From c24927cf2ac363af4c55cf701181732f1849c8f7 Mon Sep 17 00:00:00 2001
From: tin <tin@berri.ai>
Date: Tue, 4 Aug 2026 20:31:55 +0000
Subject: [PATCH 001/113] fix(proxy): report requested model on Anthropic
 streaming message_start

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../streaming_model_restamp.py                |  79 +++++++++++++
 litellm/proxy/common_request_processing.py    |  25 +++-
 .../test_streaming_model_restamp.py           | 109 ++++++++++++++++++
 3 files changed, 212 insertions(+), 1 deletion(-)
 create mode 100644 litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
 create mode 100644 tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py

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..857b6abd065
--- /dev/null
+++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
@@ -0,0 +1,79 @@
+"""
+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
+
+from pydantic import TypeAdapter, ValidationError
+
+_MESSAGE_START_EVENT = "message_start"
+_SSE_DATA_FIELD = "data:"
+
+_EVENT_ADAPTER: TypeAdapter[dict[str, object]] = TypeAdapter(dict[str, object])
+
+
+def _restamped_event(event: dict[str, object], requested_model: str) -> dict[str, object] | None:
+    message = 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 = line.strip()
+    if not stripped.startswith(_SSE_DATA_FIELD):
+        return None
+    payload = stripped[len(_SSE_DATA_FIELD) :].strip()
+    if not payload or payload == "[DONE]":
+        return None
+    try:
+        event = _EVENT_ADAPTER.validate_json(payload)
+    except ValidationError:
+        return None
+    restamped = _restamped_event(event, requested_model)
+    if restamped is None:
+        return None
+    return f"data: {json.dumps(restamped, separators=(',', ':'))}"
+
+
+def _restamped_frame(frame: str, requested_model: str) -> str | None:
+    lines = frame.split("\n")
+    restamped = tuple(_restamped_data_line(line, requested_model) for line in lines)
+    if all(line is None for line in restamped):
+        return None
+    return "\n".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 = _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 = _restamped_frame(chunk.decode("utf-8", errors="ignore"), requested_model)
+        return chunk if restamped is None else restamped.encode("utf-8")
+
+    if isinstance(chunk, str):
+        if _MESSAGE_START_EVENT not in chunk:
+            return chunk
+        restamped = _restamped_frame(chunk, requested_model)
+        return chunk if restamped is None else restamped
+
+    return chunk
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index f9cad283166..fd5de0debec 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -70,6 +70,9 @@ if TYPE_CHECKING:
     ProxyConfig = _ProxyConfig
 else:
     ProxyConfig = Any
+from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
+    restamp_anthropic_stream_chunk_model,
+)
 from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request
 from litellm.types.utils import (
     ModelResponse,
@@ -1953,6 +1956,9 @@ 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=selected_data_generator,
@@ -2801,6 +2807,18 @@ class ProxyBaseLLMRequestProcessing:
         else:
             return chunk
 
+    @staticmethod
+    def _sse_chunk_serializer(restamp_model: str | None) -> StreamChunkSerializer:
+        if not restamp_model:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk
+
+        def serialize(chunk: object) -> str:
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk(
+                restamp_anthropic_stream_chunk_model(chunk, restamp_model)
+            )
+
+        return serialize
+
     @staticmethod
     async def _finalize_streaming_generator_cleanup(
         request: Request | None,
@@ -2990,6 +3008,7 @@ 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.
@@ -2998,13 +3017,17 @@ 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.
         """
         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(restamp_model),
             serialize_error=lambda proxy_exc: (
                 f"{STREAM_SSE_DATA_PREFIX}{json.dumps({'error': proxy_exc.to_dict()})}\n\n"
             ),
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..6e2c3f49445
--- /dev/null
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
@@ -0,0 +1,109 @@
+"""
+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 (
+    restamp_anthropic_stream_chunk_model,
+)
+from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
+
+
+def _message_start_frame(model: str) -> bytes:
+    payload = {
+        "type": "message_start",
+        "message": {"id": "msg_1", "type": "message", "role": "assistant", "model": model, "content": []},
+    }
+    return f"event: message_start\ndata: {json.dumps(payload)}\n\n".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"

From 02bb3f9310e6633caefd8f739d2340ebd0d56cff Mon Sep 17 00:00:00 2001
From: Timik232 <100406268+Timik232@users.noreply.github.com>
Date: Mon, 24 Aug 2026 20:56:54 +0300
Subject: [PATCH 002/113] fix(streaming): keep response id stable across
 streamed chunks

Providers that stream via GenericStreamingChunk (e.g. GigaChat) do not
propagate an upstream response id, so every chunk of one streamed
response got a freshly generated id. Pin CustomStreamWrapper.response_id
from the first chunk it creates, mirroring the existing 'created'
pinning (#11437).

Clients that merge deltas by chunk id (e.g. goose) split one reply into
one message per chunk.

Fixes #38098
---
 .../litellm_core_utils/streaming_handler.py   |  2 +
 .../test_streaming_handler.py                 | 79 +++++++++++++++++++
 2 files changed, 81 insertions(+)

diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py
index f6340426c1b..fb693943b2b 100644
--- a/litellm/litellm_core_utils/streaming_handler.py
+++ b/litellm/litellm_core_utils/streaming_handler.py
@@ -816,6 +816,8 @@ class CustomStreamWrapper:
         model_response: Final = ModelResponseStream(**args)
         if self.response_id is not None:
             model_response.id = self.response_id
+        elif model_response.id:
+            self.response_id = model_response.id
         if self.system_fingerprint is not None:
             model_response.system_fingerprint = self.system_fingerprint
 
diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
index b5e33a4e421..a76d427495c 100644
--- a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
+++ b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
@@ -4460,3 +4460,82 @@ def test_handle_stream_fallback_error_restores_context_only_after_exception_mapp
     finally:
         trace_id_var.set("")
         session_id_var.set("")
+
+
+class TestStableStreamingResponseId:
+    """
+    All chunks of one streamed response must share the same top-level id
+    (OpenAI streaming contract). Providers streaming via GenericStreamingChunk
+    (e.g. GigaChat) do not propagate an upstream response id, so
+    CustomStreamWrapper must pin the id from the first chunk it creates,
+    mirroring the existing `created` pinning (issue #11437).
+
+    Clients such as goose merge streamed deltas into one assistant message by
+    chunk id; per-chunk ids split a single reply into many messages.
+    """
+
+    def test_generic_chunks_share_one_id(self):
+        def _generic_chunks():
+            return iter(
+                [
+                    {
+                        "text": "Hello",
+                        "tool_use": None,
+                        "is_finished": False,
+                        "finish_reason": "",
+                        "usage": None,
+                        "index": 0,
+                    },
+                    {
+                        "text": " world",
+                        "tool_use": None,
+                        "is_finished": False,
+                        "finish_reason": "",
+                        "usage": None,
+                        "index": 0,
+                    },
+                    {
+                        "text": "",
+                        "tool_use": None,
+                        "is_finished": True,
+                        "finish_reason": "stop",
+                        "usage": {
+                            "prompt_tokens": 1,
+                            "completion_tokens": 2,
+                            "total_tokens": 3,
+                        },
+                        "index": 0,
+                    },
+                ]
+            )
+
+        wrapper = CustomStreamWrapper(
+            completion_stream=_generic_chunks(),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        ids = [chunk.id for chunk in wrapper if chunk.id]
+        assert ids, "no chunks emitted"
+        assert len(set(ids)) == 1, f"chunk ids differ across one stream: {ids}"
+
+    def test_creator_pins_id_from_first_chunk(self):
+        wrapper = CustomStreamWrapper(
+            completion_stream=iter([]),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        first = wrapper.model_response_creator()
+        assert wrapper.response_id == first.id
+        assert wrapper.model_response_creator().id == first.id
+
+    def test_provider_supplied_id_still_wins(self):
+        wrapper = CustomStreamWrapper(
+            completion_stream=iter([]),
+            model="gigachat/GigaChat-2-Max",
+            logging_obj=MagicMock(),
+            custom_llm_provider="gigachat",
+        )
+        wrapper.response_id = "chatcmpl-from-provider"
+        assert wrapper.model_response_creator().id == "chatcmpl-from-provider"

From 7eb757a49b8f52c70fbd769d07b878a67872a20f Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 29 Aug 2026 00:01:02 -0700
Subject: [PATCH 003/113] fix(bedrock): route streamed responses-API output
 through the unified guardrail

Streamed /v1/responses returned 500 whenever a Bedrock post_call guardrail
was enabled: the hook fed responses-API events into stream_chunk_builder,
which only understands chat-completions chunks, and the wrapped KeyError
surfaced as litellm.APIError before any ApplyGuardrail scan ran.

Delegate responses-API routes to UnifiedLLMGuardrails, whose translation
layer scans the assembled response at end of stream and only then releases
the buffered events, so flagged content never reaches the client.
---
 .../guardrail_hooks/bedrock_guardrails.py     | 29 +++++++
 .../test_bedrock_guardrails.py                | 77 +++++++++++++++++++
 2 files changed, 106 insertions(+)

diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
index dd76a27c80f..6f005f1569f 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py
@@ -30,6 +30,7 @@ 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.llm_cost_calc.guardrail_cost import bedrock_guardrail_cost
 from litellm.llms.anthropic.chat.guardrail_translation.handler import AnthropicMessagesHandler
@@ -206,6 +207,16 @@ 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.
@@ -2660,6 +2671,24 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM):
         Collect content from the stream and run the bedrock OUTPUT scan
         (post_call only validates the response).
         """
+        # 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/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
index 36b356e34d0..ba710b4a0e9 100644
--- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py
@@ -5345,3 +5345,80 @@ def test_initialize_bedrock_forwards_aws_external_id():
         assert guardrail.optional_params["aws_external_id"] == "external-id-123"
     finally:
         litellm.logging_callback_manager.remove_callback_from_list_by_object(litellm.callbacks, guardrail)
+
+
+def _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))

From 855f56fa946674c3a25ee873fca6a09d4783edcd Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 29 Aug 2026 16:25:28 -0700
Subject: [PATCH 004/113] fix(openai): flatten top-level tool schema
 combinators on chat completions

---
 .../llms/openai/chat/gpt_transformation.py    |  82 ++++++++++--
 .../chat/test_openai_gpt_transformation.py    | 118 ++++++++++++++++++
 2 files changed, 190 insertions(+), 10 deletions(-)

diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index 5894658e5d2..89062f60fc7 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
 
@@ -19,6 +20,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo
 )
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     drop_tool_reference_parts_from_tool_messages,
+    flatten_top_level_schema_combinators,
     get_tool_call_names,
     hoist_images_from_tool_messages,
 )
@@ -65,6 +67,22 @@ else:
     LiteLLMLoggingObj = Any
 
 
+_NO_TOOLS_UPDATE: Final[Mapping[str, object]] = MappingProxyType({})
+
+
+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
+
+
 class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     """
     Reference: https://platform.openai.com/docs/api-reference/chat/create
@@ -393,6 +411,26 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                 )
         return messages, tools
 
+    def _targets_openai_hosted_endpoint(
+        self,
+        custom_llm_provider: str | None,
+        api_base: str | None,
+    ) -> bool:
+        """
+        True only for the generic `openai` provider actually pointed at
+        api.openai.com (no custom api_base, or an openai.com host): the one
+        backend enforcing OpenAI-only request strictness.
+        """
+        if custom_llm_provider != "openai":
+            return False
+        resolved_api_base = api_base or litellm.api_base or os.getenv("OPENAI_BASE_URL") or os.getenv("OPENAI_API_BASE")
+        if not resolved_api_base:
+            return True
+        hostname: Final = urlparse(resolved_api_base).hostname
+        if hostname is None:
+            return True
+        return hostname == "openai.com" or hostname.endswith(".openai.com")
+
     def _should_preserve_cache_control_for_endpoint(
         self,
         custom_llm_provider: str | None,
@@ -404,15 +442,37 @@ 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), so
+        tool schemas bound for api.openai.com get their top-level combinators
+        flattened; OpenAI-compatible backends on a custom api_base accept the
+        caller's schema as-is and keep it.
+        """
+        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,
@@ -444,6 +504,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             "model": model,
             "messages": messages,
             **optional_params,
+            **self._flattened_tools_update_for_openai(optional_params, litellm_params),
         }
 
     async def async_transform_request(
@@ -473,6 +534,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                 "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/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py b/tests/test_litellm/llms/openai/chat/test_openai_gpt_transformation.py
index 3f346b5e8e7..e65ef239068 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
@@ -975,3 +975,121 @@ 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), so requests bound for
+    api.openai.com get those combinators flattened into one object schema,
+    while OpenAI-compatible backends on a custom api_base and other providers
+    keep the caller's schema untouched.
+    """
+
+    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"}

From 1c4674441c52afe22dbbe49402529fb67c78147c Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 29 Aug 2026 16:43:05 -0700
Subject: [PATCH 005/113] docs(openai): trim tool-flattening docstrings to
 upstream facts

---
 litellm/llms/openai/chat/gpt_transformation.py         | 10 +---------
 .../llms/openai/chat/test_openai_gpt_transformation.py |  5 +----
 2 files changed, 2 insertions(+), 13 deletions(-)

diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index 89062f60fc7..a81884702e9 100644
--- a/litellm/llms/openai/chat/gpt_transformation.py
+++ b/litellm/llms/openai/chat/gpt_transformation.py
@@ -416,11 +416,6 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         custom_llm_provider: str | None,
         api_base: str | None,
     ) -> bool:
-        """
-        True only for the generic `openai` provider actually pointed at
-        api.openai.com (no custom api_base, or an openai.com host): the one
-        backend enforcing OpenAI-only request strictness.
-        """
         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")
@@ -454,10 +449,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         """
         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), so
-        tool schemas bound for api.openai.com get their top-level combinators
-        flattened; OpenAI-compatible backends on a custom api_base accept the
-        caller's schema as-is and keep it.
+        model family, unlike the Responses API, where GPT-5+ accepts them.
         """
         tools: Final = optional_params.get("tools")
         if not isinstance(tools, list):
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 e65ef239068..19b245449a3 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
@@ -981,10 +981,7 @@ 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), so requests bound for
-    api.openai.com get those combinators flattened into one object schema,
-    while OpenAI-compatible backends on a custom api_base and other providers
-    keep the caller's schema untouched.
+    family, GPT-5 included, unlike the Responses API.
     """
 
     def setup_method(self):

From b418ccd738e8d3bbad05cbc824ce959e93e65e6a Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 29 Aug 2026 21:27:57 -0700
Subject: [PATCH 006/113] fix(azure): flatten top-level tool schema combinators
 on Azure chat completions

Azure's chat completions validator rejects tool parameters carrying a
top-level anyOf/oneOf/allOf for every model family. AzureOpenAIConfig and
the o-series config now flatten them via the shared helper moved to
prompt_templates common_utils. Requests bridged to the Responses API for
gpt-5.4+ with reasoning active keep the union, which that surface accepts
---
 .../prompt_templates/common_utils.py          | 13 +++
 litellm/llms/azure/chat/gpt_transformation.py | 17 ++++
 .../azure/chat/o_series_transformation.py     |  7 +-
 .../llms/openai/chat/gpt_transformation.py    | 17 +---
 ...ore_utils_prompt_templates_common_utils.py | 74 +++++++++++++++
 .../test_azure_chat_gpt_transformation.py     | 89 +++++++++++++++++++
 ...test_azure_chat_o_series_transformation.py | 45 ++++++++++
 7 files changed, 246 insertions(+), 16 deletions(-)

diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py
index 1c8f10d3307..48b597b06b4 100644
--- a/litellm/litellm_core_utils/prompt_templates/common_utils.py
+++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py
@@ -1246,6 +1246,19 @@ 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/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/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index a81884702e9..9adfb59f8a9 100644
--- a/litellm/llms/openai/chat/gpt_transformation.py
+++ b/litellm/llms/openai/chat/gpt_transformation.py
@@ -20,9 +20,9 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo
 )
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     drop_tool_reference_parts_from_tool_messages,
-    flatten_top_level_schema_combinators,
     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,
@@ -70,19 +70,6 @@ else:
 _NO_TOOLS_UPDATE: Final[Mapping[str, object]] = MappingProxyType({})
 
 
-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
-
-
 class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     """
     Reference: https://platform.openai.com/docs/api-reference/chat/create
@@ -462,7 +449,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         ):
             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
+            tool_with_flattened_parameters(tool) if isinstance(tool, dict) else tool for tool in tools
         ]
         return MappingProxyType({"tools": flattened})
 
diff --git a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
index 772fbf98c57..dcc0d72df91 100644
--- a/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
+++ b/tests/test_litellm/litellm_core_utils/prompt_templates/test_litellm_core_utils_prompt_templates_common_utils.py
@@ -1433,3 +1433,77 @@ class TestFlattenTopLevelSchemaCombinators:
         flatten_top_level_schema_combinators(schema)
 
         assert schema == snapshot
+
+
+class TestToolWithFlattenedParameters:
+    def _anyof_tool(self):
+        return {
+            "type": "function",
+            "function": {
+                "name": "automation_update",
+                "description": "Update an automation",
+                "parameters": {
+                    "type": "object",
+                    "anyOf": [
+                        {
+                            "properties": {"id": {"type": "string"}, "enabled": {"type": "boolean"}},
+                            "required": ["id", "enabled"],
+                        },
+                        {
+                            "properties": {"id": {"type": "string"}, "schedule": {"type": "string"}},
+                            "required": ["id", "schedule"],
+                        },
+                    ],
+                    "properties": {"id": {"type": "string"}},
+                    "required": ["id"],
+                },
+            },
+        }
+
+    def test_flattens_anyof_parameters_into_new_tool(self):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        tool = self._anyof_tool()
+        result = tool_with_flattened_parameters(tool)
+
+        assert result is not tool
+        parameters = result["function"]["parameters"]
+        assert "anyOf" not in parameters
+        assert parameters["type"] == "object"
+        assert set(parameters["properties"]) == {"id", "enabled", "schedule"}
+        assert parameters["required"] == ["id"]
+        assert result["function"]["name"] == "automation_update"
+        assert tool == self._anyof_tool()
+
+    def test_clean_parameters_return_the_same_tool_object(self):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        tool = {
+            "type": "function",
+            "function": {
+                "name": "lookup",
+                "parameters": {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["id"]},
+            },
+        }
+
+        assert tool_with_flattened_parameters(tool) is tool
+
+    @pytest.mark.parametrize(
+        "tool",
+        [
+            {"type": "function"},
+            {"type": "function", "function": "not-a-dict"},
+            {"type": "function", "function": {"name": "no_params"}},
+            {"type": "function", "function": {"name": "bad_params", "parameters": "not-a-dict"}},
+        ],
+    )
+    def test_non_dict_function_or_parameters_return_the_same_tool_object(self, tool):
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            tool_with_flattened_parameters,
+        )
+
+        assert tool_with_flattened_parameters(tool) is tool
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

From 74fb398f9baddda91b0de27dfdc6ecdad6c0ffe9 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sat, 29 Aug 2026 21:40:28 -0700
Subject: [PATCH 007/113] fix(ui): hide model write affordances from view-only
 admin sessions

---
 .../AutoRouters/AutoRoutersPanel.test.tsx     |  1 +
 .../AutoRouters/AutoRoutersPanel.tsx          | 14 +++++--
 .../AutoRouters/autoRouterRows.test.ts        | 15 +++++--
 .../models-and-endpoints/page.test.tsx        | 29 +++++++++++++-
 .../(dashboard)/models-and-endpoints/page.tsx |  5 ++-
 .../panels/AutoRoutersTabPanel.test.tsx       | 39 +++++++++++++++++++
 .../panels/AutoRoutersTabPanel.tsx            |  5 ++-
 .../src/components/add_model/AddModelForm.tsx |  7 +++-
 .../src/components/model_info_view.test.tsx   | 11 ++++++
 .../src/components/model_info_view.tsx        |  4 +-
 .../src/utils/modelPermissions.test.ts        | 38 +++++++++++++++---
 .../src/utils/modelPermissions.ts             | 23 +++++++----
 12 files changed, 163 insertions(+), 28 deletions(-)
 create mode 100644 ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/panels/AutoRoutersTabPanel.test.tsx

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 521f89a39f2..8bf3f6db8dd 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(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);
+    const { getByRole, queryByRole } = renderPage();
+    expect(queryByRole("tab", { name: "Add Model" })).not.toBeInTheDocument();
+    expect(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);
+    const { getByRole } = renderPage();
+    expect(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/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/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/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/utils/modelPermissions.test.ts b/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
index 179a9b7933a..6778c92a864 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);
+  });
+
+  // A blunt view-only gate would fail this: team-admin membership legitimately grants
+  // team-scoped creation, whatever the session role says.
+  it("still requires a team from a view-only admin who admins a team", () => {
+    expect(modelCreationScope(VIEW_ONLY_ADMIN, { teams: teamWhere("u-viewer", "admin"), ...noLimits })).toBe(
+      "team-required",
+    );
+  });
 });
 
 describe("canModifyModel", () => {
@@ -80,6 +97,15 @@ 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);
+  });
+
+  it("lets a view-only user who admins the owning team act on its row", () => {
+    expect(canModifyModel(VIEW_ONLY_ADMIN, teamWhere("u-viewer", "admin"), teamRow)).toBe(true);
   });
 });
diff --git a/ui/litellm-dashboard/src/utils/modelPermissions.ts b/ui/litellm-dashboard/src/utils/modelPermissions.ts
index b5914f9d7ea..9815ac9f0e2 100644
--- a/ui/litellm-dashboard/src/utils/modelPermissions.ts
+++ b/ui/litellm-dashboard/src/utils/modelPermissions.ts
@@ -15,8 +15,17 @@ import { isProxyAdminRole, isUserTeamAdminForAnyTeam, isUserTeamAdminForSingleTe
 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";
 
@@ -37,16 +46,16 @@ const isTeamAdminOf = (teams: Team[] | null, userID: string, teamId: string): bo
  * 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 (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 +72,18 @@ 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) {
     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);
 };

From b6bd749c02891b76b9f504794c3cb6eced8b8d49 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sun, 30 Aug 2026 10:01:44 -0700
Subject: [PATCH 008/113] fix(ui): withhold team-scoped model writes from
 view-only sessions too

The route-level RBAC in litellm/proxy/auth/route_checks.py 403s
/model/new, /model/update, and /model/delete for proxy_admin_viewer on
the session role alone, before ModelManagementAuthChecks' team-admin
carve-out can run. A view-only session therefore gets no model write
affordance, team admin or not.
---
 .../src/utils/modelPermissions.test.ts        | 14 ++++++----
 .../src/utils/modelPermissions.ts             | 28 ++++++++++++-------
 2 files changed, 26 insertions(+), 16 deletions(-)

diff --git a/ui/litellm-dashboard/src/utils/modelPermissions.test.ts b/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
index 6778c92a864..afc2ecd210f 100644
--- a/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
+++ b/ui/litellm-dashboard/src/utils/modelPermissions.test.ts
@@ -53,11 +53,11 @@ describe("modelCreationScope", () => {
     expect(canCreateModels(VIEW_ONLY_ADMIN, { teams: [], ...noLimits })).toBe(false);
   });
 
-  // A blunt view-only gate would fail this: team-admin membership legitimately grants
-  // team-scoped creation, whatever the session role says.
-  it("still requires a team from a view-only admin who admins a team", () => {
+  // _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(
-      "team-required",
+      "forbidden",
     );
   });
 });
@@ -105,7 +105,9 @@ describe("canModifyModel", () => {
     expect(canModifyModel(VIEW_ONLY_ADMIN, null, teamRow)).toBe(false);
   });
 
-  it("lets a view-only user who admins the owning team act on its row", () => {
-    expect(canModifyModel(VIEW_ONLY_ADMIN, teamWhere("u-viewer", "admin"), teamRow)).toBe(true);
+  // 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 9815ac9f0e2..843d9041026 100644
--- a/ui/litellm-dashboard/src/utils/modelPermissions.ts
+++ b/ui/litellm-dashboard/src/utils/modelPermissions.ts
@@ -3,14 +3,17 @@ 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;
@@ -42,13 +45,18 @@ 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 = (
   actor: ModelActor,
   { teams, disabledForInternalUsers }: ModelCreationLimits,
 ): ModelWriteScope => {
+  if (actor.isViewOnly) {
+    return "forbidden";
+  }
   if (isWritableProxyAdmin(actor)) {
     return "unscoped-ok";
   }
@@ -76,7 +84,7 @@ export const canModifyModel = (
   teams: Team[] | null,
   { teamId, isDbModel }: ModelRowOrigin,
 ): boolean => {
-  if (!isDbModel) {
+  if (actor.isViewOnly || !isDbModel) {
     return false;
   }
   if (isWritableProxyAdmin(actor)) {

From db1e0717f9c09570b6f7d932758a6fa736bdc648 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Sun, 30 Aug 2026 12:52:03 -0700
Subject: [PATCH 009/113] fix(guardrail_translation): assemble responses stream
 text from delta events for terminal-failure scans

---
 .../guardrail_translation/handler.py          | 30 +++++-
 ...test_openai_responses_guardrail_handler.py | 92 +++++++++++++++++++
 .../test_bedrock_guardrails.py                | 73 +++++++++++++++
 3 files changed, 194 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 24dbd7c08d0..ec70fe0d795 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -82,6 +82,10 @@ 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 +662,32 @@ 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:
         """
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..ad392d4962d 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."""
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 aaaa651f538..ef263dfe268 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
@@ -5667,3 +5667,76 @@ async def test_responses_api_stream_scans_output_and_replays_buffered_events():
     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))

From 1bf3ab53884ba62c0a24540e0b9b3972b41dc843 Mon Sep 17 00:00:00 2001
From: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Mon, 31 Aug 2026 14:45:31 +0000
Subject: [PATCH 010/113] fix(proxy): resolve router model aliases in
 /utils/supported_openai_params

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/proxy/proxy_server.py                 |  7 +++--
 .../proxy/proxy_server/test_routes_utils.py   | 31 ++++++++++++++++++-
 2 files changed, 35 insertions(+), 3 deletions(-)

diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 887716a383a..d1771cc9088 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -12478,11 +12478,14 @@ async def supported_openai_params(model: str):
         --header 'Authorization: Bearer sk-1234'
     ```
     """
+    global llm_router
     try:
-        model, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
+        deployments: Final = llm_router.get_model_list(model_name=model) if llm_router is not None else None
+        model_to_map: Final = deployments[0]["litellm_params"]["model"] if deployments else model
+        litellm_model, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model_to_map)
         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:
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..7615c5e66db 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -9,7 +9,7 @@ Pins (PR2):
 from __future__ import annotations
 
 import asyncio
-from unittest.mock import AsyncMock, MagicMock
+from unittest.mock import MagicMock
 
 import pytest
 
@@ -124,6 +124,35 @@ 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 ``model_name`` alias unknown to the cost map (e.g. ``claude-opus-4-6-cached``) resolves via the router's underlying ``litellm_params.model`` instead of 400ing."""
+    router = MagicMock()
+    router.get_model_list.return_value = [
+        {"model_name": "claude-opus-4-6-cached", "litellm_params": {"model": "anthropic/claude-opus-4-6"}}
+    ]
+    monkeypatch.setattr(proxy_server, "llm_router", router)
+    seen = []
+
+    def _get_llm_provider(model):
+        seen.append(model)
+        return (model, "anthropic", None, None)
+
+    monkeypatch.setattr(litellm, "get_llm_provider", _get_llm_provider)
+    monkeypatch.setattr(
+        litellm,
+        "get_supported_openai_params",
+        lambda model, custom_llm_provider=None: ["max_tokens"],
+    )
+
+    with auth_as():
+        response = client.get("/utils/supported_openai_params", params={"model": "claude-opus-4-6-cached"})
+
+    assert response.status_code == 200
+    assert response.json() == {"supported_openai_params": ["max_tokens"]}
+    router.get_model_list.assert_called_once_with(model_name="claude-opus-4-6-cached")
+    assert seen == ["anthropic/claude-opus-4-6"]
+
+
 def test_supported_openai_params_invalid_model(client, auth_as, monkeypatch):
     """Pins ``GET /utils/supported_openai_params`` (error: unknown model)."""
 

From ba817aa9bbf45b10e37103de59afab36792f13ff Mon Sep 17 00:00:00 2001
From: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Mon, 31 Aug 2026 14:54:50 +0000
Subject: [PATCH 011/113] fix(proxy): avoid NotRequired access on
 litellm_params model

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/proxy/proxy_server.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index d1771cc9088..693769446f4 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -12481,7 +12481,7 @@ async def supported_openai_params(model: str):
     global llm_router
     try:
         deployments: Final = llm_router.get_model_list(model_name=model) if llm_router is not None else None
-        model_to_map: Final = deployments[0]["litellm_params"]["model"] if deployments else model
+        model_to_map: Final = (deployments[0]["litellm_params"].get("model") or model) if deployments else model
         litellm_model, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model_to_map)
         return {
             "supported_openai_params": litellm.get_supported_openai_params(

From 2d01397e4da5093cae5b79296bf1f8805c58ab78 Mon Sep 17 00:00:00 2001
From: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Mon, 31 Aug 2026 15:03:52 +0000
Subject: [PATCH 012/113] test: pin llm_router in supported_openai_params tests

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 tests/test_litellm/proxy/proxy_server/test_routes_utils.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

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 7615c5e66db..4d6ce0812a4 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -99,6 +99,7 @@ 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",
@@ -125,7 +126,7 @@ 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 ``model_name`` alias unknown to the cost map (e.g. ``claude-opus-4-6-cached``) resolves via the router's underlying ``litellm_params.model`` instead of 400ing."""
+    """A router alias unknown to the cost map resolves via the deployment's ``litellm_params.model``."""
     router = MagicMock()
     router.get_model_list.return_value = [
         {"model_name": "claude-opus-4-6-cached", "litellm_params": {"model": "anthropic/claude-opus-4-6"}}
@@ -159,6 +160,7 @@ def test_supported_openai_params_invalid_model(client, auth_as, monkeypatch):
     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": "??"})

From bd0b9c78bd7bb149895a94101e07c323f86f5ff0 Mon Sep 17 00:00:00 2001
From: Emerson Gomes <emerson.gomes@thalesgroup.com>
Date: Mon, 31 Aug 2026 10:21:22 -0500
Subject: [PATCH 013/113] fix(router): keep order fallback on the requested
 order level

When a pre-call filter left no order-2 deployments, target_order matching
fell through to the remaining healthy list and reselected the failed
primary. Prompt-cache and deployment affinity also pinned that hop back
to order 1. Match the requested order strictly, skip those pins while
target_order is set, and keep target_order across retries of that hop.
---
 litellm/router.py                             |   6 +-
 .../router_utils/fallback_event_handlers.py   |   2 +
 .../deployment_affinity_check.py              |   2 +
 .../prompt_caching_deployment_check.py        |   3 +
 litellm/utils.py                              |   6 +-
 .../test_deployment_affinity_check.py         |  39 +++++
 .../test_prompt_caching_deployment_check.py   |  19 +++
 .../test_router_order_fallback.py             | 154 +++++++++++++++++-
 8 files changed, 220 insertions(+), 11 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index c93c1753f0e..81e49645462 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -2174,6 +2174,7 @@ class Router:
                 "client": model_client,
                 **kwargs,
             }
+            input_kwargs.pop("_target_order", None)
             response: Final = litellm.completion(**input_kwargs)
             verbose_router_logger.info("litellm.completion(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -3197,6 +3198,7 @@ class Router:
             }
             input_kwargs.pop("silent_model", None)
             input_kwargs.pop("include_fallback_errors", None)
+            input_kwargs.pop("_target_order", None)
 
             _response: Final = litellm.acompletion(**input_kwargs)
 
@@ -11928,7 +11930,7 @@ class Router:
         )
 
         ## ORDER FILTERING ## -> if user set 'order' in deployments, return deployments with lowest order (e.g. order=1 > order=2)
-        _target_order: Final = (request_kwargs or {}).pop("_target_order", None)
+        _target_order: Final = (request_kwargs or {}).get("_target_order")
         healthy_deployments = litellm.utils._get_order_filtered_deployments(
             cast(list[dict], healthy_deployments), target_order=_target_order
         )
@@ -12693,7 +12695,7 @@ class Router:
             )
 
         ## ORDER FILTERING ## -> if user set 'order' in deployments, return deployments with lowest order (e.g. order=1 > order=2)
-        _target_order: Final = (request_kwargs or {}).pop("_target_order", None)
+        _target_order: Final = (request_kwargs or {}).get("_target_order")
         healthy_deployments = litellm.utils._get_order_filtered_deployments(
             healthy_deployments, target_order=_target_order
         )
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index 924574537f3..c37fbdc8ed7 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -414,7 +414,9 @@ async def run_async_fallback(
             verbose_router_logger.info("Falling back to model_group = %s", mask_sensitive_structure(mg))
             if isinstance(mg, str):
                 kwargs["model"] = mg
+                kwargs.pop("_target_order", None)
             elif isinstance(mg, dict):
+                kwargs.pop("_target_order", None)
                 kwargs.update(mg)
             fallback_depth = fallback_depth + 1
             _hop_metadata = dict(kwargs.get(metadata_variable_name) or {})
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/utils.py b/litellm/utils.py
index 5e9e115ed54..c2739fa3a0e 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -4859,11 +4859,7 @@ 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]] = [
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/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index 7743cb005d0..33916444003 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -6,12 +6,15 @@ should be tried first, and higher order deployments should be used as fallbacks
 when lower order deployments fail.
 """
 
-from typing import Optional
+from typing import Final, Optional
 
 import pytest
 
+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.utils import _get_deployment_order, _get_order_filtered_deployments
 
 # ---------------------------------------------------------------------------
 # Unit tests for _get_order_filtered_deployments
@@ -49,13 +52,22 @@ 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 = [
@@ -406,6 +418,140 @@ 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(Exception) 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)
+        assert getattr(exc_info.value, "_hidden_params", {}).get("model_id") != "1"
+    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
+
+
 def test_check_non_standard_fallback_format():
     from litellm.router_utils.fallback_event_handlers import (
         _check_non_standard_fallback_format,

From 9fc77f12227e36a6d8e86336e1995931659f1c25 Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Tue, 30 Jun 2026 12:10:48 -0500
Subject: [PATCH 014/113] feat(cost): support time-based off-peak pricing in
 cost calculation

Some providers charge different per-token rates depending on the time of
day. DeepSeek, for example, has historically discounted its chat and
reasoner models during an off-peak window (16:30-00:30 UTC). LiteLLM's
cost map only modeled static per-token pricing, so cost tracking could
not stay accurate for these providers.

This adds optional off-peak pricing to a model entry: input_cost_per_token_off_peak,
output_cost_per_token_off_peak, cache_read_input_token_cost_off_peak, and an
off_peak_hours_utc window expressed as "HH:MM-HH:MM" in UTC (the window may
wrap past midnight). When the current UTC time falls inside the window, the
cost calculator uses the off-peak rates and otherwise falls back to the
standard rates, so existing models are unaffected. The fields are also
accepted as custom pricing on a deployment, so they can be set from the
proxy config or the SDK.

