedrock/agentcore/my-agent"},
+        },
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_update.call_args.kwargs["data"]["litellm_params"])
+    assert stored_params["aws_secret_access_key"] == SENTINEL_AWS_SECRET_ACCESS_KEY
+
+
+@pytest.mark.asyncio
+async def test_update_agent_in_db_preserves_secret_nested_under_a_non_sensitive_key():
+    """A secret nested inside a dict held by a non-sensitively-named key
+    (e.g. a per-provider sub-config) must also survive an echoed-back
+    redaction marker, not just top-level secret keys."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value=SimpleNamespace(
+            litellm_params={
+                "provider_config": {
+                    "aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY,
+                    "region": "us-east-1",
+                }
+            },
+            object_permission_id=None,
+        )
+    )
+    updated_agent = MagicMock()
+    updated_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Test Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    updated_agent.object_permission = None
+    mock_update = AsyncMock(return_value=updated_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.update_agent_in_db(
+        agent_id="agent-123",
+        agent={
+            "agent_name": "Test Agent",
+            "agent_card_params": _sample_agent_card_params(),
+            "litellm_params": {
+                # The GET response redacted the nested secret; the caller
+                # round-trips it verbatim while changing nothing.
+                "provider_config": {
+                    "aws_secret_access_key": REDACTED_BY_LITELM_STRING,
+                    "region": "us-west-2",
+                }
+            },
+        },
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_update.call_args.kwargs["data"]["litellm_params"])
+    assert stored_params["provider_config"]["aws_secret_access_key"] == SENTINEL_AWS_SECRET_ACCESS_KEY
+    assert stored_params["provider_config"]["region"] == "us-west-2"
+
+
+@pytest.mark.asyncio
+async def test_update_agent_in_db_clears_secret_on_explicit_empty_value():
+    """An explicit empty string is a deliberate clear, distinct from an omitted
+    key or the redaction marker, and must actually clear the stored secret."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value=SimpleNamespace(
+            litellm_params={"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY},
+            object_permission_id=None,
+        )
+    )
+    updated_agent = MagicMock()
+    updated_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Test Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    updated_agent.object_permission = None
+    mock_update = AsyncMock(return_value=updated_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.update_agent_in_db(
+        agent_id="agent-123",
+        agent={
+            "agent_name": "Test Agent",
+            "agent_card_params": _sample_agent_card_params(),
+            "litellm_params": {"aws_secret_access_key": ""},
+        },
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_update.call_args.kwargs["data"]["litellm_params"])
+    assert stored_params["aws_secret_access_key"] == ""
+
+
+@pytest.mark.asyncio
+async def test_patch_agent_in_db_preserves_secret_when_litellm_params_omitted():
+    """A PATCH that only renames the agent must not touch (let alone drop) the
+    stored litellm_params secret."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value={
+            "agent_id": "agent-123",
+            "agent_name": "Old Name",
+            "litellm_params": {"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY},
+            "object_permission_id": None,
+        }
+    )
+    patched_agent = MagicMock()
+    patched_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "New Name",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {"aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY},
+        "object_permission": None,
+    }
+    patched_agent.object_permission = None
+    mock_update = AsyncMock(return_value=patched_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.patch_agent_in_db(
+        agent_id="agent-123",
+        agent={"agent_name": "New Name"},
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    update_data: Final = mock_update.call_args.kwargs["data"]
+    assert "litellm_params" not in update_data
+
+
+@pytest.mark.asyncio
+async def test_patch_agent_in_db_preserves_secret_when_echoed_back_redacted():
+    """A PATCH that includes litellm_params (e.g. to flip an unrelated flag)
+    with the secret round-tripped as the redaction marker must not clobber
+    the stored credential."""
+    registry: Final = AgentRegistry()
+    mock_prisma: Final = MagicMock()
+
+    mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+        return_value={
+            "agent_id": "agent-123",
+            "agent_name": "Test Agent",
+            "litellm_params": {
+                "aws_secret_access_key": SENTINEL_AWS_SECRET_ACCESS_KEY,
+                "is_public": False,
+            },
+            "object_permission_id": None,
+        }
+    )
+    patched_agent = MagicMock()
+    patched_agent.model_dump.return_value = {
+        "agent_id": "agent-123",
+        "agent_name": "Test Agent",
+        "agent_card_params": _sample_agent_card_params(),
+        "litellm_params": {},
+        "object_permission": None,
+    }
+    patched_agent.object_permission = None
+    mock_update = AsyncMock(return_value=patched_agent)
+    mock_prisma.db.litellm_agentstable.update = mock_update
+
+    await registry.patch_agent_in_db(
+        agent_id="agent-123",
+        agent={
+            "litellm_params": {
+                "aws_secret_access_key": REDACTED_BY_LITELM_STRING,
+                "is_public": True,
+            }
+        },
+        prisma_client=mock_prisma,
+        updated_by="test-user",
+    )
+
+    stored_params: Final = json.loads(mock_update.call_args.kwargs["data"]["litellm_params"])
+    assert stored_params["aws_secret_access_key"] == SENTINEL_AWS_SECRET_ACCESS_KEY
+    assert stored_params["is_public"] is True
diff --git a/tests/test_litellm/proxy/agent_endpoints/test_agent_search.py b/tests/test_litellm/proxy/agent_endpoints/test_agent_search.py
index 3fb09076e5f..daca244c0a1 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_agent_search.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_agent_search.py
@@ -16,13 +16,12 @@ from litellm.proxy.agent_endpoints.agent_search import (
     AgentSearchHits,
     AgentSearchIndex,
     AgentSearchNotConfigured,
-    Vector,
     agent_search_text,
-    cosine_similarity,
     search_agents,
 )
 from litellm.proxy.agent_endpoints.auth.agent_permission_handler import RestrictedAgentAccess
 from litellm.proxy.agent_endpoints.endpoints import router, user_api_key_auth
+from litellm.proxy.common_utils.semantic_text_index import Vector, cosine_similarity
 from litellm.types.agents import AgentResponse
 
 CALLER: Final = UserAPIKeyAuth(api_key="hashed-caller-key", team_id="team-1", user_id="user-1")
diff --git a/tests/test_litellm/proxy/agent_endpoints/test_endpoints.py b/tests/test_litellm/proxy/agent_endpoints/test_endpoints.py
index ea196bda529..a78b3238a9a 100644
--- a/tests/test_litellm/proxy/agent_endpoints/test_endpoints.py
+++ b/tests/test_litellm/proxy/agent_endpoints/test_endpoints.py
@@ -4,6 +4,7 @@ import pytest
 from fastapi import FastAPI
 from fastapi.testclient import TestClient
 
+from litellm.constants import REDACTED_BY_LITELM_STRING
 from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
 from litellm.proxy.agent_endpoints import endpoints as agent_endpoints
 from litellm.proxy.agent_endpoints.auth.agent_permission_handler import (
@@ -484,11 +485,15 @@ class TestAgentRBACInternalUserViewOnly:
         assert resp.status_code == 403
 
 
+SENTINEL_AGENT_API_KEY = "sk-test-sentinel-do-not-use"
+
+
 class TestAgentRBACProxyAdminViewOnly:
     """Read-only proxy admins go through the object-permission scoped branch on
     GET /v1/agents (the admin fast path stays full PROXY_ADMIN only, so viewers
-    cannot fan out health checks beyond their allowlist), and secret unredaction
-    also stays gated on full PROXY_ADMIN."""
+    cannot fan out health checks beyond their allowlist). litellm_params
+    secrets are redacted for every caller, admin included (LIT-6736); only the
+    virtual-key/header visibility stays gated on full PROXY_ADMIN."""
 
     @pytest.fixture(autouse=True)
     def _setup(self, monkeypatch):
@@ -501,7 +506,7 @@ class TestAgentRBACProxyAdminViewOnly:
                 agent_id=f"agent-{index}",
                 agent_name=f"Agent {index}",
                 agent_card_params=_sample_agent_card_params(),
-                litellm_params={"api_key": "sk-super-secret-agent-key"},
+                litellm_params={"api_key": SENTINEL_AGENT_API_KEY},
             )
             for index in (1, 2)
         ]
@@ -544,7 +549,7 @@ class TestAgentRBACProxyAdminViewOnly:
 
     def test_should_still_redact_secrets_for_view_only_admin(self):
         """An unrestricted viewer sees the same agents as an admin but with keys
-        stripped and litellm_params masked."""
+        stripped; litellm_params secrets never appear in either response."""
         self.allowed_agents_spy.return_value = UnrestrictedAgentAccess()
         viewer_resp = self._list_agents(self.viewer_client)
         admin_resp = self._list_agents(self.admin_client)
@@ -553,14 +558,12 @@ class TestAgentRBACProxyAdminViewOnly:
         viewer_by_id = {agent["agent_id"]: agent for agent in viewer_resp.json()}
         assert set(viewer_by_id) == {"agent-1", "agent-2"}
         assert viewer_by_id["agent-1"]["keys"] is None
-        assert "sk-super-secret-agent-key" not in viewer_resp.text
+        assert SENTINEL_AGENT_API_KEY not in viewer_resp.text
 
         admin_by_id = {agent["agent_id"]: agent for agent in admin_resp.json()}
         assert admin_by_id["agent-1"]["keys"][0]["token"] == "hash-aaa"
-        assert (
-            admin_by_id["agent-1"]["litellm_params"]["api_key"]
-            == "sk-super-secret-agent-key"
-        )
+        assert SENTINEL_AGENT_API_KEY not in admin_resp.text
+        assert admin_by_id["agent-1"]["litellm_params"]["api_key"] == REDACTED_BY_LITELM_STRING
 
 
 class TestAgentRBACProxyAdmin:
@@ -616,6 +619,109 @@ class TestAgentRBACProxyAdmin:
             # Security scheme is the LiteLLM scheme.
             assert "LiteLLMKey" in stored_card["securitySchemes"]
 
+    def test_create_agent_response_never_echoes_secret(self):
+        """LIT-6736: POST /v1/agents must not echo the stored secret back, even
+        though it's the caller's own value and even for a proxy admin."""
+        with patch("litellm.proxy.proxy_server.prisma_client"):  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+            self.mock_registry.get_agent_by_name = MagicMock(return_value=None)
+            self.mock_registry.add_agent_to_db = AsyncMock(
+                return_value=AgentResponse(
+                    agent_id="agent-123",
+                    agent_name="Test Agent",
+                    agent_card_params=_sample_agent_card_params(),
+                    litellm_params={
+                        "aws_secret_access_key": SENTINEL_AGENT_API_KEY,
+                        "model": "bedrock/agentcore/my-agent",
+                    },
+                )
+            )
+            self.mock_registry.register_agent = MagicMock()
+
+            resp = self.admin_client.post(
+                "/v1/agents",
+                json={
+                    "agent_name": "Test Agent",
+                    "agent_card_params": _sample_agent_card_params(),
+                    "litellm_params": {
+                        "aws_secret_access_key": SENTINEL_AGENT_API_KEY,
+                        "model": "bedrock/agentcore/my-agent",
+                    },
+                },
+                headers={"Authorization": "Bearer k"},
+            )
+
+            assert resp.status_code == 200
+            assert SENTINEL_AGENT_API_KEY not in resp.text
+            body = resp.json()
+            assert body["litellm_params"]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+            assert body["litellm_params"]["model"] == "bedrock/agentcore/my-agent"
+
+    def test_update_agent_response_never_echoes_secret(self):
+        """LIT-6736: PUT /v1/agents/{id} must not echo the stored secret back."""
+        with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+            mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+                return_value={
+                    "agent_id": "agent-123",
+                    "agent_name": "Existing Agent",
+                    "agent_card_params": _sample_agent_card_params(),
+                }
+            )
+            self.mock_registry.update_agent_in_db = AsyncMock(
+                return_value=AgentResponse(
+                    agent_id="agent-123",
+                    agent_name="Test Agent",
+                    agent_card_params=_sample_agent_card_params(),
+                    litellm_params={"aws_secret_access_key": SENTINEL_AGENT_API_KEY},
+                )
+            )
+            self.mock_registry.deregister_agent = MagicMock()
+            self.mock_registry.register_agent = MagicMock()
+
+            resp = self.admin_client.put(
+                "/v1/agents/agent-123",
+                json={
+                    "agent_name": "Test Agent",
+                    "agent_card_params": _sample_agent_card_params(),
+                    "litellm_params": {"aws_secret_access_key": REDACTED_BY_LITELM_STRING},
+                },
+                headers={"Authorization": "Bearer k"},
+            )
+
+            assert resp.status_code == 200
+            assert SENTINEL_AGENT_API_KEY not in resp.text
+            assert resp.json()["litellm_params"]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+
+    def test_patch_agent_response_never_echoes_secret(self):
+        """LIT-6736: PATCH /v1/agents/{id} must not echo the stored secret back."""
+        with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma:  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+            mock_prisma.db.litellm_agentstable.find_unique = AsyncMock(
+                return_value={
+                    "agent_id": "agent-123",
+                    "agent_name": "Existing Agent",
+                    "agent_card_params": _sample_agent_card_params(),
+                }
+            )
+            self.mock_registry.patch_agent_in_db = AsyncMock(
+                return_value=AgentResponse(
+                    agent_id="agent-123",
+                    agent_name="Renamed Agent",
+                    agent_card_params=_sample_agent_card_params(),
+                    litellm_params={"aws_secret_access_key": SENTINEL_AGENT_API_KEY},
+                )
+            )
+            self.mock_registry.deregister_agent = MagicMock()
+            self.mock_registry.register_agent = MagicMock()
+
+            resp = self.admin_client.patch(
+                "/v1/agents/agent-123",
+                json={"agent_name": "Renamed Agent"},
+                headers={"Authorization": "Bearer k"},
+            )
+
+            assert resp.status_code == 200
+            assert SENTINEL_AGENT_API_KEY not in resp.text
+            assert resp.json()["litellm_params"]["aws_secret_access_key"] == REDACTED_BY_LITELM_STRING
+
     def test_should_allow_admin_to_delete_agent(self):
         existing = {
             "agent_id": "agent-123",
diff --git a/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
new file mode 100644
index 00000000000..b7bc670c7f8
--- /dev/null
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
@@ -0,0 +1,288 @@
+"""
+Tests for restamping the public model on Anthropic Messages streaming chunks.
+"""
+
+import json
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
+    AnthropicStreamModelRestamper,
+    restamp_anthropic_stream_chunk_model,
+)
+from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
+
+
+def _message_start_frame(model: str, line_end: str = "\n") -> bytes:
+    payload = {
+        "type": "message_start",
+        "message": {"id": "msg_1", "type": "message", "role": "assistant", "model": model, "content": []},
+    }
+    return f"event: message_start{line_end}data: {json.dumps(payload)}{line_end}{line_end}".encode()
+
+
+def _proxy_logging_obj_streaming(frames: list[bytes]) -> MagicMock:
+    async def _iterator_hook(**_kwargs):
+        for frame in frames:
+            yield frame
+
+    proxy_logging_obj = MagicMock()
+    proxy_logging_obj.async_post_call_streaming_iterator_hook = _iterator_hook
+    proxy_logging_obj.async_post_call_streaming_hook = AsyncMock(side_effect=lambda **kwargs: kwargs["response"])
+    return proxy_logging_obj
+
+
+def _model_from_frame(frame: bytes | str) -> str:
+    text = frame.decode("utf-8") if isinstance(frame, bytes) else frame
+    data_line = next(line for line in text.split("\n") if line.startswith("data:"))
+    return json.loads(data_line[len("data:") :])["message"]["model"]
+
+
+def test_restamps_sse_bytes_frame():
+    restamped = restamp_anthropic_stream_chunk_model(
+        _message_start_frame("claude-haiku-4-5-20251001"), "claude-auto-1"
+    )
+
+    assert isinstance(restamped, bytes)
+    assert _model_from_frame(restamped) == "claude-auto-1"
+    assert b"event: message_start" in restamped
+
+
+def test_restamps_event_dict():
+    chunk = {"type": "message_start", "message": {"id": "msg_1", "model": "claude-sonnet-4-6"}}
+
+    restamped = restamp_anthropic_stream_chunk_model(chunk, "claude-auto-2")
+
+    assert restamped == {"type": "message_start", "message": {"id": "msg_1", "model": "claude-auto-2"}}
+    assert chunk["message"]["model"] == "claude-sonnet-4-6"
+
+
+@pytest.mark.parametrize(
+    "chunk",
+    [
+        b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n',
+        {"type": "content_block_delta", "delta": {"text": "hi"}},
+        {"type": "message_start", "message": "not-a-dict"},
+        b"event: message_start\ndata: not-json\n\n",
+        b"data: [DONE]\n\n",
+    ],
+)
+def test_leaves_chunks_without_a_model_untouched(chunk):
+    assert restamp_anthropic_stream_chunk_model(chunk, "claude-auto-1") == chunk
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_publishes_requested_model_on_message_start():
+    """The message_start event reports the requested model, not the provider's."""
+    delta_frame = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    proxy_logging_obj = _proxy_logging_obj_streaming([_message_start_frame("claude-haiku-4-5-20251001"), delta_frame])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-auto-1"
+    assert chunks[1] == delta_frame
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_keeps_provider_model_when_restamping_is_off():
+    proxy_logging_obj = _proxy_logging_obj_streaming([_message_start_frame("claude-haiku-4-5-20251001")])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-haiku-4-5-20251001"
+
+
+def test_restamps_message_start_split_across_transport_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    held = restamper.process(frame[:25])
+    emitted = restamper.process(frame[25:])
+
+    assert held == b""
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+
+
+def test_emits_coalesced_frames_with_only_message_start_rewritten():
+    delta = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    combined = _message_start_frame("claude-haiku-4-5-20251001") + delta
+
+    emitted = restamper_output = AnthropicStreamModelRestamper("claude-auto-1").process(combined)
+
+    assert isinstance(restamper_output, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+    assert emitted.endswith(delta)
+
+
+def test_ping_frames_keep_the_restamper_armed():
+    ping = b'event: ping\ndata: {"type": "ping"}\n\n'
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(ping) == ping
+    reassembled = restamper.process(frame[:10])
+    reassembled += restamper.process(frame[10:])
+
+    assert _model_from_frame(reassembled) == "claude-auto-1"
+
+
+def test_first_non_ping_event_disarms_the_restamper():
+    delta = b'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\n\n'
+    late_message_start = _message_start_frame("claude-haiku-4-5-20251001")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(delta) == delta
+    assert restamper.process(late_message_start) == late_message_start
+
+
+def test_oversized_unterminated_chunk_flushes_unmodified():
+    blob = b"data: " + b"x" * 70000
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(blob) == blob
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    assert restamper.process(frame) == frame
+
+
+def test_dict_message_start_disarms_after_restamp():
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+    first = restamper.process({"type": "message_start", "message": {"id": "msg_1", "model": "claude-sonnet-4-6"}})
+    second = {"type": "message_start", "message": {"id": "msg_2", "model": "claude-sonnet-4-6"}}
+
+    assert first == {"type": "message_start", "message": {"id": "msg_1", "model": "claude-auto-1"}}
+    assert restamper.process(second) == second
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_restamps_message_start_split_across_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+    proxy_logging_obj = _proxy_logging_obj_streaming([frame[:30], frame[30:]])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    joined = b"".join(chunk if isinstance(chunk, bytes) else chunk.encode("utf-8") for chunk in chunks)
+    assert _model_from_frame(joined) == "claude-auto-1"
+
+
+def test_restamps_crlf_terminated_message_start_frame():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    delta = b'event: content_block_delta\r\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\r\n\r\n'
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    emitted = restamper.process(frame)
+
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+    assert emitted.endswith(b"\r\n\r\n")
+    assert restamper.process(delta) == delta
+
+
+def test_restamps_cr_terminated_message_start_frame():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    emitted = restamper.process(frame)
+
+    assert isinstance(emitted, bytes)
+    assert b'"model":"claude-auto-1"' in emitted
+    assert emitted.endswith(b"\r\r")
+
+
+def test_restamps_crlf_message_start_split_across_transport_chunks():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    held = restamper.process(frame[:25])
+    emitted = restamper.process(frame[25:])
+
+    assert held == b""
+    assert isinstance(emitted, bytes)
+    assert _model_from_frame(emitted) == "claude-auto-1"
+
+
+def test_flush_returns_restamped_held_tail():
+    unterminated = _message_start_frame("claude-haiku-4-5-20251001")[:-2]
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+
+    assert restamper.process(unterminated) == b""
+    flushed = restamper.flush()
+
+    assert b'"model":"claude-auto-1"' in flushed
+    assert restamper.flush() == b""
+
+
+def test_flush_disarms_the_restamper():
+    restamper = AnthropicStreamModelRestamper("claude-auto-1")
+    frame = _message_start_frame("claude-haiku-4-5-20251001")
+
+    assert restamper.flush() == b""
+    assert restamper.process(frame) == frame
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_flushes_held_tail_at_end_of_stream():
+    unterminated = _message_start_frame("claude-haiku-4-5-20251001")[:-2]
+    proxy_logging_obj = _proxy_logging_obj_streaming([unterminated])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    joined = b"".join(chunk if isinstance(chunk, bytes) else chunk.encode("utf-8") for chunk in chunks)
+    assert b'"model":"claude-auto-1"' in joined
+
+
+@pytest.mark.asyncio
+async def test_sse_generator_restamps_crlf_stream():
+    frame = _message_start_frame("claude-haiku-4-5-20251001", line_end="\r\n")
+    delta = b'event: content_block_delta\r\ndata: {"type":"content_block_delta","delta":{"text":"hi"}}\r\n\r\n'
+    proxy_logging_obj = _proxy_logging_obj_streaming([frame, delta])
+
+    chunks = [
+        chunk
+        async for chunk in ProxyBaseLLMRequestProcessing.async_sse_data_generator(
+            response=MagicMock(),
+            user_api_key_dict=MagicMock(),
+            request_data={"model": "claude-auto-1"},
+            proxy_logging_obj=proxy_logging_obj,
+            restamp_model="claude-auto-1",
+        )
+    ]
+
+    assert _model_from_frame(chunks[0]) == "claude-auto-1"
+    assert chunks[1] == delta
diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py
index 3dea89ed67b..ffe3e0fee12 100644
--- a/tests/test_litellm/proxy/auth/test_auth_checks.py
+++ b/tests/test_litellm/proxy/auth/test_auth_checks.py
@@ -7448,3 +7448,64 @@ async def test_delete_cache_key_object_is_best_effort_when_the_cache_backend_fai
     healthy_cache.delete_cache.assert_called_once_with(key=hashed_token)
     healthy_logging_obj.internal_usage_cache.dual_cache.async_delete_cache.assert_awaited_once_with(key=hashed_token)
     assert caplog.records == [], "a healthy eviction must stay silent, and must still reach both caches"
+
+
+# ---------------------------------------------------------------------------
+# Budget-exceeded error text must not carry a raw virtual key (LIT-5909)
+# ---------------------------------------------------------------------------
+
+
+class _BudgetAlertRecorder:
+    async def budget_alerts(self, type, user_info):
+        return None
+
+
+async def _run_key_budget_check(key_name: str) -> str:
+    """Drive the over-budget key path and return the raised message."""
+    valid_token = UserAPIKeyAuth(
+        token="hashed-token",
+        key_name=key_name,
+        key_alias="prod-key",
+        spend=10.0,
+        max_budget=1.0,
+    )
+    with pytest.raises(litellm.BudgetExceededError, match="Budget has been exceeded") as exc_info:
+        await _virtual_key_max_budget_check(
+            valid_token=valid_token,
+            proxy_logging_obj=_BudgetAlertRecorder(),
+        )
+    await asyncio.sleep(0)
+    return exc_info.value.message
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "key_name",
+    [
+        "sk-mx5ous1o9Iezz5fj3pkLuA",
+        "my-company-key-2026",
+        "sk-...5LuA-but-longer",
+        # /key/generate takes a custom key ending in an escape sequence, and this
+        # message reaches a terminal and a log viewer
+        "sk-...\x1b[2J",
+        "sk-...a\x9bm",
+    ],
+)
+async def test_key_budget_error_does_not_carry_a_raw_key_name(key_name):
+    """key_name is written masked, but the column has no enforced shape (a direct DB
+    write bypasses abbreviate_api_key) and this message is returned to the caller."""
+    message = await _run_key_budget_check(key_name)
+    assert key_name not in message
+    assert "Key=prod-key Current cost" in message
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("key_name", ["sk-...5LuA", "sk-...", "sk-...ke.!", "sk-...café"])
+async def test_key_budget_error_keeps_the_masked_key_name(key_name):
+    """The masked form is the whole point of naming the key, so it must survive.
+
+    abbreviate_api_key takes the last four characters of the key verbatim, and a
+    custom key may end in punctuation or a non-ASCII character, so those masked
+    names are just as valid as the alphanumeric ones."""
+    message = await _run_key_budget_check(key_name)
+    assert f"Key=prod-key ({key_name}) Current cost" in message
diff --git a/tests/test_litellm/proxy/auth/test_auth_exception_handler.py b/tests/test_litellm/proxy/auth/test_auth_exception_handler.py
index 90b3b29d919..21e0b83791f 100644
--- a/tests/test_litellm/proxy/auth/test_auth_exception_handler.py
+++ b/tests/test_litellm/proxy/auth/test_auth_exception_handler.py
@@ -9,6 +9,7 @@ from prisma import errors as prisma_errors
 from prisma.engine.errors import (
     BinaryNotFoundError,
     EngineConnectionError,
+    EngineRequestError,
     MismatchedVersionsError,
 )
 from prisma.errors import (
@@ -26,11 +27,18 @@ from prisma.errors import (
 
 
 from litellm._logging import verbose_proxy_logger
+from litellm.constants import INVALID_VIRTUAL_KEY_ERROR_MARKER
 from litellm.exceptions import BudgetExceededError
 from litellm.proxy._types import ProxyErrorTypes, ProxyException, UserAPIKeyAuth
 from litellm.proxy.auth.auth_exception_handler import UserAPIKeyAuthExceptionHandler
 
 
+class _EngineHttp500:
+    """The response half of an EngineRequestError: the query engine answered a request with HTTP 500."""
+
+    status = 500
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     "db_error",
@@ -112,6 +120,90 @@ async def test_handle_authentication_error_permanent_fault_gets_no_fallback_iden
     assert exc_info.value.code == str(status.HTTP_503_SERVICE_UNAVAILABLE)
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "prisma_error",
+    [
+        pytest.param(BinaryNotFoundError("query engine binary not found"), id="BinaryNotFoundError"),
+        pytest.param(MismatchedVersionsError(expected="1", got="2"), id="MismatchedVersionsError"),
+        pytest.param(EngineRequestError(_EngineHttp500(), "query engine crashed"), id="EngineRequestError"),
+        pytest.param(PrismaError(), id="bare_PrismaError"),
+    ],
+)
+async def test_handle_authentication_error_permanent_fault_503_is_not_worded_as_transient(prisma_error):
+    """The 503 for a fault that never heals must not say the database is
+    "temporarily unreachable" and ask the caller to retry. The status is right
+    (the service is at fault) but that wording sends the operator to wait out an
+    outage that is not one, so the message has to say retrying will not help and
+    name the engine fault."""
+    handler = UserAPIKeyAuthExceptionHandler()
+
+    with patch(  # test-quality-ok: the handler reads general_settings off the proxy module, no injection seam
+        "litellm.proxy.proxy_server.general_settings", {"allow_requests_on_db_unavailable": False}
+    ):
+        with pytest.raises(ProxyException) as exc_info:
+            await handler._handle_authentication_error(prisma_error, MagicMock(), {}, "/test", None, "test-key")
+
+    assert exc_info.value.code == str(status.HTTP_503_SERVICE_UNAVAILABLE)
+    assert exc_info.value.type == ProxyErrorTypes.no_db_connection
+    assert "temporarily unreachable" not in exc_info.value.message
+    assert "retry shortly" not in exc_info.value.message.lower()
+    assert "will not clear by retrying" in exc_info.value.message
+    assert type(prisma_error).__name__ in exc_info.value.message
+
+
+@pytest.mark.asyncio
+async def test_handle_authentication_error_transport_error_raised_over_a_permanent_fault_names_the_fault():
+    """A reconnect attempt that fails because the engine binary is missing surfaces as a transport
+    error with the BinaryNotFoundError as __context__. The response must describe the binary, which is
+    what keeps the database down, rather than promise the connection will come back."""
+    try:
+        raise BinaryNotFoundError("query engine binary not found")
+    except BinaryNotFoundError:
+        try:
+            raise httpx.ConnectError("All connection attempts failed")
+        except httpx.ConnectError as surfaced:
+            transport_over_fault = surfaced
+    handler = UserAPIKeyAuthExceptionHandler()
+
+    with patch(  # test-quality-ok: the handler reads general_settings off the proxy module, no injection seam
+        "litellm.proxy.proxy_server.general_settings", {"allow_requests_on_db_unavailable": False}
+    ):
+        with pytest.raises(ProxyException) as exc_info:
+            await handler._handle_authentication_error(transport_over_fault, MagicMock(), {}, "/test", None, "k")
+
+    assert exc_info.value.code == str(status.HTTP_503_SERVICE_UNAVAILABLE)
+    assert "temporarily unreachable" not in exc_info.value.message
+    assert "BinaryNotFoundError" in exc_info.value.message
+    assert "will not clear by retrying" in exc_info.value.message
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "db_error",
+    [
+        pytest.param(httpx.ConnectError("All connection attempts failed"), id="ConnectError"),
+        pytest.param(EngineConnectionError(), id="EngineConnectionError"),
+        pytest.param(PrismaError("can't reach database server"), id="P1001_text"),
+    ],
+)
+async def test_handle_authentication_error_transient_outage_503_keeps_retry_wording(db_error):
+    """A genuine outage is expected to come back, so its 503 keeps telling the
+    caller the database is temporarily unreachable and to retry."""
+    handler = UserAPIKeyAuthExceptionHandler()
+
+    with patch(  # test-quality-ok: the handler reads general_settings off the proxy module, no injection seam
+        "litellm.proxy.proxy_server.general_settings", {"allow_requests_on_db_unavailable": False}
+    ):
+        with pytest.raises(ProxyException) as exc_info:
+            await handler._handle_authentication_error(db_error, MagicMock(), {}, "/test", None, "test-key")
+
+    assert exc_info.value.code == str(status.HTTP_503_SERVICE_UNAVAILABLE)
+    assert exc_info.value.message == (
+        "Service Unavailable, the authentication database is temporarily unreachable. Please retry shortly."
+    )
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     "prisma_error",
@@ -703,23 +795,43 @@ async def test_auth_failure_ip_stamp_does_not_mutate_callers_request_data():
     assert request_data == {"model": "gpt-4o"}
 
 
+def _marked_malformed_key_error() -> HTTPException:
+    """Build the malformed-key 401 as its raise site does: marker stamped on it."""
+    error = HTTPException(status_code=401, detail="LiteLLM Virtual Key expected. Received=test")
+    setattr(error, INVALID_VIRTUAL_KEY_ERROR_MARKER, True)
+    return error
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
-    "auth_error,expect_traceback",
+    "auth_error,expect_traceback,expect_level",
     [
         pytest.param(
             ProxyException(
                 message="Authentication Error", type=ProxyErrorTypes.auth_error, param=None, code=401
             ),
             False,
+            "ERROR",
             id="expected_401_no_traceback",
         ),
-        pytest.param(ValueError("unexpected internal error"), True, id="unexpected_error_keeps_traceback"),
+        pytest.param(ValueError("unexpected internal error"), True, "ERROR", id="unexpected_error_keeps_traceback"),
+        pytest.param(
+            _marked_malformed_key_error(),
+            False,
+            "WARNING",
+            id="malformed_virtual_key_warning_no_traceback",
+        ),
+        pytest.param(
+            HTTPException(status_code=401, detail="LiteLLM Virtual Key expected. Received=test"),
+            False,
+            "ERROR",
+            id="phrase_without_marker_stays_loud",
+        ),
     ],
 )
-async def test_handle_authentication_error_traceback_only_for_unexpected_errors(auth_error, expect_traceback, caplog):
+async def test_handle_authentication_error_traceback_only_for_unexpected_errors(auth_error, expect_traceback, expect_level, caplog):
     """Regression for LIT-6043: expected 4xx auth rejections must not format a
-    traceback via logger.exception; unexpected errors must keep it."""
+    traceback via logger.exception; malformed virtual keys log at WARNING."""
     handler = UserAPIKeyAuthExceptionHandler()
 
     with (
@@ -740,8 +852,8 @@ async def test_handle_authentication_error_traceback_only_for_unexpected_errors(
         try:
             try:
                 raise auth_error
-            except (ProxyException, ValueError) as caught:
-                with caplog.at_level("ERROR", logger="LiteLLM Proxy"), pytest.raises(ProxyException):
+            except (ProxyException, ValueError, HTTPException) as caught:
+                with caplog.at_level(expect_level, logger="LiteLLM Proxy"), pytest.raises((ProxyException, HTTPException)):
                     await handler._handle_authentication_error(
                         caught,
                         MagicMock(),
@@ -756,3 +868,6 @@ async def test_handle_authentication_error_traceback_only_for_unexpected_errors(
     records = [r for r in caplog.records if "user_api_key_auth(): Exception occured" in r.getMessage()]
     assert len(records) == 1
     assert (records[0].exc_info is not None) is expect_traceback
+    assert records[0].levelname == expect_level
+    expected_logger_name = "LiteLLM Proxy.stdout" if expect_level == "WARNING" else "LiteLLM Proxy"
+    assert records[0].name == expected_logger_name
diff --git a/tests/test_litellm/proxy/auth/test_auth_utils.py b/tests/test_litellm/proxy/auth/test_auth_utils.py
index 9301176f3ed..f513f397b64 100644
--- a/tests/test_litellm/proxy/auth/test_auth_utils.py
+++ b/tests/test_litellm/proxy/auth/test_auth_utils.py
@@ -3169,7 +3169,7 @@ class TestIsRequestBodySafeChecksBracketNotationMetadata:
 
 
 class TestHasUserSetupSso:
-    """_has_user_setup_sso must treat SAML IdP metadata as SSO configured.
+    """has_user_setup_sso must treat SAML IdP metadata as SSO configured.
 
     Regression: UI discovery used this helper for sso_configured, but it only
     checked OAuth client IDs, so SAML-only setups left the login button gray.
@@ -3187,29 +3187,167 @@ class TestHasUserSetupSso:
             monkeypatch.delenv(key, raising=False)
 
     def test_false_when_no_sso_env(self):
-        from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+        from litellm.proxy.auth.auth_utils import has_user_setup_sso
 
-        assert _has_user_setup_sso() is False
+        assert has_user_setup_sso() is False
 
     def test_true_for_oauth_client_ids(self, monkeypatch):
-        from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+        from litellm.proxy.auth.auth_utils import has_user_setup_sso
 
         monkeypatch.setenv("GOOGLE_CLIENT_ID", "google-client")
-        assert _has_user_setup_sso() is True
+        assert has_user_setup_sso() is True
 
     def test_true_for_saml_metadata_url(self, monkeypatch):
-        from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+        from litellm.proxy.auth.auth_utils import has_user_setup_sso
 
         monkeypatch.setenv(
             "SAML_IDP_METADATA_URL", "https://idp.example.com/metadata.xml"
         )
-        assert _has_user_setup_sso() is True
+        assert has_user_setup_sso() is True
 
     def test_true_for_saml_metadata_xml(self, monkeypatch):
-        from litellm.proxy.auth.auth_utils import _has_user_setup_sso
+        from litellm.proxy.auth.auth_utils import has_user_setup_sso
 
         monkeypatch.setenv("SAML_IDP_METADATA_XML", "<EntityDescriptor/>")
-        assert _has_user_setup_sso() is True
+        assert has_user_setup_sso() is True
+
+
+class TestIsSsoProviderFullyConfigured:
+    """A lone client id must not read as ready: `has_user_setup_sso()` only
+    checks the client id (correct for a UI-discovery "show the login button"
+    decision), but a gate that BLOCKS the password fallback needs every
+    companion setting the provider requires, or an incomplete setup locks
+    every admin out with no working login path at all."""
+
+    @pytest.fixture(autouse=True)
+    def _clear_sso_env(self, monkeypatch):
+        for key in (
+            "GOOGLE_CLIENT_ID",
+            "GOOGLE_CLIENT_SECRET",
+            "MICROSOFT_CLIENT_ID",
+            "MICROSOFT_CLIENT_SECRET",
+            "MICROSOFT_TENANT",
+            "GENERIC_CLIENT_ID",
+            "GENERIC_CLIENT_SECRET",
+            "GENERIC_AUTHORIZATION_ENDPOINT",
+            "GENERIC_TOKEN_ENDPOINT",
+            "GENERIC_USERINFO_ENDPOINT",
+            "SAML_IDP_METADATA_URL",
+            "SAML_IDP_METADATA_XML",
+        ):
+            monkeypatch.delenv(key, raising=False)
+
+    def test_false_when_nothing_configured(self):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        assert is_sso_provider_fully_configured() is False
+
+    def test_google_client_id_alone_is_not_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GOOGLE_CLIENT_ID", "google-client")
+        assert is_sso_provider_fully_configured() is False
+
+    def test_google_with_secret_is_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GOOGLE_CLIENT_ID", "google-client")
+        monkeypatch.setenv("GOOGLE_CLIENT_SECRET", "google-secret")
+        assert is_sso_provider_fully_configured() is True
+
+    def test_microsoft_client_id_alone_is_not_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("MICROSOFT_CLIENT_ID", "ms-client")
+        assert is_sso_provider_fully_configured() is False
+
+    def test_microsoft_missing_tenant_is_not_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("MICROSOFT_CLIENT_ID", "ms-client")
+        monkeypatch.setenv("MICROSOFT_CLIENT_SECRET", "ms-secret")
+        assert is_sso_provider_fully_configured() is False
+
+    def test_microsoft_with_secret_and_tenant_is_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("MICROSOFT_CLIENT_ID", "ms-client")
+        monkeypatch.setenv("MICROSOFT_CLIENT_SECRET", "ms-secret")
+        monkeypatch.setenv("MICROSOFT_TENANT", "ms-tenant")
+        assert is_sso_provider_fully_configured() is True
+
+    def test_generic_client_id_alone_is_not_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GENERIC_CLIENT_ID", "generic-client")
+        assert is_sso_provider_fully_configured() is False
+
+    def test_generic_missing_one_endpoint_is_not_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GENERIC_CLIENT_ID", "generic-client")
+        monkeypatch.setenv("GENERIC_CLIENT_SECRET", "generic-secret")
+        monkeypatch.setenv("GENERIC_AUTHORIZATION_ENDPOINT", "https://idp.example.com/authorize")
+        monkeypatch.setenv("GENERIC_TOKEN_ENDPOINT", "https://idp.example.com/token")
+        # GENERIC_USERINFO_ENDPOINT deliberately left unset.
+        assert is_sso_provider_fully_configured() is False
+
+    def test_generic_with_every_endpoint_is_ready(self, monkeypatch):
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GENERIC_CLIENT_ID", "generic-client")
+        monkeypatch.setenv("GENERIC_CLIENT_SECRET", "generic-secret")
+        monkeypatch.setenv("GENERIC_AUTHORIZATION_ENDPOINT", "https://idp.example.com/authorize")
+        monkeypatch.setenv("GENERIC_TOKEN_ENDPOINT", "https://idp.example.com/token")
+        monkeypatch.setenv("GENERIC_USERINFO_ENDPOINT", "https://idp.example.com/userinfo")
+        assert is_sso_provider_fully_configured() is True
+
+    def test_saml_metadata_url_is_ready_when_runtime_installed(self, monkeypatch):
+        from litellm.proxy.auth import auth_utils
+
+        monkeypatch.setenv("SAML_IDP_METADATA_URL", "https://idp.example.com/metadata.xml")
+        monkeypatch.setattr(auth_utils.importlib.util, "find_spec", lambda name: object())
+        assert auth_utils.is_sso_provider_fully_configured() is True
+
+    def test_saml_metadata_url_is_not_ready_without_runtime(self, monkeypatch):
+        """Regression: python3-saml (``onelogin.saml2``) is an optional
+        dependency; SAMLAuthHandler fails closed on every request when it is
+        not installed, so IdP metadata alone must not read as ready."""
+        from litellm.proxy.auth import auth_utils
+
+        monkeypatch.setenv("SAML_IDP_METADATA_URL", "https://idp.example.com/metadata.xml")
+        monkeypatch.setattr(auth_utils.importlib.util, "find_spec", lambda name: None)
+        assert auth_utils.is_sso_provider_fully_configured() is False
+
+    def test_saml_check_does_not_raise_when_package_entirely_absent(self, monkeypatch):
+        """Regression: `importlib.util.find_spec("onelogin.saml2.auth")`
+        raises ModuleNotFoundError (not merely returns None) when the
+        TOP-LEVEL `onelogin` package is not installed at all, which is
+        exactly the real-world "optional extra not installed" case. If the
+        gate does not catch this, every password login 500s instead of
+        falling back, on a deployment that configured SAML metadata but
+        skipped the extra."""
+        from litellm.proxy.auth import auth_utils
+
+        def _raise(name: str):
+            raise ModuleNotFoundError("No module named 'onelogin'")
+
+        monkeypatch.setenv("SAML_IDP_METADATA_URL", "https://idp.example.com/metadata.xml")
+        monkeypatch.setattr(auth_utils.importlib.util, "find_spec", _raise)
+        assert auth_utils.is_sso_provider_fully_configured() is False
+
+    def test_incomplete_earlier_provider_does_not_mask_a_ready_later_one(self, monkeypatch):
+        """Regression: a stray GOOGLE_CLIENT_ID with no secret (e.g. a
+        leftover from a migration) must not stop the check from reaching a
+        fully configured Microsoft provider set alongside it — every
+        provider is evaluated independently, not in a first-match order."""
+        from litellm.proxy.auth.auth_utils import is_sso_provider_fully_configured
+
+        monkeypatch.setenv("GOOGLE_CLIENT_ID", "google-client")
+        monkeypatch.setenv("MICROSOFT_CLIENT_ID", "ms-client")
+        monkeypatch.setenv("MICROSOFT_CLIENT_SECRET", "ms-secret")
+        monkeypatch.setenv("MICROSOFT_TENANT", "ms-tenant")
+        assert is_sso_provider_fully_configured() is True
 
 
 class TestIsRequestBodySafeBlocksAwsIdentitySelectors:
diff --git a/tests/test_litellm/proxy/auth/test_login_utils.py b/tests/test_litellm/proxy/auth/test_login_utils.py
index 1c66acf8678..8d93d801bfd 100644
--- a/tests/test_litellm/proxy/auth/test_login_utils.py
+++ b/tests/test_litellm/proxy/auth/test_login_utils.py
@@ -6,6 +6,7 @@ to login_utils.py for better reusability.
 """
 
 import os
+from contextlib import ExitStack
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
@@ -598,3 +599,203 @@ class TestEncodeUiSessionJwt:
         request.cookies = {"token": token}
         with patch("litellm.proxy.proxy_server.master_key", "sk-master-for-tests"):
             assert _user_id_from_session_cookie(request) == "cornell-user"
+
+
+def _patch_sso_configured(stack: ExitStack, *, configured: bool) -> None:
+    stack.enter_context(
+        patch(  # test-quality-ok: no HTTP boundary here; same internal the pre-existing tests above already mock
+            "litellm.proxy.auth.login_utils.is_sso_provider_fully_configured", return_value=configured
+        )
+    )
+
+
+def _patch_successful_admin_login_deps(stack: ExitStack) -> None:
+    """The collaborators a real admin login exercises past the SSO gate:
+    generating the UI session key, syncing the admin role, and reading the
+    experimental-login flag. Shared so the two "still allowed" tests below
+    don't each repeat the same three-mock wiring."""
+    stack.enter_context(
+        patch(  # test-quality-ok: internal orchestration, no HTTP boundary; matches pre-existing tests
+            "litellm.proxy.auth.login_utils.generate_key_helper_fn",
+            new_callable=AsyncMock,
+            return_value={"token": "test-token", "user_id": LITELLM_PROXY_ADMIN_NAME},
+        )
+    )
+    stack.enter_context(
+        patch(  # test-quality-ok: internal orchestration, no HTTP boundary; matches pre-existing tests
+            "litellm.proxy.auth.login_utils.user_update",
+            new_callable=AsyncMock,
+            return_value=None,
+        )
+    )
+    stack.enter_context(
+        patch(  # test-quality-ok: internal orchestration, no HTTP boundary; matches pre-existing tests
+            "litellm.proxy.auth.login_utils.get_secret_bool",
+            return_value=False,
+        )
+    )
+
+
+class TestDisablePasswordLoginWhenSSOEnabled:
+    """`disable_password_login_when_sso_enabled` must reject every
+    username/password login attempt (including the UI_USERNAME/UI_PASSWORD
+    admin fallback) once SSO is configured, so SSO becomes the only way to
+    reach the Admin UI. It must not affect logins when SSO is unconfigured,
+    so admins can never lock themselves out with no SSO to fall back to."""
+
+    @pytest.mark.asyncio
+    async def test_rejects_correct_admin_credentials_when_sso_configured(self):
+        master_key = "sk-1234"
+        ui_username = "admin"
+
+        mock_prisma_client = MagicMock()
+        mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
+
+        with patch.dict(os.environ, {"UI_USERNAME": ui_username, "UI_PASSWORD": master_key}):
+            with ExitStack() as stack:
+                _patch_sso_configured(stack, configured=True)
+                with pytest.raises(ProxyException) as exc_info:
+                    await authenticate_user(
+                        username=ui_username,
+                        password=master_key,
+                        master_key=master_key,
+                        prisma_client=mock_prisma_client,
+                        general_settings={"disable_password_login_when_sso_enabled": True},
+                    )
+
+        assert exc_info.value.type == ProxyErrorTypes.auth_error
+        assert exc_info.value.code == "403"
+        # The credential comparison must never even run.
+        mock_prisma_client.db.litellm_usertable.find_first.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_rejects_correct_db_user_credentials_when_sso_configured(self):
+        master_key = "sk-1234"
+        user_email = "test@example.com"
+        password = "correct-password"
+
+        mock_user = LiteLLM_UserTable(
+            user_id="test-user-123",
+            user_email=user_email,
+            password=hash_token(token=password),
+            user_role=LitellmUserRoles.INTERNAL_USER,
+        )
+        mock_prisma_client = MagicMock()
+        mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=mock_user)
+
+        with patch.dict(os.environ, {"UI_USERNAME": "admin", "UI_PASSWORD": "unrelated"}):
+            with ExitStack() as stack:
+                _patch_sso_configured(stack, configured=True)
+                with pytest.raises(ProxyException) as exc_info:
+                    await authenticate_user(
+                        username=user_email,
+                        password=password,
+                        master_key=master_key,
+                        prisma_client=mock_prisma_client,
+                        general_settings={"disable_password_login_when_sso_enabled": True},
+                    )
+
+        assert exc_info.value.code == "403"
+        mock_prisma_client.db.litellm_usertable.find_first.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_allows_password_login_when_setting_enabled_but_sso_not_configured(self):
+        """The setting alone must not lock out an admin who has not actually
+        configured SSO — there would be no fallback left."""
+        master_key = "sk-1234"
+        ui_username = "admin"
+
+        mock_prisma_client = MagicMock()
+        mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
+
+        with patch.dict(
+            os.environ,
+            {
+                "UI_USERNAME": ui_username,
+                "UI_PASSWORD": master_key,
+                "DATABASE_URL": "postgresql://test:test@localhost/test",
+            },
+            clear=True,
+        ):
+            with ExitStack() as stack:
+                _patch_sso_configured(stack, configured=False)
+                _patch_successful_admin_login_deps(stack)
+                result = await authenticate_user(
+                    username=ui_username,
+                    password=master_key,
+                    master_key=master_key,
+                    prisma_client=mock_prisma_client,
+                    general_settings={"disable_password_login_when_sso_enabled": True},
+                )
+
+        assert isinstance(result, LoginResult)
+        assert result.user_id == LITELLM_PROXY_ADMIN_NAME
+
+    @pytest.mark.asyncio
+    async def test_allows_password_login_when_sso_env_is_incomplete(self):
+        """Regression: a lone MICROSOFT_CLIENT_ID with no client secret or
+        tenant makes has_user_setup_sso() True, but a real SSO sign-in would
+        fail. The gate must read the real env (no is_sso_provider_fully_configured
+        mock here) and still let password login through, or an admin who set
+        one env var by mistake is locked out with no way in."""
+        master_key = "sk-1234"
+        ui_username = "admin"
+
+        mock_prisma_client = MagicMock()
+        mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
+
+        with patch.dict(
+            os.environ,
+            {
+                "UI_USERNAME": ui_username,
+                "UI_PASSWORD": master_key,
+                "DATABASE_URL": "postgresql://test:test@localhost/test",
+                "MICROSOFT_CLIENT_ID": "ms-client-id-only",
+            },
+            clear=True,
+        ):
+            with ExitStack() as stack:
+                _patch_successful_admin_login_deps(stack)
+                result = await authenticate_user(
+                    username=ui_username,
+                    password=master_key,
+                    master_key=master_key,
+                    prisma_client=mock_prisma_client,
+                    general_settings={"disable_password_login_when_sso_enabled": True},
+                )
+
+        assert isinstance(result, LoginResult)
+        assert result.user_id == LITELLM_PROXY_ADMIN_NAME
+
+    @pytest.mark.asyncio
+    async def test_allows_password_login_when_sso_configured_but_setting_not_enabled(self):
+        """SSO being configured must not, by itself, disable the password
+        fallback: the setting is opt-in."""
+        master_key = "sk-1234"
+        ui_username = "admin"
+
+        mock_prisma_client = MagicMock()
+        mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
+
+        with patch.dict(
+            os.environ,
+            {
+                "UI_USERNAME": ui_username,
+                "UI_PASSWORD": master_key,
+                "DATABASE_URL": "postgresql://test:test@localhost/test",
+            },
+            clear=True,
+        ):
+            with ExitStack() as stack:
+                _patch_sso_configured(stack, configured=True)
+                _patch_successful_admin_login_deps(stack)
+                result = await authenticate_user(
+                    username=ui_username,
+                    password=master_key,
+                    master_key=master_key,
+                    prisma_client=mock_prisma_client,
+                    general_settings={},
+                )
+
+        assert isinstance(result, LoginResult)
+        assert result.user_id == LITELLM_PROXY_ADMIN_NAME
diff --git a/tests/test_litellm/proxy/auth/test_mcp_ip_filtering.py b/tests/test_litellm/proxy/auth/test_mcp_ip_filtering.py
index e0585ab04f1..4c219760762 100644
--- a/tests/test_litellm/proxy/auth/test_mcp_ip_filtering.py
+++ b/tests/test_litellm/proxy/auth/test_mcp_ip_filtering.py
@@ -591,3 +591,100 @@ class TestFilterServerIdsByIpWithInfo:
         )
         assert allowed == []
         assert blocked == 2
+
+
+def _make_scheme_request(
+    scheme: str, client_host: str = "203.0.113.5", headers: dict[str, str] | None = None
+) -> Request:
+    request = MagicMock(spec=Request)
+    request.client = MagicMock()
+    request.client.host = client_host
+    request.headers = headers or {}
+    request.url = MagicMock()
+    request.url.scheme = scheme
+    return request
+
+
+class TestIsRequestHttps:
+    """Regression tests for the cookie Secure trust-boundary resolution.
+
+    litellm only sees a plain-HTTP hop when TLS terminates at a reverse
+    proxy, so a cookie's Secure attribute must not be derived from the
+    literal request scheme alone. It must also not blindly trust a
+    client-spoofable X-Forwarded-Proto header with no trust boundary.
+    """
+
+    def test_direct_https_is_secure(self, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request("https")
+        assert IPAddressUtils.is_request_https(request, general_settings={}) is True
+
+    def test_direct_http_is_not_secure(self, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request("http")
+        assert IPAddressUtils.is_request_https(request, general_settings={}) is False
+
+    def test_spoofed_forwarded_proto_without_trusted_proxy_config_is_ignored(
+        self, monkeypatch
+    ):
+        # Regression: an internal HTTP hop with an attacker-supplied
+        # X-Forwarded-Proto: https must NOT flip Secure on, because no
+        # trust boundary (use_x_forwarded_for + mcp_trusted_proxy_ranges)
+        # is configured. Blindly trusting this header is itself a
+        # vulnerability.
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request(
+            "http", headers={"X-Forwarded-Proto": "https"}
+        )
+        assert IPAddressUtils.is_request_https(request, general_settings={}) is False
+
+    def test_forwarded_proto_honored_only_from_trusted_proxy(self, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request(
+            "http",
+            client_host="10.0.0.5",
+            headers={"X-Forwarded-Proto": "https"},
+        )
+        general_settings = {
+            "use_x_forwarded_for": True,
+            "mcp_trusted_proxy_ranges": ["10.0.0.0/8"],
+        }
+        assert IPAddressUtils.is_request_https(request, general_settings=general_settings) is True
+
+    def test_forwarded_proto_http_from_trusted_proxy_is_not_secure(self, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request(
+            "https",
+            client_host="10.0.0.5",
+            headers={"X-Forwarded-Proto": "http"},
+        )
+        general_settings = {
+            "use_x_forwarded_for": True,
+            "mcp_trusted_proxy_ranges": ["10.0.0.0/8"],
+        }
+        assert IPAddressUtils.is_request_https(request, general_settings=general_settings) is False
+
+    def test_untrusted_direct_peer_falls_back_to_literal_scheme(self, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        request = _make_scheme_request(
+            "http",
+            client_host="203.0.113.5",
+            headers={"X-Forwarded-Proto": "https"},
+        )
+        general_settings = {
+            "use_x_forwarded_for": True,
+            "mcp_trusted_proxy_ranges": ["10.0.0.0/8"],
+        }
+        assert IPAddressUtils.is_request_https(request, general_settings=general_settings) is False
+
+    def test_proxy_base_url_https_overrides_literal_http_scheme(self, monkeypatch):
+        monkeypatch.setenv("PROXY_BASE_URL", "https://litellm.example.com")
+        request = _make_scheme_request("http")
+        assert IPAddressUtils.is_request_https(request, general_settings={}) is True
+
+    def test_proxy_base_url_http_overrides_literal_https_scheme(self, monkeypatch):
+        # An explicit operator-configured plain-http public origin wins over
+        # the literal connection scheme, same as the https direction above.
+        monkeypatch.setenv("PROXY_BASE_URL", "http://litellm.internal")
+        request = _make_scheme_request("https")
+        assert IPAddressUtils.is_request_https(request, general_settings={}) is False
diff --git a/tests/test_litellm/proxy/auth/test_onboarding.py b/tests/test_litellm/proxy/auth/test_onboarding.py
index d55a5472af1..524b655b465 100644
--- a/tests/test_litellm/proxy/auth/test_onboarding.py
+++ b/tests/test_litellm/proxy/auth/test_onboarding.py
@@ -231,7 +231,7 @@ async def test_claim_token_rejects_already_used_link():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with patch("litellm.proxy.proxy_server.prisma_client", prisma):
@@ -254,7 +254,7 @@ async def test_claim_token_rejects_expired_link():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with patch("litellm.proxy.proxy_server.prisma_client", prisma):
@@ -275,7 +275,7 @@ async def test_claim_token_rejects_mismatched_user_id():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="wrong-user",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with patch("litellm.proxy.proxy_server.prisma_client", prisma):
@@ -296,7 +296,7 @@ async def test_claim_token_rejects_missing_onboarding_token():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with (
@@ -322,7 +322,7 @@ async def test_claim_token_rejects_wrong_onboarding_session():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
     request = _make_claim_request(
         _make_onboarding_token(invitation_link="other-invite")
@@ -351,7 +351,7 @@ async def test_claim_token_rejects_invalid_bearer_token():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
     request = _make_claim_request("sk-regular-key")
 
@@ -380,7 +380,7 @@ async def test_claim_token_rejects_concurrent_reuse_before_password_write():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with (
@@ -418,7 +418,7 @@ async def test_claim_token_sets_accepted_at_after_password_written():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     mock_token_response = {"token": "sk-generated-key", "user_id": "user-123"}
@@ -477,7 +477,7 @@ async def test_claim_token_rolls_back_invite_when_session_key_mint_fails():
     data = InvitationClaim(
         invitation_link="invite-abc",
         user_id="user-123",
-        password="NewP@ssw0rd",
+        password="NewP@ssw0rd123",
     )
 
     with (
diff --git a/tests/test_litellm/proxy/auth/test_password_policy.py b/tests/test_litellm/proxy/auth/test_password_policy.py
new file mode 100644
index 00000000000..f6e7d443907
--- /dev/null
+++ b/tests/test_litellm/proxy/auth/test_password_policy.py
@@ -0,0 +1,136 @@
+"""
+Tests for the configurable password-strength policy in
+`litellm.proxy.auth.password_policy`, enforced on every path that persists a
+new or changed password for a locally-managed user.
+"""
+
+import pytest
+
+from litellm.proxy._types import ProxyErrorTypes, ProxyException
+from litellm.proxy.auth.password_policy import (
+    DEFAULT_MIN_LENGTH,
+    MIN_ALLOWED_LENGTH,
+    PasswordPolicy,
+    get_password_policy,
+    validate_password_policy,
+)
+
+STRONG_PASSWORD = "Str0ng!Passw0rd"
+
+
+def test_get_password_policy_defaults_to_pif_baseline():
+    policy = get_password_policy({})
+    assert policy == PasswordPolicy(
+        min_length=DEFAULT_MIN_LENGTH,
+        require_uppercase=True,
+        require_lowercase=True,
+        require_numbers=True,
+        require_special_characters=True,
+    )
+
+
+def test_get_password_policy_reads_overrides_from_general_settings():
+    policy = get_password_policy(
+        {
+            "password_policy_min_length": 20,
+            "password_policy_require_uppercase": False,
+            "password_policy_require_lowercase": False,
+            "password_policy_require_numbers": False,
+            "password_policy_require_special_characters": False,
+        }
+    )
+    assert policy == PasswordPolicy(
+        min_length=20,
+        require_uppercase=False,
+        require_lowercase=False,
+        require_numbers=False,
+        require_special_characters=False,
+    )
+
+
+def test_validate_password_policy_accepts_strong_password():
+    assert validate_password_policy(STRONG_PASSWORD, {}) is None
+
+
+@pytest.mark.parametrize(
+    "password,expected_fragment",
+    [
+        ("Sh0rt!Pw", "12 characters"),
+        ("weakpassword123!", "uppercase"),
+        ("WEAKPASSWORD123!", "lowercase"),
+        ("WeakPassword!!!!", "number"),
+        ("WeakPassword12345", "special character"),
+    ],
+)
+def test_validate_password_policy_rejects_each_missing_class(password, expected_fragment):
+    with pytest.raises(ProxyException) as exc_info:
+        validate_password_policy(password, {})
+    assert exc_info.value.code == "400"
+    assert exc_info.value.type == ProxyErrorTypes.validation_error
+    assert exc_info.value.param == "password"
+    assert expected_fragment in exc_info.value.message
+
+
+def test_validate_password_policy_reports_every_violation_at_once():
+    with pytest.raises(ProxyException) as exc_info:
+        validate_password_policy("weak", {})
+    assert "12 characters" in exc_info.value.message
+    assert "uppercase" in exc_info.value.message
+    assert "number" in exc_info.value.message
+    assert "special character" in exc_info.value.message
+
+
+def test_validate_password_policy_honors_relaxed_config():
+    general_settings = {
+        "password_policy_min_length": MIN_ALLOWED_LENGTH,
+        "password_policy_require_special_characters": False,
+    }
+    # 8 chars, has upper/lower/number, no special char: fails default policy,
+    # passes the relaxed one above.
+    validate_password_policy("Abcd1234", general_settings)
+    with pytest.raises(ProxyException):
+        validate_password_policy("Abcd1234", {})
+
+
+def test_validate_password_policy_honors_stricter_min_length():
+    general_settings = {"password_policy_min_length": 20}
+    with pytest.raises(ProxyException) as exc_info:
+        validate_password_policy(STRONG_PASSWORD, general_settings)
+    assert "20 characters" in exc_info.value.message
+
+
+@pytest.mark.parametrize("configured_min_length", [0, -1, -100, 1, 7])
+def test_get_password_policy_floors_nonpositive_or_too_low_min_length(configured_min_length):
+    """A misconfigured min_length must never disable the length check
+    entirely: it floors at MIN_ALLOWED_LENGTH instead of passing through."""
+    policy = get_password_policy({"password_policy_min_length": configured_min_length})
+    assert policy.min_length == MIN_ALLOWED_LENGTH
+
+
+def test_validate_password_policy_rejects_short_password_even_with_zero_min_length_configured():
+    general_settings = {"password_policy_min_length": 0}
+    with pytest.raises(ProxyException) as exc_info:
+        validate_password_policy("a", general_settings)
+    assert f"{MIN_ALLOWED_LENGTH} characters" in exc_info.value.message
+
+
+def test_get_password_policy_ignores_boolean_min_length():
+    """`bool` is a subclass of `int` in Python; a stray `true`/`false` value
+    must not silently coerce into a min_length of 1 or 0."""
+    policy = get_password_policy({"password_policy_min_length": False})
+    assert policy.min_length == DEFAULT_MIN_LENGTH
+
+
+def test_validate_password_policy_rejects_unicode_letter_as_special_character():
+    """Regression: an ASCII-only `[^A-Za-z0-9]` check would miscount an
+    accented letter as the required special character, so a letters-and-
+    digits-only password like this one (no real symbol) must still be
+    rejected."""
+    with pytest.raises(ProxyException) as exc_info:
+        validate_password_policy("Passwörd1234", {})
+    assert "special character" in exc_info.value.message
+
+
+def test_validate_password_policy_accepts_real_special_character_with_unicode_letters():
+    """Same base password as the rejection test above, plus an actual symbol."""
+    assert validate_password_policy("Passwörd1234!", {}) is None
diff --git a/tests/test_litellm/proxy/client/cli/autoroute/test_commands.py b/tests/test_litellm/proxy/client/cli/autoroute/test_commands.py
index 74bf1c95777..4a3b3ef22c4 100644
--- a/tests/test_litellm/proxy/client/cli/autoroute/test_commands.py
+++ b/tests/test_litellm/proxy/client/cli/autoroute/test_commands.py
@@ -157,6 +157,7 @@ class TestUpCommand:
         assert captured["settings"]["theme"] == "dark"
         assert captured["settings"]["env"]["ANTHROPIC_BASE_URL"] == "http://127.0.0.1:5483"
         assert captured["settings"]["env"]["ANTHROPIC_AUTH_TOKEN"] == "fixed-master-key"
+        assert captured["settings"]["env"]["ENABLE_TOOL_SEARCH"] == "true"
         assert "apiKeyHelper" not in captured["settings"]
         assert captured["settings_mode"] == 0o600
 
diff --git a/tests/test_litellm/proxy/client/cli/autoroute/test_settings.py b/tests/test_litellm/proxy/client/cli/autoroute/test_settings.py
index 40d3e7f2aee..87a33c79a79 100644
--- a/tests/test_litellm/proxy/client/cli/autoroute/test_settings.py
+++ b/tests/test_litellm/proxy/client/cli/autoroute/test_settings.py
@@ -19,6 +19,13 @@ def test_sets_base_url_and_auth_token():
     merged = merge_claude_settings_static_token({}, "http://127.0.0.1:4000/", "token-abc")
     assert merged["env"]["ANTHROPIC_BASE_URL"] == "http://127.0.0.1:4000"
     assert merged["env"]["ANTHROPIC_AUTH_TOKEN"] == "token-abc"
+    assert merged["env"]["ENABLE_TOOL_SEARCH"] == "true"
+
+
+def test_preserves_existing_tool_search():
+    settings = {"env": {"ENABLE_TOOL_SEARCH": "false"}}
+    merged = merge_claude_settings_static_token(settings, "http://127.0.0.1:4000", "token-abc")
+    assert merged["env"]["ENABLE_TOOL_SEARCH"] == "false"
 
 
 def test_drops_stray_api_key():
diff --git a/tests/test_litellm/proxy/client/cli/test_agents.py b/tests/test_litellm/proxy/client/cli/test_agents.py
index 32dfb8d521d..0191dad3d94 100644
--- a/tests/test_litellm/proxy/client/cli/test_agents.py
+++ b/tests/test_litellm/proxy/client/cli/test_agents.py
@@ -77,9 +77,19 @@ class TestBuildAgentEnv:
         )
         assert env["ANTHROPIC_BASE_URL"] == "http://localhost:4000"
         assert env["ANTHROPIC_AUTH_TOKEN"] == "sk-key"
+        assert env["ENABLE_TOOL_SEARCH"] == "true"
         assert "OPENAI_BASE_URL" not in env
         assert "OPENAI_API_KEY" not in env
 
+    def test_anthropic_profile_preserves_existing_tool_search(self):
+        env = build_agent_env(
+            {"ENABLE_TOOL_SEARCH": "false"},
+            "http://localhost:4000",
+            "sk-key",
+            frozenset({"anthropic"}),
+        )
+        assert env["ENABLE_TOOL_SEARCH"] == "false"
+
     def test_anthropic_profile_drops_existing_api_key(self):
         env = build_agent_env(
             {"ANTHROPIC_API_KEY": "real-key"},
@@ -96,6 +106,7 @@ class TestBuildAgentEnv:
         assert env["OPENAI_BASE_URL"] == "http://localhost:4000/v1"
         assert env["OPENAI_API_KEY"] == "sk-key"
         assert "ANTHROPIC_BASE_URL" not in env
+        assert "ENABLE_TOOL_SEARCH" not in env
 
     def test_both_profiles_set_everything(self):
         env = build_agent_env(
@@ -105,6 +116,7 @@ class TestBuildAgentEnv:
         assert env["OPENAI_BASE_URL"] == "http://localhost:4000/v1"
         assert env["ANTHROPIC_AUTH_TOKEN"] == "sk-key"
         assert env["OPENAI_API_KEY"] == "sk-key"
+        assert env["ENABLE_TOOL_SEARCH"] == "true"
 
     def test_preserves_unrelated_env_and_does_not_mutate_input(self):
         base = {"PATH": "/usr/bin", "ANTHROPIC_API_KEY": "real-key"}
@@ -201,6 +213,7 @@ class TestRunAgent:
         env = calls["env"]
         assert env["ANTHROPIC_BASE_URL"] == "http://localhost:4000"
         assert env["ANTHROPIC_AUTH_TOKEN"] == "sk-key"
+        assert env["ENABLE_TOOL_SEARCH"] == "true"
         assert "ANTHROPIC_API_KEY" not in env
         assert "OPENAI_BASE_URL" not in env
 
@@ -218,6 +231,7 @@ class TestRunAgent:
         assert calls["env"]["OPENAI_BASE_URL"] == "http://localhost:4000/v1"
         assert calls["env"]["OPENAI_API_KEY"] == "sk-key"
         assert "ANTHROPIC_BASE_URL" not in calls["env"]
+        assert "ENABLE_TOOL_SEARCH" not in calls["env"]
 
     def test_codex_injects_proxy_provider_args_before_user_args(self):
         calls = {}
diff --git a/tests/test_litellm/proxy/client/cli/test_auth_commands.py b/tests/test_litellm/proxy/client/cli/test_auth_commands.py
index 85a4d90abf9..1d0a99b8e0a 100644
--- a/tests/test_litellm/proxy/client/cli/test_auth_commands.py
+++ b/tests/test_litellm/proxy/client/cli/test_auth_commands.py
@@ -1373,6 +1373,7 @@ class TestLoginConfigClaude:
         assert result.exit_code == 0
         written = json.loads(settings_path.read_text())
         assert written["env"]["ANTHROPIC_BASE_URL"] == "https://test.example.com"
+        assert written["env"]["ENABLE_TOOL_SEARCH"] == "true"
         assert written["apiKeyHelper"] == "/usr/local/bin/lite --base-url https://test.example.com auth print-token"
         assert "Configured Claude Code" in result.output
 
diff --git a/tests/test_litellm/proxy/client/cli/test_claude_settings.py b/tests/test_litellm/proxy/client/cli/test_claude_settings.py
index 9010fb4c022..e5f2a9d95bd 100644
--- a/tests/test_litellm/proxy/client/cli/test_claude_settings.py
+++ b/tests/test_litellm/proxy/client/cli/test_claude_settings.py
@@ -26,6 +26,64 @@ def _owners(*backup_paths):
 
 CLAUDE_SETTINGS_MODULE = "litellm.proxy.client.cli.commands.claude_settings"
 AUTH_MODULE = "litellm.proxy.client.cli.commands.auth"
+WINDOWS_LITE_EXE = "C:\\Users\\u\\AppData\\Local\\Programs\\Python\\Python313\\Scripts\\lite.EXE"
+
+CMD_METACHARACTERS = frozenset("&|<>^()")
+CMD_PERCENT_GUARD = "%%cd:~,%"
+
+
+def _through_cmd_exe(command):
+    """The line cmd.exe hands to CreateProcess after reading the apiKeyHelper.
+
+    A `"` toggles cmd's quote state and the metacharacters only act outside it. cmd expands
+    `%VAR%` even inside quotes, so every `%` has to arrive as the `%%cd:~,%` guard: the first
+    `%` has no variable name and stays literal, and `%cd:~,%` is a zero length substring of `cd`.
+    """
+    assert not any(CMD_METACHARACTERS & set(run) for run in command.split('"')[::2]), command
+    assert command.count("%") == 3 * command.count(CMD_PERCENT_GUARD), command
+    return command.replace(CMD_PERCENT_GUARD, "%")
+
+
+def _through_c_runtime(command_line):
+    """argv as the Microsoft C runtime builds it for the `lite` executable.
+
+    Outside quotes whitespace ends an argument. A `"` toggles quoting, and inside quotes `""`
+    is a literal quote. Backslashes are literal unless they run up to a `"`, where each pair
+    is one backslash and an odd one left over makes the quote literal.
+    """
+    argv = []
+    current = None
+    quoted = False
+    i = 0
+    while i < len(command_line):
+        ch = command_line[i]
+        if ch in " \t" and not quoted:
+            if current is not None:
+                argv.append(current)
+            current = None
+            i += 1
+            continue
+        if current is None:
+            current = ""
+        if ch == "\\":
+            run = len(command_line[i:]) - len(command_line[i:].lstrip("\\"))
+            before_quote = command_line[i + run : i + run + 1] == '"'
+            current += "\\" * (run // 2 if before_quote else run)
+            if before_quote and run % 2:
+                current += '"'
+                i += 1
+            i += run
+        elif ch == '"':
+            if quoted and command_line[i + 1 : i + 2] == '"':
+                current += '"'
+                i += 1
+            else:
+                quoted = not quoted
+            i += 1
+        else:
+            current += ch
+            i += 1
+    return argv if current is None else [*argv, current]
 
 
 @pytest.fixture
@@ -48,6 +106,7 @@ class TestWriteClaudeSettings:
 
         written = json.loads(settings_path.read_text())
         assert written["env"]["ANTHROPIC_BASE_URL"] == "https://proxy.example.com"
+        assert written["env"]["ENABLE_TOOL_SEARCH"] == "true"
         assert written["apiKeyHelper"] == "/usr/local/bin/lite --base-url https://proxy.example.com auth print-token"
 
     def test_updates_an_existing_file_preserving_unrelated_settings(self, paths, lite_on_path):
@@ -198,6 +257,36 @@ class TestApiKeyHelperIsActuallyInvocable:
 
         assert "Not authenticated for this server" in result.output
 
+    def _windows_argv(self, lite_exe, base_url):
+        with patch(f"{CLAUDE_SETTINGS_MODULE}.shutil.which", return_value=lite_exe):
+            helper = resolve_api_key_helper(base_url, platform="win32")
+        return _through_c_runtime(_through_cmd_exe(helper))
+
+    @pytest.mark.parametrize(
+        ("lite_exe", "base_url"),
+        [
+            (WINDOWS_LITE_EXE, "http://localhost:4000"),
+            ("C:\\Program Files\\LiteLLM\\lite.EXE", "https://gateway.example.com/?a=1&b=2"),
+            ("C:\\Users\\u\\Scripts\\lite.EXE", "https://gateway.example.com/team%20a/%7Eproxy"),
+            ('C:\\odd "dir"\\lite.EXE', "http://localhost:4000/x\\"),
+        ],
+    )
+    def test_the_windows_command_survives_cmd_exe_and_the_c_runtime(self, lite_exe, base_url):
+        assert self._windows_argv(lite_exe, base_url) == [lite_exe, "--base-url", base_url, "auth", "print-token"]
+
+    def test_the_windows_command_carries_the_base_url_through_cmd_quoting(self):
+        stale = CliTokenRecord(
+            base_url="http://other-proxy.example.com",
+            key="sk-stale",
+            timestamp=time.time(),
+        )
+        argv = self._windows_argv(WINDOWS_LITE_EXE, "http://localhost:4000")
+        with patch(f"{AUTH_MODULE}.load_cli_token", return_value=stale):
+            result = CliRunner().invoke(cli, argv[1:])
+
+        assert argv[0] == WINDOWS_LITE_EXE
+        assert "Not authenticated for this server" in result.output
+
 
 class TestConflictingOwnersOfTheSettingsFile:
     """Both `lite up` and `lite autoroute up` restore a backup when they stop.
diff --git a/tests/test_litellm/proxy/client/cli/test_up_commands.py b/tests/test_litellm/proxy/client/cli/test_up_commands.py
index 9958286884b..c78bdfa75b1 100644
--- a/tests/test_litellm/proxy/client/cli/test_up_commands.py
+++ b/tests/test_litellm/proxy/client/cli/test_up_commands.py
@@ -55,8 +55,14 @@ class TestMergeClaudeSettings:
         }
         merged = merge_claude_settings(settings, "http://localhost:4000/", "new-helper")
         assert merged["env"]["ANTHROPIC_BASE_URL"] == "http://localhost:4000"
+        assert merged["env"]["ENABLE_TOOL_SEARCH"] == "true"
         assert merged["apiKeyHelper"] == "new-helper"
 
+    def test_preserves_existing_tool_search(self):
+        settings = {"env": {"ENABLE_TOOL_SEARCH": "false"}}
+        merged = merge_claude_settings(settings, "http://localhost:4000", "helper")
+        assert merged["env"]["ENABLE_TOOL_SEARCH"] == "false"
+
     def test_drops_stray_api_key(self):
         settings = {"env": {"ANTHROPIC_API_KEY": "leaked-key"}}
         merged = merge_claude_settings(settings, "http://localhost:4000", "helper")
@@ -64,7 +70,10 @@ class TestMergeClaudeSettings:
 
     def test_works_from_empty_settings(self):
         merged = merge_claude_settings({}, "http://localhost:4000", "helper")
-        assert merged["env"] == {"ANTHROPIC_BASE_URL": "http://localhost:4000"}
+        assert merged["env"] == {
+            "ANTHROPIC_BASE_URL": "http://localhost:4000",
+            "ENABLE_TOOL_SEARCH": "true",
+        }
         assert merged["apiKeyHelper"] == "helper"
 
     def test_does_not_mutate_input(self):
@@ -216,6 +225,32 @@ class TestResolveApiKeyHelper:
         with pytest.raises(ClaudeSettingsError, match="Could not find `lite`"):
             resolve_api_key_helper("http://localhost:4000")
 
+    def test_windows_quotes_for_cmd_exe_instead_of_posix_sh(self, monkeypatch):
+        """cmd.exe takes a single quote literally, so a POSIX-quoted backslashed path is unrunnable."""
+        lite_exe = "C:\\Users\\u\\AppData\\Local\\Programs\\Python\\Python313\\Scripts\\lite.EXE"
+        monkeypatch.setattr(shutil, "which", lambda name: lite_exe)
+
+        helper = resolve_api_key_helper("https://gateway.example.com", platform="win32")
+
+        assert helper == f'"{lite_exe}" "--base-url" "https://gateway.example.com" "auth" "print-token"'
+
+    def test_windows_keeps_a_spaced_path_and_a_metacharacter_url_as_single_tokens(self, monkeypatch):
+        monkeypatch.setattr(shutil, "which", lambda name: "C:\\Program Files\\LiteLLM\\lite.EXE")
+
+        helper = resolve_api_key_helper("https://gateway.example.com/?a=1&b=2", platform="win32")
+
+        assert helper == (
+            '"C:\\Program Files\\LiteLLM\\lite.EXE" "--base-url" "https://gateway.example.com/?a=1&b=2" '
+            '"auth" "print-token"'
+        )
+
+    def test_non_windows_platforms_keep_posix_quoting(self, monkeypatch):
+        monkeypatch.setattr(shutil, "which", lambda name: "/usr/local/bin/lite")
+
+        helper = resolve_api_key_helper("http://example.com/path; rm -rf /", platform="darwin")
+
+        assert helper == "/usr/local/bin/lite --base-url 'http://example.com/path; rm -rf /' auth print-token"
+
 
 def _make_ctx(base_url):
     return click.Context(click.Command("test"), obj={"base_url": base_url})
@@ -486,6 +521,7 @@ class TestUpCommand:
         assert captured["backup_existed"] is True
         assert captured["settings"]["theme"] == "dark"
         assert captured["settings"]["env"]["ANTHROPIC_BASE_URL"] == "http://localhost:4000"
+        assert captured["settings"]["env"]["ENABLE_TOOL_SEARCH"] == "true"
         assert captured["settings"]["apiKeyHelper"] == "/usr/local/bin/lite auth print-token"
         assert json.loads(settings_path.read_text()) == original
         assert not backup_path.exists()
diff --git a/tests/test_litellm/proxy/db/db_transaction_queue/test_redis_update_buffer.py b/tests/test_litellm/proxy/db/db_transaction_queue/test_redis_update_buffer.py
index 504654e103a..8f3508fc4e9 100644
--- a/tests/test_litellm/proxy/db/db_transaction_queue/test_redis_update_buffer.py
+++ b/tests/test_litellm/proxy/db/db_transaction_queue/test_redis_update_buffer.py
@@ -203,7 +203,7 @@ async def test_get_all_transactions_from_redis_buffer_pipeline(redis_update_buff
                 "window_duration": "30d",
                 "window_start": "2026-08-01T00:00:00.000000",
                 "spend": 3.0,
-                "request_ids": ["req-1"],
+                "started_at": None,
             }
         ]
     )
@@ -233,13 +233,11 @@ async def test_get_all_transactions_from_redis_buffer_pipeline(redis_update_buff
         window_spend,
     ) = result
 
-    # Budget window spend from two pods is summed per window, not overwritten,
-    # and both pods' request ids reach the seed exclusion.
+    # Budget window spend from two pods is summed per window, not overwritten.
     assert window_spend is not None
     assert len(window_spend) == 1
     assert window_spend[0]["spend"] == 6.0
     assert window_spend[0]["entity_id"] == "hashed-token"
-    assert window_spend[0]["request_ids"] == ("req-1",)
 
     # Verify db spend was parsed correctly
     assert db_spend is not None
@@ -326,7 +324,6 @@ async def test_restored_window_spend_transactions_drain_back_unchanged(redis_upd
             window_duration="30d",
             window_start=datetime(2026, 8, 1, tzinfo=timezone.utc),
             spend=3.0,
-            request_id="req-1",
             started_at=datetime(2026, 8, 10, 12, 0, tzinfo=timezone.utc),
         ),
     )
@@ -500,7 +497,6 @@ async def test_store_in_memory_spend_updates_pushes_budget_window_spend(redis_up
             window_duration="30d",
             window_start=datetime(2026, 8, 1, tzinfo=timezone.utc),
             spend=1.25,
-            request_id="req-1",
             started_at=datetime(2026, 8, 10, 12, 0, 0, tzinfo=timezone.utc),
         )
     )
@@ -526,12 +522,45 @@ async def test_store_in_memory_spend_updates_pushes_budget_window_spend(redis_up
             "window_duration": "30d",
             "window_start": "2026-08-01T00:00:00.000000",
             "spend": 1.25,
-            "request_ids": ["req-1"],
             "started_at": "2026-08-10T12:00:00.000000",
+            "request_ids": [],
         }
     ]
 
 
+@pytest.mark.asyncio
+async def test_budget_window_payloads_keep_request_ids_for_older_workers(redis_update_buffer, mock_redis_cache):
+    """A leader from before the field was dropped indexes request_ids while
+    merging what it popped, and the pop is destructive, so a payload without
+    the key would cost a rolling deploy those increments."""
+    from datetime import datetime, timezone
+
+    from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import (
+        WindowSpendUpdateQueue,
+        build_window_spend_transaction,
+    )
+
+    mock_redis_cache.async_rpush_pipeline = AsyncMock(return_value=[1])
+    window_queue = WindowSpendUpdateQueue()
+    await window_queue.add_update(
+        build_window_spend_transaction(
+            entity_type="key",
+            entity_id="hashed-token",
+            window_duration="30d",
+            window_start=datetime(2026, 8, 1, tzinfo=timezone.utc),
+            spend=1.25,
+        )
+    )
+
+    await redis_update_buffer.restore_transactions_to_redis(
+        window_spend_update_transactions=await window_queue.flush_and_get_aggregated_window_spend_transactions(),
+    )
+
+    rpush_list = mock_redis_cache.async_rpush_pipeline.call_args.kwargs["rpush_list"]
+    restored = json.loads(rpush_list[0]["values"][0])
+    assert [payload["request_ids"] for payload in restored] == [[]]
+
+
 @pytest.mark.asyncio
 async def test_store_in_memory_spend_updates_restores_budget_window_spend_on_rpush_failure(
     redis_update_buffer, mock_redis_cache
diff --git a/tests/test_litellm/proxy/db/db_transaction_queue/test_window_spend_update_queue.py b/tests/test_litellm/proxy/db/db_transaction_queue/test_window_spend_update_queue.py
index b1ecda57afa..6632b1c8e35 100644
--- a/tests/test_litellm/proxy/db/db_transaction_queue/test_window_spend_update_queue.py
+++ b/tests/test_litellm/proxy/db/db_transaction_queue/test_window_spend_update_queue.py
@@ -19,7 +19,6 @@ def _txn(
     spend: float,
     duration: str = "30d",
     entity_type: str = "key",
-    request_id: str | None = None,
     started_at: datetime | None = None,
 ):
     return build_window_spend_transaction(
@@ -28,7 +27,6 @@ def _txn(
         window_duration=duration,
         window_start=window_start,
         spend=spend,
-        request_id=request_id,
         started_at=started_at,
     )
 
@@ -38,13 +36,12 @@ def test_build_window_spend_transaction_stores_naive_utc_iso():
     TIMESTAMP(3) column, so a non-UTC input must be converted, not truncated."""
     non_utc = datetime(2026, 8, 1, 20, 0, tzinfo=timezone(timedelta(hours=-4)))
 
-    assert _txn("k1", non_utc, 1.0, request_id="req-1") == {
+    assert _txn("k1", non_utc, 1.0) == {
         "entity_type": "key",
         "entity_id": "k1",
         "window_duration": "30d",
         "window_start": "2026-08-02T00:00:00.000000",
         "spend": 1.0,
-        "request_ids": ("req-1",),
         "started_at": None,
     }
 
@@ -59,19 +56,19 @@ def test_build_window_spend_transaction_stores_started_at_as_naive_utc_iso():
 
 @pytest.mark.asyncio
 async def test_aggregation_keeps_the_earliest_started_at_of_the_batch():
-    """The seed bounds its request-id exclusion at the batch's earliest start,
-    so a later start must never win the merge."""
+    """The seed stops at the batch's earliest start, so a later start must never
+    win the merge: it would push the cutoff forward and count a request the
+    increments already cover."""
     queue = WindowSpendUpdateQueue()
     earliest = datetime(2026, 8, 10, 12, 0, 0, tzinfo=timezone.utc)
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-2", started_at=earliest + timedelta(seconds=5)))
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-1", started_at=earliest))
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-3"))
+    await queue.add_update(_txn("k1", WINDOW_A, 1.0, started_at=earliest + timedelta(seconds=5)))
+    await queue.add_update(_txn("k1", WINDOW_A, 1.0, started_at=earliest))
+    await queue.add_update(_txn("k1", WINDOW_A, 1.0))
 
     aggregated = await queue.flush_and_get_aggregated_window_spend_transactions()
 
     assert len(aggregated) == 1
     assert aggregated[0]["started_at"] == "2026-08-10T12:00:00.000000"
-    assert aggregated[0]["request_ids"] == ("req-1", "req-2", "req-3")
 
 
 def test_to_naive_utc_leaves_naive_values_alone():
@@ -208,62 +205,12 @@ def test_aggregation_survives_the_redis_json_round_trip():
     assert reloaded == aggregated
 
 
-@pytest.mark.asyncio
-async def test_aggregation_unions_the_request_ids_of_merged_increments():
-    """The seed excludes exactly the requests its batch already covers, so every
-    merged increment's id has to survive aggregation."""
-    queue = WindowSpendUpdateQueue()
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-1"))
-    await queue.add_update(_txn("k1", WINDOW_A, 2.0, request_id="req-2"))
-
-    aggregated = await queue.flush_and_get_aggregated_window_spend_transactions()
-
-    assert len(aggregated) == 1
-    assert aggregated[0]["request_ids"] == ("req-1", "req-2")
-
-
-@pytest.mark.asyncio
-async def test_request_ids_stay_with_their_own_window():
-    queue = WindowSpendUpdateQueue()
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-a"))
-    await queue.add_update(_txn("k1", WINDOW_B, 2.0, request_id="req-b"))
-
-    aggregated = await queue.flush_and_get_aggregated_window_spend_transactions()
-
-    assert {payload["window_start"]: payload["request_ids"] for payload in aggregated} == {
-        "2026-08-01T00:00:00.000000": ("req-a",),
-        "2026-08-31T00:00:00.000000": ("req-b",),
-    }
-
-
-@pytest.mark.asyncio
-async def test_request_ids_are_deduplicated_and_ordered():
-    queue = WindowSpendUpdateQueue()
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-b"))
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-a"))
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0, request_id="req-a"))
-
-    aggregated = await queue.flush_and_get_aggregated_window_spend_transactions()
-
-    assert aggregated[0]["request_ids"] == ("req-a", "req-b")
-
-
-@pytest.mark.asyncio
-async def test_increment_without_a_request_id_carries_no_exclusion():
-    queue = WindowSpendUpdateQueue()
-    await queue.add_update(_txn("k1", WINDOW_A, 1.0))
-
-    aggregated = await queue.flush_and_get_aggregated_window_spend_transactions()
-
-    assert aggregated[0]["request_ids"] == ()
-
-
-def test_request_ids_survive_the_redis_json_round_trip():
+def test_started_at_survives_the_redis_json_round_trip():
     aggregated = WindowSpendUpdateQueue.get_aggregated_window_spend_transactions(
-        [(_txn("k1", WINDOW_A, 1.0, request_id="req-1"),)]
+        [(_txn("k1", WINDOW_A, 1.0, started_at=datetime(2026, 8, 10, 12, 0, tzinfo=timezone.utc)),)]
     )
 
     reloaded = WindowSpendUpdateQueue.get_aggregated_window_spend_transactions([json.loads(json.dumps(aggregated))])
 
-    assert reloaded[0]["request_ids"] == ("req-1",)
+    assert reloaded[0]["started_at"] == "2026-08-10T12:00:00.000000"
     assert reloaded[0]["spend"] == 1.0
diff --git a/tests/test_litellm/proxy/db/test_budget_window_spend_writer.py b/tests/test_litellm/proxy/db/test_budget_window_spend_writer.py
index a849317c930..130f0c56ccf 100644
--- a/tests/test_litellm/proxy/db/test_budget_window_spend_writer.py
+++ b/tests/test_litellm/proxy/db/test_budget_window_spend_writer.py
@@ -6,9 +6,10 @@ from typing import Any
 import pytest
 
 from litellm.proxy.db.budget_window_spend_writer import (
+    WindowSeedTotals,
     commit_window_spend_updates,
     roll_window_spend_row,
-    spend_logs_total_excluding,
+    spend_logs_seed_totals,
 )
 from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import (
     build_window_spend_transaction,
@@ -70,10 +71,15 @@ class _FakePrismaClient:
 
 
 class _RecordingAggregate:
-    """Stands in for the LiteLLM_SpendLogs seed aggregate."""
+    """Stands in for the LiteLLM_SpendLogs seed aggregate. before_batch
+    defaults to the full total, the state where none of this batch's own log
+    rows have been persisted yet."""
 
-    def __init__(self, value: float = 5.0) -> None:
-        self.value = value
+    def __init__(self, total: float = 5.0, before_batch: float | None = None) -> None:
+        self.totals = WindowSeedTotals(
+            total=total,
+            before_batch=total if before_batch is None else before_batch,
+        )
         self.calls: list[dict[str, Any]] = []
 
     async def __call__(
@@ -82,25 +88,23 @@ class _RecordingAggregate:
         entity_type: str,
         entity_id: str,
         window_start: datetime,
-        exclude_request_ids: Any,
-        exclude_started_at: datetime | None,
-    ) -> float | None:
+        batch_started_at: datetime | None,
+    ) -> WindowSeedTotals | None:
         self.calls.append(
             {
                 "entity_type": entity_type,
                 "entity_id": entity_id,
                 "window_start": window_start,
-                "exclude_request_ids": tuple(exclude_request_ids),
-                "exclude_started_at": exclude_started_at,
+                "batch_started_at": batch_started_at,
             }
         )
-        return self.value
+        return self.totals
 
 
 class _SpendLogsFake:
     """Sums the LiteLLM_SpendLogs rows (request_id, spend, startTime) it holds,
-    honouring the exclusion exactly as the real aggregate's
-    NOT (request_id = ANY(...) AND startTime >= bound) does."""
+    splitting them at the batch start exactly as the real aggregate's
+    SUM(...) FILTER (WHERE startTime < bound) does."""
 
     def __init__(self, rows: tuple[tuple[str, float, datetime], ...]) -> None:
         self.rows = rows
@@ -111,25 +115,25 @@ class _SpendLogsFake:
         entity_type: str,
         entity_id: str,
         window_start: datetime,
-        exclude_request_ids: Any,
-        exclude_started_at: datetime | None,
-    ) -> float | None:
-        excluded = frozenset(exclude_request_ids) if exclude_started_at is not None else frozenset()
-        return math.fsum(
-            spend
-            for request_id, spend, started_at in self.rows
-            if not (request_id in excluded and started_at >= exclude_started_at)
+        batch_started_at: datetime | None,
+    ) -> WindowSeedTotals | None:
+        return WindowSeedTotals(
+            total=math.fsum(spend for _request_id, spend, _started_at in self.rows),
+            before_batch=math.fsum(
+                spend
+                for _request_id, spend, started_at in self.rows
+                if batch_started_at is None or started_at < batch_started_at
+            ),
         )
 
 
-def _batch(request_ids: tuple[str, ...], spend: float, started_at: datetime | None = BATCH_STARTED_AT) -> dict:
+def _batch(spend: float, started_at: datetime | None = BATCH_STARTED_AT) -> dict:
     return {
         "entity_type": "key",
         "entity_id": "k1",
         "window_duration": "30d",
         "window_start": "2026-08-01T00:00:00.000000",
         "spend": spend,
-        "request_ids": request_ids,
         "started_at": None
         if started_at is None
         else started_at.replace(tzinfo=None).isoformat(timespec="microseconds"),
@@ -156,7 +160,7 @@ async def test_missing_row_is_seeded_from_spend_logs_once():
     existed, so a brand new primary key inserts the SpendLogs total plus this
     increment."""
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=5.0)
+    aggregate = _RecordingAggregate(total=5.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -183,7 +187,7 @@ async def test_existing_row_is_never_reseeded():
     """The seed is a full LiteLLM_SpendLogs scan; running it for a row that is
     already maintained would both cost a scan and double count."""
     db = _FakeDB(existing_rows=[_existing("key", "k1", "30d")])
-    aggregate = _RecordingAggregate(value=5.0)
+    aggregate = _RecordingAggregate(total=5.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -200,7 +204,7 @@ async def test_existing_row_is_never_reseeded():
 @pytest.mark.asyncio
 async def test_seed_runs_only_for_the_primary_keys_that_are_missing():
     db = _FakeDB(existing_rows=[_existing("key", "k1", "30d")])
-    aggregate = _RecordingAggregate(value=5.0)
+    aggregate = _RecordingAggregate(total=5.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -223,7 +227,7 @@ async def test_insert_spend_and_increment_differ_only_when_a_row_is_seeded():
     """The conflict arm adds the increment alone so two pods that both seed the
     same new window cannot add the SpendLogs base twice."""
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=9.0)
+    aggregate = _RecordingAggregate(total=9.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -260,7 +264,7 @@ async def test_upsert_sql_adds_for_a_current_window_and_replaces_for_a_newer_one
 @pytest.mark.asyncio
 async def test_upsert_never_interpolates_values_into_the_sql():
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=0.0)
+    aggregate = _RecordingAggregate(total=0.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -278,7 +282,7 @@ async def test_upserts_are_ordered_by_primary_key_then_window_start():
     """Cross-pod lock ordering, plus an older window must be applied before the
     roll that supersedes it or the roll would be undone."""
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=0.0)
+    aggregate = _RecordingAggregate(total=0.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -306,7 +310,7 @@ async def test_upserts_are_ordered_by_primary_key_then_window_start():
 @pytest.mark.asyncio
 async def test_existing_row_lookup_sends_every_primary_key_as_array_params():
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=0.0)
+    aggregate = _RecordingAggregate(total=0.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
@@ -344,9 +348,7 @@ async def test_unknown_entity_type_contributes_no_seed():
     anything else starts from its increment alone."""
     db = _FakeDB(existing_rows=[])
 
-    async def no_such_column(
-        prisma_client, entity_type, entity_id, window_start, exclude_request_ids, exclude_started_at
-    ):
+    async def no_such_column(prisma_client, entity_type, entity_id, window_start, batch_started_at):
         return None
 
     await commit_window_spend_updates(
@@ -363,7 +365,7 @@ async def test_unknown_entity_type_contributes_no_seed():
 async def test_unavailable_spend_logs_aggregate_seeds_zero_rather_than_failing():
     db = _FakeDB(existing_rows=[])
 
-    async def unavailable(prisma_client, entity_type, entity_id, window_start, exclude_request_ids, exclude_started_at):
+    async def unavailable(prisma_client, entity_type, entity_id, window_start, batch_started_at):
         return None
 
     await commit_window_spend_updates(
@@ -399,32 +401,31 @@ async def test_roll_window_spend_row_is_conditional_on_the_stored_window_being_o
 
 
 @pytest.mark.asyncio
-async def test_seed_receives_the_batch_request_ids_and_earliest_start_to_exclude():
+async def test_seed_receives_the_batch_earliest_start_as_its_cutoff():
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=0.0)
+    aggregate = _RecordingAggregate(total=0.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("req-1", "req-2", "req-3"), 3.0),),
+        transactions=(_batch(3.0),),
         spend_logs_aggregate=aggregate,
     )
 
-    assert aggregate.calls[0]["exclude_request_ids"] == ("req-1", "req-2", "req-3")
-    assert aggregate.calls[0]["exclude_started_at"] == BATCH_STARTED_AT
+    assert aggregate.calls[0]["batch_started_at"] == BATCH_STARTED_AT
 
 
 @pytest.mark.asyncio
 async def test_seed_passes_no_start_bound_when_the_batch_has_none():
     db = _FakeDB(existing_rows=[])
-    aggregate = _RecordingAggregate(value=0.0)
+    aggregate = _RecordingAggregate(total=0.0)
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("req-1",), 1.0, started_at=None),),
+        transactions=(_batch(1.0, started_at=None),),
         spend_logs_aggregate=aggregate,
     )
 
-    assert aggregate.calls[0]["exclude_started_at"] is None
+    assert aggregate.calls[0]["batch_started_at"] is None
 
 
 @pytest.mark.asyncio
@@ -444,7 +445,7 @@ async def test_new_row_is_not_double_counted_when_the_batch_logs_already_flushed
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("req-1", "req-2", "req-3"), 0.000141),),
+        transactions=(_batch(0.000141),),
         spend_logs_aggregate=already_flushed,
     )
 
@@ -460,7 +461,7 @@ async def test_new_row_still_covers_spend_that_predates_the_batch():
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("req-1",), 0.000047),),
+        transactions=(_batch(0.000047),),
         spend_logs_aggregate=spend_logs,
     )
 
@@ -469,22 +470,29 @@ async def test_new_row_still_covers_spend_that_predates_the_batch():
 
 
 @pytest.mark.asyncio
-async def test_replayed_request_id_cannot_erase_historical_spend_from_the_seed():
-    """request_id can be chosen by the client via x-litellm-call-id. A request
-    that replays an id from before this batch writes no new LiteLLM_SpendLogs
-    row (the insert skips duplicates), so the seed must keep counting the
-    historical row that id belongs to; only its increment is new."""
+async def test_seed_keeps_spend_another_pod_persisted_after_this_batch_started():
+    """A concurrent request on another pod can land its spend log after this
+    batch started but before this pod seeds the row. Dropping it on a plain
+    time cutoff would lose that spend for the rest of the window if that pod
+    died before flushing its increment, so the seed takes off only this batch's
+    own spend and keeps everything else."""
     db = _FakeDB(existing_rows=[])
-    spend_logs = _SpendLogsFake(rows=(("replayed", 0.5, BEFORE_BATCH),))
+    spend_logs = _SpendLogsFake(
+        rows=(
+            ("older", 0.5, BEFORE_BATCH),
+            ("mine", 0.000047, BATCH_STARTED_AT),
+            ("other-pod", 0.25, BATCH_STARTED_AT + timedelta(seconds=1)),
+        ),
+    )
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("replayed",), 0.000047),),
+        transactions=(_batch(0.000047),),
         spend_logs_aggregate=spend_logs,
     )
 
     ((_, params),) = db.batcher.calls
-    assert params[INSERT_SPEND] == pytest.approx(0.500047)
+    assert params[INSERT_SPEND] == pytest.approx(0.750047)
 
 
 @pytest.mark.asyncio
@@ -496,7 +504,7 @@ async def test_new_row_is_correct_when_the_batch_logs_have_not_flushed_yet():
 
     await commit_window_spend_updates(
         prisma_client=_FakePrismaClient(db),
-        transactions=(_batch(("req-1", "req-2", "req-3"), 0.000141),),
+        transactions=(_batch(0.000141),),
         spend_logs_aggregate=nothing_flushed,
     )
 
@@ -509,57 +517,49 @@ async def test_new_row_is_correct_when_the_batch_logs_have_not_flushed_yet():
     "entity_type, expected_column",
     [("key", "api_key = $1"), ("team", "team_id = $1")],
 )
-async def test_seed_aggregate_sql_excludes_the_request_ids_only_within_the_batch_start_bound(
-    entity_type, expected_column
-):
-    db = _FakeDB(existing_rows=[{"total": 1.25}])
+async def test_seed_aggregate_sql_splits_the_window_at_the_batch_start(entity_type, expected_column):
+    db = _FakeDB(existing_rows=[{"total": 1.25, "before_batch": 0.75}])
 
-    total = await spend_logs_total_excluding(
+    totals = await spend_logs_seed_totals(
         prisma_client=_FakePrismaClient(db),
         entity_type=entity_type,
         entity_id="e1",
         window_start=WINDOW_A,
-        exclude_request_ids=("req-1", "req-2"),
-        exclude_started_at=BATCH_STARTED_AT,
+        batch_started_at=BATCH_STARTED_AT,
     )
 
-    assert total == pytest.approx(1.25)
+    assert totals == WindowSeedTotals(total=1.25, before_batch=0.75)
     ((query, params),) = db.query_raw_calls
     normalized = " ".join(query.split())
     assert expected_column in normalized
-    assert "NOT (request_id = ANY($3::text[]) AND \"startTime\" >= ($4::timestamptz AT TIME ZONE 'UTC'))" in normalized
+    assert "FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC'))" in normalized
     assert 'FROM "LiteLLM_SpendLogs"' in normalized
     # startTime is TIMESTAMP(3): the bound is floored to the second so the
     # batch's own earliest row cannot round under it.
-    assert params == ("e1", WINDOW_A, ("req-1", "req-2"), datetime(2026, 8, 10, 12, 0, 0))
-    # The ids are bound, never spliced into the statement.
-    assert "req-1" not in query
+    assert params == ("e1", WINDOW_A, datetime(2026, 8, 10, 12, 0, 0))
+    # Nothing the caller supplied reaches the statement text.
+    assert "e1" not in query
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize(
-    "exclude_request_ids, exclude_started_at",
-    [(("req-1",), None), ((), BATCH_STARTED_AT)],
-)
-async def test_seed_aggregate_excludes_nothing_without_both_ids_and_a_start_bound(
-    exclude_request_ids, exclude_started_at
-):
-    """Ids without a start bound would reopen the replayed-id hole, so the
-    seed counts everything instead; at worst that over-counts one batch."""
-    db = _FakeDB(existing_rows=[{"total": 1.25}])
+async def test_seed_aggregate_sums_the_whole_window_without_a_start_bound():
+    """A batch with no known start cannot place the split, so both halves are
+    the same sum and the seed counts everything; at worst that over-counts one
+    batch, which enforcement tolerates, where under-counting is a budget
+    bypass."""
+    db = _FakeDB(existing_rows=[{"total": 1.25, "before_batch": 1.25}])
 
-    total = await spend_logs_total_excluding(
+    totals = await spend_logs_seed_totals(
         prisma_client=_FakePrismaClient(db),
         entity_type="key",
         entity_id="e1",
         window_start=WINDOW_A,
-        exclude_request_ids=exclude_request_ids,
-        exclude_started_at=exclude_started_at,
+        batch_started_at=None,
     )
 
-    assert total == pytest.approx(1.25)
+    assert totals == WindowSeedTotals(total=1.25, before_batch=1.25)
     ((query, params),) = db.query_raw_calls
-    assert "request_id" not in query
+    assert '"startTime" <' not in query
     assert params == ("e1", WINDOW_A)
 
 
@@ -567,16 +567,15 @@ async def test_seed_aggregate_excludes_nothing_without_both_ids_and_a_start_boun
 async def test_seed_aggregate_returns_none_for_an_entity_type_with_no_spend_logs_column():
     db = _FakeDB(existing_rows=[])
 
-    total = await spend_logs_total_excluding(
+    totals = await spend_logs_seed_totals(
         prisma_client=_FakePrismaClient(db),
         entity_type="user",
         entity_id="u1",
         window_start=WINDOW_A,
-        exclude_request_ids=(),
-        exclude_started_at=None,
+        batch_started_at=None,
     )
 
-    assert total is None
+    assert totals is None
     assert db.query_raw_calls == []
 
 
@@ -584,13 +583,12 @@ async def test_seed_aggregate_returns_none_for_an_entity_type_with_no_spend_logs
 async def test_seed_aggregate_treats_an_entity_with_no_rows_as_zero():
     db = _FakeDB(existing_rows=[])
 
-    total = await spend_logs_total_excluding(
+    totals = await spend_logs_seed_totals(
         prisma_client=_FakePrismaClient(db),
         entity_type="key",
         entity_id="k-unknown",
         window_start=WINDOW_A,
-        exclude_request_ids=(),
-        exclude_started_at=None,
+        batch_started_at=None,
     )
 
-    assert total == 0.0
+    assert totals == WindowSeedTotals(total=0.0, before_batch=0.0)
diff --git a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
index d28cf8c9c6a..11ef911de3e 100644
--- a/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
+++ b/tests/test_litellm/proxy/db/test_db_spend_update_writer.py
@@ -2581,7 +2581,6 @@ async def test_failed_window_spend_commit_requeues_the_increments_and_continues_
         window_duration="30d",
         window_start=datetime(2026, 8, 1, tzinfo=timezone.utc),
         spend=0.5,
-        request_id="req-1",
     )
     await db_writer.window_spend_update_queue.add_update(transaction)
     db = _WindowSpendFakeDB()
@@ -2611,7 +2610,6 @@ async def test_failed_window_spend_commit_from_redis_is_restored_to_redis():
             window_duration="7d",
             window_start=datetime(2026, 8, 1, tzinfo=timezone.utc),
             spend=2.0,
-            request_id="req-1",
         ),
     )
     mock_redis_update_buffer = AsyncMock()
@@ -2638,74 +2636,6 @@ async def test_failed_window_spend_commit_from_redis_is_restored_to_redis():
     db_writer.pod_lock_manager.release_lock.assert_awaited_once()
 
 
-@pytest.mark.asyncio
-async def test_update_database_returns_the_spend_log_request_id():
-    """The budget-window seed excludes the log rows its increments already
-    cover, so the caller needs the id this call was recorded under. It cannot
-    be re-derived: cache hits append time.time() to the id."""
-    db_writer = DBSpendUpdateWriter()
-    db_writer._insert_spend_log_to_db = AsyncMock()
-    db_writer._enqueue_tool_usage_transaction = AsyncMock()
-
-    with (
-        patch.multiple(  # test-quality-ok: update_database lazily imports these proxy_server globals; no injection seam
-            "litellm.proxy.proxy_server",
-            disable_spend_logs=False,
-            prisma_client=MagicMock(),
-            litellm_proxy_budget_name="test-budget",
-        )
-    ):
-        request_id = await db_writer.update_database(
-            token="test-token",
-            user_id="test-user",
-            end_user_id=None,
-            team_id="test-team",
-            org_id=None,
-            kwargs={"model": "gpt-4", "custom_llm_provider": "openai", "litellm_call_id": "call-xyz"},
-            completion_response=MagicMock(),
-            start_time=datetime.now(),
-            end_time=datetime.now(),
-            response_cost=0.1,
-        )
-        await asyncio.sleep(0)
-
-    assert request_id is not None
-    # Same id the spend log row was queued under.
-    assert request_id == db_writer._insert_spend_log_to_db.call_args[1]["payload"]["request_id"]
-
-
-@pytest.mark.asyncio
-async def test_update_database_returns_none_when_the_payload_cannot_be_built():
-    db_writer = DBSpendUpdateWriter()
-
-    with (
-        patch.multiple(  # test-quality-ok: update_database lazily imports these proxy_server globals; no injection seam
-            "litellm.proxy.proxy_server",
-            disable_spend_logs=False,
-            prisma_client=MagicMock(),
-            litellm_proxy_budget_name="test-budget",
-        ),
-        patch(  # test-quality-ok: the payload builder is called by name inside update_database; no injection seam
-            "litellm.proxy.spend_tracking.spend_tracking_utils.get_logging_payload",
-            side_effect=Exception("payload boom"),
-        ),
-    ):
-        request_id = await db_writer.update_database(
-            token="test-token",
-            user_id="test-user",
-            end_user_id=None,
-            team_id="test-team",
-            org_id=None,
-            kwargs={"model": "gpt-4"},
-            completion_response=MagicMock(),
-            start_time=datetime.now(),
-            end_time=datetime.now(),
-            response_cost=0.1,
-        )
-
-    assert request_id is None
-
-
 @pytest.mark.asyncio
 async def test_commit_spend_updates_to_db_does_not_stamp_key_settings_updated_at():
     """Spend flushes must leave settings_updated_at alone, or it decays into
diff --git a/tests/test_litellm/proxy/db/test_exception_handler.py b/tests/test_litellm/proxy/db/test_exception_handler.py
index d80e3acb4b8..c685d778c0e 100644
--- a/tests/test_litellm/proxy/db/test_exception_handler.py
+++ b/tests/test_litellm/proxy/db/test_exception_handler.py
@@ -1,12 +1,14 @@
 import asyncio
 import json
 import sys
+from typing import Final
 from unittest.mock import MagicMock, patch
 
 import httpx
 import pytest
 from fastapi import HTTPException, Request
 from prisma import errors as prisma_errors
+from prisma.engine.errors import BinaryNotFoundError, EngineConnectionError
 from prisma.errors import (
     ClientNotConnectedError,
     DataError,
@@ -317,6 +319,43 @@ def test_is_database_service_unavailable_error_in_chain_sees_through_wrapping():
     assert PrismaDBExceptionHandler.is_database_service_unavailable_error_in_chain(ValueError("nope")) is False
 
 
+def test_find_database_service_unavailable_error_in_chain_returns_the_wrapped_outage_itself():
+    """Wording a 503 by the kind of outage needs the wrapped database error, not the ValueError
+    get_user_object wrapped it in, so the finder must hand back the inner exception."""
+    outage = _wrapped_like_get_user_object(ConnectionError("can't reach database server"))
+    found = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(outage)
+    assert isinstance(found, ConnectionError)
+    assert found is outage.__context__
+    missing_user = _wrapped_like_get_user_object(Exception())
+    assert PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(missing_user) is None
+
+
+def _raised_while_handling(inner, outer):
+    try:
+        raise inner
+    except BaseException:
+        try:
+            raise outer
+        except BaseException as surfaced:
+            return surfaced
+
+
+def test_permanent_fault_outranks_the_transient_error_that_surfaced_it():
+    """A reconnect that dies on a missing engine binary raises the transport error last, with the
+    BinaryNotFoundError left as __context__. The binary is what keeps the database down, so both the
+    finder and the 503 wording must pick it over the outer transient error, whichever way they nest."""
+    permanent = BinaryNotFoundError("query engine binary not found")
+    transient_over_permanent = _raised_while_handling(permanent, httpx.ConnectError("connection refused"))
+    permanent_over_transient = _raised_while_handling(httpx.ConnectError("connection refused"), permanent)
+
+    for chain in (transient_over_permanent, permanent_over_transient):
+        assert PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(chain) is permanent
+        message = PrismaDBExceptionHandler.database_unavailable_message(chain)
+        assert "BinaryNotFoundError" in message
+        assert "will not clear by retrying" in message
+        assert "temporarily unreachable" not in message
+
+
 def test_is_database_service_unavailable_error_in_chain_terminates_on_a_cause_cycle():
     """The walk must terminate on a pathological __cause__ cycle rather than hang. Neither link is an
     outage, so the bounded walk returns False instead of looping forever."""
@@ -508,6 +547,51 @@ def test_permanent_prisma_faults_are_still_reported_as_service_problems(prisma_e
     assert PrismaDBExceptionHandler.is_database_service_unavailable_error(prisma_error) is True
 
 
+RECONNECTABLE_CLIENT_STATE_FAULTS = (prisma_errors.ClientNotConnectedError, prisma_errors.HTTPClientClosedError)
+
+
+@pytest.mark.parametrize("prisma_error", PERMANENT_PRISMA_FAULTS)
+def test_permanent_prisma_faults_are_worded_as_not_retryable(prisma_error):
+    """A 503 for a fault that never heals must not tell the operator to wait.
+
+    The status stays 503 (the service is at fault), but the message has to say
+    the outage is not transient and name the engine fault, or an operator
+    watching a version-skewed engine keeps retrying a request that can never
+    succeed. The two client-state faults a reconnect can repair keep the retry
+    wording."""
+    reconnectable = isinstance(prisma_error, RECONNECTABLE_CLIENT_STATE_FAULTS)
+    message = PrismaDBExceptionHandler.database_unavailable_message(prisma_error)
+
+    assert PrismaDBExceptionHandler.is_permanent_database_fault(prisma_error) is (not reconnectable)
+    assert message.startswith("Service Unavailable")
+    assert ("temporarily unreachable" in message) is reconnectable
+    assert ("Please retry shortly" in message) is reconnectable
+    assert ("will not clear by retrying" in message) is (not reconnectable)
+    assert (type(prisma_error).__name__ in message) is (not reconnectable)
+
+
+@pytest.mark.parametrize(
+    "transient_error",
+    [
+        pytest.param(httpx.ConnectError("All connection attempts failed"), id="ConnectError"),
+        pytest.param(ConnectionError("connection refused"), id="ConnectionError"),
+        pytest.param(EngineConnectionError(), id="EngineConnectionError"),
+        pytest.param(prisma_errors.PrismaError("can't reach database server"), id="P1001_text"),
+        pytest.param(
+            ProxyException(message="no db", type=ProxyErrorTypes.no_db_connection, param=None, code=503),
+            id="ProxyException",
+        ),
+    ],
+)
+def test_transient_outages_keep_the_retry_wording(transient_error):
+    """A genuine outage is expected to come back, so the retry guidance is the
+    right message and must not be replaced by the permanent-fault text."""
+    assert PrismaDBExceptionHandler.is_permanent_database_fault(transient_error) is False
+    assert PrismaDBExceptionHandler.database_unavailable_message(transient_error) == (
+        "Service Unavailable, the authentication database is temporarily unreachable. Please retry shortly."
+    )
+
+
 @pytest.mark.parametrize(
     "transient_error",
     [
@@ -579,3 +663,40 @@ def test_is_deadlock_error_matches_postgres_deadlock(error):
 def test_is_deadlock_error_excludes_non_deadlocks(error):
     """Non-deadlock prisma errors, connectivity failures, and non-prisma exceptions are not treated as deadlocks."""
     assert PrismaDBExceptionHandler.is_deadlock_error(error) is False
+
+
+MOCKED_PRISMA_PREDICATES: Final = (
+    PrismaDBExceptionHandler.is_database_infrastructure_error,
+    PrismaDBExceptionHandler.is_database_transport_error,
+    PrismaDBExceptionHandler.is_deadlock_error,
+    PrismaDBExceptionHandler.is_prisma_engine_internal_error,
+    PrismaDBExceptionHandler.is_database_service_unavailable_error,
+)
+
+
+@pytest.mark.parametrize("predicate", MOCKED_PRISMA_PREDICATES, ids=lambda p: p.__name__)
+def test_predicates_answer_false_for_a_plain_exception_when_prisma_is_mocked(predicate):
+    """Suites that swap ``sys.modules["prisma"]`` for a ``MagicMock`` hand the
+    predicates mocks in place of prisma's error classes. ``isinstance`` against
+    a mock raises ``TypeError``; the predicate must instead answer for the
+    non-prisma checks it still has."""
+    with patch.dict(sys.modules, {"prisma": MagicMock()}):
+        assert predicate(Exception("db connection dropped")) is False
+
+
+def test_infrastructure_error_still_recognizes_transport_errors_when_prisma_is_mocked():
+    """Skipping the prisma classes must not skip the checks that do not need them."""
+    with patch.dict(sys.modules, {"prisma": MagicMock()}):
+        no_db: Final = ProxyException(message="no db", type=ProxyErrorTypes.no_db_connection, param=None, code=503)
+        assert PrismaDBExceptionHandler.is_database_infrastructure_error(httpx.ConnectError("refused")) is True
+        assert PrismaDBExceptionHandler.is_database_infrastructure_error(no_db) is True
+
+
+def test_connection_error_answers_when_prisma_is_mocked_after_import():
+    """``prisma.engine`` is already loaded in a real process, so a mock parent
+    still resolves ``prisma.engine.errors``; its classes are then mocks too."""
+    import prisma.engine.errors  # noqa: F401
+
+    with patch.dict(sys.modules, {"prisma": MagicMock()}):
+        assert PrismaDBExceptionHandler.is_database_connection_error(Exception("x")) is False
+        assert PrismaDBExceptionHandler.is_database_connection_error(httpx.ConnectError("refused")) is True
diff --git a/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py b/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py
index f4da8c941a4..c3f7b0100d8 100644
--- a/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py
+++ b/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py
@@ -18,7 +18,7 @@ def test_ui_discovery_endpoints_with_defaults():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
 
@@ -41,7 +41,7 @@ def test_ui_discovery_endpoints_with_custom_server_root_path():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/litellm"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
 
@@ -66,7 +66,7 @@ def test_ui_discovery_endpoints_with_proxy_base_url_when_set():
             "litellm.proxy.utils.get_proxy_base_url",
             return_value="https://proxy.example.com",
         ),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
 
@@ -91,7 +91,7 @@ def test_ui_discovery_endpoints_with_sso_configured_and_auto_redirect_enabled():
             "litellm.proxy.utils.get_proxy_base_url",
             return_value="https://proxy.example.com",
         ),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch.dict(
             os.environ,
             {"AUTO_REDIRECT_UI_LOGIN_TO_SSO": "true", "DISABLE_ADMIN_UI": "false"},
@@ -121,7 +121,7 @@ def test_ui_discovery_endpoints_with_sso_configured_and_auto_redirect_not_set_de
             "litellm.proxy.utils.get_proxy_base_url",
             return_value="https://proxy.example.com",
         ),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
         # Ensure AUTO_REDIRECT_UI_LOGIN_TO_SSO is not set (simulate default)
@@ -148,7 +148,7 @@ def test_ui_discovery_endpoints_with_sso_configured_but_auto_redirect_disabled()
             "litellm.proxy.utils.get_proxy_base_url",
             return_value="https://proxy.example.com",
         ),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch.dict(
             os.environ,
             {"AUTO_REDIRECT_UI_LOGIN_TO_SSO": "false", "DISABLE_ADMIN_UI": "false"},
@@ -174,7 +174,7 @@ def test_ui_discovery_endpoints_with_sso_not_configured_but_auto_redirect_enable
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(
             os.environ,
             {"AUTO_REDIRECT_UI_LOGIN_TO_SSO": "true", "DISABLE_ADMIN_UI": "false"},
@@ -203,7 +203,7 @@ def test_ui_discovery_endpoints_both_routes_return_same_data():
             "litellm.proxy.utils.get_proxy_base_url",
             return_value="https://proxy.example.com",
         ),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch.dict(
             os.environ,
             {"AUTO_REDIRECT_UI_LOGIN_TO_SSO": "true", "DISABLE_ADMIN_UI": "false"},
@@ -228,7 +228,7 @@ def test_ui_discovery_endpoints_with_auto_redirect_via_general_settings():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch(
             "litellm.proxy.proxy_server.general_settings",
             {"auto_redirect_ui_login_to_sso": True},
@@ -254,7 +254,7 @@ def test_ui_discovery_endpoints_with_auto_redirect_env_var_overrides_general_set
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=True),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=True),
         patch(
             "litellm.proxy.proxy_server.general_settings",
             {"auto_redirect_ui_login_to_sso": False},
@@ -281,7 +281,7 @@ def test_ui_discovery_endpoints_with_admin_ui_disabled():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "true"}, clear=False),
     ):
 
@@ -311,7 +311,7 @@ def test_ui_discovery_endpoints_is_control_plane_true_when_workers_configured():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch("litellm.proxy.proxy_server.proxy_config", mock_config),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
@@ -336,7 +336,7 @@ def test_ui_discovery_endpoints_hide_default_credentials_hint_default_false():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
         os.environ.pop("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", None)
@@ -357,7 +357,7 @@ def test_ui_discovery_endpoints_hide_default_credentials_hint_via_env_var():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch.dict(
             os.environ,
             {
@@ -384,7 +384,7 @@ def test_ui_discovery_endpoints_hide_default_credentials_hint_via_general_settin
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch(
             "litellm.proxy.proxy_server.general_settings",
             {"hide_default_credentials_hint": True},
@@ -411,7 +411,7 @@ def test_ui_discovery_endpoints_is_control_plane_false_when_no_workers():
     with (
         patch("litellm.proxy.utils.get_server_root_path", return_value="/"),
         patch("litellm.proxy.utils.get_proxy_base_url", return_value=None),
-        patch("litellm.proxy.auth.auth_utils._has_user_setup_sso", return_value=False),
+        patch("litellm.proxy.auth.auth_utils.has_user_setup_sso", return_value=False),
         patch("litellm.proxy.proxy_server.proxy_config", mock_config),
         patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False),
     ):
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_moderations.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_moderations.py
index 112bc5e6e49..2b43720a126 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_moderations.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_moderations.py
@@ -482,23 +482,25 @@ async def test_openai_moderation_guardrail_streaming_harmful_content():
                 "metadata": {"guardrails": ["test-openai-moderation"]},
             }
 
-            # Should raise HTTPException when processing streaming harmful content
-            from fastapi import HTTPException
+            # Chunks have already been flushed by end-of-stream moderation, so
+            # the block surfaces as the in-stream error frame, not a raise.
+            import json as _json
 
-            async def _drain():
-                result_chunks = []
-                async for chunk in unified_guardrail.async_post_call_streaming_iterator_hook(
-                    user_api_key_dict=user_api_key_dict,
-                    response=mock_stream(),
-                    request_data=request_data,
-                ):
-                    result_chunks.append(chunk)
+            result_chunks = []
+            async for chunk in unified_guardrail.async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=mock_stream(),
+                request_data=request_data,
+            ):
+                result_chunks.append(chunk)
 
-            with pytest.raises(HTTPException) as exc_info:
-                await _drain()
-
-            assert exc_info.value.status_code == 400
-            assert "Violated OpenAI moderation policy" in str(exc_info.value.detail)
+            frame = result_chunks[-1]
+            assert isinstance(frame, bytes)
+            text = frame.decode()
+            assert text.startswith("data: ")
+            assert "Violated OpenAI moderation policy" in text
+            payload = _json.loads(text[len("data: ") :])
+            assert payload["error"]["code"] == "400"
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_openai_moderation_streaming.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_openai_moderation_streaming.py
index 914af0e2368..476d443d8d8 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_openai_moderation_streaming.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/openai/test_openai_moderation_streaming.py
@@ -161,19 +161,27 @@ async def test_openai_moderation_guardrail_streaming_harmful_content():
                 "metadata": {"guardrails": ["test-openai-moderation"]},
             }
 
-            # Should raise HTTPException
-            with pytest.raises(HTTPException) as exc_info:
-                async for (
-                    _
-                ) in unified_guardrail.async_post_call_streaming_iterator_hook(
-                    user_api_key_dict=user_api_key_dict,
-                    response=mock_stream(),
-                    request_data=request_data,
-                ):
-                    pass
+            # Chunks have already been flushed by end-of-stream moderation, so
+            # the block surfaces as the in-stream error frame, not a raise.
+            import json as _json
 
-            assert exc_info.value.status_code == 400
-            assert "Violated OpenAI moderation policy" in str(exc_info.value.detail)
+            collected = []
+            async for (
+                chunk
+            ) in unified_guardrail.async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=mock_stream(),
+                request_data=request_data,
+            ):
+                collected.append(chunk)
+
+            frame = collected[-1]
+            assert isinstance(frame, bytes)
+            text = frame.decode()
+            assert text.startswith("data: ")
+            assert "Violated OpenAI moderation policy" in text
+            payload = _json.loads(text[len("data: ") :])
+            assert payload["error"]["code"] == "400"
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
new file mode 100644
index 00000000000..fd2e86ccde8
--- /dev/null
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
@@ -0,0 +1,614 @@
+import json
+import os
+from copy import deepcopy
+from unittest.mock import AsyncMock
+
+import httpx
+import pytest
+from httpx import Request, Response
+
+import litellm
+from litellm.exceptions import GuardrailRaisedException
+from litellm.proxy.guardrails.guardrail_hooks.alice.alice import (
+    GUARDRAIL_NAME,
+    AliceGuardrail,
+    AliceGuardrailMissingSecrets,
+    _json_safe,
+)
+from litellm.proxy.guardrails.init_guardrails import init_guardrails_v2
+
+
+def _guardrail(**overrides: object) -> AliceGuardrail:
+    params: dict[str, object] = {"api_key": "test-key", "guardrail_name": "alice", "event_hook": "pre_call"}
+    params.update(overrides)
+    return AliceGuardrail(**params)
+
+
+def _verdict(payload: dict[str, object], status_code: int = 200) -> Response:
+    return Response(
+        status_code=status_code,
+        json=payload,
+        request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+    )
+
+
+def test_alice_guardrail_config(monkeypatch: pytest.MonkeyPatch):
+    """Should register through init_guardrails_v2 like any other provider."""
+    monkeypatch.setattr(litellm, "guardrail_name_config_map", {})
+    monkeypatch.setenv("ALICE_API_KEY", "test-key")
+
+    init_guardrails_v2(
+        all_guardrails=[
+            {
+                "guardrail_name": "alice",
+                "litellm_params": {"guardrail": "alice", "mode": "pre_call", "default_on": True},
+            }
+        ],
+        config_file_path="",
+    )
+
+    registered = [cb for cb in litellm.callbacks if isinstance(cb, AliceGuardrail)]
+    assert len(registered) == 1
+    assert registered[0].guardrail_name == "alice"
+
+
+class TestAliceGuardrailInitialization:
+    def setup_method(self):
+        for key in ("ALICE_API_KEY", "ALICE_API_BASE"):
+            os.environ.pop(key, None)
+
+    def test_missing_api_key_raises(self):
+        with pytest.raises(AliceGuardrailMissingSecrets, match="API key"):
+            AliceGuardrail(guardrail_name="alice", event_hook="pre_call")
+
+    def test_reads_credentials_from_environment(self, monkeypatch: pytest.MonkeyPatch):
+        monkeypatch.setenv("ALICE_API_KEY", "env-key")
+        monkeypatch.setenv("ALICE_API_BASE", "https://env.alice.test")
+
+        guardrail = AliceGuardrail(guardrail_name="alice", event_hook="pre_call")
+
+        assert guardrail.alice_api_key == "env-key"
+        assert guardrail.api_base == "https://env.alice.test/v2/evaluate/litellm"
+
+    def test_defaults_the_api_base(self):
+        assert _guardrail().api_base == "https://api.alice.io/v2/evaluate/litellm"
+
+    def test_trailing_slash_does_not_double_up(self):
+        assert _guardrail(api_base="https://api.alice.io/").api_base == ("https://api.alice.io/v2/evaluate/litellm")
+
+
+class TestAliceForwarding:
+    """The hook's arguments cross the wire as they were received — nothing selected, nothing
+    renamed — except the caller's raw credentials, which are stripped before request_data is
+    serialized (see TestAliceCredentialStripping)."""
+
+    @pytest.mark.asyncio
+    async def test_forwards_the_hook_arguments_verbatim(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        inputs = {"texts": ["hello"], "structured_messages": [{"role": "user", "content": "hello"}]}
+        request_data = {"model": "gpt-4o", "metadata": {"user_api_key_alias": "payments-bot"}}
+        # Snapshot before the call: @log_guardrail_information writes its own entry into
+        # request_data["metadata"] afterwards, so the original is no longer what was sent.
+        sent_inputs = deepcopy(inputs)
+        sent_request_data = deepcopy(request_data)
+
+        await guardrail.apply_guardrail(inputs=inputs, request_data=request_data, input_type="request")
+
+        body = guardrail.async_handler.post.call_args.kwargs["json"]
+        assert body["input_type"] == "request"
+        assert body["inputs"] == sent_inputs
+        assert body["request_data"] == sent_request_data
+
+    @pytest.mark.asyncio
+    async def test_sends_the_credential(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data={}, input_type="request")
+
+        assert guardrail.async_handler.post.call_args.kwargs["headers"]["af-api-key"] == "test-key"
+
+    @pytest.mark.asyncio
+    async def test_marks_a_completion_as_a_response(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["answer"]}, request_data={}, input_type="response")
+
+        assert guardrail.async_handler.post.call_args.kwargs["json"]["input_type"] == "response"
+
+    @pytest.mark.asyncio
+    async def test_nothing_selectable_reaches_no_evaluation(self):
+        """No texts, images, tools, tool_calls, or structured_messages: genuinely nothing to send."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock()
+
+        result = await guardrail.apply_guardrail(inputs={"texts": []}, request_data={}, input_type="request")
+
+        assert result == {"texts": []}
+        guardrail.async_handler.post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_tool_calls_only_still_reaches_alice(self):
+        """A batch with empty texts but populated tool_calls is still a selection decision Alice
+        should make, not the plugin — see the class docstring."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        inputs = {"texts": [], "tool_calls": [{"id": "call_1", "function": {"name": "get_weather"}}]}
+
+        await guardrail.apply_guardrail(inputs=inputs, request_data={}, input_type="request")
+
+        guardrail.async_handler.post.assert_called_once()
+        assert guardrail.async_handler.post.call_args.kwargs["json"]["inputs"]["tool_calls"] == inputs["tool_calls"]
+
+    @pytest.mark.asyncio
+    async def test_images_only_still_reaches_alice(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(
+            inputs={"texts": [], "images": ["data:image/png;base64,abc"]}, request_data={}, input_type="request"
+        )
+
+        guardrail.async_handler.post.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_structured_messages_only_still_reaches_alice(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(
+            inputs={"texts": [], "structured_messages": [{"role": "user", "content": []}]},
+            request_data={},
+            input_type="request",
+        )
+
+        guardrail.async_handler.post.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_makes_exactly_one_attempt(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(side_effect=httpx.ConnectError("refused"))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data={}, input_type="request")
+
+        assert guardrail.async_handler.post.call_count == 1
+
+
+class TestAliceCredentialStripping:
+    """request_data's raw-credential keys never leave the process."""
+
+    @pytest.mark.asyncio
+    async def test_secret_fields_and_api_key_are_stripped(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {
+            "model": "gpt-4o",
+            "api_key": "sk-forwarded-provider-secret",
+            "secret_fields": {"raw_headers": {"authorization": "Bearer caller-virtual-key"}},
+            "metadata": {"user_api_key_alias": "payments-bot"},
+        }
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        sent_request_data = guardrail.async_handler.post.call_args.kwargs["json"]["request_data"]
+        assert "secret_fields" not in sent_request_data
+        assert "api_key" not in sent_request_data
+        assert sent_request_data == {"model": "gpt-4o", "metadata": {"user_api_key_alias": "payments-bot"}}
+
+    @pytest.mark.asyncio
+    async def test_nested_credentials_are_stripped_at_every_depth(self):
+        """Shaped after a real captured Claude Code payload: the caller's Authorization/x-api-key
+        lives under several independent nesting paths, none of which are the root."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {
+            "model": "claude-3-5-sonnet",
+            "secret_fields": {"raw_headers": {"authorization": "Bearer caller-virtual-key"}},
+            "provider_specific_header": {"extra_headers": {"authorization": "sk-ant-oat01-nested-oauth"}},
+            "proxy_server_request": {
+                "url": "/v1/messages",
+                "headers": {"authorization": "Bearer inbound-caller-secret", "x-request-id": "req-1"},
+                "body": {
+                    "model": "claude-3-5-sonnet",
+                    "metadata": {"headers": {"authorization": "Bearer body-metadata-secret"}},
+                },
+            },
+            "metadata": {
+                "user_api_key_alias": "payments-bot",
+                "headers": {"authorization": "Bearer metadata-secret"},
+                "requester_metadata": {"headers": {"authorization": "Bearer requester-metadata-secret"}},
+            },
+            "litellm_metadata": {"headers": {"authorization": "Bearer litellm-metadata-secret"}},
+        }
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        posted_body = guardrail.async_handler.post.call_args.kwargs["json"]
+        serialized = json.dumps(posted_body)
+        assert "authorization" not in serialized.lower()
+        assert "caller-virtual-key" not in serialized
+        assert "nested-oauth" not in serialized
+        assert "inbound-caller-secret" not in serialized
+        assert "body-metadata-secret" not in serialized
+        assert "metadata-secret" not in serialized
+        assert "requester-metadata-secret" not in serialized
+        assert "litellm-metadata-secret" not in serialized
+
+        sent_request_data = posted_body["request_data"]
+        assert sent_request_data["model"] == "claude-3-5-sonnet"
+        assert sent_request_data["proxy_server_request"]["url"] == "/v1/messages"
+        assert "headers" not in sent_request_data["proxy_server_request"]
+        assert sent_request_data["proxy_server_request"]["body"]["model"] == "claude-3-5-sonnet"
+        assert "headers" not in sent_request_data["proxy_server_request"]["body"]["metadata"]
+        assert sent_request_data["metadata"]["user_api_key_alias"] == "payments-bot"
+        assert "headers" not in sent_request_data["metadata"]
+        assert "requester_metadata" in sent_request_data["metadata"]
+        assert "headers" not in sent_request_data["metadata"]["requester_metadata"]
+        assert "headers" not in sent_request_data["litellm_metadata"]
+        assert "secret_fields" not in sent_request_data
+        assert "provider_specific_header" not in sent_request_data
+
+    @pytest.mark.asyncio
+    async def test_the_original_request_data_is_not_mutated(self):
+        """Stripping must only affect the outbound copy — api_key still has to reach the
+        provider, and secret_fields still has to reach the rest of the request pipeline."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {"api_key": "sk-forwarded-provider-secret", "secret_fields": {"raw_headers": {}}}
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        assert request_data["api_key"] == "sk-forwarded-provider-secret"
+        assert request_data["secret_fields"] == {"raw_headers": {}}
+
+
+class TestAliceVerdicts:
+    @pytest.mark.asyncio
+    async def test_allow_leaves_the_inputs_untouched(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_block_surfaces_the_policy_message(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "BLOCK",
+                    "categories": ["self_harm"],
+                    "correlation_id": "c1",
+                    "message": "Blocked by your organization's policy",
+                }
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException) as error:
+            await guardrail.apply_guardrail(inputs={"texts": ["bad"]}, request_data={}, input_type="request")
+
+        assert "Blocked by your organization's policy" in str(error.value)
+
+    @pytest.mark.asyncio
+    async def test_block_without_a_message_still_blocks(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "BLOCK", "categories": []}))
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["bad"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_substitutes_by_position(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "MASK",
+                    "categories": ["pii"],
+                    "replacements": [{"index": 1, "text": "my ssn is ***"}],
+                }
+            )
+        )
+
+        result = await guardrail.apply_guardrail(
+            inputs={"texts": ["untouched", "my ssn is 123-45-6789"]},
+            request_data={},
+            input_type="request",
+        )
+
+        assert result["texts"] == ["untouched", "my ssn is ***"]
+
+    @pytest.mark.asyncio
+    async def test_mask_that_lands_nowhere_blocks(self):
+        """A mask that wrote nothing would let the text through under a verdict that said not to."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "MASK", "categories": [], "replacements": [{"index": 9, "text": "***"}]})
+        )
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_with_no_replacements_blocks(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "MASK", "categories": []}))
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_with_one_invalid_replacement_blocks_entirely(self):
+        """A mixed valid/invalid replacement list must not let the valid half through: that
+        would leave the content named by the invalid entry unmasked while looking like success."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "MASK",
+                    "categories": ["pii"],
+                    "replacements": [{"index": 0, "text": "***"}, {"index": 9, "text": "***"}],
+                }
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(
+                inputs={"texts": ["my ssn is 123-45-6789"]}, request_data={}, input_type="request"
+            )
+
+    @pytest.mark.asyncio
+    async def test_mask_leaves_structured_messages_identical(self):
+        """A new structured_messages object makes the translation layer skip the texts write-back."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "MASK", "categories": [], "replacements": [{"index": 0, "text": "***"}]})
+        )
+        messages = [{"role": "user", "content": "secret"}]
+
+        result = await guardrail.apply_guardrail(
+            inputs={"texts": ["secret"], "structured_messages": messages},
+            request_data={},
+            input_type="request",
+        )
+
+        assert result["structured_messages"] is messages
+
+    @pytest.mark.asyncio
+    async def test_detect_allows_and_leaves_the_text_alone(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "DETECT", "categories": ["profanity"], "correlation_id": "c1"})
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["mild"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["mild"]
+
+
+class TestAliceUnreachable:
+    @pytest.mark.parametrize(
+        "failure",
+        [
+            pytest.param({"side_effect": httpx.ConnectError("refused")}, id="connect-error"),
+            pytest.param({"return_value": _verdict({"verdict": "MAYBE"})}, id="unrecognized-verdict"),
+            pytest.param({"return_value": _verdict({})}, id="no-verdict"),
+        ],
+    )
+    @pytest.mark.asyncio
+    async def test_fails_closed_by_default(self, failure: dict):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(**failure)
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(side_effect=httpx.ConnectError("refused"))
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+
+class TestAliceTransportFailures:
+    """Every path out of the HTTP call, since each decides whether traffic flows unscreened."""
+
+    @pytest.mark.asyncio
+    async def test_a_timeout_is_unreachable(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=litellm.exceptions.Timeout(message="slow", model="gpt-4o", llm_provider="openai")
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.parametrize("status", [500, 502, 503, 504])
+    @pytest.mark.asyncio
+    async def test_upstream_5xx_is_unreachable(self, status: int):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "server error",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=status),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_a_500_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "server error",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=500),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_4xx_is_not_treated_as_unreachable(self):
+        """A rejected credential is our misconfiguration, not an outage — it must not fail open."""
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "unauthorized",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=401),
+            )
+        )
+
+        with pytest.raises(httpx.HTTPStatusError):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_non_object_body_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                json=["not", "an", "object"],
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_non_object_body_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                json=["not", "an", "object"],
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_malformed_json_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"not json",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_malformed_json_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"not json",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_an_undecodable_body_fails_closed_by_default(self):
+        """UnicodeDecodeError is a sibling of JSONDecodeError under ValueError, not a subclass."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"\xff\xfe not utf-8",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_an_undecodable_body_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"\xff\xfe not utf-8",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+
+class TestAliceSerialization:
+    """`request_data` carries live objects, so it cannot be posted as it stands."""
+
+    def test_drops_what_cannot_serialize_and_keeps_the_rest(self):
+        class Span:
+            pass
+
+        result = _json_safe({"model": "x", "metadata": {"span": Span(), "user": "u1"}, "n": 1})
+
+        assert result == {"model": "x", "metadata": {"span": None, "user": "u1"}, "n": 1}
+
+    def test_survives_a_cycle(self):
+        data: dict = {"a": 1}
+        data["self"] = data
+
+        assert _json_safe(data) == {"a": 1, "self": None}
+
+    def test_drops_a_model_that_will_not_dump(self):
+        class Stubborn:
+            def model_dump(self, mode: str = "python") -> dict:
+                raise RuntimeError("cannot serialise")
+
+        assert _json_safe({"m": Stubborn()}) == {"m": None}
+
+    def test_drops_a_bare_unserialisable_value(self):
+        class Span:
+            pass
+
+        assert _json_safe(Span()) is None
+
+    def test_dumps_pydantic_models(self):
+        from pydantic import BaseModel
+
+        class Model(BaseModel):
+            name: str
+
+        assert _json_safe({"m": Model(name="x")}) == {"m": {"name": "x"}}
+
+
+def test_config_model_is_exposed_for_the_ui():
+    config_model = AliceGuardrail.get_config_model()
+
+    assert config_model is not None
+    assert config_model.ui_friendly_name() == "Alice"
+
+
+def test_guardrail_name_constant():
+    assert GUARDRAIL_NAME == "alice"
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
index 36b356e34d0..953e3de1519 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
@@ -5345,3 +5345,450 @@ def test_initialize_bedrock_forwards_aws_external_id():
         assert guardrail.optional_params["aws_external_id"] == "external-id-123"
     finally:
         litellm.logging_callback_manager.remove_callback_from_list_by_object(litellm.callbacks, guardrail)
+
+
+def _chat_chunk(content: str, finish_reason: str | None) -> litellm.ModelResponseStream:
+    return litellm.ModelResponseStream(
+        id="tid",
+        choices=[
+            litellm.types.utils.StreamingChoices(
+                delta=litellm.types.utils.Delta(content=content, role="assistant"),
+                finish_reason=finish_reason,
+                index=0,
+            )
+        ],
+        created=1,
+        model="gpt-4o-mini",
+        object="chat.completion.chunk",
+    )
+
+
+def _streaming_litellm_params(**extras):
+    from litellm.types.guardrails import LitellmParams
+
+    return LitellmParams(
+        guardrail="bedrock",
+        mode="post_call",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        **extras,
+    )
+
+
+def test_initialize_bedrock_wires_streaming_flags():
+    from litellm.proxy.guardrails.guardrail_initializers import initialize_bedrock
+
+    configured = initialize_bedrock(
+        _streaming_litellm_params(
+            streaming_buffer_until_moderated=False,
+            streaming_sampling_rate=3,
+            streaming_end_of_stream_only=True,
+        ),
+        {"guardrail_name": "bedrock-streaming"},
+    )
+    defaulted = initialize_bedrock(
+        _streaming_litellm_params(),
+        {"guardrail_name": "bedrock-defaults"},
+    )
+    for registered in (configured, defaulted):
+        litellm.logging_callback_manager.remove_callback_from_list_by_object(litellm.callbacks, registered)
+
+    assert configured.streaming_buffer_until_moderated is False
+    assert configured.streaming_sampling_rate == 3
+    assert configured.streaming_end_of_stream_only is True
+    assert defaulted.streaming_buffer_until_moderated is True
+    assert defaulted.streaming_sampling_rate == 5
+    assert defaulted.streaming_end_of_stream_only is False
+
+
+def test_initialize_bedrock_rejects_non_positive_sampling_rate():
+    from pydantic import ValidationError
+
+    from litellm.proxy.guardrails.guardrail_initializers import initialize_bedrock
+
+    with pytest.raises(ValidationError):
+        initialize_bedrock(
+            _streaming_litellm_params(streaming_sampling_rate=0),
+            {"guardrail_name": "bedrock-bad-rate"},
+        )
+
+
+def test_update_in_memory_litellm_params_round_trips_streaming_flags():
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-update",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+    )
+
+    guardrail.update_in_memory_litellm_params(
+        _streaming_litellm_params(
+            streaming_buffer_until_moderated=False,
+            streaming_sampling_rate=7,
+            streaming_end_of_stream_only=True,
+        )
+    )
+    assert guardrail.streaming_buffer_until_moderated is False
+    assert guardrail.streaming_sampling_rate == 7
+    assert guardrail.streaming_end_of_stream_only is True
+
+    guardrail.update_in_memory_litellm_params(_streaming_litellm_params())
+    assert guardrail.streaming_buffer_until_moderated is True
+    assert guardrail.streaming_sampling_rate == 5
+    assert guardrail.streaming_end_of_stream_only is False
+
+
+async def _run_streaming_hook_recording_order(guardrail: BedrockGuardrail) -> list:
+    events = []
+    minimal = {"action": "NONE", "assessments": [], "outputs": []}
+
+    async def record_scan(*args, **kwargs):
+        events.append("scan")
+        return minimal
+
+    async def mock_stream():
+        yield _chat_chunk("Hello", None)
+        yield _chat_chunk(" world", None)
+        yield _chat_chunk("", "stop")
+
+    with patch.object(guardrail, "make_bedrock_api_request", AsyncMock(side_effect=record_scan)):
+        async for chunk in guardrail.async_post_call_streaming_iterator_hook(
+            user_api_key_dict=UserAPIKeyAuth(),
+            response=mock_stream(),
+            request_data={"model": "gpt-4o-mini", "messages": [{"role": "user", "content": "hi"}]},
+        ):
+            content = chunk.choices[0].delta.content if chunk.choices else None
+            events.append(("chunk", content))
+    return events
+
+
+@pytest.mark.asyncio
+async def test_unbuffered_end_of_stream_hook_yields_chunks_before_scan():
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-audit-mode",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+        streaming_buffer_until_moderated=False,
+        streaming_end_of_stream_only=True,
+    )
+
+    events = await _run_streaming_hook_recording_order(guardrail)
+
+    scan_index = events.index("scan")
+    chunk_events = [e for e in events if e != "scan"]
+    assert events.count("scan") == 1
+    assert [e for e in events[:scan_index] if e != "scan"] == chunk_events[: scan_index]
+    assert ("chunk", "Hello") in events[:scan_index]
+    assert ("chunk", " world") in events[:scan_index]
+    assert len(chunk_events) == 3
+
+
+@pytest.mark.asyncio
+async def test_buffered_default_hook_scans_before_any_chunk():
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-buffered-default",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+    )
+
+    events = await _run_streaming_hook_recording_order(guardrail)
+
+    assert events[0] == "scan"
+    assert all(e == "scan" or e[0] == "chunk" for e in events)
+    assert len([e for e in events if e != "scan"]) >= 1
+
+
+@pytest.mark.asyncio
+async def test_masking_keeps_buffered_path_even_when_unbuffered_configured():
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-mask-buffered",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+        mask_response_content=True,
+        streaming_buffer_until_moderated=False,
+        streaming_end_of_stream_only=True,
+    )
+
+    assert guardrail._streams_incrementally() is False
+    events = await _run_streaming_hook_recording_order(guardrail)
+    assert events[0] == "scan"
+
+
+@pytest.mark.asyncio
+async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_truncating():
+    """Regression for PR #38722: a topicPolicy DENY caught by the end-of-stream
+    scan used to raise after SSE headers were flushed, so the client saw a
+    silently truncated stream. The unified hook must emit the chat in-stream
+    error frame instead. The finish chunk is withheld while the end-of-stream
+    scan runs, so on a block it is dropped rather than relayed before the
+    frame."""
+    from litellm.llms import load_guardrail_translation_mappings
+    from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail import (
+        unified_guardrail as unified_module,
+    )
+    from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import (
+        UnifiedLLMGuardrails,
+    )
+    from litellm.types.utils import Delta, ModelResponseStream, StreamingChoices
+
+    guardrail = BedrockGuardrail(
+        guardrailIdentifier="test-guardrail",
+        guardrailVersion="DRAFT",
+        streaming_end_of_stream_only=True,
+        streaming_buffer_until_moderated=False,
+        guardrail_name="bedrock-eos",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+    )
+    blocked_response = {
+        "action": "GUARDRAIL_INTERVENED",
+        "actionReason": "Guardrail blocked.",
+        "outputs": [{"text": "Sorry, the model cannot answer this question."}],
+        "assessments": [
+            {"topicPolicy": {"topics": [{"name": "Forbidden topic", "type": "DENY", "action": "BLOCKED"}]}}
+        ],
+    }
+
+    def _chunk(content, finish_reason=None):
+        return ModelResponseStream(
+            choices=[
+                StreamingChoices(
+                    index=0,
+                    delta={"content": content, "role": "assistant"},
+                    finish_reason=finish_reason,
+                )
+            ],
+        )
+
+    async def _mock_stream():
+        yield _chunk("the forbidden ")
+        yield _chunk("topic answer", finish_reason="stop")
+
+    unified_module.endpoint_guardrail_translation_mappings = load_guardrail_translation_mappings()
+    try:
+        with patch.object(guardrail, "make_bedrock_api_request", new_callable=AsyncMock) as mock_api:
+            mock_api.side_effect = guardrail._get_http_exception_for_blocked_guardrail(blocked_response)
+
+            out = []
+            async for item in UnifiedLLMGuardrails().async_post_call_streaming_iterator_hook(
+                user_api_key_dict=UserAPIKeyAuth(api_key="test", request_route="/v1/chat/completions"),
+                response=_mock_stream(),
+                request_data={"guardrail_to_apply": guardrail, "model": "gpt-4"},
+            ):
+                out.append(item)
+    finally:
+        unified_module.endpoint_guardrail_translation_mappings = None
+
+    assert len(out) == 2
+    assert isinstance(out[0], ModelResponseStream)
+    assert out[0].choices[0].finish_reason is None
+    frame = out[-1]
+    assert isinstance(frame, bytes)
+    payload = json.loads(frame.decode()[len("data: ") :])
+    assert payload["error"]["message"] == "Violated guardrail policy"
+    assert payload["error"]["code"] == "400"
+    assert payload["error"]["provider_specific_fields"]["guardrailIdentifier"] == "test-guardrail"
+
+
+def _responses_stream_events() -> list:
+    from litellm.types.llms.openai import (
+        OutputTextDeltaEvent,
+        ResponseCompletedEvent,
+        ResponsesAPIResponse,
+        ResponsesAPIStreamEvents,
+    )
+
+    deltas = [
+        OutputTextDeltaEvent(
+            type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+            item_id="msg_lit6457",
+            output_index=0,
+            content_index=0,
+            delta=part,
+        )
+        for part in ("Hello", " world")
+    ]
+    completed = ResponseCompletedEvent(
+        type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
+        response=ResponsesAPIResponse(
+            id="resp_lit6457",
+            created_at=1234567890,
+            model="gpt-4o",
+            object="response",
+            status="completed",
+            output=[
+                {
+                    "type": "message",
+                    "id": "msg_lit6457",
+                    "status": "completed",
+                    "role": "assistant",
+                    "content": [{"type": "output_text", "text": "Hello world"}],
+                }
+            ],
+        ),
+    )
+    return [*deltas, completed]
+
+
+@pytest.mark.asyncio
+async def test_responses_api_stream_scans_output_and_replays_buffered_events():
+    """Streamed /v1/responses events must be scanned via the unified translation
+    layer, not fed to stream_chunk_builder (which raises APIError on them)."""
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-responses-stream",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+    )
+    stream_events = _responses_stream_events()
+    order = []
+    yielded = []
+
+    async def record_scan(*args, **kwargs):
+        order.append("scan")
+        return {"action": "NONE", "assessments": [], "outputs": []}
+
+    async def mock_stream():
+        for event in stream_events:
+            yield event
+
+    with patch.object(guardrail, "make_bedrock_api_request", AsyncMock(side_effect=record_scan)):
+        async for chunk in guardrail.async_post_call_streaming_iterator_hook(
+            user_api_key_dict=UserAPIKeyAuth(api_key="test-key", request_route="/v1/responses"),
+            response=mock_stream(),
+            request_data={"model": "gpt-4o", "input": "hi"},
+        ):
+            order.append("chunk")
+            yielded.append(chunk)
+
+    assert order == ["scan", "chunk", "chunk", "chunk"]
+    assert len(yielded) == len(stream_events)
+    assert all(emitted is original for emitted, original in zip(yielded, stream_events))
+
+
+def _responses_failed_stream_events() -> list:
+    from litellm.types.llms.openai import (
+        OutputTextDeltaEvent,
+        ResponseFailedEvent,
+        ResponsesAPIResponse,
+        ResponsesAPIStreamEvents,
+    )
+
+    deltas = [
+        OutputTextDeltaEvent(
+            type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
+            item_id="msg_lit6457_failed",
+            output_index=0,
+            content_index=0,
+            delta=part,
+        )
+        for part in ("Hello", " world")
+    ]
+    failed = ResponseFailedEvent(
+        type=ResponsesAPIStreamEvents.RESPONSE_FAILED,
+        response=ResponsesAPIResponse(
+            id="resp_lit6457_failed",
+            created_at=1234567890,
+            model="gpt-4o",
+            object="response",
+            status="failed",
+            output=[],
+        ),
+    )
+    return [*deltas, failed]
+
+
+@pytest.mark.asyncio
+async def test_responses_api_failed_stream_scans_delta_text_before_replay():
+    """A responses stream that dies mid-generation carries its text only in delta
+    events; the end-of-stream scan must still see that text instead of skipping
+    on an empty assembled string and replaying the buffer unmoderated."""
+    guardrail = BedrockGuardrail(
+        guardrail_name="bedrock-responses-failed-stream",
+        guardrailIdentifier="test-id",
+        guardrailVersion="DRAFT",
+        event_hook=GuardrailEventHooks.post_call,
+        default_on=True,
+    )
+    stream_events = _responses_failed_stream_events()
+    order = []
+    scan_payloads = []
+    yielded = []
+
+    async def record_scan(*args, **kwargs):
+        order.append("scan")
+        scan_payloads.append(str(args) + str(kwargs))
+        return {"action": "NONE", "assessments": [], "outputs": []}
+
+    async def mock_stream():
+        for event in stream_events:
+            yield event
+
+    with patch.object(guardrail, "make_bedrock_api_request", AsyncMock(side_effect=record_scan)):
+        async for chunk in guardrail.async_post_call_streaming_iterator_hook(
+            user_api_key_dict=UserAPIKeyAuth(api_key="test-key", request_route="/v1/responses"),
+            response=mock_stream(),
+            request_data={"model": "gpt-4o", "input": "hi"},
+        ):
+            order.append("chunk")
+            yielded.append(chunk)
+
+    assert order == ["scan", "chunk", "chunk", "chunk"]
+    assert "Hello world" in scan_payloads[0]
+    assert len(yielded) == len(stream_events)
+    assert all(emitted is original for emitted, original in zip(yielded, stream_events))
+
+
+@pytest.mark.asyncio
+async def test_apply_guardrail_debug_log_masks_signed_request_headers():
+    import logging
+
+    from litellm._logging import verbose_proxy_logger
+
+    session_token = "FakeSessionTokenValueThatMustNeverAppearInLogs1234567890"
+    guardrail = BedrockGuardrail(
+        guardrailIdentifier="test-guardrail",
+        guardrailVersion="DRAFT",
+        aws_access_key_id="ASIAFAKEACCESSKEYID1",
+        aws_secret_access_key="fakeSecretAccessKeyForSigning",
+        aws_session_token=session_token,
+        aws_region_name="us-east-1",
+    )
+
+    mock_response = MagicMock()
+    mock_response.status_code = 200
+    mock_response.json.return_value = {"action": "NONE", "outputs": []}
+
+    captured_records: list[logging.LogRecord] = []
+
+    class _RecordingHandler(logging.Handler):
+        def emit(self, record: logging.LogRecord) -> None:
+            captured_records.append(record)
+
+    handler = _RecordingHandler(level=logging.DEBUG)
+    previous_level = verbose_proxy_logger.level
+    verbose_proxy_logger.addHandler(handler)
+    verbose_proxy_logger.setLevel(logging.DEBUG)
+    try:
+        with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post:
+            mock_post.return_value = mock_response
+            await guardrail.make_bedrock_api_request(
+                source="INPUT",
+                messages=[{"role": "user", "content": "hello"}],
+                request_data={},
+            )
+    finally:
+        verbose_proxy_logger.removeHandler(handler)
+        verbose_proxy_logger.setLevel(previous_level)
+
+    rendered_messages = [record.getMessage() for record in captured_records]
+    header_lines = [message for message in rendered_messages if "headers:" in message]
+    assert header_lines, "expected the signed-request debug line to be logged"
+    assert any("X-Amz-Security-Token" in message for message in header_lines)
+    assert all(session_token not in message for message in rendered_messages)
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
index 1fbc975e40a..c04fb7b30ec 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py
@@ -2199,6 +2199,164 @@ async def test_history_is_still_compressed(guardrail: HeadroomGuardrail):
     assert has_headroom_retrieve_tool(result.get("tools") or [])
 
 
+# ---------------------------------------------------------------------------
+# #38558: a client that runs its own tool loop (e.g. Claude Code via the MCP
+# gateway) executes headroom_retrieve and echoes the recovered original content
+# back as a tool result. Compressing that row re-derives the same content hash
+# it was just retrieved from -- the marker returns and the agent loops. The
+# retrieved row must be held back from the compression service.
+# ---------------------------------------------------------------------------
+
+RETRIEVE_ECHO_MESSAGES = [
+    {"role": "system", "content": "You are Claude Code. " + "S" * 5000},
+    {"role": "user", "content": "H" * 5000},
+    {
+        "role": "assistant",
+        "content": "Expanding the marker.",
+        "tool_calls": [
+            {
+                "id": "hr_1",
+                "type": "function",
+                "function": {
+                    "name": "mcp__headroom__headroom_retrieve",
+                    "arguments": '{"hash": "b573993006976af767214fac"}',
+                },
+            }
+        ],
+    },
+    {"role": "tool", "tool_call_id": "hr_1", "content": "RETRIEVED BODY " + "R" * 5000},
+    {"role": "assistant", "content": "Older answer. " + "O" * 5000},
+    {"role": "user", "content": "now summarize the description"},
+]
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_is_never_recompressed(guardrail: HeadroomGuardrail):
+    """The tool result carrying headroom_retrieve output is held back, so it can
+    never collapse back to the hash it was just retrieved from."""
+    wire, result = await _wire_and_result(guardrail, RETRIEVE_ECHO_MESSAGES)
+
+    assert not any(row.get("tool_call_id") == "hr_1" for row in wire)
+    assert not any("RETRIEVED BODY" in json.dumps(row) for row in wire)
+    # Reaches the model byte-identical, so no marker stands in for the expansion.
+    assert result["structured_messages"][3] == RETRIEVE_ECHO_MESSAGES[3]
+    # Negative control: unrelated history is still compressed, not a no-op.
+    assert any(row.get("content") == "H" * 5000 for row in wire)
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_guard_matches_direct_tool_name(guardrail: HeadroomGuardrail):
+    """Server-side the tool is named headroom_retrieve (no MCP prefix); its
+    result must be protected the same way."""
+    messages = [
+        {"role": "system", "content": "sys " + "S" * 5000},
+        {"role": "user", "content": "H" * 5000},
+        {
+            "role": "assistant",
+            "content": "",
+            "tool_calls": [
+                {
+                    "id": "hr_direct",
+                    "type": "function",
+                    "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME, "arguments": "{}"},
+                }
+            ],
+        },
+        {"role": "tool", "tool_call_id": "hr_direct", "content": "RETRIEVED BODY " + "R" * 5000},
+        {"role": "assistant", "content": "Older. " + "O" * 5000},
+        {"role": "user", "content": "summarize"},
+    ]
+    wire, result = await _wire_and_result(guardrail, messages)
+
+    assert not any(row.get("tool_call_id") == "hr_direct" for row in wire)
+    assert result["structured_messages"][3] == messages[3]
+
+
+@pytest.mark.asyncio
+async def test_retrieved_content_protected_when_mcp_tool_name_is_truncated(guardrail: HeadroomGuardrail):
+    """A long mcp__<server>__headroom_retrieve name is truncated past 64 chars in
+    the OpenAI-translated view the guardrail scans, dropping the suffix. The call
+    id read from the request's own Anthropic tool_use (never truncated) still
+    pairs the retrieved row so it is held back."""
+    from litellm.llms.anthropic.experimental_pass_through.adapters.transformation import (
+        truncate_tool_name,
+    )
+
+    long_name = "mcp__" + "s" * 45 + "__" + HEADROOM_RETRIEVE_TOOL_NAME
+    assert len(long_name) > 64
+    truncated = truncate_tool_name(long_name)
+    assert not truncated.endswith(HEADROOM_RETRIEVE_TOOL_NAME)
+
+    # What the guardrail scans: OpenAI-translated messages with the truncated name.
+    structured = [
+        {"role": "system", "content": "sys " + "S" * 5000},
+        {"role": "user", "content": "H" * 5000},
+        {
+            "role": "assistant",
+            "content": "",
+            "tool_calls": [{"id": "hr_long", "type": "function", "function": {"name": truncated, "arguments": "{}"}}],
+        },
+        {"role": "tool", "tool_call_id": "hr_long", "content": "RETRIEVED BODY " + "R" * 5000},
+        {"role": "assistant", "content": "Older. " + "O" * 5000},
+        {"role": "user", "content": "summarize"},
+    ]
+    # The request's own messages, untranslated: Anthropic tool_use carries the full name.
+    raw_messages = [
+        {"role": "assistant", "content": [{"type": "tool_use", "id": "hr_long", "name": long_name, "input": {}}]},
+        {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "hr_long", "content": "RETRIEVED BODY"}]},
+    ]
+
+    inputs = GenericGuardrailAPIInputs(texts=["x"], structured_messages=json.loads(json.dumps(structured)))
+    sent: dict = {}
+
+    def _echo(**kwargs):
+        sent["messages"] = kwargs["json"]["messages"]
+        return _make_compress_response(json.loads(json.dumps(kwargs["json"]["messages"])))
+
+    with patch.object(guardrail.async_handler, "post", new_callable=AsyncMock, side_effect=_echo):
+        result = await guardrail.apply_guardrail(
+            inputs=inputs,
+            request_data={"model": "claude-sonnet-4-5-20250929", "messages": raw_messages},
+            input_type="request",
+        )
+
+    assert not any(row.get("tool_call_id") == "hr_long" for row in sent["messages"])
+    assert result["structured_messages"][3] == structured[3]
+    assert any(row.get("content") == "H" * 5000 for row in sent["messages"])
+
+
+def test_raw_retrieve_call_ids_covers_both_shapes_and_ignores_others():
+    """Retrieve ids are read from OpenAI tool_calls and Anthropic tool_use blocks;
+    non-retrieve calls, non-tool_use blocks, string content, and non-list inputs
+    yield nothing."""
+    from litellm.proxy.guardrails.guardrail_hooks.headroom.headroom import _raw_retrieve_call_ids
+
+    messages = [
+        {
+            "role": "assistant",
+            "tool_calls": [
+                {"id": "oa1", "function": {"name": HEADROOM_RETRIEVE_TOOL_NAME}},
+                {"id": "other", "function": {"name": "get_weather"}},
+                {"id": "malformed", "function": {"name": 123}},
+                {"id": "nofunc"},
+            ],
+        },
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "tool_use", "id": "an1", "name": "mcp__hr__headroom_retrieve", "input": {}},
+                {"type": "tool_use", "id": "an2", "name": "jira_get_issue", "input": {}},
+                {"type": "text", "text": "noise"},
+            ],
+        },
+        {"role": "user", "content": "plain string content, not a list"},
+    ]
+
+    assert _raw_retrieve_call_ids(messages) == frozenset({"oa1", "an1"})
+    assert _raw_retrieve_call_ids("not a list") == frozenset()
+    assert _raw_retrieve_call_ids(None) == frozenset()
+
+
 @pytest.mark.asyncio
 async def test_nothing_compressible_returns_inputs_untouched(guardrail: HeadroomGuardrail):
     """A single-turn request is all protected, so there is nothing to send and
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_hiddenlayer.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_hiddenlayer.py
index b140082a3bf..f5d51a601d7 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_hiddenlayer.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_hiddenlayer.py
@@ -432,7 +432,7 @@ class TestHiddenlayerGuardrail:
 
     @pytest.mark.asyncio
     async def test_apply_guardrail_request_with_image(self, monkeypatch: pytest.MonkeyPatch):
-        """Test apply_guardrail sends multimodal content (image) to HiddenLayer v1."""
+        """Test apply_guardrail strips images from multimodal content before sending to HiddenLayer v1."""
         monkeypatch.setenv("HIDDENLAYER_API_BASE", "https://my.hiddenlayer")
 
         guardrail = HiddenlayerGuardrail(
@@ -485,12 +485,13 @@ class TestHiddenlayerGuardrail:
                 logging_obj=logging_obj,
             )
 
-        # v1 API requires string content — multimodal list is stringified
+        # v1 API requires string content — image_url items are stripped and the
+        # remaining (text-only) content is stringified before being sent.
         mock_post.assert_called_once()
         call_kwargs = mock_post.call_args.kwargs
         sent_content = call_kwargs["json"]["input"]["messages"][0]["content"]
         assert isinstance(sent_content, str)
-        assert sent_content == str(multimodal_content)
+        assert sent_content == str([{"type": "text", "text": "how much is on this receipt?"}])
 
         # Result should be returned without error
         assert result is not None
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
index 4ee6741ee02..84f7611c0c0 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_presidio.py
@@ -842,24 +842,37 @@ async def test_presidio_filter_scope_initializer(monkeypatch):
 
     params_input = LitellmParams(guardrail="presidio", mode="pre_call", presidio_filter_scope="input")
     guardrail_dict = {"guardrail_name": "g1"}
-    cb = initialize_presidio(params_input, guardrail_dict)
-    assert cb is created[0]
+    callbacks = initialize_presidio(params_input, guardrail_dict)
+    assert callbacks == (created[0],)
     assert created[0].apply_to_output is False
 
