diff --git a/.circleci/config.yml b/.circleci/config.yml
index 63012ce3fc0..55fa9410845 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -1483,7 +1483,7 @@ jobs:
       - run:
           name: Run tests
           command: |
-            uv run --no-sync python -m pytest -vv tests/local_testing/test_basic_python_version.py -k "not legacy_resolver"
+            uv run --no-sync python -m pytest -vv tests/local_testing/test_basic_python_version.py -k "not v2_resolver"
 
   installing_litellm_on_python_3_13:
     docker:
@@ -1507,9 +1507,9 @@ jobs:
       - run:
           name: Run tests
           command: |
-            uv run --no-sync python -m pytest -v tests/local_testing/test_basic_python_version.py -k "not legacy_resolver"
+            uv run --no-sync python -m pytest -v tests/local_testing/test_basic_python_version.py -k "not v2_resolver"
 
-  installing_litellm_on_python_legacy_migration_resolver:
+  installing_litellm_on_python_v2_migration_resolver:
     docker:
       - *python312_image
       - image: cimg/postgres:16.0@sha256:b125148bc76e8e8eee5eb3ad6020a3a14110a14e8192f1c645128afebe2e2f84
@@ -1536,10 +1536,10 @@ jobs:
           url: tcp://localhost:5432
           timeout: "60"
       - run:
-          name: Run legacy migration resolver proxy smoke test
+          name: Run v2 migration resolver proxy smoke test
           command: |
             uv run --no-sync python -m pytest -vv \
-              tests/local_testing/test_basic_python_version.py::test_litellm_proxy_server_config_no_general_settings_legacy_resolver
+              tests/local_testing/test_basic_python_version.py::test_litellm_proxy_server_config_no_general_settings_v2_resolver
 
   helm_chart_testing:
     machine:
@@ -2879,8 +2879,7 @@ jobs:
           command: |
             if grep -q "Error: P1001: Can't reach database server at" docker_output.log && \
                (grep -q "Database setup failed after multiple retries" docker_output.log || \
-                grep -q "ERROR:    Application startup failed. Exiting." docker_output.log || \
-                grep -q "Database migration cannot proceed" docker_output.log); then
+                grep -q "ERROR:    Application startup failed. Exiting." docker_output.log); then
               echo "Expected error found. Test passed."
             else
               echo "Expected error not found. Test failed."
@@ -3012,7 +3011,7 @@ workflows:
           filters: *main_branches
       - installing_litellm_on_python_3_13:
           filters: *main_branches
-      - installing_litellm_on_python_legacy_migration_resolver:
+      - installing_litellm_on_python_v2_migration_resolver:
           filters: *main_branches
       - helm_chart_testing:
           requires:
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/CLAUDE.md b/CLAUDE.md
index 6af8390b1af..d9e9e8f1586 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -37,7 +37,7 @@ Same applies for filing bug reports and feature requests, with .github/ISSUE_TEM
 
 If you're resolving a linear ticket, in the "## Linear ticket" section of the PR, say "Resolves LIT-1234", replacing "LIT-1234" with the actual ticket id that you're resolving. If you don't have the ticket id, don't make one up or search for it. Just leave the section blank
 
-Never use `pytest` commands or the like as "Screenshots / Proof of Fix". We prefer curl'ing a live proxy instance running on localhost:4000 (I like to run it with `python litellm/proxy/proxy_cli.py --config litellm/proxy/dev_config.yaml --detailed_debug --reload 2>&1 | tee litellm.log`; the Admin UI dev server is `npm run dev` in `ui/litellm-dashboard`, served on port 3000) and showing both the command run and the output. Also, it should hit real LLM provider APIs, not mocks, and cost real $$$ because that is the most realistic test. The proof of fix should be exactly what the end user / customer would see / do. The run logs in PR #27703 is a prime example of how to do it (not a huge fan of using a python test script that future me and the team will have no visibility into; I prefer just curl commands or a short list of bash commands (e.g., using `for`)). If it's a UI thing, just tell me which URLs to go to (e.g., http://localhost:4000/ui/?page=logs), where to click, what fields to fill out, etc. along with the other commands to run in an ordered list, and I'll do it myself and post the screenshots after you make the PR
+Never use `pytest` commands or the like as "Screenshots / Proof of Fix". We prefer curl'ing a live proxy instance running on localhost:4000 (I like to run it with `python litellm/proxy/proxy_cli.py --config litellm/proxy/dev_config.yaml --detailed_debug --reload --use_v2_migration_resolver 2>&1 | tee litellm.log`; the Admin UI dev server is `npm run dev` in `ui/litellm-dashboard`, served on port 3000) and showing both the command run and the output. Also, it should hit real LLM provider APIs, not mocks, and cost real $$$ because that is the most realistic test. The proof of fix should be exactly what the end user / customer would see / do. The run logs in PR #27703 is a prime example of how to do it (not a huge fan of using a python test script that future me and the team will have no visibility into; I prefer just curl commands or a short list of bash commands (e.g., using `for`)). If it's a UI thing, just tell me which URLs to go to (e.g., http://localhost:4000/ui/?page=logs), where to click, what fields to fill out, etc. along with the other commands to run in an ordered list, and I'll do it myself and post the screenshots after you make the PR
 
 If you ever write any human-facing text (pull requests, issues, commit messages, discussion posts, github comments, release notes, docs, etc.), always follow these guidelines to sound less AI-y:
 - don't use emojis
diff --git a/Dockerfile b/Dockerfile
index b3ee85e9ed1..0a92aa9a68c 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -66,6 +66,7 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -87,6 +88,7 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
@@ -101,6 +103,12 @@ 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 python-3.13 libsndfile
 
diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index df52069e71f..da788bf1ce3 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -117,7 +117,7 @@
     "limit": 111
   },
   "reportUnnecessaryComparison": {
-    "limit": 695
+    "limit": 692
   },
   "reportUnnecessaryContains": {
     "limit": 5
diff --git a/docker/Dockerfile.database b/docker/Dockerfile.database
index c1348f68231..e9ad2849bb2 100644
--- a/docker/Dockerfile.database
+++ b/docker/Dockerfile.database
@@ -64,6 +64,7 @@ RUN uv sync --frozen --no-install-project --no-install-workspace --no-default-gr
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -85,6 +86,7 @@ RUN uv sync --frozen --no-default-groups --no-editable \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 RUN HOME=/opt/prisma XDG_CACHE_HOME=/opt/prisma/.cache PRISMA_BINARY_CACHE_DIR=/opt/prisma/binaries \
diff --git a/docker/Dockerfile.non_root b/docker/Dockerfile.non_root
index 2221435a83a..edf20e8bbff 100644
--- a/docker/Dockerfile.non_root
+++ b/docker/Dockerfile.non_root
@@ -70,6 +70,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
     --extra extra_proxy \
     --extra semantic-router \
     --extra saml \
+    --extra bedrock-realtime \
     --python python3.13
 
 # Copy full source tree
@@ -97,6 +98,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
+        --extra bedrock-realtime \
         --python python3.13 \
         --no-sources-package litellm-proxy-extras; \
     else \
@@ -106,6 +108,7 @@ RUN --mount=type=cache,target=/app/.cache/uv,id=litellm-uv-cache \
         --extra extra_proxy \
         --extra semantic-router \
         --extra saml \
+        --extra bedrock-realtime \
         --python python3.13; \
     fi
 
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/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/litellm-proxy-extras/litellm_proxy_extras/utils.py b/litellm-proxy-extras/litellm_proxy_extras/utils.py
index c088609dad7..b8032dd0d28 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/utils.py
+++ b/litellm-proxy-extras/litellm_proxy_extras/utils.py
@@ -7,8 +7,7 @@ import subprocess
 import tempfile
 import time
 from pathlib import Path
-from types import MappingProxyType
-from typing import Final, Optional
+from typing import Optional
 
 from litellm_proxy_extras._logging import logger
 from litellm_proxy_extras.replica_identity import (
@@ -51,17 +50,6 @@ _SPEND_LOGS_PK_CLAUSE_RE = re.compile(
     re.IGNORECASE,
 )
 
-_PRISMA_ATTEMPTS: Final = 4
-
-_TRANSIENT_PRISMA_FAILURES: Final = MappingProxyType(
-    {
-        "deadlock detected": "a deadlock on the migration advisory lock (a concurrent migrate deploy)",
-        "P1001": "an unreachable database server",
-        "P1002": "a database server that timed out",
-    }
-)
-
-
 PARTITIONED_SPEND_LOGS_PUSH_ERROR = (
     "LiteLLM_SpendLogs is a partitioned table (see db_scripts/partition_spend_logs.sql), "
     "so its primary key must include the partition key (\"startTime\"). `prisma db push` "
@@ -286,23 +274,6 @@ class ProxyExtrasDBManager:
             env=prisma_env,
         )
 