The window check is a pure function that takes the current time as an
argument, which keeps the regression tests deterministic without patching
the clock.
---
 .../litellm_core_utils/llm_cost_calc/utils.py |  72 +++++++++
 litellm/types/utils.py                        |  14 ++
 litellm/utils.py                              |   1 +
 .../llm_cost_calc/test_llm_cost_calc_utils.py | 152 ++++++++++++++++++
 4 files changed, 239 insertions(+)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 19e3f624268..576efb18bb0 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -4,6 +4,7 @@
 import re
 from collections.abc import Mapping
 from dataclasses import dataclass
+from datetime import datetime, timezone
 from types import MappingProxyType
 from typing import Any, Final, Literal, TypedDict, cast
 
@@ -290,10 +291,75 @@ def _get_tiered_base_costs(model_info: ModelInfo, usage: Usage) -> tuple[float,
     )
 
 
+def _is_within_off_peak_window(off_peak_hours_utc: str | list[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. The start is inclusive and the end is exclusive; malformed windows are ignored.
+    """
+    if current_time is None:
+        current_time = datetime.now(timezone.utc)
+    now = current_time.time()
+    windows = [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").time()
+            end = datetime.strptime(end_str.strip(), "%H:%M").time()
+        except (ValueError, AttributeError):
+            continue
+        if start <= end:
+            if start <= now < end:
+                return True
+        elif now >= start or now < end:
+            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 windows. Applied after threshold pricing so the discount is honored rather
+    than overwritten when a model combines off-peak and above-threshold rates. Any rate left
+    unset in off_peak_pricing falls back to the standard rate.
+    """
+    off_peak = model_info.get("off_peak_pricing")
+    if not off_peak:
+        return prompt_base_cost, completion_base_cost, cache_read_cost
+    hours_utc = off_peak.get("hours_utc")
+    if not hours_utc or not _is_within_off_peak_window(hours_utc, 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 _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]:
@@ -345,6 +411,9 @@ 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:
+        prompt_base_cost, completion_base_cost, cache_read_cost = _apply_off_peak_pricing(
+            model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
+        )
         return (
             prompt_base_cost,
             completion_base_cost,
@@ -451,6 +520,9 @@ def _get_token_base_cost(
             except Exception:
                 continue
 
+    prompt_base_cost, completion_base_cost, cache_read_cost = _apply_off_peak_pricing(
+        model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
+    )
     return (
         prompt_base_cost,
         completion_base_cost,
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 4bf8289d725..6583b125b62 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -193,6 +193,19 @@ class AgenticLoopParams(TypedDict, total=False):
     """The LLM provider name (e.g., 'bedrock', 'anthropic')"""
 
 
+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;
+    a window may wrap past midnight. Any rate left unset falls back to the standard rate.
+    """
+
+    hours_utc: str | list[str]
+    input_cost_per_token: float
+    output_cost_per_token: float
+    cache_read_input_token_cost: float
+
+
 class ModelInfoBase(ProviderSpecificModelInfo, total=False):
     key: Required[str]  # the key in litellm.model_cost which is returned
 
@@ -225,6 +238,7 @@ 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: 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
diff --git a/litellm/utils.py b/litellm/utils.py
index 5e9e115ed54..3389b8fcb78 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -5842,6 +5842,7 @@ 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/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..e226e255b05 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 +32,7 @@ from litellm.litellm_core_utils.llm_cost_calc.utils import (
     TokenTypeCostBreakdown,
     _calculate_input_cost,
     _get_token_base_cost,
+    _is_within_off_peak_window,
     calculate_cache_writing_cost,
     generic_cost_per_token,
     get_token_type_cost_breakdown,
@@ -3946,3 +3947,154 @@ def test_route_image_generation_cost_falls_back_to_requested_size(monkeypatch, r
     )
 
     assert cost == expected_cost
+
+
+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_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_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_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_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

From f2c663515cd335482ab8bd29651e68cf102ab4cd Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Sun, 2 Aug 2026 21:34:09 -0500
Subject: [PATCH 015/113] fix(cost): evaluate off-peak windows in UTC for
 timezone-aware inputs

_is_within_off_peak_window used current_time.time(), which drops tzinfo, so a caller passing a non-UTC aware datetime had the window compared against local wall-clock instead of UTC. That silently mispriced off-peak requests. Normalize aware datetimes to UTC before comparing; naive datetimes stay as-is per the documented UTC contract. Added a regression test with a UTC+8 datetime that fails without the fix
---
 litellm/litellm_core_utils/llm_cost_calc/utils.py   |  2 ++
 .../llm_cost_calc/test_llm_cost_calc_utils.py       | 13 +++++++++++++
 2 files changed, 15 insertions(+)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 576efb18bb0..ffa39850a5e 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -300,6 +300,8 @@ def _is_within_off_peak_window(off_peak_hours_utc: str | list[str], current_time
     """
     if current_time is None:
         current_time = datetime.now(timezone.utc)
+    elif current_time.tzinfo is not None:
+        current_time = current_time.astimezone(timezone.utc)
     now = current_time.time()
     windows = [off_peak_hours_utc] if isinstance(off_peak_hours_utc, str) else off_peak_hours_utc
     for window in windows:
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 e226e255b05..463a871c6cc 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
@@ -3983,6 +3983,19 @@ def test_is_within_off_peak_window_multiple_windows():
     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
 

From c813386bb2a482a9fb4e5ece08267bfd5d1eb2b3 Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Mon, 10 Aug 2026 21:47:08 -0500
Subject: [PATCH 016/113] refactor(cost): conform off-peak pricing to current
 lint budgets

Rebasing onto litellm_internal_staging picked up stricter ceilings than this
branch was written against. Bind the off-peak results to fresh names instead
of reassigning the base costs, mark the new locals Final, avoid rebinding the
current_time parameter, and make the window parse explicit about UTC so
DTZ007, LIT010 and LIT011 all stay within budget
---
 .../litellm_core_utils/llm_cost_calc/utils.py | 37 +++++++++----------
 litellm/types/utils.py                        | 10 ++---
 2 files changed, 22 insertions(+), 25 deletions(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index ffa39850a5e..66f47affb4d 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -2,7 +2,7 @@
 ## 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
 from types import MappingProxyType
@@ -291,24 +291,21 @@ def _get_tiered_base_costs(model_info: ModelInfo, usage: Usage) -> tuple[float,
     )
 
 
-def _is_within_off_peak_window(off_peak_hours_utc: str | list[str], current_time: datetime | None = None) -> bool:
+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. The start is inclusive and the end is exclusive; malformed windows are ignored.
     """
-    if current_time is None:
-        current_time = datetime.now(timezone.utc)
-    elif current_time.tzinfo is not None:
-        current_time = current_time.astimezone(timezone.utc)
-    now = current_time.time()
-    windows = [off_peak_hours_utc] if isinstance(off_peak_hours_utc, str) else off_peak_hours_utc
+    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").time()
-            end = datetime.strptime(end_str.strip(), "%H:%M").time()
+            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:
@@ -344,10 +341,10 @@ def _apply_off_peak_pricing(
     than overwritten when a model combines off-peak and above-threshold rates. Any rate left
     unset in off_peak_pricing falls back to the standard rate.
     """
-    off_peak = model_info.get("off_peak_pricing")
+    off_peak: Final = model_info.get("off_peak_pricing")
     if not off_peak:
         return prompt_base_cost, completion_base_cost, cache_read_cost
-    hours_utc = off_peak.get("hours_utc")
+    hours_utc: Final = off_peak.get("hours_utc")
     if not hours_utc or not _is_within_off_peak_window(hours_utc, current_time):
         return prompt_base_cost, completion_base_cost, cache_read_cost
     return (
@@ -413,15 +410,15 @@ 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:
-        prompt_base_cost, completion_base_cost, cache_read_cost = _apply_off_peak_pricing(
+        off_peak_prompt_cost, off_peak_completion_cost, off_peak_cache_read_cost = _apply_off_peak_pricing(
             model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
         )
         return (
-            prompt_base_cost,
-            completion_base_cost,
+            off_peak_prompt_cost,
+            off_peak_completion_cost,
             cache_creation_cost,
             cache_creation_cost_above_1hr,
-            cache_read_cost,
+            off_peak_cache_read_cost,
         )
 
     # Only sort the threshold keys (typically 1-2 keys instead of 66+)
@@ -522,15 +519,15 @@ def _get_token_base_cost(
             except Exception:
                 continue
 
-    prompt_base_cost, completion_base_cost, cache_read_cost = _apply_off_peak_pricing(
+    discounted_prompt_cost, discounted_completion_cost, discounted_cache_read_cost = _apply_off_peak_pricing(
         model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
     )
     return (
-        prompt_base_cost,
-        completion_base_cost,
+        discounted_prompt_cost,
+        discounted_completion_cost,
         cache_creation_cost,
         cache_creation_cost_above_1hr,
-        cache_read_cost,
+        discounted_cache_read_cost,
     )
 
 
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 6583b125b62..3ab3a2382dc 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -200,10 +200,10 @@ class OffPeakPricing(TypedDict, total=False):
     a window may wrap past midnight. Any rate left unset falls back to the standard rate.
     """
 
-    hours_utc: str | list[str]
-    input_cost_per_token: float
-    output_cost_per_token: float
-    cache_read_input_token_cost: float
+    hours_utc: ReadOnly[str | Sequence[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):
@@ -238,7 +238,7 @@ 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: OffPeakPricing | None  # time-windowed off-peak rates
+    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

From d302301a4e6a250170ef96a621026af78760be4a Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Thu, 13 Aug 2026 17:28:00 -0500
Subject: [PATCH 017/113] test(cost): move off-peak tests beside the related
 cost tests

They sat at the end of the file, which is where everyone else appends
too, so this branch picked up a conflict there on nearly every rebase.
Grouping them with the other _get_token_base_cost test keeps them clear
of that churn and next to the code they cover. Pure move, no test changes
---
 .../llm_cost_calc/test_llm_cost_calc_utils.py | 328 +++++++++---------
 1 file changed, 164 insertions(+), 164 deletions(-)

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 463a871c6cc..f1340df8b69 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
@@ -410,6 +410,170 @@ 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_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_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_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_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"
@@ -3947,167 +4111,3 @@ def test_route_image_generation_cost_falls_back_to_requested_size(monkeypatch, r
     )
 
     assert cost == expected_cost
-
-
-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_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_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_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

From 4f174ffdd1022a0ffa21c2ae6bd2154011a9368e Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Sat, 15 Aug 2026 10:49:51 -0500
Subject: [PATCH 018/113] fix(cost): apply off-peak rates on the tiered-pricing
 path

Tiered pricing resolves its own base rates and returns early, before the
off-peak swap ran, so a model carrying both tiered_pricing and off_peak_pricing
billed the tier rate around the clock. Route every base-cost path through one
helper so the window applies wherever the rates came from, and say plainly in
the docstring that an off-peak rate replaces the rate it lands on rather than
discounting it
---
 .../litellm_core_utils/llm_cost_calc/utils.py | 63 ++++++++++++-------
 .../llm_cost_calc/test_llm_cost_calc_utils.py | 32 ++++++++++
 2 files changed, 73 insertions(+), 22 deletions(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 66f47affb4d..be289f620cf 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -337,9 +337,10 @@ def _apply_off_peak_pricing(
     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 windows. Applied after threshold pricing so the discount is honored rather
-    than overwritten when a model combines off-peak and above-threshold rates. Any rate left
-    unset in off_peak_pricing falls back to the standard rate.
+    off_peak_pricing 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 off_peak:
@@ -354,6 +355,22 @@ def _apply_off_peak_pricing(
     )
 
 
+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,
@@ -376,7 +393,7 @@ 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)
@@ -410,15 +427,16 @@ 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:
-        off_peak_prompt_cost, off_peak_completion_cost, off_peak_cache_read_cost = _apply_off_peak_pricing(
-            model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
-        )
-        return (
-            off_peak_prompt_cost,
-            off_peak_completion_cost,
-            cache_creation_cost,
-            cache_creation_cost_above_1hr,
-            off_peak_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+)
@@ -519,15 +537,16 @@ def _get_token_base_cost(
             except Exception:
                 continue
 
-    discounted_prompt_cost, discounted_completion_cost, discounted_cache_read_cost = _apply_off_peak_pricing(
-        model_info, current_time, prompt_base_cost, completion_base_cost, cache_read_cost
-    )
-    return (
-        discounted_prompt_cost,
-        discounted_completion_cost,
-        cache_creation_cost,
-        cache_creation_cost_above_1hr,
-        discounted_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/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 f1340df8b69..8f348b36d35 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
@@ -574,6 +574,38 @@ def test_get_model_info_propagates_off_peak_fields():
     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"

From 27aefade5fc9c9276cf752f949376a32ddedf3a7 Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Sat, 22 Aug 2026 23:11:57 -0500
Subject: [PATCH 019/113] fix(cost): treat an equal-ended off-peak window as
 the whole day

A window whose start equals its end is the natural way to spell off-peak all
day, and the docstring's promise that a window may wrap past midnight invites
it. It took the non-wrap branch instead, where start <= now < end can never
hold, so it matched nothing. It parses cleanly, so it never reached the branch
that ignores malformed windows: no exception, no log, and the model billed at
standard rates around the clock while the config said otherwise. Let equality
fall through to the wrap branch, which covers every instant, and say so in the
docstring.

Reported by @xyzs996 in review.
---
 litellm/litellm_core_utils/llm_cost_calc/utils.py   |  5 +++--
 .../llm_cost_calc/test_llm_cost_calc_utils.py       | 13 +++++++++++++
 2 files changed, 16 insertions(+), 2 deletions(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index be289f620cf..30c25253eea 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -296,7 +296,8 @@ def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_
 
     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. The start is inclusive and the end is exclusive; malformed windows are ignored.
+    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.
     """
     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()
@@ -308,7 +309,7 @@ def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_
             end = datetime.strptime(end_str.strip(), "%H:%M").replace(tzinfo=timezone.utc).time()
         except (ValueError, AttributeError):
             continue
-        if start <= end:
+        if start < end:
             if start <= now < end:
                 return True
         elif now >= start or now < end:
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 8f348b36d35..c9ed5936f03 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
@@ -431,6 +431,19 @@ def test_is_within_off_peak_window_wraps_midnight():
     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
 

From cc3ea1fb08387a511b7cc243613df29d41b97062 Mon Sep 17 00:00:00 2001
From: Srivatsa03 <skamb10@uic.edu>
Date: Sat, 22 Aug 2026 23:40:03 -0500
Subject: [PATCH 020/113] docs(cost): state that a naive off-peak current_time
 is read as UTC

An aware value is converted, a naive one is taken to already be UTC rather
than localised. Nothing signals the difference, so a caller passing
datetime.now() instead of datetime.now(timezone.utc) shifts every window by
the host's offset and bills silently wrong. Say so where a caller will read it.

Reported by @xyzs996 in review.
---
 litellm/litellm_core_utils/llm_cost_calc/utils.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 30c25253eea..21680129ed4 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -298,6 +298,10 @@ def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_
     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()

From f7b1cc1f41b0d527127ead73a0c5c1f088514c7e Mon Sep 17 00:00:00 2001
From: Emerson Gomes <emerson.gomes@thalesgroup.com>
Date: Mon, 31 Aug 2026 10:35:10 -0500
Subject: [PATCH 021/113] fix(router): copy kwargs instead of popping target
 order

Lint required a specific exception on the empty-order-2 regression.
Provider calls now omit _target_order by constructing a new kwargs dict.
---
 litellm/router.py                                | 6 ++----
 litellm/router_utils/fallback_event_handlers.py  | 3 +--
 tests/test_litellm/test_router_order_fallback.py | 4 ++--
 3 files changed, 5 insertions(+), 8 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index 81e49645462..6eadaaa9913 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -2172,9 +2172,8 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **kwargs,
+                **{k: v for k, v in kwargs.items() if k != "_target_order"},
             }
-            input_kwargs.pop("_target_order", None)
             response: Final = litellm.completion(**input_kwargs)
             verbose_router_logger.info("litellm.completion(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -3194,11 +3193,10 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **kwargs,
+                **{k: v for k, v in kwargs.items() if k != "_target_order"},
             }
             input_kwargs.pop("silent_model", None)
             input_kwargs.pop("include_fallback_errors", None)
-            input_kwargs.pop("_target_order", None)
 
             _response: Final = litellm.acompletion(**input_kwargs)
 
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index c37fbdc8ed7..8c33bf1481f 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -412,11 +412,10 @@ 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 = {k: v for k, v in kwargs.items() if k != "_target_order"}  # rebind-ok: next hop must not inherit the previous order target
             if isinstance(mg, str):
                 kwargs["model"] = mg
-                kwargs.pop("_target_order", None)
             elif isinstance(mg, dict):
-                kwargs.pop("_target_order", None)
                 kwargs.update(mg)
             fallback_depth = fallback_depth + 1
             _hop_metadata = dict(kwargs.get(metadata_variable_name) or {})
diff --git a/tests/test_litellm/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index 33916444003..d74e0a6ffa4 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -14,6 +14,7 @@ import litellm
 from litellm import Router
 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
 
 # ---------------------------------------------------------------------------
@@ -454,13 +455,12 @@ async def test_router_order_fallback_does_not_reselect_order_1_when_order_2_is_f
     )
     litellm.callbacks.append(drop_order_2)
     try:
-        with pytest.raises(Exception) as exc_info:
+        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)
-        assert getattr(exc_info.value, "_hidden_params", {}).get("model_id") != "1"
     finally:
         litellm.callbacks.remove(drop_order_2)
 

From 11a74719028860a72b57d4afd43e44c95422488a Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 11:08:31 -0700
Subject: [PATCH 022/113] refactor(proxy): resolve supported_openai_params
 aliases via Router.resolved_litellm_models

---
 litellm/proxy/proxy_server.py                 |  7 ++--
 .../proxy/proxy_server/test_routes_utils.py   | 33 +++++++------------
 2 files changed, 16 insertions(+), 24 deletions(-)

diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 693769446f4..170845babdb 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -12480,9 +12480,10 @@ async def supported_openai_params(model: str):
     """
     global llm_router
     try:
-        deployments: Final = llm_router.get_model_list(model_name=model) if llm_router is not None else None
-        model_to_map: Final = (deployments[0]["litellm_params"].get("model") or model) if deployments else model
-        litellm_model, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model_to_map)
+        resolved_models: Final = llm_router.resolved_litellm_models(model) if llm_router is not None else ()
+        litellm_model, custom_llm_provider, _, _ = litellm.get_llm_provider(
+            model=resolved_models[0] if resolved_models else model
+        )
         return {
             "supported_openai_params": litellm.get_supported_openai_params(
                 model=litellm_model, custom_llm_provider=custom_llm_provider
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 4d6ce0812a4..629d829ef8a 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -9,7 +9,6 @@ Pins (PR2):
 from __future__ import annotations
 
 import asyncio
-from unittest.mock import MagicMock
 
 import pytest
 
@@ -126,32 +125,24 @@ 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 unknown to the cost map resolves via the deployment's ``litellm_params.model``."""
-    router = MagicMock()
-    router.get_model_list.return_value = [
-        {"model_name": "claude-opus-4-6-cached", "litellm_params": {"model": "anthropic/claude-opus-4-6"}}
-    ]
-    monkeypatch.setattr(proxy_server, "llm_router", router)
-    seen = []
-
-    def _get_llm_provider(model):
-        seen.append(model)
-        return (model, "anthropic", None, None)
-
-    monkeypatch.setattr(litellm, "get_llm_provider", _get_llm_provider)
-    monkeypatch.setattr(
-        litellm,
-        "get_supported_openai_params",
-        lambda model, custom_llm_provider=None: ["max_tokens"],
+    """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
-    assert response.json() == {"supported_openai_params": ["max_tokens"]}
-    router.get_model_list.assert_called_once_with(model_name="claude-opus-4-6-cached")
-    assert seen == ["anthropic/claude-opus-4-6"]
+    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_invalid_model(client, auth_as, monkeypatch):

From 779b3010d4f4a9e45185df06acb6e8eabc18e170 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 12:06:35 -0700
Subject: [PATCH 023/113] fix(proxy): never run OAuth device flows when
 resolving model names

Resolving github_copilot/chatgpt names through get_llm_provider runs the
provider's OAuth device flow synchronously on the event loop. Adopt the
declared provider in PatternMatchRouter.get_pattern, which the auth
layer's zero-cost budget check walks on every request against wildcard
routers, and in /utils/supported_openai_params.
---
 litellm/proxy/proxy_server.py                 | 16 ++++--
 .../router_utils/pattern_match_deployments.py | 25 +++++----
 .../proxy/proxy_server/test_routes_utils.py   | 51 +++++++++++++++++++
 .../test_pattern_match_deployments.py         | 51 +++++++++++++++++++
 4 files changed, 127 insertions(+), 16 deletions(-)
 create mode 100644 tests/test_litellm/router_utils/test_pattern_match_deployments.py

diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 170845babdb..c5b1e251398 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -12478,11 +12478,21 @@ 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:
-        resolved_models: Final = llm_router.resolved_litellm_models(model) if llm_router is not None else ()
-        litellm_model, custom_llm_provider, _, _ = litellm.get_llm_provider(
-            model=resolved_models[0] if resolved_models else model
+        resolved_models: Final = (
+            llm_router.resolved_litellm_models(model)
+            if llm_router is not None and declared_authenticating_provider(model) is 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(
diff --git a/litellm/router_utils/pattern_match_deployments.py b/litellm/router_utils/pattern_match_deployments.py
index 0d5ef01bc04..850ca74b387 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:
@@ -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) -> str | None:
+        try:
+            return get_llm_provider(model=model)[1]
+        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/tests/test_litellm/proxy/proxy_server/test_routes_utils.py b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
index 629d829ef8a..43ef5023985 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -9,11 +9,13 @@ Pins (PR2):
 from __future__ import annotations
 
 import asyncio
+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]
 
@@ -145,6 +147,55 @@ def test_supported_openai_params_resolves_router_alias(client, auth_as, monkeypa
     assert "max_tokens" in response.json()["supported_openai_params"]
 
 
+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)."""
 
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..2fef84c8785
--- /dev/null
+++ b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
@@ -0,0 +1,51 @@
+"""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_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"]

From b134dbfe7361cd30ee3e5976588149b106b53e6a Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 12:19:51 -0700
Subject: [PATCH 024/113] test: exempt _resolved_provider in
 router_code_coverage gate

---
 tests/code_coverage_tests/router_code_coverage.py | 1 +
 1 file changed, 1 insertion(+)

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)
 ]
 
 

From c02c81452c932eff275755a43ff9c686cd8055d4 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 13:16:48 -0700
Subject: [PATCH 025/113] fix(proxy): reassemble split SSE frames before
 restamping anthropic message_start

---
 .../streaming_model_restamp.py                | 78 +++++++++++++++++
 litellm/proxy/common_request_processing.py    |  8 +-
 .../test_streaming_model_restamp.py           | 83 +++++++++++++++++++
 3 files changed, 165 insertions(+), 4 deletions(-)

diff --git a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
index bbb7f2ceaa3..e8d54f03949 100644
--- a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
+++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
@@ -14,7 +14,11 @@ 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: Final = b"\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])
 
@@ -79,3 +83,77 @@ def restamp_anthropic_stream_chunk_model(chunk: object, requested_model: str) ->
         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 are emitted as their
+    terminator closes them and an incomplete tail is held until it completes,
+    so the restamp never misses a torn frame. 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 _process_encoded(self, data: bytes) -> bytes:
+        combined: Final = self._held + data
+        if _SSE_FRAME_END not in combined:
+            if len(combined) > _MAX_HELD_BYTES:
+                self._held = b""
+                self._armed = False
+                return combined
+            self._held = combined
+            return b""
+        closed, _, tail = combined.rpartition(_SSE_FRAME_END)
+        emitted: Final = self._restamped_closed_block(closed + _SSE_FRAME_END)
+        if not self._armed:
+            self._held = b""
+            return emitted + tail
+        self._held = tail
+        return emitted
+
+    def _restamped_closed_block(self, closed: bytes) -> bytes:
+        frames: Final = tuple(closed.split(_SSE_FRAME_END)[:-1])
+        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
+        decider_frame: Final = frames[decider] + _SSE_FRAME_END
+        if _MESSAGE_START_MARKER not in decider_frame:
+            return closed
+        restamped_text: Final = _restamped_frame(decider_frame.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 + _SSE_FRAME_END
+            for index, frame in enumerate(frames)
+        )
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 23e887f34a3..989cc7c18fb 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -177,7 +177,7 @@ if TYPE_CHECKING:
 else:
     ProxyConfig = Any
 from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
-    restamp_anthropic_stream_chunk_model,
+    AnthropicStreamModelRestamper,
 )
 from litellm.proxy.litellm_pre_call_utils import (
     add_litellm_data_to_request,
@@ -3414,10 +3414,10 @@ class ProxyBaseLLMRequestProcessing:
         if not restamp_model:
             return ProxyBaseLLMRequestProcessing.return_sse_chunk
 
+        restamper: Final = AnthropicStreamModelRestamper(restamp_model)
+
         def serialize(chunk: object) -> str:
-            return ProxyBaseLLMRequestProcessing.return_sse_chunk(
-                restamp_anthropic_stream_chunk_model(chunk, restamp_model)
-            )
+            return ProxyBaseLLMRequestProcessing.return_sse_chunk(restamper.process(chunk))
 
         return serialize
 
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
index 6e2c3f49445..385173b24a9 100644
--- a/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
@@ -8,6 +8,7 @@ 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
@@ -107,3 +108,85 @@ async def test_sse_generator_keeps_provider_model_when_restamping_is_off():
     ]
 
     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"

From ec02c9a6d2b06f131baf46b8771a6d153fd1fd6f Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 13:34:14 -0700
Subject: [PATCH 026/113] fix(router): bare authenticating-provider names
 declare nothing

---
 .../get_llm_provider_logic.py                 |  2 +-
 litellm/proxy/proxy_server.py                 |  6 +-----
 .../test_get_supported_openai_params.py       |  2 ++
 .../proxy/proxy_server/test_routes_utils.py   | 21 +++++++++++++++++++
 .../test_pattern_match_deployments.py         | 13 ++++++++++++
 5 files changed, 38 insertions(+), 6 deletions(-)

diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 74a1d3e5008..4c0e0dae9ae 100644
--- a/litellm/litellm_core_utils/get_llm_provider_logic.py
+++ b/litellm/litellm_core_utils/get_llm_provider_logic.py
@@ -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 "/" in model else None)
     return declared if declared in PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO else None
 
 
diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index c5b1e251398..5f641e0b552 100644
--- a/litellm/proxy/proxy_server.py
+++ b/litellm/proxy/proxy_server.py
@@ -12482,11 +12482,7 @@ async def supported_openai_params(model: str):
 
     global llm_router
     try:
-        resolved_models: Final = (
-            llm_router.resolved_litellm_models(model)
-            if llm_router is not None and declared_authenticating_provider(model) is None
-            else ()
-        )
+        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 = (
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/proxy/proxy_server/test_routes_utils.py b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
index 43ef5023985..1e1436fcef8 100644
--- a/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
+++ b/tests/test_litellm/proxy/proxy_server/test_routes_utils.py
@@ -147,6 +147,27 @@ def test_supported_openai_params_resolves_router_alias(client, auth_as, monkeypa
     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."""
diff --git a/tests/test_litellm/router_utils/test_pattern_match_deployments.py b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
index 2fef84c8785..af43644a305 100644
--- a/tests/test_litellm/router_utils/test_pattern_match_deployments.py
+++ b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
@@ -40,6 +40,19 @@ def test_get_pattern_never_resolves_declared_authenticating_providers(monkeypatc
     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_still_resolves_unqualified_names(monkeypatch):
     monkeypatch.setattr(
         pattern_match_deployments,

From 7edf5b36cfd25666fab30f451b599b6fec524566 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 16:01:39 -0700
Subject: [PATCH 027/113] fix(guardrails): deliver modify_response block as
 valid SSE on streaming chat and Responses

A guardrail modify_response verdict on a streaming request only produced a
proper replacement on /v1/messages: the chat completions and Responses API
translations had no build_block_sse_chunks, so the ModifyResponseException
re-raised and surfaced as an in-stream 500 error frame (or a whole-request
500 in buffered mode) instead of the documented 200 replacement.

Implement build_block_sse_chunks for both OpenAI translations: chat emits a
content delta plus a finish_reason content_filter chunk with real usage;
Responses emits the typed event sequence (standalone via
build_synthetic_response_events pre-stream, or an output-item continuation
under the in-progress response id mid-stream) ending in response.completed.
---
 basedpyright-code-budget.json                 |   2 +-
 .../chat/guardrail_translation/handler.py     |  10 +-
 .../guardrail_translation/base_translation.py |   5 +-
 .../base_llm/guardrail_translation/utils.py   |  55 ++++
 .../chat/guardrail_translation/handler.py     | 117 +++++++-
 .../guardrail_translation/handler.py          | 204 +++++++++++++-
 litellm/responses/streaming_iterator.py       |   8 +-
 .../test_responses_hooks.py                   |   2 +-
 .../test_openai_guardrail_handler.py          |  51 ++++
 ...test_openai_responses_guardrail_handler.py |  63 +++++
 .../test_openai_streaming_block.py            | 265 ++++++++++++++++++
 type-discipline-budget.json                   |   4 +-
 12 files changed, 769 insertions(+), 17 deletions(-)
 create mode 100644 tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py

diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index 83969d8dedf..88a612fde98 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -117,7 +117,7 @@
     "limit": 117
   },
   "reportUnnecessaryComparison": {
-    "limit": 697
+    "limit": 696
   },
   "reportUnnecessaryContains": {
     "limit": 5
diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py
index b9ca18c7843..21390e5ddb4 100644
--- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py
+++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py
@@ -144,7 +144,7 @@ class AnthropicMessagesHandler(BaseTranslation):
         self,
         exc: "ModifyResponseException",
         stream_started: bool = False,
-        responses_so_far: list[object] | None = None,
+        responses_so_far: Sequence[object] | None = None,
     ) -> list[bytes]:
         """
         Build an Anthropic SSE sequence delivering the guardrail block message
@@ -162,7 +162,7 @@ class AnthropicMessagesHandler(BaseTranslation):
           would make Anthropic clients reject the stream.
         """
         if stream_started:
-            return self._block_continuation_chunks(exc, responses_so_far or [])
+            return self._block_continuation_chunks(exc, responses_so_far or ())
         return self._standalone_block_chunks(exc)
 
     def _standalone_block_chunks(self, exc: "ModifyResponseException") -> list[bytes]:
@@ -187,7 +187,9 @@ class AnthropicMessagesHandler(BaseTranslation):
         )
         return list(FakeAnthropicMessagesStreamIterator(response=block_response))
 
-    def _block_continuation_chunks(self, exc: "ModifyResponseException", responses_so_far: list[object]) -> list[bytes]:
+    def _block_continuation_chunks(
+        self, exc: "ModifyResponseException", responses_so_far: Sequence[object]
+    ) -> list[bytes]:
         """Continue an already-started message: close the open content block,
         append the block message as a new text block, then end the message --
         without a second message_start."""
@@ -237,7 +239,7 @@ class AnthropicMessagesHandler(BaseTranslation):
 
     @staticmethod
     def _content_block_state(
-        responses_so_far: list[object],
+        responses_so_far: Sequence[object],
     ) -> tuple[int | None, int | None]:
         """From the SSE chunks already sent to the client, return (open
         content-block index or None, highest content-block index seen or None).
diff --git a/litellm/llms/base_llm/guardrail_translation/base_translation.py b/litellm/llms/base_llm/guardrail_translation/base_translation.py
index ba96ab3dc99..247d9bc7c40 100644
--- a/litellm/llms/base_llm/guardrail_translation/base_translation.py
+++ b/litellm/llms/base_llm/guardrail_translation/base_translation.py
@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, Final, Optional
 
@@ -127,8 +128,8 @@ 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..d30cdcecff5 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 str(stream_item_field(item, "type") or "") == "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/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index 54673c77f80..31a36822c89 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -14,8 +14,14 @@ Pattern Overview:
 This pattern can be replicated for other message formats (e.g., Anthropic).
 """
 
+import json
+import time
+import uuid
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
 import litellm
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.base_llm.guardrail_translation.base_translation import (
@@ -23,6 +29,7 @@ from litellm.llms.base_llm.guardrail_translation.base_translation import (
     StreamTransformSink,
 )
 from litellm.llms.base_llm.guardrail_translation.utils import (
+    blocked_chat_stream_usage,
     effective_scan_only_tool_results_for_guardrail,
     effective_skip_system_message_for_guardrail,
     effective_skip_tool_message_for_guardrail,
@@ -31,6 +38,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import (
     openai_tool_name,
     role_out_of_guardrail_scope,
     scoped_structured_message_indices,
+    stream_item_field,
 )
 from litellm.main import stream_chunk_builder
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam
@@ -46,7 +54,10 @@ from litellm.types.utils import (
 )
 
 if TYPE_CHECKING:
-    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
 
 
@@ -1000,3 +1011,107 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                                 else:
                                     # Subsequent chunks - clear the text
                                     content_item["text"] = ""
+
+    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 _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 7c5d8ac99ad..9a58899eccd 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -28,6 +28,8 @@ Output: response.output is List[GenericResponseOutputItem] where each has:
     - text: str
 """
 
+import time
+import uuid
 from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
@@ -41,15 +43,31 @@ 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,
     OpenAIMcpServerTool,
+    OutputItemAddedEvent,
+    OutputItemDoneEvent,
+    OutputTextDeltaEvent,
+    OutputTextDoneEvent,
+    ResponseAPIUsage,
+    ResponseCompletedEvent,
+    ResponsesAPIResponse,
     ResponsesAPIStreamEvents,
+    ResponsesAPIStreamingResponse,
 )
 from litellm.types.responses.main import (
     GenericResponseOutputItem,
@@ -59,11 +77,13 @@ from litellm.types.responses.main import (
 from litellm.types.utils import GenericGuardrailAPIInputs
 
 if TYPE_CHECKING:
-    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):
@@ -802,3 +822,183 @@ 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: 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)}\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"]
+        item_model: Final = BaseLiteLLMOpenAIResponseObject.model_validate(item)
+        part: Final[_BlockedContentPart] = {"type": "output_text", "text": exc.message, "annotations": ()}
+        done_part: Final[_BlockedDoneContentPart] = {
+            "type": "output_text",
+            "text": exc.message,
+            "annotations": (),
+            "logprobs": None,
+        }
+        return (
+            OutputItemAddedEvent(
+                type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
+                output_index=output_index,
+                item=item_model,
+            ),
+            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_model,
+            ),
+            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 _BlockedOutputItem(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[_BlockedOutputItem, ...]]
+    status: ReadOnly[str]
+    usage: ReadOnly[ResponseAPIUsage]
+
+
+def _blocked_output_item(exc: "ModifyResponseException") -> _BlockedOutputItem:
+    item: Final[_BlockedOutputItem] = {
+        "type": "message",
+        "id": f"msg_{uuid.uuid4()}",
+        "status": "completed",
+        "role": "assistant",
+        "content": ({"type": "output_text", "text": exc.message, "annotations": ()},),
+    }
+    return item
+
+
+def _blocked_response(
+    exc: "ModifyResponseException",
+    response_id: str,
+    model: str,
+    output_item: _BlockedOutputItem | 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
diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py
index 63adf950142..4fd47c50b1e 100644
--- a/litellm/responses/streaming_iterator.py
+++ b/litellm/responses/streaming_iterator.py
@@ -969,7 +969,7 @@ class MockResponsesAPIStreamingIterator(BaseResponsesAPIStreamingIterator):
         transformed: ResponsesAPIResponse,
         logging_obj: LiteLLMLoggingObj,
     ) -> None:
-        self._events: list[ResponsesAPIStreamingResponse] = _build_synthetic_response_events(
+        self._events: Sequence[ResponsesAPIStreamingResponse] = build_synthetic_response_events(
             transformed=transformed,
             logging_obj=logging_obj,
             chunk_size=self.CHUNK_SIZE,
@@ -1036,7 +1036,7 @@ 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,
@@ -1218,10 +1218,10 @@ 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/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/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..8ad0026d1ab 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 +1559,54 @@ 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}
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..cd0e7f29933 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
@@ -1229,3 +1229,66 @@ 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.added"
+        assert payloads[0]["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}
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..4d5581290ba
--- /dev/null
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/unified_guardrails/test_openai_streaming_block.py
@@ -0,0 +1,265 @@
+"""
+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, List, Literal, Optional
+
+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."
+
+
+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,
+        )
+
+
+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[dict, 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[Any, None],
+    sampling_rate: int = 1,
+    end_of_stream_only: bool = False,
+    buffer_until_moderated: bool = False,
+) -> List[Any]:
+    guardrail = _BlockingGuardrail(guardrail_name="test-blocking-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": ["test-blocking-guardrail"]},
+    }
+
+    collected: List[Any] = []
+    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,
+    ):
+        collected.append(chunk)
+    return collected
+
+
+def _sse_payloads(collected: List[Any]) -> List[dict]:
+    payloads = []
+    for chunk in collected:
+        if not isinstance(chunk, bytes):
+            continue
+        for block in chunk.decode().split("\n\n"):
+            for line in block.strip().split("\n"):
+                if line.startswith("data:"):
+                    payloads.append(json.loads(line[len("data:") :].strip()))
+    return payloads
+
+
+def _assert_no_error_frame(collected: List[Any]) -> 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():
+    collected = await _run_hook("/v1/chat/completions", _chat_stream(end=True), end_of_stream_only=True)
+    _assert_no_error_frame(collected)
+    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_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: after events were already
+    forwarded, the block appends a new output item under the same response id
+    and closes with response.completed - never a second response.created."""
+    collected = await _run_hook("/v1/responses", _responses_stream(end=False))
+    _assert_no_error_frame(collected)
+    forwarded_types = [chunk["type"] for chunk in collected if isinstance(chunk, dict)]
+    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[0] == "response.output_item.added"
+    assert block_types[-1] == "response.completed"
+    assert payloads[0]["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/type-discipline-budget.json b/type-discipline-budget.json
index 7365cec4fdd..f17d0b7af4a 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,9 +1,9 @@
 {
   "LIT001": {
-    "limit": 22704
+    "limit": 22698
   },
   "LIT002": {
-    "limit": 26854
+    "limit": 26853
   },
   "LIT003": {
     "limit": 269

From 31a9f7e6ad932b0adbc24f7666178aa4c1071984 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 16:34:21 -0700
Subject: [PATCH 028/113] test(guardrails): type streaming-block test helpers
 and drop mutable accumulators

---
 .../test_openai_streaming_block.py            | 50 ++++++++++---------
 1 file changed, 27 insertions(+), 23 deletions(-)

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
index 4d5581290ba..99172ec3be6 100644
--- 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
@@ -10,7 +10,7 @@ an HTTP 500 error frame and truncates the stream.
 """
 
 import json
-from typing import Any, AsyncGenerator, List, Literal, Optional
+from typing import Any, AsyncGenerator, Dict, Literal, Optional, Tuple, Union
 
 import pytest
 
@@ -31,6 +31,9 @@ from litellm.types.utils import (
 
 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."""
@@ -67,7 +70,7 @@ async def _chat_stream(end: bool) -> AsyncGenerator[ModelResponseStream, None]:
         yield _chat_chunk(Delta(), finish_reason="stop")
 
 
-async def _responses_stream(end: bool) -> AsyncGenerator[dict, None]:
+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}
@@ -122,11 +125,11 @@ async def _responses_stream(end: bool) -> AsyncGenerator[dict, None]:
 
 async def _run_hook(
     route: str,
-    stream: AsyncGenerator[Any, None],
+    stream: AsyncGenerator[Union[ModelResponseStream, JsonPayload], None],
     sampling_rate: int = 1,
     end_of_stream_only: bool = False,
     buffer_until_moderated: bool = False,
-) -> List[Any]:
+) -> Tuple[StreamChunk, ...]:
     guardrail = _BlockingGuardrail(guardrail_name="test-blocking-guardrail", event_hook="post_call")
     guardrail.streaming_sampling_rate = sampling_rate
     guardrail.streaming_end_of_stream_only = end_of_stream_only
@@ -140,29 +143,30 @@ async def _run_hook(
         "metadata": {"guardrails": ["test-blocking-guardrail"]},
     }
 
-    collected: List[Any] = []
-    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,
-    ):
-        collected.append(chunk)
-    return collected
+    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: List[Any]) -> List[dict]:
-    payloads = []
-    for chunk in collected:
-        if not isinstance(chunk, bytes):
-            continue
-        for block in chunk.decode().split("\n\n"):
-            for line in block.strip().split("\n"):
-                if line.startswith("data:"):
-                    payloads.append(json.loads(line[len("data:") :].strip()))
-    return payloads
+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: List[Any]) -> None:
+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}"
 

From 78b57fb427de52a3fc0f10ba5c20005f46725a6f Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 17:05:45 -0700
Subject: [PATCH 029/113] fix(guardrails): withhold chat finish chunk in
 end_of_stream_only mode and close open Responses items before a mid-stream
 block

---
 .../chat/guardrail_translation/handler.py     |  22 +++
 .../guardrail_translation/handler.py          | 133 +++++++++++++++++-
 .../test_openai_guardrail_handler.py          |  33 +++++
 ...test_openai_responses_guardrail_handler.py |  26 +++-
 .../test_openai_streaming_block.py            |  74 ++++++++--
 5 files changed, 273 insertions(+), 15 deletions(-)

diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index 05716e65137..55b27947faa 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -1015,6 +1015,21 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
                                     # 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",
@@ -1097,6 +1112,13 @@ 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]:
diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 811c4feeacc..cf01242f151 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -31,6 +31,7 @@ Output: response.output is List[GenericResponseOutputItem] where each has:
 import time
 import uuid
 from collections.abc import Sequence
+from dataclasses import dataclass
 from typing import TYPE_CHECKING, Any, Final, Union, cast
 
 from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
@@ -874,10 +875,10 @@ class OpenAIResponsesHandler(BaseTranslation):
           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: 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.
+          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.
         """
@@ -887,7 +888,8 @@ class OpenAIResponsesHandler(BaseTranslation):
             else self._standalone_block_events(exc)
         )
         return tuple(
-            f"data: {event.model_dump_json(exclude_none=True, exclude_unset=True)}\n\n".encode() for event in events
+            f"data: {event.model_dump_json(exclude_none=True, exclude_unset=True, serialize_as_any=True)}\n\n".encode()
+            for event in events
         )
 
     @staticmethod
@@ -915,6 +917,7 @@ class OpenAIResponsesHandler(BaseTranslation):
             "logprobs": None,
         }
         return (
+            *_open_item_closing_events(responses_so_far),
             OutputItemAddedEvent(
                 type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
                 output_index=output_index,
@@ -1036,3 +1039,123 @@ def _continuation_identity(exc: "ModifyResponseException", responses_so_far: Seq
         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
+
+
+def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | None:
+    typed: Final = tuple((str(stream_item_field(event, "type") or ""), 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]
+    item_id: Final = stream_item_field(item_payload, "id") if item_payload is not None else None
+    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),
+    )
+
+
+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. The closing text is exactly what the client has received
+    for that item so far."""
+    open_item: Final = _open_item_state(responses_so_far)
+    if open_item is None:
+        return ()
+    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/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 8ad0026d1ab..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
@@ -1610,3 +1610,36 @@ class TestBuildBlockSseChunks:
         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/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
index cd0e7f29933..1ae4e7a699b 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
@@ -1285,10 +1285,32 @@ class TestBuildBlockSseChunks:
         )
         types = [payload["type"] for payload in payloads]
         assert "response.created" not in types
-        assert types[0] == "response.output_item.added"
-        assert payloads[0]["output_index"] == 3
+        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_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/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
index 99172ec3be6..42bdf41bc88 100644
--- 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
@@ -53,6 +53,19 @@ class _BlockingGuardrail(CustomGuardrail):
         )
 