     # output-only
     created.clear()
     params_output = LitellmParams(guardrail="presidio", mode="pre_call", presidio_filter_scope="output")
-    cb = initialize_presidio(params_output, guardrail_dict)
+    callbacks = initialize_presidio(params_output, guardrail_dict)
     assert len(created) == 1
+    assert callbacks == (created[0],)
     assert created[0].apply_to_output is True
 
-    # both -> expect two callbacks (input + output)
+    # both -> expect two callbacks (input + output), both returned, input first
     created.clear()
     params_both = LitellmParams(guardrail="presidio", mode="pre_call", presidio_filter_scope="both")
-    cb = initialize_presidio(params_both, guardrail_dict)
+    callbacks = initialize_presidio(params_both, guardrail_dict)
     assert len(created) == 2
-    assert any(not c.apply_to_output for c in created)
-    assert any(c.apply_to_output for c in created)
+    assert callbacks == tuple(created)
+    assert callbacks[0].apply_to_output is False
+    assert callbacks[1].apply_to_output is True
+
+    # both + output_parse_pii -> three callbacks, all returned, input first
+    created.clear()
+    params_all = LitellmParams(
+        guardrail="presidio", mode="pre_call", presidio_filter_scope="both", output_parse_pii=True
+    )
+    callbacks = initialize_presidio(params_all, guardrail_dict)
+    assert len(created) == 3
+    assert callbacks == tuple(created)
+    assert callbacks[0].apply_to_output is False
+    assert mgr.added[-3:] == list(created)
 
 
 @pytest.mark.asyncio
@@ -3116,6 +3129,18 @@ def test_update_in_memory_applies_analyze_chunk_size():
     assert guardrail.presidio_analyze_chunk_size_bytes == 99_000
 
 
+def test_update_in_memory_keeps_output_masker_from_unmasking():
+    masker = _OPTIONAL_PresidioPIIMasking(mock_testing=True, apply_to_output=True, output_parse_pii=False)
+    unmasker = _OPTIONAL_PresidioPIIMasking(mock_testing=True, output_parse_pii=True)
+    params = LitellmParams(guardrail="presidio", mode="pre_call", output_parse_pii=True)
+
+    masker.update_in_memory_litellm_params(params)
+    unmasker.update_in_memory_litellm_params(params)
+
+    assert (masker.apply_to_output, masker.output_parse_pii) == (True, False)
+    assert (unmasker.apply_to_output, unmasker.output_parse_pii) == (False, True)
+
+
 def test_merge_drops_truncated_same_type_fragment_from_overlap():
     """A boundary entity seen truncated by chunk 1 and whole by chunk 2 must
     merge to the single full span; keeping both overlapping spans corrupts the
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py
new file mode 100644
index 00000000000..42bdf41bc88
--- /dev/null
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py
@@ -0,0 +1,327 @@
+"""
+Regression tests for blocking an OpenAI-format streaming response from the
+unified guardrail post-call streaming iterator hook.
+
+When a guardrail's ``apply_guardrail`` raises ``ModifyResponseException``
+while (or at the end of) a chat completions or Responses API stream is being
+relayed, the hook must emit a well-formed SSE termination sequence carrying
+the block message - NOT a bare ``data: {"error": ...}`` blob that surfaces as
+an HTTP 500 error frame and truncates the stream.
+"""
+
+import json
+from typing import Any, AsyncGenerator, Dict, Literal, Optional, Tuple, Union
+
+import pytest
+
+from litellm.integrations.custom_guardrail import (
+    CustomGuardrail,
+    ModifyResponseException,
+)
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.guardrails.guardrail_hooks.unified_guardrail.unified_guardrail import (
+    UnifiedLLMGuardrails,
+)
+from litellm.types.utils import (
+    Delta,
+    GenericGuardrailAPIInputs,
+    ModelResponseStream,
+    StreamingChoices,
+)
+
+BLOCK_MESSAGE = "This response was replaced by policy."
+
+JsonPayload = Dict[str, object]
+StreamChunk = Union[ModelResponseStream, JsonPayload, bytes]
+
+
+class _BlockingGuardrail(CustomGuardrail):
+    """Mock guardrail that always blocks response scans by raising ModifyResponseException."""
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        raise ModifyResponseException(
+            message=BLOCK_MESSAGE,
+            model="gpt-5.4-mini",
+            request_data=request_data,
+            guardrail_name=self.guardrail_name,
+        )
+
+
+class _PassingGuardrail(CustomGuardrail):
+    """Mock guardrail that always lets response scans through unchanged."""
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        return inputs
+
+
+def _chat_chunk(delta: Delta, finish_reason: Optional[str] = None) -> ModelResponseStream:
+    return ModelResponseStream(
+        id="chatcmpl-live",
+        created=1724900000,
+        model="gpt-5.4-mini",
+        choices=[StreamingChoices(index=0, delta=delta, finish_reason=finish_reason)],
+    )
+
+
+async def _chat_stream(end: bool) -> AsyncGenerator[ModelResponseStream, None]:
+    yield _chat_chunk(Delta(role="assistant", content="This "))
+    for text in ["is ", "the ", "original ", "answer."]:
+        yield _chat_chunk(Delta(content=text))
+    if end:
+        yield _chat_chunk(Delta(), finish_reason="stop")
+
+
+async def _responses_stream(end: bool) -> AsyncGenerator[JsonPayload, None]:
+    original_text = "This is the original answer."
+    response_envelope = {"id": "resp_live", "model": "gpt-5.4-mini", "status": "in_progress", "output": []}
+    yield {"type": "response.created", "response": response_envelope}
+    yield {"type": "response.in_progress", "response": response_envelope}
+    yield {
+        "type": "response.output_item.added",
+        "output_index": 0,
+        "item": {"id": "msg_orig", "type": "message", "role": "assistant", "content": []},
+    }
+    yield {
+        "type": "response.content_part.added",
+        "item_id": "msg_orig",
+        "output_index": 0,
+        "content_index": 0,
+        "part": {"type": "output_text", "text": "", "annotations": []},
+    }
+    for delta in ["This ", "is ", "the ", "original ", "answer."]:
+        yield {
+            "type": "response.output_text.delta",
+            "item_id": "msg_orig",
+            "output_index": 0,
+            "content_index": 0,
+            "delta": delta,
+        }
+    yield {
+        "type": "response.output_text.done",
+        "item_id": "msg_orig",
+        "output_index": 0,
+        "content_index": 0,
+        "text": original_text,
+    }
+    if end:
+        yield {
+            "type": "response.completed",
+            "response": {
+                "id": "resp_live",
+                "model": "gpt-5.4-mini",
+                "status": "completed",
+                "output": [
+                    {
+                        "id": "msg_orig",
+                        "type": "message",
+                        "role": "assistant",
+                        "status": "completed",
+                        "content": [{"type": "output_text", "text": original_text, "annotations": []}],
+                    }
+                ],
+                "usage": {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28},
+            },
+        }
+
+
+async def _run_hook(
+    route: str,
+    stream: AsyncGenerator[Union[ModelResponseStream, JsonPayload], None],
+    sampling_rate: int = 1,
+    end_of_stream_only: bool = False,
+    buffer_until_moderated: bool = False,
+    blocks: bool = True,
+) -> Tuple[StreamChunk, ...]:
+    guardrail = (
+        _BlockingGuardrail(guardrail_name="test-blocking-guardrail", event_hook="post_call")
+        if blocks
+        else _PassingGuardrail(guardrail_name="test-passing-guardrail", event_hook="post_call")
+    )
+    guardrail.streaming_sampling_rate = sampling_rate
+    guardrail.streaming_end_of_stream_only = end_of_stream_only
+    guardrail.streaming_buffer_until_moderated = buffer_until_moderated
+
+    unified_guardrail = UnifiedLLMGuardrails()
+    user_api_key_dict = UserAPIKeyAuth(api_key="test", request_route=route)
+    request_data = {
+        "messages": [{"role": "user", "content": "hi"}],
+        "guardrail_to_apply": guardrail,
+        "metadata": {"guardrails": [guardrail.guardrail_name]},
+    }
+
+    return tuple(
+        [
+            chunk
+            async for chunk in unified_guardrail.async_post_call_streaming_iterator_hook(
+                user_api_key_dict=user_api_key_dict,
+                response=stream,
+                request_data=request_data,
+            )
+        ]
+    )
+
+
+def _sse_payloads(collected: Tuple[StreamChunk, ...]) -> Tuple[JsonPayload, ...]:
+    return tuple(
+        json.loads(line[len("data:") :].strip())
+        for chunk in collected
+        if isinstance(chunk, bytes)
+        for block in chunk.decode().split("\n\n")
+        for line in block.strip().split("\n")
+        if line.startswith("data:")
+    )
+
+
+def _assert_no_error_frame(collected: Tuple[StreamChunk, ...]) -> None:
+    raw = "".join(chunk.decode() for chunk in collected if isinstance(chunk, bytes))
+    assert '"error"' not in raw, f"unexpected error blob in stream: {raw!r}"
+
+
+@pytest.mark.asyncio
+async def test_chat_pre_stream_block_emits_standalone_completion():
+    """Block on the first chunk: a standalone completion opens with a role delta
+    and ends with finish_reason content_filter."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=False))
+    _assert_no_error_frame(collected)
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    assert payloads[0]["choices"][0]["delta"] == {"role": "assistant", "content": BLOCK_MESSAGE}
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_mid_stream_block_continues_the_completion():
+    """Regression for the LIT-6496 500 error frame: after chunks were already
+    forwarded, the block continues the same completion id and terminates with
+    finish_reason content_filter instead of raising into an error blob."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=False), sampling_rate=5)
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    assert forwarded, "original chunks should have streamed before the block"
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    assert all(payload["id"] == "chatcmpl-live" for payload in payloads), (
+        "block chunks must continue the in-progress completion, not start a new one"
+    )
+    assert payloads[0]["choices"][0]["delta"] == {"content": BLOCK_MESSAGE}
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_end_of_stream_block_terminates_cleanly():
+    """Regression for bugbot's finish-ordering finding: in end_of_stream_only
+    mode the original finish chunk must be withheld until moderation decides,
+    so a block's content_filter finish is the only stream terminator a client
+    ever sees - never policy text trailing after finish_reason stop."""
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=True), end_of_stream_only=True)
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    assert forwarded, "content chunks still stream to the client before end-of-stream moderation"
+    assert all(choice.finish_reason is None for chunk in forwarded for choice in chunk.choices), (
+        "the original finish chunk must be withheld until moderation decides"
+    )
+    payloads = _sse_payloads(collected)
+    assert BLOCK_MESSAGE in json.dumps(payloads)
+    assert payloads[-1]["choices"][0]["finish_reason"] == "content_filter"
+
+
+@pytest.mark.asyncio
+async def test_chat_end_of_stream_pass_releases_withheld_finish_chunk():
+    """When end-of-stream moderation passes, the withheld finish chunk is
+    released so a clean stream still terminates normally."""
+    collected = await _run_hook(
+        "/v1/chat/completions", _chat_stream(end=True), end_of_stream_only=True, blocks=False
+    )
+    assert not [chunk for chunk in collected if isinstance(chunk, bytes)], (
+        "a clean stream must carry no synthetic block frames"
+    )
+    forwarded = [chunk for chunk in collected if isinstance(chunk, ModelResponseStream)]
+    finish_reasons = [choice.finish_reason for chunk in forwarded for choice in chunk.choices]
+    assert finish_reasons[-1] == "stop", "the withheld finish chunk must be released after moderation passes"
+    assert all(reason is None for reason in finish_reasons[:-1])
+
+
+@pytest.mark.asyncio
+async def test_responses_buffered_block_emits_full_event_sequence():
+    """Buffered moderation blocks before anything streams: a complete synthetic
+    Responses stream from response.created through response.completed carrying
+    the block message, with the original content never released."""
+    collected = await _run_hook("/v1/responses", _responses_stream(end=True), buffer_until_moderated=True)
+    _assert_no_error_frame(collected)
+    assert not [chunk for chunk in collected if isinstance(chunk, dict)], (
+        "buffered original chunks must never be released after a block"
+    )
+    payloads = _sse_payloads(collected)
+    event_types = [payload["type"] for payload in payloads]
+    assert event_types[0] == "response.created"
+    assert "response.output_text.delta" in event_types
+    assert event_types[-1] == "response.completed"
+    completed = payloads[-1]["response"]
+    assert completed["status"] == "completed"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+    assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
+    assert "original answer" not in json.dumps(payloads)
+
+
+@pytest.mark.asyncio
+async def test_responses_mid_stream_block_continues_the_response():
+    """Regression for the LIT-6496 500 error frame and bugbot's unclosed-item
+    finding: after events were already forwarded, the block first closes the
+    output item still open on the wire, then appends the replacement item under
+    the same response id, and closes with response.completed - never a second
+    response.created and never a completed response with an item left open."""
+    collected = await _run_hook("/v1/responses", _responses_stream(end=False))
+    _assert_no_error_frame(collected)
+    forwarded = [chunk for chunk in collected if isinstance(chunk, dict)]
+    forwarded_types = [chunk["type"] for chunk in forwarded]
+    assert "response.created" in forwarded_types, "original events should have streamed before the block"
+    payloads = _sse_payloads(collected)
+    assert payloads, "no block SSE chunks were emitted"
+    block_types = [payload["type"] for payload in payloads]
+    assert "response.created" not in block_types, "a mid-stream block must not restart the response"
+    assert block_types[-1] == "response.completed"
+
+    all_events = forwarded + list(payloads)
+    opened = sorted(event["output_index"] for event in all_events if event["type"] == "response.output_item.added")
+    closed = sorted(event["output_index"] for event in all_events if event["type"] == "response.output_item.done")
+    assert opened == closed, "every output item opened on the stream must be closed before response.completed"
+    original_done_position = block_types.index("response.output_item.done")
+    block_item_position = block_types.index("response.output_item.added")
+    assert original_done_position < block_item_position, (
+        "the in-progress original item must be closed before the block item is appended"
+    )
+    assert payloads[original_done_position]["item"]["id"] == "msg_orig"
+    assert payloads[block_item_position]["output_index"] == 1, (
+        "the block item must continue after the original output item"
+    )
+    completed = payloads[-1]["response"]
+    assert completed["id"] == "resp_live"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+
+
+@pytest.mark.asyncio
+async def test_responses_end_of_stream_block_reports_original_usage():
+    collected = await _run_hook("/v1/responses", _responses_stream(end=True), end_of_stream_only=True)
+    _assert_no_error_frame(collected)
+    forwarded_types = [chunk["type"] for chunk in collected if isinstance(chunk, dict)]
+    assert "response.completed" not in forwarded_types, (
+        "the original terminal event must be withheld and replaced by the block sequence"
+    )
+    payloads = _sse_payloads(collected)
+    completed = payloads[-1]["response"]
+    assert payloads[-1]["type"] == "response.completed"
+    assert completed["id"] == "resp_live"
+    assert completed["output"][0]["content"][0]["text"] == BLOCK_MESSAGE
+    assert completed["usage"] == {"input_tokens": 7, "output_tokens": 21, "total_tokens": 28}
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
index 8b9ecfbbeee..8cad1c634a9 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_unified_guardrail.py
@@ -948,19 +948,24 @@ class TestStreamingTransform:
         assert streamed == "ABCDEFGHIJ"
 
     @pytest.mark.asyncio
-    async def test_incremental_diff_underflow_raises(self):
+    async def test_incremental_diff_underflow_emits_error_frame(self):
         """A transform shorter than what was already streamed cannot retract
-        bytes: it raises HTTPException(stream_transform_underflow)."""
+        bytes. Chunks have already been flushed by then, so the underflow
+        surfaces as the in-stream error frame, not an unraisable HTTPException."""
+        import json as _json
+
         # First sample emits "ABCDEF" (6 chars); second sample shrinks to 3.
         guardrail = _StreamingTextGuardrail(shrink_to="ABC", shrink_after=1)
 
         chunks = [_stream_chunk("abcdef"), _stream_chunk("ghij")]
 
-        with pytest.raises(unified_module.HTTPException) as exc_info:
-            await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
+        out = await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
 
-        assert exc_info.value.status_code == 400
-        assert exc_info.value.detail["error"] == "stream_transform_underflow"
+        frame = out[-1]
+        assert isinstance(frame, bytes)
+        payload = _json.loads(frame.decode()[len("data: ") :])
+        assert payload["error"]["message"] == "stream_transform_underflow"
+        assert payload["error"]["code"] == "400"
 
     @pytest.mark.asyncio
     async def test_incremental_diff_final_chunk_preserves_finish_reason(self):
@@ -1747,3 +1752,222 @@ class TestAppliedGuardrailsReflectsExecution:
     async def test_ordinary_guardrail_is_auto_marked_applied(self):
         data = await self._run(_AutoLoggingGuardrail())
         assert "auto-logging" in _applied_guardrails(data)
+
+
+class _EosHttpBlockingGuardrail(CustomGuardrail):
+    """Raises the bedrock-shaped block HTTPException at end-of-stream scan time."""
+
+    def __init__(self):
+        super().__init__(guardrail_name="eos-http-block")
+        self.streaming_end_of_stream_only = True
+
+    def should_run_guardrail(self, data, event_type):  # type: ignore[override]
+        return True
+
+    async def apply_guardrail(self, inputs, request_data, input_type, **kwargs):
+        raise unified_module.HTTPException(
+            status_code=400,
+            detail={
+                "error": "Violated guardrail policy",
+                "bedrock_guardrail_response": "BLOCKED_TOPIC",
+            },
+        )
+
+
+def _anthropic_sse_event(event_type, data):
+    import json as _json
+
+    return f"event: {event_type}\ndata: {_json.dumps(data)}\n\n".encode()
+
+
+def _anthropic_message_chunks(texts):
+    head = [
+        _anthropic_sse_event(
+            "message_start",
+            {
+                "type": "message_start",
+                "message": {
+                    "id": "msg_test",
+                    "type": "message",
+                    "role": "assistant",
+                    "model": "claude-sonnet-5",
+                    "content": [],
+                    "stop_reason": None,
+                    "usage": {"input_tokens": 1, "output_tokens": 0},
+                },
+            },
+        ),
+        _anthropic_sse_event(
+            "content_block_start",
+            {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}},
+        ),
+    ]
+    deltas = [
+        _anthropic_sse_event(
+            "content_block_delta",
+            {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": text}},
+        )
+        for text in texts
+    ]
+    tail = [
+        _anthropic_sse_event("content_block_stop", {"type": "content_block_stop", "index": 0}),
+        _anthropic_sse_event(
+            "message_delta",
+            {
+                "type": "message_delta",
+                "delta": {"stop_reason": "end_turn", "stop_sequence": None},
+                "usage": {"output_tokens": 5},
+            },
+        ),
+        _anthropic_sse_event("message_stop", {"type": "message_stop"}),
+    ]
+    return head + deltas + tail
+
+
+class TestStreamingHttpErrorFrames:
+    """A post-flush end-of-stream guardrail block (HTTPException) must surface as
+    the endpoint's in-stream error frame instead of an unhandled raise that
+    silently truncates the SSE stream (PR #38722 defect 1)."""
+
+    @pytest.fixture(autouse=True)
+    def _use_real_mappings(self):
+        unified_module.endpoint_guardrail_translation_mappings = load_guardrail_translation_mappings()
+        yield
+        unified_module.endpoint_guardrail_translation_mappings = None
+
+    @pytest.mark.asyncio
+    async def test_chat_eos_block_emits_data_error_frame(self):
+        import json as _json
+
+        guardrail = _EosHttpBlockingGuardrail()
+        chunks = [_stream_chunk("hello "), _stream_chunk("world", finish_reason="stop")]
+
+        out = await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
+
+        assert out[0] == chunks[0]
+        assert chunks[1] not in out
+        frame = out[-1]
+        assert isinstance(frame, bytes)
+        text = frame.decode()
+        assert text.startswith("data: ")
+        payload = _json.loads(text[len("data: ") :])
+        assert payload["error"]["message"] == "Violated guardrail policy"
+        assert payload["error"]["code"] == "400"
+
+    @pytest.mark.asyncio
+    async def test_messages_eos_block_emits_anthropic_error_event(self):
+        guardrail = _EosHttpBlockingGuardrail()
+        chunks = _anthropic_message_chunks(["hello ", "world"])
+
+        out = await _drive_stream(
+            UnifiedLLMGuardrails(), guardrail, chunks, request_route="/v1/messages"
+        )
+
+        raw = b"".join(c for c in out if isinstance(c, bytes)).decode()
+        assert "hello " in raw
+        assert "event: error" in raw
+        assert "Violated guardrail policy" in raw
+        assert "guardrail_error" in raw
+
+    @pytest.mark.asyncio
+    async def test_responses_eos_block_emits_error_event_with_next_sequence(self):
+        guardrail = _EosHttpBlockingGuardrail()
+        chunks = [
+            {"type": "response.created", "sequence_number": 0},
+            {"type": "response.output_text.delta", "sequence_number": 1, "delta": "hello"},
+            {
+                "type": "response.completed",
+                "sequence_number": 2,
+                "response": {
+                    "model": "gpt-4",
+                    "output": [{"type": "message", "content": [{"type": "output_text", "text": "hello"}]}],
+                },
+            },
+        ]
+
+        out = await _drive_stream(
+            UnifiedLLMGuardrails(), guardrail, chunks, request_route="/v1/responses"
+        )
+
+        assert chunks[0] in out and chunks[1] in out
+        assert chunks[2] not in out
+        error_event = out[-1]
+        assert error_event.type == "error"
+        assert error_event.sequence_number == 2
+        assert error_event.error.message == "Violated guardrail policy"
+        assert error_event.error.code == "400"
+        assert error_event.error.type == "guardrail_error"
+
+    @pytest.mark.asyncio
+    async def test_pre_flush_block_still_raises_http_exception(self):
+        guardrail = _EosHttpBlockingGuardrail()
+        guardrail.streaming_buffer_until_moderated = True
+        chunks = [_stream_chunk("hello "), _stream_chunk("world", finish_reason="stop")]
+
+        with pytest.raises(unified_module.HTTPException) as exc_info:
+            await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
+
+        assert exc_info.value.status_code == 400
+        assert exc_info.value.detail["error"] == "Violated guardrail policy"
+
+
+class _AuditRecordingGuardrail(CustomGuardrail):
+    """Successful scan that records guardrail_information, like a flags-on audit."""
+
+    def __init__(self):
+        super().__init__(guardrail_name="audit-recorder")
+        self.streaming_end_of_stream_only = True
+
+    def should_run_guardrail(self, data, event_type):  # type: ignore[override]
+        return True
+
+    async def apply_guardrail(self, inputs, request_data, input_type, **kwargs):
+        self.add_standard_logging_guardrail_information_to_request_data(
+            guardrail_json_response={"action": "NONE"},
+            request_data=request_data,
+            guardrail_status="success",
+        )
+        return inputs
+
+
+class TestStreamingGuardrailInformationBucket:
+    """guardrail_information written during a chat streaming end-of-stream scan
+    must land in the request's ``metadata`` bucket that spend logging snapshots.
+    Regression for PR #38722 defect 2: the chat handler used to plant a
+    ``litellm_metadata`` key first, flipping the bucket so every later
+    guardrail_information write was diverted and /spend/logs showed null."""
+
+    @pytest.fixture(autouse=True)
+    def _use_real_mappings(self):
+        unified_module.endpoint_guardrail_translation_mappings = load_guardrail_translation_mappings()
+        yield
+        unified_module.endpoint_guardrail_translation_mappings = None
+
+    @pytest.mark.asyncio
+    async def test_chat_eos_scan_writes_guardrail_information_to_metadata(self):
+        guardrail = _AuditRecordingGuardrail()
+        chunks = [_stream_chunk("hello "), _stream_chunk("world", finish_reason="stop")]
+
+        async def _mock_stream():
+            for chunk in chunks:
+                yield chunk
+
+        user_api_key_dict = UserAPIKeyAuth(
+            api_key="test-key", user_id="user-1", request_route="/v1/chat/completions"
+        )
+        request_data = {"guardrail_to_apply": guardrail, "model": "gpt-4", "metadata": {}}
+
+        out = []
+        async for item in UnifiedLLMGuardrails().async_post_call_streaming_iterator_hook(
+            user_api_key_dict=user_api_key_dict,
+            response=_mock_stream(),
+            request_data=request_data,
+        ):
+            out.append(item)
+
+        assert "litellm_metadata" not in request_data
+        recorded = request_data["metadata"]["standard_logging_guardrail_information"]
+        assert len(recorded) == 1
+        assert recorded[0]["guardrail_name"] == "audit-recorder"
+        assert recorded[0]["guardrail_status"] == "success"
+        assert request_data["metadata"]["user_api_key_user_id"] == "user-1"
diff --git a/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py b/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py
index e70fc61de30..8fde4cc9d5e 100644
--- a/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py
+++ b/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py
@@ -1228,3 +1228,229 @@ class TestFireDeferredStreamLogging:
         assert info is not None, "guardrail_information should be populated"
         assert len(info) == 1
         assert info[0]["guardrail_name"] == "info-writer"
+
+
+class TestResponsesIteratorDeferredLogging:
+    """Regression for PR #38722 defect 2 on /v1/responses streams: when the
+    proxy arms _on_deferred_stream_complete, the responses streaming iterator
+    must store the logging coroutine for ProxyLogging._fire_deferred_stream_logging
+    (which runs AFTER end-of-stream guardrail scans write guardrail_information)
+    instead of dispatching immediately with a premature metadata snapshot."""
+
+    def _iterator(self, logging_obj):
+        from litellm.responses.streaming_iterator import (
+            BaseResponsesAPIStreamingIterator,
+        )
+
+        iterator = object.__new__(BaseResponsesAPIStreamingIterator)
+        iterator.logging_obj = logging_obj
+        iterator.start_time = None
+        iterator.completed_response = None
+        iterator._completed_response_logged = False
+        iterator._completed_response_cache_hit = None
+        iterator._persist_completed_response_before_logging = False
+        return iterator
+
+    def _logging_obj(self):
+        recorded = {}
+
+        async def dispatch_success_handlers(result=None, **kwargs):
+            recorded["dispatched"] = True
+
+        logging_obj = MagicMock()
+        logging_obj.dispatch_success_handlers = dispatch_success_handlers
+        return logging_obj, recorded
+
+    @pytest.mark.asyncio
+    async def test_armed_iterator_stores_deferred_coroutine(self):
+        logging_obj, recorded = self._logging_obj()
+        logging_obj._on_deferred_stream_complete = MagicMock()
+        iterator = self._iterator(logging_obj)
+
+        with patch("asyncio.create_task") as mock_create_task:
+            iterator._log_completed_response(is_async=True)
+
+        mock_create_task.assert_not_called()
+        args = logging_obj._deferred_stream_complete_args
+        assert isinstance(args, tuple) and len(args) == 1
+        assert "dispatched" not in recorded
+        await args[0]
+        assert recorded["dispatched"] is True
+
+    @pytest.mark.asyncio
+    async def test_unarmed_iterator_dispatches_immediately(self):
+        logging_obj, recorded = self._logging_obj()
+        logging_obj._on_deferred_stream_complete = None
+        iterator = self._iterator(logging_obj)
+
+        created = []
+        real_create_task = asyncio.create_task
+
+        def tracking_create_task(coro):
+            task = real_create_task(coro)
+            created.append(task)
+            return task
+
+        with patch("asyncio.create_task", side_effect=tracking_create_task):
+            iterator._log_completed_response(is_async=True)
+
+        assert len(created) == 1
+        await created[0]
+        assert recorded["dispatched"] is True
+
+
+class TestArmDeferredStreamDispatch:
+    """Regression for PR #38722: the closure shape armed on logging_obj must
+    match the args the stream's logging owner stores.  Bridged /v1/responses
+    (LiteLLMCompletionStreamingIterator) shares its inner CustomStreamWrapper's
+    logging_obj, which stores (assembled_response, cache_hit); arming the
+    single-coroutine native closure there made _fire_deferred_stream_logging
+    raise TypeError inside the streaming hook, leaking an in-stream 500 error
+    frame on every streamed /v1/responses request."""
+
+    def _processor(self):
+        return ProxyBaseLLMRequestProcessing(data={"model": "gpt-test"})
+
+    def _dispatch_recording_logging_obj(self):
+        recorded = {}
+
+        async def dispatch_success_handlers(
+            result=None, start_time=None, end_time=None, cache_hit=None, prefer_async_handlers=False
+        ):
+            recorded["result"] = result
+            recorded["cache_hit"] = cache_hit
+            recorded["prefer_async_handlers"] = prefer_async_handlers
+
+        logging_obj = MagicMock()
+        logging_obj.dispatch_success_handlers = dispatch_success_handlers
+        logging_obj._on_deferred_stream_complete = None
+        logging_obj._deferred_stream_complete_args = None
+        return logging_obj, recorded
+
+    @pytest.mark.asyncio
+    async def test_bridged_responses_iterator_gets_csw_arg_shape(self):
+        from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+            LiteLLMCompletionStreamingIterator,
+        )
+
+        logging_obj, recorded = self._dispatch_recording_logging_obj()
+        bridged = object.__new__(LiteLLMCompletionStreamingIterator)
+
+        self._processor()._arm_deferred_stream_dispatch(
+            response=bridged,
+            route_type="aresponses",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+
+        assembled = object()
+        logging_obj._deferred_stream_complete_args = (assembled, False)
+        ProxyLogging._fire_deferred_stream_logging({"litellm_logging_obj": logging_obj})
+        await asyncio.sleep(0)
+
+        assert recorded["result"] is assembled
+        assert recorded["cache_hit"] is False
+        assert recorded["prefer_async_handlers"] is True
+
+    @pytest.mark.asyncio
+    async def test_router_wrapped_bridged_iterator_gets_csw_arg_shape(self):
+        """The router wraps iterators without _hidden_params in
+        HiddenParamsAsyncIteratorWrapper before the proxy arms deferral, so
+        every production streamed /v1/responses reaches arming wrapped;
+        sniffing the wrapper instead of the inner iterator armed the 1-arg
+        native closure against the CSW's 2-arg stored shape and leaked a
+        TypeError 500 frame into the stream."""
+        from litellm.responses.litellm_completion_transformation.streaming_iterator import (
+            LiteLLMCompletionStreamingIterator,
+        )
+        from litellm.router_utils.add_retry_fallback_headers import (
+            HiddenParamsAsyncIteratorWrapper,
+        )
+
+        logging_obj, recorded = self._dispatch_recording_logging_obj()
+        wrapped = HiddenParamsAsyncIteratorWrapper(object.__new__(LiteLLMCompletionStreamingIterator))
+
+        self._processor()._arm_deferred_stream_dispatch(
+            response=wrapped,
+            route_type="aresponses",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+
+        assembled = object()
+        logging_obj._deferred_stream_complete_args = (assembled, False)
+        ProxyLogging._fire_deferred_stream_logging({"litellm_logging_obj": logging_obj})
+        await asyncio.sleep(0)
+
+        assert recorded["result"] is assembled
+        assert recorded["cache_hit"] is False
+        assert recorded["prefer_async_handlers"] is True
+
+    @pytest.mark.asyncio
+    async def test_native_stream_closure_enqueues_single_coroutine(self):
+        from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER
+
+        logging_obj, _ = self._dispatch_recording_logging_obj()
+
+        async def _agen():
+            yield b"x"
+
+        self._processor()._arm_deferred_stream_dispatch(
+            response=_agen(),
+            route_type="anthropic_messages",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+        closure = logging_obj._on_deferred_stream_complete
+        assert closure is not None
+
+        async def _logging_coroutine():
+            return None
+
+        coro = _logging_coroutine()
+        with patch.object(  # test-quality-ok: GLOBAL_LOGGING_WORKER is a process-global singleton with no injection seam
+            GLOBAL_LOGGING_WORKER, "ensure_initialized_and_enqueue"
+        ) as mock_enqueue:
+            await closure(coro)
+        mock_enqueue.assert_called_once_with(async_coroutine=coro)
+        coro.close()
+
+    @pytest.mark.asyncio
+    async def test_csw_closure_routes_through_deferred_stream_guardrails(self, monkeypatch):
+        from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
+
+        logging_obj, recorded = self._dispatch_recording_logging_obj()
+        csw = object.__new__(CustomStreamWrapper)
+        processor = self._processor()
+
+        monkeypatch.setattr(  # test-quality-ok: empty the process-global callback registry so no ambient guardrail runs
+            litellm, "callbacks", []
+        )
+        processor._arm_deferred_stream_dispatch(
+            response=csw,
+            route_type="acompletion",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+        assembled = object()
+        await logging_obj._on_deferred_stream_complete(assembled, False)
+        await asyncio.sleep(0)
+
+        assert recorded["result"] is assembled
+        assert recorded["cache_hit"] is False
+        assert recorded["prefer_async_handlers"] is True
+
+    def test_non_native_route_generator_not_armed(self):
+        logging_obj, _ = self._dispatch_recording_logging_obj()
+
+        async def _agen():
+            yield b"x"
+
+        self._processor()._arm_deferred_stream_dispatch(
+            response=_agen(),
+            route_type="acompletion",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+
+        assert logging_obj._on_deferred_stream_complete is None
diff --git a/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py b/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py
index 320e51203f6..d85c6da659b 100644
--- a/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py
+++ b/tests/test_litellm/proxy/guardrails/test_guardrail_endpoints.py
@@ -917,7 +917,9 @@ async def test_bedrock_guardrail_make_api_request_passes_api_key():
             "Content-Type": "application/json",
             "Authorization": "Bearer test-api-key-789",
         }
-        mock_request_instance.prepare.return_value = Mock()
+        mock_request_instance.prepare.return_value = Mock(
+            headers=mock_request_instance.headers
+        )
         mock_aws_request.return_value = mock_request_instance
 
         await guardrail_hook.make_bedrock_api_request(
@@ -1108,7 +1110,7 @@ async def test_update_guardrail_endpoint(
 
     elif scenario == "sync_fails_invalid_config":
         # Regression for the PUT half of the fix: a TypeError from the sync (the
-        # deleted update_in_memory_guardrail raised exactly this on every PUT)
+        # in-place update_in_memory_guardrail raised exactly this on every PUT)
         # must roll back the DB write and surface a 422, not persist the
         # rejected config with a 200.
         mock_prisma_client = mocker.Mock()
diff --git a/tests/test_litellm/proxy/guardrails/test_guardrail_registry.py b/tests/test_litellm/proxy/guardrails/test_guardrail_registry.py
index beaffa73100..56661b5b843 100644
--- a/tests/test_litellm/proxy/guardrails/test_guardrail_registry.py
+++ b/tests/test_litellm/proxy/guardrails/test_guardrail_registry.py
@@ -1,3 +1,4 @@
+from collections.abc import Iterable
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -154,51 +155,29 @@ def test_duplicate_config_guardrail_names_get_distinct_stable_ids():
         registry_module.guardrail_initializer_registry.pop("dup_name_test", None)
 
 
-def test_sync_guardrail_from_db_applies_db_dict_params_to_live_instance():
-    """
-    Regression for PUT /guardrails/{id}: the DB row arrives with litellm_params as
-    a plain jsonb dict, and the deleted update_in_memory_guardrail cast it to
-    LitellmParams without constructing one, so vars() raised and the running proxy
-    kept enforcing the stale config forever. The PUT endpoint now routes through
-    sync_guardrail_from_db, which must rebuild the live instance from the dict:
-    new blocked words compiled in, old ones gone, and the event hook re-derived
-    from mode (the base-class setattr path wrote self.mode while dispatch reads
-    self.event_hook, so only a full re-init applies a mode change).
-    """
-    from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-        ContentFilterGuardrail,
+def test_update_in_memory_guardrail():
+    handler = InMemoryGuardrailHandler()
+    handler.guardrail_id_to_custom_guardrail["123"] = CustomGuardrail(
+        guardrail_name="test-guardrail",
+        default_on=False,
+        event_hook=GuardrailEventHooks.pre_call,
     )
 
-    handler = InMemoryGuardrailHandler()
-    gid = "66666666-6666-6666-6666-666666666666"
+    handler.update_in_memory_guardrail(
+        "123",
+        Guardrail(
+            guardrail_name="test-guardrail",
+            litellm_params=LitellmParams(guardrail="test-guardrail", mode="pre_call", default_on=True),
+        ),
+    )
 
-    def db_guardrail(word: str, mode: str) -> Guardrail:
-        return Guardrail(
-            guardrail_id=gid,
-            guardrail_name="cf-put-sync",
-            litellm_params={
-                "guardrail": "litellm_content_filter",
-                "mode": mode,
-                "default_on": True,
-                "blocked_words": [{"keyword": word, "action": "BLOCK"}],
-            },
+    assert (
+        handler.guardrail_id_to_custom_guardrail["123"].should_run_guardrail(
+            data={}, event_type=GuardrailEventHooks.pre_call
         )
-
-    lists = _all_callback_lists()
-    snapshots = [list(cb_list) for cb_list in lists]
-    try:
-        handler.sync_guardrail_from_db(db_guardrail("foobarblock", "pre_call"))
-        handler.sync_guardrail_from_db(db_guardrail("quxnewblock", "during_call"))
-
-        instance = handler.guardrail_id_to_custom_guardrail[gid]
-        assert isinstance(instance, ContentFilterGuardrail)
-        assert instance._check_blocked_words("hello QUXNEWBLOCK") is not None
-        assert instance._check_blocked_words("hello FOOBARBLOCK") is None
-        assert instance.event_hook == GuardrailEventHooks.during_call
-        assert instance.should_run_guardrail(data={}, event_type=GuardrailEventHooks.during_call) is True
-    finally:
-        for cb_list, snapshot in zip(lists, snapshots):
-            cb_list[:] = snapshot
+        is True
+    )
+    assert handler.guardrail_id_to_custom_guardrail["123"].event_hook is GuardrailEventHooks.pre_call
 
 
 def _make_guardrail(guardrail_id: str, name: str = "g") -> Guardrail:
@@ -513,6 +492,144 @@ def test_repeated_db_sync_does_not_accumulate_runner_instances():
             cb_list[:] = snapshot
 
 
+PRESIDIO_SIBLINGS_GID = "55555555-5555-5555-5555-555555555555"
+PRESIDIO_SIBLINGS_NAME = "presidio-siblings"
+
+
+def _presidio_db_guardrail(pii_entities_config: dict[str, str]) -> Guardrail:
+    return Guardrail(
+        guardrail_id=PRESIDIO_SIBLINGS_GID,
+        guardrail_name=PRESIDIO_SIBLINGS_NAME,
+        litellm_params={
+            "guardrail": "presidio",
+            "mode": "pre_call",
+            "default_on": True,
+            "output_parse_pii": True,
+            "presidio_filter_scope": "both",
+            "presidio_analyzer_api_base": "https://fakelink.com/v1/presidio/analyze",
+            "presidio_anonymizer_api_base": "https://fakelink.com/v1/presidio/anonymize",
+            "pii_entities_config": pii_entities_config,
+        },
+    )
+
+
+def _presidio_callbacks_in(cb_list: Iterable[object]) -> list[CustomGuardrail]:
+    return [
+        callback
+        for callback in cb_list
+        if isinstance(callback, CustomGuardrail) and getattr(callback, "guardrail_name", None) == PRESIDIO_SIBLINGS_NAME
+    ]
+
+
+def test_presidio_siblings_are_tracked_and_deleted_together():
+    """
+    A presidio guardrail scoped to both stages registers the pre_call primary plus
+    the post_call unmask and mask-output siblings. Deleting the guardrail must remove
+    all three from every callback list, not just the primary.
+    """
+    import litellm
+
+    handler = InMemoryGuardrailHandler()
+    lists = _all_callback_lists()
+    snapshots = [list(cb_list) for cb_list in lists]
+    try:
+        handler.initialize_guardrail(_presidio_db_guardrail({"EMAIL_ADDRESS": "MASK"}))
+
+        registered = _presidio_callbacks_in(litellm.callbacks)
+        assert len(registered) == 3
+        primary = handler.guardrail_id_to_custom_guardrail[PRESIDIO_SIBLINGS_GID]
+        siblings = handler.guardrail_id_to_sibling_callbacks[PRESIDIO_SIBLINGS_GID]
+        assert primary is registered[0]
+        assert siblings == tuple(registered[1:])
+        assert [sibling.event_hook for sibling in siblings] == [GuardrailEventHooks.post_call] * 2
+
+        for cb_list in lists[1:]:
+            cb_list.extend(registered)
+
+        handler.delete_in_memory_guardrail(PRESIDIO_SIBLINGS_GID)
+
+        for cb_list in lists:
+            assert _presidio_callbacks_in(cb_list) == []
+        assert PRESIDIO_SIBLINGS_GID not in handler.guardrail_id_to_custom_guardrail
+        assert PRESIDIO_SIBLINGS_GID not in handler.guardrail_id_to_sibling_callbacks
+    finally:
+        for cb_list, snapshot in zip(lists, snapshots):
+            cb_list[:] = snapshot
+
+
+def test_update_in_memory_guardrail_reaches_presidio_siblings_and_keeps_their_stage():
+    import litellm
+
+    handler = InMemoryGuardrailHandler()
+    lists = _all_callback_lists()
+    snapshots = [list(cb_list) for cb_list in lists]
+    try:
+        handler.initialize_guardrail(_presidio_db_guardrail({"EMAIL_ADDRESS": "MASK", "IP_ADDRESS": "MASK"}))
+        tracked = _presidio_callbacks_in(litellm.callbacks)
+        roles_before = [
+            (callback.apply_to_output, callback.output_parse_pii, callback.event_hook) for callback in tracked
+        ]
+        assert roles_before == [
+            (False, True, [GuardrailEventHooks.pre_call, GuardrailEventHooks.post_call]),
+            (False, True, GuardrailEventHooks.post_call),
+            (True, False, GuardrailEventHooks.post_call),
+        ]
+
+        updated = Guardrail(
+            guardrail_id=PRESIDIO_SIBLINGS_GID,
+            guardrail_name=PRESIDIO_SIBLINGS_NAME,
+            litellm_params=LitellmParams(
+                guardrail="presidio",
+                mode="pre_call",
+                default_on=True,
+                output_parse_pii=True,
+                presidio_filter_scope="both",
+                presidio_analyzer_api_base="https://fakelink.com/v1/presidio/analyze",
+                presidio_anonymizer_api_base="https://fakelink.com/v1/presidio/anonymize",
+                pii_entities_config={"EMAIL_ADDRESS": "MASK"},
+            ),
+        )
+        handler.update_in_memory_guardrail(guardrail_id=PRESIDIO_SIBLINGS_GID, guardrail=updated)
+
+        assert [callback.pii_entities_config for callback in tracked] == [{"EMAIL_ADDRESS": "MASK"}] * 3
+        assert [
+            (callback.apply_to_output, callback.output_parse_pii, callback.event_hook) for callback in tracked
+        ] == roles_before
+        assert _presidio_callbacks_in(litellm.callbacks) == tracked
+    finally:
+        for cb_list, snapshot in zip(lists, snapshots):
+            cb_list[:] = snapshot
+
+
+def test_repeated_db_sync_replaces_presidio_siblings_instead_of_leaking_stale_ones():
+    """
+    The callback manager dedupes custom loggers by their scalar attributes, so a
+    leaked post_call sibling blocks the re-initialized sibling from registering and
+    keeps serving the previous entity config. After every DB re-sync, each callback
+    list must hold exactly the three current instances, all on the latest config.
+    """
+    import litellm
+
+    handler = InMemoryGuardrailHandler()
+    lists = _all_callback_lists()
+    snapshots = [list(cb_list) for cb_list in lists]
+    try:
+        entity_configs = [{"EMAIL_ADDRESS": "MASK"}, {"EMAIL_ADDRESS": "MASK", "IP_ADDRESS": "MASK"}]
+        for cycle in range(4):
+            latest = entity_configs[cycle % 2]
+            handler.sync_guardrail_from_db(_presidio_db_guardrail(latest))
+            for cb_list in lists[1:]:
+                cb_list.extend(_presidio_callbacks_in(litellm.callbacks))
+
+            for cb_list in lists:
+                current = _presidio_callbacks_in(cb_list)
+                assert len({id(callback) for callback in current}) == 3
+                assert all(callback.pii_entities_config == latest for callback in current)
+    finally:
+        for cb_list, snapshot in zip(lists, snapshots):
+            cb_list[:] = snapshot
+
+
 def _judge_guardrail(guardrail_id: str) -> Guardrail:
     return Guardrail(
         guardrail_id=guardrail_id,
@@ -842,3 +959,50 @@ def test_reinitialize_guardrail_raises_value_error_for_non_value_error_init_fail
         assert restored is not None and restored.guardrail_name == "regex-me"
     finally:
         registry_module.guardrail_initializer_registry.pop("regex_test", None)
+
+
+def test_sync_guardrail_from_db_applies_db_dict_params_to_live_instance():
+    """
+    Regression for PUT /guardrails/{id}: the DB row arrives with litellm_params as
+    a plain jsonb dict, and the in-place update_in_memory_guardrail cast it to
+    LitellmParams without constructing one, so vars() raised and the running proxy
+    kept enforcing the stale config forever. The PUT endpoint now routes through
+    sync_guardrail_from_db, which must rebuild the live instance from the dict:
+    new blocked words compiled in, old ones gone, and the event hook re-derived
+    from mode (the base-class setattr path wrote self.mode while dispatch reads
+    self.event_hook, so only a full re-init applies a mode change).
+    """
+    from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
+        ContentFilterGuardrail,
+    )
+
+    handler = InMemoryGuardrailHandler()
+    gid = "66666666-6666-6666-6666-666666666666"
+
+    def db_guardrail(word: str, mode: str) -> Guardrail:
+        return Guardrail(
+            guardrail_id=gid,
+            guardrail_name="cf-put-sync",
+            litellm_params={
+                "guardrail": "litellm_content_filter",
+                "mode": mode,
+                "default_on": True,
+                "blocked_words": [{"keyword": word, "action": "BLOCK"}],
+            },
+        )
+
+    lists = _all_callback_lists()
+    snapshots = [list(cb_list) for cb_list in lists]
+    try:
+        handler.sync_guardrail_from_db(db_guardrail("foobarblock", "pre_call"))
+        handler.sync_guardrail_from_db(db_guardrail("quxnewblock", "during_call"))
+
+        instance = handler.guardrail_id_to_custom_guardrail[gid]
+        assert isinstance(instance, ContentFilterGuardrail)
+        assert instance._check_blocked_words("hello QUXNEWBLOCK") is not None
+        assert instance._check_blocked_words("hello FOOBARBLOCK") is None
+        assert instance.event_hook == GuardrailEventHooks.during_call
+        assert instance.should_run_guardrail(data={}, event_type=GuardrailEventHooks.during_call) is True
+    finally:
+        for cb_list, snapshot in zip(lists, snapshots):
+            cb_list[:] = snapshot
diff --git a/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py b/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py
index 26beaa78a46..ab4e15ff423 100644
--- a/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py
+++ b/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py
@@ -1,16 +1,16 @@
-from fastapi.exceptions import HTTPException
-from unittest.mock import patch, AsyncMock
-from httpx import Response, Request
+import asyncio
 import base64
+from unittest.mock import AsyncMock, patch
 
 import pytest
-
-from litellm.proxy.guardrails.guardrail_hooks.prompt_security.prompt_security import (
-    PromptSecurityGuardrailMissingSecrets,
-    PromptSecurityGuardrail,
-)
+from fastapi.exceptions import HTTPException
+from httpx import ReadTimeout, Request, Response
 
 import litellm
+from litellm.proxy.guardrails.guardrail_hooks.prompt_security.prompt_security import (
+    PromptSecurityGuardrail,
+    PromptSecurityGuardrailMissingSecrets,
+)
 from litellm.proxy.guardrails.init_guardrails import init_guardrails_v2
 
 
@@ -30,6 +30,7 @@ def test_prompt_security_guard_config(monkeypatch: pytest.MonkeyPatch):
                     "guardrail": "prompt_security",
                     "mode": "during_call",
                     "default_on": True,
+                    "file_sanitization_fail_open": False,
                 },
             }
         ],
@@ -41,6 +42,10 @@ def test_prompt_security_guard_config(monkeypatch: pytest.MonkeyPatch):
     assert registered[0].guardrail_name == "prompt_security"
     assert registered[0].default_on is True
     assert registered[0].event_hook == "during_call"
+    assert registered[0].file_sanitization_fail_open is False
+    config_model = registered[0].get_config_model()
+    assert config_model is not None
+    assert config_model().file_sanitization_fail_open is True
 
 
 def test_prompt_security_guard_config_no_api_key(monkeypatch: pytest.MonkeyPatch):
@@ -374,6 +379,86 @@ async def test_file_sanitization(monkeypatch: pytest.MonkeyPatch):
     assert result is not None
 
 
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "timeout",
+    (
+        litellm.Timeout(
+            message="Prompt Security upload timed out",
+            model="default-model-name",
+            llm_provider="litellm-httpx-handler",
+        ),
+        ReadTimeout(
+            "Prompt Security poll timed out",
+            request=Request(method="GET", url="https://test.prompt.security/api/sanitizeFile"),
+        ),
+    ),
+    ids=("litellm", "httpx"),
+)
+@pytest.mark.parametrize("fail_open", (True, False), ids=("fail-open", "fail-closed"))
+async def test_file_sanitization_request_timeout_policy(
+    monkeypatch: pytest.MonkeyPatch, timeout: Exception, fail_open: bool
+):
+    monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key")
+    monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security")
+
+    guardrail = PromptSecurityGuardrail(
+        guardrail_name="test-guard",
+        event_hook="pre_call",
+        default_on=True,
+        file_sanitization_fail_open=fail_open,
+    )
+
+    with patch.object(guardrail.async_handler, "post", AsyncMock(side_effect=timeout)):
+        if not fail_open:
+            with pytest.raises(HTTPException) as exc_info:
+                await guardrail.sanitize_file_content(b"file-content", "document.pdf")
+            assert exc_info.value.status_code == 408
+            assert exc_info.value.detail == "File sanitization timeout"
+            return
+
+        result = await guardrail.sanitize_file_content(b"file-content", "document.pdf")
+
+    assert result == {
+        "action": "allow",
+        "content": None,
+        "metadata": {},
+        "violations": (),
+    }
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("fail_open", (True, False), ids=("fail-open", "fail-closed"))
+async def test_file_sanitization_overall_timeout_policy(monkeypatch: pytest.MonkeyPatch, fail_open: bool):
+    monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key")
+    monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security")
+
+    guardrail = PromptSecurityGuardrail(
+        guardrail_name="test-guard",
+        event_hook="pre_call",
+        default_on=True,
+        file_sanitization_timeout=0.01,
+        file_sanitization_fail_open=fail_open,
+    )
+
+    async def hanging_post(*_args: object, **_kwargs: object) -> None:
+        await asyncio.sleep(60)
+        raise AssertionError("sanitization request should have been cancelled")
+
+    with patch.object(guardrail.async_handler, "post", side_effect=hanging_post):
+        if not fail_open:
+            with pytest.raises(HTTPException) as exc_info:
+                await guardrail.sanitize_file_content(b"file-content", "document.pdf")
+            assert exc_info.value.status_code == 408
+            assert exc_info.value.detail == "File sanitization timeout"
+            return
+
+        result = await guardrail.sanitize_file_content(b"file-content", "document.pdf")
+
+    assert result["action"] == "allow"
+    assert result["content"] is None
+
+
 @pytest.mark.asyncio
 async def test_file_sanitization_block(monkeypatch: pytest.MonkeyPatch):
     """Test that file sanitization blocks malicious files"""
@@ -544,7 +629,7 @@ async def test_role_filtering(monkeypatch: pytest.MonkeyPatch):
         return mock_response
 
     with patch.object(guardrail.async_handler, "post", side_effect=mock_post):
-        result = await guardrail.apply_guardrail(
+        await guardrail.apply_guardrail(
             inputs=inputs,
             request_data=request_data,
             input_type="request",
diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
index 2a540f4f522..8043a1aca3f 100644
--- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
+++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py
@@ -567,9 +567,7 @@ async def test_update_database_and_spend_counters_preserves_db_exception_when_re
 @pytest.mark.asyncio
 async def test_update_database_and_spend_counters_updates_counters_after_db_update():
     proxy_logging_obj = MagicMock()
-    proxy_logging_obj.db_spend_update_writer.update_database = AsyncMock(
-        return_value="chatcmpl-abc123"
-    )
+    proxy_logging_obj.db_spend_update_writer.update_database = AsyncMock()
     increment_spend_counters = AsyncMock()
     budget_reservation = {"reserved_cost": 0.5, "entries": []}
     start_time = datetime.now()
@@ -602,7 +600,6 @@ async def test_update_database_and_spend_counters_updates_counters_after_db_upda
         budget_reservation=budget_reservation,
         end_user_id="test_end_user_id",
         tags=["tag-a"],
-        request_id="chatcmpl-abc123",
         request_started_at=start_time,
         model_access_groups=("premium",),
     )
@@ -1884,61 +1881,6 @@ async def test_track_cost_callback_logs_unauthenticated_pass_through_request(
         )
 
 
-@pytest.mark.asyncio
-async def test_update_database_and_spend_counters_forwards_the_spend_log_request_id():
-    """The budget-window flush excludes the log rows its increments already
-    cover. That only works if the id update_database recorded the row under is
-    handed to the counter update, so this seam is load-bearing."""
-    proxy_logging_obj = MagicMock()
-    proxy_logging_obj.db_spend_update_writer.update_database = AsyncMock(
-        return_value="chatcmpl-abc123"
-    )
-    increment_spend_counters = AsyncMock()
-
-    await _update_database_and_spend_counters(
-        proxy_logging_obj=proxy_logging_obj,
-        increment_spend_counters=increment_spend_counters,
-        user_api_key="test_api_key",
-        user_id="test_user_id",
-        end_user_id=None,
-        team_id="test_team_id",
-        org_id="test_org_id",
-        kwargs={},
-        completion_response=None,
-        start_time=datetime.now(),
-        end_time=datetime.now(),
-        response_cost=0.2,
-        budget_reservation=None,
-    )
-
-    assert increment_spend_counters.await_args.kwargs["request_id"] == "chatcmpl-abc123"
-
-
-@pytest.mark.asyncio
-async def test_update_database_and_spend_counters_forwards_a_missing_request_id_as_none():
-    proxy_logging_obj = MagicMock()
-    proxy_logging_obj.db_spend_update_writer.update_database = AsyncMock(return_value=None)
-    increment_spend_counters = AsyncMock()
-
-    await _update_database_and_spend_counters(
-        proxy_logging_obj=proxy_logging_obj,
-        increment_spend_counters=increment_spend_counters,
-        user_api_key="test_api_key",
-        user_id="test_user_id",
-        end_user_id=None,
-        team_id="test_team_id",
-        org_id="test_org_id",
-        kwargs={},
-        completion_response=None,
-        start_time=datetime.now(),
-        end_time=datetime.now(),
-        response_cost=0.2,
-        budget_reservation=None,
-    )
-
-    assert increment_spend_counters.await_args.kwargs["request_id"] is None
-
-
 class _FakeDeploymentLookup:
     """Deployment lookup returning the access groups each deployment declares."""
 
diff --git a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
index 957f9fde645..1697b77b99a 100644
--- a/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/scim/test_scim_v2_endpoints.py
@@ -1,7 +1,8 @@
 import logging
 import time
-from collections.abc import Mapping
+from collections.abc import Callable, Mapping, Sequence
 from itertools import chain
+from types import MappingProxyType
 from typing import Final
 from unittest.mock import AsyncMock, MagicMock, call
 
@@ -38,6 +39,7 @@ from litellm.proxy.management_endpoints.scim.scim_v2 import (
     get_groups,
     get_users,
     get_service_provider_config,
+    merge_placeholder,
     patch_group,
     patch_team_membership,
     patch_user,
@@ -52,6 +54,7 @@ from litellm.types.proxy.management_endpoints.scim_v2 import (
     SCIMMember,
     SCIMPatchOp,
     SCIMPatchOperation,
+    SCIMPlaceholderMergeResult,
     SCIMServiceProviderConfig,
     SCIMUser,
     SCIMUserEmail,
@@ -778,13 +781,17 @@ async def test_handle_existing_user_by_email_without_teams_preserves_memberships
         "litellm.proxy.management_endpoints.scim.scim_v2.ScimTransformations.transform_litellm_user_to_scim_user",
         AsyncMock(return_value=None),
     )
-    mock_team_member_add = mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
-        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
-        AsyncMock(),
+    mock_team_member_add = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
+            AsyncMock(),
+        )
     )
-    mock_team_member_delete = mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
-        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete",
-        AsyncMock(),
+    mock_team_member_delete = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the helper
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete",
+            AsyncMock(),
+        )
     )
 
     new_user_request = NewUserRequest(
@@ -1645,6 +1652,25 @@ async def test_update_group_e2e(mocker):
     ScimTransformations.transform_litellm_team_to_scim_group.assert_called_once_with(updated_team)
 
 
+def _rows_by_exact_id(
+    user_row: Callable[[Mapping[str, str]], LiteLLM_UserTable | MagicMock | None],
+) -> Callable[..., tuple[LiteLLM_UserTable | MagicMock, ...]]:
+    """``find_many`` stand-in for the classifier's cross-field read on a table where a
+    member value only ever matches as an exact ``user_id``."""
+
+    def rows(where: Mapping[str, object], take: int | None = None) -> tuple[LiteLLM_UserTable | MagicMock, ...]:
+        clauses: Final = where["OR"]
+        assert isinstance(clauses, list)
+        found: Final = tuple(user_row(clause) for clause in clauses if "user_id" in clause)
+        return tuple(row for row in found if row is not None)
+
+    return rows
+
+
+def _user_row_for(where: Mapping[str, str]) -> LiteLLM_UserTable:
+    return LiteLLM_UserTable(user_id=where["user_id"])
+
+
 @pytest.mark.asyncio
 async def test_create_group_with_nonexistent_users_rejects(mocker, monkeypatch):
     """
@@ -1696,9 +1722,8 @@ async def test_create_group_with_nonexistent_users_rejects(mocker, monkeypatch):
             return mock_user
         return None  # new-user-1 and new-user-2 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -1782,9 +1807,8 @@ async def test_update_group_with_nonexistent_users_rejects(mocker, monkeypatch):
             return mock_user
         return None  # new-user-3 and new-user-4 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -1853,9 +1877,8 @@ async def test_create_group_with_nonexistent_users_creates_when_flag_true(mocker
             return mock_user
         return None  # new-user-1 and new-user-2 don't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock user creation
     created_user_1 = NewUserResponse(user_id="new-user-1", key="test-key-1")
@@ -1943,9 +1966,8 @@ async def test_extract_group_member_ids_with_flag_true_creates_users(mocker, mon
             return mock_user
         return None  # new-user-1 doesn't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock user creation
     created_user = NewUserResponse(user_id="new-user-1", key="test-key-1")
@@ -2013,9 +2035,8 @@ async def test_extract_group_member_ids_with_flag_false_rejects(mocker, monkeypa
             return mock_user
         return None  # new-user-1 doesn't exist
 
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=mock_user_lookup)
     mock_prisma_client.db.litellm_usertable.find_first = AsyncMock(return_value=None)
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=[])
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(mock_user_lookup))
 
     # Mock dependencies
     mocker.patch(
@@ -3121,8 +3142,7 @@ async def test_process_group_patch_operations_add_retains_existing_members(mocke
     mock_prisma_client.db = mocker.MagicMock()
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
     # new-user already exists in the DB
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock(user_id="new-user"))
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=(mocker.MagicMock(user_id="new-user"),))
 
     _, final_members, _ = await _process_group_patch_operations(
         patch_ops=patch_ops,
@@ -3415,8 +3435,7 @@ async def test_patch_group_add_applies_delta_and_keeps_concurrent_add(mocker):
     )
     mock_prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=final_team)
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock())
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(_user_row_for))
 
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
@@ -3509,8 +3528,7 @@ async def test_patch_group_replace_stays_absolute_against_concurrent_roster(mock
     )
     mock_prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=final_team)
     mock_prisma_client.db.litellm_usertable = mocker.MagicMock()
-    mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=mocker.MagicMock())
-    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    mock_prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=_rows_by_exact_id(_user_row_for))
 
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
@@ -3640,8 +3658,7 @@ async def test_process_group_patch_add_filtered_path_without_value(mocker):
     prisma_client = mocker.MagicMock()
     prisma_client.db = mocker.MagicMock()
     prisma_client.db.litellm_usertable = mocker.MagicMock()
-    prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=LiteLLM_UserTable(user_id="user-3"))
-    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=(LiteLLM_UserTable(user_id="user-3"),))
 
     _, final_members, _ = await _process_group_patch_operations(
         patch_ops=patch_ops,
@@ -3733,12 +3750,14 @@ def _member_resolution_prisma(
         starts folding it, fails here instead of passing.
 
         A caller that must know which accounts match rather than merely how many
-        passes take=None, so an unbounded read returns every match.
+        passes take=None, so an unbounded read returns every match. The row keyed by
+        the value comes last, the order a bounded read is least prepared for, since
+        the database promises no order at all.
         """
         clauses: Final = where["OR"]
         assert isinstance(clauses, list)
         fields: Final = tuple(next(iter(clause)) for clause in clauses)
-        assert fields == ("sso_user_id", "user_email"), fields
+        assert fields in (("user_id", "sso_user_id", "user_email"), ("sso_user_id", "user_email")), fields
 
         def comparison(clause: Mapping[str, object]) -> tuple[str, bool]:
             """The needle and whether production asked for a case-insensitive compare,
@@ -3749,8 +3768,9 @@ def _member_resolution_prisma(
             assert isinstance(criterion, dict), criterion
             return criterion["equals"], criterion.get("mode") == "insensitive"
 
-        sso_needle, sso_insensitive = comparison(clauses[0])
-        email_needle, email_insensitive = comparison(clauses[1])
+        by_field: Final = dict(zip(fields, (comparison(clause) for clause in clauses)))
+        sso_needle, sso_insensitive = by_field["sso_user_id"]
+        email_needle, email_insensitive = by_field["user_email"]
 
         def same(stored: str, needle: str, insensitive: bool) -> bool:
             return stored.casefold() == needle.casefold() if insensitive else stored == needle
@@ -3768,6 +3788,11 @@ def _member_resolution_prisma(
                     if same(email, email_needle, email_insensitive)
                     for user_id in user_ids
                 ),
+                (
+                    user_id
+                    for user_id in users
+                    if "user_id" in by_field and same(user_id, by_field["user_id"][0], by_field["user_id"][1])
+                ),
             )
         )
         found: Final = tuple(dict.fromkeys(matched))
@@ -4452,9 +4477,11 @@ async def test_create_group_applies_default_team_params(
         "litellm.proxy.management_endpoints.scim.scim_v2._get_prisma_client_or_raise_exception",
         AsyncMock(return_value=_member_resolution_prisma(mocker, users=set(), teams=set())),
     )
-    new_team_mock = mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
-        "litellm.proxy.management_endpoints.scim.scim_v2.new_team",
-        AsyncMock(return_value=mocker.MagicMock()),
+    new_team_mock = (
+        mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
+            "litellm.proxy.management_endpoints.scim.scim_v2.new_team",
+            AsyncMock(return_value=mocker.MagicMock()),
+        )
     )
     mocker.patch(  # test-quality-ok: endpoint collaborators are module-level, not injectable into create_group
         "litellm.proxy.management_endpoints.scim.scim_v2.ScimTransformations.transform_litellm_team_to_scim_group",
@@ -4611,9 +4638,15 @@ async def test_resolve_group_member_ids_dedupes_repeated_member(mocker, scim_ups
 
 
 def _identity_lookup(value: str) -> object:
-    """The single cross-field lookup the classifier is expected to issue."""
+    """The single cross-field lookup the classifier is expected to issue per member."""
     return call(
-        where={"OR": [{"sso_user_id": value}, {"user_email": {"equals": value, "mode": "insensitive"}}]},
+        where={
+            "OR": [
+                {"user_id": value},
+                {"sso_user_id": value},
+                {"user_email": {"equals": value, "mode": "insensitive"}},
+            ]
+        },
         take=2,
     )
 
@@ -4903,9 +4936,7 @@ async def test_process_group_patch_remove_by_the_id_the_directory_added_with(
 
 
 @pytest.mark.asyncio
-async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_literal_id(
-    mocker, scim_upsert_user_enabled
-):
+async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_literal_id(mocker, scim_upsert_user_enabled):
     """An earlier release put unmatched ids on the roster verbatim, so a remove has to
     keep clearing the id as written even once it also resolves."""
     patch_ops = SCIMPatchOp(
@@ -4916,7 +4947,10 @@ async def test_process_group_patch_remove_still_drops_a_placeholder_by_its_liter
         team_id="parent-group",
         team_alias="Parent Group",
         members=[],
-        members_with_roles=[Member(user_id="legacy@example.com", role="user"), Member(user_id="keep-user", role="user")],
+        members_with_roles=[
+            Member(user_id="legacy@example.com", role="user"),
+            Member(user_id="keep-user", role="user"),
+        ],
     )
 
     _, final_members, _ = await _process_group_patch_operations(
@@ -5081,11 +5115,8 @@ async def test_process_group_patch_remove_refuses_when_two_members_share_the_id(
     assert "more than one member of this group" in str(exc_info.value.detail)
 
 
-
 @pytest.mark.asyncio
-async def test_resolve_group_member_ids_exact_user_id_wins_when_it_names_nobody_else(
-    mocker, scim_upsert_user_enabled
-):
+async def test_resolve_group_member_ids_exact_user_id_wins_when_it_names_nobody_else(mocker, scim_upsert_user_enabled):
     """The canonical user id stays authoritative, including when the same account also
     holds that value as its email, which is how a SCIM-provisioned account is keyed."""
     prisma_client = _member_resolution_prisma(
@@ -5147,10 +5178,79 @@ async def test_resolve_group_member_ids_refuses_a_user_id_that_names_another_acc
     assert exc_info.value.status_code == 400
     assert "member-id" in str(exc_info.value.detail)
     create_user_mock.assert_not_called()
-    assert any(
-        record.levelno >= logging.WARNING and "someone-else" in record.getMessage() for record in caplog.records
+    assert any(record.levelno >= logging.WARNING and "someone-else" in record.getMessage() for record in caplog.records)
+
+
+@pytest.mark.asyncio
+async def test_resolve_group_member_ids_reads_the_exact_id_when_two_other_accounts_fill_the_lookup(
+    mocker, scim_upsert_user_enabled
+):
+    """A value that is one account's id and two other accounts' identities fills the
+    bounded lookup with the other two. The account keyed by the value must still be
+    found, or the id would lose its precedence and a non-canonical type would skip
+    a member that names a real user."""
+    prisma_client = _member_resolution_prisma(
+        mocker,
+        users={"shared"},
+        teams=set(),
+        sso_user_id_to_user_id={"shared": "by-sso"},
+        email_to_user_id={"shared": "by-email"},
+    )
+    create_user_mock = mocker.patch(  # test-quality-ok: user creation is module-level, not injectable into the resolver
+        "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
+        AsyncMock(return_value=None),
     )
 
+    with pytest.raises(HTTPException) as exc_info:
+        await _resolve_group_member_ids(
+            members=[SCIMMember(value="shared", type="direct")],
+            created_via="scim_group_membership",
+            prisma_client=prisma_client,
+        )
+
+    assert exc_info.value.status_code == 400
+    assert "shared" in str(exc_info.value.detail)
+    create_user_mock.assert_not_called()
+    assert prisma_client.db.litellm_usertable.find_many.await_args_list == [_identity_lookup("shared")]
+    prisma_client.db.litellm_usertable.find_unique.assert_awaited_once_with(where={"user_id": "shared"})
+
+
+@pytest.mark.asyncio
+async def test_resolve_group_member_ids_reads_the_user_table_once_per_member(mocker, scim_upsert_user_enabled):
+    """Every member costs one read of the user table, however it resolves: by its exact
+    id (which still outranks a non-canonical type), by identity, as a SCIM team, or not
+    at all. Looking the exact id up on its own before the identity read doubled the
+    reads of a push, and the identity read is a scan."""
+    prisma_client = _member_resolution_prisma(
+        mocker,
+        users={"by-id"},
+        teams={"by-team"},
+        email_to_user_id={"by-email@example.com": "email-user"},
+    )
+    mocker.patch(  # test-quality-ok: user creation is module-level, not injectable into the resolver
+        "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
+        AsyncMock(return_value=NewUserResponse(user_id="nobody", key="key")),
+    )
+
+    result = await _resolve_group_member_ids(
+        members=[
+            SCIMMember(value="by-id", type="direct"),
+            SCIMMember(value="by-email@example.com"),
+            SCIMMember(value="by-team"),
+            SCIMMember(value="nobody"),
+        ],
+        created_via="scim_group_membership",
+        prisma_client=prisma_client,
+    )
+
+    assert result.all_member_ids == ["by-id", "email-user", "nobody"]
+    prisma_client.db.litellm_usertable.find_unique.assert_not_awaited()
+    assert prisma_client.db.litellm_usertable.find_many.await_args_list == [
+        _identity_lookup("by-id"),
+        _identity_lookup("by-email@example.com"),
+        _identity_lookup("by-team"),
+        _identity_lookup("nobody"),
+    ]
 
 
 @pytest.mark.asyncio
@@ -5536,10 +5636,7 @@ async def test_resolve_group_member_ids_admits_member_created_concurrently(mocke
     the member is still admitted: the id resolves to a real user row, so failing
     or dropping it would be wrong either way."""
     prisma_client = _member_resolution_prisma(mocker, users=set(), teams=set())
-    prisma_client.db.litellm_usertable.find_unique = AsyncMock(
-        side_effect=[None, LiteLLM_UserTable(user_id="raced-user")]
-    )
-    prisma_client.db.litellm_usertable.find_many = AsyncMock(return_value=())
+    prisma_client.db.litellm_usertable.find_unique = AsyncMock(return_value=LiteLLM_UserTable(user_id="raced-user"))
     mocker.patch(
         "litellm.proxy.management_endpoints.scim.scim_v2._create_user_if_not_exists",
         AsyncMock(return_value=None),
@@ -5619,3 +5716,196 @@ async def test_patch_group_404s_when_team_deleted_mid_request(mocker):
 
     assert exc_info.value.code == "404"
     assert f"Group not found with ID: {group_id}" in exc_info.value.message
+
+
+_SHADOW_MEMBER_VALUE: Final = "00u1shadow"
+_SHADOWED_ACCOUNT: Final = "real-1"
+_SHADOWED_GROUP: Final = "grp-eng"
+
+
+def _shadowed_tenant_rows() -> tuple[LiteLLM_UserTable, ...]:
+    """A placeholder keyed by the raw member value, and the real account that value names by SSO id."""
+    return (
+        LiteLLM_UserTable(user_id=_SHADOW_MEMBER_VALUE, user_email=_SHADOW_MEMBER_VALUE, teams=[_SHADOWED_GROUP]),
+        LiteLLM_UserTable(user_id=_SHADOWED_ACCOUNT, user_email="alice@example.com", sso_user_id=_SHADOW_MEMBER_VALUE),
+    )
+
+
+def _shadow_tenant_prisma(
+    mocker: MockerFixture,
+    *,
+    rows: Sequence[LiteLLM_UserTable],
+    keys_owned_by: Mapping[str, int] = MappingProxyType({}),
+) -> MagicMock:
+    """Prisma fake whose user rows are live: deleting one removes it from every later lookup."""
+    users: Final[dict[str, LiteLLM_UserTable]] = {row.user_id: row for row in rows}
+    team: Final = LiteLLM_TeamTable(
+        team_id=_SHADOWED_GROUP,
+        members=[_SHADOW_MEMBER_VALUE],
+        members_with_roles=[Member(user_id=_SHADOW_MEMBER_VALUE, role="user")],
+        metadata={SCIM_MANAGED_TEAM_METADATA_KEY: True},
+    )
+
+    async def find_unique(where: Mapping[str, str]) -> LiteLLM_UserTable | None:
+        return users.get(where["user_id"])
+
+    def clause_matches(row: LiteLLM_UserTable, clause: Mapping[str, object]) -> bool:
+        if "user_id" in clause:
+            return row.user_id == clause["user_id"]
+        if "sso_user_id" in clause:
+            return row.sso_user_id == clause["sso_user_id"]
+        email_filter: Final = clause["user_email"]
+        assert isinstance(email_filter, dict)
+        return (row.user_email or "").casefold() == str(email_filter["equals"]).casefold()
+
+    async def identity_rows(where: Mapping[str, object], take: int | None = None) -> tuple[LiteLLM_UserTable, ...]:
+        clauses: Final = where["OR"]
+        assert isinstance(clauses, list)
+        matched: Final = tuple(row for row in users.values() if any(clause_matches(row, clause) for clause in clauses))
+        return matched[:take] if take else matched
+
+    async def delete(where: Mapping[str, str]) -> LiteLLM_UserTable | None:
+        return users.pop(where["user_id"], None)
+
+    async def keys_for(where: Mapping[str, object]) -> tuple[MagicMock, ...]:
+        return tuple(mocker.MagicMock() for _ in range(keys_owned_by.get(str(where["user_id"]), 0)))
+
+    async def team_lookup(where: Mapping[str, str]) -> LiteLLM_TeamTable | None:
+        return team if where["team_id"] == team.team_id else None
+
+    prisma_client = mocker.MagicMock()
+    prisma_client.db = mocker.MagicMock()
+    prisma_client.db.litellm_usertable = mocker.MagicMock()
+    prisma_client.db.litellm_usertable.find_unique = AsyncMock(side_effect=find_unique)
+    prisma_client.db.litellm_usertable.find_many = AsyncMock(side_effect=identity_rows)
+    prisma_client.db.litellm_usertable.delete = AsyncMock(side_effect=delete)
+    prisma_client.db.litellm_teamtable = mocker.MagicMock()
+    prisma_client.db.litellm_teamtable.find_unique = AsyncMock(side_effect=team_lookup)
+    prisma_client.db.litellm_teamtable.update = AsyncMock(return_value=team)
+    prisma_client.db.litellm_verificationtoken = mocker.MagicMock()
+    prisma_client.db.litellm_verificationtoken.find_many = AsyncMock(side_effect=keys_for)
+    prisma_client.db.litellm_invitationlink = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    prisma_client.db.litellm_organizationmembership = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    prisma_client.db.litellm_teammembership = mocker.MagicMock(delete_many=AsyncMock(return_value=0))
+    return prisma_client
+
+
+@pytest.fixture
+def shadowed_tenant(mocker, monkeypatch, scim_upsert_user_enabled) -> MagicMock:
+    from litellm.proxy import proxy_server
+
+    prisma_client: Final = _shadow_tenant_prisma(mocker, rows=_shadowed_tenant_rows())
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma_client)
+    return prisma_client
+
+
+async def _push_shadow_member(prisma_client: MagicMock):
+    return await _resolve_group_member_ids(
+        members=[SCIMMember(value=_SHADOW_MEMBER_VALUE)],
+        created_via="scim_group_membership",
+        prisma_client=prisma_client,
+    )
+
+
+@pytest.mark.asyncio
+async def test_merge_placeholder_hands_the_group_to_the_shadowed_account(mocker, shadowed_tenant):
+    """Every group push of the shadowing value is refused until the placeholder is folded into
+    the real account; after the merge the same push resolves to that account."""
+    team_member_add_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add", AsyncMock()
+        )
+    )
+    team_member_delete_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete", AsyncMock()
+        )
+    )
+
+    with pytest.raises(HTTPException) as before:
+        await _push_shadow_member(shadowed_tenant)
+    assert before.value.status_code == 400
+
+    result: Final = await merge_placeholder(user_id=_SHADOW_MEMBER_VALUE)
+
+    assert result == SCIMPlaceholderMergeResult(
+        placeholder_user_id=_SHADOW_MEMBER_VALUE,
+        merged_into_user_id=_SHADOWED_ACCOUNT,
+        team_ids=(_SHADOWED_GROUP,),
+    )
+    added: Final = team_member_add_mock.call_args.kwargs["data"]
+    assert (added.team_id, added.member.user_id) == (_SHADOWED_GROUP, _SHADOWED_ACCOUNT)
+    dropped: Final = team_member_delete_mock.call_args.kwargs["data"]
+    assert (dropped.team_id, dropped.user_id) == (_SHADOWED_GROUP, _SHADOW_MEMBER_VALUE)
+    shadowed_tenant.db.litellm_teammembership.delete_many.assert_awaited_once_with(
+        where={"user_id": _SHADOW_MEMBER_VALUE}
+    )
+    shadowed_tenant.db.litellm_usertable.delete.assert_awaited_once_with(where={"user_id": _SHADOW_MEMBER_VALUE})
+
+    after: Final = await _push_shadow_member(shadowed_tenant)
+    assert after.all_member_ids == [_SHADOWED_ACCOUNT]
+    assert after.created_users == []
+
+
+@pytest.mark.asyncio
+async def test_merge_placeholder_keeps_the_placeholder_when_the_roster_write_fails(mocker, shadowed_tenant):
+    """If the real account cannot join the team, the placeholder stays on it, or the membership is gone
+    from both accounts."""
+    mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+        "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add",
+        AsyncMock(side_effect=Exception("database connection lost")),
+    )
+    team_member_delete_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_delete", AsyncMock()
+        )
+    )
+
+    with pytest.raises(ProxyException):
+        await merge_placeholder(user_id=_SHADOW_MEMBER_VALUE)
+
+    team_member_delete_mock.assert_not_awaited()
+    shadowed_tenant.db.litellm_usertable.delete.assert_not_awaited()
+    assert await shadowed_tenant.db.litellm_usertable.find_unique(where={"user_id": _SHADOW_MEMBER_VALUE}) is not None
+
+
+@pytest.mark.parametrize(
+    ("rows", "keys_owned_by", "merged", "reason"),
+    [
+        pytest.param(_shadowed_tenant_rows(), {}, _SHADOWED_ACCOUNT, "SSO identity of its own", id="real-account"),
+        pytest.param(
+            _shadowed_tenant_rows(), {_SHADOW_MEMBER_VALUE: 2}, _SHADOW_MEMBER_VALUE, "2 virtual keys", id="owns-keys"
+        ),
+        pytest.param(_shadowed_tenant_rows()[:1], {}, _SHADOW_MEMBER_VALUE, "shadows no account", id="names-nobody"),
+        pytest.param(
+            (*_shadowed_tenant_rows(), LiteLLM_UserTable(user_id="real-2", user_email=_SHADOW_MEMBER_VALUE.upper())),
+            {},
+            _SHADOW_MEMBER_VALUE,
+            "names 2 accounts (real-1, real-2)",
+            id="names-two-accounts",
+        ),
+    ],
+)
+@pytest.mark.asyncio
+async def test_merge_placeholder_refuses_rows_that_are_not_a_lone_placeholder(
+    mocker, monkeypatch, scim_upsert_user_enabled, rows, keys_owned_by, merged, reason
+):
+    """Only a row with no SSO identity and no keys whose id names exactly one other account is folded;
+    anything else could move memberships to the wrong person, so nothing is written."""
+    from litellm.proxy import proxy_server
+
+    prisma_client: Final = _shadow_tenant_prisma(mocker, rows=rows, keys_owned_by=keys_owned_by)
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma_client)
+    team_member_add_mock = (
+        mocker.patch(  # test-quality-ok: roster helpers are module-level, not injectable into the endpoint
+            "litellm.proxy.management_endpoints.scim.scim_v2.team_member_add", AsyncMock()
+        )
+    )
+
+    with pytest.raises(ProxyException) as exc_info:
+        await merge_placeholder(user_id=merged)
+
+    assert int(exc_info.value.code) == 409
+    assert reason in str(exc_info.value.message)
+    team_member_add_mock.assert_not_awaited()
+    prisma_client.db.litellm_usertable.delete.assert_not_awaited()
diff --git a/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py
index 726e09f3162..c525af84511 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_auto_router_endpoints.py
@@ -878,8 +878,10 @@ def _leg_record(**overrides: object) -> MagicMock:
     defaults = {
         "id": "leg-1",
         "group_id": "job-1",
-        "api_key_id": "key-hash",
+        "target_type": "key",
+        "target_id": "key-hash",
         "router_name": "my-router",
+        "router_names": (),
         "direction": "forward",
         "baseline_model": None,
         "judge_model": "anthropic/claude-sonnet-5",
@@ -912,8 +914,29 @@ def _key_record(
     return record
 
 
+def _team_record(team_id: str, team_alias: str | None) -> MagicMock:
+    record = MagicMock(spec=["team_id", "team_alias"])
+    record.team_id = team_id
+    record.team_alias = team_alias
+    return record
+
+
+def _user_record(user_id: str, user_email: str | None) -> MagicMock:
+    record = MagicMock(spec=["user_id", "user_email"])
+    record.user_id = user_id
+    record.user_email = user_email
+    return record
+
+
 def _shadow_prisma(
-    legs=(), agg_rows=None, by_leg_rows=None, known_keys=("key-hash", "key-hash-2"), key_teams=None
+    legs=(),
+    agg_rows=None,
+    by_leg_rows=None,
+    by_router_rows=None,
+    known_keys=("key-hash", "key-hash-2"),
+    key_teams=None,
+    known_teams=None,
+    known_users=None,
 ) -> MagicMock:
     """The job-table fake honours the filters it is handed, so a read that forgets
     stopped_at sees rows the partial index would have released, one that forgets
@@ -921,6 +944,8 @@ def _shadow_prisma(
     group read that matched on a leg id would come back empty."""
     prisma = MagicMock()
     teams: Final = key_teams or {}
+    team_aliases: Final = known_teams or {}
+    user_emails: Final = known_users or {}
 
     async def find_tokens(*, where):
         """Honours the token filter, like the job-table fake below: the endpoint derives the
@@ -931,6 +956,17 @@ def _shadow_prisma(
 
     prisma.db.litellm_verificationtoken.find_many = AsyncMock(side_effect=find_tokens)
 
+    async def find_teams(*, where):
+        requested = where["team_id"]["in"]
+        return [_team_record(t, alias) for t, alias in team_aliases.items() if t in requested]
+
+    async def find_users(*, where):
+        requested = where["user_id"]["in"]
+        return [_user_record(u, email) for u, email in user_emails.items() if u in requested]
+
+    prisma.db.litellm_teamtable.find_many = AsyncMock(side_effect=find_teams)
+    prisma.db.litellm_usertable.find_many = AsyncMock(side_effect=find_users)
+
     async def execute_raw(sql: str, *params: object):
         if "SET stopped_by" in sql:
             group = [row for row in stored if row.group_id == params[0]]
@@ -959,9 +995,19 @@ def _shadow_prisma(
     async def find_many_legs(where=None, **_: object):
         current = list(stored)
         w = dict(where or {})
-        if "api_key_id" in w:
-            wanted = w["api_key_id"]["in"] if isinstance(w["api_key_id"], dict) else [w["api_key_id"]]
-            current = [row for row in current if row.api_key_id in wanted]
+        if "OR" in w:
+            pairs = [
+                (
+                    branch["target_type"],
+                    branch["target_id"]["in"] if isinstance(branch["target_id"], dict) else [branch["target_id"]],
+                )
+                for branch in w["OR"]
+            ]
+            current = [
+                row
+                for row in current
+                if any(row.target_type == target_type and row.target_id in ids for target_type, ids in pairs)
+            ]
         if "direction" in w:
             current = [row for row in current if row.direction == w["direction"]]
         if "stopped_at" in w:
@@ -983,8 +1029,10 @@ def _shadow_prisma(
         fields = (
             "id",
             "group_id",
-            "api_key_id",
+            "target_type",
+            "target_id",
             "router_name",
+            "router_names",
             "direction",
             "baseline_model",
             "judge_model",
@@ -1009,13 +1057,19 @@ def _shadow_prisma(
         if "AS attempt_count" in sql:
             return prisma.attempt_rows
         if "GROUP BY group_id" in sql:
-            scoped = [row for row in stored if "api_key_id = $2" not in sql or row.api_key_id == params[1]]
+            scoped = [
+                row
+                for row in stored
+                if "target_type = $2" not in sql or (row.target_type == params[1] and row.target_id == params[2])
+            ]
             keep = set(newest_groups(scoped, params[0]))
             return [leg_dict(row) for row in stored if row.group_id in keep]
         if "FILTER (WHERE outcome != 'error')::int AS judged_count" in sql:
             return [{"judged_count": 10, "error_count": 2, "judge_spend": 0.031}]
         if "SELECT job_id AS grp" in sql:
             return by_leg_rows if by_leg_rows is not None else []
+        if "COALESCE(a.router_name" in sql:
+            return by_router_rows if by_router_rows is not None else []
         if 'FROM "LiteLLM_ShadowEvalFunnel"' in sql:
             return prisma.funnel_rows
         return agg_rows if agg_rows is not None else []
@@ -1058,7 +1112,7 @@ async def test_start_shadow_eval_writes_one_leg_per_key_in_one_statement(monkeyp
 
     response = await start_shadow_eval(_start_request(api_key_ids=("key-hash", "key-hash-2")), ADMIN)
 
-    sweep_sql, sweep_keys = prisma.db.execute_raw.call_args.args
+    sweep_sql, sweep_ids, sweep_type = prisma.db.execute_raw.call_args.args
     assert "stopped_at IS NULL" in sweep_sql
     assert "j.ends_at <= (NOW() AT TIME ZONE 'utc')" in sweep_sql
     assert "SET stopped_at = (NOW() AT TIME ZONE 'utc')" in sweep_sql
@@ -1066,12 +1120,21 @@ async def test_start_shadow_eval_writes_one_leg_per_key_in_one_statement(monkeyp
     assert "j.max_budget IS NOT NULL" in sweep_sql
     assert ">= j.max_budget" in sweep_sql
     assert "SUM(a.judge_cost + a.shadow_cost + a.shadow_classifier_cost)" in sweep_sql
-    assert "j.api_key_id = ANY($1::text[])" in sweep_sql
-    assert sweep_keys == ["key-hash", "key-hash-2"]
+    assert "j.target_type = $2 AND j.target_id = ANY($1::text[])" in sweep_sql
+    assert sweep_ids == ["key-hash", "key-hash-2"]
+    assert sweep_type == "key"
     prisma.db.litellm_shadowevaljob.create_many.assert_awaited_once()
     rows = prisma.db.litellm_shadowevaljob.create_many.call_args.kwargs["data"]
-    assert [row["api_key_id"] for row in rows] == ["key-hash", "key-hash-2"]
-    assert len({frozenset((k, v) for k, v in row.items() if k not in ("api_key_id", "id")) for row in rows}) == 1
+    assert [(row["target_type"], row["target_id"]) for row in rows] == [("key", "key-hash"), ("key", "key-hash-2")]
+    assert (
+        len(
+            {
+                frozenset((k, tuple(v) if isinstance(v, list) else v) for k, v in row.items() if k not in ("target_id", "id"))
+                for row in rows
+            }
+        )
+        == 1
+    )
     assert len({row["id"] for row in rows}) == len(rows)
     assert len({row["group_id"] for row in rows}) == 1
     assert all(row["max_turns"] == SHADOW_EVAL_TURN_VALVE and row["created_by"] == "admin" for row in rows)
@@ -1080,11 +1143,69 @@ async def test_start_shadow_eval_writes_one_leg_per_key_in_one_statement(monkeyp
     assert response.job_id == rows[0]["group_id"]
     assert response.status == "running"
     assert response.judged_count is None
-    assert [(key.api_key_id, key.max_budget, key.key_alias) for key in response.keys] == [
+    assert [(target.target_id, target.max_budget, target.target_alias) for target in response.targets] == [
         ("key-hash", 5.0, "prod-alpha"),
         ("key-hash-2", 5.0, "prod-alpha"),
     ]
-    assert all(key.max_turns == SHADOW_EVAL_TURN_VALVE for key in response.keys)
+    assert all(target.target_type == "key" for target in response.targets)
+    assert all(target.max_turns == SHADOW_EVAL_TURN_VALVE for target in response.targets)
+
+
+@pytest.mark.asyncio
+async def test_start_shadow_eval_multi_router_writes_the_set_on_every_leg(monkeypatch: pytest.MonkeyPatch):
+    """A multi-router job stores the full set in router_names and the first router in
+    router_name, so a rolling-deploy pod that predates router_names still runs a valid
+    single-arm eval and its unstamped attempt rows attribute to that first router."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma()
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    response = await start_shadow_eval(
+        _start_request(router_name=None, router_names=("my-router", "classifier-router")), ADMIN
+    )
+
+    rows = prisma.db.litellm_shadowevaljob.create_many.call_args.kwargs["data"]
+    assert all(row["router_name"] == "my-router" for row in rows)
+    assert all(row["router_names"] == ["my-router", "classifier-router"] for row in rows)
+    assert response.router_names == ("my-router", "classifier-router")
+    assert response.router_name == "my-router"
+
+
+@pytest.mark.asyncio
+async def test_start_shadow_eval_rejects_an_unconfigured_router_in_the_set(monkeypatch: pytest.MonkeyPatch):
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma()
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    with pytest.raises(HTTPException, match="not-a-router") as exc:
+        await start_shadow_eval(_start_request(router_name=None, router_names=("my-router", "not-a-router")), ADMIN)
+
+    assert exc.value.status_code == 400
+    prisma.db.litellm_shadowevaljob.create_many.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_judge_collision_is_found_on_every_router_of_the_set(monkeypatch: pytest.MonkeyPatch):
+    """The judge-as-candidate guard walks every candidate router: a judge that serves an
+    arm of the SECOND router still poisons the whole job's win rates."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma()
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    with pytest.raises(HTTPException, match="also an arm") as exc:
+        await start_shadow_eval(_start_request(router_name=None, router_names=("my-router", "sonnet-router")), ADMIN)
+
+    assert exc.value.status_code == 400
+    prisma.db.litellm_shadowevaljob.create_many.assert_not_called()
 
 
 @pytest.mark.asyncio
@@ -1232,7 +1353,7 @@ async def test_start_shadow_eval_rejections(
     import litellm.proxy.proxy_server as proxy_server
 
     _configure_anthropic_sdk_judge(monkeypatch)
-    prisma = _shadow_prisma(legs=[_leg_record(id=f"leg-{key}", group_id="job-7", api_key_id=key) for key in claimed])
+    prisma = _shadow_prisma(legs=[_leg_record(id=f"leg-{key}", group_id="job-7", target_id=key) for key in claimed])
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
     monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
 
@@ -1315,14 +1436,14 @@ async def test_start_shadow_eval_names_the_busy_key_and_its_job(monkeypatch: pyt
     import litellm.proxy.proxy_server as proxy_server
 
     _configure_anthropic_sdk_judge(monkeypatch)
-    prisma = _shadow_prisma(legs=[_leg_record(id="leg-b", group_id="job-7", api_key_id="key-hash-2")])
+    prisma = _shadow_prisma(legs=[_leg_record(id="leg-b", group_id="job-7", target_id="key-hash-2")])
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
     monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
 
     with pytest.raises(HTTPException) as exc:
         await start_shadow_eval(_start_request(api_key_ids=("key-hash", "key-hash-2")), ADMIN)
     assert exc.value.status_code == 409
-    assert "key-hash-2 (job job-7)" in exc.value.detail
+    assert "key key-hash-2 (job job-7)" in exc.value.detail
 
 
 @pytest.mark.asyncio
@@ -1441,6 +1562,180 @@ def test_start_shadow_eval_request_dedupes_and_bounds_the_key_set():
         _start_request(api_key_ids=tuple(f"k{i}" for i in range(101)))
 
 
+def test_start_request_bounds_the_combined_target_count_across_types():
+    """The 1..100 bound counts keys, teams, and users together, so a caller cannot dodge
+    it by spreading targets over the three fields, and a request naming no target of any
+    type samples nothing and is rejected."""
+    with pytest.raises(ValidationError, match="at least one target"):
+        _start_request(api_key_ids=(), team_ids=(), user_ids=())
+    with pytest.raises(ValidationError, match="at most 100 targets"):
+        _start_request(api_key_ids=tuple(f"k{i}" for i in range(60)), team_ids=tuple(f"t{i}" for i in range(41)))
+    mixed = _start_request(api_key_ids=tuple(f"k{i}" for i in range(60)), team_ids=tuple(f"t{i}" for i in range(40)))
+    assert len(mixed.api_key_ids) + len(mixed.team_ids) == 100
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "overrides,prisma_kwargs,expected_target",
+    [
+        (
+            {"api_key_ids": (), "team_ids": ("team-eng",)},
+            {"known_teams": {"team-eng": "Engineering"}},
+            ("team", "team-eng", "Engineering"),
+        ),
+        (
+            {"api_key_ids": (), "user_ids": ("dev-alice",)},
+            {"known_users": {"dev-alice": "alice@example.com"}},
+            ("user", "dev-alice", "alice@example.com"),
+        ),
+    ],
+    ids=["team-target-labeled-by-team-alias", "user-target-labeled-by-user-email"],
+)
+async def test_start_shadow_eval_creates_typed_legs_for_team_and_user_targets(
+    monkeypatch: pytest.MonkeyPatch, overrides, prisma_kwargs, expected_target
+):
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma(**prisma_kwargs)
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    response = await start_shadow_eval(_start_request(**overrides), ADMIN)
+
+    target_type, target_id, target_alias = expected_target
+    rows = prisma.db.litellm_shadowevaljob.create_many.call_args.kwargs["data"]
+    assert [(row["target_type"], row["target_id"]) for row in rows] == [(target_type, target_id)]
+    assert response.status == "running"
+    target = response.targets[0]
+    assert (target.target_type, target.target_id, target.target_alias, target.key_name) == (
+        target_type,
+        target_id,
+        target_alias,
+        None,
+    )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    "overrides,prisma_kwargs,expected_detail",
+    [
+        (
+            {"api_key_ids": (), "team_ids": ("team-eng", "team-ghost")},
+            {"known_teams": {"team-eng": "Engineering"}},
+            "team_ids not on this proxy: team-ghost",
+        ),
+        (
+            {"api_key_ids": (), "user_ids": ("dev-alice", "dev-ghost")},
+            {"known_users": {"dev-alice": "alice@example.com"}},
+            "user_ids not on this proxy: dev-ghost",
+        ),
+    ],
+    ids=["unknown-team", "unknown-user"],
+)
+async def test_start_shadow_eval_rejects_teams_and_users_this_proxy_does_not_know(
+    monkeypatch: pytest.MonkeyPatch, overrides, prisma_kwargs, expected_detail
+):
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma(**prisma_kwargs)
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    with pytest.raises(HTTPException) as exc:
+        await start_shadow_eval(_start_request(**overrides), ADMIN)
+    assert exc.value.status_code == 400
+    assert expected_detail in exc.value.detail
+    prisma.db.litellm_shadowevaljob.create_many.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_start_shadow_eval_mixed_targets_create_both_legs_and_sweep_once_per_type(
+    monkeypatch: pytest.MonkeyPatch,
+):
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma(known_teams={"team-eng": "Engineering"})
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    response = await start_shadow_eval(_start_request(team_ids=("team-eng",)), ADMIN)
+
+    rows = prisma.db.litellm_shadowevaljob.create_many.call_args.kwargs["data"]
+    assert [(row["target_type"], row["target_id"]) for row in rows] == [("key", "key-hash"), ("team", "team-eng")]
+    assert len({row["group_id"] for row in rows}) == 1
+    sweeps = [
+        call.args
+        for call in prisma.db.execute_raw.await_args_list
+        if "SET stopped_at = (NOW() AT TIME ZONE 'utc')" in call.args[0]
+    ]
+    assert [(ids, target_type) for _, ids, target_type in sweeps] == [(["key-hash"], "key"), (["team-eng"], "team")]
+    assert [(t.target_type, t.target_id, t.target_alias) for t in response.targets] == [
+        ("key", "key-hash", "prod-alpha"),
+        ("team", "team-eng", "Engineering"),
+    ]
+
+
+@pytest.mark.asyncio
+async def test_start_shadow_eval_names_the_busy_team_target(monkeypatch: pytest.MonkeyPatch):
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma(
+        legs=[_leg_record(id="leg-t", group_id="job-7", target_type="team", target_id="team-eng")],
+        known_teams={"team-eng": "Engineering"},
+    )
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    with pytest.raises(HTTPException) as exc:
+        await start_shadow_eval(_start_request(api_key_ids=(), team_ids=("team-eng",)), ADMIN)
+    assert exc.value.status_code == 409
+    assert "team team-eng (job job-7)" in exc.value.detail
+    prisma.db.litellm_shadowevaljob.create_many.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_start_shadow_eval_claim_matches_exact_target_pairs_not_bare_ids(monkeypatch: pytest.MonkeyPatch):
+    """A key whose hash happens to spell a team's id must not hold the team's slot: the
+    claim matches (target_type, target_id) pairs, never ids across kinds."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    _configure_anthropic_sdk_judge(monkeypatch)
+    prisma = _shadow_prisma(
+        legs=[_leg_record(id="leg-k", group_id="job-7", target_type="key", target_id="team-eng")],
+        known_teams={"team-eng": "Engineering"},
+    )
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+    monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
+
+    response = await start_shadow_eval(_start_request(api_key_ids=(), team_ids=("team-eng",)), ADMIN)
+
+    assert response.status == "running"
+    prisma.db.litellm_shadowevaljob.create_many.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_list_shadow_eval_jobs_rejects_a_lone_filter_half(monkeypatch: pytest.MonkeyPatch):
+    """target_type and target_id only mean anything together: a bare id could name a key
+    or a team, and a bare type filters nothing."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    prisma = _shadow_prisma(legs=[_leg_record()])
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+
+    with pytest.raises(HTTPException) as id_only:
+        await list_shadow_eval_jobs(VIEWER, target_type=None, target_id="key-hash", limit=50)
+    assert id_only.value.status_code == 400
+
+    with pytest.raises(HTTPException) as type_only:
+        await list_shadow_eval_jobs(VIEWER, target_type="key", target_id=None, limit=50)
+    assert type_only.value.status_code == 400
+    prisma.db.query_raw.assert_not_called()
+
+
 @pytest.mark.asyncio
 async def test_start_shadow_eval_concurrent_unique_violation_is_a_409(monkeypatch: pytest.MonkeyPatch):
     import litellm.proxy.proxy_server as proxy_server
@@ -1530,7 +1825,7 @@ async def test_get_shadow_eval_job_pools_counts_and_slices_results_per_key(monke
         },
     ]
     prisma = _shadow_prisma(
-        legs=[_leg_record(), _leg_record(id="leg-2", api_key_id="key-hash-2", max_turns=50)],
+        legs=[_leg_record(), _leg_record(id="leg-2", target_id="key-hash-2", max_turns=50)],
         agg_rows=tier_rows,
         by_leg_rows=leg_rows,
     )
@@ -1549,8 +1844,10 @@ async def test_get_shadow_eval_job_pools_counts_and_slices_results_per_key(monke
     assert response.results.by_tier[0].shadow_win_rate_pct == 50.0
     assert response.results.overall_shadow_win_rate_pct == 40.0
     assert response.results.overall_tie_rate_pct == 20.0
-    assert [(s.group, s.turn_count) for s in response.results.by_key] == [("key-hash", 6), ("key-hash-2", 4)]
-    assert response.results.by_key[0].shadow_win_rate_pct == 66.7
+    verdicts_by_target = {(t.target_type, t.target_id): t.verdicts for t in response.targets}
+    assert verdicts_by_target[("key", "key-hash")].turn_count == 6
+    assert verdicts_by_target[("key", "key-hash")].shadow_win_rate_pct == 66.7
+    assert verdicts_by_target[("key", "key-hash-2")].turn_count == 4
     agg_sql = next(call.args[0] for call in prisma.db.query_raw.await_args_list if "real_spend" in call.args[0])
     assert agg_sql.count("FILTER (WHERE real_cost IS NOT NULL AND NOT real_cache_hit)") == 2
     assert response.results.by_tier[0].real_spend == 0.08
@@ -1561,13 +1858,73 @@ async def test_get_shadow_eval_job_pools_counts_and_slices_results_per_key(monke
     assert response.results.not_sampled_count is None
     assert response.results.unjudgeable_count is None
     assert response.results.shed_count is None
-    assert [(key.api_key_id, key.max_turns) for key in response.keys] == [("key-hash", 200), ("key-hash-2", 50)]
+    assert [(target.target_id, target.max_turns) for target in response.targets] == [
+        ("key-hash", 200),
+        ("key-hash-2", 50),
+    ]
     totals_args = [call.args for call in prisma.db.query_raw.await_args_list if "judged_count" in call.args[0]]
     assert totals_args == [(totals_args[0][0], ["leg-1", "leg-2"])]
     error_where = prisma.db.litellm_shadowevalattempt.find_first.call_args.kwargs["where"]
     assert error_where == {"job_id": {"in": ["leg-1", "leg-2"]}, "outcome": "error"}
 
 
+@pytest.mark.asyncio
+async def test_get_shadow_eval_job_slices_results_per_router(monkeypatch: pytest.MonkeyPatch):
+    """A multi-router job's detail carries one slice per arm, aggregated by the arm
+    stamped on each attempt row, with unstamped legacy rows attributed to the job's own
+    router by the read (the COALESCE against the leg's router_name)."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    def agg(grp: str, wins: int) -> dict[str, object]:
+        return {
+            "grp": grp,
+            "turn_count": 4,
+            "real_wins": 4 - wins,
+            "shadow_wins": wins,
+            "ties": 0,
+            "avg_confidence": 0.8,
+            "real_spend": 0.08,
+            "shadow_spend": 0.02,
+            "cache_hit_turns": 0,
+        }
+
+    prisma = _shadow_prisma(
+        legs=[_leg_record(router_names=("my-router", "alt-router"))],
+        agg_rows=[agg("SIMPLE", 3)],
+        by_router_rows=[agg("my-router", 1), agg("alt-router", 3)],
+    )
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+
+    response = await get_shadow_eval_job("job-1", VIEWER)
+
+    assert response.router_names == ("my-router", "alt-router")
+    assert response.router_name == "my-router"
+    assert [(s.group, s.shadow_win_rate_pct) for s in response.results.by_router] == [
+        ("my-router", 25.0),
+        ("alt-router", 75.0),
+    ]
+    router_sql = next(
+        call.args[0] for call in prisma.db.query_raw.await_args_list if "COALESCE(a.router_name" in call.args[0]
+    )
+    assert "COALESCE(a.router_name, j.router_name)" in router_sql
+    assert 'JOIN "LiteLLM_ShadowEvalJob" j ON j.id = a.job_id' in router_sql
+    assert "a.job_id = ANY($1::text[])" in router_sql
+
+
+@pytest.mark.asyncio
+async def test_job_responses_resolve_router_names_with_legacy_fallback(monkeypatch: pytest.MonkeyPatch):
+    """Rows from before router_names existed carry their whole set in router_name."""
+    import litellm.proxy.proxy_server as proxy_server
+
+    prisma = _shadow_prisma(legs=[_leg_record(router_names=())])
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+
+    response = await get_shadow_eval_job("job-1", VIEWER)
+
+    assert response.router_names == ("my-router",)
+    assert response.router_name == "my-router"
+
+
 @pytest.mark.asyncio
 async def test_get_shadow_eval_job_404s_and_gates_on_role(monkeypatch: pytest.MonkeyPatch):
     import litellm.proxy.proxy_server as proxy_server
@@ -1595,7 +1952,7 @@ async def test_list_shadow_eval_jobs_collapses_legs_into_jobs_newest_first(monke
             _leg_record(created_at=datetime(2026, 8, 13, tzinfo=timezone.utc)),
             _leg_record(
                 id="leg-2",
-                api_key_id="key-hash-2",
+                target_id="key-hash-2",
                 stopped_at=stamp,
                 created_at=datetime(2026, 8, 13, tzinfo=timezone.utc),
             ),
@@ -1615,14 +1972,14 @@ async def test_list_shadow_eval_jobs_collapses_legs_into_jobs_newest_first(monke
     )
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
 
     assert [(job.job_id, job.status) for job in jobs] == [
         ("job-1", "running"),
         ("job-2", "stopped"),
         ("job-3", "completed"),
     ]
-    assert [key.api_key_id for key in jobs[0].keys] == ["key-hash", "key-hash-2"]
+    assert [target.target_id for target in jobs[0].targets] == ["key-hash", "key-hash-2"]
     assert all(job.judged_count is None and job.results is None for job in jobs)
     legs_sql, legs_limit = prisma.db.query_raw.await_args_list[0].args
     assert "GROUP BY group_id ORDER BY MAX(created_at) DESC LIMIT $1::int" in legs_sql
@@ -1648,17 +2005,20 @@ async def test_list_shadow_eval_jobs_filters_to_jobs_containing_the_key(monkeypa
     prisma = _shadow_prisma(
         legs=[
             _leg_record(),
-            _leg_record(id="leg-2", api_key_id="key-hash-2"),
-            _leg_record(id="leg-3", group_id="job-2", api_key_id="key-hash-2"),
+            _leg_record(id="leg-2", target_id="key-hash-2"),
+            _leg_record(id="leg-3", group_id="job-2", target_id="key-hash-2"),
             _leg_record(id="leg-4", group_id="job-3"),
         ]
     )
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id="key-hash-2", limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type="key", target_id="key-hash-2", limit=50)
 
     assert [job.job_id for job in jobs] == ["job-1", "job-2"]
-    assert [key.api_key_id for key in jobs[0].keys] == ["key-hash", "key-hash-2"]
+    assert [target.target_id for target in jobs[0].targets] == ["key-hash", "key-hash-2"]
+    legs_sql, *legs_params = prisma.db.query_raw.await_args_list[0].args
+    assert "WHERE target_type = $2 AND target_id = $3" in legs_sql
+    assert legs_params == [50, "key", "key-hash-2"]
 
 
 @pytest.mark.parametrize(
@@ -1682,7 +2042,7 @@ async def test_job_status_runs_until_every_key_stops_and_completed_outranks_stop
         legs=[
             _leg_record(
                 id=f"leg-{index}",
-                api_key_id=f"key-{index}",
+                target_id=f"key-{index}",
                 stopped_at=stamp if stopped else None,
                 ends_at=datetime.now(timezone.utc) + timedelta(days=days_left),
             )
@@ -1691,7 +2051,7 @@ async def test_job_status_runs_until_every_key_stops_and_completed_outranks_stop
     )
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
 
     assert [job.status for job in jobs] == [expected]
 
@@ -1707,9 +2067,9 @@ async def test_list_reads_completed_once_every_key_spends_its_budget(monkeypatch
     prisma = _shadow_prisma(
         legs=[
             _leg_record(max_turns=5),
-            _leg_record(id="leg-2", api_key_id="key-hash-2", max_turns=5),
-            _leg_record(id="leg-3", group_id="job-2", api_key_id="key-hash", max_turns=5),
-            _leg_record(id="leg-4", group_id="job-2", api_key_id="key-hash-2", max_turns=5),
+            _leg_record(id="leg-2", target_id="key-hash-2", max_turns=5),
+            _leg_record(id="leg-3", group_id="job-2", target_id="key-hash", max_turns=5),
+            _leg_record(id="leg-4", group_id="job-2", target_id="key-hash-2", max_turns=5),
         ]
     )
     prisma.attempt_rows = [
@@ -1720,13 +2080,13 @@ async def test_list_reads_completed_once_every_key_spends_its_budget(monkeypatch
     ]
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
 
     by_id = {job.job_id: job for job in jobs}
     assert by_id["job-1"].status == "completed"
-    assert all(key.stopped_at is None for key in by_id["job-1"].keys)
+    assert all(target.stopped_at is None for target in by_id["job-1"].targets)
     assert by_id["job-2"].status == "running"
-    assert {key.api_key_id: key.attempt_count for key in by_id["job-2"].keys} == {"key-hash": 5, "key-hash-2": 3}
+    assert {t.target_id: t.attempt_count for t in by_id["job-2"].targets} == {"key-hash": 5, "key-hash-2": 3}
 
 
 @pytest.mark.asyncio
@@ -1740,7 +2100,7 @@ async def test_recorded_operator_stop_outranks_budget_arithmetic(monkeypatch: py
     prisma.attempt_rows = [{"job_id": "leg-1", "attempt_count": 6, "spend": 0.0}]
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
     assert jobs[0].status == "stopped"
     assert jobs[0].stopped_by == "admin"
 
@@ -1760,7 +2120,7 @@ async def test_backfilled_legacy_stop_never_reads_as_completion(monkeypatch: pyt
     prisma.attempt_rows = [{"job_id": "leg-1", "attempt_count": 6, "spend": 0.0}]
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
     assert jobs[0].status == "stopped"
 
 
@@ -1808,6 +2168,56 @@ def test_max_budget_migration_is_additive_and_leaves_legacy_rows_null():
 
 
 @pytest.mark.asyncio
+@pytest.mark.asyncio
+async def test_verdicts_keep_same_id_targets_of_different_kinds_distinct(monkeypatch):
+    """A team and a user can legitimately share an id; their slices must not merge."""
+    from litellm.proxy import proxy_server
+
+    leg_rows = [
+        {
+            "grp": "leg-1",
+            "turn_count": 6,
+            "real_wins": 2,
+            "shadow_wins": 4,
+            "ties": 0,
+            "avg_confidence": 0.8,
+            "real_spend": 0.02,
+            "shadow_spend": 0.01,
+            "cache_hit_turns": 0,
+        },
+        {
+            "grp": "leg-2",
+            "turn_count": 4,
+            "real_wins": 3,
+            "shadow_wins": 0,
+            "ties": 1,
+            "avg_confidence": 0.6,
+            "real_spend": 0.05,
+            "shadow_spend": 0.04,
+            "cache_hit_turns": 1,
+        },
+    ]
+    prisma = _shadow_prisma(
+        legs=[
+            _leg_record(target_type="team", target_id="dev-alice"),
+            _leg_record(id="leg-2", target_type="user", target_id="dev-alice"),
+        ],
+        agg_rows=leg_rows[:1],
+        by_leg_rows=leg_rows,
+        known_teams={"dev-alice": "alias"},
+        known_users={"dev-alice": "alice@example.com"},
+    )
+    monkeypatch.setattr(proxy_server, "prisma_client", prisma)
+
+    response = await get_shadow_eval_job("job-1", VIEWER)
+
+    verdicts_by_target = {(t.target_type, t.target_id): t.verdicts for t in response.targets}
+    assert verdicts_by_target[("team", "dev-alice")].turn_count == 6
+    assert verdicts_by_target[("team", "dev-alice")].shadow_win_rate_pct == 66.7
+    assert verdicts_by_target[("user", "dev-alice")].turn_count == 4
+    assert verdicts_by_target[("user", "dev-alice")].shadow_win_rate_pct == 0.0
+
+
 async def test_stop_rejects_a_job_that_already_spent_its_budget(monkeypatch: pytest.MonkeyPatch):
     import litellm.proxy.proxy_server as proxy_server
 
@@ -1832,9 +2242,9 @@ async def test_list_reads_completed_once_every_key_spends_its_dollar_budget(monk
     prisma = _shadow_prisma(
         legs=[
             _leg_record(max_turns=SHADOW_EVAL_TURN_VALVE, max_budget=1.0),
-            _leg_record(id="leg-2", api_key_id="key-hash-2", max_turns=SHADOW_EVAL_TURN_VALVE, max_budget=1.0),
+            _leg_record(id="leg-2", target_id="key-hash-2", max_turns=SHADOW_EVAL_TURN_VALVE, max_budget=1.0),
             _leg_record(
-                id="leg-3", group_id="job-2", api_key_id="key-hash", max_turns=SHADOW_EVAL_TURN_VALVE, max_budget=1.0
+                id="leg-3", group_id="job-2", target_id="key-hash", max_turns=SHADOW_EVAL_TURN_VALVE, max_budget=1.0
             ),
         ]
     )
@@ -1845,13 +2255,13 @@ async def test_list_reads_completed_once_every_key_spends_its_dollar_budget(monk
     ]
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
 
     by_id = {job.job_id: job for job in jobs}
     assert by_id["job-1"].status == "completed"
     assert by_id["job-2"].status == "running"
-    assert {key.api_key_id: key.spend for key in by_id["job-1"].keys} == {"key-hash": 1.0, "key-hash-2": 1.25}
-    assert all(key.max_budget == 1.0 for key in by_id["job-1"].keys)
+    assert {t.target_id: t.spend for t in by_id["job-1"].targets} == {"key-hash": 1.0, "key-hash-2": 1.25}
+    assert all(target.max_budget == 1.0 for target in by_id["job-1"].targets)
 
 
 @pytest.mark.asyncio
@@ -1880,11 +2290,11 @@ async def test_legacy_jobs_without_a_dollar_budget_stay_turn_gated(monkeypatch:
     prisma.attempt_rows = [{"job_id": "leg-1", "attempt_count": 40, "spend": 250.0}]
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
 
     assert jobs[0].status == "running"
-    assert jobs[0].keys[0].max_budget is None
-    assert jobs[0].keys[0].spend == 250.0
+    assert jobs[0].targets[0].max_budget is None
+    assert jobs[0].targets[0].spend == 250.0
 
 
 @pytest.mark.asyncio
@@ -1892,14 +2302,14 @@ async def test_shadow_eval_responses_name_every_shadowed_key(monkeypatch: pytest
     import litellm.proxy.proxy_server as proxy_server
 
     prisma = _shadow_prisma(
-        legs=[_leg_record(), _leg_record(id="leg-2", api_key_id="deleted-key-hash")],
+        legs=[_leg_record(), _leg_record(id="leg-2", target_id="deleted-key-hash")],
         known_keys=("key-hash", "key-hash-2"),
     )
     monkeypatch.setattr(proxy_server, "llm_router", _shadow_router())
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
-    jobs = await list_shadow_eval_jobs(VIEWER, api_key_id=None, limit=50)
-    assert [(key.key_alias, key.key_name) for key in jobs[0].keys] == [
+    jobs = await list_shadow_eval_jobs(VIEWER, target_type=None, target_id=None, limit=50)
+    assert [(target.target_alias, target.key_name) for target in jobs[0].targets] == [
         (None, None),
         ("prod-alpha", "sk-...lpha"),
     ]
@@ -1907,7 +2317,7 @@ async def test_shadow_eval_responses_name_every_shadowed_key(monkeypatch: pytest
     assert batched_where == {"token": {"in": ["deleted-key-hash", "key-hash"]}}
 
     detail = await get_shadow_eval_job("job-1", VIEWER)
-    assert [key.key_alias for key in detail.keys] == [None, "prod-alpha"]
+    assert [target.target_alias for target in detail.targets] == [None, "prod-alpha"]
 
 
 @pytest.mark.asyncio
@@ -1919,7 +2329,7 @@ async def test_stop_shadow_eval_stops_every_unstopped_leg_and_rejects_non_runnin
     import litellm.proxy.proxy_server as proxy_server
 
     earned = datetime.now(timezone.utc) - timedelta(hours=1)
-    prisma = _shadow_prisma(legs=[_leg_record(), _leg_record(id="leg-2", api_key_id="key-hash-2", stopped_at=earned)])
+    prisma = _shadow_prisma(legs=[_leg_record(), _leg_record(id="leg-2", target_id="key-hash-2", stopped_at=earned)])
     monkeypatch.setattr(proxy_server, "prisma_client", prisma)
 
     stopped = await stop_shadow_eval_job("job-1", ADMIN)
@@ -1938,9 +2348,9 @@ async def test_stop_shadow_eval_stops_every_unstopped_leg_and_rejects_non_runnin
     assert datetime.fromisoformat(stop_stamp).tzinfo is None
     assert prisma.db.execute_raw.await_count == 1
     prisma.db.litellm_shadowevaljob.update_many.assert_not_called()
-    by_key = {key.api_key_id: key.stopped_at for key in stopped.keys}
-    assert by_key["key-hash-2"] == earned
-    assert by_key["key-hash"] is not None and by_key["key-hash"] != earned
+    by_target = {target.target_id: target.stopped_at for target in stopped.targets}
+    assert by_target["key-hash-2"] == earned
+    assert by_target["key-hash"] is not None and by_target["key-hash"] != earned
 
     done_leg = _leg_record(ends_at=datetime.now(timezone.utc) - timedelta(days=1))
     prisma_done = _shadow_prisma(legs=[done_leg])
@@ -2331,7 +2741,7 @@ async def test_get_shadow_eval_job_sums_funnel_rows_across_legs(monkeypatch: pyt
         },
     ]
     prisma = _shadow_prisma(
-        legs=[_leg_record(), _leg_record(id="leg-2", api_key_id="key-hash-2")],
+        legs=[_leg_record(), _leg_record(id="leg-2", target_id="key-hash-2")],
         agg_rows=tier_rows,
     )
     prisma.funnel_rows = [{"legs_with_rows": 2, "not_sampled": 30, "unjudgeable": 5, "shed": 2, "withheld": 3}]
@@ -2366,7 +2776,7 @@ async def test_partially_seeded_funnel_reads_as_unknown_coverage(monkeypatch: py
         },
     ]
     prisma = _shadow_prisma(
-        legs=[_leg_record(), _leg_record(id="leg-2", api_key_id="key-hash-2")],
+        legs=[_leg_record(), _leg_record(id="leg-2", target_id="key-hash-2")],
         agg_rows=tier_rows,
     )
     prisma.funnel_rows = [{"legs_with_rows": 1, "not_sampled": 30, "unjudgeable": 5, "shed": 2, "withheld": 0}]
diff --git a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py
index 5c163c44cb3..1225cb80224 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_customer_endpoints.py
@@ -83,6 +83,50 @@ def test_update_customer_success(mock_prisma_client, mock_user_api_key_auth):
     assert response.json()["alias"] == "Updated Test User"
 
 
+def test_update_customer_unblock(mock_prisma_client, mock_user_api_key_auth):
+    mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", blocked=True)
+    updated_mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", blocked=False)
+
+    mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=mock_end_user)
+    mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=updated_mock_end_user)
+
+    response = client.post(
+        "/customer/update",
+        json={"user_id": "test-user-1", "blocked": False},
+        headers={"Authorization": "Bearer test-key"},
+    )
+
+    assert response.status_code == 200
+    assert response.json()["blocked"] is False
+    update_mock = mock_prisma_client.db.litellm_endusertable.update
+    update_mock.assert_called_once()
+    assert update_mock.call_args.kwargs["data"]["blocked"] is False
+
+
+def test_update_customer_keeps_blocked_when_omitted(mock_prisma_client, mock_user_api_key_auth):
+    """
+    Regression test: updating a blocked customer without supplying `blocked`
+    must NOT reset it to unblocked. `blocked=False` is the model default and
+    should only be applied when explicitly provided by the caller.
+    """
+    mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", blocked=True)
+    updated_mock_end_user = LiteLLM_EndUserTable(user_id="test-user-1", blocked=True)
+
+    mock_prisma_client.db.litellm_endusertable.find_first = AsyncMock(return_value=mock_end_user)
+    mock_prisma_client.db.litellm_endusertable.update = AsyncMock(return_value=updated_mock_end_user)
+
+    response = client.post(
+        "/customer/update",
+        json={"user_id": "test-user-1", "alias": "Updated Test User"},
+        headers={"Authorization": "Bearer test-key"},
+    )
+
+    assert response.status_code == 200
+    update_mock = mock_prisma_client.db.litellm_endusertable.update
+    update_mock.assert_called_once()
+    assert "blocked" not in update_mock.call_args.kwargs["data"]
+
+
 def test_update_customer_not_found(mock_prisma_client, mock_user_api_key_auth):
     """
     Test that update_end_user raises a 404 ProxyException when user_id does not exist.
diff --git a/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py
index 8bce967b316..f231eb66a50 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_internal_user_endpoints.py
@@ -4220,3 +4220,88 @@ async def test_user_new_persists_model_max_budget(
     )
 
     assert captured["user_data"].get("model_max_budget") == expected_written
+
+
+@pytest.fixture
+def _admin_prisma(mocker):
+    """A mocked prisma_client wired in as proxy_server's module globals, for
+    the password-policy tests below (mirrors the pattern every other test in
+    this file repeats per-test; consolidated here since these three share it
+    verbatim)."""
+    mock_prisma_client = mocker.MagicMock()
+    mocker.patch(  # test-quality-ok: same module-global mocking every test in this file already uses
+        "litellm.proxy.proxy_server.prisma_client", mock_prisma_client
+    )
+    mocker.patch(  # test-quality-ok: same module-global mocking every test in this file already uses
+        "litellm.proxy.proxy_server.litellm_proxy_admin_name", "admin"
+    )
+    return mock_prisma_client
+
+
+@pytest.mark.asyncio
+async def test_user_update_rejects_weak_password(_admin_prisma):
+    """/user/update must reject a password that fails the configured
+    policy before it ever reaches the DB write."""
+    from litellm.proxy._types import ProxyException
+    from litellm.proxy.management_endpoints.internal_user_endpoints import (
+        _update_single_user_helper,
+    )
+
+    user_request = UpdateUserRequest(user_id="target-user", password="short1!")
+    admin_caller = UserAPIKeyAuth(user_id="admin-1", user_role=LitellmUserRoles.PROXY_ADMIN)
+
+    with pytest.raises(ProxyException) as exc_info:
+        await _update_single_user_helper(user_request=user_request, user_api_key_dict=admin_caller)
+
+    assert exc_info.value.code == "400"
+    _admin_prisma.db.litellm_usertable.find_first.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_user_update_rejects_weak_password_against_configured_policy(_admin_prisma, mocker):
+    """A password that meets the default policy but not a stricter
+    admin-configured one must still be rejected."""
+    from litellm.proxy._types import ProxyException
+    from litellm.proxy.management_endpoints.internal_user_endpoints import (
+        _update_single_user_helper,
+    )
+
+    mocker.patch(  # test-quality-ok: same module-global mocking every test in this file already uses
+        "litellm.proxy.proxy_server.general_settings",
+        {"password_policy_min_length": 24},
+    )
+
+    user_request = UpdateUserRequest(user_id="target-user", password="Str0ng!Passw0rd")
+    admin_caller = UserAPIKeyAuth(user_id="admin-1", user_role=LitellmUserRoles.PROXY_ADMIN)
+
+    with pytest.raises(ProxyException) as exc_info:
+        await _update_single_user_helper(user_request=user_request, user_api_key_dict=admin_caller)
+
+    assert "24 characters" in exc_info.value.message
+
+
+@pytest.mark.asyncio
+async def test_user_update_hashes_and_persists_strong_password(_admin_prisma, mocker):
+    """A password meeting the policy is hashed (never stored in plaintext)
+    and reaches the DB write."""
+    from litellm.proxy.management_endpoints.internal_user_endpoints import (
+        _update_single_user_helper,
+    )
+
+    mock_prisma_client = _admin_prisma
+    existing_user = mocker.MagicMock()
+    existing_user.model_dump.return_value = {"user_id": "target-user"}
+    existing_user.user_id = "target-user"
+    mock_prisma_client.db.litellm_usertable.find_first = mocker.AsyncMock(return_value=existing_user)
+    mock_prisma_client.update_data = mocker.AsyncMock(return_value={"user_id": "target-user"})
+    mock_prisma_client.jsonify_object = mocker.MagicMock(side_effect=lambda x: x)
+
+    strong_password = "Str0ng!Passw0rd"
+    user_request = UpdateUserRequest(user_id="target-user", password=strong_password)
+    admin_caller = UserAPIKeyAuth(user_id="admin-1", user_role=LitellmUserRoles.PROXY_ADMIN)
+
+    await _update_single_user_helper(user_request=user_request, user_api_key_dict=admin_caller)
+
+    written_data = mock_prisma_client.update_data.call_args.kwargs["data"]
+    assert written_data.get("password") is not None
+    assert written_data["password"] != strong_password
diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
index 42e56ceabd3..7e2e680743f 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
@@ -8312,15 +8312,17 @@ async def test_key_does_not_override_explicit_budget_duration():
 @patch(
     "litellm.proxy.management_endpoints.key_management_endpoints.rotate_mcp_server_credentials_master_key"
 )
-async def test_rotate_master_key_model_data_valid_for_prisma(
+async def test_rotate_master_key_reencrypts_model_params_in_place(
     mock_rotate_mcp,
 ):
     """
-    Test that _rotate_master_key produces valid data for Prisma create_many().
-
-    Regression test for: master key rotation fails with Prisma validation error
-    because created_at/updated_at are None (non-nullable DateTime) and
-    litellm_params/model_info are JSON strings (create_many expects dicts).
+    Regression test for: master key rotation wipes every non-credential column
+    on LiteLLM_ProxyModelTable. Rotation used to rebuild the table via
+    delete_many + create_many from Deployment objects, which carry no
+    blocked/created_at/created_by/updated_at/updated_by, so every rotation
+    reset blocked to False (silently unblocking blocked models) and rewrote the
+    audit columns. Rotation must instead update only litellm_params (the sole
+    encrypted column) on each existing row, keyed by model_id.
     """
     from unittest.mock import AsyncMock, MagicMock
 
@@ -8352,6 +8354,7 @@ async def test_rotate_master_key_model_data_valid_for_prisma(
     mock_tx.litellm_proxymodeltable = MagicMock()
     mock_tx.litellm_proxymodeltable.delete_many = AsyncMock()
     mock_tx.litellm_proxymodeltable.create_many = AsyncMock()
+    mock_tx.litellm_proxymodeltable.update_many = AsyncMock()
     mock_prisma_client.db.tx = MagicMock(
         return_value=AsyncMock(
             __aenter__=AsyncMock(return_value=mock_tx),
@@ -8400,36 +8403,33 @@ async def test_rotate_master_key_model_data_valid_for_prisma(
             new_master_key="sk-new-master-key",
         )
 
-    # Verify create_many was called
-    mock_tx.litellm_proxymodeltable.create_many.assert_called_once()
+    # Rotation must never rewrite whole rows: no delete + recreate
+    mock_tx.litellm_proxymodeltable.delete_many.assert_not_called()
+    mock_tx.litellm_proxymodeltable.create_many.assert_not_called()
 
-    # Get the data passed to create_many
-    call_args = mock_tx.litellm_proxymodeltable.create_many.call_args
-    created_models = call_args.kwargs.get("data") or call_args[1].get("data")
+    mock_tx.litellm_proxymodeltable.update_many.assert_called_once()
+    call_args = mock_tx.litellm_proxymodeltable.update_many.call_args
 
-    assert len(created_models) == 1
-    model_data = created_models[0]
+    assert call_args.kwargs["where"] == {
+        "model_id": "model-1"
+    }, "the re-encrypted params must land on the same row, keyed by model_id"
 
-    # Verify timestamps are NOT present (Prisma @default(now()) should apply)
-    assert (
-        "created_at" not in model_data
-    ), "created_at should be excluded so Prisma @default(now()) applies"
-    assert (
-        "updated_at" not in model_data
-    ), "updated_at should be excluded so Prisma @default(now()) applies"
+    update_data = call_args.kwargs["data"]
+    assert set(update_data.keys()) == {"litellm_params"}, (
+        "rotation must touch only the encrypted litellm_params column; writing any "
+        f"other column wipes it (blocked, audit columns), got {sorted(update_data.keys())}"
+    )
 
-    # Verify litellm_params and model_info are prisma.Json wrappers, NOT JSON strings
     import prisma
 
     assert isinstance(
-        model_data["litellm_params"], prisma.Json
-    ), f"litellm_params should be prisma.Json for create_many(), got {type(model_data['litellm_params'])}"
-    assert isinstance(
-        model_data["model_info"], prisma.Json
-    ), f"model_info should be prisma.Json for create_many(), got {type(model_data['model_info'])}"
-
-    # Verify delete_many was called inside the transaction (before create_many)
-    mock_tx.litellm_proxymodeltable.delete_many.assert_called_once()
+        update_data["litellm_params"], prisma.Json
+    ), f"litellm_params should be prisma.Json for update_many(), got {type(update_data['litellm_params'])}"
+    reencrypted_params = update_data["litellm_params"].data
+    assert set(reencrypted_params.keys()) >= {"model", "api_key"}
+    assert (
+        reencrypted_params["api_key"] != "sk-decrypted-key"
+    ), "api_key must be stored re-encrypted under the new master key, not in plaintext"
 
 
 async def test_default_key_generate_params_duration(monkeypatch):
@@ -11033,6 +11033,123 @@ class TestLIT1884KeyUpdateValidation:
         )
 
 
+class TestLIT4891SafePresetKeyTypeTransition:
+    def _make_existing_key(self, allowed_routes):
+        row = MagicMock()
+        row.user_id = "internal-user-123"
+        row.created_by = "internal-user-123"
+        row.token = "hashed_token"
+        row.team_id = None
+        row.max_budget = None
+        row.spend = 0.0
+        row.organization_id = None
+        row.project_id = None
+        row.allowed_routes = allowed_routes
+        return row
+
+    def _make_auth(self):
+        return UserAPIKeyAuth(
+            user_id="internal-user-123",
+            user_role=LitellmUserRoles.INTERNAL_USER,
+        )
+
+    async def _run_update(self, data, existing_key_row):
+        try:
+            await _validate_update_key_data(
+                data=data,
+                existing_key_row=existing_key_row,
+                user_api_key_dict=self._make_auth(),
+                llm_router=None,
+                premium_user=False,
+                prisma_client=AsyncMock(),
+                user_api_key_cache=MagicMock(),
+            )
+        except HTTPException as exc:
+            return exc
+        return None
+
+    def _assert_routes_403(self, exc):
+        assert exc is not None
+        assert exc.status_code == 403
+        assert "Only proxy admins can set" in str(exc.detail)
+
+    @pytest.mark.asyncio
+    async def test_non_admin_owner_can_clear_safe_preset_to_full_access(self):
+        assert (
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=[]),
+                existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]),
+            )
+            is None
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_owner_can_switch_full_access_to_safe_preset(self):
+        assert (
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=["llm_api_routes"]),
+                existing_key_row=self._make_existing_key(allowed_routes=[]),
+            )
+            is None
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_owner_can_narrow_to_read_only_preset(self):
+        assert (
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=["info_routes"]),
+                existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]),
+            )
+            is None
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_can_resend_read_only_preset_unchanged(self):
+        assert (
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=["info_routes"]),
+                existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]),
+            )
+            is None
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_cannot_widen_read_only_key_to_full_access(self):
+        self._assert_routes_403(
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=[]),
+                existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]),
+            )
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_cannot_widen_read_only_key_to_llm_api(self):
+        self._assert_routes_403(
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=["llm_api_routes"]),
+                existing_key_row=self._make_existing_key(allowed_routes=["info_routes"]),
+            )
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_cannot_clear_custom_route_restriction(self):
+        self._assert_routes_403(
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=[]),
+                existing_key_row=self._make_existing_key(allowed_routes=["/chat/completions"]),
+            )
+        )
+
+    @pytest.mark.asyncio
+    async def test_non_admin_cannot_set_non_preset_routes(self):
+        self._assert_routes_403(
+            await self._run_update(
+                data=UpdateKeyRequest(key="sk-test", allowed_routes=["management_routes"]),
+                existing_key_row=self._make_existing_key(allowed_routes=["llm_api_routes"]),
+            )
+        )
+
+
 class TestKeyOwnerPrivilegeEscalation:
     """
     Policy:
@@ -12007,9 +12124,10 @@ class TestAllowedRoutesCallerPermission:
 
     @pytest.mark.asyncio
     async def test_non_admin_update_key_explicit_empty_allowed_routes_rejected(self):
-        """`update_key_fn` rejects a non-admin when `allowed_routes` is
-        present as `[]` in the request body. The value matches the model
-        default but `model_fields_set` distinguishes the two."""
+        """`update_key_fn` rejects a non-admin clearing a custom (non-preset)
+        route restriction with an explicit `[]` in the request body. The value
+        matches the model default but `model_fields_set` distinguishes the
+        two. Clearing from a safe preset is allowed (LIT-4891)."""
         from litellm.proxy.management_endpoints.key_management_endpoints import (
             update_key_fn,
         )
@@ -12032,7 +12150,7 @@ class TestAllowedRoutesCallerPermission:
             patch(
                 "litellm.proxy.management_endpoints.key_management_endpoints._get_and_validate_existing_key",
                 new_callable=AsyncMock,
-                return_value=MagicMock(),
+                return_value=MagicMock(allowed_routes=["/chat/completions"]),
             ),
         ):
             with pytest.raises(ProxyException) as exc_info:
@@ -12047,8 +12165,8 @@ class TestAllowedRoutesCallerPermission:
 
     @pytest.mark.asyncio
     async def test_non_admin_update_key_explicit_null_allowed_routes_rejected(self):
-        """`update_key_fn` rejects a non-admin when `allowed_routes` is
-        present as `null` in the request body."""
+        """`update_key_fn` rejects a non-admin clearing a custom (non-preset)
+        route restriction with an explicit `null` in the request body."""
         from litellm.proxy.management_endpoints.key_management_endpoints import (
             update_key_fn,
         )
@@ -12071,7 +12189,7 @@ class TestAllowedRoutesCallerPermission:
             patch(
                 "litellm.proxy.management_endpoints.key_management_endpoints._get_and_validate_existing_key",
                 new_callable=AsyncMock,
-                return_value=MagicMock(),
+                return_value=MagicMock(allowed_routes=["/chat/completions"]),
             ),
         ):
             with pytest.raises(ProxyException) as exc_info:
@@ -14142,6 +14260,311 @@ async def test_info_key_fn_v2_budget_table_fallback(monkeypatch):
     mock_prisma_client.db.query_raw.assert_not_awaited()
 
 
+@pytest.mark.asyncio
+async def test_info_key_fn_reports_budget_limits_usage(monkeypatch):
+    """
+    /key/info reports current-window spend per budget window under budget_limits_usage,
+    keyed by budget_duration and read from the same counter enforcement uses, while
+    budget_limits itself comes back exactly as stored.
+    """
+    from unittest.mock import AsyncMock, MagicMock
+
+    from litellm.proxy._types import LiteLLM_VerificationToken
+    from litellm.proxy.management_endpoints.key_management_endpoints import info_key_fn
+
+    test_key_token = "hashed_token_window_test"
+    budget_limits = [
+        {
+            "reset_at": "2026-08-15T18:00:00+00:00",
+            "max_budget": 2.0,
+            "budget_duration": "1h",
+        }
+    ]
+
+    mock_prisma_client = AsyncMock()
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
+    mock_user_api_key_cache = AsyncMock()
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.user_api_key_cache", mock_user_api_key_cache
+    )
+    mock_get_current_spend = AsyncMock(return_value=0.73)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    mock_key_info = MagicMock(spec=LiteLLM_VerificationToken)
+    mock_key_info.token = test_key_token
+    mock_key_info.object_permission_id = None
+    mock_key_info.user_id = "user-w"
+    mock_key_info.team_id = None
+    mock_key_info.litellm_budget_table = None
+    mock_key_info.model_dump.return_value = {
+        "token": test_key_token,
+        "budget_limits": [dict(w) for w in budget_limits],
+        "user_id": "user-w",
+        "team_id": None,
+        "object_permission_id": None,
+        "litellm_budget_table": None,
+    }
+    mock_key_info.dict.return_value = mock_key_info.model_dump.return_value
+
+    mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(
+        return_value=mock_key_info
+    )
+
+    user_api_key_dict = UserAPIKeyAuth(
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+        api_key="sk-test-window-key",
+    )
+
+    result = await info_key_fn(
+        key="sk-test-window-key",
+        user_api_key_dict=user_api_key_dict,
+    )
+
+    assert result["info"]["budget_limits"] == budget_limits
+    assert result["info"]["budget_limits_usage"] == {"1h": {"current_spend": 0.73}}
+
+    mock_get_current_spend.assert_awaited_once()
+    call_kwargs = mock_get_current_spend.await_args.kwargs
+    assert call_kwargs["counter_key"] == f"spend:key:{test_key_token}:window:1h"
+    assert call_kwargs["max_budget"] == 2.0
+    assert call_kwargs["window_entity_type"] == "Key"
+    assert call_kwargs["window_entity_id"] == test_key_token
+    assert call_kwargs["window_duration"] == "1h"
+    assert call_kwargs["window_start"] is not None
+
+
+@pytest.mark.asyncio
+async def test_info_key_fn_no_budget_limits_skips_spend_lookup(monkeypatch):
+    """Keys without budget windows get no budget_limits_usage field and trigger no spend lookup."""
+    from unittest.mock import AsyncMock, MagicMock
+
+    from litellm.proxy._types import LiteLLM_VerificationToken
+    from litellm.proxy.management_endpoints.key_management_endpoints import info_key_fn
+
+    test_key_token = "hashed_token_no_windows"
+
+    mock_prisma_client = AsyncMock()
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
+    mock_user_api_key_cache = AsyncMock()
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.user_api_key_cache", mock_user_api_key_cache
+    )
+    mock_get_current_spend = AsyncMock(return_value=0.0)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    mock_key_info = MagicMock(spec=LiteLLM_VerificationToken)
+    mock_key_info.token = test_key_token
+    mock_key_info.object_permission_id = None
+    mock_key_info.user_id = "user-nw"
+    mock_key_info.team_id = None
+    mock_key_info.litellm_budget_table = None
+    mock_key_info.model_dump.return_value = {
+        "token": test_key_token,
+        "budget_limits": None,
+        "user_id": "user-nw",
+        "team_id": None,
+        "object_permission_id": None,
+        "litellm_budget_table": None,
+    }
+    mock_key_info.dict.return_value = mock_key_info.model_dump.return_value
+
+    mock_prisma_client.db.litellm_verificationtoken.find_unique = AsyncMock(
+        return_value=mock_key_info
+    )
+
+    user_api_key_dict = UserAPIKeyAuth(
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+        api_key="sk-test-no-window-key",
+    )
+
+    result = await info_key_fn(
+        key="sk-test-no-window-key",
+        user_api_key_dict=user_api_key_dict,
+    )
+
+    assert result["info"]["budget_limits"] is None
+    assert "budget_limits_usage" not in result["info"]
+    mock_get_current_spend.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_info_key_fn_v2_reports_budget_limits_usage(monkeypatch):
+    """/v2/key/info reports budget_limits_usage per window and leaves budget_limits as stored."""
+    from unittest.mock import AsyncMock, MagicMock
+
+    from litellm.proxy._types import KeyRequest, LiteLLM_VerificationToken
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        info_key_fn_v2,
+    )
+
+    test_key_token = "hashed_token_v2_window_test"
+    budget_limits = [
+        {
+            "reset_at": "2026-08-15T18:00:00+00:00",
+            "max_budget": 2.0,
+            "budget_duration": "1h",
+        },
+        {
+            "reset_at": "2026-08-16T00:00:00+00:00",
+            "max_budget": 20.0,
+            "budget_duration": "1d",
+        },
+    ]
+
+    mock_prisma_client = AsyncMock()
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
+    mock_user_api_key_cache = AsyncMock()
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.user_api_key_cache", mock_user_api_key_cache
+    )
+    mock_get_current_spend = AsyncMock(return_value=1.25)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    mock_key = MagicMock(spec=LiteLLM_VerificationToken)
+    mock_key.token = test_key_token
+    mock_key.user_id = "user-v2-w"
+    mock_key.team_id = None
+    mock_key.model_dump.return_value = {
+        "token": test_key_token,
+        "budget_limits": [dict(w) for w in budget_limits],
+        "user_id": "user-v2-w",
+        "team_id": None,
+        "litellm_budget_table": None,
+    }
+    mock_key.dict.return_value = mock_key.model_dump.return_value
+
+    mock_prisma_client.get_data = AsyncMock(return_value=[mock_key])
+
+    user_api_key_dict = UserAPIKeyAuth(
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+        api_key="sk-admin-v2-w",
+    )
+
+    result = await info_key_fn_v2(
+        data=KeyRequest(keys=[test_key_token]),
+        user_api_key_dict=user_api_key_dict,
+    )
+
+    assert len(result["info"]) == 1
+    assert result["info"][0]["budget_limits"] == budget_limits
+    assert result["info"][0]["budget_limits_usage"] == {
+        "1h": {"current_spend": 1.25},
+        "1d": {"current_spend": 1.25},
+    }
+    assert mock_get_current_spend.await_count == 2
+    counter_keys = {
+        call.kwargs["counter_key"] for call in mock_get_current_spend.await_args_list
+    }
+    assert counter_keys == {
+        f"spend:key:{test_key_token}:window:1h",
+        f"spend:key:{test_key_token}:window:1d",
+    }
+    assert {
+        call.kwargs["window_duration"] for call in mock_get_current_spend.await_args_list
+    } == {"1h", "1d"}
+
+
+@pytest.mark.asyncio
+async def test_build_budget_limits_usage_json_string_input(monkeypatch):
+    """budget_limits stored as a JSON string is parsed and reported per window."""
+    import json as json_module
+    from unittest.mock import AsyncMock
+
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _build_budget_limits_usage,
+    )
+
+    mock_get_current_spend = AsyncMock(return_value=0.5)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    raw = json_module.dumps(
+        [{"budget_duration": "1h", "max_budget": 2.0, "reset_at": None}]
+    )
+    result = await _build_budget_limits_usage(budget_limits=raw, api_key_hash="hash-1")
+
+    assert result == {"1h": {"current_spend": 0.5}}
+    mock_get_current_spend.assert_awaited_once()
+
+
+@pytest.mark.asyncio
+async def test_build_budget_limits_usage_empty_windows_returns_none(monkeypatch):
+    """A key with no windows (None, [], or "[]") returns None so the field is left off; no spend lookup runs."""
+    from unittest.mock import AsyncMock
+
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _build_budget_limits_usage,
+    )
+
+    mock_get_current_spend = AsyncMock(return_value=0.0)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    for stored in (None, [], "[]"):
+        assert await _build_budget_limits_usage(budget_limits=stored, api_key_hash="hash-1") is None
+    mock_get_current_spend.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_build_budget_limits_usage_window_without_max_budget(monkeypatch):
+    """A window with only budget_duration still reports current_spend, read without a budget ceiling."""
+    from unittest.mock import AsyncMock
+
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _build_budget_limits_usage,
+    )
+
+    mock_get_current_spend = AsyncMock(return_value=0.75)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    result = await _build_budget_limits_usage(
+        budget_limits=[{"budget_duration": "2d"}], api_key_hash="hash-no-max"
+    )
+
+    assert result == {"2d": {"current_spend": 0.75}}
+    call_kwargs = mock_get_current_spend.await_args.kwargs
+    assert call_kwargs["counter_key"] == "spend:key:hash-no-max:window:2d"
+    assert call_kwargs["window_duration"] == "2d"
+    assert call_kwargs["max_budget"] is None
+
+
+@pytest.mark.asyncio
+async def test_build_budget_limits_usage_pydantic_windows(monkeypatch):
+    """BudgetLimitEntry windows (the shape UserAPIKeyAuth carries) are dumped to dicts and reported."""
+    from unittest.mock import AsyncMock
+
+    from litellm.models.team import BudgetLimitEntry
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _build_budget_limits_usage,
+    )
+
+    mock_get_current_spend = AsyncMock(return_value=1.0)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.get_current_spend", mock_get_current_spend
+    )
+
+    result = await _build_budget_limits_usage(
+        budget_limits=[BudgetLimitEntry(budget_duration="7d", max_budget=10.0)],
+        api_key_hash="hash-2",
+    )
+
+    assert result == {"7d": {"current_spend": 1.0}}
+    call_kwargs = mock_get_current_spend.await_args.kwargs
+    assert call_kwargs["counter_key"] == "spend:key:hash-2:window:7d"
+    assert call_kwargs["window_duration"] == "7d"
+    assert call_kwargs["max_budget"] == 10.0
+
+
 @pytest.mark.asyncio
 async def test_info_key_fn_reads_the_configured_budget_model_key(monkeypatch):
     """/key/info reads the one counter enforcement reads: the configured budget model.
@@ -17066,3 +17489,49 @@ async def test_check_project_key_limits_still_rejects_real_model_outside_project
 
     assert exc_info.value.status_code == 400
     assert "Model 'gpt-5.4-mini' not in project's allowed models" in exc_info.value.detail["error"]
+
+
+def test_generate_key_request_blank_team_id_is_personal():
+    """The UI Team-field clear submits team_id=""; it must count as no team (LIT-3925)."""
+    from litellm.proxy._types import RegenerateKeyRequest
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        _is_team_key,
+    )
+
+    cleared = GenerateKeyRequest(team_id="")
+    assert cleared.team_id is None
+    assert _is_team_key(data=cleared) is False
+    assert RegenerateKeyRequest(team_id="").team_id is None
+    assert GenerateKeyRequest(team_id="team-1").team_id == "team-1"
+
+
+def test_key_generation_check_blank_team_id_uses_personal_permissions(monkeypatch):
+    """key_generation_check with team_id="" must take the personal-key path instead
+    of failing the team lookup with "Unable to find team object" (LIT-3925)."""
+    from litellm.proxy._types import KeyManagementRoutes
+    from litellm.proxy.management_endpoints.key_management_endpoints import (
+        key_generation_check,
+    )
+
+    monkeypatch.setattr(
+        litellm,
+        "key_generation_settings",
+        {
+            "team_key_generation": {"allowed_team_member_roles": ["admin"]},
+            "personal_key_generation": {"allowed_user_roles": ["proxy_admin", "internal_user"]},
+        },
+    )
+
+    assert (
+        key_generation_check(
+            team_table=None,
+            user_api_key_dict=UserAPIKeyAuth(
+                user_role=LitellmUserRoles.INTERNAL_USER,
+                api_key="sk-alice",
+                user_id="alice",
+            ),
+            data=GenerateKeyRequest(key_alias="personal", team_id=""),
+            route=KeyManagementRoutes.KEY_GENERATE,
+        )
+        is True
+    )
diff --git a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py
index dc9fede1f65..4661cc17dbc 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py
@@ -18,6 +18,7 @@ from litellm.proxy._types import (
     ReconcileOutcome,
     UserAPIKeyAuth,
 )
+from litellm.proxy.common_utils.encrypt_decrypt_utils import encrypt_value_helper
 from litellm.proxy.management_endpoints.model_management_endpoints import (
     ModelManagementAuthChecks,
     _get_team_deployments,
@@ -263,6 +264,131 @@ class TestModelManagementAuthChecks:
             )
         assert "403" in str(exc_info.value)
 
+    def test_can_user_attach_credential_admin_success(self):
+        result = ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+            user_api_key_dict=self.admin_user,
+        )
+        assert result is True
+
+    def test_can_user_attach_credential_without_credential_allows_any_role(self):
+        result = ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=LiteLLM_Params(model="test_model"),
+            user_api_key_dict=self.team_admin_user,
+        )
+        assert result is True
+
+    def test_can_user_attach_credential_team_admin_fails(self):
+        with pytest.raises(Exception, match="Only a proxy admin can attach a stored credential") as exc_info:
+            ModelManagementAuthChecks.can_user_attach_credential(
+                litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+                user_api_key_dict=self.team_admin_user,
+            )
+        assert exc_info.value.code == "403"
+
+    def test_can_user_attach_credential_unchanged_existing_allows_any_role(self):
+        result = ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+            user_api_key_dict=self.team_admin_user,
+            existing_litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+        )
+        assert result is True
+
+    def test_can_user_attach_credential_unchanged_encrypted_existing_allows_any_role(self, monkeypatch):
+        monkeypatch.setenv("LITELLM_SALT_KEY", "sk-1234")
+        encrypted_name = encrypt_value_helper(value="shared-credential")
+        assert encrypted_name != "shared-credential"
+        result = ModelManagementAuthChecks.can_user_attach_credential(
+            litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+            user_api_key_dict=self.team_admin_user,
+            existing_litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name=encrypted_name),
+        )
+        assert result is True
+
+    @pytest.mark.asyncio
+    async def test_add_new_model_rejects_credential_attach_for_non_admin(self):
+        from litellm.proxy._types import ProxyException
+        from litellm.proxy.management_endpoints.model_management_endpoints import (
+            add_new_model,
+        )
+
+        mock_prisma = MagicMock()
+        with (
+            patch("litellm.proxy.proxy_server.prisma_client", mock_prisma),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch("litellm.proxy.proxy_server.store_model_in_db", True),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch("litellm.proxy.proxy_server.premium_user", True),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch(  # test-quality-ok: prior auth check needs a live DB; only the credential check is under test
+                "litellm.proxy.management_endpoints.model_management_endpoints.ModelManagementAuthChecks.can_user_make_model_call",
+                new=AsyncMock(return_value=None),
+            ),
+        ):
+            with pytest.raises(ProxyException) as exc_info:
+                await add_new_model(
+                    model_params=Deployment(
+                        model_name="credential-model",
+                        litellm_params=LiteLLM_Params(
+                            model="openai/gpt-4o", litellm_credential_name="shared-credential"
+                        ),
+                        model_info={"id": "credential-create-test"},
+                    ),
+                    user_api_key_dict=self.team_admin_user,
+                )
+            assert exc_info.value.code == "403"
+            mock_prisma.db.litellm_proxymodeltable.create.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_patch_model_rejects_credential_attach_for_non_admin(self):
+        from litellm.proxy._types import ProxyException
+        from litellm.proxy.management_endpoints.model_management_endpoints import (
+            patch_model,
+        )
+        from litellm.types.router import updateLiteLLMParams
+
+        model_id = "credential-patch-test"
+        db_model = Deployment(
+            model_name="credential-model",
+            litellm_params=LiteLLM_Params(model="openai/gpt-4o"),
+            model_info={"id": model_id},
+        )
+        with (
+            patch("litellm.proxy.proxy_server.prisma_client", MagicMock()),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch("litellm.proxy.proxy_server.llm_router", MagicMock()),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch("litellm.proxy.proxy_server.store_model_in_db", True),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch("litellm.proxy.proxy_server.premium_user", True),  # test-quality-ok: endpoint reads proxy server globals with no injection seam
+            patch(  # test-quality-ok: stubs the DB row fetch; only the credential check is under test
+                "litellm.proxy.management_endpoints.model_management_endpoints.get_db_model",
+                new=AsyncMock(return_value=db_model),
+            ),
+            patch(  # test-quality-ok: prior auth check needs a live DB; only the credential check is under test
+                "litellm.proxy.management_endpoints.model_management_endpoints.ModelManagementAuthChecks.can_user_make_model_call",
+                new=AsyncMock(return_value=None),
+            ),
+            patch(  # test-quality-ok: asserts the DB write is never reached on rejection
+                "litellm.proxy.management_endpoints.model_management_endpoints._update_team_model_in_db",
+                new=AsyncMock(),
+            ) as mock_update,
+        ):
+            with pytest.raises(ProxyException) as exc_info:
+                await patch_model(
+                    model_id=model_id,
+                    patch_data=updateDeployment(
+                        litellm_params=updateLiteLLMParams(
+                            model="openai/gpt-4o", litellm_credential_name="shared-credential"
+                        )
+                    ),
+                    user_api_key_dict=self.team_admin_user,
+                )
+            assert exc_info.value.code == "403"
+            mock_update.assert_not_awaited()
+
+    def test_can_user_attach_credential_internal_user_fails(self):
+        with pytest.raises(Exception, match="Only a proxy admin can attach a stored credential") as exc_info:
+            ModelManagementAuthChecks.can_user_attach_credential(
+                litellm_params=LiteLLM_Params(model="test_model", litellm_credential_name="shared-credential"),
+                user_api_key_dict=self.normal_user,
+            )
+        assert exc_info.value.code == "403"
+
 
 class MockModelTable:
     def __init__(self, model_aliases: Dict[str, str], include: Optional[dict] = None):
@@ -4466,3 +4592,65 @@ class TestEnforceRpmTpmOnModelAdd:
             _raise_if_rate_limits_required_but_missing(litellm_params=params, enforced=True)
         assert expected_missing in str(exc_info.value.message)
         assert exc_info.value.code == "400"
+
+
+class TestBlockModelResponseSerialization:
+    @pytest.mark.parametrize(
+        ("route", "blocked"), [("/model/block", True), ("/model/unblock", False)]
+    )
+    def test_block_routes_serialize_prisma_row_to_200(self, route, blocked):
+        from datetime import datetime, timezone
+
+        from prisma import models as prisma_models
+
+        import litellm.proxy.proxy_server as ps
+        from litellm.proxy.proxy_server import app
+
+        written_at = datetime(2026, 8, 29, tzinfo=timezone.utc)
+        row_fields = {
+            "model_id": "m-block-1",
+            "model_name": "gpt-4o-mini",
+            "litellm_params": json.dumps({"model": "openai/gpt-4o-mini", "api_key": "encrypted-value"}),
+            "model_info": json.dumps({"id": "m-block-1"}),
+            "created_at": written_at,
+            "created_by": "admin",
+            "updated_at": written_at,
+            "updated_by": "admin",
+        }
+        existing_row = prisma_models.LiteLLM_ProxyModelTable(blocked=not blocked, **row_fields)
+        updated_row = prisma_models.LiteLLM_ProxyModelTable(blocked=blocked, **row_fields)
+
+        mock_prisma = MagicMock()
+        mock_prisma.db.litellm_proxymodeltable.find_unique = AsyncMock(return_value=existing_row)
+        mock_prisma.db.litellm_proxymodeltable.update = AsyncMock(return_value=updated_row)
+
+        admin = UserAPIKeyAuth(user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN)
+        app.dependency_overrides[ps.user_api_key_auth] = lambda: admin
+        try:
+            with (
+                patch("litellm.proxy.proxy_server.prisma_client", mock_prisma),  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+                patch("litellm.proxy.proxy_server.store_model_in_db", True),  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+                patch(  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+                    "litellm.proxy.proxy_server.llm_router",
+                    MagicMock(**{"get_model_ids.return_value": ["m-block-1"]}),
+                ),
+                patch("litellm.proxy.proxy_server.redis_usage_cache", None),  # test-quality-ok: proxy_server module global is the endpoint's only injection point
+                patch(  # test-quality-ok: stubs the cache write so the test observes only response serialization
+                    "litellm.proxy.management_endpoints.model_management_endpoints.clear_cache",
+                    new=AsyncMock(return_value=ReconcileOutcome(still_desired=None, live_after=None)),
+                ),
+                patch(  # test-quality-ok: audit logging is a background side effect outside this test's contract
+                    "litellm.proxy.management_endpoints.model_management_endpoints.create_object_audit_log",
+                    new=AsyncMock(return_value=None),
+                ),
+            ):
+                client = TestClient(app)
+                response = client.post(route, json={"model_id": "m-block-1"})
+        finally:
+            app.dependency_overrides.pop(ps.user_api_key_auth, None)
+
+        assert response.status_code == 200, response.text
+        body = response.json()
+        assert body["model_id"] == "m-block-1"
+        assert body["blocked"] is blocked
+        assert body["litellm_params"] == {"model": "openai/gpt-4o-mini", "api_key": "encrypted-value"}
diff --git a/tests/test_litellm/proxy/management_endpoints/test_saml_sso.py b/tests/test_litellm/proxy/management_endpoints/test_saml_sso.py
index 57decc7d458..36d6414ba9f 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_saml_sso.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_saml_sso.py
@@ -642,3 +642,77 @@ async def test_read_acs_post_data_rejects_oversized_stream_without_content_lengt
     with pytest.raises(HTTPException) as exc:
         await SAMLAuthHandler.read_acs_post_data(cast(Request, request))
     assert exc.value.status_code == 413
+
+
+def _fake_request_with_scheme(scheme, headers=None, client_host="203.0.113.5"):
+    """A fuller fake Request than ``_fake_request``: adds ``url``, ``headers`` and
+    ``client``, which ``IPAddressUtils.is_request_https`` reads directly instead of
+    going through ``PROXY_BASE_URL``."""
+    return type(
+        "Req",
+        (),
+        {
+            "base_url": URL(f"{scheme}://proxy.example.com/"),
+            "url": URL(f"{scheme}://proxy.example.com/sso/saml/login"),
+            "query_params": {},
+            "cookies": {},
+            "headers": headers or {},
+            "client": type("Client", (), {"host": client_host})(),
+        },
+    )()
+
+
+class TestSAMLAuthnCookieSecureFlag:
+    """Regression tests for the litellm_saml_authn cookie's Secure attribute.
+    litellm only sees a plain-HTTP hop whenever TLS terminates at a reverse
+    proxy, so Secure must not be derived from the literal request scheme alone."""
+
+    @pytest.mark.asyncio
+    async def test_secure_over_direct_https(self, saml_env, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        cache = DualCache()
+        request = _fake_request_with_scheme("https")
+        redirect = await SAMLAuthHandler.build_login_redirect(request, cache)
+        cookie = redirect.headers["set-cookie"]
+        assert "Secure" in cookie
+        assert "SameSite=none" in cookie
+
+    @pytest.mark.asyncio
+    async def test_not_secure_over_direct_http(self, saml_env, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        cache = DualCache()
+        request = _fake_request_with_scheme("http")
+        redirect = await SAMLAuthHandler.build_login_redirect(request, cache)
+        cookie = redirect.headers["set-cookie"]
+        assert "Secure" not in cookie
+        assert "SameSite=lax" in cookie
+
+    @pytest.mark.asyncio
+    async def test_secure_behind_trusted_tls_terminating_proxy(self, saml_env, monkeypatch):
+        """THE regression: TLS terminates at a reverse proxy, litellm only sees a
+        plain-HTTP hop, but the cookie must still be marked Secure when the operator
+        has configured a trusted proxy reporting X-Forwarded-Proto: https."""
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        monkeypatch.setattr(
+            "litellm.proxy.proxy_server.general_settings",
+            {"use_x_forwarded_for": True, "mcp_trusted_proxy_ranges": ["10.0.0.0/8"]},
+        )
+        cache = DualCache()
+        request = _fake_request_with_scheme(
+            "http", headers={"X-Forwarded-Proto": "https"}, client_host="10.0.0.5"
+        )
+        redirect = await SAMLAuthHandler.build_login_redirect(request, cache)
+        cookie = redirect.headers["set-cookie"]
+        assert "Secure" in cookie
+
+    @pytest.mark.asyncio
+    async def test_untrusted_spoofed_forwarded_proto_is_ignored(self, saml_env, monkeypatch):
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+        cache = DualCache()
+        request = _fake_request_with_scheme(
+            "http", headers={"X-Forwarded-Proto": "https"}, client_host="203.0.113.5"
+        )
+        redirect = await SAMLAuthHandler.build_login_redirect(request, cache)
+        cookie = redirect.headers["set-cookie"]
+        assert "Secure" not in cookie
diff --git a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
index ffa6bc601e9..30b2ab86b9a 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py
@@ -3741,6 +3741,93 @@ async def test_list_team_v2_with_status_deleted():
         assert len(result["teams"]) == 2
 
 
+@pytest.mark.asyncio
+async def test_list_team_v2_includes_litellm_model_table():
+    """
+    Regression test for GH #26312: GET /v2/team/list must eagerly load the
+    litellm_model_table relation for active teams, same as /team/info and
+    /team/list, or a team's model_aliases always read back as null from this
+    endpoint. Deleted teams are excluded: LiteLLM_DeletedTeamTable has no such
+    relation in the Prisma schema, so requesting it there raises
+    UnknownRelationalFieldError against a real database.
+
+    The fake find_many below only attaches litellm_model_table when its own
+    `include` kwarg actually asks for the relation, so the assertions below
+    are on what the caller gets back, not on how find_many was called.
+    """
+    from unittest.mock import AsyncMock, Mock, patch
+
+    from fastapi import Request
+
+    from litellm.proxy._types import LitellmUserRoles, UserAPIKeyAuth
+    from litellm.proxy.management_endpoints.team_endpoints import list_team_v2
+
+    mock_request = Mock(spec=Request)
+    mock_user_api_key_dict_admin = UserAPIKeyAuth(
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+        user_id="admin_user_123",
+    )
+
+    def _team_row(team_id: str, include) -> Mock:
+        model_table = (
+            {
+                "id": 1,
+                "model_aliases": {"my-fast-model": "fake-model"},
+                "created_by": "u",
+                "updated_by": "u",
+                "team": None,
+            }
+            if (include or {}).get("litellm_model_table")
+            else None
+        )
+        return Mock(
+            team_id=team_id,
+            model_dump=lambda: {
+                "team_id": team_id,
+                "team_alias": "t",
+                "litellm_model_table": model_table,
+            },
+        )
+
+    with patch("litellm.proxy.proxy_server.prisma_client") as mock_prisma_client:  # test-quality-ok: this file's DB-mock convention
+        mock_db = Mock()
+        mock_prisma_client.db = mock_db
+
+        mock_db.litellm_teamtable.find_many = AsyncMock(
+            side_effect=lambda **kw: [_team_row("team_1", kw.get("include"))]
+        )
+        mock_db.litellm_teamtable.count = AsyncMock(return_value=1)
+        mock_db.litellm_verificationtoken.group_by = AsyncMock(return_value=[])
+
+        result = await list_team_v2(
+            http_request=mock_request,
+            user_id=None,
+            user_api_key_dict=mock_user_api_key_dict_admin,
+            page=1,
+            page_size=10,
+            status=None,
+        )
+
+        assert result["teams"][0].litellm_model_table is not None
+        assert result["teams"][0].litellm_model_table.model_aliases == {"my-fast-model": "fake-model"}
+
+        mock_db.litellm_deletedteamtable.find_many = AsyncMock(
+            side_effect=lambda **kw: [_team_row("team_2", kw.get("include"))]
+        )
+        mock_db.litellm_deletedteamtable.count = AsyncMock(return_value=1)
+
+        await list_team_v2(
+            http_request=mock_request,
+            user_id=None,
+            user_api_key_dict=mock_user_api_key_dict_admin,
+            page=1,
+            page_size=10,
+            status="deleted",
+        )
+
+        assert "include" not in mock_db.litellm_deletedteamtable.find_many.call_args.kwargs
+
+
 @pytest.mark.asyncio
 async def test_list_team_v2_org_admin_sees_org_teams():
     """
diff --git a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py
index e648bd09734..dd8c752a868 100644
--- a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py
+++ b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py
@@ -7604,6 +7604,112 @@ class TestPKCEStateCookieBinding:
         assert cookie_str is not None
         assert "Secure" not in cookie_str
 