-    @staticmethod
-    def _transient_prisma_failure(stderr: str) -> str | None:
-        """Why a failed prisma command is worth retrying, or None.
-
-        v1 retried every failure, so it absorbed a database that was not up yet
-        or another instance holding the migration lock. v2 fails fast, which is
-        right for a broken migration and wrong for these.
-        """
-        return next(
-            (
-                reason
-                for marker, reason in _TRANSIENT_PRISMA_FAILURES.items()
-                if marker in stderr
-            ),
-            None,
-        )
-
     @staticmethod
     def _is_permission_error(error_message: str) -> bool:
         """
@@ -684,7 +655,7 @@ class ProxyExtrasDBManager:
     @staticmethod
     def _setup_database_v2(use_migrate: bool) -> bool:
         """
-        v2 migration resolver (what the proxy CLI selects by default).
+        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
@@ -705,46 +676,20 @@ class ProxyExtrasDBManager:
             original_dir = os.getcwd()
             os.chdir(migrations_dir)
             try:
-                for attempt in range(_PRISMA_ATTEMPTS):
-                    try:
-                        subprocess.run(
-                            [_get_prisma_command(), "db", "push", "--accept-data-loss"],
-                            timeout=prisma_command_timeout(),
-                            check=True,
-                            capture_output=True,
-                            text=True,
-                            env=_get_prisma_env(),
-                        )
-                        return True
-                    except subprocess.TimeoutExpired:
-                        logger.info(
-                            "prisma db push attempt %s timed out, retrying",
-                            attempt + 1,
-                        )
-                        time.sleep(random.randrange(5, 15))
-                    except subprocess.CalledProcessError as e:
-                        stderr = e.stderr or ""
-                        transient = ProxyExtrasDBManager._transient_prisma_failure(
-                            stderr
-                        )
-                        # Re-raise as RuntimeError so proxy_cli.py's
-                        # `except RuntimeError` catches it and exits cleanly.
-                        if transient is None or attempt == _PRISMA_ATTEMPTS - 1:
-                            raise RuntimeError(
-                                f"prisma db push failed.\n\nDetail: {e}"
-                                f"\n\nPrisma error:\n{stderr}"
-                            ) from e
-                        logger.info(
-                            "prisma db push attempt %s failed on %s, retrying. "
-                            "Prisma error:\n%s",
-                            attempt + 1,
-                            transient,
-                            stderr,
-                        )
-                        time.sleep(random.randrange(5, 15))
-                raise RuntimeError(
-                    f"prisma db push failed after {_PRISMA_ATTEMPTS} attempts."
+                subprocess.run(
+                    [_get_prisma_command(), "db", "push", "--accept-data-loss"],
+                    timeout=prisma_command_timeout(),
+                    check=True,
+                    env=_get_prisma_env(),
                 )
+                return True
+            except (
+                subprocess.CalledProcessError,
+                subprocess.TimeoutExpired,
+            ) as e:
+                # Re-raise as RuntimeError so proxy_cli.py's
+                # `except RuntimeError` catches it and exits cleanly.
+                raise RuntimeError(f"prisma db push failed.\n\nDetail: {e}") from e
             finally:
                 os.chdir(original_dir)
 
@@ -754,7 +699,7 @@ class ProxyExtrasDBManager:
         original_dir = os.getcwd()
         os.chdir(migrations_dir)
         try:
-            for attempt in range(_PRISMA_ATTEMPTS):
+            for attempt in range(4):
                 try:
                     result = subprocess.run(
                         [_get_prisma_command(), "migrate", "deploy"],
@@ -869,36 +814,16 @@ class ProxyExtrasDBManager:
                             f"Manual intervention required.\n\nPrisma error:\n{stderr}"
                         ) from e
 
-                    transient = ProxyExtrasDBManager._transient_prisma_failure(stderr)
-                    if transient is None:
-                        raise RuntimeError(
-                            "Database migration failed and cannot be auto-recovered. "
-                            f"Manual intervention required.\n\nPrisma error:\n{stderr}"
-                        ) from e
-
-                    if attempt == _PRISMA_ATTEMPTS - 1:
-                        raise RuntimeError(
-                            f"Database migration failed after "
-                            f"{_PRISMA_ATTEMPTS} attempts on {transient}. "
-                            "Check database connectivity and load."
-                            f"\n\nPrisma error:\n{stderr}"
-                        ) from e
-
-                    logger.info(
-                        "prisma migrate deploy attempt %s failed on %s, retrying. "
-                        "Prisma error:\n%s",
-                        attempt + 1,
-                        transient,
-                        stderr,
-                    )
-                    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
 
             raise RuntimeError(
-                f"Database migration failed after {_PRISMA_ATTEMPTS} "
-                "attempts (retry loop exhausted by timeouts or repeated "
-                "idempotent-recovery continues). Check database connectivity, "
-                "load, and _prisma_migrations ledger state."
+                "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."
             )
         finally:
             os.chdir(original_dir)
@@ -946,11 +871,10 @@ class ProxyExtrasDBManager:
 
         Args:
             use_migrate: Whether to use prisma migrate instead of db push
-            use_v2_resolver: Run the v2 migration resolver (safer during
+            use_v2_resolver: Opt into the v2 migration resolver (safer during
                 rolling deploys; does not run the diff-and-force recovery
-                that causes schema thrashing). Defaults to False here so
-                direct callers keep the old behavior; the proxy CLI passes
-                True, so the proxy's runtime default is v2.
+                that causes schema thrashing). Defaults to False for
+                backwards compatibility.
 
         Returns:
             bool: True if setup was successful, False otherwise
@@ -968,7 +892,7 @@ class ProxyExtrasDBManager:
     @staticmethod
     def _run_migrations(use_migrate: bool, use_v2_resolver: bool) -> bool:
         if use_v2_resolver:
-            logger.info("Using v2 migration resolver")
+            logger.info("Using v2 migration resolver (--use_v2_migration_resolver)")
             return ProxyExtrasDBManager._setup_database_v2(use_migrate=use_migrate)
 