 
+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",
@@ -129,8 +142,13 @@ async def _run_hook(
     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")
+    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
@@ -140,7 +158,7 @@ async def _run_hook(
     request_data = {
         "messages": [{"role": "user", "content": "hi"}],
         "guardrail_to_apply": guardrail,
-        "metadata": {"guardrails": ["test-blocking-guardrail"]},
+        "metadata": {"guardrails": [guardrail.guardrail_name]},
     }
 
     return tuple(
@@ -203,13 +221,38 @@ async def test_chat_mid_stream_block_continues_the_completion():
 
 @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
@@ -234,20 +277,35 @@ async def test_responses_buffered_block_emits_full_event_sequence():
 
 @pytest.mark.asyncio
 async def test_responses_mid_stream_block_continues_the_response():
-    """Regression for the LIT-6496 500 error frame: after events were already
-    forwarded, the block appends a new output item under the same response id
-    and closes with response.completed - never a second response.created."""
+    """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_types = [chunk["type"] for chunk in collected if isinstance(chunk, dict)]
+    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[0] == "response.output_item.added"
     assert block_types[-1] == "response.completed"
-    assert payloads[0]["output_index"] == 1, "the block item must continue after the original output item"
+
+    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

From 38825cf9c62eeb3c374b87a4ea9b2c31cc9f19cc Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 17:19:55 -0700
Subject: [PATCH 030/113] fix(guardrails): match Responses stream event types
 by value so enum-typed events close the open item

---
 .../guardrail_translation/handler.py          |  2 +-
 ...test_openai_responses_guardrail_handler.py | 59 +++++++++++++++++++
 2 files changed, 60 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index cf01242f151..6295df1dbfa 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -1053,7 +1053,7 @@ class _OpenItemState:
 
 
 def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | None:
-    typed: Final = tuple((str(stream_item_field(event, "type") or ""), event) for event in responses_so_far)
+    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
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 1ae4e7a699b..d6e56f0faf1 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
@@ -1297,6 +1297,65 @@ class TestBuildBlockSseChunks:
         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_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_without_open_item_emits_no_closing_events(self):
         handler = OpenAIResponsesHandler()
         yielded = [

From 329654765a9d07a3f8d15abc6a86040044668473 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Mon, 31 Aug 2026 17:31:59 -0700
Subject: [PATCH 031/113] test(guardrails): update chat eos block tests for
 finish-chunk withholding

---
 .../guardrails/guardrail_hooks/test_bedrock_guardrails.py  | 7 +++++--
 .../unified_guardrails/test_unified_guardrail.py           | 3 ++-
 2 files changed, 7 insertions(+), 3 deletions(-)

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 235a5c0c09b..bacaa1c3e22 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: ") :])
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()

From a27e12367e2c3574586128a55e970fa5d17d5379 Mon Sep 17 00:00:00 2001
From: Tin Chi Lo <tin@berri.ai>
Date: Mon, 31 Aug 2026 21:50:40 -0700
Subject: [PATCH 032/113] fix(bedrock): forward native structured outputs on
 Invoke instead of silently inlining the schema

---
 litellm/llms/anthropic/chat/transformation.py |  24 +-
 .../anthropic_claude3_transformation.py       |  44 +---
 litellm/llms/bedrock/common_utils.py          |  89 ++++++++
 .../anthropic_claude3_transformation.py       |  60 ++---
 ...odel_prices_and_context_window_backup.json |  24 +-
 model_prices_and_context_window.json          |  24 +-
 .../test_anthropic_chat_transformation.py     |  42 ++++
 ...ations_anthropic_claude3_transformation.py | 131 +++++++++--
 .../test_anthropic_claude3_transformation.py  | 206 +++++++++++++++---
 .../llms/bedrock/test_bedrock_common_utils.py |  41 ++++
 10 files changed, 535 insertions(+), 150 deletions(-)

diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index e1387a9068c..a3c76d6a29b 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -1992,19 +1992,35 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         return data
 
     def _apply_output_config(self, data: dict, model: str, optional_params: dict) -> None:
-        """Validate and apply output_config to the request data."""
+        """Validate and apply output_config to the request data.
+
+        The ``drop_params`` gate here is an effort gate: ``format`` is a
+        structured-output field, not an effort field, so it survives the drop
+        and is vetted where it is consumed (the map's
+        ``supports_native_structured_output`` flag on emission paths).
+        """
         if "output_config" not in optional_params:
             return
         output_config: Final = optional_params.get("output_config")
         if not output_config or not isinstance(output_config, dict):
             return
-        if litellm.drop_params is True and not self._model_supports_effort_param(model, self._resolved_provider):
+        if (
+            litellm.drop_params is True
+            and any(key != "format" for key in output_config)
+            and not self._model_supports_effort_param(model, self._resolved_provider)
+        ):
             litellm.verbose_logger.warning(
                 DROP_UNSUPPORTED_OUTPUT_CONFIG_WARNING,
                 model,
             )
-            optional_params.pop("output_config", None)
-            data.pop("output_config", None)
+            preserved_format: Final = output_config.get("format")
+            if preserved_format is None:
+                optional_params.pop("output_config", None)
+                data.pop("output_config", None)
+                return
+            format_only: Final = {"format": preserved_format}  # mutable-ok: json body
+            optional_params["output_config"] = format_only  # rebind-ok: out-param store
+            data["output_config"] = format_only  # rebind-ok: out-param store
             return
         effort: Final = output_config.get("effort")
         valid_efforts: Final = ["high", "medium", "low", "xhigh", "max"]
diff --git a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
index 40b90014f3b..8e709349400 100644
--- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
@@ -3,7 +3,6 @@ from typing import TYPE_CHECKING, Any, Final
 import httpx
 
 from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers
-from litellm.litellm_core_utils.litellm_logging import verbose_logger
 from litellm.litellm_core_utils.prompt_templates.factory import (
     convert_to_anthropic_image_obj,
 )
@@ -16,17 +15,16 @@ from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation
     AmazonInvokeConfig,
 )
 from litellm.llms.bedrock.common_utils import (
-    convert_bedrock_invoke_output_format_to_inline_schema,
+    apply_bedrock_invoke_structured_output,
     get_anthropic_beta_from_headers,
     normalize_bedrock_opus_output_config_effort,
     normalize_custom_field_on_tools,
     normalize_tool_input_schema_types_for_bedrock_invoke,
-    pop_bedrock_invoke_output_config_format,
+    strip_unsupported_bedrock_invoke_output_config_keys,
 )
 from litellm.types.llms.anthropic import ANTHROPIC_TOOL_SEARCH_BETA_HEADER
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.utils import ModelResponse
-from litellm.utils import _supports_factory
 
 if TYPE_CHECKING:
     import tiktoken
@@ -212,36 +210,14 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig):
         anthropic_request.pop("model", None)
         anthropic_request.pop("stream", None)
         anthropic_request.pop("stream_chunk_size", None)
-        output_format: Final = anthropic_request.pop("output_format", None)
-        output_config_format: Final = pop_bedrock_invoke_output_config_format(anthropic_request)
-        if output_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_format,
-                request_body=anthropic_request,
-            )
-        elif output_config_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_config_format,
-                request_body=anthropic_request,
-            )
-        if not (
-            _supports_factory(
-                model=model,
-                custom_llm_provider="bedrock",
-                key="supports_output_config",
-            )
-            or AnthropicConfig._model_supports_effort_param(model, "bedrock")
-        ):
-            if anthropic_request.pop("output_config", None) is not None:
-                verbose_logger.warning(
-                    "Bedrock Invoke: stripping unsupported `output_config` for "
-                    "model=%s — neither `supports_output_config` nor any "
-                    "`supports_*_reasoning_effort` flag is set in "
-                    "model_prices_and_context_window.json. Add the capability "
-                    "flag to the model JSON entry if this model accepts "
-                    "`output_config`.",
-                    model,
-                )
+        apply_bedrock_invoke_structured_output(
+            model=model,
+            request_body=anthropic_request,
+        )
+        strip_unsupported_bedrock_invoke_output_config_keys(
+            model=model,
+            request_body=anthropic_request,
+        )
         if "anthropic_version" not in anthropic_request:
             anthropic_request["anthropic_version"] = self.anthropic_version
 
diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py
index 72e3cc1b326..df65df642a2 100644
--- a/litellm/llms/bedrock/common_utils.py
+++ b/litellm/llms/bedrock/common_utils.py
@@ -177,6 +177,95 @@ def convert_bedrock_invoke_output_format_to_inline_schema(
     request_body["messages"] = new_messages
 
 
+def _bedrock_model_supports(model: str, key: str) -> bool:
+    from litellm.utils import _supports_factory
+
+    return _supports_factory(model=model, custom_llm_provider="bedrock", key=key)
+
+
+def apply_bedrock_invoke_structured_output(
+    model: str,
+    request_body: dict[str, object],  # mutable-ok: edited in place like siblings
+) -> None:
+    """
+    Route Anthropic structured-output params to what the Bedrock model supports.
+
+    Consumes the legacy top-level ``output_format`` and the newer
+    ``output_config.format``, keeping the pre-existing precedence of the legacy
+    field when a request carries both. Models flagged
+    ``supports_native_structured_output`` in the model map get the schema
+    forwarded as ``output_config.format``, which Bedrock relays to the model for
+    enforced structured output. For every other model the schema is inlined into
+    the last user message as best-effort text, with a warning because nothing
+    enforces it.
+    """
+    legacy_output_format: Final = request_body.pop("output_format", None)
+    output_config_format: Final = pop_bedrock_invoke_output_config_format(request_body)
+    schema_format: Final = legacy_output_format if isinstance(legacy_output_format, dict) else output_config_format
+    if schema_format is None:
+        return
+
+    if _bedrock_model_supports(model, "supports_native_structured_output"):
+        existing_output_config: Final = request_body.get("output_config")
+        if isinstance(existing_output_config, dict):
+            existing_output_config["format"] = schema_format
+        else:
+            request_body["output_config"] = {"format": schema_format}  # rebind-ok: out-param  # mutable-ok: json
+        return
+
+    verbose_logger.warning(
+        "Bedrock Invoke: model=%s does not advertise `supports_native_structured_output` "
+        "in model_prices_and_context_window.json, so the JSON schema was inlined into "
+        "the last user message and is NOT enforced by the model.",
+        model,
+    )
+    convert_bedrock_invoke_output_format_to_inline_schema(
+        output_format=schema_format,
+        request_body=request_body,
+    )
+
+
+def strip_unsupported_bedrock_invoke_output_config_keys(
+    model: str,
+    request_body: dict[str, object],  # mutable-ok: edited in place like siblings
+) -> None:
+    """
+    Drop ``output_config`` keys the Bedrock model does not accept.
+
+    ``format`` survives unconditionally: it is only attached for models whose map
+    entry advertises ``supports_native_structured_output``. Effort-bearing keys
+    survive only when the map flags ``supports_output_config`` or a
+    ``supports_*_reasoning_effort`` tier; otherwise they are dropped with a
+    warning so Bedrock does not reject the request.
+    """
+    from litellm.llms.anthropic.chat.transformation import AnthropicConfig
+
+    output_config: Final = request_body.get("output_config")
+    if not isinstance(output_config, dict):
+        return
+    if all(key == "format" for key in output_config):
+        return
+    if _bedrock_model_supports(model, "supports_output_config") or AnthropicConfig._model_supports_effort_param(
+        model, "bedrock"
+    ):
+        return
+
+    verbose_logger.warning(
+        "Bedrock Invoke: stripping unsupported `output_config` keys for "
+        "model=%s: neither `supports_output_config` nor any "
+        "`supports_*_reasoning_effort` flag is set in "
+        "model_prices_and_context_window.json. Add the capability "
+        "flag to the model JSON entry if this model accepts "
+        "`output_config`.",
+        model,
+    )
+    preserved_format: Final = output_config.get("format")
+    if preserved_format is None:
+        request_body.pop("output_config", None)
+    else:
+        request_body["output_config"] = {"format": preserved_format}  # rebind-ok: out-param  # mutable-ok: json
+
+
 def normalize_custom_field_on_tools(request_body: dict) -> None:
     """
     Drop the ``custom`` field from each tool, first hoisting a boolean
diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
index f74a290d773..6ff9f0155f9 100644
--- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude3_transformation.py
@@ -29,14 +29,14 @@ from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation
     AmazonInvokeConfig,
 )
 from litellm.llms.bedrock.common_utils import (
-    convert_bedrock_invoke_output_format_to_inline_schema,
+    apply_bedrock_invoke_structured_output,
     ensure_bedrock_anthropic_messages_tool_names,
     get_anthropic_beta_from_headers,
     is_claude_4_5_on_bedrock,
     normalize_bedrock_opus_output_config_effort,
     normalize_custom_field_on_tools,
     normalize_tool_input_schema_types_for_bedrock_invoke,
-    pop_bedrock_invoke_output_config_format,
+    strip_unsupported_bedrock_invoke_output_config_keys,
 )
 from litellm.llms.bedrock.request_metadata import (
     bedrock_request_metadata_headers,
@@ -51,7 +51,6 @@ from litellm.types.llms.openai import AllMessageValues
 from litellm.types.router import GenericLiteLLMParams
 from litellm.types.utils import GenericStreamingChunk, ModelResponseStream
 from litellm.types.utils import GenericStreamingChunk as GChunk
-from litellm.utils import _supports_factory
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
@@ -708,52 +707,25 @@ class AmazonAnthropicClaudeMessagesConfig(
         # 4. Remove `ttl` field from cache_control in messages (Bedrock doesn't support it for older models)
         self._remove_ttl_from_cache_control(anthropic_messages_request=anthropic_messages_request, model=model)
 
-        # 5. Convert structured-output params to inline schema.
-        # Bedrock Invoke doesn't support top-level `output_format`; its
-        # accepted `output_config` subset is also narrower than Anthropic's, so
-        # consume the newer `output_config.format` shape here instead of
-        # forwarding it as an unknown nested key.
+        # 5. Route structured-output params (`output_format` /
+        # `output_config.format`) to native enforcement or the inline-schema
+        # fallback, then strip `output_config` keys the model does not accept.
+        # Ref: https://github.com/BerriAI/litellm/issues/22797
         existing_output_config: Final = anthropic_messages_request.get("output_config")
         if isinstance(existing_output_config, dict):
             anthropic_messages_request["output_config"] = dict(existing_output_config)
-        output_format: Final = anthropic_messages_request.pop("output_format", None)
-        output_config_format: Final = pop_bedrock_invoke_output_config_format(anthropic_messages_request)
-        if output_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_format,
-                request_body=anthropic_messages_request,
-            )
-        elif output_config_format:
-            convert_bedrock_invoke_output_format_to_inline_schema(
-                output_format=output_config_format,
-                request_body=anthropic_messages_request,
-            )
+        apply_bedrock_invoke_structured_output(
+            model=model,
+            request_body=anthropic_messages_request,
+        )
         normalize_bedrock_opus_output_config_effort(
             model=model,
             output_config=anthropic_messages_request.get("output_config"),
         )
-
-        # 5a. Bedrock Invoke supports output_config (effort) for Claude 4.6+ models,
-        # but older models do not — strip it to avoid request rejection.
-        # Ref: https://github.com/BerriAI/litellm/issues/22797
-        if not (
-            _supports_factory(
-                model=model,
-                custom_llm_provider="bedrock",
-                key="supports_output_config",
-            )
-            or AnthropicConfig._model_supports_effort_param(model, "bedrock")
-        ):
-            if anthropic_messages_request.pop("output_config", None) is not None:
-                verbose_logger.warning(
-                    "Bedrock Invoke: stripping unsupported `output_config` for "
-                    "model=%s — neither `supports_output_config` nor any "
-                    "`supports_*_reasoning_effort` flag is set in "
-                    "model_prices_and_context_window.json. Add the capability "
-                    "flag to the model JSON entry if this model accepts "
-                    "`output_config`.",
-                    model,
-                )
+        strip_unsupported_bedrock_invoke_output_config_keys(
+            model=model,
+            request_body=anthropic_messages_request,
+        )
 
         # 5b. Hoist `custom.defer_loading` then drop `custom` (Bedrock doesn't support it)
         # Ref: https://github.com/BerriAI/litellm/issues/22847
@@ -774,9 +746,11 @@ class AmazonAnthropicClaudeMessagesConfig(
         if filtered_betas:
             anthropic_messages_request["anthropic_beta"] = filtered_betas
 
+        remaining_output_config: Final = anthropic_messages_request.get("output_config")
         if (
             litellm.drop_params is True
-            and "output_config" in anthropic_messages_request
+            and isinstance(remaining_output_config, dict)
+            and any(key != "format" for key in remaining_output_config)
             and not AnthropicConfig._model_supports_effort_param(model, "bedrock")
         ):
             verbose_logger.warning(
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 718e6c489fd..80dc49a770b 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1591,7 +1591,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1627,7 +1627,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1663,7 +1663,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1699,7 +1699,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1735,7 +1735,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1771,7 +1771,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -2064,7 +2064,7 @@
         "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",
@@ -2101,7 +2101,7 @@
         "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",
@@ -2138,7 +2138,7 @@
         "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",
@@ -2175,7 +2175,7 @@
         "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",
@@ -2212,7 +2212,7 @@
         "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",
@@ -2249,7 +2249,7 @@
         "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",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 718e6c489fd..80dc49a770b 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -1591,7 +1591,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1627,7 +1627,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1663,7 +1663,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1699,7 +1699,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1735,7 +1735,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -1771,7 +1771,7 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_xhigh_reasoning_effort": true,
-        "supports_native_structured_output": true,
+        "supports_native_structured_output": false,
         "supports_max_reasoning_effort": true,
         "supports_output_config": true,
         "supports_parallel_tool_use_config": true,
@@ -2064,7 +2064,7 @@
         "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",
@@ -2101,7 +2101,7 @@
         "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",
@@ -2138,7 +2138,7 @@
         "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",
@@ -2175,7 +2175,7 @@
         "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",
@@ -2212,7 +2212,7 @@
         "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",
@@ -2249,7 +2249,7 @@
         "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",
diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py
index 25e2c3cda80..c4df46dea83 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
@@ -6207,3 +6207,45 @@ def test_disabled_thinking_omitted_only_for_always_on_models(
         assert "thinking" not in request
     else:
         assert request["thinking"] == {"type": "disabled"}
+
+
+def test_anthropic_drop_params_keeps_format_only_output_config(monkeypatch):
+    """``drop_params=True`` must not consume ``output_config.format``: the drop
+    gate is an effort gate and ``format`` is a structured-output field."""
+    monkeypatch.setattr(litellm, "drop_params", True)
+    config = AnthropicConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"z": {"type": "integer"}}},
+    }
+
+    result = config.transform_request(
+        model="claude-3-haiku-20240307",
+        messages=[{"role": "user", "content": "Hello"}],
+        optional_params={"output_config": {"format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_anthropic_drop_params_reduces_mixed_output_config_to_format(monkeypatch):
+    """``drop_params=True`` drops the effort key on unsupported models but keeps
+    ``format`` so structured outputs still reach the provider."""
+    monkeypatch.setattr(litellm, "drop_params", True)
+    config = AnthropicConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"z": {"type": "integer"}}},
+    }
+
+    result = config.transform_request(
+        model="claude-3-haiku-20240307",
+        messages=[{"role": "user", "content": "Hello"}],
+        optional_params={"output_config": {"effort": "low", "format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
diff --git a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
index cea299280f8..a122d97a0f0 100644
--- a/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/invoke_transformations/test_bedrock_chat_invoke_transformations_anthropic_claude3_transformation.py
@@ -428,30 +428,58 @@ def test_output_config_forwarded_for_bedrock_chat_invoke_request():
 
 
 def test_output_config_format_converted_for_bedrock_chat_invoke_request():
-    """Bedrock Invoke chat path consumes ``output_config.format`` before forwarding."""
+    """Bedrock Invoke chat path inlines ``output_config.format`` for models
+    without native structured-output support and keeps the effort key."""
     config = AmazonAnthropicClaudeConfig()
     schema = {
         "type": "object",
         "properties": {"answer": {"type": "string"}},
     }
 
-    result = config.transform_request(
+    with patch(  # test-quality-ok: pin non-native path
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
+    ):
+        result = config.transform_request(
+            model="anthropic.claude-opus-4-7",
+            messages=[{"role": "user", "content": "test"}],
+            optional_params={
+                "max_tokens": 100,
+                "output_config": {
+                    "effort": "xhigh",
+                    "format": {"type": "json_schema", "schema": schema},
+                },
+            },
+            litellm_params={},
+            headers={},
+        )
+
+    assert result.get("output_config") == {"effort": "xhigh"}
+    last_content = result["messages"][0]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
+
+
+def test_output_config_format_forwarded_for_bedrock_chat_invoke_request():
+    """Bedrock Invoke chat path forwards ``output_config.format`` alongside effort
+    for models with native structured-output support (Claude Opus 4.7)."""
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"answer": {"type": "string"}}},
+    }
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
         model="anthropic.claude-opus-4-7",
         messages=[{"role": "user", "content": "test"}],
         optional_params={
             "max_tokens": 100,
-            "output_config": {
-                "effort": "xhigh",
-                "format": {"type": "json_schema", "schema": schema},
-            },
+            "output_config": {"effort": "xhigh", "format": schema_format},
         },
         litellm_params={},
         headers={},
     )
 
-    assert result.get("output_config") == {"effort": "xhigh"}
-    last_content = result["messages"][0]["content"]
-    assert json.loads(last_content[-1]["text"]) == schema
+    assert result.get("output_config") == {"effort": "xhigh", "format": schema_format}
+    assert "answer" not in json.dumps(result["messages"])
 
 
 @pytest.mark.parametrize(
@@ -488,7 +516,7 @@ def test_bedrock_chat_invoke_checks_output_config_support_with_bedrock_provider(
     optional_params = {"max_tokens": 100, "output_config": {"effort": "high"}}
 
     with patch(
-        "litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ) as mock_supports_factory:
         result = config.transform_request(
@@ -499,11 +527,7 @@ def test_bedrock_chat_invoke_checks_output_config_support_with_bedrock_provider(
             headers={},
         )
 
-    mock_supports_factory.assert_called_once_with(
-        model="us.anthropic.claude-opus-4-7",
-        custom_llm_provider="bedrock",
-        key="supports_output_config",
-    )
+    mock_supports_factory.assert_called_once_with("us.anthropic.claude-opus-4-7", "supports_output_config")
     assert result["output_config"] == {"effort": "high"}
 
 
@@ -542,3 +566,80 @@ def test_output_format_removed_from_bedrock_invoke_request():
     assert (
         "output_format" not in result
     ), f"output_format should be removed for Bedrock Invoke, got keys: {result.keys()}"
+
+
+def test_bedrock_chat_invoke_forwards_output_config_format_natively(local_model_cost_map):
+    """Regression: ``output_config.format`` is forwarded verbatim on models Bedrock
+    enforces structured outputs for, instead of being inlined as prompt text."""
+    import json
+
+    config = AmazonAnthropicClaudeConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {"zebra_count": {"type": "integer"}},
+            "required": ["zebra_count"],
+            "additionalProperties": False,
+        },
+    }
+
+    result = config.transform_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+    assert "zebra_count" not in json.dumps(result["messages"])
+
+
+def test_bedrock_chat_invoke_drop_params_keeps_native_output_config_format(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` must not eat ``output_config.format`` before the
+    native-forwarding router runs (Sonnet 4.5 has no effort flags)."""
+    import litellm
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={"max_tokens": 100, "output_config": {"format": schema_format}},
+        litellm_params={},
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_bedrock_chat_invoke_drop_params_still_inlines_for_non_native(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` on a model without native structured-output support
+    still reaches the inline-schema fallback instead of losing the schema."""
+    import litellm
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    schema = {"type": "object", "properties": {"zebra_count": {"type": "integer"}}}
+
+    result = AmazonAnthropicClaudeConfig().transform_request(
+        model="anthropic.claude-3-haiku-20240307-v1:0",
+        messages=[{"role": "user", "content": "say hello"}],
+        optional_params={
+            "max_tokens": 100,
+            "output_config": {"format": {"type": "json_schema", "schema": schema}},
+        },
+        litellm_params={},
+        headers={},
+    )
+
+    assert "output_config" not in result
+    last_content = result["messages"][-1]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
diff --git a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
index 8d07d38b1b6..09ebc1a3c95 100644
--- a/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
+++ b/tests/test_litellm/llms/bedrock/messages/invoke_transformations/test_anthropic_claude3_transformation.py
@@ -935,7 +935,7 @@ def test_bedrock_messages_strips_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=False,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -970,7 +970,7 @@ def test_bedrock_messages_preserves_output_config_for_claude_4_6():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1003,7 +1003,7 @@ def test_bedrock_messages_checks_output_config_support_with_bedrock_provider():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ) as mock_supports_factory:
         result = cfg.transform_anthropic_messages_request(
@@ -1014,11 +1014,7 @@ def test_bedrock_messages_checks_output_config_support_with_bedrock_provider():
             headers={},
         )
 
-    mock_supports_factory.assert_called_with(
-        model="us.anthropic.claude-opus-4-7",
-        custom_llm_provider="bedrock",
-        key="supports_output_config",
-    )
+    mock_supports_factory.assert_called_with("us.anthropic.claude-opus-4-7", "supports_output_config")
     assert result["output_config"] == {"effort": "high"}
 
 
@@ -1038,7 +1034,7 @@ def test_bedrock_messages_forwards_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1054,27 +1050,29 @@ def test_bedrock_messages_forwards_output_config():
 
 
 def test_bedrock_messages_forwards_output_config_with_output_format():
-    """``output_config`` is forwarded; ``output_format`` is converted to inline schema."""
+    """Legacy ``output_format`` is forwarded as ``output_config.format`` on models
+    that support native structured outputs, alongside the effort key."""
     from unittest.mock import patch
 
     from litellm.types.router import GenericLiteLLMParams
 
     cfg = AmazonAnthropicClaudeMessagesConfig()
     messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}]
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {"answer": {"type": "string"}},
+        },
+    }
     optional_params = {
         "max_tokens": 4096,
         "output_config": {"effort": "low"},
-        "output_format": {
-            "type": "json_schema",
-            "schema": {
-                "type": "object",
-                "properties": {"answer": {"type": "string"}},
-            },
-        },
+        "output_format": schema_format,
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1085,12 +1083,14 @@ def test_bedrock_messages_forwards_output_config_with_output_format():
             headers={},
         )
 
-    assert result.get("output_config") == {"effort": "low"}
+    assert result.get("output_config") == {"effort": "low", "format": schema_format}
     assert "output_format" not in result
+    assert "answer" not in json.dumps(result["messages"])
 
 
 def test_bedrock_messages_converts_output_config_format_to_inline_schema():
-    """``output_config.format`` is consumed so Bedrock does not see an unknown nested key."""
+    """Without native structured-output support, ``output_config.format`` falls back
+    to the inline schema so Bedrock does not see an unknown nested key."""
     from unittest.mock import patch
 
     from litellm.types.router import GenericLiteLLMParams
@@ -1110,8 +1110,8 @@ def test_bedrock_messages_converts_output_config_format_to_inline_schema():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
-        return_value=True,
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
     ):
         result = cfg.transform_anthropic_messages_request(
             model="anthropic.claude-opus-4-7",
@@ -1146,7 +1146,7 @@ def test_bedrock_messages_normalizes_output_config_effort_for_opus(
     cfg = AmazonAnthropicClaudeMessagesConfig()
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1184,8 +1184,8 @@ def test_bedrock_messages_does_not_mutate_callers_messages_when_embedding_schema
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
-        return_value=True,
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
+        side_effect=lambda _model, key: key == "supports_output_config",
     ):
         result = cfg.transform_anthropic_messages_request(
             model="anthropic.claude-opus-4-7",
@@ -1229,7 +1229,7 @@ def test_bedrock_messages_does_not_mutate_callers_output_config():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         cfg.transform_anthropic_messages_request(
@@ -1271,7 +1271,7 @@ def test_bedrock_messages_strips_output_config_with_output_format():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=False,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1332,7 +1332,7 @@ def test_bedrock_messages_drop_params_keeps_output_config_for_4_7():
     litellm.drop_params = True
     try:
         with patch(
-            "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+            "litellm.llms.bedrock.common_utils._bedrock_model_supports",
             return_value=True,
         ):
             result = cfg.transform_anthropic_messages_request(
@@ -1375,7 +1375,7 @@ def test_bedrock_messages_maps_reasoning_effort_for_adaptive_model(
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -1482,7 +1482,7 @@ def test_bedrock_messages_explicit_output_config_wins_over_reasoning_effort():
     }
 
     with patch(
-        "litellm.llms.bedrock.messages.invoke_transformations.anthropic_claude3_transformation._supports_factory",
+        "litellm.llms.bedrock.common_utils._bedrock_model_supports",
         return_value=True,
     ):
         result = cfg.transform_anthropic_messages_request(
@@ -3104,3 +3104,149 @@ async def test_bedrock_sse_wrapper_dispatches_logging_on_client_disconnect():
             break
         await asyncio.sleep(0.01)
     assert logging_obj.completion_start_time is not None
+
+
+def test_bedrock_messages_forwards_output_config_format_natively(local_model_cost_map):
+    """Regression: on a model Bedrock enforces structured outputs for (Claude
+    Sonnet 4.5), ``output_config.format`` must be forwarded verbatim, not
+    silently rewritten into inline prompt text."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {
+            "type": "object",
+            "properties": {
+                "zebra_count": {"type": "integer"},
+                "is_tuesday": {"type": "boolean"},
+            },
+            "required": ["zebra_count", "is_tuesday"],
+            "additionalProperties": False,
+        },
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+    assert "zebra_count" not in json.dumps(result["messages"])
+
+
+def test_bedrock_messages_inlines_schema_for_claude_5(local_model_cost_map):
+    """Bedrock rejects ``output_config.format`` for the Claude 5 family, so the
+    schema falls back to the inline-text path instead of a deterministic 400."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema = {
+        "type": "object",
+        "properties": {"zebra_count": {"type": "integer"}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-5",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": {"type": "json_schema", "schema": schema}},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert "output_config" not in result
+    last_content = result["messages"][-1]["content"]
+    assert json.loads(last_content[-1]["text"]) == schema
+
+
+def test_bedrock_messages_legacy_output_format_wins_over_output_config_format(local_model_cost_map):
+    """When a request carries both schema forms, the legacy top-level
+    ``output_format`` keeps winning, matching the pre-existing precedence."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    legacy_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"legacy_field": {"type": "string"}}},
+    }
+    newer_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"newer_field": {"type": "string"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_format": legacy_format,
+            "output_config": {"format": newer_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": legacy_format}
+    assert "output_format" not in result
+    assert "newer_field" not in json.dumps(result)
+
+
+def test_bedrock_messages_drop_params_keeps_native_output_config_format(local_model_cost_map, monkeypatch):
+    """``drop_params=True`` must not strip a natively forwarded
+    ``output_config.format`` on models without effort support (Sonnet 4.5)."""
+    import litellm
+    from litellm.types.router import GenericLiteLLMParams
+
+    monkeypatch.setattr(litellm, "drop_params", True)
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 100,
+            "output_config": {"format": schema_format},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
+
+
+def test_bedrock_messages_strips_effort_but_keeps_format_for_sonnet_4_5(local_model_cost_map):
+    """Sonnet 4.5 has native structured-output support but no effort support, so
+    a mixed ``output_config`` keeps ``format`` and drops ``effort``."""
+    from litellm.types.router import GenericLiteLLMParams
+
+    cfg = AmazonAnthropicClaudeMessagesConfig()
+    schema_format = {
+        "type": "json_schema",
+        "schema": {"type": "object", "properties": {"zebra_count": {"type": "integer"}}},
+    }
+
+    result = cfg.transform_anthropic_messages_request(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "say hello"}]}],
+        anthropic_messages_optional_request_params={
+            "max_tokens": 4096,
+            "output_config": {"format": schema_format, "effort": "high"},
+        },
+        litellm_params=GenericLiteLLMParams(),
+        headers={},
+    )
+
+    assert result.get("output_config") == {"format": schema_format}
diff --git a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
index 389bf4a8e40..609b5c75801 100644
--- a/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
+++ b/tests/test_litellm/llms/bedrock/test_bedrock_common_utils.py
@@ -520,3 +520,44 @@ def test_merge_bedrock_aws_request_params_keeps_caller_credentials_without_stati
     assert merged["aws_secret_access_key"] == "caller-secret"
     assert merged["aws_session_token"] == "caller-token"
     assert merged["aws_region_name"] == "us-west-2"
+
+
+def test_strip_unsupported_output_config_keeps_format_drops_effort(local_model_cost_map):
+    """On a model with neither effort flag, only the ``format`` key survives."""
+    from litellm.llms.bedrock.common_utils import (
+        strip_unsupported_bedrock_invoke_output_config_keys,
+    )
+
+    schema_format = {"type": "json_schema", "schema": {"type": "object"}}
+    body = {"output_config": {"effort": "high", "format": schema_format}}
+
+    strip_unsupported_bedrock_invoke_output_config_keys(
+        model="anthropic.claude-3-haiku-20240307-v1:0",
+        request_body=body,
+    )
+
+    assert body["output_config"] == {"format": schema_format}
+
+
+def test_apply_structured_output_prefers_legacy_output_format(local_model_cost_map):
+    """The legacy ``output_format`` wins over ``output_config.format`` when a
+    request carries both, matching the pre-existing precedence."""
+    from litellm.llms.bedrock.common_utils import (
+        apply_bedrock_invoke_structured_output,
+    )
+
+    legacy = {"type": "json_schema", "schema": {"type": "object", "properties": {"a": {"type": "string"}}}}
+    newer = {"type": "json_schema", "schema": {"type": "object", "properties": {"b": {"type": "string"}}}}
+    body = {
+        "messages": [{"role": "user", "content": "hi"}],
+        "output_format": legacy,
+        "output_config": {"format": newer},
+    }
+
+    apply_bedrock_invoke_structured_output(
+        model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
+        request_body=body,
+    )
+
+    assert body["output_config"] == {"format": legacy}
+    assert "output_format" not in body

From 215bf03373617c6de89aa47c19dc3be7d5094634 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 10:59:38 +0000
Subject: [PATCH 033/113] refactor(types): replace Any with precise types
 across 73 modules

Narrows reportAny / reportExplicitAny hot spots in provider transformations,
proxy endpoints, integrations and secret managers by introducing TypedDicts,
Protocols and object-typed boundaries instead of Any, then ratchets the
budget ceilings down to match.

reportAny 14765 -> 14076, reportExplicitAny 4493 -> 4128, ANN401 387 -> 307
---
 basedpyright-code-budget.json                 |  16 +--
 litellm/caching/caching.py                    |   9 +-
 litellm/caching/qdrant_semantic_cache.py      |  18 ++-
 .../handler.py                                |  14 +--
 litellm/google_genai/main.py                  |  30 ++---
 litellm/images/main.py                        |  24 ++--
 .../SlackAlerting/slack_alerting.py           |  24 +++-
 .../bitbucket/bitbucket_prompt_manager.py     |  37 +++---
 litellm/integrations/cloudzero/transform.py   |  27 ++++-
 litellm/integrations/custom_guardrail.py      |  13 ++-
 litellm/integrations/datadog/datadog.py       |  44 ++++---
 .../integrations/datadog/datadog_llm_obs.py   |  19 ++--
 .../integrations/dotprompt/prompt_manager.py  |  25 ++--
 litellm/integrations/galileo.py               |  35 +++++-
 litellm/integrations/gitlab/gitlab_client.py  |  88 ++++++++++++--
 litellm/integrations/langfuse/langfuse.py     |  39 ++++---
 litellm/integrations/opik/opik.py             |  27 ++++-
 .../opik/opik_payload_builder/extractors.py   |  21 ++--
 litellm/integrations/otel/plumbing/metrics.py |  45 ++++++--
 .../vector_store_pre_call_hook.py             |   6 +-
 .../litellm_core_utils/realtime_streaming.py  |   2 +-
 .../streaming_chunk_builder_utils.py          |  14 ++-
 .../a2a/chat/guardrail_translation/handler.py |  27 +++--
 litellm/llms/anthropic/chat/transformation.py |  51 ++++++---
 litellm/llms/anthropic/files/handler.py       |   4 +-
 litellm/llms/azure/azure.py                   |  16 +--
 litellm/llms/azure_ai/agents/handler.py       |  20 +---
 .../llms/bedrock/realtime/transformation.py   |   6 +-
 .../black_forest_labs/image_edit/handler.py   |  56 +++++++--
 .../image_generation/handler.py               |  35 ++++--
 litellm/llms/codestral/completion/handler.py  |  52 ++++++++-
 .../llms/deepinfra/rerank/transformation.py   |  39 ++++++-
 .../gemini/interactions/transformation.py     |  62 ++++++++--
 litellm/llms/gemini/videos/transformation.py  |  36 +++---
 .../huggingface/embedding/transformation.py   |  22 +++-
 .../llms/openai/chat/gpt_transformation.py    |  14 ++-
 .../chat/guardrail_translation/handler.py     |  19 ++--
 .../llms/openai/responses/transformation.py   |  45 ++++++--
 litellm/llms/openai_like/chat/handler.py      |  28 ++++-
 .../image_generation/transformation.py        |  24 +++-
 litellm/llms/sap/credentials.py               |  55 ++++++---
 .../llms/vertex_ai/files/transformation.py    |  49 +++++---
 .../llms/vertex_ai/gemini/transformation.py   |  18 +--
 litellm/llms/vertex_ai/vertex_llm_base.py     |  53 ++++++---
 litellm/passthrough/main.py                   |  28 ++---
 .../mcp_server/semantic_tool_filter.py        |  19 ++--
 .../proxy/agent_endpoints/a2a_endpoints.py    |  19 +++-
 litellm/proxy/auth/handle_jwt.py              |  56 +++++++--
 litellm/proxy/common_utils/debug_utils.py     | 107 +++++++++++++-----
 litellm/proxy/db/db_spend_update_writer.py    |  10 +-
 .../guardrails/guardrail_hooks/akto/akto.py   |   8 +-
 .../guardrail_hooks/grayswan/grayswan.py      |  50 ++++++--
 .../guardrails/guardrail_hooks/lasso/lasso.py |  11 +-
 .../guardrail_hooks/pillar/pillar.py          |  54 +++++++--
 .../semantic_guard/semantic_guard.py          |  15 ++-
 .../guardrail_hooks/tool_permission.py        |  56 ++++++---
 .../vigil_guard/vigil_guard.py                |   2 +-
 litellm/proxy/hooks/litellm_skills/main.py    |  23 +++-
 .../hooks/parallel_request_limiter_v3.py      |  24 +++-
 .../model_management_endpoints.py             |   4 +-
 .../organization_endpoints.py                 |  15 ++-
 litellm/proxy/management_endpoints/ui_sso.py  |   6 +-
 .../vertex_passthrough_logging_handler.py     |   4 +-
 .../proxy/response_api_endpoints/endpoints.py |  12 +-
 litellm/proxy/route_llm_request.py            |   4 +-
 litellm/proxy/video_endpoints/endpoints.py    |  10 +-
 litellm/rag/main.py                           |  11 +-
 .../mcp/litellm_proxy_mcp_handler.py          |   4 +-
 litellm/router_strategy/budget_limiter.py     |  13 ++-
 .../complexity_router/complexity_router.py    |   4 +-
 .../hashicorp_secret_manager.py               | 105 ++++++++++++++---
 litellm/types/llms/openai.py                  |  18 +--
 litellm/types/router.py                       |   9 +-
 .../vector_stores/vector_store_registry.py    |   6 +-
 ruff-strict-budget.json                       |  14 +--
 type-discipline-budget.json                   |   8 +-
 76 files changed, 1458 insertions(+), 579 deletions(-)

diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index a07b9352659..df52069e71f 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -1,6 +1,6 @@
 {
   "reportAny": {
-    "limit": 14765
+    "limit": 14076
   },
   "reportArgumentType": {
     "limit": 2216
@@ -24,7 +24,7 @@
     "limit": 19
   },
   "reportExplicitAny": {
-    "limit": 4493
+    "limit": 4128
   },
   "reportFunctionMemberAccess": {
     "limit": 7
@@ -54,10 +54,10 @@
     "limit": 0
   },
   "reportMissingParameterType": {
-    "limit": 5607
+    "limit": 5601
   },
   "reportMissingTypeArgument": {
-    "limit": 15310
+    "limit": 15306
   },
   "reportMissingTypeStubs": {
     "limit": 40
@@ -105,13 +105,13 @@
     "limit": 109
   },
   "reportUnknownMemberType": {
-    "limit": 38368
+    "limit": 38350
   },
   "reportUnknownParameterType": {
-    "limit": 19633
+    "limit": 19626
   },
   "reportUnknownVariableType": {
-    "limit": 29908
+    "limit": 29890
   },
   "reportUnnecessaryCast": {
     "limit": 111
@@ -123,7 +123,7 @@
     "limit": 5
   },
   "reportUnnecessaryIsInstance": {
-    "limit": 828
+    "limit": 826
   },
   "reportUntypedBaseClass": {
     "limit": 0
diff --git a/litellm/caching/caching.py b/litellm/caching/caching.py
index cefe6aae9ed..754815fce47 100644
--- a/litellm/caching/caching.py
+++ b/litellm/caching/caching.py
@@ -12,6 +12,7 @@ import hashlib
 import json
 import time
 import traceback
+from collections.abc import Mapping
 from enum import Enum
 from typing import Any, Final
 