+    @pytest.mark.asyncio
+    async def test_redirect_response_sets_secure_flag_behind_trusted_tls_terminating_proxy(
+        self, monkeypatch
+    ):
+        """Regression: litellm sees a plain-HTTP hop when TLS terminates at a reverse
+        proxy. The Secure flag must still be set when the direct peer is a configured
+        trusted proxy and it reports X-Forwarded-Proto: https -- but NOT from an
+        unconfigured/untrusted caller spoofing the same header (see the sibling test
+        below)."""
+        from fastapi.responses import RedirectResponse
+
+        from litellm.proxy.management_endpoints.ui_sso import (
+            SSOAuthenticationHandler,
+        )
+
+        mock_redirect = RedirectResponse(
+            url="http://idp.internal/authorize?state=behind-proxy-state"
+        )
+        mock_generic_sso = MagicMock()
+        mock_generic_sso.__enter__ = MagicMock(return_value=mock_generic_sso)
+        mock_generic_sso.__exit__ = MagicMock(return_value=None)
+        mock_generic_sso.get_login_redirect = AsyncMock(return_value=mock_redirect)
+
+        proxied_request = MagicMock(spec=Request)
+        proxied_request.url.scheme = "http"
+        proxied_request.headers = {"X-Forwarded-Proto": "https"}
+        proxied_request.client = MagicMock()
+        proxied_request.client.host = "10.0.0.5"
+
+        monkeypatch.setattr(
+            "litellm.proxy.proxy_server.general_settings",
+            {"use_x_forwarded_for": True, "mcp_trusted_proxy_ranges": ["10.0.0.0/8"]},
+        )
+
+        with patch.dict(
+            os.environ,
+            {
+                "GENERIC_CLIENT_STATE": "behind-proxy-state",
+                "GENERIC_CLIENT_USE_PKCE": "true",
+            },
+        ):
+            response = await SSOAuthenticationHandler.get_generic_sso_redirect_response(
+                generic_sso=mock_generic_sso,
+                state=None,
+                generic_authorization_endpoint="http://idp.internal/authorize",
+                request=proxied_request,
+            )
+
+        cookie_headers = response.headers.getlist("set-cookie")
+        cookie_str = next(
+            (c for c in cookie_headers if "litellm_oauth_state=" in c), None
+        )
+        assert cookie_str is not None
+        assert "Secure" in cookie_str
+
+    @pytest.mark.asyncio
+    async def test_redirect_response_ignores_spoofed_forwarded_proto_without_trust_config(
+        self, monkeypatch
+    ):
+        """The same X-Forwarded-Proto: https header must NOT flip Secure on when no
+        trusted-proxy config is present -- honoring it unconditionally would let any
+        client spoof the header and would not itself be the vulnerability the ticket
+        warns against."""
+        from fastapi.responses import RedirectResponse
+
+        from litellm.proxy.management_endpoints.ui_sso import (
+            SSOAuthenticationHandler,
+        )
+
+        mock_redirect = RedirectResponse(
+            url="http://idp.internal/authorize?state=spoofed-state"
+        )
+        mock_generic_sso = MagicMock()
+        mock_generic_sso.__enter__ = MagicMock(return_value=mock_generic_sso)
+        mock_generic_sso.__exit__ = MagicMock(return_value=None)
+        mock_generic_sso.get_login_redirect = AsyncMock(return_value=mock_redirect)
+
+        spoofed_request = MagicMock(spec=Request)
+        spoofed_request.url.scheme = "http"
+        spoofed_request.headers = {"X-Forwarded-Proto": "https"}
+        spoofed_request.client = MagicMock()
+        spoofed_request.client.host = "203.0.113.5"
+
+        monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+
+        with patch.dict(
+            os.environ,
+            {
+                "GENERIC_CLIENT_STATE": "spoofed-state",
+                "GENERIC_CLIENT_USE_PKCE": "true",
+            },
+        ):
+            response = await SSOAuthenticationHandler.get_generic_sso_redirect_response(
+                generic_sso=mock_generic_sso,
+                state=None,
+                generic_authorization_endpoint="http://idp.internal/authorize",
+                request=spoofed_request,
+            )
+
+        cookie_headers = response.headers.getlist("set-cookie")
+        cookie_str = next(
+            (c for c in cookie_headers if "litellm_oauth_state=" in c), None
+        )
+        assert cookie_str is not None
+        assert "Secure" not in cookie_str
+
     @pytest.mark.asyncio
     async def test_pkce_callback_rejects_missing_cookie(self):
         """When PKCE is enabled and a code_verifier is in the cache, the
@@ -8586,6 +8692,24 @@ class TestSameOriginReturnPath:
         assert _is_same_origin_return_path("") is False
 
 
+def _make_https_request() -> Request:
+    request = MagicMock(spec=Request)
+    request.url.scheme = "https"
+    request.headers = {}
+    request.client = MagicMock()
+    request.client.host = "203.0.113.5"
+    return request
+
+
+def _make_http_request() -> Request:
+    request = MagicMock(spec=Request)
+    request.url.scheme = "http"
+    request.headers = {}
+    request.client = MagicMock()
+    request.client.host = "203.0.113.5"
+    return request
+
+
 class TestPersistReturnToCookieSharedHelper:
     """The single shared return_to helper used by EVERY sign-in branch (SSO / Okta / generic AND the
     username/password form). It must be best-effort and NEVER raise — a bad return_to can never block
@@ -8603,7 +8727,7 @@ class TestPersistReturnToCookieSharedHelper:
 
         monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
         resp = Response()
-        _persist_return_to_cookie(resp, "/mcp/authorize?client_id=llm_dcrc_abc")
+        _persist_return_to_cookie(resp, "/mcp/authorize?client_id=llm_dcrc_abc", _make_https_request())
         assert "litellm_cp_return_to=" in self._cookie(resp)
 
     def test_bad_absolute_with_control_plane_configured_does_not_raise_and_is_not_stored(self, monkeypatch):
@@ -8617,7 +8741,7 @@ class TestPersistReturnToCookieSharedHelper:
             "litellm.proxy.proxy_server.general_settings", {"control_plane_url": "https://cp.example.com"}
         )
         resp = Response()
-        _persist_return_to_cookie(resp, "https://evil.example.com/steal")  # must not raise
+        _persist_return_to_cookie(resp, "https://evil.example.com/steal", _make_https_request())  # must not raise
         assert "litellm_cp_return_to=" not in self._cookie(resp)
 
     def test_none_return_to_is_a_noop(self):
@@ -8626,7 +8750,7 @@ class TestPersistReturnToCookieSharedHelper:
         from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie
 
         resp = Response()
-        _persist_return_to_cookie(resp, None)
+        _persist_return_to_cookie(resp, None, _make_https_request())
         assert "litellm_cp_return_to=" not in self._cookie(resp)
 
     def test_control_plane_matching_absolute_is_stored(self, monkeypatch):
@@ -8638,5 +8762,126 @@ class TestPersistReturnToCookieSharedHelper:
             "litellm.proxy.proxy_server.general_settings", {"control_plane_url": "https://cp.example.com"}
         )
         resp = Response()
-        _persist_return_to_cookie(resp, "https://cp.example.com/ui?page=models")
+        _persist_return_to_cookie(resp, "https://cp.example.com/ui?page=models", _make_https_request())
         assert "litellm_cp_return_to=" in self._cookie(resp)
+
+    def test_cookie_is_secure_and_httponly_over_https(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie
+
+        monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+        resp = Response()
+        _persist_return_to_cookie(resp, "/mcp/authorize", _make_https_request())
+        cookie = self._cookie(resp)
+        assert "Secure" in cookie
+        assert "HttpOnly" in cookie
+        assert "SameSite=lax" in cookie
+
+    def test_cookie_is_not_secure_over_plain_http_direct(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie
+
+        monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+        resp = Response()
+        _persist_return_to_cookie(resp, "/mcp/authorize", _make_http_request())
+        assert "Secure" not in self._cookie(resp)
+
+    def test_cookie_is_secure_behind_trusted_tls_terminating_proxy(self, monkeypatch):
+        """Regression for the reported bug: TLS terminates at a reverse proxy, litellm only
+        sees a plain-HTTP hop, but a trusted X-Forwarded-Proto: https must still mark the
+        cookie Secure."""
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import _persist_return_to_cookie
+
+        monkeypatch.setattr(
+            "litellm.proxy.proxy_server.general_settings",
+            {"use_x_forwarded_for": True, "mcp_trusted_proxy_ranges": ["10.0.0.0/8"]},
+        )
+        resp = Response()
+        request = _make_http_request()
+        request.client.host = "10.0.0.5"
+        request.headers = {"X-Forwarded-Proto": "https"}
+        _persist_return_to_cookie(resp, "/mcp/authorize", request)
+        assert "Secure" in self._cookie(resp)
+
+
+class TestSessionTokenCookie:
+    """Regression tests for the ``token`` session cookie set by every sign-in path
+    (username/password login, SSO callback, the CLI /v2, /v3 login exchange helpers).
+    It was previously set with no Secure/HttpOnly/SameSite attributes at all -- always
+    sent over plain HTTP and readable by any script on the page. HttpOnly must stay off
+    deliberately: the dashboard reads this cookie via document.cookie."""
+
+    @staticmethod
+    def _cookie(resp) -> str:
+        return resp.headers.get("set-cookie", "")
+
+    def test_secure_over_direct_https(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        resp = Response()
+        set_session_token_cookie(resp, _make_https_request(), "jwt-token-value")
+        cookie = self._cookie(resp)
+        assert "token=jwt-token-value" in cookie
+        assert "Secure" in cookie
+        assert "SameSite=lax" in cookie
+        assert "HttpOnly" not in cookie
+
+    def test_not_secure_over_direct_http(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        resp = Response()
+        set_session_token_cookie(resp, _make_http_request(), "jwt-token-value")
+        assert "Secure" not in self._cookie(resp)
+
+    def test_secure_behind_trusted_tls_terminating_proxy(self, monkeypatch):
+        """THE regression: TLS terminates at a reverse proxy, litellm only sees a
+        plain-HTTP hop, but the session cookie must still be marked Secure when the
+        operator has configured a trusted proxy that reports X-Forwarded-Proto: https."""
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        monkeypatch.setattr(
+            "litellm.proxy.proxy_server.general_settings",
+            {"use_x_forwarded_for": True, "mcp_trusted_proxy_ranges": ["10.0.0.0/8"]},
+        )
+        request = _make_http_request()
+        request.client.host = "10.0.0.5"
+        request.headers = {"X-Forwarded-Proto": "https"}
+        resp = Response()
+        set_session_token_cookie(resp, request, "jwt-token-value")
+        assert "Secure" in self._cookie(resp)
+
+    def test_untrusted_spoofed_forwarded_proto_is_ignored(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
+        monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+        monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+        request = _make_http_request()
+        request.headers = {"X-Forwarded-Proto": "https"}
+        resp = Response()
+        set_session_token_cookie(resp, request, "jwt-token-value")
+        assert "Secure" not in self._cookie(resp)
+
+    def test_proxy_base_url_https_overrides_literal_http_scheme(self, monkeypatch):
+        from fastapi import Response
+
+        from litellm.proxy.management_endpoints.ui_sso import set_session_token_cookie
+
+        monkeypatch.setenv("PROXY_BASE_URL", "https://litellm.example.com")
+        resp = Response()
+        set_session_token_cookie(resp, _make_http_request(), "jwt-token-value")
+        assert "Secure" in self._cookie(resp)
diff --git a/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py b/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py
new file mode 100644
index 00000000000..60c36e33e09
--- /dev/null
+++ b/tests/test_litellm/proxy/management_helpers/test_access_group_key_sync.py
@@ -0,0 +1,57 @@
+from types import SimpleNamespace
+from unittest.mock import AsyncMock, MagicMock
+
+import pytest
+
+from litellm.proxy.db.prisma_client import PrismaWrapper
+from litellm.proxy.db.routing_prisma_wrapper import RoutingPrismaWrapper
+from litellm.proxy.management_helpers.access_group_key_sync import (
+    sync_key_access_group_membership,
+    sync_key_regeneration_access_group_membership,
+)
+
+
+def _routed_prisma_client():
+    writer_inner = MagicMock(name="writer_prisma")
+    reader_inner = MagicMock(name="reader_prisma")
+    writer_inner.query_raw = AsyncMock(return_value=[])
+    reader_inner.query_raw = AsyncMock(return_value=[])
+    writer = PrismaWrapper(original_prisma=writer_inner, iam_token_db_auth=False)
+    reader = PrismaWrapper(original_prisma=reader_inner, iam_token_db_auth=False)
+    routing = RoutingPrismaWrapper(writer=writer, reader=reader)
+    return SimpleNamespace(db=routing), writer_inner, reader_inner
+
+
+@pytest.mark.asyncio
+async def test_regeneration_repoint_update_runs_on_the_writer():
+    prisma_client, writer_inner, reader_inner = _routed_prisma_client()
+
+    await sync_key_regeneration_access_group_membership(
+        prisma_client=prisma_client,
+        previous_key_token="old-token",
+        new_key_token="new-token",
+        data=None,
+        existing_key_row=MagicMock(),
+    )
+
+    writer_inner.query_raw.assert_awaited_once()
+    assert writer_inner.query_raw.await_args.args[0].startswith('UPDATE "LiteLLM_AccessGroupTable"')
+    reader_inner.query_raw.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_membership_attach_and_detach_updates_run_on_the_writer():
+    prisma_client, writer_inner, reader_inner = _routed_prisma_client()
+
+    await sync_key_access_group_membership(
+        prisma_client=prisma_client,
+        key_token="token",
+        previous_access_group_ids=["ag-old"],
+        updated_access_group_ids=["ag-new"],
+    )
+
+    assert writer_inner.query_raw.await_count == 2
+    assert all(
+        call.args[0].startswith('UPDATE "LiteLLM_AccessGroupTable"') for call in writer_inner.query_raw.await_args_list
+    )
+    reader_inner.query_raw.assert_not_awaited()
diff --git a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py
index 5ef83344c1a..f2b6b799271 100644
--- a/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py
+++ b/tests/test_litellm/proxy/management_helpers/test_object_permission_utils.py
@@ -1,11 +1,9 @@
 import json
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from fastapi import HTTPException
 
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
 from litellm.proxy._types import (
     LiteLLM_ObjectPermissionBase,
     LiteLLM_ObjectPermissionTable,
@@ -13,10 +11,10 @@ from litellm.proxy._types import (
     SpecialMCPServerName,
 )
 from litellm.proxy.management_helpers.object_permission_utils import (
+    _drop_stale_object_permission_mcp_servers,
     _extract_requested_mcp_access_groups,
     _extract_requested_mcp_server_ids,
     _resolve_team_allowed_mcp_servers,
-    _rewrite_object_permission_mcp_servers,
     _set_object_permission,
     enforce_all_proxy_mcp_servers_grant_is_admin_only,
     validate_key_mcp_servers_against_team,
@@ -153,10 +151,10 @@ def test_extract_requested_mcp_server_ids_excludes_no_mcp_servers_sentinel():
     assert _extract_requested_mcp_server_ids(obj_perm) == {"server-1"}
 
 
-def test_rewrite_object_permission_mcp_servers_preserves_sentinel():
-    obj_perm = {"mcp_servers": ["no-mcp-servers", "alias-1"]}
-    _rewrite_object_permission_mcp_servers(obj_perm, {"alias-1": {"server-1"}})
-    assert obj_perm["mcp_servers"] == ["no-mcp-servers", "server-1"]
+def test_drop_stale_object_permission_mcp_servers_preserves_sentinel_and_alias():
+    obj_perm = {"mcp_servers": ["no-mcp-servers", "alias-1", "gone-id"]}
+    _drop_stale_object_permission_mcp_servers(obj_perm, {"alias-1": {"server-1"}, "gone-id": set()})
+    assert obj_perm["mcp_servers"] == ["no-mcp-servers", "alias-1"]
 
 
 @pytest.mark.asyncio
@@ -692,9 +690,10 @@ async def test_validate_mcp_server_alias_outside_team_scope_raises(
     new_callable=AsyncMock,
     return_value=[],
 )
-async def test_validate_mcp_server_alias_is_normalized_before_save(
-    mock_access_groups, mock_allow_all
-):
+async def test_validate_mcp_server_alias_persists_verbatim(mock_access_groups, mock_allow_all):
+    """Regression for the multi-region shared-DB setup: an alias grant must be
+    stored as the alias, so every instance can expand it to its own local id.
+    Rewriting to this instance's server_id breaks access on the other region."""
     team_obj = _make_team_obj(mcp_servers=["allowed-server-id"])
     object_permission = {
         "mcp_servers": ["allowed-alias"],
@@ -706,8 +705,27 @@ async def test_validate_mcp_server_alias_is_normalized_before_save(
         team_obj=team_obj,
     )
 
-    assert object_permission["mcp_servers"] == ["allowed-server-id"]
-    assert object_permission["mcp_tool_permissions"] == {"allowed-server-id": ["tool1"]}
+    assert object_permission["mcp_servers"] == ["allowed-alias"]
+    assert object_permission["mcp_tool_permissions"] == {"Allowed Server": ["tool1"]}
+
+
+def test_alias_grant_expands_on_other_region_after_save():
+    """Cross-region flow: the west instance saves an alias grant (its resolver maps
+    the alias to west's hash-derived id), then the central instance, whose registry
+    maps the same alias to a different id, expands the persisted grant. Rewriting
+    to west's id at save time is exactly the regression this guards against."""
+    west_mgr = _make_mock_mcp_manager(servers=[_make_mock_mcp_server("west-id", alias="github-mcp")])
+    central_mgr = _make_mock_mcp_manager(servers=[_make_mock_mcp_server("central-id", alias="github-mcp")])
+
+    object_permission = {"mcp_servers": ["github-mcp"]}
+    _drop_stale_object_permission_mcp_servers(object_permission, {"github-mcp": {"west-id"}})
+    assert object_permission["mcp_servers"] == ["github-mcp"]
+
+    from litellm.proxy._experimental.mcp_server.mcp_server_manager import MCPServerManager
+
+    expand = MCPServerManager.expand_permission_list
+    assert expand(west_mgr, object_permission["mcp_servers"]) == ["west-id"]
+    assert expand(central_mgr, object_permission["mcp_servers"]) == ["central-id"]
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
index 87e0319f6a1..bca97915347 100644
--- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py
@@ -4555,3 +4555,114 @@ def test_create_file_async_pre_call_hook_rejection_blocks_upload(monkeypatch, ll
     assert response.status_code == 400, response.text
     assert "file upload not allowed" in response.text
     assert provider_route.call_count == 0
+
+
+def test_create_file_non_batch_over_max_file_size_mb_rejected_before_forwarding(monkeypatch, llm_router: Router):
+    """max_file_size_mb applies to every purpose, unlike the batch-only max_batch_file_size_mb."""
+    import litellm.proxy.proxy_server as ps
+
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+    monkeypatch.setitem(ps.general_settings, "max_file_size_mb", 1)
+
+    oversized = b"x" * (2 * 1024 * 1024)
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("labels.jsonl", oversized, "application/octet-stream")},
+            data={"purpose": "user_data"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 413, response.text
+    error = response.json()["error"]
+    assert error["type"] == "invalid_request_error"
+    assert error["param"] == "file"
+    assert "max_file_size_mb" in error["message"]
+    assert "1 MB" in error["message"]
+    assert forwarded_calls == []
+
+
+def test_create_file_non_batch_under_max_file_size_mb_forwards(monkeypatch, llm_router: Router):
+    import litellm.proxy.proxy_server as ps
+
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+    monkeypatch.setitem(ps.general_settings, "max_file_size_mb", 1)
+
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("labels.jsonl", b"small content", "application/octet-stream")},
+            data={"purpose": "user_data"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 200, response.text
+    assert len(forwarded_calls) == 1
+
+
+def test_create_file_blocked_extension_rejected_before_forwarding(monkeypatch, llm_router: Router):
+    import litellm.proxy.proxy_server as ps
+
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+    monkeypatch.setitem(ps.general_settings, "blocked_file_extensions", [".exe", ".sh"])
+
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("payload.exe", b"MZ\x90\x00", "application/octet-stream")},
+            data={"purpose": "user_data"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 400, response.text
+    error = response.json()["error"]
+    assert error["type"] == "invalid_request_error"
+    assert error["param"] == "file"
+    assert ".exe" in error["message"]
+    assert "blocked_file_extensions" in error["message"]
+    assert forwarded_calls == []
+
+
+def test_create_file_blocked_extension_unset_allows_everything(monkeypatch, llm_router: Router):
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("payload.exe", b"MZ\x90\x00", "application/octet-stream")},
+            data={"purpose": "user_data"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 200, response.text
+    assert len(forwarded_calls) == 1
+
+
+def test_create_file_path_traversal_filename_rejected_before_forwarding(monkeypatch, llm_router: Router):
+    """A filename carrying a directory-traversal component must never reach storage or the provider."""
+    forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router)
+
+    try:
+        response = client.post(
+            "/v1/files",
+            files={"file": ("../../etc/passwd", b"malicious content", "text/plain")},
+            data={"purpose": "user_data"},
+            headers={"Authorization": "Bearer test-key"},
+        )
+    finally:
+        _teardown_batch_upload_endpoint()
+
+    assert response.status_code == 400, response.text
+    error = response.json()["error"]
+    assert error["type"] == "invalid_request_error"
+    assert error["param"] == "file"
+    assert "traversal" in error["message"].lower()
+    assert forwarded_calls == []
diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py b/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py
new file mode 100644
index 00000000000..9f7dd914e4a
--- /dev/null
+++ b/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py
@@ -0,0 +1,134 @@
+import io
+
+import pytest
+
+from litellm.proxy._types import ProxyException
+from litellm.proxy.openai_files_endpoints.general_upload_validation import (
+    MB,
+    UploadedFileBlockedExtension,
+    UploadedFileTooLarge,
+    UploadedFileUnsafeFilename,
+    check_blocked_extension,
+    check_unsafe_filename,
+    check_upload_file_size,
+    raise_upload_validation_failure,
+)
+
+
+def test_size_under_cap_allowed():
+    assert check_upload_file_size(b"x" * 100, 1) is None
+
+
+def test_size_over_cap_rejected_for_bytes():
+    content = b"x" * (2 * MB)
+    assert check_upload_file_size(content, 1) == UploadedFileTooLarge(size_bytes=len(content), limit_mb=1)
+
+
+def test_size_over_cap_rejected_for_binaryio_and_restores_caller_position():
+    """The handle is caller-owned; inspecting its size must not discard where the caller had it."""
+    content = b"x" * (2 * MB)
+    handle = io.BytesIO(content)
+    handle.seek(17)
+    assert check_upload_file_size(handle, 1) == UploadedFileTooLarge(size_bytes=len(content), limit_mb=1)
+    assert handle.tell() == 17
+
+
+def test_size_under_cap_allowed_for_binaryio_restores_caller_position():
+    handle = io.BytesIO(b"x" * 100)
+    handle.seek(42)
+    assert check_upload_file_size(handle, 1) is None
+    assert handle.tell() == 42
+
+
+def test_size_exactly_at_cap_allowed():
+    content = b"x" * MB
+    assert check_upload_file_size(content, 1) is None
+
+
+def test_no_cap_skips_size_check():
+    assert check_upload_file_size(b"x" * (10 * MB), None) is None
+
+
+@pytest.mark.parametrize("cap", [0, -3])
+def test_nonpositive_cap_disables_size_check(cap):
+    assert check_upload_file_size(b"x" * (10 * MB), cap) is None
+
+
+def test_blocked_extension_rejected():
+    assert check_blocked_extension("payload.exe", (".exe", ".sh")) == UploadedFileBlockedExtension(extension=".exe")
+
+
+def test_blocked_extension_match_is_case_insensitive():
+    assert check_blocked_extension("payload.EXE", (".exe",)) == UploadedFileBlockedExtension(extension=".exe")
+
+
+def test_blocked_extension_match_is_case_insensitive_for_configured_value():
+    """A config entry like blocked_file_extensions: ['.EXE'] must still catch a lowercase upload."""
+    assert check_blocked_extension("payload.exe", (".EXE",)) == UploadedFileBlockedExtension(extension=".exe")
+
+
+def test_extension_not_in_blocklist_allowed():
+    assert check_blocked_extension("report.pdf", (".exe", ".sh")) is None
+
+
+def test_empty_blocklist_allows_everything():
+    assert check_blocked_extension("payload.exe", ()) is None
+
+
+def test_no_filename_skips_extension_check():
+    assert check_blocked_extension(None, (".exe",)) is None
+
+
+def test_path_traversal_filename_rejected():
+    assert check_unsafe_filename("../../etc/passwd") == UploadedFileUnsafeFilename(filename="../../etc/passwd")
+
+
+def test_windows_style_path_traversal_filename_rejected():
+    assert check_unsafe_filename("..\\..\\windows\\system32\\config") == UploadedFileUnsafeFilename(
+        filename="..\\..\\windows\\system32\\config"
+    )
+
+
+def test_traversal_embedded_after_extension_rejected():
+    assert check_unsafe_filename("report.jsonl/../../etc/cron.d/evil") == UploadedFileUnsafeFilename(
+        filename="report.jsonl/../../etc/cron.d/evil"
+    )
+
+
+def test_null_byte_filename_rejected():
+    assert check_unsafe_filename("report.pdf\x00.exe") == UploadedFileUnsafeFilename(filename="report.pdf\x00.exe")
+
+
+@pytest.mark.parametrize("filename", ["report.pdf", ".env", "a.b.c.jsonl", "my file (1).csv", None])
+def test_ordinary_filenames_allowed(filename):
+    assert check_unsafe_filename(filename) is None
+
+
+@pytest.mark.parametrize(
+    "failure, expected_code, expected_fragments",
+    [
+        (
+            UploadedFileTooLarge(size_bytes=15728640, limit_mb=10),
+            "413",
+            ("15.0 MB", "max_file_size_mb", "10 MB", "not forwarded"),
+        ),
+        (
+            UploadedFileBlockedExtension(extension=".exe"),
+            "400",
+            (".exe", "blocked_file_extensions", "not forwarded"),
+        ),
+        (
+            UploadedFileUnsafeFilename(filename="../../etc/passwd"),
+            "400",
+            ("../../etc/passwd", "traversal", "not forwarded"),
+        ),
+    ],
+)
+def test_failures_map_to_openai_shaped_proxy_exceptions(failure, expected_code, expected_fragments):
+    with pytest.raises(ProxyException) as exc_info:
+        raise_upload_validation_failure(failure)
+    assert exc_info.value.code == expected_code
+    assert exc_info.value.type == "invalid_request_error"
+    assert exc_info.value.param == "file"
+    for fragment in expected_fragments:
+        assert fragment in exc_info.value.message
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py
index 09bab1dc416..1d4b0264879 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/test_llm_pass_through_endpoints.py
@@ -12,11 +12,13 @@ from unittest.mock import AsyncMock, MagicMock, Mock, patch
 import httpx
 import pytest
 from fastapi import HTTPException, Request, Response
+from fastapi.responses import StreamingResponse
 from fastapi.testclient import TestClient
 from starlette.datastructures import FormData
 
 
 import litellm
+from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
 from litellm.constants import LITELLM_PROXY_MASTER_KEY_ALIAS
 from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import (
     BaseOpenAIPassThroughHandler,
@@ -30,6 +32,7 @@ from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import (
     get_azure_ai_search_index_from_endpoint,
     get_vertex_base_url,
     is_azure_ai_search_service_level_index_create,
+    gigachat_proxy_route,
     llm_passthrough_factory_proxy_route,
     milvus_proxy_route,
     mistral_proxy_route,
@@ -178,7 +181,7 @@ class TestBaseOpenAIPassThroughHandler:
             assert result["api-key"] == "test_api_key"
             assert result["test-header"] == "value"
 
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.create_pass_through_route"
     )
     async def test_base_openai_pass_through_handler(self, mock_create_pass_through):
@@ -2022,15 +2025,15 @@ class TestLLMPassthroughFactoryProxyRoute:
 
 class TestVLLMProxyRoute:
     @pytest.mark.asyncio
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.get_request_body",
         return_value={"model": "router-model", "stream": False},
     )
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_passthrough_request_using_router_model",
         return_value=True,
     )
-    @patch("litellm.proxy.proxy_server.llm_router")
+    @patch("litellm.proxy.proxy_server.llm_router")  # test-quality-ok: patching litellm internal for unit test isolation
     async def test_vllm_proxy_route_with_router_model(
         self, mock_llm_router, mock_is_router, mock_get_body
     ):
@@ -2055,15 +2058,15 @@ class TestVLLMProxyRoute:
         mock_llm_router.allm_passthrough_route.assert_awaited_once()
 
     @pytest.mark.asyncio
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.get_request_body",
         return_value={"model": "other-model"},
     )
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_passthrough_request_using_router_model",
         return_value=False,
     )
-    @patch(
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
         "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.llm_passthrough_factory_proxy_route"
     )
     async def test_vllm_proxy_route_fallback_to_factory(
@@ -2085,6 +2088,312 @@ class TestVLLMProxyRoute:
         mock_factory_route.assert_awaited_once()
 
 
+class TestGigachatProxyRoute:
+    @pytest.mark.asyncio
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.get_request_body",
+        return_value={"model": "router-model", "stream": False},
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_passthrough_request_using_router_model",
+        return_value=True,
+    )
+    @patch("litellm.proxy.proxy_server.llm_router")  # test-quality-ok: patching litellm internal for unit test isolation
+    async def test_gigachat_proxy_route_with_router_model(
+        self, mock_llm_router, mock_is_router, mock_get_body
+    ):
+        mock_request = MagicMock(spec=Request)
+        mock_request.method = "POST"
+        mock_request.headers = {"content-type": "application/json"}
+        mock_request.query_params = {}
+        mock_fastapi_response = MagicMock(spec=Response)
+        mock_user_api_key_dict = MagicMock()
+        mock_llm_router.allm_passthrough_route = AsyncMock(
+            return_value=httpx.Response(200, json={"response": "success"})
+        )
+
+        result = await gigachat_proxy_route(
+            endpoint="/chat/completions",
+            request=mock_request,
+            fastapi_response=mock_fastapi_response,
+            user_api_key_dict=mock_user_api_key_dict,
+        )
+
+        mock_is_router.assert_called_once()
+        mock_llm_router.allm_passthrough_route.assert_awaited_once()
+        assert isinstance(result, Response)
+
+    @pytest.mark.asyncio
+    async def test_gigachat_router_handler_keeps_cached_body_and_payload_metadata_pristine(self):
+        """Regression: auth-metadata injection must not leak into the cached parsed body or the upstream payload."""
+        from litellm.proxy.common_utils.http_parsing_utils import get_request_body
+        from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import (
+            handle_gigachat_passthrough_router_model,
+        )
+
+        body = json.dumps(
+            {
+                "model": "gigachat-router",
+                "messages": [{"role": "user", "content": "hi"}],
+                "metadata": {"client_tag": "user-supplied"},
+            }
+        ).encode()
+        scope = {
+            "type": "http",
+            "method": "POST",
+            "headers": [(b"content-type", b"application/json")],
+            "query_string": b"",
+            "path": "/gigachat/chat/completions",
+        }
+
+        async def receive():
+            return {"type": "http.request", "body": body, "more_body": False}
+
+        request = Request(scope, receive)
+        request_body = await get_request_body(request)
+
+        captured: dict = {}
+
+        class _CapturingProcessor:
+            def __init__(self, data: dict):
+                captured["data"] = data
+
+            async def base_passthrough_process_llm_request(self, **kwargs):
+                return Response(content=b"{}", status_code=200)
+
+        with patch(  # test-quality-ok: patching litellm internal for unit test isolation
+            "litellm.proxy.common_request_processing.ProxyBaseLLMRequestProcessing",
+            _CapturingProcessor,
+        ):
+            await handle_gigachat_passthrough_router_model(
+                model="gigachat-router",
+                endpoint="/chat/completions",
+                request=request,
+                request_body=request_body,
+                fastapi_response=Response(),
+                llm_router=MagicMock(),
+                user_api_key_dict=UserAPIKeyAuth(user_id="user-1", team_id="team-1"),
+                proxy_logging_obj=MagicMock(),
+                general_settings={},
+                proxy_config=MagicMock(),
+                select_data_generator=MagicMock(),
+                user_model=None,
+                user_temperature=None,
+                user_request_timeout=None,
+                user_max_tokens=None,
+                user_api_base=None,
+                version=None,
+            )
+
+        data = captured["data"]
+        assert data["json"] is request_body
+        assert request_body["metadata"] == {"client_tag": "user-supplied"}
+        assert data["metadata"]["client_tag"] == "user-supplied"
+        assert data["metadata"]["user_api_key_user_id"] == "user-1"
+        assert data["metadata"]["user_api_key_team_id"] == "team-1"
+        cached_reread = await get_request_body(request)
+        assert cached_reread["metadata"] == {"client_tag": "user-supplied"}
+
+    @pytest.mark.asyncio
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.get_request_body",
+        return_value={"model": "other-model"},
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_passthrough_request_using_router_model",
+        return_value=False,
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_streaming_request_fn",
+        new_callable=AsyncMock,
+        return_value=False,
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.authenticator.get_access_token",
+        return_value="gigachat-test-token",
+    )
+    async def test_gigachat_proxy_route_fallback_forwards_to_gigachat_api(
+        self,
+        mock_get_token,
+        mock_is_streaming,
+        mock_is_router,
+        mock_get_body,
+        monkeypatch,
+    ):
+        monkeypatch.delenv("GIGACHAT_API_BASE", raising=False)
+        mock_request = MagicMock(spec=Request)
+        mock_fastapi_response = MagicMock(spec=Response)
+        mock_user_api_key_dict = MagicMock()
+
+        captured_kwargs = {}
+
+        async def fake_endpoint(request, fastapi_response, user_api_key_dict):
+            return Response(content=b'{"response": "success"}', status_code=200)
+
+        def fake_create_pass_through_route(**kwargs):
+            captured_kwargs.update(kwargs)
+            return fake_endpoint
+
+        with patch(  # test-quality-ok: patching litellm internal for unit test isolation
+            "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.create_pass_through_route",
+            side_effect=fake_create_pass_through_route,
+        ):
+            result = await gigachat_proxy_route(
+                endpoint="/chat/completions",
+                request=mock_request,
+                fastapi_response=mock_fastapi_response,
+                user_api_key_dict=mock_user_api_key_dict,
+            )
+
+        assert isinstance(result, Response)
+        assert result.status_code == 200
+        assert captured_kwargs["target"] == "https://gigachat.devices.sberbank.ru/api/v1/chat/completions"
+        assert captured_kwargs["custom_headers"] == {"Authorization": "Bearer gigachat-test-token"}
+
+    @pytest.mark.asyncio
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.get_request_body",
+        return_value={},
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.is_streaming_request_fn",
+        new_callable=AsyncMock,
+        return_value=False,
+    )
+    @patch(  # test-quality-ok: patching litellm internal for unit test isolation
+        "litellm.llms.gigachat.authenticator.get_access_token",
+        return_value="gigachat-test-token",
+    )
+    async def test_gigachat_proxy_route_models_endpoint_without_model(
+        self,
+        mock_get_token,
+        mock_is_streaming,
+        mock_get_body,
+        monkeypatch,
+    ):
+        monkeypatch.delenv("GIGACHAT_API_BASE", raising=False)
+        mock_request = MagicMock(spec=Request)
+        mock_fastapi_response = MagicMock(spec=Response)
+        mock_user_api_key_dict = MagicMock()
+
+        captured_kwargs = {}
+
+        async def fake_endpoint(request, fastapi_response, user_api_key_dict):
+            return Response(content=b'{"data": []}', status_code=200)
+
+        def fake_create_pass_through_route(**kwargs):
+            captured_kwargs.update(kwargs)
+            return fake_endpoint
+
+        with patch(  # test-quality-ok: patching litellm internal for unit test isolation
+            "litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints.create_pass_through_route",
+            side_effect=fake_create_pass_through_route,
+        ):
+            result = await gigachat_proxy_route(
+                endpoint="models",
+                request=mock_request,
+                fastapi_response=mock_fastapi_response,
+                user_api_key_dict=mock_user_api_key_dict,
+            )
+
+        assert isinstance(result, Response)
+        assert result.status_code == 200
+        assert captured_kwargs["target"] == "https://gigachat.devices.sberbank.ru/api/v1/models"
+        assert captured_kwargs["custom_headers"] == {"Authorization": "Bearer gigachat-test-token"}
+
+    @pytest.mark.asyncio
+    async def test_allm_passthrough_streaming_preserves_upstream_headers(self):
+        async def _stream() -> bytes:
+            yield b'data: {"id":"1"}\n\n'
+
+        class MockPassthroughStreamingResponse:
+            def __init__(self):
+                self.status_code = 201
+                self.headers = {
+                    "content-type": "text/event-stream; charset=utf-8",
+                    "x-request-id": "req-123",
+                    "x-ratelimit-remaining-requests": "77",
+                    "transfer-encoding": "chunked",
+                    "content-encoding": "gzip",
+                }
+                self._iterator = _stream()
+
+            def __aiter__(self):
+                return self
+
+            async def __anext__(self):
+                return await self._iterator.__anext__()
+
+        processor = ProxyBaseLLMRequestProcessing(
+            data={
+                "model": "some-provider/model",
+                "stream": True,
+                "litellm_call_id": "call-123",
+                "litellm_logging_obj": MagicMock(litellm_call_id="call-123"),
+            }
+        )
+
+        mock_request = MagicMock(spec=Request)
+        mock_request.headers = {"content-type": "application/json"}
+        mock_fastapi_response = MagicMock(spec=Response)
+        mock_user_api_key_dict = MagicMock()
+        mock_user_api_key_dict.allowed_model_region = ""
+        mock_user_api_key_dict.spend = 0.0
+        mock_proxy_logging_obj = MagicMock()
+        mock_proxy_logging_obj.during_call_hook = AsyncMock(return_value=None)
+        mock_proxy_logging_obj.update_request_status = AsyncMock(return_value=None)
+        mock_proxy_logging_obj.post_call_response_headers_hook = AsyncMock(
+            return_value={"x-test-callback-header": "callback-value"}
+        )
+
+        streaming_response = MockPassthroughStreamingResponse()
+
+        async def _fake_route_request(*args, **kwargs):
+            async def _inner():
+                return streaming_response
+
+            return _inner()
+
+        with patch.object(
+            processor,
+            "common_processing_pre_call_logic",
+            new=AsyncMock(
+                return_value=(
+                    processor.data,
+                    processor.data["litellm_logging_obj"],
+                )
+            ),
+        ), patch(  # test-quality-ok: patching litellm internal for unit test isolation
+            "litellm.proxy.common_request_processing.route_request",
+            new=_fake_route_request,
+        ), patch(  # test-quality-ok: patching litellm internal for unit test isolation
+            "litellm.proxy.common_request_processing.ProxyBaseLLMRequestProcessing.get_custom_headers",
+            return_value={"x-litellm-call-id": "call-123"},
+        ):
+            result = await processor.base_passthrough_process_llm_request(
+                request=mock_request,
+                fastapi_response=mock_fastapi_response,
+                user_api_key_dict=mock_user_api_key_dict,
+                proxy_logging_obj=mock_proxy_logging_obj,
+                general_settings={},
+                proxy_config=MagicMock(),
+                select_data_generator=MagicMock(),
+                llm_router=None,
+                model="some-provider/model",
+                version="test-version",
+            )
+
+        assert isinstance(result, StreamingResponse)
+        assert result.status_code == 201
+        assert result.headers["content-type"] == "text/event-stream; charset=utf-8"
+        assert result.headers["x-request-id"] == "req-123"
+        assert result.headers["x-ratelimit-remaining-requests"] == "77"
+        assert result.headers["x-litellm-call-id"] == "call-123"
+        assert result.headers["x-test-callback-header"] == "callback-value"
+        assert "transfer-encoding" not in result.headers
+        assert "content-encoding" not in result.headers
+
+
 class TestForwardHeaders:
     """
     Test cases for _forward_headers parameter in passthrough endpoints
@@ -4627,3 +4936,76 @@ class TestPassthroughRouterModelBudgetReservation:
         )
 
         self._assert_metadata_carries_attribution(captured, user_api_key_dict)
+
+
+class TestAzureRouterModelStreamingDispatch:
+    """
+    Regression: ``llm_router.allm_passthrough_route`` returns an awaited
+    ``AsyncPassthroughStreamingResponse`` for streaming calls, which is no
+    longer an async generator under ``inspect.isasyncgen``. The dispatch's
+    else branch therefore calls ``.aiter_bytes()`` / ``.status_code`` /
+    ``.headers`` on it. The router's ``set_response_headers`` also runs the
+    result through ``prepare_response_for_header_attachment``, which used to
+    wrap it in ``HiddenParamsAsyncIteratorWrapper`` (no ``aiter_bytes``), so
+    every streaming Azure router-model request 500'd with
+    ``AttributeError: aiter_bytes``; ``_hidden_params`` on the streaming
+    response keeps it unwrapped.
+    """
+
+    @pytest.mark.asyncio
+    async def test_azure_router_model_streaming_returns_streaming_response(self, monkeypatch):
+        import litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints as ep
+        import litellm.proxy.proxy_server as proxy_server
+        from litellm.passthrough.main import AsyncPassthroughStreamingResponse
+
+        upstream_body = b"data: hello\n\n"
+
+        async def _upstream_response() -> httpx.Response:
+            upstream_request = httpx.Request(
+                "POST",
+                "https://my-azure.openai.azure.com/openai/deployments/gpt-5/chat/completions",
+            )
+            return httpx.Response(
+                200,
+                headers={"content-type": "text/event-stream"},
+                content=upstream_body,
+                request=upstream_request,
+            )
+
+        logging_obj = MagicMock()
+        logging_obj.async_flush_passthrough_collected_chunks = AsyncMock()
+
+        from litellm.router_utils.add_retry_fallback_headers import prepare_response_for_header_attachment
+
+        class StreamingRouter:
+            async def allm_passthrough_route(self, **kwargs):
+                streaming_response = await AsyncPassthroughStreamingResponse(
+                    response=_upstream_response(),
+                    litellm_logging_obj=logging_obj,
+                    provider_config=MagicMock(),
+                )
+                return prepare_response_for_header_attachment(streaming_response)
+
+        async def fake_get_request_body(_request):
+            return {"model": "gpt-5", "stream": True}
+
+        monkeypatch.setattr(proxy_server, "llm_router", StreamingRouter())
+        monkeypatch.setattr(ep, "get_request_body", fake_get_request_body)
+        monkeypatch.setattr(ep, "is_passthrough_request_using_router_model", lambda *a, **k: True)
+
+        request = MagicMock(spec=Request)
+        request.method = "POST"
+        request.headers = {"content-type": "application/json"}
+        request.query_params = {}
+
+        result = await azure_proxy_route(
+            endpoint="openai/deployments/gpt-5/chat/completions",
+            request=request,
+            fastapi_response=MagicMock(spec=Response),
+            user_api_key_dict=UserAPIKeyAuth(api_key="hashed-token"),
+        )
+
+        assert isinstance(result, StreamingResponse)
+        assert result.status_code == 200
+        body = b"".join([chunk async for chunk in result.body_iterator])
+        assert body == upstream_body
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
index a3f56adb86f..d3f17c73499 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
@@ -2,6 +2,7 @@ import asyncio
 import json
 import logging
 import os
+from collections.abc import Callable
 from contextlib import ExitStack, contextmanager
 from io import BytesIO
 from types import SimpleNamespace
@@ -29,6 +30,7 @@ from litellm.proxy.pass_through_endpoints.pass_through_endpoints import (
     websocket_passthrough_request,
 )
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 from litellm.proxy._types import ProxyException, UserAPIKeyAuth
 from litellm.types.passthrough_endpoints.pass_through_endpoints import (
     LITELLM_PASS_THROUGH_RAW_BODY_STATE_KEY,
@@ -5462,3 +5464,269 @@ def test_the_marker_check_distinguishes_the_two_route_kinds():
     builtin = MagicMock(spec=Request)
     builtin.scope = {"endpoint": llm_passthrough_endpoints.anthropic_proxy_route}
     assert request_dispatched_to_pass_through_endpoint(builtin) is False
+
+
+async def _drive_passthrough_request_and_capture_logging(
+    user_api_key_dict: UserAPIKeyAuth,
+    on_pre_call: Callable[[LiteLLMLoggingObj | None], None] | None = None,
+) -> tuple[int, LiteLLMLoggingObj | None]:
+    import litellm
+    from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
+    from litellm.types.llms.custom_http import httpxSpecialProvider
+
+    def transport_handler(upstream_request: httpx.Request) -> httpx.Response:
+        return httpx.Response(200, json={"ok": True})
+
+    real_handler = get_async_httpx_client(
+        llm_provider=httpxSpecialProvider.PassThroughEndpoint,
+        params={"timeout": resolve_pass_through_request_timeout(None)},
+    )
+    cache_dict = litellm.in_memory_llm_clients_cache.cache_dict
+    cache_key = next((key for key, cached in cache_dict.items() if cached is real_handler), None)
+    assert cache_key is not None
+    cache_dict[cache_key] = SimpleNamespace(client=httpx.AsyncClient(transport=httpx.MockTransport(transport_handler)))
+
+    mock_request = MagicMock(spec=Request)
+    mock_request.method = "POST"
+    mock_request.headers = Headers({})
+    mock_request.query_params = QueryParams({})
+    mock_request.body = AsyncMock(return_value=b'{"model": "gemini-2.0-flash"}')
+
+    captured_data: dict = {}  # mutable-ok: the pre-call hook records the request data into it
+
+    async def capture_pre_call_hook(user_api_key_dict, data, call_type):
+        captured_data.update(data)
+        if on_pre_call is not None:
+            on_pre_call(data.get("litellm_logging_obj"))
+        return data
+
+    mock_proxy_logging = MagicMock()
+    mock_proxy_logging.pre_call_hook = AsyncMock(side_effect=capture_pre_call_hook)
+    mock_proxy_logging.post_call_failure_hook = AsyncMock()
+    mock_proxy_logging.post_call_response_headers_hook = AsyncMock(return_value={})
+    mock_proxy_logging.get_proxy_hook = MagicMock(return_value=None)
+
+    try:
+        with patch(  # test-quality-ok: proxy_logging_obj is a proxy_server module global read inside pass_through_request; there is no injection seam
+            "litellm.proxy.proxy_server.proxy_logging_obj", mock_proxy_logging
+        ):
+            response = await pass_through_request(
+                request=mock_request,
+                target="https://upstream.example.test/v1/generate",
+                custom_headers={},
+                user_api_key_dict=user_api_key_dict,
+            )
+    finally:
+        cache_dict[cache_key] = real_handler
+
+    return response.status_code, captured_data.get("litellm_logging_obj")
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_wires_team_callbacks():
+    """LIT-5152 regression: pass_through_request must resolve team-level logging
+    callbacks from key/team metadata and wire them into the Logging object, the
+    same way add_litellm_data_to_request does for normal LLM routes."""
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "logging": [
+                {
+                    "callback_name": "langfuse",
+                    "callback_type": "success_and_failure",
+                    "callback_vars": {
+                        "langfuse_public_key": "pk_test",
+                        "langfuse_secret_key": "sk_test",
+                        "langfuse_host": "https://langfuse.example.test",
+                    },
+                }
+            ]
+        },
+    )
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(user_api_key_dict)
+
+    assert status_code == 200
+    assert logging_obj is not None
+    assert logging_obj.dynamic_success_callbacks, "team success callbacks not wired into Logging"
+    assert logging_obj.dynamic_failure_callbacks, "team failure callbacks not wired into Logging"
+    assert logging_obj.standard_callback_dynamic_params.get("langfuse_public_key") == "pk_test"
+    assert logging_obj.standard_callback_dynamic_params.get("langfuse_secret_key") == "sk_test"
+    assert logging_obj.standard_callback_dynamic_params.get("langfuse_host") == "https://langfuse.example.test"
+    assert ("langfuse_public_key", "pk_test") in logging_obj._trusted_callback_vars
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_survives_malformed_team_logging_metadata():
+    """LIT-5152 fail-open: a malformed team ``logging`` value (here a non-iterable)
+    raises inside callback resolution; the passthrough request must still succeed,
+    just without dynamic callbacks."""
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={"logging": 5},
+    )
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(user_api_key_dict)
+
+    assert status_code == 200
+    assert logging_obj is not None
+    assert not logging_obj.dynamic_success_callbacks
+    assert not logging_obj.dynamic_failure_callbacks
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_survives_env_reference_in_deprecated_callback_settings():
+    """LIT-5152 fail-open: the deprecated ``callback_settings`` team metadata skips
+    AddTeamCallback validation, so an ``os.environ/`` callback var would otherwise
+    blow up inside ``Logging.__init__`` and fail the request; the passthrough must
+    instead succeed without dynamic callbacks."""
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "callback_settings": {
+                "success_callback": ["langfuse"],
+                "failure_callback": ["langfuse"],
+                "callback_vars": {
+                    "langfuse_public_key": "os.environ/LANGFUSE_PUBLIC_KEY",
+                    "langfuse_secret_key": "os.environ/LANGFUSE_SECRET_KEY",
+                    "langfuse_host": "https://langfuse.example.test",
+                },
+            }
+        },
+    )
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(user_api_key_dict)
+
+    assert status_code == 200
+    assert logging_obj is not None
+    assert not logging_obj.dynamic_success_callbacks
+    assert not logging_obj.dynamic_failure_callbacks
+    assert not logging_obj.standard_callback_dynamic_params.get("langfuse_public_key")
+
+
+@pytest.mark.asyncio
+async def test_resolve_team_callback_wiring_fails_open_on_operational_error():
+    """LIT-5152 fail-open: an operational error while resolving callback metadata
+    (e.g. team config lookup hitting a dead secret manager) must not raise; the
+    request proceeds without dynamic callbacks and the error is logged."""
+    from litellm.proxy.pass_through_endpoints.pass_through_endpoints import (
+        _resolve_team_callback_wiring,
+    )
+    from litellm.proxy.proxy_server import ProxyConfig
+
+    class RaisingTeamConfig(ProxyConfig):
+        def load_team_config(self, team_id: str) -> dict:
+            raise RuntimeError("secret manager unavailable")
+
+    wiring = _resolve_team_callback_wiring(
+        user_api_key_dict=UserAPIKeyAuth(api_key="test-key", team_id="test-team"),
+        proxy_config=RaisingTeamConfig(),
+        route_description="pass_through_endpoint",
+    )
+
+    assert wiring.success_callbacks is None
+    assert wiring.failure_callbacks is None
+    assert wiring.logging_kwargs is None
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_leaves_guardrail_readable_metadata():
+    """A pre-call guardrail reads the request headers off the passthrough logging
+    params without raising."""
+    from litellm.proxy.guardrails.guardrail_hooks.hiddenlayer.hiddenlayer import (
+        _logged_request_headers,
+    )
+
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "logging": [
+                {
+                    "callback_name": "langfuse",
+                    "callback_type": "success_and_failure",
+                    "callback_vars": {
+                        "langfuse_public_key": "pk_test",
+                        "langfuse_secret_key": "sk_test",
+                    },
+                }
+            ]
+        },
+    )
+
+    observed: dict[str, dict[str, str] | BaseException] = {}  # mutable-ok: the pre-call hook records into it
+
+    def read_headers_the_way_a_guardrail_does(logging_obj: LiteLLMLoggingObj | None) -> None:
+        assert logging_obj is not None
+        try:
+            observed["headers"] = _logged_request_headers(logging_obj)
+        except Exception as exc:  # noqa: BLE001 - the regression is that this used to raise
+            observed["headers"] = exc
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(
+        user_api_key_dict, on_pre_call=read_headers_the_way_a_guardrail_does
+    )
+
+    assert "headers" in observed, "the pre-call hook never ran, so nothing was observed"
+    assert observed["headers"] == {}, f"guardrail header read failed: {observed['headers']!r}"
+    assert status_code == 200
+    assert logging_obj is not None
+    assert logging_obj.dynamic_success_callbacks, "team success callbacks must stay wired"
+    assert logging_obj.standard_callback_dynamic_params.get("langfuse_public_key") == "pk_test"
+
+
+@pytest.mark.asyncio
+async def test_pass_through_request_leaves_cost_router_logger_working():
+    """The cost router's logger reads the deployment id off the passthrough logging
+    params without raising. least_busy shares the read but swallows the exception,
+    so this is the strategy where the break is observable."""
+    from litellm._logging import verbose_logger
+    from litellm.caching.caching import DualCache
+    from litellm.router_strategy.lowest_cost import LowestCostLoggingHandler
+
+    handler = LowestCostLoggingHandler(router_cache=DualCache())
+
+    user_api_key_dict = UserAPIKeyAuth(
+        api_key="test-key",
+        team_id="test-team",
+        team_metadata={
+            "logging": [
+                {
+                    "callback_name": "langfuse",
+                    "callback_type": "success_and_failure",
+                    "callback_vars": {
+                        "langfuse_public_key": "pk_test",
+                        "langfuse_secret_key": "sk_test",
+                    },
+                }
+            ]
+        },
+    )
+
+    status_code, logging_obj = await _drive_passthrough_request_and_capture_logging(user_api_key_dict)
+    assert status_code == 200
+    assert logging_obj is not None
+
+    raised: list[logging.LogRecord] = []  # mutable-ok: logging.Handler records into it
+
+    class _RecordTracebacks(logging.Handler):
+        def emit(self, record: logging.LogRecord) -> None:
+            if record.exc_info is not None:
+                raised.append(record)
+
+    recorder = _RecordTracebacks()
+    verbose_logger.addHandler(recorder)
+    try:
+        await handler.async_log_success_event(
+            kwargs=logging_obj.model_call_details,
+            response_obj=None,
+            start_time=None,
+            end_time=None,
+        )
+    finally:
+        verbose_logger.removeHandler(recorder)
+
+    assert not raised, f"cost router logger raised on the passthrough logging params: {raised[0].exc_info}"
diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_streaming_handler_interrupt.py b/tests/test_litellm/proxy/pass_through_endpoints/test_streaming_handler_interrupt.py
index 1d82a5dfc6e..56c89fed79a 100644
--- a/tests/test_litellm/proxy/pass_through_endpoints/test_streaming_handler_interrupt.py
+++ b/tests/test_litellm/proxy/pass_through_endpoints/test_streaming_handler_interrupt.py
@@ -28,12 +28,21 @@ def _make_streaming_response(chunks):
     return mock
 
 
+def _unarmed_logging_obj():
+    """Real Logging objects only carry _on_deferred_stream_complete when the
+    proxy arms deferred dispatch; a bare MagicMock's auto-attribute is truthy
+    and would spuriously trigger the deferral branch."""
+    obj = MagicMock()
+    obj._on_deferred_stream_complete = None
+    return obj
+
+
 @pytest.mark.asyncio
 async def test_chunk_processor_logs_on_normal_completion():
     chunks = [b"chunk-1", b"chunk-2", b"chunk-3"]
     response = _make_streaming_response(chunks)
 
-    mock_logging_obj = MagicMock()
+    mock_logging_obj = _unarmed_logging_obj()
     mock_passthrough_handler = MagicMock()
 
     with patch.object(
@@ -66,7 +75,7 @@ async def test_chunk_processor_logs_on_client_disconnect():
     chunks = [b"event-1", b"event-2", b"event-3"]
     response = _make_streaming_response(chunks)
 
-    mock_logging_obj = MagicMock()
+    mock_logging_obj = _unarmed_logging_obj()
     mock_passthrough_handler = MagicMock()
 
     with patch.object(
@@ -104,7 +113,7 @@ async def test_chunk_processor_does_not_schedule_success_logging_for_upstream_er
     response = _make_streaming_response(chunks)
     response.status_code = 403
 
-    mock_logging_obj = MagicMock()
+    mock_logging_obj = _unarmed_logging_obj()
     mock_passthrough_handler = MagicMock()
 
     with patch.object(
@@ -134,7 +143,7 @@ async def test_chunk_processor_does_not_schedule_success_logging_for_upstream_er
 async def test_chunk_processor_does_not_schedule_logging_when_no_chunks():
     response = _make_streaming_response([])
 
-    mock_logging_obj = MagicMock()
+    mock_logging_obj = _unarmed_logging_obj()
     mock_passthrough_handler = MagicMock()
 
     with patch.object(
@@ -189,7 +198,7 @@ async def test_chunk_processor_routes_logging_through_logging_worker():
         async for chunk in PassThroughStreamingHandler.chunk_processor(
             response=response,
             request_body={"model": "claude-3-haiku"},
-            litellm_logging_obj=MagicMock(),
+            litellm_logging_obj=_unarmed_logging_obj(),
             endpoint_type=EndpointType.GENERIC,
             start_time=datetime.now(),
             passthrough_success_handler_obj=MagicMock(),
@@ -230,7 +239,7 @@ async def test_chunk_processor_routes_logging_through_logging_worker_on_disconne
         gen = PassThroughStreamingHandler.chunk_processor(
             response=response,
             request_body={"model": "claude-3-haiku"},
-            litellm_logging_obj=MagicMock(),
+            litellm_logging_obj=_unarmed_logging_obj(),
             endpoint_type=EndpointType.GENERIC,
             start_time=datetime.now(),
             passthrough_success_handler_obj=MagicMock(),
@@ -246,7 +255,7 @@ async def test_chunk_processor_routes_logging_through_logging_worker_on_disconne
 def _logging_obj_with_write_once_cst():
     """Build a MagicMock that mirrors the real Logging behavior: _update_completion_start_time
     latches self.completion_start_time so the write-once guard actually latches."""
-    obj = MagicMock()
+    obj = _unarmed_logging_obj()
     obj.completion_start_time = None
 
     def _update(*, completion_start_time):
@@ -301,7 +310,7 @@ async def test_chunk_processor_does_not_reset_completion_start_time_on_later_chu
     response = _make_streaming_response(chunks)
 
     real_first = datetime(2020, 1, 1, 0, 0, 0)
-    mock_logging_obj = MagicMock()
+    mock_logging_obj = _unarmed_logging_obj()
     # Simulate first-chunk stamp having already landed (e.g. under contention or a
     # prior wrapper that already set it): later chunks must be no-ops.
     mock_logging_obj.completion_start_time = real_first
@@ -387,7 +396,7 @@ async def _collect_openai_passthrough_chunks(chunks, endpoint_type):
     async for chunk in PassThroughStreamingHandler.chunk_processor(
         response=response,
         request_body={"model": "gpt-4o-mini", "stream": True},
-        litellm_logging_obj=MagicMock(),
+        litellm_logging_obj=_unarmed_logging_obj(),
         endpoint_type=endpoint_type,
         start_time=datetime.now(),
         passthrough_success_handler_obj=MagicMock(),
@@ -517,3 +526,109 @@ def test_convert_raw_bytes_survives_truncated_multibyte_sequence():
     lines = PassThroughStreamingHandler._convert_raw_bytes_to_str_lines(raw_bytes)
 
     assert any('"type": "message_delta"' in line for line in lines)
+
+
+@pytest.mark.asyncio
+async def test_chunk_processor_defers_logging_until_fire_when_armed():
+    """Regression for PR #38722: native /v1/messages streams route through
+    chunk_processor, which enqueued the spend log the moment the stream ended,
+    racing the guardrail end-of-stream scan and logging
+    guardrail_information as null. With deferred dispatch armed, the completed
+    stream must park the logging coroutine on logging_obj and only enqueue it
+    when ProxyLogging._fire_deferred_stream_logging fires after the scan."""
+    from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
+    from litellm.proxy.utils import ProxyLogging
+
+    chunks = [b"event-1", b"event-2"]
+    response = _make_streaming_response(chunks)
+
+    logging_obj = _unarmed_logging_obj()
+    logging_obj._deferred_stream_complete_args = None
+
+    enqueued = []
+
+    def _capture(async_coroutine):
+        enqueued.append(async_coroutine)
+        async_coroutine.close()
+
+    with patch.object(  # test-quality-ok: GLOBAL_LOGGING_WORKER is a process-global singleton with no injection seam
+        GLOBAL_LOGGING_WORKER,
+        "ensure_initialized_and_enqueue",
+        side_effect=_capture,
+    ) as mock_enqueue:
+        gen = PassThroughStreamingHandler.chunk_processor(
+            response=response,
+            request_body={"model": "claude-3-haiku"},
+            litellm_logging_obj=logging_obj,
+            endpoint_type=EndpointType.ANTHROPIC,
+            start_time=datetime.now(),
+            passthrough_success_handler_obj=MagicMock(),
+            url_route="/v1/messages",
+            route_streaming_logging=AsyncMock(),
+        )
+        ProxyBaseLLMRequestProcessing(data={})._arm_deferred_stream_dispatch(
+            response=gen,
+            route_type="anthropic_messages",
+            user_api_key_dict=MagicMock(),
+            logging_obj=logging_obj,
+        )
+
+        received = []
+        async for chunk in gen:
+            received.append(chunk)
+        await asyncio.sleep(0)
+
+        assert received == chunks
+        mock_enqueue.assert_not_called()
+        parked = logging_obj._deferred_stream_complete_args
+        assert isinstance(parked, tuple) and len(parked) == 1
+        assert asyncio.iscoroutine(parked[0])
+
+        ProxyLogging._fire_deferred_stream_logging({"litellm_logging_obj": logging_obj})
+        await asyncio.sleep(0)
+
+        mock_enqueue.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_chunk_processor_enqueues_immediately_on_disconnect_even_when_armed():
+    """Client disconnects never reach _fire_deferred_stream_logging, so parking
+    the coroutine there would lose the partial-usage spend log (LIT-2642); the
+    disconnect path must keep enqueueing immediately."""
+    chunks = [b"event-1", b"event-2", b"event-3"]
+    response = _make_streaming_response(chunks)
+
+    logging_obj = _unarmed_logging_obj()
+
+    async def _armed_closure(logging_coroutine):
+        raise AssertionError("deferred closure must not fire on disconnect")
+
+    logging_obj._on_deferred_stream_complete = _armed_closure
+    logging_obj._deferred_stream_complete_args = None
+
+    enqueued = []
+
+    def _capture(async_coroutine):
+        enqueued.append(async_coroutine)
+        async_coroutine.close()
+
+    with patch.object(  # test-quality-ok: GLOBAL_LOGGING_WORKER is a process-global singleton with no injection seam
+        GLOBAL_LOGGING_WORKER,
+        "ensure_initialized_and_enqueue",
+        side_effect=_capture,
+    ) as mock_enqueue:
+        gen = PassThroughStreamingHandler.chunk_processor(
+            response=response,
+            request_body={"model": "claude-3-haiku"},
+            litellm_logging_obj=logging_obj,
+            endpoint_type=EndpointType.ANTHROPIC,
+            start_time=datetime.now(),
+            passthrough_success_handler_obj=MagicMock(),
+            url_route="/v1/messages",
+            route_streaming_logging=AsyncMock(),
+        )
+        await gen.__anext__()
+        await gen.aclose()
+
+    mock_enqueue.assert_called_once()
+    assert logging_obj._deferred_stream_complete_args is None
diff --git a/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py b/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py
index 054a5af4148..4fcb7d22588 100644
--- a/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py
+++ b/tests/test_litellm/proxy/policy_engine/test_pipeline_executor.py
@@ -749,6 +749,106 @@ async def test_single_step_pipeline_allow(monkeypatch):
     assert guard.calls == 1
 
 
+@pytest.mark.asyncio
+async def test_allow_restores_independent_guardrails_list(monkeypatch):
+    """
+    Request activates an independent guardrail; an unrelated pipeline runs and allows.
+    Expected: no modified_data escapes, so the request's guardrails list survives
+    and the independent guardrail still runs at later lifecycle stages (post_call).
+    Regression: LIT-6587 (pipeline clobbered the list with its last step's guardrail).
+    """
+    pipeline_guard = AlwaysPassGuardrail(guardrail_name="input-scan")
+
+    pipeline = GuardrailPipeline(
+        mode="pre_call",
+        steps=[PipelineStep(guardrail="input-scan", on_fail="block", on_pass="allow")],
+    )
+
+    monkeypatch.setattr(litellm, "callbacks", [pipeline_guard])
+
+    data = {
+        "messages": [{"role": "user", "content": "clean content"}],
+        "metadata": {"guardrails": ["independent-output-guard"]},
+    }
+    result = await PipelineExecutor.execute_steps(
+        steps=pipeline.steps,
+        mode=pipeline.mode,
+        data=data,
+        user_api_key_dict=MagicMock(),
+        call_type="completion",
+        policy_name="input-pipeline-policy",
+    )
+
+    assert pipeline_guard.calls == 1
+    assert result.terminal_action == "allow"
+    propagated = result.modified_data or data
+    assert propagated["metadata"]["guardrails"] == ["independent-output-guard"]
+    assert data["metadata"]["guardrails"] == ["independent-output-guard"]
+
+
+@pytest.mark.asyncio
+async def test_allow_does_not_leak_guardrails_into_bare_request(monkeypatch):
+    """A request without metadata must not gain a metadata.guardrails list from the pipeline."""
+    pipeline_guard = AlwaysPassGuardrail(guardrail_name="input-scan")
+
+    pipeline = GuardrailPipeline(
+        mode="pre_call",
+        steps=[PipelineStep(guardrail="input-scan", on_fail="block", on_pass="allow")],
+    )
+
+    monkeypatch.setattr(litellm, "callbacks", [pipeline_guard])
+
+    data = {"messages": [{"role": "user", "content": "clean content"}]}
+    result = await PipelineExecutor.execute_steps(
+        steps=pipeline.steps,
+        mode=pipeline.mode,
+        data=data,
+        user_api_key_dict=MagicMock(),
+        call_type="completion",
+        policy_name="input-pipeline-policy",
+    )
+
+    assert result.terminal_action == "allow"
+    propagated = result.modified_data or data
+    assert "guardrails" not in propagated.get("metadata", {})
+    assert "metadata" not in data
+
+
+@pytest.mark.asyncio
+async def test_data_forwarding_keeps_changes_and_restores_guardrails_list(monkeypatch):
+    """A pass_data pipeline's modifications propagate while the request's guardrails list is restored."""
+    pii_guard = PiiMaskingGuardrail(guardrail_name="pii-masker")
+    content_guard = ContentCheckGuardrail(guardrail_name="content-check")
+
+    pipeline = GuardrailPipeline(
+        mode="pre_call",
+        steps=[
+            PipelineStep(guardrail="pii-masker", on_fail="block", on_pass="next", pass_data=True),
+            PipelineStep(guardrail="content-check", on_fail="block", on_pass="allow"),
+        ],
+    )
+
+    monkeypatch.setattr(litellm, "callbacks", [pii_guard, content_guard])
+
+    data = {
+        "messages": [{"role": "user", "content": "Hello John Smith"}],
+        "metadata": {"guardrails": ["independent-output-guard"]},
+    }
+    result = await PipelineExecutor.execute_steps(
+        steps=pipeline.steps,
+        mode=pipeline.mode,
+        data=data,
+        user_api_key_dict=MagicMock(),
+        call_type="completion",
+        policy_name="pii-then-safety",
+    )
+
+    assert result.terminal_action == "allow"
+    assert result.modified_data is not None
+    assert result.modified_data["messages"][0]["content"] == "Hello [REDACTED]"
+    assert result.modified_data["metadata"]["guardrails"] == ["independent-output-guard"]
+
+
 @pytest.mark.asyncio
 async def test_step_results_include_duration(monkeypatch):
     """Step results should include timing information."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_audio.py b/tests/test_litellm/proxy/proxy_server/test_routes_audio.py
index 74542a3eaf6..de76c7257cf 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_audio.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_audio.py
@@ -12,13 +12,16 @@ from __future__ import annotations
 import io
 from unittest.mock import AsyncMock, MagicMock
 
+import httpx
 import pytest
 
 from litellm.proxy import proxy_server
+from litellm.types.llms.openai import HttpxBinaryResponseContent
 
 
 @pytest.fixture
-def patched_speech(monkeypatch):
+def patched_speech(monkeypatch, request):
+    upstream_content_type = getattr(request, "param", "audio/mpeg")
     monkeypatch.setattr(proxy_server, "llm_router", MagicMock())
     monkeypatch.setattr(
         proxy_server,
@@ -36,15 +39,14 @@ def patched_speech(monkeypatch):
 
     monkeypatch.setattr(proxy_server, "add_litellm_data_to_request", _add_data)
 
-    class _FakeBinaryResp:
-        async def aiter_bytes(self, chunk_size: int = 8192):
-            async def _gen():
-                yield b"\x00\x01\x02"
-
-            return _gen()
-
     async def _llm_call():
-        return _FakeBinaryResp()
+        return HttpxBinaryResponseContent(
+            httpx.Response(
+                status_code=200,
+                headers={} if upstream_content_type is None else {"content-type": upstream_content_type},
+                content=b"\x00\x01\x02",
+            )
+        )
 
     async def _fake_route_request(*args, **kwargs):
         return _llm_call()
@@ -79,6 +81,24 @@ def patched_speech_error(monkeypatch):
     yield
 
 
+@pytest.fixture
+def patched_speech_provider_rejection(monkeypatch, patched_speech_error):
+    import litellm
+
+    async def _raise(*args, **kwargs):
+        raise litellm.BadRequestError(
+            message=(
+                "Gemini TTS only produces raw PCM16 audio, so response_format='mp3' is not supported."
+                " Supported response formats: pcm, wav."
+            ),
+            model="gemini-3.1-flash-tts-preview",
+            llm_provider="gemini",
+        )
+
+    monkeypatch.setattr(proxy_server, "route_request", _raise)
+    yield
+
+
 @pytest.fixture
 def patched_transcription(monkeypatch):
     router = MagicMock()
@@ -152,6 +172,35 @@ def test_audio_speech_happy_path(client, auth_as, patched_speech, path):
     }
 
 
+@pytest.mark.parametrize(
+    ("patched_speech", "response_format", "expected_content_type"),
+    [
+        ("audio/wav", "wav", "audio/wav"),
+        ("audio/flac", "flac", "audio/flac"),
+        ("audio/pcm", "pcm", "audio/pcm"),
+        ("audio/wav", "mp3", "audio/wav"),
+        ("application/json", "flac", "audio/flac"),
+        (None, "wav", "audio/wav"),
+        (None, None, "audio/mpeg"),
+    ],
+    indirect=["patched_speech"],
+)
+def test_audio_speech_content_type_matches_audio_format(
+    client, auth_as, patched_speech, response_format, expected_content_type
+):
+    """Regression for LIT-6482: /v1/audio/speech mislabeled wav/flac/pcm as audio/mpeg."""
+    payload = {
+        "model": "tts-1",
+        "input": "Hi",
+        "voice": "alloy",
+        **({} if response_format is None else {"response_format": response_format}),
+    }
+    with auth_as():
+        response = client.post("/v1/audio/speech", json=payload)
+    assert response.status_code == 200
+    assert response.headers.get("content-type", "").split(";")[0] == expected_content_type
+
+
 @pytest.mark.parametrize("path", ["/v1/audio/speech", "/audio/speech"])
 def test_audio_speech_error(client, auth_as, patched_speech_error, path):
     """Pins ``POST /v1/audio/speech`` and ``POST /audio/speech`` (error)."""
@@ -162,6 +211,18 @@ def test_audio_speech_error(client, auth_as, patched_speech_error, path):
     assert len(response.content) > 0
 
 
+def test_audio_speech_bad_request_maps_to_400(client, auth_as, patched_speech_provider_rejection):
+    """Regression for LIT-6501: a BadRequestError from the speech path surfaced as a generic 500."""
+    payload = {"model": "gemini-tts", "input": "Hi", "voice": "Kore", "response_format": "mp3"}
+    with auth_as():
+        response = client.post("/v1/audio/speech", json=payload)
+    assert response.status_code == 400
+    error = response.json()["error"]
+    assert "response_format='mp3'" in error["message"]
+    assert "pcm" in error["message"]
+    assert "wav" in error["message"]
+
+
 @pytest.mark.parametrize("path", ["/v1/audio/transcriptions", "/audio/transcriptions"])
 def test_audio_transcription_happy_path(client, auth_as, patched_transcription, path):
     """Pins ``POST /v1/audio/transcriptions`` / ``POST /audio/transcriptions`` (happy)."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_config.py b/tests/test_litellm/proxy/proxy_server/test_routes_config.py
index ad3c470acf3..dcb63b8ca82 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_config.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_config.py
@@ -60,6 +60,141 @@ def test_config_update_happy_admin(client, auth_as, mock_prisma, monkeypatch):
     assert normalize(response.json()) == {"message": "Config updated successfully"}
 
 
+def test_config_update_persists_optional_pre_call_checks(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_pre_call_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["optional_pre_call_checks"] == ["prompt_caching"]
+
+
+def test_config_update_persists_model_group_affinity_config(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    model_group_affinity_config = {"gpt-4": ["session_affinity"]}
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"model_group_affinity_config": model_group_affinity_config}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["model_group_affinity_config"] == model_group_affinity_config
+
+
+def test_config_update_persists_disable_cooldowns(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+    fake_proxy_config = MagicMock()
+    fake_proxy_config.add_deployment = AsyncMock()
+    monkeypatch.setattr(ps, "proxy_config", fake_proxy_config)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"disable_cooldowns": True}},
+        )
+
+    assert response.status_code == 200
+    persisted = json.loads(table.upsert.call_args.kwargs["data"]["create"]["param_value"])
+    assert persisted["disable_cooldowns"] is True
+
+
+def test_config_update_rejects_assistants_config(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"assistants_config": {"enabled": True}}},
+        )
+
+    assert response.status_code == 400
+    assert "assistants_config" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_rejects_router_general_settings(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"router_general_settings": {"async_only_mode": True}}},
+        )
+
+    assert response.status_code == 400
+    assert "router_general_settings" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_rejects_unknown_router_setting(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    table = _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.PROXY_ADMIN):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_precall_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 400
+    assert "optional_precall_checks" in response.json()["error"]["message"]
+    table.upsert.assert_not_called()
+
+
+def test_config_update_unknown_router_setting_non_admin_forbidden(client, auth_as, mock_prisma, monkeypatch):
+    from litellm.proxy import proxy_server as ps
+    from litellm.proxy._types import LitellmUserRoles
+
+    _install_litellm_config(mock_prisma)
+    monkeypatch.setattr(ps, "prisma_client", mock_prisma)
+
+    with auth_as(LitellmUserRoles.INTERNAL_USER):
+        response = client.post(
+            "/config/update",
+            json={"router_settings": {"optional_precall_checks": ["prompt_caching"]}},
+        )
+
+    assert response.status_code == 403
+    assert "admin" in response.json()["error"]["message"].lower()
+
+
 def test_config_update_non_admin_forbidden(client, auth_as, mock_prisma, monkeypatch):
     """POST /config/update by a non-admin caller is rejected; the error
     surfaces as a ProxyException with the admin-only message."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py b/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py
index af37dbe85fe..45460dcecf1 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py
@@ -29,7 +29,7 @@ def _install_login_mocks(monkeypatch, raise_on_auth: bool = False) -> None:
     """
     from litellm.proxy import proxy_server as ps
 
-    async def _fake_auth(username, password, master_key, prisma_client):
+    async def _fake_auth(username, password, master_key, prisma_client, general_settings=None):
         if raise_on_auth:
             raise Exception("boom-auth-failure")
         fake = MagicMock()
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_models.py b/tests/test_litellm/proxy/proxy_server/test_routes_models.py
index 2b126b1ea95..bc6106a06f8 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_models.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_models.py
@@ -45,6 +45,7 @@ def patched_models(monkeypatch):
     deployment = MagicMock()
     deployment.litellm_params.model = "gpt-4"
     router.get_deployment_by_model_group_name = MagicMock(return_value=deployment)
+    router.get_configured_display_name = MagicMock(return_value=None)
 
     monkeypatch.setattr(proxy_server, "llm_router", router)
     monkeypatch.setattr(proxy_server, "prisma_client", MagicMock())
@@ -187,6 +188,83 @@ def test_anthropic_format_carries_router_configured_token_limits(client, auth_as
     assert (claude["max_input_tokens"], claude["max_tokens"]) == (500000, 4096)
 
 
+@pytest.mark.parametrize("path", ["/v1/models", "/models"])
+def test_anthropic_format_uses_configured_display_name(client, auth_as, patched_models, path):
+    """A deployment's ``model_info.display_name`` becomes the Anthropic-native
+    ``display_name`` so Claude Code's picker shows a clean name while the id keeps
+    routing; models without one keep the id fallback, and the OpenAI-shaped
+    listing carries no display_name either way."""
+
+    def _configured(model_name):
+        return "Kimi K3" if model_name == "gpt-4" else None
+
+    patched_models.get_configured_display_name = MagicMock(side_effect=_configured)
+
+    with auth_as():
+        anthropic_response = client.get(path, headers={"anthropic-version": "2023-06-01"})
+        openai_response = client.get(path)
+
+    assert anthropic_response.status_code == 200
+    gpt_4, claude = anthropic_response.json()["data"]
+    assert (gpt_4["id"], gpt_4["display_name"]) == ("gpt-4", "Kimi K3")
+    assert (claude["id"], claude["display_name"]) == ("claude-sonnet", "claude-sonnet")
+
+    assert openai_response.status_code == 200
+    openai_models = openai_response.json()["data"]
+    assert [m["id"] for m in openai_models] == ["gpt-4", "claude-sonnet"]
+    assert all("display_name" not in m for m in openai_models)
+
+
+@pytest.mark.parametrize("params", [{}, {"scope": "expand"}])
+def test_anthropic_display_name_resolved_via_internal_team_key(
+    client, auth_as, patched_models, monkeypatch, params
+):
+    """For a team-scoped row the configured display name must be looked up by the
+    internal routing key while the entry itself is keyed by the public name, so
+    the clean name lands on the id the client actually sees."""
+    from litellm.proxy import utils as proxy_utils
+    from litellm.proxy.auth import model_checks
+
+    internal_name = "model_name_team-1_c0ffee"
+
+    patched_models.get_model_list = MagicMock(
+        return_value=[
+            {
+                "model_name": internal_name,
+                "model_info": {
+                    "team_id": "team-1",
+                    "team_public_model_name": "gpt-4-team",
+                },
+            }
+        ]
+    )
+    patched_models.get_model_names = MagicMock(return_value=[internal_name])
+    patched_models.get_configured_display_name = MagicMock(
+        side_effect=lambda model_name: "Team GPT" if model_name == internal_name else None
+    )
+
+    async def _fake_get_available_models_for_user(**kwargs):
+        return [internal_name]
+
+    monkeypatch.setattr(
+        proxy_utils,
+        "get_available_models_for_user",
+        _fake_get_available_models_for_user,
+    )
+    monkeypatch.setattr(
+        model_checks, "get_complete_model_list", lambda **kwargs: [internal_name]
+    )
+
+    with auth_as():
+        response = client.get(
+            "/v1/models", params=params, headers={"anthropic-version": "2023-06-01"}
+        )
+
+    assert response.status_code == 200
+    (entry,) = response.json()["data"]
+    assert (entry["id"], entry["display_name"]) == ("gpt-4-team", "Team GPT")
+
+
 @pytest.mark.parametrize("path", ["/v1/models", "/models"])
 def test_get_models_invalid_scope_returns_400(client, auth_as, patched_models, path):
     """Pins: ``GET /v1/models``, ``GET /models`` (error path: invalid scope)."""
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_onboarding.py b/tests/test_litellm/proxy/proxy_server/test_routes_onboarding.py
index 5cc22cca7a0..778acc1baab 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_onboarding.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_onboarding.py
@@ -234,7 +234,7 @@ def test_claim_onboarding_link_happy(client, monkeypatch, mock_prisma):
         json={
             "invitation_link": "inv-123",
             "user_id": "user-abc",
-            "password": "hunter2",
+            "password": "Hunter2Strong!",
         },
         headers={"Authorization": f"Bearer {onboarding_jwt}"},
     )
@@ -260,7 +260,7 @@ def test_claim_onboarding_link_invalid_invite_401(client, monkeypatch, mock_pris
         json={
             "invitation_link": "missing",
             "user_id": "user-abc",
-            "password": "hunter2",
+            "password": "Hunter2Strong!",
         },
         headers={"Authorization": "Bearer irrelevant"},
     )
@@ -287,7 +287,7 @@ def test_claim_onboarding_link_user_id_mismatch_401(
         json={
             "invitation_link": "inv-123",
             "user_id": "user-attacker",
-            "password": "hunter2",
+            "password": "Hunter2Strong!",
         },
         headers={"Authorization": "Bearer irrelevant"},
     )
@@ -339,7 +339,7 @@ def test_claim_onboarding_link_bad_onboarding_jwt_401(
         json={
             "invitation_link": "inv-123",
             "user_id": "user-abc",
-            "password": "hunter2",
+            "password": "Hunter2Strong!",
         },
         headers={"Authorization": f"Bearer {bogus_jwt}"},
     )
diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
index 35b5c72f92e..1e1436fcef8 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -9,12 +9,13 @@ Pins (PR2):
 from __future__ import annotations
 
 import asyncio
-from unittest.mock import AsyncMock, MagicMock
+import json
 
 import pytest
 
 import litellm
 from litellm.proxy import proxy_server
+from litellm.router_utils import pattern_match_deployments
 
 from .conftest import normalize  # type: ignore[import-not-found]
 
@@ -99,6 +100,7 @@ def test_token_counter_missing_input_returns_400(
 
 @pytest.fixture
 def patched_supported_params(monkeypatch):
+    monkeypatch.setattr(proxy_server, "llm_router", None)
     monkeypatch.setattr(
         litellm,
         "get_llm_provider",
@@ -124,12 +126,104 @@ def test_supported_openai_params_happy_path(client, auth_as, patched_supported_p
     }
 
 
+def test_supported_openai_params_resolves_router_alias(client, auth_as, monkeypatch):
+    """A router alias absent from the cost map resolves through the deployment's underlying model."""
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "claude-opus-4-6-cached",
+                "litellm_params": {"model": "anthropic/claude-opus-4-6", "api_key": "sk-test"},
+            }
+        ]
+    )
+    monkeypatch.setattr(proxy_server, "llm_router", router)
+
+    with auth_as():
+        response = client.get("/utils/supported_openai_params", params={"model": "claude-opus-4-6-cached"})
+
+    assert response.status_code == 200
+    expected = litellm.get_supported_openai_params(model="claude-opus-4-6", custom_llm_provider="anthropic")
+    assert response.json() == {"supported_openai_params": expected}
+    assert "max_tokens" in response.json()["supported_openai_params"]
+
+
+def test_supported_openai_params_declared_prefix_alias_resolves_through_router(client, auth_as, monkeypatch):
+    """Regression: an alias whose name starts with an authenticating provider's prefix skipped
+    router resolution and answered with that provider's params instead of the deployment's."""
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "github_copilot/gpt-4o",
+                "litellm_params": {"model": "anthropic/claude-opus-4-6", "api_key": "sk-test"},
+            }
+        ]
+    )
+    monkeypatch.setattr(proxy_server, "llm_router", router)
+
+    with auth_as():
+        response = client.get("/utils/supported_openai_params", params={"model": "github_copilot/gpt-4o"})
+
+    assert response.status_code == 200
+    expected = litellm.get_supported_openai_params(model="claude-opus-4-6", custom_llm_provider="anthropic")
+    assert response.json() == {"supported_openai_params": expected}
+
+
+def test_supported_openai_params_never_runs_oauth_for_authenticating_providers(client, auth_as, monkeypatch, tmp_path):
+    """Regression: github_copilot/chatgpt names answer from their declaration; resolving them
+    through ``get_llm_provider`` would run the provider's OAuth device flow and block the event loop."""
+    monkeypatch.setenv("GITHUB_COPILOT_TOKEN_DIR", str(tmp_path))
+    (tmp_path / "access-token").write_text("fake-access-token")
+    (tmp_path / "api-key.json").write_text(
+        json.dumps(
+            {
+                "token": "fake-api-key",
+                "expires_at": 4102444800,
+                "endpoints": {"api": "https://api.githubcopilot.com"},
+            }
+        )
+    )
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "copilot-alias",
+                "litellm_params": {"model": "github_copilot/gpt-4o"},
+            },
+            {
+                "model_name": "openai/*",
+                "litellm_params": {"model": "openai/*"},
+            },
+        ]
+    )
+    monkeypatch.setattr(proxy_server, "llm_router", router)
+
+    resolution_attempts: list[str] = []
+
+    def _oauth_tripwire(model, *args, **kwargs):
+        resolution_attempts.append(model)
+        raise AssertionError("get_llm_provider would run the OAuth device flow")
+
+    monkeypatch.setattr(litellm, "get_llm_provider", _oauth_tripwire)
+    monkeypatch.setattr(pattern_match_deployments, "get_llm_provider", _oauth_tripwire)
+    expected = litellm.get_supported_openai_params(model="gpt-4o", custom_llm_provider="github_copilot")
+
+    with auth_as():
+        via_alias = client.get("/utils/supported_openai_params", params={"model": "copilot-alias"})
+        via_direct_name = client.get("/utils/supported_openai_params", params={"model": "github_copilot/gpt-4o"})
+
+    assert via_alias.status_code == 200
+    assert via_alias.json() == {"supported_openai_params": expected}
+    assert via_direct_name.status_code == 200
+    assert via_direct_name.json() == {"supported_openai_params": expected}
+    assert resolution_attempts == []
+
+
 def test_supported_openai_params_invalid_model(client, auth_as, monkeypatch):
     """Pins ``GET /utils/supported_openai_params`` (error: unknown model)."""
 
     def _raise(model):
         raise Exception("unknown")
 
+    monkeypatch.setattr(proxy_server, "llm_router", None)
     monkeypatch.setattr(litellm, "get_llm_provider", _raise)
     with auth_as():
         response = client.get("/utils/supported_openai_params", params={"model": "??"})
diff --git a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
index aa35fd64f18..0fb9b1a6d88 100644
--- a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
+++ b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py
@@ -19,7 +19,10 @@ from litellm.proxy._types import (
     LitellmUserRoles,
     UserAPIKeyAuth,
 )
-from litellm.proxy.common_utils.model_listing_utils import TeamModelNameTranslator
+from litellm.proxy.common_utils.model_listing_utils import (
+    TeamModelNameTranslator,
+    configured_display_names,
+)
 from litellm.proxy.proxy_server import (
     _get_proxy_model_info,
     _translate_model_name_for_response,
@@ -1391,6 +1394,27 @@ def test_resolve_public_name_respects_legacy_flag():
     )
 
 
+def test_configured_display_names_keyed_by_response_id():
+    """The map is keyed by the public response id while the router lookup uses
+    the internal routing key, and entries without a configured name are omitted."""
+    router = MagicMock()
+    router.get_configured_display_name = MagicMock(
+        side_effect=lambda model_name: "Team Sonnet" if model_name == "model_name_team-abc-123_4a6b8" else None
+    )
+
+    assert configured_display_names(
+        entries=[
+            ("team-claude-sonnet", "model_name_team-abc-123_4a6b8"),
+            ("gpt-4o", "gpt-4o"),
+        ],
+        llm_router=router,
+    ) == {"team-claude-sonnet": "Team Sonnet"}
+
+
+def test_configured_display_names_empty_without_router():
+    assert configured_display_names(entries=[("gpt-4o", "gpt-4o")], llm_router=None) == {}
+
+
 @pytest.mark.asyncio
 async def test_retrieve_model_by_public_name_returns_200(monkeypatch):
     """Regression: `GET /v1/models/{public_name}` must NOT 404. The listing
diff --git a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
index 31430da71e8..8006f64ba41 100644
--- a/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
+++ b/tests/test_litellm/proxy/public_endpoints/test_public_endpoints.py
@@ -1,3 +1,4 @@
+import re
 from datetime import datetime, timezone
 from unittest.mock import AsyncMock, MagicMock, patch
 
@@ -756,6 +757,45 @@ def test_public_agent_hub_returns_empty_when_no_public_groups():
     assert response.json() == []
 
 
+# ---------------------------------------------------------------------------
+# /public/agents/fields
+# ---------------------------------------------------------------------------
+
+
+def test_bedrock_agentcore_runtime_arn_validation_pattern_accepts_full_resource_path():
+    """Regression for LIT-6737: the AgentCore agent_runtime_arn field's
+    validation_pattern must accept a complete runtime ARN whose resource part
+    is itself multi-segment (``runtime/<runtime-id>``), and reject the exact
+    truncated shape a naive split("/")-by-position parse used to produce (the
+    ARN cut off right after the ``runtime`` resource type).
+    """
+    app_instance = FastAPI()
+    app_instance.include_router(router)
+    test_client = TestClient(app_instance)
+
+    response = test_client.get("/public/agents/fields")
+    assert response.status_code == 200
+    agents = response.json()
+
+    bedrock_agentcore = next((a for a in agents if a["agent_type"] == "bedrock_agentcore"), None)
+    assert bedrock_agentcore is not None, "bedrock_agentcore agent type not found"
+    assert bedrock_agentcore["model_template"] == "bedrock/agentcore/{agent_runtime_arn}"
+
+    fields_by_key = {f["key"]: f for f in bedrock_agentcore["credential_fields"]}
+    arn_field = fields_by_key["agent_runtime_arn"]
+    assert arn_field["required"] is True
+    assert arn_field["include_in_litellm_params"] is False
+
+    pattern = arn_field.get("validation_pattern")
+    assert pattern, "agent_runtime_arn must ship a validation_pattern so the UI can reject a truncated ARN"
+
+    full_arn = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs"
+    truncated_arn = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime"
+
+    assert re.match(pattern, full_arn), "the validator must accept a complete runtime ARN"
+    assert not re.match(pattern, truncated_arn), "the validator must reject the truncated ARN"
+
+
 # ---------------------------------------------------------------------------
 # /public/endpoints
 # ---------------------------------------------------------------------------
diff --git a/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py b/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
index abbf6892a98..0085b6ebd36 100644
--- a/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
+++ b/tests/test_litellm/proxy/rag_endpoints/test_rag_endpoints.py
@@ -324,6 +324,127 @@ def test_rag_query_stream_returns_event_stream(client_internal_user):
     assert "data: [DONE]" in response.text
 
 
+def test_rag_query_merges_managed_store_params(client_internal_user):
+    """
+    Regression: /v1/rag/query must consult the managed vector store registry
+    (like the direct /v1/vector_stores/{id}/search endpoint does) so that
+    provider, region, embedding model, etc. don't have to be repeated in
+    retrieval_config. Pre-fix the registry was never read, so managed S3
+    Vectors stores failed with "aws_region_name is required".
+    """
+    import litellm
+    from litellm.types.utils import ModelResponse
+
+    mock_vector_store = {
+        "vector_store_id": "s3-store",
+        "custom_llm_provider": "s3_vectors",
+        "litellm_params": {
+            "aws_region_name": "eu-west-1",
+            "embedding_model": "my-embed",
+            "vector_bucket_name": "bkt",
+        },
+    }
+    mock_registry = MagicMock()
+    mock_registry.get_litellm_managed_vector_store_from_registry.return_value = mock_vector_store
+
+    mock_response = ModelResponse(
+        id="chatcmpl-test",
+        choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
+        model="gpt-4o-mini",
+    )
+
+    with patch(  # test-quality-ok: aquery is the endpoint's downstream boundary; the forwarded config is what the test asserts
+        "litellm.proxy.rag_endpoints.endpoints.litellm.aquery",
+        new_callable=AsyncMock,
+        return_value=mock_response,
+    ) as mock_aquery, patch.object(litellm, "vector_store_registry", mock_registry), patch(  # test-quality-ok: seeds the managed-store registry the merge under test reads and grants access so real store resolution runs
+        "litellm.proxy.vector_store_endpoints.utils.can_user_access_vector_store",
+        new=AsyncMock(return_value=True),
+    ):
+        response = client_internal_user.post(
+            "/v1/rag/query",
+            json={
+                "model": "gpt-4o-mini",
+                "messages": [{"role": "user", "content": "hello"}],
+                "retrieval_config": {"vector_store_id": "s3-store"},
+            },
+        )
+
+    assert response.status_code == 200, response.json()
+    mock_aquery.assert_awaited_once()
+    forwarded_config = mock_aquery.await_args.kwargs["retrieval_config"]
+    assert forwarded_config["vector_store_id"] == "s3-store"
+    assert forwarded_config["custom_llm_provider"] == "s3_vectors"
+    assert forwarded_config["aws_region_name"] == "eu-west-1"
+    assert forwarded_config["embedding_model"] == "my-embed"
+    assert forwarded_config["vector_bucket_name"] == "bkt"
+
+
+def test_rag_query_store_params_win_over_user_retrieval_config(client_internal_user):
+    """Registry values must win over user-supplied retrieval_config keys so callers cannot override store credentials."""
+    import litellm
+    from litellm.types.utils import ModelResponse
+
+    mock_vector_store = {
+        "vector_store_id": "s3-store",
+        "custom_llm_provider": "s3_vectors",
+        "litellm_params": {"aws_region_name": "eu-west-1"},
+    }
+    mock_registry = MagicMock()
+    mock_registry.get_litellm_managed_vector_store_from_registry.return_value = mock_vector_store
+
+    mock_response = ModelResponse(
+        id="chatcmpl-test",
+        choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}],
+        model="gpt-4o-mini",
+    )
+
+    with patch(  # test-quality-ok: aquery is the endpoint's downstream boundary; the forwarded config is what the test asserts
+        "litellm.proxy.rag_endpoints.endpoints.litellm.aquery",
+        new_callable=AsyncMock,
+        return_value=mock_response,
+    ) as mock_aquery, patch.object(litellm, "vector_store_registry", mock_registry), patch(  # test-quality-ok: seeds the managed-store registry the merge under test reads and grants access so real store resolution runs
+        "litellm.proxy.vector_store_endpoints.utils.can_user_access_vector_store",
+        new=AsyncMock(return_value=True),
+    ):
+        response = client_internal_user.post(
+            "/v1/rag/query",
+            json={
+                "model": "gpt-4o-mini",
+                "messages": [{"role": "user", "content": "hello"}],
+                "retrieval_config": {"vector_store_id": "s3-store", "aws_region_name": "us-east-1"},
+            },
+        )
+
+    assert response.status_code == 200, response.json()
+    forwarded_config = mock_aquery.await_args.kwargs["retrieval_config"]
+    assert forwarded_config["aws_region_name"] == "eu-west-1"
+
+
+@pytest.mark.parametrize(
+    "blocked_key",
+    ["embedding_model", "litellm_embedding_model", "litellm_embedding_config", "litellm_credential_name"],
+)
+def test_rag_query_rejects_caller_embedding_selection_params(client_internal_user, blocked_key):
+    """
+    Regression: a caller must not pick the embedding model or credential used at
+    search time. Those resolve through the Router with the proxy's credentials,
+    bypassing the key's model permissions, so they may only come from the
+    managed store's server-side registration.
+    """
+    response = client_internal_user.post(
+        "/v1/rag/query",
+        json={
+            "model": "gpt-4o-mini",
+            "messages": [{"role": "user", "content": "hello"}],
+            "retrieval_config": {"vector_store_id": "s3-store", blocked_key: "attacker-choice"},
+        },
+    )
+
+    assert response.status_code == 400, response.json()
+    assert blocked_key in str(response.json())
+
+
 EICAR = r"X5O!P%@AP[4\PZX54(P^)7CC)7}$EICAR-STANDARD-ANTIVIRUS-TEST-FILE!$H+H*"
 INGEST_REQUEST = '{"ingest_options":{"vector_store":{"custom_llm_provider":"openai"}}}'
 
diff --git a/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py b/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py
index 791d64c6428..d7010de6405 100644
--- a/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py
+++ b/tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py
@@ -3,10 +3,12 @@ Test for response_api_endpoints/endpoints.py
 """
 
 import unittest
+from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from fastapi.testclient import TestClient
+from httpx import Response
 
 import litellm
 from litellm.proxy.proxy_server import app
@@ -82,11 +84,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
                 ResponseOutputMessage(
                     type="message",
                     role="assistant",
-                    content=[
-                        ResponseOutputText(
-                            type="output_text", text="Hello from Cursor!"
-                        )
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="Hello from Cursor!")],
                 )
             ],
         )
@@ -121,9 +119,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
     @pytest.mark.asyncio
     @patch("litellm.proxy.proxy_server.llm_router")
     @patch("litellm.proxy.proxy_server.user_api_key_auth")
-    async def test_responses_api_key_spend_header_includes_response_cost(
-        self, mock_auth, mock_router
-    ):
+    async def test_responses_api_key_spend_header_includes_response_cost(self, mock_auth, mock_router):
         """
         Test that x-litellm-key-spend header includes the current request's response_cost
         for /v1/responses endpoint.
@@ -159,9 +155,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
                 ResponseOutputMessage(
                     type="message",
                     role="assistant",
-                    content=[
-                        ResponseOutputText(type="output_text", text="Test response")
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="Test response")],
                 )
             ],
         )
@@ -356,6 +350,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "model": "gpt-4o", "input": "hello"}
         assert _extract_model_from_first_ws_event(event) == "gpt-4o"
 
@@ -363,6 +358,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "response": {"model": "gpt-4o", "input": "hello"}}
         assert _extract_model_from_first_ws_event(event) == "gpt-4o"
 
@@ -370,6 +366,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {
             "type": "response.create",
             "model": "flat-model",
@@ -381,6 +378,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "input": "hello"}
         assert _extract_model_from_first_ws_event(event) is None
 
@@ -400,9 +398,7 @@ class TestResponsesWSFirstFrameValidation:
         )
 
         ws = MagicMock()
-        ws.receive_text = AsyncMock(
-            return_value=json.dumps({"type": "session.update", "model": "gpt-4o"})
-        )
+        ws.receive_text = AsyncMock(return_value=json.dumps({"type": "session.update", "model": "gpt-4o"}))
         ws.send_text = AsyncMock()
         ws.close = AsyncMock()
 
@@ -412,10 +408,7 @@ class TestResponsesWSFirstFrameValidation:
         ws.send_text.assert_awaited_once()
         ws.close.assert_awaited_once_with(code=1008, reason="Invalid first message")
         error_payload = json.loads(ws.send_text.await_args.args[0])
-        assert (
-            error_payload["error"]["message"]
-            == "First message must be a response.create JSON object."
-        )
+        assert error_payload["error"]["message"] == "First message must be a response.create JSON object."
 
     @pytest.mark.asyncio
     async def test_rejects_non_object_json_first_frame(self):
@@ -484,16 +477,12 @@ class TestResponsesWSFirstFrameModelAuth:
         ws.url = "ws://testserver/v1/responses"
         ws.accept = AsyncMock()
         ws.receive_text = AsyncMock(
-            return_value=json.dumps(
-                {"type": "response.create", "model": "gpt-4o-mini", "input": []}
-            )
+            return_value=json.dumps({"type": "response.create", "model": "gpt-4o-mini", "input": []})
         )
         ws.close = AsyncMock()
 
         processor = MagicMock()
-        processor.common_processing_pre_call_logic = AsyncMock(
-            return_value=({"model": "gpt-4o-mini"}, MagicMock())
-        )
+        processor.common_processing_pre_call_logic = AsyncMock(return_value=({"model": "gpt-4o-mini"}, MagicMock()))
 
         async def fake_llm_call():
             return None
@@ -529,9 +518,7 @@ class TestResponsesWSFirstFrameModelAuth:
             _enforce_responses_ws_first_frame_model_auth,
         )
 
-        request = Request(
-            {"type": "http", "method": "POST", "path": "/v1/responses", "headers": []}
-        )
+        request = Request({"type": "http", "method": "POST", "path": "/v1/responses", "headers": []})
         user_api_key_dict = MagicMock()
         llm_router = MagicMock()
 
@@ -593,9 +580,7 @@ class TestReadWSModelFromFirstFrameErrors:
 
         assert result is None
         ws.send_text.assert_not_awaited()
-        ws.close.assert_awaited_once_with(
-            code=1008, reason="Timed out waiting for first message"
-        )
+        ws.close.assert_awaited_once_with(code=1008, reason="Timed out waiting for first message")
 
     @pytest.mark.asyncio
     async def test_invalid_json_sends_error_and_closes(self):
@@ -613,9 +598,7 @@ class TestReadWSModelFromFirstFrameErrors:
         assert result is None
         payload = json.loads(ws.send_text.await_args.args[0])
         assert payload["error"]["message"] == "First message is not valid JSON."
-        ws.close.assert_awaited_once_with(
-            code=1008, reason="Invalid JSON in first message"
-        )
+        ws.close.assert_awaited_once_with(code=1008, reason="Invalid JSON in first message")
 
     @pytest.mark.asyncio
     async def test_missing_model_sends_error_and_closes(self):
@@ -624,9 +607,7 @@ class TestReadWSModelFromFirstFrameErrors:
         )
 
         ws = MagicMock()
-        ws.receive_text = AsyncMock(
-            return_value=json.dumps({"type": "response.create", "input": []})
-        )
+        ws.receive_text = AsyncMock(return_value=json.dumps({"type": "response.create", "input": []}))
         ws.send_text = AsyncMock()
         ws.close = AsyncMock()
 
@@ -679,10 +660,7 @@ class TestManagedResponsesSameProvider:
         assert self._handler("gpt-4o")._same_provider("gpt-4o-mini") is True
 
     def test_different_provider_is_not_same(self):
-        assert (
-            self._handler("gpt-4o")._same_provider("vertex_ai/gemini-2.0-flash")
-            is False
-        )
+        assert self._handler("gpt-4o")._same_provider("vertex_ai/gemini-2.0-flash") is False
 
     def test_inject_credentials_keeps_provider_for_same_provider_model(self):
         handler = self._handler("gpt-4o", custom_llm_provider="openai")
@@ -697,18 +675,14 @@ class TestManagedResponsesSameProvider:
         assert "custom_llm_provider" not in call_kwargs
 
     def test_unresolvable_connection_model_falls_back_to_custom_provider(self):
-        handler = self._handler(
-            "my-custom-deployment", custom_llm_provider="openai"
-        )
+        handler = self._handler("my-custom-deployment", custom_llm_provider="openai")
         assert handler._same_provider("gpt-4o-mini") is True
         call_kwargs: dict = {}
         handler._inject_credentials(call_kwargs, model="gpt-4o-mini")
         assert call_kwargs["custom_llm_provider"] == "openai"
 
     def test_unresolvable_connection_model_still_drops_cross_provider(self):
-        handler = self._handler(
-            "my-custom-deployment", custom_llm_provider="openai"
-        )
+        handler = self._handler("my-custom-deployment", custom_llm_provider="openai")
         call_kwargs: dict = {}
         handler._inject_credentials(call_kwargs, model="vertex_ai/gemini-2.0-flash")
         assert "custom_llm_provider" not in call_kwargs
@@ -840,9 +814,7 @@ def test_cursor_chat_completions_input_body_uses_responses_pipeline_and_strips_s
                     type="message",
                     role="assistant",
                     status="completed",
-                    content=[
-                        ResponseOutputText(type="output_text", text="agent reply", annotations=[])
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="agent reply", annotations=[])],
                 )
             ],
         )
@@ -851,9 +823,12 @@ def test_cursor_chat_completions_input_body_uses_responses_pipeline_and_strips_s
 
     app.dependency_overrides[user_api_key_auth] = _auth_override
     try:
-        with patch.object(ps, "llm_router", mock_router), patch(
-            "litellm.proxy.response_api_endpoints.endpoints._read_request_body",
-            side_effect=capturing_read_request_body,
+        with (
+            patch.object(ps, "llm_router", mock_router),
+            patch(
+                "litellm.proxy.response_api_endpoints.endpoints._read_request_body",
+                side_effect=capturing_read_request_body,
+            ),
         ):
             client = TestClient(app)
             response = client.post(
@@ -1488,8 +1463,8 @@ def _router_serving_only(base_model: str) -> MagicMock:
     mock_router.router_general_settings.pass_through_all_models = False
     mock_router.default_deployment = None
     mock_router.pattern_router.patterns = {base_model: ["anthropic/*"]}
-    mock_router.pattern_router.get_pattern.side_effect = (
-        lambda model: [{"model_name": "anthropic/*"}] if model == base_model else None
+    mock_router.pattern_router.get_pattern.side_effect = lambda model: (
+        [{"model_name": "anthropic/*"}] if model == base_model else None
     )
     return mock_router
 
@@ -1739,9 +1714,7 @@ class TestCursorGateRecognizesRoutingGroups:
         from litellm.proxy.response_api_endpoints.endpoints import _resolve_cursor_model_variant
 
         router = Router(
-            model_list=[
-                {"model_name": "member-fast", "litellm_params": {"model": "openai/gpt-4o", "api_key": "fake"}}
-            ],
+            model_list=[{"model_name": "member-fast", "litellm_params": {"model": "openai/gpt-4o", "api_key": "fake"}}],
             routing_groups=[
                 {"group_name": "grouped-thinking-high", "models": ["member-fast"], "routing_strategy": "simple-shuffle"}
             ],
@@ -1836,3 +1809,153 @@ class TestGuardrailBlockedResponsesUsage:
         assert usage["input_tokens"] == 0
         assert usage["output_tokens"] == 0
         assert usage["total_tokens"] == 0
+
+
+class TestResponsesInputTokens:
+    """Regression tests for POST /v1/responses/input_tokens.
+
+    The docs promise OpenAI-format token counting on the proxy, but the route was
+    never registered, so the POST fell through to the GET/DELETE-only
+    /v1/responses/{response_id} route and returned 405."""
+
+    def _post_input_tokens(
+        self,
+        body: dict[str, Any],
+        path: str = "/v1/responses/input_tokens",
+        counter: AsyncMock | None = None,
+    ) -> tuple[Response, AsyncMock]:
+        from litellm.proxy._types import UserAPIKeyAuth
+        from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+        from litellm.proxy.response_api_endpoints.endpoints import _proxy_token_counter
+        from litellm.types.utils import TokenCountResponse
+
+        token_counter_mock = (
+            counter
+            if counter is not None
+            else AsyncMock(
+                return_value=TokenCountResponse(
+                    total_tokens=13,
+                    request_model=body.get("model", ""),
+                    model_used=body.get("model", ""),
+                    tokenizer_type="openai_api",
+                )
+            )
+        )
+        app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth(api_key="sk-test", request_route=path)
+        app.dependency_overrides[_proxy_token_counter] = lambda: token_counter_mock
+        try:
+            client = TestClient(app)
+            response = client.post(path, json=body, headers={"Authorization": "Bearer sk-1234"})
+            return response, token_counter_mock
+        finally:
+            app.dependency_overrides.pop(user_api_key_auth, None)
+            app.dependency_overrides.pop(_proxy_token_counter, None)
+
+    def test_string_input_returns_openai_input_tokens_shape(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": "Hello, how are you?"})
+
+        assert response.status_code == 200, response.text
+        assert response.json() == {"object": "response.input_tokens", "input_tokens": 13}
+        counter.assert_awaited_once()
+        assert counter.call_args.kwargs["call_endpoint"] is True
+        token_request = counter.call_args.kwargs["request"]
+        assert token_request.model == "gpt-4o"
+        assert token_request.messages == [{"role": "user", "content": "Hello, how are you?"}]
+
+    def test_every_route_alias_is_registered(self):
+        for path in ("/v1/responses/input_tokens", "/responses/input_tokens", "/openai/v1/responses/input_tokens"):
+            response, _ = self._post_input_tokens({"model": "gpt-4o", "input": "hi"}, path=path)
+            assert response.status_code == 200, f"{path}: {response.status_code} {response.text}"
+
+    def test_input_items_instructions_and_tools_are_forwarded(self):
+        tools = [
+            {
+                "type": "function",
+                "name": "get_weather",
+                "description": "Get weather for a city",
+                "parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
+            }
+        ]
+        response, counter = self._post_input_tokens(
+            {
+                "model": "gpt-4o",
+                "input": [{"role": "user", "content": "What is the weather in Paris?"}],
+                "instructions": "You are terse.",
+                "tools": tools,
+            }
+        )
+
+        assert response.status_code == 200, response.text
+        token_request = counter.call_args.kwargs["request"]
+        assert token_request.messages == [
+            {"role": "system", "content": "You are terse."},
+            {"role": "user", "content": "What is the weather in Paris?"},
+        ]
+        assert token_request.tools == tools
+
+    def test_missing_model_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"input": "Hello"})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": "Missing required parameter: 'model'.",
+                "type": "invalid_request_error",
+                "param": "model",
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    def test_missing_input_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o"})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": "Missing required parameter: 'input'.",
+                "type": "invalid_request_error",
+                "param": "input",
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    @pytest.mark.parametrize("empty_input", ["", []])
+    def test_empty_input_returns_openai_400(self, empty_input):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": empty_input})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": """One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""",
+                "type": "invalid_request_error",
+                "param": None,
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    def test_invalid_tools_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": "hi", "tools": "not-a-list"})
+
+        assert response.status_code == 400, response.text
+        error = response.json()["error"]
+        assert error["type"] == "invalid_request_error"
+        counter.assert_not_awaited()
+
+    def test_provider_error_maps_status_code(self):
+        from litellm.proxy._types import ProxyException
+
+        failing_counter = AsyncMock(
+            side_effect=ProxyException(
+                message="rate limited",
+                type="token_counting_error",
+                param="model",
+                code="429",
+            )
+        )
+        response, _ = self._post_input_tokens({"model": "gpt-4o", "input": "hi"}, counter=failing_counter)
+
+        assert response.status_code == 429, response.text
+        assert response.json()["error"]["message"] == "rate limited"
diff --git a/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py b/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py
new file mode 100644
index 00000000000..f65f68812a2
--- /dev/null
+++ b/tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py
@@ -0,0 +1,48 @@
+from typing import Final
+
+import pytest
+
+from litellm.caching import DualCache
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+from litellm.proxy.spend_tracking.budget_reservation import reserve_budget_for_request
+from litellm.proxy.utils import ProxyLogging
+
+TOKEN_COUNTING_ROUTES: Final = (
+    "/responses/input_tokens",
+    "/v1/responses/input_tokens",
+    "/openai/v1/responses/input_tokens",
+    "/utils/token_counter",
+)
+
+
+def _budgeted_token() -> UserAPIKeyAuth:
+    return UserAPIKeyAuth(api_key="sk-test", token="hashed-token", max_budget=100.0, spend=0.0)
+
+
+async def _reserve(route: str) -> dict | None:
+    return await reserve_budget_for_request(
+        request_body={"model": "gpt-4o", "input": "hello"},
+        route=route,
+        llm_router=None,
+        valid_token=_budgeted_token(),
+        team_object=None,
+        user_object=None,
+        prisma_client=None,
+        user_api_key_cache=UserApiKeyCache(),
+        proxy_logging_obj=ProxyLogging(user_api_key_cache=DualCache()),
+    )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("route", TOKEN_COUNTING_ROUTES)
+async def test_token_counting_routes_are_exempt_from_budget_reservation(route):
+    assert await _reserve(route) is None
+
+
+@pytest.mark.asyncio
+async def test_non_exempt_llm_route_still_reserves_budget():
+    reservation: Final = await _reserve("/v1/responses")
+
+    assert reservation is not None
+    assert reservation["reserved_cost"] > 0
diff --git a/tests/test_litellm/proxy/spend_tracking/test_savings.py b/tests/test_litellm/proxy/spend_tracking/test_savings.py
index 5fda4fb20b5..7dd18587df3 100644
--- a/tests/test_litellm/proxy/spend_tracking/test_savings.py
+++ b/tests/test_litellm/proxy/spend_tracking/test_savings.py
@@ -6,6 +6,7 @@ import litellm
 from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token
 from litellm.proxy.spend_tracking.savings import (
     _baseline_usage,
+    _resolve_model,
     compute_autorouter_savings,
     compute_savings_spend,
     marks_gateway_injection,
@@ -13,6 +14,8 @@ from litellm.proxy.spend_tracking.savings import (
 from litellm.router import Router
 from litellm.types.utils import Usage
 
+pytestmark = pytest.mark.usefixtures("local_model_cost_map")
+
 
 def _anthropic_costs(model: str) -> tuple[float, float]:
     info = litellm.get_model_info(model=model, custom_llm_provider="anthropic")
@@ -754,24 +757,55 @@ def test_a_baseline_that_prices_caching_implicitly_still_pays_for_its_prompt():
     assert reported > 0, "routing a cold first turn onto a cheaper model is a saving, not a loss"
 
 
+def _priced_chat_model_without_cache_read_rate() -> tuple[str, str, str]:
+    """A chat model the bundled map prices per token for input and output but not for cache
+    reads, derived from the map itself: a hardcoded pick goes stale the moment the registry
+    prices that model's cache reads, which is exactly how this test's premise last broke.
+    Candidates go through the savings module's own resolver, so the pick is one the code
+    under test can actually price."""
+    for key in sorted(litellm.model_cost):
+        entry = litellm.model_cost[key]
+        provider = entry.get("litellm_provider")
+        if not isinstance(provider, str) or not key.startswith(f"{provider}/"):
+            continue
+        if entry.get("mode") != "chat" or entry.get("cache_read_input_token_cost") is not None:
+            continue
+        if not entry.get("input_cost_per_token") or not entry.get("output_cost_per_token"):
+            continue
+        if _resolve_model(key, None) is None:
+            continue
+        priced = compute_autorouter_savings(
+            baseline_model=key,
+            selected_model="claude-haiku-4-5",
+            selected_provider="anthropic",
+            usage=_usage(fresh=1_000, cached=0, written=0, out=100),
+            conversation_continuing=True,
+        )
+        if priced == 0.0:
+            continue
+        return key, key.removeprefix(f"{provider}/"), provider
+    raise AssertionError("the bundled map has no per-token chat model without a cache-read rate")
+
+
 def test_a_baseline_with_no_cache_read_rate_is_charged_its_input_rate():
     """The same hole on the other bucket. A baseline whose entry has no
     `cache_read_input_token_cost` reads for 0.0, so a continuing turn priced the whole
     prompt at nothing and every switch away from it reported a loss.
     """
+    baseline_key, baseline_name, baseline_provider = _priced_chat_model_without_cache_read_rate()
     continuing = _usage(fresh=0, cached=0, written=20_000, out=1_000)
     reported = compute_autorouter_savings(
-        baseline_model="xai/grok-4",
+        baseline_model=baseline_key,
         selected_model="claude-haiku-4-5",
         selected_provider="anthropic",
         usage=continuing,
         conversation_continuing=True,
     )
 
-    grok = litellm.get_model_info("grok-4", "xai")
-    assert grok.get("cache_read_input_token_cost") is None, "pick a baseline with no cache-read rate"
+    baseline = litellm.get_model_info(baseline_name, baseline_provider)
+    assert baseline.get("cache_read_input_token_cost") is None, "pick a baseline with no cache-read rate"
     haiku = litellm.get_model_info("claude-haiku-4-5", "anthropic")
-    baseline_pays_input = 20_000 * grok["input_cost_per_token"] + 1_000 * grok["output_cost_per_token"]
+    baseline_pays_input = 20_000 * baseline["input_cost_per_token"] + 1_000 * baseline["output_cost_per_token"]
     actually_paid = 20_000 * haiku["cache_creation_input_token_cost"] + 1_000 * haiku["output_cost_per_token"]
     assert reported == pytest.approx(baseline_pays_input - actually_paid)
 
diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py
index 10c3e5fecf8..a0dcbf802ef 100644
--- a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py
+++ b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py
@@ -2865,7 +2865,7 @@ class TestSpendLogsPayload:
                     "model": "gpt-4o",
                     "user": "",
                     "team_id": "",
-                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "usage_object": {"completion_tokens": 20, "prompt_tokens": 10, "total_tokens": 30, "completion_tokens_details": null, "prompt_tokens_details": null}, "model_map_information": {"model_map_key": "gpt-4o", "model_map_value": {"key": "gpt-4o", "max_tokens": 16384, "max_input_tokens": 128000, "max_output_tokens": 16384, "input_cost_per_token": 2.5e-06, "cache_creation_input_token_cost": null, "cache_read_input_token_cost": 1.25e-06, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": 1.25e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token": 1e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_reasoning_token": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "openai", "mode": "chat", "supports_system_messages": true, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": false, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": false, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": true, "supports_reasoning": false, "search_context_cost_per_query": {"search_context_size_low": 0.03, "search_context_size_medium": 0.035, "search_context_size_high": 0.05}, "tpm": null, "rpm": null, "supported_openai_params": ["frequency_penalty", "logit_bias", "logprobs", "top_logprobs", "max_tokens", "max_completion_tokens", "modalities", "prediction", "n", "presence_penalty", "seed", "stop", "stream", "stream_options", "temperature", "top_p", "tools", "tool_choice", "function_call", "functions", "max_retries", "extra_headers", "parallel_tool_calls", "audio", "response_format", "user"]}}, "additional_usage_values": {"completion_tokens_details": null, "prompt_tokens_details": null}}',
+                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "router_metadata": null, "usage_object": {"completion_tokens": 20, "prompt_tokens": 10, "total_tokens": 30, "completion_tokens_details": null, "prompt_tokens_details": null}, "model_map_information": {"model_map_key": "gpt-4o", "model_map_value": {"key": "gpt-4o", "max_tokens": 16384, "max_input_tokens": 128000, "max_output_tokens": 16384, "input_cost_per_token": 2.5e-06, "cache_creation_input_token_cost": null, "cache_read_input_token_cost": 1.25e-06, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": 1.25e-06, "output_cost_per_token_batches": 5e-06, "output_cost_per_token": 1e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_reasoning_token": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "openai", "mode": "chat", "supports_system_messages": true, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": false, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": false, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": true, "supports_reasoning": false, "search_context_cost_per_query": {"search_context_size_low": 0.03, "search_context_size_medium": 0.035, "search_context_size_high": 0.05}, "tpm": null, "rpm": null, "supported_openai_params": ["frequency_penalty", "logit_bias", "logprobs", "top_logprobs", "max_tokens", "max_completion_tokens", "modalities", "prediction", "n", "presence_penalty", "seed", "stop", "stream", "stream_options", "temperature", "top_p", "tools", "tool_choice", "function_call", "functions", "max_retries", "extra_headers", "parallel_tool_calls", "audio", "response_format", "user"]}}, "additional_usage_values": {"completion_tokens_details": null, "prompt_tokens_details": null}}',
                     "cache_key": "Cache OFF",
                     "spend": 0.00022500000000000002,
                     "total_tokens": 30,
@@ -2961,7 +2961,7 @@ class TestSpendLogsPayload:
                     "model": "claude-4-sonnet-20250514",
                     "user": "",
                     "team_id": "",
-                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}',
+                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": null, "original_model_group": null, "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "router_metadata": null, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}',
                     "cache_key": "Cache OFF",
                     "spend": 0.01383,
                     "total_tokens": 2598,
@@ -3055,7 +3055,7 @@ class TestSpendLogsPayload:
                     "model": "claude-4-sonnet-20250514",
                     "user": "",
                     "team_id": "",
-                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": 0, "original_model_group": "my-anthropic-model-group", "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}',
+                    "metadata": '{"applied_guardrails": [], "attempted_fallbacks": 0, "original_model_group": "my-anthropic-model-group", "batch_models": null, "batch_successful_requests": null, "batch_failed_requests": null, "mcp_tool_call_metadata": null, "vector_store_request_metadata": null, "routing_decision": null, "internal_call_origin": null, "guardrail_information": null, "compression_savings": null, "litellm_gateway_injected_cache": null, "router_metadata": null, "usage_object": {"completion_tokens": 503, "prompt_tokens": 2095, "total_tokens": 2598, "completion_tokens_details": null, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}, "model_map_information": {"model_map_key": "claude-4-sonnet-20250514", "model_map_value": {"key": "claude-4-sonnet-20250514", "max_tokens": 128000, "max_input_tokens": 200000, "max_output_tokens": 128000, "input_cost_per_token": 3e-06, "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "input_cost_per_character": null, "input_cost_per_token_above_128k_tokens": null, "input_cost_per_token_above_200k_tokens": null, "input_cost_per_query": null, "input_cost_per_second": null, "input_cost_per_audio_token": null, "input_cost_per_token_batches": null, "output_cost_per_token_batches": null, "output_cost_per_token": 1.5e-05, "output_cost_per_audio_token": null, "output_cost_per_character": null, "output_cost_per_token_above_128k_tokens": null, "output_cost_per_character_above_128k_tokens": null, "output_cost_per_token_above_200k_tokens": null, "output_cost_per_second": null, "output_cost_per_image": null, "output_vector_size": null, "litellm_provider": "anthropic", "mode": "chat", "supports_system_messages": null, "supports_response_schema": true, "supports_vision": true, "supports_function_calling": true, "supports_tool_choice": true, "supports_assistant_prefill": true, "supports_prompt_caching": true, "supports_audio_input": false, "supports_audio_output": false, "supports_pdf_input": true, "supports_embedding_image_input": false, "supports_native_streaming": null, "supports_web_search": false, "supports_reasoning": true, "search_context_cost_per_query": null, "tpm": null, "rpm": null, "supported_openai_params": ["stream", "stop", "temperature", "top_p", "max_tokens", "max_completion_tokens", "tools", "tool_choice", "extra_headers", "parallel_tool_calls", "response_format", "user", "reasoning_effort", "thinking"]}}, "additional_usage_values": {"completion_tokens_details": {"accepted_prediction_tokens": null, "audio_tokens": null, "reasoning_tokens": null, "rejected_prediction_tokens": null, "text_tokens": 503, "image_tokens": null}, "prompt_tokens_details": {"audio_tokens": null, "cached_tokens": 0, "text_tokens": null, "image_tokens": null}, "cache_creation_input_tokens": 0, "cache_read_input_tokens": 0}}',
                     "cache_key": "Cache OFF",
                     "spend": 0.01383,
                     "total_tokens": 2598,
diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py
index 5022dab32be..9e5917637a8 100644
--- a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py
+++ b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py
@@ -2,6 +2,7 @@ import asyncio
 import datetime
 import json
 from datetime import timezone
+from collections.abc import Mapping
 from typing import Any, Final, cast
 from unittest.mock import AsyncMock, MagicMock, patch
 
@@ -3956,3 +3957,71 @@ def test_passthrough_caching_carries_no_injection_marker():
     )
     metadata = json.loads(payload["metadata"])
     assert metadata["litellm_gateway_injected_cache"] is None
+
+
+def _routed_call_kwargs(model_info: Mapping[str, object]) -> dict[str, object]:
+    return {
+        "model": "claude-haiku-4-5",
+        "custom_llm_provider": "azure_ai",
+        "litellm_call_id": "router-corr-123",
+        "litellm_params": {
+            "metadata": {
+                "user_api_key": "test-key",
+                "model_group": "internal-router/gpt-5.4",
+                "deployment": "azure_ai/claude-haiku-4-5",
+                "model_info": model_info,
+            }
+        },
+    }
+
+
+def test_router_metadata_stamped_for_internal_router_model_deployment():
+    """A deployment flagged model_info.internal_router_model gets a router_metadata
+    block correlating the requested model group with the selected deployment."""
+    payload = get_logging_payload(
+        kwargs=_routed_call_kwargs({"id": "mi-1", "internal_router_model": True}),
+        response_obj=litellm.ModelResponse(id="chatcmpl-router-meta", choices=[], usage=litellm.Usage()),
+        start_time=datetime.datetime.now(timezone.utc),
+        end_time=datetime.datetime.now(timezone.utc),
+    )
+    metadata = json.loads(payload["metadata"])
+    assert metadata["router_metadata"] == {
+        "requested_model": "internal-router/gpt-5.4",
+        "selected_model": "azure_ai/claude-haiku-4-5",
+        "selected_provider": "azure_ai",
+        "router_correlation_id": "router-corr-123",
+    }
+
+
+def test_router_metadata_absent_without_internal_router_model_flag():
+    payload = get_logging_payload(
+        kwargs=_routed_call_kwargs({"id": "mi-1"}),
+        response_obj=litellm.ModelResponse(id="chatcmpl-unflagged", choices=[], usage=litellm.Usage()),
+        start_time=datetime.datetime.now(timezone.utc),
+        end_time=datetime.datetime.now(timezone.utc),
+    )
+    metadata = json.loads(payload["metadata"])
+    assert metadata["router_metadata"] is None
+
+
+@pytest.mark.parametrize("bucket", ["metadata", "litellm_metadata"])
+def test_caller_forged_router_metadata_is_discarded(bucket):
+    """The raw request bucket is client-writable and _get_spend_logs_metadata projects
+    every SpendLogsMetadata key from it, so the server-derived value must overwrite
+    unconditionally or a caller could plant router provenance the router never produced."""
+    payload = get_logging_payload(
+        kwargs={
+            "model": "gpt-4o-mini",
+            "litellm_params": {
+                bucket: {
+                    "user_api_key": "test-key",
+                    "router_metadata": {"requested_model": "forged", "router_correlation_id": "forged-id"},
+                }
+            },
+        },
+        response_obj=litellm.ModelResponse(id="chatcmpl-forged-router-meta", choices=[], usage=litellm.Usage()),
+        start_time=datetime.datetime.now(timezone.utc),
+        end_time=datetime.datetime.now(timezone.utc),
+    )
+    metadata = json.loads(payload["metadata"])
+    assert metadata["router_metadata"] is None
diff --git a/tests/test_litellm/proxy/test_audio_speech_prometheus_hooks.py b/tests/test_litellm/proxy/test_audio_speech_prometheus_hooks.py
index 99f6f3a9b72..959cb2b1e89 100644
--- a/tests/test_litellm/proxy/test_audio_speech_prometheus_hooks.py
+++ b/tests/test_litellm/proxy/test_audio_speech_prometheus_hooks.py
@@ -2,6 +2,7 @@ import asyncio
 import os
 from unittest.mock import AsyncMock, MagicMock, patch
 
+import httpx
 import pytest
 from fastapi.testclient import TestClient
 
@@ -29,6 +30,7 @@ def _make_mock_tts_response():
     inner = MagicMock()
     inner.aiter_bytes = _aiter_bytes
     inner._hidden_params = {}
+    inner.response = httpx.Response(status_code=200, headers={"content-type": "audio/mpeg"})
 
     async def _resolver():
         return inner
diff --git a/tests/test_litellm/proxy/test_budget_reservation.py b/tests/test_litellm/proxy/test_budget_reservation.py
index 95067929ac1..b8fb6170d34 100644
--- a/tests/test_litellm/proxy/test_budget_reservation.py
+++ b/tests/test_litellm/proxy/test_budget_reservation.py
@@ -819,6 +819,94 @@ async def test_should_cap_known_estimate_to_remaining_budget(
     ) == pytest.approx(0.9)
 
 
+@pytest.mark.asyncio
+async def test_fail_closed_rejects_known_estimate_exceeding_remaining_budget(
+    spend_counter_state,
+):
+    """LIT-5922: with strict enforcement on, a request whose known estimate does
+    not fit the remaining budget must be rejected before dispatch instead of
+    having its reservation shrunk to the headroom and admitted, and the counter
+    must be restored to the pre-request spend."""
+    counter_cache, key_cache = spend_counter_state
+    proxy_logging_obj = ProxyLogging(user_api_key_cache=key_cache)
+    valid_token = UserAPIKeyAuth(
+        token="key-budget-known-estimate-fail-closed",
+        spend=0.9,
+        max_budget=1.0,
+    )
+    counter_cache.in_memory_cache.set_cache(
+        key="spend:key:key-budget-known-estimate-fail-closed",
+        value=0.9,
+    )
+
+    with patch(  # test-quality-ok: reserve_budget_for_request takes no estimator, so pinning the estimate needs this attribute
+        "litellm.proxy.spend_tracking.budget_reservation.estimate_request_max_cost",
+        return_value=0.6,
+    ):
+        with pytest.raises(litellm.BudgetExceededError) as exc_info:
+            await reserve_budget_for_request(
+                request_body=_request_body(),
+                route="/chat/completions",
+                llm_router=None,
+                valid_token=valid_token,
+                team_object=None,
+                user_object=None,
+                prisma_client=None,
+                user_api_key_cache=key_cache,
+                proxy_logging_obj=proxy_logging_obj,
+                fail_closed_budget_enforcement=True,
+            )
+
+    assert exc_info.value.current_cost == pytest.approx(0.9)
+    assert exc_info.value.max_budget == pytest.approx(1.0)
+    assert "Current cost: 0.9, Estimated request cost: 0.6, Max budget: 1.0" in str(exc_info.value)
+    assert counter_cache.in_memory_cache.get_cache(
+        key="spend:key:key-budget-known-estimate-fail-closed"
+    ) == pytest.approx(0.9)
+
+
+@pytest.mark.asyncio
+async def test_fail_closed_tolerates_float_noise_when_estimate_exactly_fits(
+    spend_counter_state,
+):
+    """0.1 + 0.2 lands a hair above 0.3 in floating point. Strict enforcement
+    must treat that as fitting the budget, not reject it."""
+    counter_cache, key_cache = spend_counter_state
+    proxy_logging_obj = ProxyLogging(user_api_key_cache=key_cache)
+    valid_token = UserAPIKeyAuth(
+        token="key-budget-fail-closed-float-noise",
+        spend=0.1,
+        max_budget=0.3,
+    )
+    counter_cache.in_memory_cache.set_cache(
+        key="spend:key:key-budget-fail-closed-float-noise",
+        value=0.1,
+    )
+
+    with patch(  # test-quality-ok: reserve_budget_for_request takes no estimator, so pinning the estimate needs this attribute
+        "litellm.proxy.spend_tracking.budget_reservation.estimate_request_max_cost",
+        return_value=0.2,
+    ):
+        reservation = await reserve_budget_for_request(
+            request_body=_request_body(),
+            route="/chat/completions",
+            llm_router=None,
+            valid_token=valid_token,
+            team_object=None,
+            user_object=None,
+            prisma_client=None,
+            user_api_key_cache=key_cache,
+            proxy_logging_obj=proxy_logging_obj,
+            fail_closed_budget_enforcement=True,
+        )
+
+    assert reservation is not None
+    assert reservation["reserved_cost"] == pytest.approx(0.2)
+    assert counter_cache.in_memory_cache.get_cache(
+        key="spend:key:key-budget-fail-closed-float-noise"
+    ) == pytest.approx(0.3)
+
+
 @pytest.mark.asyncio
 async def test_should_clamp_reservation_to_default_when_output_cap_missing(
     spend_counter_state,
diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py
index 833c3754022..df14224af5c 100644
--- a/tests/test_litellm/proxy/test_common_request_processing.py
+++ b/tests/test_litellm/proxy/test_common_request_processing.py
@@ -1659,29 +1659,29 @@ class TestCommonRequestProcessingHelpers:
     async def test_serialize_http_exception_detail_helper(self):
         """Direct unit coverage for the L1 helper across all branches."""
         from litellm.proxy.common_request_processing import (
-            _serialize_http_exception_detail,
+            serialize_http_exception_detail,
         )
         import json as _json
 
-        assert _serialize_http_exception_detail("plain") == ("plain", None)
+        assert serialize_http_exception_detail("plain") == ("plain", None)
 
-        msg, fields = _serialize_http_exception_detail({"error": "Violated", "extra": "x"})
+        msg, fields = serialize_http_exception_detail({"error": "Violated", "extra": "x"})
         assert msg == "Violated"
         assert fields == {"error": "Violated", "extra": "x"}
 
-        msg, fields = _serialize_http_exception_detail({"error": {"message": "blocked", "code": "x"}})
+        msg, fields = serialize_http_exception_detail({"error": {"message": "blocked", "code": "x"}})
         assert msg == "blocked"
         assert fields == {"error": {"message": "blocked", "code": "x"}}
 
-        msg, fields = _serialize_http_exception_detail({"message": "top-level"})
+        msg, fields = serialize_http_exception_detail({"message": "top-level"})
         assert msg == "top-level"
         assert fields == {"message": "top-level"}
 
-        msg, fields = _serialize_http_exception_detail({"weird": ["a", "b"]})
+        msg, fields = serialize_http_exception_detail({"weird": ["a", "b"]})
         assert msg == _json.dumps({"weird": ["a", "b"]})
         assert fields == {"weird": ["a", "b"]}
 
-        assert _serialize_http_exception_detail(42) == ("42", None)
+        assert serialize_http_exception_detail(42) == ("42", None)
 
     async def test_proxy_exception_from_http_exception_helper(self):
         """The shared HTTPException -> ProxyException conversion keeps a clean
@@ -4694,7 +4694,7 @@ class TestAllmPassthroughStreamingProviderGate:
         }
         return ProxyBaseLLMRequestProcessing(data=data)
 
-    async def _run(self, processing_obj, monkeypatch, chunks):
+    async def _run(self, processing_obj, monkeypatch, chunks, stream=None):
         import litellm.proxy.common_request_processing as crp
         from litellm.proxy._types import UserAPIKeyAuth as RealUserAPIKeyAuth
 
@@ -4702,9 +4702,11 @@ class TestAllmPassthroughStreamingProviderGate:
             for chunk in chunks:
                 yield chunk
 
+        upstream_stream = stream if stream is not None else streaming_response()
+
         async def fake_route_request(**kwargs):
             async def _llm_call():
-                return streaming_response()
+                return upstream_stream
 
             return _llm_call()
 
@@ -4729,6 +4731,40 @@ class TestAllmPassthroughStreamingProviderGate:
             skip_pre_call_logic=True,
         )
 
+    @pytest.mark.asyncio
+    async def test_client_disconnect_closes_unbuffered_passthrough_stream(self, monkeypatch):
+        """Starlette abandons the body iterator when the client disconnects, so the
+        unbuffered passthrough branch must return _UpstreamClosingStreamingResponse,
+        whose shielded cleanup closes the upstream stream; that close is what flushes
+        buffered passthrough usage into spend logs."""
+        processing_obj = self._build_processing_obj("gigachat")
+        monkeypatch.setattr(litellm, "callbacks", [])
+        upstream_closed = asyncio.Event()
+
+        async def hanging_stream():
+            try:
+                yield b"chunk-1"
+                await asyncio.Event().wait()
+            finally:
+                upstream_closed.set()
+
+        result = await self._run(processing_obj, monkeypatch, [], stream=hanging_stream())
+
+        assert isinstance(result, _UpstreamClosingStreamingResponse)
+
+        first_chunk_sent = asyncio.Event()
+
+        async def receive():
+            await first_chunk_sent.wait()
+            return {"type": "http.disconnect"}
+
+        async def send(message):
+            if message["type"] == "http.response.body" and message.get("body"):
+                first_chunk_sent.set()
+
+        await result({"type": "http"}, receive, send)
+        await asyncio.wait_for(upstream_closed.wait(), timeout=5)
+
     @pytest.mark.asyncio
     async def test_non_bedrock_stream_is_not_buffered(self, monkeypatch):
         processing_obj = self._build_processing_obj("anthropic")
diff --git a/tests/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py
index 6ea6f208bb5..3e70dee23b7 100644
--- a/tests/test_litellm/proxy/test_proxy_cli.py
+++ b/tests/test_litellm/proxy/test_proxy_cli.py
@@ -2452,6 +2452,96 @@ class TestReadReplicaConnectionParams:
         assert "DATABASE_URL_READ_REPLICA" not in captured
 
 
+class TestMaxIdleConnectionLifetimeDefault:
+    """The proxy defaults `max_idle_connection_lifetime` below common infra idle
+    timeouts so stale pooled connections are recycled instead of failing requests."""
+
+    def _config(self, tmp_path, general_settings):
+        config_path = tmp_path / "config.yaml"
+        config_path.write_text(yaml.dump({"model_list": [], "general_settings": general_settings}))
+        return str(config_path)
+
+    def test_default_applied_to_database_and_direct_url(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            direct_url="postgresql://t:t@localhost:5432/t",
+        )
+
+        for env_var in ("DATABASE_URL", "DIRECT_URL"):
+            query = urlparse.parse_qs(urlparse.urlparse(captured[env_var]).query)
+            assert query["max_idle_connection_lifetime"] == ["60"], env_var
+
+    def test_url_pinned_value_wins_over_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            database_url="postgresql://t:t@localhost:5432/t?max_idle_connection_lifetime=300",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["300"]
+
+    def test_url_pinned_value_wins_over_config_key(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            database_url="postgresql://t:t@localhost:5432/t?max_idle_connection_lifetime=300",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["300"]
+
+    def test_config_key_overrides_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["45"]
+
+    def test_extra_connection_params_override_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(
+                tmp_path,
+                {"database_extra_connection_params": {"max_idle_connection_lifetime": 120}},
+            ),
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["120"]
+
+    def test_read_replica_gets_the_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            read_replica_url="postgresql://t:t@reader:5432/t",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["60"]
+
+    def test_replica_pinned_value_wins(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            read_replica_url="postgresql://t:t@reader:5432/t?max_idle_connection_lifetime=200",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["200"]
+
+    def test_config_key_reaches_the_read_replica(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            read_replica_url="postgresql://t:t@reader:5432/t",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["45"]
+
+    def test_idle_lifetime_params_prefers_configured_value(self):
+        from litellm.proxy.db.db_url_settings import idle_lifetime_params
+
+        assert dict(idle_lifetime_params(45)) == {"max_idle_connection_lifetime": 45}
+        assert dict(idle_lifetime_params(None)) == {"max_idle_connection_lifetime": 60}
+
+
 class TestTokenAuthCliFlags:
     """`--azure_postgresql_auth` has to reach the URL assembly the same way the env var does."""
 
diff --git a/tests/test_litellm/proxy/test_proxy_logging_hook_detection.py b/tests/test_litellm/proxy/test_proxy_logging_hook_detection.py
index 542572e1e56..9f1321aec2c 100644
--- a/tests/test_litellm/proxy/test_proxy_logging_hook_detection.py
+++ b/tests/test_litellm/proxy/test_proxy_logging_hook_detection.py
@@ -346,14 +346,14 @@ async def test_post_call_stream_guardrail_keeps_own_iterator_on_chat_completions
 
 
 @pytest.mark.asyncio
-async def test_unified_guardrail_iterator_accepts_explicit_guardrail(monkeypatch):
+async def test_unified_guardrail_iterator_accepts_explicit_guardrail():
     """
     The dispatch passes each guardrail explicitly instead of through a shared
     request_data key, so chaining two unified-routed guardrails cannot drop
-    all but the last one.
+    all but the last one.  The block fires after the deltas were already
+    flushed to the client, so it surfaces as a trailing in-stream error frame
+    rather than a raised HTTPException.
     """
-    from fastapi import HTTPException
-
     from litellm.proxy.utils import unified_guardrail
 
     guardrail = _content_filter_guardrail("BLOCK")
@@ -367,14 +367,19 @@ async def test_unified_guardrail_iterator_accepts_explicit_guardrail(monkeypatch
         for chunk in _anthropic_stream_chunks(["the", " zebra runs"]):
             yield chunk
 
-    with pytest.raises(HTTPException):
-        async for _ in unified_guardrail.async_post_call_streaming_iterator_hook(
-            user_api_key_dict=UserAPIKeyAuth(api_key="sk-1234", request_route="/v1/messages"),
-            response=fake_stream(),
-            request_data=request_data,
-            guardrail_to_apply=guardrail,
-        ):
-            pass
+    delivered = []
+    async for item in unified_guardrail.async_post_call_streaming_iterator_hook(
+        user_api_key_dict=UserAPIKeyAuth(api_key="sk-1234", request_route="/v1/messages"),
+        response=fake_stream(),
+        request_data=request_data,
+        guardrail_to_apply=guardrail,
+    ):
+        delivered.append(item)
+
+    raw = b"".join(c for c in delivered if isinstance(c, bytes)).decode()
+    assert "event: error" in raw
+    assert "guardrail_error" in raw
+    assert raw.index("guardrail_error") > raw.index(" zebra runs")
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py
index 1de3ed6e56d..4ed6a468371 100644
--- a/tests/test_litellm/proxy/test_proxy_server.py
+++ b/tests/test_litellm/proxy/test_proxy_server.py
@@ -130,6 +130,7 @@ def test_login_v2_returns_redirect_url_and_sets_cookie(monkeypatch):
         password="secret",
         master_key="test-master-key",
         prisma_client=mock_prisma_client,
+        general_settings={},
     )
     mock_create_ui_token_object.assert_called_once_with(
         login_result=mock_login_result,
@@ -147,6 +148,72 @@ def test_login_v2_returns_redirect_url_and_sets_cookie(monkeypatch):
     assert mock_jwt_encode.call_args.kwargs == {"algorithm": "HS256"}
 
 
+def _mock_login_v2_deps(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(
+        "litellm.proxy.auth.login_utils.authenticate_user",
+        AsyncMock(return_value={"user_id": "test-user"}),
+    )
+    monkeypatch.setattr(
+        "litellm.proxy.auth.login_utils.create_ui_token_object",
+        MagicMock(return_value={"user_id": "test-user"}),
+    )
+    monkeypatch.setattr("jwt.encode", MagicMock(return_value="signed-token"))
+    monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
+    monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", MagicMock())
+    monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
+    monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
+    monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+
+
+def test_login_v2_sets_secure_cookie_over_direct_https(monkeypatch):
+    """Regression: the token cookie previously carried no Secure/HttpOnly/SameSite
+    attributes at all, so it was always sent over plain HTTP."""
+    _mock_login_v2_deps(monkeypatch)
+    monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+
+    client = TestClient(app, base_url="https://testserver")
+    response = client.post("/v2/login", json={"username": "alice", "password": "secret"})
+
+    assert response.status_code == 200
+    cookie = response.headers.get("set-cookie")
+    assert "Secure" in cookie
+    assert "HttpOnly" not in cookie  # deliberate: the dashboard reads this cookie via JS
+    assert "samesite=lax" in cookie.lower()
+
+
+def test_login_v2_does_not_set_secure_cookie_over_direct_http(monkeypatch):
+    _mock_login_v2_deps(monkeypatch)
+    monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {})
+
+    client = TestClient(app, base_url="http://testserver")
+    response = client.post("/v2/login", json={"username": "alice", "password": "secret"})
+
+    assert response.status_code == 200
+    assert "Secure" not in response.headers.get("set-cookie")
+
+
+def test_login_v2_sets_secure_cookie_behind_trusted_tls_terminating_proxy(monkeypatch):
+    """THE regression: litellm only sees a plain-HTTP hop when TLS terminates at a
+    reverse proxy, but the token cookie must still be Secure when the direct peer is
+    a configured trusted proxy reporting X-Forwarded-Proto: https."""
+    _mock_login_v2_deps(monkeypatch)
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.general_settings",
+        {"use_x_forwarded_for": True, "mcp_trusted_proxy_ranges": ["10.0.0.0/8"]},
+    )
+
+    client = TestClient(app, base_url="http://testserver", client=("10.0.0.5", 50000))
+    response = client.post(
+        "/v2/login",
+        json={"username": "alice", "password": "secret"},
+        headers={"X-Forwarded-Proto": "https"},
+    )
+
+    assert response.status_code == 200
+    assert "Secure" in response.headers.get("set-cookie")
+
+
 def test_login_v2_returns_json_on_proxy_exception(monkeypatch):
     """Test that /v2/login returns JSON error when ProxyException is raised"""
     from litellm.proxy._types import ProxyErrorTypes, ProxyException
@@ -355,6 +422,51 @@ def test_login_v3_exchange_happy_path(monkeypatch):
     assert exchange_response.cookies.get("token") == "signed-token"
 
 
+def test_login_v3_exchange_sets_secure_cookie_behind_trusted_tls_terminating_proxy(monkeypatch):
+    """Regression: /v3/login/exchange's token cookie must be Secure behind a trusted
+    TLS-terminating reverse proxy even though litellm only sees a plain-HTTP hop."""
+    mock_prisma_client = MagicMock()
+    monkeypatch.setattr(
+        "litellm.proxy.auth.login_utils.authenticate_user",
+        AsyncMock(return_value={"user_id": "test-user"}),
+    )
+    monkeypatch.setattr(
+        "litellm.proxy.auth.login_utils.create_ui_token_object",
+        MagicMock(return_value={"user_id": "test-user"}),
+    )
+    monkeypatch.setattr("jwt.encode", MagicMock(return_value="signed-token"))
+    monkeypatch.setattr("litellm.proxy.proxy_server.master_key", "test-master-key")
+    monkeypatch.setattr(
+        "litellm.proxy.proxy_server.general_settings",
+        {
+            "control_plane_url": "https://cp.example.com",
+            "use_x_forwarded_for": True,
+            "mcp_trusted_proxy_ranges": ["10.0.0.0/8"],
+        },
+    )
+    monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False)
+    monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client)
+    mock_config = MagicMock()
+    mock_config.worker_registry = []
+    monkeypatch.setattr("litellm.proxy.proxy_server.proxy_config", mock_config)
+    monkeypatch.setattr("litellm.proxy.utils.get_server_root_path", lambda: "")
+    monkeypatch.setattr("litellm.proxy.utils.get_proxy_base_url", lambda: None)
+    monkeypatch.delenv("PROXY_BASE_URL", raising=False)
+
+    client = TestClient(app, base_url="http://testserver", client=("10.0.0.5", 50000))
+
+    login_response = client.post("/v3/login", json={"username": "alice", "password": "secret"})
+    code = login_response.json()["code"]
+
+    exchange_response = client.post(
+        "/v3/login/exchange",
+        json={"code": code},
+        headers={"X-Forwarded-Proto": "https"},
+    )
+    assert exchange_response.status_code == 200
+    assert "Secure" in exchange_response.headers.get("set-cookie")
+
+
 def test_login_v3_exchange_single_use(monkeypatch):
     """Code can only be redeemed once."""
     mock_prisma_client = MagicMock()
@@ -10445,6 +10557,75 @@ async def test_update_config_general_settings_emits_audit_log(monkeypatch):
     assert before["some_api_key"] != "sk-stored-secret"
 
 
+@pytest.mark.asyncio
+async def test_update_config_field_rejects_out_of_range_alerting_args(monkeypatch):
+    """Out-of-range alerting_args must be rejected at save time. If they land in the
+    DB, SlackAlertingArgs raises during the config reload and alerting breaks."""
+    from unittest.mock import MagicMock
+
+    from fastapi import HTTPException
+
+    import litellm.proxy.proxy_server as proxy_server_module
+    from litellm.proxy._types import ConfigFieldUpdate
+    from litellm.proxy.proxy_server import update_config_general_settings
+
+    monkeypatch.setattr(proxy_server_module, "prisma_client", MagicMock())
+
+    admin = UserAPIKeyAuth(
+        api_key="hashed-admin",
+        user_id="admin-1",
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+    )
+    with pytest.raises(HTTPException) as exc_info:
+        await update_config_general_settings(
+            data=ConfigFieldUpdate(
+                field_name="alerting_args",
+                field_value={
+                    "daily_spend_per_user_threshold": -5.0,
+                    "user_spend_check_interval": 20,
+                },
+                config_type="general_settings",
+            ),
+            user_api_key_dict=admin,
+        )
+
+    assert exc_info.value.status_code == 400
+    error_msg = exc_info.value.detail["error"]
+    assert "daily_spend_per_user_threshold" in error_msg
+    assert "user_spend_check_interval" in error_msg
+
+
+@pytest.mark.asyncio
+async def test_update_config_field_accepts_valid_alerting_args(monkeypatch):
+    import litellm.proxy.proxy_server as proxy_server_module
+    from litellm.proxy._types import ConfigFieldUpdate
+    from litellm.proxy.proxy_server import update_config_general_settings
+
+    fake = _fake_prisma_with_config({})
+    monkeypatch.setattr(proxy_server_module, "prisma_client", fake)
+    monkeypatch.setattr(litellm, "store_audit_logs", False)
+
+    admin = UserAPIKeyAuth(
+        api_key="hashed-admin",
+        user_id="admin-1",
+        user_role=LitellmUserRoles.PROXY_ADMIN,
+    )
+    await update_config_general_settings(
+        data=ConfigFieldUpdate(
+            field_name="alerting_args",
+            field_value={
+                "daily_spend_per_user_threshold": 5.0,
+                "user_spend_check_interval": 60,
+            },
+            config_type="general_settings",
+        ),
+        user_api_key_dict=admin,
+    )
+
+    written = json.loads(fake.db.litellm_config.upsert.call_args.kwargs["data"]["update"]["param_value"])
+    assert written["alerting_args"]["daily_spend_per_user_threshold"] == 5.0
+
+
 @pytest.mark.asyncio
 async def test_update_config_general_settings_applies_ssrf_globals(monkeypatch):
     import litellm.proxy.proxy_server as proxy_server_module
@@ -10713,11 +10894,54 @@ def test_update_config_redacts_all_environment_variable_values(_update_config_se
 class _EnvBuiltRedisCache(RedisCache):
     """RedisCache stand-in that records its constructor kwargs and never
     opens a network connection, so tests can assert which connection params
-    the proxy used to build its coordination Redis."""
+    the proxy used to build its coordination Redis. `ping()` reports reachable
+    by default, matching a real Redis the env fallback should adopt."""
 
     def __init__(self, **kwargs):
         self.init_kwargs = kwargs
 
+    async def ping(self) -> bool:
+        return True
+
+
+class _UnreachableRedisCache(_EnvBuiltRedisCache):
+    """Same stand-in, but `ping()` fails like a REDIS_* env var naming a Redis
+    that is not actually reachable (wrong host, no service running, ...)."""
+
+    async def ping(self) -> bool:
+        raise ConnectionError("connection refused")
+
+
+@contextlib.contextmanager
+def _patched_coordination_redis_module_state(
+    *,
+    spend_cache: DualCache,
+    config_cache: types.SimpleNamespace,
+    redis_cache_class: type = _EnvBuiltRedisCache,
+):
+    """Stub every `litellm.proxy.proxy_server` global that
+    `_attach_redis_usage_cache` (and its callers) can write to, shared by the
+    whole coordination-Redis test family below.
+
+    Centralizing this is not just DRY: `_attach_redis_usage_cache` always sets
+    `cli_sso_session_cache.redis_cache` unconditionally, and a call site that
+    forgets to patch that one real (persistent) global leaks a throwaway
+    Redis stand-in into it for the rest of the pytest session, breaking
+    unrelated tests that run later. One patched-state helper means a new call
+    site cannot forget a global this family already knows to isolate.
+    """
+    with (
+        patch.object(proxy_server_module, "redis_usage_cache", None),
+        patch.object(proxy_server_module, "spend_counter_cache", spend_cache),
+        patch.object(proxy_server_module, "user_api_key_cache", DualCache()),
+        patch.object(proxy_server_module, "cli_sso_session_cache", DualCache()),
+        patch.object(proxy_server_module, "llm_router", None),
+        patch.object(proxy_server_module, "litellm_config_cache", config_cache),
+        patch.object(proxy_server_module, "RedisCache", redis_cache_class),
+        patch.object(proxy_server_module, "RedisClusterCache", _EnvBuiltClusterCache),
+    ):
+        yield
+
 
 def _run_init_cache_with_backend(cache_backend, redis_env_kwargs):
     """Run ProxyConfig._init_cache with a stubbed response-cache backend and a
@@ -10729,12 +10953,7 @@ def _run_init_cache_with_backend(cache_backend, redis_env_kwargs):
     fresh_config_cache = types.SimpleNamespace(redis_cache=None)
 
     with (
-        patch.object(proxy_server_module, "redis_usage_cache", None),
-        patch.object(proxy_server_module, "spend_counter_cache", fresh_spend_cache),
-        patch.object(proxy_server_module, "user_api_key_cache", DualCache()),
-        patch.object(proxy_server_module, "llm_router", None),
-        patch.object(proxy_server_module, "litellm_config_cache", fresh_config_cache),
-        patch.object(proxy_server_module, "RedisCache", _EnvBuiltRedisCache),
+        _patched_coordination_redis_module_state(spend_cache=fresh_spend_cache, config_cache=fresh_config_cache),
         patch(
             "litellm._redis._redis_kwargs_from_environment",
             return_value=redis_env_kwargs,
@@ -10809,12 +11028,7 @@ def _run_init_coordination_redis(config, env=None):
     fresh_config_cache = types.SimpleNamespace(redis_cache=None)
 
     with (
-        patch.object(proxy_server_module, "redis_usage_cache", None),
-        patch.object(proxy_server_module, "spend_counter_cache", fresh_spend_cache),
-        patch.object(proxy_server_module, "user_api_key_cache", DualCache()),
-        patch.object(proxy_server_module, "litellm_config_cache", fresh_config_cache),
-        patch.object(proxy_server_module, "RedisCache", _EnvBuiltRedisCache),
-        patch.object(proxy_server_module, "RedisClusterCache", _EnvBuiltClusterCache),
+        _patched_coordination_redis_module_state(spend_cache=fresh_spend_cache, config_cache=fresh_config_cache),
         mock.patch.dict(os.environ, env or {}, clear=False),
     ):
         built = proxy_server_module.ProxyConfig()._init_coordination_redis(config=config)
@@ -10902,13 +11116,7 @@ def test_explicit_coordination_redis_takes_precedence_over_cache_backend():
     mock_litellm_cache.cache = cache_backend
 
     with (
-        patch.object(proxy_server_module, "redis_usage_cache", None),
-        patch.object(proxy_server_module, "spend_counter_cache", fresh_spend_cache),
-        patch.object(proxy_server_module, "user_api_key_cache", DualCache()),
-        patch.object(proxy_server_module, "llm_router", None),
-        patch.object(proxy_server_module, "litellm_config_cache", fresh_config_cache),
-        patch.object(proxy_server_module, "RedisCache", _EnvBuiltRedisCache),
-        patch.object(proxy_server_module, "RedisClusterCache", _EnvBuiltClusterCache),
+        _patched_coordination_redis_module_state(spend_cache=fresh_spend_cache, config_cache=fresh_config_cache),
         patch("litellm.Cache", return_value=mock_litellm_cache),
     ):
         litellm.cache = None
@@ -10926,6 +11134,95 @@ def test_explicit_coordination_redis_takes_precedence_over_cache_backend():
         assert fresh_spend_cache.redis_cache is usage_cache
 
 
+async def _run_init_coordination_redis_env_fallback(
+    litellm_settings, redis_env_kwargs, redis_cache_class=_EnvBuiltRedisCache
+):
+    """Run ProxyConfig._init_coordination_redis_env_fallback against a
+    stubbed module state and a controlled REDIS_* environment, returning
+    (built, spend_counter redis)."""
+    fresh_spend_cache = DualCache()
+    fresh_config_cache = types.SimpleNamespace(redis_cache=None)
+
+    with (
+        _patched_coordination_redis_module_state(
+            spend_cache=fresh_spend_cache, config_cache=fresh_config_cache, redis_cache_class=redis_cache_class
+        ),
+        patch(
+            "litellm._redis._redis_kwargs_from_environment",
+            return_value=redis_env_kwargs,
+        ),
+    ):
+        built = await proxy_server_module.ProxyConfig._init_coordination_redis_env_fallback(
+            litellm_settings=litellm_settings
+        )
+        return built, fresh_spend_cache.redis_cache
+
+
+@pytest.mark.asyncio
+async def test_init_coordination_redis_env_fallback_builds_from_environment():
+    """A deployment with no coordination_redis block and no litellm_settings.cache
+    but with bare REDIS_HOST/REDIS_PORT env vars must still get a coordination
+    Redis: otherwise spend counters, budget-window enforcement, and the
+    reset_spend cache-eviction broadcast stay per-pod local and a reset issued
+    on one pod never clears another pod's stale enforcement."""
+    built, spend_redis = await _run_init_coordination_redis_env_fallback(
+        litellm_settings={},
+        redis_env_kwargs={"host": "env-fallback-host", "port": "6390"},
+    )
+
+    assert isinstance(built, _EnvBuiltRedisCache)
+    assert built.init_kwargs["host"] == "env-fallback-host"
+    assert spend_redis is built
+
+
+@pytest.mark.asyncio
+async def test_init_coordination_redis_env_fallback_without_redis_env_returns_none():
+    """With no REDIS_* connection info at all, the fallback must leave the
+    coordination Redis unset rather than building a broken client."""
+    built, spend_redis = await _run_init_coordination_redis_env_fallback(
+        litellm_settings={},
+        redis_env_kwargs={},
+    )
+
+    assert built is None
+    assert spend_redis is None
+
+
+@pytest.mark.asyncio
+async def test_init_coordination_redis_env_fallback_unreachable_stays_in_memory():
+    """REDIS_* env vars can name a Redis that is not actually reachable (wrong
+    host, leftover from an unrelated job/service). Guessing "coordination
+    available" from bare env vars must not turn a previously harmless
+    in-memory-only proxy into one that raises on its next cache write, so an
+    unreachable ping must leave everything exactly as if no REDIS_* vars were
+    set at all."""
+    built, spend_redis = await _run_init_coordination_redis_env_fallback(
+        litellm_settings={},
+        redis_env_kwargs={"host": "unreachable-host", "port": "6390"},
+        redis_cache_class=_UnreachableRedisCache,
+    )
+
+    assert built is None
+    assert spend_redis is None
+
+
+@pytest.mark.asyncio
+async def test_init_coordination_redis_env_fallback_malformed_cluster_nodes_stays_in_memory():
+    """REDIS_CLUSTER_NODES can be set to a malformed value nothing here ever
+    asked to be parsed. Unlike the explicit coordination_redis block (a
+    deliberate opt-in, so a bad value there should fail loudly), this
+    inferred fallback must not abort proxy startup over it -- it has to
+    decline the same way it does for an absent or unreachable Redis."""
+    with mock.patch.dict(os.environ, {"REDIS_CLUSTER_NODES": "not-valid-json"}, clear=False):
+        built, spend_redis = await _run_init_coordination_redis_env_fallback(
+            litellm_settings={},
+            redis_env_kwargs={},
+        )
+
+    assert built is None
+    assert spend_redis is None
+
+
 def test_env_fallback_builds_cluster_client_from_cluster_nodes_env():
     """A deployment whose only Redis env is REDIS_CLUSTER_NODES must still get
     a coordination Redis from the env fallback, and it must be a cluster
@@ -10967,11 +11264,7 @@ async def test_startup_applies_coordination_redis_saved_in_database():
     fresh_config_cache = types.SimpleNamespace(redis_cache=None)
 
     with (
-        patch.object(proxy_server_module, "spend_counter_cache", fresh_spend_cache),
-        patch.object(proxy_server_module, "user_api_key_cache", DualCache()),
-        patch.object(proxy_server_module, "litellm_config_cache", fresh_config_cache),
-        patch.object(proxy_server_module, "RedisCache", _EnvBuiltRedisCache),
-        patch.object(proxy_server_module, "RedisClusterCache", _EnvBuiltClusterCache),
+        _patched_coordination_redis_module_state(spend_cache=fresh_spend_cache, config_cache=fresh_config_cache),
         patch.object(
             proxy_server_module,
             "get_persisted_coordination_redis_settings",
@@ -11399,35 +11692,10 @@ async def test_no_window_spend_row_enqueued_without_budget_limits():
     assert enqueued == []
 
 
-@pytest.mark.asyncio
-async def test_window_spend_row_carries_the_spend_log_request_id():
-    """The flush excludes these ids from its one-time seed, so the id threaded
-    here has to be the same one the LiteLLM_SpendLogs row was written under."""
-    from litellm.proxy.proxy_server import increment_spend_counters
-
-    reset_at = datetime.now(timezone.utc) + timedelta(days=10)
-    key_obj = MagicMock()
-    key_obj.budget_limits = [
-        {"budget_duration": "30d", "max_budget": 100.0, "reset_at": reset_at.isoformat()}
-    ]
-
-    with _window_spend_enqueue_env({"hashed-token": key_obj}) as queue:
-        await increment_spend_counters(
-            token="hashed-token",
-            team_id=None,
-            user_id=None,
-            response_cost=0.25,
-            request_id="chatcmpl-abc123",
-        )
-        enqueued = await _drain(queue)
-
-    assert enqueued[0]["request_ids"] == ("chatcmpl-abc123",)
-
-
 @pytest.mark.asyncio
 async def test_window_spend_row_carries_the_request_start_time():
-    """The seed only excludes a batch id whose LiteLLM_SpendLogs.startTime is at
-    or after this, so it must be the same start the spend log was written with."""
+    """The seed sums LiteLLM_SpendLogs only up to this point, so it must be the
+    same start the spend log row was written with."""
     from litellm.proxy.proxy_server import increment_spend_counters
 
     reset_at = datetime.now(timezone.utc) + timedelta(days=10)
@@ -11442,7 +11710,6 @@ async def test_window_spend_row_carries_the_request_start_time():
             team_id=None,
             user_id=None,
             response_cost=0.25,
-            request_id="chatcmpl-abc123",
             request_started_at=datetime(2026, 8, 10, 12, 0, 0, 500_000, tzinfo=timezone.utc),
         )
         enqueued = await _drain(queue)
@@ -11451,26 +11718,7 @@ async def test_window_spend_row_carries_the_request_start_time():
 
 
 @pytest.mark.asyncio
-async def test_window_spend_row_without_a_request_id_excludes_nothing():
-    from litellm.proxy.proxy_server import increment_spend_counters
-
-    reset_at = datetime.now(timezone.utc) + timedelta(days=10)
-    key_obj = MagicMock()
-    key_obj.budget_limits = [
-        {"budget_duration": "30d", "max_budget": 100.0, "reset_at": reset_at.isoformat()}
-    ]
-
-    with _window_spend_enqueue_env({"hashed-token": key_obj}) as queue:
-        await increment_spend_counters(
-            token="hashed-token", team_id=None, user_id=None, response_cost=0.25
-        )
-        enqueued = await _drain(queue)
-
-    assert enqueued[0]["request_ids"] == ()
-
-
-@pytest.mark.asyncio
-async def test_team_window_spend_row_carries_the_request_id():
+async def test_team_window_spend_row_carries_the_request_start_time():
     from litellm.proxy.proxy_server import increment_spend_counters
 
     reset_at = datetime.now(timezone.utc) + timedelta(days=3)
@@ -11485,11 +11733,11 @@ async def test_team_window_spend_row_carries_the_request_id():
             team_id="team-1",
             user_id=None,
             response_cost=1.5,
-            request_id="chatcmpl-team",
+            request_started_at=datetime(2026, 8, 10, 12, 0, 0, 500_000, tzinfo=timezone.utc),
         )
         enqueued = await _drain(queue)
 