         schema_path = ProxyExtrasDBManager._get_prisma_dir() + "/schema.prisma"
diff --git a/litellm-proxy-extras/tests/__init__.py b/litellm-proxy-extras/tests/__init__.py
new file mode 100644
index 00000000000..e69de29bb2d
diff --git a/litellm-proxy-extras/tests/test_setup_database_fail_fast.py b/litellm-proxy-extras/tests/test_setup_database_fail_fast.py
new file mode 100644
index 00000000000..8d66bf872de
--- /dev/null
+++ b/litellm-proxy-extras/tests/test_setup_database_fail_fast.py
@@ -0,0 +1,242 @@
+"""Regression tests for ProxyExtrasDBManager v2 migration resolver.
+
+The v2 resolver is opt-in via `--use_v2_migration_resolver` / the
+`use_v2_resolver=True` kwarg. These tests exercise the v2 path; the v1
+(default) behavior is unchanged from pre-fix.
+"""
+
+import subprocess
+from unittest.mock import patch
+
+import pytest
+
+from litellm_proxy_extras.utils import (
+    ProxyExtrasDBManager,
+    _max_migration_timestamp,
+    _migration_timestamp,
+)
+
+
+def _fake_migrate_deploy_failure(returncode: int, stderr: str):
+    def _run(*args, **kwargs):
+        raise subprocess.CalledProcessError(
+            returncode=returncode,
+            cmd=args[0],
+            stderr=stderr,
+            output="",
+        )
+
+    return _run
+
+
+def test_v2_p3018_permission_error_raises_runtime_error(monkeypatch, tmp_path):
+    """v2: a permission failure during migrate deploy raises RuntimeError."""
+    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")
+
+    stderr = (
+        "Error: P3018\nMigration name: 20250326162113_baseline\n"
+        "Database error code: 42501\npermission denied for schema public"
+    )
+    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
+        with pytest.raises(RuntimeError, match="permission"):
+            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+
+
+def test_v2_non_idempotent_p3009_raises_runtime_error(monkeypatch, tmp_path):
+    """v2: a non-idempotent migration failure raises (no silent recovery)."""
+    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")
+
+    stderr = (
+        "Error: P3009\nMigration `20260101000000_genuinely_broken` failed\n"
+        'Reason: syntax error at or near "BRKN" LINE 42'
+    )
+    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_strip_prisma_query_params_removes_connection_limit():
+    """DATABASE_URLs with Prisma-specific params should be parseable by psycopg."""
+    url = "postgresql://u:p@h:5432/db?connection_limit=100&pool_timeout=60&sslmode=require"
+    stripped = ProxyExtrasDBManager._strip_prisma_query_params(url)
+    assert "connection_limit" not in stripped
+    assert "pool_timeout" not in stripped
+    assert "sslmode=require" in stripped
+
+
+def test_strip_prisma_query_params_passthrough_no_query():
+    """URLs without query strings are returned unchanged."""
+    url = "postgresql://u:p@h:5432/db"
+    assert ProxyExtrasDBManager._strip_prisma_query_params(url) == url
+
+
+def test_migration_timestamp_extracts_leading_digits():
+    assert _migration_timestamp("20260101000000_add_foo") == 20260101000000
+    assert _migration_timestamp("20250326162113_baseline") == 20250326162113
+
+
+def test_migration_timestamp_returns_zero_on_malformed():
+    assert _migration_timestamp("0_init") == 0
+    assert _migration_timestamp("not_a_migration") == 0
+
+
+def test_max_migration_timestamp():
+    names = {"20250326000000_a", "20260415000000_b", "20251115000000_c"}
+    assert _max_migration_timestamp(names) == 20260415000000
+
+
+def test_max_migration_timestamp_empty_set():
+    assert _max_migration_timestamp(set()) == 0
+
+
+def test_v1_default_still_calls_resolve_all_migrations(monkeypatch, tmp_path):
+    """v1 (default) continues to call _resolve_all_migrations on the happy path.
+
+    This is the existing buggy behavior — we're not fixing it in v1, only
+    offering v2 as opt-in. This test pins the default so that a future
+    inadvertent default flip is caught.
+    """
+    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
+    (tmp_path / "schema.prisma").write_text("// stub")
+
+    # Stub `prisma migrate deploy` to claim success with pending migrations
+    # applied, which is the code path that triggers the legacy post-migration
+    # sanity check (a call to _resolve_all_migrations).
+    class FakeResult:
+        stdout = "Applied migration.\n"
+        stderr = ""
+
+    def fake_run(cmd, *args, **kwargs):
+        return FakeResult()
+
+    resolve_called = {"n": 0}
+
+    def fake_resolve(*args, **kwargs):
+        resolve_called["n"] += 1
+
+    monkeypatch.setattr("subprocess.run", fake_run)
+    monkeypatch.setattr(ProxyExtrasDBManager, "_resolve_all_migrations", fake_resolve)
+
+    ok = ProxyExtrasDBManager.setup_database(use_migrate=True)  # v2 flag NOT set
+    assert ok is True
+    assert resolve_called["n"] == 1, "v1 default should still invoke the legacy path"
+
+
+def test_v2_db_push_wraps_subprocess_error_as_runtime_error(monkeypatch, tmp_path):
+    """v2: a failing `prisma db push` must raise RuntimeError, not leak
+    CalledProcessError past proxy_cli.py's `except RuntimeError`."""
+    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
+    (tmp_path / "schema.prisma").write_text("// stub")
+
+    stderr = "db push error"
+    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
+        with pytest.raises(RuntimeError, match="prisma db push failed"):
+            ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=True)
+
+
+def test_v2_warn_ahead_of_head_swallows_db_errors(monkeypatch, tmp_path):
+    """_warn_if_db_ahead_of_head must never raise — it's informational.
+
+    Non-connection DB errors (e.g. InsufficientPrivilege from a user
+    without SELECT on _prisma_migrations) must be caught, not propagated.
+    """
+    import psycopg
+
+    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
+    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
+    (tmp_path / "schema.prisma").write_text("// stub")
+
+    class _FakeConn:
+        def __enter__(self):
+            return self
+
+        def __exit__(self, *a):
+            return False
+
+        def execute(self, *a, **kw):
+            # Simulate an InsufficientPrivilege (subclass of DatabaseError).
+            raise psycopg.errors.InsufficientPrivilege("permission denied")
+
+    def _fake_connect(*a, **kw):
+        return _FakeConn()
+
+    monkeypatch.setattr("psycopg.connect", _fake_connect)
+
+    # Must not raise.
+    ProxyExtrasDBManager._warn_if_db_ahead_of_head(str(tmp_path))
+
+
+def test_v2_resolve_specific_migration_failure_raises_runtime_error(
+    monkeypatch, tmp_path
+):
+    """If marking a migration as applied fails inside P3009 idempotent
+    recovery, the subprocess error must be re-raised as RuntimeError so
+    proxy_cli.py catches it cleanly (instead of leaking CalledProcessError)."""
+    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(
+        ProxyExtrasDBManager, "_roll_back_migration", lambda *a, **kw: None
+    )
+
+    # First call: migrate deploy -> P3009 idempotent error.
+    # Recovery path tries _resolve_specific_migration; that also raises.
+    def _failing_resolve(*a, **kw):
+        raise subprocess.CalledProcessError(
+            returncode=1,
+            cmd="prisma migrate resolve --applied",
+            stderr="resolve failed",
+            output="",
+        )
+
+    monkeypatch.setattr(
+        ProxyExtrasDBManager, "_resolve_specific_migration", _failing_resolve
+    )
+
+    stderr = (
+        "Error: P3009\nMigration `20260101000000_some_migration` failed\n"
+        "relation already exists"
+    )
+    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
+        with pytest.raises(
+            RuntimeError, match="Failed to mark migration .* as applied"
+        ):
+            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
+
+
+def test_v2_does_not_call_resolve_all_migrations(monkeypatch, tmp_path):
+    """v2 must never call _resolve_all_migrations — that's the bug it fixes."""
+    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")
+
+    class FakeResult:
+        stdout = "Applied migration.\n"
+        stderr = ""
+
+    monkeypatch.setattr("subprocess.run", lambda *a, **kw: FakeResult())
+
+    resolve_called = {"n": 0}
+    monkeypatch.setattr(
+        ProxyExtrasDBManager,
+        "_resolve_all_migrations",
+        lambda *a, **kw: resolve_called.__setitem__("n", resolve_called["n"] + 1),
+    )
+
+    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"
diff --git a/litellm/constants.py b/litellm/constants.py
index b9bea466247..1bd977dd9a9 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -13,6 +13,12 @@ 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 +136,7 @@ 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.
@@ -1583,6 +1590,7 @@ 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"
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/integrations/SlackAlerting/slack_alerting.py b/litellm/integrations/SlackAlerting/slack_alerting.py
index c137164ecdb..748ef938cea 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
@@ -1944,6 +1945,69 @@ 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
+
+        if prisma_client is None:
+            from litellm.proxy.proxy_server import prisma_client as global_prisma_client
+
+            prisma_client = global_prisma_client  # rebind-ok: fall back to the proxy's global client
+        if prisma_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=prisma_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
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/datadog/datadog_llm_obs.py b/litellm/integrations/datadog/datadog_llm_obs.py
index e5789965c6e..5e116b7301a 100644
--- a/litellm/integrations/datadog/datadog_llm_obs.py
+++ b/litellm/integrations/datadog/datadog_llm_obs.py
@@ -11,6 +11,7 @@ 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
@@ -30,12 +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,
@@ -44,6 +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):
@@ -222,12 +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,
@@ -241,22 +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",
@@ -314,6 +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
@@ -335,7 +557,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
     def _get_response_messages(
         self, standard_logging_payload: StandardLoggingPayload, call_type: str | None
-    ) -> list[object]:
+    ) -> tuple[Message, ...]:
         """
         Get the messages from the response object
 
@@ -344,7 +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):
@@ -357,7 +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,
@@ -375,12 +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
@@ -485,17 +707,6 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         # Default fallback for unknown or passthrough operations
         return "llm"
 
-    def _ensure_string_content(self, messages: str | Sequence[object] | Mapping[object, object] | None) -> list[object]:
-        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, object]:
         """
         Fields to track in DD LLM Observability metadata from litellm standard logging payload
@@ -524,10 +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
@@ -647,107 +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: Sequence[object]) -> list[dict[str, object]]:
-        """
-        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, object]:
-        """
-        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, object]] = {}
-        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, object]:
-        """
-        Extract tool call information from both input messages and response for Datadog metadata.
-        """
-        tool_call_metadata: Final[dict[str, object]] = {}
-
-        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/otel/model/payloads.py b/litellm/integrations/otel/model/payloads.py
index d35405538f6..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
@@ -104,12 +130,25 @@ class LLMUsage:
         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=as_int(usage_object.get("cache_creation_input_tokens")),
-            cache_read_input_tokens=as_int(usage_object.get("cache_read_input_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"),
+            ),
         )
 
 
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/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/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 207e024ce0b..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
 
 
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 350e5403e4c..9a6fb11f978 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
@@ -2957,13 +2959,25 @@ 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:
@@ -3003,32 +3017,39 @@ 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")
 
@@ -5033,7 +5054,9 @@ 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
@@ -5051,7 +5074,7 @@ 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
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/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 2fca19dc8d1..ff46440ff5c 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -1281,6 +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
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/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index 0bfe7dddd7f..aa805ccea71 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -1516,7 +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",
diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py
index b1f927fd8f9..c60ebd844ba 100644
--- a/litellm/llms/anthropic/common_utils.py
+++ b/litellm/llms/anthropic/common_utils.py
@@ -325,13 +325,17 @@ 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 AnthropicModelInfo._get_model_capability(model, "supports_forced_tool_use") is not False:
+        if not AnthropicModelInfo.forced_tool_use_unsupported(model):
             return False
         if not (litellm.drop_params or drop_params):
             raise litellm.utils.UnsupportedParamsError(
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 45c7825344b..66e36dab2ba 100644
--- a/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
+++ b/litellm/llms/anthropic/experimental_pass_through/messages/streaming_iterator.py
@@ -86,22 +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)
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/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/base_llm/guardrail_translation/base_translation.py b/litellm/llms/base_llm/guardrail_translation/base_translation.py
index b07a6b986d7..220fcedb0f8 100644
--- a/litellm/llms/base_llm/guardrail_translation/base_translation.py
+++ b/litellm/llms/base_llm/guardrail_translation/base_translation.py
@@ -155,8 +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.
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/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 6f99f572686..5363c3c0366 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,
@@ -1073,6 +1074,7 @@ 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)
@@ -1148,7 +1150,7 @@ 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)
@@ -1612,7 +1614,7 @@ 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)
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 8e709349400..2a4c38e71ea 100644
--- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
@@ -3,6 +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.constants import RESPONSE_FORMAT_TOOL_NAME
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_anthropic_image_obj,
 )
@@ -11,6 +12,7 @@ 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,
 )
@@ -74,10 +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"
 
@@ -101,6 +107,16 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
         # Restore original model name
         model = original_model
 