@@ -506,7 +507,7 @@ class Cache:
 
     def _get_cache_logic(
         self,
-        cached_result: Any | None,
+        cached_result: object | None,
         max_age: float | None,
     ):
         """
@@ -538,8 +539,8 @@ class Cache:
         return cached_result
 
     @staticmethod
-    def _get_safe_cache_lookup_kwargs(kwargs: dict[str, Any]) -> dict[str, Any]:
-        cache_lookup_kwargs: Final[dict[str, Any]] = {}
+    def _get_safe_cache_lookup_kwargs(kwargs: Mapping[str, object]) -> dict[str, object]:
+        cache_lookup_kwargs: Final[dict[str, object]] = {}
         for prompt_kwarg in ("messages", "input"):
             if prompt_kwarg in kwargs:
                 cache_lookup_kwargs[prompt_kwarg] = kwargs[prompt_kwarg]
@@ -552,7 +553,7 @@ class Cache:
 
     @staticmethod
     def _update_metadata_from_cache_lookup_kwargs(
-        original_kwargs: dict[str, Any], cache_lookup_kwargs: dict[str, Any]
+        original_kwargs: Mapping[str, object], cache_lookup_kwargs: Mapping[str, object]
     ) -> None:
         original_metadata: Final = original_kwargs.get("metadata")
         cache_lookup_metadata: Final = cache_lookup_kwargs.get("metadata")
diff --git a/litellm/caching/qdrant_semantic_cache.py b/litellm/caching/qdrant_semantic_cache.py
index 4898700c403..c5876e993d3 100644
--- a/litellm/caching/qdrant_semantic_cache.py
+++ b/litellm/caching/qdrant_semantic_cache.py
@@ -12,7 +12,7 @@ import ast
 import asyncio
 import json
 import os
-from typing import TYPE_CHECKING, Any, Final, cast
+from typing import TYPE_CHECKING, Any, Final, Protocol, cast
 
 import litellm
 from litellm._logging import print_verbose
@@ -39,6 +39,12 @@ if TYPE_CHECKING:
     from litellm.router import Router
 
 
+class _QdrantCollectionDetailsResponse(Protocol):
+    """The qdrant `/collections/{name}` response, whose body is kept as an opaque JSON object."""
+
+    def json(self) -> dict[str, object]: ...
+
+
 class QdrantSemanticCache(BaseCache):
     CACHE_KEY_FIELD_NAME = "litellm_cache_key"
     embedding_max_input_tokens: int | None = None
@@ -115,15 +121,15 @@ class QdrantSemanticCache(BaseCache):
             raise ValueError(f"Error from qdrant checking if /collections exist {collection_exists.text}")
 
         if collection_exists.json()["result"]["exists"]:
-            collection_details = self.sync_client.get(
+            collection_details: _QdrantCollectionDetailsResponse = self.sync_client.get(
                 url=f"{self.qdrant_api_base}/collections/{self.collection_name}",
                 headers=self.headers,
             )
-            self.collection_info = collection_details.json()
+            self.collection_info: dict[str, object] = collection_details.json()
             print_verbose(f"Collection already exists.\nCollection details:{self.collection_info}")
             self._ensure_cache_key_payload_index()
         else:
-            quantization_params: dict[str, Any]
+            quantization_params: dict[str, dict[str, object]]
             if quantization_config is None or quantization_config == "binary":
                 quantization_params = {
                     "binary": {
@@ -214,7 +220,7 @@ class QdrantSemanticCache(BaseCache):
             resolve_embedding_max_input_tokens(self.embedding_max_input_tokens, self.embedding_model, router),
         )
 
-    def _get_embedding(self, prompt: str, metadata: dict[str, Any] | None = None) -> EmbeddingResponse:
+    def _get_embedding(self, prompt: str, metadata: dict[str, object] | None = None) -> EmbeddingResponse:
         """Embed via the proxy Router when it serves the model, else direct."""
         try:
             from litellm.proxy.proxy_server import llm_model_list, llm_router
@@ -241,7 +247,7 @@ class QdrantSemanticCache(BaseCache):
             num_retries=0,
         )
 
-    async def _get_async_embedding(self, prompt: str, metadata: dict[str, Any] | None = None) -> EmbeddingResponse:
+    async def _get_async_embedding(self, prompt: str, metadata: dict[str, object] | None = None) -> EmbeddingResponse:
         try:
             from litellm.proxy.proxy_server import llm_model_list, llm_router
         except ImportError:
diff --git a/litellm/completion_extras/litellm_responses_transformation/handler.py b/litellm/completion_extras/litellm_responses_transformation/handler.py
index 727c39c16ec..f494d6610a1 100644
--- a/litellm/completion_extras/litellm_responses_transformation/handler.py
+++ b/litellm/completion_extras/litellm_responses_transformation/handler.py
@@ -45,14 +45,14 @@ class ResponsesToCompletionBridgeHandler:
         return bool(stream)
 
     @staticmethod
-    def _is_preformatted_cached_chat_stream(result: Any) -> bool:
+    def _is_preformatted_cached_chat_stream(result: object) -> bool:
         from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
 
         return isinstance(result, CustomStreamWrapper) and result.custom_llm_provider == "cached_response"
 
     @staticmethod
     def _coerce_response_object(
-        response_obj: Any,
+        response_obj: object,
         hidden_params: dict | None,
     ) -> "ResponsesAPIResponse":
         if isinstance(response_obj, ResponsesAPIResponse):
@@ -78,8 +78,8 @@ class ResponsesToCompletionBridgeHandler:
         for _ in stream_iter:
             pass
 
-        completed: Final = getattr(stream_iter, "completed_response", None)
-        response_obj: Final = getattr(completed, "response", None) if completed else None
+        completed: Final[object] = getattr(stream_iter, "completed_response", None)
+        response_obj: Final[object] = getattr(completed, "response", None) if completed else None
         if response_obj is None:
             raise ValueError("Stream ended without a completed response")
 
@@ -93,8 +93,8 @@ class ResponsesToCompletionBridgeHandler:
         async for _ in stream_iter:
             pass
 
-        completed: Final = getattr(stream_iter, "completed_response", None)
-        response_obj: Final = getattr(completed, "response", None) if completed else None
+        completed: Final[object] = getattr(stream_iter, "completed_response", None)
+        response_obj: Final[object] = getattr(completed, "response", None) if completed else None
         if response_obj is None:
             raise ValueError("Stream ended without a completed response")
 
@@ -157,7 +157,7 @@ class ResponsesToCompletionBridgeHandler:
     def completion(
         self, *args, **kwargs
     ) -> Union[
-        Coroutine[Any, Any, Union["ModelResponse", "CustomStreamWrapper"]],
+        Coroutine[None, None, Union["ModelResponse", "CustomStreamWrapper"]],
         "ModelResponse",
         "CustomStreamWrapper",
     ]:
diff --git a/litellm/google_genai/main.py b/litellm/google_genai/main.py
index b5815bd3f7c..c1822e4720d 100644
--- a/litellm/google_genai/main.py
+++ b/litellm/google_genai/main.py
@@ -52,10 +52,10 @@ class GenerateContentSetupResult(BaseModel):
     model_config: ClassVar[ConfigDict] = ConfigDict(arbitrary_types_allowed=True)
 
     model: str
-    request_body: dict[str, Any]
+    request_body: dict[str, object]
     custom_llm_provider: str
     generate_content_provider_config: BaseGoogleGenAIGenerateContentConfig | None
-    generate_content_config_dict: dict[str, Any]
+    generate_content_config_dict: dict[str, object]
     native_request_fields: dict[str, object]
     litellm_params: GenericLiteLLMParams
     litellm_logging_obj: LiteLLMLoggingObj
@@ -68,7 +68,7 @@ class GenerateContentHelper:
     @staticmethod
     def mock_generate_content_response(
         mock_response: str = "This is a mock response from Google GenAI generate_content.",
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Mock response for generate_content for testing purposes"""
         return {
             "text": mock_response,
@@ -239,9 +239,9 @@ async def agenerate_content(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -307,9 +307,9 @@ def generate_content(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -397,9 +397,9 @@ async def agenerate_content_stream(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -492,9 +492,9 @@ def generate_content_stream(
     tools: ToolConfigDict | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
diff --git a/litellm/images/main.py b/litellm/images/main.py
index 1688087c2da..617f8e08ab6 100644
--- a/litellm/images/main.py
+++ b/litellm/images/main.py
@@ -3,7 +3,7 @@ import contextvars
 import importlib
 from collections.abc import Coroutine
 from functools import partial
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional, cast, overload
+from typing import TYPE_CHECKING, Final, Literal, Optional, cast, overload
 
 if TYPE_CHECKING:
     from litellm.images.utils import ImageEditRequestUtils
@@ -151,7 +151,7 @@ def image_generation(
     *,
     aimg_generation: Literal[True],
     **kwargs,
-) -> Coroutine[Any, Any, ImageResponse]: 
+) -> Coroutine[object, object, ImageResponse]:
     ...
 
 
@@ -197,7 +197,7 @@ def image_generation(
     api_version: str | None = None,
     custom_llm_provider=None,
     **kwargs,
-) -> ImageResponse | Coroutine[Any, Any, ImageResponse]:
+) -> ImageResponse | Coroutine[object, object, ImageResponse]:
     """
     Maps the https://api.openai.com/v1/images/generations endpoint.
 
@@ -723,14 +723,14 @@ def image_edit(
     user: str | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
     **kwargs,
-) -> ImageResponse | Coroutine[Any, Any, ImageResponse]:
+) -> ImageResponse | Coroutine[object, object, ImageResponse]:
     """
     Maps the image edit functionality, similar to OpenAI's images/edits endpoint.
     """
@@ -769,7 +769,7 @@ def image_edit(
         images: Final = image if isinstance(image, list) else ([image] if image is not None else [])
 
         headers_from_kwargs: Final = kwargs.get("headers")
-        merged_extra_headers: Final[dict[str, Any]] = {}
+        merged_extra_headers: Final[dict[str, object]] = {}
         if isinstance(headers_from_kwargs, dict):
             merged_extra_headers.update(headers_from_kwargs)
         if isinstance(extra_headers, dict):
@@ -974,9 +974,9 @@ async def aimage_edit(
     user: str | None = None,
     # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
     # The extra values given here take precedence over values defined on the client or passed to this method.
-    extra_headers: dict[str, Any] | None = None,
-    extra_query: dict[str, Any] | None = None,
-    extra_body: dict[str, Any] | None = None,
+    extra_headers: dict[str, object] | None = None,
+    extra_query: dict[str, object] | None = None,
+    extra_body: dict[str, object] | None = None,
     timeout: float | httpx.Timeout | None = None,
     # LiteLLM specific params,
     custom_llm_provider: str | None = None,
@@ -1044,7 +1044,7 @@ async def aimage_edit(
         )
 
 
-def __getattr__(name: str) -> Any:
+def __getattr__(name: str) -> type["ImageEditRequestUtils"]:
     """Lazy import handler for images.main module"""
     if name == "ImageEditRequestUtils":
         # Lazy load ImageEditRequestUtils to avoid heavy import from images.utils at module load time
diff --git a/litellm/integrations/SlackAlerting/slack_alerting.py b/litellm/integrations/SlackAlerting/slack_alerting.py
index 94d734546be..c137164ecdb 100644
--- a/litellm/integrations/SlackAlerting/slack_alerting.py
+++ b/litellm/integrations/SlackAlerting/slack_alerting.py
@@ -545,7 +545,6 @@ class SlackAlerting(CustomBatchLogger):
         # Get the appropriate budget alert type handler
         budget_alert_class: Final = get_budget_alert_type(type)
         _id: Final = budget_alert_class.get_id(user_info)
-        user_info_json: Final = user_info.model_dump(exclude_none=True)
         user_info_str: Final = self._get_user_info_str(user_info)
         event_message = budget_alert_class.get_event_message()
 
@@ -575,7 +574,22 @@ class SlackAlerting(CustomBatchLogger):
                 webhook_event = WebhookEvent(
                     event=event,
                     event_message=event_message,
-                    **user_info_json,
+                    spend=user_info.spend,
+                    max_budget=user_info.max_budget,
+                    soft_budget=user_info.soft_budget,
+                    token=user_info.token,
+                    customer_id=user_info.customer_id,
+                    user_id=user_info.user_id,
+                    team_id=user_info.team_id,
+                    team_alias=user_info.team_alias,
+                    organization_id=user_info.organization_id,
+                    user_email=user_info.user_email,
+                    key_alias=user_info.key_alias,
+                    projected_exceeded_date=user_info.projected_exceeded_date,
+                    projected_spend=user_info.projected_spend,
+                    event_group=user_info.event_group,
+                    alert_emails=user_info.alert_emails,
+                    max_budget_alert_emails=user_info.max_budget_alert_emails,
                 )
                 await self.send_alert(
                     message=event_message + "\n\n" + user_info_str,
@@ -657,7 +671,7 @@ class SlackAlerting(CustomBatchLogger):
         """
         Create a standard message for a budget alert
         """
-        _all_fields_as_dict: Final = user_info.model_dump(exclude_none=True)
+        _all_fields_as_dict: Final[dict[str, object]] = user_info.model_dump(exclude_none=True)
         _all_fields_as_dict.pop("token")
         msg = ""
         for k, v in _all_fields_as_dict.items():
@@ -1006,7 +1020,7 @@ class SlackAlerting(CustomBatchLogger):
         except Exception:
             pass
 
-    async def model_added_alert(self, model_name: str, litellm_model_name: str, passed_model_info: Any):
+    async def model_added_alert(self, model_name: str, litellm_model_name: str, passed_model_info: object):
         base_model_from_user: Final = getattr(passed_model_info, "base_model", None)
         model_info = {}
         base_model = ""
@@ -1973,7 +1987,7 @@ Model Info:
         try:
             message = f"`{event_name}`\n"
 
-            key_event_dict: Final = key_event.model_dump()
+            key_event_dict: Final[dict[str, object]] = key_event.model_dump()
 
             # Add Created by information first
             message += "*Action Done by:*\n"
diff --git a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
index 6a03e3ee93c..ff34bd91e31 100644
--- a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
+++ b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py
@@ -3,6 +3,7 @@ BitBucket prompt manager that integrates with LiteLLM's prompt management system
 Fetches .prompt files from BitBucket repositories and provides team-based access control.
 """
 
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 from jinja2 import DictLoader, select_autoescape
@@ -65,7 +66,7 @@ class BitBucketTemplateManager:
 
     def __init__(
         self,
-        bitbucket_config: dict[str, Any],
+        bitbucket_config: Mapping[str, object],
         prompt_id: str | None = None,
     ):
         self.bitbucket_config = bitbucket_config
@@ -123,7 +124,7 @@ class BitBucketTemplateManager:
             template_content = content
 
         # Parse YAML frontmatter
-        metadata: dict[str, Any] = {}
+        metadata: dict[str, object] = {}
         if frontmatter_str:
             try:
                 import yaml
@@ -141,9 +142,9 @@ class BitBucketTemplateManager:
             metadata=metadata,
         )
 
-    def _parse_yaml_basic(self, yaml_str: str) -> dict[str, Any]:
+    def _parse_yaml_basic(self, yaml_str: str) -> dict[str, object]:
         """Basic YAML parser for simple cases when PyYAML is not available."""
-        result: Final[dict[str, Any]] = {}
+        result: Final[dict[str, object]] = {}
         for line in yaml_str.split("\n"):
             line = line.strip()
             if ":" in line and not line.startswith("#"):
@@ -162,7 +163,7 @@ class BitBucketTemplateManager:
                     result[key] = value.strip("\"'")
         return result
 
-    def render_template(self, template_id: str, variables: dict[str, Any] | None = None) -> str:
+    def render_template(self, template_id: str, variables: Mapping[str, object] | None = None) -> str:
         """Render a template with the given variables."""
         if template_id not in self.prompts:
             raise ValueError(f"Template '{template_id}' not found")
@@ -209,7 +210,7 @@ class BitBucketPromptManager(CustomPromptManagement):
 
     def __init__(
         self,
-        bitbucket_config: dict[str, Any],
+        bitbucket_config: Mapping[str, object],
         prompt_id: str | None = None,
     ):
         self.bitbucket_config = bitbucket_config
@@ -234,7 +235,7 @@ class BitBucketPromptManager(CustomPromptManagement):
     def get_prompt_template(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
     ) -> tuple[str, dict[str, Any]]:
         """
         Get a prompt template and render it with variables.
@@ -267,12 +268,12 @@ class BitBucketPromptManager(CustomPromptManagement):
         self,
         user_id: str | None,
         messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: dict[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         **kwargs,
-    ) -> tuple[list[AllMessageValues], dict[str, Any] | None]:
+    ) -> tuple[list[AllMessageValues], dict[str, object] | None]:
         """
         Pre-call hook that processes the prompt template before making the LLM call.
         """
@@ -316,9 +317,9 @@ class BitBucketPromptManager(CustomPromptManagement):
 
         except Exception as e:
             # Log error but don't fail the call
-            import litellm
+            from litellm._logging import verbose_proxy_logger
 
-            litellm._logging.verbose_proxy_logger.error("Error in BitBucket prompt pre_call_hook: %s", e)
+            verbose_proxy_logger.error("Error in BitBucket prompt pre_call_hook: %s", e)
             return messages, litellm_params
 
     def _parse_prompt_to_messages(self, prompt_content: str) -> list[AllMessageValues]:
@@ -384,14 +385,14 @@ class BitBucketPromptManager(CustomPromptManagement):
     def post_call_hook(
         self,
         user_id: str | None,
-        response: Any,
+        response: object,
         input_messages: list[AllMessageValues],
-        function_call: dict[str, Any] | str | None = None,
-        litellm_params: dict[str, Any] | None = None,
+        function_call: Mapping[str, object] | str | None = None,
+        litellm_params: Mapping[str, object] | None = None,
         prompt_id: str | None = None,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         **kwargs,
-    ) -> Any:
+    ) -> object:
         """
         Post-call hook for any post-processing after the LLM call.
         """
diff --git a/litellm/integrations/cloudzero/transform.py b/litellm/integrations/cloudzero/transform.py
index f0d4d67fc22..ffc8fe1c1f5 100644
--- a/litellm/integrations/cloudzero/transform.py
+++ b/litellm/integrations/cloudzero/transform.py
@@ -19,14 +19,29 @@
 """Transform LiteLLM data to CloudZero AnyCost CBF format."""
 
 from datetime import datetime
-from typing import Any, Final
+from typing import Final, SupportsFloat, SupportsIndex, SupportsInt
 
 import polars as pl
+from typing_extensions import Buffer
 
 from ...types.integrations.cloudzero import CBFRecord
 from .cz_resource_names import CZEntityType, CZRNGenerator
 
 
+def _as_int(value: object) -> int:
+    """The integer form of a spend table cell, computed the way :func:`int` computes it."""
+    if isinstance(value, (str, Buffer, SupportsInt, SupportsIndex)):
+        return int(value)
+    raise TypeError(f"int() argument must be a string or a number, not {type(value).__name__!r}")
+
+
+def _as_float(value: object) -> float:
+    """The floating point form of a spend table cell, computed the way :func:`float` computes it."""
+    if isinstance(value, (str, Buffer, SupportsFloat, SupportsIndex)):
+        return float(value)
+    raise TypeError(f"float() argument must be a string or a number, not {type(value).__name__!r}")
+
+
 class CBFTransformer:
     """Transform LiteLLM usage data to CloudZero Billing Format (CBF)."""
 
@@ -82,15 +97,15 @@ class CBFTransformer:
 
         return pl.DataFrame(cbf_data)
 
-    def _create_cbf_record(self, row: dict[str, Any]) -> CBFRecord:
+    def _create_cbf_record(self, row: dict[str, object]) -> CBFRecord:
         """Create a single CBF record from LiteLLM daily spend row."""
 
         # Parse date (daily spend tables use date strings like '2025-04-19')
         usage_date: Final = self._parse_date(row.get("date"))
 
         # Calculate total tokens
-        prompt_tokens: Final = int(row.get("prompt_tokens", 0))
-        completion_tokens: Final = int(row.get("completion_tokens", 0))
+        prompt_tokens: Final = _as_int(row.get("prompt_tokens", 0))
+        completion_tokens: Final = _as_int(row.get("completion_tokens", 0))
         total_tokens: Final = prompt_tokens + completion_tokens
 
         # Create CloudZero Resource Name (CZRN) as resource_id
@@ -154,7 +169,7 @@ class CBFTransformer:
             "time/usage_start": (
                 usage_date.isoformat() if usage_date else None
             ),  # Required: ISO-formatted UTC datetime
-            "cost/cost": float(row.get("spend", 0.0)),  # Required: billed cost
+            "cost/cost": _as_float(row.get("spend", 0.0)),  # Required: billed cost
             "resource/id": resource_id,  # CZRN (CloudZero Resource Name)
             # Usage metrics for token consumption
             "usage/amount": total_tokens,  # Numeric value of tokens consumed
@@ -187,7 +202,7 @@ class CBFTransformer:
 
         return CBFRecord(cbf_record)
 
-    def _parse_date(self, date_str) -> datetime | None:
+    def _parse_date(self, date_str: object) -> datetime | None:
         """Parse date string from daily spend tables (e.g., '2025-04-19')."""
         if date_str is None:
             return None
diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py
index 8dc6881d23e..e87ac9521ae 100644
--- a/litellm/integrations/custom_guardrail.py
+++ b/litellm/integrations/custom_guardrail.py
@@ -2,6 +2,7 @@ import contextvars
 import hashlib
 import os
 import secrets
+from collections.abc import Mapping
 from datetime import datetime
 from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, Optional, get_args
 
@@ -227,13 +228,13 @@ class CustomGuardrail(CustomLogger):
                 )
         super().__init__(**kwargs)
 
-    def render_violation_message(self, default: str, context: dict[str, Any] | None = None) -> str:
+    def render_violation_message(self, default: str, context: Mapping[str, object] | None = None) -> str:
         """Return a custom violation message if template is configured."""
 
         if not self.violation_message_template:
             return default
 
-        format_context: Final[dict[str, Any]] = {"default_message": default}
+        format_context: Final[dict[str, object]] = {"default_message": default}
         if context:
             format_context.update(context)
         try:
@@ -661,7 +662,7 @@ class CustomGuardrail(CustomLogger):
         value: Final = self._get_admin_metadata(data).get("opted_out_global_guardrails")
         return value if isinstance(value, list) else []
 
-    def _is_valid_response_type(self, result: Any) -> bool:
+    def _is_valid_response_type(self, result: object) -> bool:
         """
         Check if result is a valid LLMResponseTypes instance.
 
@@ -722,7 +723,7 @@ class CustomGuardrail(CustomLogger):
             return None
         return f"{_PRE_CALL_EXECUTED_TOKEN}:{name}"
 
-    def mark_pre_call_hook_ran(self, data: dict[str, Any]) -> None:
+    def mark_pre_call_hook_ran(self, data: dict[str, object]) -> None:
         """
         Record that this guardrail's ``async_pre_call_hook`` already ran for this
         request, so the deployment-level hook does not run it a second time.
@@ -747,7 +748,7 @@ class CustomGuardrail(CustomLogger):
                 return
         data["metadata"] = {PRE_CALL_EXECUTED_GUARDRAILS_KEY: [marker]}
 
-    def _pre_call_hook_already_ran(self, data: dict[str, Any]) -> bool:
+    def _pre_call_hook_already_ran(self, data: dict[str, object]) -> bool:
         marker: Final = self._pre_call_marker()
         if marker is None:
             return False
@@ -1170,7 +1171,7 @@ class CustomGuardrail(CustomLogger):
         This gets logged on downsteam Langfuse, DataDog, etc.
         """
         # Convert None to empty dict to satisfy type requirements
-        guardrail_response: dict[str, Any] | str = {} if response is None else response
+        guardrail_response: dict[str, object] | str = {} if response is None else response
 
         # For apply_guardrail functions in custom_code_guardrail scenario,
         # simplify the logged response to "allow", "deny", or "mask"
diff --git a/litellm/integrations/datadog/datadog.py b/litellm/integrations/datadog/datadog.py
index 04f1c6dff15..866076a3c49 100644
--- a/litellm/integrations/datadog/datadog.py
+++ b/litellm/integrations/datadog/datadog.py
@@ -20,10 +20,11 @@ import time
 import traceback
 from collections.abc import Sequence
 from datetime import datetime as datetimeObj
-from typing import Any, Final
+from typing import TYPE_CHECKING, Any, Final
 
 import httpx
 from httpx import Response
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -62,6 +63,18 @@ from litellm.types.utils import StandardLoggingPayload
 
 from ..additional_logging_utils import AdditionalLoggingUtils
 
+if TYPE_CHECKING:
+    from fastapi import HTTPException
+
+    from litellm.proxy._types import UserAPIKeyAuth
+
+
+class _DatadogLoggingKwargs(TypedDict, total=False):
+    """The subset of logging ``kwargs`` that the Datadog payload builder reads."""
+
+    standard_logging_object: ReadOnly[StandardLoggingPayload | None]
+
+
 # max number of logs DD API can accept
 
 
@@ -87,6 +100,11 @@ def _resolve_dd_batch_size() -> int:
     return max(1, min(value, DD_MAX_BATCH_SIZE))
 
 
+def _span_attribute(span: object, name: str) -> object:
+    """Read an optional attribute off whatever span object the active tracer hands back."""
+    return getattr(span, name, None)
+
+
 class DataDogLogger(
     CustomBatchLogger,
     AdditionalLoggingUtils,
@@ -271,9 +289,9 @@ class DataDogLogger(
         self,
         request_data: dict,
         original_exception: Exception,
-        user_api_key_dict: Any,
+        user_api_key_dict: "UserAPIKeyAuth",
         traceback_str: str | None = None,
-    ) -> Any | None:
+    ) -> "HTTPException | None":
         """
         Log proxy-level failures (e.g. 401 auth, DB connection errors) to Datadog.
 
@@ -297,7 +315,7 @@ class DataDogLogger(
                 status_code = int(_code)
 
             # Use project-standard sanitized user context when running in proxy
-            user_context: dict[str, Any] = {}
+            user_context: dict[str, object] = {}
             try:
                 from litellm.proxy.litellm_pre_call_utils import (
                     LiteLLMProxyRequestSetup,
@@ -553,8 +571,8 @@ class DataDogLogger(
 
     def create_datadog_logging_payload(
         self,
-        kwargs: dict | Any,
-        response_obj: Any,
+        kwargs: _DatadogLoggingKwargs,
+        response_obj: object,
         start_time: datetime.datetime,
         end_time: datetime.datetime,
     ) -> DatadogPayload:
@@ -562,8 +580,8 @@ class DataDogLogger(
         Helper function to create a datadog payload for logging
 
         Args:
-            kwargs (Union[dict, Any]): request kwargs
-            response_obj (Any): llm api response
+            kwargs: request kwargs, read for its standard logging object
+            response_obj: llm api response
             start_time (datetime.datetime): start time of request
             end_time (datetime.datetime): end time of request
 
@@ -625,7 +643,7 @@ class DataDogLogger(
         self,
         payload: ServiceLoggerPayload,
         error: str | None = "",
-        parent_otel_span: Any | None = None,
+        parent_otel_span: object = None,
         start_time: datetimeObj | float | None = None,
         end_time: float | datetimeObj | None = None,
         event_metadata: dict | None = None,
@@ -659,7 +677,7 @@ class DataDogLogger(
         self,
         payload: ServiceLoggerPayload,
         error: str | None = "",
-        parent_otel_span: Any | None = None,
+        parent_otel_span: object = None,
         start_time: datetimeObj | float | None = None,
         end_time: float | datetimeObj | None = None,
         event_metadata: dict | None = None,
@@ -696,7 +714,7 @@ class DataDogLogger(
 
     def _create_v0_logging_payload(
         self,
-        kwargs: dict | Any,
+        kwargs: dict,
         response_obj: Any,
         start_time: datetime.datetime,
         end_time: datetime.datetime,
@@ -810,11 +828,11 @@ class DataDogLogger(
             if current_span is None:
                 return None
 
-            trace_id: Final = getattr(current_span, "trace_id", None)
+            trace_id: Final = _span_attribute(current_span, "trace_id")
             if trace_id is None:
                 return None
 
-            span_id: Final = getattr(current_span, "span_id", None)
+            span_id: Final = _span_attribute(current_span, "span_id")
             trace_context: Final[dict[str, str]] = {"trace_id": str(trace_id)}
             if span_id is not None:
                 trace_context["span_id"] = str(span_id)
diff --git a/litellm/integrations/datadog/datadog_llm_obs.py b/litellm/integrations/datadog/datadog_llm_obs.py
index 704f0323e95..e5789965c6e 100644
--- a/litellm/integrations/datadog/datadog_llm_obs.py
+++ b/litellm/integrations/datadog/datadog_llm_obs.py
@@ -9,6 +9,7 @@ API Reference: https://docs.datadoghq.com/llm_observability/setup/api/?tab=examp
 import asyncio
 import json
 import os
+from collections.abc import Mapping, Sequence
 from datetime import datetime
 from typing import Any, Final, Literal
 
@@ -334,7 +335,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
     def _get_response_messages(
         self, standard_logging_payload: StandardLoggingPayload, call_type: str | None
-    ) -> list[Any]:
+    ) -> list[object]:
         """
         Get the messages from the response object
 
@@ -484,7 +485,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         # Default fallback for unknown or passthrough operations
         return "llm"
 
-    def _ensure_string_content(self, messages: str | list[Any] | dict[Any, Any] | None) -> list[Any]:
+    def _ensure_string_content(self, messages: str | Sequence[object] | Mapping[object, object] | None) -> list[object]:
         if messages is None:
             return []
         if isinstance(messages, str):
@@ -495,11 +496,11 @@ class DataDogLLMObsLogger(CustomBatchLogger):
             return [str(messages.get("content", ""))]
         return []
 
-    def _get_dd_llm_obs_payload_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, Any]:
+    def _get_dd_llm_obs_payload_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, object]:
         """
         Fields to track in DD LLM Observability metadata from litellm standard logging payload
         """
-        _metadata: Final[dict[str, Any]] = {
+        _metadata: Final[dict[str, object]] = {
             "model_name": standard_logging_payload.get("model", "unknown"),
             "model_provider": standard_logging_payload.get("custom_llm_provider", "unknown"),
             "id": standard_logging_payload.get("id", "unknown"),
@@ -647,7 +648,7 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
         return spend_metrics
 
-    def _process_input_messages_preserving_tool_calls(self, messages: list[Any]) -> list[dict[str, Any]]:
+    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.
 
@@ -671,13 +672,13 @@ class DataDogLLMObsLogger(CustomBatchLogger):
         return processed
 
     @staticmethod
-    def _tool_calls_kv_pair(tool_calls: list[dict[str, Any]]) -> dict[str, Any]:
+    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, Any]] = {}
+        kv_pairs: Final[dict[str, object]] = {}
         for idx, tool_call in enumerate(tool_calls):
             try:
                 # Extract tool call ID
@@ -712,11 +713,11 @@ class DataDogLLMObsLogger(CustomBatchLogger):
 
         return kv_pairs
 
-    def _extract_tool_call_metadata(self, standard_logging_payload: StandardLoggingPayload) -> dict[str, Any]:
+    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, Any]] = {}
+        tool_call_metadata: Final[dict[str, object]] = {}
 
         try:
             # Extract tool calls from input messages
diff --git a/litellm/integrations/dotprompt/prompt_manager.py b/litellm/integrations/dotprompt/prompt_manager.py
index fd0b17ba746..9c82ff7c5ba 100644
--- a/litellm/integrations/dotprompt/prompt_manager.py
+++ b/litellm/integrations/dotprompt/prompt_manager.py
@@ -3,12 +3,21 @@ Based on Google's GenAI Kit dotprompt implementation: https://google.github.io/d
 """
 
 import re
+from collections.abc import Mapping
 from pathlib import Path
 from typing import Any, Final
 
 import yaml
 from jinja2 import DictLoader, select_autoescape
 from jinja2.sandbox import ImmutableSandboxedEnvironment
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
+
+class _PromptFileJson(TypedDict):
+    """JSON form of a .prompt file: rendered template text plus its frontmatter."""
+
+    content: ReadOnly[NotRequired[str]]
+    metadata: ReadOnly[NotRequired[dict[str, object]]]
 
 
 def strip_version_suffix(prompt_id: str) -> str | None:
@@ -167,7 +176,7 @@ class PromptManager:
             template_id=prompt_id,
         )
 
-    def _parse_frontmatter(self, content: str) -> tuple[dict[str, Any], str]:
+    def _parse_frontmatter(self, content: str) -> tuple[dict[str, object], str]:
         """Parse YAML frontmatter from prompt content."""
         # Match YAML frontmatter between --- delimiters
         frontmatter_pattern: Final = r"^---\s*\n(.*?)\n---\s*\n(.*)$"
@@ -178,7 +187,7 @@ class PromptManager:
             template_content = match.group(2)
 
             try:
-                frontmatter = yaml.safe_load(frontmatter_yaml) or {}
+                frontmatter: dict[str, object] = yaml.safe_load(frontmatter_yaml) or {}
             except yaml.YAMLError as e:
                 raise ValueError(f"Invalid YAML frontmatter: {e}")
         else:
@@ -191,7 +200,7 @@ class PromptManager:
     def render(
         self,
         prompt_id: str,
-        prompt_variables: dict[str, Any] | None = None,
+        prompt_variables: Mapping[str, object] | None = None,
         version: int | None = None,
     ) -> str:
         """
@@ -231,7 +240,7 @@ class PromptManager:
         except Exception as e:
             raise ValueError(f"Error rendering template '{prompt_id}': {e}")
 
-    def _validate_input(self, variables: dict[str, Any], schema: dict[str, Any]) -> None:
+    def _validate_input(self, variables: Mapping[str, object], schema: Mapping[str, str]) -> None:
         """Basic validation of input variables against schema."""
         for field_name, field_type in schema.items():
             if field_name in variables:
@@ -291,7 +300,7 @@ class PromptManager:
         """Get a list of all available prompt IDs."""
         return list(self.prompts.keys())
 
-    def get_prompt_metadata(self, prompt_id: str) -> dict[str, Any] | None:
+    def get_prompt_metadata(self, prompt_id: str) -> dict[str, object] | None:
         """Get metadata for a specific prompt."""
         template: Final = self.prompts.get(prompt_id)
         return template.metadata if template else None
@@ -302,12 +311,12 @@ class PromptManager:
         if self.prompt_directory:
             self._load_prompts()
 
-    def add_prompt(self, prompt_id: str, content: str, metadata: dict[str, Any] | None = None) -> None:
+    def add_prompt(self, prompt_id: str, content: str, metadata: dict[str, object] | None = None) -> None:
         """Add a prompt template programmatically."""
         template: Final = PromptTemplate(content=content, metadata=metadata or {}, template_id=prompt_id)
         self.prompts[prompt_id] = template
 
-    def prompt_file_to_json(self, file_path: str | Path) -> dict[str, Any]:
+    def prompt_file_to_json(self, file_path: str | Path) -> _PromptFileJson:
         """Convert a .prompt file to JSON format.
 
         Args:
@@ -324,7 +333,7 @@ class PromptManager:
 
         return {"content": template_content.strip(), "metadata": frontmatter}
 
-    def json_to_prompt_file(self, prompt_data: dict[str, Any]) -> str:
+    def json_to_prompt_file(self, prompt_data: _PromptFileJson) -> str:
         """Convert JSON prompt data to .prompt file format.
 