-    assert enqueued[0]["request_ids"] == ("chatcmpl-team",)
+    assert enqueued[0]["started_at"] == "2026-08-10T12:00:00.500000"
 
 
 def _mock_startup_prisma_client(health_check_error=None, connect_error=None):
@@ -12165,3 +12413,97 @@ async def test_load_config_router_authorizes_fallback_targets_against_the_callin
     router, _, _ = await ProxyConfig().load_config(router=None, config_file_path=str(config_file))
 
     assert router.fallback_access_check is router_fallback_access_check
+
+
+def test_docs_redoc_openapi_are_reachable_by_default():
+    """
+    LIT-6745: the interactive/machine-readable docs surfaces are on by
+    default (the customer-facing production toggle is opt-in, not opt-out).
+    """
+    client = TestClient(app)
+
+    assert client.get("/redoc").status_code == 200
+    openapi_response = client.get("/openapi.json")
+    assert openapi_response.status_code == 200
+    assert "paths" in openapi_response.json()
+
+
+def test_production_app_docs_urls_are_wired_to_the_real_env_helpers():
+    """
+    LIT-6745: pins the actual `FastAPI(docs_url=..., redoc_url=..., openapi_url=...)`
+    construction in proxy_server.py to _get_docs_url/_get_redoc_url/_get_openapi_url,
+    so a hardcoded or drifted value at that call site fails this test even though
+    the helpers themselves are covered separately.
+    """
+    from litellm.proxy import utils as proxy_utils
+
+    assert app.docs_url == proxy_utils._get_docs_url()
+    assert app.redoc_url == proxy_utils._get_redoc_url()
+    assert app.openapi_url == proxy_utils._get_openapi_url()
+
+
+def _build_app_with_docs_env(monkeypatch, *, disabled: bool) -> FastAPI:
+    from litellm.proxy import utils as proxy_utils
+    from litellm.proxy.health_endpoints._health_endpoints import router as health_router
+
+    for flag in ("DOCS_URL", "REDOC_URL", "OPENAPI_URL"):
+        monkeypatch.delenv(flag, raising=False)
+    for flag in ("NO_DOCS", "NO_REDOC", "NO_OPENAPI"):
+        if disabled:
+            monkeypatch.setenv(flag, "True")
+        else:
+            monkeypatch.delenv(flag, raising=False)
+
+    # Mirrors the exact FastAPI() construction in proxy_server.py, so this
+    # exercises the real gating mechanism rather than a reimplementation of it.
+    app_under_test = FastAPI(
+        docs_url=proxy_utils._get_docs_url(),
+        redoc_url=proxy_utils._get_redoc_url(),
+        openapi_url=proxy_utils._get_openapi_url(),
+    )
+    app_under_test.include_router(health_router)
+    return app_under_test
+
+
+def test_docs_endpoints_enabled_when_env_unset(monkeypatch):
+    app_under_test = _build_app_with_docs_env(monkeypatch, disabled=False)
+    assert app_under_test.docs_url == "/"
+    assert app_under_test.redoc_url == "/redoc"
+    assert app_under_test.openapi_url == "/openapi.json"
+
+    client = TestClient(app_under_test)
+    assert client.get(app_under_test.docs_url).status_code == 200
+    assert client.get(app_under_test.redoc_url).status_code == 200
+    assert client.get(app_under_test.openapi_url).status_code == 200
+
+
+def test_no_docs_no_redoc_no_openapi_disable_every_documentation_surface(monkeypatch):
+    """
+    LIT-6745: NO_DOCS, NO_REDOC and NO_OPENAPI must each 404 their surface
+    with no schema in the body, so a production/air-gapped deployment can
+    restrict every doc route consistently.
+    """
+    app_under_test = _build_app_with_docs_env(monkeypatch, disabled=True)
+    assert app_under_test.docs_url is None
+    assert app_under_test.redoc_url is None
+    assert app_under_test.openapi_url is None
+
+    client = TestClient(app_under_test)
+    for route in ("/", "/redoc", "/openapi.json"):
+        response = client.get(route)
+        assert response.status_code == 404
+        assert "openapi" not in response.text.lower()
+        assert "paths" not in response.text.lower()
+
+
+def test_disabling_docs_does_not_disable_other_routes(monkeypatch):
+    """
+    LIT-6745: disabling the doc surfaces must not affect inference/management
+    routes, since NO_DOCS/NO_REDOC/NO_OPENAPI only remove the routes FastAPI
+    itself auto-registers for docs_url/redoc_url/openapi_url.
+    """
+    app_under_test = _build_app_with_docs_env(monkeypatch, disabled=True)
+    client = TestClient(app_under_test)
+
+    assert client.get("/redoc").status_code == 404
+    assert client.get("/health/liveliness").status_code == 200
diff --git a/tests/test_litellm/proxy/test_redis_auth_cache_flag.py b/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
index 772b08bc9d0..573bfc40c96 100644
--- a/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
+++ b/tests/test_litellm/proxy/test_redis_auth_cache_flag.py
@@ -5,7 +5,7 @@ Verifies that _init_cache attaches Redis to user_api_key_cache only when
 the flag is explicitly set to True, and leaves it in-memory-only otherwise.
 """
 
-from contextlib import contextmanager
+from contextlib import ExitStack, contextmanager
 import json
 from unittest.mock import MagicMock, patch
 
@@ -167,3 +167,25 @@ class TestRedisAuthCacheFlag:
                     f"cli_sso_session_cache must always get Redis "
                     f"(enable_redis_auth_cache={flag_value!r})"
                 )
+
+    def test_flag_absent_still_shares_the_model_budget_counters_over_redis(self):
+        """
+        Per-model budget counters are spend counters: the limiter must be able to
+        push and read them through Redis without the auth-cache opt-in, or every
+        worker enforces and reports its own share of a key's spend
+        """
+        fake_redis = _FakeRedisCache()
+        limiter_cache = ps.model_max_budget_limiter.dual_cache
+        touched_caches = (
+            limiter_cache,
+            ps.spend_counter_cache,
+            ps.cli_sso_session_cache,
+            ps.user_api_key_cache,
+            ps.litellm_config_cache,
+        )
+        with ExitStack() as detached:
+            for cache in touched_caches:
+                detached.enter_context(patch.object(cache, "redis_cache", None))
+            ps._attach_redis_usage_cache(fake_redis, enable_redis_auth_cache=False)
+            assert limiter_cache.redis_cache is fake_redis
+            assert ps.user_api_key_cache.redis_cache is None
diff --git a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py
index dc256ccf718..709447d23c0 100644
--- a/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py
+++ b/tests/test_litellm/proxy/ui_crud_endpoints/test_proxy_setting_endpoints.py
@@ -3006,6 +3006,128 @@ def test_update_mcp_semantic_filter_settings_requires_proxy_admin(monkeypatch):
         app.dependency_overrides.pop(user_api_key_auth, None)
 
 
+class TestMcpToolSearchSettingsEndpoints:
+    """`litellm_settings.mcp_tool_search` drives the native `mcp_tool_search` virtual tool, so the UI must round-trip it."""
+
+    @staticmethod
+    def _override_auth(role: LitellmUserRoles):
+        from litellm.proxy._types import UserAPIKeyAuth
+        from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+
+        app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth(
+            user_id="u", api_key="hashed", user_role=role
+        )
+
+    def test_get_returns_stored_values_and_field_schema(self, mock_proxy_config, mock_auth, monkeypatch):
+        monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", object())
+        mock_proxy_config["config"]["litellm_settings"]["mcp_tool_search"] = {
+            "embedding_model": "text-embedding-3-small",
+            "core_tools": ["treasury-get_rates"],
+        }
+
+        resp = client.get("/get/mcp_tool_search_settings")
+
+        assert resp.status_code == 200, resp.text
+        assert resp.json()["values"] == {
+            "embedding_model": "text-embedding-3-small",
+            "top_k": 5,
+            "similarity_threshold": 0.0,
+            "core_tools": ["treasury-get_rates"],
+        }
+        assert resp.json()["field_schema"]["properties"]["core_tools"]["type"] == "array"
+
+    def test_update_requires_proxy_admin(self, monkeypatch):
+        monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True)
+        self._override_auth(LitellmUserRoles.INTERNAL_USER)
+        try:
+            resp = client.patch("/update/mcp_tool_search_settings", json={"top_k": 3})
+        finally:
+            app.dependency_overrides.clear()
+        assert resp.status_code == 403
+
+    def test_update_persists_and_applies_in_memory(self, mock_proxy_config, monkeypatch):
+        import litellm
+
+        monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True)
+        monkeypatch.setattr(litellm, "mcp_tool_search", None)
+        self._override_auth(LitellmUserRoles.PROXY_ADMIN)
+        payload = {
+            "embedding_model": "text-embedding-3-small",
+            "top_k": 3,
+            "similarity_threshold": 0.25,
+            "core_tools": ["treasury-get_rates"],
+        }
+        try:
+            resp = client.patch("/update/mcp_tool_search_settings", json=payload)
+        finally:
+            app.dependency_overrides.clear()
+
+        assert resp.status_code == 200, resp.text
+        assert mock_proxy_config["save_call_count"]() == 1
+        assert litellm.mcp_tool_search == payload
+        assert mock_proxy_config["config"]["litellm_settings"]["mcp_tool_search"] == payload
+
+    def test_update_rejects_out_of_range_top_k(self, mock_proxy_config, monkeypatch):
+        monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", True)
+        self._override_auth(LitellmUserRoles.PROXY_ADMIN)
+        try:
+            resp = client.patch("/update/mcp_tool_search_settings", json={"top_k": 0})
+        finally:
+            app.dependency_overrides.clear()
+        assert resp.status_code == 422
+        assert mock_proxy_config["save_call_count"]() == 0
+
+
+def test_upload_logo_requires_proxy_admin(monkeypatch):
+    """Any authenticated key could previously write a file to the server's disk here."""
+    from litellm.proxy._types import UserAPIKeyAuth
+    from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+
+    async def _internal_user_auth():
+        return UserAPIKeyAuth(
+            user_id="internal-user-1",
+            api_key="hashed-internal-key",
+            user_role=LitellmUserRoles.INTERNAL_USER,
+        )
+
+    app.dependency_overrides[user_api_key_auth] = _internal_user_auth
+    try:
+        resp = client.post(
+            "/upload/logo",
+            files={"file": ("logo.png", b"\x89PNG\r\n\x1a\n" + b"x" * 32, "image/png")},
+        )
+        assert resp.status_code == 403
+        assert "proxy admin" in resp.json()["detail"].lower()
+    finally:
+        app.dependency_overrides.pop(user_api_key_auth, None)
+
+
+def test_upload_logo_allows_proxy_admin(monkeypatch, tmp_path):
+    from litellm.proxy._types import UserAPIKeyAuth
+    from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+
+    async def _admin_auth():
+        return UserAPIKeyAuth(
+            user_id="admin-1",
+            api_key="hashed-admin-key",
+            user_role=LitellmUserRoles.PROXY_ADMIN,
+        )
+
+    app.dependency_overrides[user_api_key_auth] = _admin_auth
+    try:
+        resp = client.post(
+            "/upload/logo",
+            files={"file": ("logo.png", b"\x89PNG\r\n\x1a\n" + b"x" * 32, "image/png")},
+        )
+        assert resp.status_code == 200, resp.text
+        assert resp.json()["status"] == "success"
+    finally:
+        app.dependency_overrides.pop(user_api_key_auth, None)
+        uploaded_path = resp.json().get("file_path")
+        if uploaded_path and os.path.exists(uploaded_path):
+            os.remove(uploaded_path)
+
+
 class TestPtuCostAttributionUISetting:
     """``enable_ptu_cost_attribution`` is derived from the environment on every GET.
 
diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py b/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py
index cede859cb38..77c0f71dbf9 100644
--- a/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py
+++ b/tests/test_litellm/proxy/utils/proxy_logging/test_alerting.py
@@ -115,6 +115,35 @@ async def test_budget_alerts_slack_when_slack_alerting(proxy_logging):
     assert snapshot == {"type": "user_budget", "user_info_is_callinfo": True, "user_id": "u1"}
 
 
+@pytest.mark.asyncio
+async def test_budget_alerts_webhook_only_forwards_to_slack_alerting_instance(proxy_logging):
+    proxy_logging.alerting = ["webhook"]
+    captured: Dict[str, Any] = {}
+
+    async def fake_alert(**kwargs):
+        captured.update(kwargs)
+
+    proxy_logging.slack_alerting_instance = MagicMock(budget_alerts=fake_alert)
+    proxy_logging.email_logging_instance = None
+    await proxy_logging.budget_alerts(type="user_budget", user_info=_user_info())
+    snapshot = {
+        "type": captured["type"],
+        "user_info_is_callinfo": isinstance(captured["user_info"], CallInfo),
+        "user_id": captured["user_info"].user_id,
+    }
+    assert snapshot == {"type": "user_budget", "user_info_is_callinfo": True, "user_id": "u1"}
+
+
+@pytest.mark.asyncio
+async def test_budget_alerts_email_only_skips_slack_alerting_instance(proxy_logging):
+    proxy_logging.alerting = ["email"]
+    proxy_logging.slack_alerting_instance = MagicMock(budget_alerts=AsyncMock())
+    proxy_logging.email_logging_instance = MagicMock(budget_alerts=AsyncMock())
+    await proxy_logging.budget_alerts(type="user_budget", user_info=_user_info())
+    proxy_logging.slack_alerting_instance.budget_alerts.assert_not_called()
+    proxy_logging.email_logging_instance.budget_alerts.assert_called_once()
+
+
 @pytest.mark.asyncio
 async def test_budget_alerts_soft_budget_with_alert_emails_bypasses_global(proxy_logging):
     proxy_logging.alerting = None
diff --git a/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py b/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
index eae6f90863a..45a0221c8a6 100644
--- a/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
+++ b/tests/test_litellm/proxy/vector_store_endpoints/test_vector_store_endpoints.py
@@ -3158,3 +3158,35 @@ class TestAzureAIAnalyzeNamedIndexClassification:
             user_api_key_dict=self._team_member("analyze", ["read"]),
         )
         assert result is True
+
+
+@pytest.mark.parametrize(
+    "blocked_key",
+    ["embedding_model", "litellm_embedding_model", "litellm_embedding_config", "litellm_credential_name"],
+)
+def test_vector_store_search_rejects_caller_embedding_selection_params(blocked_key):
+    """
+    Regression: the search request body must not pick the embedding model or
+    credential used to embed the query. Those resolve through the Router with
+    the proxy's credentials, bypassing the key's model permissions, so they may
+    only come from the managed store's server-side registration.
+    """
+    from fastapi.testclient import TestClient
+
+    from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+    from litellm.proxy.proxy_server import app
+
+    mock_auth = UserAPIKeyAuth(user_id="test_internal_user", user_role=LitellmUserRoles.INTERNAL_USER.value)
+    original_overrides = app.dependency_overrides.copy()
+    app.dependency_overrides[user_api_key_auth] = lambda: mock_auth
+    try:
+        client = TestClient(app)
+        response = client.post(
+            "/v1/vector_stores/s3-store/search",
+            json={"query": "hello", blocked_key: "attacker-choice"},
+        )
+    finally:
+        app.dependency_overrides = original_overrides
+
+    assert response.status_code == 400, response.json()
+    assert blocked_key in str(response.json())
diff --git a/tests/test_litellm/rag/test_main.py b/tests/test_litellm/rag/test_main.py
index 2d1b460513f..51d03544910 100644
--- a/tests/test_litellm/rag/test_main.py
+++ b/tests/test_litellm/rag/test_main.py
@@ -259,6 +259,135 @@ async def test_aquery_streaming_bills_sub_call_costs_into_final_event():
     assert standard_logging_object["response_cost"] >= 0.003
 
 
+@pytest.mark.asyncio
+async def test_aquery_forwards_provider_retrieval_config_and_router_to_search():
+    """
+    Regression: provider-specific retrieval_config keys (aws_region_name,
+    embedding_model, vector_bucket_name, ...) and the router must be forwarded
+    to the vector store search call. Pre-fix they were silently dropped, so
+    /v1/rag/query failed with provider config errors (e.g. S3 Vectors
+    "aws_region_name is required") even when the caller supplied them.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-4o-mini",
+                "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "test-key"},
+            }
+        ]
+    )
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        response = await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={
+                "vector_store_id": "bkt:idx",
+                "custom_llm_provider": "s3_vectors",
+                "top_k": 5,
+                "aws_region_name": "eu-west-1",
+                "embedding_model": "my-embed",
+                "vector_bucket_name": "bkt",
+            },
+            router=router,
+            mock_response="hi",
+        )
+
+    assert isinstance(response, ModelResponse)
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["vector_store_id"] == "bkt:idx"
+    assert search_kwargs["custom_llm_provider"] == "s3_vectors"
+    assert search_kwargs["max_num_results"] == 5
+    assert search_kwargs["router"] is router
+    # provider-specific extras forwarded
+    assert search_kwargs["aws_region_name"] == "eu-west-1"
+    assert search_kwargs["embedding_model"] == "my-embed"
+    assert search_kwargs["vector_bucket_name"] == "bkt"
+    # consumed keys are not duplicated into the spread
+    assert "top_k" not in search_kwargs
+
+
+@pytest.mark.asyncio
+async def test_aquery_minimal_retrieval_config_forwards_no_extras():
+    """
+    A minimal retrieval_config must not leak consumed keys (or invent extras)
+    into the vector store search call.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={"vector_store_id": "vs_test_123", "custom_llm_provider": "openai"},
+            mock_response="hi",
+        )
+
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["vector_store_id"] == "vs_test_123"
+    assert search_kwargs["custom_llm_provider"] == "openai"
+    assert search_kwargs["router"] is None
+    leaked = {"top_k", "filters", "retrieval_filter", "aws_region_name", "embedding_model", "vector_bucket_name"}
+    assert not (leaked & set(search_kwargs.keys()))
+
+
+@pytest.mark.asyncio
+async def test_aquery_does_not_forward_connection_override_keys_to_search():
+    """
+    Only allowlisted retrieval_config keys may reach the vector store search
+    call. Caller-controlled connection overrides (api_base, api_key, arbitrary
+    extras) must be dropped, otherwise a caller could redirect store
+    credentials to an attacker-chosen host.
+    """
+    from unittest.mock import AsyncMock
+
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    fake_search = AsyncMock(
+        return_value=VectorStoreSearchResponse(
+            object="vector_store.search_results.page", search_query="q", data=[]
+        )
+    )
+    with patch("litellm.vector_stores.asearch", new=fake_search):  # test-quality-ok: asearch is the boundary the forwarding contract under test targets
+        await litellm.aquery(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": "hello"}],
+            retrieval_config={
+                "vector_store_id": "bkt:idx",
+                "custom_llm_provider": "s3_vectors",
+                "aws_region_name": "eu-west-1",
+                "api_base": "https://attacker.example.com",
+                "api_key": "attacker-key",
+                "arbitrary_extra": "nope",
+            },
+            mock_response="hi",
+        )
+
+    fake_search.assert_awaited_once()
+    search_kwargs = fake_search.await_args.kwargs
+    assert search_kwargs["aws_region_name"] == "eu-west-1"
+    blocked = {"api_base", "api_key", "arbitrary_extra"}
+    assert not (blocked & set(search_kwargs.keys()))
+
+
 def test_rag_call_types_are_registered():
     """
     query/aquery/ingest/aingest are @client-decorated entry points, so their
diff --git a/tests/test_litellm/rerank_api/test_main.py b/tests/test_litellm/rerank_api/test_main.py
index 587be59c550..2b6cfeda2c2 100644
--- a/tests/test_litellm/rerank_api/test_main.py
+++ b/tests/test_litellm/rerank_api/test_main.py
@@ -111,6 +111,99 @@ def test_together_rerank_honors_api_base(respx_mock: respx.MockRouter):
     assert mock_route.calls[0].request.headers["authorization"] == "Bearer fake-together-key"
 
 
+DASHSCOPE_404_BODY = {
+    "error": {
+        "message": "The model `does-not-exist` does not exist or you do not have access to it.",
+        "type": "invalid_request_error",
+        "param": None,
+        "code": "model_not_found",
+    },
+    "request_id": "mock-request-id",
+}
+
+
+def test_rerank_error_names_provider_and_keeps_body(respx_mock: respx.MockRouter, monkeypatch):
+    """Regression for the rerank error path mapping with the unresolved provider param:
+    a provider 404 surfaced as 'None - ' instead of naming the provider and its error body."""
+    monkeypatch.delenv("DASHSCOPE_API_BASE", raising=False)
+    monkeypatch.delenv("DASHSCOPE_API_BASE_RERANK", raising=False)
+
+    mock_route = respx_mock.post("https://dashscope.example/v1/reranks")
+    mock_route.return_value = httpx.Response(404, json=DASHSCOPE_404_BODY)
+
+    with pytest.raises(litellm.NotFoundError) as exc_info:
+        litellm.rerank(
+            model="dashscope/does-not-exist",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+            api_key="fake-dashscope-key",
+            api_base="https://dashscope.example/v1",
+        )
+
+    assert mock_route.called
+    assert "DashscopeException" in str(exc_info.value)
+    assert "does not exist or you do not have access to it" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_arerank_error_is_mapped_to_litellm_exception(respx_mock: respx.MockRouter, monkeypatch):
+    """Regression for arerank's bare re-raise: provider errors escaped as raw
+    provider exception classes instead of the mapped litellm exception contract."""
+    monkeypatch.delenv("DASHSCOPE_API_BASE", raising=False)
+    monkeypatch.delenv("DASHSCOPE_API_BASE_RERANK", raising=False)
+    monkeypatch.setenv("DISABLE_AIOHTTP_TRANSPORT", "True")
+
+    mock_route = respx_mock.post("https://dashscope.example/v1/reranks")
+    mock_route.return_value = httpx.Response(404, json=DASHSCOPE_404_BODY)
+
+    with pytest.raises(litellm.NotFoundError) as exc_info:
+        await litellm.arerank(
+            model="dashscope/does-not-exist",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+            api_key="fake-dashscope-key",
+            api_base="https://dashscope.example/v1",
+        )
+
+    assert mock_route.called
+    assert "DashscopeException" in str(exc_info.value)
+    assert "does not exist or you do not have access to it" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
+@pytest.mark.asyncio
+async def test_arerank_declared_authenticating_provider_skips_resolution(monkeypatch):
+    """Regression for the event-loop hazard in arerank's provider pre-resolution:
+    get_llm_provider runs the blocking OAuth device flow for github_copilot/chatgpt,
+    so arerank must adopt the declared provider instead of resolving it, while the
+    except path still maps with that declared provider."""
+    from litellm.llms.base_llm.chat.transformation import BaseLLMException
+
+    resolution_calls = []
+
+    def record_resolution(*args, **kwargs):
+        resolution_calls.append((args, kwargs))
+        return "gpt-4o", "github_copilot", None, None
+
+    def rerank_raises_provider_error(*args, **kwargs):
+        raise BaseLLMException(status_code=401, message='{"error":"bad key"}')
+
+    monkeypatch.setattr(litellm, "get_llm_provider", record_resolution)
+    monkeypatch.setattr("litellm.rerank_api.main.rerank", rerank_raises_provider_error)
+
+    with pytest.raises(litellm.AuthenticationError) as exc_info:
+        await litellm.arerank(
+            model="github_copilot/gpt-4o",
+            query=MARKER_QUERY,
+            documents=[MARKER_DOC],
+        )
+
+    assert resolution_calls == []
+    assert "Github_copilotException" in str(exc_info.value)
+    assert "None - " not in str(exc_info.value)
+
+
 @pytest.mark.asyncio
 async def test_together_rerank_async_honors_env_api_base(respx_mock: respx.MockRouter, monkeypatch):
     """Regression: TOGETHER_AI_API_BASE was honored by chat but ignored by rerank."""
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index b96d2eb5322..b2b8eb5da80 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
@@ -124,6 +124,25 @@ class TestLiteLLMCompletionResponsesConfig:
         assert "extra_field" not in result["file"]
         assert "another_field" not in result["file"]
 
+    def test_transform_input_file_item_to_file_item_keeps_filename(self):
+        """OpenAI rejects file_data with no filename beside it, so dropping it 400s the request"""
+        result = (
+            LiteLLMCompletionResponsesConfig._transform_input_file_item_to_file_item(
+                {
+                    "type": "input_file",
+                    "filename": "report.pdf",
+                    "file_data": "data:application/pdf;base64,JVBERi0=",
+                }
+            )
+        )
+        assert result == {
+            "type": "file",
+            "file": {
+                "file_data": "data:application/pdf;base64,JVBERi0=",
+                "filename": "report.pdf",
+            },
+        }
+
     def test_transform_input_file_item_to_file_item_with_file_url(self):
         """file_url should be mapped to file_id for downstream URL handling"""
         result = (
@@ -629,6 +648,72 @@ class TestLiteLLMCompletionResponsesConfig:
 
         assert responses_api_response.status == "incomplete"
 
+    def test_tool_call_only_response_emits_no_null_text_message_item(self):
+        """A tool-calls-only turn (message content None, e.g. from Anthropic)
+        must not emit a message output item whose output_text has text null.
+        OpenAI rejects such an item on replay with
+        "Invalid type for 'input[..].content[..].text': expected a string, but
+        got null instead." Native OpenAI tool-only turns carry no message item."""
+        chat_completion_response = ModelResponse(
+            id="test-response-id",
+            created=1234567890,
+            model="claude-sonnet-4-5",
+            object="chat.completion",
+            choices=[
+                Choices(
+                    finish_reason="tool_calls",
+                    index=0,
+                    message=Message(
+                        content=None,
+                        role="assistant",
+                        tool_calls=[
+                            ChatCompletionMessageToolCall(
+                                id="toolu_01OnlyToolCall",
+                                type="function",
+                                function=Function(name="get_weather", arguments='{"city": "SF"}'),
+                            )
+                        ],
+                    ),
+                )
+            ],
+        )
+
+        responses_api_response = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+            request_input="what's the weather in SF?",
+            responses_api_request={},
+            chat_completion_response=chat_completion_response,
+        )
+
+        output_types = [item.type for item in responses_api_response.output]
+        assert "message" not in output_types
+        assert "function_call" in output_types
+
+    def test_content_bearing_response_still_emits_message_item(self):
+        """Turns with real text content must keep their message output item."""
+        chat_completion_response = ModelResponse(
+            id="test-response-id",
+            created=1234567890,
+            model="claude-sonnet-4-5",
+            object="chat.completion",
+            choices=[
+                Choices(
+                    finish_reason="stop",
+                    index=0,
+                    message=Message(content="It is sunny.", role="assistant"),
+                )
+            ],
+        )
+
+        responses_api_response = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+            request_input="what's the weather in SF?",
+            responses_api_request={},
+            chat_completion_response=chat_completion_response,
+        )
+
+        message_items = [item for item in responses_api_response.output if item.type == "message"]
+        assert len(message_items) == 1
+        assert message_items[0].content[0].text == "It is sunny."
+
     def test_transform_chat_completion_response_preserves_hidden_params(self):
         """Test that _hidden_params from chat completion response are preserved in responses API response"""
         # Setup
@@ -966,6 +1051,55 @@ class TestFunctionCallTransformation:
 
         assert result[0]["tool_calls"][0]["function"]["arguments"] == "{}"
 
+    def test_function_call_transformation_json_encodes_object_arguments(self):
+        """A decoded arguments object must be JSON-encoded, not str()'d.
+
+        Clients and providers sometimes send `arguments` as an object rather
+        than a JSON string; `str()` on a dict produces a Python repr with
+        single quotes, which downstream JSON parsers reject with errors like
+        "Expecting ',' delimiter".
+        """
+        function_call_item = {
+            "type": "function_call",
+            "name": "shell",
+            "arguments": {"command": "ls", "timeout": 30, "flags": ["-l", "-a"]},
+            "call_id": "call_123",
+            "id": "call_123",
+            "status": "completed",
+        }
+
+        result = LiteLLMCompletionResponsesConfig._transform_responses_api_function_call_to_chat_completion_message(
+            function_call=function_call_item
+        )
+
+        arguments = result[0].get("tool_calls", [])[0].get("function", {}).get("arguments")
+        assert json.loads(arguments) == {"command": "ls", "timeout": 30, "flags": ["-l", "-a"]}
+        assert "'" not in arguments
+
+    def test_create_tool_call_chunk_json_encodes_object_arguments(self):
+        """Cached tool_call definitions with object arguments stay valid JSON."""
+        chunk = LiteLLMCompletionResponsesConfig._create_tool_call_chunk(
+            tool_use_definition={
+                "id": "call_456",
+                "type": "function",
+                "function": {"name": "shell", "arguments": {"command": "ls"}},
+            },
+            tool_call_id="call_456",
+            index=0,
+        )
+
+        assert json.loads(chunk["function"]["arguments"]) == {"command": "ls"}
+
+    def test_create_tool_call_chunk_keeps_empty_arguments_default(self):
+        """Missing arguments still fall back to an empty JSON object."""
+        chunk = LiteLLMCompletionResponsesConfig._create_tool_call_chunk(
+            tool_use_definition={"id": "call_789", "type": "function", "function": {"name": "shell"}},
+            tool_call_id="call_789",
+            index=0,
+        )
+
+        assert chunk["function"]["arguments"] == "{}"
+
     def test_complete_input_transformation_with_function_calls(self):
         """Test the complete transformation with the exact input from the issue"""
         test_input = [
@@ -3275,6 +3409,7 @@ class TestEnsureOutputItemContentPartAdded:
         iterator._pending_tool_events = []
         iterator._tool_output_index_by_call_id = {}
         iterator._tool_args_by_call_id = {}
+        iterator._tool_item_id_by_call_id = {}
         iterator._tool_call_id_by_index = {}
         iterator._ambiguous_tool_call_indexes = set()
         iterator._next_tool_output_index = 1
diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
index 823f656ddc5..4a03913f55a 100644
--- a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
+++ b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py
@@ -10,6 +10,7 @@ before response.completed, and that every event of a bridged stream carries the
 spend tracking stores, so a follow-up previous_response_id still finds the conversation.
 """
 
+import json
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -131,7 +132,7 @@ def test_tool_call_delta_is_emitted_as_responses_events():
     evt2 = iterator._transform_chat_completion_chunk_to_response_api_chunk(chunk)
     assert evt2 is not None
     assert evt2.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA
-    assert evt2.item_id == "call_1"
+    assert evt2.item_id == "fc_call_1"
     assert evt2.output_index == 1
     # The delta will be a chunk of the arguments, not the full arguments
     assert len(evt2.delta) <= 10  # Chunks are max 10 characters
@@ -196,7 +197,7 @@ def test_tool_calls_present_only_in_final_response_are_emitted_before_completed(
 
     # The last event should be FUNCTION_CALL_ARGUMENTS_DONE
     assert evt.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE
-    assert evt.item_id == "call_2"
+    assert evt.item_id == "fc_call_2"
     assert evt.output_index == 1
     assert evt.arguments == '{"y":2}'
 
@@ -290,7 +291,7 @@ def test_tool_call_arguments_are_chunked_to_match_openai_behavior():
     # Verify each delta is at most 10 characters
     for evt in delta_events:
         assert len(evt.delta) <= 10
-        assert evt.item_id == "call_test"
+        assert evt.item_id == "fc_call_test"
         assert evt.output_index == 1
         assert hasattr(evt, "__dict__") and "sequence_number" in evt.__dict__
 
@@ -348,7 +349,8 @@ def test_tool_call_delta_without_id_uses_index_mapping():
         if evt.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED
     ]
     assert len(output_item_added_events) == 1
-    assert output_item_added_events[0].item.id == "call_abc123"
+    assert output_item_added_events[0].item.id == "fc_call_abc123"
+    assert output_item_added_events[0].item.call_id == "call_abc123"
 
 
 def test_parallel_tool_calls_without_ids_use_index_mapping():
@@ -403,8 +405,8 @@ def test_parallel_tool_calls_without_ids_use_index_mapping():
         arguments_by_call_id.setdefault(evt.item_id, "")
         arguments_by_call_id[evt.item_id] += evt.delta
 
-    assert arguments_by_call_id["call_a"] == '{"x":1}'
-    assert arguments_by_call_id["call_b"] == '{"y":2}'
+    assert arguments_by_call_id["fc_call_a"] == '{"x":1}'
+    assert arguments_by_call_id["fc_call_b"] == '{"y":2}'
 
 
 def test_reused_index_with_new_call_id_marks_fallback_ambiguous():
@@ -460,10 +462,10 @@ def test_reused_index_with_new_call_id_marks_fallback_ambiguous():
         arguments_by_call_id.setdefault(evt.item_id, "")
         arguments_by_call_id[evt.item_id] += evt.delta
 
-    assert arguments_by_call_id["call_a"] == '{"a":'
-    assert arguments_by_call_id["call_b"] == '{"b":'
-    assert arguments_by_call_id["call_a"] != '{"a":1}'
-    assert arguments_by_call_id["call_b"] != '{"b":1}'
+    assert arguments_by_call_id["fc_call_a"] == '{"a":'
+    assert arguments_by_call_id["fc_call_b"] == '{"b":'
+    assert arguments_by_call_id["fc_call_a"] != '{"a":1}'
+    assert arguments_by_call_id["fc_call_b"] != '{"b":1}'
 
 
 @pytest.mark.asyncio
@@ -523,3 +525,91 @@ async def test_streaming_response_id_falls_back_when_upstream_yields_nothing():
     assert response_ids
     assert len(set(response_ids)) == 1
     assert response_ids[0].startswith("resp_")
+
+
+def test_object_tool_call_arguments_stream_as_valid_json():
+    """A provider that sends decoded object arguments must still stream valid JSON.
+
+    `str()` on a dict yields a Python repr with single quotes, which clients
+    parsing function_call_arguments reject with errors like
+    "Expecting ',' delimiter".
+    """
+    iterator = LiteLLMCompletionStreamingIterator(
+        model="test-model",
+        litellm_custom_stream_wrapper=AsyncMock(),
+        request_input="Test input",
+        responses_api_request={},
+    )
+    iterator._queue_tool_call_delta_events(
+        [
+            {
+                "index": 0,
+                "id": "call_obj",
+                "type": "function",
+                "function": {"name": "shell", "arguments": {"command": "ls", "flags": ["-l"]}},
+            }
+        ]
+    )
+
+    streamed_arguments = "".join(
+        evt.delta
+        for evt in iterator._pending_tool_events
+        if evt.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA
+    )
+
+    assert json.loads(streamed_arguments) == {"command": "ls", "flags": ["-l"]}
+
+
+def test_streamed_anthropic_tool_call_events_correlate_on_normalized_item_id():
+    iterator = LiteLLMCompletionStreamingIterator(
+        model="test-model",
+        litellm_custom_stream_wrapper=AsyncMock(),
+        request_input="Test input",
+        responses_api_request={},
+    )
+
+    response = ModelResponse(
+        id="resp-anthropic",
+        created=123,
+        model="test-model",
+        object="chat.completion",
+        choices=[
+            {
+                "index": 0,
+                "finish_reason": "tool_calls",
+                "message": {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {
+                            "id": "toolu_01AbCdEf",
+                            "type": "function",
+                            "function": {"name": "get_weather", "arguments": '{"city":"Paris"}'},
+                            "index": 0,
+                        }
+                    ],
+                },
+            }
+        ],
+    )
+    iterator.litellm_model_response = response
+
+    events = []
+    while True:
+        evt = iterator.common_done_event_logic(sync_mode=True)
+        events.append(evt)
+        if evt.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE:
+            break
+
+    added = [e for e in events if e.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED]
+    deltas = [e for e in events if e.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA]
+    dones = [e for e in events if e.type == ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE]
+    item_dones = [e for e in events if e.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE]
+
+    assert len(added) == 1 and len(dones) == 1 and len(item_dones) == 1 and deltas
+    assert added[0].item.id == "fc_toolu_01AbCdEf"
+    assert added[0].item.call_id == "toolu_01AbCdEf"
+    assert item_dones[0].item.id == "fc_toolu_01AbCdEf"
+    assert item_dones[0].item.call_id == "toolu_01AbCdEf"
+    for evt in deltas + dones:
+        assert evt.item_id == added[0].item.id
diff --git a/tests/test_litellm/responses/test_custom_tool_call.py b/tests/test_litellm/responses/test_custom_tool_call.py
index c605ef24934..5122c1c1d67 100644
--- a/tests/test_litellm/responses/test_custom_tool_call.py
+++ b/tests/test_litellm/responses/test_custom_tool_call.py
@@ -20,6 +20,7 @@ from litellm.responses.litellm_completion_transformation.transformation import (
 from litellm.responses.litellm_completion_transformation.custom_tools import (
     extract_custom_tool_names,
     is_custom_tool_call,
+    openai_shaped_tool_call_item_id,
     unwrap_custom_tool_arguments,
     build_tool_call_item_kwargs,
     convert_custom_tool_to_function_tool,
@@ -129,6 +130,41 @@ class TestCustomToolUtilities:
         assert kwargs["arguments"] == raw
         assert "input" not in kwargs
 
+    def test_openai_shaped_tool_call_item_id_prefixes_foreign_ids(self):
+        """Anthropic-style tool ids must be normalized to OpenAI's item id
+        shapes (fc/ctc prefixes) so replaying the item to OpenAI does not 400
+        with "Expected an ID that begins with 'fc'"."""
+        assert openai_shaped_tool_call_item_id("function_call", "toolu_01Abc") == "fc_toolu_01Abc"
+        assert openai_shaped_tool_call_item_id("function_call", "srvtoolu_01Xyz") == "fc_srvtoolu_01Xyz"
+        assert openai_shaped_tool_call_item_id("custom_tool_call", "toolu_01Abc") == "ctc_toolu_01Abc"
+        assert openai_shaped_tool_call_item_id("function_call", "fc_already") == "fc_already"
+        assert openai_shaped_tool_call_item_id("custom_tool_call", "ctc_already") == "ctc_already"
+        assert openai_shaped_tool_call_item_id("function_call", "") == ""
+        assert openai_shaped_tool_call_item_id("message", "toolu_01Abc") == "toolu_01Abc"
+
+    def test_build_tool_call_item_kwargs_normalizes_item_id_keeps_call_id(self):
+        """The streaming item id gets the OpenAI shape while call_id stays raw
+        so tool_result pairing (which keys off call_id) keeps working."""
+        function_kwargs = build_tool_call_item_kwargs(
+            call_id="toolu_01Abc",
+            name="get_weather",
+            arguments_or_input="{}",
+            status="completed",
+            custom_tool_names=set(),
+        )
+        assert function_kwargs["id"] == "fc_toolu_01Abc"
+        assert function_kwargs["call_id"] == "toolu_01Abc"
+
+        custom_kwargs = build_tool_call_item_kwargs(
+            call_id="toolu_01Def",
+            name="apply_patch",
+            arguments_or_input=json.dumps({"content": "patch"}),
+            status="completed",
+            custom_tool_names={"apply_patch"},
+        )
+        assert custom_kwargs["id"] == "ctc_toolu_01Def"
+        assert custom_kwargs["call_id"] == "toolu_01Def"
+
     def test_unwrap_custom_tool_arguments_oversized_returns_raw(self):
         """Arguments larger than the safety cap are returned unchanged to avoid
         OOM on JSON parsing a pathologically large string."""
@@ -293,6 +329,52 @@ class TestTransformationCustomTools:
         assert item.name == "regular_tool"
         assert item.arguments == json.dumps({"param": "value"})
 
+    def test_transform_anthropic_tool_call_ids_get_openai_item_id_shape(self):
+        """Anthropic tool ids (toolu_/srvtoolu_) surfacing through the bridge
+        must be emitted with fc/ctc-prefixed item ids so a Responses client can
+        replay them to OpenAI verbatim, while call_id stays raw for pairing."""
+        from litellm.types.utils import ModelResponse, Choices, Message, ChatCompletionMessageToolCall, Function
+
+        client_call = ChatCompletionMessageToolCall(
+            id="toolu_01ClientCall",
+            type="function",
+            function=Function(name="get_weather", arguments=json.dumps({"city": "SF"})),
+        )
+        server_call = ChatCompletionMessageToolCall(
+            id="srvtoolu_01ServerCall",
+            type="function",
+            function=Function(name="web_search", arguments=json.dumps({"query": "zig"})),
+        )
+        custom_call = ChatCompletionMessageToolCall(
+            id="toolu_01CustomCall",
+            type="function",
+            function=Function(name="apply_patch", arguments=json.dumps({"content": "patch content"})),
+        )
+
+        message = Message(role="assistant", content=None, tool_calls=[client_call, server_call, custom_call])
+        choices = [Choices(index=0, message=message, finish_reason="tool_calls")]
+        response = ModelResponse(
+            id="test_response", choices=choices, created=1234567890, model="claude-sonnet-4-5", object="chat.completion"
+        )
+        responses_api_request = {
+            "tools": [{"type": "custom", "name": "apply_patch"}, {"type": "function", "name": "get_weather"}]
+        }
+
+        result = LiteLLMCompletionResponsesConfig.transform_chat_completion_tools_to_responses_tools(
+            response, responses_api_request=responses_api_request
+        )
+
+        assert [item.id for item in result] == [
+            "fc_toolu_01ClientCall",
+            "fc_srvtoolu_01ServerCall",
+            "ctc_toolu_01CustomCall",
+        ]
+        assert [item.call_id for item in result] == [
+            "toolu_01ClientCall",
+            "srvtoolu_01ServerCall",
+            "toolu_01CustomCall",
+        ]
+
     def test_transform_mixed_tool_calls(self):
         """Test transformation with both custom and regular tool calls."""
         from litellm.types.utils import ModelResponse, Choices, Message, ChatCompletionMessageToolCall, Function
diff --git a/tests/test_litellm/responses/test_rust_bridge_websocket.py b/tests/test_litellm/responses/test_rust_bridge_websocket.py
index c9a5b988be6..1233ddf1785 100644
--- a/tests/test_litellm/responses/test_rust_bridge_websocket.py
+++ b/tests/test_litellm/responses/test_rust_bridge_websocket.py
@@ -3,7 +3,7 @@ from __future__ import annotations
 import pytest
 
 from litellm.llms.custom_httpx.llm_http_handler import _rust_responses_websocket_enabled
-from litellm.rust_bridge import responses_websocket
+from litellm.rust_bridge import configuration, responses_websocket
 from litellm.types.router import GenericLiteLLMParams
 
 
@@ -39,12 +39,33 @@ class _FakeNativeBridge:
         return _FakeNativeConnection()
 
 
+@pytest.fixture(autouse=True)
+def reset_responses_websocket():
+    responses_websocket.set_rust_responses_websocket(connection=None)
+    configuration.reset_rust_configuration()
+    yield
+    responses_websocket.set_rust_responses_websocket(connection=None)
+    configuration.reset_rust_configuration()
+
+
 def test_rust_websocket_bridge_is_disabled_without_flag() -> None:
     assert not _rust_responses_websocket_enabled("openai", GenericLiteLLMParams())
     assert not _rust_responses_websocket_enabled("anthropic", GenericLiteLLMParams(rust=True))
     assert _rust_responses_websocket_enabled("openai", GenericLiteLLMParams(rust=True))
 
 
+def test_explicit_false_overrides_process_enable() -> None:
+    configuration.use_litellm_rust(True)
+
+    assert not _rust_responses_websocket_enabled("openai", GenericLiteLLMParams(rust=False))
+
+
+def test_process_enable_applies_without_request_override() -> None:
+    configuration.use_litellm_rust(True)
+
+    assert _rust_responses_websocket_enabled("openai", GenericLiteLLMParams())
+
+
 @pytest.mark.asyncio
 async def test_adapter_raises_clean_close_when_rust_connection_ends() -> None:
     adapter = responses_websocket._ConnectionAdapter(_ClosedNativeConnection())
diff --git a/tests/test_litellm/responses/test_streaming_iterator.py b/tests/test_litellm/responses/test_streaming_iterator.py
index 677faf7f655..9edcaaef034 100644
--- a/tests/test_litellm/responses/test_streaming_iterator.py
+++ b/tests/test_litellm/responses/test_streaming_iterator.py
@@ -326,3 +326,55 @@ def test_run_post_success_hooks_does_not_report_generation_time_as_overhead():
 
     assert iterator.completed_response._hidden_params["_response_ms"] == 10000.0
     assert "litellm_overhead_time_ms" not in iterator.completed_response._hidden_params
+
+
+def _responses_api_response_with_usage() -> ResponsesAPIResponse:
+    from litellm.types.llms.openai import ResponseAPIUsage
+
+    return ResponsesAPIResponse(
+        id="resp_lit6427",
+        created_at=int(datetime(2025, 1, 1).timestamp()),
+        status="completed",
+        model="mantle-claude",
+        object="response",
+        output=[],
+        usage=ResponseAPIUsage(input_tokens=20, output_tokens=60, total_tokens=80),
+    )
+
+
+def test_stamp_responses_usage_cost_stamps_computed_cost():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+    logging_obj._response_cost_calculator.return_value = 0.000704
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
+    logging_obj._response_cost_calculator.assert_called_once_with(result=response)
+
+
+def test_stamp_responses_usage_cost_keeps_provider_reported_cost():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    setattr(response.usage, "cost", 0.5)
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
+    logging_obj._response_cost_calculator.assert_not_called()
+
+
+def test_stamp_responses_usage_cost_survives_calculator_failure():
+    from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
+
+    response = _responses_api_response_with_usage()
+    logging_obj = Mock(spec=LiteLLMLoggingObj)
+    logging_obj._response_cost_calculator.side_effect = RuntimeError("cost map unavailable")
+
+    _stamp_responses_usage_cost(response, logging_obj)
+
+    assert getattr(response.usage, "cost", None) is None
diff --git a/tests/test_litellm/router_strategy/test_complexity_router.py b/tests/test_litellm/router_strategy/test_complexity_router.py
index eee4e9aa185..941d78085e4 100644
--- a/tests/test_litellm/router_strategy/test_complexity_router.py
+++ b/tests/test_litellm/router_strategy/test_complexity_router.py
@@ -12,7 +12,6 @@ from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 from pydantic import ValidationError
 
-
 import litellm
 from litellm import Router
 from litellm._logging import verbose_router_logger
@@ -34,10 +33,14 @@ from litellm.router_strategy.complexity_router.config import (
     DEFAULT_CLASSIFIER_CONTEXT_WINDOW_SIZE,
     DEFAULT_COMPLEXITY_CONFIG,
     DEFAULT_TECHNICAL_KEYWORDS,
+    ClassificationRubric,
     ClassifierLLMConfig,
     ComplexityRouterConfig,
     ComplexityTier,
-    ClassificationRubric,
+)
+from litellm.router_strategy.complexity_router.tier_predictor import (
+    TierGlobalStatistic,
+    TrainedTierArtifact,
 )
 from litellm.types.router import (
     Deployment,
@@ -46,6 +49,16 @@ from litellm.types.router import (
 )
 
 
+def _heuristic_v2_artifact() -> TrainedTierArtifact:
+    return TrainedTierArtifact(
+        global_statistics=tuple(
+            TierGlobalStatistic(tier=tier, successes=successes, observations=100)
+            for tier, successes in enumerate((10, 20, 90, 99), start=1)
+        ),
+        routing_threshold=0.8,
+    )
+
+
 @pytest.fixture
 def mock_router_instance():
     """Create a mock LiteLLM Router instance."""
@@ -1696,6 +1709,59 @@ class TestLLMClassifier:
         assert outcome.cause == "heuristic_scorer"
         assert outcome.score is not None
 
+    @pytest.mark.asyncio
+    async def test_heuristic_v2_routes_directly_to_predicted_builtin_tier(self, mock_router_instance):
+        router = ComplexityRouter(
+            model_name="tier-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={
+                "classifier_type": "heuristic_v2",
+                "heuristic_v2_artifact": _heuristic_v2_artifact(),
+                "tiers": {
+                    "SIMPLE": "simple-model",
+                    "MEDIUM": "medium-model",
+                    "COMPLEX": "complex-model",
+                    "REASONING": "reasoning-model",
+                },
+            },
+        )
+
+        response = await router.async_pre_routing_hook(
+            model="tier-router",
+            request_kwargs={},
+            messages=[{"role": "user", "content": "Handle this new request"}],
+        )
+
+        assert response is not None
+        assert response.model == "complex-model"
+        assert response.routing_decision["tier"] == "COMPLEX"
+        assert response.routing_decision["cause"] == "heuristic_v2"
+        assert response.routing_decision["signals"] == [
+            "request-type:general",
+            "tier-probability:simple=0.107843",
+            "tier-probability:medium=0.205882",
+            "tier-probability:complex=0.892157",
+            "tier-probability:reasoning=0.980392",
+        ]
+
+    def test_heuristic_v2_needs_no_classifier_model(self):
+        config = ComplexityRouterConfig(classifier_type="heuristic_v2")
+
+        assert config.classifier_llm_config is None
+        assert config.heuristic_v2_artifact == "ultrafeedback"
+
+    def test_heuristic_v2_rejects_custom_tier_definitions(self):
+        with pytest.raises(ValidationError, match="as does heuristic_v2"):
+            ComplexityRouterConfig(
+                classifier_type="heuristic_v2",
+                tier_definitions=(
+                    {"name": "low", "description": "easy work"},
+                    {"name": "high", "description": "hard work"},
+                ),
+                tiers={"low": "cheap", "high": "expensive"},
+                fallback_tier="high",
+            )
+
     @pytest.mark.asyncio
     async def test_aclassify_llm_success_routes_by_llm_verdict(self, llm_complexity_router, mock_router_instance):
         """A well-formed structured LLM response should decide the tier directly.
@@ -4425,6 +4491,265 @@ class _DummyPlugin:
         return context
 
 
+class TestClassificationMode:
+    """Test classification_mode='user_turn': classify only requests whose newest turn is a new
+    human ask; tool-loop continuation turns replay the session's held routing decision."""
+
+    REASONING_ASK = {
+        "role": "user",
+        "content": "Let's think step by step and reason through this problem carefully.",
+    }
+    SIMPLE_ASK = {"role": "user", "content": "Hello!"}
+    ASSISTANT_ANSWER = {"role": "assistant", "content": "the answer"}
+    TOOL_CALL_1 = {
+        "role": "assistant",
+        "content": None,
+        "tool_calls": [{"id": "call_1", "type": "function", "function": {"name": "read_file", "arguments": "{}"}}],
+    }
+    TOOL_RESULT_1 = {"role": "tool", "tool_call_id": "call_1", "content": "file contents"}
+    TOOL_CALL_2 = {
+        "role": "assistant",
+        "content": None,
+        "tool_calls": [{"id": "call_2", "type": "function", "function": {"name": "run_tests", "arguments": "{}"}}],
+    }
+    TOOL_RESULT_2 = {"role": "tool", "tool_call_id": "call_2", "content": "3 passed"}
+
+    @pytest.fixture
+    def user_turn_config(self, basic_config) -> dict:
+        return {**basic_config, "classification_mode": "user_turn"}
+
+    @staticmethod
+    def _request_kwargs(session_id: str) -> dict:
+        return {"metadata": {"session_id": session_id}}
+
+    def _router(self, mock_router_instance, config: dict) -> ComplexityRouter:
+        mock_router_instance.cache = DualCache()
+        return ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config=config,
+        )
+
+    def _tool_loop_turns(self) -> list[list[dict]]:
+        return [
+            [self.REASONING_ASK],
+            [self.REASONING_ASK, self.TOOL_CALL_1, self.TOOL_RESULT_1],
+            [self.REASONING_ASK, self.TOOL_CALL_1, self.TOOL_RESULT_1, self.TOOL_CALL_2, self.TOOL_RESULT_2],
+        ]
+
+    def test_default_mode_is_every_request(self, complexity_router):
+        assert complexity_router.config.classification_mode == "every_request"
+
+    def test_invalid_classification_mode_rejected(self, mock_router_instance, basic_config):
+        with pytest.raises(ValidationError):
+            ComplexityRouter(
+                model_name="test-router",
+                litellm_router_instance=mock_router_instance,
+                complexity_router_config={**basic_config, "classification_mode": "sometimes"},
+            )
+
+    @pytest.mark.asyncio
+    async def test_user_turn_mode_classifies_tool_loop_once(self, mock_router_instance, user_turn_config):
+        """The mutation check: a 3-request tool loop drives exactly one classification, and both
+        continuation turns hold the classified model under the user_turn_continuation cause."""
+        router = self._router(mock_router_instance, user_turn_config)
+        with patch.object(router, "_classify_and_route", wraps=router._classify_and_route) as spy:
+            responses = [
+                await router.async_pre_routing_hook(
+                    model="test-model", request_kwargs=self._request_kwargs("loop-1"), messages=turn
+                )
+                for turn in self._tool_loop_turns()
+            ]
+        assert spy.call_count == 1
+        assert [r.model for r in responses] == ["o1-preview", "o1-preview", "o1-preview"]
+        assert [r.routing_decision["cause"] for r in responses[1:]] == [
+            "user_turn_continuation",
+            "user_turn_continuation",
+        ]
+
+    @pytest.mark.asyncio
+    async def test_every_request_default_classifies_every_tool_loop_turn(self, mock_router_instance, basic_config):
+        """Pins today's default: every request classifies, including tool-loop continuations."""
+        router = self._router(mock_router_instance, basic_config)
+        with patch.object(router, "_classify_and_route", wraps=router._classify_and_route) as spy:
+            responses = [
+                await router.async_pre_routing_hook(
+                    model="test-model", request_kwargs=self._request_kwargs("loop-2"), messages=turn
+                )
+                for turn in self._tool_loop_turns()
+            ]
+        assert spy.call_count == 3
+        assert [r.model for r in responses] == ["o1-preview", "o1-preview", "o1-preview"]
+        assert all(r.routing_decision["cause"] != "user_turn_continuation" for r in responses)
+
+    @pytest.mark.asyncio
+    async def test_continuation_without_session_id_still_classifies(self, mock_router_instance, user_turn_config):
+        """No resolvable session id means no held decision to replay, so every request classifies."""
+        router = self._router(mock_router_instance, user_turn_config)
+        with patch.object(router, "_classify_and_route", wraps=router._classify_and_route) as spy:
+            responses = [
+                await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=turn)
+                for turn in self._tool_loop_turns()
+            ]
+        assert spy.call_count == 3
+        assert [r.model for r in responses] == ["o1-preview", "o1-preview", "o1-preview"]
+        assert all(r.routing_decision["cause"] != "user_turn_continuation" for r in responses)
+
+    @pytest.mark.asyncio
+    async def test_plugins_suppress_user_turn_gate(self, mock_router_instance, basic_config):
+        """A replayed decision would bypass the plugin pipeline, so plugins force every request
+        through _classify_and_route, exactly as they do for session_affinity."""
+        router = self._router(
+            mock_router_instance,
+            {**basic_config, "classification_mode": "user_turn", "plugins": [_DummyPlugin()]},
+        )
+        with patch.object(router, "_classify_and_route", wraps=router._classify_and_route) as spy:
+            responses = [
+                await router.async_pre_routing_hook(
+                    model="test-model", request_kwargs=self._request_kwargs("loop-3"), messages=turn
+                )
+                for turn in self._tool_loop_turns()
+            ]
+        assert spy.call_count == 3
+        assert [r.model for r in responses] == ["o1-preview", "o1-preview", "o1-preview"]
+        assert all(r.routing_decision["cause"] != "user_turn_continuation" for r in responses)
+
+    @pytest.mark.asyncio
+    async def test_new_human_ask_reclassifies_and_repins(self, mock_router_instance, user_turn_config):
+        """Unlike session_affinity, a new human ask never short-circuits on the pin: the session
+        re-classifies, moves tier, and the moved decision becomes the next held decision."""
+        router = self._router(mock_router_instance, user_turn_config)
+        first = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs=self._request_kwargs("s-repin"), messages=[self.REASONING_ASK]
+        )
+        second = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-repin"),
+            messages=[self.REASONING_ASK, self.ASSISTANT_ANSWER, self.SIMPLE_ASK],
+        )
+        third = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-repin"),
+            messages=[self.REASONING_ASK, self.ASSISTANT_ANSWER, self.SIMPLE_ASK, self.TOOL_CALL_1, self.TOOL_RESULT_1],
+        )
+        assert first.model == "o1-preview"
+        assert second.model == "gpt-4o-mini"
+        assert third.model == "gpt-4o-mini"
+        assert third.routing_decision["cause"] == "user_turn_continuation"
+
+    @pytest.mark.asyncio
+    async def test_new_ask_with_trailing_system_reminder_reclassifies(self, mock_router_instance, user_turn_config):
+        """Claude Code appends a system-role reminder after the human turn; that trailing plumbing
+        must not turn a new ask into a continuation, and a continuation turn carrying the same
+        trailing reminder stays a continuation."""
+        router = self._router(mock_router_instance, user_turn_config)
+        reminder = {"role": "system", "content": "<total_tokens>100 tokens left</total_tokens>"}
+        first = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs=self._request_kwargs("s-reminder"), messages=[self.REASONING_ASK]
+        )
+        second = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-reminder"),
+            messages=[self.REASONING_ASK, self.ASSISTANT_ANSWER, self.SIMPLE_ASK, reminder],
+        )
+        third = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-reminder"),
+            messages=[
+                self.REASONING_ASK,
+                self.ASSISTANT_ANSWER,
+                self.SIMPLE_ASK,
+                reminder,
+                self.TOOL_CALL_1,
+                self.TOOL_RESULT_1,
+                reminder,
+            ],
+        )
+        assert first.model == "o1-preview"
+        assert second.model == "gpt-4o-mini"
+        assert second.routing_decision["cause"] != "user_turn_continuation"
+        assert third.model == "gpt-4o-mini"
+        assert third.routing_decision["cause"] == "user_turn_continuation"
+
+    @pytest.mark.asyncio
+    async def test_escalation_keyword_turn_is_a_new_ask(self, mock_router_instance, user_turn_config):
+        """An escalation keyword arrives as human text, so the turn classifies and escalates
+        instead of replaying the held decision."""
+        router = self._router(mock_router_instance, user_turn_config)
+        first = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs=self._request_kwargs("s-esc"), messages=[self.SIMPLE_ASK]
+        )
+        second = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-esc"),
+            messages=[self.SIMPLE_ASK, self.ASSISTANT_ANSWER, {"role": "user", "content": "LITELLM ESCALATE"}],
+        )
+        assert first.model == "gpt-4o-mini"
+        assert second.model == "gpt-4o"
+        assert second.routing_decision["escalated"] is True
+
+    @pytest.mark.asyncio
+    async def test_messages_surface_tool_result_shapes(self, mock_router_instance, user_turn_config):
+        """Messages-surface shapes: a tool_result-only user turn is a continuation, while an ask
+        riding alongside a tool_result in the same turn is a new ask."""
+        router = self._router(mock_router_instance, user_turn_config)
+        tool_use = {"role": "assistant", "content": [{"type": "tool_use", "id": "x", "name": "t", "input": {}}]}
+        tool_result = {"type": "tool_result", "tool_use_id": "x", "content": "ok"}
+        first = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs=self._request_kwargs("s-msgs"), messages=[self.REASONING_ASK]
+        )
+        pure = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-msgs"),
+            messages=[self.REASONING_ASK, tool_use, {"role": "user", "content": [tool_result]}],
+        )
+        hybrid = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-msgs"),
+            messages=[
+                self.REASONING_ASK,
+                tool_use,
+                {"role": "user", "content": [tool_result, {"type": "text", "text": "Hello!"}]},
+            ],
+        )
+        assert first.model == "o1-preview"
+        assert pure.model == "o1-preview"
+        assert pure.routing_decision["cause"] == "user_turn_continuation"
+        assert hybrid.model == "gpt-4o-mini"
+
+    @pytest.mark.asyncio
+    async def test_session_affinity_wins_when_both_knobs_are_on(self, mock_router_instance, user_turn_config):
+        """With session_affinity also on, the pin short-circuits new asks too and keeps its own
+        cause, so the session stays on turn 1's model."""
+        router = self._router(mock_router_instance, {**user_turn_config, "session_affinity": True})
+        first = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs=self._request_kwargs("s-both"), messages=[self.REASONING_ASK]
+        )
+        second = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs=self._request_kwargs("s-both"),
+            messages=[self.REASONING_ASK, self.ASSISTANT_ANSWER, self.SIMPLE_ASK],
+        )
+        assert first.model == "o1-preview"
+        assert second.model == "o1-preview"
+        assert second.routing_decision["cause"] == "session_affinity_pin"
+
+    def test_user_turn_mode_enables_tier_and_deployment_pins(self, mock_router_instance, basic_config):
+        """user_turn implies the tier pin machinery (the pin write is what gives a continuation
+        a held decision) and the tier pin implies the deployment pin; plugins suppress both."""
+        default = self._router(mock_router_instance, basic_config)
+        enabled = self._router(mock_router_instance, {**basic_config, "classification_mode": "user_turn"})
+        suppressed = self._router(
+            mock_router_instance,
+            {**basic_config, "classification_mode": "user_turn", "plugins": [_DummyPlugin()]},
+        )
+        assert default._uses_tier_pin is False
+        assert enabled._uses_tier_pin is True
+        assert enabled._uses_deployment_pin is True
+        assert suppressed._uses_tier_pin is False
+        assert suppressed._uses_deployment_pin is False
+
+
 class TestRoutingPlugins:
     """Test the `complexity_router_config.plugins` field: narrows the classified
     tier's candidate pool before a model is picked. Discussion:
@@ -9762,3 +10087,922 @@ class TestHeuristicFirst:
         )
         outcome = await router.aclassify(NO_SIGNAL_PROMPT)
         assert outcome.cause == "default_model_fallback"
+
+
+# Scores 0.175 with one signal, so it sits 0.025 from simple_medium: the pair of tiers either side of
+# that boundary are different model pools, and a hair's difference in score picks the other one.
+NEAR_BOUNDARY_PROMPT = (
+    "design a distributed cache with consistent hashing, then explain the failure modes step by step"
+)
+
+# Scores 0.075 with signals, the far side of any margin under 0.075: the scorer is decided here.
+CLEAR_OF_BOUNDARY_PROMPT = "explain step by step how consistent hashing rebalances keys"
+
+
+def _hybrid_router(mock_router_instance, **config_overrides):
+    config = {
+        "tiers": dict(HEURISTIC_FIRST_TIERS),
+        "tier_boundaries": dict(HEURISTIC_FIRST_BOUNDARIES),
+        "classifier_type": "hybrid",
+        "hybrid_boundary_margin": 0.03,
+        "classifier_llm_config": {"model": "haiku-classifier", "timeout_ms": 400},
+        **config_overrides,
+    }
+    return ComplexityRouter(
+        model_name="test-complexity-router",
+        litellm_router_instance=mock_router_instance,
+        complexity_router_config=config,
+    )
+
+
+class TestHybridConfig:
+    """Config validation for classifier_type='hybrid'."""
+
+    @pytest.mark.parametrize(
+        "overrides, expected",
+        [
+            ({"classifier_llm_config": None}, "classifier_llm_config is required"),
+            ({"hybrid_boundary_margin": None}, "hybrid_boundary_margin is required"),
+            ({"hybrid_boundary_margin": -0.01}, "greater than or equal to 0"),
+            ({"hybrid_boundary_margin": 1.01}, "less than or equal to 1"),
+        ],
+    )
+    def test_rejects_incoherent_config(self, overrides, expected):
+        config = {
+            "tiers": dict(HEURISTIC_FIRST_TIERS),
+            "classifier_type": "hybrid",
+            "hybrid_boundary_margin": 0.03,
+            "classifier_llm_config": {"model": "haiku-classifier"},
+            **overrides,
+        }
+        with pytest.raises(ValidationError, match=expected):
+            ComplexityRouterConfig(**config)
+
+    @pytest.mark.parametrize("classifier_type", ["heuristic", "llm", "custom", "heuristic_first"])
+    def test_margin_rejected_on_every_other_classifier_type(self, classifier_type):
+        """A margin on a router that never compares a score to a boundary is a silent no-op, so it is
+        refused rather than accepted and ignored. heuristic_first is in this list on purpose: its
+        ceiling is a different question from proximity, and accepting both on one router would make
+        two modes out of one classifier_type."""
+        config: dict[str, object] = {
+            "tiers": dict(HEURISTIC_FIRST_TIERS),
+            "classifier_type": classifier_type,
+            "hybrid_boundary_margin": 0.03,
+        }
+        if classifier_type in ("llm", "heuristic_first"):
+            config["classifier_llm_config"] = {"model": "haiku-classifier"}
+        if classifier_type == "heuristic_first":
+            config["heuristic_first_max_tier"] = "SIMPLE"
+        if classifier_type == "custom":
+            config["classifier_plugin"] = _FixedTierClassifier("SIMPLE")
+        with pytest.raises(ValidationError, match="hybrid_boundary_margin is set but classifier_type"):
+            ComplexityRouterConfig(**config)
+
+    def test_the_cheap_tier_ceiling_is_rejected_here(self):
+        """The two modes are told apart by which knob they take, so the ceiling is refused on hybrid
+        exactly as the margin is refused on heuristic_first."""
+        with pytest.raises(ValidationError, match="heuristic_first_max_tier is set but classifier_type"):
+            ComplexityRouterConfig(
+                tiers=dict(HEURISTIC_FIRST_TIERS),
+                classifier_type="hybrid",
+                hybrid_boundary_margin=0.03,
+                heuristic_first_max_tier="SIMPLE",
+                classifier_llm_config={"model": "haiku-classifier"},
+            )
+
+    def test_custom_tier_set_is_rejected(self):
+        """The scorer only emits the four built-in tiers, so it cannot judge proximity on a replaced set."""
+        with pytest.raises(ValidationError, match="tier_definitions requires classifier_type"):
+            ComplexityRouterConfig(
+                classifier_type="hybrid",
+                hybrid_boundary_margin=0.03,
+                classifier_llm_config={"model": "haiku-classifier"},
+                tier_definitions=[{"name": "lo", "description": "x"}, {"name": "hi", "description": "y"}],
+                tiers={"lo": "gpt-4o-mini", "hi": "gpt-4o"},
+            )
+
+    def test_classifier_model_is_a_dependency(self):
+        config = ComplexityRouterConfig(
+            tiers=dict(HEURISTIC_FIRST_TIERS),
+            classifier_type="hybrid",
+            hybrid_boundary_margin=0.03,
+            classifier_llm_config={"model": "haiku-classifier"},
+        )
+        assert config.uses_llm_classifier is True
+
+
+class TestHybrid:
+    """Behavior of the hybrid chain: the scorer keeps its tier unless the score is near a boundary."""
+
+    @pytest.mark.asyncio
+    async def test_near_boundary_prompt_escalates(self, mock_router_instance):
+        mock_router_instance.acompletion = AsyncMock(return_value=_llm_response('{"tier": "COMPLEX"}'))
+        router = _hybrid_router(mock_router_instance)
+
+        _tier, score, signals, _cause = router._score_and_classify(NEAR_BOUNDARY_PROMPT)
+        assert signals and abs(score - HEURISTIC_FIRST_BOUNDARIES["simple_medium"]) < 0.03
+
+        outcome = await router.aclassify(NEAR_BOUNDARY_PROMPT)
+        mock_router_instance.acompletion.assert_awaited_once()
+        assert outcome.tier == ComplexityTier.COMPLEX
+        assert outcome.cause == "llm_classifier"
+
+    @pytest.mark.asyncio
+    async def test_score_clear_of_every_boundary_keeps_the_heuristic_tier(self, mock_router_instance):
+        mock_router_instance.acompletion = AsyncMock()
+        router = _hybrid_router(mock_router_instance)
+        outcome = await router.aclassify(CLEAR_OF_BOUNDARY_PROMPT)
+        mock_router_instance.acompletion.assert_not_called()
+        assert outcome.tier == ComplexityTier.SIMPLE
+        assert outcome.cause == "hybrid_short_circuit"
+
+    @pytest.mark.asyncio
+    async def test_an_expensive_tier_short_circuits_too(self, mock_router_instance):
+        """This is the whole difference from heuristic_first, which would have escalated this by tier
+        alone. Hybrid asks whether the score is DECIDED, not whether the tier is cheap."""
+        mock_router_instance.acompletion = AsyncMock()
+        router = _hybrid_router(
+            mock_router_instance,
+            tier_boundaries={"simple_medium": -0.9, "medium_complex": -0.8, "complex_reasoning": -0.7},
+        )
+
+        tier, _score, signals, _cause = router._score_and_classify(CLEAR_OF_BOUNDARY_PROMPT)
+        assert (tier, bool(signals)) == (ComplexityTier.REASONING, True)
+
+        outcome = await router.aclassify(CLEAR_OF_BOUNDARY_PROMPT)
+        mock_router_instance.acompletion.assert_not_called()
+        assert outcome.tier == ComplexityTier.REASONING
+        assert outcome.cause == "hybrid_short_circuit"
+
+    @pytest.mark.asyncio
+    async def test_widening_the_margin_escalates_what_a_narrow_one_kept(self, mock_router_instance):
+        """The margin is the knob: the same prompt short-circuits at 0.03 and escalates at 0.08."""
+        mock_router_instance.acompletion = AsyncMock(return_value=_llm_response('{"tier": "MEDIUM"}'))
+        router = _hybrid_router(mock_router_instance, hybrid_boundary_margin=0.08)
+        outcome = await router.aclassify(CLEAR_OF_BOUNDARY_PROMPT)
+        mock_router_instance.acompletion.assert_awaited_once()
+        assert outcome.cause == "llm_classifier"
+
+    @pytest.mark.asyncio
+    async def test_a_zero_margin_escalates_only_an_exact_boundary_score(self, mock_router_instance):
+        """0 is a real margin, not an off switch: a score sitting exactly on the line still escalates.
+
+        The boundary is spelled as the scorer's own accumulated float rather than the 0.075 it prints
+        as, because the comparison is on raw floats: a boundary written 0.075 sits 1.4e-17 away from
+        this score and a zero margin correctly declines to call that exact."""
+        mock_router_instance.acompletion = AsyncMock(return_value=_llm_response('{"tier": "MEDIUM"}'))
+        on_the_line = 0.07499999999999998
+        router = _hybrid_router(
+            mock_router_instance,
+            tier_boundaries={"simple_medium": on_the_line, "medium_complex": 0.35, "complex_reasoning": 0.60},
+            hybrid_boundary_margin=0,
+        )
+
+        _tier, score, _signals, _cause = router._score_and_classify(CLEAR_OF_BOUNDARY_PROMPT)
+        assert score == on_the_line
+
+        outcome = await router.aclassify(CLEAR_OF_BOUNDARY_PROMPT)
+        mock_router_instance.acompletion.assert_awaited_once()
+        assert outcome.cause == "llm_classifier"
+
+    @pytest.mark.asyncio
+    async def test_no_signal_prompt_escalates_however_far_from_a_boundary(self, mock_router_instance):
+        """The scorer with no opinion has no tier to be confident about, so proximity cannot save it."""
+        mock_router_instance.acompletion = AsyncMock(return_value=_llm_response('{"tier": "COMPLEX"}'))
+        router = _hybrid_router(mock_router_instance)
+
+        tier, score, signals, _cause = router._score_and_classify(NO_SIGNAL_PROMPT)
+        assert (tier, score, signals) == (ComplexityTier.SIMPLE, 0.0, ())
+
+        outcome = await router.aclassify(NO_SIGNAL_PROMPT)
+        mock_router_instance.acompletion.assert_awaited_once()
+        assert outcome.cause == "llm_classifier"
+
+    @pytest.mark.asyncio
+    async def test_classifier_failure_falls_back_to_the_scorer(self, mock_router_instance):
+        mock_router_instance.acompletion = AsyncMock(side_effect=RuntimeError("classifier exploded"))
+        router = _hybrid_router(mock_router_instance)
+        expected_tier, expected_score, expected_signals, _cause = router._score_and_classify(NEAR_BOUNDARY_PROMPT)
+
+        outcome = await router.aclassify(NEAR_BOUNDARY_PROMPT)
+
+        assert (outcome.tier, outcome.score, outcome.signals) == (expected_tier, expected_score, expected_signals)
+        assert outcome.cause == "heuristic_scorer"
+
+
+def _windowed_router(*deployments: tuple) -> Router:
+    """Real Router; each deployment is (group, provider_model, declared window or None).
+    None means no declared override on a model the cost map does not know: unresolvable."""
+    return Router(
+        model_list=[
+            {
+                "model_name": group,
+                "litellm_params": {"model": provider_model, "mock_response": "ok"},
+                **({"model_info": {"max_input_tokens": window}} if window is not None else {}),
+            }
+            for group, provider_model, window in deployments
+        ]
+    )
+
+
+_SMALL = ("small-model", "openai/gpt-3.5-turbo", 16385)
+_BIG = ("big-model", "openai/gpt-4o-mini", 200000)
+
+# A long agentic session whose newest ask is trivial: low-density filler the heuristic scores
+# SIMPLE, sized well past a 16,385-token window so the fit check must move it.
+_CONTEXT_FILLER = "The meeting notes were saved to the shared folder for later review this week. " * 2000
+_OVERSIZED_TURNS = [
+    {"role": "user", "content": "Here is everything discussed so far. " + _CONTEXT_FILLER},
+    {"role": "assistant", "content": "Noted, I have read all of it."},
+    {"role": "user", "content": "ok continue"},
+]
+# ~40k CJK chars: chars/4 says ~10k tokens, the real tokenizer says several times that. A
+# character-based shortcut would skip counting and dispatch this to a 16k window.
+_CJK_TURNS = [
+    {"role": "user", "content": "会议记录已经保存到共享文件夹里，供大家本周晚些时候查阅和讨论使用。" * 1300},
+    {"role": "user", "content": "ok continue"},
+]
+
+
+def _tier_config(**overrides) -> Dict:
+    return {"tiers": {"SIMPLE": "small-model", "COMPLEX": "big-model"}, **overrides}
+
+
+class TestContextWindowEscalation:
+    """A tier decided on complexity alone must still hold the prompt, or the provider 400s.
+
+    The classifier never weighs prompt size (token count is a 0.10-weight scoring dimension,
+    below every tier boundary), so a long session ending in a trivial ask lands on the
+    smallest tier and dies upstream with no retry. The gate checks fit pre-dispatch, against
+    windows resolved through the real Router deployment chain.
+    """
+
+    @pytest.mark.asyncio
+    async def test_an_oversized_simple_prompt_escalates_to_the_lowest_tier_that_fits(self):
+        """The LIT-6503 regression: SIMPLE verdict, 17k-token prompt, 16,385-token tier model.
+
+        Unfixed, this dispatched to the small model and the provider rejected it with a
+        context-window 400 that neither the retry layer nor tier-keyed fallbacks catch.
+        """
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(),
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "big-model"
+        assert result.routing_decision["context_escalated"] is True
+        assert result.routing_decision["context_escalation_original_tier"] == "SIMPLE"
+        assert result.routing_decision["tier"] == "COMPLEX"
+        assert "context_escalation" in result.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    async def test_a_prompt_that_fits_routes_exactly_as_before(self):
+        """The gate must be invisible for normal traffic: same model, no escalation facts."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(),
+        )
+
+        result = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs={}, messages=[{"role": "user", "content": "ok continue"}]
+        )
+
+        assert result is not None
+        assert result.model == "small-model"
+        assert "context_escalated" not in result.routing_decision
+        assert "context_escalation_original_tier" not in result.routing_decision
+
+    @pytest.mark.asyncio
+    async def test_the_pick_prefers_a_fitting_group_inside_the_decided_tier(self):
+        """A tier holding both a small and a large group keeps the request and picks the one
+        that fits, which is cheaper than escalating and preserves the classifier's decision."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, ("mid-model", "openai/gpt-4o-mini", 200000), _BIG),
+            complexity_router_config={"tiers": {"SIMPLE": ["small-model", "mid-model"], "COMPLEX": "big-model"}},
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "mid-model"
+        assert result.routing_decision["tier"] == "SIMPLE"
+        assert "context_escalated" not in result.routing_decision
+
+    @pytest.mark.asyncio
+    async def test_a_group_is_only_as_safe_as_its_smallest_deployment(self):
+        """One group name can front deployments with different windows, and the core router
+        picks among them with no fit check, so retaining the group on its largest member
+        turns the pick into a coin flip against a 400. The gate judges the group by its
+        smallest resolvable window and escalates past it."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=Router(
+                model_list=[
+                    {
+                        "model_name": "mixed-pool",
+                        "litellm_params": {"model": "openai/gpt-3.5-turbo", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 16385},
+                    },
+                    {
+                        "model_name": "mixed-pool",
+                        "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 200000},
+                    },
+                    {
+                        "model_name": "big-model",
+                        "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 200000},
+                    },
+                ]
+            ),
+            complexity_router_config={"tiers": {"SIMPLE": "mixed-pool", "COMPLEX": "big-model"}},
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "big-model"
+        assert result.routing_decision["context_escalated"] is True
+
+    @pytest.mark.asyncio
+    async def test_token_dense_text_cannot_slip_past_the_counting_shortcut(self):
+        """CJK text runs several tokens per four characters, so a chars/4 shortcut would skip
+        the real count and dispatch an oversized prompt. The skip is gated on the UTF-8 byte
+        length, which the token count can never exceed."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(),
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_CJK_TURNS)
+
+        assert result is not None
+        assert result.model == "big-model"
+        assert result.routing_decision["context_escalated"] is True
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "deployments,tiers,expected_model",
+        [
+            (
+                (("small-model", "openai/unmapped-model-under-test", None), _BIG),
+                {"SIMPLE": "small-model", "COMPLEX": "big-model"},
+                "small-model",
+            ),
+            (
+                (_SMALL, ("mid-model", "openai/another-unmapped-model", None), _BIG),
+                {"SIMPLE": "small-model", "MEDIUM": "mid-model", "COMPLEX": "big-model"},
+                "big-model",
+            ),
+            ((_SMALL,), {"SIMPLE": "small-model"}, "small-model"),
+        ],
+        ids=["unknown-window-stays", "unproven-target-skipped", "nothing-fits-stays"],
+    )
+    async def test_unknown_windows_are_never_acted_on(self, deployments, tiers, expected_model):
+        """No faith in either direction: a model with no resolvable window is never escalated
+        away from (its misfit is unprovable) and never escalated onto (its fit is unprovable);
+        when nothing provably fits, the classified tier stands and the client owns overflow."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(*deployments),
+            complexity_router_config={"tiers": tiers},
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == expected_model
+
+    @pytest.mark.asyncio
+    async def test_the_disabled_gate_dispatches_on_complexity_alone(self):
+        """The escape hatch: enable_context_window_escalation false restores today's behavior."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(enable_context_window_escalation=False),
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "small-model"
+        assert "context_escalated" not in result.routing_decision
+
+    @pytest.mark.asyncio
+    async def test_out_of_band_system_and_tools_count_against_the_window(self):
+        """The Claude Code shape that live-testing caught: a tiny ask riding a top-level
+        `system` block and tool definitions that together dwarf the message list. None of
+        that reaches resolved messages on /v1/messages, so a gate reading only messages
+        dispatches a provably oversized request and the provider 400s anyway."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(),
+        )
+
+        result = await router.async_pre_routing_hook(
+            model="test-router",
+            request_kwargs={
+                "proxy_server_request": {
+                    "body": {
+                        "system": _CONTEXT_FILLER,
+                        "tools": [{"name": f"tool_{i}", "description": _CONTEXT_FILLER[:500]} for i in range(20)],
+                    }
+                }
+            },
+            messages=[{"role": "user", "content": "reply with exactly: rig check ok"}],
+        )
+
+        assert result is not None
+        assert result.model == "big-model"
+        assert result.routing_decision["context_escalated"] is True
+
+    @pytest.mark.asyncio
+    async def test_an_escalated_first_turn_never_becomes_the_session_pin(self):
+        """Escalation describes the prompt's size, not the session: once the client compacts,
+        the next turn fits again, so pinning the big-window tier would hold the whole session
+        on it for the TTL. The escalated turn routes big, and the next fitting turn classifies
+        fresh instead of inheriting a pin."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(session_affinity=True),
+        )
+        def session_kwargs() -> dict[str, object]:
+            return {"metadata": {"session_id": "s-1", "user_api_key_hash": "k-1"}}
+
+        first = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs=session_kwargs(), messages=_OVERSIZED_TURNS
+        )
+        second = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs=session_kwargs(), messages=[{"role": "user", "content": "ok continue"}]
+        )
+
+        assert first is not None and first.model == "big-model"
+        assert second is not None and second.model == "small-model"
+        assert second.routing_decision["cause"] != "session_affinity_pin"
+
+    @pytest.mark.asyncio
+    async def test_a_pinned_session_escalates_per_request_and_keeps_its_pin(self):
+        """The pin fast path skips classification, not physics: an oversized turn on a session
+        pinned to the small tier is served by the fitting tier, while the stored pin keeps the
+        session's own model so the first turn that fits again routes exactly as pinned."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=_windowed_router(_SMALL, _BIG),
+            complexity_router_config=_tier_config(session_affinity=True),
+        )
+        def session_kwargs() -> dict[str, object]:
+            return {"metadata": {"session_id": "s-2", "user_api_key_hash": "k-2"}}
+
+        pinned = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs=session_kwargs(), messages=[{"role": "user", "content": "ok continue"}]
+        )
+        oversized = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs=session_kwargs(), messages=_OVERSIZED_TURNS
+        )
+        back_to_small = await router.async_pre_routing_hook(
+            model="test-router", request_kwargs=session_kwargs(), messages=[{"role": "user", "content": "ok continue"}]
+        )
+
+        assert pinned is not None and pinned.model == "small-model"
+        assert oversized is not None and oversized.model == "big-model"
+        assert oversized.routing_decision["cause"] == "session_affinity_pin"
+        assert oversized.routing_decision["context_escalated"] is True
+        assert oversized.routing_decision["context_escalation_original_tier"] == "SIMPLE"
+        assert back_to_small is not None and back_to_small.model == "small-model"
+        assert back_to_small.routing_decision["cause"] == "session_affinity_pin"
+
+    @pytest.mark.asyncio
+    async def test_the_adaptive_cold_start_never_samples_a_model_that_cannot_hold_the_prompt(self):
+        """The bandit's exploration is still bounded by physics: with the whole classified tier
+        unobserved, cold start samples only among models whose window holds the prompt."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=Router(
+                model_list=[
+                    {
+                        "model_name": "small-model",
+                        "litellm_params": {"model": "openai/gpt-3.5-turbo", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 16385},
+                    },
+                    {
+                        "model_name": "mid-model",
+                        "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 200000},
+                    },
+                ]
+            ),
+            complexity_router_config={"adaptive": True, "tiers": {"SIMPLE": ["small-model", "mid-model"]}},
+        )
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "mid-model"
+
+    @pytest.mark.asyncio
+    async def test_the_gate_never_resolves_an_authenticating_provider(self, monkeypatch, tmp_path):
+        """Resolving github_copilot runs its OAuth device flow, so a window question must adopt
+        the declaration instead of resolving: the copilot group reads as unknown-window and the
+        request stays put, with zero copilot resolutions recorded."""
+        import json
+        import time
+
+        monkeypatch.setenv("GITHUB_COPILOT_TOKEN_DIR", str(tmp_path))
+        (tmp_path / "api-key.json").write_text(json.dumps({"token": "tid=test", "expires_at": int(time.time()) + 3600}))
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=Router(
+                model_list=[
+                    {"model_name": "cop-pool", "litellm_params": {"model": "github_copilot/gpt-4o"}},
+                    {
+                        "model_name": "big-model",
+                        "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": "ok"},
+                        "model_info": {"max_input_tokens": 200000},
+                    },
+                ]
+            ),
+            complexity_router_config={"tiers": {"SIMPLE": "cop-pool", "COMPLEX": "big-model"}},
+        )
+        real_get_llm_provider = litellm.get_llm_provider
+        copilot_resolutions: List = []
+
+        def _guarded(*args, **kwargs):
+            target = str(kwargs.get("model") or (args[0] if args else "")) + str(kwargs.get("custom_llm_provider") or "")
+            if "github_copilot" in target:
+                copilot_resolutions.append(target)
+                raise RuntimeError("the gate must not resolve an authenticating provider")
+            return real_get_llm_provider(*args, **kwargs)
+
+        monkeypatch.setattr(litellm, "get_llm_provider", _guarded)
+
+        result = await router.async_pre_routing_hook(model="test-router", request_kwargs={}, messages=_OVERSIZED_TURNS)
+
+        assert result is not None
+        assert result.model == "cop-pool"
+        assert copilot_resolutions == []
+
+    @pytest.mark.asyncio
+    async def test_the_full_routing_path_serves_the_escalated_deployment(self):
+        """End to end through Router.async_get_available_deployment: the auto-router alias with
+        an oversized prompt resolves to the big tier's deployment, and a small prompt to the
+        small tier's, with no mocking anywhere in the resolution chain."""
+        router = Router(
+            model_list=[
+                {
+                    "model_name": "smart-router",
+                    "litellm_params": {
+                        "model": "auto_router/complexity_router",
+                        "complexity_router_config": {"tiers": {"SIMPLE": "small-model", "COMPLEX": "big-model"}},
+                    },
+                },
+                {
+                    "model_name": "small-model",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "mock_response": "ok"},
+                    "model_info": {"max_input_tokens": 16385},
+                },
+                {
+                    "model_name": "big-model",
+                    "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": "ok"},
+                    "model_info": {"max_input_tokens": 200000},
+                },
+            ]
+        )
+
+        oversized = await router.async_get_available_deployment(
+            model="smart-router", request_kwargs={}, messages=_OVERSIZED_TURNS
+        )
+        small = await router.async_get_available_deployment(
+            model="smart-router", request_kwargs={}, messages=[{"role": "user", "content": "ok continue"}]
+        )
+
+        assert oversized["model_name"] == "big-model"
+        assert small["model_name"] == "small-model"
+
+
+IMG_PART = {"type": "image_url", "image_url": {"url": "data:image/png;base64,aGk="}}
+PLAN_BODY = {
+    "messages": [{"role": "system", "content": [{"type": "text", "text": "Plan mode is active. Do not execute."}]}]
+}
+
+
+class TestModalityRouting:
+    """modality_routing: the response gate replaces a routed model that cannot take images."""
+
+    IMAGE_MESSAGE = [{"role": "user", "content": [{"type": "text", "text": "What color is this?"}, IMG_PART]}]
+    BASE_TIERS = {"SIMPLE": "text-cheap", "MEDIUM": "vision-mid", "COMPLEX": "vision-big"}
+    BASE_VISION = {"text-cheap": False, "vision-mid": True, "vision-big": True, "vision-default": True}
+
+    @staticmethod
+    def _router(mock_router_instance, config, vision_by_model):
+        """vision_by_model: model name -> True/False (deployment model_info) or None (undeclared)."""
+
+        def get_model_list(model_name=None):
+            if model_name not in vision_by_model:
+                return []
+            declared = vision_by_model[model_name]
+            return [
+                {
+                    "model_name": model_name,
+                    "litellm_params": {"model": f"openai/unmapped-{model_name}"},
+                    "model_info": {} if declared is None else {"supports_vision": declared},
+                }
+            ]
+
+        mock_router_instance.get_model_list = get_model_list
+        return ComplexityRouter(
+            model_name="modality-test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config=config,
+        )
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "config_extra, vision, send_image, expected_model, expect_marker",
+        [
+            ({}, {"text-cheap": False}, True, "text-cheap", False),
+            ({"modality_routing": True}, {"text-cheap": False}, False, "text-cheap", False),
+            ({"modality_routing": True}, {"text-cheap": None}, True, "text-cheap", False),
+        ],
+        ids=["flag_off", "no_image", "undeclared_model_stays_routable"],
+    )
+    async def test_gate_leaves_ungated_requests_untouched(
+        self, mock_router_instance, config_extra, vision, send_image, expected_model, expect_marker
+    ):
+        router = self._router(mock_router_instance, {"tiers": dict(self.BASE_TIERS), **config_extra}, vision)
+        request = self.IMAGE_MESSAGE if send_image else [{"role": "user", "content": "What color is the sky?"}]
+        result = await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=request)
+        assert result.model == expected_model
+        assert result.routing_decision["cause"] == "heuristic_scorer"
+        assert ("modality:image" in (result.routing_decision.get("signals") or ())) is expect_marker
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "part",
+        [
+            IMG_PART,
+            {"type": "input_image", "image_url": "data:image/png;base64,aGk="},
+            {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "aGk="}},
+            {"type": "tool_result", "tool_use_id": "tu_1", "content": [dict(IMG_PART, type="image")]},
+        ],
+        ids=["image_url", "input_image", "anthropic_image", "tool_result_nested"],
+    )
+    async def test_every_image_dialect_escalates(self, mock_router_instance, part):
+        router = self._router(
+            mock_router_instance, {"tiers": dict(self.BASE_TIERS), "modality_routing": True}, dict(self.BASE_VISION)
+        )
+        message = [{"role": "user", "content": [{"type": "text", "text": "What color is this?"}, part]}]
+        result = await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=message)
+        assert result.model == "vision-mid"
+        assert result.routing_decision["cause"] == "modality_escalation"
+        assert "modality_escalated_from:SIMPLE" in result.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "path, expected_model, expected_cause",
+        [
+            ("classifier_escalates", "vision-mid", "modality_escalation"),
+            ("same_tier_repick_keeps_cause", "vision-cheap", "heuristic_scorer"),
+            ("keyword_tier_escalates", "vision-mid", "modality_escalation"),
+            ("no_ask_capable_default_kept", "vision-default", "default_fallback"),
+            ("no_ask_text_default_displaced", "vision-mid", "modality_escalation"),
+            ("custom_tiers_walk", "premium-model", "modality_escalation"),
+            ("pin_kept_bypasses", "text-cheap", "session_affinity_pin"),
+            ("pin_replacement_gated", "vision-big", "modality_escalation"),
+            ("adaptive_pick_rewritten", "vision-mid", "modality_escalation"),
+        ],
+    )
+    async def test_placements_across_decision_paths(self, mock_router_instance, path, expected_model, expected_cause):
+        config = {"tiers": dict(self.BASE_TIERS), "modality_routing": True}
+        vision = dict(self.BASE_VISION)
+        request_kwargs = {}
+        messages = self.IMAGE_MESSAGE
+        if path == "same_tier_repick_keeps_cause":
+            config["tiers"]["SIMPLE"] = ["text-cheap", "vision-cheap"]
+            vision["vision-cheap"] = True
+            with patch(  # test-quality-ok: the mixed-pool repick is unreachable deterministically without pinning the first random pick
+                "litellm.router_strategy.complexity_router.complexity_router.random.choice",
+                side_effect=lambda pool: sorted(pool)[0],
+            ):
+                router = self._router(mock_router_instance, config, vision)
+                result = await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=messages)
+            assert result.model == expected_model
+            assert result.routing_decision["cause"] == expected_cause
+            assert result.routing_decision["signals"][-1] == "modality:image"
+            return
+        if path == "keyword_tier_escalates":
+            config["keyword_tier_rules"] = [{"keywords": ["quick lookup"], "tier": "SIMPLE"}]
+            messages = [
+                {"role": "user", "content": [{"type": "text", "text": "quick lookup: what is this?"}, IMG_PART]}
+            ]
+        elif path == "no_ask_capable_default_kept":
+            config["default_model"] = "vision-default"
+            messages = [{"role": "user", "content": [IMG_PART]}]
+        elif path == "no_ask_text_default_displaced":
+            config["default_model"] = "text-default"
+            vision["text-default"] = False
+            messages = [{"role": "user", "content": [IMG_PART]}]
+        elif path == "custom_tiers_walk":
+            config = {
+                "classifier_type": "llm",
+                "classifier_llm_config": {"model": "gpt-4o-mini"},
+                "fallback_tier": "cheap",
+                "tier_definitions": [
+                    {"name": "cheap", "description": "trivial asks"},
+                    {"name": "premium", "description": "hard asks"},
+                ],
+                "tiers": {"cheap": "cheap-model", "premium": "premium-model"},
+                "keyword_tier_rules": [{"keywords": ["quick lookup"], "tier": "cheap"}],
+                "modality_routing": True,
+            }
+            vision = {"cheap-model": False, "premium-model": True}
+            messages = [
+                {"role": "user", "content": [{"type": "text", "text": "quick lookup: what is this?"}, IMG_PART]}
+            ]
+        elif path in ("pin_kept_bypasses", "pin_replacement_gated"):
+            cache = AsyncMock()
+            cache.async_get_cache = AsyncMock(return_value={"model": "text-cheap", "tier": "SIMPLE"})
+            mock_router_instance.cache = cache
+            config["session_affinity"] = True
+            request_kwargs = {"metadata": {"session_id": "s1"}}
+            if path == "pin_replacement_gated":
+                config["tiers"]["MEDIUM"] = "text-mid"
+                vision["text-mid"] = False
+                messages = [
+                    {"role": "user", "content": [{"type": "text", "text": "LITELLM ESCALATE describe this"}, IMG_PART]}
+                ]
+        elif path == "adaptive_pick_rewritten":
+            config["adaptive"] = True
+            mock_router_instance.model_list = []
+            mock_router_instance.model_name_to_deployment_indices = {}
+        router = self._router(mock_router_instance, config, vision)
+        result = await router.async_pre_routing_hook(model="m", request_kwargs=request_kwargs, messages=messages)
+        assert result.model == expected_model
+        assert result.routing_decision["cause"] == expected_cause
+        if path == "adaptive_pick_rewritten":
+            assert request_kwargs["metadata"]["adaptive_router_chosen_model"] == expected_model
+
+    @pytest.mark.asyncio
+    async def test_plan_floored_decision_never_falls_to_default_model(self, mock_router_instance):
+        """An upward-only walk cannot undercut the floor; default_model must not either."""
+        config = {
+            "tiers": {"SIMPLE": "vision-cheap", "MEDIUM": "text-mid"},
+            "default_model": "vision-default",
+            "plan_mode_min_tier": "MEDIUM",
+            "modality_routing": True,
+        }
+        vision = {"vision-cheap": True, "text-mid": False, "vision-default": True}
+        router = self._router(mock_router_instance, config, vision)
+        with pytest.raises(litellm.BadRequestError, match="no model"):
+            await router.async_pre_routing_hook(
+                model="m",
+                request_kwargs={"proxy_server_request": {"body": PLAN_BODY}},
+                messages=[{"role": "user", "content": [{"type": "text", "text": "plan this"}, IMG_PART]}],
+            )
+
+    @pytest.mark.asyncio
+    async def test_at_floor_plan_turn_never_falls_to_default_model(self, mock_router_instance):
+        """A sentinel turn whose classified tier already satisfies the floor keeps its ordinary
+        cause, so the record carries no floor marker; the default arm must still refuse it."""
+        config = {
+            "tiers": {"SIMPLE": "text-a", "MEDIUM": "text-b"},
+            "default_model": "vision-default",
+            "plan_mode_min_tier": "SIMPLE",
+            "modality_routing": True,
+        }
+        vision = {"text-a": False, "text-b": False, "vision-default": True}
+        router = self._router(mock_router_instance, config, vision)
+        with pytest.raises(litellm.BadRequestError, match="no model"):
+            await router.async_pre_routing_hook(
+                model="m",
+                request_kwargs={"proxy_server_request": {"body": PLAN_BODY}},
+                messages=[{"role": "user", "content": [{"type": "text", "text": "plan this"}, IMG_PART]}],
+            )
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "default_model, default_vision, expect_error",
+        [(None, None, True), ("text-default", False, True), ("vision-default", True, False)],
+        ids=["no_default", "text_only_default", "vision_default_serves"],
+    )
+    async def test_no_capable_tier_above_uses_default_or_rejects(
+        self, mock_router_instance, default_model, default_vision, expect_error
+    ):
+        config = {"tiers": {"SIMPLE": "text-cheap", "COMPLEX": "text-big"}, "modality_routing": True}
+        vision = {"text-cheap": False, "text-big": False}
+        if default_model is not None:
+            config["default_model"] = default_model
+            vision[default_model] = default_vision
+        router = self._router(mock_router_instance, config, vision)
+        if expect_error:
+            with pytest.raises(litellm.BadRequestError, match="no model"):
+                await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=self.IMAGE_MESSAGE)
+            return
+        result = await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=self.IMAGE_MESSAGE)
+        assert result.model == "vision-default"
+        assert result.routing_decision["cause"] == "modality_escalation"
+        assert "modality_escalated_from:SIMPLE" in result.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    async def test_mixed_deployment_group_is_treated_text_only(self, mock_router_instance):
+        def get_model_list(model_name=None):
+            declared = {"mixed-group": [True, False], "vision-big": [True]}.get(model_name)
+            if declared is None:
+                return []
+            return [
+                {
+                    "model_name": model_name,
+                    "litellm_params": {"model": f"openai/unmapped-{model_name}-{i}"},
+                    "model_info": {"supports_vision": accepts},
+                }
+                for i, accepts in enumerate(declared)
+            ]
+
+        mock_router_instance.get_model_list = get_model_list
+        router = ComplexityRouter(
+            model_name="modality-test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={
+                "tiers": {"SIMPLE": "mixed-group", "COMPLEX": "vision-big"},
+                "modality_routing": True,
+            },
+        )
+        result = await router.async_pre_routing_hook(model="m", request_kwargs={}, messages=self.IMAGE_MESSAGE)
+        assert result.model == "vision-big"
+        assert result.routing_decision["cause"] == "modality_escalation"
+
+    @pytest.mark.asyncio
+    async def test_continuation_turn_screenshot_escalates_past_the_held_model(self, mock_router_instance):
+        """classification_mode user_turn replays the held model on continuation turns; a
+        continuation carrying a screenshot must still be re-placed when that model is text-only."""
+        mock_router_instance.cache = DualCache()
+        config = {
+            "tiers": dict(self.BASE_TIERS),
+            "classification_mode": "user_turn",
+            "modality_routing": True,
+        }
+        router = self._router(mock_router_instance, config, dict(self.BASE_VISION))
+        first = await router.async_pre_routing_hook(
+            model="m",
+            request_kwargs={"metadata": {"session_id": "cont-1"}},
+            messages=[{"role": "user", "content": "hi there"}],
+        )
+        assert first.model == "text-cheap"
+        continuation = [
+            {"role": "user", "content": "hi there"},
+            {"role": "assistant", "content": [{"type": "tool_use", "id": "tu_1", "name": "screenshot", "input": {}}]},
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "tu_1",
+                        "content": [{"type": "image", "source": {"type": "base64", "data": "aGk="}}],
+                    }
+                ],
+            },
+        ]
+        second = await router.async_pre_routing_hook(
+            model="m", request_kwargs={"metadata": {"session_id": "cont-1"}}, messages=continuation
+        )
+        assert second.model == "vision-mid"
+        assert second.routing_decision["cause"] == "modality_escalation"
+        assert "modality_escalated_from:SIMPLE" in second.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    async def test_rewrite_carries_the_context_escalation_record(self, mock_router_instance):
+        """A context-window escalation and a modality re-place are separate facts on one
+        record; rewriting for the image must not drop the sibling gate's fields."""
+        from litellm.types.router import PreRoutingHookResponse
+
+        router = self._router(
+            mock_router_instance,
+            {"tiers": dict(self.BASE_TIERS), "modality_routing": True},
+            dict(self.BASE_VISION),
+        )
+        decision = router._build_routing_decision(
+            routed_model="text-cheap",
+            cause="heuristic_scorer",
+            tier=ComplexityTier.SIMPLE,
+            context_escalation_original_tier=ComplexityTier.SIMPLE,
+        )
+        response = PreRoutingHookResponse(model="text-cheap", messages=None, routing_decision=decision)
+        rewritten = await router._gate_response_modality(response, None, self.IMAGE_MESSAGE, {})
+        assert rewritten.model == "vision-mid"
+        assert rewritten.routing_decision["cause"] == "modality_escalation"
+        assert rewritten.routing_decision["context_escalated"] is True
+        assert rewritten.routing_decision["context_escalation_original_tier"] == "SIMPLE"
+
+    def test_modality_escalation_is_never_pinnable(self):
+        from litellm.router_strategy.complexity_router.complexity_router import _decision_is_pinnable
+
+        assert _decision_is_pinnable({"cause": "modality_escalation"}) is False
+        assert _decision_is_pinnable({"cause": "heuristic_scorer"}) is True
diff --git a/tests/test_litellm/router_strategy/test_complexity_tier_predictor.py b/tests/test_litellm/router_strategy/test_complexity_tier_predictor.py
new file mode 100644
index 00000000000..5bbe0fb5669
--- /dev/null
+++ b/tests/test_litellm/router_strategy/test_complexity_tier_predictor.py
@@ -0,0 +1,91 @@
+from typing import Final
+
+import pytest
+
+from litellm.router_strategy.complexity_router.tier_predictor import (
+    TierCohortStatistic,
+    TierDomainStatistic,
+    TierGlobalStatistic,
+    TierSuccessPredictor,
+    TrainedTierArtifact,
+    resolve_tier_artifact,
+    similarity_cohort,
+)
+from litellm.types.router import RequestType
+
+
+def _artifact(
+    global_successes: tuple[float, float, float, float] = (4.0, 5.0, 6.0, 7.0),
+    threshold: float = 0.75,
+    domain_statistics: tuple[TierDomainStatistic, ...] = (),
+    cohort_statistics: tuple[TierCohortStatistic, ...] = (),
+) -> TrainedTierArtifact:
+    return TrainedTierArtifact(
+        global_statistics=tuple(
+            TierGlobalStatistic(tier=tier, successes=successes, observations=10.0)
+            for tier, successes in enumerate(global_successes, start=1)
+        ),
+        domain_statistics=domain_statistics,
+        cohort_statistics=cohort_statistics,
+        domain_prior_mass=10.0,
+        cohort_prior_mass=10.0,
+        routing_threshold=threshold,
+    )
+
+
+def test_predictions_are_monotonic_across_tiers() -> None:
+    predictor: Final = TierSuccessPredictor(_artifact(global_successes=(9.0, 2.0, 7.0, 6.0)))
+
+    prediction: Final = predictor.predict("hello", RequestType.GENERAL)
+
+    probabilities: Final = tuple(prediction.probabilities.values())
+    assert probabilities == tuple(sorted(probabilities))
+
+
+def test_domain_and_cohort_statistics_back_off_hierarchically() -> None:
+    matching_cohort: Final = similarity_cohort("hello", RequestType.GENERAL)
+    artifact: Final = _artifact(
+        global_successes=(1.0, 5.0, 6.0, 7.0),
+        domain_statistics=(
+            TierDomainStatistic(
+                tier=1,
+                request_type=RequestType.GENERAL,
+                successes=10.0,
+                observations=10.0,
+            ),
+        ),
+        cohort_statistics=(
+            TierCohortStatistic(
+                tier=1,
+                cohort=matching_cohort,
+                successes=0.0,
+                observations=10.0,
+            ),
+        ),
+    )
+    predictor: Final = TierSuccessPredictor(artifact)
+
+    cohort_probability: Final = predictor.predict("hello", RequestType.GENERAL).probabilities[1]
+    domain_probability: Final = predictor.predict("hello " * 100, RequestType.GENERAL).probabilities[1]
+    global_probability: Final = predictor.predict("hello", RequestType.WRITING).probabilities[1]
+
+    assert cohort_probability == pytest.approx(7.0 / 24.0)
+    assert domain_probability == pytest.approx(7.0 / 12.0)
+    assert global_probability == pytest.approx(1.0 / 6.0)
+
+
+def test_selects_first_tier_above_probability_threshold() -> None:
+    predictor: Final = TierSuccessPredictor(_artifact(global_successes=(4.0, 6.0, 8.0, 9.0), threshold=0.7))
+
+    prediction: Final = predictor.predict("hello", RequestType.GENERAL)
+
+    assert prediction.required_tier == 3
+
+
+def test_builtin_ultrafeedback_artifact_is_loadable() -> None:
+    artifact: Final = resolve_tier_artifact("ultrafeedback")
+
+    assert artifact.routing_threshold == 0.75
+    assert artifact.domain_prior_mass == 200.0
+    assert artifact.cohort_prior_mass == 20.0
+    assert artifact.datasets[0].license == "MIT"
diff --git a/tests/test_litellm/router_utils/pre_call_checks/test_deployment_affinity_check.py b/tests/test_litellm/router_utils/pre_call_checks/test_deployment_affinity_check.py
index b3a2bdda53c..60433921de6 100644
--- a/tests/test_litellm/router_utils/pre_call_checks/test_deployment_affinity_check.py
+++ b/tests/test_litellm/router_utils/pre_call_checks/test_deployment_affinity_check.py
@@ -598,6 +598,45 @@ async def test_async_filter_deployments_falls_back_when_cached_deployment_is_unh
     assert filtered == healthy_deployments
 
 
+@pytest.mark.asyncio
+async def test_async_filter_deployments_does_not_pin_when_target_order_is_set():
+    user_key = "user-key-order-fallback"
+    stable_model_map_key = "claude-sonnet-4-5@20250929"
+    cache = AsyncMock()
+    cache.async_get_cache = AsyncMock(return_value={"model_id": "deployment-1"})
+    callback = DeploymentAffinityCheck(
+        cache=cache,
+        ttl_seconds=123,
+        enable_user_key_affinity=True,
+        enable_responses_api_affinity=False,
+    )
+    healthy_deployments = [
+        {
+            "model_name": stable_model_map_key,
+            "litellm_params": {"model": f"vertex_ai/{stable_model_map_key}"},
+            "model_info": {"id": "deployment-1"},
+        },
+        {
+            "model_name": stable_model_map_key,
+            "litellm_params": {
+                "model": f"bedrock/global.anthropic.{stable_model_map_key}-v1:0"
+            },
+            "model_info": {"id": "deployment-2"},
+        },
+    ]
+
+    filtered = await callback.async_filter_deployments(
+        model="some-router-model-group",
+        healthy_deployments=healthy_deployments,
+        messages=None,
+        request_kwargs={"_target_order": 2, "metadata": {"user_api_key_hash": user_key}},
+        parent_otel_span=None,
+    )
+
+    assert filtered == healthy_deployments
+    cache.async_get_cache.assert_not_called()
+
+
 @pytest.mark.asyncio
 async def test_async_user_key_affinity_ttl_expiry_allows_reroute():
     """
diff --git a/tests/test_litellm/router_utils/pre_call_checks/test_prompt_caching_deployment_check.py b/tests/test_litellm/router_utils/pre_call_checks/test_prompt_caching_deployment_check.py
index f54a1cfa284..79ae00e155c 100644
--- a/tests/test_litellm/router_utils/pre_call_checks/test_prompt_caching_deployment_check.py
+++ b/tests/test_litellm/router_utils/pre_call_checks/test_prompt_caching_deployment_check.py
@@ -150,6 +150,25 @@ async def test_async_filter_deployments_narrows_prompt_above_model_minimum():
     assert filtered == [deployments[1]]
 
 
+@pytest.mark.asyncio
+async def test_async_filter_deployments_does_not_pin_when_target_order_is_set():
+    cache = DualCache()
+    check = PromptCachingDeploymentCheck(cache=cache)
+    deployments = _deployments("anthropic/claude-opus-4-6", "anthropic/claude-opus-4-6")
+    messages = _messages(word_count=5000)
+
+    await PromptCachingCache(cache=cache).async_add_model_id(model_id="dep-2", messages=messages, tools=None)
+
+    filtered = await check.async_filter_deployments(
+        model=MODEL_GROUP_ALIAS,
+        healthy_deployments=deployments,
+        messages=messages,
+        request_kwargs={"_target_order": 2},
+    )
+
+    assert filtered == deployments
+
+
 @pytest.mark.asyncio
 async def test_async_filter_deployments_narrows_for_group_whose_model_minimum_is_lower():
     """
diff --git a/tests/test_litellm/router_utils/test_fallback_event_handlers.py b/tests/test_litellm/router_utils/test_fallback_event_handlers.py
index 8336926c050..a4965c49f07 100644
--- a/tests/test_litellm/router_utils/test_fallback_event_handlers.py
+++ b/tests/test_litellm/router_utils/test_fallback_event_handlers.py
@@ -11,7 +11,10 @@ from litellm.router_utils.fallback_event_handlers import (
     AttemptedFallbackTargets,
     _trigger_cooldown_for_failed_deployment,
     fallback_attempt_key,
+    clear_pre_routing_selection,
     get_fallback_model_group,
+    get_pre_routing_selection,
+    record_pre_routing_selection,
     run_async_fallback,
 )
 
@@ -611,6 +614,27 @@ async def test_run_async_fallback_forwards_attempted_model_groups_to_nested_call
     )
 
 
+@pytest.mark.asyncio
+async def test_run_async_fallback_can_target_the_requested_group_when_a_pre_router_replaced_it():
+    """The requested group was never called when a pre-router selected a tier, so a
+    tier fallback may legitimately target that originally requested group."""
+    router = RecordingRouter()
+
+    await run_async_fallback(
+        litellm_router=router,
+        fallback_model_group=["requested-model"],
+        original_model_group="requested-model",
+        original_exception=RuntimeError("selected tier failed"),
+        max_fallbacks=3,
+        fallback_depth=0,
+        model="requested-model",
+        metadata={"pre_routing_selected_model": "selected-tier"},
+    )
+
+    assert router.received_kwargs["model"] == "requested-model"
+    assert router.received_kwargs["attempted_targets"].keys == frozenset({"selected-tier", "requested-model"})
+
+
 @pytest.mark.asyncio
 @pytest.mark.parametrize(
     "entry",
@@ -1090,3 +1114,141 @@ async def test_run_async_fallback_preserves_original_model_group_on_nested_fallb
     metadata = router.received_kwargs["metadata"]
     assert metadata["attempted_fallbacks"] == 2
     assert metadata["original_model_group"] == "primary-model"
+
+
+class TestPreRoutingSelectionCarriesToFallbacks:
+    """#38832: a complexity/auto router picks a tier behind the router name, but fallback
+    lookup kept using the router name, so the tier's configured chain never ran."""
+
+    def test_selection_is_recorded_in_the_metadata_bucket(self):
+        kwargs = {"model": "smart-router", "metadata": {}}
+        record_pre_routing_selection(kwargs, "tier1")
+        assert kwargs["metadata"]["pre_routing_selected_model"] == "tier1"
+        assert get_pre_routing_selection(kwargs) == "tier1"
+
+    def test_selection_is_recorded_in_the_litellm_metadata_bucket(self):
+        kwargs = {"model": "smart-router", "litellm_metadata": {}}
+        record_pre_routing_selection(kwargs, "tier2")
+        assert get_pre_routing_selection(kwargs) == "tier2"
+
+    def test_a_bucket_survives_the_kwargs_copy_that_fallbacks_run_on(self):
+        """The bucket is shared by reference, which is the whole reason this works."""
+        outer = {"model": "smart-router", "metadata": {}}
+        inner = {**outer}
+        record_pre_routing_selection(inner, "tier1")
+        assert get_pre_routing_selection(outer) == "tier1"
+
+    def test_no_selection_reads_as_none(self):
+        assert get_pre_routing_selection({"model": "smart-router", "metadata": {}}) is None
+        assert get_pre_routing_selection({"model": "smart-router"}) is None
+
+    def test_missing_kwargs_is_a_no_op(self):
+        """A caller with no kwargs must not raise, and must not leak the selection anywhere."""
+        record_pre_routing_selection(None, "tier1")
+
+        assert get_pre_routing_selection({}) is None
+
+    def test_a_non_dict_bucket_is_ignored(self):
+        kwargs = {"model": "smart-router", "metadata": "not-a-dict"}
+        record_pre_routing_selection(kwargs, "tier1")
+        assert get_pre_routing_selection(kwargs) is None
+
+    def test_fallbacks_resolve_against_the_selected_tier(self):
+        """The lookup the router performs, keyed on the tier rather than the router name."""
+        fallbacks = [{"tier1": ["backup-a", "backup-b"]}, {"tier2": ["backup-c"]}]
+        assert get_fallback_model_group(fallbacks=fallbacks, model_group="tier1")[0] == ["backup-a", "backup-b"]
+        assert get_fallback_model_group(fallbacks=fallbacks, model_group="smart-router")[0] is None
+
+
+class TestPreRoutingSelectionIsPerHop:
+    """#38832 review: the buckets also carry whatever the caller sent, and a fallback hop
+    inherits the previous hop's tier, so a hop must start without a selection."""
+
+    def test_a_caller_supplied_selection_is_dropped(self):
+        kwargs = {"model": "plain", "metadata": {"pre_routing_selected_model": "tier1"}}
+
+        clear_pre_routing_selection(kwargs)
+
+        assert get_pre_routing_selection(kwargs) is None
+        assert "pre_routing_selected_model" not in kwargs["metadata"]
+
+    def test_both_buckets_are_cleared(self):
+        kwargs = {
+            "metadata": {"pre_routing_selected_model": "tier1"},
+            "litellm_metadata": {"pre_routing_selected_model": "tier2"},
+        }
+
+        clear_pre_routing_selection(kwargs)
+
+        assert get_pre_routing_selection(kwargs) is None
+
+    def test_the_rest_of_the_bucket_is_left_alone(self):
+        kwargs = {"metadata": {"pre_routing_selected_model": "tier1", "tags": ["a"]}}
+
+        clear_pre_routing_selection(kwargs)
+
+        assert kwargs["metadata"] == {"tags": ["a"]}
+
+    def test_clearing_is_a_no_op_without_a_usable_bucket(self):
+        kwargs = {"model": "plain", "metadata": "not-a-dict"}
+
+        clear_pre_routing_selection(None)
+        clear_pre_routing_selection(kwargs)
+
+        assert kwargs == {"model": "plain", "metadata": "not-a-dict"}
+
+    def test_a_selection_recorded_after_clearing_is_kept(self):
+        """Clearing runs before routing, so the hook's own write must survive it."""
+        kwargs = {"model": "smart-router", "metadata": {"pre_routing_selected_model": "stale"}}
+
+        clear_pre_routing_selection(kwargs)
+        record_pre_routing_selection(kwargs, "tier1")
+
+        assert get_pre_routing_selection(kwargs) == "tier1"
+
+
+class TestOrderedFallbackLookupGroups:
+    def test_tier_first_then_requested_group_deduped(self):
+        from litellm.router_utils.fallback_event_handlers import (
+            PRE_ROUTING_SELECTED_MODEL_KEY,
+            fallback_lookup_groups,
+        )
+
+        kwargs = {"litellm_metadata": {PRE_ROUTING_SELECTED_MODEL_KEY: "tier1"}}
+        assert fallback_lookup_groups(kwargs, "smart-router") == ("tier1", "smart-router")
+        assert fallback_lookup_groups(kwargs, "tier1") == ("tier1",)
+        assert fallback_lookup_groups({}, "smart-router") == ("smart-router",)
+        assert fallback_lookup_groups({}, None) == ()
+
+    def test_session_remap_keeps_the_bound_router_between_tier_and_requested_group(self):
+        from litellm.router_utils.fallback_event_handlers import (
+            PRE_ROUTING_SELECTED_MODEL_KEY,
+            fallback_lookup_groups,
+        )
+
+        kwargs = {
+            "litellm_metadata": {
+                PRE_ROUTING_SELECTED_MODEL_KEY: "tier1",
+                "model_group": "smart-router",
+            }
+        }
+
+        assert fallback_lookup_groups(kwargs, "requested-model") == (
+            "tier1",
+            "smart-router",
+            "requested-model",
+        )
+        assert fallback_lookup_groups({"metadata": {"model_group": []}}, "requested-model") == (
+            "requested-model",
+        )
+
+    def test_first_resolving_group_wins_and_generic_idx_survives_a_miss(self):
+        from litellm.router_utils.fallback_event_handlers import (
+            get_fallback_model_group_for_lookup_groups,
+        )
+
+        fallbacks = [{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}, {"*": ["backup-c"]}]
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier1", "smart-router")) == (["backup-a"], None)
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier9", "smart-router")) == (["backup-b"], None)
+        assert get_fallback_model_group_for_lookup_groups(fallbacks, ("tier9", "no-such")) == (["backup-c"], 2)
+        assert get_fallback_model_group_for_lookup_groups([{"tier1": ["backup-a"]}], ("no", "nope")) == (None, None)
diff --git a/tests/test_litellm/router_utils/test_pattern_match_deployments.py b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
new file mode 100644
index 00000000000..795d448ef5f
--- /dev/null
+++ b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
@@ -0,0 +1,78 @@
+"""Behavior pins for ``litellm/router_utils/pattern_match_deployments.py``."""
+
+from __future__ import annotations
+
+from litellm.router_utils import pattern_match_deployments
+from litellm.router_utils.pattern_match_deployments import PatternMatchRouter
+
+
+def _wildcard_deployment(model_name: str) -> dict:
+    return {"model_name": model_name, "litellm_params": {"model": model_name}}
+
+
+def _matched_models(matches: list[dict] | None) -> list[str]:
+    return [deployment["litellm_params"]["model"] for deployment in matches or []]
+
+
+def test_get_pattern_never_resolves_declared_authenticating_providers(monkeypatch):
+    """Regression: resolving a github_copilot/chatgpt name through ``get_llm_provider`` runs the
+    provider's OAuth device flow; the auth layer walks every wildcard router on every request, so
+    a single metadata lookup for an unserved name would block the proxy's event loop."""
+    resolution_attempts: list[str] = []
+
+    def _oauth_tripwire(model, *args, **kwargs):
+        resolution_attempts.append(model)
+        raise AssertionError("get_llm_provider would run the OAuth device flow")
+
+    monkeypatch.setattr(pattern_match_deployments, "get_llm_provider", _oauth_tripwire)
+
+    unmatched_router = PatternMatchRouter()
+    unmatched_router.add_pattern("anthropic/*", _wildcard_deployment("anthropic/*"))
+    assert unmatched_router.get_pattern("github_copilot/gpt-4o") is None
+
+    matched_router = PatternMatchRouter()
+    matched_router.add_pattern("github_copilot/*", _wildcard_deployment("github_copilot/*"))
+    assert _matched_models(matched_router.get_pattern("github_copilot/gpt-4o")) == ["github_copilot/gpt-4o"]
+    assert _matched_models(matched_router.get_pattern("gpt-4o", custom_llm_provider="github_copilot")) == [
+        "github_copilot/gpt-4o"
+    ]
+
+    assert resolution_attempts == []
+
+
+def test_get_pattern_bare_provider_name_never_matches_that_providers_wildcard(monkeypatch):
+    """Regression: a bare ``github_copilot`` adopted itself as its provider and retried as
+    ``github_copilot/github_copilot``, false-matching the wildcard for a name no deployment serves."""
+
+    def _unknown_provider(model, *args, **kwargs):
+        raise ValueError(f"unknown provider for {model}")
+
+    monkeypatch.setattr(pattern_match_deployments, "get_llm_provider", _unknown_provider)
+    router = PatternMatchRouter()
+    router.add_pattern("github_copilot/*", _wildcard_deployment("github_copilot/*"))
+    assert router.get_pattern("github_copilot") is None
+
+
+def test_get_pattern_missing_model_returns_none(monkeypatch):
+    """Regression: a request without a model reaches the auth layer's pattern walk as ``None``; the
+    declared-provider guard raised ``TypeError`` where the old inline resolve swallowed every
+    resolver error, so the proxy's missing-model 400 became a crash."""
+
+    def _unknown_provider(model, *args, **kwargs):
+        raise ValueError(f"unknown provider for {model}")
+
+    monkeypatch.setattr(pattern_match_deployments, "get_llm_provider", _unknown_provider)
+    router = PatternMatchRouter()
+    router.add_pattern("openai/*", _wildcard_deployment("openai/*"))
+    assert router.get_pattern(None) is None
+
+
+def test_get_pattern_still_resolves_unqualified_names(monkeypatch):
+    monkeypatch.setattr(
+        pattern_match_deployments,
+        "get_llm_provider",
+        lambda model, **kwargs: (model, "openai", None, None),
+    )
+    router = PatternMatchRouter()
+    router.add_pattern("openai/*", _wildcard_deployment("openai/*"))
+    assert _matched_models(router.get_pattern("gpt-4o")) == ["openai/gpt-4o"]
diff --git a/tests/test_litellm/rust_bridge/native_route_wheel_test.py b/tests/test_litellm/rust_bridge/native_route_wheel_test.py
new file mode 100644
index 00000000000..0ce49d51aed
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/native_route_wheel_test.py
@@ -0,0 +1,349 @@
+from __future__ import annotations
+
+import asyncio
+import importlib.util
+import json
+import os
+import signal
+import subprocess
+import sys
+import tempfile
+import threading
+import zipfile
+from http.client import HTTPMessage
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+from socket import socket as Socket
+from typing import Final
+
+REQUEST_STARTED: Final = threading.Event()
+REQUEST_CANCELLED: Final = threading.Event()
+
+ANTHROPIC_RESPONSE: Final = (
+    b'{"id":"msg_native","type":"message","role":"assistant",'
+    b'"model":"claude-sonnet-4-5","content":[{"type":"text","text":"native-message"}],'
+    b'"stop_reason":"end_turn","stop_sequence":null,'
+    b'"usage":{"input_tokens":2,"output_tokens":3}}'
+)
+
+
+class NativeRouteHandler(BaseHTTPRequestHandler):
+    protocol_version = "HTTP/1.1"
+
+    def do_POST(self) -> None:
+        content_length: Final = int(self.headers.get("content-length", "0"))
+        body: Final = json.loads(self.rfile.read(content_length))
+        route: Final = self.headers.get("x-test-route")
+        outcome: Final = self.headers.get("x-test-outcome")
+        assert_native_request(route, outcome, self.path, self.headers, body)
+        if outcome == "hang":
+            REQUEST_STARTED.set()
+            self.connection.settimeout(5)
+            if connection_was_cancelled(self.connection):
+                REQUEST_CANCELLED.set()
+            return
+
+        status: Final = 429 if outcome == "429" else 200
+        response_body: Final = native_response(status, route)
+
+        self.send_response(status)
+        self.send_header("content-type", "application/json")
+        self.send_header("content-length", str(len(response_body)))
+        self.send_header("connection", "close")
+        self.end_headers()
+        self.wfile.write(response_body)
+
+    def log_message(self, _message_format: str, *_args: object) -> None:
+        pass
+
+
+def connection_was_cancelled(connection: Socket) -> bool:
+    try:
+        return connection.recv(1) == b""
+    except TimeoutError:
+        return False
+    except OSError:
+        return True
+
+
+def assert_native_request(
+    route: str | None,
+    outcome: str | None,
+    path: str,
+    headers: HTTPMessage,
+    body: object,
+) -> None:
+    if route not in {"ocr", "transcription", "messages", "chat_completions"}:
+        raise AssertionError(f"unexpected route marker: {route!r}")
+    if outcome not in {"success", "429", "hang"}:
+        raise AssertionError(f"unexpected outcome marker: {outcome!r}")
+    if not isinstance(body, dict):
+        raise TypeError(f"{route} sent {type(body).__name__}, expected a JSON object")
+    if route == "ocr":
+        assert path == "/v1/ocr"
+        assert headers.get("authorization") == "Bearer sk-native"
+        assert body["model"] == "mistral-ocr-latest"
+        assert body["document"]["document_url"] == "https://example.com/document.pdf"
+        assert body["include_image_base64"] is True
+        return
+    if route == "transcription":
+        assert path == "/model/mistral.voxtral-mini-3b-2507/converse"
+        assert headers.get("authorization", "").startswith("AWS4-HMAC-SHA256 ")
+        assert headers.get("x-amz-date")
+        assert body["messages"][0]["content"][0]["audio"]["source"]["bytes"] == "AQI="
+        assert "The audio language is en" in body["messages"][0]["content"][1]["text"]
+        return
+    assert path == "/v1/messages"
+    assert headers.get("x-api-key") == "sk-native"
+    assert body["model"] == "claude-sonnet-4-5"
+    if route == "messages":
+        assert body["max_tokens"] == 16
+        assert body["messages"][0]["content"] == "hello-from-messages"
+        return
+    assert body["max_tokens"] == 17
+    assert body["messages"][0]["content"] == [{"type": "text", "text": "hello-from-chat"}]
+
+
+def native_response(status: int, route: str | None) -> bytes:
+    if status == 429:
+        return b'{"error":"native-rate-limit"}'
+    if route == "ocr":
+        return b'{"pages":[{"index":0,"markdown":"native-ocr"}]}'
+    if route == "transcription":
+        return b'{"output":{"message":{"content":[{"text":"native-transcription"}]}}}'
+    return ANTHROPIC_RESPONSE
+
+
+def load_native(native_path: Path) -> object:
+    module_spec: Final = importlib.util.spec_from_file_location("litellm.rust_bridge._native", native_path)
+    if module_spec is None or module_spec.loader is None:
+        raise RuntimeError("cannot create native extension import specification")
+    native_module: Final = importlib.util.module_from_spec(module_spec)
+    module_spec.loader.exec_module(native_module)
+    return native_module
+
+
+def route_kwargs(route: str, api_base: str, outcome: str) -> dict[str, object]:
+    common: Final = {
+        "api_base": api_base,
+        "extra_headers": {"x-test-outcome": outcome, "x-test-route": route},
+        "timeout_seconds": 3.0,
+    }
+    if route == "ocr":
+        return common | {
+            "model": "mistral-ocr-latest",
+            "document": {"type": "document_url", "document_url": "https://example.com/document.pdf"},
+            "api_key": "sk-native",
+            "custom_llm_provider": "mistral",
+            "optional_params": {"include_image_base64": True},
+        }
+    if route == "transcription":
+        return common | {
+            "model": "mistral.voxtral-mini-3b-2507",
+            "audio": {"data": "AQI=", "format": "wav", "filename": "audio.wav"},
+            "custom_llm_provider": "bedrock",
+            "optional_params": {
+                "aws_access_key_id": "native-access-key",
+                "aws_secret_access_key": "native-secret-key",
+                "aws_region_name": "us-east-1",
+                "language": "en",
+            },
+        }
+    if route == "messages":
+        return common | {
+            "model": "claude-sonnet-4-5",
+            "body": {
+                "model": "claude-sonnet-4-5",
+                "max_tokens": 16,
+                "messages": [{"role": "user", "content": "hello-from-messages"}],
+            },
+            "api_key": "sk-native",
+            "custom_llm_provider": "anthropic",
+        }
+    if route == "chat_completions":
+        return common | {
+            "model": "anthropic/claude-sonnet-4-5",
+            "messages": [{"role": "user", "content": "hello-from-chat"}],
+            "optional_params": {"max_tokens": 17},
+            "api_key": "sk-native",
+        }
+    raise AssertionError(f"unknown route: {route}")
+
+
+def assert_success(route: str, response: object) -> None:
+    if not isinstance(response, dict):
+        raise TypeError(f"{route} returned {type(response).__name__}, expected dict")
+    actual: Final = success_value(route, response)
+    expected: Final = (
+        "native-ocr" if route == "ocr" else "native-transcription" if route == "transcription" else "native-message"
+    )
+    if actual != expected:
+        raise AssertionError(f"{route} returned {actual!r}, expected {expected!r}")
+
+
+def assert_traced_success(route: str, response: object) -> None:
+    if not isinstance(response, dict):
+        raise TypeError(f"{route} returned {type(response).__name__}, expected a traced dict")
+    assert_success(route, response["response"])
+    expected_function: Final = "audio_transcription" if route == "transcription" else route
+    assert response["trace"][0] == {"function": expected_function, "depth": 0}
+
+
+def success_value(route: str, response: dict[object, object]) -> object:
+    if route == "ocr":
+        return response["pages"][0]["markdown"]
+    if route == "transcription":
+        return response["text"]
+    if route == "messages":
+        return response["content"][0]["text"]
+    return response["choices"][0]["message"]["content"]
+
+
+def assert_rate_limit(native: object, route: str, error: BaseException) -> None:
+    if route == "chat_completions":
+        upstream_error: Final = native.RustUpstreamError
+        if not isinstance(error, upstream_error) or error.args[0] != 429:
+            raise AssertionError(f"{route} returned the wrong 429 error: {error!r}")
+        return
+    if not isinstance(error, RuntimeError) or "429" not in str(error):
+        raise AssertionError(f"{route} returned the wrong 429 error: {error!r}")
+
+
+def exercise_sync(native: object, api_base: str) -> None:
+    for route in ("ocr", "transcription", "messages", "chat_completions"):
+        function: Final = getattr(native, route)
+        assert_success(route, function(**route_kwargs(route, api_base, "success")))
+        assert_traced_success(route, function(**route_kwargs(route, api_base, "success"), trace=True))
+        try:
+            function(**route_kwargs(route, api_base, "429"))
+        except (RuntimeError, native.RustUpstreamError) as error:
+            assert_rate_limit(native, route, error)
+        else:
+            raise AssertionError(f"{route} accepted a 429 response")
+
+
+async def exercise_async(native: object, api_base: str) -> None:
+    for route in ("ocr", "transcription", "messages", "chat_completions"):
+        function: Final = getattr(native, f"a{route}")
+        assert_success(route, await function(**route_kwargs(route, api_base, "success")))
+        assert_traced_success(route, await function(**route_kwargs(route, api_base, "success"), trace=True))
+        try:
+            await function(**route_kwargs(route, api_base, "429"))
+        except (RuntimeError, native.RustUpstreamError) as error:
+            assert_rate_limit(native, route, error)
+        else:
+            raise AssertionError(f"a{route} accepted a 429 response")
+
+
+async def exercise_async_concurrency(native: object, api_base: str) -> None:
+    responses: Final = await asyncio.wait_for(
+        asyncio.gather(
+            *(
+                native.amessages(**route_kwargs("messages", api_base, "success"))
+                for _ in range(32)
+            )
+        ),
+        timeout=15,
+    )
+    for response in responses:
+        assert_success("messages", response)
+
+
+def exercise_routes(native_path: Path, api_base: str) -> object:
+    native: Final = load_native(native_path)
+    exercise_sync(native, api_base)
+    asyncio.run(exercise_async(native, api_base))
+    asyncio.run(exercise_async_concurrency(native, api_base))
+    return native
+
+
+def exercise_signal(native: object, api_base: str) -> int:
+    try:
+        native.messages(
+            **route_kwargs("messages", api_base, "hang"),
+        )
+    except KeyboardInterrupt:
+        sys.stdout.write("KeyboardInterrupt\n")
+        sys.stdout.flush()
+        sys.stdin.read(1)
+        return 0
+    raise AssertionError("sync native route ignored SIGINT")
+
+
+def verify_sigint(native_path: Path, api_base: str) -> None:
+    REQUEST_STARTED.clear()
+    REQUEST_CANCELLED.clear()
+    process: Final = subprocess.Popen(
+        (sys.executable, __file__, "child", str(native_path), api_base),
+        stdin=subprocess.PIPE,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.PIPE,
+        text=True,
+    )
+    try:
+        if not REQUEST_STARTED.wait(30):
+            process.kill()
+            stdout, stderr = process.communicate(timeout=5)
+            raise AssertionError(
+                f"native route matrix did not reach the hanging upstream\nstdout:\n{stdout}\nstderr:\n{stderr}"
+            )
+        os.kill(process.pid, signal.SIGINT)
+        if not REQUEST_CANCELLED.wait(5):
+            raise AssertionError("interrupted native route did not cancel its upstream future")
+        if process.poll() is not None:
+            raise AssertionError("signal child exited before cancellation was observed")
+        stdout, stderr = process.communicate(input="\n", timeout=5)
+        if process.returncode != 0 or stdout != "KeyboardInterrupt\n":
+            raise AssertionError(
+                f"signal child exited with status {process.returncode}\nstdout:\n{stdout}\nstderr:\n{stderr}"
+            )
+    finally:
+        if process.poll() is None:
+            process.kill()
+            process.wait(timeout=5)
+
+
+def verify_wheel(wheel: Path) -> int:
+    with tempfile.TemporaryDirectory() as temporary_directory, zipfile.ZipFile(wheel) as archive:
+        wheel_root: Final = Path(temporary_directory)
+        for member in archive.infolist():
+            target: Final = wheel_root / member.filename
+            if member.is_dir():
+                target.mkdir(parents=True, exist_ok=True)
+            else:
+                target.parent.mkdir(parents=True, exist_ok=True)
+                target.write_bytes(archive.read(member))
+        native_members: Final = tuple(
+            member
+            for member in archive.infolist()
+            if member.filename.startswith("litellm/rust_bridge/_native.") and member.filename.endswith(".so")
+        )
+        if len(native_members) != 1:
+            raise AssertionError(f"expected one native extension, found {len(native_members)}")
+        native_path: Final = wheel_root / native_members[0].filename
+
+        server: Final = ThreadingHTTPServer(("127.0.0.1", 0), NativeRouteHandler)
+        server_thread: Final = threading.Thread(target=server.serve_forever, daemon=True)
+        server_thread.start()
+        api_base: Final = f"http://127.0.0.1:{server.server_address[1]}"
+        try:
+            verify_sigint(native_path, api_base)
+        finally:
+            server.shutdown()
+            server.server_close()
+            server_thread.join(timeout=5)
+    return 0
+
+
+def main() -> int:
+    if len(sys.argv) == 2:
+        return verify_wheel(Path(sys.argv[1]))
+    if len(sys.argv) == 4 and sys.argv[1] == "child":
+        native: Final = exercise_routes(Path(sys.argv[2]), sys.argv[3])
+        return exercise_signal(native, sys.argv[3])
+    sys.stderr.write(f"usage: {Path(sys.argv[0]).name} WHEEL\n")
+    return 2
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/tests/test_litellm/rust_bridge/test_bindings.py b/tests/test_litellm/rust_bridge/test_bindings.py
new file mode 100644
index 00000000000..88036a5a556
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/test_bindings.py
@@ -0,0 +1,35 @@
+from types import SimpleNamespace
+from typing import Final
+
+import pytest
+
+from litellm.rust_bridge import bindings
+
+
+def test_binding_distinguishes_disable_from_reset(monkeypatch) -> None:
+    native = SimpleNamespace(route=lambda: "native")
+    monkeypatch.setattr(bindings, "get_native_bridge", lambda: native)
+    binding: bindings.NativeBinding[object] = bindings.NativeBinding("route", validate=lambda value: value)
+
+    assert binding.load() is native.route
+
+    binding.override(None)
+    assert binding.load() is None
+
+    replacement = object()
+    binding.override(replacement)
+    assert binding.load() is replacement
+
+    binding.reset()
+    assert binding.load() is native.route
+
+
+@pytest.mark.parametrize(("value", "expected"), ((3, 3), ("invalid", None), (None, None)))
+def test_binding_validates_native_attribute(
+    monkeypatch: pytest.MonkeyPatch, value: object, expected: int | None
+) -> None:
+    native: Final = SimpleNamespace(route=value)
+    monkeypatch.setattr(bindings, "get_native_bridge", lambda: native)
+    binding: Final = bindings.NativeBinding("route", validate=lambda item: item if isinstance(item, int) else None)
+
+    assert binding.load() == expected
diff --git a/tests/test_litellm/rust_bridge/test_chat_completions.py b/tests/test_litellm/rust_bridge/test_chat_completions.py
index 47cb66932b7..03921133c77 100644
--- a/tests/test_litellm/rust_bridge/test_chat_completions.py
+++ b/tests/test_litellm/rust_bridge/test_chat_completions.py
@@ -11,6 +11,7 @@ import pytest
 
 import litellm
 from litellm.rust_bridge import chat_completions as bridge
+from litellm.rust_bridge import configuration
 from litellm.types.utils import ModelResponse
 
 RUST_RESPONSE = {
@@ -68,13 +69,11 @@ def _hide_native_bridge(monkeypatch):
 @pytest.fixture(autouse=True)
 def reset_bridge():
     """Every test starts with no injected callables, and leaves none behind."""
-    bridge.set_rust_chat_completions(
-        chat_completions=None, achat_completions=None, decline=None
-    )
+    bridge.set_rust_chat_completions(chat_completions=None, achat_completions=None, decline=None)
+    configuration.reset_rust_configuration()
     yield
-    bridge.set_rust_chat_completions(
-        chat_completions=None, achat_completions=None, decline=None
-    )
+    bridge.set_rust_chat_completions(chat_completions=None, achat_completions=None, decline=None)
+    configuration.reset_rust_configuration()
 
 
 class _RecordingDecline:
@@ -138,6 +137,18 @@ class TestGate:
         assert gate.calls[0]["model"] == "claude-sonnet-4-5"
         assert gate.calls[0]["custom_llm_provider"] == "anthropic"
 
+    def test_explicit_false_overrides_process_enable(self):
+        bridge.set_rust_chat_completions(decline=_RecordingDecline())
+        configuration.use_litellm_rust(True)
+
+        assert _accepts(litellm_params={"rust": False}) is False
+
+    def test_process_enable_applies_without_request_override(self):
+        bridge.set_rust_chat_completions(decline=_RecordingDecline())
+        configuration.use_litellm_rust(True)
+
+        assert _accepts(litellm_params={}) is True
+
     def test_the_env_var_opts_in_without_a_per_model_flag(self, monkeypatch):
         monkeypatch.setenv("LITELLM_RUST", "true")
         bridge.set_rust_chat_completions(decline=_RecordingDecline())
@@ -253,9 +264,7 @@ class TestSyncCall:
         assert result.usage.completion_tokens == 4
         assert result.usage.total_tokens == 15
         assert result._hidden_params["additional_headers"] == {"x-litellm-rust": "true"}
-        assert result.id == original_id, (
-            "the rust path must keep the chatcmpl id litellm already minted"
-        )
+        assert result.id == original_id, "the rust path must keep the chatcmpl id litellm already minted"
 
     def test_passes_the_timeout_through_as_seconds(self):
         native = _RecordingCall()
@@ -269,9 +278,7 @@ class TestSyncCall:
 
     def test_falls_back_when_the_core_declines_before_calling_the_provider(self, monkeypatch):
         _fake_native_bridge(monkeypatch)
-        bridge.set_rust_chat_completions(
-            chat_completions=_RecordingCall(error=_FakeDeclined("streaming"))
-        )
+        bridge.set_rust_chat_completions(chat_completions=_RecordingCall(error=_FakeDeclined("streaming")))
         assert bridge.chat_completions(**_call_kwargs(ModelResponse())) is None
 
 
@@ -290,13 +297,9 @@ class TestAsyncCall:
         assert await bridge.achat_completions(**_call_kwargs(ModelResponse())) is None
 
     @pytest.mark.asyncio
-    async def test_falls_back_when_the_core_declines_before_calling_the_provider(
-        self, monkeypatch
-    ):
+    async def test_falls_back_when_the_core_declines_before_calling_the_provider(self, monkeypatch):
         _fake_native_bridge(monkeypatch)
-        bridge.set_rust_chat_completions(
-            achat_completions=_RecordingAsyncCall(error=_FakeDeclined("streaming"))
-        )
+        bridge.set_rust_chat_completions(achat_completions=_RecordingAsyncCall(error=_FakeDeclined("streaming")))
         assert await bridge.achat_completions(**_call_kwargs(ModelResponse())) is None
 
 
@@ -310,25 +313,19 @@ class TestAsyncFallbackWrapper:
             ran.append(True)
             return "python"
 
-        result = await bridge.achat_completions_or_fallback(
-            **_call_kwargs(ModelResponse()), python_fallback=fallback
-        )
+        result = await bridge.achat_completions_or_fallback(**_call_kwargs(ModelResponse()), python_fallback=fallback)
         assert result.choices[0].message.content == "hello from rust"
         assert ran == []
 
     @pytest.mark.asyncio
     async def test_runs_the_fallback_when_the_core_declines(self, monkeypatch):
         _fake_native_bridge(monkeypatch)
-        bridge.set_rust_chat_completions(
-            achat_completions=_RecordingAsyncCall(error=_FakeDeclined("streaming"))
-        )
+        bridge.set_rust_chat_completions(achat_completions=_RecordingAsyncCall(error=_FakeDeclined("streaming")))
 
         async def fallback():
             return "python"
 
-        result = await bridge.achat_completions_or_fallback(
-            **_call_kwargs(ModelResponse()), python_fallback=fallback
-        )
+        result = await bridge.achat_completions_or_fallback(**_call_kwargs(ModelResponse()), python_fallback=fallback)
         assert result == "python"
 
     @pytest.mark.asyncio
@@ -338,9 +335,7 @@ class TestAsyncFallbackWrapper:
         async def fallback():
             return "python"
 
-        result = await bridge.achat_completions_or_fallback(
-            **_call_kwargs(ModelResponse()), python_fallback=fallback
-        )
+        result = await bridge.achat_completions_or_fallback(**_call_kwargs(ModelResponse()), python_fallback=fallback)
         assert result == "python"
 
 
@@ -353,17 +348,13 @@ class TestFailureClassification:
         _fake_native_bridge(monkeypatch)
 
     def test_a_decline_falls_back_because_nothing_was_sent(self):
-        bridge.set_rust_chat_completions(
-            chat_completions=_RecordingCall(error=_FakeDeclined("streaming"))
-        )
+        bridge.set_rust_chat_completions(chat_completions=_RecordingCall(error=_FakeDeclined("streaming")))
         assert bridge.chat_completions(**_call_kwargs(ModelResponse())) is None
 
     def test_an_upstream_failure_is_surfaced_with_its_status(self):
         from litellm.exceptions import APIError
 
-        bridge.set_rust_chat_completions(
-            chat_completions=_RecordingCall(error=_FakeUpstream(429, "429: rate limited"))
-        )
+        bridge.set_rust_chat_completions(chat_completions=_RecordingCall(error=_FakeUpstream(429, "429: rate limited")))
         with pytest.raises(APIError) as raised:
             bridge.chat_completions(**_call_kwargs(ModelResponse()))
         assert raised.value.status_code == 429
@@ -372,17 +363,13 @@ class TestFailureClassification:
     def test_a_transport_failure_with_no_response_surfaces_as_a_500(self):
         from litellm.exceptions import APIError
 
-        bridge.set_rust_chat_completions(
-            chat_completions=_RecordingCall(error=_FakeUpstream(0, "connection reset"))
-        )
+        bridge.set_rust_chat_completions(chat_completions=_RecordingCall(error=_FakeUpstream(0, "connection reset")))
         with pytest.raises(APIError) as raised:
             bridge.chat_completions(**_call_kwargs(ModelResponse()))
         assert raised.value.status_code == 500
 
     def test_an_unrecognized_error_is_not_swallowed(self):
-        bridge.set_rust_chat_completions(
-            chat_completions=_RecordingCall(error=RuntimeError("something else"))
-        )
+        bridge.set_rust_chat_completions(chat_completions=_RecordingCall(error=RuntimeError("something else")))
         with pytest.raises(RuntimeError):
             bridge.chat_completions(**_call_kwargs(ModelResponse()))
 
@@ -390,9 +377,7 @@ class TestFailureClassification:
     async def test_the_async_wrapper_does_not_fall_back_on_an_upstream_failure(self):
         from litellm.exceptions import APIError
 
-        bridge.set_rust_chat_completions(
-            achat_completions=_RecordingAsyncCall(error=_FakeUpstream(500, "500: boom"))
-        )
+        bridge.set_rust_chat_completions(achat_completions=_RecordingAsyncCall(error=_FakeUpstream(500, "500: boom")))
         ran = []
 
         async def fallback():
@@ -400,9 +385,7 @@ class TestFailureClassification:
             return "python"
 
         with pytest.raises(APIError):
-            await bridge.achat_completions_or_fallback(
-                **_call_kwargs(ModelResponse()), python_fallback=fallback
-            )
+            await bridge.achat_completions_or_fallback(**_call_kwargs(ModelResponse()), python_fallback=fallback)
         assert ran == [], "a request the provider already served must not be re-issued"
 
     @pytest.mark.asyncio
@@ -414,7 +397,5 @@ class TestFailureClassification:
         async def fallback():
             return "python"
 
-        result = await bridge.achat_completions_or_fallback(
-            **_call_kwargs(ModelResponse()), python_fallback=fallback
-        )
+        result = await bridge.achat_completions_or_fallback(**_call_kwargs(ModelResponse()), python_fallback=fallback)
         assert result == "python"
diff --git a/tests/test_litellm/rust_bridge/test_configuration.py b/tests/test_litellm/rust_bridge/test_configuration.py
new file mode 100644
index 00000000000..1c81c1fb624
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/test_configuration.py
@@ -0,0 +1,175 @@
+from __future__ import annotations
+
+import os
+import subprocess
+import sys
+from collections.abc import Generator
+from concurrent.futures import ThreadPoolExecutor
+from typing import Final
+
+import pytest
+
+from litellm.rust_bridge import configuration
+from litellm.rust_bridge import ocr as rust_ocr
+
+
+class _OcrBridge:
+    def __call__(
+        self,
+        model: str,
+        document: dict[str, object],
+        api_key: str | None,
+        api_base: str | None,
+        custom_llm_provider: str | None,
+        extra_headers: dict[str, object] | None,
+        optional_params: dict[str, object],
+        timeout_seconds: float | None,
+    ) -> dict[str, object]:
+        return {}
+
+
+@pytest.fixture(autouse=True)
+def _isolated_configuration(  # pyright: ignore[reportUnusedFunction]  # pytest discovers fixtures dynamically
+    monkeypatch: pytest.MonkeyPatch,
+) -> Generator[None]:
+    configuration.reset_rust_configuration()
+    monkeypatch.delenv("LITELLM_RUST", raising=False)
+    monkeypatch.delenv("LITELLM_USE_RUST_OCR", raising=False)
+    rust_ocr.set_rust_ocr(ocr=None, aocr=None)
+    yield
+    configuration.reset_rust_configuration()
+    rust_ocr.set_rust_ocr(ocr=None, aocr=None)
+
+
+@pytest.mark.parametrize(
+    ("request_override", "process", "environment", "legacy_ocr", "release_default", "expected"),
+    (
+        (False, True, True, True, True, False),
+        (True, False, False, False, False, True),
+        (None, False, True, True, True, False),
+        (None, True, False, False, False, True),
+        (None, None, False, True, True, False),
+        (None, None, True, False, False, True),
+        (None, None, None, False, True, False),
+        (None, None, None, True, False, True),
+        (None, None, None, None, False, False),
+        (None, None, None, None, True, True),
+    ),
+)
+def test_resolution_precedence(
+    request_override: bool | None,
+    process: bool | None,
+    environment: bool | None,
+    legacy_ocr: bool | None,
+    release_default: bool,
+    expected: bool,
+) -> None:
+    assert (
+        configuration.resolve_rust_enabled(
+            request_override=request_override,
+            process_override=process,
+            environment_override=environment,
+            legacy_ocr_override=legacy_ocr,
+            release_default=release_default,
+        )
+        is expected
+    )
+
+
+def test_release_default_remains_disabled() -> None:
+    assert configuration.DEFAULT_RUST_ENABLED is False
+    assert configuration.rust_enabled() is False
+
+
+def test_process_override_wins_over_environment(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_RUST", "0")
+    configuration.use_litellm_rust(True)
+
+    assert configuration.rust_enabled() is True
+    assert configuration.rust_enabled(request_override=False) is False
+
+
+def test_global_environment_accepts_explicit_false(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_RUST", "off")
+
+    assert configuration.rust_enabled() is False
+
+
+@pytest.mark.parametrize("value", ("", " ", "sometimes", "2"))
+def test_invalid_environment_value_disables_rust(monkeypatch: pytest.MonkeyPatch, value: str) -> None:
+    monkeypatch.setenv("LITELLM_RUST", value)
+    monkeypatch.setenv("LITELLM_USE_RUST_OCR", "1")
+
+    assert configuration.rust_enabled() is False
+    assert configuration.rust_ocr_enabled() is False
+
+
+@pytest.mark.parametrize("value", ("", " ", "sometimes", "2"))
+def test_invalid_legacy_environment_value_disables_ocr(monkeypatch: pytest.MonkeyPatch, value: str) -> None:
+    monkeypatch.setenv("LITELLM_USE_RUST_OCR", value)
+
+    with pytest.warns(DeprecationWarning, match="LITELLM_USE_RUST_OCR is deprecated"):
+        assert configuration.rust_ocr_enabled() is False
+
+
+def test_process_override_and_reset_apply_to_existing_threads(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_RUST", "1")
+
+    with ThreadPoolExecutor(max_workers=1) as executor:
+        assert executor.submit(configuration.rust_enabled).result() is True
+        configuration.use_litellm_rust(False)
+        assert executor.submit(configuration.rust_enabled).result() is False
+        assert executor.submit(configuration.rust_ocr_enabled).result() is False
+        configuration.reset_rust_configuration()
+        assert executor.submit(configuration.rust_enabled).result() is True
+        assert executor.submit(configuration.rust_ocr_enabled).result() is True
+
+
+def test_explicit_override_precedes_invalid_environment(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_RUST", "sometimes")
+
+    assert configuration.rust_enabled(request_override=False) is False
+    configuration.use_litellm_rust(True)
+    assert configuration.rust_enabled() is True
+
+
+def test_legacy_ocr_environment_is_deprecated_and_ocr_only(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_USE_RUST_OCR", "1")
+
+    with pytest.warns(DeprecationWarning, match="LITELLM_USE_RUST_OCR is deprecated"):
+        assert configuration.rust_ocr_enabled() is True
+    assert configuration.rust_enabled() is False
+
+
+def test_global_environment_precedes_legacy_ocr_environment(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_RUST", "0")
+    monkeypatch.setenv("LITELLM_USE_RUST_OCR", "1")
+
+    assert configuration.rust_ocr_enabled() is False
+
+
+def test_deprecated_public_injection_delegates_to_internal_binding() -> None:
+    bridge: Final = _OcrBridge()
+
+    with pytest.warns(DeprecationWarning, match="Injecting Rust bridge implementations"):
+        configuration.use_litellm_rust(True, ocr=bridge)
+
+    assert rust_ocr.load_rust_ocr() is bridge
+
+
+@pytest.mark.parametrize(("value", "expected"), (("1", "True"), ("0", "False")))
+def test_environment_controls_startup(value: str, expected: str) -> None:
+    environment: Final = {**os.environ, "LITELLM_RUST": value}
+    result: Final = subprocess.run(
+        (
+            sys.executable,
+            "-c",
+            "from litellm.rust_bridge.configuration import rust_enabled; print(rust_enabled())",
+        ),
+        check=True,
+        capture_output=True,
+        text=True,
+        env=environment,
+    )
+
+    assert result.stdout.strip() == expected
diff --git a/tests/test_litellm/rust_bridge/test_runtime.py b/tests/test_litellm/rust_bridge/test_runtime.py
new file mode 100644
index 00000000000..b0fa510069b
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/test_runtime.py
@@ -0,0 +1,95 @@
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+import pytest
+
+from litellm.exceptions import APIError
+from litellm.rust_bridge import bindings, runtime
+
+
+class RustBridgeDeclined(Exception):
+    pass
+
+
+class RustUpstreamError(Exception):
+    pass
+
+
+@pytest.fixture(autouse=True)
+def native_exceptions(monkeypatch: pytest.MonkeyPatch) -> None:
+    native = SimpleNamespace(
+        RustBridgeDeclined=RustBridgeDeclined,
+        RustUpstreamError=RustUpstreamError,
+    )
+    monkeypatch.setattr(bindings, "get_native_bridge", lambda: native)
+
+
+def context() -> runtime.BridgeErrorContext:
+    return runtime.BridgeErrorContext(route="messages", provider="anthropic", model="model")
+
+
+def test_invoke_tags_native_decline_before_running_fallback() -> None:
+    calls: list[str] = []
+
+    def decline() -> object:
+        calls.append("rust")
+        raise RustBridgeDeclined("unsupported")
+
+    value = runtime.invoke(
+        native_call=decline,
+        fallback=lambda: calls.append("python") or "fallback",
+        adapt=str,
+        mode=runtime.FallbackMode.PYTHON,
+        context=context(),
+    )
+
+    assert value == "fallback"
+    assert calls == ["rust", "python"]
+
+
+def test_invoke_translates_upstream_without_fallback() -> None:
+    def fail() -> object:
+        raise RustUpstreamError(429, "rate limited")
+
+    with pytest.raises(APIError, match="rate limited") as caught:
+        runtime.invoke(
+            native_call=fail,
+            fallback=lambda: pytest.fail("fallback must not run"),
+            adapt=str,
+            mode=runtime.FallbackMode.PYTHON,
+            context=context(),
+        )
+
+    assert caught.value.status_code == 429
+
+
+@pytest.mark.asyncio
+async def test_ainvoke_handles_native_success() -> None:
+    async def native() -> int:
+        return 3
+
+    async def fallback() -> str:
+        pytest.fail("fallback must not run")
+
+    assert (
+        await runtime.ainvoke(
+            native_call=native,
+            fallback=fallback,
+            adapt=str,
+            mode=runtime.FallbackMode.PYTHON,
+            context=context(),
+        )
+        == "3"
+    )
+
+
+def test_required_mode_rejects_unavailable_bridge() -> None:
+    with pytest.raises(RuntimeError, match="is unavailable"):
+        runtime.invoke(
+            native_call=None,
+            fallback=lambda: pytest.fail("fallback must not run"),
+            adapt=str,
+            mode=runtime.FallbackMode.RUST_REQUIRED,
+            context=context(),
+        )
diff --git a/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py b/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py
new file mode 100644
index 00000000000..e449d4392d8
--- /dev/null
+++ b/tests/test_litellm/rust_bridge/test_verify_linux_native_wheel.py
@@ -0,0 +1,197 @@
+from __future__ import annotations
+
+import importlib.util
+import subprocess
+import sys
+import zipfile
+from collections.abc import Callable, Mapping, Sequence
+from pathlib import Path
+from types import MappingProxyType, ModuleType
+from typing import Final, Protocol, cast
+
+import pytest
+
+
+class _CommandRunner(Protocol):
+    def __call__(
+        self,
+        command: tuple[str, ...],
+        *,
+        check: bool,
+        capture_output: bool,
+        text: bool,
+    ) -> subprocess.CompletedProcess[str]: ...
+
+
+class _VerifierModule(Protocol):
+    main: Callable[
+        [
+            Sequence[str] | None,
+            Mapping[str, str] | None,
+            Callable[[Path], ModuleType | None],
+            _CommandRunner,
+        ],
+        int,
+    ]
+
+
+_REPO_ROOT: Final = Path(__file__).resolve().parents[3]
+_MODULE_PATH: Final = _REPO_ROOT / ".github" / "scripts" / "verify_linux_native_wheel.py"
+_SPEC: Final = importlib.util.spec_from_file_location("verify_linux_native_wheel", _MODULE_PATH)
+assert _SPEC is not None and _SPEC.loader is not None
+_LOADED_VERIFIER: Final = importlib.util.module_from_spec(_SPEC)
+sys.modules[_SPEC.name] = _LOADED_VERIFIER
+_SPEC.loader.exec_module(_LOADED_VERIFIER)
+verifier: Final = cast(_VerifierModule, _LOADED_VERIFIER)
+
+_EXPECTED_TAG: Final = "cp310-abi3-linux_x86_64"
+_NATIVE_MEMBER: Final = "litellm/rust_bridge/_native.abi3.so"
+_DIST_INFO: Final = "litellm-1.100.0.dist-info"
+
+
+def _write_wheel(
+    tmp_path: Path,
+    *,
+    filename_tag: str,
+    metadata_tags: tuple[str, ...] | None = (_EXPECTED_TAG,),
+    dist_info: str = _DIST_INFO,
+    duplicate_wheel: bool = False,
+) -> Path:
+    wheel: Final = tmp_path / f"litellm-1.100.0-{filename_tag}.whl"
+    with zipfile.ZipFile(wheel, "w", compression=zipfile.ZIP_DEFLATED) as archive:
+        archive.writestr(_NATIVE_MEMBER, b"synthetic native extension")
+        archive.writestr(
+            f"{dist_info}/METADATA",
+            "Metadata-Version: 2.1\nName: litellm\nVersion: 1.100.0\n",
+        )
+        archive.writestr(
+            f"{dist_info}/RECORD",
+            f"{_NATIVE_MEMBER},,\n{dist_info}/WHEEL,,\n",
+        )
+        if metadata_tags is not None:
+            wheel_metadata: Final = (
+                "Wheel-Version: 1.0\nGenerator: regression-test\nRoot-Is-Purelib: false\n"
+                + "".join(f"Tag: {tag}\n" for tag in metadata_tags)
+            )
+            archive.writestr(f"{dist_info}/WHEEL", wheel_metadata)
+            if duplicate_wheel:
+                archive.writestr(f"{dist_info}/WHEEL", wheel_metadata)
+    return wheel
+
+
+def _fake_subprocess_run(
+    command: tuple[str, ...],
+    *,
+    check: bool,
+    capture_output: bool,
+    text: bool,
+) -> subprocess.CompletedProcess[str]:
+    assert check and capture_output and text
+    if command == ("rustc", "--version"):
+        return subprocess.CompletedProcess(command, 0, stdout="rustc 1.98.0 (regression-test)\n", stderr="")
+    if "--sections" in command:
+        return subprocess.CompletedProcess(command, 0, stdout="[ 1] .text PROGBITS\n", stderr="")
+    if "--dyn-syms" in command:
+        return subprocess.CompletedProcess(command, 0, stdout="PyInit__native\n", stderr="")
+    raise AssertionError(f"unexpected subprocess command: {command}")
+
+
+class _NativeModuleWithPanicHook(ModuleType):
+    def _panic_for_test(self) -> None:
+        return None
+
+
+def _run_verifier(
+    wheel: Path,
+    *,
+    exposes_panic: bool = False,
+) -> int:
+    native_module: Final = (
+        _NativeModuleWithPanicHook("litellm.rust_bridge._native")
+        if exposes_panic
+        else ModuleType("litellm.rust_bridge._native")
+    )
+
+    def _fake_load_native_module(_: Path) -> ModuleType:
+        return native_module
+
+    environment: Final = MappingProxyType({"GITHUB_STEP_SUMMARY": str(wheel.parent / "summary.md")})
+    return verifier.main(
+        (str(_MODULE_PATH), str(wheel)),
+        environment,
+        _fake_load_native_module,
+        _fake_subprocess_run,
+    )
+
+
+def test_accepts_expected_release_wheel_tags(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG)
+
+    assert _run_verifier(wheel) == 0
+
+
+def test_rejects_cp312_version_specific_wheel(tmp_path: Path) -> None:
+    tag: Final = "cp312-cp312-linux_x86_64"
+    wheel: Final = _write_wheel(tmp_path, filename_tag=tag, metadata_tags=(tag,))
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_non_linux_platform_tag(tmp_path: Path) -> None:
+    tag: Final = "cp310-abi3-win_amd64"
+    wheel: Final = _write_wheel(tmp_path, filename_tag=tag, metadata_tags=(tag,))
+
+    assert _run_verifier(wheel) == 1
+
+
+@pytest.mark.parametrize(
+    "metadata_tags",
+    (None, ("cp312-cp312-linux_x86_64",)),
+    ids=("missing", "mismatched"),
+)
+def test_rejects_missing_or_mismatched_wheel_metadata_tag(
+    tmp_path: Path,
+    metadata_tags: tuple[str, ...] | None,
+) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG, metadata_tags=metadata_tags)
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_wheel_metadata_from_wrong_dist_info_directory(
+    tmp_path: Path,
+) -> None:
+    wheel: Final = _write_wheel(
+        tmp_path,
+        filename_tag=_EXPECTED_TAG,
+        dist_info="decoy-1.0.0.dist-info",
+    )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_duplicate_wheel_metadata_tags(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(
+        tmp_path,
+        filename_tag=_EXPECTED_TAG,
+        metadata_tags=(_EXPECTED_TAG, _EXPECTED_TAG),
+    )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_duplicate_wheel_metadata_file(tmp_path: Path) -> None:
+    with pytest.warns(UserWarning, match="Duplicate name"):
+        wheel: Final = _write_wheel(
+            tmp_path,
+            filename_tag=_EXPECTED_TAG,
+            duplicate_wheel=True,
+        )
+
+    assert _run_verifier(wheel) == 1
+
+
+def test_rejects_production_module_exposing_panic_hook(tmp_path: Path) -> None:
+    wheel: Final = _write_wheel(tmp_path, filename_tag=_EXPECTED_TAG)
+
+    assert _run_verifier(wheel, exposes_panic=True) == 1
diff --git a/tests/test_litellm/test_bedrock_usgov_pricing.py b/tests/test_litellm/test_bedrock_usgov_pricing.py
index 6b3312b5cc4..f7d95ecda01 100644
--- a/tests/test_litellm/test_bedrock_usgov_pricing.py
+++ b/tests/test_litellm/test_bedrock_usgov_pricing.py
@@ -26,9 +26,7 @@ import pytest
 
 @pytest.fixture(scope="module")
 def model_data():
-    json_path = os.path.join(
-        os.path.dirname(__file__), "../../model_prices_and_context_window.json"
-    )
+    json_path = os.path.join(os.path.dirname(__file__), "../../model_prices_and_context_window.json")
     with open(json_path) as f:
         return json.load(f)
 
@@ -51,21 +49,14 @@ def test_usgov_sonnet_4_5_pricing(model_data, model_key):
     info = model_data[model_key]
 
     assert info["input_cost_per_token"] == 3.6e-06, (
-        f"{model_key}: input_cost_per_token should be $3.60/MTok "
-        f"(got {info['input_cost_per_token']})"
+        f"{model_key}: input_cost_per_token should be $3.60/MTok (got {info['input_cost_per_token']})"
     )
-    assert (
-        info["output_cost_per_token"] == 1.8e-05
-    ), f"{model_key}: output_cost_per_token should be $18.00/MTok"
-    assert (
-        info["cache_creation_input_token_cost"] == 4.5e-06
-    ), f"{model_key}: 5m cache write should be $4.50/MTok"
-    assert (
-        info["cache_creation_input_token_cost_above_1hr"] == 7.2e-06
-    ), f"{model_key}: 1h cache write should be $7.20/MTok"
-    assert (
-        info["cache_read_input_token_cost"] == 3.6e-07
-    ), f"{model_key}: cache read should be $0.36/MTok"
+    assert info["output_cost_per_token"] == 1.8e-05, f"{model_key}: output_cost_per_token should be $18.00/MTok"
+    assert info["cache_creation_input_token_cost"] == 4.5e-06, f"{model_key}: 5m cache write should be $4.50/MTok"
+    assert info["cache_creation_input_token_cost_above_1hr"] == 7.2e-06, (
+        f"{model_key}: 1h cache write should be $7.20/MTok"
+    )
+    assert info["cache_read_input_token_cost"] == 3.6e-07, f"{model_key}: cache read should be $0.36/MTok"
 
 
 def test_usgov_carries_20_percent_premium_over_global(model_data):
@@ -84,9 +75,7 @@ def test_usgov_carries_20_percent_premium_over_global(model_data):
         "cache_read_input_token_cost",
     ):
         ratio = usgov_info[field] / global_info[field]
-        assert (
-            abs(ratio - 1.2) < 1e-9
-        ), f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+        assert abs(ratio - 1.2) < 1e-9, f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
 
 
 # The us-gov.anthropic.* cross-region inference profile is the only us-gov
@@ -112,9 +101,7 @@ def test_usgov_cross_region_above_200k_carries_gov_premium(model_data, field, ex
     """
     info = model_data[USGOV_CROSS_REGION_KEY]
     assert field in info, f"{USGOV_CROSS_REGION_KEY}: missing field {field}"
-    assert (
-        info[field] == expected
-    ), f"{USGOV_CROSS_REGION_KEY}: {field} should be {expected} (got {info[field]})"
+    assert info[field] == expected, f"{USGOV_CROSS_REGION_KEY}: {field} should be {expected} (got {info[field]})"
 
 
 def test_usgov_cross_region_above_200k_ratio_to_global(model_data):
@@ -127,6 +114,176 @@ def test_usgov_cross_region_above_200k_ratio_to_global(model_data):
     usgov_info = model_data[USGOV_CROSS_REGION_KEY]
     for field in EXPECTED_USGOV_ABOVE_200K:
         ratio = usgov_info[field] / global_info[field]
-        assert (
-            abs(ratio - 1.2) < 1e-9
-        ), f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+        assert abs(ratio - 1.2) < 1e-9, f"{field}: us-gov / global ratio is {ratio}, expected 1.2"
+
+
+CLAUDE_GOV_EXPECTED = {
+    "anthropic.claude-sonnet-5": {
+        "input_cost_per_token": 2.4e-06,
+        "output_cost_per_token": 1.2e-05,
+        "cache_creation_input_token_cost": 3e-06,
+        "cache_creation_input_token_cost_above_1hr": 4.8e-06,
+        "cache_read_input_token_cost": 2.4e-07,
+    },
+    "anthropic.claude-opus-4-8": {
+        "input_cost_per_token": 6e-06,
+        "output_cost_per_token": 3e-05,
+        "cache_creation_input_token_cost": 7.5e-06,
+        "cache_creation_input_token_cost_above_1hr": 1.2e-05,
+        "cache_read_input_token_cost": 6e-07,
+    },
+}
+
+
+USGOV_CLAUDE_KEY_TEMPLATES = {
+    "bedrock/us-gov-east-1/{base_key}": "bedrock",
+    "bedrock/us-gov-west-1/{base_key}": "bedrock",
+    "us-gov.{base_key}": "bedrock_converse",
+}
+
+
+@pytest.mark.parametrize("base_key", CLAUDE_GOV_EXPECTED)
+@pytest.mark.parametrize("key_template,expected_provider", USGOV_CLAUDE_KEY_TEMPLATES.items())
+def test_usgov_claude_sonnet5_opus48_pricing(model_data, key_template, expected_provider, base_key):
+    """Sonnet 5 and Opus 4.8 gov entries, both in-region keys and the us-gov.
+    geo inference profile the model cards list for GovCloud, must match the
+    rates AWS publishes on the Bedrock pricing page (1.2x global).
+    """
+    gov_key = key_template.format(base_key=base_key)
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    assert info["litellm_provider"] == expected_provider
+    for field, expected in CLAUDE_GOV_EXPECTED[base_key].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+        ratio = info[field] / model_data[base_key][field]
+        assert abs(ratio - 1.2) < 1e-9, f"{gov_key}: {field} gov/global ratio is {ratio}, expected 1.2"
+
+
+CONVERSE_GOV_EXPECTED = {
+    "nvidia.nemotron-nano-3-30b": (7.2e-08, 2.88e-07),
+    "nvidia.nemotron-nano-12b-v2": (2.4e-07, 7.2e-07),
+    "nvidia.nemotron-super-3-120b": (1.8e-07, 7.8e-07),
+    "openai.gpt-oss-20b-1:0": (8.4e-08, 3.6e-07),
+    "openai.gpt-oss-120b-1:0": (1.8e-07, 7.2e-07),
+}
+
+
+@pytest.mark.parametrize("base_key", CONVERSE_GOV_EXPECTED)
+@pytest.mark.parametrize("region", ["us-gov-east-1", "us-gov-west-1"])
+def test_usgov_converse_model_pricing(model_data, region, base_key):
+    """Nemotron and gpt-oss gov entries must match the AWS Bedrock offer file,
+    which prices both GovCloud regions identically at 1.2x commercial.
+    """
+    gov_key = f"bedrock/{region}/{base_key}"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    expected_input, expected_output = CONVERSE_GOV_EXPECTED[base_key]
+    assert info["input_cost_per_token"] == expected_input
+    assert info["output_cost_per_token"] == expected_output
+    assert info["litellm_provider"] == "bedrock"
+    base = model_data[base_key]
+    assert abs(info["input_cost_per_token"] / base["input_cost_per_token"] - 1.2) < 1e-9
+    assert abs(info["output_cost_per_token"] / base["output_cost_per_token"] - 1.2) < 1e-9
+
+
+def test_usgov_west_llama3_8b_output_price_fixed(model_data):
+    """The us-gov-west-1 llama3-8b entry carried the 70B output rate ($2.65/MTok);
+    the AWS Bedrock offer file prices output at $0.60/MTok. AWS lists the model
+    in us-gov-west-1 only, so there is no east entry to check.
+    """
+    info = model_data["bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0"]
+    assert info["input_cost_per_token"] == 3e-07
+    assert info["output_cost_per_token"] == 6e-07
+
+
+MANTLE_GOV_TIERED_EXPECTED = {
+    "openai.gpt-5.6-luna": {
+        "input_cost_per_token": 2.64e-07,
+        "input_cost_per_token_above_272k_tokens": 5.28e-07,
+        "cache_creation_input_token_cost": 3.3e-07,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07,
+        "cache_read_input_token_cost": 2.64e-08,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-08,
+        "output_cost_per_token": 1.584e-06,
+        "output_cost_per_token_above_272k_tokens": 2.376e-06,
+    },
+    "openai.gpt-5.6-terra": {
+        "input_cost_per_token": 2.64e-06,
+        "input_cost_per_token_above_272k_tokens": 5.28e-06,
+        "cache_creation_input_token_cost": 3.3e-06,
+        "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06,
+        "cache_read_input_token_cost": 2.64e-07,
+        "cache_read_input_token_cost_above_272k_tokens": 5.28e-07,
+        "output_cost_per_token": 1.584e-05,
+        "output_cost_per_token_above_272k_tokens": 2.376e-05,
+    },
+}
+
+
+@pytest.mark.parametrize("model", MANTLE_GOV_TIERED_EXPECTED)
+def test_usgov_west_mantle_terra_luna_pricing(model_data, model):
+    """Terra and Luna carry 1.2x commercial across every tier in the
+    us-gov-west-1 offer file; the us-gov-east-1 offer file has no SKUs for them.
+    """
+    gov_key = f"bedrock_mantle/us-gov-west-1/{model}"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    for field, expected in MANTLE_GOV_TIERED_EXPECTED[model].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+    assert info["litellm_provider"] == "bedrock_mantle"
+    assert f"bedrock_mantle/us-gov-east-1/{model}" not in model_data
+
+
+@pytest.mark.parametrize("region", ["us-gov-east-1", "us-gov-west-1"])
+def test_usgov_mantle_gpt_5_4_pricing_has_no_long_context_tier(model_data, region):
+    """gpt-5.4 gov rates come from the offer file, which publishes only the
+    standard tier in GovCloud: no long-context SKUs exist there, unlike commercial.
+    """
+    gov_key = f"bedrock_mantle/{region}/openai.gpt-5.4"
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    assert info["input_cost_per_token"] == 3.3e-06
+    assert info["cache_read_input_token_cost"] == 3.3e-07
+    assert info["output_cost_per_token"] == 1.98e-05
+    assert not any(field.endswith("_above_272k_tokens") for field in info)
+
+
+def test_usgov_mantle_grok_4_3_west_only(model_data):
+    """grok-4.3 is priced in the us-gov-west-1 offer file only; the east offer
+    file carries grok-4.6 instead.
+    """
+    info = model_data["bedrock_mantle/us-gov-west-1/xai.grok-4.3"]
+    assert info["input_cost_per_token"] == 1.5e-06
+    assert info["output_cost_per_token"] == 3e-06
+    assert info["cache_read_input_token_cost"] == 2.4e-07
+    assert "bedrock_mantle/us-gov-east-1/xai.grok-4.3" not in model_data
+
+
+AZURE_GOV_EXPECTED = {
+    "azure/us-gov/gpt-5.1": {
+        "input_cost_per_token": 1.71875e-06,
+        "cache_read_input_token_cost": 1.71875e-07,
+        "output_cost_per_token": 1.375e-05,
+    },
+    "azure/us-gov/o3-mini": {
+        "input_cost_per_token": 1.513e-06,
+        "cache_read_input_token_cost": 7.57e-07,
+        "output_cost_per_token": 6.05e-06,
+    },
+    "azure/us-gov/text-embedding-3-large": {"input_cost_per_token": 1.63e-07},
+    "azure/us-gov/text-embedding-3-small": {"input_cost_per_token": 2.5e-08},
+}
+
+
+@pytest.mark.parametrize("gov_key", AZURE_GOV_EXPECTED)
+def test_azure_usgov_pricing(model_data, gov_key):
+    """Azure Government meters from the Azure retail prices API
+    (usgovvirginia/usgovarizona, serviceName 'Foundry Models'). No Government
+    retirement schedule is published, so these entries carry no deprecation_date.
+    """
+    assert gov_key in model_data, f"Missing model entry: {gov_key}"
+    info = model_data[gov_key]
+    for field, expected in AZURE_GOV_EXPECTED[gov_key].items():
+        assert info[field] == expected, f"{gov_key}: {field} should be {expected} (got {info[field]})"
+    assert info["litellm_provider"] == "azure"
+    assert "deprecation_date" not in info
diff --git a/tests/test_litellm/test_circleci_rust_toolchain.py b/tests/test_litellm/test_circleci_rust_toolchain.py
index c35ced51e16..800ca21b95d 100644
--- a/tests/test_litellm/test_circleci_rust_toolchain.py
+++ b/tests/test_litellm/test_circleci_rust_toolchain.py
@@ -17,28 +17,27 @@ Two invariants are pinned here:
      Windows job, so the check accepts either. A new job that syncs without one
      falls back to the unpinned path, which is exactly the regression a static
      check catches at PR time and a green CI run does not.
-  2. `install_rust` itself pins what it downloads: an explicit rustup version in
-     the URL, a verified SHA-256, and an exact toolchain version rather than a
-     channel name.
-
-The Windows job predates `install_rust` and provisions its toolchain inline, so
-invariant 2 is scoped to `install_rust`; invariant 1 covers both.
+  2. Both installers pin what they download: an explicit rustup version, a
+     verified SHA-256, and the exact toolchain in `rust-toolchain.toml`.
 """
 
 from __future__ import annotations
 
 import re
 from pathlib import Path
+from typing import Final
 
 import pytest
 import yaml
 
 REPO_ROOT = Path(__file__).resolve().parents[2]
 CONFIG = REPO_ROOT / ".circleci" / "config.yml"
+TOOLCHAIN: Final = REPO_ROOT / "rust-toolchain.toml"
 
 BUILDS_WORKSPACE = re.compile(r"\buv\s+(?:sync|build)\b")
 RUSTUP_ARCHIVE_URL = re.compile(r"https://static\.rust-lang\.org/rustup/archive/\d+\.\d+\.\d+/")
-EXACT_TOOLCHAIN = re.compile(r"--default-toolchain\s+\"?\d+\.\d+\.\d+\"?")
+EXACT_TOOLCHAIN = re.compile(r"--default-toolchain\s+\"?(\d+\.\d+\.\d+)\"?")
+TOOLCHAIN_CHANNEL: Final = re.compile(r'^channel = "(\d+\.\d+\.\d+)"$', re.MULTILINE)
 
 
 def _config() -> dict[str, object]:
@@ -57,6 +56,12 @@ def _step_text(step: object) -> str:
     return ""
 
 
+def _pinned_toolchain() -> str:
+    match: Final = TOOLCHAIN_CHANNEL.search(TOOLCHAIN.read_text())
+    assert match is not None, "rust-toolchain.toml must pin an exact channel"
+    return match.group(1)
+
+
 def _without_comments(text: str) -> str:
     return "\n".join(line for line in text.splitlines() if not line.lstrip().startswith("#"))
 
@@ -142,7 +147,17 @@ def test_install_rust_verifies_the_installer_checksum(install_rust_command: str)
 
 
 def test_install_rust_pins_an_exact_toolchain_version(install_rust_command: str) -> None:
-    assert EXACT_TOOLCHAIN.search(install_rust_command), (
-        "install_rust must pin an exact toolchain version (e.g. 1.97.1); a channel name like "
+    match: Final = EXACT_TOOLCHAIN.search(install_rust_command)
+    assert match is not None, (
+        "install_rust must pin an exact toolchain version (e.g. 1.98.0); a channel name like "
         "stable/beta/nightly makes the compiler drift with whatever upstream published that day"
     )
+    assert match.group(1) == _pinned_toolchain()
+
+
+def test_windows_installer_matches_the_repo_toolchain() -> None:
+    windows_steps: Final = _step_lists()["job using_litellm_on_windows"]
+    windows_command: Final = "\n".join(_step_text(step) for step in windows_steps)
+    match: Final = EXACT_TOOLCHAIN.search(windows_command)
+    assert match is not None
+    assert match.group(1) == _pinned_toolchain()
diff --git a/tests/test_litellm/test_claude_fable_5_config.py b/tests/test_litellm/test_claude_fable_5_config.py
index 99c59ffa58e..3ecf94602d9 100644
--- a/tests/test_litellm/test_claude_fable_5_config.py
+++ b/tests/test_litellm/test_claude_fable_5_config.py
@@ -1,5 +1,5 @@
 """
-Validate Claude Fable 5 model configuration entries.
+Validate Claude Fable 5 and Claude Fable 5.1 model configuration entries.
 