+        # 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
diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py
index 30a77d57f24..66ee5f10679 100644
--- a/litellm/llms/bedrock/common_utils.py
+++ b/litellm/llms/bedrock/common_utils.py
@@ -816,6 +816,30 @@ 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
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/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index 3a7f78fd5ba..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
@@ -397,6 +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,
@@ -408,15 +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,
@@ -443,11 +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(
@@ -473,10 +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
diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index ed628f55350..96a5ed663fc 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -14,9 +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 (
@@ -24,6 +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,
@@ -32,6 +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
@@ -49,7 +56,10 @@ from litellm.types.utils import (
 if TYPE_CHECKING:
     from fastapi import HTTPException
 
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    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
 
@@ -1005,3 +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/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 24dbd7c08d0..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
@@ -41,17 +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,
@@ -63,11 +83,13 @@ from litellm.types.utils import GenericGuardrailAPIInputs
 if TYPE_CHECKING:
     from fastapi import HTTPException
 
-    from litellm.integrations.custom_guardrail import CustomGuardrail
+    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):
@@ -82,6 +104,10 @@ 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:
@@ -658,8 +684,32 @@ class OpenAIResponsesHandler(BaseTranslation):
     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:
         """
@@ -837,3 +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 09028b6dc5f..01313e95878 100644
--- a/litellm/llms/openai/responses/transformation.py
+++ b/litellm/llms/openai/responses/transformation.py
@@ -15,6 +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 *
@@ -36,6 +37,7 @@ 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):
@@ -210,8 +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
@@ -248,6 +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,
@@ -773,7 +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/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/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/transformation.py
index d7ad69593c6..ef03e61a858 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
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index ce725a69bd9..c710db1a749 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1482,7 +1482,7 @@
         "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",
@@ -1557,7 +1557,7 @@
         "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",
@@ -1632,7 +1632,7 @@
         "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",
@@ -1707,7 +1707,7 @@
         "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",
@@ -3254,6 +3254,7 @@
         "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,
@@ -38565,12 +38566,22 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
     },
     "parallel_ai/search": {
-        "input_cost_per_query": 0.004,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-fast": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
     "parallel_ai/search-pro": {
-        "input_cost_per_query": 0.009,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-turbo": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
@@ -44142,6 +44153,7 @@
         "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,
@@ -44212,6 +44224,7 @@
         "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,
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/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index 3efb6429326..d1ef73a15cd 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,
@@ -86,8 +92,6 @@ def _connection_error_message(exc: BaseException) -> str:
 
 
 if MCP_AVAILABLE:
-    from mcp.types import Tool as MCPTool
-
     from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
         _UPSTREAM_OAUTH_DISCOVERY_AUTH_TYPES,
         global_mcp_server_manager,
@@ -99,6 +103,7 @@ 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 +808,6 @@ 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 +851,19 @@ 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 +871,36 @@ 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"),
-            }
+                # Query all servers the user has access to
+                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
@@ -1173,6 +1184,7 @@ 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,
@@ -1402,11 +1414,28 @@ 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 = None  # rebind-ok: set inside the timeout scope below
+            with anyio.move_on_after(listing_deadline):
+                list_tools_result = await client.list_tools(raise_on_error=True)  # rebind-ok: fills the init above
+            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/_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 c549f48126e..18714256a8f 100644
--- a/litellm/proxy/_types.py
+++ b/litellm/proxy/_types.py
@@ -1216,6 +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
@@ -2436,9 +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(
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/client/cli/commands/agents.py b/litellm/proxy/client/cli/commands/agents.py
index 45e05d353fb..c591cbabee1 100644
--- a/litellm/proxy/client/cli/commands/agents.py
+++ b/litellm/proxy/client/cli/commands/agents.py
@@ -9,6 +9,7 @@ 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"
@@ -151,31 +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.
 
@@ -202,7 +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/claude_settings.py b/litellm/proxy/client/cli/commands/claude_settings.py
index ea1fa019c83..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
@@ -17,6 +18,8 @@ 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"
@@ -87,9 +90,12 @@ def merge_claude_settings(
     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
@@ -106,7 +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:
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/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 1d860b02875..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,
@@ -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(
@@ -3442,6 +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,
@@ -3502,11 +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
@@ -3569,6 +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
@@ -3579,8 +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,
@@ -3634,6 +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.
@@ -3642,17 +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/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/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
index 0237d82a0d9..30526d30dc5 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
@@ -31,6 +31,7 @@ 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
@@ -215,6 +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.
@@ -2709,6 +2720,24 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
                 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
diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py
index 14d2332a7eb..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 (
@@ -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,
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/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
index ff306eb65f1..79d5d0a016f 100644
--- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
+++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py
@@ -812,6 +812,8 @@ def _resolve_team_callback_wiring(
         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(
diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py
index 86f6853a625..23932ba7c8c 100644
--- a/litellm/proxy/proxy_cli.py
+++ b/litellm/proxy/proxy_cli.py
@@ -913,14 +913,13 @@ class ProxyInitializationHelpers:
     envvar="ENFORCE_PRISMA_MIGRATION_CHECK",
 )
 @click.option(
-    "--use_v2_migration_resolver/--use_legacy_migration_resolver",
-    default=True,
+    "--use_v2_migration_resolver",
+    is_flag=True,
+    default=False,
     help=(
-        "Which database migration resolver to run at startup. The default v2 "
-        "resolver avoids the diff-and-force recovery path that can cause schema "
-        "thrashing during rolling deploys where two LiteLLM versions contend for "
-        "the same DB. Pass --use_legacy_migration_resolver, or set "
-        "USE_V2_MIGRATION_RESOLVER=false, to fall back to v1."
+        "Opt into the v2 migration resolver. Avoids the diff-and-force recovery "
+        "path that can cause schema thrashing during rolling deploys where two "
+        "LiteLLM versions contend for the same DB. Default is the v1 resolver."
     ),
     envvar="USE_V2_MIGRATION_RESOLVER",
 )
@@ -1226,6 +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,
@@ -1254,6 +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
@@ -1271,11 +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
@@ -1289,10 +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
@@ -1311,11 +1317,10 @@ def run_server(
                 else:
                     if not use_v2_migration_resolver:
                         print(
-                            "\033[1;33mLiteLLM Proxy: Using the legacy (v1) migration resolver. "
-                            "The default v2 resolver is safer: it avoids the diff-and-force "
-                            "recovery that caused schema thrashing during rolling deploys. "
-                            "Remove --use_legacy_migration_resolver / "
-                            "USE_V2_MIGRATION_RESOLVER=false to switch back to it.\033[0m"
+                            "\033[1;33mLiteLLM Proxy: Using default (v1) migration resolver. "
+                            "If your deployment has seen schema thrashing during rolling "
+                            "deploys, try --use_v2_migration_resolver (safer: avoids the "
+                            "diff-and-force recovery that caused the thrash).\033[0m"
                         )
                     try:
                         setup_ok: Final = PrismaManager.setup_database(
@@ -1323,10 +1328,10 @@ def run_server(
                             use_v2_resolver=use_v2_migration_resolver,
                         )
                     except RuntimeError as e:
-                        # Raised on unrecoverable migration errors: permission
-                        # failures from either resolver, the v2 resolver's
-                        # non-idempotent failures, and any `prisma db push`
-                        # against a partitioned LiteLLM_SpendLogs.
+                        # Raised on unrecoverable migration errors: the v2
+                        # resolver's non-idempotent failures and permission
+                        # issues, and any `prisma db push` against a
+                        # partitioned LiteLLM_SpendLogs.
                         print(
                             f"\033[1;31mLiteLLM Proxy: Database migration cannot proceed. {e}\033[0m",
                             file=sys.stderr,
diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 70bf8fd0554..77a80ea0052 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, ValidationError
 from typing_extensions import NotRequired, ReadOnly, assert_never
 
 from litellm._uuid import uuid
@@ -253,6 +253,7 @@ from litellm.constants import (
     PROXY_BUDGET_RESCHEDULER_MAX_TIME,
     PROXY_BUDGET_RESCHEDULER_MIN_TIME,
     PROXY_CONFIG_RELOAD_INTERVAL_SECONDS,
+    USER_SPEND_ALERTS_JOB_ID,
     WEEKLY_SPEND_REPORT_JOB_ID,
 )
 from litellm.exceptions import RejectedRequestError
@@ -9866,6 +9867,35 @@ 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
 
@@ -12481,11 +12511,21 @@ 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:
@@ -14962,17 +15002,25 @@ 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()
@@ -14987,7 +15035,7 @@ 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,
@@ -15006,7 +15054,7 @@ 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,
@@ -16434,6 +16482,16 @@ 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"}
diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py
index f4d8fd7d906..91d2ece7a51 100644
--- a/litellm/proxy/spend_tracking/budget_reservation.py
+++ b/litellm/proxy/spend_tracking/budget_reservation.py
@@ -120,13 +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)
@@ -134,21 +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),
@@ -258,6 +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:
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/responses/litellm_completion_transformation/custom_tools.py b/litellm/responses/litellm_completion_transformation/custom_tools.py
index 90491739bb0..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"``."""
@@ -103,7 +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 b2edf2bf9ed..db1c3acbefb 100644
--- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py
+++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py
@@ -114,6 +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
@@ -227,6 +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(
@@ -248,7 +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,
                     )
@@ -300,6 +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(
@@ -325,7 +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,
                     )
@@ -335,7 +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,
             )
@@ -345,6 +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(
diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py
index 3b7810e97e5..5f3e88bb12f 100644
--- a/litellm/responses/litellm_completion_transformation/transformation.py
+++ b/litellm/responses/litellm_completion_transformation/transformation.py
@@ -93,6 +93,7 @@ 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,
@@ -2034,7 +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",
@@ -2065,7 +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",
                     )
@@ -2502,8 +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",
diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py
index de802b95086..82abac3e772 100644
--- a/litellm/responses/streaming_iterator.py
+++ b/litellm/responses/streaming_iterator.py
@@ -1023,7 +1023,7 @@ 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,
@@ -1090,7 +1090,7 @@ 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,
@@ -1274,10 +1274,10 @@ def _add_text_like_part_events(
         )
 