         Args:
diff --git a/litellm/integrations/galileo.py b/litellm/integrations/galileo.py
index 23727801a6f..b27618993a3 100644
--- a/litellm/integrations/galileo.py
+++ b/litellm/integrations/galileo.py
@@ -6,10 +6,11 @@ import re
 import uuid
 from collections.abc import Mapping, Sequence
 from datetime import datetime, timezone, tzinfo
-from typing import Any, Final, TypedDict, cast
+from typing import Any, Final, Protocol, cast
 
 import httpx
 from pydantic import BaseModel, Field
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -35,6 +36,34 @@ GALILEO_CLOUD_API_BASE_URL: Final = "https://api.galileo.ai"
 GALILEO_MAX_IN_MEMORY_RECORDS: Final = 1000
 
 
+class _GalileoLoginBody(TypedDict):
+    """Decoded body of the Galileo login response."""
+
+    access_token: ReadOnly[str]
+
+
+class _GalileoLoginResponse(Protocol):
+    """The login call's HTTP response, read for the access token it carries."""
+
+    def json(self) -> _GalileoLoginBody: ...
+
+
+class _JsonResponse(Protocol):
+    """An HTTP response read only for whatever JSON body it decodes to."""
+
+    def json(self) -> object: ...
+
+
+def _login_access_token(response: _GalileoLoginResponse) -> str:
+    """Read the bearer token out of a Galileo login response body."""
+    return response.json()["access_token"]
+
+
+def _decoded_body(response: _JsonResponse) -> object:
+    """Decode a response body without asserting anything about its shape."""
+    return response.json()
+
+
 class GalileoStandardLoggingFields(TypedDict, total=False):
     call_type: str
     model: str
@@ -156,7 +185,7 @@ class GalileoObserve(CustomLogger):
             },
         )
         galileo_login_response.raise_for_status()
-        access_token: Final = galileo_login_response.json()["access_token"]
+        access_token: Final = _login_access_token(galileo_login_response)
         self.headers = {
             "accept": "application/json",
             "Content-Type": "application/json",
@@ -421,7 +450,7 @@ class GalileoObserve(CustomLogger):
         try:
             verbose_logger.debug(
                 "Galileo Logger HTTP error response json: %s",
-                response.json(),
+                _decoded_body(response),
             )
         except Exception:
             pass
diff --git a/litellm/integrations/gitlab/gitlab_client.py b/litellm/integrations/gitlab/gitlab_client.py
index 0690ccc8c15..813a2ef2821 100644
--- a/litellm/integrations/gitlab/gitlab_client.py
+++ b/litellm/integrations/gitlab/gitlab_client.py
@@ -4,12 +4,80 @@ Now supports selecting a tag via `config["tag"]`; falls back to branch ("main").
 """
 
 import base64
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, Protocol, TypedDict
 from urllib.parse import quote
 
+from typing_extensions import ReadOnly
+
 from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
 
+class GitLabFilePayload(TypedDict, total=False):
+    """A repository-files API entry."""
+
+    content: ReadOnly[str]
+    encoding: ReadOnly[str]
+
+
+class GitLabTreeEntry(TypedDict, total=False):
+    """A repository-tree API entry."""
+
+    path: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class GitLabBranch(TypedDict, total=False):
+    """A repository-branches API entry."""
+
+    name: ReadOnly[str]
+    type: ReadOnly[str]
+
+
+class GitLabFileMetadata(TypedDict):
+    """The response headers a raw file request exposes as metadata."""
+
+    content_type: ReadOnly[str | None]
+    content_length: ReadOnly[str | None]
+    last_modified: ReadOnly[str | None]
+
+
+class _FileJsonResponse(Protocol):
+    def json(self) -> GitLabFilePayload: ...
+
+
+class _TreeJsonResponse(Protocol):
+    def json(self) -> Sequence[GitLabTreeEntry] | None: ...
+
+
+class _ProjectJsonResponse(Protocol):
+    def json(self) -> Mapping[str, object]: ...
+
+
+class _BranchesJsonResponse(Protocol):
+    def json(self) -> Sequence[GitLabBranch] | None: ...
+
+
+def _file_payload(resp: _FileJsonResponse) -> GitLabFilePayload:
+    """The JSON body of a repository-files response."""
+    return resp.json()
+
+
+def _tree_entries(resp: _TreeJsonResponse) -> Sequence[GitLabTreeEntry]:
+    """The entries of a repository-tree response."""
+    return resp.json() or []
+
+
+def _project_info(resp: _ProjectJsonResponse) -> Mapping[str, object]:
+    """The JSON body of a project response."""
+    return resp.json()
+
+
+def _branch_entries(resp: _BranchesJsonResponse) -> Sequence[GitLabBranch] | None:
+    """The JSON body of a repository-branches response."""
+    return resp.json()
+
+
 class GitLabClient:
     """
     Client for interacting with the GitLab API to fetch files.
@@ -42,12 +110,12 @@ class GitLabClient:
 
         self.project: str | int = project
         self.access_token: str = str(access_token)
-        self.auth_method = config.get("auth_method", "token")  # 'token' or 'oauth'
+        self.auth_method: str = config.get("auth_method", "token")  # 'token' or 'oauth'
         self.branch = config.get("branch", None)
         if not self.branch:
             self.branch = "main"
         self.tag = config.get("tag")
-        self.base_url = config.get("base_url", "https://gitlab.com/api/v4")
+        self.base_url: str = config.get("base_url", "https://gitlab.com/api/v4")
 
         if not all([self.project, self.access_token]):
             raise ValueError("project and access_token are required")
@@ -159,7 +227,7 @@ class GitLabClient:
             if resp.status_code == 404:
                 return None
             resp.raise_for_status()
-            data: Final = resp.json()
+            data: Final = _file_payload(resp)
             content: Final = data.get("content")
             encoding: Final = data.get("encoding", "")
             if content and encoding == "base64":
@@ -208,7 +276,7 @@ class GitLabClient:
                 return []
             resp.raise_for_status()
 
-            data: Final = resp.json() or []
+            data: Final = _tree_entries(resp)
             files: Final[list[str]] = []
             for item in data:
                 if item.get("type") == "blob":
@@ -229,13 +297,13 @@ class GitLabClient:
                 raise Exception("Authentication failed. Check your GitLab token and auth_method.")
             raise Exception(f"Failed to list files in '{directory_path}': {e}")
 
-    def get_repository_info(self) -> dict[str, Any]:
+    def get_repository_info(self) -> Mapping[str, object]:
         """Get information about the project/repository."""
         url: Final = f"{self.base_url}/projects/{self._project_enc}"
         try:
             resp: Final = self.http_handler.get(url, headers=self.headers)
             resp.raise_for_status()
-            return resp.json()
+            return _project_info(resp)
         except Exception as e:
             raise Exception(f"Failed to get repository info: {e}")
 
@@ -247,18 +315,18 @@ class GitLabClient:
         except Exception:
             return False
 
-    def get_branches(self) -> list[dict[str, Any]]:
+    def get_branches(self) -> list[GitLabBranch]:
         """Get list of branches in the repository."""
         url: Final = f"{self.base_url}/projects/{self._project_enc}/repository/branches"
         try:
             resp: Final = self.http_handler.get(url, headers=self.headers)
             resp.raise_for_status()
-            data: Final = resp.json()
+            data: Final = _branch_entries(resp)
             return data if isinstance(data, list) else []
         except Exception as e:
             raise Exception(f"Failed to get branches: {e}")
 
-    def get_file_metadata(self, file_path: str, *, ref: str | None = None) -> dict[str, Any] | None:
+    def get_file_metadata(self, file_path: str, *, ref: str | None = None) -> GitLabFileMetadata | None:
         """
         Get minimal metadata about a file via RAW endpoint headers at a given ref.
 
diff --git a/litellm/integrations/langfuse/langfuse.py b/litellm/integrations/langfuse/langfuse.py
index 296c2b5714e..9576eabaa34 100644
--- a/litellm/integrations/langfuse/langfuse.py
+++ b/litellm/integrations/langfuse/langfuse.py
@@ -89,7 +89,7 @@ def _extract_cache_read_input_tokens(usage_obj) -> int:
 
     # Check prompt_tokens_details.cached_tokens (used by Gemini and other providers)
     if hasattr(usage_obj, "prompt_tokens_details"):
-        prompt_tokens_details: Final = getattr(usage_obj, "prompt_tokens_details", None)
+        prompt_tokens_details: Final[object] = getattr(usage_obj, "prompt_tokens_details", None)
         if prompt_tokens_details is not None and hasattr(prompt_tokens_details, "cached_tokens"):
             cached_tokens: Final = getattr(prompt_tokens_details, "cached_tokens", None)
             if cached_tokens is not None and isinstance(cached_tokens, (int, float)) and cached_tokens > 0:
@@ -623,9 +623,16 @@ class LangFuseLogger:
             )
 
             # Apply custom masking function if provided
-            if masking_function is not None and callable(masking_function):
-                input = self._apply_masking_function(input, masking_function)
-                output = self._apply_masking_function(output, masking_function)
+            masked_input: Final[object] = (
+                self._apply_masking_function(input, masking_function)
+                if masking_function is not None and callable(masking_function)
+                else input
+            )
+            masked_output: Final[object] = (
+                self._apply_masking_function(output, masking_function)
+                if masking_function is not None and callable(masking_function)
+                else output
+            )
 
             clean_metadata = redact_user_api_key_info(metadata=clean_metadata)
 
@@ -651,15 +658,15 @@ class LangFuseLogger:
 
                 # Special keys that are found in the function arguments and not the metadata
                 if "input" in update_trace_keys:
-                    trace_params["input"] = input if not mask_input else "redacted-by-litellm"
+                    trace_params["input"] = masked_input if not mask_input else "redacted-by-litellm"
                 if "output" in update_trace_keys:
-                    trace_params["output"] = output if not mask_output else "redacted-by-litellm"
+                    trace_params["output"] = masked_output if not mask_output else "redacted-by-litellm"
             else:  # don't overwrite an existing trace
                 trace_params = {
                     "id": trace_id,
                     "name": trace_name,
                     "session_id": session_id,
-                    "input": input if not mask_input else "redacted-by-litellm",
+                    "input": masked_input if not mask_input else "redacted-by-litellm",
                     "version": clean_metadata.pop(
                         "trace_version", clean_metadata.get("version", None)
                     ),  # If provided just version, it will applied to the trace as well, if applied a trace version it will take precedence
@@ -669,9 +676,9 @@ class LangFuseLogger:
                     trace_params[key.replace("trace_", "")] = clean_metadata.pop(key, None)
 
                 if level == "ERROR":
-                    trace_params["status_message"] = output
+                    trace_params["status_message"] = masked_output
                 else:
-                    trace_params["output"] = output if not mask_output else "redacted-by-litellm"
+                    trace_params["output"] = masked_output if not mask_output else "redacted-by-litellm"
 
             if debug is True or (isinstance(debug, str) and debug.lower() == "true"):
                 debug_metadata: Final = {
@@ -708,7 +715,7 @@ class LangFuseLogger:
                 ("aws_region_name", aws_region_name, bool(aws_region_name)),
                 ("cache_hit", kwargs.get("cache_hit") or False, self._supports_tags() and "cache_hit" in kwargs),
             )
-            enrichments: Final[Mapping[str, Any]] = {
+            enrichments: Final[Mapping[str, object]] = {
                 key: value for key, value, include in candidate_enrichments if include
             }
 
@@ -802,8 +809,8 @@ class LangFuseLogger:
                 "end_time": end_time,
                 "model": model_name,
                 "model_parameters": optional_params,
-                "input": input if not mask_input else "redacted-by-litellm",
-                "output": output if not mask_output else "redacted-by-litellm",
+                "input": masked_input if not mask_input else "redacted-by-litellm",
+                "output": masked_output if not mask_output else "redacted-by-litellm",
                 "usage": usage,
                 "usage_details": usage_details,
                 "metadata": {
@@ -825,8 +832,8 @@ class LangFuseLogger:
                     prompt_management_metadata=prompt_management_metadata,
                     langfuse_client=self.Langfuse,
                 )
-            if output is not None and isinstance(output, str) and level == "ERROR":
-                generation_params["status_message"] = output
+            if masked_output is not None and isinstance(masked_output, str) and level == "ERROR":
+                generation_params["status_message"] = masked_output
 
             if self._supports_completion_start_time():
                 generation_params["completion_start_time"] = kwargs.get("completion_start_time", None)
@@ -935,7 +942,7 @@ class LangFuseLogger:
         return Version(self.langfuse_sdk_version) >= Version("2.7.3")
 
     @staticmethod
-    def _apply_masking_function(data: Any, masking_function: Callable[[Any], Any]) -> Any:
+    def _apply_masking_function(data: object, masking_function: Callable[[object], object]) -> object:
         """
         Apply a masking function to data, handling different data types.
 
@@ -1049,7 +1056,7 @@ def _add_prompt_to_generation_params(
     generation_params: dict,
     clean_metadata: dict,
     prompt_management_metadata: StandardLoggingPromptManagementMetadata | None,
-    langfuse_client: Any,
+    langfuse_client: object,
 ) -> dict:
     from langfuse import Langfuse
     from langfuse.model import (
diff --git a/litellm/integrations/opik/opik.py b/litellm/integrations/opik/opik.py
index fae93f03d1e..ce47d7fe27a 100644
--- a/litellm/integrations/opik/opik.py
+++ b/litellm/integrations/opik/opik.py
@@ -4,9 +4,12 @@ Opik Logger that logs LLM events to an Opik server
 
 import asyncio
 import traceback
+from collections.abc import Mapping
 from datetime import datetime
 from typing import Any, Final
 
+from typing_extensions import ReadOnly, TypedDict, Unpack
+
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_batch_logger import CustomBatchLogger
 from litellm.llms.custom_httpx.http_handler import (
@@ -23,7 +26,7 @@ except Exception:
     opik_client = None
 
 
-def _should_skip_event(kwargs: dict[str, Any]) -> bool:
+def _should_skip_event(kwargs: Mapping[str, object]) -> bool:
     """Check if event should be skipped due to missing standard_logging_object."""
     if kwargs.get("standard_logging_object") is None:
         verbose_logger.debug("OpikLogger skipping event; no standard_logging_object found")
@@ -31,12 +34,24 @@ def _should_skip_event(kwargs: dict[str, Any]) -> bool:
     return False
 
 
+class _OpikLoggerKwargs(TypedDict, total=False):
+    """Constructor options accepted by ``OpikLogger``."""
+
+    project_name: ReadOnly[str | None]
+    url: ReadOnly[str | None]
+    api_key: ReadOnly[str | None]
+    workspace: ReadOnly[str | None]
+    batch_size: ReadOnly[int | None]
+    flush_interval: ReadOnly[int | None]
+    max_queue_size: ReadOnly[int | None]
+
+
 class OpikLogger(CustomBatchLogger):
     """
     Opik Logger for logging events to an Opik Server
     """
 
-    def __init__(self, **kwargs: Any) -> None:
+    def __init__(self, **kwargs: Unpack[_OpikLoggerKwargs]) -> None:
         self.async_httpx_client = get_async_httpx_client(llm_provider=httpxSpecialProvider.LoggingCallback)
         self.sync_httpx_client = _get_httpx_client()
 
@@ -95,7 +110,7 @@ class OpikLogger(CustomBatchLogger):
 
     async def async_log_success_event(
         self,
-        kwargs: dict[str, Any],
+        kwargs: dict[str, object],
         response_obj: Any,
         start_time: datetime,
         end_time: datetime,
@@ -163,7 +178,7 @@ class OpikLogger(CustomBatchLogger):
         except Exception as e:
             verbose_logger.exception("OpikLogger failed to log success event - %s\n%s", e, traceback.format_exc())
 
-    def _sync_send(self, url: str, headers: dict[str, str], batch: dict[str, Any]) -> None:
+    def _sync_send(self, url: str, headers: dict[str, str], batch: dict[str, object]) -> None:
         try:
             response: Final = self.sync_httpx_client.post(
                 url=url,
@@ -178,7 +193,7 @@ class OpikLogger(CustomBatchLogger):
 
     def log_success_event(
         self,
-        kwargs: dict[str, Any],
+        kwargs: dict[str, object],
         response_obj: Any,
         start_time: datetime,
         end_time: datetime,
@@ -247,7 +262,7 @@ class OpikLogger(CustomBatchLogger):
         except Exception as e:
             verbose_logger.exception("OpikLogger failed to log success event - %s\n%s", e, traceback.format_exc())
 
-    async def _submit_batch(self, url: str, headers: dict[str, str], batch: dict[str, Any]) -> None:
+    async def _submit_batch(self, url: str, headers: dict[str, str], batch: dict[str, object]) -> None:
         try:
             response: Final = await self.async_httpx_client.post(
                 url=url,
diff --git a/litellm/integrations/opik/opik_payload_builder/extractors.py b/litellm/integrations/opik/opik_payload_builder/extractors.py
index 92a7eca7f3e..4dd3d40fae3 100644
--- a/litellm/integrations/opik/opik_payload_builder/extractors.py
+++ b/litellm/integrations/opik/opik_payload_builder/extractors.py
@@ -1,6 +1,7 @@
 """Data extraction functions for Opik payload building."""
 
 import json
+from collections.abc import Mapping
 from typing import Any, Final
 
 from litellm import _logging
@@ -35,8 +36,8 @@ def normalize_provider_name(provider: str | None) -> str | None:
 
 
 def extract_opik_metadata(
-    litellm_metadata: dict[str, Any],
-    standard_logging_metadata: dict[str, Any],
+    litellm_metadata: Mapping[str, Any],
+    standard_logging_metadata: Mapping[str, Any],
 ) -> dict[str, Any]:
     """
     Merge Opik metadata from three sources in increasing priority order:
@@ -97,7 +98,7 @@ def extract_span_identifiers(
 
 
 def extract_tags(
-    opik_metadata: dict[str, Any],
+    opik_metadata: Mapping[str, Any],
     custom_llm_provider: str | None,
 ) -> list[str]:
     """
@@ -122,7 +123,7 @@ def apply_proxy_header_overrides(
     project_name: str,
     tags: list[str],
     thread_id: str | None,
-    proxy_headers: dict[str, Any],
+    proxy_headers: Mapping[str, str],
 ) -> tuple[str, list[str], str | None]:
     """
     Apply overrides from proxy request headers (opik_* prefix).
@@ -148,7 +149,7 @@ def apply_proxy_header_overrides(
             thread_id = value
         elif param_key == "tags":
             try:
-                parsed_tags = json.loads(value)
+                parsed_tags: object = json.loads(value)
                 if isinstance(parsed_tags, list):
                     tags.extend(parsed_tags)
             except (json.JSONDecodeError, TypeError):
@@ -158,11 +159,11 @@ def apply_proxy_header_overrides(
 
 
 def extract_and_build_metadata(
-    opik_metadata: dict[str, Any],
-    standard_logging_metadata: dict[str, Any],
-    standard_logging_object: dict[str, Any],
-    litellm_kwargs: dict[str, Any],
-) -> dict[str, Any]:
+    opik_metadata: Mapping[str, object],
+    standard_logging_metadata: Mapping[str, object],
+    standard_logging_object: Mapping[str, object],
+    litellm_kwargs: Mapping[str, object],
+) -> dict[str, object]:
     """
     Build the complete metadata dictionary from all available sources.
 
diff --git a/litellm/integrations/otel/plumbing/metrics.py b/litellm/integrations/otel/plumbing/metrics.py
index c7e491c002a..e1623f4697f 100644
--- a/litellm/integrations/otel/plumbing/metrics.py
+++ b/litellm/integrations/otel/plumbing/metrics.py
@@ -11,9 +11,10 @@ identical metrics. The attribute cardinality filter is reused from v1 by import
 from collections.abc import Mapping
 from dataclasses import dataclass
 from datetime import datetime
-from typing import Any, Final, TypeAlias
+from typing import Any, Final, Literal, Protocol, TypeAlias
 
 from opentelemetry.metrics import Histogram, Meter
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -151,6 +152,29 @@ METRIC_ATTRIBUTE_CEILING: Final[frozenset[str]] = frozenset(
 BOUNDED_HIDDEN_PARAM_KEYS: Final[tuple[str, ...]] = ("model_id",)
 
 
+class _TokenUsage(TypedDict, total=False):
+    """The token counts a response's ``usage`` carries, as the recorder reads them."""
+
+    prompt_tokens: ReadOnly[int]
+    completion_tokens: ReadOnly[int]
+
+
+class _ResponseView(Protocol):
+    """The one read the recorder makes on a litellm response object."""
+
+    def get(self, key: Literal["usage"], /) -> _TokenUsage | None: ...
+
+
+class _MetricKwargs(TypedDict, total=False):
+    """The logging kwargs the recorder reads directly."""
+
+    call_type: ReadOnly[str | None]
+    litellm_params: ReadOnly[Mapping[str, object] | None]
+    response_cost: ReadOnly[float | None]
+    completion_start_time: ReadOnly[datetime | float | str | None]
+    api_call_start_time: ReadOnly[datetime | float | str | None]
+
+
 def resolve_error_type(kwargs: Mapping[str, Any]) -> str:
     """The ``error.type`` value for a failed request.
 
@@ -192,8 +216,8 @@ class GenAIMetricRecorder:
 
     def record(
         self,
-        kwargs: Mapping[str, Any],
-        response_obj: Any,
+        kwargs: _MetricKwargs,
+        response_obj: _ResponseView | None,
         start_time: datetime,
         end_time: datetime,
     ) -> None:
@@ -218,7 +242,7 @@ class GenAIMetricRecorder:
 
     def record_failure(
         self,
-        kwargs: Mapping[str, Any],
+        kwargs: _MetricKwargs,
         start_time: datetime,
         end_time: datetime,
     ) -> None:
@@ -342,7 +366,7 @@ class GenAIMetricRecorder:
     #  Per-metric recording
     # ------------------------------------------------------------------ #
 
-    def _record_token_usage(self, response_obj: Any, common_attrs: dict) -> None:
+    def _record_token_usage(self, response_obj: _ResponseView | None, common_attrs: dict) -> None:
         if not response_obj:
             return
         usage: Final = response_obj.get("usage")
@@ -353,7 +377,7 @@ class GenAIMetricRecorder:
         self._metrics.token_usage.record(usage.get("prompt_tokens", 0), attributes=in_attrs)
         self._metrics.token_usage.record(usage.get("completion_tokens", 0), attributes=out_attrs)
 
-    def _record_time_to_first_token(self, kwargs: Mapping[str, Any], common_attrs: dict) -> None:
+    def _record_time_to_first_token(self, kwargs: _MetricKwargs, common_attrs: dict) -> None:
         time_to_first_chunk: Final = time_to_first_chunk_seconds(kwargs)
         if time_to_first_chunk is None:
             return
@@ -361,15 +385,14 @@ class GenAIMetricRecorder:
 
     def _record_time_per_output_token(
         self,
-        kwargs: Mapping[str, Any],
-        response_obj: Any,
+        kwargs: _MetricKwargs,
+        response_obj: _ResponseView | None,
         end_time: datetime,
         duration_s: float,
         common_attrs: dict,
     ) -> None:
-        completion_tokens = None
-        if response_obj and (usage := response_obj.get("usage")):
-            completion_tokens = usage.get("completion_tokens")
+        usage: Final = response_obj.get("usage") if response_obj else None
+        completion_tokens: Final = usage.get("completion_tokens") if usage else None
         if completion_tokens is None or completion_tokens <= 0:
             return
 
diff --git a/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py b/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
index aa29162ba1f..07d4f959489 100644
--- a/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
+++ b/litellm/integrations/vector_store_integrations/vector_store_pre_call_hook.py
@@ -13,7 +13,7 @@ from litellm._logging import verbose_logger
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.llms.openai import AllMessageValues, ChatCompletionUserMessage
 from litellm.types.prompts.init_prompts import PromptSpec
-from litellm.types.utils import StandardCallbackDynamicParams
+from litellm.types.utils import CallTypes, StandardCallbackDynamicParams
 from litellm.types.vector_stores import (
     LiteLLM_ManagedVectorStore,
     VectorStoreResultContent,
@@ -226,7 +226,7 @@ class VectorStorePreCallHook(CustomLogger):
         self,
         request_data: dict,
         response: Any,
-        call_type: Any | None,
+        call_type: CallTypes | None,
     ) -> Any | None:
         """
         Add search results to the response after successful LLM call.
@@ -283,7 +283,7 @@ class VectorStorePreCallHook(CustomLogger):
         self,
         request_data: dict,
         response_chunk: Any,
-        call_type: Any | None,
+        call_type: CallTypes | None,
     ) -> Any | None:
         """
         Add search results to the final streaming chunk.
diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py
index 9125ed6e70a..8479e108d17 100644
--- a/litellm/litellm_core_utils/realtime_streaming.py
+++ b/litellm/litellm_core_utils/realtime_streaming.py
@@ -1500,6 +1500,6 @@ class RealTimeStreaming:
                     pass
 
 
-def client_sent_openai_beta_realtime_header(websocket: Any) -> bool:
+def client_sent_openai_beta_realtime_header(websocket: _ScopedWebSocket) -> bool:
     """True when the client WebSocket includes ``OpenAI-Beta: realtime=v1``."""
     return RealTimeStreaming._detect_beta_header(websocket)
diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
index 0e2139d688b..3978a01a5db 100644
--- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
+++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py
@@ -73,6 +73,18 @@ class _ContentChunk(TypedDict):
     choices: Sequence[_ContentChoice]
 
 
+class _FunctionCallDelta(TypedDict):
+    function_call: ReadOnly[FunctionCall]
+
+
+class _FunctionCallChoice(TypedDict):
+    delta: ReadOnly[_FunctionCallDelta]
+
+
+class _FunctionCallChunk(TypedDict):
+    choices: ReadOnly[Sequence[_FunctionCallChoice]]
+
+
 class _AudioDelta(TypedDict, total=False):
     audio: ChatCompletionAudioDelta | None
 
@@ -588,7 +600,7 @@ class ChunkProcessor:
 
         return tool_calls_list
 
-    def get_combined_function_call_content(self, function_call_chunks: list[dict[str, Any]]) -> FunctionCall:
+    def get_combined_function_call_content(self, function_call_chunks: Sequence["_FunctionCallChunk"]) -> FunctionCall:
         argument_list: Final = []
         delta = function_call_chunks[0]["choices"][0]["delta"]
         function_call = delta.get("function_call", "")
diff --git a/litellm/llms/a2a/chat/guardrail_translation/handler.py b/litellm/llms/a2a/chat/guardrail_translation/handler.py
index 1c5ba951942..f1c7451796d 100644
--- a/litellm/llms/a2a/chat/guardrail_translation/handler.py
+++ b/litellm/llms/a2a/chat/guardrail_translation/handler.py
@@ -11,8 +11,11 @@ A2A Protocol Format:
 """
 
 import json
+from collections.abc import Sequence
 from typing import TYPE_CHECKING, Any, Final, Optional
 
+from typing_extensions import ReadOnly, TypedDict
+
 from litellm._logging import verbose_proxy_logger
 from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
 from litellm.types.utils import GenericGuardrailAPIInputs
@@ -23,6 +26,13 @@ if TYPE_CHECKING:
     from litellm.proxy._types import UserAPIKeyAuth
 
 
+class _A2ATextPart(TypedDict, total=False):
+    """The subset of an A2A message part this handler reads text from."""
+
+    kind: ReadOnly[str]
+    text: ReadOnly[str]
+
+
 class A2AGuardrailHandler(BaseTranslation):
     """
     Handler for processing A2A Protocol messages with guardrails.
@@ -41,7 +51,7 @@ class A2AGuardrailHandler(BaseTranslation):
         data: dict,
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
-    ) -> Any:
+    ) -> dict:
         """
         Process A2A input messages by applying guardrails to text content.
 
@@ -214,12 +224,12 @@ class A2AGuardrailHandler(BaseTranslation):
 
     async def process_output_streaming_response(
         self,
-        responses_so_far: list[Any],
+        responses_so_far: list[object],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
         user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
         request_data: dict | None = None,
-    ) -> list[Any]:
+    ) -> list[object]:
         """
         Process A2A streaming output by applying guardrails to accumulated text.
 
@@ -305,11 +315,12 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _parse_streaming_responses(
         self,
-        responses_so_far: list[Any],
-    ) -> tuple[list[dict[str, Any] | None], list[tuple[int, dict[str, Any]]]]:
+        responses_so_far: list[object],
+    ) -> tuple[list[dict[str, object] | None], list[tuple[int, dict[str, object]]]]:
         """Parse JSON-RPC items, returning aligned parsed list and valid entries."""
-        parsed: Final[list[dict[str, Any] | None]] = [None] * len(responses_so_far)
+        parsed: Final[list[dict[str, object] | None]] = [None] * len(responses_so_far)
         for i, item in enumerate(responses_so_far):
+            obj: dict[str, object]
             if isinstance(item, dict):
                 obj = item
             elif isinstance(item, str):
@@ -326,7 +337,7 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _collect_text_from_parsed_chunks(
         self,
-        valid_parsed: list[tuple[int, dict[str, Any]]],
+        valid_parsed: list[tuple[int, dict[str, object]]],
     ) -> tuple[str, list[int]]:
         """Collect text from parsed chunks, returning combined text and indices."""
         from litellm.llms.a2a.common_utils import extract_text_from_a2a_response
@@ -411,7 +422,7 @@ class A2AGuardrailHandler(BaseTranslation):
 
     def _extract_texts_from_parts(
         self,
-        parts: list[dict[str, Any]],
+        parts: Sequence[_A2ATextPart],
         path: tuple[str, ...],
         texts_to_check: list[str],
         task_mappings: list[tuple[tuple[str, ...], int]],
diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index e1387a9068c..057a96ebd49 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any, Final, NoReturn, cast
 
 import httpx
 from pydantic import ValidationError
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm.constants import (
@@ -125,7 +126,25 @@ else:
 _ANTHROPIC_TOOL_NAME_INVALID_CHARS: Final = re.compile(r"[^a-zA-Z0-9_-]")
 _ANTHROPIC_TOOL_NAME_MAX_LEN: Final = 128
 
-_ENUM_TYPE_CHECKS: Final[Mapping[str, Callable[[Any], bool]]] = MappingProxyType(
+
+class _AnthropicUsageIteration(TypedDict, total=False):
+    """One entry of the ``usage.iterations`` array on an Anthropic response."""
+
+    input_tokens: ReadOnly[int | None]
+    output_tokens: ReadOnly[int | None]
+    cache_creation_input_tokens: ReadOnly[int | None]
+    cache_read_input_tokens: ReadOnly[int | None]
+
+
+class _AnthropicToolResultBlock(TypedDict, total=False):
+    """A ``*_tool_result`` content block on an Anthropic response."""
+
+    type: ReadOnly[str]
+    tool_use_id: ReadOnly[str]
+    content: ReadOnly[object]
+
+
+_ENUM_TYPE_CHECKS: Final[Mapping[str, Callable[[object], bool]]] = MappingProxyType(
     {
         "null": lambda v: v is None,
         "boolean": lambda v: isinstance(v, bool),
@@ -440,7 +459,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         optional_params.pop("speed", None)
 
     @staticmethod
-    def _raise_invalid_reasoning_effort(model: str, value: Any, llm_provider: str) -> NoReturn:
+    def _raise_invalid_reasoning_effort(model: str, value: object, llm_provider: str) -> NoReturn:
         """Raise a ``BadRequestError`` for an unrecognised ``reasoning_effort``.
 
         Args:
@@ -2059,22 +2078,22 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         self, completion_response: dict
     ) -> tuple[
         str,
-        list[Any] | None,
+        list[object] | None,
         list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None,
         str | None,
         list[ChatCompletionToolCallChunk],
-        list[Any] | None,
-        list[Any] | None,
-        list[Any] | None,
+        list[object] | None,
+        list[_AnthropicToolResultBlock] | None,
+        list[object] | None,
     ]:
         text_content = ""
-        citations: list[Any] | None = None
+        citations: list[object] | None = None
         thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None = None
         reasoning_content: str | None = None
         tool_calls: Final[list[ChatCompletionToolCallChunk]] = []
-        web_search_results: list[Any] | None = None
-        tool_results: list[Any] | None = None
-        compaction_blocks: list[Any] | None = None
+        web_search_results: list[object] | None = None
+        tool_results: list[_AnthropicToolResultBlock] | None = None
+        compaction_blocks: list[object] | None = None
         for idx, content in enumerate(completion_response["content"]):
             if content["type"] == "text":
                 text_content += content["text"]
@@ -2284,7 +2303,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
         raw_speed: Final = _usage.get("speed")
         resolved_speed: Final = raw_speed if isinstance(raw_speed, str) else speed
 
-        iterations: Final[list[Any] | None] = _usage.get("iterations")
+        iterations: Final[Sequence[_AnthropicUsageIteration] | None] = _usage.get("iterations")
         if iterations:
             prompt_tokens = sum(it.get("input_tokens", 0) or 0 for it in iterations)
             completion_tokens = sum(it.get("output_tokens", 0) or 0 for it in iterations)
@@ -2377,7 +2396,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
 
     def _build_code_interpreter_results(
         self,
-        tool_results: list[Any],
+        tool_results: Sequence[_AnthropicToolResultBlock],
         code_by_id: dict[str, str],
         container_id: str | None,
     ) -> list[OutputCodeInterpreterCall]:
@@ -2403,11 +2422,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
     def _build_provider_specific_fields(
         self,
         completion_response: dict,
-        citations: list[Any] | None,
+        citations: Sequence[object] | None,
         thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None,
-        web_search_results: list[Any] | None,
-        tool_results: list[Any] | None,
-        compaction_blocks: list[Any] | None,
+        web_search_results: Sequence[object] | None,
+        tool_results: Sequence[_AnthropicToolResultBlock] | None,
+        compaction_blocks: Sequence[object] | None,
         tool_calls: list[ChatCompletionToolCallChunk],
     ) -> dict[str, Any]:
         provider_specific_fields: Final[dict[str, Any]] = {
diff --git a/litellm/llms/anthropic/files/handler.py b/litellm/llms/anthropic/files/handler.py
index 5fdf2ceff7f..dfd62ca575b 100644
--- a/litellm/llms/anthropic/files/handler.py
+++ b/litellm/llms/anthropic/files/handler.py
@@ -2,7 +2,7 @@ import asyncio
 import json
 import time
 from collections.abc import Coroutine
-from typing import Any, Final
+from typing import Final
 
 import httpx
 
@@ -116,7 +116,7 @@ class AnthropicFilesHandler:
         api_key: str | None = None,
         timeout: float | httpx.Timeout = 600.0,
         max_retries: int | None = None,
-    ) -> HttpxBinaryResponseContent | Coroutine[Any, Any, HttpxBinaryResponseContent]:
+    ) -> HttpxBinaryResponseContent | Coroutine[object, object, HttpxBinaryResponseContent]:
         """
         Retrieve file content from Anthropic.
 
diff --git a/litellm/llms/azure/azure.py b/litellm/llms/azure/azure.py
index 2bcc830851a..46a9dd1a531 100644
--- a/litellm/llms/azure/azure.py
+++ b/litellm/llms/azure/azure.py
@@ -2,7 +2,7 @@ import asyncio
 import json
 import time
 from collections.abc import Callable, Coroutine
-from typing import Any, Final
+from typing import Final
 
 import httpx
 from openai import (
@@ -374,7 +374,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         except Exception as e:
             status_code: Final = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
-            error_response: Final = getattr(e, "response", None)
+            error_response: Final[object] = getattr(e, "response", None)
             error_body: Final = getattr(e, "body", None)
             if error_headers is None and error_response:
                 error_headers = getattr(error_response, "headers", None)
@@ -392,7 +392,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         model: str,
         api_base: str,
         data: dict,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         dynamic_params: bool,
         model_response: ModelResponse,
         logging_obj: LiteLLMLoggingObj,
@@ -502,7 +502,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         dynamic_params: bool,
         data: dict[str, object],
         model: str,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         max_retries: int,
         azure_ad_token: str | None = None,
         azure_ad_token_provider: Callable | None = None,
@@ -578,7 +578,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         dynamic_params: bool,
         data: dict,
         model: str,
-        timeout: Any,
+        timeout: float | httpx.Timeout,
         max_retries: int,
         azure_ad_token: str | None = None,
         azure_ad_token_provider: Callable | None = None,
@@ -634,7 +634,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         except Exception as e:
             status_code: Final = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
-            error_response: Final = getattr(e, "response", None)
+            error_response: Final[object] = getattr(e, "response", None)
             message: Final = getattr(e, "message", str(e))
             error_body: Final = getattr(e, "body", None)
             if error_headers is None and error_response:
@@ -754,7 +754,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
         aembedding=None,
         headers: dict | None = None,
         litellm_params: dict | None = None,
-    ) -> EmbeddingResponse | Coroutine[Any, Any, EmbeddingResponse]:
+    ) -> EmbeddingResponse | Coroutine[object, object, EmbeddingResponse]:
         if headers:
             optional_params["extra_headers"] = headers
         if self._client_session is None:
@@ -1268,7 +1268,7 @@ class AzureChatCompletion(BaseAzureLLM, BaseLLM):
                     headers["Authorization"] = f"Bearer {azure_ad_token}"
 
             # init AzureOpenAI Client
-            azure_client_params: Final[dict[str, Any]] = self.initialize_azure_sdk_client(
+            azure_client_params: Final[dict[str, object]] = self.initialize_azure_sdk_client(
                 litellm_params=litellm_params or {},
                 api_key=api_key,
                 model_name=model or "",
diff --git a/litellm/llms/azure_ai/agents/handler.py b/litellm/llms/azure_ai/agents/handler.py
index a13b1300e55..f7382190fca 100644
--- a/litellm/llms/azure_ai/agents/handler.py
+++ b/litellm/llms/azure_ai/agents/handler.py
@@ -51,15 +51,13 @@ else:
     AsyncHTTPHandler = Any
 
 
-class _AzureRawAnnotation(TypedDict, total=False):
-    type: ReadOnly[str]
+class _AzureRawAnnotation(ChatCompletionAnnotation, total=False):
     text: ReadOnly[str]
     start_index: ReadOnly[int]
     end_index: ReadOnly[int]
-    url_citation: ReadOnly[ChatCompletionAnnotationURLCitation]
 
 
-_TransformedAnnotation: TypeAlias = ChatCompletionAnnotation | _AzureRawAnnotation
+_TransformedAnnotation: TypeAlias = ChatCompletionAnnotation
 
 
 class _AzureText(TypedDict, total=False):
@@ -223,18 +221,11 @@ class AzureAIAgentsHandler:
         """Build the ModelResponse from agent output."""
         from litellm.types.utils import Choices, Message, Usage
 
-        message_kwargs: Final[dict[str, Any]] = {
-            "content": content,
-            "role": "assistant",
-        }
-        if annotations:
-            message_kwargs["annotations"] = annotations
-
         model_response.choices = [
             Choices(
                 finish_reason="stop",
                 index=0,
-                message=Message(**message_kwargs),
+                message=Message(content=content, role="assistant", annotations=annotations or None),
             )
         ]
         model_response.model = model
@@ -655,9 +646,6 @@ class AzureAIAgentsHandler:
 
                 if data_str == "[DONE]":
                     # Send final chunk with finish_reason
-                    final_delta_kwargs: dict[str, Any] = {"content": None}
-                    if collected_annotations:
-                        final_delta_kwargs["annotations"] = collected_annotations
                     final_chunk = ModelResponseStream(
                         id=response_id,
                         created=created,
@@ -667,7 +655,7 @@ class AzureAIAgentsHandler:
                             StreamingChoices(
                                 finish_reason="stop",
                                 index=0,
-                                delta=Delta(**final_delta_kwargs),
+                                delta=Delta(content=None, annotations=collected_annotations or None),
                             )
                         ],
                     )
diff --git a/litellm/llms/bedrock/realtime/transformation.py b/litellm/llms/bedrock/realtime/transformation.py
index 28c2e446d10..1f4c81d6491 100644
--- a/litellm/llms/bedrock/realtime/transformation.py
+++ b/litellm/llms/bedrock/realtime/transformation.py
@@ -7,7 +7,7 @@ Transforms between OpenAI Realtime API format and Bedrock Nova Sonic format.
 import base64
 import json
 import uuid as uuid_lib
-from typing import Any, Final, cast
+from typing import Final, cast
 
 from pydantic import BaseModel
 
@@ -633,7 +633,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
             List of Bedrock format messages (JSON strings)
         """
         try:
-            json_message: Final = json.loads(message)
+            json_message: Final[dict[str, object]] = json.loads(message)
         except json.JSONDecodeError:
             verbose_logger.warning("Invalid JSON message: %s", message[:200])
             return []
@@ -1182,7 +1182,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
 
         # Create a function call arguments done event
         # This is a custom event format that matches what clients expect
-        function_call_event: Final[dict[str, Any]] = {
+        function_call_event: Final[dict[str, object]] = {
             "type": "response.function_call_arguments.done",
             "event_id": f"event_{uuid.uuid4()}",
             "response_id": current_response_id,
diff --git a/litellm/llms/black_forest_labs/image_edit/handler.py b/litellm/llms/black_forest_labs/image_edit/handler.py
index 1ff02a6f8d9..178acb0de0d 100644
--- a/litellm/llms/black_forest_labs/image_edit/handler.py
+++ b/litellm/llms/black_forest_labs/image_edit/handler.py
@@ -8,9 +8,11 @@ then we poll until the result is ready.
 
 import asyncio
 import time
-from typing import Any, Final
+from collections.abc import Coroutine, Mapping
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,6 +35,42 @@ from ..common_utils import (
 from .transformation import BlackForestLabsImageEditConfig
 
 
+class _BFLSubmitBody(TypedDict, total=False):
+    """Decoded body of the BFL submit response, which hands back a polling URL."""
+
+    errors: ReadOnly[object]
+    polling_url: ReadOnly[str]
+
+
+class _BFLPollBody(TypedDict, total=False):
+    """Decoded body of a BFL polling response."""
+
+    status: ReadOnly[str]
+
+
+class _BFLSubmitResponse(Protocol):
+    """The submit call's HTTP response, read for its status, body text and decoded body."""
+
+    @property
+    def status_code(self) -> int: ...
+
+    @property
+    def text(self) -> str: ...
+
+    def json(self) -> _BFLSubmitBody: ...
+
+
+class _BFLPollResponse(Protocol):
+    """A polling call's HTTP response, read only for the task status it carries."""
+
+    def json(self) -> _BFLPollBody: ...
+
+
+def _poll_status(response: _BFLPollResponse) -> str | None:
+    """Read the task status out of a BFL polling response body."""
+    return response.json().get("status")
+
+
 class BlackForestLabsImageEdit:
     """
     Black Forest Labs Image Edit handler.
@@ -53,10 +91,10 @@ class BlackForestLabsImageEdit:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, object] | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         aimage_edit: bool = False,
-    ) -> ImageResponse | Any:
+    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
         """
         Main entry point for image edit requests.
 