 Fable 5 is a new tier above Opus ($10/$50 per MTok) with the same adaptive-only
 API surface as Opus 4.7/4.8. The cost-map entries below are what make the model
@@ -210,6 +210,156 @@ def test_adaptive_thinking_detected_for_fable_5(local_model_cost_map, model):
     assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
 
 
+FABLE_5_1_VARIANTS = (
+    "claude-fable-5-1",
+    "anthropic.claude-fable-5-1",
+    "global.anthropic.claude-fable-5-1",
+    "us.anthropic.claude-fable-5-1",
+    "eu.anthropic.claude-fable-5-1",
+    "vertex_ai/claude-fable-5-1",
+    "vertex_ai/claude-fable-5-1@default",
+    "azure_ai/claude-fable-5-1",
+)
+
+
+def test_fable_5_1_model_pricing_and_capabilities():
+    model_data = _load_root_cost_map()
+
+    expected_models = [
+        ("claude-fable-5-1", "anthropic"),
+        ("anthropic.claude-fable-5-1", "bedrock_converse"),
+        ("vertex_ai/claude-fable-5-1", "vertex_ai-anthropic_models"),
+        ("azure_ai/claude-fable-5-1", "azure_ai"),
+    ]
+
+    for model_name, provider in expected_models:
+        assert model_name in model_data, f"Missing model entry: {model_name}"
+        info = model_data[model_name]
+
+        assert info["litellm_provider"] == provider
+        assert info["mode"] == "chat"
+        assert info["max_input_tokens"] == 1000000
+        assert info["max_output_tokens"] == 128000
+        assert info["max_tokens"] == 128000
+
+        assert info["input_cost_per_token"] == 1e-05
+        assert info["output_cost_per_token"] == 5e-05
+        assert info["cache_creation_input_token_cost"] == 1.25e-05
+        assert info["cache_creation_input_token_cost_above_1hr"] == 2e-05
+
+        assert "input_cost_per_token_above_200k_tokens" not in info
+        assert "output_cost_per_token_above_200k_tokens" not in info
+
+        assert info["supports_assistant_prefill"] is False
+        assert info["supports_forced_tool_use"] is False
+        assert info["supports_function_calling"] is True
+        assert info["supports_prompt_caching"] is True
+        assert info["supports_reasoning"] is True
+        assert info["supports_tool_choice"] is True
+        assert info["supports_vision"] is True
+        assert info["supports_xhigh_reasoning_effort"] is True
+        assert info["supports_max_reasoning_effort"] is True
+        assert info["prompt_cache_min_tokens"] == 512
+
+
+@pytest.mark.parametrize(
+    "cost_map",
+    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
+    ids=["root", "bundled_backup"],
+)
+def test_fable_5_1_cache_reads_cost_a_quarter_of_fable_5(cost_map):
+    """Fable 5.1 prices cache hits at 0.025x base input instead of the usual
+    0.1x, so copying Fable 5's cache-read price overcharges every cache hit 4x."""
+    for model_name in FABLE_5_1_VARIANTS:
+        info = cost_map[model_name]
+        geo_premium = model_name.startswith(("us.", "eu."))
+        expected = 2.75e-07 if geo_premium else 2.5e-07
+        assert info["cache_read_input_token_cost"] == expected, model_name
+        assert info["cache_read_input_token_cost"] == pytest.approx(
+            info["input_cost_per_token"] * 0.025
+        ), model_name
+
+
+def test_fable_5_1_bedrock_regional_model_pricing():
+    model_data = _load_root_cost_map()
+
+    expected_models = {
+        "global.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1e-05,
+            "output_cost_per_token": 5e-05,
+            "cache_creation_input_token_cost": 1.25e-05,
+            "cache_read_input_token_cost": 2.5e-07,
+        },
+        "us.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1.1e-05,
+            "output_cost_per_token": 5.5e-05,
+            "cache_creation_input_token_cost": 1.375e-05,
+            "cache_read_input_token_cost": 2.75e-07,
+        },
+        "eu.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1.1e-05,
+            "output_cost_per_token": 5.5e-05,
+            "cache_creation_input_token_cost": 1.375e-05,
+            "cache_read_input_token_cost": 2.75e-07,
+        },
+    }
+
+    for model_name, expected in expected_models.items():
+        assert model_name in model_data, f"Missing model entry: {model_name}"
+        info = model_data[model_name]
+        assert info["litellm_provider"] == "bedrock_converse"
+        assert info["max_input_tokens"] == 1000000
+        assert info["max_output_tokens"] == 128000
+        assert info["bedrock_output_config_effort_ceiling"] == "xhigh"
+        for key, value in expected.items():
+            assert info[key] == value
+
+
+def test_fable_5_1_geo_multiplier_without_fast_mode():
+    """Fable 5.1 has no fast mode, so a ``fast`` key here would misprice
+    ``speed='fast'`` requests."""
+    model_data = _load_root_cost_map()
+    assert model_data["claude-fable-5-1"]["provider_specific_entry"] == {"us": 1.1}
+
+
+def test_fable_5_1_present_in_bundled_backup():
+    backup = GetModelCostMap.load_local_model_cost_map()
+    root = _load_root_cost_map()
+    for model_name in FABLE_5_1_VARIANTS:
+        assert model_name in backup, f"Missing from backup cost map: {model_name}"
+        assert backup[model_name] == root[model_name], model_name
+
+
+def test_fable_5_1_registered_for_bedrock_converse():
+    assert "anthropic.claude-fable-5-1" in BEDROCK_CONVERSE_MODELS
+
+
+def test_fable_5_1_provider_resolves_via_model_info(local_model_cost_map):
+    info = litellm.get_model_info(model="claude-fable-5-1")
+    assert info["litellm_provider"] == "anthropic"
+    assert info["max_input_tokens"] == 1000000
+    assert info["max_output_tokens"] == 128000
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "claude-fable-5-1",
+        "anthropic/claude-fable-5-1",
+        "anthropic.claude-fable-5-1",
+        "bedrock/us.anthropic.claude-fable-5-1",
+        "bedrock/invoke/eu.anthropic.claude-fable-5-1",
+        "bedrock/global.anthropic.claude-fable-5-1",
+        "vertex_ai/claude-fable-5-1",
+        "azure_ai/claude-fable-5-1",
+    ],
+)
+def test_adaptive_thinking_detected_for_fable_5_1(local_model_cost_map, model):
+    from litellm.llms.anthropic.common_utils import AnthropicModelInfo
+
+    assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
+
+
 @pytest.mark.parametrize(
     "cost_map",
     [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
diff --git a/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py b/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
index 9ca4515239a..e33bcfb8378 100644
--- a/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
+++ b/tests/test_litellm/test_cloudflare_workers_ai_model_metadata.py
@@ -75,6 +75,22 @@ def test_additional_current_models_are_present():
         assert entry["output_cost_per_token"] > 0
 
 
+@pytest.mark.parametrize(
+    "key, published_price_per_audio_minute",
+    [
+        ("cloudflare/@cf/openai/whisper", 0.00045),
+        ("cloudflare/@cf/openai/whisper-large-v3-turbo", 0.00051),
+    ],
+)
+def test_whisper_transcription_pricing_is_stored_per_second(key, published_price_per_audio_minute):
+    entry = litellm.model_cost[key]
+    assert entry["litellm_provider"] == "cloudflare"
+    assert entry["mode"] == "audio_transcription"
+    assert entry["supported_endpoints"] == ["/v1/audio/transcriptions"]
+    assert entry["output_cost_per_second"] == 0.0
+    assert entry["input_cost_per_second"] == pytest.approx(published_price_per_audio_minute / 60)
+
+
 def test_root_and_backup_have_identical_cloudflare_keys():
     if not os.path.exists(ROOT_MAP):
         pytest.skip("root cost map only ships in source checkouts")
diff --git a/tests/test_litellm/test_dockerfile_apk_repository.py b/tests/test_litellm/test_dockerfile_apk_repository.py
new file mode 100644
index 00000000000..cbd772defbf
--- /dev/null
+++ b/tests/test_litellm/test_dockerfile_apk_repository.py
@@ -0,0 +1,52 @@
+"""
+Static checks on the root Dockerfile's apk repository configuration.
+
+The base image (cgr.dev/chainguard/wolfi-base) only configures the
+authenticated Chainguard apk repo (https://apk.cgr.dev/chainguard) in
+/etc/apk/repositories, which requires a Chainguard enterprise subscription.
+Anyone pulling the published litellm image and running `apk add` inside it
+hits SSL/auth failures with no fallback repo configured, so nothing can be
+installed. See https://github.com/BerriAI/litellm/issues/33518
+"""
+
+import os
+import re
+
+import pytest
+
+DOCKERFILE_PATH = os.path.join(
+    os.path.dirname(__file__),
+    "..",
+    "..",
+    "Dockerfile",
+)
+
+
+def _runtime_stage(dockerfile_text: str) -> str:
+    """Return the contents of the final `FROM ... AS runtime` build stage."""
+    match = re.search(r"^FROM .*\bAS runtime\b(.*)\Z", dockerfile_text, re.MULTILINE | re.DOTALL)
+    assert match, "Dockerfile has no `FROM ... AS runtime` stage"
+    return match.group(1)
+
+
+@pytest.mark.skipif(
+    not os.path.exists(DOCKERFILE_PATH),
+    reason="Dockerfile not present in this checkout",
+)
+def test_runtime_stage_adds_public_wolfi_repo():
+    """The runtime stage must add the public Wolfi apk repo so `apk add`
+    works for users without a Chainguard enterprise subscription."""
+    with open(DOCKERFILE_PATH, "r", encoding="utf-8") as f:
+        contents = f.read()
+
+    runtime_stage = _runtime_stage(contents)
+
+    assert re.search(
+        r"echo\s+[\"']?https://packages\.wolfi\.dev/os[\"']?\s*>>\s*/etc/apk/repositories",
+        runtime_stage,
+    ), (
+        "Runtime stage must append the public Wolfi apk repo "
+        '(RUN echo "https://packages.wolfi.dev/os" >> /etc/apk/repositories) '
+        "so `apk add` works without Chainguard enterprise credentials. "
+        "See https://github.com/BerriAI/litellm/issues/33518"
+    )
diff --git a/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py
new file mode 100644
index 00000000000..44572aed08e
--- /dev/null
+++ b/tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py
@@ -0,0 +1,56 @@
+"""
+Static checks that every proxy Docker image installs the `bedrock-realtime` extra.
+
+Bedrock Nova Sonic speech-to-speech (`/v1/realtime`) needs `aws-sdk-bedrock-runtime`,
+which only ships in the `bedrock-realtime` extra. An image whose `uv sync` stages
+omit the extra fails every Nova Sonic realtime session with
+"Missing aws_sdk_bedrock_runtime. Install with: pip install aws-sdk-bedrock-runtime".
+"""
+
+import os
+import re
+from typing import Final
+
+import pytest
+
+REPO_ROOT: Final = os.path.join(os.path.dirname(__file__), "..", "..")
+
+PROXY_DOCKERFILES: Final = (
+    "Dockerfile",
+    os.path.join("docker", "Dockerfile.non_root"),
+    os.path.join("docker", "Dockerfile.database"),
+    os.path.join("gateway", "Dockerfile"),
+)
+
+CONTINUED_LINE_RE: Final = re.compile(r"(?:\\\n|[^\n])+")
+UV_SYNC_BOUNDARY_RE: Final = re.compile(r"(?=uv sync)")
+
+
+def _uv_sync_invocations(dockerfile_text: str) -> tuple[str, ...]:
+    """Return each `uv sync ...` command, split apart when one RUN holds several (if/else branches)."""
+    return tuple(
+        part
+        for line in CONTINUED_LINE_RE.finditer(dockerfile_text)
+        for part in UV_SYNC_BOUNDARY_RE.split(line.group(0))
+        if part.startswith("uv sync")
+    )
+
+
+@pytest.mark.parametrize("relative_path", PROXY_DOCKERFILES)
+def test_every_uv_sync_installs_bedrock_realtime_extra(relative_path: str):
+    dockerfile_path: Final = os.path.join(REPO_ROOT, relative_path)
+    if not os.path.exists(dockerfile_path):
+        pytest.skip(f"{relative_path} not present in this checkout")
+
+    with open(dockerfile_path, "r", encoding="utf-8") as f:
+        contents: Final = f.read()
+
+    invocations: Final = _uv_sync_invocations(contents)
+    assert invocations, f"{relative_path} has no `uv sync` invocation"
+
+    missing: Final = tuple(invocation for invocation in invocations if "--extra bedrock-realtime" not in invocation)
+    assert not missing, (
+        f"{relative_path}: {len(missing)} of {len(invocations)} `uv sync` invocations omit "
+        "`--extra bedrock-realtime`, so aws-sdk-bedrock-runtime is absent and Bedrock Nova Sonic "
+        "/v1/realtime sessions fail with 'Missing aws_sdk_bedrock_runtime'"
+    )
diff --git a/tests/test_litellm/test_fireworks_serverless_model_costs.py b/tests/test_litellm/test_fireworks_serverless_model_costs.py
index 0458af0da0e..a7a9e0fc37d 100644
--- a/tests/test_litellm/test_fireworks_serverless_model_costs.py
+++ b/tests/test_litellm/test_fireworks_serverless_model_costs.py
@@ -84,3 +84,41 @@ def test_bare_fireworks_ids_resolve_through_prefixed_entries():
         assert info["output_cost_per_token"] == pytest.approx(expected["output_cost_per_token"])
         assert info["max_input_tokens"] == expected["max_input_tokens"]
         assert info["max_output_tokens"] == expected["max_output_tokens"]
+
+
+TWIN_PINNED_PRICES = {
+    "deepseek-v4-flash-0731": {
+        "input_cost_per_token": 2.2e-07,
+        "cache_read_input_token_cost": 7e-09,
+        "output_cost_per_token": 6.6e-07,
+    },
+}
+
+
+def test_deepseek_v4_flash_0731_twins_pin_published_pricing(model_data):
+    """Both 0731 entries carry the price published at docs.fireworks.ai/serverless/pricing."""
+    for bare_suffix, expected in TWIN_PINNED_PRICES.items():
+        for key in (
+            f"fireworks_ai/{bare_suffix}",
+            f"fireworks_ai/accounts/fireworks/models/{bare_suffix}",
+        ):
+            entry = model_data[key]
+            for field, value in expected.items():
+                assert entry[field] == pytest.approx(value), f"{key}.{field}"
+
+
+def test_fireworks_account_prefixed_twins_agree_on_price(model_data):
+    """Every accounts/fireworks/models/X entry prices identically to its bare fireworks_ai/X twin."""
+    prefix = "fireworks_ai/accounts/fireworks/models/"
+    pairs_checked = 0
+    for key, entry in model_data.items():
+        if not key.startswith(prefix):
+            continue
+        bare_key = f"fireworks_ai/{key[len(prefix):]}"
+        bare_entry = model_data.get(bare_key)
+        if bare_entry is None:
+            continue
+        pairs_checked += 1
+        for field in sorted({f for f in (*entry, *bare_entry) if "cost" in f}):
+            assert entry.get(field) == bare_entry.get(field), f"{key} vs {bare_key}: {field}"
+    assert pairs_checked >= 20
diff --git a/tests/test_litellm/test_friendli_glm_5_3_flash_model_metadata.py b/tests/test_litellm/test_friendli_glm_5_3_flash_model_metadata.py
new file mode 100644
index 00000000000..7e94205fb09
--- /dev/null
+++ b/tests/test_litellm/test_friendli_glm_5_3_flash_model_metadata.py
@@ -0,0 +1,35 @@
+import json
+from pathlib import Path
+
+from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+
+
+def test_friendli_glm_5_3_flash_model_info():
+    model = "friendliai/zai-org/GLM-5.3-Flash"
+    json_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
+    with open(json_path) as f:
+        model_cost = json.load(f)
+
+    info = model_cost.get(model)
+    assert (
+        info is not None
+    ), f"{model} not found in model_prices_and_context_window.json"
+    assert info["litellm_provider"] == "friendliai"
+    assert info["mode"] == "chat"
+    assert info["input_cost_per_token"] == 1.5e-07
+    assert info["output_cost_per_token"] == 5e-07
+    assert info["cache_read_input_token_cost"] == 3e-08
+    assert info["max_input_tokens"] == 1048576
+    assert info["max_output_tokens"] == 1048576
+    assert info["supports_function_calling"] is True
+    assert info["supports_reasoning"] is True
+    assert info["reasoning_effort_levels"] == ["low", "high", "max"]
+    assert info["supports_tool_choice"] is True
+    assert info["supports_prompt_caching"] is True
+    assert info["supports_vision"] is True
+    assert info["supports_image_input"] is True
+    assert info["supports_video_input"] is True
+
+    routed_model, provider, _, _ = get_llm_provider(model=model)
+    assert routed_model == "zai-org/GLM-5.3-Flash"
+    assert provider == "friendliai"
diff --git a/tests/test_litellm/test_friendli_glm_5_3_model_metadata.py b/tests/test_litellm/test_friendli_glm_5_3_model_metadata.py
new file mode 100644
index 00000000000..5282b0f589e
--- /dev/null
+++ b/tests/test_litellm/test_friendli_glm_5_3_model_metadata.py
@@ -0,0 +1,34 @@
+import json
+from pathlib import Path
+
+from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+
+
+def test_friendli_glm_5_3_model_info():
+    model = "friendliai/zai-org/GLM-5.3"
+    json_path = Path(__file__).parents[2] / "model_prices_and_context_window.json"
+    with open(json_path) as f:
+        model_cost = json.load(f)
+
+    info = model_cost.get(model)
+    assert (
+        info is not None
+    ), f"{model} not found in model_prices_and_context_window.json"
+    assert info["litellm_provider"] == "friendliai"
+    assert info["mode"] == "chat"
+    assert info["input_cost_per_token"] == 1.26e-06
+    assert info["output_cost_per_token"] == 3.96e-06
+    assert info["cache_read_input_token_cost"] == 2.34e-07
+    assert info["max_input_tokens"] == 1048576
+    assert info["max_output_tokens"] == 1048576
+    assert info["supports_function_calling"] is True
+    assert info["supports_reasoning"] is True
+    assert info["reasoning_effort_levels"] == ["low", "high", "max"]
+    assert info["supports_tool_choice"] is True
+    assert info["supports_prompt_caching"] is True
+    assert info["supports_vision"] is False
+    assert info["supports_image_input"] is False
+
+    routed_model, provider, _, _ = get_llm_provider(model=model)
+    assert routed_model == "zai-org/GLM-5.3"
+    assert provider == "friendliai"
diff --git a/tests/test_litellm/test_logging.py b/tests/test_litellm/test_logging.py
index 087a1c8b3ad..bf3757e6886 100644
--- a/tests/test_litellm/test_logging.py
+++ b/tests/test_litellm/test_logging.py
@@ -1,26 +1,30 @@
 import ast
 import asyncio
 import json
+import logging
 import re
 import sys
+import time
+from io import StringIO
 from pathlib import Path
 from typing import List
 
 import pytest
 
-import logging
-
 import litellm
 from litellm._logging import (
     _COLOR_LOG_FORMAT,
+    _MAX_SCRUBBED_ACCESS_ARG,
     _PLAIN_LOG_FORMAT,
     ALL_LOGGERS,
+    AccessLogRedactionFilter,
     CorrelationContextFilter,
     CorrelationPlainFormatter,
     JsonFormatter,
     LevelRoutingStreamHandler,
     SecretRedactionFilter,
     StdoutLogTruncationFilter,
+    _get_uvicorn_json_log_config,
     _initialize_loggers_with_handler,
     _parse_json_logs_env,
     _plain_log_format,
@@ -968,3 +972,209 @@ def test_plain_log_format_survives_none_streams():
     """sys.stdout/sys.stderr can be None in embedded interpreters; import must not crash."""
     assert _plain_log_format(None, None) == _PLAIN_LOG_FORMAT
     assert _plain_log_format(_FakeStream(True), None) == _PLAIN_LOG_FORMAT
+
+
+# ---------------------------------------------------------------------------
+# Access-log redaction (LIT-5909)
+# ---------------------------------------------------------------------------
+
+_LEAKED_KEY = "sk-mx5ous1o9Iezz5fj3pkLuA"
+
+
+def _access_record(full_path: str) -> logging.LogRecord:
+    """A record shaped exactly like the one uvicorn.access emits per request."""
+    return logging.LogRecord(
+        name="uvicorn.access",
+        level=logging.INFO,
+        pathname="",
+        lineno=0,
+        msg='%s - "%s %s HTTP/%s" %d',
+        args=("127.0.0.1:1", "GET", full_path, "1.1", 200),
+        exc_info=None,
+    )
+
+
+@pytest.mark.parametrize(
+    "full_path",
+    [
+        f"/key/info?key={_LEAKED_KEY}",
+        f"/global/spend/report?api_key={_LEAKED_KEY}&start_date=2026-08-01",
+        f"/key/spend/report?api_key={_LEAKED_KEY}",
+        f"/spend/logs?api_key={_LEAKED_KEY}",
+        f"/user/daily/activity?api_key={_LEAKED_KEY}",
+        f"/gemini/v1beta/models/gemini-2.0-flash:generateContent?key={_LEAKED_KEY}",
+    ],
+)
+def test_access_log_filter_redacts_a_credential_query_parameter(full_path):
+    record = _access_record(full_path)
+    assert AccessLogRedactionFilter().filter(record) is True
+    assert _LEAKED_KEY not in record.getMessage()
+    assert "REDACTED" in record.getMessage()
+
+
+def test_access_log_filter_keeps_the_record_formattable_by_uvicorn():
+    """uvicorn's AccessFormatter unpacks record.args, so the filter must scrub the
+    args in place rather than collapse them the way SecretRedactionFilter does."""
+    from uvicorn.logging import AccessFormatter
+
+    record = _access_record(f"/key/info?key={_LEAKED_KEY}")
+    AccessLogRedactionFilter().filter(record)
+    assert isinstance(record.args, tuple)
+    assert len(record.args) == 5
+
+    formatted = AccessFormatter('%(client_addr)s - "%(request_line)s" %(status_code)s', use_colors=False).format(record)
+    assert _LEAKED_KEY not in formatted
+    assert "GET" in formatted
+    assert "200 OK" in formatted
+
+
+@pytest.mark.parametrize(
+    "full_path, want",
+    [
+        # The delimiter must survive so the logged request line stays well formed.
+        (f"/key/info?key={_LEAKED_KEY}&page=2", "/key/info?REDACTED&page=2"),
+        ("/download?sig=AbCd1234%2Fxy&page=2", "/download?REDACTED&page=2"),
+        (
+            f"/global/spend/report?api_key={_LEAKED_KEY}&start_date=2026-01-01",
+            "/global/spend/report?REDACTED&start_date=2026-01-01",
+        ),
+        ("/sso/callback?client_secret=abcdefgh12345&state=xyz", "/sso/callback?REDACTED&state=xyz"),
+        (f"/v1/models?token={_LEAKED_KEY}&page=2", "/v1/models?REDACTED&page=2"),
+    ],
+)
+def test_access_log_filter_keeps_the_query_delimiter(full_path, want):
+    record = _access_record(full_path)
+    AccessLogRedactionFilter().filter(record)
+    assert record.args[2] == want
+
+
+@pytest.mark.parametrize(
+    "full_path, want",
+    [
+        # Both the param name and the value are encoded, so neither is literal text
+        # the patterns can see, yet the request parser decodes it into a working key.
+        (f"/key/info?k%65y=sk%2D{_LEAKED_KEY[3:]}", "/key/info?REDACTED"),
+        (f"/key/info?k%65y=sk%2D{_LEAKED_KEY[3:]}&page=2", "/key/info?REDACTED"),
+        (f"/v1/models/sk%2D{_LEAKED_KEY[3:]}", "REDACTED"),
+        # A decoded credential must never be echoed back: it can carry a newline and
+        # forge a following log line.
+        (f"/v1/models?k%65y=sk%2D{_LEAKED_KEY[3:]}%0AINFO:%20forged", "/v1/models?REDACTED"),
+    ],
+)
+def test_access_log_filter_redacts_a_percent_encoded_credential(full_path, want):
+    record = _access_record(full_path)
+    AccessLogRedactionFilter().filter(record)
+    assert record.args[2] == want
+
+
+@pytest.mark.parametrize(
+    "full_path",
+    [
+        "/v1/models?filter=gpt%2D4o&page=2",
+        "/gemini/v1beta/models/gemini-2.0-flash%3AgenerateContent",
+    ],
+)
+def test_access_log_filter_leaves_harmless_percent_encoding_alone(full_path):
+    """Decoding is a detector, not a rewrite, so a request line with no credential
+    in it survives encoded exactly as the client sent it."""
+    record = _access_record(full_path)
+    AccessLogRedactionFilter().filter(record)
+    assert record.args[2] == full_path
+
+
+def test_access_log_filter_caps_how_much_of_a_request_target_it_scans():
+    """The request target is the only input to the secret regex an unauthenticated
+    caller controls end to end, so it is bounded before it is scanned, and the
+    dropped tail must not reach the log either."""
+    record = _access_record("/v1/models?u=" + "a://" * 8192 + f"&key={_LEAKED_KEY}")
+
+    started = time.perf_counter()
+    AccessLogRedactionFilter().filter(record)
+    elapsed = time.perf_counter() - started
+
+    scrubbed = record.args[2]
+    assert _LEAKED_KEY not in scrubbed
+    assert len(scrubbed) < 1024
+    assert elapsed < 1.0, f"scrubbing one access line took {elapsed:.2f}s"
+
+
+@pytest.mark.parametrize("chars_before_the_cut", range(1, 12))
+def test_access_log_filter_never_logs_a_half_scanned_credential(chars_before_the_cut):
+    """Cutting mid-value would leave a prefix too short for the key= pattern to match,
+    and that prefix would then be logged raw, so the cut lands on a param boundary."""
+    prefix = "/v1/models?u="
+    padding = _MAX_SCRUBBED_ACCESS_ARG - len(prefix) - len("&key=") - chars_before_the_cut
+    record = _access_record(f"{prefix}{'a' * padding}&key={_LEAKED_KEY}")
+
+    AccessLogRedactionFilter().filter(record)
+
+    assert f"key={_LEAKED_KEY[:chars_before_the_cut]}" not in record.args[2]
+
+
+def test_access_log_filter_leaves_a_credential_free_request_line_intact():
+    record = _access_record("/v1/chat/completions")
+    AccessLogRedactionFilter().filter(record)
+    assert record.getMessage() == '127.0.0.1:1 - "GET /v1/chat/completions HTTP/1.1" 200'
+
+
+def test_access_log_filter_redacts_a_record_that_carries_no_positional_args():
+    record = logging.LogRecord(
+        name="uvicorn.access",
+        level=logging.INFO,
+        pathname="",
+        lineno=0,
+        msg=f'127.0.0.1:1 - "GET /key/info?key={_LEAKED_KEY} HTTP/1.1" 200',
+        args=None,
+        exc_info=None,
+    )
+    assert AccessLogRedactionFilter().filter(record) is True
+    assert _LEAKED_KEY not in record.getMessage()
+
+
+def _emit_access_line(full_path: str) -> str:
+    """Hand one real record to uvicorn.access and return what a handler wrote out."""
+    from uvicorn.logging import AccessFormatter
+
+    logger = logging.getLogger("uvicorn.access")
+    stream = StringIO()
+    handler = logging.StreamHandler(stream)
+    handler.setFormatter(AccessFormatter('%(client_addr)s - "%(request_line)s" %(status_code)s', use_colors=False))
+    saved_level, saved_propagate = logger.level, logger.propagate
+    logger.addHandler(handler)
+    logger.setLevel(logging.INFO)
+    logger.propagate = False
+    try:
+        logger.handle(_access_record(full_path))
+    finally:
+        logger.removeHandler(handler)
+        logger.setLevel(saved_level)
+        logger.propagate = saved_propagate
+    return stream.getvalue()
+
+
+def test_uvicorn_access_logger_redacts_a_credential_it_is_handed():
+    """Registration happens at litellm import; without it the filter never runs."""
+    emitted = _emit_access_line(f"/key/info?key={_LEAKED_KEY}")
+
+    assert _LEAKED_KEY not in emitted
+    assert "REDACTED" in emitted
+
+
+def test_access_redaction_survives_the_uvicorn_json_log_config():
+    """litellm hands uvicorn a dictConfig when json_logs is on. dictConfig clears a
+    logger's handlers but not its filters, so redaction has to still be attached."""
+    import logging.config
+
+    names = ("uvicorn", "uvicorn.error", "uvicorn.access")
+    saved = tuple((logging.getLogger(n), logging.getLogger(n).handlers[:], logging.getLogger(n).level) for n in names)
+    try:
+        logging.config.dictConfig(_get_uvicorn_json_log_config())
+        emitted = _emit_access_line(f"/key/info?key={_LEAKED_KEY}")
+
+        assert _LEAKED_KEY not in emitted
+        assert "REDACTED" in emitted
+    finally:
+        for lg, handlers, level in saved:
+            lg.handlers[:] = handlers
+            lg.setLevel(level)
+            lg.propagate = True
diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py
index 8cf878d05d9..7c2b9d0be05 100644
--- a/tests/test_litellm/test_main.py
+++ b/tests/test_litellm/test_main.py
@@ -3150,8 +3150,8 @@ def _stream_builder_logging_obj() -> LiteLLMLogging:
     return logging_obj
 
 
-def test_stream_chunk_builder_reports_streaming_usage_cost_when_enabled(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", True)
+def test_stream_chunk_builder_stamps_streaming_usage_cost_by_default(monkeypatch: pytest.MonkeyPatch):
+    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", False)
     chunks: Final = [
         _stream_builder_text_chunk("gpt-4o", "Hello "),
         _stream_builder_text_chunk("gpt-4o", "world.", finish_reason="stop"),
@@ -3168,11 +3168,45 @@ def test_stream_chunk_builder_reports_streaming_usage_cost_when_enabled(monkeypa
     assert response._hidden_params["response_cost"] == pytest.approx(usage_cost)
 
 
-def test_stream_chunk_builder_defers_cost_to_logging_obj_when_usage_cost_absent(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setattr(litellm, "include_cost_in_streaming_usage", False)
+def test_stream_chunk_builder_skips_stamp_when_cost_is_unpriceable():
+    import time as time_module
+
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
+
+    logging_obj: Final = LiteLLMLogging(
+        model="us.anthropic.claude-opus-5",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=True,
+        call_type="completion",
+        start_time=time_module.time(),
+        litellm_call_id="stream-builder-alias-unpriceable",
+        function_id="1",
+    )
+    logging_obj.model_call_details["custom_llm_provider"] = "bedrock"
+    logging_obj.optional_params = {}
+    usage_chunk: Final = _stream_builder_text_chunk("bedrock-claude-opus-5", "")
+    usage_chunk.usage = Usage(prompt_tokens=40, completion_tokens=5, total_tokens=45)
+    chunks: Final = [
+        _stream_builder_text_chunk("bedrock-claude-opus-5", "Hello ", finish_reason="stop"),
+        usage_chunk,
+    ]
+
+    response: Final = litellm.stream_chunk_builder(
+        chunks=chunks, messages=[{"role": "user", "content": "hi"}], logging_obj=logging_obj
+    )
+
+    assert response is not None
+    assert getattr(response.usage, "cost", None) is None
+    assert response._hidden_params.get("response_cost") is None
+
+
+def test_stream_chunk_builder_keeps_provider_reported_usage_cost():
+    usage_chunk: Final = _stream_builder_text_chunk("gpt-4o", "")
+    usage_chunk.usage = Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15, cost=0.5)
     chunks: Final = [
         _stream_builder_text_chunk("gpt-4o", "Hello "),
         _stream_builder_text_chunk("gpt-4o", "world.", finish_reason="stop"),
+        usage_chunk,
     ]
 
     response: Final = litellm.stream_chunk_builder(
@@ -3180,4 +3214,26 @@ def test_stream_chunk_builder_defers_cost_to_logging_obj_when_usage_cost_absent(
     )
 
     assert response is not None
-    assert response._hidden_params.get("response_cost") is None
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
+    assert response._hidden_params["response_cost"] == pytest.approx(0.5)
+
+
+def test_stream_chunk_builder_prices_alias_from_openai_sdk_usage_chunk():
+    from openai.types.completion_usage import CompletionUsage
+
+    usage_chunk: Final = _stream_builder_text_chunk("mantle-claude", "")
+    usage_chunk.usage = CompletionUsage(prompt_tokens=20, completion_tokens=60, total_tokens=80, cost=0.000704)
+    assert type(usage_chunk.usage) is CompletionUsage
+    chunks: Final = [
+        _stream_builder_text_chunk("mantle-claude", "Hello "),
+        _stream_builder_text_chunk("mantle-claude", "world.", finish_reason="stop"),
+        usage_chunk,
+    ]
+
+    response: Final = litellm.stream_chunk_builder(chunks=chunks, messages=[{"role": "user", "content": "hi"}])
+
+    assert response is not None
+    assert response.usage.prompt_tokens == 20
+    assert response.usage.completion_tokens == 60
+    assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
+    assert response._hidden_params["response_cost"] == pytest.approx(0.000704)
diff --git a/tests/test_litellm/test_muse_spark_1_3_model_metadata.py b/tests/test_litellm/test_muse_spark_1_3_model_metadata.py
new file mode 100644
index 00000000000..1ecd9490f78
--- /dev/null
+++ b/tests/test_litellm/test_muse_spark_1_3_model_metadata.py
@@ -0,0 +1,107 @@
+import json
+from pathlib import Path
+
+import pytest
+
+import litellm
+from litellm.cost_calculator import cost_per_token
+from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import StandardBuiltInToolCostTracking
+
+MUSE_SPARK_STANDARD = "meta/muse-spark-1.3"
+MUSE_SPARK_CONTRIBUTOR = "meta/muse-spark-1.3-contributor"
+WEB_SEARCH_COST_PER_QUERY = 0.0025
+
+PRICING = (
+    (MUSE_SPARK_STANDARD, 1.25e-06, 1.5e-07, 4.25e-06),
+    (MUSE_SPARK_CONTRIBUTOR, 1e-07, 2e-09, 2e-07),
+)
+
+
+def _load_cost_map(filename: str = "model_prices_and_context_window.json") -> dict:
+    with open(Path(__file__).parents[2] / filename) as f:
+        return json.load(f)
+
+
+
+@pytest.mark.parametrize("model, input_cost, cached_cost, output_cost", PRICING)
+def test_muse_spark_1_3_model_info(model: str, input_cost: float, cached_cost: float, output_cost: float):
+    info = _load_cost_map().get(model)
+    assert info is not None, f"{model} not found in model_prices_and_context_window.json"
+
+    assert info["litellm_provider"] == "meta"
+    assert info["mode"] == "chat"
+
+    assert info["input_cost_per_token"] == input_cost
+    assert info["output_cost_per_token"] == output_cost
+    assert info["cache_read_input_token_cost"] == cached_cost
+
+    assert info["max_input_tokens"] == 1048576
+    assert info["max_output_tokens"] == 131072
+    assert info["max_tokens"] == 131072
+
+    assert info["supports_function_calling"] is True
+    assert info["supports_parallel_function_calling"] is True
+    assert info["supports_prompt_caching"] is True
+    assert info["supports_reasoning"] is True
+    assert info["supports_response_schema"] is True
+    assert info["supports_tool_choice"] is True
+    assert info["supports_vision"] is True
+    assert info["supports_pdf_input"] is True
+    assert info["supports_web_search"] is True
+    assert info["supports_minimal_reasoning_effort"] is True
+    assert info["supports_xhigh_reasoning_effort"] is True
+
+    assert info["supported_endpoints"] == ["/v1/chat/completions", "/v1/responses", "/v1/messages"]
+    assert info["supported_modalities"] == ["text", "image", "video"]
+    assert info["supported_output_modalities"] == ["text"]
+
+    assert info["search_context_cost_per_query"] == {
+        "search_context_size_high": WEB_SEARCH_COST_PER_QUERY,
+        "search_context_size_low": WEB_SEARCH_COST_PER_QUERY,
+        "search_context_size_medium": WEB_SEARCH_COST_PER_QUERY,
+    }
+
+
+@pytest.mark.parametrize("model, input_cost, cached_cost, output_cost", PRICING)
+def test_muse_spark_1_3_cost_per_token(
+    local_model_cost_map, model: str, input_cost: float, cached_cost: float, output_cost: float
+):
+    prompt_cost, completion_cost = cost_per_token(model=model, prompt_tokens=1000, completion_tokens=500)
+
+    assert prompt_cost == pytest.approx(1000 * input_cost)
+    assert completion_cost == pytest.approx(500 * output_cost)
+
+
+@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
+def test_muse_spark_1_3_routes_to_meta_model_api(model: str):
+    routed_model, provider, _, api_base = get_llm_provider(model=model, api_key="sk-test")
+
+    assert routed_model == model.split("/", 1)[1]
+    assert provider == "meta"
+    assert api_base == "https://api.meta.ai/v1"
+
+
+@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
+def test_muse_spark_1_3_web_search_cost_per_query(local_model_cost_map, model: str):
+    info = litellm.get_model_info(model=model)
+
+    assert StandardBuiltInToolCostTracking.get_cost_for_web_search(model_info=info) == WEB_SEARCH_COST_PER_QUERY
+
+
+@pytest.mark.parametrize("model", (MUSE_SPARK_STANDARD, MUSE_SPARK_CONTRIBUTOR))
+def test_muse_spark_1_3_backup_matches_main(model: str):
+    """Ensure the bundled model cost map stays in sync with the canonical file."""
+    main_cost = _load_cost_map()
+    backup_cost = _load_cost_map("litellm/model_prices_and_context_window_backup.json")
+
+    assert backup_cost.get(model) == main_cost.get(model), f"{model} differs between main and backup model cost maps"
+
+
+def test_muse_spark_contributor_tier_is_cheaper_than_standard():
+    cost_map = _load_cost_map()
+    standard = cost_map[MUSE_SPARK_STANDARD]
+    contributor = cost_map[MUSE_SPARK_CONTRIBUTOR]
+
+    for field in ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost"):
+        assert contributor[field] < standard[field], f"contributor {field} should undercut the standard tier"
diff --git a/tests/test_litellm/test_openai_embedding_encoding_format_default.py b/tests/test_litellm/test_openai_embedding_encoding_format_default.py
index 94e4e3c81e5..7a42eaf0f0a 100644
--- a/tests/test_litellm/test_openai_embedding_encoding_format_default.py
+++ b/tests/test_litellm/test_openai_embedding_encoding_format_default.py
@@ -1,124 +1,121 @@
-from unittest.mock import MagicMock, patch
+import json
+from typing import Final
 
+import httpx
 import pytest
+import respx
 
-from litellm import embedding
+import litellm
 
 
-@pytest.mark.parametrize(
-    "set_env, env_value, expected",
-    [
-        (False, None, "float"),
-        (True, "base64", "base64"),
-    ],
-)
-def test_openai_embedding_encoding_format_default(
-    monkeypatch, set_env, env_value, expected
-):
-    monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False)
-    if set_env:
-        monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_value)
-
-    mock_response = MagicMock()
-    mock_response.parse.return_value = MagicMock(
-        model_dump=lambda: {
-            "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}],
-            "model": "text-embedding-ada-002",
-            "object": "list",
-            "usage": {"prompt_tokens": 1, "total_tokens": 1},
-        }
+def _mock_openai_embedding_route(respx_mock: respx.MockRouter) -> respx.Route:
+    return respx_mock.post("https://api.openai.com/v1/embeddings").mock(
+        return_value=httpx.Response(
+            200,
+            json={
+                "object": "list",
+                "data": [{"object": "embedding", "index": 0, "embedding": [0.1, 0.2, 0.3]}],
+                "model": "text-embedding-3-small",
+                "usage": {"prompt_tokens": 2, "total_tokens": 2},
+            },
+        )
     )
-    mock_response.headers = {}
 
-    with patch(
-        "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client"
-    ) as mock_get_client:
-        mock_client_instance = MagicMock()
-        mock_get_client.return_value = mock_client_instance
-        mock_client_instance.embeddings.with_raw_response.create.return_value = (
-            mock_response
-        )
 
-        embedding(
-            model="text-embedding-ada-002",
-            input="Hello world",
-        )
+@pytest.fixture(autouse=True)
+def clear_default_encoding_format_env(monkeypatch: pytest.MonkeyPatch):
+    monkeypatch.delenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", raising=False)
 
-        call_kwargs = (
-            mock_client_instance.embeddings.with_raw_response.create.call_args[1]
-        )
-        assert call_kwargs["encoding_format"] == expected
+
+def test_embedding_openai_omits_encoding_format_when_client_omits_it(respx_mock: respx.MockRouter) -> None:
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
+
+    response: Final = litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test")
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert "encoding_format" not in request_body
+    assert response.data[0]["embedding"] == [0.1, 0.2, 0.3]
+
+
+def test_embedding_openai_forwards_explicit_encoding_format(respx_mock: respx.MockRouter) -> None:
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
+
+    litellm.embedding(
+        model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", encoding_format="base64"
+    )
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert request_body["encoding_format"] == "base64"
+
+
+def test_embedding_openai_explicit_encoding_format_wins_over_env_var(
+    respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", "float")
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
+
+    litellm.embedding(
+        model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", encoding_format="base64"
+    )
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert request_body["encoding_format"] == "base64"
+
+
+@pytest.mark.parametrize("env_value", ["float", "base64"])
+def test_embedding_openai_env_var_sets_default_encoding_format(
+    respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, env_value: str
+) -> None:
+    monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_value)
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
+
+    litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test")
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert request_body["encoding_format"] == env_value
 
 
 @pytest.mark.parametrize("env_none", ["none", "NONE", " none "])
-def test_openai_embedding_encoding_format_env_none_omits_param(
-    monkeypatch, env_none
-):
-    """LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT=none omits encoding_format (provider default)."""
+def test_embedding_openai_env_none_omits_encoding_format(
+    respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, env_none: str
+) -> None:
     monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", env_none)
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
 
-    mock_response = MagicMock()
-    mock_response.parse.return_value = MagicMock(
-        model_dump=lambda: {
-            "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}],
-            "model": "text-embedding-ada-002",
-            "object": "list",
-            "usage": {"prompt_tokens": 1, "total_tokens": 1},
-        }
+    litellm.embedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test")
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert "encoding_format" not in request_body
+
+
+@pytest.mark.asyncio
+async def test_aembedding_openai_omits_encoding_format_when_client_omits_it(
+    respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+    mock_route: Final = _mock_openai_embedding_route(respx_mock)
+
+    response: Final = await litellm.aembedding(model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test")
+
+    request_body: Final = json.loads(mock_route.calls.last.request.read())
+    assert "encoding_format" not in request_body
+    assert response.data[0]["embedding"] == [0.1, 0.2, 0.3]
+
+
+def test_embedding_openai_omitted_encoding_format_maps_provider_errors(
+    respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    respx_mock.post("https://api.openai.com/v1/embeddings").mock(
+        return_value=httpx.Response(
+            429,
+            headers={"retry-after": "42", "x-should-retry": "false"},
+            json={"error": {"message": "rate limited", "type": "rate_limit_error"}},
+        )
     )
-    mock_response.headers = {}
 
-    with patch(
-        "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client"
-    ) as mock_get_client:
-        mock_client_instance = MagicMock()
-        mock_get_client.return_value = mock_client_instance
-        mock_client_instance.embeddings.with_raw_response.create.return_value = (
-            mock_response
+    with pytest.raises(litellm.RateLimitError) as exc_info:
+        litellm.embedding(
+            model="openai/text-embedding-3-small", input=["hello"], api_key="sk-test", max_retries=0
         )
 
-        embedding(
-            model="text-embedding-ada-002",
-            input="Hello world",
-        )
-
-        call_kwargs = (
-            mock_client_instance.embeddings.with_raw_response.create.call_args[1]
-        )
-        assert "encoding_format" not in call_kwargs
-
-
-def test_openai_embedding_encoding_format_explicit_overrides_env(monkeypatch):
-    """Request `encoding_format` wins over LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT."""
-    monkeypatch.setenv("LITELLM_DEFAULT_EMBEDDING_ENCODING_FORMAT", "float")
-
-    mock_response = MagicMock()
-    mock_response.parse.return_value = MagicMock(
-        model_dump=lambda: {
-            "data": [{"embedding": [0.1, 0.2, 0.3], "index": 0}],
-            "model": "text-embedding-ada-002",
-            "object": "list",
-            "usage": {"prompt_tokens": 1, "total_tokens": 1},
-        }
-    )
-    mock_response.headers = {}
-
-    with patch(
-        "litellm.llms.openai.openai.OpenAIChatCompletion._get_openai_client"
-    ) as mock_get_client:
-        mock_client_instance = MagicMock()
-        mock_get_client.return_value = mock_client_instance
-        mock_client_instance.embeddings.with_raw_response.create.return_value = (
-            mock_response
-        )
-
-        embedding(
-            model="text-embedding-ada-002",
-            input="Hello world",
-            encoding_format="base64",
-        )
-
-        call_kwargs = (
-            mock_client_instance.embeddings.with_raw_response.create.call_args[1]
-        )
-        assert call_kwargs["encoding_format"] == "base64"
+    assert int(exc_info.value.litellm_response_headers["retry-after"]) == 42
diff --git a/tests/test_litellm/test_openai_service_tier_long_context_pricing.py b/tests/test_litellm/test_openai_service_tier_long_context_pricing.py
new file mode 100644
index 00000000000..c0860a5b55f
--- /dev/null
+++ b/tests/test_litellm/test_openai_service_tier_long_context_pricing.py
@@ -0,0 +1,156 @@
+import json
+from functools import lru_cache
+from pathlib import Path
+
+import pytest
+
+import litellm
+
+REPO_ROOT = Path(__file__).parents[2]
+MAIN_PATH = REPO_ROOT / "model_prices_and_context_window.json"
+BACKUP_PATH = REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
+
+FLEX_LONG_CONTEXT = {
+    "gpt-5.4": {
+        "input_cost_per_token_above_272k_tokens_flex": 2.5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 1.125e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07,
+    },
+    "gpt-5.4-pro": {
+        "input_cost_per_token_above_272k_tokens_flex": 3e-05,
+        "output_cost_per_token_above_272k_tokens_flex": 0.000135,
+    },
+    "gpt-5.5": {
+        "input_cost_per_token_above_272k_tokens_flex": 5e-06,
+        "output_cost_per_token_above_272k_tokens_flex": 2.25e-05,
+        "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07,
+    },
+}
+
+PRIORITY_LONG_CONTEXT = {
+    "gpt-5.6": {
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
+    },
+    "gpt-5.6-sol": {
+        "input_cost_per_token_above_272k_tokens_priority": 1.6e-05,
+        "output_cost_per_token_above_272k_tokens_priority": 6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 2e-05,
+    },
+    "gpt-5.6-terra": {
+        "input_cost_per_token_above_272k_tokens_priority": 8e-06,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-05,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-05,
+    },
+    "gpt-5.6-luna": {
+        "input_cost_per_token_above_272k_tokens_priority": 8e-07,
+        "output_cost_per_token_above_272k_tokens_priority": 3.6e-06,
+        "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08,
+        "cache_creation_input_token_cost_above_272k_tokens_priority": 1e-06,
+    },
+}
+
+EXPECTED = {**FLEX_LONG_CONTEXT, **PRIORITY_LONG_CONTEXT}
+
+NO_PUBLISHED_PRIORITY_LONG_CONTEXT = ("gpt-5.4", "gpt-5.5")
+
+
+@pytest.fixture(autouse=True)
+def _local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+
+@lru_cache(maxsize=2)
+def _load(path: Path) -> dict[str, dict[str, object]]:
+    with open(path) as f:
+        return json.load(f)
+
+
+@pytest.mark.parametrize("path", [MAIN_PATH, BACKUP_PATH], ids=["main", "backup"])
+@pytest.mark.parametrize("model", sorted(EXPECTED))
+def test_service_tier_long_context_rates_are_published(model: str, path: Path) -> None:
+    """Each tier must carry its own above-272K rates, in both price files."""
+    info = _load(path).get(model)
+    assert info is not None, f"{model} not found in {path.name}"
+    for key, expected in EXPECTED[model].items():
+        assert info.get(key) == pytest.approx(expected), f"{model}.{key} is {info.get(key)!r}, expected {expected!r}"
+
+
+@pytest.mark.parametrize("model", sorted(EXPECTED))
+def test_tier_long_context_rate_is_half_or_double_the_standard(model: str) -> None:
+    """Flex is half the standard long-context rate; priority is double it."""
+    info = _load(MAIN_PATH)[model]
+    tier = "flex" if model in FLEX_LONG_CONTEXT else "priority"
+    ratio = 0.5 if tier == "flex" else 2.0
+    for base in ("input_cost_per_token", "output_cost_per_token"):
+        standard = info[f"{base}_above_272k_tokens"]
+        tiered = info[f"{base}_above_272k_tokens_{tier}"]
+        assert tiered == pytest.approx(standard * ratio), (
+            f"{model}.{base}_above_272k_tokens_{tier} is {tiered!r}, "
+            f"expected {ratio}x the standard long-context rate {standard!r}"
+        )
+
+
+@pytest.mark.parametrize("model", NO_PUBLISHED_PRIORITY_LONG_CONTEXT)
+def test_no_priority_long_context_rates_where_openai_publishes_none(model: str) -> None:
+    """Guard against back-filling a rate OpenAI does not publish."""
+    info = _load(MAIN_PATH)[model]
+    assert "input_cost_per_token_above_272k_tokens_priority" not in info
+
+
+LONG_CONTEXT_PROMPT_TOKENS = 300_000
+COMPLETION_TOKENS = 1_000
+
+TIERED_COST_CASES = [
+    ("gpt-5.4", "flex", 2.5e-06, 1.125e-05),
+    ("gpt-5.4-pro", "flex", 3e-05, 0.000135),
+    ("gpt-5.5", "flex", 5e-06, 2.25e-05),
+    ("gpt-5.6", "priority", 1.6e-05, 6e-05),
+    ("gpt-5.6-sol", "priority", 1.6e-05, 6e-05),
+    ("gpt-5.6-terra", "priority", 8e-06, 3.6e-05),
+    ("gpt-5.6-luna", "priority", 8e-07, 3.6e-06),
+]
+
+
+@pytest.mark.parametrize("model,tier,input_rate,output_rate", TIERED_COST_CASES)
+def test_cost_per_token_bills_long_context_at_the_tier_rate(
+    model: str, tier: str, input_rate: float, output_rate: float
+) -> None:
+    """A prompt over 272K on flex or priority must bill at that tier's long-context rate."""
+    input_cost, output_cost = litellm.cost_per_token(
+        model=model,
+        prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+        completion_tokens=COMPLETION_TOKENS,
+        service_tier=tier,
+    )
+    assert input_cost == pytest.approx(LONG_CONTEXT_PROMPT_TOKENS * input_rate)
+    assert output_cost == pytest.approx(COMPLETION_TOKENS * output_rate)
+
+
+@pytest.mark.parametrize("model,tier,input_rate,output_rate", TIERED_COST_CASES)
+def test_cost_per_token_tier_differs_from_the_standard_long_context_cost(
+    model: str, tier: str, input_rate: float, output_rate: float
+) -> None:
+    """Flex halves the standard long-context bill and priority doubles it."""
+    ratio = 0.5 if tier == "flex" else 2.0
+    standard = sum(
+        litellm.cost_per_token(
+            model=model,
+            prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+            completion_tokens=COMPLETION_TOKENS,
+        )
+    )
+    tiered = sum(
+        litellm.cost_per_token(
+            model=model,
+            prompt_tokens=LONG_CONTEXT_PROMPT_TOKENS,
+            completion_tokens=COMPLETION_TOKENS,
+            service_tier=tier,
+        )
+    )
+    assert tiered == pytest.approx(standard * ratio)
diff --git a/tests/test_litellm/test_redis.py b/tests/test_litellm/test_redis.py
index 826beb74a27..a96e8541e06 100644
--- a/tests/test_litellm/test_redis.py
+++ b/tests/test_litellm/test_redis.py
@@ -1,3 +1,4 @@
+import inspect
 import json
 from types import SimpleNamespace
 from unittest.mock import AsyncMock, MagicMock, patch
@@ -600,6 +601,72 @@ def test_reconnect_kwargs_in_cluster_kwargs():
     assert "socket_keepalive" in kwargs
 
 
+def test_retry_attempts_in_cluster_kwargs():
+    """cluster_error_retry_attempts must survive the cluster kwarg allow-list so
+    operators can bound worst-case retry latency on a Redis Cluster: it was being
+    silently dropped because the allow-list was built from redis.RedisCluster's
+    decorated __init__ without unwrapping it, so getfullargspec saw an empty
+    (self, *args, **kwargs) wrapper signature."""
+    kwargs = _get_redis_cluster_kwargs()
+    assert "cluster_error_retry_attempts" in kwargs
+
+
+def test_async_only_kwargs_in_cluster_kwargs_when_async_client_requested():
+    """decode_responses is on the async cluster client's constructor and not the sync
+    one, on every redis-py the matrix covers. Introspecting the sync class regardless
+    of which client is actually built silently drops it for every async cluster caller."""
+    sync_kwargs = _get_redis_cluster_kwargs()
+    async_kwargs = _get_redis_cluster_kwargs(async_redis.RedisCluster)
+
+    assert "decode_responses" not in sync_kwargs
+    assert "decode_responses" in async_kwargs
+
+
+@patch(  # test-quality-ok: redis-py >= 6 keeps no cluster_error_retry_attempts attribute on the built client, so the constructor call is the only place the value is observable
+    "litellm.caching.redis_cluster_node_isolation.get_litellm_async_redis_cluster_class"
+)
+def test_async_cluster_forwards_retry_attempts(mock_get_cluster_class):
+    """Regression: cluster_error_retry_attempts must reach the constructed async
+    cluster client. Silently dropping it removes an operator's only lever for
+    bounding a stuck node's worst-case retry latency, and the client falls back
+    to redis-py's own default (3 retries) instead."""
+    mock_cluster_cls = mock_get_cluster_class.return_value
+    get_redis_async_client(
+        startup_nodes=[{"host": "cluster-node", "port": 6379}],
+        cluster_error_retry_attempts=2,
+    )
+
+    call_kwargs = mock_cluster_cls.call_args[1]
+    assert call_kwargs["cluster_error_retry_attempts"] == 2
+
+
+def test_async_cluster_passes_async_only_kwargs():
+    """Regression: decode_responses is an async-cluster-only constructor arg. When
+    the allow-list came from the sync class it was filtered out and values came
+    back as bytes instead of str."""
+    client = get_redis_async_client(
+        startup_nodes=[{"host": "cluster-node", "port": 6379}],
+        decode_responses=True,
+    )
+
+    assert client.connection_kwargs["decode_responses"] is True
+
+
+@pytest.mark.parametrize("cluster_client", [redis.RedisCluster, async_redis.RedisCluster], ids=["sync", "async"])
+def test_cluster_kwargs_exclude_variadic_parameters(cluster_client):
+    """*args / **kwargs are signature placeholders, not connection settings, and
+    must never land in the allow-list regardless of which cluster client is
+    introspected."""
+    variadic = {
+        name
+        for name, param in inspect.signature(cluster_client).parameters.items()
+        if param.kind in (param.VAR_POSITIONAL, param.VAR_KEYWORD)
+    }
+
+    leaked = variadic & set(_get_redis_cluster_kwargs(cluster_client))
+    assert not leaked, f"variadic params leaked into the allow-list: {leaked}"
+
+
 @patch("litellm.caching.redis_cluster_node_isolation.get_litellm_async_redis_cluster_class")
 def test_async_cluster_sets_reconnect_defaults(mock_get_cluster_class):
     """
diff --git a/tests/test_litellm/test_register_model_custom_pricing.py b/tests/test_litellm/test_register_model_custom_pricing.py
index 39f498b4e58..452a15334ef 100644
--- a/tests/test_litellm/test_register_model_custom_pricing.py
+++ b/tests/test_litellm/test_register_model_custom_pricing.py
@@ -793,3 +793,203 @@ def test_embedding_direct_sdk_custom_pricing_still_registers_shared_key():
     finally:
         litellm.model_cost.pop(model_key, None)
         _invalidate_model_cost_lowercase_map()
+
+
+def test_update_dictionary_merges_nested_dicts_without_aliasing():
+    """A nested dict must be merged copy-on-write: the pre-existing nested dict
+    object stays untouched, and the caller's incoming nested dict is never
+    inserted by reference into the merged result.
+    """
+    from litellm.utils import _update_dictionary
+
+    existing_nested = {"hours_utc": "01:00-02:00"}
+    existing = {"off_peak_pricing": existing_nested}
+    incoming_nested = {"windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}]}
+    incoming = {"off_peak_pricing": incoming_nested}
+
+    merged = _update_dictionary(existing, incoming)
+
+    assert merged["off_peak_pricing"] == {
+        "hours_utc": "01:00-02:00",
+        "windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}],
+    }
+    assert existing_nested == {"hours_utc": "01:00-02:00"}
+    assert merged["off_peak_pricing"] is not incoming_nested
+
+    fresh = _update_dictionary({}, incoming)
+    assert fresh["off_peak_pricing"] == incoming_nested
+    assert fresh["off_peak_pricing"] is not incoming_nested
+
+
+def test_router_deployments_sharing_backend_keep_their_own_off_peak_pricing():
+    """Two deployments of the same backend model with different
+    ``off_peak_pricing`` blocks must each keep their own schedule under their
+    unique model id, and neither block may leak onto the shared backend keys.
+
+    Before the fix, ``register_model`` inserted the first deployment's block by
+    reference into the built-in ``gpt-4o-mini`` entry, and the second
+    deployment's registration merged its keys into that same object, corrupting
+    the first deployment's schedule and polluting the built-in entry.
+    """
+    from litellm import Router
+
+    active_block = {
+        "windows": [{"hours_utc": "16:00-19:00", "weekdays": [2]}],
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    inactive_block = {
+        "hours_utc": "05:00-06:00",
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_ids = ["offpeak-alias-dep-1", "offpeak-alias-dep-2"]
+    original_entries = _snapshot_model_cost_entries(shared_keys)
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-active-weekday",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {
+                    "id": deployment_ids[0],
+                    "input_cost_per_token": 1e-06,
+                    "output_cost_per_token": 2e-06,
+                    "off_peak_pricing": dict(active_block),
+                },
+            },
+            {
+                "model_name": "offpeak-inactive-hours",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {
+                    "id": deployment_ids[1],
+                    "input_cost_per_token": 1e-06,
+                    "output_cost_per_token": 2e-06,
+                    "off_peak_pricing": dict(inactive_block),
+                },
+            },
+        ]
+    )
+
+    try:
+        registered_first = litellm.model_cost[deployment_ids[0]]["off_peak_pricing"]
+        registered_second = litellm.model_cost[deployment_ids[1]]["off_peak_pricing"]
+        assert registered_first == active_block
+        assert registered_second == inactive_block
+        for shared_key in shared_keys:
+            shared_entry = litellm.model_cost.get(shared_key) or {}
+            assert not shared_entry.get("off_peak_pricing")
+    finally:
+        for deployment_id in deployment_ids:
+            litellm.model_cost.pop(deployment_id, None)
+        _restore_model_cost_entries(original_entries)
+        del router
+
+
+def test_router_off_peak_only_deployment_inherits_builtin_base_rates():
+    """A deployment that sets only ``off_peak_pricing`` on its model_info must
+    still be costed from its deployment-scoped entry: the base token rates are
+    inherited from the backend model's built-in cost map entry, since the
+    shared backend key deliberately never carries the off-peak block.
+    """
+    from litellm import Router
+
+    block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-05,
+        "output_cost_per_token": 1e-04,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_id = "offpeak-only-dep-1"
+    original_entries = _snapshot_model_cost_entries(shared_keys + [deployment_id])
+    builtin_info = litellm.get_model_info(model="openai/gpt-4o-mini")
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-only",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {"id": deployment_id, "off_peak_pricing": dict(block)},
+            }
+        ]
+    )
+
+    try:
+        entry = litellm.model_cost[deployment_id]
+        assert entry["off_peak_pricing"] == block
+        assert entry["input_cost_per_token"] is not None
+        assert entry["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+        assert entry["output_cost_per_token"] == builtin_info["output_cost_per_token"]
+        for shared_key in shared_keys:
+            shared_entry = litellm.model_cost.get(shared_key) or {}
+            assert not shared_entry.get("off_peak_pricing")
+    finally:
+        _restore_model_cost_entries(original_entries)
+        del router
+
+
+def test_use_custom_pricing_for_model_sees_off_peak_only_model_info():
+    from litellm.litellm_core_utils.litellm_logging import use_custom_pricing_for_model
+
+    block = {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-05}
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"off_peak_pricing": block}}}) is True
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"off_peak_pricing": None}}}) is False
+    assert use_custom_pricing_for_model({"metadata": {"model_info": {"id": "some-id"}}}) is False
+
+
+def test_completion_cost_applies_off_peak_only_deployment_pricing():
+    """End to end through the cost calculator: with ``custom_pricing`` set and
+    a ``router_model_id`` whose entry carries only an always-on off-peak block,
+    the request bills at the block's rates rather than the shared backend rate.
+    """
+    from litellm import Router
+    from litellm.types.utils import ModelResponse, Usage
+
+    block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-05,
+        "output_cost_per_token": 1e-04,
+    }
+    shared_keys = ["gpt-4o-mini", "openai/gpt-4o-mini"]
+    deployment_id = "offpeak-only-dep-2"
+    original_entries = _snapshot_model_cost_entries(shared_keys + [deployment_id])
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "offpeak-only",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "fake-key-for-registration",
+                },
+                "model_info": {"id": deployment_id, "off_peak_pricing": dict(block)},
+            }
+        ]
+    )
+
+    try:
+        response = ModelResponse(
+            model="gpt-4o-mini",
+            usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150),
+        )
+        cost = litellm.completion_cost(
+            completion_response=response,
+            model="openai/gpt-4o-mini",
+            custom_llm_provider="openai",
+            custom_pricing=True,
+            router_model_id=deployment_id,
+        )
+        assert cost == pytest.approx(100 * 5e-05 + 50 * 1e-04)
+    finally:
+        _restore_model_cost_entries(original_entries)
+        del router
diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py
index 97286017ffe..c843a66a1c1 100644
--- a/tests/test_litellm/test_router.py
+++ b/tests/test_litellm/test_router.py
@@ -6,6 +6,7 @@ import logging
 import os
 import threading
 from types import SimpleNamespace
+from typing import Final
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import httpx
@@ -1537,6 +1538,91 @@ async def test_ageneric_api_call_deployment_model_overrides_alias():
     ), f"Expected deployment model 'vertex_ai/gemini-2.5-flash', got '{captured['model']}'"
 
 
+@pytest.mark.asyncio
+async def test_ageneric_api_call_resolves_realtime_session_model():
+    """
+    Regression for #36742: realtime client secret requests carry the model inside `session` too, and the proxy
+    fills it with the pre-routing model group name. The underlying litellm function reads session.model first,
+    so it must see the resolved deployment, while a caller's nested transcription model stays untouched.
+    """
+    routed: Final = AsyncMock(return_value={"result": "ok"})
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "my-realtime-group",
+                "litellm_params": {
+                    "model": "openai/gpt-realtime-2.1-mini",
+                    "api_key": "fake-key",
+                },
+                "model_info": {"mode": "realtime"},
+            }
+        ]
+    )
+
+    await router._ageneric_api_call_with_fallbacks(
+        model="my-realtime-group",
+        original_function=routed,
+        session={
+            "type": "realtime",
+            "model": "my-realtime-group",
+            "audio": {"input": {"transcription": {"model": "gpt-4o-transcribe"}}},
+        },
+    )
+
+    sent: Final = routed.call_args.kwargs
+    assert sent["model"] == "openai/gpt-realtime-2.1-mini"
+    assert sent["session"]["model"] == "openai/gpt-realtime-2.1-mini"
+    assert sent["session"]["audio"]["input"]["transcription"]["model"] == "gpt-4o-transcribe"
+
+
+@pytest.mark.asyncio
+async def test_ageneric_api_call_does_not_add_session_model():
+    """
+    A session that never carried a model must not gain one from routing: the underlying function then falls back
+    to the resolved `model` kwarg itself, and the outgoing session body keeps the caller's shape.
+    """
+    routed: Final = AsyncMock(return_value={"result": "ok"})
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "my-realtime-group",
+                "litellm_params": {
+                    "model": "openai/gpt-realtime-2.1-mini",
+                    "api_key": "fake-key",
+                },
+                "model_info": {"mode": "realtime"},
+            }
+        ]
+    )
+
+    await router._ageneric_api_call_with_fallbacks(
+        model="my-realtime-group",
+        original_function=routed,
+        session={"type": "realtime"},
+    )
+
+    sent: Final = routed.call_args.kwargs
+    assert sent["model"] == "openai/gpt-realtime-2.1-mini"
+    assert sent["session"] == {"type": "realtime"}
+
+
+@pytest.mark.parametrize(
+    "session, expected",
+    [
+        ({"type": "realtime", "model": "my-realtime-group"}, {"session": {"type": "realtime", "model": "resolved"}}),
+        ({"type": "realtime"}, {}),
+        (None, {}),
+        ("not-a-session", {}),
+    ],
+)
+def test_with_router_resolved_session_model(session, expected):
+    from litellm.router import _with_router_resolved_session_model
+
+    assert dict(_with_router_resolved_session_model(session, "resolved")) == expected
+
+
 def test_router_get_model_access_groups_team_only_models():
     """
     Test that Router.get_model_access_groups returns the correct response for team-only models
@@ -7271,6 +7357,71 @@ def test_get_configured_token_limits_coerces_numeric_strings():
     assert router.get_configured_token_limits("quoted-limits-model") == (32000, 8000)
 
 
+def test_get_configured_display_name_reads_deployment_model_info():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "Kimi K3-claude-compatible",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+                "model_info": {"display_name": "Kimi K3"},
+            }
+        ]
+    )
+
+    assert router.get_configured_display_name("Kimi K3-claude-compatible") == "Kimi K3"
+
+
+def test_get_configured_display_name_returns_none_for_unset_or_unknown():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "no-display-model",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+            }
+        ]
+    )
+
+    assert router.get_configured_display_name("no-display-model") is None
+    assert router.get_configured_display_name("not-a-real-model") is None
+
+
+def test_get_configured_display_name_skips_wildcard_pattern_matching():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "bedrock/*",
+                "litellm_params": {"model": "bedrock/*"},
+                "model_info": {"display_name": "Bedrock"},
+            }
+        ]
+    )
+
+    with patch.object(
+        router.pattern_router, "route", side_effect=AssertionError("pattern route called")
+    ):
+        assert (
+            router.get_configured_display_name("bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0")
+            is None
+        )
+
+
+def test_get_configured_display_name_treats_malformed_values_as_absent():
+    malformed = ["", "   ", 12345, ["Kimi K3"], {"name": "Kimi K3"}, True]
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": f"bad-display-{i}",
+                "litellm_params": {"model": "openai/some-unmapped-model"},
+                "model_info": {"display_name": bad},
+            }
+            for i, bad in enumerate(malformed)
+        ]
+    )
+
+    for i in range(len(malformed)):
+        assert router.get_configured_display_name(f"bad-display-{i}") is None
+
+
 @pytest.mark.asyncio
 async def test_acreate_batch_disable_fallbacks_surfaces_owning_provider_error():
     router = litellm.Router(
@@ -7510,6 +7661,118 @@ async def test_acreate_batch_request_bedrock_tags_override_deployment_tags():
         assert mock_sign.call_args.kwargs["data"]["tags"] == request_tags
 
 
+@pytest.mark.asyncio
+async def test_avector_store_search_injects_router():
+    """
+    Regression: router.avector_store_search must pass the router down to the
+    SDK search call so provider transforms can resolve router-managed
+    embedding models (e.g. S3 Vectors query embeddings).
+    """
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    expected_response = VectorStoreSearchResponse(
+        object="vector_store.search_results.page", search_query="q", data=[]
+    )
+    mock_asearch = AsyncMock(return_value=expected_response)
+    # Router.__init__ binds asearch via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.asearch", new=mock_asearch):  # test-quality-ok: the SDK call is the only place the injected router kwarg is observable
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        search_response = await router.avector_store_search(
+            vector_store_id="v", query="q", custom_llm_provider="s3_vectors"
+        )
+
+    assert search_response is expected_response
+    mock_asearch.assert_awaited_once()
+    assert mock_asearch.await_args.kwargs["router"] is router
+
+
+@pytest.mark.asyncio
+async def test_avector_store_create_does_not_inject_router():
+    """The router injection is gated on the search call type: the create path
+    must keep calling the SDK without a router kwarg."""
+    expected_response = {"id": "vs_1", "object": "vector_store"}
+    mock_acreate = AsyncMock(return_value=expected_response)
+    # avector_store_create(model=None) resolves acreate via a local import at
+    # call time, so patching after Router construction works here.
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt-3.5-turbo",
+                "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+            }
+        ]
+    )
+    with patch("litellm.vector_stores.main.acreate", new=mock_acreate):  # test-quality-ok: the SDK call is the only place a leaked router kwarg would surface
+        create_response = await router.avector_store_create(model=None, custom_llm_provider="openai")
+
+    assert create_response is expected_response
+    mock_acreate.assert_awaited_once()
+    assert "router" not in mock_acreate.await_args.kwargs
+
+
+def test_vector_store_search_injects_router():
+    """
+    Sync parity for the router injection: router.vector_store_search must pass
+    the router down to the SDK search call so provider transforms can resolve
+    router-managed embedding models, same as avector_store_search.
+    """
+    from litellm.types.vector_stores import VectorStoreSearchResponse
+
+    expected_response = VectorStoreSearchResponse(
+        object="vector_store.search_results.page", search_query="q", data=[]
+    )
+    mock_search = MagicMock(return_value=expected_response)
+    # Router.__init__ binds search via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.search", new=mock_search):  # test-quality-ok: the SDK call is the only place the injected router kwarg is observable
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        search_response = router.vector_store_search(
+            vector_store_id="v", query="q", custom_llm_provider="s3_vectors"
+        )
+
+    assert search_response is expected_response
+    mock_search.assert_called_once()
+    assert mock_search.call_args.kwargs["router"] is router
+    assert mock_search.call_args.kwargs["custom_llm_provider"] == "s3_vectors"
+
+
+def test_vector_store_create_does_not_inject_router():
+    """The sync create path must keep calling the SDK without a router kwarg."""
+    expected_response = {"id": "vs_1", "object": "vector_store"}
+    mock_create = MagicMock(return_value=expected_response)
+    # Router.__init__ binds create via a local import, so patch the module
+    # attribute before constructing the Router.
+    with patch("litellm.vector_stores.main.create", new=mock_create):  # test-quality-ok: the SDK call is the only place a leaked router kwarg would surface
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {"model": "openai/gpt-3.5-turbo", "api_key": "test-key"},
+                }
+            ]
+        )
+        create_response = router.vector_store_create(custom_llm_provider="openai")
+
+    assert create_response is expected_response
+    mock_create.assert_called_once()
+    assert "router" not in mock_create.call_args.kwargs
+
+
 class TestPreRoutingStrategyRegistryLifecycle:
     """
     Regression tests: a deployment leaving the model_list must release the
@@ -8155,6 +8418,71 @@ class TestUpsertDeploymentRollback:
         assert len(router.model_list) == 1
 
 
+class TestUpsertDeploymentRename:
+    """
+    Issue #38360: renaming a model wrote the new `model_name` to the db, but the reload's
+    `upsert_deployment` compared only `litellm_params` and `model_info`. A rename with no
+    other edit therefore compared equal and the router kept the old name until a restart,
+    so `/model/info` and `/v1/models` served the stale name and the new one was unroutable.
+    """
+
+    @staticmethod
+    def _router() -> "litellm.Router":
+        return litellm.Router(
+            model_list=[
+                {
+                    "model_name": "old-name",
+                    "litellm_params": {"model": "openai/gpt-4o", "api_key": "sk-test"},
+                    "model_info": {"id": "rename-1", "db_model": True},
+                }
+            ]
+        )
+
+    @staticmethod
+    def _deployment(model_name: str, tpm: int | None = None):
+        from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo
+
+        return Deployment(
+            model_name=model_name,
+            litellm_params=LiteLLM_Params(model="openai/gpt-4o", api_key="sk-test", tpm=tpm),
+            model_info=ModelInfo(id="rename-1", db_model=True),
+        )
+
+    def test_rename_only_updates_the_router(self):
+        router = self._router()
+
+        assert router.upsert_deployment(deployment=self._deployment("new-name")) is not None
+
+        assert [model["model_name"] for model in router.model_list] == ["new-name"]
+        renamed = router.get_deployment(model_id="rename-1")
+        assert renamed is not None
+        assert renamed.model_name == "new-name"
+
+    def test_rename_only_makes_the_new_name_routable(self):
+        router = self._router()
+
+        router.upsert_deployment(deployment=self._deployment("new-name"))
+
+        assert router.get_model_ids(model_name="new-name") == ["rename-1"]
+        assert router.get_model_ids(model_name="old-name") == []
+
+    def test_rename_alongside_another_edit_still_updates(self):
+        router = self._router()
+
+        router.upsert_deployment(deployment=self._deployment("new-name", tpm=1234))
+
+        assert router.get_model_ids(model_name="new-name") == ["rename-1"]
+        renamed = router.get_deployment(model_id="rename-1")
+        assert renamed is not None
+        assert renamed.litellm_params.tpm == 1234
+
+    def test_unchanged_deployment_is_still_a_no_op(self):
+        router = self._router()
+
+        assert router.upsert_deployment(deployment=self._deployment("old-name")) is None
+        assert [model["model_name"] for model in router.model_list] == ["old-name"]
+
+
 class TestConsumedRequestTagsStamp:
     """Issue #36621: when a request's tags select a tagged pre-routing strategy, those
     tags are consumed by the selection; the hook must stamp the rewritten model group so
@@ -8251,6 +8579,398 @@ class TestConsumedRequestTagsStamp:
         assert CONSUMED_REQUEST_TAGS_METADATA_KEY not in request_kwargs["metadata"]
 
 
+class TestClaudeCodeSubagentSessionRouterBinding:
+    class _RewriteStrategy:
+        def __init__(self, routed_model: str = "cheap-model") -> None:
+            self.routed_model = routed_model
+
+        async def async_pre_routing_hook(
+            self, model, request_kwargs, messages=None, input=None, specific_deployment=False
+        ):
+            from litellm.types.router import PreRoutingHookResponse
+
+            return PreRoutingHookResponse(
+                model=self.routed_model,
+                messages=messages,
+                routing_decision={
+                    "router_model_name": "smart-router",
+                    "router_type": "complexity",
+                    "routed_model": self.routed_model,
+                    "cause": "heuristic_scorer",
+                },
+            )
+
+    @classmethod
+    def _router(
+        cls,
+        cheap_response: str = "cheap response",
+        fallbacks: list[dict[str, list[str]]] | None = None,
+    ) -> "litellm.Router":
+        from litellm.types.router import TaggedPreRoutingStrategy
+
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "cheap-model",
+                    "litellm_params": {"model": "openai/gpt-4o-mini", "mock_response": cheap_response},
+                },
+                {
+                    "model_name": "expensive-model",
+                    "litellm_params": {"model": "openai/gpt-4o", "mock_response": "expensive response"},
+                },
+            ],
+            fallbacks=fallbacks,
+            num_retries=0,
+        )
+        router.complexity_routers = {
+            "smart-router": (TaggedPreRoutingStrategy(tags=(), strategy=cls._RewriteStrategy()),),
+            "premium-router": (TaggedPreRoutingStrategy(tags=(), strategy=cls._RewriteStrategy("expensive-model")),),
+        }
+        return router
+
+    @staticmethod
+    def _request_kwargs(
+        *,
+        key_hash: str = "key-hash-a",
+        app: str = "cli",
+        agent_id: str | None = None,
+        fallback_depth: int | None = None,
+    ) -> dict:
+        headers = {
+            "X-Claude-Code-Session-Id": "session-1234",
+            "x-app": app,
+            **({"x-claude-code-agent-id": agent_id} if agent_id is not None else {}),
+        }
+        return {
+            "metadata": {"user_api_key_hash": key_hash},
+            "proxy_server_request": {"headers": headers},
+            **({"fallback_depth": fallback_depth} if fallback_depth is not None else {}),
+        }
+
+    @pytest.mark.asyncio
+    async def test_subagent_concrete_model_uses_the_main_sessions_router(self):
+        router = self._router()
+
+        await router.acompletion(
+            model="smart-router",
+            messages=[{"role": "user", "content": "main turn"}],
+            **self._request_kwargs(),
+        )
+        subagent_kwargs = self._request_kwargs(agent_id="agent-1234")
+
+        response = await router.acompletion(
+            model="expensive-model",
+            messages=[{"role": "user", "content": "subagent turn"}],
+            **subagent_kwargs,
+        )
+
+        assert response.choices[0].message.content == "cheap response"
+        assert subagent_kwargs["metadata"]["model_group"] == "smart-router"
+        assert subagent_kwargs["metadata"]["routing_decision"]["router_model_name"] == "smart-router"
+
+    @pytest.mark.asyncio
+    async def test_main_thread_side_calls_to_a_plain_model_keep_the_session_router(self):
+        router = self._router()
+
+        await router.async_pre_routing_hook(model="smart-router", request_kwargs=self._request_kwargs())
+        await router.async_pre_routing_hook(model="expensive-model", request_kwargs=self._request_kwargs())
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert response is not None
+        assert response.model == "cheap-model"
+
+    @pytest.mark.asyncio
+    async def test_redis_cleanup_failure_does_not_reject_a_subagent_request(self):
+        from litellm.caching.caching import RedisCache
+
+        router = self._router()
+        del router.complexity_routers["smart-router"]
+        redis_cache = MagicMock(spec=RedisCache)
+        redis_cache.async_get_cache = AsyncMock(return_value="smart-router")
+        redis_cache.async_delete_cache = AsyncMock(side_effect=ConnectionError("redis unavailable"))
+        router._update_redis_cache(cache=redis_cache)
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert response is None
+        redis_cache.async_delete_cache.assert_awaited_once()
+
+    @pytest.mark.asyncio
+    async def test_redis_read_failure_does_not_reject_a_subagent_request(self):
+        from litellm.caching.caching import RedisCache
+
+        router = self._router()
+        request_kwargs = self._request_kwargs(agent_id="agent-1234")
+        cache_key = router._claude_code_session_router_cache_key(request_kwargs)
+        assert cache_key is not None
+        await router._claude_code_session_router_cache.in_memory_cache.async_set_cache(
+            cache_key,
+            "smart-router",
+        )
+        redis_cache = MagicMock(spec=RedisCache)
+        redis_cache.async_get_cache = AsyncMock(side_effect=Exception("Redis circuit breaker is open"))
+        router._update_redis_cache(cache=redis_cache)
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=request_kwargs,
+        )
+
+        assert response is None
+        assert "model_group" not in request_kwargs["metadata"]
+        redis_cache.async_get_cache.assert_awaited_once()
+
+    @pytest.mark.asyncio
+    async def test_redis_write_failures_do_not_reject_main_or_subagent_requests(self):
+        from litellm.caching.caching import RedisCache
+
+        router = self._router()
+        redis_cache = MagicMock(spec=RedisCache)
+        redis_cache.async_get_cache = AsyncMock(return_value="smart-router")
+        redis_cache.async_set_cache = AsyncMock(side_effect=Exception("redis unavailable"))
+        router._update_redis_cache(cache=redis_cache)
+
+        main_response = await router.async_pre_routing_hook(
+            model="smart-router",
+            request_kwargs=self._request_kwargs(),
+        )
+        subagent_response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert main_response is not None
+        assert main_response.model == "cheap-model"
+        assert subagent_response is not None
+        assert subagent_response.model == "cheap-model"
+        assert redis_cache.async_set_cache.await_count == 2
+
+    @pytest.mark.asyncio
+    async def test_subagents_follow_the_main_threads_latest_router_across_workers(self):
+        from types import SimpleNamespace
+
+        from litellm.caching.caching import RedisCache
+
+        shared_binding = SimpleNamespace(value=None)
+        shared_redis = MagicMock(spec=RedisCache)
+        shared_redis.async_get_cache = AsyncMock(side_effect=lambda key, **_: shared_binding.value)
+        shared_redis.async_set_cache = AsyncMock(
+            side_effect=lambda key, value, **_: setattr(shared_binding, "value", value)
+        )
+        main_worker, subagent_worker = self._router(), self._router()
+        main_worker._update_redis_cache(cache=shared_redis)
+        subagent_worker._update_redis_cache(cache=shared_redis)
+
+        await main_worker.async_pre_routing_hook(model="smart-router", request_kwargs=self._request_kwargs())
+        first = await subagent_worker.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+        await main_worker.async_pre_routing_hook(model="premium-router", request_kwargs=self._request_kwargs())
+        second = await subagent_worker.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert first is not None
+        assert first.model == "cheap-model"
+        assert second is not None
+        assert second.model == "expensive-model"
+        assert shared_binding.value == "premium-router"
+
+    @pytest.mark.asyncio
+    async def test_no_pre_routing_strategies_means_no_session_cache_traffic(self):
+        from litellm.caching.caching import RedisCache
+
+        router = self._router()
+        router.complexity_routers.clear()
+        redis_cache = MagicMock(spec=RedisCache)
+        redis_cache.async_get_cache = AsyncMock(return_value=None)
+        redis_cache.async_set_cache = AsyncMock()
+        redis_cache.async_delete_cache = AsyncMock()
+        router._update_redis_cache(cache=redis_cache)
+
+        for request_kwargs in (self._request_kwargs(), self._request_kwargs(agent_id="agent-1234")):
+            response = await router.async_pre_routing_hook(model="expensive-model", request_kwargs=request_kwargs)
+            assert response is None
+
+        redis_cache.async_get_cache.assert_not_awaited()
+        redis_cache.async_set_cache.assert_not_awaited()
+        redis_cache.async_delete_cache.assert_not_awaited()
+
+    @pytest.mark.asyncio
+    async def test_session_bindings_do_not_evict_router_rate_limit_state(self):
+        router = self._router()
+        assert router._update_usage(deployment_id="deployment-id", parent_otel_span=None) == 1
+
+        for session_index in range(201):
+            request_kwargs = self._request_kwargs()
+            request_kwargs["proxy_server_request"]["headers"]["X-Claude-Code-Session-Id"] = (
+                f"session-{session_index:04d}"
+            )
+            await router.async_pre_routing_hook(model="smart-router", request_kwargs=request_kwargs)
+
+        assert router._update_usage(deployment_id="deployment-id", parent_otel_span=None) == 2
+
+    @pytest.mark.asyncio
+    async def test_background_and_fallback_requests_do_not_clear_the_session_router(self):
+        router = self._router()
+
+        await router.async_pre_routing_hook(model="smart-router", request_kwargs=self._request_kwargs())
+        await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(app="cli-bg"),
+        )
+        await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(fallback_depth=1),
+        )
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert response is not None
+        assert response.model == "cheap-model"
+
+    @pytest.mark.asyncio
+    async def test_subagent_fallback_does_not_reapply_the_session_router(self):
+        router = self._router()
+
+        await router.async_pre_routing_hook(model="smart-router", request_kwargs=self._request_kwargs())
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(agent_id="agent-1234", fallback_depth=1),
+        )
+
+        assert response is None
+
+    @pytest.mark.asyncio
+    async def test_subagent_can_fallback_to_its_original_requested_model(self):
+        router = self._router(
+            cheap_response="litellm.RateLimitError",
+            fallbacks=[{"cheap-model": ["expensive-model"]}],
+        )
+
+        await router.acompletion(
+            model="smart-router",
+            messages=[{"role": "user", "content": "main turn"}],
+            **self._request_kwargs(),
+        )
+        subagent_kwargs = self._request_kwargs(agent_id="agent-1234")
+
+        response = await router.acompletion(
+            model="expensive-model",
+            messages=[{"role": "user", "content": "subagent turn"}],
+            **subagent_kwargs,
+        )
+
+        assert response.choices[0].message.content == "expensive response"
+        assert subagent_kwargs["metadata"]["routing_decision"]["routed_model"] == "cheap-model"
+
+    @pytest.mark.asyncio
+    async def test_subagent_can_use_the_bound_router_name_fallback(self):
+        router = self._router(
+            cheap_response="litellm.RateLimitError",
+            fallbacks=[{"smart-router": ["expensive-model"]}],
+        )
+
+        await router.acompletion(
+            model="smart-router",
+            messages=[{"role": "user", "content": "main turn"}],
+            **self._request_kwargs(),
+        )
+
+        response = await router.acompletion(
+            model="expensive-model",
+            messages=[{"role": "user", "content": "subagent turn"}],
+            **self._request_kwargs(agent_id="agent-1234"),
+        )
+
+        assert response.choices[0].message.content == "expensive response"
+
+    @pytest.mark.asyncio
+    async def test_anthropic_subagent_four_fallback_hops_use_each_current_model_chain(self):
+        from litellm.types.router import TaggedPreRoutingStrategy
+
+        failing_groups = ("cheap-model", "fallback-1", "fallback-2", "fallback-3")
+        router = litellm.Router(
+            model_list=[
+                *(
+                    {
+                        "model_name": group,
+                        "litellm_params": {
+                            "model": "anthropic/claude-3-haiku-20240307",
+                            "mock_response": "litellm.RateLimitError",
+                        },
+                    }
+                    for group in failing_groups
+                ),
+                {
+                    "model_name": "requested-model",
+                    "litellm_params": {
+                        "model": "anthropic/claude-3-haiku-20240307",
+                        "mock_response": "requested response",
+                    },
+                },
+                {
+                    "model_name": "fallback-4",
+                    "litellm_params": {
+                        "model": "anthropic/claude-3-haiku-20240307",
+                        "mock_response": "fourth fallback response",
+                    },
+                },
+            ],
+            fallbacks=[
+                {"smart-router": ["fallback-1"]},
+                {"fallback-1": ["fallback-2"]},
+                {"fallback-2": ["fallback-3"]},
+                {"fallback-3": ["fallback-4"]},
+            ],
+            num_retries=0,
+            max_fallbacks=4,
+        )
+        router.complexity_routers = {
+            "smart-router": (TaggedPreRoutingStrategy(tags=(), strategy=self._RewriteStrategy()),)
+        }
+        main_kwargs = self._request_kwargs()
+        main_kwargs["litellm_metadata"] = main_kwargs.pop("metadata")
+        await router.async_pre_routing_hook(model="smart-router", request_kwargs=main_kwargs)
+        subagent_kwargs = self._request_kwargs(agent_id="agent-1234")
+        subagent_kwargs["litellm_metadata"] = subagent_kwargs.pop("metadata")
+
+        response = await router.aanthropic_messages(
+            model="requested-model",
+            messages=[{"role": "user", "content": "subagent turn"}],
+            max_tokens=64,
+            **subagent_kwargs,
+        )
+
+        assert response["content"][0]["text"] == "fourth fallback response"
+
+    @pytest.mark.asyncio
+    async def test_session_router_binding_is_scoped_to_the_authenticated_key(self):
+        router = self._router()
+
+        await router.async_pre_routing_hook(model="smart-router", request_kwargs=self._request_kwargs())
+
+        response = await router.async_pre_routing_hook(
+            model="expensive-model",
+            request_kwargs=self._request_kwargs(key_hash="key-hash-b", agent_id="agent-1234"),
+        )
+
+        assert response is None
+
+
 class TestAutoRouterMaxInputCharsWiring:
     """`auto_router_max_input_chars` on the deployment has to reach the AutoRouter that embeds prompts.
 
@@ -11530,3 +12250,190 @@ class TestTierParamsTheTargetAccepts:
         accepted = router._tier_params_the_target_accepts("no-such-group", {"reasoning_effort": "max"}, {})
 
         assert accepted == {"reasoning_effort": "max"}
+
+
+class TestPreRoutingTierDrivesFallbacks:
+    """#38832: a complexity/auto router picks a tier behind the router name, but fallback
+    lookup stayed on the router name, so the tier's configured chain never ran and a
+    provider failure on the tier's first hop was returned to the client."""
+
+    class _TierRouter(litellm.Router):
+        async def async_pre_routing_hook(
+            self, model, request_kwargs, messages=None, input=None, specific_deployment=False
+        ):
+            from litellm.types.router import PreRoutingHookResponse
+
+            if model == "smart-router":
+                return PreRoutingHookResponse(model="tier1", messages=messages)
+            return None
+
+    @classmethod
+    def _router(cls, fallbacks) -> "litellm.Router":
+        return cls._TierRouter(
+            model_list=[
+                {
+                    "model_name": "smart-router",
+                    "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-x"},
+                },
+                {
+                    "model_name": "tier1",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+                {
+                    "model_name": "backup-a",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "from backup-a",
+                    },
+                },
+                {
+                    "model_name": "backup-b",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "from backup-b",
+                    },
+                },
+                {
+                    "model_name": "failing-backup",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+                {
+                    "model_name": "plain",
+                    "litellm_params": {
+                        "model": "openai/gpt-4o-mini",
+                        "api_key": "sk-x",
+                        "mock_response": "litellm.RateLimitError",
+                    },
+                },
+            ],
+            fallbacks=fallbacks,
+            num_retries=0,
+        )
+
+    @pytest.mark.asyncio
+    async def test_the_selected_tier_fallback_chain_runs(self):
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        response = await router.acompletion(
+            model="smart-router", messages=[{"role": "user", "content": "hi"}]
+        )
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_chain_keyed_on_the_router_name_is_not_used(self):
+        """The router name has no chain of its own, so nothing should rescue this call."""
+        router = self._router([{"tier2": ["backup-a"]}])
+
+        with pytest.raises(litellm.RateLimitError):
+            await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+    @pytest.mark.asyncio
+    async def test_a_chain_keyed_on_the_router_name_rescues_when_no_tier_chain_exists(self):
+        """The documented contract: configs keyed on the requested name keep working behind auto-routers."""
+        router = self._router([{"smart-router": ["backup-a"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_the_tier_chain_wins_over_the_router_name_chain(self):
+        router = self._router([{"tier1": ["backup-a"]}, {"smart-router": ["backup-b"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_request_without_a_pre_routing_hook_still_uses_its_own_group(self):
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        response = await router.acompletion(
+            model="tier1", messages=[{"role": "user", "content": "hi"}]
+        )
+
+        assert response.choices[0].message.content == "from backup-a"
+
+    @pytest.mark.asyncio
+    async def test_a_caller_cannot_pick_the_chain_by_sending_the_selection(self):
+        """The metadata bucket carries caller-supplied keys, so only the hook may set the tier."""
+        router = self._router([{"tier1": ["backup-a"]}])
+
+        with pytest.raises(litellm.RateLimitError):
+            await router.acompletion(
+                model="plain",
+                messages=[{"role": "user", "content": "hi"}],
+                metadata={"pre_routing_selected_model": "tier1"},
+            )
+
+    @pytest.mark.asyncio
+    async def test_each_fallback_hop_resolves_its_own_chain(self):
+        """The second hop must key off the group it is running, not the tier that failed."""
+        router = self._router([{"tier1": ["failing-backup"]}, {"failing-backup": ["backup-b"]}])
+
+        response = await router.acompletion(model="smart-router", messages=[{"role": "user", "content": "hi"}])
+
+        assert response.choices[0].message.content == "from backup-b"
+
+
+@pytest.mark.asyncio
+async def test_prompt_management_factory_marks_injection_for_every_deployment(monkeypatch):
+    """The factory stamps a provisional deployment's model_info into kwargs before the
+    prompt pass runs, then routes on the returned model, so any deployment can end up
+    billed. An injection recorded there must carry the every-deployment sentinel, never
+    the provisional deployment's id, or a differently-billed deployment loses the credit."""
+    import time
+
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "cached-claude",
+                "litellm_params": {
+                    "model": "anthropic_cache_control_hook/claude-sonnet-5",
+                    "prompt_id": "cache-points",
+                },
+                "model_info": {"id": "provisional-dep"},
+            }
+        ]
+    )
+    captured: dict = {}
+
+    async def _capture_acompletion(**kwargs):
+        captured.update(kwargs)
+        return litellm.ModelResponse()
+
+    monkeypatch.setattr(litellm, "acompletion", _capture_acompletion)
+    logging_obj = LiteLLMLogging(
+        model="cached-claude",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=False,
+        call_type="acompletion",
+        start_time=time.time(),
+        litellm_call_id="lit-6445",
+        function_id="f",
+    )
+    await router.acompletion(
+        model="cached-claude",
+        messages=[
+            {"role": "system", "content": "a static system prompt"},
+            {"role": "user", "content": "hi"},
+        ],
+        cache_control_injection_points=[{"location": "message", "role": "system"}],
+        litellm_logging_obj=logging_obj,
+    )
+    bucket = captured.get("litellm_metadata") or captured["metadata"]
+    assert captured["model_info"]["id"] == "provisional-dep"
+    assert bucket["litellm_gateway_injected_cache"] == ""
diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index b580b03574e..30b265905f3 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -538,6 +538,157 @@ def test_inherit_builtin_cache_pricing_noop_for_unknown_backend():
     assert model_info == {"input_cost_per_token": 0.000003}
 
 
+def test_inherit_builtin_base_rates_for_off_peak_fills_missing_rates():
+    """Direct unit test of the helper: an entry carrying only an
+    off_peak_pricing block inherits the backend model's built-in base token
+    rates, so cost lookup via the deployment id can bill standard rates
+    outside the windows.
+    """
+    backend_model = "gpt-4o-mini"
+    builtin_info = litellm.get_model_info(model=backend_model, custom_llm_provider="openai")
+    off_peak_block = {
+        "hours_utc": "00:00-00:00",
+        "input_cost_per_token": 5e-07,
+        "output_cost_per_token": 1e-06,
+    }
+    model_info = {"off_peak_pricing": off_peak_block}
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="openai",
+    )
+
+    assert model_info["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+    assert model_info["output_cost_per_token"] == builtin_info["output_cost_per_token"]
+    assert model_info["off_peak_pricing"] == off_peak_block
+
+
+def test_inherit_builtin_base_rates_for_off_peak_carries_threshold_rates():
+    """A backend with above-threshold pricing hands the whole rate structure to
+    the deployment entry, so peak-hour billing of large prompts through that
+    entry matches the shared backend entry instead of flattening to the base
+    rate.
+    """
+    backend_model = "gemini/gemini-2.5-pro"
+    builtin_info = litellm.get_model_info(model=backend_model)
+    assert builtin_info["input_cost_per_token_above_200k_tokens"] is not None
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="gemini",
+    )
+
+    assert model_info["input_cost_per_token"] == builtin_info["input_cost_per_token"]
+    assert (
+        model_info["input_cost_per_token_above_200k_tokens"]
+        == builtin_info["input_cost_per_token_above_200k_tokens"]
+    )
+    assert (
+        model_info["output_cost_per_token_above_200k_tokens"]
+        == builtin_info["output_cost_per_token_above_200k_tokens"]
+    )
+
+
+def test_inherit_builtin_base_rates_for_off_peak_carries_companion_billing_fields():
+    """Billing rules that are not literal cost rates, like the web search
+    billing unit, must ride along, or grounding and regional uplifts would
+    bill differently through the deployment entry than through the shared
+    backend entry.
+    """
+    backend_model = "gemini-3-pro-image"
+    raw_entry = litellm.model_cost[backend_model]
+    assert raw_entry.get("web_search_billing_unit") is not None
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider=None,
+    )
+
+    assert model_info["web_search_billing_unit"] == raw_entry["web_search_billing_unit"]
+    assert model_info["input_cost_per_token"] == raw_entry["input_cost_per_token"]
+
+
+def test_inherit_builtin_base_rates_for_off_peak_tiered_only_backend_stores_no_zero():
+    """A tiered-only backend has no flat token rates; get_model_info synthesizes
+    zeros for them, and storing those would mark the deployment explicitly
+    priced free. The tier table itself must carry over as an isolated copy so
+    mutating the deployment entry never touches the shared cost map.
+    """
+    backend_model = "dashscope/qwen-flash"
+    raw_tiers = litellm.model_cost[backend_model]["tiered_pricing"]
+
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model=backend_model,
+        custom_llm_provider="dashscope",
+    )
+
+    assert model_info.get("input_cost_per_token") != 0
+    assert model_info.get("output_cost_per_token") != 0
+    assert model_info["tiered_pricing"] == raw_tiers
+    assert model_info["tiered_pricing"] is not raw_tiers
+    assert model_info["tiered_pricing"][0] is not raw_tiers[0]
+
+    original_first_tier = copy.deepcopy(raw_tiers[0])
+    model_info["tiered_pricing"][0]["input_cost_per_token"] = 123.0
+    assert raw_tiers[0] == original_first_tier
+
+
+def test_inherit_builtin_base_rates_for_off_peak_leaves_explicit_rates_alone():
+    """An entry that sets its own base rate beside the block already counts as
+    a full custom pricing entry; the helper must not mix builtin rates into it.
+    """
+    model_info = {
+        "off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07},
+        "input_cost_per_token": 3e-06,
+    }
+
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=model_info,
+        backend_model="gpt-4o-mini",
+        custom_llm_provider="openai",
+    )
+
+    assert model_info["input_cost_per_token"] == 3e-06
+    assert "output_cost_per_token" not in model_info
+
+
+def test_inherit_builtin_base_rates_for_off_peak_noop_without_block_or_backend():
+    """Nothing happens without an off_peak_pricing block, and an unmapped
+    backend model leaves the entry unchanged rather than raising.
+    """
+    plain_info = {"id": "dep-1"}
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=plain_info,
+        backend_model="gpt-4o-mini",
+        custom_llm_provider="openai",
+    )
+    assert plain_info == {"id": "dep-1"}
+
+    off_peak_info = {"off_peak_pricing": {"hours_utc": "00:00-00:00", "input_cost_per_token": 5e-07}}
+    Router._inherit_builtin_base_rates_for_off_peak(
+        model_info=off_peak_info,
+        backend_model="this-backend-model-does-not-exist-x9y8z7",
+        custom_llm_provider=None,
+    )
+    assert "input_cost_per_token" not in off_peak_info
+
+
 def test_custom_pricing_field_denylist_covers_all_builtin_pricing_fields():
     """The shared-backend-key stripping in Router relies on
     CustomPricingLiteLLMParams enumerating every per-deployment pricing field.
@@ -2130,3 +2281,83 @@ def test_every_declaring_deployment_is_named(caplog):
     assert "azure-ptu-east" in warnings[0]
     assert "azure-ptu-west" in warnings[0]
     assert "plain-gpt-4o" not in warnings[0]
+
+
+def _simulate_price_data_reload_with_provider_sets(monkeypatch, fetched_catalog):
+    """Like `_simulate_price_data_reload`, plus the provider model-set refresh the proxy's
+    `_swap_in_model_cost_map` does before replaying, so bare names in the new catalog resolve."""
+    monkeypatch.setattr(litellm, "model_cost", fetched_catalog)
+    _invalidate_model_cost_lowercase_map()
+    litellm.add_known_models(model_cost_map=fetched_catalog)
+    reapply_runtime_model_cost_registrations()
+
+
+def test_a_config_deployment_dropped_by_a_stale_cost_map_comes_back_on_reload(monkeypatch):
+    """
+    Booting on the bundled backup, a bare model that only the remote catalog knows
+    cannot be provider-resolved, so the proxy router (ignore_invalid_deployments) drops
+    it. Once a reload brings in a catalog that knows the model, the deployment must be
+    served again with its access groups, and exactly once however many reloads follow.
+    """
+    backend = "lit-5766-only-in-remote-catalog"
+    try:
+        router = Router(
+            model_list=[
+                {
+                    "model_name": "new-model",
+                    "litellm_params": {"model": backend, "api_key": "k"},
+                    "model_info": {"id": "new-id", "access_groups": ["team-models"]},
+                },
+                {
+                    "model_name": "control-model",
+                    "litellm_params": {"model": "hosted_vllm/control-backend", "api_key": "k"},
+                    "model_info": {"id": "control-id", "access_groups": ["team-models"]},
+                },
+            ],
+            ignore_invalid_deployments=True,
+        )
+        assert router.get_model_names() == ["control-model"]
+        assert router.get_model_access_groups(model_name="new-model") == {}
+
+        fresh_catalog = {**litellm.model_cost, backend: {"litellm_provider": "openai", "mode": "chat"}}
+        _simulate_price_data_reload_with_provider_sets(monkeypatch, fresh_catalog)
+        _simulate_price_data_reload_with_provider_sets(monkeypatch, fresh_catalog)
+
+        assert sorted(router.get_model_names()) == ["control-model", "new-model"]
+        assert router.get_model_access_groups(model_name="new-model") == {"team-models": ["new-model"]}
+        assert [d["model_info"]["id"] for d in router.model_list] == ["control-id", "new-id"]
+        assert "new-id" in litellm.model_cost
+    finally:
+        litellm.open_ai_chat_completion_models.discard(backend)
+        litellm.models_by_provider["openai"].discard(backend)
+
+
+def test_a_config_deployment_dropped_for_a_permanent_reason_is_not_retried_on_reload(monkeypatch):
+    """
+    Only provider-resolution drops can be healed by a fresh catalog. A deployment that
+    fails after its provider resolved (here a pass-through vertex entry with no project)
+    has already touched router state, so replaying it on every reload would leak into
+    `deployment_names` each time.
+    """
+    router = Router(
+        model_list=[
+            {
+                "model_name": "vertex-passthrough",
+                "litellm_params": {"model": "vertex_ai/gemini-2.5-flash", "use_in_pass_through": True},
+                "model_info": {"id": "vertex-id"},
+            },
+            {
+                "model_name": "control-model",
+                "litellm_params": {"model": "hosted_vllm/control-backend", "api_key": "k"},
+                "model_info": {"id": "control-id"},
+            },
+        ],
+        ignore_invalid_deployments=True,
+    )
+    assert router.get_model_names() == ["control-model"]
+    names_after_boot = list(router.deployment_names)
+
+    _simulate_price_data_reload_with_provider_sets(monkeypatch, dict(litellm.model_cost))
+
+    assert router.get_model_names() == ["control-model"]
+    assert router.deployment_names == names_after_boot
diff --git a/tests/test_litellm/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index 7743cb005d0..fde870e5abe 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -6,12 +6,19 @@ should be tried first, and higher order deployments should be used as fallbacks
 when lower order deployments fail.
 """
 
-from typing import Optional
+import json
+from typing import Final, Optional
 
+import httpx
 import pytest
+from openai import AsyncOpenAI
 
+import litellm
 from litellm import Router
-from litellm.utils import _get_order_filtered_deployments
+from litellm.integrations.custom_logger import CustomLogger
+from litellm.router_utils.prompt_caching_cache import PromptCachingCache
+from litellm.types.router import RouterRateLimitError
+from litellm.utils import _get_deployment_order, _get_order_filtered_deployments
 
 # ---------------------------------------------------------------------------
 # Unit tests for _get_order_filtered_deployments
@@ -49,13 +56,22 @@ class TestGetOrderFilteredDeployments:
         assert len(result) == 1
         assert result[0]["model_info"]["id"] == "b"
 
-    def test_target_order_no_match_returns_all(self):
+    def test_target_order_no_match_returns_empty(self):
         deps = [
             self._make_deployment(1, "a"),
             self._make_deployment(2, "b"),
         ]
         result = _get_order_filtered_deployments(deps, target_order=99)
-        assert len(result) == 2
+        assert result == []
+
+    def test_target_order_no_match_does_not_reselect_lower_order(self):
+        deps = [
+            self._make_deployment(1, "a"),
+            self._make_deployment(2, "b"),
+        ]
+        remaining_after_pre_call = [deps[0]]
+        result = _get_order_filtered_deployments(remaining_after_pre_call, target_order=2)
+        assert result == []
 
     def test_no_order_set_returns_all(self):
         deps = [
@@ -406,35 +422,239 @@ async def test_router_order_fallback_with_hidden_model_group_alias():
     assert response._hidden_params["model_id"] == "2"
 
 
+@pytest.mark.asyncio
+async def test_router_order_fallback_does_not_reselect_order_1_when_order_2_is_filtered_out():
+    class _DropOrder2(CustomLogger):
+        async def async_filter_deployments(
+            self, model, healthy_deployments, messages, request_kwargs=None, parent_otel_span=None
+        ):
+            return [d for d in healthy_deployments if _get_deployment_order(d) != 2]
+
+    drop_order_2: Final = _DropOrder2()
+    router = Router(
+        model_list=[
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "key",
+                    "mock_response": "litellm.RateLimitError",
+                    "order": 1,
+                },
+                "model_info": {"id": "1"},
+            },
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "key",
+                    "mock_response": "success from order 2",
+                    "order": 2,
+                },
+                "model_info": {"id": "2"},
+            },
+        ],
+        num_retries=0,
+    )
+    litellm.callbacks.append(drop_order_2)
+    try:
+        with pytest.raises(RouterRateLimitError, match="No deployments available") as exc_info:
+            await router.acompletion(
+                model="test-model",
+                messages=[{"role": "user", "content": "hi"}],
+            )
+        assert "success from order 2" not in str(exc_info.value)
+    finally:
+        litellm.callbacks.remove(drop_order_2)
+
+
+@pytest.mark.asyncio
+async def test_router_order_fallback_ignores_prompt_cache_pin_on_target_order():
+    messages = [{"role": "user", "content": "word " * 5000}]
+    router = Router(
+        model_list=[
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "bad",
+                    "mock_response": Exception("azure peak load"),
+                    "order": 1,
+                },
+                "model_info": {"id": "1"},
+            },
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "good",
+                    "mock_response": "success from order 2",
+                    "order": 2,
+                },
+                "model_info": {"id": "2"},
+            },
+        ],
+        num_retries=0,
+        optional_pre_call_checks=["prompt_caching"],
+    )
+    await PromptCachingCache(cache=router.cache).async_add_model_id(
+        model_id="1",
+        messages=messages,
+        tools=None,
+    )
+    response = await router.acompletion(model="test-model", messages=messages)
+    assert response._hidden_params["model_id"] == "2"
+
+
+@pytest.mark.asyncio
+async def test_router_order_fallback_retries_keep_target_order():
+    seen_target_orders: Final = []
+
+    class _RecordTargetOrder(CustomLogger):
+        async def async_filter_deployments(
+            self, model, healthy_deployments, messages, request_kwargs=None, parent_otel_span=None
+        ):
+            seen_target_orders.append((request_kwargs or {}).get("_target_order"))
+            return healthy_deployments
+
+    recorder: Final = _RecordTargetOrder()
+    router = Router(
+        model_list=[
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "bad",
+                    "mock_response": Exception("fail order 1"),
+                    "order": 1,
+                },
+                "model_info": {"id": "1"},
+            },
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "gpt-4o",
+                    "api_key": "bad",
+                    "mock_response": Exception("fail order 2"),
+                    "order": 2,
+                },
+                "model_info": {"id": "2"},
+            },
+        ],
+        num_retries=1,
+    )
+    litellm.callbacks.append(recorder)
+    try:
+        with pytest.raises(Exception, match="fail order 2"):
+            await router.acompletion(
+                model="test-model",
+                messages=[{"role": "user", "content": "hi"}],
+            )
+    finally:
+        litellm.callbacks.remove(recorder)
+    assert seen_target_orders.count(2) >= 2
+
+
+@pytest.mark.asyncio
+async def test_generic_api_call_strips_target_order_from_provider_kwargs():
+    captured: Final = {}
+
+    async def _fake_provider(**provider_kwargs):
+        captured.update(provider_kwargs)
+        return "ok"
+
+    router = Router(
+        model_list=[
+            {
+                "model_name": "test-model",
+                "litellm_params": {"model": "gpt-4o", "api_key": "key", "order": 2},
+                "model_info": {"id": "2"},
+            },
+        ],
+    )
+    response = await router._ageneric_api_call_with_fallbacks_helper(
+        model="test-model",
+        original_generic_function=_fake_provider,
+        _target_order=2,
+        messages=[{"role": "user", "content": "hi"}],
+    )
+    assert response == "ok"
+    assert captured["model"] == "gpt-4o"
+    assert "_target_order" not in captured
+
+
+@pytest.mark.asyncio
+async def test_text_completion_order_fallback_hop_does_not_send_target_order_upstream():
+    upstream_bodies: Final[list[dict]] = []
+
+    def _upstream(request: httpx.Request) -> httpx.Response:
+        upstream_bodies.append(json.loads(request.content))
+        return httpx.Response(
+            200,
+            json={
+                "id": "cmpl-1",
+                "object": "text_completion",
+                "created": 0,
+                "model": "gpt-3.5-turbo-instruct",
+                "choices": [{"text": "ok from order 2", "index": 0, "logprobs": None, "finish_reason": "stop"}],
+                "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+            },
+        )
+
+    upstream_client: Final = AsyncOpenAI(
+        api_key="key",
+        base_url="http://upstream.test",
+        http_client=httpx.AsyncClient(transport=httpx.MockTransport(_upstream)),
+    )
+    router = Router(
+        model_list=[
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "text-completion-openai/gpt-3.5-turbo-instruct",
+                    "api_key": "key",
+                    "mock_response": Exception("fail order 1"),
+                    "order": 1,
+                },
+                "model_info": {"id": "1"},
+            },
+            {
+                "model_name": "test-model",
+                "litellm_params": {
+                    "model": "text-completion-openai/gpt-3.5-turbo-instruct",
+                    "api_key": "key",
+                    "api_base": "http://upstream.test",
+                    "order": 2,
+                },
+                "model_info": {"id": "2"},
+            },
+        ],
+        num_retries=0,
+    )
+    try:
+        response = await router.atext_completion(model="test-model", prompt="hi", client=upstream_client)
+    finally:
+        await upstream_client.close()
+
+    assert response._hidden_params["model_id"] == "2"
+    assert upstream_bodies
+    assert all("_target_order" not in body for body in upstream_bodies)
+
+
 def test_check_non_standard_fallback_format():
     from litellm.router_utils.fallback_event_handlers import (
         _check_non_standard_fallback_format,
     )
 
     # Standard formats
-    assert (
-        _check_non_standard_fallback_format([{"gpt-3.5-turbo": ["claude-3-haiku"]}])
-        == False
-    )
+    assert _check_non_standard_fallback_format([{"gpt-3.5-turbo": ["claude-3-haiku"]}]) == False
     assert _check_non_standard_fallback_format([{"model": ["qwen-backup"]}]) == False
-    assert (
-        _check_non_standard_fallback_format(
-            [{"model": ["qwen-backup"], "region": ["us-east-1"]}]
-        )
-        == False
-    )
+    assert _check_non_standard_fallback_format([{"model": ["qwen-backup"], "region": ["us-east-1"]}]) == False
 
     # Non-standard formats
     assert _check_non_standard_fallback_format([{"model": "qwen-backup"}]) == True
     assert (
-        _check_non_standard_fallback_format(
-            [{"model": "qwen-backup", "messages": [{"role": "user", "content": "hi"}]}]
-        )
-        == True
-    )
-    assert (
-        _check_non_standard_fallback_format(
-            [{"model": ["qwen-backup"], "api_key": "some-key"}]
-        )
+        _check_non_standard_fallback_format([{"model": "qwen-backup", "messages": [{"role": "user", "content": "hi"}]}])
         == True
     )
+    assert _check_non_standard_fallback_format([{"model": ["qwen-backup"], "api_key": "some-key"}]) == True
diff --git a/tests/test_litellm/test_router_retry_policy_update.py b/tests/test_litellm/test_router_retry_policy_update.py
index 1b98b8c1ae8..be568134763 100644
--- a/tests/test_litellm/test_router_retry_policy_update.py
+++ b/tests/test_litellm/test_router_retry_policy_update.py
@@ -21,6 +21,7 @@ This file pins both halves of the fix.
 
 import json
 from dataclasses import dataclass
+from typing import Final
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -28,8 +29,19 @@ from pydantic import ValidationError
 
 
 import litellm
+from litellm.router_strategy.budget_limiter import RouterBudgetLimiting
+from litellm.router_utils.pre_call_checks.model_rate_limit_check import ModelRateLimitingCheck
+from litellm.router_utils.pre_call_checks.prompt_caching_deployment_check import PromptCachingDeploymentCheck
 from litellm.types.router import RetryPolicy, UpdateRouterConfig
 
+
+@pytest.fixture(autouse=True)
+def isolate_litellm_callbacks():
+    callbacks_before: Final = litellm.callbacks.copy()
+    yield
+    litellm.callbacks = callbacks_before  # test-quality-ok: required callback-state restoration fixture
+
+
 # ---------------------------------------------------------------------------
 # UpdateRouterConfig schema membership (LIT-3152 part 1)
 # ---------------------------------------------------------------------------
@@ -100,6 +112,114 @@ def _build_router() -> litellm.Router:
     )
 
 
+def test_update_settings_adds_optional_pre_call_check_once():
+    router = _build_router()
+
+    router.update_settings(num_retries=7, optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    prompt_caching_callbacks = [
+        callback for callback in router.optional_callbacks if isinstance(callback, PromptCachingDeploymentCheck)
+    ]
+    assert len(prompt_caching_callbacks) == 1
+    assert router.num_retries == 7
+
+
+def test_update_settings_clears_omitted_toggleable_pre_call_checks():
+    router = _build_router()
+
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=[])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+
+
+def test_set_optional_pre_call_checks_reconciles_callback_types():
+    router = _build_router()
+
+    router.set_optional_pre_call_checks(["prompt_caching"])
+    router.set_optional_pre_call_checks([])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_removes_local_and_global_callbacks():
+    router = _build_router()
+
+    router.set_optional_pre_call_checks(["prompt_caching"])
+    router._remove_optional_callbacks_of_type(PromptCachingDeploymentCheck)
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_keeps_global_callback_for_another_router():
+    router_a = _build_router()
+    router_b = _build_router()
+
+    router_a.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router_b.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    router_a.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_a.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+    router_b.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_remove_optional_pre_call_check_keeps_global_callback_when_second_router_clears_first():
+    router_a = _build_router()
+    router_b = _build_router()
+
+    router_a.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router_b.update_settings(optional_pre_call_checks=["prompt_caching"])
+
+    router_b.update_settings(optional_pre_call_checks=[])
+
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in (router_a.optional_callbacks or []))
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in (router_b.optional_callbacks or []))
+    assert any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+    router_a.update_settings(optional_pre_call_checks=[])
+
+    assert not any(type(callback) is PromptCachingDeploymentCheck for callback in litellm.callbacks)
+
+
+def test_update_settings_replaces_toggleable_pre_call_checks():
+    router = _build_router()
+
+    router.update_settings(optional_pre_call_checks=["prompt_caching"])
+    router.update_settings(optional_pre_call_checks=["enforce_model_rate_limits"])
+
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in (router.optional_callbacks or []))
+    assert not any(isinstance(callback, PromptCachingDeploymentCheck) for callback in litellm.callbacks)
+    assert any(isinstance(callback, ModelRateLimitingCheck) for callback in (router.optional_callbacks or []))
+
+
+@pytest.mark.asyncio
+async def test_update_settings_preserves_router_budget_limiting_when_omitted(monkeypatch):
+    async def _disable_periodic_sync(*args, **kwargs):
+        return None
+
+    monkeypatch.setattr(
+        "litellm.router_strategy.budget_limiter.RouterBudgetLimiting.periodic_sync_in_memory_spend_with_redis",
+        _disable_periodic_sync,
+    )
+    router = _build_router()
+
+    router.add_optional_pre_call_checks(["router_budget_limiting"])
+    router.update_settings(optional_pre_call_checks=[])
+
+    assert any(isinstance(callback, RouterBudgetLimiting) for callback in (router.optional_callbacks or []))
+
+
 def test_update_settings_persists_retry_policy_dict():
     """When the proxy's ``_add_router_settings_from_db_config`` calls
     ``llm_router.update_settings(retry_policy={...})`` after reading the
@@ -255,8 +375,12 @@ async def test_config_update_persists_and_reads_back_retry_policy(monkeypatch):
             RateLimitErrorRetries=7,
         )
     )
+    request = MagicMock()
+    request.json = AsyncMock(return_value={"router_settings": {"retry_policy": posted.model_dump()}})
+
     await proxy_server.update_config(
         config_info=ConfigYAML(router_settings=posted),
+        request=request,
         user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234"),
     )
 
diff --git a/tests/test_litellm/test_secret_redaction.py b/tests/test_litellm/test_secret_redaction.py
index 7d50694c805..303efcab9c7 100644
--- a/tests/test_litellm/test_secret_redaction.py
+++ b/tests/test_litellm/test_secret_redaction.py
@@ -1,8 +1,10 @@
 import logging
 import logging.config
 import sys
+import time
 from collections.abc import Callable
 from io import StringIO
+from typing import Final
 from unittest.mock import patch
 
 import pytest
@@ -67,6 +69,50 @@ def test_redact_string_catches_secret_patterns():
     assert redact_string(normal) == normal
 
 
+@pytest.mark.parametrize(
+    "connection_string",
+    [
+        "postgres://admin:pass3cret@db.example.com:5432/mydb",
+        "redis://:pass3cret@cache.example.com:6379",
+        "postgres://admin:pass/s3cret@db.example.com:5432/mydb",
+        "amqp://admin:pass:s3cret@rabbit:5672",
+        "https://ad@min:pass3cret@host",
+        # An unencoded "@" inside the password, with a ":" after it
+        "postgresql://admin:p@ss3cret:2026@db.example.com:5432/mydb",
+        "amqp://guest:gu@st3cret:1@rabbit:5672/",
+        # An AWS RDS IAM auth token is a presigned query string used as the
+        # password, so the userinfo runs to several hundred characters.
+        "postgresql://litellm:host%3A5432%2F%3FAction%3Dconnect%26X-Amz-Signature%3D"
+        + "f" * 540
+        + "s3cret@db.host:5432/litellm",
+    ],
+)
+def test_redact_string_still_catches_connection_string_credentials(connection_string):
+    """The bounded userinfo pattern must keep matching real connection strings."""
+    assert "s3cret" not in redact_string(connection_string)
+
+
+def _redaction_cost(url_bytes: int) -> float:
+    url: Final = "/x?u=" + "a://" * (url_bytes // 4)
+
+    def once() -> float:
+        started = time.perf_counter()
+        redact_string(url)
+        return time.perf_counter() - started
+
+    return min(once() for _ in range(3))
+
+
+def test_redact_string_stays_sub_quadratic_on_a_long_adversarial_url():
+    """Access-log redaction runs on attacker-controlled request lines, so quadrupling
+    a URL of scheme separators must not multiply the cost by sixteen. Comparing two
+    sizes rather than asserting a wall-clock ceiling keeps this honest on a slow box:
+    the unbounded pattern this replaced cost 5s at 4 KB and 314s at 16 KB."""
+    growth: Final = _redaction_cost(16 * 1024) / _redaction_cost(4 * 1024)
+
+    assert growth < 11.0, f"cost grew {growth:.1f}x for 4x the URL length"
+
+
 def test_redact_string_catches_minimum_length_virtual_key():
     """Regression test for LIT-4355: keys at the enforced 16-char minimum
     (MINIMUM_CUSTOM_KEY_LENGTH) must be treated as key-shaped by the scrubber."""
diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py
index 6524353aa48..200cfd02197 100644
--- a/tests/test_litellm/test_utils.py
+++ b/tests/test_litellm/test_utils.py
@@ -41,7 +41,6 @@ from litellm.utils import (
     _snapshot_exception_for_hook,
     async_post_call_failure_deployment_hook,
     client,
-    get_api_key,
     get_llm_provider,
     get_non_default_completion_params,
     get_optional_params_image_gen,
@@ -1005,6 +1004,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid():
                 "gemini_native_audio": {"type": "boolean"},
                 "gemini_audio_only_live": {"type": "boolean"},
                 "supports_embedding_image_input": {"type": "boolean"},
+                "supports_forced_tool_use": {"type": "boolean"},
                 "supports_function_calling": {"type": "boolean"},
                 "supports_image_input": {"type": "boolean"},
                 "supports_nova_canvas_image_edit": {"type": "boolean"},
@@ -1416,6 +1416,26 @@ def test_get_provider_rerank_config():
     assert isinstance(config, HostedVLLMRerankConfig)
 
 
+def test_get_provider_text_to_speech_config_vertex_gemini_skips_cloud_tts():
+    """Regression for LIT-6501: mapping vertex Gemini TTS params through Google Cloud TTS
+    dropped response_format before the speech_to_completion bridge could honor it."""
+    from litellm.llms.vertex_ai.text_to_speech.transformation import VertexAITextToSpeechConfig
+    from litellm.utils import LlmProviders
+
+    assert (
+        ProviderConfigManager.get_provider_text_to_speech_config(
+            model="gemini-2.5-flash-preview-tts", provider=LlmProviders.VERTEX_AI
+        )
+        is None
+    )
+    assert isinstance(
+        ProviderConfigManager.get_provider_text_to_speech_config(
+            model="en-US-Studio-O", provider=LlmProviders.VERTEX_AI
+        ),
+        VertexAITextToSpeechConfig,
+    )
+
+
 # Models that should be skipped during testing
 OLD_PROVIDERS = ["aleph_alpha", "palm"]
 SKIP_MODELS = [
@@ -4634,6 +4654,7 @@ GEMINI_4096_CACHE_MIN_MODELS: Final = tuple(
         "gemini-3.5-flash",
         "gemini-3.6-flash",
         "gemini-3.7-flash",
+        "gemini-3.8-flash",
         "gemini-3.1-pro-preview",
         "gemini-3.1-pro-preview-customtools",
     )
@@ -4895,17 +4916,6 @@ def test_reapply_runtime_registrations_drops_request_scoped_registrations(monkey
         _invalidate_model_cost_lowercase_map()
 
 
-def test_ai21_api_key_is_resolved_from_the_documented_env_var(monkeypatch: pytest.MonkeyPatch) -> None:
-    """The ai21 branch resolved a misspelled env var, so the name every other ai21 code path
-    reads, and the only name documented, was ignored."""
-    monkeypatch.setattr(litellm, "api_key", None)
-    monkeypatch.setattr(litellm, "ai21_key", None)
-    monkeypatch.delenv("AI211_API_KEY", raising=False)
-    monkeypatch.setenv("AI21_API_KEY", "sk-ai21-resolved-from-env")
-
-    assert get_api_key(llm_provider="ai21", dynamic_api_key=None) == "sk-ai21-resolved-from-env"
-
-
 class _JsonCapture(logging.Handler):
     def __init__(self):
         super().__init__()
@@ -5765,3 +5775,33 @@ class TestHuggingFaceConfigFetch:
         assert _get_max_position_embeddings("some-org/some-model") == 512
         request_timeout = hf_config_route.calls.last.request.extensions["timeout"]
         assert request_timeout["read"] == HF_CONFIG_FETCH_TIMEOUT_SECONDS
+
+
+class TestIsVisionExplicitlyDisabled:
+    """github_copilot and chatgpt run an OAuth device flow inside get_llm_provider; the
+    explicit-disable lookup must adopt the declared prefix instead of resolving it, exactly
+    as _supports_factory does, or a capability check on a copilot deployment blocks routing
+    on a device-code prompt."""
+
+    @pytest.mark.parametrize("model", ["github_copilot/gpt-4o", "chatgpt/gpt-5"])
+    def test_never_resolves_an_authenticating_prefix(self, model, monkeypatch):
+        from litellm.utils import is_vision_explicitly_disabled
+
+        lookups: list = []
+
+        def _record(*args, **kwargs):
+            lookups.append((args, kwargs))
+            raise RuntimeError("provider resolution must not run for an authenticating provider")
+
+        monkeypatch.setattr(litellm, "get_llm_provider", _record)
+
+        assert is_vision_explicitly_disabled(model) is False
+        assert lookups == []
+
+    def test_explicit_false_detected_and_absent_reads_enabled(self):
+        from litellm.utils import is_vision_explicitly_disabled
+
+        assert (
+            is_vision_explicitly_disabled("fireworks_ai/accounts/fireworks/models/deepseek-v4-flash-0731") is True
+        )
+        assert is_vision_explicitly_disabled("anthropic/claude-sonnet-4-5") is False
diff --git a/tests/test_litellm/test_video_generation.py b/tests/test_litellm/test_video_generation.py
index b166e902d6e..2a60ff9c4b5 100644
--- a/tests/test_litellm/test_video_generation.py
+++ b/tests/test_litellm/test_video_generation.py
@@ -532,6 +532,41 @@ class TestVideoGeneration:
         assert abs(cost_for("runwayml/seedance2_5", "480p", 8.0) - 1.6) < 0.001
         assert abs(cost_for("runwayml/gen4.5", None, 8.0) - 0.96) < 0.001
 
+    def test_completion_cost_veo_31_tiers_pin_published_rates(self, monkeypatch):
+        """The gemini and vertex_ai veo 3.1 entries bill Google's published per-second tier rates."""
+        from litellm.cost_calculator import completion_cost
+
+        local_map_path = os.path.join(
+            os.path.dirname(__file__), "..", "..", "model_prices_and_context_window.json"
+        )
+        with open(local_map_path, "r") as f:
+            monkeypatch.setattr(litellm, "model_cost", json.load(f))
+
+        def cost_for(model: str, provider: str, resolution: str | None, duration: float) -> float:
+            mock_response = MagicMock()
+            mock_response.usage = {
+                "duration_seconds": duration,
+                **({"video_resolution": resolution} if resolution else {}),
+            }
+            type(mock_response)._hidden_params = {}
+            return completion_cost(
+                completion_response=mock_response,
+                model=model,
+                call_type="create_video",
+                custom_llm_provider=provider,
+            )
+
+        for provider in ("gemini", "vertex_ai"):
+            for suffix in ("generate-preview", "generate-001"):
+                standard = f"{provider}/veo-3.1-{suffix}"
+                fast = f"{provider}/veo-3.1-fast-{suffix}"
+                assert abs(cost_for(standard, provider, None, 8.0) - 3.2) < 1e-6
+                assert abs(cost_for(standard, provider, "1080p", 8.0) - 3.2) < 1e-6
+                assert abs(cost_for(standard, provider, "4k", 8.0) - 4.8) < 1e-6
+                assert abs(cost_for(fast, provider, "720p", 8.0) - 0.8) < 1e-6
+                assert abs(cost_for(fast, provider, "1080p", 8.0) - 0.96) < 1e-6
+                assert abs(cost_for(fast, provider, "4k", 8.0) - 2.4) < 1e-6
+
     def test_video_generation_with_files(self):
         """Test video generation with file uploads."""
         config = OpenAIVideoConfig()
diff --git a/tests/test_litellm/vector_stores/__init__.py b/tests/test_litellm/vector_stores/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/tests/test_litellm/vector_stores/test_main.py b/tests/test_litellm/vector_stores/test_main.py
new file mode 100644
index 00000000000..d01e696906a
--- /dev/null
+++ b/tests/test_litellm/vector_stores/test_main.py
@@ -0,0 +1,78 @@
+"""
+Tests for litellm/vector_stores/main.py.
+
+Pins the router threading contract for vector store search: the router is an
+explicit named parameter that reaches the HTTP handler, and it must never leak
+into litellm_params/kwargs where logging would model_dump() it (the #19550
+serialization trap).
+"""
+
+from unittest.mock import MagicMock, patch
+
+import litellm.vector_stores.main as vector_stores_main
+from litellm.vector_stores.main import search
+
+MOCK_SEARCH_RESPONSE = {
+    "object": "vector_store.search_results.page",
+    "search_query": "q",
+    "data": [],
+}
+
+
+def test_search_threads_router_to_handler():
+    """search() must pass its router param through to the HTTP handler"""
+    mock_router = MagicMock()
+    logger = MagicMock()
+
+    with (
+        patch(  # test-quality-ok: stubs provider config resolution; the seam under test is the router kwarg threading
+            "litellm.vector_stores.main.ProviderConfigManager.get_provider_vector_stores_config",
+            return_value=MagicMock(),
+        ),
+        patch.object(  # test-quality-ok: the handler call is the observable boundary for the router kwarg contract
+            vector_stores_main.base_llm_http_handler,
+            "vector_store_search_handler",
+            return_value=MOCK_SEARCH_RESPONSE,
+        ) as mock_handler,
+    ):
+        response = search(
+            vector_store_id="bkt:idx",
+            query="q",
+            custom_llm_provider="s3_vectors",
+            router=mock_router,
+            litellm_logging_obj=logger,
+        )
+
+    assert response == MOCK_SEARCH_RESPONSE
+    mock_handler.assert_called_once()
+    assert mock_handler.call_args.kwargs["router"] is mock_router
+
+
+def test_search_router_not_in_litellm_params():
+    """Regression (#19550 class): the router must stay out of GenericLiteLLMParams,
+    otherwise pre-call logging model_dump()s it and breaks serialization."""
+    mock_router = MagicMock()
+    logger = MagicMock()
+
+    with (
+        patch(  # test-quality-ok: stubs provider config resolution; the seam under test is litellm_params contents
+            "litellm.vector_stores.main.ProviderConfigManager.get_provider_vector_stores_config",
+            return_value=MagicMock(),
+        ),
+        patch.object(  # test-quality-ok: the handler call is where a leaked router in litellm_params would surface
+            vector_stores_main.base_llm_http_handler,
+            "vector_store_search_handler",
+            return_value=MOCK_SEARCH_RESPONSE,
+        ) as mock_handler,
+    ):
+        search(
+            vector_store_id="bkt:idx",
+            query="q",
+            custom_llm_provider="s3_vectors",
+            router=mock_router,
+            litellm_logging_obj=logger,
+        )
+
+    litellm_params = mock_handler.call_args.kwargs["litellm_params"]
+    assert "router" not in litellm_params.model_dump(exclude_none=True)
+    assert getattr(litellm_params, "router", None) is None
diff --git a/tests/test_rust_python_harness.py b/tests/test_rust_python_harness.py
new file mode 100644
index 00000000000..90dc38663dd
--- /dev/null
+++ b/tests/test_rust_python_harness.py
@@ -0,0 +1,236 @@
+from __future__ import annotations
+
+import importlib
+import json
+from pathlib import Path
+
+import pytest
+
+catalog = importlib.import_module("tests.rust-python-harness.catalog")
+cli = importlib.import_module("tests.rust-python-harness.cli")
+models = importlib.import_module("tests.rust-python-harness.models")
+runner = importlib.import_module("tests.rust-python-harness.runner")
+ui = importlib.import_module("tests.rust-python-harness.ui")
+
+load_catalog = catalog.load_catalog
+_pick_values = cli._pick_values
+_coverage_pytest_args = cli._coverage_pytest_args
+_select = cli._select
+CaseResult = models.CaseResult
+Coverage = models.Coverage
+HarnessCase = models.HarnessCase
+HarnessRun = models.HarnessRun
+RunStatus = models.RunStatus
+SDK_FUNCTIONS = models.SDK_FUNCTIONS
+section_confidence = models.section_confidence
+run_pytest = runner.run_pytest
+runnable_selectors = runner.runnable_selectors
+selector_matches_node = runner.selector_matches_node
+_format_duration = ui._format_duration
+_rerun_command = ui._rerun_command
+_summary = ui._summary
+
+
+def _case(
+    *, selectors: tuple[str, ...] = (), coverage: Coverage = Coverage.COMPLETE
+) -> HarnessCase:
+    return HarnessCase(
+        strategy_id="example",
+        strategy_label="Example",
+        sdk_function="messages",
+        coverage=coverage,
+        selectors=selectors,
+    )
+
+
+def _manifest() -> dict[str, object]:
+    return {
+        "order": 1,
+        "id": "example",
+        "label": "Example strategy",
+        "description": "Example description",
+        "functions": {
+            function: {"coverage": "planned", "selectors": []}
+            for function in SDK_FUNCTIONS
+        },
+    }
+
+
+def test_should_load_the_three_harness_strategies_in_order() -> None:
+    strategies = load_catalog()
+
+    assert [strategy.id for strategy in strategies] == [
+        "e2e_fuzz_tests",
+        "unit_tests_rust",
+        "validate_sub_methods",
+    ]
+    assert all(
+        tuple(case.sdk_function for case in strategy.cases) == SDK_FUNCTIONS
+        for strategy in strategies
+    )
+
+
+def test_should_reject_a_manifest_missing_an_sdk_function(tmp_path: Path) -> None:
+    strategy_directory = tmp_path / "example"
+    strategy_directory.mkdir()
+    manifest = _manifest()
+    del manifest["functions"]["count_tokens"]  # type: ignore[index]
+    (strategy_directory / "strategy.json").write_text(
+        json.dumps(manifest), encoding="utf-8"
+    )
+
+    with pytest.raises(ValueError, match="functions must exactly match"):
+        load_catalog(tmp_path)
+
+
+@pytest.mark.parametrize(
+    ("selector", "nodeid", "matches"),
+    [
+        ("tests/test_parity.py", "tests/test_parity.py::test_one", True),
+        ("tests/test_parity.py::test_one", "tests/test_parity.py::test_one", True),
+        (
+            "tests/test_parity.py::test_one",
+            "tests/test_parity.py::test_one[value]",
+            True,
+        ),
+        ("tests/test_parity.py::test_one", "tests/test_parity.py::test_two", False),
+    ],
+)
+def test_should_match_pytest_file_and_node_selectors(
+    selector: str, nodeid: str, matches: bool
+) -> None:
+    assert selector_matches_node(selector, nodeid) is matches
+
+
+def test_should_only_return_selectors_whose_files_exist(tmp_path: Path) -> None:
+    existing = tmp_path / "tests" / "test_parity.py"
+    existing.parent.mkdir()
+    existing.write_text("", encoding="utf-8")
+    case = _case(
+        selectors=("tests/test_parity.py", "tests/test_missing.py::test_missing")
+    )
+
+    assert runnable_selectors((case,), tmp_path) == ("tests/test_parity.py",)
+
+
+def test_should_mark_planned_and_not_applicable_cases_without_running() -> None:
+    planned = CaseResult(case=_case(coverage=Coverage.PLANNED))
+    not_applicable = CaseResult(case=_case(coverage=Coverage.NOT_APPLICABLE))
+
+    planned.set_initial_status()
+    not_applicable.set_initial_status()
+
+    assert planned.status is RunStatus.PLANNED
+    assert not_applicable.status is RunStatus.NOT_APPLICABLE
+
+
+def test_should_treat_an_all_planned_filtered_run_as_success(tmp_path: Path) -> None:
+    exit_code, run = run_pytest(
+        cases=(_case(coverage=Coverage.PLANNED),),
+        repo_root=tmp_path,
+        on_update=lambda _: None,
+    )
+
+    assert exit_code == 0
+    assert next(iter(run.results.values())).status is RunStatus.PLANNED
+
+
+def test_should_finalize_a_fully_passing_case() -> None:
+    result = CaseResult(case=_case(selectors=("tests/test_parity.py",)))
+    result.set_initial_status()
+    result.collected.update({"one", "two"})
+    result.completed.update({"one", "two"})
+    result.passed = 2
+
+    result.finalize()
+
+    assert result.status is RunStatus.PASSED
+
+
+def test_should_replace_a_pass_with_a_teardown_error() -> None:
+    result = CaseResult(case=_case(selectors=("tests/test_parity.py",)))
+    result.set_initial_status()
+    result.collected.add("one")
+
+    result.record("one", RunStatus.PASSED, 0.1)
+    result.record("one", RunStatus.ERROR, 0.2)
+
+    assert result.status is RunStatus.ERROR
+    assert result.passed == 0
+    assert result.errors == 1
+    assert result.duration == pytest.approx(0.3)
+
+
+def test_should_filter_the_catalog_by_strategy_and_sdk_function() -> None:
+    strategies = load_catalog()
+
+    cases = _select(strategies, {"e2e_fuzz_tests"}, {"messages"})
+
+    assert len(cases) == 1
+    assert cases[0].key == "e2e_fuzz_tests:messages"
+
+
+def test_should_reject_an_unknown_strategy() -> None:
+    with pytest.raises(ValueError, match="Unknown strategy"):
+        _select(load_catalog(), {"not-real"}, set())
+
+
+def test_should_pick_multiple_interactive_filters() -> None:
+    answers = iter(["nope", "1, 3"])
+
+    selected = _pick_values(
+        "Examples",
+        (("one", "One"), ("two", "Two"), ("three", "Three")),
+        input_fn=lambda _: next(answers),
+    )
+
+    assert selected == {"one", "three"}
+
+
+def test_should_format_developer_facing_run_context() -> None:
+    run = HarnessRun.from_cases((_case(selectors=("tests/test_parity.py",)),))
+    result = next(iter(run.results.values()))
+    result.collected.add("tests/test_parity.py::test_one")
+    result.record("tests/test_parity.py::test_one", RunStatus.PASSED, 1.25)
+
+    assert _summary(run) == (1, 0, 0, 0)
+    assert _format_duration(1.25) == "1.2s"
+    assert _rerun_command("tests/test_parity.py::test_one") == (
+        "poetry run pytest tests/test_parity.py::test_one -q"
+    )
+    assert _rerun_command("tests/test_parity.py::test_one[value with spaces]") == (
+        "poetry run pytest 'tests/test_parity.py::test_one[value with spaces]' -q"
+    )
+
+
+def test_should_build_python_coverage_reports_below_the_target_directory(
+    tmp_path: Path,
+) -> None:
+    args = _coverage_pytest_args(tmp_path)
+
+    assert tmp_path.is_dir()
+    assert "--cov=litellm" in args
+    assert "--cov-context=test" in args
+    assert f"--cov-report=json:{tmp_path / 'python.json'}" in args
+    assert f"--cov-report=xml:{tmp_path / 'python.xml'}" in args
+    assert f"--cov-report=html:{tmp_path / 'python-html'}" in args
+
+
+def test_should_report_confidence_for_each_sdk_section() -> None:
+    strategies = load_catalog()
+    cases = tuple(case for strategy in strategies for case in strategy.cases)
+    run = HarnessRun.from_cases(cases)
+    passing = run.results["e2e_fuzz_tests:responses"]
+    passing.collected.add("tests/test_parity.py::test_one")
+    passing.record("tests/test_parity.py::test_one", RunStatus.PASSED)
+
+    scores = {
+        score.sdk_function: score for score in section_confidence(run, strategies)
+    }
+
+    assert scores["responses"].verified_strategies == 1
+    assert scores["responses"].required_strategies == 3
+    assert scores["responses"].percentage == 33
+    assert scores["responses"].level.value == "MEDIUM"
+    assert scores["count_tokens"].percentage == 0
+    assert scores["count_tokens"].level.value == "LOW"
diff --git a/type-discipline-budget.json b/type-discipline-budget.json
index 7365cec4fdd..839f7be2d50 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,21 +1,21 @@
 {
   "LIT001": {
-    "limit": 22704
+    "limit": 22358
   },
   "LIT002": {
-    "limit": 26854
+    "limit": 26772
   },
   "LIT003": {
-    "limit": 269
+    "limit": 261
   },
   "LIT004": {
-    "limit": 43
+    "limit": 40
   },
   "LIT005": {
     "limit": 0
   },
   "LIT006": {
-    "limit": 1063
+    "limit": 1039
   },
   "LIT007": {
     "limit": 0
@@ -27,12 +27,12 @@
     "limit": 0
   },
   "LIT010": {
-    "limit": 16564
+    "limit": 16486
   },
   "LIT011": {
-    "limit": 5577
+    "limit": 5521
   },
   "LIT012": {
-    "limit": 4506
+    "limit": 4495
   }
 }
diff --git a/ui/litellm-dashboard/eslint-budgets.json b/ui/litellm-dashboard/eslint-budgets.json
index bbf69c4a77a..e8207d179bd 100644
--- a/ui/litellm-dashboard/eslint-budgets.json
+++ b/ui/litellm-dashboard/eslint-budgets.json
@@ -4,5 +4,8 @@
   "complexity": { "max": 140, "target": 80 },
   "max-depth": { "max": 70, "target": 30 },
   "local/no-large-inline-object-arg": { "max": 559, "target": 300 },
-  "local/no-long-condition-chain": { "max": 265, "target": 120 }
+  "local/no-long-condition-chain": { "max": 265, "target": 120 },
+  "testing-library/no-container": { "max": 133, "target": 50 },
+  "testing-library/no-node-access": { "max": 716, "target": 500 },
+  "testing-library/prefer-screen-queries": { "max": 18, "target": 18 }
 }
diff --git a/ui/litellm-dashboard/eslint.config.mjs b/ui/litellm-dashboard/eslint.config.mjs
index 23cc5096bb1..f5e3b23b3ec 100644
--- a/ui/litellm-dashboard/eslint.config.mjs
+++ b/ui/litellm-dashboard/eslint.config.mjs
@@ -104,10 +104,13 @@ const eslintConfig = [
     plugins: { "testing-library": testingLibrary, "jest-dom": jestDom },
     rules: {
       "testing-library/await-async-queries": "error",
+      "testing-library/no-container": "warn",
+      "testing-library/no-node-access": "warn",
       "testing-library/no-wait-for-multiple-assertions": "error",
       "testing-library/no-wait-for-side-effects": "error",
       "testing-library/prefer-find-by": "error",
       "testing-library/prefer-presence-queries": "error",
+      "testing-library/prefer-screen-queries": "warn",
       "jest-dom/prefer-checked": "error",
       "jest-dom/prefer-empty": "error",
       "jest-dom/prefer-enabled-disabled": "error",
diff --git a/ui/litellm-dashboard/package-lock.json b/ui/litellm-dashboard/package-lock.json
index d2a64b93384..4e5b0c1dda6 100644
--- a/ui/litellm-dashboard/package-lock.json
+++ b/ui/litellm-dashboard/package-lock.json
@@ -4891,9 +4891,9 @@
       }
     },
     "node_modules/baseline-browser-mapping": {
-      "version": "2.10.27",
-      "resolved": "https://registry.npmjs.org/baseline-browser-mapping/-/baseline-browser-mapping-2.10.27.tgz",
-      "integrity": "sha512-zEs/ufmZoUd7WftKpKyXaT6RFxpQ5Qm9xytKRHvJfxFV9DFJkZph9RvJ1LcOUi0Z1ZVijMte65JbILeV+8QQEA==",
+      "version": "2.11.20",
+      "resolved": "https://registry.npmjs.org/baseline-browser-mapping/-/baseline-browser-mapping-2.11.20.tgz",
+      "integrity": "sha512-H0ulySigv6icDJ1F7SjtdCD6PrhTpdYCmP0CactWy1+ekh0AFd0o1Wn5T8b+hnTmdBx19u9yhL6wvCylXMY7zw==",
       "license": "Apache-2.0",
       "bin": {
         "baseline-browser-mapping": "dist/cli.cjs"
@@ -4939,9 +4939,9 @@
       }
     },
     "node_modules/browserslist": {
-      "version": "4.28.2",
-      "resolved": "https://registry.npmjs.org/browserslist/-/browserslist-4.28.2.tgz",
-      "integrity": "sha512-48xSriZYYg+8qXna9kwqjIVzuQxi+KYWp2+5nCYnYKPTr0LvD89Jqk2Or5ogxz0NUMfIjhh2lIUX/LyX9B4oIg==",
+      "version": "4.28.8",
+      "resolved": "https://registry.npmjs.org/browserslist/-/browserslist-4.28.8.tgz",
+      "integrity": "sha512-V2NpofLblG64mfOtSgDhOJESZEGogzDMBv/q+W6oc4LXWP/q75eOXoOaaOu1EOadB9U4Bwx/e0yzbvwKH8zalA==",
       "dev": true,
       "funding": [
         {
@@ -4959,11 +4959,11 @@
       ],
       "license": "MIT",
       "dependencies": {
-        "baseline-browser-mapping": "^2.10.12",
-        "caniuse-lite": "^1.0.30001782",
-        "electron-to-chromium": "^1.5.328",
-        "node-releases": "^2.0.36",
-        "update-browserslist-db": "^1.2.3"
+        "baseline-browser-mapping": "^2.11.12",
+        "caniuse-lite": "^1.0.30001809",
+        "electron-to-chromium": "^1.5.402",
+        "node-releases": "^2.0.53",
+        "update-browserslist-db": "^1.3.0"
       },
       "bin": {
         "browserslist": "cli.js"
@@ -5042,9 +5042,9 @@
       }
     },
     "node_modules/caniuse-lite": {
-      "version": "1.0.30001791",
-      "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001791.tgz",
-      "integrity": "sha512-yk0l/YSrOnFZk3UROpDLQD9+kC1l4meK/wed583AXrzoarMGJcbRi2Q4RaUYbKxYAsZ8sWmaSa/DsLmdBeI1vQ==",
+      "version": "1.0.30001810",
+      "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001810.tgz",
+      "integrity": "sha512-TITQPUkaz+aVk5GL6NhOdwk1aEaNTSDPsGFWrTuhKGtjTF70jL/Oht2W4c6rXUe5fu7Ie19VIahAXHIIiWWNeg==",
       "funding": [
         {
           "type": "opencollective",
@@ -5706,9 +5706,9 @@
       }
     },
     "node_modules/electron-to-chromium": {
-      "version": "1.5.349",
-      "resolved": "https://registry.npmjs.org/electron-to-chromium/-/electron-to-chromium-1.5.349.tgz",
-      "integrity": "sha512-QsWVGyRuY07Aqb234QytTfwd5d9AJlfNIQ5wIOl1L+PZDzI9d9+Fn0FRale/QYlFxt/bUnB0/nLd1jFPGxGK1A==",
+      "version": "1.5.416",
+      "resolved": "https://registry.npmjs.org/electron-to-chromium/-/electron-to-chromium-1.5.416.tgz",
+      "integrity": "sha512-K6bvB2BjnNrugtIih6ewlbBI9DXa976jIdiIlRLHhBoEI9a4JaQjjHyF+A1IQI543aQYR4LnmOrT/K5fZj0aPA==",
       "dev": true,
       "license": "ISC"
     },
@@ -9901,11 +9901,14 @@
       }
     },
     "node_modules/node-releases": {
-      "version": "2.0.38",
-      "resolved": "https://registry.npmjs.org/node-releases/-/node-releases-2.0.38.tgz",
-      "integrity": "sha512-3qT/88Y3FbH/Kx4szpQQ4HzUbVrHPKTLVpVocKiLfoYvw9XSGOX2FmD2d6DrXbVYyAQTF2HeF6My8jmzx7/CRw==",
+      "version": "2.0.54",
+      "resolved": "https://registry.npmjs.org/node-releases/-/node-releases-2.0.54.tgz",
+      "integrity": "sha512-YHs7BmmcsdAI5Ozuf8JZo6PT0mv2GIWC9vMfvUC3dp65M8hn7Ux8CPL+2oBI7juNuj9d0ndhTcznq2ODBps9cQ==",
       "dev": true,
-      "license": "MIT"
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      }
     },
     "node_modules/nuqs": {
       "version": "2.9.4",
@@ -12350,9 +12353,9 @@
       }
     },
     "node_modules/update-browserslist-db": {
-      "version": "1.2.3",
-      "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.2.3.tgz",
-      "integrity": "sha512-Js0m9cx+qOgDxo0eMiFGEueWztz+d4+M3rGlmKPT+T4IS/jP4ylw3Nwpu6cpTTP8R1MAC1kF4VbdLt3ARf209w==",
+      "version": "1.3.2",
+      "resolved": "https://registry.npmjs.org/update-browserslist-db/-/update-browserslist-db-1.3.2.tgz",
+      "integrity": "sha512-UQ+MSxlhRm1bzjhU+DcuXfjFO1FzNtqhK5+9Yvlp90ItDLk5vT932A0rFu619nf7RVS+Y/VeaUW1jaRDqZ8VJw==",
       "dev": true,
       "funding": [
         {
diff --git a/ui/litellm-dashboard/public/assets/logos/alice.svg b/ui/litellm-dashboard/public/assets/logos/alice.svg
new file mode 100644
index 00000000000..f18f887b98c
--- /dev/null
+++ b/ui/litellm-dashboard/public/assets/logos/alice.svg
@@ -0,0 +1,4 @@
+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<rect width="24" height="24" rx="8" fill="#E686B4"/>
+<path d="M12.0001 4C16.165 4.00002 19 7.1202 19 10.7146V19.1637C19 19.6256 18.6256 20 18.1637 20H16.9259C16.4641 20 16.0896 19.6256 16.0896 19.1637V11.3386C16.0896 9.31676 14.9356 6.74578 12.0001 6.74575C10.4696 6.74575 7.91038 7.76917 7.91038 11.3386V14.0344H13.801C14.2629 14.0344 14.6373 14.4088 14.6373 14.8707V15.9188C14.6373 16.3807 14.2629 16.7551 13.801 16.7551H7.91038V19.1637C7.91038 19.6256 7.53595 20 7.07406 20H5.83632C5.37443 20 5 19.6256 5 19.1637V10.7146C5 7.12018 7.83522 4 12.0001 4Z" fill="white"/>
+</svg>
diff --git a/ui/litellm-dashboard/public/assets/logos/gigachat.svg b/ui/litellm-dashboard/public/assets/logos/gigachat.svg
new file mode 100644
index 00000000000..e7abe47b221
--- /dev/null
+++ b/ui/litellm-dashboard/public/assets/logos/gigachat.svg
@@ -0,0 +1,27 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 28.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Слой_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 1000 1000" enable-background="new 0 0 1000 1000" xml:space="preserve">
+<path fill-rule="evenodd" clip-rule="evenodd" fill="#000001" d="M500,0c276.1218262,0,500,223.8403168,500,500
+	c0,276.1593628-223.8781738,500-500,500C223.8771973,1000,0,776.1218262,0,500C0.0000314,223.8771973,223.8771973,0.0000314,500,0z
+	 M911.703125,378.8250122c-12.6343384,87.6312561-57.1812744,159.9468384-94.3469238,207.0031128
+	c-57.359314,70.65625-134.203064,131.828125-222.3842773,177.03125
+	c-87.2250366,44.7218628-181.578186,71.8875122-272.8406677,78.5562744
+	c-15.4475098,0.890625-29.7947083,1.3311768-43.2412415,1.3311768c-16.0025024,0-30.7562714-0.640625-44.759079-1.8999023
+	c73.1806183,57.3218384,165.3878326,91.499939,265.5440674,91.499939l-0.0562744-0.0562744
+	c238.0687561,0,431.1000061-192.999939,431.1000061-431.0686951c0-41.3156433-5.828125-81.2562561-16.6843872-119.0875244
+	C913.2562256,381.0218811,912.4812622,379.8999939,911.703125,378.8250122z M561.3343506,45.6000023
+	c-147.2843323,0-281.1668701,60.73843-358.1281128,162.4078064l-0.4881287,0.5968781
+	c-33.2709351,40.5328217-55.3865662,84.9996796-63.910614,128.6078033
+	c-4.8540802,26.53125-3.9568939,50.8968811,2.7127991,72.1312561v-0.0562439
+	c15.8215637,47.5031128,54.3062439,85.5968628,97.9543762,96.7875061
+	c18.1562653,4.5218506,35.6100006,6.4124756,51.8393707,5.671875l4.2859497-0.3812256
+	C405.9468689,502.4718628,504.34375,432.9312439,586.046875,366.046875
+	c51.1312256-42.7937622,100.0405884-99.4146729,103.1906128-135.9850006
+	C617.9468384,264.6322021,544.3500366,309.6121826,459.5,370.4156189
+	c-9.4125061,6.7062378-22.2406311,4.828125-29.2437439-4.2875061
+	c-42.1281128-54.5405884-78.8125305-98.8321838-115.53125-139.2943726
+	c-3.9968872-4.4449921-5.9906311-10.4062347-5.3987427-16.3302917c0.555603-5.9284515,3.6299744-11.4168854,8.4081116-14.9740753
+	C430.2281189,111.1612473,542.125,63.3568764,650.6875,53.2768745
+	C621.5718994,48.1650009,591.7124634,45.6006279,561.3343506,45.6000023z"/>
+</svg>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.test.tsx
index 06099a9fc22..4d18ec2ef5f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.test.tsx
@@ -74,6 +74,42 @@ describe("AgentsTable", () => {
     expect(onDeleteClick).toHaveBeenCalledWith("agent-9", "Doomed Agent");
   });
 