 
-def _build_synthetic_response_events(
+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()
diff --git a/litellm/router.py b/litellm/router.py
index edff8294c3e..23d8907fb49 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
 
@@ -143,7 +143,11 @@ 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 (
@@ -821,6 +825,7 @@ 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
@@ -4918,6 +4923,19 @@ 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 +4982,11 @@ 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 +4996,14 @@ 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 +5061,10 @@ 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 +5103,35 @@ 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 +5243,13 @@ 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 +5305,11 @@ 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 +5319,14 @@ 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
@@ -6807,6 +6882,9 @@ 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:
@@ -6851,15 +6929,15 @@ 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]["*"]
@@ -6917,9 +6995,9 @@ 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:
@@ -6950,9 +7028,9 @@ 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:
@@ -6979,14 +7057,14 @@ 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:
@@ -6995,12 +7073,12 @@ 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(
@@ -7046,6 +7124,7 @@ 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)
@@ -7471,6 +7550,24 @@ 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.
@@ -7886,6 +7983,31 @@ 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.
@@ -7898,27 +8020,26 @@ 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 = []
@@ -8165,6 +8286,52 @@ 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
@@ -8253,6 +8420,11 @@ 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,
@@ -8301,6 +8473,19 @@ 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
                 )
@@ -8730,6 +8915,7 @@ 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
@@ -8994,6 +9180,11 @@ 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,
@@ -9249,6 +9440,11 @@ 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,
@@ -9342,8 +9538,12 @@ 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)
@@ -12026,6 +12226,7 @@ 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
@@ -12141,6 +12342,7 @@ 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
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index 924574537f3..3d37ca216a7 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -214,6 +214,91 @@ 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.
+    """
+    from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs
+
+    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,
+    and the requested group still resolves when no tier-keyed chain exists, so configs keyed
+    on the router name (the documented contract) keep working behind auto-routers.
+    """
+    ordered: Final = (get_pre_routing_selection(kwargs), 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:
@@ -412,6 +497,7 @@ 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/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/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/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/utils.py b/litellm/types/utils.py
index addb7b730de..5783a39b30c 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
@@ -3486,17 +3519,22 @@ 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}
 
@@ -3598,6 +3636,8 @@ all_litellm_params = (
         "client",
         "rpm",
         "tpm",
+        "default_api_key_rpm_limit",
+        "default_api_key_tpm_limit",
         "itpm",
         "otpm",
         "max_parallel_requests",
diff --git a/litellm/utils.py b/litellm/utils.py
index 028682661f7..252b6756937 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2869,10 +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
 
@@ -4877,11 +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]] = [
@@ -5860,6 +5855,7 @@ 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),
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index ce725a69bd9..c710db1a749 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -1482,7 +1482,7 @@
         "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",
@@ -1557,7 +1557,7 @@
         "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",
@@ -1632,7 +1632,7 @@
         "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",
@@ -1707,7 +1707,7 @@
         "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",
@@ -3254,6 +3254,7 @@
         "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,
@@ -38565,12 +38566,22 @@
         "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models"
     },
     "parallel_ai/search": {
-        "input_cost_per_query": 0.004,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-fast": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
     "parallel_ai/search-pro": {
-        "input_cost_per_query": 0.009,
+        "input_cost_per_query": 0.005,
+        "litellm_provider": "parallel_ai",
+        "mode": "search"
+    },
+    "parallel_ai/search-turbo": {
+        "input_cost_per_query": 0.001,
         "litellm_provider": "parallel_ai",
         "mode": "search"
     },
@@ -44142,6 +44153,7 @@
         "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,
@@ -44212,6 +44224,7 @@
         "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,
diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py
index c541c035db7..a5e00799519 100644
--- a/tests/code_coverage_tests/router_code_coverage.py
+++ b/tests/code_coverage_tests/router_code_coverage.py
@@ -81,6 +81,7 @@ 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)
 ]
 