@@ -185,7 +223,7 @@ class BlackForestLabsImageEdit:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, object] | None = None,
         client: AsyncHTTPHandler | None = None,
     ) -> ImageResponse:
         """
@@ -281,7 +319,7 @@ class BlackForestLabsImageEdit:
 
     def _poll_for_result_sync(
         self,
-        initial_response: httpx.Response,
+        initial_response: _BFLSubmitResponse,
         headers: dict,
         sync_client: HTTPHandler,
         max_wait: float = DEFAULT_MAX_POLLING_TIME,
@@ -356,8 +394,7 @@ class BlackForestLabsImageEdit:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
-            status = data.get("status")
+            status = _poll_status(response)
 
             verbose_logger.debug("BFL poll status: %s", status)
 
@@ -383,7 +420,7 @@ class BlackForestLabsImageEdit:
 
     async def _poll_for_result_async(
         self,
-        initial_response: httpx.Response,
+        initial_response: _BFLSubmitResponse,
         headers: dict,
         async_client: AsyncHTTPHandler,
         max_wait: float = DEFAULT_MAX_POLLING_TIME,
@@ -447,8 +484,7 @@ class BlackForestLabsImageEdit:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
-            status = data.get("status")
+            status = _poll_status(response)
 
             verbose_logger.debug("BFL poll status: %s", status)
 
diff --git a/litellm/llms/black_forest_labs/image_generation/handler.py b/litellm/llms/black_forest_labs/image_generation/handler.py
index 03e4999c5aa..879bef37b58 100644
--- a/litellm/llms/black_forest_labs/image_generation/handler.py
+++ b/litellm/llms/black_forest_labs/image_generation/handler.py
@@ -8,9 +8,11 @@ then we poll until the result is ready.
 
 import asyncio
 import time
-from typing import Any, Final
+from collections.abc import Coroutine, Mapping
+from typing import Final, Protocol, TypedDict
 
 import httpx
+from typing_extensions import ReadOnly
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,6 +35,23 @@ from ..common_utils import (
 from .transformation import BlackForestLabsImageGenerationConfig
 
 
+class _BFLTaskPayload(TypedDict, total=False):
+    """The body BFL returns for a submitted or polled generation task."""
+
+    errors: ReadOnly[object]
+    polling_url: ReadOnly[str]
+    status: ReadOnly[str]
+
+
+class _TaskJsonResponse(Protocol):
+    def json(self) -> _BFLTaskPayload: ...
+
+
+def _task_payload(response: _TaskJsonResponse) -> _BFLTaskPayload:
+    """The JSON body of a BFL task submission or poll response."""
+    return response.json()
+
+
 class BlackForestLabsImageGeneration:
     """
     Black Forest Labs Image Generation handler.
@@ -53,10 +72,10 @@ class BlackForestLabsImageGeneration:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, str] | None = None,
         client: HTTPHandler | AsyncHTTPHandler | None = None,
         aimg_generation: bool = False,
-    ) -> ImageResponse | Any:
+    ) -> ImageResponse | Coroutine[object, object, ImageResponse]:
         """
         Main entry point for image generation requests.
 
@@ -187,7 +206,7 @@ class BlackForestLabsImageGeneration:
         litellm_params: GenericLiteLLMParams | dict,
         logging_obj: LiteLLMLoggingObj,
         timeout: float | httpx.Timeout | None,
-        extra_headers: dict[str, Any] | None = None,
+        extra_headers: Mapping[str, str] | None = None,
         client: AsyncHTTPHandler | None = None,
     ) -> ImageResponse:
         """
@@ -305,7 +324,7 @@ class BlackForestLabsImageGeneration:
 
         # Parse initial response to get polling URL
         try:
-            response_data: Final = initial_response.json()
+            response_data: Final = _task_payload(initial_response)
         except Exception as e:
             raise BlackForestLabsError(
                 status_code=initial_response.status_code,
@@ -350,7 +369,7 @@ class BlackForestLabsImageGeneration:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
+            data = _task_payload(response)
             status = data.get("status")
 
             verbose_logger.debug("BFL poll status: %s", status)
@@ -396,7 +415,7 @@ class BlackForestLabsImageGeneration:
 
         # Parse initial response to get polling URL
         try:
-            response_data: Final = initial_response.json()
+            response_data: Final = _task_payload(initial_response)
         except Exception as e:
             raise BlackForestLabsError(
                 status_code=initial_response.status_code,
@@ -441,7 +460,7 @@ class BlackForestLabsImageGeneration:
                     message=f"Polling failed: {response.text}",
                 )
 
-            data = response.json()
+            data = _task_payload(response)
             status = data.get("status")
 
             verbose_logger.debug("BFL poll status: %s", status)
diff --git a/litellm/llms/codestral/completion/handler.py b/litellm/llms/codestral/completion/handler.py
index 8c08b2bc33c..f8486d3b274 100644
--- a/litellm/llms/codestral/completion/handler.py
+++ b/litellm/llms/codestral/completion/handler.py
@@ -4,9 +4,10 @@
 import json
 from collections.abc import Callable
 from functools import partial
-from typing import Final
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
@@ -23,6 +24,53 @@ from litellm.types.utils import TextChoices
 from litellm.utils import CustomStreamWrapper, TextCompletionResponse
 
 
+class _CodestralChoiceMessage(TypedDict):
+    """`choices[].message` of a Codestral FIM completion."""
+
+    role: ReadOnly[NotRequired[str]]
+    content: ReadOnly[NotRequired[str | None]]
+
+
+class _CodestralChoice(TypedDict):
+    """One entry of `choices` in a Codestral FIM completion."""
+
+    index: ReadOnly[int]
+    message: ReadOnly[NotRequired[_CodestralChoiceMessage]]
+    finish_reason: ReadOnly[NotRequired[str | None]]
+    logprobs: ReadOnly[NotRequired[dict[str, object] | None]]
+
+
+class _CodestralUsage(TypedDict):
+    """Token accounting returned alongside a Codestral FIM completion."""
+
+    prompt_tokens: ReadOnly[NotRequired[int]]
+    completion_tokens: ReadOnly[NotRequired[int]]
+    total_tokens: ReadOnly[NotRequired[int]]
+
+
+class _CodestralCompletionResponse(TypedDict):
+    """Body returned by the Codestral `/v1/fim/completions` endpoint."""
+
+    id: ReadOnly[NotRequired[str]]
+    created: ReadOnly[NotRequired[int]]
+    model: ReadOnly[NotRequired[str]]
+    object: ReadOnly[NotRequired[str]]
+    usage: ReadOnly[NotRequired[_CodestralUsage]]
+    choices: ReadOnly[NotRequired[list[_CodestralChoice]]]
+
+
+class _CodestralHTTPResponse(Protocol):
+    """The Codestral completion response as this handler reads it."""
+
+    @property
+    def status_code(self) -> int: ...
+
+    @property
+    def text(self) -> str: ...
+
+    def json(self) -> _CodestralCompletionResponse: ...
+
+
 class TextCompletionCodestralError(Exception):
     def __init__(
         self,
@@ -115,7 +163,7 @@ class CodestralTextCompletion:
     def process_text_completion_response(
         self,
         model: str,
-        response: httpx.Response,
+        response: _CodestralHTTPResponse,
         model_response: TextCompletionResponse,
         stream: bool,
         logging_obj: LiteLLMLogging,
diff --git a/litellm/llms/deepinfra/rerank/transformation.py b/litellm/llms/deepinfra/rerank/transformation.py
index e52c56af82b..a3d0482af0a 100644
--- a/litellm/llms/deepinfra/rerank/transformation.py
+++ b/litellm/llms/deepinfra/rerank/transformation.py
@@ -2,10 +2,11 @@
 Translate between Cohere's `/rerank` format and Deepinfra's `/rerank` format.
 """
 
-from collections.abc import Mapping
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._uuid import uuid
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
@@ -24,6 +25,36 @@ from litellm.types.rerank import (
 )
 
 
+class _DeepinfraInferenceStatus(TypedDict, total=False):
+    """The ``inference_status`` block of a DeepInfra rerank response."""
+
+    status: ReadOnly[str]
+    runtime_ms: ReadOnly[float]
+    cost: ReadOnly[float]
+    tokens_generated: ReadOnly[int]
+    tokens_input: ReadOnly[int]
+
+
+class _DeepinfraRerankResponse(TypedDict, total=False):
+    """Body of a DeepInfra ``/rerank`` response."""
+
+    scores: ReadOnly[Sequence[float]]
+    input_tokens: ReadOnly[int]
+    request_id: ReadOnly[str | None]
+    inference_status: ReadOnly[_DeepinfraInferenceStatus]
+
+
+class _DeepinfraRerankResponseSource(Protocol):
+    """The DeepInfra ``/rerank`` HTTP response, read for the body it decodes to."""
+
+    def json(self) -> _DeepinfraRerankResponse: ...
+
+
+def _deepinfra_rerank_body(response: _DeepinfraRerankResponseSource) -> _DeepinfraRerankResponse:
+    """Decode the body of a DeepInfra ``/rerank`` response."""
+    return response.json()
+
+
 class DeepinfraRerankConfig(BaseRerankConfig):
     """
     Deepinfra Rerank - Follows the same Spec as Cohere Rerank
@@ -95,7 +126,7 @@ class DeepinfraRerankConfig(BaseRerankConfig):
         model: str,
         drop_params: bool,
         query: str,
-        documents: list[str | dict[str, Any]],
+        documents: list[str | dict[str, object]],
         custom_llm_provider: str | None = None,
         top_n: int | None = None,
         rank_fields: list[str] | None = None,
@@ -150,7 +181,7 @@ class DeepinfraRerankConfig(BaseRerankConfig):
         litellm_params: dict = {},
     ) -> RerankResponse:
         try:
-            response_json: Final = raw_response.json()
+            response_json: Final = _deepinfra_rerank_body(raw_response)
             logging_obj.post_call(original_response=raw_response.text)
 
             # Extract the scores from the response
diff --git a/litellm/llms/gemini/interactions/transformation.py b/litellm/llms/gemini/interactions/transformation.py
index dcd2e4e3471..6d0f211ed7b 100644
--- a/litellm/llms/gemini/interactions/transformation.py
+++ b/litellm/llms/gemini/interactions/transformation.py
@@ -12,9 +12,10 @@ Schema versioning:
   litellm.use_legacy_interactions_schema = True. Remove flag after June 8, 2026.
 """
 
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol, TypeAlias
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -41,6 +42,53 @@ else:
     LiteLLMLoggingObj = Any
 
 
+_JsonObject: TypeAlias = dict[str, object]
+
+
+class _InteractionPayload(TypedDict, total=False):
+    """JSON body of an Interactions API interaction, keyed as ``InteractionsAPIResponse`` fields."""
+
+    id: ReadOnly[str | None]
+    object: ReadOnly[str | None]
+    model: ReadOnly[str | None]
+    agent: ReadOnly[str | None]
+    status: ReadOnly[str | None]
+    created: ReadOnly[str | None]
+    updated: ReadOnly[str | None]
+    outputs: ReadOnly[list[_JsonObject] | None]
+    steps: ReadOnly[list[_JsonObject] | None]
+    usage: ReadOnly[_JsonObject | None]
+
+
+class _CancelPayload(TypedDict, total=False):
+    """JSON body of an Interactions API cancel response."""
+
+    id: ReadOnly[str | None]
+    status: ReadOnly[str | None]
+
+
+class _InteractionPayloadSource(Protocol):
+    """An Interactions API HTTP response, read for the interaction body it decodes to."""
+
+    def json(self) -> _InteractionPayload: ...
+
+
+class _CancelPayloadSource(Protocol):
+    """An Interactions API cancel HTTP response, read for the body it decodes to."""
+
+    def json(self) -> _CancelPayload: ...
+
+
+def _interaction_body(response: _InteractionPayloadSource) -> _InteractionPayload:
+    """Decode the body of an Interactions API interaction response."""
+    return response.json()
+
+
+def _cancel_body(response: _CancelPayloadSource) -> _CancelPayload:
+    """Decode the body of an Interactions API cancel response."""
+    return response.json()
+
+
 class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
     """
     Configuration for Google AI Studio Interactions API.
@@ -143,7 +191,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         """
         use_legacy: Final[bool] = litellm.use_legacy_interactions_schema
 
-        request_body: Final[dict[str, Any]] = {}
+        request_body: Final[dict[str, object]] = {}
 
         # Model or Agent (one required)
         if model:
@@ -189,7 +237,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
                 and (not isinstance(response_format, dict) or "mime_type" not in response_format)
             ):
                 # Wrap the legacy schema into the new polymorphic format.
-                new_rf: Final[dict[str, Any]] = {
+                new_rf: Final[dict[str, object]] = {
                     "type": "text",
                     "mime_type": response_mime_type,
                 }
@@ -215,7 +263,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
 
                 if image_config is not None:
                     # Move image_config to response_format with type=image.
-                    image_rf: Final[dict[str, Any]] = {"type": "image", **image_config}
+                    image_rf: Final[_JsonObject] = {"type": "image", **image_config}
                     existing_rf: Final = request_body.get("response_format")
                     if existing_rf is None:
                         request_body["response_format"] = image_rf
@@ -239,7 +287,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
                 original_response=raw_response.text,
                 additional_args={"complete_input_dict": {}},
             )
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _interaction_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
@@ -290,7 +338,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> InteractionsAPIResponse:
         try:
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _interaction_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
@@ -355,7 +403,7 @@ class GoogleAIStudioInteractionsConfig(BaseInteractionsAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> CancelInteractionResult:
         try:
-            raw_json: Final = raw_response.json()
+            raw_json: Final = _cancel_body(raw_response)
         except Exception:
             raise GeminiError(
                 message=raw_response.text,
diff --git a/litellm/llms/gemini/videos/transformation.py b/litellm/llms/gemini/videos/transformation.py
index 6a1fc144c42..ff4c675b02f 100644
--- a/litellm/llms/gemini/videos/transformation.py
+++ b/litellm/llms/gemini/videos/transformation.py
@@ -1,4 +1,5 @@
 import base64
+from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
@@ -54,8 +55,13 @@ def _convert_image_to_gemini_format(image_file) -> dict[str, str]:
     return {"bytesBase64Encoded": base64_encoded, "mimeType": mime_type}
 
 
+def _json_payload(raw_response: httpx.Response) -> object:
+    """Read an HTTP response body as an opaque JSON payload."""
+    return raw_response.json()
+
+
 def _usage_video_resolution_from_parameters(
-    parameters: dict[str, Any],
+    parameters: Mapping[str, object],
 ) -> str | None:
     """Normalize Veo ``parameters.resolution`` for usage and cost tracking."""
     res: Final = parameters.get("resolution")
@@ -97,7 +103,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         video_create_optional_params: VideoCreateOptionalRequestParams,
         model: str,
         drop_params: bool,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Map OpenAI-style parameters to Veo format.
 
@@ -111,7 +117,7 @@ class GeminiVideoConfig(BaseVideoConfig):
 
         All other params are passed through as-is to support Gemini-specific parameters.
         """
-        mapped_params: Final[dict[str, Any]] = {}
+        mapped_params: Final[dict[str, object]] = {}
 
         # Get supported OpenAI params (exclude "model" and "prompt" which are handled separately)
         supported_openai_params: Final = self.get_supported_openai_params(model)
@@ -312,11 +318,11 @@ class GeminiVideoConfig(BaseVideoConfig):
         - status: "processing"
         - usage: includes duration_seconds and optional video_resolution for cost calculation
         """
-        response_data: Final = raw_response.json()
+        response_data: Final = _json_payload(raw_response)
 
         # Parse response using Pydantic model for type safety
         try:
-            operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+            operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
         except Exception as e:
             raise ValueError(f"Failed to parse operation response: {e}")
 
@@ -336,7 +342,7 @@ class GeminiVideoConfig(BaseVideoConfig):
             model=model,
         )
 
-        usage_data: Final[dict[str, Any]] = {}
+        usage_data: Final[dict[str, float | str]] = {}
         if request_data:
             parameters: Final = request_data.get("parameters", {})
             duration: Final = parameters.get("durationSeconds") or DEFAULT_GOOGLE_VIDEO_DURATION_SECONDS
@@ -367,7 +373,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         """
         operation_name: Final = extract_original_video_id(video_id)
         url: Final = f"{api_base.rstrip('/')}/v1beta/{operation_name}"
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
 
         return url, params
 
@@ -403,9 +409,9 @@ class GeminiVideoConfig(BaseVideoConfig):
             }
         }
         """
-        response_data: Final = raw_response.json()
+        response_data: Final = _json_payload(raw_response)
         # Parse response using Pydantic model for type safety
-        operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+        operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
 
         operation_name: Final = operation_response.name
         is_done: Final = operation_response.done
@@ -443,9 +449,9 @@ class GeminiVideoConfig(BaseVideoConfig):
         client: Final = litellm.module_level_client
         status_response: Final = client.get(url=status_url, headers=headers)
         status_response.raise_for_status()
-        response_data: Final = status_response.json()
+        response_data: Final = _json_payload(status_response)
 
-        operation_response: Final = GeminiLongRunningOperationResponse(**response_data)
+        operation_response: Final = GeminiLongRunningOperationResponse.model_validate(response_data)
 
         if not operation_response.done:
             raise ValueError(
@@ -458,7 +464,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         generated_samples: Final = operation_response.response.generateVideoResponse.generatedSamples
         download_url: Final = generated_samples[0].video.uri
 
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
 
         return download_url, params
 
@@ -480,7 +486,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         api_base: str,
         litellm_params: GenericLiteLLMParams,
         headers: dict,
-        extra_body: dict[str, Any] | None = None,
+        extra_body: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """
         Video remix is not supported by Veo API.
@@ -506,7 +512,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         after: str | None = None,
         limit: int | None = None,
         order: str | None = None,
-        extra_query: dict[str, Any] | None = None,
+        extra_query: Mapping[str, object] | None = None,
     ) -> tuple[str, dict]:
         """
         Video list is not supported by Veo API.
@@ -547,7 +553,7 @@ class GeminiVideoConfig(BaseVideoConfig):
         """Video delete is not supported."""
         raise NotImplementedError("Video delete is not supported by Google Veo.")
 
-    def transform_video_create_character_request(self, name, video, api_base, litellm_params, headers):
+    def transform_video_create_character_request(self, name, video: object, api_base, litellm_params, headers):
         raise NotImplementedError("video create character is not supported for Gemini")
 
     def transform_video_create_character_response(self, raw_response, logging_obj):
diff --git a/litellm/llms/huggingface/embedding/transformation.py b/litellm/llms/huggingface/embedding/transformation.py
index d3db3530109..f6fe7f2fa10 100644
--- a/litellm/llms/huggingface/embedding/transformation.py
+++ b/litellm/llms/huggingface/embedding/transformation.py
@@ -1,8 +1,9 @@
 import json
 import os
 import time
+from collections.abc import Sequence
 from copy import deepcopy
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 
 import httpx
 
@@ -24,6 +25,8 @@ from litellm.utils import token_counter
 from ..common_utils import HuggingFaceError, hf_task_list, hf_tasks, output_parser
 
 if TYPE_CHECKING:
+    import tiktoken
+
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
 
     LoggingClass = LiteLLMLoggingObj
@@ -31,6 +34,12 @@ else:
     LoggingClass = Any
 
 
+class _TokenEncoding(Protocol):
+    """Tokenizer handle the caller passes in; only `encode` is used, to count completion tokens."""
+
+    def encode(self, text: str, /) -> Sequence[object]: ...
+
+
 tgi_models_cache = None
 conv_models_cache = None
 
@@ -369,7 +378,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         model_response: ModelResponse,
         task: hf_tasks | None,
         optional_params: dict,
-        encoding: Any,
+        encoding: "_TokenEncoding | None",
         messages: list[AllMessageValues],
         model: str,
     ):
@@ -439,9 +448,10 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         if output_text is not None and len(output_text) > 0:
             completion_tokens = 0
             try:
-                completion_tokens = len(
-                    encoding.encode(model_response["choices"][0]["message"].get("content", ""))
-                )  ##[TODO] use the llama2 tokenizer here
+                if encoding is not None:
+                    completion_tokens = len(
+                        encoding.encode(model_response["choices"][0]["message"].get("content", ""))
+                    )  ##[TODO] use the llama2 tokenizer here
             except Exception:
                 # this should remain non blocking we should not block a response returning if calculating usage fails
                 pass
@@ -469,7 +479,7 @@ class HuggingFaceEmbeddingConfig(BaseConfig):
         messages: list[AllMessageValues],
         optional_params: dict,
         litellm_params: dict,
-        encoding: Any,
+        encoding: "tiktoken.Encoding | None",
         api_key: str | None = None,
         json_mode: bool | None = None,
     ) -> ModelResponse:
diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index d4747b2fb06..3a7f78fd5ba 100644
--- a/litellm/llms/openai/chat/gpt_transformation.py
+++ b/litellm/llms/openai/chat/gpt_transformation.py
@@ -325,7 +325,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     @overload
     def _transform_messages(
         self, messages: list[AllMessageValues], model: str, is_async: Literal[True]
-    ) -> Coroutine[Any, Any, list[AllMessageValues]]: 
+    ) -> Coroutine[object, object, list[AllMessageValues]]:
         ...
 
     @overload
@@ -341,7 +341,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
 
     def _transform_messages(
         self, messages: list[AllMessageValues], model: str, is_async: bool = False
-    ) -> list[AllMessageValues] | Coroutine[Any, Any, list[AllMessageValues]]:
+    ) -> list[AllMessageValues] | Coroutine[object, object, list[AllMessageValues]]:
         """OpenAI no longer supports image_url as a string, so we need to convert it to a dict"""
         stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(messages)
         hoisted_messages: Final = hoist_images_from_tool_messages(stripped_messages)
@@ -497,8 +497,12 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             return None
         tool_call_names: Final = get_tool_call_names(optional_params.get("tools", []))
         try:
-            json_content: Final = json.loads(content)
-            if json_content.get("type") == "function" and json_content.get("name") in tool_call_names:
+            json_content: Final[object] = json.loads(content)
+            if (
+                isinstance(json_content, dict)
+                and json_content.get("type") == "function"
+                and json_content.get("name") in tool_call_names
+            ):
                 return ChatCompletionMessageToolCall(
                     function=Function(
                         name=json_content.get("name"),
@@ -622,7 +626,7 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
 
         ## RESPONSE OBJECT
         try:
-            completion_response: Final = raw_response.json()
+            completion_response: Final[dict[str, object]] = raw_response.json()
         except Exception as e:
             response_headers: Final = getattr(raw_response, "headers", None)
             raise OpenAIError(
diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py
index de15fefe943..ed628f55350 100644
--- a/litellm/llms/openai/chat/guardrail_translation/handler.py
+++ b/litellm/llms/openai/chat/guardrail_translation/handler.py
@@ -51,6 +51,7 @@ if TYPE_CHECKING:
 
     from litellm.integrations.custom_guardrail import CustomGuardrail
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.proxy._types import UserAPIKeyAuth
 
 
 class OpenAIChatCompletionsHandler(BaseTranslation):
@@ -80,7 +81,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         data: dict,
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-    ) -> Any:
+    ) -> dict:
         """
         Process input messages by applying guardrails to text content.
         """
@@ -329,9 +330,9 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         response: "ModelResponse",
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-        user_api_key_dict: Any | None = None,
+        user_api_key_dict: "UserAPIKeyAuth | None" = None,
         request_data: dict | None = None,
-    ) -> Any:
+    ) -> ModelResponse:
         """
         Process output response by applying guardrails to text content.
 
@@ -436,7 +437,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None" = None,
-        user_api_key_dict: Any | None = None,
+        user_api_key_dict: "UserAPIKeyAuth | None" = None,
         request_data: dict | None = None,
         stream_transform_sink: StreamTransformSink | None = None,
     ) -> list["ModelResponseStream"]:
@@ -486,7 +487,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None",
-        user_api_key_dict: Any | None,
+        user_api_key_dict: "UserAPIKeyAuth | None",
         request_data: dict | None,
     ) -> list["ModelResponseStream"]:
         """Block-only streaming path: run the guardrail so an in-flight BLOCK can
@@ -589,8 +590,8 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
     def build_stream_error_items(
         self,
         exc: "HTTPException",
-        responses_so_far: Sequence[Any] | None = None,
-    ) -> Sequence[Any] | None:
+        responses_so_far: Sequence[object] | None = None,
+    ) -> Sequence[bytes] | None:
         import json
 
         from litellm.proxy.common_request_processing import sse_error_payload
@@ -630,7 +631,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
         responses_so_far: list["ModelResponseStream"],
         guardrail_to_apply: "CustomGuardrail",
         litellm_logging_obj: "LiteLLMLoggingObj | None",
-        user_api_key_dict: Any | None,
+        user_api_key_dict: "UserAPIKeyAuth | None",
         request_data: dict | None,
         sink: StreamTransformSink,
     ) -> None:
@@ -794,7 +795,7 @@ class OpenAIChatCompletionsHandler(BaseTranslation):
 
         # Determine content source and tool calls based on choice type
         content = None
-        tool_calls: list[Any] | None = None
+        tool_calls: Sequence[object] | None = None
         if isinstance(choice, litellm.Choices):
             content = choice.message.content
             tool_calls = choice.message.tool_calls
diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py
index eadc087383a..09028b6dc5f 100644
--- a/litellm/llms/openai/responses/transformation.py
+++ b/litellm/llms/openai/responses/transformation.py
@@ -1,10 +1,11 @@
 from collections.abc import Mapping, Sequence
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, cast, get_type_hints
+from typing import TYPE_CHECKING, Any, Final, Protocol, cast, get_type_hints
 
 import httpx
 from openai.types.responses import ResponseReasoningItem
 from pydantic import BaseModel, ValidationError
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -37,6 +38,36 @@ _MODEL_FAMILIES_REJECTING_TOP_LEVEL_SCHEMA_COMBINATORS: Final = ("gpt-4", "gpt-3
 _PROVIDERS_WITH_COMBINATOR_REJECTING_VALIDATOR: Final = frozenset({LlmProviders.AZURE, LlmProviders.OPENAI})
 
 
+class _DeleteResponseBody(TypedDict):
+    """Decoded body of the Responses API delete call."""
+
+    id: ReadOnly[str | None]
+    object: ReadOnly[str | None]
+    deleted: ReadOnly[bool | None]
+
+
+class _DeleteResponse(Protocol):
+    """The delete call's HTTP response, read for the decoded body it carries."""
+
+    def json(self) -> _DeleteResponseBody: ...
+
+
+class _JsonObjectResponse(Protocol):
+    """A Responses API HTTP response, read for the JSON object it decodes to."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _delete_response_body(response: _DeleteResponse) -> _DeleteResponseBody:
+    """Decode a delete response body into the id, object and deleted fields it carries."""
+    return response.json()
+
+
+def _json_object_body(response: _JsonObjectResponse) -> dict[str, object]:
+    """Decode a Responses API response body into its JSON object form."""
+    return response.json()
+
+
 class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
     @property
     def custom_llm_provider(self) -> LlmProviders:
@@ -469,7 +500,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         return None
 
     @staticmethod
-    def get_event_model_class(event_type: str) -> Any:
+    def get_event_model_class(event_type: str) -> type[BaseLiteLLMOpenAIResponseObject]:
         """
         Returns the appropriate event model class based on the event type.
 
@@ -583,7 +614,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the delete response API response into a DeleteResponseResult
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _delete_response_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         return DeleteResponseResult(**raw_response_json)
@@ -618,7 +649,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the get response API response into a ResponsesAPIResponse
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         raw_response_headers: Final = dict(raw_response.headers)
@@ -646,7 +677,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
     ) -> tuple[str, dict]:
         encoded_response_id: Final = encode_url_path_segment(response_id, field_name="response_id")
         url: Final = f"{api_base}/{encoded_response_id}/input_items"
-        params: Final[dict[str, Any]] = {}
+        params: Final[dict[str, object]] = {}
         if after is not None:
             params["after"] = after
         if before is not None:
@@ -665,7 +696,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         logging_obj: LiteLLMLoggingObj,
     ) -> dict:
         try:
-            return raw_response.json()
+            return _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
 
@@ -699,7 +730,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
         Transform the cancel response API response into a ResponsesAPIResponse
         """
         try:
-            raw_response_json: Final = raw_response.json()
+            raw_response_json: Final = _json_object_body(raw_response)
         except Exception:
             raise OpenAIError(message=raw_response.text, status_code=raw_response.status_code)
         raw_response_headers: Final = dict(raw_response.headers)
diff --git a/litellm/llms/openai_like/chat/handler.py b/litellm/llms/openai_like/chat/handler.py
index 8c548b6b0d6..855c49c320b 100644
--- a/litellm/llms/openai_like/chat/handler.py
+++ b/litellm/llms/openai_like/chat/handler.py
@@ -5,10 +5,11 @@ For handling OpenAI-like chat completions, like IBM WatsonX, etc.
 """
 
 import json
-from collections.abc import Callable
-from typing import Any, Final
+from collections.abc import Callable, Mapping, Sequence
+from typing import Final, TypedDict
 
 import httpx
+from typing_extensions import ReadOnly
 
 import litellm
 from litellm import LlmProviders
@@ -25,6 +26,23 @@ from ..common_utils import OpenAILikeBase, OpenAILikeError
 from .transformation import OpenAILikeChatConfig
 
 
+class _OpenAILikeChatCompletion(TypedDict, total=False):
+    """The chat-completion JSON body an OpenAI-like provider returns for a non-streamed call."""
+
+    id: ReadOnly[str]
+    choices: ReadOnly[Sequence[Mapping[str, object]]]
+    created: ReadOnly[int]
+    model: ReadOnly[str]
+    system_fingerprint: ReadOnly[str]
+    usage: ReadOnly[Mapping[str, object]]
+    object: ReadOnly[str]
+
+
+def _fake_streamed_model_response(payload: _OpenAILikeChatCompletion) -> ModelResponse:
+    """Build the single response a fake-streamed provider call replays as one chunk."""
+    return ModelResponse(**payload)
+
+
 async def make_call(
     client: AsyncHTTPHandler | None,
     api_base: str,
@@ -42,9 +60,9 @@ async def make_call(
     response: Final = await client.post(api_base, headers=headers, data=data, stream=not fake_stream)
 
     if streaming_decoder is not None:
-        completion_stream: Any = streaming_decoder.aiter_bytes(response.aiter_bytes(chunk_size=1024))
+        completion_stream = streaming_decoder.aiter_bytes(response.aiter_bytes(chunk_size=1024))
     elif fake_stream:
-        model_response: Final = ModelResponse(**response.json())
+        model_response: Final = _fake_streamed_model_response(response.json())
         completion_stream = MockResponseIterator(model_response=model_response)
     else:
         completion_stream = ModelResponseIterator(streaming_response=response.aiter_lines(), sync_stream=False)
@@ -82,7 +100,7 @@ def make_sync_call(
     if streaming_decoder is not None:
         completion_stream = streaming_decoder.iter_bytes(response.iter_bytes(chunk_size=1024))
     elif fake_stream:
-        model_response: Final = ModelResponse(**response.json())
+        model_response: Final = _fake_streamed_model_response(response.json())
         completion_stream = MockResponseIterator(model_response=model_response)
     else:
         completion_stream = ModelResponseIterator(streaming_response=response.iter_lines(), sync_stream=True)
diff --git a/litellm/llms/runwayml/image_generation/transformation.py b/litellm/llms/runwayml/image_generation/transformation.py
index cde65addb65..5913709c8a0 100644
--- a/litellm/llms/runwayml/image_generation/transformation.py
+++ b/litellm/llms/runwayml/image_generation/transformation.py
@@ -1,8 +1,10 @@
 import asyncio
 import time
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_logger
 from litellm.constants import (
@@ -29,6 +31,16 @@ else:
     LiteLLMLoggingObj = Any
 
 
+class _RunwayMLTask(TypedDict, total=False):
+    """The RunwayML task payload returned by POST /v1/text_to_image and GET /v1/tasks/{id}."""
+
+    id: ReadOnly[str]
+    status: ReadOnly[str]
+    output: ReadOnly[Sequence[str | Mapping[str, str]]]
+    failure: ReadOnly[str]
+    failureCode: ReadOnly[str]
+
+
 class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
     """
     Configuration for RunwayML image generation models.
@@ -80,7 +92,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
 
     @staticmethod
     def _transform_runwayml_response_to_openai(
-        response_data: dict[str, Any],
+        response_data: _RunwayMLTask,
         model_response: ImageResponse,
     ) -> ImageResponse:
         """
@@ -155,7 +167,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             raise TimeoutError(f"RunwayML task polling timed out after {timeout_secs} seconds")
 
     @staticmethod
-    def _check_task_status(response_data: dict[str, Any]) -> str:
+    def _check_task_status(response_data: _RunwayMLTask) -> str:
         """
         Check RunwayML task status from response.
 
@@ -227,7 +239,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             response = client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayMLTask = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -276,7 +288,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
             response = await client.get(url=task_url, headers=headers)
             response.raise_for_status()
 
-            response_data = response.json()
+            response_data: _RunwayMLTask = response.json()
 
             # Check task status
             status = self._check_task_status(response_data=response_data)
@@ -322,7 +334,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
         }
         """
         try:
-            response_data = raw_response.json()
+            response_data: _RunwayMLTask = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error transforming image generation response: {e}",
@@ -382,7 +394,7 @@ class RunwayMLImageGenerationConfig(BaseImageGenerationConfig):
         We need to poll the task until it completes (status SUCCEEDED) using async polling.
         """
         try:
-            response_data = raw_response.json()
+            response_data: _RunwayMLTask = raw_response.json()
         except Exception as e:
             raise self.get_error_class(
                 error_message=f"Error transforming image generation response: {e}",
diff --git a/litellm/llms/sap/credentials.py b/litellm/llms/sap/credentials.py
index d7743d4d337..a2a93b6114a 100644
--- a/litellm/llms/sap/credentials.py
+++ b/litellm/llms/sap/credentials.py
@@ -8,9 +8,10 @@ from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
 from threading import Lock
-from typing import Any, Final
+from typing import Any, Final, Protocol
 
 import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -33,8 +34,8 @@ def _get_home() -> str:
     return os.getenv(HOME_PATH_ENV_VAR, DEFAULT_HOME_PATH)
 
 
-def _get_nested(d: dict[str, Any] | str, path: Sequence[str]) -> Any:
-    cur: Any = d
+def _get_nested(d: object, path: Sequence[str]) -> object:
+    cur: object = d
     if isinstance(cur, str):
         # This shouldn't happen if service keys are pre-parsed correctly
         try:
@@ -54,7 +55,7 @@ def _get_nested(d: dict[str, Any] | str, path: Sequence[str]) -> Any:
     return cur
 
 
-def _load_json_env(var_name: str) -> dict[str, Any] | None:
+def _load_json_env(var_name: str) -> dict[str, object] | None:
     raw: Final = os.environ.get(var_name)
     if not raw:
         return None
@@ -64,7 +65,7 @@ def _load_json_env(var_name: str) -> dict[str, Any] | None:
         return None
 
 
-def _str_or_none(value) -> str | None:
+def _str_or_none(value: object) -> str | None:
     try:
         return str(value) if value is not None else None
     except Exception:
@@ -124,7 +125,7 @@ CREDENTIAL_VALUES: Final[list[CredentialsValue]] = [
 ]
 
 
-def init_conf(profile: str | None = None) -> dict[str, Any]:
+def init_conf(profile: str | None = None) -> dict[str, object]:
     """
     Loads config JSON from:
       1) $AICORE_CONFIG if set, otherwise
@@ -191,7 +192,7 @@ def resolve_resource_group(sources: list[Source]) -> str | None:
 
 def _parse_service_key_once(
     service_key: str | dict | None,
-) -> dict[str, Any] | None:
+) -> dict[str, object] | None:
     """
     Pre-parse service_key if it's a string to avoid repeated JSON parsing.
 
@@ -348,8 +349,33 @@ def validate_credentials(
         )
 
 
+class _TokenBody(TypedDict):
+    """Decoded body of the SAP AI Core OAuth2 token response."""
+
+    access_token: ReadOnly[str]
+    expires_in: ReadOnly[NotRequired[int]]
+
+
+class _TokenResponse(Protocol):
+    """The token endpoint's HTTP response, read for the decoded token body it carries."""
+
+    def json(self) -> _TokenBody: ...
+
+
+def _bearer_token_and_expiry(response: _TokenResponse) -> tuple[str, datetime]:
+    """Read a token response into the Authorization header value and the token's absolute expiry."""
+    payload: Final = response.json()
+    expires_in: Final = int(payload.get("expires_in", 3600))
+    access_token: Final = payload["access_token"]
+    return f"Bearer {access_token}", datetime.now(timezone.utc) + timedelta(seconds=expires_in)
+
+
 def _request_token(
-    client_id: str, auth_url: str, timeout: float, cert_pair=None, client_secret=None
+    client_id: str,
+    auth_url: str,
+    timeout: float,
+    cert_pair: tuple[str, str] | None = None,
+    client_secret: str | None = None,
 ) -> tuple[str, datetime]:
     data: Final = {"grant_type": "client_credentials", "client_id": client_id}
     if client_secret:
@@ -361,15 +387,10 @@ def _request_token(
             with httpx.Client(cert=cert_pair) as raw_client:
                 handler = HTTPHandler(client=raw_client)
                 resp = handler.post(auth_url, data=data, timeout=timeout)
-                payload = resp.json()
-        else:
-            handler = _get_httpx_client()
-            resp = handler.post(auth_url, data=data, timeout=timeout)
-            payload = resp.json()
-        access_token: Final = payload["access_token"]
-        expires_in: Final = int(payload.get("expires_in", 3600))
-        expiry_date: Final = datetime.now(timezone.utc) + timedelta(seconds=expires_in)
-        return f"Bearer {access_token}", expiry_date
+                return _bearer_token_and_expiry(resp)
+        handler = _get_httpx_client()
+        resp = handler.post(auth_url, data=data, timeout=timeout)
+        return _bearer_token_and_expiry(resp)
     except Exception as e:
         msg: Final = resp.text if resp is not None else getattr(e, "text", str(e))
         raise RuntimeError(f"Token request failed: {msg}") from e
diff --git a/litellm/llms/vertex_ai/files/transformation.py b/litellm/llms/vertex_ai/files/transformation.py
index b7f91bfba0d..b6ad9fbcc04 100644
--- a/litellm/llms/vertex_ai/files/transformation.py
+++ b/litellm/llms/vertex_ai/files/transformation.py
@@ -12,7 +12,7 @@ from urllib.parse import quote, unquote
 import httpx
 from httpx import Headers, Response
 from openai.types.file_deleted import FileDeleted
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, Required
 
 import litellm
 from litellm._uuid import uuid
@@ -104,6 +104,27 @@ class _VertexBatchRow(TypedDict, total=False):
     processed_time: ReadOnly[str]
 
 
+class _VertexEmbeddingVector(TypedDict):
+    values: ReadOnly[list[float]]
+
+
+class _VertexEmbeddingUsageMetadata(TypedDict, total=False):
+    promptTokenCount: ReadOnly[int]
+
+
+class _VertexEmbeddingResponse(TypedDict, total=False):
+    embedding: ReadOnly[Required[_VertexEmbeddingVector]]
+    usageMetadata: ReadOnly[_VertexEmbeddingUsageMetadata]
+    tokenCount: ReadOnly[int]
+
+
+class _VertexEmbeddingBatchRow(TypedDict, total=False):
+    key: ReadOnly[str]
+    request: ReadOnly[Mapping[str, object]]
+    status: ReadOnly[Required[str]]
+    response: ReadOnly[Required[_VertexEmbeddingResponse]]
+
+
 class _OpenAIBatchOutputError(TypedDict):
     code: ReadOnly[str]
     message: ReadOnly[str]
@@ -111,7 +132,7 @@ class _OpenAIBatchOutputError(TypedDict):
 
 class _OpenAIBatchOutputResponse(TypedDict):
     status_code: ReadOnly[int]
-    request_id: ReadOnly[str]
+    request_id: ReadOnly[object]
     body: ReadOnly[Mapping[str, object]]
 
 
@@ -218,7 +239,7 @@ def _get_litellm_batch_custom_id_from_labels(labels: Mapping[str, object] | None
     return str(labels.get("litellm_custom_id", "unknown"))
 
 
-def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, Any]) -> bool:
+def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, object]) -> bool:
     """
     Whether a Vertex batch output row came from an `EmbedContentRequest`.
 