+  it("filters agents by name or by agent card description", async () => {
+    const user = userEvent.setup();
+    render(
+      <AgentsTable
+        agents={[
+          makeAgent({ agent_id: "a1", agent_name: "Billing Router" }),
+          makeAgent({
+            agent_id: "a2",
+            agent_name: "Second Agent",
+            agent_card_params: { description: "handles support tickets" },
+          }),
+        ]}
+        {...baseProps}
+      />,
+    );
+
+    const search = screen.getByPlaceholderText("Search agent names or descriptions...");
+    await user.type(search, "billing");
+    expect(screen.getByText("Billing Router")).toBeInTheDocument();
+    expect(screen.queryByText("Second Agent")).not.toBeInTheDocument();
+
+    await user.clear(search);
+    await user.type(search, "support tickets");
+    expect(screen.getByText("Second Agent")).toBeInTheDocument();
+    expect(screen.queryByText("Billing Router")).not.toBeInTheDocument();
+  });
+
+  it("shows the no-match empty state when the search matches nothing", async () => {
+    const user = userEvent.setup();
+    render(<AgentsTable agents={[makeAgent()]} {...baseProps} />);
+
+    await user.type(screen.getByPlaceholderText("Search agent names or descriptions..."), "zzzz");
+    expect(screen.queryByText("Test Agent")).not.toBeInTheDocument();
+    expect(screen.getByText("No matching agents")).toBeInTheDocument();
+  });
+
   it("hides the actions column entirely for non-admins", () => {
     const agent = makeAgent({ agent_id: "agent-2" });
     render(<AgentsTable agents={[agent]} {...baseProps} isAdmin={false} />);
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.tsx
index 67c7ed74180..35ed6b66425 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/AgentsTable.tsx
@@ -1,13 +1,15 @@
 "use client";
 
 import { SortingState } from "@tanstack/react-table";
-import { Bot, CircleCheck } from "lucide-react";
+import { Bot, CircleCheck, Search as SearchIcon, X } from "lucide-react";
 import React, { useMemo, useState } from "react";
 
 import { Agent } from "@/components/agents/types";
 import { DataTable } from "@/components/shared/DataTable";
+import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group";
 import { Switch } from "@/components/ui/switch";
 import { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger } from "@/components/ui/tooltip";
+import { filterBySearchTerm } from "@/utils/searchUtils";
 
 import { getAgentsTableColumns } from "./AgentsTableColumns";
 
@@ -24,14 +26,18 @@ interface AgentsTableProps {
 
 const DEFAULT_SORTING: SortingState = [{ id: "created_at", desc: true }];
 
-function EmptyState() {
+function EmptyState({ isFiltered }: { isFiltered: boolean }) {
   return (
     <div className="flex flex-col items-center gap-1 py-6">
       <div className="mb-1 flex size-10 items-center justify-center rounded-lg bg-muted">
         <Bot className="size-5 text-muted-foreground" />
       </div>
-      <div className="text-sm font-medium text-foreground">No agents yet</div>
-      <div className="text-sm text-muted-foreground">Add an agent to make it available in your organization.</div>
+      <div className="text-sm font-medium text-foreground">{isFiltered ? "No matching agents" : "No agents yet"}</div>
+      <div className="text-sm text-muted-foreground">
+        {isFiltered
+          ? "Adjust the search to see more agents."
+          : "Add an agent to make it available in your organization."}
+      </div>
     </div>
   );
 }
@@ -47,6 +53,11 @@ const AgentsTable: React.FC<AgentsTableProps> = ({
   onDeleteClick,
 }) => {
   const [sorting, setSorting] = useState<SortingState>(DEFAULT_SORTING);
+  const [searchTerm, setSearchTerm] = useState("");
+  const filteredAgents = useMemo(
+    () => filterBySearchTerm(agents, searchTerm, (agent) => [agent.agent_name, agent.agent_card_params?.description]),
+    [agents, searchTerm],
+  );
 
   const columns = useMemo(
     () => getAgentsTableColumns({ isAdmin, onAgentClick, onDeleteClick }),
@@ -55,7 +66,7 @@ const AgentsTable: React.FC<AgentsTableProps> = ({
 
   return (
     <DataTable
-      data={agents}
+      data={filteredAgents}
       columns={columns}
       getRowId={(agent, index) => agent.agent_id || String(index)}
       sortingMode="client"
@@ -63,10 +74,27 @@ const AgentsTable: React.FC<AgentsTableProps> = ({
       onSortingChange={setSorting}
       isLoading={isLoading}
       loadingMessage="Loading agents…"
-      noDataMessage={<EmptyState />}
+      noDataMessage={<EmptyState isFiltered={agents.length > 0} />}
       size="compact"
       toolbar={() => (
-        <div className="flex items-center justify-end">
+        <div className="flex flex-wrap items-center justify-between gap-2">
+          <InputGroup className="max-w-sm">
+            <InputGroupAddon>
+              <SearchIcon className="size-4 text-muted-foreground" />
+            </InputGroupAddon>
+            <InputGroupInput
+              placeholder="Search agent names or descriptions..."
+              value={searchTerm}
+              onChange={(e) => setSearchTerm(e.target.value)}
+            />
+            {searchTerm && (
+              <InputGroupAddon align="inline-end">
+                <InputGroupButton size="icon-xs" aria-label="Clear search" onClick={() => setSearchTerm("")}>
+                  <X />
+                </InputGroupButton>
+              </InputGroupAddon>
+            )}
+          </InputGroup>
           <TooltipProvider delay={300}>
             <Tooltip>
               <TooltipTrigger
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/add_agent_form.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/add_agent_form.integration.test.tsx
index bffc7b0fbc8..dad8599e967 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/add_agent_form.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/add_agent_form.integration.test.tsx
@@ -5,6 +5,7 @@ import { describe, it, expect, vi, beforeEach } from "vitest";
 import AddAgentForm from "./add_agent_form";
 import * as networking from "@/components/networking";
 import type { AgentCreateInfo } from "@/components/networking";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 vi.mock("@/components/networking", () => ({
   createAgentCall: vi.fn(),
@@ -309,8 +310,7 @@ describe("AddAgentForm submit payload", () => {
 
     await user.type(await screen.findByLabelText("Allowed Models"), "gpt-4o,");
     await user.keyboard("{Escape}");
-    await user.click(screen.getByLabelText("Allowed Agents (Sub-Agents)"));
-    await user.click(await screen.findByTitle("Sub Agent One"));
+    await chooseSelectOption(user, screen.getByLabelText("Allowed Agents (Sub-Agents)"), "Sub Agent One");
     await user.keyboard("{Escape}");
     await user.click(screen.getByText(/Configure which models, agents, and MCP tools/));
     await user.click(screen.getByRole("button", { name: /^Next/ }));
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
index 79bd2f6a21b..de1eb153f6f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_info.integration.test.tsx
@@ -75,6 +75,40 @@ const langgraphInfo: AgentCreateInfo = {
   ],
 };
 
+const FULL_RUNTIME_ARN = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs";
+
+const BEDROCK_AGENTCORE_AGENT = {
+  agent_id: "agent-3",
+  agent_name: "bedrock-agent",
+  agent_card_params: { name: "bedrock-agent", description: "agentcore agent", url: "", version: "1.0.0", skills: [] },
+  litellm_params: {
+    custom_llm_provider: "bedrock",
+    model: `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+  },
+};
+
+const bedrockAgentcoreInfo: AgentCreateInfo = {
+  agent_type: "bedrock_agentcore",
+  agent_type_display_name: "Bedrock AgentCore",
+  description: "Bedrock AgentCore runtimes",
+  logo_url: "/b.png",
+  use_a2a_form_fields: false,
+  litellm_params_template: { custom_llm_provider: "bedrock" },
+  model_template: "bedrock/agentcore/{agent_runtime_arn}",
+  credential_fields: [
+    {
+      key: "agent_runtime_arn",
+      label: "Agent Runtime ARN",
+      field_type: "text",
+      required: true,
+      include_in_litellm_params: false,
+      validation_pattern: "^arn:aws[a-zA-Z0-9-]*:bedrock-agentcore:[a-z0-9-]+:[0-9]{12}:runtime/.+$",
+      validation_message:
+        'Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after "runtime/".',
+    },
+  ],
+};
+
 const setup = () => userEvent.setup({ pointerEventsCheck: PointerEventsCheckLevel.Never });
 
 const renderView = () => render(<AgentInfoView agentId="agent-1" onClose={vi.fn()} accessToken="tok" isAdmin={true} />);
@@ -247,6 +281,69 @@ describe("AgentInfoView update payload", () => {
     });
   });
 
+  it("preserves the full AgentCore runtime ARN (including the resource id after runtime/) across an unedited save", async () => {
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([bedrockAgentcoreInfo]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    expect(await screen.findByLabelText("Agent Runtime ARN")).toHaveValue(FULL_RUNTIME_ARN);
+
+    await save(user);
+
+    expect((patchedPayload().litellm_params as Record<string, unknown>).model).toBe(
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+  });
+
+  it("blocks the save and shows a validation error when the Agent Runtime ARN is truncated", async () => {
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([bedrockAgentcoreInfo]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    const arnField = await screen.findByLabelText("Agent Runtime ARN");
+    await user.clear(arnField);
+    fireEvent.change(arnField, {
+      target: { value: "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime" },
+    });
+    await user.click(screen.getByRole("button", { name: "Save Changes" }));
+
+    expect(
+      await screen.findByText(
+        'Enter the complete Bedrock AgentCore runtime ARN, including the runtime ID after "runtime/".',
+      ),
+    ).toBeInTheDocument();
+    expect(networking.patchAgentCall).not.toHaveBeenCalled();
+  });
+
+  it("renders and saves normally when a field's validation_pattern is not a valid regex", async () => {
+    const infoWithBadPattern: AgentCreateInfo = {
+      ...bedrockAgentcoreInfo,
+      credential_fields: [
+        {
+          ...bedrockAgentcoreInfo.credential_fields[0],
+          validation_pattern: "(unterminated",
+        },
+      ],
+    };
+    vi.mocked(networking.getAgentCreateMetadata).mockResolvedValue([infoWithBadPattern]);
+    vi.mocked(networking.getAgentInfo).mockResolvedValue(BEDROCK_AGENTCORE_AGENT as never);
+    const user = setup();
+    renderView();
+    await openEditor(user);
+
+    expect(await screen.findByLabelText("Agent Runtime ARN")).toHaveValue(FULL_RUNTIME_ARN);
+
+    await save(user);
+
+    expect((patchedPayload().litellm_params as Record<string, unknown>).model).toBe(
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+  });
+
   it("reloads the agent and leaves edit mode when the edit is cancelled", async () => {
     const user = setup();
     renderView();
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts
new file mode 100644
index 00000000000..0c2d2500776
--- /dev/null
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.test.ts
@@ -0,0 +1,73 @@
+import { describe, it, expect } from "vitest";
+import { detectAgentType, extractModelTemplateValues, parseDynamicAgentForForm } from "./agent_type_utils";
+import type { AgentCreateInfo } from "@/components/networking";
+import type { Agent } from "@/components/agents/types";
+
+const FULL_RUNTIME_ARN = "arn:aws:bedrock-agentcore:eu-central-1:123456789012:runtime/hosted_agent_4vm3i-BaTdfOELAs";
+
+const bedrockAgentcoreInfo: AgentCreateInfo = {
+  agent_type: "bedrock_agentcore",
+  agent_type_display_name: "Bedrock AgentCore",
+  model_template: "bedrock/agentcore/{agent_runtime_arn}",
+  credential_fields: [
+    {
+      key: "agent_runtime_arn",
+      label: "Agent Runtime ARN",
+      required: true,
+      include_in_litellm_params: false,
+    },
+  ],
+};
+
+describe("extractModelTemplateValues", () => {
+  it("recovers a placeholder value that itself contains '/' (an AWS ARN resource path)", () => {
+    const values = extractModelTemplateValues(
+      "bedrock/agentcore/{agent_runtime_arn}",
+      `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+    );
+
+    expect(values.agent_runtime_arn).toBe(FULL_RUNTIME_ARN);
+  });
+
+  it("recovers a placeholder value with no '/' (single path segment)", () => {
+    const values = extractModelTemplateValues("langgraph/{assistant_id}", "langgraph/asst_1");
+
+    expect(values.assistant_id).toBe("asst_1");
+  });
+
+  it("returns no match when the model does not fit the template", () => {
+    const values = extractModelTemplateValues("langgraph/{assistant_id}", "azure_ai/agents/asst_1");
+
+    expect(values).toEqual({});
+  });
+});
+
+describe("parseDynamicAgentForForm", () => {
+  it("preserves the full runtime ARN, including the resource id after 'runtime/', when populating the edit form", () => {
+    const agent = {
+      agent_id: "agent-1",
+      agent_name: "bedrock-agent",
+      agent_card_params: { description: "" },
+      litellm_params: {
+        custom_llm_provider: "bedrock",
+        model: `bedrock/agentcore/${FULL_RUNTIME_ARN}`,
+      },
+    } as unknown as Agent;
+
+    const values = parseDynamicAgentForForm(agent, bedrockAgentcoreInfo);
+
+    expect(values.agent_runtime_arn).toBe(FULL_RUNTIME_ARN);
+  });
+});
+
+describe("detectAgentType", () => {
+  it("detects bedrock_agentcore agents from the model prefix", () => {
+    const agent = {
+      agent_id: "agent-1",
+      agent_name: "bedrock-agent",
+      litellm_params: { model: `bedrock/agentcore/${FULL_RUNTIME_ARN}` },
+    } as unknown as Agent;
+
+    expect(detectAgentType(agent)).toBe("bedrock_agentcore");
+  });
+});
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
index f91590c5732..506f355c519 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/agent_type_utils.ts
@@ -25,6 +25,29 @@ export const detectAgentType = (agent: Agent): string => {
   return "a2a";
 };
 
+const escapeRegExp = (segment: string): string => segment.replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+
+/**
+ * Reverses a `model_template` (e.g. "bedrock/agentcore/{agent_runtime_arn}") against a stored
+ * `model` string to recover the placeholder values that produced it. Builds a regex from the
+ * template's literal segments rather than matching by split("/") position, because a
+ * placeholder's value can itself contain "/" (an AWS ARN's "runtime/<runtime-id>" resource path,
+ * a Vertex AI reasoning engine's "projects/.../reasoningEngines/..." resource id) and would
+ * otherwise be cut off at the first one.
+ */
+export const extractModelTemplateValues = (template: string, model: string): Record<string, string> => {
+  // Splitting on a regex with a capturing group interleaves the captured placeholder
+  // names between the surrounding literal segments, e.g. "a/{x}/b" -> ["a/", "x", "/b"].
+  const parts = template.split(/\{([a-zA-Z0-9_]+)\}/g);
+  const fieldNames = parts.filter((_part, index) => index % 2 === 1);
+  const pattern = parts.map((part, index) => (index % 2 === 1 ? "(.+)" : escapeRegExp(part))).join("");
+
+  const match = model.match(new RegExp(`^${pattern}$`));
+  if (!match) return {};
+
+  return Object.fromEntries(fieldNames.map((name, index) => [name, match[index + 1]]));
+};
+
 /**
  * Parses agent data for dynamic form fields (non-A2A agents).
  * Extracts values from litellm_params based on the agent type metadata.
@@ -35,24 +58,18 @@ export const parseDynamicAgentForForm = (agent: Agent, agentTypeInfo: AgentCreat
     description: agent.agent_card_params?.description || "",
   };
 
+  const templateValues =
+    agentTypeInfo.model_template && agent.litellm_params?.model
+      ? extractModelTemplateValues(agentTypeInfo.model_template, agent.litellm_params.model)
+      : {};
+
   // Extract credential field values from litellm_params
   for (const field of agentTypeInfo.credential_fields) {
     if (field.include_in_litellm_params !== false) {
       values[field.key] = agent.litellm_params?.[field.key] || field.default_value || "";
-    } else {
-      // For fields not in litellm_params (like agent_id), try to extract from model string
-      if (agentTypeInfo.model_template && agent.litellm_params?.model) {
-        const model = agent.litellm_params.model;
-        const templateParts = agentTypeInfo.model_template.split("/");
-        const modelParts = model.split("/");
-
-        // Find the placeholder position and extract the value
-        templateParts.forEach((part, index) => {
-          if (part === `{${field.key}}` && modelParts[index]) {
-            values[field.key] = modelParts[index];
-          }
-        });
-      }
+    } else if (templateValues[field.key] !== undefined) {
+      // For fields not in litellm_params (like agent_runtime_arn), recover from the model string
+      values[field.key] = templateValues[field.key];
     }
   }
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
index 04a8b0df9d9..0f3355fe073 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/agents/_components/dynamic_agent_form_fields.tsx
@@ -24,58 +24,80 @@ interface DynamicAgentFormFieldsProps {
 export const unmountedDynamicFieldNames = (mountedPanels: readonly string[]): readonly string[] =>
   mountedPanels.includes(AGENT_FORM_CONFIG.cost.key) ? [] : COST_FIELD_NAMES;
 
-const CredentialField = ({ field }: { field: AgentCredentialFieldMetadata }) => (
-  <AgentFormField
-    name={field.key}
-    label={field.tooltip ? labelWithHint(field.label, field.tooltip) : field.label}
-    defaultValue={field.default_value ?? undefined}
-    rules={field.required ? { required: `Please enter ${field.label}` } : undefined}
-  >
-    {({ value, onChange, ref, ...control }) => {
-      const text = typeof value === "string" ? value : "";
-      if (field.field_type === "password") {
-        return (
-          <PasswordInput
-            {...control}
-            value={typeof value === "string" ? value : ""}
-            onChange={onChange}
-            ref={ref}
-            placeholder={field.placeholder || ""}
-          />
-        );
-      }
-      if (field.field_type === "textarea") {
-        return (
-          <Textarea
-            {...control}
-            ref={ref}
-            rows={3}
-            placeholder={field.placeholder || ""}
-            value={text}
-            onChange={onChange}
-          />
-        );
-      }
-      if (field.field_type === "select" && field.options) {
-        return (
-          <Select value={text || null} onValueChange={onChange}>
-            <SelectTrigger {...control} className="w-full">
-              <SelectValue placeholder={field.placeholder || ""} />
-            </SelectTrigger>
-            <SelectContent>
-              {field.options.map((option) => (
-                <SelectItem key={option} value={option} title={option}>
-                  {option}
-                </SelectItem>
-              ))}
-            </SelectContent>
-          </Select>
-        );
-      }
-      return <Input {...control} ref={ref} placeholder={field.placeholder || ""} value={text} onChange={onChange} />;
-    }}
-  </AgentFormField>
-);
+// A field's validation_pattern is server-supplied metadata; if it's ever not a valid regex, skip
+// validation rather than throwing during render and taking the whole form down with it.
+const buildValidationPatternRule = (
+  field: AgentCredentialFieldMetadata,
+): { value: RegExp; message: string } | undefined => {
+  if (!field.validation_pattern) return undefined;
+  try {
+    return {
+      value: new RegExp(field.validation_pattern),
+      message: field.validation_message || `${field.label} looks incomplete or malformed`,
+    };
+  } catch {
+    return undefined;
+  }
+};
+
+const CredentialField = ({ field }: { field: AgentCredentialFieldMetadata }) => {
+  const patternRule = buildValidationPatternRule(field);
+  return (
+    <AgentFormField
+      name={field.key}
+      label={field.tooltip ? labelWithHint(field.label, field.tooltip) : field.label}
+      defaultValue={field.default_value ?? undefined}
+      rules={{
+        ...(field.required ? { required: `Please enter ${field.label}` } : {}),
+        ...(patternRule ? { pattern: patternRule } : {}),
+      }}
+    >
+      {({ value, onChange, ref, ...control }) => {
+        const text = typeof value === "string" ? value : "";
+        if (field.field_type === "password") {
+          return (
+            <PasswordInput
+              {...control}
+              value={typeof value === "string" ? value : ""}
+              onChange={onChange}
+              ref={ref}
+              placeholder={field.placeholder || ""}
+            />
+          );
+        }
+        if (field.field_type === "textarea") {
+          return (
+            <Textarea
+              {...control}
+              ref={ref}
+              rows={3}
+              placeholder={field.placeholder || ""}
+              value={text}
+              onChange={onChange}
+            />
+          );
+        }
+        if (field.field_type === "select" && field.options) {
+          return (
+            <Select value={text || null} onValueChange={onChange}>
+              <SelectTrigger {...control} className="w-full">
+                <SelectValue placeholder={field.placeholder || ""} />
+              </SelectTrigger>
+              <SelectContent>
+                {field.options.map((option) => (
+                  <SelectItem key={option} value={option} title={option}>
+                    {option}
+                  </SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
+          );
+        }
+        return <Input {...control} ref={ref} placeholder={field.placeholder || ""} value={text} onChange={onChange} />;
+      }}
+    </AgentFormField>
+  );
+};
 
 const DynamicAgentFormFields: React.FC<DynamicAgentFormFieldsProps> = ({ agentTypeInfo, panels }) => (
   <>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx
index b2e0a42eecb..dae19032e20 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/api-reference/_components/APIReferenceView.test.tsx
@@ -13,17 +13,17 @@ describe("APIReferenceView", () => {
 
   it("uses the API doc base url when provided", () => {
     const apiDocUrl = "https://docs.litellm.test";
-    const { getAllByTestId } = render(<APIReferenceView proxySettings={{ LITELLM_UI_API_DOC_BASE_URL: apiDocUrl }} />);
+    render(<APIReferenceView proxySettings={{ LITELLM_UI_API_DOC_BASE_URL: apiDocUrl }} />);
 
-    const codeBlocks = getAllByTestId(codeBlockTestId);
+    const codeBlocks = screen.getAllByTestId(codeBlockTestId);
     expect(codeBlocks[0]).toHaveTextContent(new RegExp(apiDocUrl));
   });
 
   it("falls back to the proxy base url when the docs url is missing", () => {
     const proxyUrl = "https://proxy.litellm.test";
-    const { getAllByTestId } = render(<APIReferenceView proxySettings={{ PROXY_BASE_URL: proxyUrl }} />);
+    render(<APIReferenceView proxySettings={{ PROXY_BASE_URL: proxyUrl }} />);
 
-    const codeBlocks = getAllByTestId(codeBlockTestId);
+    const codeBlocks = screen.getAllByTestId(codeBlockTestId);
     expect(codeBlocks[0]).toHaveTextContent(new RegExp(proxyUrl));
   });
 
@@ -31,7 +31,7 @@ describe("APIReferenceView", () => {
     const apiDocUrl = "https://docs-preferred.litellm.test";
     const proxyUrl = "https://proxy-backup.litellm.test";
 
-    const { getAllByTestId } = render(
+    render(
       <APIReferenceView
         proxySettings={{
           LITELLM_UI_API_DOC_BASE_URL: apiDocUrl,
@@ -40,7 +40,7 @@ describe("APIReferenceView", () => {
       />,
     );
 
-    const codeBlocks = getAllByTestId(codeBlockTestId);
+    const codeBlocks = screen.getAllByTestId(codeBlockTestId);
     const renderedCode = codeBlocks[0].textContent ?? "";
     expect(renderedCode).toContain(apiDocUrl);
     expect(renderedCode).not.toContain(proxyUrl);
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/budget_modal.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/budget_modal.integration.test.tsx
index bc920e55abd..17a297d203d 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/budget_modal.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/budget_modal.integration.test.tsx
@@ -4,6 +4,7 @@ import React from "react";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 
 import BudgetModal from "./budget_modal";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 const { createMock } = vi.hoisted(() => ({ createMock: vi.fn() }));
 
@@ -63,8 +64,7 @@ describe("BudgetModal", () => {
     await openOptionalSettings(user);
     fireEvent.change(screen.getByLabelText("Max Budget (USD)"), { target: { value: "42.567" } });
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("monthly"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "monthly");
 
     await create(user);
 
@@ -80,8 +80,7 @@ describe("BudgetModal", () => {
 
     await openOptionalSettings(user);
     fireEvent.change(screen.getByLabelText("Max Budget (USD)"), { target: { value: "42.567" } });
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("monthly"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "monthly");
 
     await user.click(screen.getByText("Optional Settings"));
     await waitFor(() => expect(screen.queryByLabelText("Max Budget (USD)")).not.toBeInTheDocument());
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/edit_budget_modal.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/edit_budget_modal.integration.test.tsx
index 3fa96b54f1d..fe0ecfc10dd 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/edit_budget_modal.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/budgets/_components/edit_budget_modal.integration.test.tsx
@@ -6,6 +6,7 @@ import { beforeEach, describe, expect, it, vi } from "vitest";
 import type { components } from "@/lib/http/schema";
 
 import EditBudgetModal from "./edit_budget_modal";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 const { updateMock } = vi.hoisted(() => ({ updateMock: vi.fn() }));
 
@@ -73,8 +74,7 @@ describe("EditBudgetModal", () => {
     await user.clear(screen.getByLabelText("Max Budget (USD)"));
     fireEvent.change(screen.getByLabelText("Max Budget (USD)"), { target: { value: "42.567" } });
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("monthly"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "monthly");
 
     await save(user);
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx
index 9d4d5a6d425..372f27e2be1 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_settings/RedisTypeSelector.test.tsx
@@ -1,12 +1,10 @@
 import { describe, expect, it } from "vitest";
 import RedisTypeSelector from "./RedisTypeSelector";
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 
 describe("RedisTypeSelector", () => {
   it("should render the component", () => {
-    const { getAllByText } = render(
-      <RedisTypeSelector redisType="redis" redisTypeDescriptions={{}} onTypeChange={() => {}} />,
-    );
-    expect(getAllByText(/Redis/i).length).toBeGreaterThan(0);
+    render(<RedisTypeSelector redisType="redis" redisTypeDescriptions={{}} onTypeChange={() => {}} />);
+    expect(screen.getAllByText(/Redis/i).length).toBeGreaterThan(0);
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/coordination_redis_settings/CoordinationRedisTypeSelector.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/coordination_redis_settings/CoordinationRedisTypeSelector.test.tsx
index 76287e6e724..563c684237a 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/coordination_redis_settings/CoordinationRedisTypeSelector.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/coordination_redis_settings/CoordinationRedisTypeSelector.test.tsx
@@ -5,6 +5,7 @@ import userEvent from "@testing-library/user-event";
 import { renderWithProviders } from "@/../tests/test-utils";
 import CoordinationRedisTypeSelector from "./CoordinationRedisTypeSelector";
 import { COORDINATION_REDIS_TYPE_DESCRIPTIONS } from "./coordinationRedisFields";
+import { chooseSelectOption } from "../../../../../../tests/test-utils";
 
 describe("CoordinationRedisTypeSelector", () => {
   it("labels the control and shows the current selection", () => {
@@ -36,8 +37,7 @@ describe("CoordinationRedisTypeSelector", () => {
     const user = userEvent.setup();
     renderWithProviders(<CoordinationRedisTypeSelector redisType="node" onTypeChange={onTypeChange} />);
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("Cluster"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "Cluster");
 
     expect(onTypeChange).toHaveBeenCalledTimes(1);
     expect(onTypeChange.mock.calls[0][0]).toBe("cluster");
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
index 8c36b934789..f320d8e0f97 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
@@ -1,4 +1,4 @@
-import { fireEvent, render } from "@testing-library/react";
+import { fireEvent, render, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 
 import type { DailyData, KeyMetricWithMetadata, SpendMetrics } from "@/components/UsagePage/types";
@@ -79,25 +79,25 @@ const renderWith = (results: DailyData[], overrides: Partial<DailyActivityRange>
 
 describe("CacheLeakageCard", () => {
   it("ranks leaking keys by uncached prompt tokens and shows cache hit ratio", () => {
-    const { getByText, getByLabelText } = renderWith([
+    renderWith([
       dayWithKeys("2026-07-12", {
         "hash-caching": key("caching-key", { prompt_tokens: 1000, cache_read_input_tokens: 900 }),
         "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }),
       }),
     ]);
 
-    expect(getByText("leaky-key")).toBeInTheDocument();
-    expect(getByText("0.0%")).toBeInTheDocument();
-    expect(getByText("90.0%")).toBeInTheDocument();
+    expect(screen.getByText("leaky-key")).toBeInTheDocument();
+    expect(screen.getByText("0.0%")).toBeInTheDocument();
+    expect(screen.getByText("90.0%")).toBeInTheDocument();
     [
       "Input tokens you sent in this range that weren't served from or written to the cache",
       "Share of your input tokens that were served from the cache",
       "About how much you'd save if this uncached input used prompt caching. Estimated as uncached input tokens times what your cached traffic already nets per cached token (realized cache savings, after write premiums, ÷ cache read and write tokens). Blank when caching is not currently saving anything overall.",
-    ].forEach((info) => expect(getByLabelText(info)).toBeInTheDocument());
+    ].forEach((info) => expect(screen.getByLabelText(info)).toBeInTheDocument());
   });
 
   it("sorts by the clicked column, worst cache hit rate first", () => {
-    const { getAllByRole, getByText } = renderWith([
+    renderWith([
       dayWithKeys("2026-07-12", {
         "hash-a": key("alpha", {
           prompt_tokens: 10000,
@@ -111,48 +111,48 @@ describe("CacheLeakageCard", () => {
         }),
       }),
     ]);
-    const firstDataRow = () => getAllByRole("row")[1];
+    const firstDataRow = () => screen.getAllByRole("row")[1];
 
     expect(firstDataRow()).toHaveTextContent("alpha");
 
-    fireEvent.click(getByText("Cache hit rate"));
+    fireEvent.click(screen.getByText("Cache hit rate"));
     expect(firstDataRow()).toHaveTextContent("bravo");
 
-    fireEvent.click(getByText("Cache hit rate"));
+    fireEvent.click(screen.getByText("Cache hit rate"));
     expect(firstDataRow()).toHaveTextContent("alpha");
   });
 
   it("switches to the model view and lists only Anthropic models", () => {
-    const { getByText, queryByText } = renderWith([
+    renderWith([
       dayWithModels("2026-07-12", {
         "claude-sonnet-5": { prompt_tokens: 5000, cache_read_input_tokens: 0 },
         "gpt-4o": { prompt_tokens: 8000, cache_read_input_tokens: 0 },
       }),
     ]);
 
-    fireEvent.click(getByText("By model"));
+    fireEvent.click(screen.getByText("By model"));
 
-    expect(getByText("Cache leakage by model")).toBeInTheDocument();
-    expect(getByText("claude-sonnet-5")).toBeInTheDocument();
-    expect(queryByText("gpt-4o")).not.toBeInTheDocument();
+    expect(screen.getByText("Cache leakage by model")).toBeInTheDocument();
+    expect(screen.getByText("claude-sonnet-5")).toBeInTheDocument();
+    expect(screen.queryByText("gpt-4o")).not.toBeInTheDocument();
   });
 
   it("shows an empty state when no key used tokens in the range", () => {
-    const { getByText, queryByRole } = renderWith([dayWithKeys("2026-07-12", {})]);
+    renderWith([dayWithKeys("2026-07-12", {})]);
 
-    expect(getByText("No key usage in this range.")).toBeInTheDocument();
-    expect(queryByRole("table")).not.toBeInTheDocument();
+    expect(screen.getByText("No key usage in this range.")).toBeInTheDocument();
+    expect(screen.queryByRole("table")).not.toBeInTheDocument();
   });
 
   it("tells the user the table is still filling in while fallback pages stream", () => {
     const day = dayWithKeys("2026-07-12", {
       "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }),
     });
-    const { getByText, getByRole } = renderWith([day], { isFetchingMore: true });
+    renderWith([day], { isFetchingMore: true });
 
-    expect(getByRole("table")).toBeInTheDocument();
+    expect(screen.getByRole("table")).toBeInTheDocument();
     expect(
-      getByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
+      screen.getByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
     ).toBeInTheDocument();
   });
 
@@ -160,10 +160,10 @@ describe("CacheLeakageCard", () => {
     const day = dayWithKeys("2026-07-12", {
       "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }),
     });
-    const { queryByText } = renderWith([day], { loading: true });
+    renderWith([day], { loading: true });
 
     expect(
-      queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
+      screen.queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
     ).not.toBeInTheDocument();
   });
 
@@ -171,10 +171,10 @@ describe("CacheLeakageCard", () => {
     const day = dayWithKeys("2026-07-12", {
       "hash-leaky": key("leaky-key", { prompt_tokens: 10000, cache_read_input_tokens: 0 }),
     });
-    const { queryByText } = renderWith([day]);
+    renderWith([day]);
 
     expect(
-      queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
+      screen.queryByText("Data is still loading; rows and totals will update as the rest of the range arrives."),
     ).not.toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx
index 1cc7bec13d1..03250e3e53b 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.activity.test.tsx
@@ -1,5 +1,5 @@
 import React from "react";
-import { fireEvent, render, waitFor } from "@testing-library/react";
+import { fireEvent, render, waitFor, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
 
@@ -56,7 +56,7 @@ describe("CostOptimizationView daily activity", () => {
     useAuthorizedMock.mockReturnValue({ accessToken: "test-token", userId: "u1", userRole: "proxy_admin" });
     const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } });
 
-    const { getByRole, getByTestId, findByTestId, queryByText } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <CostOptimizationView accessToken="test-token" userId="u1" userRole="proxy_admin" />
       </QueryClientProvider>,
@@ -64,12 +64,12 @@ describe("CostOptimizationView daily activity", () => {
 
     await waitFor(() => expect(mockUserDailyActivityAggregatedCall).toHaveBeenCalledTimes(1));
 
-    fireEvent.click(getByRole("tab", { name: "Prompt Caching" }));
-    await findByTestId("caching-settings");
+    fireEvent.click(screen.getByRole("tab", { name: "Prompt Caching" }));
+    await screen.findByTestId("caching-settings");
 
     expect(mockUserDailyActivityAggregatedCall).toHaveBeenCalledTimes(1);
     expect(mockUserDailyActivityCall).not.toHaveBeenCalled();
-    expect(queryByText(/Currently fetching spend data/)).not.toBeInTheDocument();
+    expect(screen.queryByText(/Currently fetching spend data/)).not.toBeInTheDocument();
   });
 
   it("shows the fetch-progress banner while the paginated fallback streams pages in", async () => {
@@ -84,13 +84,13 @@ describe("CostOptimizationView daily activity", () => {
     useAuthorizedMock.mockReturnValue({ accessToken: "test-token", userId: "u1", userRole: "proxy_admin" });
     const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false } } });
 
-    const { findByText, getByRole } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <CostOptimizationView accessToken="test-token" userId="u1" userRole="proxy_admin" />
       </QueryClientProvider>,
     );
 
-    expect(await findByText(/Currently fetching spend data: fetched 1 \/ 3 pages/)).toBeInTheDocument();
-    expect(getByRole("button", { name: "Stop" })).toBeInTheDocument();
+    expect(await screen.findByText(/Currently fetching spend data: fetched 1 \/ 3 pages/)).toBeInTheDocument();
+    expect(screen.getByRole("button", { name: "Stop" })).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx
index d5df5aa75da..028367555a1 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CostOptimizationView.test.tsx
@@ -1,5 +1,5 @@
 import React from "react";
-import { fireEvent, render } from "@testing-library/react";
+import { fireEvent, render, screen } from "@testing-library/react";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
 
@@ -45,32 +45,32 @@ describe("CostOptimizationView", () => {
   });
 
   it("renders the standard page header with the sidebar's Cost Optimization icon", () => {
-    const { container, getByRole, getByText } = renderView();
+    const { container } = renderView();
 
-    expect(getByRole("heading", { level: 1, name: "Cost Optimization" })).toBeInTheDocument();
-    expect(getByText(/Track and configure the mechanisms that save you money/)).toBeInTheDocument();
+    expect(screen.getByRole("heading", { level: 1, name: "Cost Optimization" })).toBeInTheDocument();
+    expect(screen.getByText(/Track and configure the mechanisms that save you money/)).toBeInTheDocument();
     expect(container.querySelector(".lucide-piggy-bank")).not.toBeNull();
   });
 
   it("renders the four cost-optimization tabs", () => {
-    const { getByText } = renderView();
+    renderView();
 
-    expect(getByText("Overall")).toBeInTheDocument();
-    expect(getByText("Prompt Compression")).toBeInTheDocument();
-    expect(getByText("Prompt Caching")).toBeInTheDocument();
-    expect(getByText("Auto-Router")).toBeInTheDocument();
+    expect(screen.getByText("Overall")).toBeInTheDocument();
+    expect(screen.getByText("Prompt Compression")).toBeInTheDocument();
+    expect(screen.getByText("Prompt Caching")).toBeInTheDocument();
+    expect(screen.getByText("Auto-Router")).toBeInTheDocument();
   });
 
   it("defaults to the Overall tab and switches the active tab on click", () => {
-    const { getByRole } = renderView();
+    renderView();
 
-    expect(getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "true");
-    expect(getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "false");
+    expect(screen.getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "true");
+    expect(screen.getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "false");
 
-    fireEvent.click(getByRole("tab", { name: "Prompt Compression" }));
+    fireEvent.click(screen.getByRole("tab", { name: "Prompt Compression" }));
 
-    expect(getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "false");
-    expect(getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "true");
+    expect(screen.getByRole("tab", { name: "Overall" })).toHaveAttribute("aria-selected", "false");
+    expect(screen.getByRole("tab", { name: "Prompt Compression" })).toHaveAttribute("aria-selected", "true");
   });
 
   // Unlike the other three pages in this cleanup, Cost Optimization keeps its
@@ -80,21 +80,21 @@ describe("CostOptimizationView", () => {
   // are proxy-admin-only, so those are what disappear.
   describe("proxy-admin-only tabs", () => {
     it.each(["Internal User", "Internal Viewer", "Org Admin"])("shows %s the Overall tab only", (userRole) => {
-      const { getByRole, queryByRole } = renderView(userRole);
+      renderView(userRole);
 
-      expect(getByRole("tab", { name: "Overall" })).toBeInTheDocument();
-      expect(queryByRole("tab", { name: "Prompt Compression" })).not.toBeInTheDocument();
-      expect(queryByRole("tab", { name: "Prompt Caching" })).not.toBeInTheDocument();
-      expect(queryByRole("tab", { name: "Auto-Router" })).not.toBeInTheDocument();
+      expect(screen.getByRole("tab", { name: "Overall" })).toBeInTheDocument();
+      expect(screen.queryByRole("tab", { name: "Prompt Compression" })).not.toBeInTheDocument();
+      expect(screen.queryByRole("tab", { name: "Prompt Caching" })).not.toBeInTheDocument();
+      expect(screen.queryByRole("tab", { name: "Auto-Router" })).not.toBeInTheDocument();
     });
 
     it("never mounts the panels behind the admin-only endpoints for an internal user", () => {
-      const { getByTestId, queryByTestId } = renderView("Internal User");
+      renderView("Internal User");
 
-      expect(getByTestId("usage-tab")).toBeInTheDocument();
-      expect(queryByTestId("compression-tab")).not.toBeInTheDocument();
-      expect(queryByTestId("caching-tab")).not.toBeInTheDocument();
-      expect(queryByTestId("autorouter-benchmarks-tab")).not.toBeInTheDocument();
+      expect(screen.getByTestId("usage-tab")).toBeInTheDocument();
+      expect(screen.queryByTestId("compression-tab")).not.toBeInTheDocument();
+      expect(screen.queryByTestId("caching-tab")).not.toBeInTheDocument();
+      expect(screen.queryByTestId("autorouter-benchmarks-tab")).not.toBeInTheDocument();
     });
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx
index 38517dab0ab..2c602033171 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/PromptCachingTab.test.tsx
@@ -1,4 +1,4 @@
-import { render, waitFor } from "@testing-library/react";
+import { render, waitFor, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 
 const mockGetGeneralSettingsCall = vi.fn();
@@ -37,10 +37,10 @@ describe("PromptCachingTab", () => {
       cancelled: false,
       cancel: vi.fn(),
     };
-    const { getByTestId } = render(<PromptCachingTab accessToken="test-token" activity={activity} />);
+    render(<PromptCachingTab accessToken="test-token" activity={activity} />);
 
-    expect(getByTestId("caching-settings")).toBeInTheDocument();
-    expect(getByTestId("cache-leakage-card")).toBeInTheDocument();
+    expect(screen.getByTestId("caching-settings")).toBeInTheDocument();
+    expect(screen.getByTestId("cache-leakage-card")).toBeInTheDocument();
     await waitFor(() => expect(mockCacheLeakageCard).toHaveBeenCalledWith(expect.objectContaining({ activity })));
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.test.tsx
index ef6e224761d..a1de608d0bb 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.test.tsx
@@ -39,6 +39,35 @@ vi.mock("@/app/(dashboard)/hooks/keys/useKeys", () => ({
   })),
 }));
 
+vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({
+  useInfiniteTeams: vi.fn(() => ({
+    data: { pages: [{ teams: [{ team_id: "team-eng", team_alias: "engineering" }], page: 1, total_pages: 1 }] },
+    isLoading: false,
+    fetchNextPage: vi.fn(),
+    hasNextPage: false,
+    isFetchingNextPage: false,
+  })),
+}));
+
+vi.mock("@/app/(dashboard)/hooks/users/useUsers", () => ({
+  useInfiniteUsers: vi.fn(() => ({
+    data: {
+      pages: [
+        {
+          users: [{ user_id: "dev-alice", user_alias: null, user_email: "alice@example.com" }],
+          page: 1,
+          total_pages: 1,
+        },
+      ],
+    },
+    isPending: false,
+    isError: false,
+    fetchNextPage: vi.fn(),
+    hasNextPage: false,
+    isFetchingNextPage: false,
+  })),
+}));
+
 vi.mock("@/app/(dashboard)/hooks/models/useModels", () => ({
   useAutoRouters: vi.fn(() => ({
     data: [
@@ -60,7 +89,7 @@ vi.mock("@/app/(dashboard)/hooks/models/useModelCostMap", () => ({
   })),
 }));
 
-import ShadowEvalSection, { shadowedKeyLabel } from "./ShadowEvalSection";
+import ShadowEvalSection, { shadowedTargetLabel } from "./ShadowEvalSection";
 import {
   useShadowEvalJob,
   useShadowEvalJobs,
@@ -68,23 +97,26 @@ import {
   useStopShadowEval,
   type ShadowEvalJob,
 } from "./useShadowEval";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 const job = (overrides: Partial<ShadowEvalJob> = {}): ShadowEvalJob => ({
   job_id: "job-1",
   status: "running",
   router_name: "claude-auto",
+  router_names: ["claude-auto"],
   direction: "forward",
   baseline_model: null,
   judge_model: "anthropic/claude-sonnet-5",
   shadow_percentage: 10,
-  keys: [
+  targets: [
     {
-      api_key_id: "hashed-key-abc",
+      target_type: "key",
+      target_id: "hashed-key-abc",
       max_turns: 10000,
       max_budget: 10,
       spend: 3.21,
       stopped_at: null,
-      key_alias: "prod-alpha",
+      target_alias: "prod-alpha",
       key_name: "sk-...alpha",
     },
   ],
@@ -129,7 +161,6 @@ const job = (overrides: Partial<ShadowEvalJob> = {}): ShadowEvalJob => ({
         cache_hit_turns: 2,
       },
     ],
-    by_key: [],
     overall_shadow_win_rate_pct: 48.0,
     overall_tie_rate_pct: 22.0,
     sampled_real_spend: 0.6,
@@ -144,17 +175,18 @@ const job = (overrides: Partial<ShadowEvalJob> = {}): ShadowEvalJob => ({
   ...overrides,
 });
 
-const keyEntry = (
-  api_key_id: string,
-  overrides: Partial<ShadowEvalJob["keys"][number]> = {},
-): ShadowEvalJob["keys"][number] => ({
-  api_key_id,
+const targetEntry = (
+  target_id: string,
+  overrides: Partial<ShadowEvalJob["targets"][number]> = {},
+): ShadowEvalJob["targets"][number] => ({
+  target_type: "key",
+  target_id,
   max_turns: 10000,
   max_budget: 10,
   spend: 0,
   stopped_at: null,
   attempt_count: null,
-  key_alias: null,
+  target_alias: null,
   key_name: null,
   ...overrides,
 });
@@ -235,8 +267,8 @@ describe("ShadowEvalSection", () => {
   it("gives every active job its own card with a stop button, with the form still offered", () => {
     mockHooks({
       jobs: [
-        job({ job_id: "job-a", status: "running", keys: [keyEntry("key-a")] }),
-        job({ job_id: "job-b", status: "running", keys: [keyEntry("key-b")] }),
+        job({ job_id: "job-a", status: "running", targets: [targetEntry("key-a")] }),
+        job({ job_id: "job-b", status: "running", targets: [targetEntry("key-b")] }),
       ],
     });
     render(<ShadowEvalSection />);
@@ -347,7 +379,7 @@ describe("ShadowEvalSection", () => {
   });
 
   it("shows spend without a budget cap for a job from before spend budgets existed", () => {
-    const j = job({ keys: [keyEntry("hashed-key-abc", { max_budget: null, spend: 3.21 })] });
+    const j = job({ targets: [targetEntry("hashed-key-abc", { max_budget: null, spend: 3.21 })] });
     mockHooks({ jobs: [j], detailsById: { "job-1": j } });
     render(<ShadowEvalSection />);
     expect(screen.getByText(/\$3\.21 eval spend/)).toBeInTheDocument();
@@ -406,8 +438,7 @@ describe("ShadowEvalSection", () => {
     await user.click(within(keyList).getByText("prod-alpha"));
     await user.click(keyInput);
     await user.click(within(keyList).getByText("staging-beta"));
-    await user.click(screen.getByPlaceholderText("Select an auto-router"));
-    await user.click(await screen.findByText("gpt-auto"));
+    await chooseSelectOption(user, screen.getByPlaceholderText("Select up to 4 auto-routers"), "gpt-auto");
 
     expect(screen.getByText("Start shadow eval")).toBeDisabled();
 
@@ -417,7 +448,38 @@ describe("ShadowEvalSection", () => {
 
     const expectedBody = {
       api_key_ids: ["hash-alpha", "hash-beta"],
-      router_name: "gpt-auto",
+      team_ids: [],
+      user_ids: [],
+      router_names: ["gpt-auto"],
+      direction: "forward",
+      shadow_percentage: 10,
+      duration_days: 7,
+      max_budget: 10,
+      judge_model: "anthropic/claude-sonnet-5",
+    };
+    expect(start.mutate).toHaveBeenCalledWith(expectedBody);
+  });
+
+  it("submits a team-only job with team_ids and no keys", async () => {
+    const user = userEvent.setup();
+    const { start } = mockHooks({});
+    render(<ShadowEvalSection />);
+
+    expect(screen.getByText("Start shadow eval")).toBeDisabled();
+
+    await user.click(screen.getByPlaceholderText("Search teams by alias"));
+    const teamList = await screen.findByTestId("paginated-multi-select-list");
+    await user.click(within(teamList).getByText("engineering"));
+    await chooseSelectOption(user, screen.getByPlaceholderText("Select up to 4 auto-routers"), "gpt-auto");
+    await user.click(screen.getByPlaceholderText("Select a judge model"));
+    await user.click(await screen.findByRole("option", { name: /anthropic\/claude-sonnet-5/ }));
+    await user.click(screen.getByText("Start shadow eval"));
+
+    const expectedBody = {
+      api_key_ids: [],
+      team_ids: ["team-eng"],
+      user_ids: [],
+      router_names: ["gpt-auto"],
       direction: "forward",
       shadow_percentage: 10,
       duration_days: 7,
@@ -439,8 +501,7 @@ describe("ShadowEvalSection", () => {
     await user.click(screen.getByPlaceholderText("Search keys by alias"));
     const keyList = await screen.findByTestId("paginated-multi-select-list");
     await user.click(within(keyList).getByText("prod-alpha"));
-    await user.click(screen.getByPlaceholderText("Select an auto-router"));
-    await user.click(await screen.findByText("gpt-auto"));
+    await chooseSelectOption(user, screen.getByPlaceholderText("Select up to 4 auto-routers"), "gpt-auto");
     await user.click(screen.getByPlaceholderText("Select a judge model"));
     await user.click(await screen.findByRole("option", { name: /anthropic\/claude-sonnet-5/ }));
 
@@ -453,7 +514,9 @@ describe("ShadowEvalSection", () => {
 
     const expectedBody = {
       api_key_ids: ["hash-alpha"],
-      router_name: "gpt-auto",
+      team_ids: [],
+      user_ids: [],
+      router_names: ["gpt-auto"],
       direction: "reverse",
       baseline_model: "prod-claude",
       shadow_percentage: 10,
@@ -464,6 +527,119 @@ describe("ShadowEvalSection", () => {
     expect(start.mutate).toHaveBeenCalledWith(expectedBody);
   });
 
+  it("submits every picked auto-router so one job compares them on the same traffic", async () => {
+    const user = userEvent.setup();
+    const { start } = mockHooks({});
+    render(<ShadowEvalSection />);
+
+    await user.click(screen.getByPlaceholderText("Search keys by alias"));
+    const keyList = await screen.findByTestId("paginated-multi-select-list");
+    await user.click(within(keyList).getByText("prod-alpha"));
+    const routerInput = screen.getByPlaceholderText("Select up to 4 auto-routers");
+    await user.click(routerInput);
+    await user.click(await screen.findByText("gpt-auto"));
+    await user.click(routerInput);
+    await user.click(await screen.findByText("claude-auto"));
+    expect(
+      screen.getByText("Every router sees the same sampled requests, judged against the same live responses"),
+    ).toBeInTheDocument();
+    await user.click(screen.getByPlaceholderText("Select a judge model"));
+    await user.click(await screen.findByRole("option", { name: /anthropic\/claude-sonnet-5/ }));
+    await user.click(screen.getByText("Start shadow eval"));
+
+    const expectedBody = {
+      api_key_ids: ["hash-alpha"],
+      team_ids: [],
+      user_ids: [],
+      router_names: ["gpt-auto", "claude-auto"],
+      direction: "forward",
+      shadow_percentage: 10,
+      duration_days: 7,
+      max_budget: 10,
+      judge_model: "anthropic/claude-sonnet-5",
+    };
+    expect(start.mutate).toHaveBeenCalledWith(expectedBody);
+  });
+
+  it("blocks starting a reverse job with more than one router and says why", async () => {
+    const user = userEvent.setup();
+    mockHooks({});
+    render(<ShadowEvalSection />);
+
+    await user.click(screen.getByPlaceholderText("Search keys by alias"));
+    const keyList = await screen.findByTestId("paginated-multi-select-list");
+    await user.click(within(keyList).getByText("prod-alpha"));
+    const routerInput = screen.getByPlaceholderText("Select up to 4 auto-routers");
+    await user.click(routerInput);
+    await user.click(await screen.findByText("gpt-auto"));
+    await user.click(routerInput);
+    await user.click(await screen.findByText("claude-auto"));
+    await user.click(screen.getByText("Adoption check: key's traffic vs the router"));
+    await user.click(await screen.findByText("Regression check: router's picks vs a baseline"));
+    await user.click(screen.getByPlaceholderText("Select a judge model"));
+    await user.click(await screen.findByRole("option", { name: /anthropic\/claude-sonnet-5/ }));
+    await user.click(screen.getByPlaceholderText("Select a baseline model"));
+    await user.click(screen.getByRole("option", { name: /prod-claude/ }));
+
+    expect(screen.getByText("A regression check compares one router to its baseline")).toBeInTheDocument();
+    expect(screen.getByText("Start shadow eval")).toBeDisabled();
+  });
+
+  it("renders a per-router comparison table only when the job ran several routers", () => {
+    const routerSlice = (group: string, wins: number) => ({
+      group,
+      turn_count: 20,
+      real_win_rate_pct: 100 - wins - 10,
+      shadow_win_rate_pct: wins,
+      tie_rate_pct: 10,
+      avg_judge_confidence: 0.8,
+      real_spend: 0.4,
+      shadow_spend: 0.2,
+      cache_hit_turns: 0,
+    });
+    const base = job();
+    const multi = job({
+      router_names: ["claude-auto", "gpt-auto"],
+      results: { ...base.results!, by_router: [routerSlice("claude-auto", 40), routerSlice("gpt-auto", 70)] },
+    });
+    mockHooks({ jobs: [multi], detailsById: { "job-1": multi } });
+    render(<ShadowEvalSection />);
+
+    expect(screen.getByText("Router")).toBeInTheDocument();
+    const rows = screen.getAllByRole("row").map((row) => row.textContent ?? "");
+    expect(rows.some((text) => text.includes("claude-auto") && text.includes("40.0%"))).toBe(true);
+    expect(rows.some((text) => text.includes("gpt-auto") && text.includes("70.0%"))).toBe(true);
+    expect(
+      screen.getByText(
+        (_, element) =>
+          element?.textContent === "Shadowing 10% of prod-alpha traffic via claude-auto, gpt-auto" &&
+          element.tagName === "P",
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it("renders a job from an older proxy that predates router_names", () => {
+    const legacy = { ...job(), router_names: undefined } as unknown as ShadowEvalJob;
+    mockHooks({ jobs: [legacy], detailsById: { "job-1": legacy } });
+    render(<ShadowEvalSection />);
+
+    expect(
+      screen.getByText(
+        (_, element) =>
+          element?.textContent === "Shadowing 10% of prod-alpha traffic via claude-auto" && element.tagName === "P",
+      ),
+    ).toBeInTheDocument();
+  });
+
+  it("keeps the per-router table hidden for a single-router job", () => {
+    const base = job();
+    const single = job({ results: { ...base.results!, by_router: [] } });
+    mockHooks({ jobs: [single], detailsById: { "job-1": single } });
+    render(<ShadowEvalSection />);
+
+    expect(screen.queryByText("Router")).not.toBeInTheDocument();
+  });
+
   it("flips the arm labels and headline for a reverse job's results", () => {
     const j = job({ direction: "reverse", baseline_model: "openai/gpt-4o" });
     mockHooks({ jobs: [j], detailsById: { "job-1": j } });
@@ -485,9 +661,13 @@ describe("ShadowEvalSection", () => {
   });
 
   it("labels the shadowed key by alias, then masked name, then truncated hash", () => {
-    expect(shadowedKeyLabel(job().keys[0])).toBe("prod-alpha");
-    expect(shadowedKeyLabel(keyEntry("hashed-key-abc", { key_name: "sk-...alpha" }))).toBe("sk-...alpha");
-    expect(shadowedKeyLabel(keyEntry("hashed-key-abc"))).toBe("hashed-key…");
+    expect(shadowedTargetLabel(job().targets[0])).toBe("prod-alpha");
+    expect(shadowedTargetLabel(targetEntry("hashed-key-abc", { key_name: "sk-...alpha" }))).toBe("sk-...alpha");
+    expect(shadowedTargetLabel(targetEntry("hashed-key-abc"))).toBe("hashed-key…");
+    expect(shadowedTargetLabel(targetEntry("team-eng", { target_type: "team" }))).toBe("team-eng");
+    expect(shadowedTargetLabel(targetEntry("team-eng", { target_type: "team", target_alias: "engineering" }))).toBe(
+      "engineering",
+    );
   });
 
   it("breaks results down per key, so one key exhausting its own budget is visible while a sibling runs on", () => {
@@ -495,15 +675,12 @@ describe("ShadowEvalSection", () => {
       jobs: [
         job({
           judged_count: 205,
-          keys: [
-            keyEntry("hash-spent", { max_budget: 2, spend: 1.5, stopped_at: "2026-08-08T00:00:00Z" }),
-            keyEntry("hash-hungry", { max_budget: 5, spend: 0.2 }),
-          ],
-          results: {
-            by_tier: [],
-            by_current_model: [],
-            by_key: [
-              {
+          targets: [
+            targetEntry("hash-spent", {
+              max_budget: 2,
+              spend: 1.5,
+              stopped_at: "2026-08-08T00:00:00Z",
+              verdicts: {
                 group: "hash-spent",
                 turn_count: 200,
                 real_win_rate_pct: 20.0,
@@ -514,7 +691,12 @@ describe("ShadowEvalSection", () => {
                 shadow_spend: 0.5,
                 cache_hit_turns: 0,
               },
-            ],
+            }),
+            targetEntry("hash-hungry", { max_budget: 5, spend: 0.2 }),
+          ],
+          results: {
+            by_tier: [],
+            by_current_model: [],
             overall_shadow_win_rate_pct: 60.0,
             overall_tie_rate_pct: 20.0,
             sampled_real_spend: 0.9,
@@ -539,7 +721,7 @@ describe("ShadowEvalSection", () => {
 
     expect(screen.getByText(/205 turns judged/)).toBeInTheDocument();
     expect(screen.getByText(/Shadowing 10% of/)).toBeInTheDocument();
-    expect(screen.getByText("2 keys")).toBeInTheDocument();
+    expect(screen.getByText("2 targets")).toBeInTheDocument();
   });
 
   it("reads a key that spent its budget as completed even before the sweep stamps it", () => {
@@ -547,9 +729,9 @@ describe("ShadowEvalSection", () => {
     mockHooks({
       jobs: [
         job({
-          keys: [
-            keyEntry("hash-spent", { max_budget: 2, spend: 2, attempt_count: 40 }),
-            keyEntry("hash-hungry", legacyTurnBudgetLeg),
+          targets: [
+            targetEntry("hash-spent", { max_budget: 2, spend: 2, attempt_count: 40 }),
+            targetEntry("hash-hungry", legacyTurnBudgetLeg),
           ],
         }),
       ],
@@ -571,9 +753,9 @@ describe("ShadowEvalSection", () => {
         job({
           judged_count: 0,
           results: null,
-          keys: [
-            keyEntry("hash-spent", { max_budget: 0.5, spend: 0.5, attempt_count: 2 }),
-            keyEntry("hash-hungry", { max_budget: 5, spend: 0.01, attempt_count: 1 }),
+          targets: [
+            targetEntry("hash-spent", { max_budget: 0.5, spend: 0.5, attempt_count: 2 }),
+            targetEntry("hash-hungry", { max_budget: 5, spend: 0.01, attempt_count: 1 }),
           ],
         }),
       ],
@@ -594,9 +776,9 @@ describe("ShadowEvalSection", () => {
       jobs: [
         job({
           status: "completed",
-          keys: [
-            keyEntry("hash-spent", { max_turns: 200, stopped_at: "2026-08-08T00:00:00Z" }),
-            keyEntry("hash-hungry", { max_turns: 500 }),
+          targets: [
+            targetEntry("hash-spent", { max_turns: 200, stopped_at: "2026-08-08T00:00:00Z" }),
+            targetEntry("hash-hungry", { max_turns: 500 }),
           ],
         }),
       ],
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.tsx
index 39dee28390a..c66d74074c2 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.tsx
@@ -2,32 +2,24 @@
 
 import React, { useMemo, useState } from "react";
 
-import { useInfiniteKeys } from "@/app/(dashboard)/hooks/keys/useKeys";
 import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized";
-import { useModelCostMap } from "@/app/(dashboard)/hooks/models/useModelCostMap";
-import { useAutoRouters, usePlainModelGroups } from "@/app/(dashboard)/hooks/models/useModels";
-import { PaginatedMultiSelect } from "@/components/shared/PaginatedMultiSelect";
-import { SearchSelect, type SearchSelectOption } from "@/components/shared/SearchSelect";
 import { Badge } from "@/components/ui/badge";
 import { Button } from "@/components/ui/button";
 import { CircleHelp } from "lucide-react";
 
-import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
+import { Card } from "@/components/ui/card";
 import { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger } from "@/components/ui/tooltip";
-import { Input } from "@/components/ui/input";
-import { Label } from "@/components/ui/label";
-import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select";
 import { Table, TableBody, TableCell, TableHead, TableHeader, TableRow } from "@/components/ui/table";
 import { ApiError } from "@/lib/http/client";
 
 import { usd } from "./costOptimizationUtils";
+import { StartForm } from "./ShadowEvalStartForm";
 import {
   useShadowEvalJob,
   useShadowEvalJobs,
-  useStartShadowEval,
   useStopShadowEval,
   type ShadowEvalJob,
-  type ShadowEvalJobKey,
+  type ShadowEvalJobTarget,
   type ShadowEvalSlice,
 } from "./useShadowEval";
 
@@ -66,42 +58,46 @@ const routerMatchedOrBeatPct = (
     ? 100 - results.overall_shadow_win_rate_pct
     : results.overall_shadow_win_rate_pct + results.overall_tie_rate_pct;
 
-export const shadowedKeyLabel = (key: ShadowEvalJobKey): string =>
-  key.key_alias || key.key_name || `${key.api_key_id.slice(0, 10)}…`;
+export const shadowedTargetLabel = (target: ShadowEvalJobTarget): string =>
+  target.target_alias ||
+  target.key_name ||
+  (target.target_type === "key" ? `${target.target_id.slice(0, 10)}…` : target.target_id);
 
-const shadowedKeysLabel = (job: ShadowEvalJob): string =>
-  job.keys.length === 1 ? shadowedKeyLabel(job.keys[0]) : `${job.keys.length} keys`;
+const shadowedTargetsLabel = (job: ShadowEvalJob): string =>
+  job.targets.length === 1 ? shadowedTargetLabel(job.targets[0]) : `${job.targets.length} targets`;
 
 const totalBudget = (job: ShadowEvalJob): number | null =>
-  job.keys.reduce<number | null>(
-    (sum, key) => (sum === null || key.max_budget == null ? null : sum + key.max_budget),
+  job.targets.reduce<number | null>(
+    (sum, target) => (sum === null || target.max_budget == null ? null : sum + target.max_budget),
     0,
   );
 
-const totalSpend = (job: ShadowEvalJob): number => job.keys.reduce((sum, key) => sum + (key.spend ?? 0), 0);
+const totalSpend = (job: ShadowEvalJob): number => job.targets.reduce((sum, target) => sum + (target.spend ?? 0), 0);
 
-const keySpent = (key: ShadowEvalJobKey): boolean => {
-  const spendBudgetReached = key.max_budget != null && key.spend != null && key.spend >= key.max_budget;
-  const turnValveReached = key.attempt_count != null && key.attempt_count >= key.max_turns;
+const targetSpent = (target: ShadowEvalJobTarget): boolean => {
+  const spendBudgetReached = target.max_budget != null && target.spend != null && target.spend >= target.max_budget;
+  const turnValveReached = target.attempt_count != null && target.attempt_count >= target.max_turns;
   return spendBudgetReached || turnValveReached;
 };
 
-const keyStatus = (job: ShadowEvalJob, key: ShadowEvalJobKey): string => {
-  if (job.status === "completed" || (key.stopped_at == null && keySpent(key))) return "completed";
-  return key.stopped_at != null ? "stopped" : "running";
+const targetStatus = (job: ShadowEvalJob, target: ShadowEvalJobTarget): string => {
+  if (job.status === "completed" || (target.stopped_at == null && targetSpent(target))) return "completed";
+  return target.stopped_at != null ? "stopped" : "running";
 };
 
+const jobRouters = (job: ShadowEvalJob): string => (job.router_names ?? [job.router_name]).join(", ");
+
 const jobHeadline = (job: ShadowEvalJob): React.ReactNode =>
   job.direction === "reverse" ? (
     <>
-      Comparing <span className="font-mono text-xs">{job.router_name}</span> to{" "}
+      Comparing <span className="font-mono text-xs">{jobRouters(job)}</span> to{" "}
       <span className="font-mono text-xs">{job.baseline_model}</span> on {job.shadow_percentage}% of{" "}
-      <span className="font-mono text-xs">{shadowedKeysLabel(job)}</span> traffic
+      <span className="font-mono text-xs">{shadowedTargetsLabel(job)}</span> traffic
     </>
   ) : (
     <>
-      Shadowing {job.shadow_percentage}% of <span className="font-mono text-xs">{shadowedKeysLabel(job)}</span> traffic
-      via <span className="font-mono text-xs">{job.router_name}</span>
+      Shadowing {job.shadow_percentage}% of <span className="font-mono text-xs">{shadowedTargetsLabel(job)}</span>{" "}
+      traffic via <span className="font-mono text-xs">{jobRouters(job)}</span>
     </>
   );
 
@@ -255,13 +251,12 @@ const VerdictBar: React.FC<{ direction: ShadowEvalDirection; results: NonNullabl
   );
 };
 
-const KeyTable: React.FC<{ job: ShadowEvalJob }> = ({ job }) => {
-  const slices = new Map((job.results?.by_key ?? []).map((slice) => [slice.group, slice]));
+const TargetTable: React.FC<{ job: ShadowEvalJob }> = ({ job }) => {
   return (
     <Table>
       <TableHeader>
         <TableRow>
-          <TableHead>Key</TableHead>
+          <TableHead>Target</TableHead>
           <TableHead>Status</TableHead>
           {["Budget used", "Router wins", `${otherArmLabel(job.direction)} wins`].map((label) => (
             <TableHead key={label} className="text-right">
@@ -271,18 +266,23 @@ const KeyTable: React.FC<{ job: ShadowEvalJob }> = ({ job }) => {
         </TableRow>
       </TableHeader>
       <TableBody>
-        {job.keys.map((key) => {
-          const slice = slices.get(key.api_key_id);
+        {job.targets.map((target) => {
+          const slice = target.verdicts;
           return (
-            <TableRow key={key.api_key_id}>
-              <TableCell className="font-medium text-foreground">{shadowedKeyLabel(key)}</TableCell>
+            <TableRow key={`${target.target_type}:${target.target_id}`}>
+              <TableCell className="font-medium text-foreground">
+                {shadowedTargetLabel(target)}
+                {target.target_type !== "key" && (
+                  <span className="ml-2 text-xs font-normal text-muted-foreground">{target.target_type}</span>
+                )}
+              </TableCell>
               <TableCell>
-                <StatusBadge status={keyStatus(job, key)} />
+                <StatusBadge status={targetStatus(job, target)} />
               </TableCell>
               <TableCell className="text-right tabular-nums">
-                {key.max_budget != null
-                  ? `${usd(key.spend ?? 0)} / ${usd(key.max_budget)}`
-                  : `${(key.attempt_count ?? slice?.turn_count ?? 0).toLocaleString()} / ${key.max_turns.toLocaleString()} turns`}
+                {target.max_budget != null
+                  ? `${usd(target.spend ?? 0)} / ${usd(target.max_budget)}`
+                  : `${(target.attempt_count ?? slice?.turn_count ?? 0).toLocaleString()} / ${target.max_turns.toLocaleString()} turns`}
               </TableCell>
               {slice ? (
                 <>
@@ -318,9 +318,9 @@ const ResultsBody: React.FC<{ job: ShadowEvalJob; resultsError?: boolean }> = ({
   const hasVerdicts = results != null && (results.by_tier.length > 0 || results.by_current_model.length > 0);
   return (
     <>
-      {job.keys.length > 1 && (
+      {job.targets.length > 1 && (
         <div className="border-b">
-          <KeyTable job={job} />
+          <TargetTable job={job} />
         </div>
       )}
       {/* results == null re-stated for TS narrowing; hasVerdicts alone cannot narrow it */}
@@ -343,6 +343,11 @@ const ResultsBody: React.FC<{ job: ShadowEvalJob; resultsError?: boolean }> = ({
             <CostComparison direction={job.direction} results={results} />
           </div>
           <VerdictBar direction={job.direction} results={results} />
+          {(results.by_router ?? []).length > 1 && (
+            <div className="border-b">
+              <SliceTable groupHeader="Router" direction={job.direction} slices={results.by_router ?? []} />
+            </div>
+          )}
           {results.by_current_model.length > 0 && (
             <SliceTable
               groupHeader={job.direction === "reverse" ? "Router pick" : "Compared against"}
@@ -401,282 +406,6 @@ const JobResults: React.FC<{
   );
 };
 
-const RECOMMENDED_JUDGE_MODELS = ["anthropic/claude-sonnet-5", "openai/gpt-4o", "gemini/gemini-2.5-pro"] as const;
-
-interface CostMapEntry {
-  litellm_provider?: string;
-  mode?: string;
-}
-
-const useChatModelNames = (): string[] => {
-  const { data: costMap } = useModelCostMap();
-  return useMemo(() => {
-    if (!costMap) return [];
-    const chatModels = Object.entries(costMap as Record<string, CostMapEntry>)
-      .filter(([, value]) => value?.mode === "chat" && value?.litellm_provider)
-      .map(([key, value]) => (key.startsWith(`${value.litellm_provider}/`) ? key : `${value.litellm_provider}/${key}`));
-    return [...new Set(chatModels)].toSorted((a, b) => a.localeCompare(b));
-  }, [costMap]);
-};
-
-const useJudgeModelOptions = (): SearchSelectOption[] => {
-  const chatModels = useChatModelNames();
-  return useMemo(() => {
-    const pinned: SearchSelectOption[] = RECOMMENDED_JUDGE_MODELS.map((model) => ({
-      label: model,
-      value: model,
-      sublabel: "Recommended",
-    }));
-    const pinnedNames = new Set<string>(RECOMMENDED_JUDGE_MODELS);
-    const rest = chatModels.filter((model) => !pinnedNames.has(model)).map((model) => ({ label: model, value: model }));
-    return [...pinned, ...rest];
-  }, [chatModels]);
-};
-
-const useBaselineModelOptions = (): SearchSelectOption[] => {
-  const configuredGroups = usePlainModelGroups();
-  const chatModels = useChatModelNames();
-  return useMemo(() => {
-    const configured = [...configuredGroups]
-      .toSorted((a, b) => a.localeCompare(b))
-      .map((model) => ({ label: model, value: model, sublabel: "Configured on this gateway" }));
-    const rest = chatModels
-      .filter((model) => !configuredGroups.has(model))
-      .map((model) => ({ label: model, value: model }));
-    return [...configured, ...rest];
-  }, [configuredGroups, chatModels]);
-};
-
-const DIRECTION_OPTIONS: readonly { value: ShadowEvalDirection; label: string }[] = [
-  { value: "forward", label: "Adoption check: key's traffic vs the router" },
-  { value: "reverse", label: "Regression check: router's picks vs a baseline" },
-] as const;
-
-const START_FORM_DESCRIPTION: Record<ShadowEvalDirection, string> = {
-  forward:
-    "Duplicates a sampled slice of the selected keys' traffic through the auto-router and has an LLM judge compare both answers blind. Each key gets its own spend budget. The router's answers are never served to users; judge calls bill to the shadowed key.",
-  reverse:
-    "Duplicates a sampled slice of the traffic the auto-router already serves against a fixed baseline model and has an LLM judge compare both answers blind. Each key gets its own spend budget. The baseline's answers are never served to users; judge calls bill to the shadowed key.",
-};
-
-const DURATION_OPTIONS = [
-  { value: "1", label: "1 day" },
-  { value: "3", label: "3 days" },
-  { value: "7", label: "7 days" },
-  { value: "14", label: "14 days" },
-  { value: "30", label: "30 days" },
-] as const;
-
-const Field: React.FC<{ label: string; htmlFor?: string; className?: string; children: React.ReactNode }> = ({
-  label,
-  htmlFor,
-  className,
-  children,
-}) => (
-  <div className={`space-y-1.5 ${className ?? ""}`}>
-    <Label htmlFor={htmlFor} className="text-xs">
-      {label}
-    </Label>
-    {children}
-  </div>
-);
-
-const KeySelect: React.FC<{ value: string[]; onChange: (tokens: string[]) => void }> = ({ value, onChange }) => {
-  const [search, setSearch] = useState("");
-  const { data, isPending, isError, fetchNextPage, hasNextPage, isFetchingNextPage } = useInfiniteKeys(50, {
-    selectedKeyAlias: search || null,
-  });
-  const options = useMemo<SearchSelectOption[]>(
-    () =>
-      (data?.pages ?? [])
-        .flatMap((page) => page.keys)
-        .map((key) => ({
-          label: key.key_alias || key.key_name || key.token,
-          value: key.token,
-          sublabel: key.token,
-        })),
-    [data],
-  );
-  return (
-    <PaginatedMultiSelect
-      inputId="shadow-eval-key"
-      options={options}
-      value={value}
-      onValueChange={onChange}
-      onSearchChange={setSearch}
-      onLoadMore={() => void fetchNextPage()}
-      hasNextPage={hasNextPage}
-      isFetchingNextPage={isFetchingNextPage}
-      isLoading={isPending}
-      placeholder="Search keys by alias"
-      emptyText="No matching keys"
-      errorText={isError ? "Keys could not be loaded. Refresh the page to retry." : undefined}
-    />
-  );
-};
-
-const StartForm: React.FC = () => {
-  const { accessToken } = useAuthorized();
-  const [apiKeyIds, setApiKeyIds] = useState<string[]>([]);
-  const [routerName, setRouterName] = useState("");
-  const [direction, setDirection] = useState<ShadowEvalDirection>("forward");
-  const [baselineModel, setBaselineModel] = useState("");
-  const [percentage, setPercentage] = useState("10");
-  const [durationDays, setDurationDays] = useState("7");
-  const [judgeModel, setJudgeModel] = useState("");
-  const [maxBudget, setMaxBudget] = useState("10");
-  const { data: autoRouters } = useAutoRouters();
-  const judgeModelOptions = useJudgeModelOptions();
-  const baselineModelOptions = useBaselineModelOptions();
-  const start = useStartShadowEval();
-
-  const routerOptions = useMemo<SearchSelectOption[]>(() => {
-    const names = new Set(
-      (autoRouters ?? []).map((deployment) => deployment.model_name).filter((name): name is string => Boolean(name)),
-    );
-    return [...names].toSorted().map((name) => ({ label: name, value: name }));
-  }, [autoRouters]);
-
-  const parsedPct = Number.parseFloat(percentage);
-  const percentageValid = parsedPct >= 0.1 && parsedPct <= 100;
-  const parsedMaxBudget = Number.parseFloat(maxBudget);
-  const maxBudgetValid = parsedMaxBudget >= 0.01 && parsedMaxBudget <= 10000;
-  const baselinePicked = direction === "forward" || baselineModel !== "";
-  const filled = apiKeyIds.length > 0 && [routerName, judgeModel].every((field) => field !== "") && baselinePicked;
-  const boundsValid = percentageValid && maxBudgetValid;
-  const valid = Boolean(accessToken) && filled && boundsValid;
-  const handleStart = () => {
-    const startBody = {
-      api_key_ids: apiKeyIds,
-      router_name: routerName,
-      direction,
-      ...(direction === "reverse" ? { baseline_model: baselineModel } : {}),
-      shadow_percentage: parsedPct,
-      duration_days: Number.parseInt(durationDays, 10),
-      max_budget: parsedMaxBudget,
-      judge_model: judgeModel,
-    };
-    start.mutate(startBody);
-  };
-
-  return (
-    <Card size="sm">
-      <CardHeader>
-        <CardTitle className="text-sm font-medium text-foreground">Start a shadow eval</CardTitle>
-        <p className="text-xs text-muted-foreground">{START_FORM_DESCRIPTION[direction]}</p>
-      </CardHeader>
-      <CardContent className="space-y-3">
-        <div className="grid gap-3 sm:grid-cols-3">
-          <Field label="Direction">
-            <Select
-              value={direction}
-              onValueChange={(v: string | null) => setDirection(v === "reverse" ? "reverse" : "forward")}
-            >
-              <SelectTrigger className="w-full">
-                <SelectValue>{DIRECTION_OPTIONS.find((o) => o.value === direction)?.label}</SelectValue>
-              </SelectTrigger>
-              <SelectContent>
-                {DIRECTION_OPTIONS.map((option) => (
-                  <SelectItem key={option.value} value={option.value}>
-                    {option.label}
-                  </SelectItem>
-                ))}
-              </SelectContent>
-            </Select>
-          </Field>
-          <Field label="Keys to shadow" htmlFor="shadow-eval-key">
-            <KeySelect value={apiKeyIds} onChange={setApiKeyIds} />
-          </Field>
-          <Field label="Auto-router">
-            <SearchSelect
-              options={routerOptions}
-              value={routerName}
-              onValueChange={setRouterName}
-              placeholder="Select an auto-router"
-              emptyText="No auto-routers configured"
-            />
-          </Field>
-          <Field label="Traffic sampled" htmlFor="shadow-eval-pct">
-            <div className="flex items-center gap-2">
-              <Input
-                id="shadow-eval-pct"
-                type="number"
-                min={0.1}
-                max={100}
-                step={0.1}
-                className="w-24"
-                value={percentage}
-                onChange={(e) => setPercentage(e.target.value)}
-              />
-              <span className="text-sm text-muted-foreground">% of traffic</span>
-            </div>
-            <div>
-              {percentage.trim() !== "" && !percentageValid && (
-                <p className="text-xs text-destructive">Enter a value from 0.1 to 100</p>
-              )}
-            </div>
-          </Field>
-          <Field label="Duration">
-            <Select value={durationDays} onValueChange={(v: string | null) => setDurationDays(v ?? "7")}>
-              <SelectTrigger className="w-full">
-                <SelectValue>{DURATION_OPTIONS.find((o) => o.value === durationDays)?.label}</SelectValue>
-              </SelectTrigger>
-              <SelectContent>
-                {DURATION_OPTIONS.map((option) => (
-                  <SelectItem key={option.value} value={option.value}>
-                    {option.label}
-                  </SelectItem>
-                ))}
-              </SelectContent>
-            </Select>
-          </Field>
-          <Field label="Spend budget">
-            <div className="flex items-center gap-2">
-              <span className="text-sm text-muted-foreground">$</span>
-              <Input
-                type="number"
-                min={0.01}
-                max={10000}
-                step={0.01}
-                className="w-24"
-                value={maxBudget}
-                onChange={(e) => setMaxBudget(e.target.value)}
-              />
-              <span className="text-sm text-muted-foreground">max shadow + judge spend, per key</span>
-            </div>
-            {maxBudget.trim() !== "" && !maxBudgetValid && (
-              <p className="text-xs text-destructive">Enter a value from 0.01 to 10000</p>
-            )}
-          </Field>
-          {direction === "reverse" && (
-            <Field label="Baseline model">
-              <SearchSelect
-                options={baselineModelOptions}
-                value={baselineModel}
-                onValueChange={setBaselineModel}
-                placeholder="Select a baseline model"
-                emptyText="No chat models available"
-              />
-            </Field>
-          )}
-          <Field label="Judge model" className="sm:col-span-2">
-            <SearchSelect
-              options={judgeModelOptions}
-              value={judgeModel}
-              onValueChange={setJudgeModel}
-              placeholder="Select a judge model"
-              emptyText="No chat models available"
-            />
-          </Field>
-        </div>
-        <Button disabled={!valid || start.isPending} onClick={handleStart}>
-          {start.isPending ? "Starting..." : "Start shadow eval"}
-        </Button>
-      </CardContent>
-    </Card>
-  );
-};
-
 const previousSummary = (job: ShadowEvalJob): string => {
   const results = job.results;
   if (results) return pct(routerMatchedOrBeatPct(job.direction, results));
@@ -774,8 +503,9 @@ const ShadowEvalSection: React.FC = () => {
       <div className="flex flex-wrap items-baseline gap-2">
         <h2 className="text-xl font-semibold text-foreground">Shadow eval</h2>
         <p className="text-sm text-muted-foreground">
-          Blind-judge the auto-router on your real traffic: against the models a key uses today before switching, or
-          against a fixed baseline after it has switched.
+          Blind-judge the auto-router on the real traffic of a key, team, or user (teams and users cover
+          JWT-authenticated traffic): against the models they use today before switching, or against a fixed baseline
+          after they have switched.
         </p>
       </div>
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalStartForm.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalStartForm.tsx
new file mode 100644
index 00000000000..f96910a4ad6
--- /dev/null
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalStartForm.tsx
@@ -0,0 +1,432 @@
+"use client";
+
+import React, { useMemo, useState } from "react";
+
+import { useInfiniteKeys } from "@/app/(dashboard)/hooks/keys/useKeys";
+import { useInfiniteUsers } from "@/app/(dashboard)/hooks/users/useUsers";
+import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized";
+import { useModelCostMap } from "@/app/(dashboard)/hooks/models/useModelCostMap";
+import { useAutoRouters, usePlainModelGroups } from "@/app/(dashboard)/hooks/models/useModels";
+import { MultiSelect } from "@/components/shared/MultiSelect";
+import { PaginatedMultiSelect } from "@/components/shared/PaginatedMultiSelect";
+import TeamMultiSelect from "@/components/common_components/team_multi_select";
+import { userOptionLabel } from "@/components/common_components/UserDropdown";
+import { SearchSelect, type SearchSelectOption } from "@/components/shared/SearchSelect";
+import { Button } from "@/components/ui/button";
+import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
+import { Input } from "@/components/ui/input";
+import { Label } from "@/components/ui/label";
+import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select";
+
+import { useStartShadowEval, type ShadowEvalJob } from "./useShadowEval";
+
+type ShadowEvalDirection = ShadowEvalJob["direction"];
+
+const MAX_ROUTERS = 4;
+
+const RECOMMENDED_JUDGE_MODELS = ["anthropic/claude-sonnet-5", "openai/gpt-4o", "gemini/gemini-2.5-pro"] as const;
+
+interface CostMapEntry {
+  litellm_provider?: string;
+  mode?: string;
+}
+
+const useChatModelNames = (): string[] => {
+  const { data: costMap } = useModelCostMap();
+  return useMemo(() => {
+    if (!costMap) return [];
+    const chatModels = Object.entries(costMap as Record<string, CostMapEntry>)
+      .filter(([, value]) => value?.mode === "chat" && value?.litellm_provider)
+      .map(([key, value]) => (key.startsWith(`${value.litellm_provider}/`) ? key : `${value.litellm_provider}/${key}`));
+    return [...new Set(chatModels)].toSorted((a, b) => a.localeCompare(b));
+  }, [costMap]);
+};
+
+const useJudgeModelOptions = (): SearchSelectOption[] => {
+  const chatModels = useChatModelNames();
+  return useMemo(() => {
+    const pinned: SearchSelectOption[] = RECOMMENDED_JUDGE_MODELS.map((model) => ({
+      label: model,
+      value: model,
+      sublabel: "Recommended",
+    }));
+    const pinnedNames = new Set<string>(RECOMMENDED_JUDGE_MODELS);
+    const rest = chatModels.filter((model) => !pinnedNames.has(model)).map((model) => ({ label: model, value: model }));
+    return [...pinned, ...rest];
+  }, [chatModels]);
+};
+
+const useBaselineModelOptions = (): SearchSelectOption[] => {
+  const configuredGroups = usePlainModelGroups();
+  const chatModels = useChatModelNames();
+  return useMemo(() => {
+    const configured = [...configuredGroups]
+      .toSorted((a, b) => a.localeCompare(b))
+      .map((model) => ({ label: model, value: model, sublabel: "Configured on this gateway" }));
+    const rest = chatModels
+      .filter((model) => !configuredGroups.has(model))
+      .map((model) => ({ label: model, value: model }));
+    return [...configured, ...rest];
+  }, [configuredGroups, chatModels]);
+};
+
+const DIRECTION_OPTIONS: readonly { value: ShadowEvalDirection; label: string }[] = [
+  { value: "forward", label: "Adoption check: key's traffic vs the router" },
+  { value: "reverse", label: "Regression check: router's picks vs a baseline" },
+] as const;
+
+const START_FORM_DESCRIPTION: Record<ShadowEvalDirection, string> = {
+  forward:
+    "Duplicates a sampled slice of the selected targets' traffic (keys, teams, or users) through the auto-router and has an LLM judge compare both answers blind. Each target gets its own spend budget. The router's answers are never served to users; judge calls bill to the sampled traffic's own identity.",
+  reverse:
+    "Duplicates a sampled slice of the traffic the auto-router already serves against a fixed baseline model and has an LLM judge compare both answers blind. Each target gets its own spend budget. The baseline's answers are never served to users; judge calls bill to the sampled traffic's own identity.",
+};
+
+const DURATION_OPTIONS = [
+  { value: "1", label: "1 day" },
+  { value: "3", label: "3 days" },
+  { value: "7", label: "7 days" },
+  { value: "14", label: "14 days" },
+  { value: "30", label: "30 days" },
+] as const;
+
+const Field: React.FC<{ label: string; htmlFor?: string; className?: string; children: React.ReactNode }> = ({
+  label,
+  htmlFor,
+  className,
+  children,
+}) => (
+  <div className={`space-y-1.5 ${className ?? ""}`}>
+    <Label htmlFor={htmlFor} className="text-xs">
+      {label}
+    </Label>
+    {children}
+  </div>
+);
+
+const KeySelect: React.FC<{ value: string[]; onChange: (tokens: string[]) => void }> = ({ value, onChange }) => {
+  const [search, setSearch] = useState("");
+  const { data, isPending, isError, fetchNextPage, hasNextPage, isFetchingNextPage } = useInfiniteKeys(50, {
+    selectedKeyAlias: search || null,
+  });
+  const options = useMemo<SearchSelectOption[]>(
+    () =>
+      (data?.pages ?? [])
+        .flatMap((page) => page.keys)
+        .map((key) => ({
+          label: key.key_alias || key.key_name || key.token,
+          value: key.token,
+          sublabel: key.token,
+        })),
+    [data],
+  );
+  return (
+    <PaginatedMultiSelect
+      inputId="shadow-eval-key"
+      options={options}
+      value={value}
+      onValueChange={onChange}
+      onSearchChange={setSearch}
+      onLoadMore={() => void fetchNextPage()}
+      hasNextPage={hasNextPage}
+      isFetchingNextPage={isFetchingNextPage}
+      isLoading={isPending}
+      placeholder="Search keys by alias"
+      emptyText="No matching keys"
+      errorText={isError ? "Keys could not be loaded. Refresh the page to retry." : undefined}
+    />
+  );
+};
+
+const UserSelect: React.FC<{ value: string[]; onChange: (ids: string[]) => void }> = ({ value, onChange }) => {
+  const [search, setSearch] = useState("");
+  const { data, isPending, isError, fetchNextPage, hasNextPage, isFetchingNextPage } = useInfiniteUsers(
+    50,
+    search || undefined,
+  );
+  const options = useMemo<SearchSelectOption[]>(
+    () =>
+      Array.from(
+        new Map(
+          (data?.pages ?? [])
+            .flatMap((page) => page.users)
+            .map((user) => [user.user_id, { label: userOptionLabel(user), value: user.user_id }] as const),
+        ).values(),
+      ),
+    [data],
+  );
+  return (
+    <PaginatedMultiSelect
+      inputId="shadow-eval-user"
+      options={options}
+      value={value}
+      onValueChange={onChange}
+      onSearchChange={setSearch}
+      onLoadMore={() => void fetchNextPage()}
+      hasNextPage={hasNextPage}
+      isFetchingNextPage={isFetchingNextPage}
+      isLoading={isPending}
+      placeholder="Search users by email"
+      emptyText="No matching users"
+      errorText={isError ? "Users could not be loaded. Refresh the page to retry." : undefined}
+    />
+  );
+};
+
+const RouterField: React.FC<{
+  options: SearchSelectOption[];
+  routerNames: string[];
+  onChange: (names: string[]) => void;
+  direction: ShadowEvalDirection;
+}> = ({ options, routerNames, onChange, direction }) => (
+  <Field label="Auto-routers">
+    <MultiSelect
+      options={options}
+      value={routerNames}
+      onValueChange={onChange}
+      placeholder="Select up to 4 auto-routers"
+      emptyText="No auto-routers configured"
+    />
+    {routerNames.length > MAX_ROUTERS && (
+      <p className="text-xs text-destructive">Pick at most {MAX_ROUTERS} auto-routers</p>
+    )}
+    {direction === "reverse" && routerNames.length > 1 && (
+      <p className="text-xs text-destructive">A regression check compares one router to its baseline</p>
+    )}
+    {direction === "forward" && routerNames.length > 1 && (
+      <p className="text-xs text-muted-foreground">
+        Every router sees the same sampled requests, judged against the same live responses
+      </p>
+    )}
+  </Field>
+);
+
+interface StartFormValidityInputs {
+  accessToken: string | null | undefined;
+  apiKeyIds: string[];
+  teamIds: string[];
+  userIds: string[];
+  routerNames: string[];
+  direction: ShadowEvalDirection;
+  baselineModel: string;
+  judgeModel: string;
+  percentage: string;
+  maxBudget: string;
+}
+
+const startFormValidity = (inputs: StartFormValidityInputs) => {
+  const parsedPct = Number.parseFloat(inputs.percentage);
+  const percentageValid = parsedPct >= 0.1 && parsedPct <= 100;
+  const parsedMaxBudget = Number.parseFloat(inputs.maxBudget);
+  const maxBudgetValid = parsedMaxBudget >= 0.01 && parsedMaxBudget <= 10000;
+  const baselinePicked = inputs.direction === "forward" || inputs.baselineModel !== "";
+  const targetsPicked = inputs.apiKeyIds.length + inputs.teamIds.length + inputs.userIds.length > 0;
+  const routerCountValid = inputs.routerNames.length >= 1 && inputs.routerNames.length <= MAX_ROUTERS;
+  const routersMatchDirection = inputs.direction === "forward" || inputs.routerNames.length === 1;
+  const routersValid = routerCountValid && routersMatchDirection;
+  const modelsPicked = routersValid && inputs.judgeModel !== "" && baselinePicked;
+  const filled = targetsPicked && modelsPicked;
+  const boundsValid = percentageValid && maxBudgetValid;
+  const valid = Boolean(inputs.accessToken) && filled && boundsValid;
+  return { parsedPct, parsedMaxBudget, percentageValid, maxBudgetValid, valid };
+};
+
+interface StartBodyInputs {
+  apiKeyIds: string[];
+  teamIds: string[];
+  userIds: string[];
+  routerNames: string[];
+  direction: ShadowEvalDirection;
+  baselineModel: string;
+  shadowPercentage: number;
+  durationDays: number;
+  maxBudget: number;
+  judgeModel: string;
+}
+
+const buildStartBody = (inputs: StartBodyInputs) => ({
+  api_key_ids: inputs.apiKeyIds,
+  team_ids: inputs.teamIds,
+  user_ids: inputs.userIds,
+  router_names: inputs.routerNames,
+  direction: inputs.direction,
+  ...(inputs.direction === "reverse" ? { baseline_model: inputs.baselineModel } : {}),
+  shadow_percentage: inputs.shadowPercentage,
+  duration_days: inputs.durationDays,
+  max_budget: inputs.maxBudget,
+  judge_model: inputs.judgeModel,
+});
+
+export const StartForm: React.FC = () => {
+  const { accessToken } = useAuthorized();
+  const [apiKeyIds, setApiKeyIds] = useState<string[]>([]);
+  const [teamIds, setTeamIds] = useState<string[]>([]);
+  const [userIds, setUserIds] = useState<string[]>([]);
+  const [routerNames, setRouterNames] = useState<string[]>([]);
+  const [direction, setDirection] = useState<ShadowEvalDirection>("forward");
+  const [baselineModel, setBaselineModel] = useState("");
+  const [percentage, setPercentage] = useState("10");
+  const [durationDays, setDurationDays] = useState("7");
+  const [judgeModel, setJudgeModel] = useState("");
+  const [maxBudget, setMaxBudget] = useState("10");
+  const { data: autoRouters } = useAutoRouters();
+  const judgeModelOptions = useJudgeModelOptions();
+  const baselineModelOptions = useBaselineModelOptions();
+  const start = useStartShadowEval();
+
+  const routerOptions = useMemo<SearchSelectOption[]>(() => {
+    const names = new Set(
+      (autoRouters ?? []).map((deployment) => deployment.model_name).filter((name): name is string => Boolean(name)),
+    );
+    return [...names].toSorted().map((name) => ({ label: name, value: name }));
+  }, [autoRouters]);
+
+  const validityInputs: StartFormValidityInputs = {
+    accessToken,
+    apiKeyIds,
+    teamIds,
+    userIds,
+    routerNames,
+    direction,
+    baselineModel,
+    judgeModel,
+    percentage,
+    maxBudget,
+  };
+  const { parsedPct, parsedMaxBudget, percentageValid, maxBudgetValid, valid } = startFormValidity(validityInputs);
+  const handleStart = () => {
+    const bodyInputs: StartBodyInputs = {
+      apiKeyIds,
+      teamIds,
+      userIds,
+      routerNames,
+      direction,
+      baselineModel,
+      shadowPercentage: parsedPct,
+      durationDays: Number.parseInt(durationDays, 10),
+      maxBudget: parsedMaxBudget,
+      judgeModel,
+    };
+    start.mutate(buildStartBody(bodyInputs));
+  };
+
+  return (
+    <Card size="sm">
+      <CardHeader>
+        <CardTitle className="text-sm font-medium text-foreground">Start a shadow eval</CardTitle>
+        <p className="text-xs text-muted-foreground">{START_FORM_DESCRIPTION[direction]}</p>
+      </CardHeader>
+      <CardContent className="space-y-3">
+        <div className="grid gap-3 sm:grid-cols-3">
+          <Field label="Direction">
+            <Select
+              value={direction}
+              onValueChange={(v: string | null) => setDirection(v === "reverse" ? "reverse" : "forward")}
+            >
+              <SelectTrigger className="w-full">
+                <SelectValue>{DIRECTION_OPTIONS.find((o) => o.value === direction)?.label}</SelectValue>
+              </SelectTrigger>
+              <SelectContent>
+                {DIRECTION_OPTIONS.map((option) => (
+                  <SelectItem key={option.value} value={option.value}>
+                    {option.label}
+                  </SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
+          </Field>
+          <Field label="Keys to shadow" htmlFor="shadow-eval-key">
+            <KeySelect value={apiKeyIds} onChange={setApiKeyIds} />
+          </Field>
+          <Field label="Teams to shadow">
+            <TeamMultiSelect value={teamIds} onChange={setTeamIds} placeholder="Search teams by alias" />
+          </Field>
+          <Field label="Users to shadow" htmlFor="shadow-eval-user">
+            <UserSelect value={userIds} onChange={setUserIds} />
+          </Field>
+          <RouterField
+            options={routerOptions}
+            routerNames={routerNames}
+            onChange={setRouterNames}
+            direction={direction}
+          />
+          <Field label="Traffic sampled" htmlFor="shadow-eval-pct">
+            <div className="flex items-center gap-2">
+              <Input
+                id="shadow-eval-pct"
+                type="number"
+                min={0.1}
+                max={100}
+                step={0.1}
+                className="w-24"
+                value={percentage}
+                onChange={(e) => setPercentage(e.target.value)}
+              />
+              <span className="text-sm text-muted-foreground">% of traffic</span>
+            </div>
+            <div>
+              {percentage.trim() !== "" && !percentageValid && (
+                <p className="text-xs text-destructive">Enter a value from 0.1 to 100</p>
+              )}
+            </div>
+          </Field>
+          <Field label="Duration">
+            <Select value={durationDays} onValueChange={(v: string | null) => setDurationDays(v ?? "7")}>
+              <SelectTrigger className="w-full">
+                <SelectValue>{DURATION_OPTIONS.find((o) => o.value === durationDays)?.label}</SelectValue>
+              </SelectTrigger>
+              <SelectContent>
+                {DURATION_OPTIONS.map((option) => (
+                  <SelectItem key={option.value} value={option.value}>
+                    {option.label}
+                  </SelectItem>
+                ))}
+              </SelectContent>
+            </Select>
+          </Field>
+          <Field label="Spend budget">
+            <div className="flex items-center gap-2">
+              <span className="text-sm text-muted-foreground">$</span>
+              <Input
+                type="number"
+                min={0.01}
+                max={10000}
+                step={0.01}
+                className="w-24"
+                value={maxBudget}
+                onChange={(e) => setMaxBudget(e.target.value)}
+              />
+              <span className="text-sm text-muted-foreground">max shadow + judge spend, per target</span>
+            </div>
+            {maxBudget.trim() !== "" && !maxBudgetValid && (
+              <p className="text-xs text-destructive">Enter a value from 0.01 to 10000</p>
+            )}
+          </Field>
+          {direction === "reverse" && (
+            <Field label="Baseline model">
+              <SearchSelect
+                options={baselineModelOptions}
+                value={baselineModel}
+                onValueChange={setBaselineModel}
+                placeholder="Select a baseline model"
+                emptyText="No chat models available"
+              />
+            </Field>
+          )}
+          <Field label="Judge model" className="sm:col-span-2">
+            <SearchSelect
+              options={judgeModelOptions}
+              value={judgeModel}
+              onValueChange={setJudgeModel}
+              placeholder="Select a judge model"
+              emptyText="No chat models available"
+            />
+          </Field>
+        </div>
+        <Button disabled={!valid || start.isPending} onClick={handleStart}>
+          {start.isPending ? "Starting..." : "Start shadow eval"}
+        </Button>
+      </CardContent>
+    </Card>
+  );
+};
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx
index df23e5509bf..f85a667a074 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/UsageTab.test.tsx
@@ -1,4 +1,4 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 import type { ToolSpendResponse } from "@/components/networking";
@@ -152,13 +152,13 @@ describe("UsageTab", () => {
       gateway_injected_caching_savings_spend: 0.006,
       compression_saved_tokens: 100000,
     };
-    const { getByText } = renderWith([day("2026-07-12", firstDay), day("2026-07-13", secondDay)]);
+    renderWith([day("2026-07-12", firstDay), day("2026-07-13", secondDay)]);
 
-    expect(getByText("$0.1500")).toBeInTheDocument();
-    expect(getByText("$0.1400")).toBeInTheDocument();
-    expect(getByText("$0.0100")).toBeInTheDocument();
-    expect(getByText("$0.0160")).toBeInTheDocument();
-    expect(getByText("140,000 tokens compressed")).toBeInTheDocument();
+    expect(screen.getByText("$0.1500")).toBeInTheDocument();
+    expect(screen.getByText("$0.1400")).toBeInTheDocument();
+    expect(screen.getByText("$0.0100")).toBeInTheDocument();
+    expect(screen.getByText("$0.0160")).toBeInTheDocument();
+    expect(screen.getByText("140,000 tokens compressed")).toBeInTheDocument();
   });
 
   const twoDays = () => [
@@ -167,11 +167,11 @@ describe("UsageTab", () => {
   ];
 
   it("opens on a running total anchored at $0 at the start of the range", () => {
-    const { getByTestId } = renderWith(twoDays());
+    renderWith(twoDays());
 
     // Cumulative prepends a synthetic $0 point at the range start (Jul 1) so the
     // line rises from zero rather than floating; the daily running totals follow.
-    const series = readSeries(getByTestId("area-chart"));
+    const series = readSeries(screen.getByTestId("area-chart"));
     expect(series).toHaveLength(3);
     expect(series[0]).toMatchObject({ date: "Jul 1", Compression: 0, "Prompt caching": 0 });
     expect(series[1]).toMatchObject({ Compression: 0.04, "Prompt caching": 0.006 });
@@ -183,12 +183,12 @@ describe("UsageTab", () => {
     // The original complaint: a one-day range plotted a single floating dot. The
     // synthetic start anchor gives the line a zero origin to climb from.
     const oneDay = new Date(2026, 6, 24);
-    const { getByTestId } = renderWith(
-      [day("2026-07-24", { compression_savings_spend: 0.2, gateway_injected_caching_savings_spend: 0.05 })],
-      { from: oneDay, to: oneDay },
-    );
+    renderWith([day("2026-07-24", { compression_savings_spend: 0.2, gateway_injected_caching_savings_spend: 0.05 })], {
+      from: oneDay,
+      to: oneDay,
+    });
 
-    const series = readSeries(getByTestId("area-chart"));
+    const series = readSeries(screen.getByTestId("area-chart"));
     expect(series).toHaveLength(2);
     expect(series[0]).toMatchObject({ date: "Jul 24", Compression: 0, "Prompt caching": 0 });
     expect(series[1]).toMatchObject({ date: "Jul 24", Compression: 0.2, "Prompt caching": 0.05 });
@@ -202,49 +202,49 @@ describe("UsageTab", () => {
       day("2026-07-13", { gateway_injected_caching_savings_spend: 0.1 }),
       day("2026-07-12", { gateway_injected_caching_savings_spend: 0.04 }),
     ];
-    const { getByTestId, getByRole } = renderWith(newestFirst);
+    renderWith(newestFirst);
 
     // The $0 anchor leads, then the days climb oldest to newest.
-    const cumulative = readSeries(getByTestId("area-chart"));
+    const cumulative = readSeries(screen.getByTestId("area-chart"));
     expect(cumulative.map((p: { date: string }) => p.date)).toEqual(["Jul 1", "Jul 12", "Jul 13"]);
     expect(cumulative[1]["Prompt caching"]).toBeCloseTo(0.04, 5);
     expect(cumulative[2]["Prompt caching"]).toBeCloseTo(0.14, 5);
     expect(cumulative[2]["Prompt caching"]).toBeGreaterThan(cumulative[1]["Prompt caching"]);
 
-    await userEvent.click(getByRole("tab", { name: "Per day" }));
-    const perDay = readSeries(getByTestId("bar-chart"));
+    await userEvent.click(screen.getByRole("tab", { name: "Per day" }));
+    const perDay = readSeries(screen.getByTestId("bar-chart"));
     expect(perDay.map((p: { date: string }) => p.date)).toEqual(["Jul 12", "Jul 13"]);
   });
 
   it("draws bars of the raw per-interval readings on the other tab", async () => {
-    const { getByRole, getByTestId, queryByTestId } = renderWith(twoDays());
+    renderWith(twoDays());
 
     // Cumulative opens on the area line.
-    expect(getByTestId("area-chart")).toBeInTheDocument();
+    expect(screen.getByTestId("area-chart")).toBeInTheDocument();
 
-    await userEvent.click(getByRole("tab", { name: "Per day" }));
+    await userEvent.click(screen.getByRole("tab", { name: "Per day" }));
 
     // Per day switches to a bar chart of the unaccumulated daily savings, with no
     // synthetic anchor prepended.
-    expect(queryByTestId("area-chart")).not.toBeInTheDocument();
-    const series = readSeries(getByTestId("bar-chart"));
+    expect(screen.queryByTestId("area-chart")).not.toBeInTheDocument();
+    const series = readSeries(screen.getByTestId("bar-chart"));
     expect(series).toHaveLength(2);
     expect(series[0]).toMatchObject({ Compression: 0.04, "Prompt caching": 0.006 });
     expect(series[1]).toMatchObject({ Compression: 0.1, "Prompt caching": 0.01 });
   });
 
   it("says what the line means and over what range", async () => {
-    const { getByText, getByRole } = renderWith(twoDays());
+    renderWith(twoDays());
 
-    expect(getByText("Running total saved · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument();
-    await userEvent.click(getByRole("tab", { name: "Per day" }));
-    expect(getByText("Saved per day · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument();
+    expect(screen.getByText("Running total saved · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument();
+    await userEvent.click(screen.getByRole("tab", { name: "Per day" }));
+    expect(screen.getByText("Saved per day · Jul 1 – Jul 14 (UTC)")).toBeInTheDocument();
   });
 
   it("builds the per-driver donut from the range totals, not the running total", () => {
-    const { getByTestId } = renderWith(twoDays());
+    renderWith(twoDays());
 
-    const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
+    const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
     expect(slices).toEqual([
       { driver: "Compression", color: "emerald", usd: expect.closeTo(0.14, 5) },
       { driver: "Prompt caching", color: "blue", usd: expect.closeTo(0.016, 5) },
@@ -252,9 +252,9 @@ describe("UsageTab", () => {
   });
 
   it("omits a driver slice when that driver has no savings", () => {
-    const { getByTestId } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })]);
+    renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })]);
 
-    const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
+    const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
     expect(slices).toEqual([{ driver: "Compression", color: "emerald", usd: expect.closeTo(0.04, 5) }]);
   });
 
@@ -262,7 +262,7 @@ describe("UsageTab", () => {
     // Stacking sums the series into one bar. Auto-router savings go negative when a
     // model switch pays for a cold cache, and that segment would be drawn below the
     // axis while the rest of the bar still read as the day's total.
-    const { getByRole, getByTestId } = renderWith([
+    renderWith([
       day("2026-07-12", {
         compression_savings_spend: 0.1,
         gateway_injected_caching_savings_spend: 0.02,
@@ -270,8 +270,8 @@ describe("UsageTab", () => {
       }),
     ]);
 
-    await userEvent.click(getByRole("tab", { name: "Per day" }));
-    const bars = getByTestId("bar-chart");
+    await userEvent.click(screen.getByRole("tab", { name: "Per day" }));
+    const bars = screen.getByTestId("bar-chart");
     expect(bars).toHaveAttribute("data-stack", "false");
     expect(readSeries(bars)[0]).toMatchObject({ "Auto-router": -0.05 });
   });
@@ -281,10 +281,10 @@ describe("UsageTab", () => {
     // per day"). Hand-rolled rows made it compete with the legend and the toggle for
     // width, so the header grew a line on one tab and the chart moved with it. CardHeader
     // sizes the action column to its content and gives the rest to the title column.
-    const { getByRole, getByTestId, container } = renderWith(twoDays());
+    const { container } = renderWith(twoDays());
 
     const header = () => {
-      const legend = getByTestId("chart-legend");
+      const legend = screen.getByTestId("chart-legend");
       const action = legend.closest('[data-slot="card-action"]') as HTMLElement;
       const cardHeader = action.parentElement as HTMLElement;
       const description = cardHeader.querySelector('[data-slot="card-description"]') as HTMLElement;
@@ -295,12 +295,12 @@ describe("UsageTab", () => {
     expect(before.action).toBeTruthy();
     expect(before.description).toBeTruthy();
     // the toggle rides in the same action slot as the legend, so neither moves alone
-    expect(before.action.contains(getByRole("tablist"))).toBe(true);
+    expect(before.action.contains(screen.getByRole("tablist"))).toBe(true);
     // the subtitle lives outside that slot, so its length cannot reposition the controls
     expect(before.action.contains(before.description)).toBe(false);
     expect(before.description).toHaveTextContent(/Running total saved/);
 
-    await userEvent.click(getByRole("tab", { name: "Per day" }));
+    await userEvent.click(screen.getByRole("tab", { name: "Per day" }));
 
     const after = header();
     expect(after.action).toBe(before.action);
@@ -314,7 +314,7 @@ describe("UsageTab", () => {
     // Switching models leaves the new one with a cold cache, so a route can cost more
     // than the baseline would have. A negative slice is meaningless in a donut, but the
     // total has to keep the loss or the page can only ever report good news.
-    const { getByText, getByTestId } = renderWith([
+    renderWith([
       day("2026-07-12", {
         compression_savings_spend: 0.1,
         gateway_injected_caching_savings_spend: 0.02,
@@ -322,16 +322,16 @@ describe("UsageTab", () => {
       }),
     ]);
 
-    expect(getByText("$0.0700")).toBeInTheDocument();
-    expect(getByText("-$0.0500")).toBeInTheDocument();
+    expect(screen.getByText("$0.0700")).toBeInTheDocument();
+    expect(screen.getByText("-$0.0500")).toBeInTheDocument();
 
-    const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
+    const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
     expect(slices.map((d: { driver: string }) => d.driver)).toEqual(["Compression", "Prompt caching"]);
-    expect(getByTestId("donut-chart")).toHaveAttribute("data-label", "$0.1200");
+    expect(screen.getByTestId("donut-chart")).toHaveAttribute("data-label", "$0.1200");
   });
 
   it("carries auto-router savings into the summary card, donut slice, and cumulative series", () => {
-    const { getByText, getByTestId } = renderWith([
+    renderWith([
       day("2026-07-12", {
         compression_savings_spend: 0.04,
         gateway_injected_caching_savings_spend: 0.006,
@@ -345,11 +345,11 @@ describe("UsageTab", () => {
     ]);
 
     // Total saved now sums three drivers, and the auto-router card carries its own total.
-    expect(getByText("$0.2260")).toBeInTheDocument();
-    expect(getByText("$0.0700")).toBeInTheDocument();
+    expect(screen.getByText("$0.2260")).toBeInTheDocument();
+    expect(screen.getByText("$0.0700")).toBeInTheDocument();
 
     // The driver donut gains a third slice priced from the range totals.
-    const slices = JSON.parse(getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
+    const slices = JSON.parse(screen.getByTestId("donut-chart").getAttribute("data-slices") ?? "[]");
     expect(slices).toEqual([
       { driver: "Compression", color: "emerald", usd: expect.closeTo(0.14, 5) },
       { driver: "Prompt caching", color: "blue", usd: expect.closeTo(0.016, 5) },
@@ -357,7 +357,7 @@ describe("UsageTab", () => {
     ]);
 
     // And the cumulative line accumulates the auto-router series alongside the others.
-    const series = readSeries(getByTestId("area-chart"));
+    const series = readSeries(screen.getByTestId("area-chart"));
     expect(series[2]["Auto-router"]).toBeCloseTo(0.07, 5);
   });
 
@@ -371,9 +371,9 @@ describe("UsageTab", () => {
       start_date: "2026-07-12",
       end_date: "2026-07-12",
     };
-    const { findAllByTestId } = renderWith([day("2026-07-12", {})], { toolSpend });
+    renderWith([day("2026-07-12", {})], { toolSpend });
 
-    const bars = await findAllByTestId("bar-chart");
+    const bars = await screen.findAllByTestId("bar-chart");
     const series = JSON.parse(bars[0].getAttribute("data-series") ?? "[]");
     expect(series[0]).toMatchObject({ tool_name: "search", spend: 4.0 });
     // The 64px bar cap is this card's opt-in; the shared BarChart must not cap
@@ -391,14 +391,16 @@ describe("UsageTab", () => {
       start_date: "2026-07-12",
       end_date: "2026-07-12",
     };
-    const { findAllByTestId, getAllByTestId } = renderWith([day("2026-07-12", {})], { toolSpend });
+    renderWith([day("2026-07-12", {})], { toolSpend });
 
-    const bars = await findAllByTestId("bar-chart");
+    const bars = await screen.findAllByTestId("bar-chart");
     const [totalByTool, dailyByTool] = bars.slice(-2);
     expect(dailyByTool).toHaveAttribute("data-show-legend", "false");
     expect(totalByTool).toHaveAttribute("data-colors", dailyByTool.getAttribute("data-colors"));
 
-    const toolLegends = getAllByTestId("chart-legend").filter((legend) => legend.textContent === "search,read_file");
+    const toolLegends = screen
+      .getAllByTestId("chart-legend")
+      .filter((legend) => legend.textContent === "search,read_file");
     expect(toolLegends).toHaveLength(1);
   });
 
@@ -415,23 +417,23 @@ describe("UsageTab", () => {
     it.each(["Internal User", "Internal Viewer", "Org Admin"])(
       "hides the card and never calls the endpoint for %s",
       async (userRole) => {
-        const { queryByText, getByTestId } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], {
+        renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], {
           toolSpend,
           userRole,
         });
 
         // Liveness gate: the daily-activity charts still render for this role,
         // so the absence below is the gate, not an empty tab.
-        expect(getByTestId("donut-chart")).toBeInTheDocument();
-        expect(queryByText("Spend by tool")).not.toBeInTheDocument();
+        expect(screen.getByTestId("donut-chart")).toBeInTheDocument();
+        expect(screen.queryByText("Spend by tool")).not.toBeInTheDocument();
         await vi.waitFor(() => expect(mockGetToolSpend).not.toHaveBeenCalled());
       },
     );
 
     it("keeps the card and the endpoint call for an admin", async () => {
-      const { findByText } = renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { toolSpend });
+      renderWith([day("2026-07-12", { compression_savings_spend: 0.04 })], { toolSpend });
 
-      expect(await findByText("Spend by tool")).toBeInTheDocument();
+      expect(await screen.findByText("Spend by tool")).toBeInTheDocument();
       expect(mockGetToolSpend).toHaveBeenCalled();
     });
   });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/useShadowEval.ts b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/useShadowEval.ts
index eef98320e67..107df0f594a 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/useShadowEval.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/useShadowEval.ts
@@ -7,7 +7,7 @@ import { $api, fetchClient } from "@/lib/http/api";
 import type { components } from "@/lib/http/schema";
 
 export type ShadowEvalJob = components["schemas"]["ShadowEvalJobResponse"];
-export type ShadowEvalJobKey = components["schemas"]["ShadowEvalJobKeyResponse"];
+export type ShadowEvalJobTarget = components["schemas"]["ShadowEvalJobTargetResponse"];
 export type ShadowEvalSlice = components["schemas"]["ShadowEvalSlice"];
 export type StartShadowEvalRequest = components["schemas"]["StartShadowEvalRequest"];
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
index 03cfeed42ff..7785a8e44ab 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
@@ -312,4 +312,10 @@ export const GUARDRAIL_PRESETS: Record<string, GuardrailPreset> = {
     mode: "pre_call",
     defaultOn: false,
   },
+  alice: {
+    provider: "Alice",
+    guardrailNameSuggestion: "Alice",
+    mode: "pre_call",
+    defaultOn: false,
+  },
 };
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
index 13909e48185..1e486639840 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
@@ -27,6 +27,7 @@ const EXPECTED_PARTNER_LOGO_FILES: Record<string, string> = {
   deepkeep: "deepkeep.svg",
   repelloai: "repelloai.png",
   straiker: "straiker.svg",
+  alice: "alice.svg",
 };
 
 describe("guardrail_garden_data logos", () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
index 744af89a357..931b3a111d8 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
@@ -464,6 +464,16 @@ export const PARTNER_GUARDRAIL_CARDS: GuardrailCardInfo[] = [
     tags: ["Agentic", "Prompt Injection", "Tool Misuse", "MCP", "Skills"],
     providerKey: "Straiker",
   },
+  {
+    id: "alice",
+    name: "Alice",
+    description:
+      "Policy-based guardrails for prompts and model responses, evaluated per application so one proxy can enforce a different policy set per team or product.",
+    category: "partner",
+    logo: guardrailLogoMap["Alice"],
+    tags: ["Content Moderation", "Prompt Injection", "PII", "Policy"],
+    providerKey: "Alice",
+  },
 ];
 
 export const ALL_CARDS = [...LITELLM_CONTENT_FILTER_CARDS, ...PARTNER_GUARDRAIL_CARDS];
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
index 0a0f70b6bc2..dda56a06ab1 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
@@ -1,6 +1,7 @@
 import React, { useState } from "react";
 import { ArrowLeft } from "lucide-react";
 import { Button } from "@/components/ui/button";
+import { cn } from "@/lib/cva.config";
 import AddGuardrailForm from "./add_guardrail_form";
 import { Logo } from "@/components/molecules/logo/Logo";
 import { GUARDRAIL_PRESETS } from "./guardrail_garden_configs";
@@ -40,7 +41,7 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
   const tabs = [{ key: "overview", label: "Overview" }, ...(card.eval ? [{ key: "eval", label: "Eval Results" }] : [])];
 
   return (
-    <div style={{ maxWidth: 960, margin: "0 auto" }}>
+    <div className="mx-auto max-w-[960px]">
       {/* Back link */}
       <div
         onClick={onBack}
@@ -51,12 +52,12 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
       </div>
 
       {/* ── Header block (Vertex-style) ── */}
-      <div style={{ display: "flex", alignItems: "center", gap: 16, marginBottom: 8 }}>
+      <div className="mb-2 flex items-center gap-4">
         <Logo src={card.logo} label={card.name} className="w-10 h-10 rounded-lg object-contain shrink-0" />
-        <h1 style={{ fontSize: 28, fontWeight: 400, color: "#202124", margin: 0, lineHeight: 1.2 }}>{card.name}</h1>
+        <h1 className="m-0 text-[28px] font-normal leading-tight text-foreground">{card.name}</h1>
       </div>
 
-      <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 20px 0", lineHeight: 1.6 }}>{card.description}</p>
+      <p className="m-0 mb-5 text-sm leading-relaxed text-muted-foreground">{card.description}</p>
 
       {/* Action buttons — outlined style like Vertex */}
       <div className="mb-8 flex gap-2.5">
@@ -66,21 +67,18 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
       </div>
 
       {/* ── Tab bar ──────────────────────────────────── */}
-      <div style={{ borderBottom: "1px solid #dadce0", marginBottom: 28 }}>
-        <div style={{ display: "flex", gap: 0 }}>
+      <div className="mb-7 border-b border-border">
+        <div className="flex">
           {tabs.map((tab) => (
             <div
               key={tab.key}
               onClick={() => setActiveTab(tab.key)}
-              style={{
-                padding: "12px 20px",
-                fontSize: 14,
-                color: activeTab === tab.key ? "#1a73e8" : "#5f6368",
-                borderBottom: activeTab === tab.key ? "3px solid #1a73e8" : "3px solid transparent",
-                cursor: "pointer",
-                fontWeight: activeTab === tab.key ? 500 : 400,
-                marginBottom: -1,
-              }}
+              className={cn(
+                "-mb-px cursor-pointer border-b-[3px] px-5 py-3 text-sm",
+                activeTab === tab.key
+                  ? "border-info font-medium text-info"
+                  : "border-transparent font-normal text-muted-foreground",
+              )}
             >
               {tab.label}
             </div>
@@ -90,31 +88,27 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
 
       {/* ── Tab content ──────────────────────────────── */}
       {activeTab === "overview" && (
-        <div style={{ display: "flex", gap: 64 }}>
+        <div className="flex gap-16">
           {/* Left column — overview + details table */}
-          <div style={{ flex: 1, minWidth: 0 }}>
-            <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 12px 0" }}>Overview</h2>
-            <p style={{ fontSize: 14, color: "#3c4043", lineHeight: 1.7, margin: "0 0 32px 0" }}>{card.description}</p>
+          <div className="min-w-0 flex-1">
+            <h2 className="m-0 mb-3 text-lg font-normal text-foreground">Overview</h2>
+            <p className="m-0 mb-8 text-sm leading-[1.7] text-foreground">{card.description}</p>
 
-            <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 4px 0" }}>Guardrail Details</h2>
-            <p style={{ fontSize: 13, color: "#5f6368", margin: "0 0 16px 0" }}>Details are as follows</p>
+            <h2 className="m-0 mb-1 text-lg font-normal text-foreground">Guardrail Details</h2>
+            <p className="m-0 mb-4 text-[13px] text-muted-foreground">Details are as follows</p>
 
-            <table style={{ width: "100%", borderCollapse: "collapse", fontSize: 14 }}>
+            <table className="w-full border-collapse text-sm">
               <thead>
-                <tr style={{ borderBottom: "1px solid #dadce0" }}>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500, width: 200 }}>
-                    Property
-                  </th>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500 }}>
-                    {card.name}
-                  </th>
+                <tr className="border-b border-border">
+                  <th className="w-50 py-3 text-left font-medium text-muted-foreground">Property</th>
+                  <th className="py-3 text-left font-medium text-muted-foreground">{card.name}</th>
                 </tr>
               </thead>
               <tbody>
                 {detailRows.map((row, i) => (
-                  <tr key={i} style={{ borderBottom: "1px solid #f1f3f4" }}>
-                    <td style={{ padding: "12px 0", color: "#3c4043" }}>{row.property}</td>
-                    <td style={{ padding: "12px 0", color: "#202124" }}>{row.value}</td>
+                  <tr key={i} className="border-b border-border">
+                    <td className="py-3 text-foreground">{row.property}</td>
+                    <td className="py-3 text-foreground">{row.value}</td>
                   </tr>
                 ))}
               </tbody>
@@ -122,37 +116,30 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
           </div>
 
           {/* Right column — metadata sidebar like Vertex */}
-          <div style={{ width: 240, flexShrink: 0 }}>
+          <div className="w-60 shrink-0">
             {/* Guardrail ID */}
-            <div style={{ marginBottom: 28 }}>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Guardrail ID</div>
-              <div style={{ fontSize: 13, color: "#202124", wordBreak: "break-all" }}>litellm/{card.id}</div>
+            <div className="mb-7">
+              <div className="mb-1 text-xs text-muted-foreground">Guardrail ID</div>
+              <div className="break-all text-[13px] text-foreground">litellm/{card.id}</div>
             </div>
 
             {/* Type */}
-            <div style={{ marginBottom: 28 }}>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Type</div>
-              <div style={{ fontSize: 13, color: "#202124" }}>
+            <div className="mb-7">
+              <div className="mb-1 text-xs text-muted-foreground">Type</div>
+              <div className="text-[13px] text-foreground">
                 {card.category === "litellm" ? "Content Filter" : "Partner"}
               </div>
             </div>
 
             {/* Tags — pill style like Vertex */}
             {card.tags.length > 0 && (
-              <div style={{ marginBottom: 28 }}>
-                <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 8 }}>Tags</div>
-                <div style={{ display: "flex", flexWrap: "wrap", gap: 6 }}>
+              <div className="mb-7">
+                <div className="mb-2 text-xs text-muted-foreground">Tags</div>
+                <div className="flex flex-wrap gap-1.5">
                   {card.tags.map((tag) => (
                     <span
                       key={tag}
-                      style={{
-                        fontSize: 12,
-                        padding: "4px 12px",
-                        borderRadius: 16,
-                        border: "1px solid #dadce0",
-                        color: "#3c4043",
-                        backgroundColor: "#fff",
-                      }}
+                      className="rounded-2xl border border-border bg-card px-3 py-1 text-xs text-foreground"
                     >
                       {tag}
                     </span>
@@ -166,19 +153,19 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
 
       {activeTab === "eval" && (
         <div>
-          <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 16px 0" }}>Eval Results</h2>
-          <table style={{ width: "100%", maxWidth: 560, borderCollapse: "collapse", fontSize: 14 }}>
+          <h2 className="m-0 mb-4 text-lg font-normal text-foreground">Eval Results</h2>
+          <table className="w-full max-w-[560px] border-collapse text-sm">
             <thead>
-              <tr style={{ backgroundColor: "#f8f9fa", borderBottom: "1px solid #dadce0" }}>
-                <th style={{ textAlign: "left", padding: "12px 16px", color: "#5f6368", fontWeight: 500 }}>Metric</th>
-                <th style={{ textAlign: "left", padding: "12px 16px", color: "#5f6368", fontWeight: 500 }}>Value</th>
+              <tr className="border-b border-border bg-muted">
+                <th className="px-4 py-3 text-left font-medium text-muted-foreground">Metric</th>
+                <th className="px-4 py-3 text-left font-medium text-muted-foreground">Value</th>
               </tr>
             </thead>
             <tbody>
               {evalRows.map((row, i) => (
-                <tr key={i} style={{ borderBottom: "1px solid #f1f3f4" }}>
-                  <td style={{ padding: "12px 16px", color: "#3c4043" }}>{row.metric}</td>
-                  <td style={{ padding: "12px 16px", color: "#202124", fontWeight: 500 }}>{row.value}</td>
+                <tr key={i} className="border-b border-border">
+                  <td className="px-4 py-3 text-foreground">{row.metric}</td>
+                  <td className="px-4 py-3 font-medium text-foreground">{row.value}</td>
                 </tr>
               ))}
             </tbody>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx
index 2b90a1d8cbc..fcffc2122e7 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info.test.tsx
@@ -1,5 +1,5 @@
 import * as networking from "@/components/networking";
-import { fireEvent, render, waitFor, within } from "@testing-library/react";
+import { fireEvent, render, waitFor, within, screen } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { afterEach, describe, expect, it, vi } from "vitest";
 import GuardrailInfoView from "./guardrail_info";
@@ -65,21 +65,19 @@ describe("Guardrail Info", () => {
 
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { getAllByText, getByText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
     // Wait for the loading to complete and data to be rendered
     await waitFor(() => {
       // The guardrail name appears in multiple places (title and settings tab)
-      const elements = getAllByText("Test Guardrail");
+      const elements = screen.getAllByText("Test Guardrail");
       expect(elements.length).toBeGreaterThan(0);
     });
 
     // Verify other key elements are present
-    expect(getByText("Back to Guardrails")).toBeInTheDocument();
-    expect(getByText("Overview")).toBeInTheDocument();
-    expect(getByText("Settings")).toBeInTheDocument();
+    expect(screen.getByText("Back to Guardrails")).toBeInTheDocument();
+    expect(screen.getByText("Overview")).toBeInTheDocument();
+    expect(screen.getByText("Settings")).toBeInTheDocument();
   });
 
   it("should render a tag-based mode object rather than crashing the detail view", async () => {
@@ -105,11 +103,9 @@ describe("Guardrail Info", () => {
 
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { findAllByText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
-    expect(await findAllByText("pre_call, post_call (tag-based)")).not.toHaveLength(0);
+    expect(await screen.findAllByText("pre_call, post_call (tag-based)")).not.toHaveLength(0);
   });
 
   it("should render the provider logo from the bundled guardrail logo map", async () => {
@@ -135,11 +131,9 @@ describe("Guardrail Info", () => {
 
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { findByAltText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
-    const logo = await findByAltText("Presidio PII logo");
+    const logo = await screen.findByAltText("Presidio PII logo");
     expect(logo).toHaveAttribute("src", expect.stringContaining("microsoft_azure.svg"));
   });
 
@@ -167,25 +161,27 @@ describe("Guardrail Info", () => {
 
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { getByText, findByText, container } = render(
+    const { container } = render(
       <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
     );
 
     await waitFor(() => {
-      expect(getByText("Settings")).toBeInTheDocument();
+      expect(screen.getByText("Settings")).toBeInTheDocument();
     });
 
     // Click the Settings tab
-    fireEvent.click(getByText("Settings"));
+    fireEvent.click(screen.getByText("Settings"));
 
     // Wait for the Settings panel to render
     await waitFor(() => {
-      expect(getByText("Guardrail Settings")).toBeInTheDocument();
+      expect(screen.getByText("Guardrail Settings")).toBeInTheDocument();
     });
 
     await userEvent.hover(within(container).getByRole("img", { name: "Config guardrail details" }));
 
-    expect(await findByText("Guardrail is defined in the config file and cannot be edited.")).toBeInTheDocument();
+    expect(
+      await screen.findByText("Guardrail is defined in the config file and cannot be edited."),
+    ).toBeInTheDocument();
   });
 
   it("should render the guardrail info", async () => {
@@ -216,12 +212,10 @@ describe("Guardrail Info", () => {
 
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { getByText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
     await waitFor(() => {
-      expect(getByText("PII Entity Configuration")).toBeInTheDocument();
+      expect(screen.getByText("PII Entity Configuration")).toBeInTheDocument();
     });
   });
   it("should handle content filter updates correctly", async () => {
@@ -251,30 +245,28 @@ describe("Guardrail Info", () => {
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
     vi.mocked(networking.updateGuardrailCall).mockResolvedValue({ status: "success" });
 
-    const { getByText, getByLabelText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
     await waitFor(() => {
-      expect(getByText("Settings")).toBeInTheDocument();
+      expect(screen.getByText("Settings")).toBeInTheDocument();
     });
 
     // Go to Settings tab
-    fireEvent.click(getByText("Settings"));
+    fireEvent.click(screen.getByText("Settings"));
 
     await waitFor(() => {
-      expect(getByText("Guardrail Settings")).toBeInTheDocument();
+      expect(screen.getByText("Guardrail Settings")).toBeInTheDocument();
     });
 
     // Enter Edit Mode
-    fireEvent.click(getByText("Edit Settings"));
+    fireEvent.click(screen.getByText("Edit Settings"));
 
     // Modify Guardrail Name to force an update
-    const nameInput = getByLabelText("Guardrail Name");
+    const nameInput = screen.getByLabelText("Guardrail Name");
     fireEvent.change(nameInput, { target: { value: "Updated Name" } });
 
     // Save with only name change
-    const saveButton = getByText("Save Changes");
+    const saveButton = screen.getByText("Save Changes");
     fireEvent.click(saveButton);
 
     await waitFor(() => {
@@ -300,16 +292,16 @@ describe("Guardrail Info", () => {
 
     // Enter Edit Mode again to make changes
     await waitFor(() => {
-      expect(getByText("Edit Settings")).toBeInTheDocument();
+      expect(screen.getByText("Edit Settings")).toBeInTheDocument();
     });
-    fireEvent.click(getByText("Edit Settings"));
+    fireEvent.click(screen.getByText("Edit Settings"));
 
     // Now modify the values using the mock button
-    const simulateChangeButton = getByText("Simulate Change");
+    const simulateChangeButton = screen.getByText("Simulate Change");
     fireEvent.click(simulateChangeButton);
 
     // Save again
-    fireEvent.click(getByText("Save Changes"));
+    fireEvent.click(screen.getByText("Save Changes"));
 
     await waitFor(() => {
       expect(networking.updateGuardrailCall).toHaveBeenCalled();
@@ -339,12 +331,10 @@ describe("Guardrail Info", () => {
     });
     vi.mocked(networking.getGuardrailProviderSpecificParams).mockResolvedValue({});
 
-    const { findByRole, getByRole, getByText } = render(
-      <GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />,
-    );
+    render(<GuardrailInfoView guardrailId="123" onClose={() => {}} accessToken="123" isAdmin={true} />);
 
-    expect(await findByRole("tab", { name: "Overview" })).toHaveAttribute("aria-selected", "true");
-    expect(getByRole("tab", { name: "Settings" })).toHaveAttribute("aria-selected", "false");
-    expect(getByText("Guardrail Settings")).toBeInTheDocument();
+    expect(await screen.findByRole("tab", { name: "Overview" })).toHaveAttribute("aria-selected", "true");
+    expect(screen.getByRole("tab", { name: "Settings" })).toHaveAttribute("aria-selected", "false");
+    expect(screen.getByText("Guardrail Settings")).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
index 83038b8e0e7..c1f2ddcf51c 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
@@ -1,5 +1,6 @@
 import aimSecurityLogo from "../../../../../public/assets/logos/aim_security.jpeg";
 import aktoLogo from "../../../../../public/assets/logos/akto.svg";
+import aliceLogo from "../../../../../public/assets/logos/alice.svg";
 import aporiaLogo from "../../../../../public/assets/logos/aporia.png";
 import bedrockLogo from "../../../../../public/assets/logos/bedrock.svg";
 import catoNetworksLogo from "../../../../../public/assets/logos/cato_networks.svg";
@@ -83,6 +84,7 @@ export const guardrail_provider_map: Record<string, string> = {
   Deepkeep: "deepkeep",
   QostodianNexus: "qostodian_nexus",
   Repelloai: "repelloai",
+  Alice: "alice",
 };
 
 // Function to populate provider map from API response - updates the original map
@@ -204,6 +206,7 @@ export const guardrailLogoMap = {
   "Qostodian Nexus": qohashLogo.src,
   "RepelloAI Argus": repelloAiLogo.src,
   Straiker: straikerLogo.src,
+  Alice: aliceLogo.src,
 } satisfies Record<string, string>;
 
 export const getGuardrailLogo = (displayName: string): string | undefined =>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx
index 2f839487111..30ff2cf7c5f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_components.test.tsx
@@ -1,4 +1,4 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import { describe, it, expect } from "vitest";
 import { CategoryFilter, QuickActions, PiiEntityList } from "./pii_components";
 import type { PiiEntityCategory } from "@/components/guardrails/types";
@@ -6,25 +6,21 @@ import type { PiiEntityCategory } from "@/components/guardrails/types";
 describe("CategoryFilter", () => {
   it("should render", () => {
     const emptyCategories: PiiEntityCategory[] = [];
-    const { getByText } = render(
-      <CategoryFilter categories={emptyCategories} selectedCategories={[]} onChange={() => {}} />,
-    );
-    expect(getByText("Filter by category")).toBeInTheDocument();
+    render(<CategoryFilter categories={emptyCategories} selectedCategories={[]} onChange={() => {}} />);
+    expect(screen.getByText("Filter by category")).toBeInTheDocument();
   });
 });
 
 describe("QuickActions", () => {
   it("should render", () => {
-    const { getByText } = render(
-      <QuickActions onSelectAll={() => {}} onUnselectAll={() => {}} hasSelectedEntities={false} />,
-    );
-    expect(getByText("Quick Actions")).toBeInTheDocument();
+    render(<QuickActions onSelectAll={() => {}} onUnselectAll={() => {}} hasSelectedEntities={false} />);
+    expect(screen.getByText("Quick Actions")).toBeInTheDocument();
   });
 });
 
 describe("PiiEntityList", () => {
   it("should render", () => {
-    const { getByText } = render(
+    render(
       <PiiEntityList
         entities={[]}
         selectedEntities={[]}
@@ -35,6 +31,6 @@ describe("PiiEntityList", () => {
         entityToCategoryMap={new Map()}
       />,
     );
-    expect(getByText("No PII types match your filter criteria")).toBeInTheDocument();
+    expect(screen.getByText("No PII types match your filter criteria")).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx
index 00c568ef35b..4f822578fe8 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/pii_configuration.test.tsx
@@ -1,10 +1,10 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import { describe, it, expect } from "vitest";
 import PiiConfiguration from "./pii_configuration";
 
 describe("PiiConfiguration", () => {
   it("should render", () => {
-    const { getByText } = render(
+    render(
       <PiiConfiguration
         entities={[]}
         actions={[]}
@@ -15,6 +15,6 @@ describe("PiiConfiguration", () => {
         entityCategories={[]}
       />,
     );
-    expect(getByText("Configure PII Protection")).toBeInTheDocument();
+    expect(screen.getByText("Configure PII Protection")).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings.ts
new file mode 100644
index 00000000000..8645e867c16
--- /dev/null
+++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings.ts
@@ -0,0 +1,47 @@
+import { useMutation, useQuery, useQueryClient } from "@tanstack/react-query";
+import { apiClient } from "@/components/networking";
+import type { components } from "@/lib/http/schema";
+import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized";
+import { createQueryKeys } from "../common/queryKeysFactory";
+
+export type MCPToolSearchSettings = components["schemas"]["MCPToolSearchSettings"];
+export type MCPToolSearchSettingsResponse = components["schemas"]["MCPToolSearchSettingsResponse"];
+
+const GET_PATH = "/get/mcp_tool_search_settings";
+const UPDATE_PATH = "/update/mcp_tool_search_settings";
+
+const mcpToolSearchSettingsKeys = createQueryKeys("mcpToolSearchSettings");
+
+export const getMCPToolSearchSettings = (accessToken: string): Promise<MCPToolSearchSettingsResponse> =>
+  apiClient.get<MCPToolSearchSettingsResponse>(GET_PATH, { accessToken });
+
+export const updateMCPToolSearchSettings = (
+  accessToken: string,
+  settings: MCPToolSearchSettings,
+): Promise<MCPToolSearchSettings> =>
+  apiClient.patch<MCPToolSearchSettings>(UPDATE_PATH, { accessToken, body: settings });
+
+export const useMCPToolSearchSettings = () => {
+  const { accessToken } = useAuthorized();
+  return useQuery<MCPToolSearchSettingsResponse>({
+    queryKey: mcpToolSearchSettingsKeys.list({}),
+    queryFn: () => getMCPToolSearchSettings(accessToken),
+    enabled: !!accessToken,
+  });
+};
+
+export const useUpdateMCPToolSearchSettings = () => {
+  const { accessToken } = useAuthorized();
+  const queryClient = useQueryClient();
+  return useMutation<MCPToolSearchSettings, Error, MCPToolSearchSettings>({
+    mutationFn: (settings) => {
+      if (!accessToken) {
+        throw new Error("Access token is required");
+      }
+      return updateMCPToolSearchSettings(accessToken, settings);
+    },
+    onSuccess: () => {
+      queryClient.invalidateQueries({ queryKey: mcpToolSearchSettingsKeys.all });
+    },
+  });
+};
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/ToolTestPanel.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/ToolTestPanel.test.tsx
index 26e66c8338c..81c55e7982a 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/ToolTestPanel.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/ToolTestPanel.test.tsx
@@ -6,6 +6,7 @@ import { describe, expect, it, vi } from "vitest";
 
 import { ToolTestPanel } from "./ToolTestPanel";
 import { InputSchema, MCPTool } from "@/components/mcp_tools/types";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 const buildTool = (schema: InputSchema | string): MCPTool => ({
   name: "demo-tool",
@@ -229,8 +230,7 @@ describe("ToolTestPanel argument payload", () => {
     const onSubmit = await submitPanel(
       { type: "object", properties: { active: { type: "boolean", default: false } } },
       async (user) => {
-        await user.click(screen.getByLabelText("active"));
-        await user.click(await screen.findByText("True"));
+        await chooseSelectOption(user, screen.getByLabelText("active"), "True");
       },
     );
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx
index 8dca87e24ef..8abb8855e3d 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.test.tsx
@@ -45,7 +45,7 @@ describe("MCPServers", () => {
     vi.mocked(networking.fetchMCPServers).mockResolvedValue([]);
 
     const queryClient = createQueryClient();
-    const { getByText } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <MCPServers {...defaultProps} />
       </QueryClientProvider>,
@@ -53,11 +53,11 @@ describe("MCPServers", () => {
 
     // Wait for the component to load and check if title renders
     await waitFor(() => {
-      expect(getByText("MCP Servers")).toBeInTheDocument();
+      expect(screen.getByText("MCP Servers")).toBeInTheDocument();
     });
 
     // Verify the title is rendered
-    expect(getByText("MCP Servers")).toBeInTheDocument();
+    expect(screen.getByText("MCP Servers")).toBeInTheDocument();
   });
 
   it("should render mocked MCP servers data in the table", async () => {
@@ -96,7 +96,7 @@ describe("MCPServers", () => {
     vi.mocked(networking.fetchMCPServers).mockResolvedValue(mockServers);
 
     const queryClient = createQueryClient();
-    const { getByText, getAllByText } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <MCPServers {...defaultProps} />
       </QueryClientProvider>,
@@ -104,19 +104,19 @@ describe("MCPServers", () => {
 
     // Wait for the component to load
     await waitFor(() => {
-      expect(getByText("MCP Servers")).toBeInTheDocument();
+      expect(screen.getByText("MCP Servers")).toBeInTheDocument();
     });
 
     // Wait for the mocked data to render in the table
     await waitFor(() => {
-      expect(getByText("Test Server 1")).toBeInTheDocument();
+      expect(screen.getByText("Test Server 1")).toBeInTheDocument();
     });
 
     // Verify the mocked server data is rendered in the table
-    expect(getByText("Test Server 1")).toBeInTheDocument();
-    expect(getByText("Test Server 2")).toBeInTheDocument();
-    expect(getAllByText("test-server-1").length).toBeGreaterThan(0);
-    expect(getAllByText("test-server-2").length).toBeGreaterThan(0);
+    expect(screen.getByText("Test Server 1")).toBeInTheDocument();
+    expect(screen.getByText("Test Server 2")).toBeInTheDocument();
+    expect(screen.getAllByText("test-server-1").length).toBeGreaterThan(0);
+    expect(screen.getAllByText("test-server-2").length).toBeGreaterThan(0);
 
     // Verify the API was called
     // Note: useMCPServers uses useAuthorized() internally, which returns "123" from global mock
@@ -168,7 +168,7 @@ describe("MCPServers", () => {
     vi.mocked(networking.fetchMCPServerHealth).mockResolvedValue(mockHealthStatuses);
 
     const queryClient = createQueryClient();
-    const { getByText } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <MCPServers {...defaultProps} />
       </QueryClientProvider>,
@@ -176,7 +176,7 @@ describe("MCPServers", () => {
 
     // Wait for the component to load
     await waitFor(() => {
-      expect(getByText("MCP Servers")).toBeInTheDocument();
+      expect(screen.getByText("MCP Servers")).toBeInTheDocument();
     });
 
     // Verify the health check API was called (without a server ID filter — the hook always
@@ -211,7 +211,7 @@ describe("MCPServers", () => {
     );
 
     const queryClient = createQueryClient();
-    const { getByText } = render(
+    render(
       <QueryClientProvider client={queryClient}>
         <MCPServers {...defaultProps} />
       </QueryClientProvider>,
@@ -219,7 +219,7 @@ describe("MCPServers", () => {
 
     // Wait for the component to load
     await waitFor(() => {
-      expect(getByText("MCP Servers")).toBeInTheDocument();
+      expect(screen.getByText("MCP Servers")).toBeInTheDocument();
     });
 
     // Verify that health check was initiated
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.tsx b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.tsx
index 6e70b1ac59a..e6148d5d997 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/mcp-servers/_components/mcp_servers.tsx
@@ -36,6 +36,7 @@ import type {
   Team,
 } from "@/components/mcp_tools/types";
 import MCPSemanticFilterSettings from "@/components/Settings/AdminSettings/MCPSemanticFilterSettings/MCPSemanticFilterSettings";
+import MCPToolSearchSettings from "@/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings";
 import MCPNetworkSettings from "./MCPNetworkSettings";
 import MCPDiscovery from "./mcp_discovery";
 import { ByokCredentialModal } from "@/components/mcp_tools/ByokCredentialModal";
@@ -544,6 +545,11 @@ const MCPServers: React.FC<MCPServerProps> = ({ accessToken, userRole, userID })
                 Semantic Filter
               </TabsTrigger>
             )}
+            {isAdminRole(userRole) && (
+              <TabsTrigger value="tool-search" className="flex-none rounded-none px-4 py-2">
+                Tool Search
+              </TabsTrigger>
+            )}
             {isAdminRole(userRole) && (
               <TabsTrigger value="network-settings" className="flex-none rounded-none px-4 py-2">
                 Network Settings
@@ -726,6 +732,11 @@ const MCPServers: React.FC<MCPServerProps> = ({ accessToken, userRole, userID })
               <MCPSemanticFilterSettings accessToken={accessToken} />
             </TabsContent>
           )}
+          {isAdminRole(userRole) && (
+            <TabsContent value="tool-search" keepMounted>
+              <MCPToolSearchSettings accessToken={accessToken} />
+            </TabsContent>
+          )}
           {isAdminRole(userRole) && (
             <TabsContent value="network-settings" keepMounted>
               <MCPNetworkSettings accessToken={accessToken} />
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.test.tsx
index 8c683f230e0..f460b77c2c7 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.test.tsx
@@ -140,6 +140,7 @@ const renderPanel = (canModify = true) =>
       accessToken="token"
       userRole="Admin"
       userID="u-admin"
+      isViewOnly={false}
       teams={null}
       createScope={canModify ? "unscoped-ok" : "forbidden"}
     />,
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.tsx
index db5120cebce..5b53217f9c1 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/AutoRoutersPanel.tsx
@@ -21,12 +21,20 @@ interface AutoRoutersPanelProps {
   accessToken: string;
   userRole: string;
   userID: string | null;
+  isViewOnly: boolean;
   teams: Team[] | null;
   /** Owned by the page, which knows how this caller must scope what they create. */
   createScope: ModelWriteScope;
 }
 
-export function AutoRoutersPanel({ accessToken, userRole, userID, teams, createScope }: AutoRoutersPanelProps) {
+export function AutoRoutersPanel({
+  accessToken,
+  userRole,
+  userID,
+  isViewOnly,
+  teams,
+  createScope,
+}: AutoRoutersPanelProps) {
   const canCreate = createScope !== "forbidden";
   const { data: deployments, isLoading } = useAutoRouters();
   const invalidateAutoRouters = useInvalidateAutoRouters();
@@ -39,8 +47,8 @@ export function AutoRoutersPanel({ accessToken, userRole, userID, teams, createS
   const [isDeleting, setIsDeleting] = useState(false);
 
   const routers = useMemo(
-    () => toAutoRouterRows(deployments ?? [], { userRole, userID }, teams),
-    [deployments, userRole, userID, teams],
+    () => toAutoRouterRows(deployments ?? [], { userRole, userID, isViewOnly }, teams),
+    [deployments, userRole, userID, isViewOnly, teams],
   );
 
   const handleCreated = () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.test.ts
index 9944653b638..23585f6c110 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.test.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.test.ts
@@ -5,8 +5,9 @@ import { toAutoRouterRow, toAutoRouterRows } from "./autoRouterRows";
 
 // Existing cases assert resource classification, so they run as a proxy admin: the actor
 // gate is then a pass-through and canEdit/canDelete still reflect the row itself.
-const ADMIN = { userRole: "Admin", userID: "u-admin" };
-const TEAM_ADMIN = { userRole: "Internal User", userID: "u-team-admin" };
+const ADMIN = { userRole: "Admin", userID: "u-admin", isViewOnly: false };
+const TEAM_ADMIN = { userRole: "Internal User", userID: "u-team-admin", isViewOnly: false };
+const VIEW_ONLY_ADMIN = { userRole: "Admin", userID: "u-viewer", isViewOnly: true };
 
 const complexityDeployment = {
   model_name: "tri-tier-router",
@@ -224,7 +225,7 @@ describe("autoRouterRows actor gating", () => {
     { team_id: "team-1", members_with_roles: [{ user_id: "u-team-admin", user_email: "t@t", role: "admin" }] },
   ] as never;
 
-  const rowIn = (actor: { userRole: string; userID: string }, teamId: string | null) =>
+  const rowIn = (actor: { userRole: string; userID: string; isViewOnly: boolean }, teamId: string | null) =>
     toAutoRouterRow(
       { ...complexityDeployment, model_info: { id: "cid-1", db_model: true, team_id: teamId } },
       0,
@@ -259,4 +260,12 @@ describe("autoRouterRows actor gating", () => {
     expect(row.canEdit).toBe(true);
     expect(row.canDelete).toBe(true);
   });
+
+  // A proxy_admin_viewer session reads "Admin" through the masquerade, but PATCH and
+  // DELETE both 403 it, so its rows must not offer the affordances.
+  it("hides write affordances from a view-only admin session", () => {
+    const row = rowIn(VIEW_ONLY_ADMIN, null);
+    expect(row.canEdit).toBe(false);
+    expect(row.canDelete).toBe(false);
+  });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.ts b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.ts
index bbdf4697315..c4d7f45b7cc 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AutoRouters/autoRouterRows.ts
@@ -58,6 +58,7 @@ const dedupe = (models: string[]): string[] => Array.from(new Set(models));
 const COMPLEXITY_TYPE_LABELS: Record<string, string> = {
   llm: "LLM Classifier",
   heuristic_first: "Heuristic first",
+  hybrid: "Hybrid",
   custom: "Custom classifier",
 };
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx
index 8b34d61ebad..7cd418bc176 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/PriceDataManagementTab.test.tsx
@@ -1,5 +1,5 @@
 /* @vitest-environment jsdom */
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 import PriceDataManagementTab from "./PriceDataManagementTab";
 
@@ -11,7 +11,7 @@ vi.mock("@/app/(dashboard)/hooks/models/useModelCostMap", () => ({
 
 describe("PriceDataManagementTab", () => {
   it("renders its content standalone, without a tab-panel ancestor", () => {
-    const { getByText } = render(<PriceDataManagementTab />);
-    expect(getByText("Price Data Management")).toBeInTheDocument();
+    render(<PriceDataManagementTab />);
+    expect(screen.getByText("Price Data Management")).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
index 521f89a39f2..84a05113177 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
@@ -1,6 +1,6 @@
 /* @vitest-environment jsdom */
 import { QueryClient, QueryClientProvider } from "@tanstack/react-query";
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 import ModelsAndEndpointsPage from "./page";
@@ -38,8 +38,17 @@ vi.mock("./useModelDashboardData", () => ({
   useModelDashboardData: () => ({ availableModelAccessGroups: [], allModelsOnProxy: [], availableModelGroups: [] }),
 }));
 
-const ADMIN = { accessToken: "at", token: "t", userRole: "Admin", userId: "u1", premiumUser: false };
-const NON_ADMIN = { accessToken: "at", token: "t", userRole: "Internal User", userId: "u1", premiumUser: false };
+const ADMIN = { accessToken: "at", token: "t", userRole: "Admin", userId: "u1", premiumUser: false, isViewOnly: false };
+const NON_ADMIN = {
+  accessToken: "at",
+  token: "t",
+  userRole: "Internal User",
+  userId: "u1",
+  premiumUser: false,
+  isViewOnly: false,
+};
+// A proxy_admin_viewer session: effectiveSessionRole masquerades the role as "Admin".
+const VIEW_ONLY_ADMIN = { ...ADMIN, isViewOnly: true };
 
 const renderPage = () => {
   const queryClient = new QueryClient({ defaultOptions: { queries: { retry: false, gcTime: 0 } } });
@@ -64,48 +73,64 @@ describe("ModelsAndEndpointsPage", () => {
   });
 
   it("renders the admin tab bar and the All Models panel by default", () => {
-    const { getByRole, getByTestId } = renderPage();
-    expect(getByRole("tab", { name: "All Models" })).toBeInTheDocument();
-    expect(getByRole("tab", { name: "LLM Credentials" })).toBeInTheDocument();
-    expect(getByRole("tab", { name: "Health Status" })).toBeInTheDocument();
-    expect(getByTestId("panel-all-models")).toBeInTheDocument();
+    renderPage();
+    expect(screen.getByRole("tab", { name: "All Models" })).toBeInTheDocument();
+    expect(screen.getByRole("tab", { name: "LLM Credentials" })).toBeInTheDocument();
+    expect(screen.getByRole("tab", { name: "Health Status" })).toBeInTheDocument();
+    expect(screen.getByTestId("panel-all-models")).toBeInTheDocument();
   });
 
   it("switches tabs in-memory, mounting only the active panel", async () => {
     const user = userEvent.setup();
-    const { getByRole, getByTestId, queryByTestId } = renderPage();
-    await user.click(getByRole("tab", { name: "Health Status" }));
-    expect(getByTestId("panel-health")).toBeInTheDocument();
-    expect(queryByTestId("panel-all-models")).not.toBeInTheDocument();
+    renderPage();
+    await user.click(screen.getByRole("tab", { name: "Health Status" }));
+    expect(screen.getByTestId("panel-health")).toBeInTheDocument();
+    expect(screen.queryByTestId("panel-all-models")).not.toBeInTheDocument();
   });
 
   it("renders the model detail overlay from the ?model drill-in and hides the tabs", () => {
     detailState.modelId = "abc-123";
-    const { getByTestId, queryByRole } = renderPage();
-    expect(getByTestId("model-info")).toHaveTextContent("model:abc-123");
-    expect(queryByRole("tab", { name: "All Models" })).not.toBeInTheDocument();
+    renderPage();
+    expect(screen.getByTestId("model-info")).toHaveTextContent("model:abc-123");
+    expect(screen.queryByRole("tab", { name: "All Models" })).not.toBeInTheDocument();
   });
 
   it("renders the team detail overlay from the ?team drill-in", () => {
     detailState.teamId = "team-9";
-    const { getByTestId } = renderPage();
-    expect(getByTestId("team-info")).toHaveTextContent("team:team-9");
+    renderPage();
+    expect(screen.getByTestId("team-info")).toHaveTextContent("team:team-9");
   });
 
   it("hides admin-only tabs for a non-admin user", () => {
     mockUseAuthorized.mockReturnValue(NON_ADMIN);
-    const { queryByRole } = renderPage();
-    expect(queryByRole("tab", { name: "LLM Credentials" })).not.toBeInTheDocument();
-    expect(queryByRole("tab", { name: "Health Status" })).not.toBeInTheDocument();
+    renderPage();
+    expect(screen.queryByRole("tab", { name: "LLM Credentials" })).not.toBeInTheDocument();
+    expect(screen.queryByRole("tab", { name: "Health Status" })).not.toBeInTheDocument();
+  });
+
+  // POST /model/new 403s a proxy_admin_viewer, so the form's tab must not render for one.
+  it("hides the Add Model tab for a view-only admin session", () => {
+    mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN);
+    renderPage();
+    expect(screen.queryByRole("tab", { name: "Add Model" })).not.toBeInTheDocument();
+    expect(screen.getByRole("tab", { name: "All Models" })).toBeInTheDocument();
+  });
+
+  // Read parity: the Auto-Routers list stays reachable for a view-only admin; only the
+  // create affordance inside it is withheld, which AutoRoutersTabPanel decides.
+  it("keeps the Auto-Routers tab for a view-only admin session", () => {
+    mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN);
+    renderPage();
+    expect(screen.getByRole("tab", { name: /Auto-Routers/ })).toBeInTheDocument();
   });
 
   // Auto-routers are excluded from the All Models table, so this tab is their home: the only
   // place in the product to list, create, edit or delete one.
   describe("Auto-Routers tab", () => {
     it("sits third, after All Models and Add Model", () => {
-      const { getAllByRole } = renderPage();
+      renderPage();
 
-      const tabs = getAllByRole("tab").map((tab) => tab.textContent);
+      const tabs = screen.getAllByRole("tab").map((tab) => tab.textContent);
       expect(tabs[0]).toContain("All Models");
       expect(tabs[1]).toBe("Add Model");
       expect(tabs[2]).toContain("Auto-Routers");
@@ -115,17 +140,17 @@ describe("ModelsAndEndpointsPage", () => {
 
     it("renders its panel when selected", async () => {
       const user = userEvent.setup();
-      const { getByRole, getByTestId } = renderPage();
+      renderPage();
 
-      await user.click(getByRole("tab", { name: /Auto-Routers/ }));
-      expect(getByTestId("panel-auto-routers")).toBeInTheDocument();
+      await user.click(screen.getByRole("tab", { name: /Auto-Routers/ }));
+      expect(screen.getByTestId("panel-auto-routers")).toBeInTheDocument();
     });
 
     it("is hidden from non-admins, who cannot write models", () => {
       mockUseAuthorized.mockReturnValue(NON_ADMIN);
-      const { queryByRole } = renderPage();
+      renderPage();
 
-      expect(queryByRole("tab", { name: /Auto-Routers/ })).not.toBeInTheDocument();
+      expect(screen.queryByRole("tab", { name: /Auto-Routers/ })).not.toBeInTheDocument();
     });
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx
index 9ae7dc12f81..34c9d87004e 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx
@@ -80,7 +80,7 @@ const renderPanel = (key: string) => {
 };
 
 export default function ModelsAndEndpointsPage() {
-  const { accessToken, userRole, userId: userID, premiumUser } = useAuthorized();
+  const { accessToken, userRole, userId: userID, premiumUser, isViewOnly } = useAuthorized();
   const { data: teams } = useTeams();
   const { data: uiSettings } = useUISettings();
   const queryClient = useQueryClient();
@@ -92,7 +92,7 @@ export default function ModelsAndEndpointsPage() {
 
   const isInternalUser = userRole && internalUserRoles.includes(userRole);
   const canCreate = canCreateModels(
-    { userRole, userID },
+    { userRole, userID, isViewOnly },
     {
       teams: teams ?? null,
       disabledForInternalUsers:
@@ -182,6 +182,7 @@ export default function ModelsAndEndpointsPage() {
             accessToken={accessToken}
             userID={userID}
             userRole={userRole}
+            isViewOnly={isViewOnly}
             onModelUpdate={invalidateModels}
             modelAccessGroups={availableModelAccessGroups}
           />
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AddModelPanel.integration.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AddModelPanel.integration.test.tsx
index 19e1e3aa8bd..efba26734ff 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AddModelPanel.integration.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AddModelPanel.integration.test.tsx
@@ -87,7 +87,6 @@ const alwaysMounted = {
   api_key: undefined,
   api_base: undefined,
   custom_llm_provider: "openai",
-  litellm_credential_name: null,
   model: "gpt-4o",
 };
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.test.tsx
new file mode 100644
index 00000000000..12f0b95bf13
--- /dev/null
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.test.tsx
@@ -0,0 +1,39 @@
+/* @vitest-environment jsdom */
+import { render } from "@testing-library/react";
+import { describe, expect, it, vi } from "vitest";
+import AutoRoutersTabPanel from "./AutoRoutersTabPanel";
+
+const panelProps = vi.fn();
+vi.mock("../components/AutoRouters/AutoRoutersPanel", () => ({
+  AutoRoutersPanel: (props: Record<string, unknown>) => {
+    panelProps(props);
+    return <div data-testid="auto-routers-panel" />;
+  },
+}));
+
+const mockUseAuthorized = vi.fn();
+vi.mock("@/app/(dashboard)/hooks/useAuthorized", () => ({ default: () => mockUseAuthorized() }));
+vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({ useTeams: () => ({ data: [] }) }));
+vi.mock("@/app/(dashboard)/hooks/uiSettings/useUISettings", () => ({
+  useUISettings: () => ({ data: { values: {} } }),
+}));
+
+const SESSION = { accessToken: "at", userRole: "Admin", userId: "u1", isViewOnly: false };
+
+const lastProps = () => panelProps.mock.calls.at(-1)?.[0] as { createScope: string };
+
+describe("AutoRoutersTabPanel", () => {
+  it("grants an unscoped create to a real proxy admin", () => {
+    mockUseAuthorized.mockReturnValue(SESSION);
+    render(<AutoRoutersTabPanel />);
+    expect(lastProps().createScope).toBe("unscoped-ok");
+  });
+
+  // The masqueraded "Admin" a proxy_admin_viewer session carries: POST /model/new 403s it,
+  // so the panel must not be told it may create.
+  it("withholds the create affordance from a view-only admin session", () => {
+    mockUseAuthorized.mockReturnValue({ ...SESSION, isViewOnly: true });
+    render(<AutoRoutersTabPanel />);
+    expect(lastProps().createScope).toBe("forbidden");
+  });
+});
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.tsx
index 5f7d56e8e33..69b442da09b 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.tsx
@@ -15,13 +15,13 @@ import { AutoRoutersPanel } from "../components/AutoRouters/AutoRoutersPanel";
  * Viewer roles reach the list without write affordances.
  */
 export default function AutoRoutersTabPanel() {
-  const { accessToken, userRole, userId: userID } = useAuthorized();
+  const { accessToken, userRole, userId: userID, isViewOnly } = useAuthorized();
   const { data: teams } = useTeams();
   const { data: uiSettings } = useUISettings();
 
   const isInternalUser = userRole != null && internalUserRoles.includes(userRole);
   const scope = modelCreationScope(
-    { userRole, userID },
+    { userRole, userID, isViewOnly },
     {
       teams: teams ?? null,
       disabledForInternalUsers: isInternalUser && uiSettings?.values?.disable_model_add_for_internal_users === true,
@@ -33,6 +33,7 @@ export default function AutoRoutersTabPanel() {
       accessToken={accessToken}
       userRole={userRole ?? ""}
       userID={userID ?? null}
+      isViewOnly={isViewOnly}
       teams={teams ?? null}
       createScope={scope}
     />
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
index a83c11d1444..ed02e7e16cc 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.test.tsx
@@ -93,13 +93,13 @@ describe("ChatMessageBubble", () => {
   ])("should paint the $role surface from theme tokens, not fixed colours", ({ role, bubble, avatar }) => {
     render(<ChatMessageBubble {...defaultProps} message={{ role, content: "Hello" }} />);
 
-    const header = screen.getByText(role).closest("div") as HTMLElement;
-    const surface = header.parentElement as HTMLElement;
+    const surface = screen.getByTestId("message-surface");
+    const avatarEl = screen.getByTestId("message-avatar");
 
     expect(surface).toHaveClass(...bubble);
     expect(surface).not.toHaveAttribute("style");
-    expect(header.firstElementChild).toHaveClass(avatar);
-    expect(header.firstElementChild).not.toHaveAttribute("style");
+    expect(avatarEl).toHaveClass(avatar);
+    expect(avatarEl).not.toHaveAttribute("style");
   });
 
   it("should show model badge for assistant messages when model is provided", () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
index 8c54d9e89fa..bd6a4bc49a4 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/chat_ui/ChatMessageBubble.tsx
@@ -46,6 +46,7 @@ function ChatMessageBubble({
   return (
     <div className={`mb-4 min-w-0 ${isUser ? "text-right" : "text-left"}`}>
       <div
+        data-testid="message-surface"
         className={`inline-block min-w-0 max-w-[92%] overflow-hidden rounded-lg border p-3 text-left text-card-foreground shadow-xs sm:max-w-[85%] sm:px-4 ${
           isUser ? "border-info/20 bg-info/10" : "border-border bg-card"
         }`}
@@ -53,6 +54,7 @@ function ChatMessageBubble({
         {/* Header: role icon + name + model badge */}
         <div className="mb-1.5 flex min-w-0 items-center gap-2">
           <div
+            data-testid="message-avatar"
             className={`flex items-center justify-center w-6 h-6 rounded-full mr-1 ${
               isUser ? "bg-info/20" : "bg-muted"
             }`}
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/CompareUI.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/CompareUI.test.tsx
index f1bf0c634bb..dad25e12882 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/CompareUI.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/CompareUI.test.tsx
@@ -90,21 +90,19 @@ beforeEach(() => {
 
 describe("CompareUI", () => {
   it("should render", () => {
-    const { getByTestId } = render(<CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />);
-    expect(getByTestId("comparison-panel-1")).toBeInTheDocument();
-    expect(getByTestId("comparison-panel-2")).toBeInTheDocument();
-    expect(getByTestId("message-input")).toBeInTheDocument();
+    render(<CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />);
+    expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument();
+    expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument();
+    expect(screen.getByTestId("message-input")).toBeInTheDocument();
   });
 
   it("adds a comparison when Add Comparison button is clicked", async () => {
     const user = userEvent.setup();
-    const { container, getByTestId } = render(
-      <CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />,
-    );
+    const { container } = render(<CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />);
 
     // Verify initial state: 2 comparison panels
-    expect(getByTestId("comparison-panel-1")).toBeInTheDocument();
-    expect(getByTestId("comparison-panel-2")).toBeInTheDocument();
+    expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument();
+    expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument();
     let comparisonPanels = container.querySelectorAll('[data-testid^="comparison-panel-"]');
     expect(comparisonPanels).toHaveLength(2);
 
@@ -117,15 +115,13 @@ describe("CompareUI", () => {
     });
 