 
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/models.py b/tests/e2e/models.py
index 967144dfb16..79d9e011f7e 100644
--- a/tests/e2e/models.py
+++ b/tests/e2e/models.py
@@ -806,6 +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"]
@@ -820,6 +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..c0596177cc1
--- /dev/null
+++ b/tests/e2e/test_junit_properties.py
@@ -0,0 +1,146 @@
+"""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,
+)
+
+
+class FakeMarker:
+    def __init__(self, name: str, *args: object) -> None:
+        self.name = name
+        self.args = args
+
+
+class FakeItem:
+    """The three attributes junit_properties reads off a pytest Item."""
+
+    def __init__(
+        self, nodeid: str, location: tuple[str, int | None, str], markers: tuple[FakeMarker, ...] = ()
+    ) -> None:
+        self.nodeid = nodeid
+        self.location = location
+        self.user_properties: list[tuple[str, str]] = []
+        self._markers = markers
+
+    def iter_markers(self, name: str):
+        return (marker for marker in self._markers if marker.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) -> None:
+        item = FakeItem(
+            "logging/test_x.py::TestFoo::test_bar",
+            ("logging/test_x.py", 40, "TestFoo.test_bar"),
+            (FakeMarker("covers", "LOG-1", "LOG-2"),),
+        )
+        assert result_properties(item) == (
+            ("package", "logging"),
+            ("covers", "LOG-1,LOG-2"),
+            ("source", "tests/e2e/logging/test_x.py:41"),
+        )
+
+    def test_attach_is_idempotent(self) -> None:
+        """Collection can run the hook more than once; a second pass must not
+        double the <property> entries in the report."""
+        item = FakeItem("logging/test_x.py::test_bar", ("logging/test_x.py", 40, "test_bar"))
+        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/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_setup_database_fail_fast.py b/tests/litellm-proxy-extras/test_setup_database_fail_fast.py
deleted file mode 100644
index ef447315a8c..00000000000
--- a/tests/litellm-proxy-extras/test_setup_database_fail_fast.py
+++ /dev/null
@@ -1,571 +0,0 @@
-"""Regression tests for ProxyExtrasDBManager's v2 migration resolver.
-
-v2 is the proxy CLI default; v1 stays reachable via the `use_v2_resolver`
-kwarg, which still defaults to False for direct callers.
-"""
-
-import subprocess
-from unittest.mock import patch
-
-import pytest
-
-from litellm_proxy_extras.utils import (
-    _PRISMA_ATTEMPTS,
-    ProxyExtrasDBManager,
-    _max_migration_timestamp,
-    _migration_timestamp,
-)
-
-
-def _fake_migrate_deploy_failure(returncode: int, stderr: str):
-    def _run(*args, **kwargs):
-        raise subprocess.CalledProcessError(
-            returncode=returncode,
-            cmd=args[0],
-            stderr=stderr,
-            output="",
-        )
-
-    return _run
-
-
-def test_v2_p3018_permission_error_raises_runtime_error(monkeypatch, tmp_path):
-    """v2: a permission failure during migrate deploy raises RuntimeError."""
-    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")
-
-    stderr = (
-        "Error: P3018\nMigration name: 20250326162113_baseline\n"
-        "Database error code: 42501\npermission denied for schema public"
-    )
-    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
-        with pytest.raises(RuntimeError, match="permission"):
-            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-
-def test_v2_non_idempotent_p3009_raises_runtime_error(monkeypatch, tmp_path):
-    """v2: a non-idempotent migration failure raises (no silent recovery)."""
-    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")
-
-    stderr = (
-        "Error: P3009\nMigration `20260101000000_genuinely_broken` failed\n"
-        'Reason: syntax error at or near "BRKN" LINE 42'
-    )
-    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_strip_prisma_query_params_removes_connection_limit():
-    """DATABASE_URLs with Prisma-specific params should be parseable by psycopg."""
-    url = "postgresql://u:p@h:5432/db?connection_limit=100&pool_timeout=60&sslmode=require"
-    stripped = ProxyExtrasDBManager._strip_prisma_query_params(url)
-    assert "connection_limit" not in stripped
-    assert "pool_timeout" not in stripped
-    assert "sslmode=require" in stripped
-
-
-def test_strip_prisma_query_params_passthrough_no_query():
-    """URLs without query strings are returned unchanged."""
-    url = "postgresql://u:p@h:5432/db"
-    assert ProxyExtrasDBManager._strip_prisma_query_params(url) == url
-
-
-def test_migration_timestamp_extracts_leading_digits():
-    assert _migration_timestamp("20260101000000_add_foo") == 20260101000000
-    assert _migration_timestamp("20250326162113_baseline") == 20250326162113
-
-
-def test_migration_timestamp_returns_zero_on_malformed():
-    assert _migration_timestamp("0_init") == 0
-    assert _migration_timestamp("not_a_migration") == 0
-
-
-def test_max_migration_timestamp():
-    names = {"20250326000000_a", "20260415000000_b", "20251115000000_c"}
-    assert _max_migration_timestamp(names) == 20260415000000
-
-
-def test_max_migration_timestamp_empty_set():
-    assert _max_migration_timestamp(set()) == 0
-
-
-def test_v1_default_still_calls_resolve_all_migrations(monkeypatch, tmp_path):
-    """v1 (default) continues to call _resolve_all_migrations on the happy path.
-
-    This is the existing buggy behavior — we're not fixing it in v1, only
-    offering v2 as opt-in. This test pins the default so that a future
-    inadvertent default flip is caught.
-    """
-    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
-    (tmp_path / "schema.prisma").write_text("// stub")
-
-    # Stub `prisma migrate deploy` to claim success with pending migrations
-    # applied, which is the code path that triggers the legacy post-migration
-    # sanity check (a call to _resolve_all_migrations).
-    class FakeResult:
-        stdout = "Applied migration.\n"
-        stderr = ""
-
-    def fake_run(cmd, *args, **kwargs):
-        return FakeResult()
-
-    resolve_called = {"n": 0}
-
-    def fake_resolve(*args, **kwargs):
-        resolve_called["n"] += 1
-
-    monkeypatch.setattr("subprocess.run", fake_run)
-    monkeypatch.setattr(ProxyExtrasDBManager, "_resolve_all_migrations", fake_resolve)
-
-    ok = ProxyExtrasDBManager.setup_database(use_migrate=True)  # v2 flag NOT set
-    assert ok is True
-    assert resolve_called["n"] == 1, "v1 default should still invoke the legacy path"
-
-
-def test_v2_db_push_wraps_subprocess_error_as_runtime_error(monkeypatch, tmp_path):
-    """v2: a failing `prisma db push` must raise RuntimeError, not leak
-    CalledProcessError past proxy_cli.py's `except RuntimeError`."""
-    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
-    (tmp_path / "schema.prisma").write_text("// stub")
-
-    stderr = "db push error"
-    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
-        with pytest.raises(RuntimeError, match="prisma db push failed"):
-            ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=True)
-
-
-def test_v2_warn_ahead_of_head_swallows_db_errors(monkeypatch, tmp_path):
-    """_warn_if_db_ahead_of_head must never raise — it's informational.
-
-    Non-connection DB errors (e.g. InsufficientPrivilege from a user
-    without SELECT on _prisma_migrations) must be caught, not propagated.
-    """
-    import psycopg
-
-    monkeypatch.setenv("DATABASE_URL", "postgresql://u:p@localhost:9/x")
-    monkeypatch.setattr(ProxyExtrasDBManager, "_get_prisma_dir", lambda: str(tmp_path))
-    (tmp_path / "schema.prisma").write_text("// stub")
-
-    class _FakeConn:
-        def __enter__(self):
-            return self
-
-        def __exit__(self, *a):
-            return False
-
-        def execute(self, *a, **kw):
-            # Simulate an InsufficientPrivilege (subclass of DatabaseError).
-            raise psycopg.errors.InsufficientPrivilege("permission denied")
-
-    connects = {"n": 0}
-
-    def _fake_connect(*a, **kw):
-        connects["n"] += 1
-        return _FakeConn()
-
-    monkeypatch.setattr("psycopg.connect", _fake_connect)
-
-    assert ProxyExtrasDBManager._warn_if_db_ahead_of_head(str(tmp_path)) is None
-    assert connects["n"] == 1, "the failing query must actually have been reached"
-
-
-def test_v2_resolve_specific_migration_failure_raises_runtime_error(
-    monkeypatch, tmp_path
-):
-    """If marking a migration as applied fails inside P3009 idempotent
-    recovery, the subprocess error must be re-raised as RuntimeError so
-    proxy_cli.py catches it cleanly (instead of leaking CalledProcessError)."""
-    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(
-        ProxyExtrasDBManager, "_roll_back_migration", lambda *a, **kw: None
-    )
-
-    # First call: migrate deploy -> P3009 idempotent error.
-    # Recovery path tries _resolve_specific_migration; that also raises.
-    def _failing_resolve(*a, **kw):
-        raise subprocess.CalledProcessError(
-            returncode=1,
-            cmd="prisma migrate resolve --applied",
-            stderr="resolve failed",
-            output="",
-        )
-
-    monkeypatch.setattr(
-        ProxyExtrasDBManager, "_resolve_specific_migration", _failing_resolve
-    )
-
-    stderr = (
-        "Error: P3009\nMigration `20260101000000_some_migration` failed\n"
-        "relation already exists"
-    )
-    with patch("subprocess.run", side_effect=_fake_migrate_deploy_failure(1, stderr)):
-        with pytest.raises(
-            RuntimeError, match=r"Failed to mark migration .* as applied"
-        ):
-            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-
-def test_v2_does_not_call_resolve_all_migrations(monkeypatch, tmp_path):
-    """v2 must never call _resolve_all_migrations — that's the bug it fixes."""
-    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")
-
-    class FakeResult:
-        stdout = "Applied migration.\n"
-        stderr = ""
-
-    monkeypatch.setattr("subprocess.run", lambda *a, **kw: FakeResult())
-
-    resolve_called = {"n": 0}
-    monkeypatch.setattr(
-        ProxyExtrasDBManager,
-        "_resolve_all_migrations",
-        lambda *a, **kw: resolve_called.__setitem__("n", resolve_called["n"] + 1),
-    )
-
-    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_STDERR = (
-    "Error: ERROR: deadlock detected\n"
-    "DETAIL: Process 277 waits for ExclusiveLock on advisory lock "
-    "[17556,0,72707369,1]; blocked by process 278.\n"
-    "Process 278 waits for ShareLock on virtual transaction 3/1041; "
-    "blocked by process 277."
-)
-
-
-class _DeployApplied:
-    stdout = "All migrations have been successfully applied."
-    stderr = ""
-    returncode = 0
-
-
-def _deploy_only(deploy_side_effect):
-    """subprocess.run stand-in that only intercepts `prisma migrate deploy`.
-
-    Scoped by argv so the Prisma toolchain check cannot consume the mock first.
-    """
-    deploys = {"n": 0}
-
-    def _run(*args, **kwargs):
-        cmd = args[0] if args else kwargs.get("args", [])
-        if list(cmd)[-2:] == ["migrate", "deploy"]:
-            deploys["n"] += 1
-            return deploy_side_effect(deploys["n"], cmd)
-        return _DeployApplied()
-
-    return _run, deploys
-
-
-def _prepare_v2_resolver(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 *_a, **_k: None)
-
-
-def test_v2_retries_transient_advisory_lock_deadlock(monkeypatch, tmp_path):
-    """v2: replicas racing `migrate deploy` deadlock on Prisma's advisory
-    lock, which is transient and must be retried rather than kill the boot."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        if n == 1:
-            raise subprocess.CalledProcessError(
-                returncode=1, cmd=cmd, stderr=_DEADLOCK_STDERR, output=""
-            )
-        return _DeployApplied()
-
-    run, deploys = _deploy_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-    assert ok is True
-    assert deploys["n"] == 2, "the deadlocked deploy must be retried, not raised"
-
-
-def test_v2_persistent_advisory_lock_deadlock_eventually_raises(monkeypatch, tmp_path):
-    """v2: the deadlock retry is bounded, so a deadlock that never clears
-    still raises instead of looping or reporting success."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        raise subprocess.CalledProcessError(
-            returncode=1, cmd=cmd, stderr=_DEADLOCK_STDERR, output=""
-        )
-
-    run, deploys = _deploy_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        with pytest.raises(RuntimeError, match="after 4 attempts"):
-            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-    assert deploys["n"] == 4
-
-
-@pytest.mark.parametrize(
-    "stderr",
-    [
-        "Error: P1001: Can't reach database server at `db`:`5432`",
-        "Error: P1002: The database server was reached but timed out.",
-    ],
-)
-def test_v2_retries_transient_database_connectivity_errors(monkeypatch, tmp_path, stderr):
-    """v2: a database not accepting connections yet is retried, not fatal."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        if n == 1:
-            raise subprocess.CalledProcessError(
-                returncode=1, cmd=cmd, stderr=stderr, output=""
-            )
-        return _DeployApplied()
-
-    run, deploys = _deploy_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        ok = ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-    assert ok is True
-    assert deploys["n"] == 2, "an unreachable database must be retried, not raised"
-
-
-def test_v2_unreachable_database_still_fails_after_the_retries(monkeypatch, tmp_path):
-    """v2: a genuinely unreachable database still raises once the attempts
-    are spent, rather than passing as a successful migration."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        raise subprocess.CalledProcessError(
-            returncode=1,
-            cmd=cmd,
-            stderr="Error: P1001: Can't reach database server at `db`:`5432`",
-            output="",
-        )
-
-    run, deploys = _deploy_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        with pytest.raises(RuntimeError, match="after 4 attempts"):
-            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-    assert deploys["n"] == 4
-
-
-def test_v2_exhausted_retries_report_the_prisma_error(monkeypatch, tmp_path, caplog):
-    """v2: retrying must not swallow Prisma's stderr, which is captured and is
-    the only place the cause appears for an operator or a boot-log grep."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-    stderr = "Error: P1001: Can't reach database server at `wrong`:`5432`"
-
-    def _side_effect(n, cmd):
-        raise subprocess.CalledProcessError(
-            returncode=1, cmd=cmd, stderr=stderr, output=""
-        )
-
-    run, _ = _deploy_only(_side_effect)
-    with caplog.at_level("INFO", logger="litellm_proxy_extras"):
-        with patch("subprocess.run", side_effect=run):
-            with pytest.raises(RuntimeError) as exc_info:
-                ProxyExtrasDBManager.setup_database(
-                    use_migrate=True, use_v2_resolver=True
-                )
-
-    assert "P1001" in str(exc_info.value)
-    assert "P1001" in caplog.text
-
-
-def test_v2_db_push_retries_transient_failures(monkeypatch, tmp_path):
-    """v2: `prisma db push` retries a transient failure like v1 did.
-
-    Reached from the migrations Job (USE_PRISMA_DB_PUSH=true), not from the
-    proxy CLI, whose --use_prisma_db_push has its own loop in prisma_client.
-    """
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    pushes = {"n": 0}
-
-    def _run(*args, **kwargs):
-        cmd = list(args[0] if args else kwargs.get("args", []))
-        if cmd[-3:] != ["db", "push", "--accept-data-loss"]:
-            return _DeployApplied()
-        pushes["n"] += 1
-        if pushes["n"] == 1:
-            raise subprocess.CalledProcessError(
-                returncode=1,
-                cmd=cmd,
-                stderr="Error: P1001: Can't reach database server at `db`:`5432`",
-                output="",
-            )
-        return _DeployApplied()
-
-    monkeypatch.setattr(
-        ProxyExtrasDBManager, "spend_logs_is_partitioned", lambda: False
-    )
-    with patch("subprocess.run", side_effect=_run):
-        ok = ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=True)
-
-    assert ok is True
-    assert pushes["n"] == 2
-
-
-def test_v2_db_push_retries_are_bounded_and_report_the_prisma_error(
-    monkeypatch, tmp_path
-):
-    """v2: a database that never comes back stops after _PRISMA_ATTEMPTS and
-    surfaces the prisma error, rather than retrying the boot forever."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    pushes = {"n": 0}
-
-    def _run(*args, **kwargs):
-        cmd = list(args[0] if args else kwargs.get("args", []))
-        if cmd[-3:] != ["db", "push", "--accept-data-loss"]:
-            return _DeployApplied()
-        pushes["n"] += 1
-        raise subprocess.CalledProcessError(
-            returncode=1,
-            cmd=cmd,
-            stderr="Error: P1001: Can't reach database server at `db`:`5432`",
-            output="",
-        )
-
-    monkeypatch.setattr(
-        ProxyExtrasDBManager, "spend_logs_is_partitioned", lambda: False
-    )
-    with patch("subprocess.run", side_effect=_run):
-        with pytest.raises(RuntimeError) as exc:
-            ProxyExtrasDBManager.setup_database(
-                use_migrate=False, use_v2_resolver=True
-            )
-
-    assert pushes["n"] == _PRISMA_ATTEMPTS
-    assert "P1001" in str(exc.value)
-
-
-def _db_push_only(push_side_effect):
-    """subprocess.run stand-in that only intercepts `prisma db push`."""
-    pushes = {"n": 0}
-
-    def _run(*args, **kwargs):
-        cmd = list(args[0] if args else kwargs.get("args", []))
-        if cmd[-3:] != ["db", "push", "--accept-data-loss"]:
-            return _DeployApplied()
-        pushes["n"] += 1
-        return push_side_effect(pushes["n"], cmd)
-
-    return _run, pushes
-
-
-def _timed_out_for_real():
-    """Capture what subprocess.run really puts on a TimeoutExpired.
-
-    Under text=True it still leaves stderr as bytes, unlike CalledProcessError,
-    so hardcoding a str here would test a shape production never sees. Derived
-    at import, before any test patches subprocess.run.
-    """
-    try:
-        subprocess.run(
-            ["sh", "-c", "echo 'Error: P1001 unreachable' >&2; sleep 5"],
-            timeout=0.2,
-            check=True,
-            capture_output=True,
-            text=True,
-        )
-    except subprocess.TimeoutExpired as e:
-        return e
-    raise AssertionError("the helper command was supposed to time out")
-
-
-_TIMEOUT_TEMPLATE = _timed_out_for_real()
-
-
-def _real_timeout_expired(cmd):
-    return subprocess.TimeoutExpired(
-        cmd=cmd,
-        timeout=_TIMEOUT_TEMPLATE.timeout,
-        output=_TIMEOUT_TEMPLATE.stdout,
-        stderr=_TIMEOUT_TEMPLATE.stderr,
-    )
-
-
-def test_v2_db_push_retries_a_timeout(monkeypatch, tmp_path):
-    """v2: a `prisma db push` that times out is retried, not turned into a
-    TypeError by classifying its bytes stderr as if it were text."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        if n == 1:
-            raise _real_timeout_expired(cmd)
-        return _DeployApplied()
-
-    monkeypatch.setattr(
-        ProxyExtrasDBManager, "spend_logs_is_partitioned", lambda: False
-    )
-    run, pushes = _db_push_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        ok = ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=True)
-
-    assert ok is True
-    assert pushes["n"] == 2
-
-
-def test_v2_db_push_timeouts_are_bounded(monkeypatch, tmp_path):
-    """v2: a `prisma db push` that never stops timing out gives up as a
-    RuntimeError, which is the only exception proxy_cli.py exits cleanly on."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        raise _real_timeout_expired(cmd)
-
-    monkeypatch.setattr(
-        ProxyExtrasDBManager, "spend_logs_is_partitioned", lambda: False
-    )
-    run, pushes = _db_push_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        with pytest.raises(RuntimeError, match=r"prisma db push failed after \d+"):
-            ProxyExtrasDBManager.setup_database(use_migrate=False, use_v2_resolver=True)
-
-    assert pushes["n"] == _PRISMA_ATTEMPTS
-
-
-def test_v2_unclassified_failure_is_not_treated_as_transient(monkeypatch, tmp_path):
-    """v2: an unrecognised deploy failure still raises on the first attempt."""
-    _prepare_v2_resolver(monkeypatch, tmp_path)
-
-    def _side_effect(n, cmd):
-        raise subprocess.CalledProcessError(
-            returncode=1,
-            cmd=cmd,
-            stderr="Error: relation \"LiteLLM_SpendLogs\" does not exist",
-            output="",
-        )
-
-    run, deploys = _deploy_only(_side_effect)
-    with patch("subprocess.run", side_effect=run):
-        with pytest.raises(RuntimeError, match="cannot be auto-recovered"):
-            ProxyExtrasDBManager.setup_database(use_migrate=True, use_v2_resolver=True)
-
-    assert deploys["n"] == 1
-
-
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/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_basic_python_version.py b/tests/local_testing/test_basic_python_version.py
index 506c58d26b4..fb06ed6b69d 100644
--- a/tests/local_testing/test_basic_python_version.py
+++ b/tests/local_testing/test_basic_python_version.py
@@ -305,16 +305,14 @@ def _run_proxy_server_smoke_test(extra_proxy_args=None):
 