@@ -237,7 +258,7 @@ def _is_vertex_embeddings_batch_output_row(vertex_output_row: Mapping[str, Any])
 
 def _openai_batch_output_row(
     custom_id: str,
-    body: Mapping[str, Any] | None = None,
+    body: Mapping[str, object] | None = None,
     error_code: str | None = None,
     error_message: str = "",
 ) -> _OpenAIBatchOutputRow:
@@ -259,7 +280,7 @@ def _openai_batch_output_row(
     }
 
 
-def _split_vertex_batch_key(vertex_output_row: Mapping[str, Any]) -> tuple[str, int, int]:
+def _split_vertex_batch_key(vertex_output_row: Mapping[str, object]) -> tuple[str, int, int]:
     """
     Resolve `(custom_id, index within that custom_id, group size)` for a Vertex batch
     output row.
@@ -278,7 +299,7 @@ def _split_vertex_batch_key(vertex_output_row: Mapping[str, Any]) -> tuple[str,
     return unquote(match["custom_id"]), int(match["index"]), int(match["total"])
 
 
-def _embedding_prompt_token_count(vertex_response: Mapping[str, Any]) -> int:
+def _embedding_prompt_token_count(vertex_response: _VertexEmbeddingResponse) -> int:
     """
     Prompt tokens billed for one Vertex Gemini Embedding batch row.
 
@@ -293,7 +314,7 @@ def _embedding_prompt_token_count(vertex_response: Mapping[str, Any]) -> int:
 
 def _vertex_embeddings_rows_to_openai_batch_output_row(
     custom_id: str,
-    vertex_output_rows: tuple[Mapping[str, Any], ...],
+    vertex_output_rows: tuple[_VertexEmbeddingBatchRow, ...],
     element_indices: tuple[int, ...],
     element_count: int,
     model: str | None,
@@ -348,7 +369,7 @@ def _vertex_embeddings_rows_to_openai_batch_output_row(
 
 
 def _transform_vertex_embeddings_batch_output_to_openai(
-    vertex_output_rows: Iterable[Mapping[str, Any]],
+    vertex_output_rows: Iterable[_VertexEmbeddingBatchRow],
     model: str | None,
 ) -> tuple[_OpenAIBatchOutputRow, ...]:
     """
@@ -388,7 +409,7 @@ def _model_from_managed_gcs_url(url: str) -> str | None:
     return match.group(1) if match else None
 
 
-def _is_embeddings_batch_entry(openai_entry: Mapping[str, Any]) -> bool:
+def _is_embeddings_batch_entry(openai_entry: Mapping[str, object]) -> bool:
     """
     Whether an OpenAI batch JSONL line targets the embeddings endpoint.
 
@@ -431,7 +452,7 @@ def _vertex_batch_embeddings_key(custom_id: str, index: int, total: int) -> str:
     return encoded_custom_id if total < 2 else f"{encoded_custom_id}#{index}/{total}"
 
 
-def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str, Any]) -> Mapping[str, Any]:
+def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str, object]) -> Mapping[str, object]:
     """
     One Vertex Gemini Embedding batch input row.
 
@@ -453,8 +474,8 @@ def _vertex_embeddings_row(key: str | None, embed_content_request: Mapping[str,
 
 
 def _openai_batch_jsonl_entry_to_vertex_embeddings_rows(
-    openai_entry: Mapping[str, Any],
-) -> tuple[Mapping[str, Any], ...]:
+    openai_entry: Mapping[str, object],
+) -> tuple[Mapping[str, object], ...]:
     """
     Transforms a single OpenAI `/v1/embeddings` batch entry into Vertex Gemini Embedding
     batch rows, one per requested embedding.
@@ -512,7 +533,7 @@ def _openai_batch_jsonl_entry_to_vertex_embeddings_rows(
 def _openai_batch_jsonl_entry_to_vertex_rows(
     openai_entry: dict[str, Any],
     map_openai_to_vertex_params: Callable[[dict[str, Any]], dict[str, Any]],
-) -> tuple[Mapping[str, Any], ...]:
+) -> tuple[Mapping[str, object], ...]:
     """
     Transforms a single OpenAI JSONL batch entry into the Vertex rows it maps to.
 
@@ -533,7 +554,7 @@ def _openai_batch_jsonl_entry_to_vertex_rows(
         cached_content=None,
     )
 
-    custom_id: Final = openai_entry.get("custom_id")
+    custom_id: Final[object] = openai_entry.get("custom_id")
     if custom_id is not None:
         if "labels" not in vertex_request_body:
             vertex_request_body["labels"] = {}
diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py
index 11c026010ee..e2d62be6a69 100644
--- a/litellm/llms/vertex_ai/gemini/transformation.py
+++ b/litellm/llms/vertex_ai/gemini/transformation.py
@@ -250,7 +250,7 @@ def _gs_uri_requires_content_type_metadata(url: str) -> bool:
 
 
 def _image_url_payload_may_need_sync_gcs_metadata_fetch(
-    raw_image_url: Any,
+    raw_image_url: object,
 ) -> bool:
     """
     True when this image_url value (content-part image_url or assistant ``images[]``
@@ -326,7 +326,7 @@ def _openai_messages_may_need_sync_gcs_metadata_fetch(
 def _get_gcs_object_content_type(
     image_url: str,
     vertex_project: str | None = None,
-    vertex_credentials: Any | None = None,
+    vertex_credentials: object = None,
 ) -> str | None:
     """
     Resolve content type from GCS object metadata.
@@ -479,7 +479,7 @@ def _process_gemini_media(
     model: str | None = None,
     video_metadata: dict[str, Any] | None = None,
     vertex_project: str | None = None,
-    vertex_credentials: Any | None = None,
+    vertex_credentials: object = None,
 ) -> PartType:
     """
     Given a media URL (image, audio, or video), return the appropriate PartType for Gemini
@@ -1002,7 +1002,7 @@ def _gemini_convert_messages_with_history(
                     if isinstance(_ss_invocations, list):
                         for invocation in _ss_invocations:
                             # Re-inject toolCall part
-                            tc_part: dict[str, Any] = {
+                            tc_part: dict[str, object] = {
                                 "toolCall": {
                                     "toolType": invocation.get("tool_type"),
                                     "id": invocation.get("id"),
@@ -1015,13 +1015,13 @@ def _gemini_convert_messages_with_history(
 
                             # Re-inject toolResponse part if response is present
                             if "response" in invocation:
-                                tr_dict: dict[str, Any] = {
+                                tr_dict: dict[str, object] = {
                                     "id": invocation.get("id"),
                                     "response": invocation.get("response"),
                                 }
                                 if invocation.get("tool_type"):
                                     tr_dict["toolType"] = invocation["tool_type"]
-                                tr_part: dict[str, Any] = {"toolResponse": tr_dict}
+                                tr_part: dict[str, object] = {"toolResponse": tr_dict}
                                 if "response_thought_signature" in invocation:
                                     tr_part["thoughtSignature"] = invocation["response_thought_signature"]
                                 assistant_content.append(tr_part)
@@ -1090,7 +1090,7 @@ def _pop_and_merge_extra_body(data: RequestBody, optional_params: dict) -> None:
                 data_dict[k] = v
 
 
-def _has_google_maps_tool(tools: Any | None) -> bool:
+def _has_google_maps_tool(tools: object) -> bool:
     """Return True if any tool object in the list has a 'googleMaps' key."""
     if not isinstance(tools, list):
         return False
@@ -1127,7 +1127,7 @@ def _rewrite_mime_type_to_response_format(generation_config: GenerationConfig) -
         schema = generation_config.pop("response_schema", None)
     generation_config.pop("response_mime_type", None)
 
-    response_format: Final[dict[str, Any]] = {"text": {"mimeType": "APPLICATION_JSON"}}
+    response_format: Final[dict[str, dict[str, object]]] = {"text": {"mimeType": "APPLICATION_JSON"}}
     if schema is not None:
         response_format["text"]["schema"] = schema
     generation_config["responseFormat"] = response_format
@@ -1316,7 +1316,7 @@ async def async_transform_request_body(
     timeout: float | httpx.Timeout | None,
     extra_headers: dict | None,
     optional_params: dict,
-    logging_obj: litellm.litellm_core_utils.litellm_logging.Logging,
+    logging_obj: LiteLLMLoggingObj,
     custom_llm_provider: Literal["vertex_ai", "vertex_ai_beta", "gemini"],
     litellm_params: dict,
     vertex_project: str | None,
diff --git a/litellm/llms/vertex_ai/vertex_llm_base.py b/litellm/llms/vertex_ai/vertex_llm_base.py
index aca257dc095..1942bc850f1 100644
--- a/litellm/llms/vertex_ai/vertex_llm_base.py
+++ b/litellm/llms/vertex_ai/vertex_llm_base.py
@@ -9,7 +9,7 @@ import json
 import os
 import threading
 from collections.abc import Mapping
-from typing import TYPE_CHECKING, Any, Final, Literal
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol
 from urllib.parse import urlparse
 
 import litellm
@@ -47,6 +47,21 @@ else:
     GoogleCredentialsObject = Any
 
 
+class _VertexCredentialsObject(Protocol):
+    """Structural view of the google-auth credentials handle that this class caches and refreshes."""
+
+    @property
+    def token(self) -> object: ...
+
+    @property
+    def quota_project_id(self) -> str | None: ...
+
+    @property
+    def expired(self) -> object: ...
+
+    def refresh(self, request: object) -> None: ...
+
+
 class VertexBase:
     def __init__(self) -> None:
         super().__init__()
@@ -55,7 +70,7 @@ class VertexBase:
         self._credentials: GoogleCredentialsObject | None = None
         self._credentials_project_mapping: dict[
             tuple[VERTEX_CREDENTIALS_TYPES | None, str | None],
-            tuple[GoogleCredentialsObject, str | None],
+            tuple[_VertexCredentialsObject, str | None],
         ] = {}
         self.project_id: str | None = None
         self.async_handler: AsyncHTTPHandler | None = None
@@ -109,7 +124,7 @@ class VertexBase:
         self,
         credentials: VERTEX_CREDENTIALS_TYPES | None,
         project_id: str | None,
-    ) -> tuple[Any, str]:
+    ) -> tuple[_VertexCredentialsObject | None, str]:
         if credentials is not None:
             if isinstance(credentials, str):
                 _is_path: Final = os.path.exists(
@@ -209,7 +224,7 @@ class VertexBase:
         return creds, project_id
 
     # Google Auth Helpers -- extracted for mocking purposes in tests
-    def _credentials_from_identity_pool(self, json_obj, scopes):
+    def _credentials_from_identity_pool(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import identity_pool
         except ImportError:
@@ -220,7 +235,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_pluggable(self, json_obj, scopes):
+    def _credentials_from_pluggable(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import pluggable
         except ImportError:
@@ -231,7 +246,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_identity_pool_with_aws(self, json_obj, scopes):
+    def _credentials_from_identity_pool_with_aws(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             from google.auth import aws
         except ImportError:
@@ -242,7 +257,7 @@ class VertexBase:
             creds = creds.with_scopes(scopes)
         return creds
 
-    def _credentials_from_authorized_user(self, json_obj, scopes):
+    def _credentials_from_authorized_user(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             import google.oauth2.credentials
         except ImportError:
@@ -250,7 +265,7 @@ class VertexBase:
 
         return google.oauth2.credentials.Credentials.from_authorized_user_info(json_obj, scopes=scopes)
 
-    def _credentials_from_service_account(self, json_obj, scopes):
+    def _credentials_from_service_account(self, json_obj, scopes) -> _VertexCredentialsObject:
         try:
             import google.oauth2.service_account
         except ImportError:
@@ -258,7 +273,7 @@ class VertexBase:
 
         return google.oauth2.service_account.Credentials.from_service_account_info(json_obj, scopes=scopes)
 
-    def _credentials_from_default_auth(self, scopes):
+    def _credentials_from_default_auth(self, scopes) -> tuple[_VertexCredentialsObject, str | None]:
         try:
             import google.auth as google_auth
         except ImportError:
@@ -350,7 +365,7 @@ class VertexBase:
         )
         return api_base
 
-    def refresh_auth(self, credentials: Any) -> None:
+    def refresh_auth(self, credentials: _VertexCredentialsObject) -> None:
         try:
             from google.auth.transport.requests import (
                 Request,
@@ -426,7 +441,7 @@ class VertexBase:
         self,
         credential_cache_key: tuple,
         project_id: str | None,
-    ) -> tuple[str, str, "TokenState", Any, str | None] | None:
+    ) -> tuple[str, str, "TokenState", _VertexCredentialsObject, str | None] | None:
         """
         Look up cached credentials and return usable token info for FRESH or
         STALE tokens (both are still valid for outbound requests). STALE
@@ -449,7 +464,9 @@ class VertexBase:
             return None
         return creds.token, resolved_project, token_state, creds, cached_project_id
 
-    def _unpack_cached_credentials(self, credential_cache_key: tuple) -> tuple[Any, str | None]:
+    def _unpack_cached_credentials(
+        self, credential_cache_key: tuple
+    ) -> tuple[_VertexCredentialsObject | None, str | None]:
         """
         Return (credentials, project_id) from the cache, or (None, None) if
         not cached. Handles both tuple and legacy cache formats.
@@ -461,7 +478,7 @@ class VertexBase:
             return cached_entry
         return cached_entry, cached_entry.quota_project_id or getattr(cached_entry, "project_id", None)
 
-    def _get_token_state(self, credentials: Any) -> "TokenState":
+    def _get_token_state(self, credentials: _VertexCredentialsObject) -> "TokenState":
         """
         Return the token state using google-auth's TokenState enum.
 
@@ -485,7 +502,7 @@ class VertexBase:
         credentials: VERTEX_CREDENTIALS_TYPES | None,
         project_id: str | None,
         credential_cache_key: tuple,
-    ) -> tuple[Any, str | None]:
+    ) -> tuple[_VertexCredentialsObject, str | None]:
         """Load credentials via load_auth (in thread) and cache the result."""
         try:
             _credentials, credential_project_id = await asyncify(self.load_auth)(
@@ -505,7 +522,7 @@ class VertexBase:
 
     async def _background_refresh_credentials(
         self,
-        credentials: Any,
+        credentials: _VertexCredentialsObject,
         credential_cache_key: tuple,
         credential_project_id: str | None,
     ) -> None:
@@ -557,7 +574,7 @@ class VertexBase:
 
     def _schedule_background_refresh(
         self,
-        credentials: Any,
+        credentials: _VertexCredentialsObject,
         credential_cache_key: tuple,
         credential_project_id: str | None,
     ) -> None:
@@ -575,7 +592,7 @@ class VertexBase:
             self._background_refresh_credentials(credentials, credential_cache_key, credential_project_id)
         )
 
-        def _drop_background_refresh_task(_fut: asyncio.Future[Any]) -> None:
+        def _drop_background_refresh_task(_fut: asyncio.Future[None]) -> None:
             if self._background_refresh_tasks.get(credential_cache_key) is _fut:
                 self._background_refresh_tasks.pop(credential_cache_key, None)
 
@@ -888,7 +905,7 @@ class VertexBase:
         # Convert dict credentials to string for caching
         cache_credentials: Final = json.dumps(credentials) if isinstance(credentials, dict) else credentials
         credential_cache_key: Final = (cache_credentials, project_id)
-        _credentials: GoogleCredentialsObject | None = None
+        _credentials: _VertexCredentialsObject | None = None
 
         verbose_logger.debug("Checking cached credentials for project_id: %s", project_id)
 
diff --git a/litellm/passthrough/main.py b/litellm/passthrough/main.py
index 9095cee15a9..c4bd03fb1c3 100644
--- a/litellm/passthrough/main.py
+++ b/litellm/passthrough/main.py
@@ -6,7 +6,7 @@ from __future__ import annotations
 
 import asyncio
 import contextvars
-from collections.abc import AsyncGenerator, AsyncIterator, Coroutine, Generator, Iterator
+from collections.abc import AsyncGenerator, AsyncIterator, Awaitable, Coroutine, Generator, Iterator
 from functools import partial
 from types import TracebackType
 from typing import Any, Final, cast
@@ -27,19 +27,19 @@ base_llm_http_handler = BaseLLMHTTPHandler()
 from .utils import BasePassthroughUtils
 
 
-async def _as_async_generator(iterable: AsyncIterator[bytes]) -> AsyncGenerator[bytes, Any]:
+async def _as_async_generator(iterable: AsyncIterator[bytes]) -> AsyncGenerator[bytes, bytes]:
     async for chunk in iterable:
         yield chunk
 
 
-def _as_generator(iterable: Iterator[bytes]) -> Generator[bytes, Any, Any]:
+def _as_generator(iterable: Iterator[bytes]) -> Generator[bytes, bytes, None]:
     yield from iterable
 
 
-class AsyncPassthroughStreamingResponse(AsyncGenerator[Any, Any]):
+class AsyncPassthroughStreamingResponse(AsyncGenerator[bytes, bytes]):
     def __init__(
         self,
-        response: Coroutine[Any, Any, httpx.Response],
+        response: Awaitable[httpx.Response],
         litellm_logging_obj: LiteLLMLoggingObj,
         provider_config: BasePassthroughConfig,
     ) -> None:
@@ -48,7 +48,7 @@ class AsyncPassthroughStreamingResponse(AsyncGenerator[Any, Any]):
         self._headers = httpx.Headers()
         self._response_coro = response
         self._response: httpx.Response
-        self._iterator: AsyncGenerator[bytes, Any]
+        self._iterator: AsyncGenerator[bytes, bytes]
         self._litellm_logging_obj = litellm_logging_obj
         self._provider_config = provider_config
         self._raw_bytes: list[bytes] = []  # mutable-ok: instance buffer for streaming chunks
@@ -172,7 +172,7 @@ class AsyncPassthroughStreamingResponse(AsyncGenerator[Any, Any]):
             pass
 
 
-class PassthroughStreamingResponse(Generator[Any, Any, Any]):
+class PassthroughStreamingResponse(Generator[bytes, bytes, None]):
     def __init__(
         self,
         response: httpx.Response,
@@ -184,7 +184,7 @@ class PassthroughStreamingResponse(Generator[Any, Any, Any]):
         self.status_code = response.status_code
         self._litellm_logging_obj = litellm_logging_obj
         self._provider_config = provider_config
-        self._iterator: Generator[bytes, Any, Any] = _as_generator(response.iter_bytes())
+        self._iterator: Generator[bytes, bytes, None] = _as_generator(response.iter_bytes())
         self._raw_bytes: list[bytes] = []  # mutable-ok: instance buffer for streaming chunks
         self._flush_scheduled = False
 
@@ -263,7 +263,7 @@ async def allm_passthrough_route(
     cookies: CookieTypes | None = None,
     client: HTTPHandler | AsyncHTTPHandler | None = None,
     **kwargs,
-) -> httpx.Response | AsyncGenerator[Any, Any]:
+) -> httpx.Response | AsyncGenerator[bytes, bytes]:
     """
     Async: Reranks a list of documents based on their relevance to the query
     """
@@ -390,10 +390,10 @@ def llm_passthrough_route(
     **kwargs,
 ) -> (
     httpx.Response
-    | Coroutine[Any, Any, httpx.Response]
-    | Coroutine[Any, Any, httpx.Response | AsyncGenerator[Any, Any]]
-    | Generator[Any, Any, Any]
-    | AsyncGenerator[Any, Any]
+    | Coroutine[object, object, httpx.Response]
+    | Coroutine[object, object, httpx.Response | AsyncGenerator[bytes, bytes]]
+    | Generator[bytes, bytes, None]
+    | AsyncGenerator[bytes, bytes]
 ):
     """
     Pass through requests to the LLM APIs.
@@ -592,7 +592,7 @@ async def _async_passthrough_request(
     is_streaming_request: bool,
     litellm_logging_obj: LiteLLMLoggingObj,
     provider_config: BasePassthroughConfig,
-) -> httpx.Response | AsyncGenerator[Any, Any]:
+) -> httpx.Response | AsyncGenerator[bytes, bytes]:
     """
     Handle async passthrough requests.
     Uses async client to send request and properly handles streaming.
diff --git a/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py b/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
index 7ec0f4b5192..dcf1b01bc25 100644
--- a/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
+++ b/litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py
@@ -5,6 +5,7 @@ Filters MCP tools semantically for /chat/completions and /responses endpoints.
 """
 
 import asyncio
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final
 
 from litellm._logging import verbose_logger
@@ -74,7 +75,7 @@ class SemanticMCPToolFilter:
         self.router_instance = litellm_router_instance
         self.tool_router: SemanticRouter | None = None
         self.context_window_error: str | None = None
-        self._tool_map: dict[str, Any] = {}  # MCPTool objects or OpenAI function dicts
+        self._tool_map: dict[str, object] = {}  # MCPTool objects or OpenAI function dicts
         self._index_sync_lock = asyncio.Lock()
 
     async def build_router_from_mcp_registry(self) -> None:
@@ -182,11 +183,11 @@ class SemanticMCPToolFilter:
                 return
             raise
 
-    def _has_tools_missing_from_index(self, tools: list[Any]) -> bool:
+    def _has_tools_missing_from_index(self, tools: Sequence[object]) -> bool:
         """Allocation-free check for any named tool not yet in the semantic index."""
         return any(name and name not in self._tool_map for name in (self._extract_tool_info(t)[0] for t in tools))
 
-    def _tools_missing_from_index(self, tools: list[Any]) -> dict[str, Any]:
+    def _tools_missing_from_index(self, tools: Sequence[object]) -> Mapping[str, object]:
         """Map name -> tool for every named tool not yet in the semantic index."""
         return {
             name: tool
@@ -194,7 +195,7 @@ class SemanticMCPToolFilter:
             if name and name not in self._tool_map
         }
 
-    async def _ensure_tools_indexed(self, available_tools: list[Any]) -> None:
+    async def _ensure_tools_indexed(self, available_tools: Sequence[object]) -> None:
         """
         Index request-time tools the startup build never saw.
 
@@ -385,7 +386,7 @@ class SemanticMCPToolFilter:
         separator: Final = client_name[-len(canonical) - 1]
         return separator in ("_", "-")
 
-    def _get_tools_by_names(self, tool_names: list[str], available_tools: list[Any]) -> list[Any]:
+    def _get_tools_by_names(self, tool_names: Sequence[str], available_tools: Sequence[object]) -> list[object]:
         """
         Get tools from available_tools by their names, preserving the
         semantic router's ordering.
@@ -401,14 +402,14 @@ class SemanticMCPToolFilter:
         # Exact matches win over suffix matches when both are present, and
         # each incoming tool is returned at most once even if two canonical
         # names happen to be tail-compatible with the same incoming name.
-        available_by_name: Final[dict[str, Any]] = {}
+        available_by_name: Final[dict[str, object]] = {}
         for tool in available_tools:
             client_name, _ = self._extract_tool_info(tool)
             if client_name and client_name not in available_by_name:
                 available_by_name[client_name] = tool
 
-        matched: Final[list[Any]] = []
-        used_ids: Final[set] = set()
+        matched: Final[list[object]] = []
+        used_ids: Final[set[int]] = set()
         for canonical in tool_names:
             tool = available_by_name.get(canonical)
             if tool is None:
@@ -430,7 +431,7 @@ class SemanticMCPToolFilter:
                 used_ids.add(id(tool))
         return matched
 
-    def extract_user_query(self, messages: list[dict[str, Any]]) -> str:
+    def extract_user_query(self, messages: Sequence[Mapping[str, object]]) -> str:
         """
         Extract user query from messages for /chat/completions or /responses.
 
diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py
index bd02cfdf907..31b05320cd3 100644
--- a/litellm/proxy/agent_endpoints/a2a_endpoints.py
+++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py
@@ -14,7 +14,7 @@ import json
 from collections.abc import AsyncGenerator, Mapping
 from copy import deepcopy
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 from urllib.parse import urlparse
 
 from fastapi import APIRouter, Depends, HTTPException, Request, Response
@@ -215,11 +215,20 @@ def _enforce_inbound_trace_id(agent: "AgentResponse", request: Request) -> None:
         )
 
 
+class _JsonRpcResponse(Protocol):
+    def json(self) -> dict[str, object]: ...
+
+
+def _jsonrpc_body(response: _JsonRpcResponse) -> dict[str, object]:
+    """The decoded JSON-RPC body of ``response``."""
+    return response.json()
+
+
 async def _forward_jsonrpc(
     agent_url: str,
     body: dict[str, object],
     extra_headers: Mapping[str, str] | None = None,
-) -> dict[str, Any]:
+) -> dict[str, object]:
     from litellm.llms.custom_httpx.http_handler import get_async_httpx_client
     from litellm.types.llms.custom_http import httpxSpecialProvider
 
@@ -230,7 +239,7 @@ async def _forward_jsonrpc(
     )
     resp: Final = await handler.post(agent_url, json=body, headers=headers)
     try:
-        result: Final = resp.json()
+        result: Final = _jsonrpc_body(resp)
     except Exception:
         resp.raise_for_status()
         raise
@@ -940,8 +949,8 @@ async def invoke_agent_a2a(
             )
             result = await _forward_jsonrpc(agent_url, forward_body, extra_headers=caller_headers)
             if method == "agent/getAuthenticatedExtendedCard":
-                if isinstance(result.get("result"), dict):
-                    card: Final = result["result"]
+                card: Final = result.get("result")
+                if isinstance(card, dict):
                     proxy_url: Final = get_custom_url(str(request.base_url), route=f"a2a/{agent_id}")
                     # Rewrite the upstream agent URL in both 0.3 (top-level `url`)
                     # and 1.0 (`supportedInterfaces[0].url`) wire formats so that
diff --git a/litellm/proxy/auth/handle_jwt.py b/litellm/proxy/auth/handle_jwt.py
index 39e6ca9a369..0795cee7409 100644
--- a/litellm/proxy/auth/handle_jwt.py
+++ b/litellm/proxy/auth/handle_jwt.py
@@ -14,8 +14,8 @@ import hashlib
 import os
 import re
 import time
-from collections.abc import Awaitable, Callable
-from typing import Any, Final, Literal, NoReturn, TypeVar, cast
+from collections.abc import Awaitable, Callable, Sequence
+from typing import Any, Final, Literal, NoReturn, Protocol, TypeVar, cast
 
 import httpx
 import jwt
@@ -24,6 +24,7 @@ from cryptography.hazmat.backends import default_backend
 from cryptography.hazmat.primitives import serialization
 from fastapi import HTTPException, status
 from jwt.api_jwk import PyJWK
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.litellm_core_utils.dot_notation_indexing import get_nested_value
@@ -93,6 +94,47 @@ UNREACHABLE_CACHE_KEY_PREFIX: Final = "litellm_jwks_unreachable_"
 _CachedValueT = TypeVar("_CachedValueT", bound=JWKKeyValue | str)
 
 
+class _JWTAuthSettings(Protocol):
+    """The JWT auth settings block this handler reads back through ``getattr``, when one is configured."""
+
+    @property
+    def issuers(self) -> Sequence[JWTIssuerConfig] | None: ...
+
+    @property
+    def public_key_ttl(self) -> float: ...
+
+    @property
+    def public_key_stale_ttl(self) -> float: ...
+
+
+class _OIDCDiscoveryBody(TypedDict, total=False):
+    """Decoded OIDC discovery document, read for the JWKS endpoint it advertises."""
+
+    jwks_uri: ReadOnly[str]
+
+
+class _OIDCDiscoveryResponse(Protocol):
+    """The discovery endpoint's HTTP response, read for the decoded document it carries."""
+
+    def json(self) -> _OIDCDiscoveryBody: ...
+
+
+class _UserInfoResponse(Protocol):
+    """The OIDC UserInfo endpoint's HTTP response, read for the identity document it carries."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _discovery_document(response: _OIDCDiscoveryResponse) -> _OIDCDiscoveryBody:
+    """Decode an OIDC discovery response body."""
+    return response.json()
+
+
+def _userinfo_document(response: _UserInfoResponse) -> dict[str, object]:
+    """Decode an OIDC UserInfo response body into its JSON object form."""
+    return response.json()
+
+
 def jwks_unavailable_exception(error: JWKSUnreachableError) -> ProxyException:
     return ProxyException(
         message=(
@@ -794,7 +836,7 @@ class JWTHandler:
                 f"JWT Auth: OIDC discovery endpoint {url} returned status {response.status_code}: {response.text}"
             )
         try:
-            discovery: Final = response.json()
+            discovery: Final = _discovery_document(response)
         except Exception as e:
             raise Exception(f"JWT Auth: Failed to parse OIDC discovery document at {url}: {e}")
 
@@ -806,13 +848,13 @@ class JWTHandler:
         return jwks_uri
 
     def _get_public_key_cache_ttl(self) -> float:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return 600
         return litellm_jwtauth.public_key_ttl
 
     def _get_public_key_stale_ttl(self) -> float:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return DEFAULT_JWKS_STALE_TTL
         return litellm_jwtauth.public_key_stale_ttl
@@ -938,7 +980,7 @@ class JWTHandler:
             if response.status_code != 200:
                 raise Exception(f"OIDC UserInfo endpoint returned status {response.status_code}: {response.text}")
 
-            userinfo: Final = response.json()
+            userinfo: Final = _userinfo_document(response)
             verbose_proxy_logger.debug("Received OIDC UserInfo: %s", userinfo)
 
             # Cache the userinfo response
@@ -996,7 +1038,7 @@ class JWTHandler:
         }
 
     def _get_configured_issuer(self, token: str) -> JWTIssuerConfig | None:
-        litellm_jwtauth: Final = getattr(self, "litellm_jwtauth", None)
+        litellm_jwtauth: Final[_JWTAuthSettings | None] = getattr(self, "litellm_jwtauth", None)
         if litellm_jwtauth is None:
             return None
 
diff --git a/litellm/proxy/common_utils/debug_utils.py b/litellm/proxy/common_utils/debug_utils.py
index 3a1d18b48cc..554a6ae8d1a 100644
--- a/litellm/proxy/common_utils/debug_utils.py
+++ b/litellm/proxy/common_utils/debug_utils.py
@@ -6,9 +6,11 @@ import os
 import sys
 import tracemalloc
 from collections import Counter
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, NamedTuple, Protocol, TypedDict
 
 from fastapi import APIRouter, Depends, HTTPException, Query
+from typing_extensions import ReadOnly
 
 from litellm import get_secret_str
 from litellm._logging import verbose_proxy_logger
@@ -194,6 +196,42 @@ async def memory_usage_in_mem_cache_items(
     }
 
 
+class _ProcessMemoryInfo(Protocol):
+    """The resident and virtual sizes psutil reports for a process."""
+
+    @property
+    def rss(self) -> int: ...
+
+    @property
+    def vms(self) -> int: ...
+
+
+class _ProcessHandle(Protocol):
+    """The psutil process handle members this module reads."""
+
+    def memory_info(self) -> _ProcessMemoryInfo: ...
+
+    def memory_percent(self) -> float: ...
+
+
+class _ProcessMemoryUsage(NamedTuple):
+    """Memory usage of a single worker process."""
+
+    resident_megabytes: float
+    virtual_megabytes: float
+    percent: float
+
+
+def _process_memory_usage(process: _ProcessHandle) -> _ProcessMemoryUsage:
+    """Read resident/virtual megabytes and system memory share for ``process``."""
+    memory_info: Final = process.memory_info()
+    return _ProcessMemoryUsage(
+        resident_megabytes=memory_info.rss / (1024 * 1024),
+        virtual_megabytes=memory_info.vms / (1024 * 1024),
+        percent=process.memory_percent(),
+    )
+
+
 @router.get("/debug/memory/summary", include_in_schema=False)
 async def get_memory_summary(
     _: UserAPIKeyAuth = Depends(user_api_key_auth),
@@ -227,10 +265,9 @@ async def get_memory_summary(
     try:
         import psutil
 
-        process: Final = psutil.Process()
-        memory_info: Final = process.memory_info()
-        memory_mb: Final = memory_info.rss / (1024 * 1024)
-        memory_percent: Final = process.memory_percent()
+        usage: Final = _process_memory_usage(psutil.Process())
+        memory_mb: Final = usage.resident_megabytes
+        memory_percent: Final = usage.percent
 
         process_memory = {
             "summary": f"{memory_mb:.1f} MB ({memory_percent:.1f}% of system memory)",
@@ -252,7 +289,7 @@ async def get_memory_summary(
         process_memory["error"] = str(e)
 
     # Get cache information
-    caches: Final[dict[str, Any]] = {}
+    caches: Final[dict[str, object]] = {}
     total_cache_items = 0
 
     try:
@@ -313,7 +350,7 @@ async def get_memory_summary(
     }
 
 
-def _get_gc_statistics() -> dict[str, Any]:
+def _get_gc_statistics() -> Mapping[str, object]:
     """Get garbage collector statistics."""
     return {
         "enabled": gc.isenabled(),
@@ -341,30 +378,42 @@ def _get_gc_statistics() -> dict[str, Any]:
     }
 
 
-def _get_object_type_counts(top_n: int) -> tuple[int, list[dict[str, Any]]]:
+class _ObjectTypeCount(TypedDict):
+    """One row of the tracked-object histogram."""
+
+    type: ReadOnly[str]
+    count: ReadOnly[int]
+    count_readable: ReadOnly[str]
+
+
+def _type_name_counts(objects: Sequence[object]) -> Counter[str]:
+    """Count ``objects`` by the name of their type."""
+    return Counter(type(obj).__name__ for obj in objects)
+
+
+def _get_object_type_counts(top_n: int) -> tuple[int, list[_ObjectTypeCount]]:
     """Count objects by type and return total count and top N types."""
-    type_counts: Final[Counter] = Counter()
-    total_objects = 0
+    type_counts: Final = _type_name_counts(gc.get_objects())
 
-    for obj in gc.get_objects():
-        total_objects += 1
-        obj_type = type(obj).__name__
-        type_counts[obj_type] += 1
-
-    top_object_types: Final = [
+    top_object_types: Final[list[_ObjectTypeCount]] = [
         {"type": obj_type, "count": count, "count_readable": f"{count:,}"}
         for obj_type, count in type_counts.most_common(top_n)
     ]
 
-    return total_objects, top_object_types
+    return sum(type_counts.values()), top_object_types
 
 
-def _get_uncollectable_objects_info() -> dict[str, Any]:
+def _type_names(objects: Sequence[object]) -> Sequence[str]:
+    """The type name of each object in ``objects``."""
+    return [type(obj).__name__ for obj in objects]
+
+
+def _get_uncollectable_objects_info() -> Mapping[str, object]:
     """Get information about uncollectable objects (potential memory leaks)."""
     uncollectable: Final = gc.garbage
     return {
         "count": len(uncollectable),
-        "sample_types": [type(obj).__name__ for obj in uncollectable[:10]],
+        "sample_types": _type_names(uncollectable[:10]),
         "warning": (
             "If count > 0, you may have reference cycles preventing garbage collection"
             if len(uncollectable) > 0
@@ -373,9 +422,11 @@ def _get_uncollectable_objects_info() -> dict[str, Any]:
     }
 
 
-def _get_cache_memory_stats(user_api_key_cache, llm_router, proxy_logging_obj, redis_usage_cache) -> dict[str, Any]:
+def _get_cache_memory_stats(
+    user_api_key_cache, llm_router, proxy_logging_obj, redis_usage_cache
+) -> Mapping[str, object]:
     """Calculate memory usage for all caches."""
-    cache_stats: Final[dict[str, Any]] = {}
+    cache_stats: Final[dict[str, object]] = {}
     try:
         # User API key cache
         user_cache_size: Final = sys.getsizeof(user_api_key_cache.in_memory_cache.cache_dict)
@@ -439,9 +490,9 @@ def _get_cache_memory_stats(user_api_key_cache, llm_router, proxy_logging_obj, r
     return cache_stats
 
 
-def _get_router_memory_stats(llm_router) -> dict[str, Any]:
+def _get_router_memory_stats(llm_router) -> Mapping[str, object]:
     """Get memory usage statistics for LiteLLM router."""
-    litellm_router_memory: dict[str, Any] = {}
+    litellm_router_memory: dict[str, object] = {}
     try:
         if llm_router is not None:
             # Model list memory size
@@ -505,7 +556,7 @@ def _get_router_memory_stats(llm_router) -> dict[str, Any]:
     return litellm_router_memory
 
 
-def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> dict[str, Any] | None:
+def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> Mapping[str, object] | None:
     """Get process-level memory information using psutil."""
     if not include_process_info:
         return None
@@ -514,10 +565,10 @@ def _get_process_memory_info(worker_pid: int, include_process_info: bool) -> dic
         import psutil
 
         process: Final = psutil.Process()
-        memory_info: Final = process.memory_info()
-        ram_usage_mb: Final = round(memory_info.rss / (1024 * 1024), 2)
-        virtual_memory_mb: Final = round(memory_info.vms / (1024 * 1024), 2)
-        memory_percent: Final = round(process.memory_percent(), 2)
+        usage: Final = _process_memory_usage(process)
+        ram_usage_mb: Final = round(usage.resident_megabytes, 2)
+        virtual_memory_mb: Final = round(usage.virtual_megabytes, 2)
+        memory_percent: Final = round(usage.percent, 2)
 
         return {
             "pid": worker_pid,
diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py
index 202a95ba29b..e6880d521f1 100644
--- a/litellm/proxy/db/db_spend_update_writer.py
+++ b/litellm/proxy/db/db_spend_update_writer.py
@@ -211,7 +211,7 @@ class DBSpendUpdateWriter:
         org_id: str | None,
         # Completion object fields
         kwargs: dict | None,
-        completion_response: litellm.ModelResponse | Any | Exception | None,
+        completion_response: object,
         start_time: datetime | None,
         end_time: datetime | None,
         response_cost: float | None,
@@ -323,7 +323,7 @@ class DBSpendUpdateWriter:
     async def _enqueue_tool_usage_transaction(
         self,
         payload: SpendLogsPayload,
-        completion_response: "litellm.ModelResponse | Any | Exception | None",
+        completion_response: object,
         prisma_client: "PrismaClient | None",
         kwargs: "dict | None" = None,
     ) -> None:
@@ -396,7 +396,7 @@ class DBSpendUpdateWriter:
     def _enqueue_tool_registry_upsert(
         self,
         kwargs: dict | None,
-        completion_response: Any | None,
+        completion_response: object,
         hashed_token: str | None = None,
         team_id: str | None = None,
     ) -> None:
@@ -849,7 +849,7 @@ class DBSpendUpdateWriter:
                 return
 
             # Parse tags from JSON string
-            tags = []
+            tags: Sequence[object] = []
             if isinstance(request_tags, str):
                 tags = safe_json_loads(request_tags, default=[])
                 if not tags:
@@ -2260,7 +2260,7 @@ class DBSpendUpdateWriter:
             verbose_proxy_logger.debug("request_tags is None for request. Skipping incrementing tag spend.")
             return
 
-        request_tags = []
+        request_tags: Sequence[str] = []
         if isinstance(payload["request_tags"], str):
             request_tags = json.loads(payload["request_tags"])
         elif isinstance(payload["request_tags"], list):
diff --git a/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py b/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
index 3716d00774f..2c27531cea1 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/akto/akto.py
@@ -162,10 +162,10 @@ class AktoGuardrail(CustomGuardrail):
     def build_request_body(
         inputs: GenericGuardrailAPIInputs,
         request_data: dict | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the LLM request body from guardrail inputs (messages, model, tools)."""
         model: Final = inputs.get("model", "") or ""
-        body: Final[dict[str, Any]] = {"model": model}
+        body: Final[dict[str, object]] = {"model": model}
 
         structured: Final = inputs.get("structured_messages")
         if structured:
@@ -194,7 +194,7 @@ class AktoGuardrail(CustomGuardrail):
     def build_response_body(
         inputs: GenericGuardrailAPIInputs,
         request_data: dict | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the LLM response body, preferring the actual model response if available."""
         model_response: Final = request_data.get("response") if request_data else None
         if model_response is not None and hasattr(model_response, "model_dump"):
@@ -224,7 +224,7 @@ class AktoGuardrail(CustomGuardrail):
         *,
         status_code: int = 200,
         include_response: bool = False,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """Build the flat MIRRORING payload sent to Akto's HTTP proxy endpoint.
 