     // Verify the original 2 panels are still there
-    expect(getByTestId("comparison-panel-1")).toBeInTheDocument();
-    expect(getByTestId("comparison-panel-2")).toBeInTheDocument();
+    expect(screen.getByTestId("comparison-panel-1")).toBeInTheDocument();
+    expect(screen.getByTestId("comparison-panel-2")).toBeInTheDocument();
   });
 
   it("should handle image upload and send message with attachment", async () => {
     const user = userEvent.setup();
-    const { getByTestId, queryByTestId } = render(
-      <CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />,
-    );
+    render(<CompareUI accessToken="test-token" disabledPersonalKeyCreation={false} />);
 
     const file = new File(["test content"], "test-image.png", { type: "image/png" });
 
@@ -138,13 +134,13 @@ describe("CompareUI", () => {
     }
 
     await waitFor(() => {
-      expect(getByTestId("has-attachment")).toBeInTheDocument();
+      expect(screen.getByTestId("has-attachment")).toBeInTheDocument();
     });
 
-    const textarea = getByTestId("message-textarea");
+    const textarea = screen.getByTestId("message-textarea");
     fireEvent.change(textarea, { target: { value: "Describe this image" } });
 
-    const sendButton = getByTestId("send-button");
+    const sendButton = screen.getByTestId("send-button");
     expect(sendButton).toBeEnabled();
     await user.click(sendButton);
 
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx
index 72a1d41f9fe..69b50d4088f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/playground/components/compareUI/components/MessageDisplay.test.tsx
@@ -1,4 +1,4 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 import type { MessageType } from "@/components/chat_ui/types";
 import { MessageDisplay } from "./MessageDisplay";
@@ -39,9 +39,9 @@ describe("MessageDisplay", () => {
         model: "gpt-4",
       },
     ];
-    const { getByText } = render(<MessageDisplay messages={messages} isLoading={false} />);
-    expect(getByText("Hello")).toBeInTheDocument();
-    expect(getByText("Hi there!")).toBeInTheDocument();
+    render(<MessageDisplay messages={messages} isLoading={false} />);
+    expect(screen.getByText("Hello")).toBeInTheDocument();
+    expect(screen.getByText("Hi there!")).toBeInTheDocument();
   });
 
   it("displays user and assistant messages with proper grouping and shows loading state", () => {
@@ -64,13 +64,13 @@ describe("MessageDisplay", () => {
         },
       },
     ];
-    const { getByText, getByTestId } = render(<MessageDisplay messages={messages} isLoading={false} />);
-    expect(getByText("You")).toBeInTheDocument();
-    expect(getByText("What is 2+2?")).toBeInTheDocument();
-    expect(getByText("gpt-4")).toBeInTheDocument();
-    expect(getByText("calculator")).toBeInTheDocument();
-    expect(getByText("2+2 equals 4")).toBeInTheDocument();
-    expect(getByTestId("response-metrics")).toBeInTheDocument();
+    render(<MessageDisplay messages={messages} isLoading={false} />);
+    expect(screen.getByText("You")).toBeInTheDocument();
+    expect(screen.getByText("What is 2+2?")).toBeInTheDocument();
+    expect(screen.getByText("gpt-4")).toBeInTheDocument();
+    expect(screen.getByText("calculator")).toBeInTheDocument();
+    expect(screen.getByText("2+2 equals 4")).toBeInTheDocument();
+    expect(screen.getByTestId("response-metrics")).toBeInTheDocument();
   });
 
   it("should display image attachment in user message", () => {
@@ -86,10 +86,10 @@ describe("MessageDisplay", () => {
         model: "gpt-4",
       },
     ];
-    const { getByTestId, getByText } = render(<MessageDisplay messages={messages} isLoading={false} />);
-    expect(getByText("What is in this image? [Image attached]")).toBeInTheDocument();
-    expect(getByTestId("chat-image-renderer")).toBeInTheDocument();
-    const image = getByTestId("chat-image-renderer").querySelector("img");
+    render(<MessageDisplay messages={messages} isLoading={false} />);
+    expect(screen.getByText("What is in this image? [Image attached]")).toBeInTheDocument();
+    expect(screen.getByTestId("chat-image-renderer")).toBeInTheDocument();
+    const image = screen.getByTestId("chat-image-renderer").querySelector("img");
     expect(image).toHaveAttribute("src", "blob:test-image-url");
   });
 });
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/policies/_components/policy_test_panel.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/policies/_components/policy_test_panel.test.tsx
index c8779be06c4..f23145a917a 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/policies/_components/policy_test_panel.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/policies/_components/policy_test_panel.test.tsx
@@ -5,6 +5,7 @@ import userEvent, { PointerEventsCheckLevel } from "@testing-library/user-event"
 import { renderWithProviders } from "@/../tests/test-utils";
 import * as networking from "@/components/networking";
 import PolicyTestPanel from "./policy_test_panel";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 vi.mock("@/components/networking");
 
@@ -24,8 +25,7 @@ const setup = () => {
 };
 
 const pickOption = async (user: ReturnType<typeof userEvent.setup>, label: string, option: string) => {
-  await user.click(screen.getByLabelText(label));
-  await user.click(await screen.findByTitle(option));
+  await chooseSelectOption(user, screen.getByLabelText(label), option);
 };
 
 const simulate = async (user: ReturnType<typeof userEvent.setup>) => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/prompts/_components/index.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/prompts/_components/index.test.tsx
index d6a4aaea2e1..3b0ee3a3ce2 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/prompts/_components/index.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/prompts/_components/index.test.tsx
@@ -5,6 +5,7 @@ import { beforeEach, describe, expect, it, vi } from "vitest";
 import { deletePromptCall, getPromptsList } from "@/components/networking";
 
 import PromptsPanel from "./index";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 vi.mock("@/components/networking", () => ({
   getPromptsList: vi.fn(),
@@ -118,8 +119,7 @@ describe("PromptsPanel toolbar", () => {
 
     expect(screen.getByText("All Environments")).toBeInTheDocument();
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("Production"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "Production");
 
     await waitFor(() => expect(mockGetPromptsList).toHaveBeenLastCalledWith("sk-test", "production"));
   });
@@ -131,12 +131,10 @@ describe("PromptsPanel toolbar", () => {
     renderPanel("Admin");
     await screen.findByText("table-loaded");
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("Production"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "Production");
     await waitFor(() => expect(screen.getByRole("combobox")).toHaveTextContent("Production"));
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("All Environments"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "All Environments");
 
     await waitFor(() => expect(screen.getByRole("combobox")).toHaveTextContent("All Environments"));
     await waitFor(() => expect(mockGetPromptsList).toHaveBeenLastCalledWith("sk-test", undefined));
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
index 34643811e29..4203a3dbf70 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.test.tsx
@@ -116,16 +116,33 @@ describe("VectorStoreTester", () => {
     await waitFor(() => expect(mockSearch).toHaveBeenCalledTimes(1));
   });
 
-  it("reports a failed search and keeps the history empty", async () => {
+  it("shows the backend error in the history when a search fails", async () => {
     const user = userEvent.setup();
-    mockSearch.mockRejectedValue(new Error("boom"));
+    const errorBody = '{"error":{"message":"OpenAIException - api_key is required"}}';
+    mockSearch.mockRejectedValue(new Error(errorBody));
     renderTester();
 
     await user.type(queryInput(), "hello");
     await user.click(searchButton());
 
-    await waitFor(() => expect(mockFromBackend).toHaveBeenCalledWith("Failed to search vector store"));
-    expect(screen.getByText(EMPTY_STATE)).toBeInTheDocument();
+    await waitFor(() => expect(mockFromBackend).toHaveBeenCalledWith(errorBody));
+    expect(screen.getByText(`Search failed: ${errorBody}`)).toBeInTheDocument();
+    expect(screen.queryByText("No results found")).not.toBeInTheDocument();
+    expect(screen.queryByText(EMPTY_STATE)).not.toBeInTheDocument();
+    // the failed query stays in the input for retry
+    expect(queryInput()).toHaveValue("hello");
+  });
+
+  it('renders "No results found" for an empty result set, not an error', async () => {
+    const user = userEvent.setup();
+    mockSearch.mockResolvedValue({ object: "vector_store.search_results.page", search_query: "hello", data: [] });
+    renderTester();
+
+    await user.type(queryInput(), "hello");
+    await user.click(searchButton());
+
+    expect(await screen.findByText("No results found")).toBeInTheDocument();
+    expect(screen.queryByText(/search failed/i)).not.toBeInTheDocument();
   });
 
   it("clears the search history", async () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
index 6d12880319b..a9c4e0d1061 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/vector-stores/_components/VectorStoreTester.tsx
@@ -40,6 +40,7 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
     {
       query: string;
       response: VectorStoreSearchResponse | null;
+      error: string | null;
       timestamp: number;
     }[]
   >([]);
@@ -59,6 +60,7 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
       const historyEntry = {
         query,
         response,
+        error: null,
         timestamp: Date.now(),
       };
 
@@ -66,7 +68,9 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
       setQuery("");
     } catch (error) {
       console.error("Error searching vector store:", error);
-      toast.fromError("Failed to search vector store");
+      const errorMessage = error instanceof Error ? error.message : String(error);
+      toast.fromError(errorMessage);
+      setSearchHistory((prev) => [{ query, response: null, error: errorMessage, timestamp: Date.now() }, ...prev]);
     } finally {
       setIsLoading(false);
     }
@@ -228,7 +232,13 @@ export const VectorStoreTester: React.FC<VectorStoreTesterProps> = ({ vectorStor
                           })}
                         </div>
                       ) : (
-                        <div className="text-sm text-muted-foreground">No results found</div>
+                        <div
+                          className={
+                            entry.error ? "text-sm break-words text-destructive" : "text-sm text-muted-foreground"
+                          }
+                        >
+                          {entry.error ? `Search failed: ${entry.error}` : "No results found"}
+                        </div>
                       )}
                     </div>
                   </div>
diff --git a/ui/litellm-dashboard/src/autorouter_presets.json b/ui/litellm-dashboard/src/autorouter_presets.json
index 4cbb548a855..1e0d40567d7 100644
--- a/ui/litellm-dashboard/src/autorouter_presets.json
+++ b/ui/litellm-dashboard/src/autorouter_presets.json
@@ -14,7 +14,9 @@
       },
       "classifier_type": "heuristic",
       "escalation_keywords": ["LITELLM ESCALATE"],
+      "classification_mode": "every_request",
       "session_affinity": false,
+      "modality_routing": false,
       "deployment_affinity": true
     }
   },
@@ -30,7 +32,9 @@
       },
       "classifier_type": "heuristic",
       "escalation_keywords": ["LITELLM ESCALATE"],
+      "classification_mode": "every_request",
       "session_affinity": false,
+      "modality_routing": false,
       "deployment_affinity": true
     }
   },
@@ -56,23 +60,30 @@
       },
       "classifier_context_window_size": 0,
       "escalation_keywords": ["LITELLM ESCALATE"],
+      "classification_mode": "every_request",
       "session_affinity": false,
+      "modality_routing": false,
       "deployment_affinity": true
     }
   },
   "openai_family": {
     "label": "OpenAI Family",
-    "description": "Routes across the GPT model family: gpt-5.4-nano for simple queries, gpt-5.4-mini for medium, gpt-5.4 for complex, o3 for reasoning-heavy requests.",
+    "description": "Routes across the GPT model family: Luna for simple queries, Terra for medium, Sol for complex, Sol at xhigh thinking for reasoning.",
     "complexity_router_config": {
       "tiers": {
-        "SIMPLE": ["gpt-5.4-nano"],
-        "MEDIUM": ["gpt-5.4-mini"],
-        "COMPLEX": ["gpt-5.4"],
-        "REASONING": ["o3"]
+        "SIMPLE": ["gpt-5.6-luna"],
+        "MEDIUM": ["gpt-5.6-terra"],
+        "COMPLEX": ["gpt-5.6-sol"],
+        "REASONING": ["gpt-5.6-sol"]
+      },
+      "tier_model_configs": {
+        "REASONING": [{ "model_name": "gpt-5.6-sol", "litellm_params": { "reasoning_effort": "xhigh" } }]
       },
       "classifier_type": "heuristic",
       "escalation_keywords": ["LITELLM ESCALATE"],
+      "classification_mode": "every_request",
       "session_affinity": false,
+      "modality_routing": false,
       "deployment_affinity": true
     }
   }
diff --git a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx
index 397e2ab10fa..906565750b1 100644
--- a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.test.tsx
@@ -203,12 +203,12 @@ describe("ModelHubTable", () => {
   });
 
   describe("hub tabs", () => {
-    const renderHub = async () => {
+    const renderHub = async (agents: object[] = []) => {
       vi.mocked(networking.modelHubCall).mockResolvedValue({
         data: [{ model_group: "claude-opus-4-8", providers: ["anthropic"], mode: "chat" }],
       });
       vi.mocked(networking.getConfigFieldSetting).mockResolvedValue({ field_value: false });
-      vi.mocked(networking.getAgentsList).mockResolvedValue({ agents: [] });
+      vi.mocked(networking.getAgentsList).mockResolvedValue({ agents });
       vi.mocked(networking.fetchMCPServers).mockResolvedValue([]);
       vi.mocked(networking.getUiSettings).mockResolvedValue({ values: {} });
       mockUseUISettings.mockReturnValue({ data: { values: {} }, isLoading: false });
@@ -230,6 +230,37 @@ describe("ModelHubTable", () => {
       expect(await screen.findByPlaceholderText("Search model names...")).toHaveValue("opus");
     });
 
+    it("filters the Agent Hub table by name or description and shows the no-match state", async () => {
+      const { user } = await renderHub([
+        {
+          agent_id: "a1",
+          agent_card_params: { name: "Billing Router", description: "routes billing questions" },
+          litellm_params: { is_public: false },
+        },
+        {
+          agent_id: "a2",
+          agent_card_params: { name: "Support Bot", description: "handles support tickets" },
+          litellm_params: { is_public: false },
+        },
+      ]);
+      const agentCount = (expected: string) =>
+        screen.getByText((_, el) => el?.tagName === "P" && el.textContent === expected);
+
+      await user.click(screen.getByRole("tab", { name: "Agent Hub" }));
+      expect(await screen.findByText("Billing Router")).toBeInTheDocument();
+
+      const search = screen.getByPlaceholderText("Search agent names or descriptions...");
+      await user.type(search, "support tickets");
+      expect(screen.queryByText("Billing Router")).not.toBeInTheDocument();
+      expect(screen.getByText("Support Bot")).toBeInTheDocument();
+      expect(agentCount("Showing 1 of 2 agents")).toBeInTheDocument();
+
+      await user.clear(search);
+      await user.type(search, "zzzz");
+      expect(screen.getByText("No matching agents")).toBeInTheDocument();
+      expect(agentCount("Showing 0 of 2 agents")).toBeInTheDocument();
+    });
+
     it("renders the hub strip as underlined tabs rather than a segmented pill", async () => {
       await renderHub();
 
diff --git a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx
index 299104b271b..475e3dcd70b 100644
--- a/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx
+++ b/ui/litellm-dashboard/src/components/AIHub/ModelHubTable.tsx
@@ -23,13 +23,15 @@ import {
 import PublicModelHub from "@/components/public_model_hub";
 import { copyToClipboard } from "@/utils/dataUtils";
 import { isAdminRole, isProxyAdminRole } from "@/utils/roles";
+import { filterBySearchTerm } from "@/utils/searchUtils";
 import { SortingState } from "@tanstack/react-table";
 import { Badge } from "@/components/ui/badge";
 import { Button } from "@/components/ui/button";
 import { Card } from "@/components/ui/card";
 import { Dialog, DialogContent, DialogHeader, DialogTitle } from "@/components/ui/dialog";
+import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
-import { Copy, Inbox } from "lucide-react";
+import { Copy, Inbox, Search as SearchIcon, X } from "lucide-react";
 import { useRouter } from "next/navigation";
 import React, { useCallback, useEffect, useMemo, useState } from "react";
 import { Prism as SyntaxHighlighter } from "react-syntax-highlighter";
@@ -80,6 +82,7 @@ const ModelHubTable: React.FC<ModelHubTableProps> = ({ accessToken, publicPage,
   const [agentLoading, setAgentLoading] = useState<boolean>(true);
   const [selectedAgent, setSelectedAgent] = useState<null | AgentHubData>(null);
   const [isAgentModalVisible, setIsAgentModalVisible] = useState(false);
+  const [agentSearchTerm, setAgentSearchTerm] = useState("");
   // MCP Hub state
   const [mcpHubData, setMcpHubData] = useState<MCPServerData[] | null>(null);
   const [mcpLoading, setMcpLoading] = useState<boolean>(true);
@@ -385,6 +388,10 @@ const ModelHubTable: React.FC<ModelHubTableProps> = ({ accessToken, publicPage,
 
   const modelColumns = useMemo(() => getModelHubTableColumns({ onModelClick: showModal }), [showModal]);
   const agentColumns = useMemo(() => getAgentHubTableColumns({ onAgentClick: showAgentModal }), [showAgentModal]);
+  const filteredAgentData = useMemo(
+    () => filterBySearchTerm(agentHubData ?? [], agentSearchTerm, (agent) => [agent.name, agent.description]),
+    [agentHubData, agentSearchTerm],
+  );
   const mcpColumns = useMemo(() => getMCPHubTableColumns({ onServerClick: showMcpModal }), [showMcpModal]);
 
   // If this is a public page, use the dedicated PublicModelHub component
@@ -505,9 +512,34 @@ const ModelHubTable: React.FC<ModelHubTableProps> = ({ accessToken, publicPage,
                     </div>
                   )}
 
+                  <div className="mb-4">
+                    <p className="text-sm font-medium mb-2">Search Agents:</p>
+                    <InputGroup className="max-w-sm">
+                      <InputGroupAddon>
+                        <SearchIcon className="size-4 text-muted-foreground" />
+                      </InputGroupAddon>
+                      <InputGroupInput
+                        placeholder="Search agent names or descriptions..."
+                        value={agentSearchTerm}
+                        onChange={(e) => setAgentSearchTerm(e.target.value)}
+                      />
+                      {agentSearchTerm && (
+                        <InputGroupAddon align="inline-end">
+                          <InputGroupButton
+                            size="icon-xs"
+                            aria-label="Clear search"
+                            onClick={() => setAgentSearchTerm("")}
+                          >
+                            <X />
+                          </InputGroupButton>
+                        </InputGroupAddon>
+                      )}
+                    </InputGroup>
+                  </div>
+
                   {/* Agent Table */}
                   <DataTable
-                    data={agentHubData || []}
+                    data={filteredAgentData}
                     columns={agentColumns}
                     getRowId={(agent, index) => agent.agent_id || agent.name || String(index)}
                     sortingMode="client"
@@ -516,7 +548,14 @@ const ModelHubTable: React.FC<ModelHubTableProps> = ({ accessToken, publicPage,
                     isLoading={agentLoading}
                     loadingMessage="Loading agents…"
                     noDataMessage={
-                      <HubEmptyState title="No agents yet" body="Agents added to this proxy will appear here." />
+                      <HubEmptyState
+                        title={agentHubData?.length ? "No matching agents" : "No agents yet"}
+                        body={
+                          agentHubData?.length
+                            ? "Adjust the search to see more agents."
+                            : "Agents added to this proxy will appear here."
+                        }
+                      />
                     }
                     size="compact"
                   />
@@ -524,7 +563,7 @@ const ModelHubTable: React.FC<ModelHubTableProps> = ({ accessToken, publicPage,
 
                 <div className="mt-4 text-center space-y-2">
                   <p className="text-sm text-muted-foreground">
-                    Showing {agentHubData?.length || 0} agent{agentHubData?.length !== 1 ? "s" : ""}
+                    Showing {filteredAgentData.length} of {agentHubData?.length || 0} agents
                   </p>
                 </div>
               </TabsContent>
diff --git a/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx b/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx
index 3777c46973f..68bfd94bd63 100644
--- a/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx
+++ b/ui/litellm-dashboard/src/components/CreateUserButton.test.tsx
@@ -5,6 +5,7 @@ import { describe, it, expect, vi, beforeEach } from "vitest";
 import { CreateUserButton } from "./CreateUserButton";
 import * as networking from "./networking";
 import { toast } from "@/lib/toast";
+import { expectControlBesideLabel } from "../../tests/fieldOrientation";
 
 vi.mock("./networking", () => ({
   userCreateCall: vi.fn(),
@@ -294,6 +295,20 @@ describe("CreateUserButton", () => {
     });
   });
 
+  it("lays the send invitation email checkbox out beside its label", async () => {
+    const user = userEvent.setup({ pointerEventsCheck: PointerEventsCheckLevel.Never });
+    renderWithProviders(<CreateUserButton {...defaultProps} />);
+
+    await waitFor(() => {
+      expect(screen.getByRole("button", { name: /\+ invite user/i })).toBeInTheDocument();
+    });
+    await user.click(screen.getByRole("button", { name: /\+ invite user/i }));
+
+    const dialog = screen.getByRole("dialog", { name: /invite user/i });
+
+    expectControlBesideLabel(within(dialog).getByRole("checkbox"));
+  });
+
   describe("organizations", () => {
     it("should send organizations list in POST body when organizations are selected", async () => {
       const { useOrganizations } = await import("@/app/(dashboard)/hooks/organizations/useOrganizations");
diff --git a/ui/litellm-dashboard/src/components/CreateUserButton.tsx b/ui/litellm-dashboard/src/components/CreateUserButton.tsx
index e052a9e0818..0f7c356b8cc 100644
--- a/ui/litellm-dashboard/src/components/CreateUserButton.tsx
+++ b/ui/litellm-dashboard/src/components/CreateUserButton.tsx
@@ -270,7 +270,7 @@ export const CreateUserButton: React.FC<CreateuserProps> = ({
   );
 
   const sendInviteEmailField = (
-    <FormField control={form.control} name="send_invite_email" label="Send invitation email">
+    <FormField control={form.control} name="send_invite_email" label="Send invitation email" orientation="horizontal">
       {({ id, value, onChange, onBlur }) => (
         <Checkbox id={id} checked={value} onCheckedChange={onChange} onBlur={onBlur} />
       )}
diff --git a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx
index 8edf2174eee..cb04323e4c9 100644
--- a/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx
+++ b/ui/litellm-dashboard/src/components/EntityUsageExport/EntityUsageExportModal.test.tsx
@@ -10,6 +10,7 @@
  */
 
 import { describe, it, expect, vi, beforeEach } from "vitest";
+import { screen } from "@testing-library/react";
 import { renderWithProviders } from "../../../tests/test-utils";
 import userEvent from "@testing-library/user-event";
 import EntityUsageExportModal from "./EntityUsageExportModal";
@@ -73,13 +74,13 @@ describe("EntityUsageExportModal", () => {
     const user = userEvent.setup();
     const { handleExportCSV } = await import("./utils");
 
-    const { getByRole } = renderWithProviders(<EntityUsageExportModal {...baseProps} />);
+    renderWithProviders(<EntityUsageExportModal {...baseProps} />);
 
     // Default primary action reflects CSV export
-    expect(getByRole("button", { name: /Export CSV/i })).toBeInTheDocument();
+    expect(screen.getByRole("button", { name: /Export CSV/i })).toBeInTheDocument();
 
     // Click export
-    await user.click(getByRole("button", { name: /Export CSV/i }));
+    await user.click(screen.getByRole("button", { name: /Export CSV/i }));
 
     // Verifies export function was invoked with correct parameters
     expect(handleExportCSV).toHaveBeenCalledWith(baseProps.spendData, "daily", "Tag", "tag", {});
@@ -97,14 +98,14 @@ describe("EntityUsageExportModal", () => {
     const user = userEvent.setup();
     const { handleExportCSV } = await import("./utils");
 
-    const { getByText, getByRole } = renderWithProviders(<EntityUsageExportModal {...baseProps} />);
+    renderWithProviders(<EntityUsageExportModal {...baseProps} />);
 
     // Choose the alternate export type - click the label to trigger radio
-    const dailyModelLabel = getByText(/Day-by-day by tag and model/i);
+    const dailyModelLabel = screen.getByText(/Day-by-day by tag and model/i);
     await user.click(dailyModelLabel);
 
     // Export with default CSV format
-    const exportBtn = getByRole("button", { name: /Export CSV/i });
+    const exportBtn = screen.getByRole("button", { name: /Export CSV/i });
     await user.click(exportBtn);
 
     // Ensure the selected scope flowed through
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.test.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.test.tsx
new file mode 100644
index 00000000000..6e312bea651
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.test.tsx
@@ -0,0 +1,96 @@
+import React from "react";
+import { describe, it, expect, vi, beforeEach } from "vitest";
+import { render, screen, act, fireEvent } from "@testing-library/react";
+import MCPToolSearchSettings from "./MCPToolSearchSettings";
+import {
+  useMCPToolSearchSettings,
+  useUpdateMCPToolSearchSettings,
+} from "@/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings";
+
+vi.mock("@/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings", () => ({
+  useMCPToolSearchSettings: vi.fn(),
+  useUpdateMCPToolSearchSettings: vi.fn(),
+}));
+
+vi.mock("@/components/llm_calls/fetch_models", () => ({
+  fetchAvailableModels: vi.fn().mockResolvedValue([{ model_group: "text-embedding-3-small", mode: "embedding" }]),
+}));
+
+vi.mock("@/lib/toast", () => ({ toast: { success: vi.fn(), fromError: vi.fn() } }));
+
+const mockMutate = vi.fn();
+
+const EDITED_PAYLOAD = {
+  embedding_model: "text-embedding-3-small",
+  top_k: 8,
+  similarity_threshold: 0.25,
+  core_tools: ["treasury-get_rates", "weather-forecast"],
+};
+
+const STORED = {
+  field_schema: {},
+  values: {
+    embedding_model: "text-embedding-3-small",
+    top_k: 3,
+    similarity_threshold: 0.25,
+    core_tools: ["treasury-get_rates"],
+  },
+};
+
+type SettingsQuery = ReturnType<typeof useMCPToolSearchSettings>;
+type SettingsMutation = ReturnType<typeof useUpdateMCPToolSearchSettings>;
+
+const settled = (data: typeof STORED | undefined, overrides: Partial<SettingsQuery> = {}) =>
+  ({ data, isLoading: false, isError: false, error: null, ...overrides }) as SettingsQuery;
+
+async function renderSettings(accessToken: string | null = "token") {
+  const result = render(<MCPToolSearchSettings accessToken={accessToken} />);
+  await act(async () => {});
+  return result;
+}
+
+describe("MCPToolSearchSettings", () => {
+  beforeEach(() => {
+    vi.clearAllMocks();
+    vi.mocked(useMCPToolSearchSettings).mockReturnValue(settled(STORED));
+    vi.mocked(useUpdateMCPToolSearchSettings).mockReturnValue({
+      mutate: mockMutate,
+      isPending: false,
+    } as unknown as SettingsMutation);
+  });
+
+  it("shows the stored settings and keeps Save disabled until something changes", async () => {
+    await renderSettings();
+
+    expect(screen.getByLabelText(/top k results/i)).toHaveValue(3);
+    expect(screen.getByLabelText(/always returned first/i)).toHaveValue("treasury-get_rates");
+    expect(screen.getByRole("slider", { hidden: true })).toHaveAttribute("aria-valuenow", "0.25");
+    expect(screen.getByRole("button", { name: /save settings/i })).toBeDisabled();
+  });
+
+  it("sends the edited settings as the proxy's PATCH payload", async () => {
+    await renderSettings();
+
+    fireEvent.change(screen.getByLabelText(/top k results/i), { target: { value: "8" } });
+    fireEvent.change(screen.getByLabelText(/always returned first/i), {
+      target: { value: "treasury-get_rates\nweather-forecast" },
+    });
+    await act(async () => {
+      fireEvent.click(screen.getByRole("button", { name: /save settings/i }));
+    });
+
+    expect(mockMutate).toHaveBeenCalledTimes(1);
+    expect(mockMutate.mock.calls[0][0]).toEqual(EDITED_PAYLOAD);
+  });
+
+  it("asks the user to log in without a token and surfaces load errors", async () => {
+    await renderSettings(null);
+    expect(screen.getByText(/please log in/i)).toBeInTheDocument();
+
+    vi.mocked(useMCPToolSearchSettings).mockReturnValue(
+      settled(undefined, { isError: true, error: new Error("Database not connected") }),
+    );
+    await renderSettings();
+    expect(screen.getByText("Database not connected")).toBeInTheDocument();
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.tsx
new file mode 100644
index 00000000000..2ad9a56d0f3
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/MCPToolSearchSettings.tsx
@@ -0,0 +1,251 @@
+"use client";
+
+import {
+  useMCPToolSearchSettings,
+  useUpdateMCPToolSearchSettings,
+} from "@/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings";
+import { toast } from "@/lib/toast";
+import { Skeleton } from "@/components/ui/skeleton";
+import { CircleHelp, Info, Save } from "lucide-react";
+import { Alert, AlertDescription, AlertTitle } from "@/components/shared/Alert";
+import { useEffect, useState } from "react";
+import { useForm } from "react-hook-form";
+import { fetchAvailableModels, ModelGroup } from "@/components/llm_calls/fetch_models";
+import { FieldGroup } from "@/components/ui/field";
+import { FormField } from "@/components/shared/form/FormField";
+import { SearchSelect } from "@/components/shared/SearchSelect";
+import { Button } from "@/components/ui/button";
+import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
+import { Input } from "@/components/ui/input";
+import { Slider } from "@/components/ui/slider";
+import { Textarea } from "@/components/ui/textarea";
+import { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger } from "@/components/ui/tooltip";
+import { UiLoadingSpinner } from "@/components/ui/ui-loading-spinner";
+import {
+  DEFAULT_FORM_VALUES,
+  TOP_K_MAX,
+  TOP_K_MIN,
+  clampTopK,
+  formToPayload,
+  storedValuesToForm,
+  ToolSearchFormValues,
+} from "./toolSearchForm";
+
+interface MCPToolSearchSettingsProps {
+  accessToken: string | null;
+}
+
+const SIMILARITY_THRESHOLD_MARKS = [0, 0.3, 0.5, 0.7, 1];
+
+const labelWithHint = (label: string, hint: string): React.ReactNode => (
+  <>
+    {label}
+    <Tooltip>
+      <TooltipTrigger render={<CircleHelp className="size-3.5 shrink-0 cursor-help text-muted-foreground" />} />
+      <TooltipContent>{hint}</TooltipContent>
+    </Tooltip>
+  </>
+);
+
+export default function MCPToolSearchSettings({ accessToken }: MCPToolSearchSettingsProps) {
+  const { data, isLoading, isError, error } = useMCPToolSearchSettings();
+  const { mutate: updateSettings, isPending: isUpdating } = useUpdateMCPToolSearchSettings();
+  const form = useForm<ToolSearchFormValues>({ defaultValues: DEFAULT_FORM_VALUES });
+  const isDirty = form.formState.isDirty;
+  const [embeddingModels, setEmbeddingModels] = useState<ModelGroup[]>([]);
+  const [loadingModels, setLoadingModels] = useState(true);
+  const storedValues = data?.values;
+
+  useEffect(() => {
+    if (!accessToken) return;
+    fetchAvailableModels(accessToken)
+      .then((models) => setEmbeddingModels(models.filter((model) => model.mode === "embedding")))
+      .catch((fetchError: unknown) => console.error("Error fetching embedding models:", fetchError))
+      .finally(() => setLoadingModels(false));
+  }, [accessToken]);
+
+  useEffect(() => {
+    if (!storedValues) return;
+    form.reset(storedValuesToForm(storedValues));
+  }, [storedValues, form]);
+
+  const handleSave = (formValues: ToolSearchFormValues) => {
+    updateSettings(formToPayload(formValues), {
+      onSuccess: () => {
+        form.reset(formValues);
+        toast.success("Settings updated successfully. Changes will be applied across all pods within 10 seconds.");
+      },
+      onError: (saveError) => toast.fromError(saveError),
+    });
+  };
+
+  if (!accessToken) {
+    return <div className="p-6 text-center text-muted-foreground">Please log in to configure tool search.</div>;
+  }
+
+  if (isLoading) {
+    return (
+      <div className="flex flex-col gap-3">
+        <Skeleton className="h-4 w-2/5" />
+        <Skeleton className="h-4 w-full" />
+        <Skeleton className="h-4 w-3/5" />
+      </div>
+    );
+  }
+
+  if (isError) {
+    return (
+      <Alert variant="error" className="mb-6">
+        <AlertTitle>Could not load MCP tool search settings</AlertTitle>
+        {error instanceof Error && <AlertDescription>{error.message}</AlertDescription>}
+      </Alert>
+    );
+  }
+
+  return (
+    <div className="w-full">
+      <Alert variant="info" className="mb-6">
+        <Info />
+        <AlertTitle>Native MCP Tool Search</AlertTitle>
+        <AlertDescription>
+          Controls the <code>mcp_tool_search</code> virtual tool that native MCP clients call to discover tools. With an
+          embedding model set, tools are ranked by the meaning of their name and description, so a query like
+          &quot;FX&quot; finds a &quot;foreign exchange rates&quot; tool. Without one, keyword matching is used. Callers
+          only ever see tools their key, team and server permissions already allow.
+        </AlertDescription>
+      </Alert>
+
+      <TooltipProvider>
+        <form onSubmit={(event) => event.preventDefault()} noValidate>
+          <Card className="mb-4">
+            <CardHeader className="border-b">
+              <CardTitle>Ranking</CardTitle>
+            </CardHeader>
+            <CardContent>
+              <FieldGroup>
+                <FormField
+                  control={form.control}
+                  name="embedding_model"
+                  label={labelWithHint(
+                    "Embedding Model",
+                    "Embedding model from your model list used to rank tools by meaning. Clear it to fall back to keyword matching.",
+                  )}
+                >
+                  {({ value, onChange, id }) => (
+                    <SearchSelect
+                      inputId={id}
+                      options={embeddingModels.map((model) => ({ label: model.model_group, value: model.model_group }))}
+                      value={value}
+                      onValueChange={onChange}
+                      allowClear
+                      placeholder={loadingModels ? "Loading models..." : "Keyword matching (no embedding model)"}
+                      emptyText={loadingModels ? "Loading..." : "No embedding models available"}
+                      disabled={isUpdating || loadingModels}
+                    />
+                  )}
+                </FormField>
+
+                <FormField
+                  control={form.control}
+                  name="top_k"
+                  label={labelWithHint(
+                    "Top K Results",
+                    "Most ranked tools a search returns. A smaller top_k in the tool call wins. Core tools do not count.",
+                  )}
+                >
+                  {({ ref, value, onChange, onBlur, id }) => (
+                    <Input
+                      id={id}
+                      ref={ref}
+                      type="number"
+                      min={TOP_K_MIN}
+                      max={TOP_K_MAX}
+                      value={value}
+                      onChange={(event) => onChange(event.target.valueAsNumber)}
+                      onBlur={() => {
+                        onChange(Number.isNaN(value) ? DEFAULT_FORM_VALUES.top_k : clampTopK(value));
+                        onBlur();
+                      }}
+                      disabled={isUpdating}
+                    />
+                  )}
+                </FormField>
+
+                <FormField
+                  control={form.control}
+                  name="similarity_threshold"
+                  label={labelWithHint(
+                    "Similarity Threshold",
+                    "Lowest cosine similarity a tool needs to appear in semantic results. 0 means no cutoff.",
+                  )}
+                >
+                  {({ value, onChange, id }) => (
+                    <div className="w-full">
+                      <Slider
+                        id={id}
+                        min={0}
+                        max={1}
+                        step={0.05}
+                        value={[value]}
+                        onValueChange={(next) => onChange(Array.isArray(next) ? next[0] : next)}
+                        disabled={isUpdating}
+                      />
+                      <div className="relative mt-2 h-4 text-xs text-muted-foreground">
+                        {SIMILARITY_THRESHOLD_MARKS.map((mark) => (
+                          <span key={mark} className="absolute -translate-x-1/2" style={{ left: `${mark * 100}%` }}>
+                            {mark.toFixed(1)}
+                          </span>
+                        ))}
+                      </div>
+                    </div>
+                  )}
+                </FormField>
+              </FieldGroup>
+            </CardContent>
+          </Card>
+
+          <Card className="mb-4">
+            <CardHeader className="border-b">
+              <CardTitle>Core Tools</CardTitle>
+            </CardHeader>
+            <CardContent>
+              <FieldGroup>
+                <FormField
+                  control={form.control}
+                  name="core_tools_text"
+                  label={labelWithHint(
+                    "Always Returned First",
+                    "One tool name per line, e.g. my_server-get_rates. Listed before ranked results whenever the caller is allowed to use them.",
+                  )}
+                >
+                  {({ ref, value, onChange, onBlur, id }) => (
+                    <Textarea
+                      id={id}
+                      ref={ref}
+                      value={value}
+                      placeholder={"my_server-get_rates\nmy_server-list_accounts"}
+                      onChange={(event) => onChange(event.target.value)}
+                      onBlur={onBlur}
+                      disabled={isUpdating}
+                    />
+                  )}
+                </FormField>
+              </FieldGroup>
+            </CardContent>
+          </Card>
+
+          <div className="flex justify-end gap-2">
+            <Button
+              type="button"
+              onClick={() => void form.handleSubmit(handleSave)()}
+              disabled={!isDirty || isUpdating}
+            >
+              {isUpdating ? <UiLoadingSpinner className="size-4" /> : <Save />}
+              Save Settings
+            </Button>
+          </div>
+        </form>
+      </TooltipProvider>
+    </div>
+  );
+}
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.test.ts b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.test.ts
new file mode 100644
index 00000000000..2f9032537c1
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.test.ts
@@ -0,0 +1,60 @@
+import { describe, expect, it } from "vitest";
+import { DEFAULT_FORM_VALUES, formToPayload, parseCoreTools, storedValuesToForm } from "./toolSearchForm";
+
+const STORED_SEMANTIC = {
+  embedding_model: "text-embedding-3-small",
+  top_k: 3,
+  similarity_threshold: 0.25,
+  core_tools: ["treasury-get_rates", "treasury-list_accounts"],
+};
+
+const SEMANTIC_FORM = {
+  embedding_model: "text-embedding-3-small",
+  top_k: 3,
+  similarity_threshold: 0.25,
+  core_tools_text: "treasury-get_rates\ntreasury-list_accounts",
+};
+
+const KEYWORD_PAYLOAD = { embedding_model: null, top_k: 5, similarity_threshold: 0, core_tools: [] };
+
+const OVERSIZED_FORM = {
+  embedding_model: "emb",
+  top_k: 400,
+  similarity_threshold: 0.5,
+  core_tools_text: "treasury-get_rates",
+};
+
+const CLAMPED_PAYLOAD = {
+  embedding_model: "emb",
+  top_k: 100,
+  similarity_threshold: 0.5,
+  core_tools: ["treasury-get_rates"],
+};
+
+describe("storedValuesToForm", () => {
+  it("maps stored settings onto the form, joining core tools one per line", () => {
+    expect(storedValuesToForm(STORED_SEMANTIC)).toEqual(SEMANTIC_FORM);
+  });
+
+  it("falls back to keyword defaults when nothing usable is stored", () => {
+    expect(storedValuesToForm({})).toEqual(DEFAULT_FORM_VALUES);
+    expect(storedValuesToForm({ embedding_model: null, top_k: "7" })).toEqual(DEFAULT_FORM_VALUES);
+  });
+});
+
+describe("parseCoreTools", () => {
+  it("splits on newlines and commas, trims, drops blanks and duplicates in order", () => {
+    expect(parseCoreTools(" a-x \n\nb-y, a-x ,c-z\n")).toEqual(["a-x", "b-y", "c-z"]);
+  });
+});
+
+describe("formToPayload", () => {
+  it("sends null for a cleared embedding model so the proxy returns to keyword matching", () => {
+    expect(formToPayload({ ...DEFAULT_FORM_VALUES, embedding_model: "  " })).toEqual(KEYWORD_PAYLOAD);
+  });
+
+  it("clamps top_k into the range the proxy accepts and lists core tools", () => {
+    expect(formToPayload(OVERSIZED_FORM)).toEqual(CLAMPED_PAYLOAD);
+    expect(formToPayload({ ...DEFAULT_FORM_VALUES, top_k: 0 }).top_k).toBe(1);
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.ts b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.ts
new file mode 100644
index 00000000000..f10bfd249d7
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/MCPToolSearchSettings/toolSearchForm.ts
@@ -0,0 +1,49 @@
+import type { MCPToolSearchSettings } from "@/app/(dashboard)/hooks/mcpToolSearchSettings/useMCPToolSearchSettings";
+
+export interface ToolSearchFormValues {
+  embedding_model: string;
+  top_k: number;
+  similarity_threshold: number;
+  core_tools_text: string;
+}
+
+export const TOP_K_MIN = 1;
+export const TOP_K_MAX = 100;
+
+export const DEFAULT_FORM_VALUES: ToolSearchFormValues = {
+  embedding_model: "",
+  top_k: 5,
+  similarity_threshold: 0,
+  core_tools_text: "",
+};
+
+const isString = (value: unknown): value is string => typeof value === "string";
+const isNumber = (value: unknown): value is number => typeof value === "number" && Number.isFinite(value);
+
+export const parseCoreTools = (text: string): string[] =>
+  Array.from(
+    new Set(
+      text
+        .split(/[\n,]/)
+        .map((name) => name.trim())
+        .filter((name) => name.length > 0),
+    ),
+  );
+
+export const clampTopK = (value: number): number => Math.min(TOP_K_MAX, Math.max(TOP_K_MIN, Math.round(value)));
+
+export const storedValuesToForm = (values: Record<string, unknown>): ToolSearchFormValues => ({
+  embedding_model: isString(values.embedding_model) ? values.embedding_model : DEFAULT_FORM_VALUES.embedding_model,
+  top_k: isNumber(values.top_k) ? values.top_k : DEFAULT_FORM_VALUES.top_k,
+  similarity_threshold: isNumber(values.similarity_threshold)
+    ? values.similarity_threshold
+    : DEFAULT_FORM_VALUES.similarity_threshold,
+  core_tools_text: Array.isArray(values.core_tools) ? values.core_tools.filter(isString).join("\n") : "",
+});
+
+export const formToPayload = (form: ToolSearchFormValues): MCPToolSearchSettings => ({
+  embedding_model: form.embedding_model.trim() === "" ? null : form.embedding_model.trim(),
+  top_k: clampTopK(form.top_k),
+  similarity_threshold: form.similarity_threshold,
+  core_tools: parseCoreTools(form.core_tools_text),
+});
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx
index 54566e1d75a..eddc5716305 100644
--- a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.test.tsx
@@ -9,6 +9,7 @@ import BaseSSOSettingsForm, {
   submitMountedSSOValues,
   useSSOSettingsForm,
 } from "./BaseSSOSettingsForm";
+import { expectControlBesideLabel } from "../../../../../../tests/fieldOrientation";
 
 const user = () => userEvent.setup({ pointerEventsCheck: 0 });
 
@@ -233,6 +234,38 @@ describe("BaseSSOSettingsForm", () => {
 
     expect(screen.queryByText("Use Team Mappings")).not.toBeInTheDocument();
   });
+
+  it("lays a provider checkbox field out beside its label", async () => {
+    const TestWrapper = () => {
+      const form = useSSOSettingsForm("sso-settings");
+
+      return <BaseSSOSettingsForm form={form} onFormSubmit={vi.fn()} />;
+    };
+
+    renderWithProviders(<TestWrapper />);
+
+    await openProviderDropdown();
+    await user().click(await screen.findByText(/saml sso/i));
+
+    expectControlBesideLabel(
+      await screen.findByRole("checkbox", { name: "Allow IdP-initiated (unsolicited) responses" }),
+    );
+  });
+
+  it.each(["Use Role Mappings", "Use Team Mappings"])("lays the %s toggle out beside its label", async (label) => {
+    const TestWrapper = () => {
+      const form = useSSOSettingsForm("sso-settings");
+
+      return <BaseSSOSettingsForm form={form} onFormSubmit={vi.fn()} />;
+    };
+
+    renderWithProviders(<TestWrapper />);
+
+    await openProviderDropdown();
+    await user().click(await screen.findByText(/okta/i));
+
+    expectControlBesideLabel(await screen.findByRole("checkbox", { name: label }));
+  });
 });
 
 describe("renderProviderFields", () => {
diff --git a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx
index 5216da382d0..cb97304f77a 100644
--- a/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx
+++ b/ui/litellm-dashboard/src/components/Settings/AdminSettings/SSOSettings/Modals/BaseSSOSettingsForm.tsx
@@ -303,7 +303,7 @@ const SSOProviderField = ({ field }: { field: SSOProviderConfig["fields"][number
 
   if (field.type === "checkbox") {
     return (
-      <FormField control={control} name={field.name} label={field.label}>
+      <FormField control={control} name={field.name} label={field.label} orientation="horizontal">
         {({ value, onChange, onBlur, id, ...rest }) => (
           <Checkbox
             id={id}
@@ -413,7 +413,7 @@ export const MappingToggleField = ({
   const { control } = useFormContext<SSOSettingsFormValues>();
 
   return (
-    <FormField control={control} name={name} label={label}>
+    <FormField control={control} name={name} label={label} orientation="horizontal">
       {({ value, onChange, onBlur, id, ...rest }) => (
         <Checkbox
           id={id}
diff --git a/ui/litellm-dashboard/src/components/TeamsPage/TeamsTable.test.tsx b/ui/litellm-dashboard/src/components/TeamsPage/TeamsTable.test.tsx
index 9375673ba10..d3b9a55a7d5 100644
--- a/ui/litellm-dashboard/src/components/TeamsPage/TeamsTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/TeamsPage/TeamsTable.test.tsx
@@ -2,7 +2,7 @@ import { fireEvent, screen, waitFor, within } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { beforeEach, describe, expect, it, MockedFunction, vi } from "vitest";
 
-import { renderWithProviders } from "../../../tests/test-utils";
+import { chooseSelectOption, renderWithProviders } from "../../../tests/test-utils";
 import { Team } from "../key_team_helpers/key_list";
 import { TeamsResponse, useTeamsTable } from "@/app/(dashboard)/hooks/teams/useTeams";
 import { TeamsTable } from "./TeamsTable";
@@ -243,8 +243,7 @@ describe("row actions", () => {
     await user.click(await screen.findByText("Edit team"));
     expect(onEditTeam).toHaveBeenCalledWith(expect.objectContaining({ team_id: "team-1" }));
 
-    await user.click(screen.getByTestId("team-actions-team-1"));
-    await user.click(await screen.findByText("Delete team"));
+    await chooseSelectOption(user, screen.getByTestId("team-actions-team-1"), "Delete team", "menuitem");
     expect(onDeleteTeam).toHaveBeenCalledWith(expect.objectContaining({ team_id: "team-1" }));
   });
 
diff --git a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
index d09ccbf8826..b06448912d0 100644
--- a/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/VirtualKeysPage/VirtualKeysTable.test.tsx
@@ -2,7 +2,7 @@ import { screen, waitFor, within, fireEvent } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import type { OnUrlUpdateFunction } from "nuqs/adapters/testing";
 import { vi, it, expect, beforeEach, describe, Mock, MockedFunction } from "vitest";
-import { renderWithProviders } from "../../../tests/test-utils";
+import { chooseSelectOption, renderWithProviders } from "../../../tests/test-utils";
 import { VirtualKeysTable } from "./VirtualKeysTable";
 import { KeyResponse, Team } from "../key_team_helpers/key_list";
 import { useKeyInfo } from "@/app/(dashboard)/hooks/keys/useKeyInfo";
@@ -327,8 +327,7 @@ it("sorts by the backend max_budget field when 'Budget descending' is chosen fro
   const user = userEvent.setup();
   renderWithProviders(<VirtualKeysTable />);
 
-  await user.click(screen.getByTestId("sort-trigger-spend"));
-  await user.click(await screen.findByText("Budget descending"));
+  await chooseSelectOption(user, screen.getByTestId("sort-trigger-spend"), "Budget descending", "menuitem");
 
   await waitFor(() => {
     expect(mockUseKeys).toHaveBeenLastCalledWith(
@@ -343,8 +342,7 @@ it("emphasizes the active field in the Spend / Budget header so the sorted colum
   const user = userEvent.setup();
   renderWithProviders(<VirtualKeysTable />);
 
-  await user.click(screen.getByTestId("sort-trigger-spend"));
-  await user.click(await screen.findByText("Budget descending"));
+  await chooseSelectOption(user, screen.getByTestId("sort-trigger-spend"), "Budget descending", "menuitem");
 
   await waitFor(() => {
     expect(screen.getByText("Budget", { selector: "[data-sort-field='max_budget']" })).toHaveClass("font-semibold");
@@ -356,8 +354,7 @@ it("sorts by spend ascending when 'Spend ascending' is chosen from the Spend / B
   const user = userEvent.setup();
   renderWithProviders(<VirtualKeysTable />);
 
-  await user.click(screen.getByTestId("sort-trigger-spend"));
-  await user.click(await screen.findByText("Spend ascending"));
+  await chooseSelectOption(user, screen.getByTestId("sort-trigger-spend"), "Spend ascending", "menuitem");
 
   await waitFor(() => {
     expect(mockUseKeys).toHaveBeenLastCalledWith(1, 50, expect.objectContaining({ sortBy: "spend", sortOrder: "asc" }));
diff --git a/ui/litellm-dashboard/src/components/add_model/AddModelForm.tsx b/ui/litellm-dashboard/src/components/add_model/AddModelForm.tsx
index ad0f749b189..92951b68fd5 100644
--- a/ui/litellm-dashboard/src/components/add_model/AddModelForm.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/AddModelForm.tsx
@@ -82,7 +82,7 @@ const AddModelForm: React.FC<AddModelFormProps> = ({
   // Using a unique ID to force the ConnectionErrorDisplay to remount and run a fresh test
   const [connectionTestId, setConnectionTestId] = useState<string>("");
 
-  const { accessToken, userRole, premiumUser, userId } = useAuthorized();
+  const { accessToken, userRole, premiumUser, userId, isViewOnly } = useAuthorized();
   const {
     data: providerMetadata,
     isLoading: isProviderMetadataLoading,
@@ -157,7 +157,10 @@ const AddModelForm: React.FC<AddModelFormProps> = ({
   const isTeamAdmin = isUserTeamAdminForAnyTeam(teams, userId);
   // Same owner the Auto-Routers tab uses, so the two creation forms cannot disagree about
   // who has to name a team. This form is only reachable when creation is allowed at all.
-  const createScope = modelCreationScope({ userRole, userID: userId }, { teams, disabledForInternalUsers: false });
+  const createScope = modelCreationScope(
+    { userRole, userID: userId, isViewOnly },
+    { teams, disabledForInternalUsers: false },
+  );
   const requiresTeamScope = createScope === "team-required";
 
   return (
diff --git a/ui/litellm-dashboard/src/components/add_model/AffinityControls.tsx b/ui/litellm-dashboard/src/components/add_model/AffinityControls.tsx
new file mode 100644
index 00000000000..4d9e2122739
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/add_model/AffinityControls.tsx
@@ -0,0 +1,26 @@
+import React from "react";
+
+import { Switch } from "@/components/ui/switch";
+
+import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig";
+import { DEFAULT_DEPLOYMENT_AFFINITY } from "./ComplexityRouterConfig";
+
+export const AffinityControls: React.FC<{
+  value: ComplexityRouterConfigValue;
+  onChange: (value: ComplexityRouterConfigValue) => void;
+}> = ({ value, onChange }) => (
+  <>
+    <div className="flex items-center gap-2 mb-2">
+      <Switch
+        checked={value.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY}
+        onCheckedChange={(deploymentAffinity) => onChange({ ...value, deployment_affinity: deploymentAffinity })}
+        aria-label="Pin a session to one deployment per model group"
+      />
+      <strong className="font-semibold">Pin a session to one deployment per model group</strong>
+    </div>
+    <span className="block text-xs text-muted-foreground">
+      Keeps a session on the same deployment within a group, so provider prompt caches stay warm. Turn off to
+      load-balance every turn.
+    </span>
+  </>
+);
diff --git a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx
index 2947e29319b..a29527a20fa 100644
--- a/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/ClassificationMethodConfig.tsx
@@ -15,9 +15,12 @@ import { RestrictedSection, restrictedBy } from "./TierRestrictions";
 import HeuristicScoringConfig from "./HeuristicScoringConfig";
 import { useComplexityScorerDefaults } from "@/app/(dashboard)/hooks/autoRouter/useComplexityScorerDefaults";
 import {
+  ClassificationFrequency,
   ClassifierFallback,
   ClassifierType,
   ComplexityRouterConfigValue,
+  classificationFrequency,
+  withClassificationFrequency,
   DEFAULT_CLASSIFIER_CONTEXT_BUDGET_CHARS,
   MIN_QUOTED_CONTEXT_TURN_CHARS,
   DEFAULT_CLASSIFIER_CONTEXT_WINDOW_SIZE,
@@ -32,6 +35,7 @@ import {
   heuristicScoringRole,
   usesLlmClassifier,
   DEFAULT_HEURISTIC_FIRST_MAX_TIER,
+  DEFAULT_HYBRID_BOUNDARY_MARGIN,
   HEURISTIC_FIRST_MAX_TIER_KEYS,
   effectiveClassifierType,
 } from "./ComplexityRouterConfig";
@@ -40,9 +44,14 @@ const DEFAULT_SCORING_EXPLANATION =
   "The router scores each request across 7 dimensions: token count, code presence, reasoning markers, technical " +
   "terms, simple indicators, multi-step patterns, and question complexity. The weighted score determines the tier:";
 
+const HEURISTIC_V2_EXPLANATION =
+  "The router estimates success probability for all four tiers with the bundled calibrated model, then selects " +
+  "the first tier that meets its trained threshold. It runs locally with no classifier API call.";
+
 const CLASSIFIER_TIMEOUT_ID = "classifier-timeout-ms";
 const CLASSIFIER_CONTEXT_WINDOW_SIZE_ID = "classifier-context-window-size";
 const CLASSIFIER_CONTEXT_BUDGET_CHARS_ID = "classifier-context-budget-chars";
+const HYBRID_BOUNDARY_MARGIN_ID = "hybrid-boundary-margin";
 
 const CUSTOM_PROMPT_WITH_HEURISTIC_FALLBACK =
   "This router classifies with your own prompt, so the tier comes from whatever rubric it states. The four tier " +
@@ -59,6 +68,7 @@ const CUSTOM_PROMPT_WITH_DEFAULT_MODEL_FALLBACK =
  * at all, so the panel must not keep implying a score is involved on either router.
  */
 const scoringExplanation = (value: ComplexityRouterConfigValue): string => {
+  if (value.classifier_type === "heuristic_v2") return HEURISTIC_V2_EXPLANATION;
   const usesCustomPrompt =
     usesLlmClassifier(value.classifier_type) && Boolean(value.classifier_llm_config?.system_prompt?.trim());
   if (!usesCustomPrompt) return DEFAULT_SCORING_EXPLANATION;
@@ -111,7 +121,7 @@ const HowClassificationWorks: React.FC<{ value: ComplexityRouterConfigValue }> =
         <strong className="block mb-2 font-semibold">How Classification Works</strong>
         <span className="text-[13px] text-muted-foreground">{scoringExplanation(value)}</span>
         {scorerRuns && ranges && (
-          <ul style={{ marginTop: 8, marginBottom: 0, paddingLeft: 20, fontSize: 13, color: "rgba(0, 0, 0, 0.45)" }}>
+          <ul className="mt-2 pl-5 text-[13px] text-muted-foreground">
             <li>
               <strong>{effectiveTierLabel("SIMPLE", value.tier_labels)}</strong>: Score &lt; {ranges.simpleMedium}
             </li>
@@ -176,6 +186,17 @@ const ClassifierTypeRadios: React.FC<{
             </span>
           </Label>
         </SimpleTooltip>
+        <SimpleTooltip content={scorerLockedReason}>
+          <Label className="items-start font-normal leading-normal has-data-disabled:cursor-not-allowed has-data-disabled:opacity-50">
+            <RadioGroupItem value="heuristic_v2" className="mt-0.5" disabled={scorerLocked} />
+            <span>
+              <strong className="font-semibold">Heuristic v2</strong>{" "}
+              <span className="text-muted-foreground">
+                uses bundled calibrated four-tier probabilities with no API call
+              </span>
+            </span>
+          </Label>
+        </SimpleTooltip>
         <Label className="items-start font-normal leading-normal">
           <RadioGroupItem value="llm" className="mt-0.5" />
           <span>
@@ -194,6 +215,18 @@ const ClassifierTypeRadios: React.FC<{
             </span>
           </Label>
         </SimpleTooltip>
+        <SimpleTooltip content={scorerLockedReason}>
+          <Label className="items-start font-normal leading-normal has-data-disabled:cursor-not-allowed has-data-disabled:opacity-50">
+            <RadioGroupItem value="hybrid" className="mt-0.5" disabled={scorerLocked} />
+            <span>
+              <strong className="font-semibold">Hybrid</strong>{" "}
+              <span className="text-muted-foreground">
+                keeps the local score at any tier, and only pays for the classifier when that score lands near a tier
+                boundary
+              </span>
+            </span>
+          </Label>
+        </SimpleTooltip>
       </div>
     </RadioGroup>
   );
@@ -211,6 +244,7 @@ const ClassificationMethodConfig: React.FC<ClassificationMethodConfigProps> = ({
   const [draft, setDraft] = React.useState<{ id: string; raw: string } | null>(null);
   const hasDefaultModel = Boolean(defaultModel);
   const classifierType = effectiveClassifierType(value);
+  const sessionFrequencyRestriction = restrictedBy(value, "sessionAffinity");
   const classifierModelMissing =
     showValidationErrors && usesLlmClassifier(classifierType) && !value.classifier_llm_config?.model;
   const usesCustomPrompt = Boolean(value.classifier_llm_config?.system_prompt?.trim());
@@ -243,6 +277,8 @@ const ClassificationMethodConfig: React.FC<ClassificationMethodConfigProps> = ({
         classifierType === "heuristic_first"
           ? value.heuristic_first_max_tier ?? DEFAULT_HEURISTIC_FIRST_MAX_TIER
           : undefined,
+      hybrid_boundary_margin:
+        classifierType === "hybrid" ? value.hybrid_boundary_margin ?? DEFAULT_HYBRID_BOUNDARY_MARGIN : undefined,
     };
     onChange(nextValue);
   };
@@ -251,6 +287,13 @@ const ClassificationMethodConfig: React.FC<ClassificationMethodConfigProps> = ({
     onChange({ ...value, heuristic_first_max_tier: tier });
   };
 
+  const handleHybridBoundaryMarginChange = (raw: string) => {
+    setDraft({ id: HYBRID_BOUNDARY_MARGIN_ID, raw });
+    const parsed = Number(raw);
+    if (raw.trim() === "" || !Number.isFinite(parsed)) return;
+    onChange({ ...value, hybrid_boundary_margin: Math.min(1, Math.max(0, parsed)) });
+  };
+
   const handleClassificationPromptChange = (classificationPrompt: string | undefined) => {
     onChange({ ...value, classification_prompt: classificationPrompt });
   };
@@ -305,6 +348,10 @@ const ClassificationMethodConfig: React.FC<ClassificationMethodConfigProps> = ({
     onChange({ ...value, classifier_fallback: fallback });
   };
 
+  const handleClassificationFrequencyChange = (frequency: ClassificationFrequency) => {
+    onChange(withClassificationFrequency(value, frequency));
+  };
+
   const handleClassifierContextWindowSizeChange = (windowSize: number) => {
     onChange({
       ...value,
@@ -367,6 +414,73 @@ const ClassificationMethodConfig: React.FC<ClassificationMethodConfigProps> = ({
         </div>
       )}
 
+      {classifierType === "hybrid" && (
+        <div className="mt-4 space-y-2">
+          <strong className="block font-semibold">Boundary margin</strong>
+          <Input
+            id={HYBRID_BOUNDARY_MARGIN_ID}
+            type="text"
+            inputMode="decimal"
+            value={
+              draft?.id === HYBRID_BOUNDARY_MARGIN_ID
+                ? draft.raw
+                : String(value.hybrid_boundary_margin ?? DEFAULT_HYBRID_BOUNDARY_MARGIN)
+            }
+            onChange={(event) => handleHybridBoundaryMarginChange(event.target.value)}
+            onBlur={() => setDraft(null)}
+            className="w-full"
+          />
+          <p className="text-sm text-muted-foreground">
+            A score further than this from every tier boundary routes on the scorer&apos;s own tier, however expensive
+            that tier is. A score closer than this, and anything the scorer found no signal for at all, goes to the
+            classifier to break the tie
+          </p>
+        </div>
+      )}
+
+      <div className="mt-4 space-y-2">
+        <strong className="block font-semibold">How often to classify</strong>
+        <RadioGroup
+          value={classificationFrequency(value)}
+          onValueChange={(frequency: unknown) =>
+            handleClassificationFrequencyChange(frequency as ClassificationFrequency)
+          }
+        >
+          <div className="inline-flex flex-col gap-2">
+            <Label className="items-start font-normal leading-normal">
+              <RadioGroupItem value="every_request" className="mt-0.5" />
+              <span>
+                <span>Every request</span>{" "}
+                <span className="text-muted-foreground">: score every turn, tool-result continuations included</span>
+              </span>
+            </Label>
+            <Label className="items-start font-normal leading-normal">
+              <RadioGroupItem value="user_turn" className="mt-0.5" />
+              <span>
+                <span>Every new user message</span>{" "}
+                <span className="text-muted-foreground">
+                  : score each new human ask, then hold that tier for the tool calls that follow it
+                </span>
+              </span>
+            </Label>
+            <Label className="items-start font-normal leading-normal">
+              <RadioGroupItem value="session" className="mt-0.5" disabled={Boolean(sessionFrequencyRestriction)} />
+              <span>
+                <span>Once per session</span>{" "}
+                <span className="text-muted-foreground">
+                  {sessionFrequencyRestriction?.reason ??
+                    ": score the first turn only, then hold that tier and its deployment for the whole session"}
+                </span>
+              </span>
+            </Label>
+          </div>
+        </RadioGroup>
+        <p className="text-sm text-muted-foreground">
+          Holding the tier keeps an agent on one model for a whole tool loop and cuts scoring cost. A turn the router
+          cannot match to a held decision, such as one with no session id or an expired one, is scored again
+        </p>
+      </div>
+
       {usesLlmClassifier(classifierType) && (
         <div className="mt-4 space-y-3">
           <div>
diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx
index 33ce1169c46..349d03356f8 100644
--- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.test.tsx
@@ -80,6 +80,15 @@ describe("ComplexityRouterConfig", () => {
     expect(screen.getByText(/Score > 0.60/)).toBeInTheDocument();
   });
 
+  it("leaves the score threshold list color to the theme instead of an inline style", () => {
+    renderWithProviders(<ComplexityRouterConfig {...baseProps} />);
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    const list = screen.getByText(/Score < 0.15/).closest<HTMLUListElement>("ul");
+    expect(list).toBeInTheDocument();
+    expect(list).toHaveClass("text-muted-foreground");
+    expect(list?.style.color).toBe("");
+  });
+
   it("should default to heuristic and hide classifier model/timeout fields", () => {
     renderWithProviders(<ComplexityRouterConfig modelInfo={mockModelInfo} value={defaultValue} onChange={vi.fn()} />);
     expect(screen.getByText("Advanced: Classification Method")).toBeInTheDocument();
@@ -118,6 +127,31 @@ describe("ComplexityRouterConfig", () => {
     expect(onChange).toHaveBeenCalledWith(expectedValue);
   });
 
+  it("selects heuristic v2 without requiring a classifier model or showing weighted scoring", () => {
+    const onChange = vi.fn();
+    const { rerender } = renderWithProviders(
+      <ComplexityRouterConfig modelInfo={mockModelInfo} value={defaultValue} onChange={onChange} />,
+    );
+
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    fireEvent.click(screen.getByText("Heuristic v2"));
+
+    expect(onChange).toHaveBeenCalledWith(
+      expect.objectContaining({
+        classifier_type: "heuristic_v2",
+        classifier_llm_config: undefined,
+      }),
+    );
+
+    const heuristicV2Value: ComplexityRouterConfigValue = { ...defaultValue, classifier_type: "heuristic_v2" };
+    rerender(<ComplexityRouterConfig modelInfo={mockModelInfo} value={heuristicV2Value} onChange={onChange} />);
+
+    expect(screen.queryByText("Classifier Model")).not.toBeInTheDocument();
+    expect(screen.queryByText("Advanced scoring")).not.toBeInTheDocument();
+    expect(screen.getByText(/estimates success probability for all four tiers/)).toBeInTheDocument();
+    expect(screen.queryByText(/Score < 0.15/)).not.toBeInTheDocument();
+  });
+
   it("should show classifier fields and use the configured values when classifier_type is llm", () => {
     const llmValue: ComplexityRouterConfigValue = {
       ...defaultValue,
@@ -589,6 +623,82 @@ describe("ComplexityRouterConfig classifier fallback", () => {
   });
 });
 
+describe("ComplexityRouterConfig classification frequency", () => {
+  const llmValue: ComplexityRouterConfigValue = {
+    ...defaultValue,
+    classifier_type: "llm",
+    classifier_llm_config: { model: "gpt-3.5-turbo", timeout_ms: 3000 },
+  };
+
+  it("defaults to every request, matching both backend field defaults", () => {
+    renderWithProviders(<ComplexityRouterConfig modelInfo={mockModelInfo} value={llmValue} onChange={vi.fn()} />);
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    expect(screen.getByRole("radio", { name: /Every request/ })).toBeChecked();
+    expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked();
+    expect(screen.getByRole("radio", { name: /Once per session/ })).not.toBeChecked();
+  });
+
+  it("writes both wire fields when the frequency moves to every new user message", () => {
+    const onChange = vi.fn();
+    renderWithProviders(<ComplexityRouterConfig modelInfo={mockModelInfo} value={llmValue} onChange={onChange} />);
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    fireEvent.click(screen.getByRole("radio", { name: /Every new user message/ }));
+    expect(onChange).toHaveBeenCalledWith({
+      ...llmValue,
+      classification_mode: "user_turn",
+      session_affinity: false,
+    });
+  });
+
+  it("writes session affinity, not a classification mode, when the frequency moves to once per session", () => {
+    const onChange = vi.fn();
+    renderWithProviders(<ComplexityRouterConfig modelInfo={mockModelInfo} value={llmValue} onChange={onChange} />);
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    fireEvent.click(screen.getByRole("radio", { name: /Once per session/ }));
+    expect(onChange).toHaveBeenCalledWith({
+      ...llmValue,
+      classification_mode: "every_request",
+      session_affinity: true,
+    });
+  });
+
+  it("shows a hand-authored config that sets both fields as once per session, matching the backend", () => {
+    renderWithProviders(
+      <ComplexityRouterConfig
+        modelInfo={mockModelInfo}
+        value={{ ...llmValue, classification_mode: "user_turn", session_affinity: true }}
+        onChange={vi.fn()}
+      />,
+    );
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    expect(screen.getByRole("radio", { name: /Once per session/ })).toBeChecked();
+    expect(screen.getByRole("radio", { name: /Every new user message/ })).not.toBeChecked();
+  });
+
+  it("records a switch back to every request", () => {
+    const onChange = vi.fn();
+    renderWithProviders(
+      <ComplexityRouterConfig
+        modelInfo={mockModelInfo}
+        value={{ ...llmValue, classification_mode: "user_turn" }}
+        onChange={onChange}
+      />,
+    );
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeChecked();
+    fireEvent.click(screen.getByRole("radio", { name: /Every request/ }));
+    expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ classification_mode: "every_request" }));
+  });
+
+  it("offers the frequency on a heuristic router, where holding the tier still pins the model", () => {
+    // The backend pin is gated on the two fields alone, so a heuristic router that switches models
+    // mid tool loop is fixed by this control too.
+    renderWithProviders(<ComplexityRouterConfig modelInfo={mockModelInfo} value={defaultValue} onChange={vi.fn()} />);
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    expect(screen.getByRole("radio", { name: /Every new user message/ })).toBeInTheDocument();
+  });
+});
+
 describe("ComplexityRouterConfig classifier rubric", () => {
   const llmValue: ComplexityRouterConfigValue = {
     ...defaultValue,
@@ -751,13 +861,34 @@ describe("ComplexityRouterConfig tier labels", () => {
   });
 });
 
+describe("ComplexityRouterConfig modality panel", () => {
+  it("defaults the image-routing switch off and writes modality_routing through onChange", () => {
+    const onChange = vi.fn();
+    renderWithProviders(<ComplexityRouterConfig {...baseProps} onChange={onChange} />);
+    fireEvent.click(screen.getByText("Advanced: Modality Routing"));
+
+    const toggle = screen.getByRole("switch", { name: "Route image requests to vision-capable models" });
+    expect(toggle).not.toBeChecked();
+    fireEvent.click(toggle);
+
+    expect(onChange).toHaveBeenCalledWith({ ...defaultValue, modality_routing: true });
+  });
+
+  it("renders a stored modality_routing=true as on", () => {
+    renderWithProviders(<ComplexityRouterConfig {...baseProps} value={{ ...defaultValue, modality_routing: true }} />);
+    fireEvent.click(screen.getByText("Advanced: Modality Routing"));
+
+    expect(screen.getByRole("switch", { name: "Route image requests to vision-capable models" })).toBeChecked();
+  });
+});
+
 describe("ComplexityRouterConfig affinity panel", () => {
-  it("holds both affinity switches with their backend defaults", () => {
+  it("holds the deployment switch at its backend default, session pinning having moved to the frequency choice", () => {
     renderWithProviders(<ComplexityRouterConfig {...baseProps} />);
     fireEvent.click(screen.getByText("Advanced: Affinity"));
 
     expect(screen.getByRole("switch", { name: "Pin a session to one deployment per model group" })).toBeChecked();
-    expect(screen.getByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked();
+    expect(screen.queryByRole("switch", { name: "Pin a session to its first model" })).not.toBeInTheDocument();
   });
 
   it("writes deployment_affinity through onChange without touching other keys", () => {
@@ -1282,10 +1413,18 @@ describe("ComplexityRouterConfig tier editing", () => {
     expect(screen.getByLabelText("Fallback tier")).toBeInTheDocument();
   });
 
-  it("disables session pinning and says why, rather than letting a stripped value look saved", () => {
-    renderWithProviders(<ComplexityRouterConfig {...baseProps} value={customValue} onEditingTiersChange={vi.fn()} />);
-    fireEvent.click(screen.getByText("Advanced: Affinity"));
-    expect(screen.getByLabelText("Pin a session to its first model")).toHaveAttribute("data-disabled");
+  it("disables the once-per-session frequency and says why, rather than letting a stripped value look saved", () => {
+    renderWithProviders(
+      <ComplexityRouterConfig
+        {...baseProps}
+        value={{ ...customValue, session_affinity: true }}
+        onEditingTiersChange={vi.fn()}
+      />,
+    );
+    fireEvent.click(screen.getByText("Advanced: Classification Method"));
+    const sessionOption = screen.getByRole("radio", { name: /Once per session/ });
+    expect(sessionOption).toHaveAttribute("aria-disabled", "true");
+    expect(sessionOption).not.toBeChecked();
     expect(
       screen.getByText("Session pinning escalates along the built-in tier ladder", { exact: false }),
     ).toBeInTheDocument();
diff --git a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx
index 153afa0b586..73ab4f0abef 100644
--- a/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx
@@ -4,6 +4,9 @@ import { SearchSelect } from "@/components/shared/SearchSelect";
 import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select";
 import { ChevronRight, Info, Plus, Trash2, X } from "lucide-react";
 import { Switch } from "@/components/ui/switch";
+
+import { AffinityControls } from "./AffinityControls";
+import { ModalityRoutingControls } from "./ModalityRoutingControls";
 import { Card, CardContent } from "@/components/ui/card";
 import { Collapsible, CollapsibleContent, CollapsibleTrigger } from "@/components/ui/collapsible";
 import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group";
@@ -29,6 +32,7 @@ import React from "react";
 import { ModelGroup } from "@/components/llm_calls/fetch_models";
 import AdaptiveRoutingConfig from "./AdaptiveRoutingConfig";
 import ClassificationMethodConfig from "./ClassificationMethodConfig";
+import ContextWindowEscalationConfig from "./ContextWindowEscalationConfig";
 import { Restricted, restrictedBy } from "./TierRestrictions";
 import { type TierSetAction, applyTierSetAction, setFallbackTier } from "./tier_set_actions";
 import {
@@ -55,6 +59,16 @@ export const MIN_QUOTED_CONTEXT_TURN_CHARS = 120;
 export const DEFAULT_SESSION_AFFINITY = false;
 export const DEFAULT_DEPLOYMENT_AFFINITY = true;
 
+export type ClassificationMode = "every_request" | "user_turn";
+
+export const DEFAULT_CLASSIFICATION_MODE: ClassificationMode = "every_request";
+
+/**
+ * One operator-facing choice over the two wire fields that share the router's tier-pin machinery:
+ * session affinity pins every turn, user_turn pins every turn except a new human ask.
+ */
+export type ClassificationFrequency = ClassificationMode | "session";
+
 export type ComplexityTiers = {
   SIMPLE: string[];
   MEDIUM: string[];
@@ -114,7 +128,7 @@ export interface ClassifierLLMConfig {
   system_prompt?: string;
 }
 
-export type ClassifierType = "heuristic" | "llm" | "heuristic_first";
+export type ClassifierType = "heuristic" | "heuristic_v2" | "llm" | "heuristic_first" | "hybrid";
 
 /**
  * Whether this router can call classifier_llm_config.model. Mirrors the backend's
@@ -122,7 +136,7 @@ export type ClassifierType = "heuristic" | "llm" | "heuristic_first";
  * control and payload key, so a new chaining type cannot strip knobs the operator set.
  */
 export const usesLlmClassifier = (classifierType: ClassifierType): boolean =>
-  classifierType === "llm" || classifierType === "heuristic_first";
+  classifierType === "llm" || classifierType === "heuristic_first" || classifierType === "hybrid";
 
 export type ClassifierFallback = "heuristic" | "default_model";
 
@@ -147,7 +161,9 @@ export const heuristicScoringRoleFor = (
   classifierType: ClassifierType,
   classifierFallback: ClassifierFallback | undefined,
 ): HeuristicScoringRole => {
-  if (classifierType === "heuristic" || classifierType === "heuristic_first") return "decides";
+  if (classifierType === "heuristic_v2") return "never";
+  if (classifierType === "heuristic" || classifierType === "heuristic_first" || classifierType === "hybrid")
+    return "decides";
   return (classifierFallback ?? DEFAULT_CLASSIFIER_FALLBACK) === "heuristic" ? "fallback_only" : "never";
 };
 
@@ -174,13 +190,19 @@ const builtInTierInfo = (rowId: string): { label: string; description: string; e
   return builtIn ? TIER_DESCRIPTIONS[builtIn] : undefined;
 };
 
+const tierConfigIntroText = (value: ComplexityRouterConfigValue): string => {
+  if (value.classifier_type === "heuristic_v2") {
+    return "The complexity router classifies each request with a calibrated local four-tier model (no API calls). Configure which model(s) handle each tier.";
+  }
+  if (heuristicScoringRole(value) === "never") {
+    return "The complexity router classifies each request with your classifier model and routes it to that tier. Configure which model(s) handle each tier.";
+  }
+  return "The complexity router automatically classifies requests by complexity using rule-based scoring (no API calls, <1ms latency). Configure which model(s) handle each tier.";
+};
+
 const TierConfigIntro: React.FC<{ value: ComplexityRouterConfigValue }> = ({ value }) => (
   <>
-    <span className="block mb-6 text-muted-foreground">
-      {heuristicScoringRole(value) === "never"
-        ? "The complexity router classifies each request with your classifier model and routes it to that tier. Configure which model(s) handle each tier."
-        : "The complexity router automatically classifies requests by complexity using rule-based scoring (no API calls, <1ms latency). Configure which model(s) handle each tier."}
-    </span>
+    <span className="block mb-6 text-muted-foreground">{tierConfigIntroText(value)}</span>
 
     <span className="block mb-4 text-xs text-muted-foreground">
       {restrictedBy(value, "displayNames")?.reason ??
@@ -383,7 +405,11 @@ export interface ComplexityRouterConfigValue {
   classification_prompt?: string;
   /** Highest tier the scorer may decide alone under heuristic_first. Required by that type, rejected by the others. */
   heuristic_first_max_tier?: string;
+  /** How near a tier boundary a score may land before hybrid defers to the classifier. Required by that type, rejected by the others. */
+  hybrid_boundary_margin?: number;
+  classification_mode?: ClassificationMode;
   session_affinity?: boolean;
+  modality_routing?: boolean;
   deployment_affinity?: boolean;
   /** Plan-mode floor as a tier ROW ID, unset meaning off. The wire carries the row's name. */
   plan_mode_min_tier?: string;
@@ -392,6 +418,13 @@ export interface ComplexityRouterConfigValue {
   tier_distance_penalty?: number;
   adaptive_eligible?: AdaptiveEligible;
   return_raw_model_name?: boolean;
+  /**
+   * Context-window escalation gate. Undefined means untouched, which keeps both keys out of the
+   * payload so the router tracks the backend defaults (enabled, 0.95 buffer); an explicit false
+   * is a real opt-out and must survive the edit round-trip.
+   */
+  enable_context_window_escalation?: boolean;
+  context_window_escalation_buffer?: number;
   /**
    * Heuristic scorer knobs. Undefined means the operator never touched them, which keeps the key out of the
    * payload so the router tracks the backend defaults rather than freezing today's numbers.
@@ -412,6 +445,21 @@ export interface ComplexityRouterConfigValue {
   tier_model_params?: TierModelParamsByTier;
 }
 
+/** Session affinity wins where a hand-authored config sets both, matching the backend's own `or`. */
+export const classificationFrequency = (value: ComplexityRouterConfigValue): ClassificationFrequency => {
+  if (!value.custom_tier_set && (value.session_affinity ?? DEFAULT_SESSION_AFFINITY)) return "session";
+  return value.classification_mode === "user_turn" ? "user_turn" : "every_request";
+};
+
+export const withClassificationFrequency = (
+  value: ComplexityRouterConfigValue,
+  frequency: ClassificationFrequency,
+): ComplexityRouterConfigValue => ({
+  ...value,
+  classification_mode: frequency === "user_turn" ? "user_turn" : "every_request",
+  session_affinity: frequency === "session",
+});
+
 interface ComplexityRouterConfigProps {
   modelInfo: ModelGroup[];
   value: ComplexityRouterConfigValue;
@@ -471,45 +519,15 @@ export const effectiveTierLabel = (tier: keyof ComplexityTiers, tierLabels: Comp
 
 export const DEFAULT_HEURISTIC_FIRST_MAX_TIER = "SIMPLE";
 
+/** What the Hybrid radio starts at. Required by that type, so the form always has a value to send. */
+export const DEFAULT_HYBRID_BOUNDARY_MARGIN = 0.03;
+
 /**
  * Tiers the heuristic_first threshold may name. The top tier is excluded because it would short
  * circuit every request and leave the classifier unreachable, which the backend rejects.
  */
 export const HEURISTIC_FIRST_MAX_TIER_KEYS = TIER_KEYS.slice(0, -1);
 
-const AffinityControls: React.FC<{
-  value: ComplexityRouterConfigValue;
-  onChange: (value: ComplexityRouterConfigValue) => void;
-}> = ({ value, onChange }) => (
-  <>
-    <div className="flex items-center gap-2 mb-2">
-      <Switch
-        checked={value.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY}
-        onCheckedChange={(deploymentAffinity) => onChange({ ...value, deployment_affinity: deploymentAffinity })}
-        aria-label="Pin a session to one deployment per model group"
-      />
-      <strong className="font-semibold">Pin a session to one deployment per model group</strong>
-    </div>
-    <span className="block text-xs mb-3 text-muted-foreground">
-      Keeps a session on the same deployment within a group, so provider prompt caches stay warm. Turn off to
-      load-balance every turn.
-    </span>
-    <div className="flex items-center gap-2 mb-2">
-      <Switch
-        checked={value.custom_tier_set ? false : value.session_affinity ?? DEFAULT_SESSION_AFFINITY}
-        disabled={Boolean(value.custom_tier_set)}
-        onCheckedChange={(sessionAffinity) => onChange({ ...value, session_affinity: sessionAffinity })}
-        aria-label="Pin a session to its first model"
-      />
-      <strong className="font-semibold">Pin a session to its first model</strong>
-    </div>
-    <span className="block text-xs text-muted-foreground">
-      {restrictedBy(value, "sessionAffinity")?.reason ??
-        "Keeps a session on its first turn's model instead of re-classifying each turn. Also pins the deployment."}
-    </span>
-  </>
-);
-
 const PlanModeOverrideControls: React.FC<{
   value: ComplexityRouterConfigValue;
   onChange: (value: ComplexityRouterConfigValue) => void;
@@ -820,6 +838,11 @@ const ComplexityRouterConfig: React.FC<ComplexityRouterConfigProps> = ({
             label: <strong className="text-foreground font-semibold">Advanced: Affinity</strong>,
             children: <AffinityControls value={value} onChange={onChange} />,
           },
+          {
+            key: "modality",
+            label: <strong className="text-foreground font-semibold">Advanced: Modality Routing</strong>,
+            children: <ModalityRoutingControls value={value} onChange={onChange} />,
+          },
           {
             key: "plan-mode",
             label: <strong className="text-foreground font-semibold">Advanced: Plan-Mode Override</strong>,
@@ -827,6 +850,11 @@ const ComplexityRouterConfig: React.FC<ComplexityRouterConfigProps> = ({
               <PlanModeOverrideControls value={value} onChange={onChange} planModeTierOptions={planModeTierOptions} />
             ),
           },
+          {
+            key: "context-window",
+            label: <strong className="text-foreground font-semibold">Advanced: Context Window Escalation</strong>,
+            children: <ContextWindowEscalationConfig value={value} onChange={onChange} />,
+          },
           {
             key: "response",
             label: <strong className="text-foreground font-semibold">Advanced: Response Format</strong>,
diff --git a/ui/litellm-dashboard/src/components/add_model/ContextWindowEscalationConfig.tsx b/ui/litellm-dashboard/src/components/add_model/ContextWindowEscalationConfig.tsx
new file mode 100644
index 00000000000..c0a65076d20
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/add_model/ContextWindowEscalationConfig.tsx
@@ -0,0 +1,60 @@
+import { Input } from "@/components/ui/input";
+import { Switch } from "@/components/ui/switch";
+import React from "react";
+import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig";
+
+const ContextWindowEscalationConfig: React.FC<{
+  value: ComplexityRouterConfigValue;
+  onChange: (value: ComplexityRouterConfigValue) => void;
+}> = ({ value, onChange }) => {
+  const enabled = value.enable_context_window_escalation ?? true;
+  // A number input renders Number("0.") as "0", so a decimal cannot be typed without a local draft.
+  const [bufferDraft, setBufferDraft] = React.useState<string | null>(null);
+  const commitBuffer = (raw: string) => {
+    setBufferDraft(null);
+    if (raw.trim() === "") {
+      onChange({ ...value, context_window_escalation_buffer: undefined });
+      return;
+    }
+    const parsed = Number(raw);
+    if (!Number.isFinite(parsed)) return;
+    onChange({ ...value, context_window_escalation_buffer: Math.min(1, Math.max(0.01, parsed)) });
+  };
+  return (
+    <>
+      <div className="flex items-center gap-2 mb-2">
+        <Switch
+          checked={enabled}
+          onCheckedChange={(next) => onChange({ ...value, enable_context_window_escalation: next })}
+          aria-label="Escalate oversized prompts to a tier that fits"
+        />
+        <strong className="font-semibold">Escalate oversized prompts to a tier that fits</strong>
+      </div>
+      <span className="block text-xs mb-3 text-muted-foreground">
+        When a prompt provably cannot fit the decided tier&apos;s context windows, route it to the lowest tier whose
+        window holds it instead of letting the provider reject it. Off means requests dispatch on complexity alone.
+      </span>
+      {enabled && (
+        <div style={{ maxWidth: 320 }}>
+          <label className="block text-sm font-medium mb-1" htmlFor="context-window-escalation-buffer">
+            Window fit buffer
+          </label>
+          <Input
+            id="context-window-escalation-buffer"
+            inputMode="decimal"
+            value={bufferDraft ?? value.context_window_escalation_buffer ?? ""}
+            placeholder="0.95"
+            onChange={(event) => setBufferDraft(event.target.value)}
+            onBlur={(event) => commitBuffer(event.target.value)}
+          />
+          <span className="block text-xs mt-1 text-muted-foreground">
+            Fraction of a model&apos;s window the counted prompt must fit within, above 0 up to 1. Empty tracks the
+            backend default of 0.95.
+          </span>
+        </div>
+      )}
+    </>
+  );
+};
+
+export default ContextWindowEscalationConfig;
diff --git a/ui/litellm-dashboard/src/components/add_model/HeuristicScoringConfig.test.tsx b/ui/litellm-dashboard/src/components/add_model/HeuristicScoringConfig.test.tsx
index 9dccd767e49..329aef3f9d4 100644
--- a/ui/litellm-dashboard/src/components/add_model/HeuristicScoringConfig.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/HeuristicScoringConfig.test.tsx
@@ -165,6 +165,7 @@ describe("ClassificationMethodConfig scorer gating", () => {
 
   it.each([
     ["heuristic decides the tier", "heuristic" as ClassifierType, undefined, true],
+    ["heuristic v2 decides without the weighted scorer", "heuristic_v2" as ClassifierType, undefined, false],
     ["an LLM classifier falls back to the heuristic", "llm" as ClassifierType, "heuristic" as ClassifierFallback, true],
     [
       "an LLM classifier falls back to the default model",
diff --git a/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx b/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx
new file mode 100644
index 00000000000..dd697b35239
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/add_model/ModalityRoutingControls.tsx
@@ -0,0 +1,26 @@
+import React from "react";
+
+import { Switch } from "@/components/ui/switch";
+
+import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig";
+
+export const ModalityRoutingControls: React.FC<{
+  value: ComplexityRouterConfigValue;
+  onChange: (value: ComplexityRouterConfigValue) => void;
+}> = ({ value, onChange }) => (
+  <>
+    <div className="flex items-center gap-2 mb-2">
+      <Switch
+        checked={value.modality_routing ?? false}
+        onCheckedChange={(modalityRouting) => onChange({ ...value, modality_routing: modalityRouting })}
+        aria-label="Route image requests to vision-capable models"
+      />
+      <strong className="font-semibold">Route image requests to vision-capable models</strong>
+    </div>
+    <span className="block text-xs text-muted-foreground">
+      Replaces a routed model that cannot take image input with the nearest higher tier that can, then the default
+      model, instead of failing with a provider 400. Only models explicitly declared supports_vision false are replaced,
+      and a kept session pin still wins.
+    </span>
+  </>
+);
diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
index 01cb41bcb95..ba380662403 100644
--- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
@@ -101,18 +101,24 @@ vi.mock("./build_complexity_router_config", async (importOriginal) => {
 });
 
 // A real TeamDropdown fetches teams and renders an antd Select; the wiring under test is
-// whether team_id is registered, validated and forwarded, so a plain control stands in.
+// whether team_id is registered, validated and forwarded, so a plain control stands in. The
+// clear button mirrors the real dropdown's x, which emits null rather than a string.
 vi.mock("../common_components/team_dropdown", () => ({
-  default: ({ value, onChange }: { value?: string; onChange?: (next: string) => void }) => (
-    <select
-      data-testid="team-dropdown"
-      value={value ?? ""}
-      onChange={(event) => onChange?.(event.target.value)}
-      aria-label="Select Team"
-    >
-      <option value="">none</option>
-      <option value="team-1">team-1</option>
-    </select>
+  default: ({ value, onChange }: { value?: string; onChange?: (next: string | null) => void }) => (
+    <>
+      <select
+        data-testid="team-dropdown"
+        value={value ?? ""}
+        onChange={(event) => onChange?.(event.target.value)}
+        aria-label="Select Team"
+      >
+        <option value="">none</option>
+        <option value="team-1">team-1</option>
+      </select>
+      <button type="button" data-testid="team-dropdown-clear" onClick={() => onChange?.(null)}>
+        clear team
+      </button>
+    </>
   ),
 }));
 
@@ -354,6 +360,25 @@ describe("AddAutoRouterTab", () => {
     expect(handleAddAutoRouterSubmit).not.toHaveBeenCalled();
   });
 
+  // The shared dropdown emits null on clear while this form's schema wants a string, so the
+  // form maps null back to "": the user sees the pick-a-team message, not a zod type error.
+  it("treats a team picked and then cleared like no team at all", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(
+      <AddAutoRouterTab handleOk={vi.fn()} accessToken="token" userRole="Internal User" createScope="team-required" />,
+    );
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "team-scoped-router");
+    await user.selectOptions(screen.getByTestId("team-dropdown"), "team-1");
+    await user.click(screen.getByTestId("team-dropdown-clear"));
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    expect(await screen.findByText("Please select a team to continue")).toBeInTheDocument();
+    expect(handleAddAutoRouterSubmit).not.toHaveBeenCalled();
+  });
+
   it("defaults a new router to session affinity off, matching the backend field default", async () => {
     const user = userEvent.setup();
     vi.mocked(getMissingTiersError).mockReturnValue(null);
@@ -362,8 +387,8 @@ describe("AddAutoRouterTab", () => {
 
     await user.type(screen.getByPlaceholderText(/smart_router/i), "affinity-router");
     expandDetailedConfiguration();
-    await user.click(screen.getByText("Advanced: Affinity"));
-    expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked();
+    await user.click(screen.getByText("Advanced: Classification Method"));
+    expect(await screen.findByRole("radio", { name: /Once per session/ })).not.toBeChecked();
 
     await user.click(screen.getByRole("button", { name: /add auto router/i }));
 
@@ -373,6 +398,71 @@ describe("AddAutoRouterTab", () => {
     });
   });
 
+  it("carries a context-window escalation opt-out through to the create payload", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(<Harness />);
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "ctx-window-router");
+    expandDetailedConfiguration();
+    await user.click(screen.getByText("Advanced: Context Window Escalation"));
+    const toggle = await screen.findByRole("switch", { name: "Escalate oversized prompts to a tier that fits" });
+    expect(toggle).toBeChecked();
+    await user.click(toggle);
+
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled());
+    expect(vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config).toMatchObject({
+      enable_context_window_escalation: false,
+    });
+  });
+
+  it("clamps the context-window buffer to 1 and keeps an untouched buffer out of the payload", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(<Harness />);
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "ctx-buffer-router");
+    expandDetailedConfiguration();
+    await user.click(screen.getByText("Advanced: Context Window Escalation"));
+    const buffer = await screen.findByLabelText("Window fit buffer");
+    fireEvent.change(buffer, { target: { value: "1.5" } });
+    fireEvent.blur(buffer, { target: { value: "1.5" } });
+
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled());
+    const config = vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config;
+    expect(config).toMatchObject({ context_window_escalation_buffer: 1 });
+    expect(config).not.toHaveProperty("enable_context_window_escalation");
+  });
+
+  it("clearing the buffer removes it from the payload so the router tracks the backend default", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(<Harness />);
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "ctx-clear-router");
+    expandDetailedConfiguration();
+    await user.click(screen.getByText("Advanced: Context Window Escalation"));
+    const buffer = await screen.findByLabelText("Window fit buffer");
+    fireEvent.change(buffer, { target: { value: "0.8" } });
+    fireEvent.blur(buffer, { target: { value: "0.8" } });
+    fireEvent.change(buffer, { target: { value: "" } });
+    fireEvent.blur(buffer, { target: { value: "" } });
+
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled());
+    expect(vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config).not.toHaveProperty(
+      "context_window_escalation_buffer",
+    );
+  });
+
   // The scalar floor is the one scorer knob with no group dict behind it, so its wiring into the create
   // payload is only proven end to end. 0 is the case a truthy check would silently drop.
   it("carries a reasoning override floor of 0 through to the create payload", async () => {
@@ -403,8 +493,8 @@ describe("AddAutoRouterTab", () => {
 
     await user.type(screen.getByPlaceholderText(/smart_router/i), "affinity-router");
     expandDetailedConfiguration();
-    await user.click(screen.getByText("Advanced: Affinity"));
-    await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" }));
+    await user.click(screen.getByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Once per session/ }));
 
     await user.click(screen.getByRole("button", { name: /add auto router/i }));
 
@@ -414,6 +504,44 @@ describe("AddAutoRouterTab", () => {
     });
   });
 
+  it("carries every new user message through to the create payload", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(<Harness />);
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "user-turn-router");
+    expandDetailedConfiguration();
+    await user.click(screen.getByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Every new user message/ }));
+
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled());
+    expect(vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config).toMatchObject({
+      classification_mode: "user_turn",
+    });
+  });
+
+  it("writes every_request into the create payload when the default frequency stays selected", async () => {
+    const user = userEvent.setup();
+    vi.mocked(getMissingTiersError).mockReturnValue(null);
+
+    renderWithProviders(<Harness />);
+
+    await user.type(screen.getByPlaceholderText(/smart_router/i), "default-timing-router");
+    expandDetailedConfiguration();
+    await user.click(screen.getByText("Advanced: Classification Method"));
+    expect(await screen.findByRole("radio", { name: /Every request/ })).toBeChecked();
+
+    await user.click(screen.getByRole("button", { name: /add auto router/i }));
+
+    await waitFor(() => expect(handleAddAutoRouterSubmit).toHaveBeenCalled());
+    expect(
+      vi.mocked(handleAddAutoRouterSubmit).mock.calls.at(-1)?.[0].complexity_router_config.classification_mode,
+    ).toBe("every_request");
+  });
+
   it("defaults a new router to deployment affinity on, matching the backend field default", async () => {
     const user = userEvent.setup();
     vi.mocked(getMissingTiersError).mockReturnValue(null);
diff --git a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
index 4e5e5e8d460..81acb7b7e50 100644
--- a/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx
@@ -342,6 +342,8 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
     planModeMinTier: complexityRouterConfig.plan_mode_min_tier,
     classificationPrompt: complexityRouterConfig.classification_prompt,
     heuristicFirstMaxTier: complexityRouterConfig.heuristic_first_max_tier,
+    hybridBoundaryMargin: complexityRouterConfig.hybrid_boundary_margin,
+    classificationMode: complexityRouterConfig.classification_mode,
     tierLabels: complexityRouterConfig.tier_labels,
     classifierType: complexityRouterConfig.classifier_type,
     classifierLlmConfig: complexityRouterConfig.classifier_llm_config,
@@ -350,6 +352,7 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
     classifierContextIncludeAssistantTurns: complexityRouterConfig.classifier_context_include_assistant_turns,
     classifierFallback: complexityRouterConfig.classifier_fallback,
     sessionAffinity: complexityRouterConfig.session_affinity ?? DEFAULT_SESSION_AFFINITY,
+    modalityRouting: complexityRouterConfig.modality_routing ?? false,
     deploymentAffinity: complexityRouterConfig.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY,
     customTechnicalKeywords,
     keywordTierRules,
@@ -367,6 +370,8 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
     tokenThresholds: complexityRouterConfig.token_thresholds,
     dimensionWeights: complexityRouterConfig.dimension_weights,
     reasoningOverrideMinScore: complexityRouterConfig.reasoning_override_min_score,
+    enableContextWindowEscalation: complexityRouterConfig.enable_context_window_escalation,
+    contextWindowEscalationBuffer: complexityRouterConfig.context_window_escalation_buffer,
   };
 
   const submitRecommendedRouter = async (name: string) => {
@@ -544,7 +549,9 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
                     "Select the team this auto router belongs to. Only keys for this team will be able to call it.",
                   )}
                 >
-                  {({ id, value, onChange }) => <TeamDropdown id={id} value={value} onChange={onChange} />}
+                  {({ id, value, onChange }) => (
+                    <TeamDropdown id={id} value={value} onChange={(next) => onChange(next ?? "")} />
+                  )}
                 </FormField>
               )}
 
diff --git a/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx b/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx
index 01e00d903aa..ceb9d1ca713 100644
--- a/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/advanced_settings.test.tsx
@@ -1,4 +1,4 @@
-import { act, fireEvent, render, waitFor } from "@testing-library/react";
+import { act, fireEvent, render, waitFor, screen } from "@testing-library/react";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 import { MountedFormHost } from "../../../tests/mounted-form-host";
 import AdvancedSettings from "./advanced_settings";
@@ -35,51 +35,51 @@ describe("AdvancedSettings", () => {
   });
 
   it("should render tags list", async () => {
-    const { getByText } = renderAdvancedSettings();
-    fireEvent.click(getByText("Advanced Settings"));
+    renderAdvancedSettings();
+    fireEvent.click(screen.getByText("Advanced Settings"));
     await waitFor(() => {
-      expect(getByText("Tags")).toBeInTheDocument();
+      expect(screen.getByText("Tags")).toBeInTheDocument();
     });
   });
 
   it("should render the litellm params", async () => {
-    const { getByText } = renderAdvancedSettings();
+    renderAdvancedSettings();
     act(() => {
-      fireEvent.click(getByText("Advanced Settings"));
+      fireEvent.click(screen.getByText("Advanced Settings"));
     });
     await waitFor(() => {
-      expect(getByText("LiteLLM Params")).toBeInTheDocument();
+      expect(screen.getByText("LiteLLM Params")).toBeInTheDocument();
     });
   });
 
   it("hides every PTU field when PTU cost attribution is disabled", async () => {
-    const { getByText, queryByText } = renderAdvancedSettings();
+    renderAdvancedSettings();
     act(() => {
-      fireEvent.click(getByText("Advanced Settings"));
+      fireEvent.click(screen.getByText("Advanced Settings"));
     });
     await waitFor(() => {
-      expect(getByText("Tags")).toBeInTheDocument();
+      expect(screen.getByText("Tags")).toBeInTheDocument();
     });
 
     for (const label of PTU_LABELS) {
-      expect(queryByText(label)).not.toBeInTheDocument();
+      expect(screen.queryByText(label)).not.toBeInTheDocument();
     }
-    expect(queryByText("PTU Effective To (UTC)")).not.toBeInTheDocument();
+    expect(screen.queryByText("PTU Effective To (UTC)")).not.toBeInTheDocument();
   });
 
   it("shows every PTU field when PTU cost attribution is enabled", async () => {
     mockUsePtuCostAttributionEnabled.mockReturnValue(true);
-    const { getByText } = renderAdvancedSettings();
+    renderAdvancedSettings();
     act(() => {
-      fireEvent.click(getByText("Advanced Settings"));
+      fireEvent.click(screen.getByText("Advanced Settings"));
     });
 
     await waitFor(() => {
-      expect(getByText("PTU Count")).toBeInTheDocument();
+      expect(screen.getByText("PTU Count")).toBeInTheDocument();
     });
     for (const label of PTU_LABELS) {
-      expect(getByText(label)).toBeInTheDocument();
+      expect(screen.getByText(label)).toBeInTheDocument();
     }
-    expect(getByText("PTU Effective To (UTC)")).toBeInTheDocument();
+    expect(screen.getByText("PTU Effective To (UTC)")).toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts
index 84406a2093e..c6370541a45 100644
--- a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts
+++ b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts
@@ -52,13 +52,25 @@ describe("buildComplexityRouterConfig", () => {
     const expected = {
       tiers,
       classifier_type: "heuristic",
+      classification_mode: "every_request",
       session_affinity: false,
       deployment_affinity: true,
+      modality_routing: false,
       escalation_keywords: ["LITELLM ESCALATE"],
     };
     expect(config).toEqual(expected);
   });
 
+  it("carries an explicit context-window escalation opt-out and buffer, false included", () => {
+    const config = buildComplexityRouterConfig({
+      ...baseParams,
+      enableContextWindowEscalation: false,
+      contextWindowEscalationBuffer: 0.9,
+    });
+    expect(config.enable_context_window_escalation).toBe(false);
+    expect(config.context_window_escalation_buffer).toBe(0.9);
+  });
+
   it("trims escalation keywords and drops blank entries", () => {
     const config = buildComplexityRouterConfig({
       ...baseParams,
@@ -99,6 +111,21 @@ describe("buildComplexityRouterConfig", () => {
     expect(config.classifier_llm_config).toBeUndefined();
   });
 
+  it("emits heuristic_v2 without classifier-only fields", () => {
+    const trainedParams: BuildComplexityRouterConfigParams = {
+      ...baseParams,
+      classifierType: "heuristic_v2",
+      classifierLlmConfig: { model: "gpt-4o-mini", timeout_ms: 3000 },
+      classifierContextWindowSize: 5,
+      classifierFallback: "heuristic",
+    };
+    const config = buildComplexityRouterConfig(trainedParams);
+    expect(config.classifier_type).toBe("heuristic_v2");
+    expect(config.classifier_llm_config).toBeUndefined();
+    expect(config.classifier_context_window_size).toBeUndefined();
+    expect(config.classifier_fallback).toBeUndefined();
+  });
+
   it("includes classifier_context_window_size and classifier_context_budget_chars only when classifier_type is llm", () => {
     const params: BuildComplexityRouterConfigParams = {
       ...baseParams,
@@ -237,6 +264,12 @@ describe("buildComplexityRouterConfig", () => {
     expect(config.return_raw_model_name).toBeUndefined();
   });
 
+  it("writes modality_routing explicitly both ways, so the stored config never relies on the backend default", () => {
+    expect(buildComplexityRouterConfig({ ...baseParams, modalityRouting: true }).modality_routing).toBe(true);
+    expect(buildComplexityRouterConfig(baseParams).modality_routing).toBe(false);
+    expect(buildComplexityRouterConfig({ ...baseParams, modalityRouting: false }).modality_routing).toBe(false);
+  });
+
   it("writes session_affinity=true so turning the toggle on overrides the backend's off-by-default", () => {
     const config = buildComplexityRouterConfig({ ...baseParams, sessionAffinity: true });
     expect(config.session_affinity).toBe(true);
@@ -695,6 +728,10 @@ describe("getClassifierModelError", () => {
     expect(getClassifierModelError({ classifier_type: "heuristic" })).toBeNull();
   });
 
+  it("stays quiet for a heuristic v2 router, which runs locally", () => {
+    expect(getClassifierModelError({ classifier_type: "heuristic_v2" })).toBeNull();
+  });
+
   it("blocks an LLM classifier with no model, which the router cannot start without", () => {
     expect(getClassifierModelError({ classifier_type: "llm" })).toBe(
       "Please select a classifier model, or switch back to Heuristic",
@@ -773,13 +810,60 @@ describe("heuristic_first", () => {
   });
 
   it("omits heuristic_first_max_tier on every other classifier type, which the backend rejects it on", () => {
-    for (const classifierType of ["heuristic", "llm"] as const) {
+    for (const classifierType of ["heuristic", "heuristic_v2", "llm"] as const) {
       const config = buildComplexityRouterConfig({ ...heuristicFirstParams, classifierType });
       expect(config.heuristic_first_max_tier).toBeUndefined();
     }
   });
 });
 
+describe("hybrid", () => {
+  const hybridParams: BuildComplexityRouterConfigParams = {
+    ...baseParams,
+    classifierType: "hybrid",
+    hybridBoundaryMargin: 0.03,
+    classifierLlmConfig: { model: "gpt-4o-mini", timeout_ms: 3000 },
+    classifierFallback: "default_model",
+  };
+
+  it("emits hybrid_boundary_margin, zero included since exactly-on-a-boundary is a real setting", () => {
+    expect(buildComplexityRouterConfig(hybridParams).hybrid_boundary_margin).toBe(0.03);
+    expect(buildComplexityRouterConfig({ ...hybridParams, hybridBoundaryMargin: 0 }).hybrid_boundary_margin).toBe(0);
+  });
+
+  it("keeps every classifier key the operator set, since hybrid still calls the classifier", () => {
+    const config = buildComplexityRouterConfig(hybridParams);
+    expect(config.classifier_type).toBe("hybrid");
+    expect(config.classifier_llm_config).toEqual({ model: "gpt-4o-mini", timeout_ms: 3000 });
+    expect(config.classifier_fallback).toBe("default_model");
+  });
+
+  it("omits hybrid_boundary_margin on every other classifier type, which the backend rejects it on", () => {
+    for (const classifierType of ["heuristic", "llm", "heuristic_first"] as const) {
+      const config = buildComplexityRouterConfig({
+        ...hybridParams,
+        classifierType,
+        ...(classifierType === "heuristic_first" && { heuristicFirstMaxTier: "SIMPLE" }),
+      });
+      expect(config.hybrid_boundary_margin).toBeUndefined();
+    }
+  });
+});
+
+describe("classification_mode", () => {
+  it("emits user_turn", () => {
+    const config = buildComplexityRouterConfig({ ...baseParams, classificationMode: "user_turn" });
+    expect(config.classification_mode).toBe("user_turn");
+  });
+
+  it("writes every_request explicitly, so a saved router never depends on the backend default", () => {
+    expect(
+      buildComplexityRouterConfig({ ...baseParams, classificationMode: "every_request" }).classification_mode,
+    ).toBe("every_request");
+    expect(buildComplexityRouterConfig(baseParams).classification_mode).toBe("every_request");
+  });
+});
+
 describe("buildComplexityRouterConfig with an edited tier set", () => {
   const customTierSet = {
     tiers: [
@@ -873,10 +957,12 @@ describe("buildComplexityRouterConfig with an edited tier set", () => {
       dimensionWeights: { length: 1 },
       reasoningOverrideMinScore: 0.5,
       heuristicFirstMaxTier: "SIMPLE",
+      hybridBoundaryMargin: 0.03,
       customTechnicalKeywords: ["kubernetes"],
     };
     const emittingType = key === "heuristic_first_max_tier" ? "heuristic_first" : "llm";
-    expect(buildComplexityRouterConfig({ ...baseParams, ...loaded, classifierType: emittingType })).toHaveProperty(key);
+    const typeForKey = key === "hybrid_boundary_margin" ? "hybrid" : emittingType;
+    expect(buildComplexityRouterConfig({ ...baseParams, ...loaded, classifierType: typeForKey })).toHaveProperty(key);
     expect(build(loaded)).not.toHaveProperty(key);
   });
 
@@ -892,6 +978,10 @@ describe("buildComplexityRouterConfig with an edited tier set", () => {
     expect(payload.classifier_llm_config).toEqual({ model: "gpt-4o-mini", timeout_ms: 3000 });
   });
 
+  it("keeps classification_mode, which the backend accepts beside tier_definitions", () => {
+    expect(build({ classificationMode: "user_turn" }).classification_mode).toBe("user_turn");
+  });
+
   it("carries the plan-mode floor as the row's name, not the row id the form holds", () => {
     expect(build({ planModeMinTier: "sec" }).plan_mode_min_tier).toBe("SECURITY_REVIEW");
   });
diff --git a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts
index ba500d116ce..94c5badf6d1 100644
--- a/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts
+++ b/ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts
@@ -19,10 +19,12 @@ import {
 import {
   AdaptiveEligible,
   AdaptiveRouterWeights,
+  ClassificationMode,
   ClassifierFallback,
   ClassifierLLMConfig,
   ClassifierType,
   ComplexityTierLabels,
+  DEFAULT_CLASSIFICATION_MODE,
   ComplexityRouterConfigValue,
   ComplexityTiers,
   DimensionWeights,
@@ -105,7 +107,10 @@ export interface BuildComplexityRouterConfigParams {
   classifierFallback: ClassifierFallback | undefined;
   classificationPrompt: string | undefined;
   heuristicFirstMaxTier: string | undefined;
+  hybridBoundaryMargin?: number;
+  classificationMode: ClassificationMode | undefined;
   sessionAffinity: boolean;
+  modalityRouting?: boolean;
   deploymentAffinity: boolean;
   customTechnicalKeywords: string[];
   keywordTierRules: KeywordTierRule[];
@@ -123,6 +128,8 @@ export interface BuildComplexityRouterConfigParams {
   dimensionWeights?: DimensionWeights;
   reasoningOverrideMinScore?: number;
   tierModelParams?: TierModelParamsByTier;
+  enableContextWindowEscalation?: boolean;
+  contextWindowEscalationBuffer?: number;
 }
 
 /**
@@ -157,8 +164,11 @@ export interface ComplexityRouterConfigPayload {
   classifier_fallback?: ClassifierFallback;
   classification_prompt?: string;
   heuristic_first_max_tier?: string;
+  hybrid_boundary_margin?: number;
+  classification_mode: ClassificationMode;
   session_affinity: boolean;
   deployment_affinity: boolean;
+  modality_routing: boolean;
   custom_technical_keywords?: string[];
   keyword_tier_rules?: { keywords: string[]; tier: KeywordTierRule["tier"] }[];
   semantic_keyword_matching?: boolean;
@@ -174,6 +184,8 @@ export interface ComplexityRouterConfigPayload {
   token_thresholds?: TokenThresholds;
   dimension_weights?: DimensionWeights;
   reasoning_override_min_score?: number;
+  enable_context_window_escalation?: boolean;
+  context_window_escalation_buffer?: number;
   tier_model_configs?: Record<string, { model_name: string; litellm_params: TierModelParams }[]>;
 }
 
@@ -342,6 +354,7 @@ const classifierWireFields = (
     classifierLlmConfig,
     classifierFallback,
     heuristicFirstMaxTier,
+    hybridBoundaryMargin,
     classifierContextWindowSize,
     classifierContextBudgetChars,
     classifierContextIncludeAssistantTurns,
@@ -350,6 +363,7 @@ const classifierWireFields = (
     | "classifierLlmConfig"
     | "classifierFallback"
     | "heuristicFirstMaxTier"
+    | "hybridBoundaryMargin"
     | "classifierContextWindowSize"
     | "classifierContextBudgetChars"
     | "classifierContextIncludeAssistantTurns"
@@ -361,6 +375,8 @@ const classifierWireFields = (
     classifierFallback !== undefined && { classifier_fallback: classifierFallback }),
   ...(effectiveType === "heuristic_first" &&
     heuristicFirstMaxTier?.trim() && { heuristic_first_max_tier: heuristicFirstMaxTier }),
+  ...(effectiveType === "hybrid" &&
+    hybridBoundaryMargin !== undefined && { hybrid_boundary_margin: hybridBoundaryMargin }),
   ...(usesLlmClassifier(effectiveType) &&
     classifierContextWindowSize !== undefined && {
       classifier_context_window_size: classifierContextWindowSize,
@@ -389,7 +405,10 @@ export const buildComplexityRouterConfig = ({
   classifierFallback,
   classificationPrompt,
   heuristicFirstMaxTier,
+  hybridBoundaryMargin,
+  classificationMode,
   sessionAffinity,
+  modalityRouting,
   deploymentAffinity,
   customTechnicalKeywords,
   keywordTierRules,
@@ -407,6 +426,8 @@ export const buildComplexityRouterConfig = ({
   dimensionWeights,
   reasoningOverrideMinScore,
   tierModelParams,
+  enableContextWindowEscalation,
+  contextWindowEscalationBuffer,
 }: BuildComplexityRouterConfigParams): ComplexityRouterConfigPayload => {
   const serializedTierModelConfigs = customTierSet
     ? serializeTierModelConfigs(
@@ -430,6 +451,7 @@ export const buildComplexityRouterConfig = ({
     classifierLlmConfig,
     classifierFallback,
     heuristicFirstMaxTier,
+    hybridBoundaryMargin,
     classifierContextWindowSize,
     classifierContextBudgetChars,
     classifierContextIncludeAssistantTurns,
@@ -446,8 +468,10 @@ export const buildComplexityRouterConfig = ({
     ...(cleanedTierLabels && { tier_labels: cleanedTierLabels }),
     classifier_type: classifierType,
     ...classifierWireFields(effectiveType, classifierInputs),
+    classification_mode: classificationMode ?? DEFAULT_CLASSIFICATION_MODE,
     session_affinity: sessionAffinity,
     deployment_affinity: deploymentAffinity,
+    modality_routing: modalityRouting ?? false,
     ...(customTechnicalKeywords.length > 0 && { custom_technical_keywords: customTechnicalKeywords }),
     ...(cleanedKeywordTierRules.length > 0 && { keyword_tier_rules: cleanedKeywordTierRules }),
     escalation_keywords: cleanedEscalationKeywords,
@@ -463,6 +487,12 @@ export const buildComplexityRouterConfig = ({
       adaptive_eligible: adaptiveEligible,
     }),
     ...(returnRawModelName && { return_raw_model_name: true }),
+    ...(enableContextWindowEscalation !== undefined && {
+      enable_context_window_escalation: enableContextWindowEscalation,
+    }),
+    ...(contextWindowEscalationBuffer !== undefined && {
+      context_window_escalation_buffer: contextWindowEscalationBuffer,
+    }),
     ...scorerKnobs,
   };
   if (!customTierSet) return payload;
diff --git a/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.test.tsx b/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.test.tsx
index 7ef09d34924..9d792480c9f 100644
--- a/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.test.tsx
@@ -1,6 +1,10 @@
-import { describe, expect, it } from "vitest";
+import { describe, expect, it, vi } from "vitest";
 import { prepareModelAddRequest } from "./handle_add_model_submit";
 
+vi.mock("../networking", () => ({
+  modelCreateCall: vi.fn(),
+}));
+
 describe("prepareModelAddRequest", () => {
   it("returns deployment data for the most basic form", async () => {
     const formValues = {
@@ -73,4 +77,28 @@ describe("prepareModelAddRequest", () => {
     expect(deployment.litellmParamsObj.litellm_credential_name).toBe("selected-credential");
     expect(deployment.litellmParamsObj.timeout).toBe(5);
   });
+
+  it("keeps litellm_credential_name from LiteLLM Params JSON when no credential is selected", async () => {
+    const formValues = {
+      model_mappings: [
+        {
+          public_name: "Public Model",
+          litellm_model: "litellm/public",
+        },
+      ],
+      model_name: "custom-model-name",
+      litellm_extra_params: JSON.stringify({
+        litellm_credential_name: "from-json",
+        timeout: 5,
+      }),
+      litellm_credential_name: null,
+    };
+
+    const deployments = await prepareModelAddRequest({ ...formValues }, "token", null);
+
+    expect(deployments).toHaveLength(1);
+    const [deployment] = deployments!;
+    expect(deployment.litellmParamsObj.litellm_credential_name).toBe("from-json");
+    expect(deployment.litellmParamsObj.timeout).toBe(5);
+  });
 });
diff --git a/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.tsx b/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.tsx
index bb2f78fa84e..41133958c0a 100644
--- a/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/handle_add_model_submit.tsx
@@ -91,6 +91,9 @@ export const prepareModelAddRequest = async (formValues: Record<string, any>, ac
         if (value === "") {
           continue;
         }
+        if (key === "litellm_credential_name" && value == null) {
+          continue;
+        }
         // Skip the custom_pricing and pricing_model fields as they're only used for UI control
         if (key === "custom_pricing" || key === "pricing_model" || key === "cache_control") {
           continue;
@@ -124,13 +127,13 @@ export const prepareModelAddRequest = async (formValues: Record<string, any>, ac
           if (value && value != undefined) {
             try {
               litellmExtraParams = JSON.parse(value);
-              if ("litellm_credential_name" in litellmExtraParams) {
-                delete litellmExtraParams.litellm_credential_name;
-              }
             } catch (error) {
               toast.fromError("Failed to parse LiteLLM Extra Params: " + error);
               throw new Error("Failed to parse litellm_extra_params: " + error);
             }
+            if ("litellm_credential_name" in litellmExtraParams && formValues.litellm_credential_name) {
+              delete litellmExtraParams.litellm_credential_name;
+            }
             for (const [key, value] of Object.entries(litellmExtraParams)) {
               litellmParamsObj[key] = value;
             }
diff --git a/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx b/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx
index 64074481603..d6476089cd7 100644
--- a/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_model/litellm_model_name.test.tsx
@@ -1,4 +1,4 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import { describe, expect, it } from "vitest";
 import { getPlaceholder, Providers } from "../provider_info_helpers";
 import { MountedFormHost } from "../../../tests/mounted-form-host";
@@ -6,7 +6,7 @@ import LiteLLMModelNameField from "./litellm_model_name";
 
 describe("LitellmModelNameField", () => {
   it("should render", () => {
-    const { getByText } = render(
+    render(
       <MountedFormHost>
         <LiteLLMModelNameField
           selectedProvider={Providers.OpenAI}
@@ -15,16 +15,16 @@ describe("LitellmModelNameField", () => {
         />
       </MountedFormHost>,
     );
-    expect(getByText("LiteLLM Model Name(s)")).toBeInTheDocument();
+    expect(screen.getByText("LiteLLM Model Name(s)")).toBeInTheDocument();
   });
 
   it("should show Azure placeholder as 'my-deployment'", () => {
-    const { getByPlaceholderText, queryByPlaceholderText } = render(
+    render(
       <MountedFormHost>
         <LiteLLMModelNameField selectedProvider={Providers.Azure} providerModels={[]} getPlaceholder={getPlaceholder} />
       </MountedFormHost>,
     );
-    expect(getByPlaceholderText("my-deployment")).toBeInTheDocument();
-    expect(queryByPlaceholderText("gpt-3.5-turbo")).not.toBeInTheDocument();
+    expect(screen.getByPlaceholderText("my-deployment")).toBeInTheDocument();
+    expect(screen.queryByPlaceholderText("gpt-3.5-turbo")).not.toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/components/add_model/tier_rows.ts b/ui/litellm-dashboard/src/components/add_model/tier_rows.ts
index d2706a82037..3c5b149f4da 100644
--- a/ui/litellm-dashboard/src/components/add_model/tier_rows.ts
+++ b/ui/litellm-dashboard/src/components/add_model/tier_rows.ts
@@ -122,10 +122,10 @@ export const CUSTOM_TIER_RESTRICTIONS = {
     reason: "Session pinning escalates along the built-in tier ladder, which your tier set replaces",
   },
   heuristicClassifier: {
-    omit: ["heuristic_first_max_tier"],
+    omit: ["heuristic_first_max_tier", "hybrid_boundary_margin"],
     reason:
       "The heuristic scorer only produces the built-in tiers, so an edited set needs the LLM classifier. " +
-      "Heuristic first is out for the same reason: its local scorer decides the cheap traffic",
+      "Heuristic first and hybrid are out for the same reason: their local scorer decides the traffic it is sure of",
   },
   heuristicScoring: {
     omit: [
diff --git a/ui/litellm-dashboard/src/components/add_pass_through.integration.test.tsx b/ui/litellm-dashboard/src/components/add_pass_through.integration.test.tsx
index df4dbff4111..daaacd7f0e2 100644
--- a/ui/litellm-dashboard/src/components/add_pass_through.integration.test.tsx
+++ b/ui/litellm-dashboard/src/components/add_pass_through.integration.test.tsx
@@ -1,6 +1,6 @@
 import { describe, it, expect, vi, beforeEach } from "vitest";
 import userEvent, { PointerEventsCheckLevel } from "@testing-library/user-event";
-import { fireEvent, renderWithProviders, screen, waitFor } from "../../tests/test-utils";
+import { chooseSelectOption, fireEvent, renderWithProviders, screen, waitFor } from "../../tests/test-utils";
 import AddPassThroughEndpoint from "./add_pass_through";
 
 const createPassThroughEndpoint = vi.fn();
@@ -153,8 +153,7 @@ describe("add_pass_through submit payload", () => {
     await openModal(user);
     await fillRequiredFields(user);
 
-    await user.click(screen.getByLabelText(/HTTP Methods/));
-    await user.click(await screen.findByTitle("POST"));
+    await chooseSelectOption(user, screen.getByLabelText(/HTTP Methods/), "POST");
 
     await submit(user);
 
diff --git a/ui/litellm-dashboard/src/components/alerting/alerting_settings.tsx b/ui/litellm-dashboard/src/components/alerting/alerting_settings.tsx
index 98e876801ac..cff33546fbc 100644
--- a/ui/litellm-dashboard/src/components/alerting/alerting_settings.tsx
+++ b/ui/litellm-dashboard/src/components/alerting/alerting_settings.tsx
@@ -5,6 +5,7 @@ import React, { useState, useEffect } from "react";
 
 import { alertingSettingsCall, updateConfigFieldSetting } from "../networking";
 import DynamicForm from "./dynamic_form";
+import { extractProxyErrorMessage } from "@/lib/http/client";
 import { toast } from "@/lib/toast";
 interface alertingSettingsItem {
   field_name: string;
@@ -43,7 +44,7 @@ const AlertingSettings: React.FC<AlertingSettingsProps> = ({ accessToken, premiu
     setAlertingSettings(updatedSettings);
   };
 
-  const handleSubmit = (formValues: Record<string, any>) => {
+  const handleSubmit = async (formValues: Record<string, any>) => {
     if (!accessToken) {
       return;
     }
@@ -64,18 +65,18 @@ const AlertingSettings: React.FC<AlertingSettingsProps> = ({ accessToken, premiu
     const mergedFormValues = { ...formValues, ...initialFormValues };
     const { slack_alerting, ...alertingArgs } = mergedFormValues;
     try {
-      updateConfigFieldSetting(accessToken, "alerting_args", alertingArgs);
+      await updateConfigFieldSetting(accessToken, "alerting_args", alertingArgs);
       if (typeof slack_alerting === "boolean") {
         if (slack_alerting == true) {
-          updateConfigFieldSetting(accessToken, "alerting", ["slack"]);
+          await updateConfigFieldSetting(accessToken, "alerting", ["slack"]);
         } else {
-          updateConfigFieldSetting(accessToken, "alerting", []);
+          await updateConfigFieldSetting(accessToken, "alerting", []);
         }
       }
       // update value in state
       toast.success("Wait 10s for proxy to update.");
     } catch (error) {
-      // do something
+      toast.error(extractProxyErrorMessage(error));
     }
   };
 
diff --git a/ui/litellm-dashboard/src/components/alerting/dynamic_form.integration.test.tsx b/ui/litellm-dashboard/src/components/alerting/dynamic_form.integration.test.tsx
index f9b9765f59e..7764052173c 100644
--- a/ui/litellm-dashboard/src/components/alerting/dynamic_form.integration.test.tsx
+++ b/ui/litellm-dashboard/src/components/alerting/dynamic_form.integration.test.tsx
@@ -38,6 +38,14 @@ const SETTINGS: Setting[] = [
     stored_in_db: null,
     premium_field: false,
   },
+  {
+    field_name: "daily_spend_per_user_threshold",
+    field_description: "Daily spend threshold per user",
+    field_type: "Float",
+    field_value: 5.5,
+    stored_in_db: true,
+    premium_field: false,
+  },
 ];
 
 const renderForm = (
@@ -170,6 +178,19 @@ describe("DynamicForm change notifications", () => {
     expect(handleInputChange).toHaveBeenCalledWith("daily_report_frequency", 128);
   });
 
+  it("renders a Float field as a decimal-friendly number input and reports changes as numbers", async () => {
+    const user = userEvent.setup();
+    const { handleInputChange } = renderForm();
+
+    const input = screen.getByDisplayValue("5.5");
+    expect(input).toHaveAttribute("type", "number");
+    expect(input).toHaveAttribute("step", "any");
+
+    await user.type(input, "1");
+
+    expect(handleInputChange).toHaveBeenCalledWith("daily_spend_per_user_threshold", 5.51);
+  });
+
   it("reports a reset with the field name and its row index", async () => {
     const user = userEvent.setup();
     const { handleResetField } = renderForm();
@@ -216,7 +237,7 @@ describe("DynamicForm presentation", () => {
 
     expect(screen.getByText("daily_report_frequency")).toBeInTheDocument();
     expect(screen.getByText("How often the report runs")).toBeInTheDocument();
-    expect(screen.getByText("In DB")).toBeInTheDocument();
+    expect(screen.getAllByText("In DB")).toHaveLength(2);
     expect(screen.getByText("In Config")).toBeInTheDocument();
     expect(screen.getByText("Not Set")).toBeInTheDocument();
   });
diff --git a/ui/litellm-dashboard/src/components/alerting/dynamic_form.tsx b/ui/litellm-dashboard/src/components/alerting/dynamic_form.tsx
index be5e76ab0df..42aa58ca0ea 100644
--- a/ui/litellm-dashboard/src/components/alerting/dynamic_form.tsx
+++ b/ui/litellm-dashboard/src/components/alerting/dynamic_form.tsx
@@ -63,11 +63,11 @@ const DynamicForm: React.FC<DynamicFormProps> = ({
   };
 
   const renderControl = (setting: AlertingSetting) => {
-    if (setting.field_type === "Integer") {
+    if (setting.field_type === "Integer" || setting.field_type === "Float") {
       return (
         <Input
           type="number"
-          step={1}
+          step={setting.field_type === "Integer" ? 1 : "any"}
           value={setting.field_value ?? ""}
           onChange={(event) => handleNumericChange(setting, event.target.value)}
         />
diff --git a/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx b/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx
index 24685f9c129..e1faf8be1df 100644
--- a/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx
+++ b/ui/litellm-dashboard/src/components/bulk_create_users_button.test.tsx
@@ -26,8 +26,8 @@ const openUploadStep = async () => {
 
 describe("BulkCreateUsersButton", () => {
   it("should render", () => {
-    const { getByText } = render(<BulkCreateUsersButton accessToken="test-token" teams={[]} possibleUIRoles={null} />);
-    expect(getByText("+ Bulk Invite Users")).toBeInTheDocument();
+    render(<BulkCreateUsersButton accessToken="test-token" teams={[]} possibleUIRoles={null} />);
+    expect(screen.getByText("+ Bulk Invite Users")).toBeInTheDocument();
   });
 
   it("parses a CSV chosen through the file input", async () => {
diff --git a/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx b/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
index 25b35c34861..7cbbb08b623 100644
--- a/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
+++ b/ui/litellm-dashboard/src/components/claude_code_plugins/skill_detail.tsx
@@ -1,5 +1,6 @@
 import React, { useState } from "react";
 import { ArrowLeft, Check, Copy, Link2 } from "lucide-react";
+import { cn } from "@/lib/cva.config";
 import { buildMarketplaceSettingsSnippet, formatInstallCommand } from "./helpers";
 import { Plugin } from "./types";
 
@@ -50,48 +51,37 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
   ];
 
   return (
-    <div style={{ padding: "24px 32px 24px 0" }}>
+    <div className="py-6 pl-0 pr-8">
       {/* Back link */}
       <div
         onClick={onBack}
-        style={{
-          display: "inline-flex",
-          alignItems: "center",
-          gap: 6,
-          color: "#5f6368",
-          cursor: "pointer",
-          fontSize: 14,
-          marginBottom: 24,
-        }}
+        className="mb-6 inline-flex cursor-pointer items-center gap-1.5 text-sm text-muted-foreground"
       >
         <ArrowLeft className="size-3" />
         <span>Skills</span>
       </div>
 
       {/* Header */}
-      <div style={{ marginBottom: 8 }}>
-        <h1 style={{ fontSize: 28, fontWeight: 400, color: "#202124", margin: 0, lineHeight: 1.2 }}>{skill.name}</h1>
+      <div className="mb-2">
+        <h1 className="m-0 text-[28px] font-normal leading-tight text-foreground">{skill.name}</h1>
         {skill.description && (
-          <p style={{ fontSize: 14, color: "#5f6368", margin: "8px 0 0 0", lineHeight: 1.6 }}>{skill.description}</p>
+          <p className="mb-0 ml-0 mr-0 mt-2 text-sm leading-relaxed text-muted-foreground">{skill.description}</p>
         )}
       </div>
 
       {/* Tab bar */}
-      <div style={{ borderBottom: "1px solid #dadce0", marginBottom: 28, marginTop: 24 }}>
-        <div style={{ display: "flex", gap: 0 }}>
+      <div className="mb-7 mt-6 border-b border-border">
+        <div className="flex">
           {tabs.map((tab) => (
             <div
               key={tab.key}
               onClick={() => setActiveTab(tab.key)}
-              style={{
-                padding: "12px 20px",
-                fontSize: 14,
-                color: activeTab === tab.key ? "#1a73e8" : "#5f6368",
-                borderBottom: activeTab === tab.key ? "3px solid #1a73e8" : "3px solid transparent",
-                cursor: "pointer",
-                fontWeight: activeTab === tab.key ? 500 : 400,
-                marginBottom: -1,
-              }}
+              className={cn(
+                "-mb-px cursor-pointer border-b-[3px] px-5 py-3 text-sm",
+                activeTab === tab.key
+                  ? "border-info font-medium text-info"
+                  : "border-transparent font-normal text-muted-foreground",
+              )}
             >
               {tab.label}
             </div>
@@ -101,27 +91,23 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
 
       {/* Overview tab */}
       {activeTab === "overview" && (
-        <div style={{ display: "flex", gap: 64 }}>
+        <div className="flex gap-16">
           {/* Left column */}
-          <div style={{ flex: 1, minWidth: 0 }}>
-            <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 4px 0" }}>Skill Details</h2>
-            <p style={{ fontSize: 13, color: "#5f6368", margin: "0 0 16px 0" }}>Metadata registered with this skill</p>
-            <table style={{ width: "100%", borderCollapse: "collapse", fontSize: 14 }}>
+          <div className="min-w-0 flex-1">
+            <h2 className="m-0 mb-1 text-lg font-normal text-foreground">Skill Details</h2>
+            <p className="m-0 mb-4 text-[13px] text-muted-foreground">Metadata registered with this skill</p>
+            <table className="w-full border-collapse text-sm">
               <thead>
-                <tr style={{ borderBottom: "1px solid #dadce0" }}>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500, width: 160 }}>
-                    Property
-                  </th>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500 }}>
-                    {skill.name}
-                  </th>
+                <tr className="border-b border-border">
+                  <th className="w-40 py-3 text-left font-medium text-muted-foreground">Property</th>
+                  <th className="py-3 text-left font-medium text-muted-foreground">{skill.name}</th>
                 </tr>
               </thead>
               <tbody>
                 {detailRows.map((row, i) => (
-                  <tr key={i} style={{ borderBottom: "1px solid #f1f3f4" }}>
-                    <td style={{ padding: "12px 0", color: "#3c4043" }}>{row.property}</td>
-                    <td style={{ padding: "12px 0", color: "#202124" }}>{row.value}</td>
+                  <tr key={i} className="border-b border-border">
+                    <td className="py-3 text-foreground">{row.property}</td>
+                    <td className="py-3 text-foreground">{row.value}</td>
                   </tr>
                 ))}
               </tbody>
@@ -129,38 +115,27 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
           </div>
 
           {/* Right sidebar */}
-          <div style={{ width: 240, flexShrink: 0 }}>
-            <div style={{ marginBottom: 24 }}>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Status</div>
+          <div className="w-60 shrink-0">
+            <div className="mb-6">
+              <div className="mb-1 text-xs text-muted-foreground">Status</div>
               <span
-                style={{
-                  fontSize: 12,
-                  padding: "3px 10px",
-                  borderRadius: 12,
-                  backgroundColor: skill.enabled ? "#e6f4ea" : "#f1f3f4",
-                  color: skill.enabled ? "#137333" : "#5f6368",
-                  fontWeight: 500,
-                }}
+                className={cn(
+                  "rounded-xl px-2.5 py-[3px] text-xs font-medium",
+                  skill.enabled ? "bg-success/10 text-success" : "bg-muted text-muted-foreground",
+                )}
               >
                 {skill.enabled ? "Public" : "Draft"}
               </span>
             </div>
 
             {sourceUrl && (
-              <div style={{ marginBottom: 24 }}>
-                <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Source</div>
+              <div className="mb-6">
+                <div className="mb-1 text-xs text-muted-foreground">Source</div>
                 <a
                   href={sourceUrl}
                   target="_blank"
                   rel="noopener noreferrer"
-                  style={{
-                    fontSize: 13,
-                    color: "#1a73e8",
-                    wordBreak: "break-all",
-                    display: "flex",
-                    alignItems: "center",
-                    gap: 4,
-                  }}
+                  className="flex items-center gap-1 break-all text-[13px] text-info"
                 >
                   {sourceUrl.replace("https://", "")}
                   <Link2 className="size-3 shrink-0" />
@@ -169,20 +144,13 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
             )}
 
             {skill.keywords && skill.keywords.length > 0 && (
-              <div style={{ marginBottom: 24 }}>
-                <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 8 }}>Tags</div>
-                <div style={{ display: "flex", flexWrap: "wrap", gap: 6 }}>
+              <div className="mb-6">
+                <div className="mb-2 text-xs text-muted-foreground">Tags</div>
+                <div className="flex flex-wrap gap-1.5">
                   {skill.keywords.map((kw) => (
                     <span
                       key={kw}
-                      style={{
-                        fontSize: 12,
-                        padding: "4px 12px",
-                        borderRadius: 16,
-                        border: "1px solid #dadce0",
-                        color: "#3c4043",
-                        backgroundColor: "#fff",
-                      }}
+                      className="rounded-2xl border border-border bg-card px-3 py-1 text-xs text-foreground"
                     >
                       {kw}
                     </span>
@@ -192,10 +160,8 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
             )}
 
             <div>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Skill ID</div>
-              <div style={{ fontSize: 12, fontFamily: "monospace", color: "#3c4043", wordBreak: "break-all" }}>
-                {skill.id}
-              </div>
+              <div className="mb-1 text-xs text-muted-foreground">Skill ID</div>
+              <div className="break-all font-mono text-xs text-foreground">{skill.id}</div>
             </div>
           </div>
         </div>
@@ -203,93 +169,43 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
 
       {/* How to Use tab */}
       {activeTab === "usage" && (
-        <div style={{ maxWidth: 640 }}>
-          <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 8px 0" }}>Using this skill</h2>
-          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 24px 0", lineHeight: 1.6 }}>
+        <div className="max-w-[640px]">
+          <h2 className="m-0 mb-2 text-lg font-normal text-foreground">Using this skill</h2>
+          <p className="m-0 mb-6 text-sm leading-relaxed text-muted-foreground">
             Once your proxy is set as a marketplace, enable this skill in Claude Code with one command:
           </p>
 
           {/* Install command */}
-          <div
-            style={{
-              border: "1px solid #dadce0",
-              borderRadius: 8,
-              overflow: "hidden",
-              marginBottom: 24,
-            }}
-          >
-            <div
-              style={{
-                display: "flex",
-                alignItems: "center",
-                justifyContent: "space-between",
-                padding: "10px 16px",
-                backgroundColor: "#f8f9fa",
-                borderBottom: "1px solid #dadce0",
-              }}
-            >
-              <span style={{ fontSize: 13, color: "#3c4043", fontWeight: 500 }}>Run in Claude Code</span>
+          <div className="mb-6 overflow-hidden rounded-lg border border-border">
+            <div className="flex items-center justify-between border-b border-border bg-muted px-4 py-2.5">
+              <span className="text-[13px] font-medium text-foreground">Run in Claude Code</span>
               <button
                 onClick={() => copyToClipboard(installCommand, "install")}
-                style={{
-                  display: "flex",
-                  alignItems: "center",
-                  gap: 4,
-                  fontSize: 12,
-                  color: copiedKey === "install" ? "#137333" : "#1a73e8",
-                  background: "none",
-                  border: "none",
-                  cursor: "pointer",
-                  padding: 0,
-                }}
+                className={cn(
+                  "flex cursor-pointer items-center gap-1 border-none bg-transparent p-0 text-xs",
+                  copiedKey === "install" ? "text-success" : "text-info",
+                )}
               >
                 {copiedKey === "install" ? <Check className="size-3" /> : <Copy className="size-3" />}
                 {copiedKey === "install" ? "Copied" : "Copy"}
               </button>
             </div>
-            <pre
-              style={{
-                margin: 0,
-                padding: "14px 16px",
-                fontSize: 14,
-                fontFamily: "monospace",
-                color: "#202124",
-                backgroundColor: "#fff",
-              }}
-            >
-              {installCommand}
-            </pre>
+            <pre className="m-0 bg-card px-4 py-3.5 font-mono text-sm text-foreground">{installCommand}</pre>
           </div>
 
           {/* Shown when the marketplace catalog is stale and the plugin isn't found yet */}
-          <div
-            style={{
-              border: "1px solid #fce8b2",
-              borderRadius: 8,
-              padding: "12px 16px",
-              backgroundColor: "#fefce8",
-              marginBottom: 16,
-            }}
-          >
-            <p style={{ fontSize: 13, color: "#5f6368", lineHeight: 1.6, margin: "0 0 8px 0" }}>
+          <div className="mb-4 rounded-lg border border-warning/30 bg-warning/10 px-4 py-3">
+            <p className="m-0 mb-2 text-[13px] leading-relaxed text-muted-foreground">
               If you see &quot;Plugin {skill.name} not found in marketplace&quot;, update the catalog first:
             </p>
-            <pre
-              style={{
-                margin: 0,
-                fontSize: 13,
-                fontFamily: "monospace",
-                color: "#202124",
-                backgroundColor: "transparent",
-              }}
-            >
+            <pre className="m-0 bg-transparent font-mono text-[13px] text-foreground">
               /plugin marketplace update litellm
             </pre>
           </div>
 
-          <p style={{ fontSize: 13, color: "#5f6368", lineHeight: 1.6, margin: 0 }}>
+          <p className="m-0 text-[13px] leading-relaxed text-muted-foreground">
             Don&apos;t have the marketplace configured yet?{" "}
-            <span onClick={() => setActiveTab("setup")} style={{ color: "#1a73e8", cursor: "pointer" }}>
+            <span onClick={() => setActiveTab("setup")} className="cursor-pointer text-info">
               See one-time setup →
             </span>
           </p>
@@ -298,126 +214,56 @@ const SkillDetail: React.FC<SkillDetailProps> = ({ skill, onBack }) => {
 
       {/* Setup tab (linked from usage) */}
       {activeTab === "setup" && (
-        <div style={{ maxWidth: 640 }}>
-          <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 8px 0" }}>
-            One-time marketplace setup
-          </h2>
+        <div className="max-w-[640px]">
+          <h2 className="m-0 mb-2 text-lg font-normal text-foreground">One-time marketplace setup</h2>
 
           {/* Option 1: single command — fastest path for most users */}
-          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 12px 0", lineHeight: 1.6 }}>
+          <p className="m-0 mb-3 text-sm leading-relaxed text-muted-foreground">
             Run this command in Claude Code to register the marketplace:
           </p>
-          <div
-            style={{
-              border: "1px solid #dadce0",
-              borderRadius: 8,
-              overflow: "hidden",
-              marginBottom: 24,
-            }}
-          >
-            <div
-              style={{
-                display: "flex",
-                alignItems: "center",
-                justifyContent: "space-between",
-                padding: "10px 16px",
-                backgroundColor: "#f8f9fa",
-                borderBottom: "1px solid #dadce0",
-              }}
-            >
-              <span style={{ fontSize: 13, color: "#3c4043", fontWeight: 500 }}>Run in Claude Code</span>
+          <div className="mb-6 overflow-hidden rounded-lg border border-border">
+            <div className="flex items-center justify-between border-b border-border bg-muted px-4 py-2.5">
+              <span className="text-[13px] font-medium text-foreground">Run in Claude Code</span>
               <button
                 onClick={() => {
                   const origin = typeof window !== "undefined" ? window.location.origin : "";
                   copyToClipboard(`/plugin marketplace add ${origin}/claude-code/marketplace.json`, "marketplace-cmd");
                 }}
-                style={{
-                  display: "flex",
-                  alignItems: "center",
-                  gap: 4,
-                  fontSize: 12,
-                  color: copiedKey === "marketplace-cmd" ? "#137333" : "#1a73e8",
-                  background: "none",
-                  border: "none",
-                  cursor: "pointer",
-                  padding: 0,
-                }}
+                className={cn(
+                  "flex cursor-pointer items-center gap-1 border-none bg-transparent p-0 text-xs",
+                  copiedKey === "marketplace-cmd" ? "text-success" : "text-info",
+                )}
               >
                 {copiedKey === "marketplace-cmd" ? <Check className="size-3" /> : <Copy className="size-3" />}
                 {copiedKey === "marketplace-cmd" ? "Copied" : "Copy"}
               </button>
             </div>
-            <pre
-              style={{
-                margin: 0,
-                padding: "14px 16px",
-                fontSize: 13,
-                fontFamily: "monospace",
-                color: "#202124",
-                backgroundColor: "#fff",
-              }}
-            >
+            <pre className="m-0 bg-card px-4 py-3.5 font-mono text-[13px] text-foreground">
               {`/plugin marketplace add ${typeof window !== "undefined" ? window.location.origin : "<proxy-url>"}/claude-code/marketplace.json`}
             </pre>
           </div>
 
           {/* Option 2: settings.json — for persistent config or managed deployments.
               extraKnownMarketplaces requires source to be a nested object, not a flat string. */}
-          <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 12px 0", lineHeight: 1.6 }}>
-            Or add this to{" "}
-            <code style={{ fontSize: 13, backgroundColor: "#f1f3f4", padding: "1px 6px", borderRadius: 4 }}>
-              ~/.claude/settings.json
-            </code>{" "}
+          <p className="m-0 mb-3 text-sm leading-relaxed text-muted-foreground">
+            Or add this to <code className="rounded bg-muted px-1.5 py-px text-[13px]">~/.claude/settings.json</code>{" "}
             for a persistent configuration:
           </p>
-          <div
-            style={{
-              border: "1px solid #dadce0",
-              borderRadius: 8,
-              overflow: "hidden",
-            }}
-          >
-            <div
-              style={{
-                display: "flex",
-                alignItems: "center",
-                justifyContent: "space-between",
-                padding: "10px 16px",
-                backgroundColor: "#f8f9fa",
-                borderBottom: "1px solid #dadce0",
-              }}
-            >
-              <span style={{ fontSize: 13, color: "#3c4043", fontWeight: 500 }}>~/.claude/settings.json</span>
+          <div className="overflow-hidden rounded-lg border border-border">
+            <div className="flex items-center justify-between border-b border-border bg-muted px-4 py-2.5">
+              <span className="text-[13px] font-medium text-foreground">~/.claude/settings.json</span>
               <button
                 onClick={() => copyToClipboard(settingsSnippet, "settings")}
-                style={{
-                  display: "flex",
-                  alignItems: "center",
-                  gap: 4,
-                  fontSize: 12,
-                  color: copiedKey === "settings" ? "#137333" : "#1a73e8",
-                  background: "none",
-                  border: "none",
-                  cursor: "pointer",
-                  padding: 0,
-                }}
+                className={cn(
+                  "flex cursor-pointer items-center gap-1 border-none bg-transparent p-0 text-xs",
+                  copiedKey === "settings" ? "text-success" : "text-info",
+                )}
               >
                 {copiedKey === "settings" ? <Check className="size-3" /> : <Copy className="size-3" />}
                 {copiedKey === "settings" ? "Copied" : "Copy"}
               </button>
             </div>
-            <pre
-              style={{
-                margin: 0,
-                padding: "14px 16px",
-                fontSize: 13,
-                fontFamily: "monospace",
-                color: "#202124",
-                backgroundColor: "#fff",
-              }}
-            >
-              {settingsSnippet}
-            </pre>
+            <pre className="m-0 bg-card px-4 py-3.5 font-mono text-[13px] text-foreground">{settingsSnippet}</pre>
           </div>
         </div>
       )}
diff --git a/ui/litellm-dashboard/src/components/common_components/KeyLifecycleSettings.test.tsx b/ui/litellm-dashboard/src/components/common_components/KeyLifecycleSettings.test.tsx
index 6e627e3b45c..df21444cbad 100644
--- a/ui/litellm-dashboard/src/components/common_components/KeyLifecycleSettings.test.tsx
+++ b/ui/litellm-dashboard/src/components/common_components/KeyLifecycleSettings.test.tsx
@@ -2,7 +2,7 @@ import React, { useState } from "react";
 import { Controller, useForm } from "react-hook-form";
 import userEvent, { PointerEventsCheckLevel } from "@testing-library/user-event";
 import { describe, expect, it, vi, beforeEach } from "vitest";
-import { fireEvent, renderWithProviders, screen, waitFor } from "../../../tests/test-utils";
+import { chooseSelectOption, fireEvent, renderWithProviders, screen, waitFor } from "../../../tests/test-utils";
 import KeyLifecycleSettings from "./KeyLifecycleSettings";
 
 const CREATE_PLACEHOLDER = "e.g., 30d or leave empty to never expire";
@@ -167,8 +167,7 @@ describe("KeyLifecycleSettings", () => {
       await user.click(screen.getByRole("switch"));
       expect(await screen.findByText("Rotation Interval")).toBeInTheDocument();
 
-      await user.click(screen.getByRole("combobox"));
-      await user.click(await screen.findByText("90 days"));
+      await chooseSelectOption(user, screen.getByRole("combobox"), "90 days");
 
       await waitFor(() => expect(screen.getAllByTitle("90 days").some(isRenderedSelection)).toBe(true));
       expect(screen.getByTestId("rotation-interval-value")).toHaveTextContent("90d");
@@ -181,8 +180,7 @@ describe("KeyLifecycleSettings", () => {
       await user.click(screen.getByRole("switch"));
       expect(await screen.findByText("Rotation Interval")).toBeInTheDocument();
 
-      await user.click(screen.getByRole("combobox"));
-      await user.click(await screen.findByText("Custom interval"));
+      await chooseSelectOption(user, screen.getByRole("combobox"), "Custom interval");
 
       expect(await screen.findByPlaceholderText("e.g., 1s, 5m, 2h, 14d")).toBeInTheDocument();
       expect(screen.getByText("Supported formats: seconds (s), minutes (m), hours (h), days (d)")).toBeInTheDocument();
@@ -196,8 +194,7 @@ describe("KeyLifecycleSettings", () => {
       await user.click(screen.getByRole("switch"));
       expect(await screen.findByText("Rotation Interval")).toBeInTheDocument();
 
-      await user.click(screen.getByRole("combobox"));
-      await user.click(await screen.findByText("Custom interval"));
+      await chooseSelectOption(user, screen.getByRole("combobox"), "Custom interval");
 
       const customInput = await screen.findByPlaceholderText("e.g., 1s, 5m, 2h, 14d");
       fireEvent.change(customInput, { target: { value: "14d" } });
@@ -213,14 +210,12 @@ describe("KeyLifecycleSettings", () => {
       await user.click(screen.getByRole("switch"));
       expect(await screen.findByText("Rotation Interval")).toBeInTheDocument();
 
-      await user.click(screen.getByRole("combobox"));
-      await user.click(await screen.findByText("Custom interval"));
+      await chooseSelectOption(user, screen.getByRole("combobox"), "Custom interval");
       const customInput = await screen.findByPlaceholderText("e.g., 1s, 5m, 2h, 14d");
       fireEvent.change(customInput, { target: { value: "14d" } });
       await waitFor(() => expect(screen.getByTestId("rotation-interval-value")).toHaveTextContent("14d"));
 
-      await user.click(screen.getByRole("combobox"));
-      await user.click(await screen.findByText("7 days"));
+      await chooseSelectOption(user, screen.getByRole("combobox"), "7 days");
 
       await waitFor(() => expect(screen.getByTestId("rotation-interval-value")).toHaveTextContent("7d"));
       expect(screen.queryByPlaceholderText("e.g., 1s, 5m, 2h, 14d")).not.toBeInTheDocument();
diff --git a/ui/litellm-dashboard/src/components/common_components/ModelSelector.test.tsx b/ui/litellm-dashboard/src/components/common_components/ModelSelector.test.tsx
index bd7b56f1817..7a5db4667e9 100644
--- a/ui/litellm-dashboard/src/components/common_components/ModelSelector.test.tsx
+++ b/ui/litellm-dashboard/src/components/common_components/ModelSelector.test.tsx
@@ -2,6 +2,7 @@ import { act, fireEvent, render, screen } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { afterEach, describe, expect, it, vi } from "vitest";
 import ModelSelector from "./ModelSelector";
+import { chooseSelectOption } from "../../../tests/test-utils";
 
 vi.mock("@/components/llm_calls/fetch_models", () => ({
   fetchAvailableModels: vi.fn().mockResolvedValue([]),
@@ -9,8 +10,7 @@ vi.mock("@/components/llm_calls/fetch_models", () => ({
 
 const openCustomModelInput = async () => {
   const user = userEvent.setup();
-  await user.click(screen.getByRole("combobox"));
-  await user.click(await screen.findByText("Enter custom model"));
+  await chooseSelectOption(user, screen.getByRole("combobox"), "Enter custom model");
   return screen.getByPlaceholderText("Enter custom model name");
 };
 
diff --git a/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx b/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
new file mode 100644
index 00000000000..01b8a12d99c
--- /dev/null
+++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
@@ -0,0 +1,48 @@
+import { render, screen } from "@testing-library/react";
+import userEvent from "@testing-library/user-event";
+import { describe, expect, it, vi } from "vitest";
+
+import { chooseSelectOption } from "../../../tests/test-utils";
+import type { Team } from "../key_team_helpers/key_list";
+import TeamDropdown from "./team_dropdown";
+
+const TEAMS = [
+  { team_id: "team-1", team_alias: "Alpha Team" },
+  { team_id: "team-2", team_alias: "Beta Team" },
+] as unknown as Team[];
+
+vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({
+  useInfiniteTeams: () => ({
+    data: { pages: [{ teams: TEAMS }] },
+    fetchNextPage: vi.fn(),
+    hasNextPage: false,
+    isFetchingNextPage: false,
+    isLoading: false,
+  }),
+}));
+
+describe("TeamDropdown", () => {
+  it("emits the picked team's id and full object", async () => {
+    const user = userEvent.setup();
+    const onChange = vi.fn();
+    const onTeamSelect = vi.fn();
+    render(<TeamDropdown onChange={onChange} onTeamSelect={onTeamSelect} />);
+
+    await chooseSelectOption(user, screen.getByRole("combobox"), /^Beta Team/);
+
+    expect(onChange).toHaveBeenCalledWith("team-2");
+    expect(onTeamSelect).toHaveBeenCalledWith(TEAMS[1]);
+  });
+
+  it("emits null, never the empty string, when the selection is cleared", async () => {
+    const user = userEvent.setup();
+    const onChange = vi.fn();
+    const onTeamSelect = vi.fn();
+    render(<TeamDropdown value="team-1" onChange={onChange} onTeamSelect={onTeamSelect} />);
+
+    await user.click(screen.getByRole("button", { name: "Clear" }));
+
+    expect(onChange).toHaveBeenCalledWith(null);
+    expect(onTeamSelect).toHaveBeenCalledWith(null);
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
index 35121f41598..7d385c2a3f7 100644
--- a/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
+++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.tsx
@@ -5,7 +5,7 @@ import { Team } from "../key_team_helpers/key_list";
 
 interface TeamDropdownProps {
   value?: string;
-  onChange?: (value: string) => void;
+  onChange?: (value: string | null) => void;
   /** Callback with the full Team object (or null on clear). */
   onTeamSelect?: (team: Team | null) => void;
   disabled?: boolean;
@@ -47,7 +47,7 @@ const TeamDropdown: React.FC<TeamDropdownProps> = ({
   }, [data]);
 
   const handleChange = (teamId: string) => {
-    onChange?.(teamId);
+    onChange?.(teamId || null);
     if (onTeamSelect) {
       onTeamSelect(teamId ? teams.find((t) => t.team_id === teamId) ?? null : null);
     }
diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts b/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts
index a7bd4b8eab4..fae6744d3ac 100644
--- a/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts
+++ b/ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts
@@ -257,6 +257,33 @@ describe("buildUpdatedComplexityRouterConfig session affinity", () => {
   });
 });
 
+describe("buildUpdatedComplexityRouterConfig classification mode", () => {
+  it("round-trips a stored user_turn through hydrate then save", () => {
+    const stored = { ...STORED, classification_mode: "user_turn" };
+    const hydrated = hydrateComplexityRouterConfig(stored, undefined);
+
+    expect(hydrated.classification_mode).toBe("user_turn");
+    expect(buildUpdatedComplexityRouterConfig(stored, hydrated).classification_mode).toBe("user_turn");
+  });
+
+  it("round-trips an explicitly stored every_request, so an untouched save leaves it as written", () => {
+    const stored = { ...STORED, classification_mode: "every_request" };
+    const hydrated = hydrateComplexityRouterConfig(stored, undefined);
+
+    expect(hydrated.classification_mode).toBe("every_request");
+    expect(buildUpdatedComplexityRouterConfig(stored, hydrated).classification_mode).toBe("every_request");
+  });
+
+  it("rewrites a stored user_turn to every_request once the operator picks the default back", () => {
+    const stored = { ...STORED, classification_mode: "user_turn" };
+    const result = buildUpdatedComplexityRouterConfig(stored, {
+      ...FORM_VALUE,
+      classification_mode: "every_request",
+    });
+    expect(result.classification_mode).toBe("every_request");
+  });
+});
+
 describe("buildUpdatedComplexityRouterConfig deployment affinity", () => {
   it("writes deployment_affinity=false when the toggle is off", () => {
     const result = buildUpdatedComplexityRouterConfig(STORED, { ...FORM_VALUE, deployment_affinity: false });
@@ -476,6 +503,7 @@ describe("managed keys survive an untouched open-and-save", () => {
     classifier_context_budget_chars: 4000,
     classifier_context_include_assistant_turns: true,
     classifier_fallback: "default_model",
+    classification_mode: "user_turn",
     session_affinity: true,
     deployment_affinity: false,
     adaptive: true,
@@ -487,19 +515,26 @@ describe("managed keys survive an untouched open-and-save", () => {
     token_thresholds: { simple: 20, complex: 500 },
     dimension_weights: { tokenCount: 0.1 },
     reasoning_override_min_score: 0.3,
+    enable_context_window_escalation: false,
+    context_window_escalation_buffer: 0.9,
   };
 
   // tier_definitions, fallback_tier and classification_prompt cannot sit beside heuristic_first, which
-  // this fixture uses, so no single stored config can hold every managed key. They get their own round
-  // trip below.
-  const CUSTOM_TIER_ONLY_KEYS = new Set(["tier_definitions", "fallback_tier", "classification_prompt"]);
+  // this fixture uses, and hybrid_boundary_margin belongs to the sibling hybrid type, so no single
+  // stored config can hold every managed key. Each gets its own round trip below.
+  const KEYS_ANOTHER_CLASSIFIER_TYPE_OWNS = new Set([
+    "tier_definitions",
+    "fallback_tier",
+    "classification_prompt",
+    "hybrid_boundary_margin",
+  ]);
 
   it("carries every managed key a built-in router can hold through hydrate then save", () => {
     const hydrated = hydrateComplexityRouterConfig(STORED_ALL_MANAGED, undefined);
     const saved = buildUpdatedComplexityRouterConfig(STORED_ALL_MANAGED, hydrated);
 
     const dropped = [...MANAGED_COMPLEXITY_ROUTER_KEYS]
-      .filter((key) => !CUSTOM_TIER_ONLY_KEYS.has(key))
+      .filter((key) => !KEYS_ANOTHER_CLASSIFIER_TYPE_OWNS.has(key))
       .filter((key) => saved[key] === undefined);
     expect(dropped).toEqual([]);
   });
@@ -553,6 +588,18 @@ describe("managed keys survive an untouched open-and-save", () => {
     );
   });
 
+  it("round-trips a hybrid router's margin, which save requires and the backend rejects without", () => {
+    const storedHybrid: Record<string, unknown> = {
+      ...STORED_ALL_MANAGED,
+      classifier_type: "hybrid",
+      hybrid_boundary_margin: 0.05,
+    };
+    delete storedHybrid.heuristic_first_max_tier;
+    const hydrated = hydrateComplexityRouterConfig(storedHybrid, undefined);
+    expect(hydrated.hybrid_boundary_margin).toBe(0.05);
+    expect(buildUpdatedComplexityRouterConfig(storedHybrid, hydrated).hybrid_boundary_margin).toBe(0.05);
+  });
+
   it("round-trips the heuristic_first threshold, which save requires and the backend rejects without", () => {
     const hydrated = hydrateComplexityRouterConfig(STORED_ALL_MANAGED, undefined);
     expect(hydrated.heuristic_first_max_tier).toBe("SIMPLE");
diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts
index 027e01a9351..481ba2b6b00 100644
--- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts
+++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.ts
@@ -1,4 +1,4 @@
-import { buildUpdatedComplexityRouterConfig } from "./edit_auto_router_modal";
+import { buildUpdatedComplexityRouterConfig, hydrateComplexityRouterConfig } from "./edit_auto_router_modal";
 
 const storedConfigValue = {
   tiers: {
@@ -47,8 +47,10 @@ const expectedClassifiedTierConfig = {
   semantic_keyword_matching: true,
   embedding_model: "voyage-4-large",
   match_threshold: 0.65,
+  classification_mode: "every_request",
   session_affinity: false,
   deployment_affinity: true,
+  modality_routing: false,
   adaptive: true,
   adaptive_weights: { quality: 0.4, cost: 0.6 },
   adaptive_eligible: "classified_tier",
@@ -68,8 +70,10 @@ const expectedAdaptiveDisabledConfig = {
   semantic_keyword_matching: true,
   embedding_model: "voyage-4-large",
   match_threshold: 0.65,
+  classification_mode: "every_request",
   session_affinity: false,
   deployment_affinity: true,
+  modality_routing: false,
 };
 
 describe("buildUpdatedComplexityRouterConfig", () => {
@@ -85,6 +89,26 @@ describe("buildUpdatedComplexityRouterConfig", () => {
     expect(updatedConfig).toEqual(expectedAdaptiveDisabledConfig);
   });
 
+  it("hydrates a stored modality_routing into form state and defaults absent to off", () => {
+    expect(hydrateComplexityRouterConfig({ ...storedConfig, modality_routing: true }, null).modality_routing).toBe(
+      true,
+    );
+    expect(hydrateComplexityRouterConfig(storedConfig, null).modality_routing).toBe(false);
+  });
+
+  it("round-trips modality_routing explicitly in both directions", () => {
+    const enabled = buildUpdatedComplexityRouterConfig(storedConfig, {
+      ...classifiedTierValue,
+      modality_routing: true,
+    });
+    expect(enabled.modality_routing).toBe(true);
+    const disabled = buildUpdatedComplexityRouterConfig(
+      { ...storedConfig, modality_routing: true },
+      { ...classifiedTierValue, modality_routing: false },
+    );
+    expect(disabled.modality_routing).toBe(false);
+  });
+
   it("includes return_raw_model_name only when enabled", () => {
     const updatedConfig = buildUpdatedComplexityRouterConfig(storedConfig, {
       ...classifiedTierValue,
diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx
index a4921fcfcb5..96e8549eac8 100644
--- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx
+++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.test.tsx
@@ -364,7 +364,7 @@ describe("EditAutoRouterModal assistant turns", () => {
   });
 });
 
-describe("EditAutoRouterModal session affinity", () => {
+describe("EditAutoRouterModal classification frequency", () => {
   beforeEach(() => {
     modelPatchUpdateCall.mockClear();
   });
@@ -381,15 +381,15 @@ describe("EditAutoRouterModal session affinity", () => {
       />,
     );
 
-  // A stored config with no session_affinity key now runs with affinity OFF, because the backend
-  // field defaults to False. The toggle has to render what the router actually does, and an
-  // untouched save must not flip it.
-  it("shows a stored config with no session_affinity key as off", async () => {
+  // A stored config with neither key now runs with affinity OFF, because both backend fields
+  // default that way. The picker has to render what the router actually does, and an untouched
+  // save must not flip it.
+  it("shows a stored config with neither key as every request", async () => {
     const user = userEvent.setup();
     renderWithStoredConfig(STORED_CONFIG);
 
-    await user.click(await screen.findByText("Advanced: Affinity"));
-    expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).not.toBeChecked();
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    expect(await screen.findByRole("radio", { name: /Every request/ })).toBeChecked();
 
     await user.click(screen.getByRole("button", { name: /save changes/i }));
 
@@ -397,12 +397,12 @@ describe("EditAutoRouterModal session affinity", () => {
     expect(savedConfig().session_affinity).toBe(false);
   });
 
-  it("shows a stored session_affinity=true as on and preserves it through an untouched save", async () => {
+  it("shows a stored session_affinity=true as once per session and preserves it through an untouched save", async () => {
     const user = userEvent.setup();
     renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true });
 
-    await user.click(await screen.findByText("Advanced: Affinity"));
-    expect(await screen.findByRole("switch", { name: "Pin a session to its first model" })).toBeChecked();
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    expect(await screen.findByRole("radio", { name: /Once per session/ })).toBeChecked();
 
     await user.click(screen.getByRole("button", { name: /save changes/i }));
 
@@ -410,12 +410,12 @@ describe("EditAutoRouterModal session affinity", () => {
     expect(savedConfig().session_affinity).toBe(true);
   });
 
-  it("persists turning session affinity on", async () => {
+  it("persists picking once per session", async () => {
     const user = userEvent.setup();
     renderWithStoredConfig(STORED_CONFIG);
 
-    await user.click(await screen.findByText("Advanced: Affinity"));
-    await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" }));
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Once per session/ }));
 
     await user.click(screen.getByRole("button", { name: /save changes/i }));
 
@@ -423,18 +423,71 @@ describe("EditAutoRouterModal session affinity", () => {
     expect(savedConfig().session_affinity).toBe(true);
   });
 
-  it("persists turning session affinity back off", async () => {
+  it("persists picking every request back over a stored session pin", async () => {
     const user = userEvent.setup();
     renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true });
 