 
 def test_litellm_proxy_server_config_no_general_settings():
-    """Exercises the default (v2) migration resolver."""
+    """Exercises the default (v1) migration resolver."""
     _run_proxy_server_smoke_test()
 
 
-def test_litellm_proxy_server_config_no_general_settings_legacy_resolver():
-    """Exercises the legacy (v1) migration resolver against a real database.
+def test_litellm_proxy_server_config_no_general_settings_v2_resolver():
+    """Exercises the opt-in v2 migration resolver.
 
-    v2 is the default, so the no-arg test above already covers it. This one is
-    the only place the v1 opt-out gets real-DB migration plus proxy-boot
-    coverage, and it runs in a separate CI job against its own Postgres to
-    avoid collisions with the default variant.
+    Runs in a separate CI job against a local Postgres to avoid collisions
+    with the v1 variant when they share a database.
     """
-    _run_proxy_server_smoke_test(extra_proxy_args=["--use_legacy_migration_resolver"])
+    _run_proxy_server_smoke_test(extra_proxy_args=["--use_v2_migration_resolver"])
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/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/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/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_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/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_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_otel_v2_sources_of_truth.py b/tests/test_litellm/integrations/otel/test_otel_v2_sources_of_truth.py
index ca628aa3405..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
@@ -541,6 +541,74 @@ def test_llm_call_adapter_extracts_cache_tokens_from_usage_object():
     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
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/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..0e1c832ebf5 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"
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 9ab66d55f3f..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
@@ -1435,6 +1435,80 @@ class TestFlattenTopLevelSchemaCombinators:
         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."""
 