-    await user.click(await screen.findByText("Advanced: Affinity"));
-    await user.click(await screen.findByRole("switch", { name: "Pin a session to its first model" }));
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Every request/ }));
 
     await user.click(screen.getByRole("button", { name: /save changes/i }));
 
     await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled());
     expect(savedConfig().session_affinity).toBe(false);
   });
+
+  it("clears a stored session pin when the operator moves to every new user message", async () => {
+    const user = userEvent.setup();
+    renderWithStoredConfig({ ...STORED_CONFIG, session_affinity: true });
+
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Every new user message/ }));
+
+    await user.click(screen.getByRole("button", { name: /save changes/i }));
+
+    await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled());
+    expect(savedConfig().session_affinity).toBe(false);
+    expect(savedConfig().classification_mode).toBe("user_turn");
+  });
+
+  it("shows a stored user_turn as selected and preserves it through an untouched save", async () => {
+    const user = userEvent.setup();
+    renderWithStoredConfig({ ...STORED_CONFIG, classification_mode: "user_turn" });
+
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    expect(await screen.findByRole("radio", { name: /Every new user message/ })).toBeChecked();
+
+    await user.click(screen.getByRole("button", { name: /save changes/i }));
+
+    await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled());
+    expect(savedConfig().classification_mode).toBe("user_turn");
+  });
+
+  it("persists switching a stored config to every new user message", async () => {
+    const user = userEvent.setup();
+    renderWithStoredConfig(STORED_CONFIG);
+
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Every new user message/ }));
+
+    await user.click(screen.getByRole("button", { name: /save changes/i }));
+
+    await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled());
+    expect(savedConfig().classification_mode).toBe("user_turn");
+  });
+
+  it("rewrites the stored mode to every_request when the operator picks it back", async () => {
+    const user = userEvent.setup();
+    renderWithStoredConfig({ ...STORED_CONFIG, classification_mode: "user_turn" });
+
+    await user.click(await screen.findByText("Advanced: Classification Method"));
+    await user.click(await screen.findByRole("radio", { name: /Every request/ }));
+
+    await user.click(screen.getByRole("button", { name: /save changes/i }));
+
+    await waitFor(() => expect(modelPatchUpdateCall).toHaveBeenCalled());
+    expect(savedConfig().classification_mode).toBe("every_request");
+  });
 });
 
 describe("EditAutoRouterModal deployment affinity", () => {
diff --git a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx
index 425d5d51f06..7aa5f4beb1f 100644
--- a/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx
+++ b/ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx
@@ -89,6 +89,7 @@ export interface StoredComplexityRouterConfig {
   plan_mode_min_tier?: unknown;
   classification_prompt?: unknown;
   heuristic_first_max_tier?: unknown;
+  hybrid_boundary_margin?: unknown;
   tier_labels?: unknown;
   classifier_type?: ClassifierType;
   classifier_llm_config?: ClassifierLLMConfig;
@@ -96,17 +97,21 @@ export interface StoredComplexityRouterConfig {
   classifier_context_budget_chars?: unknown;
   classifier_context_include_assistant_turns?: unknown;
   classifier_fallback?: unknown;
+  classification_mode?: unknown;
   tier_boundaries?: unknown;
   token_thresholds?: unknown;
   dimension_weights?: unknown;
   reasoning_override_min_score?: unknown;
   session_affinity?: unknown;
+  modality_routing?: unknown;
   deployment_affinity?: unknown;
   adaptive?: boolean;
   adaptive_weights?: AdaptiveRouterWeights;
   tier_distance_penalty?: number;
   adaptive_eligible?: AdaptiveEligible;
   return_raw_model_name?: boolean;
+  enable_context_window_escalation?: unknown;
+  context_window_escalation_buffer?: unknown;
 }
 
 /**
@@ -163,12 +168,19 @@ export const hydrateComplexityRouterConfig = (
       typeof parsedConfig.heuristic_first_max_tier === "string" && parsedConfig.heuristic_first_max_tier.trim() !== ""
         ? parsedConfig.heuristic_first_max_tier
         : undefined,
+    hybrid_boundary_margin:
+      typeof parsedConfig.hybrid_boundary_margin === "number" ? parsedConfig.hybrid_boundary_margin : undefined,
+    classification_mode:
+      parsedConfig.classification_mode === "user_turn" || parsedConfig.classification_mode === "every_request"
+        ? parsedConfig.classification_mode
+        : undefined,
     tier_boundaries: hydrateTierBoundaries(parsedConfig.tier_boundaries),
     token_thresholds: hydrateTokenThresholds(parsedConfig.token_thresholds),
     dimension_weights: hydrateDimensionWeights(parsedConfig.dimension_weights),
     reasoning_override_min_score: hydrateReasoningOverrideMinScore(parsedConfig.reasoning_override_min_score),
     session_affinity:
       typeof parsedConfig.session_affinity === "boolean" ? parsedConfig.session_affinity : DEFAULT_SESSION_AFFINITY,
+    modality_routing: typeof parsedConfig.modality_routing === "boolean" ? parsedConfig.modality_routing : false,
     deployment_affinity:
       typeof parsedConfig.deployment_affinity === "boolean"
         ? parsedConfig.deployment_affinity
@@ -178,6 +190,14 @@ export const hydrateComplexityRouterConfig = (
     tier_distance_penalty: parsedConfig.tier_distance_penalty,
     adaptive_eligible: parsedConfig.adaptive_eligible || "all",
     return_raw_model_name: parsedConfig.return_raw_model_name || false,
+    enable_context_window_escalation:
+      typeof parsedConfig.enable_context_window_escalation === "boolean"
+        ? parsedConfig.enable_context_window_escalation
+        : undefined,
+    context_window_escalation_buffer:
+      typeof parsedConfig.context_window_escalation_buffer === "number"
+        ? parsedConfig.context_window_escalation_buffer
+        : undefined,
   };
 };
 
@@ -197,7 +217,10 @@ export const MANAGED_COMPLEXITY_ROUTER_KEYS = new Set([
   "classifier_fallback",
   "classification_prompt",
   "heuristic_first_max_tier",
+  "hybrid_boundary_margin",
+  "classification_mode",
   "session_affinity",
+  "modality_routing",
   "deployment_affinity",
   "adaptive",
   "adaptive_weights",
@@ -208,6 +231,8 @@ export const MANAGED_COMPLEXITY_ROUTER_KEYS = new Set([
   "token_thresholds",
   "dimension_weights",
   "reasoning_override_min_score",
+  "enable_context_window_escalation",
+  "context_window_escalation_buffer",
 ]);
 
 // Managed only when the caller passes the corresponding state. A caller that does not render
@@ -282,6 +307,8 @@ export const buildUpdatedComplexityRouterConfig = (
     planModeMinTier: value.plan_mode_min_tier,
     classificationPrompt: value.classification_prompt,
     heuristicFirstMaxTier: value.heuristic_first_max_tier,
+    hybridBoundaryMargin: value.hybrid_boundary_margin,
+    classificationMode: value.classification_mode,
     tierLabels: value.tier_labels,
     classifierType: value.classifier_type,
     classifierLlmConfig: value.classifier_llm_config,
@@ -290,6 +317,7 @@ export const buildUpdatedComplexityRouterConfig = (
     classifierContextIncludeAssistantTurns: value.classifier_context_include_assistant_turns,
     classifierFallback: value.classifier_fallback,
     sessionAffinity: value.session_affinity ?? DEFAULT_SESSION_AFFINITY,
+    modalityRouting: value.modality_routing ?? false,
     deploymentAffinity: value.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY,
     customTechnicalKeywords: customTechnicalKeywords ?? [],
     keywordTierRules: keywordMatching?.keywordTierRules ?? [],
@@ -307,6 +335,8 @@ export const buildUpdatedComplexityRouterConfig = (
     dimensionWeights: value.dimension_weights,
     reasoningOverrideMinScore: value.reasoning_override_min_score,
     tierModelParams: value.tier_model_params,
+    enableContextWindowEscalation: value.enable_context_window_escalation,
+    contextWindowEscalationBuffer: value.context_window_escalation_buffer,
   };
   const built = buildComplexityRouterConfig(builderParams);
 
diff --git a/ui/litellm-dashboard/src/components/leftnav.test.tsx b/ui/litellm-dashboard/src/components/leftnav.test.tsx
index b0bb0e8a5b5..c3e1f924d09 100644
--- a/ui/litellm-dashboard/src/components/leftnav.test.tsx
+++ b/ui/litellm-dashboard/src/components/leftnav.test.tsx
@@ -213,6 +213,20 @@ describe("Sidebar (leftnav)", () => {
       expect(screen.getByText("Search Tools")).toBeInTheDocument();
     });
   });
+  it("reports whether a nested tab is expanded", async () => {
+    renderWithProviders(<Sidebar {...defaultProps} />);
+
+    const toggle = screen.getByText("Tools").closest("button")!;
+    expect(toggle).toHaveAttribute("aria-expanded", "false");
+
+    act(() => {
+      fireEvent.click(toggle);
+    });
+    await waitFor(() => {
+      expect(toggle).toHaveAttribute("aria-expanded", "true");
+    });
+  });
+
   it("keeps Router Settings as a single Settings child", () => {
     // Router Settings is admin-only, so getAvailablePages() filters it out entirely and the
     // page_utils duplicate-key guard cannot see it. Walk menuGroups directly, otherwise a
diff --git a/ui/litellm-dashboard/src/components/leftnav.tsx b/ui/litellm-dashboard/src/components/leftnav.tsx
index 42389facac2..51ba36348e1 100644
--- a/ui/litellm-dashboard/src/components/leftnav.tsx
+++ b/ui/litellm-dashboard/src/components/leftnav.tsx
@@ -570,6 +570,7 @@ const Sidebar_: React.FC<SidebarProps> = ({
       <SidebarMenuItem key={item.key}>
         <SidebarMenuButton
           isActive={active}
+          aria-expanded={open}
           onClick={() => toggleGroup(item.key)}
           title={collapsed ? labelText(item) : undefined}
         >
diff --git a/ui/litellm-dashboard/src/components/model_filters.tsx b/ui/litellm-dashboard/src/components/model_filters.tsx
index 96041905d97..0ce82d6d050 100644
--- a/ui/litellm-dashboard/src/components/model_filters.tsx
+++ b/ui/litellm-dashboard/src/components/model_filters.tsx
@@ -1,5 +1,6 @@
 import React, { useState, useEffect, useMemo, useRef } from "react";
 import { Card } from "@/components/ui/card";
+import { matchesSearchTerm } from "@/utils/searchUtils";
 
 interface ModelGroupInfo {
   model_group: string;
@@ -76,7 +77,7 @@ const ModelFilters: React.FC<ModelFiltersProps> = ({
   const filteredData = useMemo(() => {
     return (
       modelHubData?.filter((model) => {
-        const matchesSearch = model.model_group.toLowerCase().includes(searchTerm.toLowerCase());
+        const matchesSearch = matchesSearchTerm(searchTerm, [model.model_group]);
         const matchesProvider = selectedProvider === "" || model.providers.includes(selectedProvider);
         const matchesMode = selectedMode === "" || model.mode === selectedMode;
 
diff --git a/ui/litellm-dashboard/src/components/model_info_view.test.tsx b/ui/litellm-dashboard/src/components/model_info_view.test.tsx
index 742d2593ade..768183907db 100644
--- a/ui/litellm-dashboard/src/components/model_info_view.test.tsx
+++ b/ui/litellm-dashboard/src/components/model_info_view.test.tsx
@@ -87,6 +87,7 @@ describe("ModelInfoView", () => {
     accessToken: "test-token",
     userID: "123",
     userRole: "Admin",
+    isViewOnly: false,
     onModelUpdate: vi.fn(),
     modelAccessGroups: ["group1", "group2"],
   };
@@ -328,6 +329,16 @@ describe("ModelInfoView", () => {
     });
   });
 
+  // A proxy_admin_viewer session reads "Admin" through effectiveSessionRole, but the update
+  // and delete endpoints 403 it, so the write buttons must not be offered.
+  it("should disable delete and update buttons for a view-only admin session", async () => {
+    render(<ModelInfoView {...DEFAULT_ADMIN_PROPS} isViewOnly={true} />, { wrapper });
+    await waitFor(() => {
+      expect(screen.getByTestId("delete-model-button")).toBeDisabled();
+    });
+    expect(screen.getByTestId("update-api-key-button")).toBeDisabled();
+  });
+
   it("should disable delete button when model is not a DB model", async () => {
     const nonDbModelData = {
       ...defaultModelData,
diff --git a/ui/litellm-dashboard/src/components/model_info_view.tsx b/ui/litellm-dashboard/src/components/model_info_view.tsx
index f21e98e084c..35afcdb2985 100644
--- a/ui/litellm-dashboard/src/components/model_info_view.tsx
+++ b/ui/litellm-dashboard/src/components/model_info_view.tsx
@@ -53,6 +53,7 @@ interface ModelInfoViewProps {
   accessToken: string | null;
   userID: string | null;
   userRole: string | null;
+  isViewOnly: boolean;
   onModelUpdate?: (updatedModel: any) => void;
   modelAccessGroups: string[] | null;
 }
@@ -117,6 +118,7 @@ export default function ModelInfoView({
   accessToken,
   userID,
   userRole,
+  isViewOnly,
   onModelUpdate,
   modelAccessGroups,
 }: ModelInfoViewProps) {
@@ -167,7 +169,7 @@ export default function ModelInfoView({
   // Keep modelData variable name for backwards compatibility
   const modelData = transformedModelData;
 
-  const canEditModel = canModifyModel({ userRole, userID }, teams ?? null, {
+  const canEditModel = canModifyModel({ userRole, userID, isViewOnly }, teams ?? null, {
     teamId: modelData?.model_info?.team_id,
     isDbModel: modelData?.model_info?.db_model === true,
   });
diff --git a/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx b/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx
index bad92555bd5..3fc1d41dfdd 100644
--- a/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx
+++ b/ui/litellm-dashboard/src/components/molecules/cost_optimization_feedback_banner.test.tsx
@@ -1,4 +1,4 @@
-import { fireEvent, render } from "@testing-library/react";
+import { fireEvent, render, screen } from "@testing-library/react";
 import { beforeEach, describe, expect, it } from "vitest";
 import CostOptimizationFeedbackBanner from "./cost_optimization_feedback_banner";
 
@@ -10,24 +10,24 @@ describe("CostOptimizationFeedbackBanner", () => {
   });
 
   it("renders with a link to the feedback discussion", () => {
-    const { getByText } = render(<CostOptimizationFeedbackBanner />);
-    const link = getByText("Share Feedback").closest("a");
+    render(<CostOptimizationFeedbackBanner />);
+    const link = screen.getByText("Share Feedback").closest("a");
     expect(link).toHaveAttribute("href", "https://github.com/BerriAI/litellm/discussions/32172");
   });
 
   it("hides itself and persists the dismissal when the dismiss button is clicked", () => {
-    const { getByText, queryByText, getByLabelText } = render(<CostOptimizationFeedbackBanner />);
-    expect(getByText("Help shape cost optimization")).toBeInTheDocument();
+    render(<CostOptimizationFeedbackBanner />);
+    expect(screen.getByText("Help shape cost optimization")).toBeInTheDocument();
 
-    fireEvent.click(getByLabelText("Dismiss banner"));
+    fireEvent.click(screen.getByLabelText("Dismiss banner"));
 
-    expect(queryByText("Help shape cost optimization")).not.toBeInTheDocument();
+    expect(screen.queryByText("Help shape cost optimization")).not.toBeInTheDocument();
     expect(localStorage.getItem(STORAGE_KEY)).toBe("true");
   });
 
   it("stays dismissed on remount once persisted", () => {
     localStorage.setItem(STORAGE_KEY, "true");
-    const { queryByText } = render(<CostOptimizationFeedbackBanner />);
-    expect(queryByText("Help shape cost optimization")).not.toBeInTheDocument();
+    render(<CostOptimizationFeedbackBanner />);
+    expect(screen.queryByText("Help shape cost optimization")).not.toBeInTheDocument();
   });
 });
diff --git a/ui/litellm-dashboard/src/components/networking.tsx b/ui/litellm-dashboard/src/components/networking.tsx
index b53a67f9bcc..db7baf5e171 100644
--- a/ui/litellm-dashboard/src/components/networking.tsx
+++ b/ui/litellm-dashboard/src/components/networking.tsx
@@ -310,6 +310,8 @@ export interface AgentCredentialFieldMetadata {
   options?: string[] | null;
   default_value?: string | null;
   include_in_litellm_params?: boolean;
+  validation_pattern?: string | null;
+  validation_message?: string | null;
 }
 
 export interface AgentCreateInfo {
@@ -6970,7 +6972,7 @@ export const vectorStoreSearchCall = async (
     if (!response.ok) {
       const errorData = await response.text();
       await handleError(errorData);
-      return null;
+      throw new Error(errorData);
     }
 
     const data = await response.json();
diff --git a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
index b8d8e3ba9c8..700d19eb13c 100644
--- a/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
+++ b/ui/litellm-dashboard/src/components/organization/organization_view.test.tsx
@@ -108,7 +108,7 @@ beforeEach(() => {
 test("renders organization view after loading data", async () => {
   mockUseOrganization.mockReturnValue({ data: mockOrg, isLoading: false } as any);
 
-  const { findAllByText } = renderWithProviders(
+  renderWithProviders(
     <OrganizationInfoView
       organizationId="org_123"
       onClose={() => {}}
@@ -120,7 +120,7 @@ test("renders organization view after loading data", async () => {
     />,
   );
 
-  const [orgName] = await findAllByText("Acme Corp");
+  const [orgName] = await screen.findAllByText("Acme Corp");
   expect(orgName).toBeInTheDocument();
 });
 
diff --git a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
index c97bb8ede3d..d01a6a34cbe 100644
--- a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
+++ b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
@@ -20,6 +20,7 @@ import falAiLogo from "../../public/assets/logos/fal_ai.jpg";
 import featherlessLogo from "../../public/assets/logos/featherless.svg";
 import fireworksLogo from "../../public/assets/logos/fireworks.svg";
 import friendliLogo from "../../public/assets/logos/friendli.svg";
+import gigachatLogo from "../../public/assets/logos/gigachat.svg";
 import githubCopilotLogo from "../../public/assets/logos/github_copilot.svg";
 import googleLogo from "../../public/assets/logos/google.svg";
 import groqLogo from "../../public/assets/logos/groq.svg";
@@ -107,6 +108,7 @@ export enum Providers {
   FireworksAI = "Fireworks AI",
   FRIENDLIAI = "Friendliai",
   GALADRIEL = "Galadriel",
+  GIGACHAT = "GigaChat",
   GITHUB_COPILOT = "Github Copilot",
   Google_AI_Studio = "Google AI Studio",
   GradientAI = "GradientAI",
@@ -148,6 +150,8 @@ export enum Providers {
   PETALS = "Petals",
   PG_VECTOR = "Pg Vector",
   PREDIBASE = "Predibase",
+  Qwen_AI_Platform = "Qwen AI Platform",
+  QwenCloud = "QwenCloud",
   RECRAFT = "Recraft",
   REPLICATE = "Replicate",
   RunwayML = "RunwayML",
@@ -218,6 +222,7 @@ export const provider_map: Record<string, string> = {
   FireworksAI: "fireworks_ai",
   FRIENDLIAI: "friendliai",
   GALADRIEL: "galadriel",
+  GIGACHAT: "gigachat",
   GITHUB_COPILOT: "github_copilot",
   Google_AI_Studio: "gemini",
   GradientAI: "gradient_ai",
@@ -259,6 +264,8 @@ export const provider_map: Record<string, string> = {
   PETALS: "petals",
   PG_VECTOR: "pg_vector",
   PREDIBASE: "predibase",
+  Qwen_AI_Platform: "qwen_ai_platform",
+  QwenCloud: "qwencloud",
   RECRAFT: "recraft",
   REPLICATE: "replicate",
   RunwayML: "runwayml",
@@ -323,6 +330,7 @@ export const providerLogoMap: Partial<Record<Providers, string>> = {
   [Providers.FEATHERLESS_AI]: featherlessLogo.src,
   [Providers.FireworksAI]: fireworksLogo.src,
   [Providers.FRIENDLIAI]: friendliLogo.src,
+  [Providers.GIGACHAT]: gigachatLogo.src,
   [Providers.GITHUB_COPILOT]: githubCopilotLogo.src,
   [Providers.Google_AI_Studio]: googleLogo.src,
   [Providers.Groq]: groqLogo.src,
@@ -353,6 +361,8 @@ export const providerLogoMap: Partial<Record<Providers, string>> = {
   [Providers.Openrouter]: openrouterLogo.src,
   [Providers.Oracle]: oracleLogo.src,
   [Providers.Perplexity]: perplexityAiLogo.src,
+  [Providers.Qwen_AI_Platform]: qwenLogo.src,
+  [Providers.QwenCloud]: qwenLogo.src,
   [Providers.RECRAFT]: recraftLogo.src,
   [Providers.REPLICATE]: replicateLogo.src,
   [Providers.RunwayML]: runwayLogo.src,
diff --git a/ui/litellm-dashboard/src/components/public_model_hub.test.tsx b/ui/litellm-dashboard/src/components/public_model_hub.test.tsx
index 875f89b5adc..fec46e98077 100644
--- a/ui/litellm-dashboard/src/components/public_model_hub.test.tsx
+++ b/ui/litellm-dashboard/src/components/public_model_hub.test.tsx
@@ -134,6 +134,27 @@ describe("PublicModelHub", () => {
       expect(within(gpt35Row as HTMLElement).getByText("Unknown")).toBeInTheDocument();
     });
   });
+  it("shows no models when the search has no matches (LIT-5230 regression)", async () => {
+    const networkingModule = await import("./networking");
+    vi.mocked(networkingModule.modelHubPublicModelsCall).mockResolvedValue([
+      { model_group: "gpt-4", providers: ["openai"], mode: "chat" },
+      { model_group: "claude-3", providers: ["anthropic"], mode: "chat" },
+    ]);
+
+    render(<PublicModelHub />);
+    expect(await screen.findByText("gpt-4")).toBeInTheDocument();
+
+    fireEvent.change(screen.getByPlaceholderText("Search model names... (smart search enabled)"), {
+      target: { value: "zzzz" },
+    });
+
+    await waitFor(() => {
+      expect(screen.queryByText("gpt-4")).not.toBeInTheDocument();
+      expect(screen.queryByText("claude-3")).not.toBeInTheDocument();
+      expect(screen.getByText("No matching models")).toBeInTheDocument();
+    });
+  });
+
   it("handles non-array response gracefully (regression test for e.filter crash)", async () => {
     const networkingModule = await import("./networking");
     // Mock the API to return an object (like an error response) instead of an array
diff --git a/ui/litellm-dashboard/src/components/public_model_hub.tsx b/ui/litellm-dashboard/src/components/public_model_hub.tsx
index 171b7992325..f6364b5d9d1 100644
--- a/ui/litellm-dashboard/src/components/public_model_hub.tsx
+++ b/ui/litellm-dashboard/src/components/public_model_hub.tsx
@@ -47,6 +47,7 @@ import { generateCodeSnippet } from "@/components/chat_ui/CodeSnippets";
 import { getEndpointType } from "@/components/chat_ui/mode_endpoint_mapping";
 import { MessageType } from "@/components/chat_ui/types";
 import { getProviderLogoAndName } from "./provider_info_helpers";
+import { filterBySearchTerm, rankBySearchRelevance } from "@/utils/searchUtils";
 
 interface PublicModelHubProps {
   accessToken?: string | null;
@@ -236,52 +237,11 @@ const PublicModelHub: React.FC<PublicModelHubProps> = ({ accessToken, isEmbedded
   const filteredData = useMemo(() => {
     if (!modelHubData || !Array.isArray(modelHubData)) return [];
 
-    let searchResults = modelHubData;
-
-    // Apply search if there's a search term
-    if (searchTerm.trim()) {
-      const lowercaseSearch = searchTerm.toLowerCase();
-      const searchWords = lowercaseSearch.split(/\s+/);
-
-      // First, try flexible matching that handles different separators
-      const exactMatches = modelHubData.filter((model) => {
-        const modelName = model.model_group.toLowerCase();
-
-        // Check if it contains the exact search term
-        if (modelName.includes(lowercaseSearch)) {
-          return true;
-        }
-
-        // Check if it contains all search words (handles spaces vs slashes/dashes)
-        return searchWords.every((word) => modelName.includes(word));
-      });
-
-      // If we have exact matches, rank them by relevance
-      if (exactMatches.length > 0) {
-        searchResults = exactMatches.sort((a, b) => {
-          const aName = a.model_group.toLowerCase();
-          const bName = b.model_group.toLowerCase();
-
-          // Calculate relevance scores
-          const aExactMatch = aName === lowercaseSearch ? 1000 : 0;
-          const bExactMatch = bName === lowercaseSearch ? 1000 : 0;
-
-          const aStartsWith = aName.startsWith(lowercaseSearch) ? 100 : 0;
-          const bStartsWith = bName.startsWith(lowercaseSearch) ? 100 : 0;
-
-          const aContainsWords = lowercaseSearch.split(/\s+/).every((word) => aName.includes(word)) ? 50 : 0;
-          const bContainsWords = lowercaseSearch.split(/\s+/).every((word) => bName.includes(word)) ? 50 : 0;
-
-          const aLength = aName.length;
-          const bLength = bName.length;
-
-          const aScore = aExactMatch + aStartsWith + aContainsWords + (1000 - aLength);
-          const bScore = bExactMatch + bStartsWith + bContainsWords + (1000 - bLength);
-
-          return bScore - aScore; // Higher score first
-        });
-      }
-    }
+    const searchResults = rankBySearchRelevance(
+      filterBySearchTerm(modelHubData, searchTerm, (model) => [model.model_group]),
+      searchTerm,
+      (model) => model.model_group,
+    );
 
     // Apply other filters
     return searchResults.filter((model) => {
@@ -310,43 +270,11 @@ const PublicModelHub: React.FC<PublicModelHubProps> = ({ accessToken, isEmbedded
   const filteredAgentData = useMemo(() => {
     if (!agentHubData || !Array.isArray(agentHubData)) return [];
 
-    let searchResults = agentHubData;
-
-    // Apply search if there's a search term
-    if (agentSearchTerm.trim()) {
-      const lowercaseSearch = agentSearchTerm.toLowerCase();
-      const searchWords = lowercaseSearch.split(/\s+/);
-
-      searchResults = agentHubData.filter((agent) => {
-        const agentName = agent.name.toLowerCase();
-        const agentDescription = agent.description.toLowerCase();
-
-        // Check if it contains the exact search term
-        if (agentName.includes(lowercaseSearch) || agentDescription.includes(lowercaseSearch)) {
-          return true;
-        }
-
-        // Check if it contains all search words
-        return searchWords.every((word) => agentName.includes(word) || agentDescription.includes(word));
-      });
-
-      // Sort by relevance
-      searchResults = searchResults.sort((a, b) => {
-        const aName = a.name.toLowerCase();
-        const bName = b.name.toLowerCase();
-
-        const aExactMatch = aName === lowercaseSearch ? 1000 : 0;
-        const bExactMatch = bName === lowercaseSearch ? 1000 : 0;
-
-        const aStartsWith = aName.startsWith(lowercaseSearch) ? 100 : 0;
-        const bStartsWith = bName.startsWith(lowercaseSearch) ? 100 : 0;
-
-        const aScore = aExactMatch + aStartsWith + (1000 - aName.length);
-        const bScore = bExactMatch + bStartsWith + (1000 - bName.length);
-
-        return bScore - aScore;
-      });
-    }
+    const searchResults = rankBySearchRelevance(
+      filterBySearchTerm(agentHubData, agentSearchTerm, (agent) => [agent.name, agent.description]),
+      agentSearchTerm,
+      (agent) => agent.name,
+    );
 
     // Apply skill filters
     return searchResults.filter((agent) => {
@@ -361,43 +289,11 @@ const PublicModelHub: React.FC<PublicModelHubProps> = ({ accessToken, isEmbedded
   const filteredMcpData = useMemo(() => {
     if (!mcpHubData || !Array.isArray(mcpHubData)) return [];
 
-    let searchResults = mcpHubData;
-
-    // Apply search if there's a search term
-    if (mcpSearchTerm.trim()) {
-      const lowercaseSearch = mcpSearchTerm.toLowerCase();
-      const searchWords = lowercaseSearch.split(/\s+/);
-
-      searchResults = mcpHubData.filter((server) => {
-        const serverName = server.server_name.toLowerCase();
-        const serverDescription = (server.mcp_info?.description || "").toLowerCase();
-
-        // Check if it contains the exact search term
-        if (serverName.includes(lowercaseSearch) || serverDescription.includes(lowercaseSearch)) {
-          return true;
-        }
-
-        // Check if it contains all search words
-        return searchWords.every((word) => serverName.includes(word) || serverDescription.includes(word));
-      });
-
-      // Sort by relevance
-      searchResults = searchResults.sort((a, b) => {
-        const aName = a.server_name.toLowerCase();
-        const bName = b.server_name.toLowerCase();
-
-        const aExactMatch = aName === lowercaseSearch ? 1000 : 0;
-        const bExactMatch = bName === lowercaseSearch ? 1000 : 0;
-
-        const aStartsWith = aName.startsWith(lowercaseSearch) ? 100 : 0;
-        const bStartsWith = bName.startsWith(lowercaseSearch) ? 100 : 0;
-
-        const aScore = aExactMatch + aStartsWith + (1000 - aName.length);
-        const bScore = bExactMatch + bStartsWith + (1000 - bName.length);
-
-        return bScore - aScore;
-      });
-    }
+    const searchResults = rankBySearchRelevance(
+      filterBySearchTerm(mcpHubData, mcpSearchTerm, (server) => [server.server_name, server.mcp_info?.description]),
+      mcpSearchTerm,
+      (server) => server.server_name,
+    );
 
     // Apply transport filters
     return searchResults.filter((server) => {
diff --git a/ui/litellm-dashboard/src/components/settings.test.tsx b/ui/litellm-dashboard/src/components/settings.test.tsx
index b97fef32402..762b23f413e 100644
--- a/ui/litellm-dashboard/src/components/settings.test.tsx
+++ b/ui/litellm-dashboard/src/components/settings.test.tsx
@@ -77,21 +77,21 @@ describe("Settings", () => {
   });
 
   it("should render the logging callbacks tab when access token is provided", async () => {
-    const { getByText } = render(<Settings {...defaultProps} />);
+    render(<Settings {...defaultProps} />);
 
     await waitFor(() => {
-      expect(getByText("Active Logging Callbacks")).toBeInTheDocument();
+      expect(screen.getByText("Active Logging Callbacks")).toBeInTheDocument();
     });
   });
 
   it("should display additional settings tabs", async () => {
-    const { getByText } = render(<Settings {...defaultProps} />);
+    render(<Settings {...defaultProps} />);
 
     await waitFor(() => {
-      expect(getByText("CloudZero Cost Tracking")).toBeInTheDocument();
-      expect(getByText("Alerting Types")).toBeInTheDocument();
-      expect(getByText("Alerting Settings")).toBeInTheDocument();
-      expect(getByText("Email Alerts")).toBeInTheDocument();
+      expect(screen.getByText("CloudZero Cost Tracking")).toBeInTheDocument();
+      expect(screen.getByText("Alerting Types")).toBeInTheDocument();
+      expect(screen.getByText("Alerting Settings")).toBeInTheDocument();
+      expect(screen.getByText("Email Alerts")).toBeInTheDocument();
     });
   });
 
@@ -279,13 +279,13 @@ describe("Settings", () => {
   });
 
   it("should display CloudZero Cost Tracking tab", async () => {
-    const { getByText } = render(<Settings {...defaultProps} />);
+    render(<Settings {...defaultProps} />);
 
     await waitFor(() => {
-      expect(getByText("Active Logging Callbacks")).toBeInTheDocument();
+      expect(screen.getByText("Active Logging Callbacks")).toBeInTheDocument();
     });
 
-    expect(getByText("CloudZero Cost Tracking")).toBeInTheDocument();
+    expect(screen.getByText("CloudZero Cost Tracking")).toBeInTheDocument();
   });
 });
 
diff --git a/ui/litellm-dashboard/src/components/settings.tsx b/ui/litellm-dashboard/src/components/settings.tsx
index 05e66985e6f..9cb55b6ed5c 100644
--- a/ui/litellm-dashboard/src/components/settings.tsx
+++ b/ui/litellm-dashboard/src/components/settings.tsx
@@ -293,6 +293,8 @@ const Settings: React.FC<SettingsPageProps> = ({ accessToken, userRole, userID,
     llm_too_slow: "LLM Responses Too Slow",
     llm_requests_hanging: "LLM Requests Hanging",
     budget_alerts: "Budget Alerts (API Keys, Users)",
+    user_spend_thresholds: "User Spend Thresholds (Daily/Monthly)",
+    user_spend_anomalies: "User Spend Anomaly Detection",
     db_exceptions: "Database Exceptions (Read/Write)",
     daily_reports: "Weekly/Monthly Spend Reports",
     outage_alerts: "Outage Alerts",
@@ -522,7 +524,8 @@ const Settings: React.FC<SettingsPageProps> = ({ accessToken, userRole, userID,
           <TabsContent value="alerting-types" keepMounted>
             <Card className="p-6">
               <p className="my-2">
-                Alerts are only supported for Slack Webhook URLs. Get your webhook urls from{" "}
+                Alerts are sent to any Slack-compatible incoming webhook URL (Slack, Rocket.Chat, Mattermost, etc.). Get
+                Slack webhook urls from{" "}
                 <a href="https://api.slack.com/messaging/webhooks" target="_blank" style={{ color: "blue" }}>
                   here
                 </a>
@@ -532,7 +535,7 @@ const Settings: React.FC<SettingsPageProps> = ({ accessToken, userRole, userID,
                   <TableRow>
                     <TableHead></TableHead>
                     <TableHead></TableHead>
-                    <TableHead>Slack Webhook URL</TableHead>
+                    <TableHead>Webhook URL (Slack-compatible)</TableHead>
                   </TableRow>
                 </TableHeader>
 
diff --git a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx
index 58a0cd94997..f502ea77127 100644
--- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx
@@ -1,5 +1,5 @@
 import type { ColumnDef, ExpandedState } from "@tanstack/react-table";
-import { render, screen, waitFor } from "@testing-library/react";
+import { render, screen, waitFor, within } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { useState } from "react";
 import { describe, expect, it, vi } from "vitest";
@@ -7,6 +7,7 @@ import { describe, expect, it, vi } from "vitest";
 import { DataTable } from "./DataTable";
 import { DataTableMultiSortHeader, DataTableSortHeader } from "./DataTableSortHeader";
 import { DataTableViewOptions } from "./DataTableViewOptions";
+import { chooseSelectOption } from "../../../../tests/test-utils";
 
 interface Person {
   id: string;
@@ -21,6 +22,12 @@ function person(id: string, name: string, flagged = false): Person {
 
 const names = (): (string | null)[] => screen.getAllByTestId("name-cell").map((el) => el.textContent);
 
+const heightClassesOf = (el: HTMLElement | undefined): string[] =>
+  (el?.className ?? "")
+    .split(/\s+/)
+    .filter((cls) => cls.startsWith("h-"))
+    .sort();
+
 const nameCellColumns: ColumnDef<Person, unknown>[] = [
   {
     accessorKey: "name",
@@ -170,16 +177,13 @@ describe("DataTable sorting", () => {
     const user = userEvent.setup();
     render(<DataTable data={CHARLIE_ALICE_BOB} columns={dropdownSortColumns} sortingMode="client" />);
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Ascending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Ascending", "menuitem");
     expect(names()).toEqual(["Alice", "Bob", "Charlie"]);
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Descending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Descending", "menuitem");
     expect(names()).toEqual(["Charlie", "Bob", "Alice"]);
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Reset"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Reset", "menuitem");
     expect(names()).toEqual(["Charlie", "Alice", "Bob"]);
   });
 
@@ -196,12 +200,10 @@ describe("DataTable sorting", () => {
       />,
     );
 
-    await user.click(screen.getByTestId("sort-trigger-spend"));
-    await user.click(await screen.findByText("Budget descending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-spend"), "Budget descending", "menuitem");
     expect(onSortingChange).toHaveBeenLastCalledWith([{ id: "max_budget", desc: true }]);
 
-    await user.click(screen.getByTestId("sort-trigger-spend"));
-    await user.click(await screen.findByText("Spend ascending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-spend"), "Spend ascending", "menuitem");
     expect(onSortingChange).toHaveBeenLastCalledWith([{ id: "spend", desc: false }]);
   });
 
@@ -229,12 +231,10 @@ describe("DataTable sorting", () => {
 
 describe("DataTable layout", () => {
   it("stretches the table to fill the container when resizing is on, so hidden columns leave no right-side gap", () => {
-    const { container } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} enableColumnResizing />);
+    render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} enableColumnResizing />);
 
-    const table = container.querySelector("table");
-    expect(table).not.toBeNull();
     // width pins the natural column total (horizontal scroll on overflow); minWidth:100% fills the gap on underflow.
-    expect(table?.style.minWidth).toBe("100%");
+    expect(screen.getByRole("table")).toHaveStyle({ minWidth: "100%" });
   });
 });
 
@@ -354,17 +354,21 @@ describe("DataTable loading", () => {
     const { rerender } = render(
       <DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} size="compact" isLoading />,
     );
-    const skeletonRow = screen.getAllByTestId("skeleton-row").at(0);
-    const loadedRowHeight = "h-8";
-    expect(skeletonRow?.className).toContain(loadedRowHeight);
+    const skeletonHeight = heightClassesOf(screen.getAllByRole("row").at(-1));
 
     rerender(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} size="compact" />);
-    expect(document.querySelector("[data-row-id]")?.className).toContain(loadedRowHeight);
+    const loadedHeight = heightClassesOf(screen.getByRole("row", { name: /Charlie/ }));
+
+    expect(loadedHeight).not.toEqual([]);
+    expect(skeletonHeight).toEqual(loadedHeight);
   });
 
   it("does not force the compact height on default-size skeleton rows", () => {
-    render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} isLoading />);
-    expect(screen.getAllByTestId("skeleton-row").at(0)?.className).not.toContain("h-8");
+    const { rerender } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} isLoading />);
+    const skeletonHeight = heightClassesOf(screen.getAllByRole("row").at(-1));
+
+    rerender(<DataTable data={CHARLIE_ALICE_BOB} columns={nameCellColumns} size="compact" isLoading />);
+    expect(heightClassesOf(screen.getAllByRole("row").at(-1))).not.toEqual(skeletonHeight);
   });
 
   it("varies skeleton shape and width per column instead of one fixed bar", () => {
@@ -420,7 +424,7 @@ describe("DataTable loading", () => {
 describe("DataTable column visibility", () => {
   it("hides a column when toggled off in the view-options menu", async () => {
     const user = userEvent.setup();
-    const { container } = render(
+    render(
       <DataTable
         data={CHARLIE_ALICE_BOB}
         columns={nameEmailColumns}
@@ -428,13 +432,13 @@ describe("DataTable column visibility", () => {
       />,
     );
 
-    expect(container.querySelector('th[data-header-id="email"]')).not.toBeNull();
+    expect(screen.getByRole("columnheader", { name: "Email" })).toBeInTheDocument();
     await user.click(screen.getByTestId("view-options-trigger"));
     await user.click(await screen.findByTestId("view-option-email"));
-    await waitFor(() => expect(container.querySelector('th[data-header-id="email"]')).toBeNull());
+    await waitFor(() => expect(screen.queryByRole("columnheader", { name: "Email" })).not.toBeInTheDocument());
 
     await user.click(screen.getByTestId("view-option-email"));
-    await waitFor(() => expect(container.querySelector('th[data-header-id="email"]')).not.toBeNull());
+    expect(await screen.findByRole("columnheader", { name: "Email" })).toBeInTheDocument();
   });
 
   it("omits columns that opt out of hiding from the menu", async () => {
@@ -468,14 +472,10 @@ describe("DataTable column visibility", () => {
 
 describe("DataTable pinned columns", () => {
   it("applies sticky positioning to a pinned column only", () => {
-    const { container } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={pinnedColumns} />);
+    render(<DataTable data={CHARLIE_ALICE_BOB} columns={pinnedColumns} />);
 
-    const pinnedHead = container.querySelector<HTMLElement>('th[data-header-id="name"]');
-    const normalHead = container.querySelector<HTMLElement>('th[data-header-id="email"]');
-
-    expect(pinnedHead?.style.position).toBe("sticky");
-    expect(pinnedHead?.style.left).toBe("0px");
-    expect(normalHead?.style.position).toBe("");
+    expect(screen.getByRole("columnheader", { name: "Name" })).toHaveStyle({ position: "sticky", left: "0px" });
+    expect(screen.getByRole("columnheader", { name: "Email" })).not.toHaveStyle({ position: "sticky" });
   });
 });
 
@@ -570,7 +570,7 @@ describe("DataTable expansion", () => {
 describe("DataTable row styling and footer", () => {
   it("applies rowClassName to the matching row only", () => {
     const data = [person("a", "Alice", true), person("b", "Bob", false)];
-    const { container } = render(
+    render(
       <DataTable
         data={data}
         columns={nameCellColumns}
@@ -579,8 +579,8 @@ describe("DataTable row styling and footer", () => {
       />,
     );
 
-    expect(container.querySelector('tr[data-row-id="a"]')?.className).toContain("flagged-row");
-    expect(container.querySelector('tr[data-row-id="b"]')?.className).not.toContain("flagged-row");
+    expect(screen.getByRole("row", { name: /Alice/ })).toHaveClass("flagged-row");
+    expect(screen.getByRole("row", { name: /Bob/ })).not.toHaveClass("flagged-row");
   });
 
   it("renders the footer slot inside a tfoot element", () => {
@@ -596,63 +596,57 @@ describe("DataTable row styling and footer", () => {
       />,
     );
 
-    expect(screen.getByTestId("footer-row").closest("tfoot")).not.toBeNull();
+    const rowGroups = screen.getAllByRole("rowgroup");
+    expect(within(rowGroups.at(-1) as HTMLElement).getByText("Total: 3")).toBeInTheDocument();
   });
 });
 
 describe("DataTable layout", () => {
   it("exposes resize handles with stable selectors only when resizing is enabled", () => {
-    const { container, rerender } = render(
-      <DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} enableColumnResizing />,
-    );
-    expect(container.querySelectorAll("[data-resizer][data-header-id]").length).toBe(2);
+    const { rerender } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} enableColumnResizing />);
+    expect(screen.getByTestId("column-resizer-name")).toBeInTheDocument();
+    expect(screen.getByTestId("column-resizer-email")).toBeInTheDocument();
 
     rerender(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} />);
-    expect(container.querySelectorAll("[data-resizer]").length).toBe(0);
+    expect(screen.queryByTestId("column-resizer-name")).not.toBeInTheDocument();
   });
 
   it("makes the header sticky and constrains body height when maxBodyHeight is set", () => {
-    const { container } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} maxBodyHeight={240} />);
-    expect(container.querySelector("thead")?.className).toContain("sticky");
-    const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement;
-    expect(scroller).toHaveStyle({ maxHeight: "240px" });
+    render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} maxBodyHeight={240} />);
+    expect(screen.getByTestId("data-table-head")).toHaveClass("sticky");
+    expect(screen.getByTestId("data-table-scroller")).toHaveStyle({ maxHeight: "240px" });
   });
 
   it("caps fillHeight at the parent's height instead of stretching to it, so a short table stays short", () => {
-    const { container } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} fillHeight />);
-    const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement;
-    const frame = scroller.parentElement as HTMLElement;
-    const outer = frame.parentElement as HTMLElement;
+    render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} fillHeight />);
+    const outer = screen.getByTestId("data-table-root");
+    const frame = screen.getByTestId("data-table-frame");
+    const scroller = screen.getByTestId("data-table-scroller");
 
     // A ceiling, not a stretch: flex-1 here would hold the footer at the bottom on a two-row table.
-    expect(outer.className).toContain("max-h-full");
-    expect(outer.className).not.toContain("flex-1");
-    expect(frame.className).not.toContain("flex-1");
-    expect(scroller.className).not.toContain("flex-1");
+    expect(outer).toHaveClass("max-h-full", "flex-col");
+    expect(outer).not.toHaveClass("flex-1");
+    expect(frame).toHaveClass("flex-col");
+    expect(frame).not.toHaveClass("flex-1");
+    expect(scroller).not.toHaveClass("flex-1");
 
-    expect(outer.className).toContain("flex-col");
-    expect(frame.className).toContain("flex-col");
-    expect(scroller.className).toContain("min-h-0");
-    expect(scroller.className).toContain("overflow-auto");
+    expect(scroller).toHaveClass("min-h-0", "overflow-auto");
     expect(scroller).toHaveStyle({ maxHeight: "" });
     // Without this the Table primitive's own overflow container captures the sticky header.
-    expect(scroller.className).toContain("[&_[data-slot=table-container]]:overflow-visible");
+    expect(scroller).toHaveClass("[&_[data-slot=table-container]]:overflow-visible");
 
-    const thead = container.querySelector("thead") as HTMLElement;
-    expect(thead.className).toContain("sticky");
     // Rows pass under the header, so the semi-transparent row tint alone would let them show through.
-    expect(thead.className).toContain("bg-background");
+    expect(screen.getByTestId("data-table-head")).toHaveClass("sticky", "bg-background");
   });
 
   it("leaves the default layout untouched when neither height mode is set", () => {
-    const { container } = render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} />);
-    const scroller = container.querySelector('[data-slot="table-container"]')?.parentElement as HTMLElement;
+    render(<DataTable data={CHARLIE_ALICE_BOB} columns={nameEmailColumns} />);
+    const scroller = screen.getByTestId("data-table-scroller");
 
-    expect(scroller.className).toContain("overflow-x-auto");
-    expect(scroller.className).not.toContain("min-h-0");
+    expect(scroller).toHaveClass("overflow-x-auto");
+    expect(scroller).not.toHaveClass("min-h-0");
     expect(scroller).toHaveStyle({ maxHeight: "" });
-    expect((scroller.parentElement as HTMLElement).className).not.toContain("flex-col");
-    expect(container.querySelector("thead")?.className).not.toContain("sticky");
-    expect(container.querySelector("thead")?.className).not.toContain("bg-background");
+    expect(screen.getByTestId("data-table-frame")).not.toHaveClass("flex-col");
+    expect(screen.getByTestId("data-table-head")).not.toHaveClass("sticky", "bg-background");
   });
 });
diff --git a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx
index e8357b37715..60267606951 100644
--- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx
+++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.tsx
@@ -195,8 +195,7 @@ function DataTableHeadCell<TData>({ header, size, stickyHeader, enableColumnResi
       )}
       {canResize && (
         <div
-          data-resizer
-          data-header-id={header.id}
+          data-testid={`column-resizer-${header.id}`}
           onMouseDown={header.getResizeHandler()}
           onTouchStart={header.getResizeHandler()}
           onDoubleClick={() => column.resetSize()}
@@ -589,15 +588,19 @@ export function DataTable<TData extends RowData, TValue>(props: DataTableProps<T
   const paginationNode = renderPagination();
 
   return (
-    <div className={cn("w-full", fill.outer)}>
-      <div className={cn("overflow-hidden rounded-lg border border-border", fill.frame)}>
+    <div data-testid="data-table-root" className={cn("w-full", fill.outer)}>
+      <div data-testid="data-table-frame" className={cn("overflow-hidden rounded-lg border border-border", fill.frame)}>
         {toolbar !== undefined && <div className="shrink-0 border-b border-border px-4 py-3">{toolbar(table)}</div>}
         <div
+          data-testid="data-table-scroller"
           className={cn(stickyHeader ? "overflow-auto" : "overflow-x-auto", fill.body)}
           style={maxBodyHeight !== undefined ? { maxHeight: maxBodyHeight } : undefined}
         >
           <TableRoot className={enableColumnResizing ? "table-fixed" : ""} style={tableStyle}>
-            <TableHeader className={cn(stickyHeader ? "sticky top-0 z-sticky" : "", fill.header)}>
+            <TableHeader
+              data-testid="data-table-head"
+              className={cn(stickyHeader ? "sticky top-0 z-sticky" : "", fill.header)}
+            >
               {table.getHeaderGroups().map((headerGroup) => (
                 <TableRow key={headerGroup.id} className="bg-muted/50">
                   {headerGroup.headers.map((header) => (
diff --git a/ui/litellm-dashboard/src/components/shared/DataTable/DataTableSortHeader.test.tsx b/ui/litellm-dashboard/src/components/shared/DataTable/DataTableSortHeader.test.tsx
index 70403ba2efe..aeb6fa44e91 100644
--- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTableSortHeader.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTableSortHeader.test.tsx
@@ -13,6 +13,7 @@ import { useState } from "react";
 import { describe, expect, it, vi } from "vitest";
 
 import { DataTableSortHeader, type DataTableSortVariant } from "./DataTableSortHeader";
+import { chooseSelectOption } from "../../../../tests/test-utils";
 
 interface Item {
   name: string;
@@ -84,16 +85,13 @@ describe("DataTableSortHeader", () => {
     const user = userEvent.setup();
     render(<SortHeaderHarness variant="dropdown-tristate" />);
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Descending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Descending", "menuitem");
     expect(screen.getByTestId("sort-trigger-name").querySelector('[data-sort-indicator="desc"]')).not.toBeNull();
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Ascending"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Ascending", "menuitem");
     expect(screen.getByTestId("sort-trigger-name").querySelector('[data-sort-indicator="asc"]')).not.toBeNull();
 
-    await user.click(screen.getByTestId("sort-trigger-name"));
-    await user.click(await screen.findByText("Reset"));
+    await chooseSelectOption(user, screen.getByTestId("sort-trigger-name"), "Reset", "menuitem");
     expect(screen.getByTestId("sort-trigger-name").querySelector('[data-sort-indicator="none"]')).not.toBeNull();
   });
 
diff --git a/ui/litellm-dashboard/src/components/shared/PaginatedSearchSelect.test.tsx b/ui/litellm-dashboard/src/components/shared/PaginatedSearchSelect.test.tsx
index d248cf311cc..04c8d3e9012 100644
--- a/ui/litellm-dashboard/src/components/shared/PaginatedSearchSelect.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/PaginatedSearchSelect.test.tsx
@@ -5,6 +5,7 @@ import { describe, expect, it, vi } from "vitest";
 
 import { PaginatedSearchSelect } from "./PaginatedSearchSelect";
 import type { SearchSelectOption } from "./SearchSelect";
+import { chooseSelectOption } from "../../../tests/test-utils";
 
 const OPTIONS: SearchSelectOption[] = [
   { label: "alias-alpha", value: "alias-alpha" },
@@ -63,8 +64,7 @@ describe("PaginatedSearchSelect", () => {
     }
     render(<Controlled />);
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("alias-beta"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "alias-beta");
 
     expect(screen.getByRole("combobox")).toHaveValue("alias-beta");
     await new Promise((resolve) => setTimeout(resolve, 400));
@@ -136,8 +136,7 @@ describe("PaginatedSearchSelect", () => {
     const onValueChange = vi.fn();
     renderSelect({ onValueChange });
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("alias-beta"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "alias-beta");
 
     expect(onValueChange).toHaveBeenCalledWith("alias-beta");
   });
@@ -255,8 +254,7 @@ describe("PaginatedSearchSelect", () => {
     }
     render(<Refetching />);
 
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("Beta Team"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "Beta Team");
     await user.click(screen.getByRole("button", { name: "refetch" }));
 
     expect(screen.getByRole("combobox")).toHaveValue("Beta Team");
diff --git a/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx b/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx
index 3698b68155e..5bd48b1aa4c 100644
--- a/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/PaginationStatusAlerts.test.tsx
@@ -1,4 +1,4 @@
-import { fireEvent, render } from "@testing-library/react";
+import { fireEvent, render, screen } from "@testing-library/react";
 import { describe, expect, it, vi } from "vitest";
 
 import PaginationStatusAlerts from "./PaginationStatusAlerts";
@@ -6,7 +6,7 @@ import PaginationStatusAlerts from "./PaginationStatusAlerts";
 describe("PaginationStatusAlerts", () => {
   it("shows page progress and wires the Stop button while fetching", () => {
     const cancel = vi.fn();
-    const { getByRole, getByText } = render(
+    render(
       <PaginationStatusAlerts
         isFetchingMore={true}
         cancelled={false}
@@ -15,13 +15,13 @@ describe("PaginationStatusAlerts", () => {
       />,
     );
 
-    expect(getByText(/Currently fetching spend data: fetched 7 \/ 42 pages/)).toBeInTheDocument();
-    fireEvent.click(getByRole("button", { name: "Stop" }));
+    expect(screen.getByText(/Currently fetching spend data: fetched 7 \/ 42 pages/)).toBeInTheDocument();
+    fireEvent.click(screen.getByRole("button", { name: "Stop" }));
     expect(cancel).toHaveBeenCalledTimes(1);
   });
 
   it("shows the partial-data notice after a cancel, frozen at the last fetched page", () => {
-    const { getByText } = render(
+    render(
       <PaginationStatusAlerts
         isFetchingMore={false}
         cancelled={true}
@@ -30,11 +30,11 @@ describe("PaginationStatusAlerts", () => {
       />,
     );
 
-    expect(getByText("Showing partial spend data (7/42 pages loaded)")).toBeInTheDocument();
+    expect(screen.getByText("Showing partial spend data (7/42 pages loaded)")).toBeInTheDocument();
   });
 
   it("names the subject it is fetching", () => {
-    const { getByText } = render(
+    render(
       <PaginationStatusAlerts
         isFetchingMore={true}
         cancelled={false}
@@ -44,7 +44,7 @@ describe("PaginationStatusAlerts", () => {
       />,
     );
 
-    expect(getByText(/Currently fetching agent data: fetched 1 \/ 3 pages/)).toBeInTheDocument();
+    expect(screen.getByText(/Currently fetching agent data: fetched 1 \/ 3 pages/)).toBeInTheDocument();
   });
 
   it("renders nothing when idle", () => {
diff --git a/ui/litellm-dashboard/src/components/shared/SearchSelect.test.tsx b/ui/litellm-dashboard/src/components/shared/SearchSelect.test.tsx
index c0b9bc7d8ae..62a510268dd 100644
--- a/ui/litellm-dashboard/src/components/shared/SearchSelect.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/SearchSelect.test.tsx
@@ -3,6 +3,7 @@ import userEvent from "@testing-library/user-event";
 import { describe, expect, it, vi } from "vitest";
 
 import { SearchSelect } from "./SearchSelect";
+import { chooseSelectOption } from "../../../tests/test-utils";
 
 const OPTIONS = [
   { label: "Acme Prod", value: "team-1" },
@@ -71,8 +72,7 @@ describe("SearchSelect", () => {
     const onValueChange = vi.fn();
     const user = userEvent.setup();
     render(<SearchSelect options={OPTIONS} onValueChange={onValueChange} />);
-    await user.click(screen.getByRole("combobox"));
-    await user.click(await screen.findByText("Growth"));
+    await chooseSelectOption(user, screen.getByRole("combobox"), "Growth");
     expect(onValueChange).toHaveBeenCalledWith("team-2");
   });
 
diff --git a/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx b/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx
index 6e4ab14be33..c81ade526dd 100644
--- a/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/charts/area_chart.test.tsx
@@ -1,4 +1,4 @@
-import { render } from "@testing-library/react";
+import { render, screen } from "@testing-library/react";
 import React from "react";
 import { describe, expect, it } from "vitest";
 import { AreaChart } from "./area_chart";
@@ -21,9 +21,9 @@ describe("AreaChart", () => {
   });
 
   it("renders the No data placeholder instead of a chart when data is empty", () => {
-    const { container, getByText } = render(<AreaChart data={[]} index="date" categories={["tokens"]} />);
+    const { container } = render(<AreaChart data={[]} index="date" categories={["tokens"]} />);
 
-    expect(getByText("No data")).toBeInTheDocument();
+    expect(screen.getByText("No data")).toBeInTheDocument();
     expect(container.querySelector('[data-slot="chart"]')).toBeNull();
   });
 
diff --git a/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx b/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx
index a322eeb3ad0..3cd7bd2fd08 100644
--- a/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/charts/bar_chart.test.tsx
@@ -21,9 +21,9 @@ describe("BarChart", () => {
   });
 
   it("renders the No data placeholder instead of a chart when data is empty", () => {
-    const { container, getByText } = render(<BarChart data={[]} index="date" categories={["passed"]} />);
+    const { container } = render(<BarChart data={[]} index="date" categories={["passed"]} />);
 
-    expect(getByText("No data")).toBeInTheDocument();
+    expect(screen.getByText("No data")).toBeInTheDocument();
     expect(container.querySelector('[data-slot="chart"]')).toBeNull();
   });
 
diff --git a/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx b/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx
index 6592ff8c357..705679fe2e6 100644
--- a/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx
+++ b/ui/litellm-dashboard/src/components/templates/KeyInfoView.handleKeyUpdate.test.tsx
@@ -445,7 +445,7 @@ describe("KeyInfoView handleKeyUpdate budget_duration", () => {
     );
 
     fireEvent.click(screen.getByText("Settings"));
-    expect(screen.getByText("Budget Reset").parentElement?.textContent).toContain("Every 30d");
+    expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Every 30d");
 
     fireEvent.click(screen.getByText("Edit Settings"));
     (globalThis as any).__TEST_FORM_VALUES = {
@@ -456,7 +456,7 @@ describe("KeyInfoView handleKeyUpdate budget_duration", () => {
     fireEvent.click(screen.getByText("Mock Submit"));
 
     await waitFor(() => {
-      expect(screen.getByText("Budget Reset").parentElement?.textContent).toBe("Budget ResetNever");
+      expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Never");
     });
   });
 });
diff --git a/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx b/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx
index bf8f43b8b5f..97b09e00808 100644
--- a/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx
+++ b/ui/litellm-dashboard/src/components/templates/key_edit_view.test.tsx
@@ -1,7 +1,7 @@
 import { fireEvent, screen, waitFor } from "@testing-library/react";
 import userEvent from "@testing-library/user-event";
 import { beforeEach, describe, expect, it, vi } from "vitest";
-import { renderWithProviders } from "../../../tests/test-utils";
+import { chooseSelectOption, renderWithProviders } from "../../../tests/test-utils";
 import { KeyResponse } from "../key_team_helpers/key_list";
 import { MODEL_MAX_BUDGET_PREMIUM_HINT } from "../key_team_helpers/ModelMaxBudgetEditor";
 import {
@@ -300,7 +300,7 @@ describe("KeyEditView", () => {
   });
 
   it("should render", async () => {
-    const { getByText } = renderWithProviders(
+    renderWithProviders(
       <KeyEditView
         keyData={MOCK_KEY_DATA}
         onCancel={() => {}}
@@ -313,12 +313,12 @@ describe("KeyEditView", () => {
     );
 
     await waitFor(() => {
-      expect(getByText("Save Changes")).toBeInTheDocument();
+      expect(screen.getByText("Save Changes")).toBeInTheDocument();
     });
   });
 
   it("should render tags", async () => {
-    const { getByText } = renderWithProviders(
+    renderWithProviders(
       <KeyEditView
         keyData={MOCK_KEY_DATA}
         onCancel={() => {}}
@@ -331,12 +331,12 @@ describe("KeyEditView", () => {
     );
 
     await waitFor(() => {
-      expect(getByText("test-tag")).toBeInTheDocument();
+      expect(screen.getByText("test-tag")).toBeInTheDocument();
     });
   });
 
   it("should not render tags in metadata textarea", async () => {
-    const { getByLabelText } = renderWithProviders(
+    renderWithProviders(
       <KeyEditView
         keyData={MOCK_KEY_DATA}
         onCancel={() => {}}
@@ -348,7 +348,7 @@ describe("KeyEditView", () => {
       />,
     );
 
-    const metadataTextarea = getByLabelText("Metadata") as HTMLTextAreaElement;
+    const metadataTextarea = screen.getByLabelText("Metadata") as HTMLTextAreaElement;
     await waitFor(() => {
       expect(metadataTextarea).toHaveValue("{}");
     });
@@ -963,10 +963,7 @@ describe("KeyEditView", () => {
       />,
     );
 
-    await userEvent.click(await screen.findByLabelText("Reset Budget"));
-
-    const weeklyOption = await screen.findByText("weekly");
-    await userEvent.click(weeklyOption);
+    await chooseSelectOption(userEvent, await screen.findByLabelText("Reset Budget"), "weekly");
 
     const submitButton = screen.getByRole("button", { name: /save changes/i });
     await userEvent.click(submitButton);
@@ -1042,8 +1039,7 @@ describe("KeyEditView", () => {
     );
 
     const resetBudget = await screen.findByLabelText("Reset Budget");
-    await userEvent.click(resetBudget);
-    await userEvent.click(await screen.findByText("Never resets"));
+    await chooseSelectOption(userEvent, resetBudget, "Never resets");
 
     await waitFor(() => {
       expect(resetBudget).toHaveTextContent("Never resets");
@@ -1074,8 +1070,7 @@ describe("KeyEditView", () => {
       />,
     );
 
-    await userEvent.click(await screen.findByLabelText("Reset Budget"));
-    await userEvent.click(await screen.findByText("Never resets"));
+    await chooseSelectOption(userEvent, await screen.findByLabelText("Reset Budget"), "Never resets");
 
     await userEvent.click(screen.getByRole("button", { name: /save changes/i }));
 
@@ -1946,8 +1941,7 @@ describe("KeyEditView", () => {
       await userEvent.clear(duration);
       await userEvent.type(duration, "45d");
 
-      await userEvent.click(screen.getByLabelText(/TPM Rate Limit Type/));
-      await userEvent.click(await screen.findByTitle("Guaranteed throughput"));
+      await chooseSelectOption(userEvent, screen.getByLabelText(/TPM Rate Limit Type/), /^Guaranteed throughput/);
 
       await userEvent.click(screen.getByRole("button", { name: /save changes/i }));
 
@@ -2103,8 +2097,7 @@ describe("KeyEditView", () => {
       renderForPayload(onSubmitMock);
       await screen.findByRole("button", { name: /save changes/i });
 
-      await userEvent.click(screen.getByLabelText(/RPM Rate Limit Type/));
-      await userEvent.click(await screen.findByTitle("Guaranteed throughput"));
+      await chooseSelectOption(userEvent, screen.getByLabelText(/RPM Rate Limit Type/), /^Guaranteed throughput/);
 
       await userEvent.click(screen.getByRole("button", { name: /save changes/i }));
 
diff --git a/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx b/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx
index f506c0e51d7..a02f80f7800 100644
--- a/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx
+++ b/ui/litellm-dashboard/src/components/templates/key_info_view.budget_display.test.tsx
@@ -381,6 +381,6 @@ describe("KeyInfoView budget reset visibility", () => {
     await waitFor(() => {
       expect(screen.getByText("Budget Reset")).toBeInTheDocument();
     });
-    expect(screen.getByText("Budget Reset").parentElement).toHaveTextContent("Never");
+    expect(screen.getByTestId("budget-reset-value")).toHaveTextContent("Never");
   });
 });
diff --git a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
index 0be80c3e173..0dd0dd6d6af 100644
--- a/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
+++ b/ui/litellm-dashboard/src/components/templates/key_info_view.tsx
@@ -895,7 +895,7 @@ export default function KeyInfoView({
 
                   <div>
                     <p className="text-sm font-medium">Budget Reset</p>
-                    <p className="text-sm">
+                    <p data-testid="budget-reset-value" className="text-sm">
                       {currentKeyData.budget_reset_at
                         ? `${currentKeyData.budget_duration ? `Every ${currentKeyData.budget_duration}, next ` : ""}${formatTimestamp(currentKeyData.budget_reset_at)}`
                         : "Never"}
diff --git a/ui/litellm-dashboard/src/components/ui/field.test.tsx b/ui/litellm-dashboard/src/components/ui/field.test.tsx
index 4bb3d0ec665..5765a637526 100644
--- a/ui/litellm-dashboard/src/components/ui/field.test.tsx
+++ b/ui/litellm-dashboard/src/components/ui/field.test.tsx
@@ -14,6 +14,7 @@ import {
   FieldSet,
   FieldTitle,
 } from "./field";
+import { ROW_LAYOUT_CLASSES, STRETCH_CHILDREN_CLASS } from "../../../tests/fieldOrientation";
 
 describe("FieldError", () => {
   it("renders nothing when there are no errors and no children", () => {
@@ -85,6 +86,20 @@ describe("Field", () => {
 
     expect(screen.getByRole("group")).toHaveAttribute("data-orientation", "horizontal");
   });
+
+  it("stretches every child when vertical, which is what inputs, selects and textareas want", () => {
+    render(<Field />);
+
+    expect(screen.getByRole("group")).toHaveClass("flex-col", STRETCH_CHILDREN_CLASS);
+  });
+
+  it("lays children in a row at their own width when horizontal, so a checkbox stays square", () => {
+    render(<Field orientation="horizontal" />);
+    const field = screen.getByRole("group");
+
+    expect(field).toHaveClass(...ROW_LAYOUT_CLASSES);
+    expect(field).not.toHaveClass(STRETCH_CHILDREN_CLASS);
+  });
 });
 
 describe("field primitives forward refs to their DOM node", () => {
diff --git a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.test.tsx b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.test.tsx
index e084fdf37e6..bf6a20a4af8 100644
--- a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.test.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.test.tsx
@@ -186,6 +186,12 @@ describe("RoutingDecisionCard", () => {
     expect(screen.queryByText("housekeeping")).not.toBeInTheDocument();
   });
 
+  it("labels a modality escalation instead of showing the raw cause token", () => {
+    render(<RoutingDecisionCard decision={{ ...heuristic, cause: "modality_escalation" }} />);
+    expect(screen.getByText("Escalated for image input")).toBeInTheDocument();
+    expect(screen.queryByText("modality_escalation")).not.toBeInTheDocument();
+  });
+
   it("shows the escalation keyword", () => {
     render(
       <RoutingDecisionCard decision={{ ...heuristic, escalated: true, escalation_keyword: "LITELLM ESCALATE" }} />,
diff --git a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.tsx b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.tsx
index 8c77b2db630..ffef01010b7 100644
--- a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/RoutingDecisionCard.tsx
@@ -84,11 +84,15 @@ function describeReasoningOverride(tierLabel: string | undefined, floor: number
 
 const CONSTANT_CAUSE_LABELS: Record<string, string> = {
   heuristic_scorer: "Heuristic scorer",
+  heuristic_v2: "Heuristic v2",
   heuristic_first_short_circuit: "Heuristic scorer, classifier skipped",
+  hybrid_short_circuit: "Heuristic scorer, score clear of every boundary",
   classifier_plugin: "Custom classifier plugin",
   semantic_keyword_match: "Semantic keyword match",
   session_affinity_pin: "Pinned to session",
   session_affinity_escalation: "Escalated from session pin",
+  user_turn_continuation: "Continuation turn, classifier skipped",
+  modality_escalation: "Escalated for image input",
   quality_tier: "Quality tier mapping",
   bandit: "Adaptive bandit",
   default_fallback: "Default model, no route matched",
diff --git a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.test.tsx b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.test.tsx
index 5aee6b33ec5..6cd9f476628 100644
--- a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.test.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.test.tsx
@@ -53,6 +53,24 @@ describe("SectionHeader", () => {
     expect(onToggleCollapse).toHaveBeenCalledTimes(1);
   });
 
+  it("reports its collapsed state to assistive technology", () => {
+    const { rerender } = render(
+      <SectionHeader type="input" onCopy={vi.fn()} onToggleCollapse={vi.fn()} isCollapsed={false} />,
+    );
+
+    expect(screen.getByRole("button", { name: /^Input/ })).toHaveAttribute("aria-expanded", "true");
+
+    rerender(<SectionHeader type="input" onCopy={vi.fn()} onToggleCollapse={vi.fn()} isCollapsed={true} />);
+
+    expect(screen.getByRole("button", { name: /^Input/ })).toHaveAttribute("aria-expanded", "false");
+  });
+
+  it("names each copy button for the section it belongs to", () => {
+    render(<SectionHeader type="output" onCopy={vi.fn()} onToggleCollapse={vi.fn()} />);
+
+    expect(screen.getByRole("button", { name: "Copy output" })).toBeInTheDocument();
+  });
+
   it("stays inert when no toggle handler is given", async () => {
     const onCopy = vi.fn();
     render(<SectionHeader type="input" onCopy={onCopy} />);
diff --git a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.tsx b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.tsx
index 93e9953b2ee..6a18aaf8642 100644
--- a/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/LogDetailsDrawer/SectionHeader.tsx
@@ -17,6 +17,8 @@ interface SectionHeaderProps {
   turnCount?: number;
 }
 
+const SUMMARY_CLASSES = "flex flex-1 items-center gap-4";
+
 export function SectionHeader({
   type,
   tokens,
@@ -26,42 +28,53 @@ export function SectionHeader({
   onToggleCollapse,
   turnCount,
 }: SectionHeaderProps) {
+  const summary = (
+    <>
+      {onToggleCollapse &&
+        (isCollapsed ? (
+          <ChevronDown className="size-2.5 text-muted-foreground" />
+        ) : (
+          <ChevronUp className="size-2.5 text-muted-foreground" />
+        ))}
+
+      <div className="flex items-center gap-2">
+        {type === "input" ? (
+          <MessageSquare className="size-3.5 text-muted-foreground" />
+        ) : (
+          <span className="text-sm opacity-60 grayscale">✨</span>
+        )}
+        <span className="text-sm font-medium">{type === "input" ? "Input" : "Output"}</span>
+      </div>
+
+      {tokens !== undefined && <span className="text-xs text-muted-foreground">Tokens: {tokens.toLocaleString()}</span>}
+
+      {cost !== undefined && <span className="text-xs text-muted-foreground">Cost: ${cost.toFixed(6)}</span>}
+
+      {turnCount !== undefined && turnCount > 0 && (
+        <span className="text-xs text-muted-foreground">Turns: {turnCount}</span>
+      )}
+    </>
+  );
+
   return (
     <div
-      onClick={onToggleCollapse}
       className={cn(
         "flex items-center justify-between bg-muted px-4 py-2.5 transition-colors",
         isCollapsed ? "border-b-0" : "border-b border-border",
-        onToggleCollapse ? "cursor-pointer hover:bg-accent" : "cursor-default",
       )}
     >
-      <div className="flex items-center gap-4">
-        {onToggleCollapse &&
-          (isCollapsed ? (
-            <ChevronDown className="size-2.5 text-muted-foreground" />
-          ) : (
-            <ChevronUp className="size-2.5 text-muted-foreground" />
-          ))}
-
-        <div className="flex items-center gap-2">
-          {type === "input" ? (
-            <MessageSquare className="size-3.5 text-muted-foreground" />
-          ) : (
-            <span className="text-sm opacity-60 grayscale">✨</span>
-          )}
-          <span className="text-sm font-medium">{type === "input" ? "Input" : "Output"}</span>
-        </div>
-
-        {tokens !== undefined && (
-          <span className="text-xs text-muted-foreground">Tokens: {tokens.toLocaleString()}</span>
-        )}
-
-        {cost !== undefined && <span className="text-xs text-muted-foreground">Cost: ${cost.toFixed(6)}</span>}
-
-        {turnCount !== undefined && turnCount > 0 && (
-          <span className="text-xs text-muted-foreground">Turns: {turnCount}</span>
-        )}
-      </div>
+      {onToggleCollapse ? (
+        <button
+          type="button"
+          onClick={onToggleCollapse}
+          aria-expanded={!isCollapsed}
+          className={cn(SUMMARY_CLASSES, "-mx-2 cursor-pointer rounded-md px-2 py-1 text-left hover:bg-accent")}
+        >
+          {summary}
+        </button>
+      ) : (
+        <div className={SUMMARY_CLASSES}>{summary}</div>
+      )}
 
       <Tooltip>
         <TooltipTrigger
@@ -69,7 +82,7 @@ export function SectionHeader({
             <Button
               variant="ghost"
               size="icon-sm"
-              aria-label="Copy"
+              aria-label={type === "input" ? "Copy input" : "Copy output"}
               onClick={(e) => {
                 e.stopPropagation();
                 onCopy();
diff --git a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx
index e0ec66e1ae2..5a35c7ae16b 100644
--- a/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/RequestLogsFilters.test.tsx
@@ -3,7 +3,7 @@ import userEvent from "@testing-library/user-event";
 import { useState } from "react";
 import { beforeEach, describe, expect, it, vi } from "vitest";
 
-import { renderWithProviders, testQueryClient } from "../../../tests/test-utils";
+import { chooseSelectOption, renderWithProviders, testQueryClient } from "../../../tests/test-utils";
 import { ERROR_CODE_OPTIONS } from "./constants";
 import { LOG_FILTER_IDS } from "./log_filter_logic";
 import { RequestLogsFilters } from "./RequestLogsFilters";
@@ -125,8 +125,7 @@ describe("RequestLogsFilters", () => {
     const user = userEvent.setup();
     const { set } = renderFilters();
 
-    await user.click(await screen.findByPlaceholderText("Search an internal user"));
-    await user.click(await screen.findByText("alice@example.com"));
+    await chooseSelectOption(user, await screen.findByPlaceholderText("Search an internal user"), "alice@example.com");
 
     expect(set).toHaveBeenCalledWith(LOG_FILTER_IDS.USER_ID, "alice@example.com");
   });
diff --git a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/FormattedToolView.tsx b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/FormattedToolView.tsx
index 1a6afd7fcfe..8a56312572c 100644
--- a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/FormattedToolView.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/FormattedToolView.tsx
@@ -25,31 +25,15 @@ export function FormattedToolView({ tool }: FormattedToolViewProps) {
     <div>
       {/* Description */}
       {tool.description && (
-        <div style={{ marginBottom: 16 }}>
-          <span
-            style={{
-              lineHeight: 1.6,
-              whiteSpace: "pre-wrap",
-            }}
-          >
-            {tool.description}
-          </span>
+        <div className="mb-4">
+          <span className="whitespace-pre-wrap leading-relaxed">{tool.description}</span>
         </div>
       )}
 
       {/* Parameters Table */}
       {parameterRows.length > 0 && (
         <div>
-          <span
-            className="text-muted-foreground"
-            style={{
-              fontSize: 12,
-              display: "block",
-              marginBottom: 8,
-            }}
-          >
-            Parameters
-          </span>
+          <span className="mb-2 block text-xs text-muted-foreground">Parameters</span>
           <Table>
             <TableHeader>
               <TableRow>
@@ -82,33 +66,10 @@ export function FormattedToolView({ tool }: FormattedToolViewProps) {
 
       {/* If tool was called, show the arguments used */}
       {tool.called && tool.callData && (
-        <div style={{ marginTop: 16 }}>
-          <span
-            className="text-muted-foreground"
-            style={{
-              fontSize: 12,
-              display: "block",
-              marginBottom: 8,
-            }}
-          >
-            Called With
-          </span>
-          <div
-            style={{
-              background: "#f6ffed",
-              border: "1px solid #b7eb8f",
-              borderRadius: 4,
-              padding: 12,
-            }}
-          >
-            <pre
-              style={{
-                margin: 0,
-                fontSize: 12,
-                whiteSpace: "pre-wrap",
-                wordBreak: "break-word",
-              }}
-            >
+        <div className="mt-4">
+          <span className="mb-2 block text-xs text-muted-foreground">Called With</span>
+          <div className="rounded border border-success/30 bg-success/10 p-3">
+            <pre className="m-0 whitespace-pre-wrap break-words text-xs text-foreground">
               {JSON.stringify(tool.callData.arguments, null, 2)}
             </pre>
           </div>
diff --git a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/JsonToolView.tsx b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/JsonToolView.tsx
index 2a2ceb644dc..d8431e52a51 100644
--- a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/JsonToolView.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/JsonToolView.tsx
@@ -20,19 +20,7 @@ export function JsonToolView({ tool }: JsonToolViewProps) {
   };
 
   return (
-    <pre
-      style={{
-        margin: 0,
-        whiteSpace: "pre-wrap",
-        wordBreak: "break-word",
-        fontSize: 12,
-        background: "#fafafa",
-        padding: 12,
-        borderRadius: 4,
-        maxHeight: 300,
-        overflow: "auto",
-      }}
-    >
+    <pre className="m-0 max-h-[300px] overflow-auto whitespace-pre-wrap break-words rounded bg-muted p-3 text-xs text-foreground">
       {JSON.stringify(toolJson, null, 2)}
     </pre>
   );
diff --git a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/ToolItem.tsx b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/ToolItem.tsx
index 112364f5ff3..26b39579859 100644
--- a/ui/litellm-dashboard/src/components/view_logs/ToolsSection/ToolItem.tsx
+++ b/ui/litellm-dashboard/src/components/view_logs/ToolsSection/ToolItem.tsx
@@ -5,6 +5,7 @@
 import { useState } from "react";
 import { ChevronDown, ChevronRight, Wrench } from "lucide-react";
 import { Badge } from "@/components/ui/badge";
+import { cn } from "@/lib/cva.config";
 import { ParsedTool } from "./types";
 import { ToolExpandedContent } from "./ToolExpandedContent";
 
@@ -16,34 +17,23 @@ export function ToolItem({ tool }: ToolItemProps) {
   const [expanded, setExpanded] = useState(false);
 
   return (
-    <div
-      style={{
-        border: "1px solid #f0f0f0",
-        borderRadius: 8,
-        overflow: "hidden",
-      }}
-    >
+    <div className="overflow-hidden rounded-lg border border-border">
       {/* Header Row - Always Visible */}
       <div
         onClick={() => setExpanded(!expanded)}
-        style={{
-          display: "flex",
-          alignItems: "center",
-          justifyContent: "space-between",
-          padding: "12px 16px",
-          cursor: "pointer",
-          background: expanded ? "#fafafa" : "#fff",
-          transition: "background 0.2s",
-        }}
+        className={cn(
+          "flex cursor-pointer items-center justify-between gap-3 px-4 py-3 text-card-foreground transition-colors",
+          expanded ? "bg-muted" : "bg-card",
+        )}
       >
-        <div style={{ display: "flex", alignItems: "center", gap: 10 }}>
+        <div className="flex items-center gap-2.5">
           <Wrench className="size-3.5 text-muted-foreground" />
-          <span style={{ fontSize: 14 }}>
+          <span className="text-sm">
             {tool.index}. {tool.name}
           </span>
         </div>
 
-        <div style={{ display: "flex", alignItems: "center", gap: 8 }}>
+        <div className="flex items-center gap-2">
           <Badge variant={tool.called ? "default" : "secondary"}>{tool.called ? "called" : "not called"}</Badge>
           {expanded ? (
             <ChevronDown className="size-3 text-muted-foreground" />
@@ -55,13 +45,7 @@ export function ToolItem({ tool }: ToolItemProps) {
 
       {/* Expanded Content */}
       {expanded && (
-        <div
-          style={{
-            padding: "16px",
-            borderTop: "1px solid #f0f0f0",
-            background: "#fff",
-          }}
-        >
+        <div className="border-t border-border bg-card p-4 text-card-foreground">
           <ToolExpandedContent tool={tool} />
         </div>
       )}
diff --git a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
index 2de1ac11db2..b5802ffa2dc 100644
--- a/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
+++ b/ui/litellm-dashboard/src/lib/autorouter_presets.test.ts
@@ -129,6 +129,18 @@ describe("autorouter_presets", () => {
     }
   });
 
+  it("carries a preset's modality_routing into the prefilled form state", () => {
+    const preset = getPresetByKey("anthropic_family")!;
+    const withFlag = { ...preset.complexity_router_config, modality_routing: true };
+    const prefill = buildPresetPrefill(withFlag, groupsOnly(getRequiredModelsInPreset(preset)));
+    expect(prefill.complexityRouterConfig.modality_routing).toBe(true);
+    const withoutFlag = buildPresetPrefill(
+      preset.complexity_router_config,
+      groupsOnly(getRequiredModelsInPreset(preset)),
+    );
+    expect(withoutFlag.complexityRouterConfig.modality_routing).toBe(false);
+  });
+
   it("prefills the anthropic preset's effort through to tier_model_params", () => {
     const preset = getPresetByKey("anthropic_family")!;
     const prefill = buildPresetPrefill(preset.complexity_router_config, groupsOnly(getRequiredModelsInPreset(preset)));
@@ -146,6 +158,24 @@ describe("autorouter_presets", () => {
     });
   });
 
+  it("pins the OpenAI preset to the Luna, Terra, and Sol progression", () => {
+    const preset = getPresetByKey("openai_family")!;
+    const expectedTiers = {
+      SIMPLE: ["gpt-5.6-luna"],
+      MEDIUM: ["gpt-5.6-terra"],
+      COMPLEX: ["gpt-5.6-sol"],
+      REASONING: ["gpt-5.6-sol"],
+    };
+    expect(preset.complexity_router_config.tiers).toEqual(expectedTiers);
+    expect(preset.complexity_router_config.tier_model_configs).toEqual({
+      REASONING: [{ model_name: "gpt-5.6-sol", litellm_params: { reasoning_effort: "xhigh" } }],
+    });
+    const prefill = buildPresetPrefill(preset.complexity_router_config, groupsOnly(getRequiredModelsInPreset(preset)));
+    expect(prefill.complexityRouterConfig.tier_model_params).toEqual({
+      REASONING: { "gpt-5.6-sol": { reasoning_effort: "xhigh" } },
+    });
+  });
+
   it("pins the gemini preset to concrete model ids, never Google's hot-swapping -latest aliases", () => {
     const gemini = getPresetByKey("gemini_family")!;
     const config = gemini.complexity_router_config;
@@ -230,6 +260,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: [presetModel], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -273,6 +304,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: ["claude-opus-5"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -287,6 +319,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: ["claude-opus-5"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -320,6 +353,7 @@ describe("autorouter_presets", () => {
     const simpleTierConfig = (presetModel: string) => ({
       tiers: { SIMPLE: [presetModel], MEDIUM: [], COMPLEX: [], REASONING: [] },
       classifier_type: "heuristic" as const,
+      classification_mode: "every_request" as const,
       session_affinity: false,
       deployment_affinity: true,
     });
@@ -563,6 +597,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
         match_threshold: 0,
@@ -573,11 +608,46 @@ describe("autorouter_presets", () => {
       expect(prefill.escalationKeywords).toEqual([]);
     });
 
+    it("carries a preset's context-window escalation opt-out and buffer through the prefill", () => {
+      const prefill = buildPresetPrefill(
+        {
+          tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] },
+          classifier_type: "heuristic",
+          classification_mode: "every_request",
+          session_affinity: false,
+          deployment_affinity: true,
+          enable_context_window_escalation: false,
+          context_window_escalation_buffer: 0.9,
+        },
+        groupsOnly(["gpt-5-nano"]),
+      );
+      expect(prefill.complexityRouterConfig.enable_context_window_escalation).toBe(false);
+      expect(prefill.complexityRouterConfig.context_window_escalation_buffer).toBe(0.9);
+    });
+
+    it("carries a preset's classification_mode and defaults it when the preset omits one", () => {
+      const tiers = { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] };
+      const base = {
+        tiers,
+        classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
+        session_affinity: false,
+        deployment_affinity: true,
+      };
+      const availability = groupsOnly(["gpt-5-nano"]);
+      expect(
+        buildPresetPrefill({ ...base, classification_mode: "user_turn" }, availability).complexityRouterConfig
+          .classification_mode,
+      ).toBe("user_turn");
+      expect(buildPresetPrefill(base, availability).complexityRouterConfig.classification_mode).toBe("every_request");
+    });
+
     it("falls back to the defaults when a preset omits match_threshold and escalation_keywords", () => {
       const prefill = buildPresetPrefill(
         {
           tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] },
           classifier_type: "heuristic",
+          classification_mode: "every_request" as const,
           session_affinity: false,
           deployment_affinity: true,
         },
@@ -594,6 +664,7 @@ describe("autorouter_presets", () => {
       const base = {
         tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -609,6 +680,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: ["claude-sonnet-4-5"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -623,6 +695,7 @@ describe("autorouter_presets", () => {
           REASONING: [{ model_name: "o3", litellm_params: { reasoning_effort: "high" } }],
         },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -642,6 +715,7 @@ describe("autorouter_presets", () => {
           REASONING: [{ model_name: "claude-sonnet-4-5", litellm_params: { reasoning_effort: "high" } }],
         },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
@@ -664,6 +738,9 @@ describe("autorouter_presets", () => {
           ],
         },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
+        session_affinity: false,
+        deployment_affinity: true,
       };
       const prefill = buildPresetPrefill(config, groupsOnly(["claude-sonnet-4.5"]));
       // temperature survives from the spelling that would otherwise have been overwritten;
@@ -677,6 +754,7 @@ describe("autorouter_presets", () => {
       const config = {
         tiers: { SIMPLE: ["gpt-5-nano"], MEDIUM: [], COMPLEX: [], REASONING: [] },
         classifier_type: "heuristic" as const,
+        classification_mode: "every_request" as const,
         session_affinity: false,
         deployment_affinity: true,
       };
diff --git a/ui/litellm-dashboard/src/lib/autorouter_presets.ts b/ui/litellm-dashboard/src/lib/autorouter_presets.ts
index a35b868db5e..721bd6f2b2a 100644
--- a/ui/litellm-dashboard/src/lib/autorouter_presets.ts
+++ b/ui/litellm-dashboard/src/lib/autorouter_presets.ts
@@ -6,6 +6,7 @@ import {
   ComplexityRouterConfigValue,
   ClassifierType,
   ClassifierLLMConfig,
+  DEFAULT_CLASSIFICATION_MODE,
   DEFAULT_SESSION_AFFINITY,
   DEFAULT_DEPLOYMENT_AFFINITY,
   usesLlmClassifier,
@@ -288,13 +289,17 @@ export const buildPresetPrefill = (
       classifier_context_budget_chars: config.classifier_context_budget_chars,
       classifier_context_per_turn_chars: config.classifier_context_per_turn_chars,
       classifier_context_include_assistant_turns: config.classifier_context_include_assistant_turns,
+      classification_mode: config.classification_mode ?? DEFAULT_CLASSIFICATION_MODE,
       session_affinity: config.session_affinity ?? DEFAULT_SESSION_AFFINITY,
       deployment_affinity: config.deployment_affinity ?? DEFAULT_DEPLOYMENT_AFFINITY,
+      modality_routing: config.modality_routing ?? false,
       adaptive: config.adaptive,
       adaptive_weights: config.adaptive_weights,
       tier_distance_penalty: config.tier_distance_penalty,
       adaptive_eligible: config.adaptive_eligible,
       return_raw_model_name: config.return_raw_model_name,
+      enable_context_window_escalation: config.enable_context_window_escalation,
+      context_window_escalation_buffer: config.context_window_escalation_buffer,
     },
     customTechnicalKeywords: config.custom_technical_keywords ?? [],
     keywordTierRules: hydrateKeywordTierRules(config.keyword_tier_rules ?? []),
diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index 137c67e837c..be81450b941 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -1234,8 +1234,8 @@ export interface paths {
         };
         /**
          * List Shadow Eval Jobs
-         * @description List shadow eval jobs, newest first, each key with its attempt count so status is
-         *     accurate. Judged counts, spend, and results ride the detail endpoint only.
+         * @description List shadow eval jobs, newest first, each target with its attempt count so status
+         *     is accurate. Judged counts, spend, and results ride the detail endpoint only.
          */
         get: operations["list_shadow_eval_jobs_auto_router_shadow_eval_get"];
         put?: never;
@@ -1257,22 +1257,29 @@ export interface paths {
         put?: never;
         /**
          * Start Shadow Eval
-         * @description Start a shadow eval: duplicate a sampled slice of one or more keys' live traffic against
-         *     a second arm, judge the two responses blind, and stratify win rates by tier, by the model
-         *     that served the real arm, and by key.
+         * @description Start a shadow eval: duplicate a sampled slice of one or more targets' live traffic
+         *     against a second arm, judge the two responses blind, and stratify win rates by tier,
+         *     by the model that served the real arm, and by target.
          *
-         *     A forward job answers whether the keys should adopt router_name: it samples the requests
-         *     the router did not serve and duplicates them through it. A reverse job answers whether a
-         *     key already on the router still gains from it: it samples the requests the router did
-         *     serve and duplicates them against baseline_model. A key can hold one active job per
-         *     direction, so both questions can run at once.
+         *     A target is a virtual key, a team, or a user. Team and user targets match on the
+         *     identity every request resolves to at auth time, so they cover JWT-authenticated
+         *     traffic, which presents no virtual key; a user target samples that user's traffic
+         *     across all their teams, whether it arrives on a JWT or a key they own.
          *
-         *     Shadow responses are never served to users. Each key samples until its recorded eval
-         *     spend, the shadow and judge calls' own cost, reaches max_budget dollars, the job's
-         *     window ends, or the job is stopped, so one key running out of budget does not end
-         *     sampling for the others; sampling changes propagate to pods within about 10 seconds.
-         *     Shadow and judge calls bill to the shadowed key but are excluded from request counts
-         *     and auto-router adoption metrics.
+         *     A forward job answers whether the targets should adopt router_name: it samples the
+         *     requests the router did not serve and duplicates them through it. A reverse job
+         *     answers whether a target already on the router still gains from it: it samples the
+         *     requests the router did serve and duplicates them against baseline_model. A target
+         *     can hold one active job per direction, so both questions can run at once, and a
+         *     request matching several jobs' targets (say its key and its team) is sampled by
+         *     each, separately budgeted.
+         *
+         *     Shadow responses are never served to users. Each target samples until its recorded
+         *     eval spend, the shadow and judge calls' own cost, reaches max_budget dollars, the
+         *     job's window ends, or the job is stopped, so one target running out of budget does
+         *     not end sampling for the others; sampling changes propagate to pods within about 10
+         *     seconds. Shadow and judge calls bill to the sampled request's own identity but are
+         *     excluded from request counts and auto-router adoption metrics.
          */
         post: operations["start_shadow_eval_auto_router_shadow_eval_start_post"];
         delete?: never;
@@ -1312,8 +1319,8 @@ export interface paths {
         put?: never;
         /**
          * Stop Shadow Eval Job
-         * @description Stop an active shadow eval job, every key it scopes at once. Attempts are kept;
-         *     sampling halts within ~10s. Keys that already stopped on their own budget keep the
+         * @description Stop an active shadow eval job, every target it scopes at once. Attempts are kept;
+         *     sampling halts within ~10s. Targets that already stopped on their own budget keep the
          *     stopped_at they earned. The statement is the whole state machine: it claims the job
          *     only while a leg still samples inside the window with no stop recorded, so a racing
          *     operator, a same-instant budget spend, and a repeat stop all read the same 400 with
@@ -5103,6 +5110,26 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/get/mcp_tool_search_settings": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /**
+         * Get Mcp Tool Search Settings
+         * @description Get the `litellm_settings.mcp_tool_search` configuration used by the native `mcp_tool_search` virtual tool.
+         */
+        get: operations["get_mcp_tool_search_settings_get_mcp_tool_search_settings_get"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/get/sso_settings": {
         parameters: {
             query?: never;
@@ -5258,6 +5285,42 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/gigachat/{endpoint}": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /**
+         * Gigachat Proxy Route
+         * @description [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+         */
+        get: operations["gigachat_proxy_route_gigachat__endpoint__get"];
+        /**
+         * Gigachat Proxy Route
+         * @description [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+         */
+        put: operations["gigachat_proxy_route_gigachat__endpoint__put"];
+        /**
+         * Gigachat Proxy Route
+         * @description [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+         */
+        post: operations["gigachat_proxy_route_gigachat__endpoint__post"];
+        /**
+         * Gigachat Proxy Route
+         * @description [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+         */
+        delete: operations["gigachat_proxy_route_gigachat__endpoint__delete"];
+        options?: never;
+        head?: never;
+        /**
+         * Gigachat Proxy Route
+         * @description [Docs](https://docs.litellm.ai/docs/pass_through/gigachat)
+         */
+        patch: operations["gigachat_proxy_route_gigachat__endpoint__patch"];
+        trace?: never;
+    };
     "/global/activity": {
         parameters: {
             query?: never;
@@ -7649,8 +7712,9 @@ export interface paths {
          * @description Retrieve information about a key.
          *
          *     Parameters:
-         *     - key: str | None (query parameter) - The key to look up. Accepts the plaintext key or its hash.
-         *       Defaults to the key in the Authorization header.
+         *     - key: str | None (query parameter) - The key to look up. Accepts the plaintext key or its hash;
+         *       prefer the hash, since a query parameter is recorded verbatim by any HTTP access log in front
+         *       of the proxy. Defaults to the key in the Authorization header.
          *
          *     Returns:
          *     - key: str - The key that was looked up, echoed back as it was passed in
@@ -7667,6 +7731,10 @@ export interface paths {
          *         - model_max_budget: dict - Per-model budgets, e.g. {"gpt-4": {"budget_limit": 0.0005, "time_period": "30d"}}
          *         - model_max_budget_usage: dict | None - Current-window spend per model, present only when
          *           the key has per-model budgets
+         *         - budget_limits: list | None - Concurrent budget windows, exactly as stored
+         *         - budget_limits_usage: dict | None - Current-window spend per budget window, e.g.
+         *           {"1h": {"current_spend": 0.0009}}, present only when the key has budget windows
+         *           (read from the same cross-pod spend counter the budget enforcement uses)
          *         - models: list - Model_name's the key is allowed to call
          *         - tpm_limit / rpm_limit: int | None - Tokens and requests per minute limits
          *         - metadata: dict - Metadata for the key, e.g. {"team": "core-infra"}
@@ -7678,7 +7746,7 @@ export interface paths {
          *
          *     Example Curl:
          *     ```
-         *     curl -X GET "http://0.0.0.0:4000/key/info?key=sk-test-example-key-123" -H "Authorization: Bearer sk-1234"
+         *     curl -X GET "http://0.0.0.0:4000/key/info?key=d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa" -H "Authorization: Bearer sk-1234"
          *     ```
          *
          *     Example Curl - if no key is passed, it will use the Key Passed in Authorization Header
@@ -9700,6 +9768,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/openai/v1/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_openai_v1_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/openai/v1/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -12619,6 +12718,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -13180,6 +13310,58 @@ export interface paths {
         patch: operations["patch_user_scim_v2_Users__user_id__patch"];
         trace?: never;
     };
+    "/scim/v2/placeholders": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /**
+         * List Placeholders
+         * @description List user rows whose id is another account's SSO identity or email.
+         *
+         *     An earlier release provisioned a group member it could not match as a user keyed
+         *     by the raw member value, and that row now shadows the account the value really
+         *     names, so every push of that member is refused. This lists those rows so an
+         *     operator can fold each one into the account it shadows with
+         *     ``POST /scim/v2/placeholders/{user_id}/merge``. A row that has an SSO identity of
+         *     its own or owns virtual keys is left out: someone uses that account.
+         */
+        get: operations["list_placeholders_scim_v2_placeholders_get"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
+    "/scim/v2/placeholders/{user_id}/merge": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Merge Placeholder
+         * @description Fold a placeholder user into the one account its id names by SSO identity or email.
+         *
+         *     The account is added to every team the placeholder is on, then the placeholder is
+         *     deleted the way ``DELETE /scim/v2/Users/{id}`` deletes a user, so the next group
+         *     push resolves the member value to the real account. Refused with 409 when the row
+         *     has an SSO identity of its own, owns virtual keys, or names no account or several.
+         */
+        post: operations["merge_placeholder_scim_v2_placeholders__user_id__merge_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/search": {
         parameters: {
             query?: never;
@@ -13860,7 +14042,7 @@ export interface paths {
          *
          *     Example Request for specific api_key
          *     ```
-         *     curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=sk-test-example-key-123" -H "Authorization: Bearer sk-1234"
+         *     curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa" -H "Authorization: Bearer sk-1234"
          *     ```
          *
          *     Example Request for specific user_id
@@ -15505,7 +15687,7 @@ export interface paths {
          *     Use this if if you want different teams to have different success/failure callbacks
          *
          *     Parameters:
-         *     - callback_name (Literal["langfuse", "langsmith", "gcs"], required): The name of the callback to add
+         *     - callback_name (str, required): The name of the callback to add, e.g. "langfuse", "langsmith", "gcs", "newrelic". The value is validated against the callbacks that support team-scoped credentials
          *     - callback_type (Literal["success", "failure", "success_and_failure"], required): The type of callback to add. One of:
          *         - "success": Callback for successful LLM calls
          *         - "failure": Callback for failed LLM calls
@@ -15521,6 +15703,8 @@ export interface paths {
          *         - langsmith_api_key: The API key for the Langsmith callback
          *         - langsmith_project: The project for the Langsmith callback
          *         - langsmith_base_url: The base URL for the Langsmith callback
+         *         - newrelic_api_key: The ingest license key for the team's New Relic account; routes both LLM/agent traces and cost metrics to that account. Requires the proxy to run with LITELLM_OTEL_V2=true, otherwise this callback is rejected with a 400
+         *         - newrelic_region: The New Relic region for the team's account ("us" or "eu"), riding the team's own key
          *
          *     Example curl:
          *     ```
@@ -15963,6 +16147,27 @@ export interface paths {
         patch: operations["update_mcp_semantic_filter_settings_update_mcp_semantic_filter_settings_patch"];
         trace?: never;
     };
+    "/update/mcp_tool_search_settings": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        /**
+         * Update Mcp Tool Search Settings
+         * @description Update `litellm_settings.mcp_tool_search` in the database.
+         *     Settings will be picked up by all pods within approximately 10 seconds via background polling.
+         */
+        patch: operations["update_mcp_tool_search_settings_update_mcp_tool_search_settings_patch"];
+        trace?: never;
+    };
     "/update/sso_settings": {
         parameters: {
             query?: never;
@@ -16210,6 +16415,11 @@ export interface paths {
          *
          *     Meant to optimize querying spend data for analytics for a user.
          *
+         *     Reads daily spend records that only ever accumulate and are never affected by budget
+         *     resets. Their total can legitimately exceed the `spend` field returned by
+         *     `/v2/user/info`, which is a running budget counter that every budget reset sets back
+         *     to zero (or to the overage above `max_budget` when `budget_rollover` is enabled).
+         *
          *     Returns:
          *     (by date)
          *     - spend
@@ -16241,6 +16451,11 @@ export interface paths {
          * Get User Daily Activity Aggregated
          * @description Aggregated analytics for a user's daily activity without pagination.
          *     Returns the same response shape as the paginated endpoint with page metadata set to single-page.
+         *
+         *     Reads daily spend records that only ever accumulate and are never affected by budget
+         *     resets. Their total can legitimately exceed the `spend` field returned by
+         *     `/v2/user/info`, which is a running budget counter that every budget reset sets back
+         *     to zero (or to the overage above `max_budget` when `budget_rollover` is enabled).
          */
         get: operations["get_user_daily_activity_aggregated_user_daily_activity_aggregated_get"];
         put?: never;
@@ -19182,6 +19397,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/v1/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_v1_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/v1/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -21004,6 +21250,14 @@ export interface paths {
          *     This is the v2 replacement for /user/info, designed to avoid the "god endpoint" problem
          *     where the old endpoint loaded all keys and teams into memory.
          *
+         *     Note on `spend`: this is the user's running budget counter, which the budget reset job
+         *     resets whenever `budget_reset_at` elapses (see `budget_duration`): to zero by default,
+         *     or to the overage above `max_budget` when `budget_rollover` is enabled. It is NOT
+         *     lifetime or per-period historical spend. For historical spend over a date range, use
+         *     `/user/daily/activity` or `/user/daily/activity/aggregated`, which read daily spend
+         *     records that only ever accumulate and are never reset. The two values are expected to
+         *     diverge once a budget reset has occurred within the queried period.
+         *
          *     Access control:
          *     - Proxy admins can query any user
          *     - Team admins can query users within their teams
@@ -22656,6 +22910,10 @@ export interface components {
             required: boolean;
             /** Tooltip */
             tooltip?: string | null;
+            /** Validation Message */
+            validation_message?: string | null;
+            /** Validation Pattern */
+            validation_pattern?: string | null;
         };
         /**
          * AgentExtension
@@ -22802,7 +23060,7 @@ export interface components {
          * @description Enum for alert types and management event types
          * @enum {string}
          */
-        AlertType: "llm_exceptions" | "llm_too_slow" | "llm_requests_hanging" | "budget_alerts" | "spend_reports" | "failed_tracking_spend" | "db_exceptions" | "daily_reports" | "cooldown_deployment" | "new_model_added" | "model_deprecation_warnings" | "outage_alerts" | "region_outage_alerts" | "fallback_reports" | "new_virtual_key_created" | "virtual_key_updated" | "virtual_key_deleted" | "new_team_created" | "team_updated" | "team_deleted" | "new_internal_user_created" | "internal_user_updated" | "internal_user_deleted";
+        AlertType: "llm_exceptions" | "llm_too_slow" | "llm_requests_hanging" | "budget_alerts" | "spend_reports" | "failed_tracking_spend" | "user_spend_thresholds" | "user_spend_anomalies" | "db_exceptions" | "daily_reports" | "cooldown_deployment" | "new_model_added" | "model_deprecation_warnings" | "outage_alerts" | "region_outage_alerts" | "fallback_reports" | "new_virtual_key_created" | "virtual_key_updated" | "virtual_key_deleted" | "new_team_created" | "team_updated" | "team_deleted" | "new_internal_user_created" | "internal_user_updated" | "internal_user_deleted";
         /** AllowedVectorStoreIndexItem */
         AllowedVectorStoreIndexItem: {
             /** Index Name */
@@ -25182,7 +25440,7 @@ export interface components {
             alert_types?: components["schemas"]["AlertType"][] | null;
             /**
              * Alerting
-             * @description List of alerting integrations. Today, just slack - `alerting: ['slack']`
+             * @description List of alerting integrations - e.g. `alerting: ['slack', 'webhook', 'email']`. 'slack' posts Slack-format messages to any Slack-compatible webhook (Slack, Rocket.Chat, Mattermost); 'webhook' posts structured JSON budget alerts to WEBHOOK_URL
              */
             alerting?: unknown[] | null;
             /**
@@ -25222,6 +25480,11 @@ export interface components {
              * @description run health checks in background
              */
             background_health_checks?: boolean | null;
+            /**
+             * Blocked File Extensions
+             * @description file extensions (e.g. ['.exe', '.sh']) rejected on /v1/files uploads, for any purpose, matched case-insensitively against the uploaded filename
+             */
+            blocked_file_extensions?: string[] | null;
             /**
              * Cancel On Disconnect
              * @description cancel the in-flight upstream LLM request (non-streaming) when the client disconnects, freeing backend capacity (e.g. a vLLM GPU slot); the request is logged as a 499 failure
@@ -25275,9 +25538,15 @@ export interface components {
             database_extra_connection_params?: {
                 [key: string]: unknown;
             } | null;
+            /**
+             * Database Max Idle Connection Lifetime
+             * @description Prisma `max_idle_connection_lifetime` URL param (seconds). A pooled connection idle longer than this is closed and replaced instead of being handed to the next request. Defaults to 60 so connections are recycled before common infra idle timeouts (AWS NLB / RDS Proxy ~350s, many LBs 60-350s) silently drop them and requests fail with `Error { kind: Closed }`. A value pinned on the DATABASE_URL or set via `database_extra_connection_params` takes precedence.
+             * @default 60
+             */
+            database_max_idle_connection_lifetime: number | null;
             /**
              * Database Socket Timeout
-             * @description Prisma `socket_timeout` URL param (seconds). When set, an idle/slow connection that has not produced data within this window is closed. This is the main knob for capping idle DB connections from LiteLLM.
+             * @description Prisma `socket_timeout` URL param (seconds). When set, an in-flight operation that has not produced data within this window is aborted. For capping how long idle pooled connections are kept, see `database_max_idle_connection_lifetime`.
              */
             database_socket_timeout?: number | null;
             /**
@@ -25300,6 +25569,11 @@ export interface components {
              * @description If True, disables the optimistic per-request budget reservation introduced in v1.84.0. WARNING: This weakens hard budget enforcement. Without the reservation, a burst of concurrent requests from a single key can each pass the read-time spend check before any of them is charged, allowing a configured budget to be exceeded under high concurrency. Budgets are still evaluated on every request at read time, so an already-exhausted budget is still rejected. Enable only if your deployment is experiencing phantom BudgetExceededError responses caused by leaked reservations (see GitHub issue #27639). A proxy-level WARNING is logged on every request while this flag is active as a reminder that hard enforcement is relaxed.
              */
             disable_budget_reservation?: boolean | null;
+            /**
+             * Disable Password Login When Sso Enabled
+             * @description If True and SSO is configured (MICROSOFT_CLIENT_ID, GOOGLE_CLIENT_ID, GENERIC_CLIENT_ID, or SAML_IDP_METADATA_URL/XML), disables username/password login on /login, /v2/login, and /v3/login so SSO is the only way to reach the Admin UI. An admin locked out of the UI can still administer the proxy over the API with the master key; unset this setting and restart the proxy to restore UI username/password login. Default is False.
+             */
+            disable_password_login_when_sso_enabled?: boolean | null;
             /**
              * Enable Public Model Hub
              * @description Public model hub for users to see what models they have access to, supported openai params, etc.
@@ -25355,6 +25629,11 @@ export interface components {
              * @description max batch input file size in MB for /v1/files uploads with purpose=batch, if a file is larger than this size it will be rejected before being forwarded to the provider
              */
             max_batch_file_size_mb?: number | null;
+            /**
+             * Max File Size Mb
+             * @description max file size in MB for /v1/files uploads, for any purpose, if a file is larger than this size it will be rejected before being forwarded to the provider
+             */
+            max_file_size_mb?: number | null;
             /**
              * Max Parallel Requests
              * @description maximum parallel requests for each api key
@@ -25445,6 +25724,31 @@ export interface components {
              * @description Default upstream request timeout in seconds for native and custom pass-through endpoints that use pass_through_request. Defaults to 600 when unset.
              */
             pass_through_request_timeout?: number | null;
+            /**
+             * Password Policy Min Length
+             * @description Minimum length required for a locally-managed user's password. Default is 12; a value below 8 is floored to 8 rather than weakening the requirement further.
+             */
+            password_policy_min_length?: number | null;
+            /**
+             * Password Policy Require Lowercase
+             * @description If True (default), a locally-managed user's password must contain a lowercase letter.
+             */
+            password_policy_require_lowercase?: boolean | null;
+            /**
+             * Password Policy Require Numbers
+             * @description If True (default), a locally-managed user's password must contain a number.
+             */
+            password_policy_require_numbers?: boolean | null;
+            /**
+             * Password Policy Require Special Characters
+             * @description If True (default), a locally-managed user's password must contain a special (non-alphanumeric) character.
+             */
+            password_policy_require_special_characters?: boolean | null;
+            /**
+             * Password Policy Require Uppercase
+             * @description If True (default), a locally-managed user's password must contain an uppercase letter.
+             */
+            password_policy_require_uppercase?: boolean | null;
             /**
              * Plugins
              * @description external services registered as embeddable UI plugins
@@ -29018,6 +29322,8 @@ export interface components {
             regional_processing_uplift_multiplier_us?: number | null;
             /** Rpm */
             rpm?: number | null;
+            /** Rust */
+            rust?: boolean | null;
             /** S3 Bucket Name */
             s3_bucket_name?: string | null;
             /** S3 Encryption Key Id */
@@ -30851,6 +31157,49 @@ export interface components {
             /** Total */
             total: number;
         };
+        /**
+         * MCPToolSearchSettings
+         * @description `litellm_settings.mcp_tool_search`: how the native `mcp_tool_search` virtual tool ranks the caller's tools.
+         */
+        MCPToolSearchSettings: {
+            /**
+             * Core Tools
+             * @description Tool names always returned first when the caller can access them, e.g. `my_server-get_rates`.
+             * @default []
+             */
+            core_tools: string[];
+            /**
+             * Embedding Model
+             * @description Embedding model from model_list used to rank tools by meaning. Unset keeps keyword matching.
+             */
+            embedding_model?: string | null;
+            /**
+             * Similarity Threshold
+             * @description Lowest cosine similarity a tool needs to appear in semantic results (0.0 = no cutoff).
+             * @default 0
+             */
+            similarity_threshold: number;
+            /**
+             * Top K
+             * @description Most ranked tools a search returns. A smaller top_k in the tool call wins. Core tools do not count.
+             * @default 5
+             */
+            top_k: number;
+        };
+        /**
+         * MCPToolSearchSettingsResponse
+         * @description Response model for native MCP tool search settings
+         */
+        MCPToolSearchSettingsResponse: {
+            /** Field Schema */
+            field_schema: {
+                [key: string]: unknown;
+            };
+            /** Values */
+            values: {
+                [key: string]: unknown;
+            };
+        };
         /** MCPToolsetTool */
         MCPToolsetTool: {
             /** Server Id */
@@ -34169,6 +34518,13 @@ export interface components {
             adaptive_eligible: "all" | "classified_tier";
             /** @description Quality vs cost weights for adaptive selection (used when adaptive=True) */
             adaptive_weights?: components["schemas"]["AdaptiveRouterWeights"];
+            /**
+             * Classification Mode
+             * @description When to run the complexity classifier. 'every_request' (the default) classifies every inference request, including the tool-result continuation turns of an agentic loop. 'user_turn' classifies only requests whose newest turn is a new human ask and replays the session's held routing decision on continuation turns, which cuts classifier spend and eliminates mid-loop model switches. Continuations with no held decision to replay (no resolvable session_id, expired pin, fresh restart) still classify. Unlike session_affinity, a new human ask always re-classifies, so a session can still move tiers between asks. Suppressed when plugins are configured, for the same reason session_affinity is: a replayed decision would bypass the plugin pipeline.
+             * @default every_request
+             * @enum {string}
+             */
+            classification_mode: "every_request" | "user_turn";
             /**
              * Classification Prompt
              * @description Replaces the opening instructions of the LLM classifier rubric (the judging-criteria prose) for a custom tier set. The per-tier bullets and the trust-boundary paragraph telling the classifier to ignore tier requests embedded in quoted caller text are always appended after it and cannot be overridden. Requires tier_definitions; a built-in-tier router customizes its prompt via classifier_llm_config.system_prompt or classification_rubric instead.
@@ -34204,7 +34560,7 @@ export interface components {
              * @enum {string}
              */
             classifier_fallback: "heuristic" | "default_model";
-            /** @description Configuration for the LLM classifier; required when classifier_type is 'llm' or 'heuristic_first' */
+            /** @description Configuration for the LLM classifier; required when classifier_type is 'llm', 'heuristic_first' or 'hybrid' */
             classifier_llm_config?: components["schemas"]["ClassifierLLMConfig"] | null;
             /**
              * Classifier Plugin
@@ -34219,16 +34575,22 @@ export interface components {
             classifier_plugin_timeout_ms: number;
             /**
              * Classifier Type
-             * @description Classification strategy: local regex/keyword scoring, an LLM call, a custom classifier plugin, or 'heuristic_first', which scores locally and only pays for the LLM classifier when the local scorer does not confidently land a cheap tier
+             * @description Classification strategy: local regex/keyword scoring, the bundled trained four-tier heuristic, an LLM call, a custom classifier plugin, 'heuristic_first', which scores locally and only pays for the LLM classifier when the local scorer does not confidently land a cheap tier, or 'hybrid', which trusts the local scorer everywhere except when its score lands near a tier boundary
              * @default heuristic
              * @enum {string}
              */
-            classifier_type: "heuristic" | "llm" | "custom" | "heuristic_first";
+            classifier_type: "heuristic" | "heuristic_v2" | "llm" | "custom" | "heuristic_first" | "hybrid";
             /**
              * Code Keywords
              * @description Keywords indicating code-related content
              */
             code_keywords?: string[] | null;
+            /**
+             * Context Window Escalation Buffer
+             * @description Fraction of a model's declared context window the estimated prompt must fit within. The token count is an estimate, so fitting against the full window would dispatch prompts that the provider's own tokenizer then rejects; 0.95 leaves room for that drift plus the response tokens.
+             * @default 0.95
+             */
+            context_window_escalation_buffer: number;
             /**
              * Custom Technical Keywords
              * @description Domain-specific technical keywords appended to the effective base list (technical_keywords if set, otherwise DEFAULT_TECHNICAL_KEYWORDS). Order is preserved; duplicates are removed case-insensitively against the base list and within this list.
@@ -34257,6 +34619,12 @@ export interface components {
              * @description Embedding model (LiteLLM model name) used when semantic_keyword_matching is enabled
              */
             embedding_model?: string | null;
+            /**
+             * Enable Context Window Escalation
+             * @description Escalate a request off a tier whose models provably cannot hold its prompt, before dispatch. The classifier scores complexity and never prompt size, so a long agentic session whose newest ask is trivial lands on a small-window tier and the provider rejects it with a context-window 400 that nothing retries. When every model of the decided tier has a declared window smaller than the estimated prompt, the request moves to the lowest configured tier with a model whose declared window fits; when only some of the tier's models fit, the pick is restricted to those and the tier keeps the request. Models with no resolvable window are never escalated away from and never escalated onto. Set false to dispatch on complexity alone, as before.
+             * @default true
+             */
+            enable_context_window_escalation: boolean;
             /**
              * Escalation Keywords
              * @description Case-sensitive phrases a user can include to force a bump to the next-higher complexity tier when they aren't satisfied with results (they can force a stronger model, but not choose which one). Defaults to ['LITELLM ESCALATE'] when unset; set to an empty list to disable.
@@ -34272,11 +34640,22 @@ export interface components {
              * @description The highest tier the local scorer may decide on its own; required when classifier_type is 'heuristic_first' and rejected otherwise. A request whose heuristic tier is at or below this one skips the LLM classifier and routes straight to that heuristic tier, so the classifier call is only paid for on traffic the scorer could not place cheaply. The scorer must also have produced at least one signal: a prompt where no dimension fired scores 0.0 and would otherwise land SIMPLE by default rather than by evidence, which is how a chained router would silently send unclassified traffic to the cheapest model. Names a built-in tier, and may not name the highest one, since that would make the LLM classifier unreachable.
              */
             heuristic_first_max_tier?: string | null;
+            /**
+             * Heuristic V2 Artifact
+             * @description Success-probability artifact used by classifier_type 'heuristic_v2'. The bundled UltraFeedback artifact is selected by default; an inline trained artifact may replace it
+             * @default ultrafeedback
+             */
+            heuristic_v2_artifact: components["schemas"]["TrainedTierArtifact"] | "ultrafeedback";
             /**
              * Housekeeping Patterns
              * @description Additional case-sensitive literal sentinels that mark a request as client housekeeping, on top of the built-in conversation-title ones. For clients whose wording the built-ins don't cover, or after a client release changes its strings.
              */
             housekeeping_patterns?: string[] | null;
+            /**
+             * Hybrid Boundary Margin
+             * @description How close to a tier boundary a heuristic score has to land before the LLM classifier breaks the tie; required when classifier_type is 'hybrid' and rejected otherwise. Everything further than this from every active boundary routes on the scorer's own tier with no classifier call, at any tier, which is what separates 'hybrid' from 'heuristic_first' and its cheap-tier ceiling. A prompt where no dimension fired still goes to the classifier, since the scorer has no opinion to be near a boundary with. 0 escalates only scores sitting exactly on a boundary.
+             */
+            hybrid_boundary_margin?: number | null;
             /**
              * Keyword Tier Rules
              * @description Rules that force a specific tier when their keywords match the prompt
@@ -34288,6 +34667,12 @@ export interface components {
              * @default 0.5
              */
             match_threshold: number;
+            /**
+             * Modality Routing
+             * @description Route image-bearing requests only to models that can accept image input. The classifier reads text alone, so an image request whose text classifies cheap otherwise lands on a text-only model and fails with a provider 400. When enabled, a routed model explicitly declared supports_vision false (deployment model_info or the model cost map; unmapped names stay routable) is replaced by the nearest HIGHER tier holding a capable model, then default_model, else a clear 400. A kept session-affinity pin still wins even when an image arrives.
+             * @default false
+             */
+            modality_routing: boolean;
             /**
              * Plan Mode Min Tier
              * @description When set, requests carrying a coding-agent plan-mode sentinel (Claude Code plan mode, VS Code Copilot Plan mode, Copilot CLI's exit_plan_mode tool) are routed to at least this tier: the classified tier still wins when it is higher, and the floor also overrides a session-affinity pin to a lower tier for exactly the turns carrying the sentinel, without rewriting the pin -- the first turn after plan mode exits routes as if plan mode had never happened. Names a built-in tier, or with tier_definitions set, one of the defined tier names (list order is ascending severity, same as keyword_tier_rules). Unset disables detection entirely. The sentinels ride in client-injected prompt text, so a caller who pastes one can spend up to this tier's models -- never down, and never outside the configured pools.
@@ -34404,6 +34789,12 @@ export interface components {
         } & {
             [key: string]: unknown;
         };
+        /**
+         * RequestType
+         * @description Fixed v0 taxonomy. User-extensible types come in v1.
+         * @enum {string}
+         */
+        RequestType: "code_generation" | "code_understanding" | "technical_design" | "analytical_reasoning" | "writing" | "factual_lookup" | "general";
         /** ResetSpendRequest */
         ResetSpendRequest: {
             /** Reset To */
@@ -34736,6 +35127,27 @@ export interface components {
             /** Value */
             value?: unknown | null;
         };
+        /**
+         * SCIMPlaceholder
+         * @description A user row keyed by a value that names another account by SSO identity or email.
+         */
+        SCIMPlaceholder: {
+            /** Placeholder User Id */
+            placeholder_user_id: string;
+            /** Resolved User Ids */
+            resolved_user_ids: string[];
+            /** Team Ids */
+            team_ids: string[];
+        };
+        /** SCIMPlaceholderMergeResult */
+        SCIMPlaceholderMergeResult: {
+            /** Merged Into User Id */
+            merged_into_user_id: string;
+            /** Placeholder User Id */
+            placeholder_user_id: string;
+            /** Team Ids */
+            team_ids: string[];
+        };
         /** SCIMServiceProviderConfig */
         SCIMServiceProviderConfig: {
             /** Authenticationschemes */
@@ -35094,56 +35506,10 @@ export interface components {
             /** Timeout */
             timeout?: number | null;
         };
-        /**
-         * ShadowEvalJobKeyResponse
-         * @description One key a job shadows, with its own budget and stop state.
-         */
-        ShadowEvalJobKeyResponse: {
-            /**
-             * Api Key Id
-             * @description The hashed virtual key whose traffic this entry scopes
-             */
-            api_key_id: string;
-            /**
-             * Attempt Count
-             * @description This key's sampled attempts so far, judged and errored alike, the same count the sampler budgets against max_turns; populated on list and detail responses. Frozen at stopped_at once the key is stamped, so in-flight attempts landing after a stop never reclassify it
-             */
-            attempt_count?: number | null;
-            /**
-             * Key Alias
-             * @description Alias of the shadowed key, resolved from the key row at read time; None when unset or deleted
-             */
-            key_alias?: string | null;
-            /**
-             * Key Name
-             * @description Masked display name (sk-...) of the shadowed key, resolved at read time like key_alias
-             */
-            key_name?: string | null;
-            /**
-             * Max Budget
-             * @description This key's own USD budget for the eval's shadow and judge spend, independent of its siblings'; None on jobs created before spend budgets existed, which max_turns alone bounds
-             */
-            max_budget?: number | null;
-            /**
-             * Max Turns
-             * @description This key's sample-count ceiling: the whole budget for jobs created before max_budget existed, and the error-loop safety valve otherwise
-             */
-            max_turns: number;
-            /**
-             * Spend
-             * @description This key's recorded shadow plus judge spend in USD, the same figure the sampler budgets against max_budget; populated on list and detail responses and frozen at stopped_at exactly like attempt_count
-             */
-            spend?: number | null;
-            /**
-             * Stopped At
-             * @description When this key's slot was stamped free, whether its own budget ran out, the window closed, or an operator stopped the job; status is derived, so a spent budget reads completed even while this is still unset
-             */
-            stopped_at?: string | null;
-        };
         /**
          * ShadowEvalJobResponse
-         * @description A shadow-eval job over one or more keys, each with its own budget and stop state;
-         *     status is derived from stopped_by, the keys' stop and budget state, and ends_at,
+         * @description A shadow-eval job over one or more targets, each with its own budget and stop state;
+         *     status is derived from stopped_by, the targets' stop and budget state, and ends_at,
          *     never stored, so no writer anywhere can produce an inconsistent one. Aggregate
          *     fields are populated by the detail endpoint only and stay None on list responses.
          */
@@ -35185,11 +35551,6 @@ export interface components {
              * @description Verdicts recorded; detail endpoint only
              */
             judged_count?: number | null;
-            /**
-             * Keys
-             * @description The keys whose traffic this job evaluates, and only those keys', each with its own budget
-             */
-            keys: components["schemas"]["ShadowEvalJobKeyResponse"][];
             /**
              * Last Error
              * @description Most recent attempt error; detail endpoint only
@@ -35197,16 +35558,25 @@ export interface components {
             last_error?: string | null;
             /** @description Stratified verdicts; detail endpoint only */
             results?: components["schemas"]["ShadowEvalResult"] | null;
-            /** Router Name */
-            router_name: string;
+            /**
+             * Router Name
+             * @description The first router, kept for callers that predate router_names; derived so the
+             *     two fields can never disagree.
+             */
+            readonly router_name: string;
+            /**
+             * Router Names
+             * @description Every auto-router this job runs as a shadow arm. Multi-router jobs sample one slice of traffic and judge every arm against the same real responses
+             */
+            router_names: string[];
             /** Shadow Percentage */
             shadow_percentage: number;
             /**
              * Status
              * @description Three recorded facts, no history-guessing: a stop is stopped_by (the migration
              *     backfills it for every job that displayed stopped when the column arrived, so the
-             *     pre-column population is closed), completion is the window passing or every key
-             *     spending its budget, and anything else is running. The all-keys-stamped fallback
+             *     pre-column population is closed), completion is the window passing or every target
+             *     spending its budget, and anything else is running. The all-targets-stamped fallback
              *     covers only stops written by pre-column pods during a rolling deploy.
              * @enum {string}
              */
@@ -35216,6 +35586,65 @@ export interface components {
              * @description The operator who stopped the job early, recorded by the stop endpoint; 'unknown' backfilled by migration for jobs that displayed stopped when the column arrived; None when the job ended on its own. Its presence is what makes a job read stopped rather than completed
              */
             stopped_by?: string | null;
+            /**
+             * Targets
+             * @description The targets whose traffic this job evaluates, and only theirs, each with its own budget
+             */
+            targets: components["schemas"]["ShadowEvalJobTargetResponse"][];
+        };
+        /**
+         * ShadowEvalJobTargetResponse
+         * @description One target a job shadows (a key, team, or user), with its own budget and stop state.
+         */
+        ShadowEvalJobTargetResponse: {
+            /**
+             * Attempt Count
+             * @description This target's sampled attempts so far, judged and errored alike, the same count the sampler budgets against max_turns; populated on list and detail responses. Frozen at stopped_at once the target is stamped, so in-flight attempts landing after a stop never reclassify it
+             */
+            attempt_count?: number | null;
+            /**
+             * Key Name
+             * @description Masked display name (sk-...) for key targets, resolved at read time; None for teams and users
+             */
+            key_name?: string | null;
+            /**
+             * Max Budget
+             * @description This target's own USD budget for the eval's shadow and judge spend, independent of its siblings'; None on jobs created before spend budgets existed, which max_turns alone bounds
+             */
+            max_budget?: number | null;
+            /**
+             * Max Turns
+             * @description This target's sample-count ceiling: the whole budget for jobs created before max_budget existed, and the error-loop safety valve otherwise
+             */
+            max_turns: number;
+            /**
+             * Spend
+             * @description This target's recorded shadow plus judge spend in USD, the same figure the sampler budgets against max_budget; populated on list and detail responses and frozen at stopped_at exactly like attempt_count
+             */
+            spend?: number | null;
+            /**
+             * Stopped At
+             * @description When this target's slot was stamped free, whether its own budget ran out, the window closed, or an operator stopped the job; status is derived, so a spent budget reads completed even while this is still unset
+             */
+            stopped_at?: string | null;
+            /**
+             * Target Alias
+             * @description Display label resolved from the target's own row at read time: the key's alias, the team's alias, or the user's email; None when unset or deleted
+             */
+            target_alias?: string | null;
+            /**
+             * Target Id
+             * @description The hashed virtual key, team id, or user id whose traffic this entry scopes
+             */
+            target_id: string;
+            /**
+             * Target Type
+             * @description What kind of entity this entry scopes
+             * @enum {string}
+             */
+            target_type: "key" | "team" | "user";
+            /** @description This target's own judged-verdict slice; detail endpoint only, None until a turn is judged */
+            verdicts?: components["schemas"]["ShadowEvalSlice"] | null;
         };
         /**
          * ShadowEvalResult
@@ -35228,10 +35657,11 @@ export interface components {
              */
             by_current_model: components["schemas"]["ShadowEvalSlice"][];
             /**
-             * By Key
-             * @description One slice per scoped key that has judged verdicts, grouped on the raw key hash. Keys the job scopes but has not judged a turn for yet are absent rather than reported as zero
+             * By Router
+             * @description One slice per router arm, grouped on the router name. Every arm of a multi-router job is judged against the same real responses over the same sampled requests, so these slices compare routers head-to-head: like-for-like win rates and spends on identical traffic. Verdicts from before arm stamping existed count toward the job's own router
+             * @default []
              */
-            by_key: components["schemas"]["ShadowEvalSlice"][];
+            by_router: components["schemas"]["ShadowEvalSlice"][];
             /** By Tier */
             by_tier: components["schemas"]["ShadowEvalSlice"][];
             /**
@@ -35245,13 +35675,13 @@ export interface components {
             overall_tie_rate_pct: number;
             /**
              * Sampled Real Spend
-             * @description USD the real arm billed across all judged turns, cache-served turns excluded
+             * @description USD the real arm billed across all judged turns, cache-served turns excluded. A judged turn is one (request, router arm) verdict, so a multi-router job counts the real response once per arm it was judged against; per-router comparisons read by_router
              * @default 0
              */
             sampled_real_spend: number;
             /**
              * Sampled Shadow Spend
-             * @description USD the shadow arm billed across the same turns, judge excluded, like for like
+             * @description USD the shadow arms billed across the same turns, judge excluded, like for like
              * @default 0
              */
             sampled_shadow_spend: number;
@@ -35273,8 +35703,9 @@ export interface components {
         };
         /**
          * ShadowEvalSlice
-         * @description Judge outcomes for one slice of a job's verdicts (a router tier, or one of the
-         *     models that served the real arm).
+         * @description Judge outcomes for one slice of a job's verdicts: a router tier, one of the
+         *     models that served the real arm, or one scoped target (embedded on that target's
+         *     own entry, so slices never need re-joining to a target by id).
          */
         ShadowEvalSlice: {
             /** Avg Judge Confidence */
@@ -35441,11 +35872,15 @@ export interface components {
              * Cause
              * @enum {string}
              */
-            cause?: "heuristic_scorer" | "reasoning_override" | "llm_classifier" | "heuristic_first_short_circuit" | "classifier_plugin" | "classifier_fallback" | "default_model_fallback" | "literal_keyword_match" | "semantic_keyword_match" | "plan_mode" | "housekeeping" | "session_affinity_pin" | "session_affinity_escalation" | "default_fallback" | "keyword" | "quality_tier" | "bandit";
+            cause?: "heuristic_scorer" | "heuristic_v2" | "reasoning_override" | "llm_classifier" | "heuristic_first_short_circuit" | "hybrid_short_circuit" | "classifier_plugin" | "classifier_fallback" | "default_model_fallback" | "literal_keyword_match" | "semantic_keyword_match" | "plan_mode" | "housekeeping" | "modality_escalation" | "session_affinity_pin" | "session_affinity_escalation" | "user_turn_continuation" | "default_fallback" | "keyword" | "quality_tier" | "bandit";
             /** Classifier Cost */
             classifier_cost?: number;
             /** Classifier Model */
             classifier_model?: string;
+            /** Context Escalated */
+            context_escalated?: boolean;
+            /** Context Escalation Original Tier */
+            context_escalation_original_tier?: string;
             /** Conversation Continuing */
             conversation_continuing?: boolean;
             /** Escalated */
@@ -35500,12 +35935,18 @@ export interface components {
         };
         /**
          * StartShadowEvalRequest
-         * @description Start duplicating one or more keys' traffic for blind comparison against an auto-router.
+         * @description Start duplicating one or more targets' traffic for blind comparison against an auto-router.
+         *
+         *     A target is a virtual key, a team, or a user; each becomes its own leg with its own
+         *     budget and stop state. Team and user targets match on the identity every request
+         *     carries after auth (user_api_key_team_id / user_api_key_user_id), so they cover
+         *     JWT-authenticated traffic, which presents no virtual key at all.
          */
         StartShadowEvalRequest: {
             /**
              * Api Key Ids
-             * @description The hashed virtual keys whose traffic will be shadowed. Shadow evaluation runs ONLY on these keys' traffic; requests made with any other key are not sampled. Each key carries its own max_budget spend budget, so one key exhausting its budget leaves the others sampling. At most 100 keys per job, which also bounds every read the job's endpoints make.
+             * @description Hashed virtual keys whose traffic will be shadowed. Combined with team_ids and user_ids the job needs at least one target and at most 100, which also bounds every read the job's endpoints make. Each target carries its own max_budget spend budget, so one exhausting its budget leaves the others sampling.
+             * @default []
              */
             api_key_ids: string[];
             /**
@@ -35534,20 +35975,38 @@ export interface components {
             judge_model: string;
             /**
              * Max Budget
-             * @description Per-key USD budget for the eval's own overhead, the shadow-arm and judge calls, priced with the same figures the spend pipeline bills. EACH scoped key samples until its recorded eval spend reaches this, so a job over N keys spends at most about N times max_budget; in-flight samples can overshoot the cap by one sampling cache window
+             * @description Per-target USD budget for the eval's own overhead, the shadow-arm and judge calls, priced with the same figures the spend pipeline bills. EACH scoped target samples until its recorded eval spend reaches this, so a job over N targets spends at most about N times max_budget; in-flight samples can overshoot the cap by one sampling cache window. Every router arm draws from the same per-target budget, so a multi-router job reaches it proportionally sooner
              * @default 10
              */
             max_budget: number;
             /**
              * Router Name
-             * @description The auto-router under evaluation, in either direction
+             * @description The auto-router under evaluation, in either direction: the single-router spelling of router_names. Provide exactly one of the two fields
              */
-            router_name: string;
+            router_name?: string | null;
+            /**
+             * Router Names
+             * @description The auto-routers under evaluation, at most 4. Every sampled request runs through every router listed and each arm is judged independently against the same real response, so routers compare head-to-head on identical traffic. More than one router requires direction 'forward'. After validation this field always carries the full deduplicated set, whichever spelling the caller used
+             * @default []
+             */
+            router_names: string[];
             /**
              * Shadow Percentage
-             * @description Percentage of the key's requests to duplicate through the router
+             * @description Percentage of each target's requests to duplicate through the router
              */
             shadow_percentage: number;
+            /**
+             * Team Ids
+             * @description Teams whose traffic will be shadowed, matched on the team every authenticated request resolves to, so a team's JWT-auth and virtual-key traffic are both sampled
+             * @default []
+             */
+            team_ids: string[];
+            /**
+             * User Ids
+             * @description Users whose traffic will be shadowed, matched on the user every authenticated request resolves to across all their teams: JWT requests carrying their subject claim and virtual keys they own
+             * @default []
+             */
+            user_ids: string[];
         };
         /**
          * SuccessfulKeyUpdate
@@ -36296,6 +36755,33 @@ export interface components {
                 [key: string]: unknown;
             };
         };
+        /** TierCohortStatistic */
+        TierCohortStatistic: {
+            /** Cohort */
+            cohort: string;
+            /** Observations */
+            observations: number;
+            /** Successes */
+            successes: number;
+            /** Tier */
+            tier: number;
+        };
+        /** TierDataset */
+        TierDataset: {
+            /** License */
+            license: string;
+            /** Name */
+            name: string;
+            /** Rows */
+            rows: number;
+            /**
+             * Success Definition
+             * @default quality score meets the dataset success threshold
+             */
+            success_definition: string;
+            /** Url */
+            url: string;
+        };
         /**
          * TierDefinition
          * @description An operator-defined tier: the name the LLM classifier must return and its rubric description.
@@ -36312,6 +36798,25 @@ export interface components {
              */
             name: string;
         };
+        /** TierDomainStatistic */
+        TierDomainStatistic: {
+            /** Observations */
+            observations: number;
+            request_type: components["schemas"]["RequestType"];
+            /** Successes */
+            successes: number;
+            /** Tier */
+            tier: number;
+        };
+        /** TierGlobalStatistic */
+        TierGlobalStatistic: {
+            /** Observations */
+            observations: number;
+            /** Successes */
+            successes: number;
+            /** Tier */
+            tier: number;
+        };
         /**
          * TokenCountDetailsResponse
          * @description Response structure for token count details with modality breakdown.
@@ -36581,6 +37086,57 @@ export interface components {
         } & {
             [key: string]: unknown;
         };
+        /** TrainedTierArtifact */
+        TrainedTierArtifact: {
+            /**
+             * Cohort Prior Mass
+             * @default 20
+             */
+            cohort_prior_mass: number;
+            /**
+             * Cohort Statistics
+             * @default []
+             */
+            cohort_statistics: components["schemas"]["TierCohortStatistic"][];
+            /**
+             * Datasets
+             * @default []
+             */
+            datasets: components["schemas"]["TierDataset"][];
+            /**
+             * Domain Prior Mass
+             * @default 200
+             */
+            domain_prior_mass: number;
+            /**
+             * Domain Statistics
+             * @default []
+             */
+            domain_statistics: components["schemas"]["TierDomainStatistic"][];
+            /** Global Statistics */
+            global_statistics: components["schemas"]["TierGlobalStatistic"][];
+            /**
+             * Routing Threshold
+             * @default 0.75
+             */
+            routing_threshold: number;
+            /**
+             * Schema Version
+             * @default 1
+             * @constant
+             */
+            schema_version: 1;
+            /**
+             * Split Method
+             * @default sha256(prompt): 70% train, 15% validation, 15% test
+             */
+            split_method: string;
+            /**
+             * Success Definition
+             * @default quality score meets the dataset success threshold
+             */
+            success_definition: string;
+        };
         /** TransformRequestBody */
         TransformRequestBody: {
             call_type: components["schemas"]["CallTypes"];
@@ -37162,6 +37718,8 @@ export interface components {
             } | null;
             /** Num Retries */
             num_retries?: number | null;
+            /** Optional Pre Call Checks */
+            optional_pre_call_checks?: ("prompt_caching" | "router_budget_limiting" | "responses_api_deployment_check" | "deployment_affinity" | "session_affinity" | "forward_client_headers_by_model_group" | "enforce_model_rate_limits" | "encrypted_content_affinity")[] | null;
             /** Retry After */
             retry_after?: number | null;
             retry_policy?: components["schemas"]["RetryPolicy"] | null;
@@ -38418,6 +38976,8 @@ export interface components {
             input_cost_per_character?: number | null;
             /** Input Cost Per Token */
             input_cost_per_token?: number | null;
+            /** Internal Router Model */
+            internal_router_model?: boolean | null;
             /** Output Cost Per Character */
             output_cost_per_character?: number | null;
             /** Output Cost Per Token */
@@ -38752,6 +39312,8 @@ export interface components {
             regional_processing_uplift_multiplier_us?: number | null;
             /** Rpm */
             rpm?: number | null;
+            /** Rust */
+            rust?: boolean | null;
             /** S3 Bucket Name */
             s3_bucket_name?: string | null;
             /** S3 Encryption Key Id */
@@ -40507,8 +41069,10 @@ export interface operations {
     list_shadow_eval_jobs_auto_router_shadow_eval_get: {
         parameters: {
             query?: {
-                /** @description Filter to jobs that shadow this key, alone or alongside others */
-                api_key_id?: string | null;
+                /** @description Kind of target to filter on; requires target_id */
+                target_type?: ("key" | "team" | "user") | null;
+                /** @description Filter to jobs that shadow this target, alone or alongside others */
+                target_id?: string | null;
                 /** @description Newest jobs to return */
                 limit?: number;
             };
@@ -46284,6 +46848,26 @@ export interface operations {
             };
         };
     };
+    get_mcp_tool_search_settings_get_mcp_tool_search_settings_get: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["MCPToolSearchSettingsResponse"];
+                };
+            };
+        };
+    };
     get_sso_settings_get_sso_settings_get: {
         parameters: {
             query?: never;
@@ -46435,6 +47019,161 @@ export interface operations {
             };
         };
     };
+    gigachat_proxy_route_gigachat__endpoint__get: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                endpoint: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    gigachat_proxy_route_gigachat__endpoint__put: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                endpoint: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    gigachat_proxy_route_gigachat__endpoint__post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                endpoint: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    gigachat_proxy_route_gigachat__endpoint__delete: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                endpoint: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    gigachat_proxy_route_gigachat__endpoint__patch: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path: {
+                endpoint: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
     get_global_activity_global_activity_get: {
         parameters: {
             query?: {
@@ -46865,7 +47604,7 @@ export interface operations {
                 end_date?: string | null;
                 /** @description Group spend by internal team or customer or api_key */
                 group_by?: ("team" | "customer" | "api_key") | null;
-                /** @description View spend for a specific api_key. Example api_key='sk-1234 */
+                /** @description View spend for a specific api_key. Pass the key's sha256 hash so the raw key stays out of URLs and access logs. Example api_key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa' */
                 api_key?: string | null;
                 /** @description View spend for a specific internal_user_id. Example internal_user_id='1234 */
                 internal_user_id?: string | null;
@@ -48738,7 +49477,7 @@ export interface operations {
     info_key_fn_key_info_get: {
         parameters: {
             query?: {
-                /** @description Key in the request parameters */
+                /** @description Key to look up. Pass the key's sha256 hash so the raw key stays out of URLs and access logs. Example key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa' */
                 key?: string | null;
             };
             header?: never;
@@ -48916,7 +49655,7 @@ export interface operations {
                 start_date?: string | null;
                 /** @description Time till which to view spend (YYYY-MM-DD) */
                 end_date?: string | null;
-                /** @description View spend for a specific api_key. Proxy admin only; other callers are scoped to their own key. */
+                /** @description View spend for a specific api_key. Proxy admin only; other callers are scoped to their own key. Pass the key's sha256 hash so the raw key stays out of URLs and access logs. Example api_key='d5345c0ecc68ae6295c69f91926b2bd379e25481a40c34b5884d157a9f65d8fa' */
                 api_key?: string | null;
             };
             header?: never;
@@ -51474,6 +52213,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_openai_v1_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_openai_v1_responses__response_id__get: {
         parameters: {
             query?: never;
@@ -54438,6 +55197,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_responses__response_id__get: {
         parameters: {
             query?: never;
@@ -55421,6 +56200,70 @@ export interface operations {
             };
         };
     };
+    list_placeholders_scim_v2_placeholders_get: {
+        parameters: {
+            query?: {
+                feature?: string | null;
+            };
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["SCIMPlaceholder"][];
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
+    merge_placeholder_scim_v2_placeholders__user_id__merge_post: {
+        parameters: {
+            query?: {
+                feature?: string | null;
+            };
+            header?: never;
+            path: {
+                user_id: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["SCIMPlaceholderMergeResult"];
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
     search_search_post: {
         parameters: {
             query?: {
@@ -58356,6 +59199,41 @@ export interface operations {
             };
         };
     };
+    update_mcp_tool_search_settings_update_mcp_tool_search_settings_patch: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody: {
+            content: {
+                "application/json": components["schemas"]["MCPToolSearchSettings"];
+            };
+        };
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": {
+                        [key: string]: unknown;
+                    };
+                };
+            };
+            /** @description Validation Error */
+            422: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["HTTPValidationError"];
+                };
+            };
+        };
+    };
     update_sso_settings_update_sso_settings_patch: {
         parameters: {
             query?: never;
@@ -62860,6 +63738,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_v1_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_v1_responses__response_id__get: {
         parameters: {
             query?: never;
diff --git a/ui/litellm-dashboard/src/utils/modelPermissions.test.ts b/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
index 179a9b7933a..afc2ecd210f 100644
--- a/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
+++ b/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
@@ -1,14 +1,16 @@
 import { describe, expect, it } from "vitest";
 
 import { Team } from "@/components/networking";
-import { canModifyModel, modelCreationScope } from "./modelPermissions";
+import { canCreateModels, canModifyModel, modelCreationScope } from "./modelPermissions";
 
 const teamWhere = (userId: string, role: string, teamId = "team-1"): Team[] =>
   [{ team_id: teamId, members_with_roles: [{ user_id: userId, user_email: "t@test.com", role }] }] as unknown as Team[];
 
-const PROXY_ADMIN = { userRole: "Admin", userID: "u-admin" };
-const TEAM_ADMIN = { userRole: "Internal User", userID: "u-team-admin" };
-const MEMBER = { userRole: "Internal User", userID: "u-member" };
+const PROXY_ADMIN = { userRole: "Admin", userID: "u-admin", isViewOnly: false };
+const TEAM_ADMIN = { userRole: "Internal User", userID: "u-team-admin", isViewOnly: false };
+const MEMBER = { userRole: "Internal User", userID: "u-member", isViewOnly: false };
+// proxy_admin_viewer sessions: effectiveSessionRole masquerades the role as "Admin".
+const VIEW_ONLY_ADMIN = { userRole: "Admin", userID: "u-viewer", isViewOnly: true };
 
 const noLimits = { disabledForInternalUsers: false };
 
@@ -40,9 +42,24 @@ describe("modelCreationScope", () => {
   // an unscoped create from them 403s. Treating them as admins here is what let a form submit
   // a payload the backend always rejected.
   it("does not treat an org admin as able to create unscoped", () => {
-    const orgAdmin = { userRole: "org_admin", userID: "u-org" };
+    const orgAdmin = { userRole: "org_admin", userID: "u-org", isViewOnly: false };
     expect(modelCreationScope(orgAdmin, { teams: teamWhere("u-org", "admin"), ...noLimits })).toBe("team-required");
   });
+
+  // Server-side, POST /model/new 403s the viewer roles, so the "Admin" the masquerade
+  // reports must not read as a proxy admin here.
+  it("forbids a view-only admin session despite the masqueraded Admin role", () => {
+    expect(modelCreationScope(VIEW_ONLY_ADMIN, { teams: [], ...noLimits })).toBe("forbidden");
+    expect(canCreateModels(VIEW_ONLY_ADMIN, { teams: [], ...noLimits })).toBe(false);
+  });
+
+  // _check_proxy_admin_viewer_access (route_checks.py) 403s /model/new on the session role
+  // alone, before the team-scoped carve-out in ModelManagementAuthChecks can run.
+  it("forbids a view-only admin even when they admin a team", () => {
+    expect(modelCreationScope(VIEW_ONLY_ADMIN, { teams: teamWhere("u-viewer", "admin"), ...noLimits })).toBe(
+      "forbidden",
+    );
+  });
 });
 
 describe("canModifyModel", () => {
@@ -80,6 +97,17 @@ describe("canModifyModel", () => {
   });
 
   it("does not treat two absent identities as a match", () => {
-    expect(canModifyModel({ userRole: "Internal User", userID: null }, null, teamRow)).toBe(false);
+    expect(canModifyModel({ userRole: "Internal User", userID: null, isViewOnly: false }, null, teamRow)).toBe(false);
+  });
+
+  // PATCH /model/{id}/update and POST /model/delete 403 the viewer roles like /model/new does.
+  it("refuses a view-only admin session on a DB row", () => {
+    expect(canModifyModel(VIEW_ONLY_ADMIN, null, teamRow)).toBe(false);
+  });
+
+  // The route RBAC blocks /model/update and /model/delete for the viewer role before the
+  // team-scoped carve-out runs, so team-admin membership changes nothing here either.
+  it("refuses a view-only user even when they admin the owning team", () => {
+    expect(canModifyModel(VIEW_ONLY_ADMIN, teamWhere("u-viewer", "admin"), teamRow)).toBe(false);
   });
 });
diff --git a/ui/litellm-dashboard/src/utils/modelPermissions.ts b/ui/litellm-dashboard/src/utils/modelPermissions.ts
index b5914f9d7ea..843d9041026 100644
--- a/ui/litellm-dashboard/src/utils/modelPermissions.ts
+++ b/ui/litellm-dashboard/src/utils/modelPermissions.ts
@@ -3,20 +3,32 @@ import { Team } from "@/components/networking";
 import { isProxyAdminRole, isUserTeamAdminForAnyTeam, isUserTeamAdminForSingleTeam } from "./roles";
 
 /**
- * The dashboard's mirror of ModelManagementAuthChecks in
- * litellm/proxy/management_endpoints/model_management_endpoints.py.
+ * The dashboard's mirror of the two server layers that gate model writes: the role-level
+ * route RBAC (`_check_proxy_admin_viewer_access` in litellm/proxy/auth/route_checks.py),
+ * which 403s /model/new, /model/update, and /model/delete for every view-only session
+ * before the endpoint runs, and ModelManagementAuthChecks in
+ * litellm/proxy/management_endpoints/model_management_endpoints.py behind it.
  *
- * Both questions below are answered there by exactly two inputs: the caller's role, and
- * whether the caller admins the team named in `model_info.team_id`. `created_by` is written
- * at creation and never read by an auth check, so it is deliberately absent here; gating on
- * it hid controls from team admins the API accepts, and showed controls to former team admins
- * the API rejects.
+ * Past that route gate, both questions below are answered by exactly two inputs: the
+ * caller's role, and whether the caller admins the team named in `model_info.team_id`.
+ * `created_by` is written at creation and never read by an auth check, so it is deliberately
+ * absent here; gating on it hid controls from team admins the API accepts, and showed
+ * controls to former team admins the API rejects.
  */
 export interface ModelActor {
   userRole: string | null;
   userID: string | null;
+  /**
+   * From useAuthorized(). A proxy_admin_viewer session masquerades as "Admin" in userRole
+   * (effectiveSessionRole, for read parity), yet every management write 403s it, so the role
+   * alone cannot answer a write question.
+   */
+  isViewOnly: boolean;
 }
 
+const isWritableProxyAdmin = ({ userRole, isViewOnly }: ModelActor): boolean =>
+  !isViewOnly && userRole != null && isProxyAdminRole(userRole);
+
 /** How this actor must scope a deployment they create, or that they may not create one. */
 export type ModelWriteScope = "forbidden" | "unscoped-ok" | "team-required";
 
@@ -33,20 +45,25 @@ const isTeamAdminOf = (teams: Team[] | null, userID: string, teamId: string): bo
 
 /**
  * POST /model/new takes a proxy admin unconditionally, or a team admin whose payload names a
- * team; an unscoped create from anyone else is a 403. Returning the requirement rather than a
- * pair of booleans keeps "may not create" and "may create unscoped" from being confused.
+ * team; an unscoped create from anyone else is a 403. A view-only session is 403d by the
+ * route RBAC on its role alone, so team-admin membership cannot rescue it. Returning the
+ * requirement rather than a pair of booleans keeps "may not create" and "may create
+ * unscoped" from being confused.
  */
 export const modelCreationScope = (
-  { userRole, userID }: ModelActor,
+  actor: ModelActor,
   { teams, disabledForInternalUsers }: ModelCreationLimits,
 ): ModelWriteScope => {
-  if (userRole != null && isProxyAdminRole(userRole)) {
+  if (actor.isViewOnly) {
+    return "forbidden";
+  }
+  if (isWritableProxyAdmin(actor)) {
     return "unscoped-ok";
   }
   if (disabledForInternalUsers) {
     return "forbidden";
   }
-  if (userID != null && isUserTeamAdminForAnyTeam(teams, userID)) {
+  if (actor.userID != null && isUserTeamAdminForAnyTeam(teams, actor.userID)) {
     return "team-required";
   }
   return "forbidden";
@@ -63,18 +80,18 @@ export interface ModelRowOrigin {
 
 /** May this actor edit or delete this specific deployment? */
 export const canModifyModel = (
-  { userRole, userID }: ModelActor,
+  actor: ModelActor,
   teams: Team[] | null,
   { teamId, isDbModel }: ModelRowOrigin,
 ): boolean => {
-  if (!isDbModel) {
+  if (actor.isViewOnly || !isDbModel) {
     return false;
   }
-  if (userRole != null && isProxyAdminRole(userRole)) {
+  if (isWritableProxyAdmin(actor)) {
     return true;
   }
-  if (userID == null || teamId == null) {
+  if (actor.userID == null || teamId == null) {
     return false;
   }
-  return isTeamAdminOf(teams, userID, teamId);
+  return isTeamAdminOf(teams, actor.userID, teamId);
 };
diff --git a/ui/litellm-dashboard/src/utils/searchUtils.test.ts b/ui/litellm-dashboard/src/utils/searchUtils.test.ts
new file mode 100644
index 00000000000..4935e8ab15d
--- /dev/null
+++ b/ui/litellm-dashboard/src/utils/searchUtils.test.ts
@@ -0,0 +1,64 @@
+import { describe, expect, it } from "vitest";
+
+import { filterBySearchTerm, matchesSearchTerm, rankBySearchRelevance } from "./searchUtils";
+
+describe("matchesSearchTerm", () => {
+  it("matches everything on an empty or whitespace-only term", () => {
+    expect(matchesSearchTerm("", ["anything"])).toBe(true);
+    expect(matchesSearchTerm("   ", ["anything"])).toBe(true);
+  });
+
+  it("matches a substring of any field, case-insensitively", () => {
+    expect(matchesSearchTerm("BILL", ["Billing Router", "routes invoices"])).toBe(true);
+    expect(matchesSearchTerm("invoice", ["Billing Router", "routes invoices"])).toBe(true);
+  });
+
+  it("matches when every word appears in some field", () => {
+    expect(matchesSearchTerm("router invoices", ["Billing Router", "routes invoices"])).toBe(true);
+    expect(matchesSearchTerm("router refunds", ["Billing Router", "routes invoices"])).toBe(false);
+  });
+
+  it("returns false when nothing matches", () => {
+    expect(matchesSearchTerm("zzzz", ["Billing Router", "routes invoices"])).toBe(false);
+  });
+
+  it("ignores null and undefined fields", () => {
+    expect(matchesSearchTerm("billing", [null, undefined, "Billing Router"])).toBe(true);
+    expect(matchesSearchTerm("billing", [null, undefined])).toBe(false);
+  });
+});
+
+describe("filterBySearchTerm", () => {
+  const agents = [
+    { name: "Billing Router", description: "routes invoices" },
+    { name: "Support Bot", description: "handles tickets" },
+  ];
+
+  it("keeps only items whose fields match", () => {
+    expect(filterBySearchTerm(agents, "tickets", (a) => [a.name, a.description])).toEqual([agents[1]]);
+  });
+
+  it("returns an empty list when nothing matches", () => {
+    expect(filterBySearchTerm(agents, "zzzz", (a) => [a.name, a.description])).toEqual([]);
+  });
+
+  it("returns all items for an empty term", () => {
+    expect(filterBySearchTerm(agents, "", (a) => [a.name, a.description])).toEqual(agents);
+  });
+});
+
+describe("rankBySearchRelevance", () => {
+  it("orders exact match, then prefix match, then shorter names", () => {
+    const items = [{ name: "gpt-4o-mini-transcribe" }, { name: "gpt-4o" }, { name: "chatgpt-4o-latest" }];
+    expect(rankBySearchRelevance(items, "gpt-4o", (m) => m.name).map((m) => m.name)).toEqual([
+      "gpt-4o",
+      "gpt-4o-mini-transcribe",
+      "chatgpt-4o-latest",
+    ]);
+  });
+
+  it("keeps the original order for an empty term", () => {
+    const items = [{ name: "b" }, { name: "a" }];
+    expect(rankBySearchRelevance(items, "", (m) => m.name)).toEqual(items);
+  });
+});
diff --git a/ui/litellm-dashboard/src/utils/searchUtils.ts b/ui/litellm-dashboard/src/utils/searchUtils.ts
new file mode 100644
index 00000000000..b256a5db0c4
--- /dev/null
+++ b/ui/litellm-dashboard/src/utils/searchUtils.ts
@@ -0,0 +1,32 @@
+type SearchField = string | null | undefined;
+
+const normalizeTerm = (term: string): string => term.trim().toLowerCase();
+
+export function matchesSearchTerm(term: string, fields: ReadonlyArray<SearchField>): boolean {
+  const needle = normalizeTerm(term);
+  if (needle === "") return true;
+
+  const haystacks = fields.filter((field): field is string => typeof field === "string").map((f) => f.toLowerCase());
+  if (haystacks.some((haystack) => haystack.includes(needle))) return true;
+
+  return needle.split(/\s+/).every((word) => haystacks.some((haystack) => haystack.includes(word)));
+}
+
+export function filterBySearchTerm<T>(
+  items: ReadonlyArray<T>,
+  term: string,
+  fields: (item: T) => ReadonlyArray<SearchField>,
+): T[] {
+  return items.filter((item) => matchesSearchTerm(term, fields(item)));
+}
+
+export function rankBySearchRelevance<T>(items: ReadonlyArray<T>, term: string, name: (item: T) => string): T[] {
+  const needle = normalizeTerm(term);
+  if (needle === "") return [...items];
+
+  const score = (item: T): number => {
+    const candidate = name(item).toLowerCase();
+    return (candidate === needle ? 1000 : 0) + (candidate.startsWith(needle) ? 100 : 0) + (1000 - candidate.length);
+  };
+  return [...items].sort((a, b) => score(b) - score(a));
+}
diff --git a/ui/litellm-dashboard/tests/fieldOrientation.ts b/ui/litellm-dashboard/tests/fieldOrientation.ts
new file mode 100644
index 00000000000..49ba5056d66
--- /dev/null
+++ b/ui/litellm-dashboard/tests/fieldOrientation.ts
@@ -0,0 +1,18 @@
+import { expect } from "vitest";
+
+export const ROW_LAYOUT_CLASSES = ["flex-row", "items-center"] as const;
+export const STRETCH_CHILDREN_CLASS = "*:w-full";
+
+/**
+ * Asserts a control sits beside its label at its own width instead of being stretched across the
+ * field. Reaches for the resolved classes because the defect is purely visual: nothing accessible
+ * distinguishes a square checkbox from a full-width bar.
+ */
+export const expectControlBesideLabel = (control: HTMLElement): void => {
+  const field = control.closest('[data-slot="field"]');
+  if (field === null) throw new Error("control is not rendered inside a form field");
+
+  expect(field).toHaveAttribute("data-orientation", "horizontal");
+  expect(field).toHaveClass(...ROW_LAYOUT_CLASSES);
+  expect(field).not.toHaveClass(STRETCH_CHILDREN_CLASS);
+};
diff --git a/ui/litellm-dashboard/tests/test-utils.tsx b/ui/litellm-dashboard/tests/test-utils.tsx
index 66966201a9c..553726faff0 100644
--- a/ui/litellm-dashboard/tests/test-utils.tsx
+++ b/ui/litellm-dashboard/tests/test-utils.tsx
@@ -44,20 +44,14 @@ const pointerBlocked = (element: HTMLElement): boolean => {
   return false;
 };
 
-/**
- * Opens a Base UI Select and picks an option by its accessible name.
- *
- * The option is in the DOM one render before the popup finishes entering, and until then its
- * positioner still carries `pointer-events: none`, which user-event refuses to click. Waiting on
- * the option text alone is a race that React 19's flush timing loses.
- */
 export const chooseSelectOption = async (
-  user: ReturnType<typeof userEvent.setup>,
+  user: Pick<ReturnType<typeof userEvent.setup>, "click">,
   trigger: HTMLElement,
   optionName: string | RegExp,
+  role: "option" | "menuitem" | "menuitemradio" = "option",
 ) => {
   await user.click(trigger);
-  const option = await screen.findByRole("option", { name: optionName });
+  const option = await screen.findByRole(role, { name: optionName });
   await waitFor(() => expect(pointerBlocked(option)).toBe(false));
   await user.click(option);
 };
diff --git a/uv.lock b/uv.lock
index 8ef72116466..aa59ff7b229 100644
--- a/uv.lock
+++ b/uv.lock
@@ -10,7 +10,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-08-26T18:33:25.773031Z"
+exclude-newer = "2026-08-30T17:51:25.171404Z"
 exclude-newer-span = "P3D"
 
 [manifest]
@@ -25,7 +25,7 @@ constraints = [
     { name = "packaging", specifier = ">=24.0" },
     { name = "setuptools", specifier = ">=83.0.0" },
     { name = "soupsieve", specifier = ">=2.8.4" },
-    { name = "tornado", specifier = ">=6.5.6" },
+    { name = "tornado", specifier = ">=6.5.8" },
 ]
 overrides = [
     { name = "cryptography", specifier = ">=50.0.0,<51.0" },
@@ -4266,7 +4266,7 @@ wheels = [
 
 [[package]]
 name = "litellm"
-version = "1.100.0"
+version = "1.101.0"
 source = { editable = "." }
 dependencies = [
     { name = "aiohttp" },
@@ -4306,6 +4306,8 @@ extra-proxy = [
     { name = "google-cloud-iam" },
     { name = "google-cloud-kms" },
     { name = "prisma" },
+    { name = "psycopg" },
+    { name = "psycopg-binary" },
     { name = "redisvl" },
     { name = "resend" },
 ]
@@ -4544,11 +4546,13 @@ requires-dist = [
     { name = "polars", marker = "extra == 'proxy'", specifier = ">=1.38.1,<2.0" },
     { name = "prisma", marker = "extra == 'extra-proxy'", specifier = ">=0.11.0,<1.0" },
     { name = "prometheus-client", marker = "extra == 'proxy-runtime'", specifier = ">=0.20.0,<1.0" },
+    { name = "psycopg", marker = "extra == 'extra-proxy'", specifier = ">=3.2,<4.0" },
+    { name = "psycopg-binary", marker = "extra == 'extra-proxy'", specifier = ">=3.2,<4.0" },
     { name = "pydantic", specifier = ">=2.10.0,<3.0.0" },
     { name = "pydantic-settings", specifier = ">=2.14.1,<3.0" },
     { name = "pyjwt", marker = "extra == 'proxy'", specifier = ">=2.13.0,<3.0" },
     { name = "pynacl", marker = "extra == 'proxy'", specifier = ">=1.6.2,<2.0" },
-    { name = "pypdf", marker = "extra == 'proxy-runtime'", specifier = ">=6.12.0,<7.0" },
+    { name = "pypdf", marker = "extra == 'proxy-runtime'", specifier = ">=6.16.1,<7.0" },
     { name = "pyroscope-io", marker = "sys_platform != 'win32' and extra == 'proxy'", specifier = ">=0.8.16,<1.0" },
     { name = "python-dotenv", specifier = ">=1.0.0,<2.0" },
     { name = "python-multipart", marker = "extra == 'proxy'", specifier = ">=0.0.27,<1.0" },
@@ -4665,12 +4669,12 @@ proxy-dev = [
 
 [[package]]
 name = "litellm-enterprise"
-version = "0.1.62"
+version = "0.1.63"
 source = { editable = "enterprise" }
 
 [[package]]
 name = "litellm-proxy-extras"
-version = "0.4.91"
+version = "0.4.92"
 source = { editable = "litellm-proxy-extras" }
 
 [[package]]
@@ -7560,14 +7564,14 @@ wheels = [
 
 [[package]]
 name = "pypdf"
-version = "6.15.0"
+version = "6.16.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/17/17/ee75a92718ec7212de831e71454d702225aa5e474a805cce169806044453/pypdf-6.15.0.tar.gz", hash = "sha256:d39c4d955a76409284a905e2d65b40076d77ab76129e0faaeeb6612403ecfc79", size = 6993794, upload-time = "2026-08-06T13:06:49.929Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/44/66/54212e75406afd9f3e933d0dda23072f6aecc55c5a273077dc2e0b028b23/pypdf-6.16.2.tar.gz", hash = "sha256:595647f6191de6f402cfde1d0c455d6cbccbd509aac32b34783009c032de5d6e", size = 7008996, upload-time = "2026-08-23T13:50:07.135Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/af/72/ce3067ac31e214a66388159f8462ddb8c13dd00170f24d555a1f1ae8ee91/pypdf-6.15.0-py3-none-any.whl", hash = "sha256:14e001d6504822cb1ca9c7ed9a69bccb320f59b320730f55af804361abe4d5ee", size = 378123, upload-time = "2026-08-06T13:06:47.709Z" },
+    { url = "https://files.pythonhosted.org/packages/13/f1/a2da3b55acd4ab737bf728c97edaaed5ec1d3c1236acb639dcdfa97e42c7/pypdf-6.16.2-py3-none-any.whl", hash = "sha256:c8b09a59399062fb45a1b8156c18a787a10a3dae03ac9674397a226712c94604", size = 385060, upload-time = "2026-08-23T13:50:05.349Z" },
 ]
 
 [[package]]
@@ -9437,19 +9441,19 @@ wheels = [
 
 [[package]]
 name = "tornado"
-version = "6.5.7"
+version = "6.5.8"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/64/24/95ec527ad67b76d59299e5465b3935d05e4294b7e0290a3924b7487df30b/tornado-6.5.7.tar.gz", hash = "sha256:66c513a76cda70d53907bc27cf1447557699c2e95aa48ba27a442ff61c3ddfc2", size = 519252, upload-time = "2026-06-08T17:34:51.232Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/10/d3/343e5bb989d6515b1646cf3d40135d73f3d5e45339bded401b56cdac24dd/tornado-6.5.8.tar.gz", hash = "sha256:9452e1b208a8bd771e2cb1f2ff564985b9b214bdebbe622793e1799e0a6bd23f", size = 520493, upload-time = "2026-08-07T02:12:42.971Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/02/dc/c7043cab6fed8ae159fc1923ce829ada35c4dbd797d408a43858ffaf9639/tornado-6.5.7-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:148b2eb15c2c765a50796172c1e499649b35f30d2e3c3d3e15913cfa56bfb163", size = 448543, upload-time = "2026-06-08T17:34:38.052Z" },
-    { url = "https://files.pythonhosted.org/packages/92/4f/090b1431e5a43df696feceffc268c5383cc079ecb5f08ce58f917109aafe/tornado-6.5.7-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:9da38de27f1da3b78a966f0dae12b5a1ea9afe72ca805d84ff06508272ddf100", size = 446707, upload-time = "2026-06-08T17:34:39.594Z" },
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+    { url = "https://files.pythonhosted.org/packages/97/cf/fe33cf062834487d34d1559746a4a12521033c22645b6d74d4bca702e018/tornado-6.5.8-cp39-abi3-win32.whl", hash = "sha256:67832909c4779c64942380cb5f044a5c6163d00831472d80e25e115de9917836", size = 451952, upload-time = "2026-08-07T02:12:38.512Z" },
+    { url = "https://files.pythonhosted.org/packages/cb/e1/468ad54333e92ccb62627e62cb88e5fc14a2171daa67ed47b1b8542d5b86/tornado-6.5.8-cp39-abi3-win_amd64.whl", hash = "sha256:11881db6b7c168494be2c2d12e65931451bdf7ee718535418ae1d8855dd5a0ee", size = 452391, upload-time = "2026-08-07T02:12:39.971Z" },
+    { url = "https://files.pythonhosted.org/packages/ad/3e/cd5e4f06e34cde33b8ef66cf36aa2b5ad46354cc1af7d2136bbe365fee1d/tornado-6.5.8-cp39-abi3-win_arm64.whl", hash = "sha256:68a7468c7e289f8514d7d664101753903217eff1bb6822c6b5994a0b5f5bcb26", size = 451411, upload-time = "2026-08-07T02:12:41.469Z" },
 ]
 
 [[package]]
diff --git a/whitelisted_bedrock_models.txt b/whitelisted_bedrock_models.txt
index 7e20081988d..8753d7c3c77 100644
--- a/whitelisted_bedrock_models.txt
+++ b/whitelisted_bedrock_models.txt
@@ -217,3 +217,17 @@ bedrock/us-east-1/zai.glm-5
 bedrock/us-west-2/zai.glm-5
 bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0
 bedrock/us-gov-west-1/anthropic.claude-haiku-4-5-20251001-v1:0
+bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b
+bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2
+bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b
+bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0
+bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0
+bedrock/us-gov-west-1/anthropic.claude-sonnet-5
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