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_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 c7328adb0b3..366f61ded49 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,
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 2a955845861..0f9f8259bef 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
@@ -6354,3 +6354,33 @@ def test_anthropic_drop_params_reduces_mixed_output_config_to_format(monkeypatch
     )
 
     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/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/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 a122d97a0f0..41d82e4f960 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
@@ -643,3 +643,31 @@ def test_bedrock_chat_invoke_drop_params_still_inlines_for_non_native(local_mode
     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
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 37ca801a7a7..70f3153ed7e 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -5248,6 +5248,84 @@ 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
@@ -6211,7 +6289,7 @@ 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",
     )
 
@@ -6497,6 +6575,39 @@ def test_unforced_tool_choice_unaffected_on_fable_5_1_converse(local_model_cost_
     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
 ):
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/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/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 3ef5e39fc5f..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
@@ -871,6 +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)."""
@@ -1038,3 +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_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/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/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..9419f88a981 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 +727,28 @@ 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
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..0480bbc40a7 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
@@ -214,6 +214,46 @@ 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 +564,131 @@ 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 +951,7 @@ 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 +1031,7 @@ 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 +1113,123 @@ 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 +1431,11 @@ 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 +1501,11 @@ 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
@@ -3021,9 +3308,7 @@ 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/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/client/cli/test_claude_settings.py b/tests/test_litellm/proxy/client/cli/test_claude_settings.py
index 898f9ab1ed7..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
@@ -199,6 +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 053c90c36b4..c78bdfa75b1 100644
--- a/tests/test_litellm/proxy/client/cli/test_up_commands.py
+++ b/tests/test_litellm/proxy/client/cli/test_up_commands.py
@@ -225,6 +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})
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 bcda1b8b61d..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
@@ -5524,7 +5524,9 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca
     """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."""
+    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,
@@ -5582,8 +5584,9 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca
     finally:
         unified_module.endpoint_guardrail_translation_mappings = None
 
-    assert len(out) == 3
+    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: ") :])
@@ -5592,6 +5595,156 @@ async def test_streaming_end_of_stream_block_emits_error_frame_instead_of_trunca
     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
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 0b32558a00a..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
@@ -1844,7 +1844,8 @@ class TestStreamingHttpErrorFrames:
 
         out = await _drive_stream(UnifiedLLMGuardrails(), guardrail, chunks)
 
-        assert out[:2] == chunks
+        assert out[0] == chunks[0]
+        assert chunks[1] not in out
         frame = out[-1]
         assert isinstance(frame, bytes)
         text = frame.decode()
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_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py
index a81c6b4c656..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
@@ -17489,3 +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 393953ccf68..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):
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 f5ae0fe5977..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,
@@ -5464,7 +5466,10 @@ def test_the_marker_check_distinguishes_the_two_route_kinds():
     assert request_dispatched_to_pass_through_endpoint(builtin) is False
 
 
-async def _drive_passthrough_request_and_capture_logging(user_api_key_dict: UserAPIKeyAuth) -> tuple[int, object]:
+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
@@ -5487,10 +5492,12 @@ async def _drive_passthrough_request_and_capture_logging(user_api_key_dict: User
     mock_request.query_params = QueryParams({})
     mock_request.body = AsyncMock(return_value=b'{"model": "gemini-2.0-flash"}')
 
-    captured_data: dict = {}
+    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()
@@ -5623,3 +5630,103 @@ async def test_resolve_team_callback_wiring_fails_open_on_operational_error():
     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/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/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_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py
index 5e2dd358d75..3e70dee23b7 100644
--- a/tests/test_litellm/proxy/test_proxy_cli.py
+++ b/tests/test_litellm/proxy/test_proxy_cli.py
@@ -1737,8 +1737,7 @@ class TestRunServerDbSetup:
         mock_atexit_register,
         mock_subprocess_run,
     ):
-        """Which resolver and which migration mode run_server hands setup_database,
-        across the db push flag, the v2/legacy flag pair and USE_V2_MIGRATION_RESOLVER."""
+        """Test that use_prisma_db_push flag correctly controls PrismaManager.setup_database use_migrate parameter"""
         from litellm.proxy.proxy_cli import run_server
 
         # Mock subprocess.run to simulate prisma being available
@@ -1788,7 +1787,7 @@ class TestRunServerDbSetup:
             # use_prisma_db_push should be False (default), so use_migrate should be True
             run_server.main(["--local", "--skip_server_startup"], standalone_mode=False)
             mock_setup_database.assert_called_with(
-                use_migrate=True, use_v2_resolver=True
+                use_migrate=True, use_v2_resolver=False
             )
 
             # Reset mocks
@@ -1803,38 +1802,9 @@ class TestRunServerDbSetup:
                 standalone_mode=False,
             )
             mock_setup_database.assert_called_with(
-                use_migrate=False, use_v2_resolver=True
+                use_migrate=False, use_v2_resolver=False
             )
 
-            for argv, env_value, expected_v2 in (
-                ([], None, True),
-                (["--use_v2_migration_resolver"], None, True),
-                (["--use_legacy_migration_resolver"], None, False),
-                ([], "false", False),
-                ([], "true", True),
-                (["--use_v2_migration_resolver"], "false", True),
-                (["--use_legacy_migration_resolver"], "true", False),
-            ):
-                mock_setup_database.reset_mock()
-                mock_should_update_schema.reset_mock()
-                mock_should_update_schema.return_value = True
-
-                resolver_env = (
-                    {"USE_V2_MIGRATION_RESOLVER": env_value}
-                    if env_value is not None
-                    else {}
-                )
-                os.environ.pop("USE_V2_MIGRATION_RESOLVER", None)
-                with patch.dict(os.environ, resolver_env):
-                    run_server.main(
-                        ["--local", "--skip_server_startup", *argv],
-                        standalone_mode=False,
-                    )
-                assert mock_setup_database.call_args.kwargs == {
-                    "use_migrate": True,
-                    "use_v2_resolver": expected_v2,
-                }, f"argv={argv} env={env_value}"
-
     @patch("subprocess.run")
     @patch("atexit.register")
     @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database")
@@ -1899,7 +1869,7 @@ class TestRunServerDbSetup:
                 )
             assert exc_info.value.code == 1
             mock_setup_database.assert_called_once_with(
-                use_migrate=True, use_v2_resolver=True
+                use_migrate=True, use_v2_resolver=False
             )
 
     @patch("subprocess.run")
@@ -2011,6 +1981,7 @@ class TestRunServerDbSetup:
             use_migrate=True, use_v2_resolver=True
         )
 
+
 # --- Module-level helpers for worker startup hook tests ---
 
 _dummy_hook_called = False
@@ -2481,6 +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_server.py b/tests/test_litellm/proxy/test_proxy_server.py
index 43280258153..91fca8f1e27 100644
--- a/tests/test_litellm/proxy/test_proxy_server.py
+++ b/tests/test_litellm/proxy/test_proxy_server.py
@@ -10445,6 +10445,75 @@ 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
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 aba79fe11bf..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
@@ -648,6 +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
@@ -3343,6 +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 01148f627f1..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
@@ -132,7 +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
@@ -197,7 +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}'
 
@@ -291,7 +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__
 
@@ -349,7 +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():
@@ -404,8 +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():
@@ -461,10 +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
@@ -557,3 +558,58 @@ def test_object_tool_call_arguments_stream_as_valid_json():
     )
 
     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/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..894b2d9e74f 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,
 )
 
@@ -1090,3 +1093,119 @@ 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_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/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_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 44c1cdbff06..84f6344be35 100644
--- a/tests/test_litellm/test_router.py
+++ b/tests/test_litellm/test_router.py
@@ -11595,3 +11595,138 @@ 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"
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/type-discipline-budget.json b/type-discipline-budget.json
index 3d2e97d55a5..52cb9628252 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,6 +1,6 @@
 {
   "LIT001": {
-    "limit": 22367
+    "limit": 22364
   },
   "LIT002": {
     "limit": 26777
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)/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/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/ShadowEvalSection.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/ShadowEvalSection.test.tsx
index 64e03985f57..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
@@ -97,6 +97,7 @@ import {
   useStopShadowEval,
   type ShadowEvalJob,
 } from "./useShadowEval";
+import { chooseSelectOption } from "../../../../../tests/test-utils";
 
 const job = (overrides: Partial<ShadowEvalJob> = {}): ShadowEvalJob => ({
   job_id: "job-1",
@@ -437,8 +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 up to 4 auto-routers"));
-    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();
 
@@ -470,8 +470,7 @@ describe("ShadowEvalSection", () => {
     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 user.click(screen.getByPlaceholderText("Select up to 4 auto-routers"));
-    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/ }));
     await user.click(screen.getByText("Start shadow eval"));
@@ -502,8 +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 up to 4 auto-routers"));
-    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/ }));
 
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)/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/page.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx
index a504d75bb63..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
@@ -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 } } });
@@ -99,6 +108,22 @@ describe("ModelsAndEndpointsPage", () => {
     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", () => {
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)/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/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/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/add_auto_router_tab.test.tsx b/ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.test.tsx
index d8a955b719c..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);
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 318adcce369..03b7432e4ec 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
@@ -548,7 +548,9 @@ 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/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_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/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/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/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.tsx b/ui/litellm-dashboard/src/components/settings.tsx
index 72da01d0918..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",
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 7ead9bb64d4..f502ea77127 100644
--- a/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx
+++ b/ui/litellm-dashboard/src/components/shared/DataTable/DataTable.test.tsx
@@ -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;
@@ -176,16 +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"]);
   });
 
@@ -202,12 +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 }]);
   });
 
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/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/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/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index e944062e15e..6f044fec3f3 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -13289,6 +13289,58 @@ 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;
@@ -22962,7 +23014,7 @@ 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 */
@@ -25435,9 +25487,15 @@ 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;
             /**
@@ -34921,6 +34979,27 @@ 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 */
@@ -55852,6 +55931,70 @@ 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?: {
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/test-utils.tsx b/ui/litellm-dashboard/tests/test-utils.tsx
index 162b8a3df7b..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: 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);
 };