         All body fields use double-encoding: json.dumps({"body": json.dumps(actual_body)})
diff --git a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
index 955a868a0d6..48832f8ed5e 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/grayswan/grayswan.py
@@ -2,9 +2,10 @@
 
 import os
 import time
-from typing import TYPE_CHECKING, Any, Final, Literal, Optional
+from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol
 
 from fastapi import HTTPException
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.integrations.custom_guardrail import (
@@ -27,6 +28,33 @@ if TYPE_CHECKING:
 GRAYSWAN_BLOCK_ERROR_MSG: Final = "Blocked by Gray Swan Guardrail"
 
 
+class _GraySwanMonitorResponse(TypedDict):
+    """Body returned by Gray Swan's `/cygnal/monitor` endpoint."""
+
+    violation: ReadOnly[NotRequired[float | None]]
+    violated_rules: ReadOnly[NotRequired[list[object]]]
+    violated_rule_descriptions: ReadOnly[NotRequired[list[object]]]
+    mutation: ReadOnly[NotRequired[bool | None]]
+    ipi: ReadOnly[NotRequired[bool | None]]
+
+
+class _GraySwanMonitorHTTPResponse(Protocol):
+    def raise_for_status(self) -> object: ...
+
+    def json(self) -> _GraySwanMonitorResponse: ...
+
+
+class _GraySwanMonitorHTTPClient(Protocol):
+    async def post(
+        self,
+        *,
+        url: str,
+        headers: dict[str, str],
+        json: dict[str, object],
+        timeout: float,
+    ) -> _GraySwanMonitorHTTPResponse: ...
+
+
 class GraySwanGuardrailMissingSecrets(Exception):
     """Raised when the Gray Swan API key is missing."""
 
@@ -77,7 +105,9 @@ class GraySwanGuardrail(CustomGuardrail):
         guardrail_timeout: float | None = 30.0,
         **kwargs: Any,
     ) -> None:
-        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+        self.async_handler: _GraySwanMonitorHTTPClient = get_async_httpx_client(
+            llm_provider=httpxSpecialProvider.GuardrailCallback
+        )
 
         api_key_value: Final = api_key or os.getenv("GRAYSWAN_API_KEY")
         if not api_key_value:
@@ -266,7 +296,7 @@ class GraySwanGuardrail(CustomGuardrail):
     # Legacy Test Interface (for backward compatibility)
     # ------------------------------------------------------------------
 
-    async def run_grayswan_guardrail(self, payload: dict) -> dict[str, Any]:
+    async def run_grayswan_guardrail(self, payload: dict[str, object]) -> _GraySwanMonitorResponse:
         """
         Run the GraySwan guardrail on a payload.
 
@@ -285,7 +315,7 @@ class GraySwanGuardrail(CustomGuardrail):
 
     def _process_grayswan_response(
         self,
-        response_json: dict,
+        response_json: _GraySwanMonitorResponse,
         data: dict | None = None,
         hook_type: GuardrailEventHooks | None = None,
     ) -> None:
@@ -385,7 +415,7 @@ class GraySwanGuardrail(CustomGuardrail):
     # Core GraySwan API interaction
     # ------------------------------------------------------------------
 
-    async def _call_grayswan_api(self, payload: dict) -> dict[str, Any]:
+    async def _call_grayswan_api(self, payload: dict[str, object]) -> _GraySwanMonitorResponse:
         """Call the GraySwan monitoring API."""
         headers: Final = self._prepare_headers()
 
@@ -406,7 +436,7 @@ class GraySwanGuardrail(CustomGuardrail):
 
     def _process_response_internal(
         self,
-        response_json: dict[str, Any],
+        response_json: _GraySwanMonitorResponse,
         request_data: dict,
         inputs: GenericGuardrailAPIInputs,
         is_output: bool,
@@ -534,8 +564,8 @@ class GraySwanGuardrail(CustomGuardrail):
         dynamic_body: dict,
         request_data: dict,
         logging_obj: Optional["LiteLLMLoggingObj"] = None,
-    ) -> dict[str, Any] | None:
-        payload: Final[dict[str, Any]] = {"messages": messages}
+    ) -> dict[str, object] | None:
+        payload: Final[dict[str, object]] = {"messages": messages}
 
         categories: Final = dynamic_body.get("categories") or self.categories
         if categories:
@@ -563,13 +593,13 @@ class GraySwanGuardrail(CustomGuardrail):
                 {**existing_headers, **inbound_headers} if isinstance(existing_headers, dict) else inbound_headers
             )
         if cleaned_litellm_metadata:
-            sanitized: Final = safe_json_loads(safe_dumps(cleaned_litellm_metadata), default={})
+            sanitized: Final[object] = safe_json_loads(safe_dumps(cleaned_litellm_metadata), default={})
             if isinstance(sanitized, dict) and sanitized:
                 payload["litellm_metadata"] = sanitized
 
         return payload
 
-    def _format_violation_message(self, detection_info: Any, is_output: bool = False) -> str:
+    def _format_violation_message(self, detection_info: object, is_output: bool = False) -> str:
         """
         Format detection info into a user-friendly violation message.
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py b/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
index ea022510309..cf5da27e9ca 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/lasso/lasso.py
@@ -8,6 +8,7 @@
 import json
 import os
 import uuid
+from collections.abc import Mapping, Sequence
 from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict
 
 try:
@@ -128,7 +129,7 @@ class LassoGuardrail(CustomGuardrail):
 
     @staticmethod
     def _extract_tool_call_fields(
-        call: Any,
+        call: object,
     ) -> tuple[str | None, str | None, dict[str, object] | None]:
         """Extract (call_id, name, parsed_input) from a tool call.
 
@@ -476,7 +477,7 @@ class LassoGuardrail(CustomGuardrail):
     def _map_masked_messages_back(
         self,
         original_messages: list[dict[str, Any]],
-        masked_messages: list[dict[str, Any]],
+        masked_messages: Sequence[Mapping[str, object]],
     ) -> list[dict[str, object]]:
         """Map Lasso-format masked messages back onto the original OpenAI-format messages.
 
@@ -638,7 +639,7 @@ class LassoGuardrail(CustomGuardrail):
             },
         )
 
-    def _expand_messages_for_classification(self, messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    def _expand_messages_for_classification(self, messages: list[dict[str, Any]]) -> list[dict[str, object]]:
         """
         Convert raw OpenAI-format messages to Lasso API format with content blocks.
 
@@ -646,7 +647,7 @@ class LassoGuardrail(CustomGuardrail):
         - role=tool messages → developer role + tool_result block
         - plain text messages pass through unchanged
         """
-        expanded: Final[list[dict[str, Any]]] = []
+        expanded: Final[list[dict[str, object]]] = []
         for msg in messages:
             role = msg.get("role", "")
             content = msg.get("content")
@@ -917,7 +918,7 @@ class LassoGuardrail(CustomGuardrail):
     def _apply_masking_to_model_response(
         self,
         model_response: litellm.ModelResponse,
-        masked_messages: list[dict[str, Any]],
+        masked_messages: Sequence[Mapping[str, object]],
     ) -> None:
         """Apply masking to the actual model response when mask=True and masked content is available."""
         # Index masked tool_use blocks by id for O(1) lookup.
diff --git a/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py b/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
index 78639ce4fd0..7021d41475b 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/pillar/pillar.py
@@ -8,11 +8,12 @@
 # Standard library imports
 import json
 import os
-from typing import TYPE_CHECKING, Any, Final, Literal
+from typing import TYPE_CHECKING, Any, Final, Literal, Protocol
 from urllib.parse import quote
 
 # Third-party imports
 from fastapi import HTTPException
+from typing_extensions import NotRequired, ReadOnly, TypedDict
 
 # LiteLLM imports
 from litellm import DualCache
@@ -42,7 +43,34 @@ if TYPE_CHECKING:
 MAX_PILLAR_HEADER_VALUE_BYTES: Final = 8 * 1024
 
 
-def _encode_json_for_header(data: Any) -> str:
+class _PillarProtectResponse(TypedDict):
+    """Body returned by Pillar's `/api/v1/protect` endpoint."""
+
+    flagged: ReadOnly[NotRequired[bool]]
+    session_id: ReadOnly[NotRequired[str]]
+    scanners: ReadOnly[NotRequired[dict[str, object]]]
+    evidence: ReadOnly[NotRequired[list[object]]]
+    masked_session_messages: ReadOnly[NotRequired[list[object]]]
+
+
+class _PillarProtectHTTPResponse(Protocol):
+    def raise_for_status(self) -> object: ...
+
+    def json(self) -> _PillarProtectResponse: ...
+
+
+class _PillarProtectHTTPClient(Protocol):
+    async def post(
+        self,
+        *,
+        url: str,
+        headers: dict[str, str],
+        json: dict[str, object],
+        timeout: float,
+    ) -> _PillarProtectHTTPResponse: ...
+
+
+def _encode_json_for_header(data: object) -> str:
     """
     JSON-serialize and URL-encode data for safe header transmission.
     """
@@ -50,7 +78,9 @@ def _encode_json_for_header(data: Any) -> str:
     return quote(json_payload, safe="")
 
 
-def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER_VALUE_BYTES) -> tuple[Any, str, bool]:
+def _truncate_evidence_payload(
+    evidence: object, max_bytes: int = MAX_PILLAR_HEADER_VALUE_BYTES
+) -> tuple[object, str, bool]:
     """
     Truncate evidence payload so the encoded header value stays within max_bytes.
 
@@ -66,12 +96,12 @@ def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER
         truncated_value: Final = "[truncated]"
         return truncated_value, _encode_json_for_header(truncated_value), True
 
-    truncated: Final[list[Any]] = []
+    truncated: Final[list[object]] = []
     encoded = _encode_json_for_header(truncated)
     truncated_flag = False
 
     for entry in evidence:
-        working_entry: Any
+        working_entry: object
         if isinstance(entry, dict):
             working_entry = dict(entry)
         else:
@@ -105,7 +135,7 @@ def _truncate_evidence_payload(evidence: Any, max_bytes: int = MAX_PILLAR_HEADER
     return truncated, encoded, truncated_flag
 
 
-def build_pillar_response_headers(metadata_store: dict[str, Any]) -> dict[str, str]:
+def build_pillar_response_headers(metadata_store: dict[str, object]) -> dict[str, str]:
     """
     Create URL-safe Pillar response headers and apply truncation metadata.
     """
@@ -191,7 +221,9 @@ class PillarGuardrail(CustomGuardrail):
             LiteLLM virtual key context (user_id, team_id, key_alias, etc.) is always
             automatically passed as X-LiteLLM-* headers to enable application/user tracking.
         """
-        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+        self.async_handler: _PillarProtectHTTPClient = get_async_httpx_client(
+            llm_provider=httpxSpecialProvider.GuardrailCallback
+        )
         self.api_key = api_key or os.environ.get("PILLAR_API_KEY")
 
         if self.api_key is None:
@@ -686,7 +718,7 @@ class PillarGuardrail(CustomGuardrail):
         )
         return payload
 
-    async def _call_pillar_api(self, headers: dict[str, str], payload: dict[str, Any]) -> dict[str, Any]:
+    async def _call_pillar_api(self, headers: dict[str, str], payload: dict[str, Any]) -> _PillarProtectResponse:
         """
         Call the Pillar API and return the response.
 
@@ -714,7 +746,7 @@ class PillarGuardrail(CustomGuardrail):
         verbose_proxy_logger.debug("Pillar Guardrail: Analysis complete - flagged=%s, session=%s", flagged, session_id)
         return res
 
-    def _process_pillar_response(self, pillar_response: dict[str, Any], original_data: dict) -> None:
+    def _process_pillar_response(self, pillar_response: _PillarProtectResponse, original_data: dict) -> None:
         """
         Process the Pillar API response and handle detections based on configuration.
 
@@ -774,7 +806,7 @@ class PillarGuardrail(CustomGuardrail):
 
         build_pillar_response_headers(metadata_store)
 
-    def _raise_pillar_detection_exception(self, pillar_response: dict[str, Any]) -> None:
+    def _raise_pillar_detection_exception(self, pillar_response: _PillarProtectResponse) -> None:
         """
         Raise an HTTPException for Pillar security detections.
 
@@ -784,7 +816,7 @@ class PillarGuardrail(CustomGuardrail):
         Raises:
             HTTPException: Always raises with security detection details
         """
-        pillar_response_dict: Final = {
+        pillar_response_dict: Final[dict[str, object]] = {
             "session_id": pillar_response.get("session_id"),
         }
 
diff --git a/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py b/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
index e34beec4d3e..2fbd50b5863 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/semantic_guard/semantic_guard.py
@@ -6,7 +6,7 @@ via embedding similarity. Smarter than regex (understands intent), lighter
 than an LLM call (~20-50ms per request for embedding).
 """
 
-from typing import TYPE_CHECKING, Any, Final
+from typing import TYPE_CHECKING, Any, Final, Protocol
 
 from litellm._logging import verbose_logger
 from litellm.integrations.custom_guardrail import (
@@ -50,7 +50,7 @@ class SemanticGuardrail(CustomGuardrail):
         similarity_threshold: float,
         route_templates: list[str] | None = None,
         custom_routes_file: str | None = None,
-        custom_routes: list[dict[str, Any]] | None = None,
+        custom_routes: list[dict[str, object]] | None = None,
         on_flagged_action: str = "block",
         event_hook: GuardrailEventHooks | list[GuardrailEventHooks] | Mode | None = None,
         default_on: bool = False,
@@ -157,7 +157,14 @@ class SemanticGuardrail(CustomGuardrail):
         return response
 
 
-def _get_top_route_choice(result: Any) -> Any:
+class _RouteChoice(Protocol):
+    """The semantic-router match this guardrail reads: the route that fired, if any."""
+
+    @property
+    def name(self) -> str | None: ...
+
+
+def _get_top_route_choice(result: _RouteChoice | list[_RouteChoice] | None) -> _RouteChoice | None:
     """Extract the top RouteChoice from SemanticRouter result.
 
     SemanticRouter.__call__ can return RouteChoice or List[RouteChoice].
@@ -194,7 +201,7 @@ def _extract_response_text(response: Any) -> str:
     return ""
 
 
-def _content_to_text(content: Any) -> str:
+def _content_to_text(content: object) -> str:
     if isinstance(content, str):
         return content
     if isinstance(content, list):
diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
index 3c5625bc272..a8b33109900 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py
@@ -1,9 +1,10 @@
 import json
 import re
 from collections.abc import AsyncGenerator, AsyncIterable, Mapping, Sequence
-from typing import Any, Final, Literal
+from typing import Any, Final, Literal, TypedDict
 
 from fastapi import HTTPException
+from typing_extensions import ReadOnly, Required
 
 from litellm import ChatCompletionToolParam
 from litellm._logging import verbose_proxy_logger
@@ -51,6 +52,27 @@ def _object_list(value: object) -> Sequence[object] | None:
     return value if isinstance(value, list) else None
 
 
+class _ToolPermissionRuleFields(TypedDict, total=False):
+    """The config-file shape a :class:`ToolPermissionRule` is built from."""
+
+    id: ReadOnly[Required[str]]
+    tool_name: ReadOnly[str | None]
+    tool_type: ReadOnly[str | None]
+    decision: ReadOnly[Required[Literal["allow", "deny"]]]
+    allowed_param_patterns: ReadOnly[dict[str, str] | None]
+
+
+def _rule_from_fields(fields: _ToolPermissionRuleFields) -> ToolPermissionRule:
+    """Validate one config-file rule entry into a :class:`ToolPermissionRule`."""
+    return ToolPermissionRule(**fields)
+
+
+def _is_tool_use_block(block: object) -> bool:
+    """Whether ``block`` is an Anthropic ``tool_use`` content block."""
+    fields: Final = _object_mapping(block)
+    return fields is not None and fields.get("type") == "tool_use"
+
+
 class ToolPermissionGuardrail(CustomGuardrail):
     def __init__(
         self,
@@ -101,7 +123,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         compiled_patterns: Final[dict[str, dict[str, re.Pattern]]] = {}
 
         for rule_item in rules or []:
-            rule = rule_item if isinstance(rule_item, ToolPermissionRule) else ToolPermissionRule(**rule_item)
+            rule = rule_item if isinstance(rule_item, ToolPermissionRule) else _rule_from_fields(rule_item)
 
             target_patterns: dict[str, re.Pattern | None] = {
                 "tool_name": None,
@@ -440,7 +462,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         return is_allowed, None, message
 
     @staticmethod
-    def _get_mapping_value(item: Any, key: str) -> Any:
+    def _get_mapping_value(item: object, key: str) -> Any:
         if isinstance(item, dict):
             return item.get(key)
         return getattr(item, key, None)
@@ -450,7 +472,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         return f"legacy_function_call_{choice_index}"
 
     def _legacy_function_call_to_tool_call(
-        self, function_call: Any, choice_index: int
+        self, function_call: object, choice_index: int
     ) -> ChatCompletionMessageToolCall | None:
         if function_call is None:
             return None
@@ -549,7 +571,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
     def _modify_anthropic_content_with_permission_errors(
         self,
         response: object,
-        content: tuple[Any, ...],
+        content: tuple[object, ...],
         denied_tools: tuple[tuple[ChatCompletionMessageToolCall, PermissionError], ...],
     ) -> None:
         if not denied_tools or not isinstance(response, dict):
@@ -557,27 +579,33 @@ class ToolPermissionGuardrail(CustomGuardrail):
 
         verbose_proxy_logger.info("Blocking %s unauthorized tool uses", len(denied_tools))
 
-        error_by_tool_use_id: Final = {  # mutable-ok: read-only lookup, never mutated after construction
+        error_by_tool_use_id: Final[
+            Mapping[object, str]
+        ] = {  # mutable-ok: read-only lookup, never mutated after construction
             tool_call.id: self._create_permission_error_result(tool_call, error).content
             for tool_call, error in denied_tools
         }
-        denied_block_ids: Final = frozenset(error_by_tool_use_id)
 
-        def _is_denied(block: object) -> bool:
-            return isinstance(block, dict) and block.get("type") == "tool_use" and block.get("id") in denied_block_ids
+        def _denied_message(block: object) -> str | None:
+            fields: Final = _object_mapping(block)
+            if fields is None or fields.get("type") != "tool_use":
+                return None
+            return error_by_tool_use_id.get(fields.get("id"))
 
-        error_messages: Final = tuple(error_by_tool_use_id[block["id"]] for block in content if _is_denied(block))
-        kept_blocks: Final = tuple(block for block in content if not _is_denied(block))
+        error_messages: Final = tuple(
+            message for message in (_denied_message(block) for block in content) if message is not None
+        )
+        kept_blocks: Final = tuple(block for block in content if _denied_message(block) is None)
         new_content: Final = [  # mutable-ok: response content is a JSON array on the wire
             *kept_blocks,
             {"type": "text", "text": "\n".join(error_messages)},  # mutable-ok: content block is a JSON object
         ]
 
         response["content"] = new_content  # rebind-ok: the guardrail rewrites the provider response in place
-        if not any(isinstance(block, dict) and block.get("type") == "tool_use" for block in kept_blocks):
+        if not any(_is_tool_use_block(block) for block in kept_blocks):
             response["stop_reason"] = "end_turn"  # rebind-ok: dropping every tool_use ends the turn
 
-    def _get_request_tool_name(self, tool: Any) -> tuple[str | None, str | None]:
+    def _get_request_tool_name(self, tool: object) -> tuple[str | None, str | None]:
         tool_type: Final = self._get_mapping_value(tool, "type")
         if tool_type != "function":
             return None, tool_type
@@ -586,7 +614,7 @@ class ToolPermissionGuardrail(CustomGuardrail):
         tool_name: Final = self._get_mapping_value(function, "name")
         return tool_name, tool_type
 
-    def _get_legacy_function_name(self, function: Any) -> str | None:
+    def _get_legacy_function_name(self, function: object) -> str | None:
         return self._get_mapping_value(function, "name")
 
     def _get_named_tool_choice(self, data: dict) -> str | None:
diff --git a/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py b/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
index 6b8148645aa..a5945a39589 100644
--- a/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
+++ b/litellm/proxy/guardrails/guardrail_hooks/vigil_guard/vigil_guard.py
@@ -433,7 +433,7 @@ class VigilGuardGuardrail(CustomGuardrail):
         return collected
 
     @staticmethod
-    def _clamp_metadata_value(value: Any) -> _MetadataValue | None:
+    def _clamp_metadata_value(value: object) -> _MetadataValue | None:
         if isinstance(value, bool):
             return None
         if isinstance(value, str):
diff --git a/litellm/proxy/hooks/litellm_skills/main.py b/litellm/proxy/hooks/litellm_skills/main.py
index 569ec32c1a0..9edbc6dbf1c 100644
--- a/litellm/proxy/hooks/litellm_skills/main.py
+++ b/litellm/proxy/hooks/litellm_skills/main.py
@@ -67,6 +67,24 @@ class _ChatMessage(Protocol):
     def tool_calls(self) -> Sequence[_ChatToolCall] | None: ...
 
 
+class _ChatChoice(Protocol):
+    @property
+    def message(self) -> _ChatMessage: ...
+
+    @property
+    def finish_reason(self) -> str | None: ...
+
+
+class _ChatCompletion(Protocol):
+    @property
+    def choices(self) -> Sequence[_ChatChoice]: ...
+
+
+def _first_choice(response: _ChatCompletion) -> _ChatChoice:
+    """The first choice of an OpenAI shaped completion response."""
+    return response.choices[0]
+
+
 class SkillsInjectionHook(CustomLogger):
     """
     Pre/Post-call hook that processes skills from container.skills parameter.
@@ -738,8 +756,9 @@ print('No executable skill module found')
 
         for iteration in range(self.max_iterations):
             # OpenAI format response has choices[0].message
-            assistant_message: _ChatMessage = current_response.choices[0].message
-            stop_reason: str | None = current_response.choices[0].finish_reason
+            choice: _ChatChoice = _first_choice(current_response)
+            assistant_message: _ChatMessage = choice.message
+            stop_reason: str | None = choice.finish_reason
 
             # Build assistant message for conversation history
             assistant_msg_dict: dict[str, object] = {
diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py
index 1e65da5b867..63129602082 100644
--- a/litellm/proxy/hooks/parallel_request_limiter_v3.py
+++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py
@@ -8,7 +8,7 @@ import asyncio
 import binascii
 import os
 import uuid
-from collections.abc import Callable, Mapping, Sequence, Set
+from collections.abc import Awaitable, Callable, Mapping, Sequence, Set
 from contextvars import ContextVar
 from dataclasses import dataclass, field
 from datetime import datetime
@@ -386,6 +386,12 @@ CacheCounterValues: TypeAlias = Sequence[CacheCounterValue | None]
 ParallelGaugeCacheValue: TypeAlias = dict[str, object] | int | float | str | bytes
 
 
+class _AsyncLuaScript(Protocol):
+    """A Lua script registered against the async Redis client, called with KEYS and ARGV."""
+
+    def __call__(self, *, keys: Sequence[str], args: Sequence[object]) -> Awaitable[list[CacheCounterValue]]: ...
+
+
 class RateLimitDescriptorRateLimitObject(TypedDict, total=False):
     requests_per_unit: int | None
     tokens_per_unit: int | None
@@ -577,6 +583,14 @@ def _parse_output_cap_value(raw_value: object) -> int | None:
 
 
 class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
+    batch_rate_limiter_script: _AsyncLuaScript | None
+    token_increment_script: _AsyncLuaScript | None
+    check_and_increment_by_n_script: _AsyncLuaScript | None
+    window_guarded_token_increment_script: _AsyncLuaScript | None
+    parallel_acquire_script: _AsyncLuaScript | None
+    parallel_release_script: _AsyncLuaScript | None
+    parallel_count_script: _AsyncLuaScript | None
+
     def __init__(
         self,
         internal_usage_cache: InternalUsageCache,
@@ -3855,7 +3869,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
                 expected_window_start = operation.get("expected_window_start")
                 if window_key is None or expected_window_start is None:
                     continue
-                active_window_start = await self.internal_usage_cache.async_get_cache(
+                active_window_start: CacheCounterValue | None = await self.internal_usage_cache.async_get_cache(
                     key=window_key,
                     litellm_parent_otel_span=parent_otel_span,
                     local_only=True,
@@ -4144,7 +4158,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
     def _collect_tpm_scope_targets(
         self,
         standard_logging_metadata: dict[str, Any],
-        kwargs: Any,
+        kwargs: object,
         model_group: str | None,
     ) -> list[tuple[str, str]]:
         """
@@ -4301,8 +4315,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger):
 
     def _build_success_event_pipeline_operations(
         self,
-        kwargs: Any,
-        response_obj: Any,
+        kwargs: dict[str, Any],
+        response_obj: object,
         rate_limit_type: Literal["output", "input", "total"],
     ) -> list[RedisPipelineIncrementOperation]:
         """Build Redis pipeline increment ops for TPM / parallel-request counters."""
diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py
index 012aec38458..14d2332a7eb 100644
--- a/litellm/proxy/management_endpoints/model_management_endpoints.py
+++ b/litellm/proxy/management_endpoints/model_management_endpoints.py
@@ -543,7 +543,7 @@ def update_db_model(db_model: Deployment, updated_patch: updateDeployment) -> Pr
         _raise_if_ptu_cost_attribution_disabled(updated_patch.model_info.model_dump(exclude_none=True))
     merged_model_name: Final = updated_patch.model_name or db_model.model_name
     merged_litellm_params: Final = db_model.litellm_params.model_dump(exclude_none=True)
-    merged_model_info: Final = db_model.model_info.model_dump(exclude_none=True)
+    merged_model_info: Final[dict[str, object]] = db_model.model_info.model_dump(exclude_none=True)
 
     # update litellm params
     if updated_patch.litellm_params:
@@ -1982,7 +1982,7 @@ async def update_model(
 
             ### MERGE WITH EXISTING DATA ###
             merged_dictionary: Final = {}
-            _mp: Final = model_params.litellm_params.dict()
+            _mp: Final[dict[str, object]] = model_params.litellm_params.dict()
 
             for key, value in _mp.items():
                 if value is not None:
diff --git a/litellm/proxy/management_endpoints/organization_endpoints.py b/litellm/proxy/management_endpoints/organization_endpoints.py
index 9198aa35f3f..5e38a016099 100644
--- a/litellm/proxy/management_endpoints/organization_endpoints.py
+++ b/litellm/proxy/management_endpoints/organization_endpoints.py
@@ -487,12 +487,11 @@ async def new_organization(
         for m in data.models:
             await can_user_call_model(m, llm_router=llm_router, user_object=user_object_correct_type)
 
-    organization_row: Final = LiteLLM_OrganizationTable(
-        **data.json(exclude_none=True),
-        object_permission_id=object_permission_id,
-        created_by=user_api_key_dict.user_id or litellm_proxy_admin_name,
-        updated_by=user_api_key_dict.user_id or litellm_proxy_admin_name,
-    )
+    organization_payload: Final = _STR_OBJECT_DICT_ADAPTER.validate_python(data.json(exclude_none=True))
+    organization_payload["object_permission_id"] = object_permission_id
+    organization_payload["created_by"] = user_api_key_dict.user_id or litellm_proxy_admin_name
+    organization_payload["updated_by"] = user_api_key_dict.user_id or litellm_proxy_admin_name
+    organization_row: Final = LiteLLM_OrganizationTable.model_validate(organization_payload)
 
     for field in LiteLLM_ManagementEndpoint_MetadataFields:
         if getattr(data, field, None) is not None:
@@ -644,7 +643,7 @@ async def update_organization(
         )
 
     # Transform UI payload to expected format
-    raw_data: Final = await request.json()
+    raw_data: Final[dict[str, object]] = await request.json()
     raw_data_with_flat_budget_fields: Final = handle_nested_budget_structure_in_organization_update_request(raw_data)
 
     # Create validated data model
@@ -691,7 +690,7 @@ async def update_organization(
     # Merge metadata from existing organization with updated metadata
     if updated_organization_row_json.get("metadata") is not None:
         existing_metadata: Final = existing_organization_row.metadata or {}
-        updated_metadata: Final = updated_organization_row_json.get("metadata", {})
+        updated_metadata: Final[dict[str, object]] = updated_organization_row_json.get("metadata", {})
         merged_metadata: Final[Mapping[str, object]] = _update_dictionary(
             existing_dict=cast(  # cast-ok: prisma de-serializes a Json column to the plain python dict it stores
                 "dict[str, object]", existing_metadata
diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py
index 613508da22b..606569c5b8b 100644
--- a/litellm/proxy/management_endpoints/ui_sso.py
+++ b/litellm/proxy/management_endpoints/ui_sso.py
@@ -502,7 +502,7 @@ def _set_nested_metadata_value(metadata: dict[str, object], key_path: str, value
     placeholder: Final = "\x00"
     parts = key_path.replace("\\.", placeholder).split(".")
     parts = [p.replace(placeholder, ".") for p in parts]
-    current: Any = metadata
+    current: dict[str, object] = metadata
     for part in parts[:-1]:
         existing = current.get(part)
         if not isinstance(existing, dict):
@@ -4076,7 +4076,7 @@ class SSOAuthenticationHandler:
                 )
                 if resp.status_code == 200:
                     try:
-                        userinfo_raw: Final = resp.json()
+                        userinfo_raw: Final[dict[str, object] | None] = resp.json()
                         if not userinfo_raw:
                             # JSON null (None) or empty dict ({}) — no identity claims.
                             # Treat as failure so id_token fallback can be attempted.
@@ -4406,7 +4406,7 @@ class MicrosoftSSOHandler:
     ) -> tuple[list[str], str | None]:
         """Helper function to fetch and parse group data from a URL"""
         response: Final = await async_client.get(url, headers=headers)
-        response_json: Final = response.json()
+        response_json: Final[dict[str, object]] = response.json()
         response_typed: Final = await MicrosoftSSOHandler._cast_graph_api_response_dict(response=response_json)
         group_ids: Final = MicrosoftSSOHandler._get_group_ids_from_graph_api_response(response=response_typed)
         return group_ids, response_typed.get("odata_nextLink")
diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
index ee9a5d94440..49ec18013b5 100644
--- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
+++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_passthrough_logging_handler.py
@@ -267,7 +267,7 @@ class VertexPassthroughLoggingHandler:
 
         model: Final = VertexPassthroughLoggingHandler.extract_model_from_url(url_route)
 
-        _json_response: Final = httpx_response.json()
+        _json_response: Final[dict[str, object]] = httpx_response.json()
 
         litellm_prediction_response: ModelResponse | EmbeddingResponse | ImageResponse = ModelResponse()
         if vertex_image_generation_class.is_image_generation_response(_json_response):
@@ -422,7 +422,7 @@ class VertexPassthroughLoggingHandler:
         - Creates standard logging object
         - Logs in litellm callbacks
         """
-        kwargs: dict[str, Any] = {}
+        kwargs: dict[str, object] = {}
         vertex_location: Final = get_vertex_location_from_url(url_route)
         if vertex_location is not None:
             litellm_logging_obj.optional_params["vertex_location"] = vertex_location
diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py
index aa7595ed13d..5907ffc64eb 100644
--- a/litellm/proxy/response_api_endpoints/endpoints.py
+++ b/litellm/proxy/response_api_endpoints/endpoints.py
@@ -52,7 +52,7 @@ _TOOL_PAYLOAD_KEYS: Final[Mapping[str, tuple[str, ...]]] = MappingProxyType(
         "function": ("name", "description", "parameters", "strict"),
     }
 )
-_EMPTY_TOOL_PAYLOAD: Final[Mapping[str, Any]] = MappingProxyType({})
+_EMPTY_TOOL_PAYLOAD: Final[Mapping[str, object]] = MappingProxyType({})
 
 
 def _convert_tool_payload_value(key: str, value: object, *, to_chat: bool) -> object:
@@ -105,7 +105,7 @@ def _normalize_tool_dialect(
     return {**data, **{key: value for key, value in replaceable if key in data}}  # mutable-ok: plain body dict
 
 
-def _is_chat_completions_body(data: Mapping[str, Any]) -> bool:
+def _is_chat_completions_body(data: Mapping[str, object]) -> bool:
     messages: Final = data.get("messages")
     if isinstance(messages, list) and messages:
         return True
@@ -1373,7 +1373,7 @@ async def _enforce_responses_ws_first_frame_model_auth(
     request: Request,
     model: str,
     user_api_key_dict: UserAPIKeyAuth,
-    llm_router: Any | None,
+    llm_router: "Router | None",
 ) -> None:
     from litellm.proxy.auth.user_api_key_auth import (
         _enforce_key_and_fallback_model_access,
@@ -1417,7 +1417,7 @@ async def _enforce_responses_ws_first_frame_model_auth(
 async def responses_websocket_endpoint(
     websocket: WebSocket,
     model: str | None = fastapi.Query(None, description="The model to use for the responses WebSocket session."),
-    user_api_key_dict=Depends(user_api_key_auth_websocket),
+    user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth_websocket),
 ):
     """
     Responses API WebSocket mode endpoint.
@@ -1462,7 +1462,7 @@ async def responses_websocket_endpoint(
             return
         model, first_message = result
 
-    data: dict[str, Any] = {
+    data: dict[str, object] = {
         "model": model,
         "websocket": websocket,
     }
@@ -1471,7 +1471,7 @@ async def responses_websocket_endpoint(
 
     # Construct a synthetic Request for pre-call processing
     headers_list: Final = list(websocket.scope.get("headers") or [])
-    scope: Final[dict[str, Any]] = {
+    scope: Final[dict[str, object]] = {
         "type": "http",
         "method": "POST",
         "path": "/v1/responses",
diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py
index 91a0c68fd58..3d0bd5e61c9 100644
--- a/litellm/proxy/route_llm_request.py
+++ b/litellm/proxy/route_llm_request.py
@@ -50,12 +50,12 @@ def _route_user_config_request(data: dict, route_type: str):
     return ret_val
 
 
-def _is_a2a_agent_model(model_name: Any) -> bool:
+def _is_a2a_agent_model(model_name: object) -> bool:
     """Check if the model name is for an A2A agent (a2a/ prefix)."""
     return isinstance(model_name, str) and model_name.startswith("a2a/")
 
 
-def _raise_if_model_fully_blocked(llm_router: LitellmRouter, model_name: Any, team_id: str | None) -> None:
+def _raise_if_model_fully_blocked(llm_router: LitellmRouter, model_name: object, team_id: str | None) -> None:
     if not isinstance(model_name, str) or not model_name:
         return
     if not isinstance(llm_router, litellm.Router):
diff --git a/litellm/proxy/video_endpoints/endpoints.py b/litellm/proxy/video_endpoints/endpoints.py
index d985a546fa7..66071c05b4f 100644
--- a/litellm/proxy/video_endpoints/endpoints.py
+++ b/litellm/proxy/video_endpoints/endpoints.py
@@ -1,6 +1,6 @@
 #### Video Endpoints #####
 
-from typing import Any, Final
+from typing import Final
 
 from fastapi import APIRouter, Depends, File, Form, Request, Response, UploadFile
 from fastapi.responses import ORJSONResponse
@@ -161,7 +161,7 @@ async def video_list(
 
     # Read query parameters
     query_params: Final = dict(request.query_params)
-    data: Final[dict[str, Any]] = {"query_params": query_params}
+    data: Final[dict[str, object]] = {"query_params": query_params}
 
     # Extract custom_llm_provider from headers, query params, or body
     custom_llm_provider: Final = (
@@ -246,7 +246,7 @@ async def video_status(
     )
 
     # Create data with video_id
-    data: Final[dict[str, Any]] = {"video_id": video_id}
+    data: Final[dict[str, object]] = {"video_id": video_id}
 
     decoded: Final = decode_video_id_with_provider(video_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
@@ -345,7 +345,7 @@ async def video_content(
     )
 
     # Create data with video_id
-    data: Final[dict[str, Any]] = {"video_id": video_id}
+    data: Final[dict[str, object]] = {"video_id": video_id}
 
     decoded: Final = decode_video_id_with_provider(video_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
@@ -653,7 +653,7 @@ async def video_get_character(
     )
 
     original_requested_character_id: Final = character_id
-    data: Final[dict[str, Any]] = {"character_id": character_id}
+    data: Final[dict[str, object]] = {"character_id": character_id}
 
     decoded: Final = decode_character_id_with_provider(character_id)
     provider_from_id: Final = decoded.get("custom_llm_provider")
diff --git a/litellm/rag/main.py b/litellm/rag/main.py
index 2dcaa200cc6..7bc1a6a52a3 100644
--- a/litellm/rag/main.py
+++ b/litellm/rag/main.py
@@ -29,6 +29,7 @@ from litellm.rag.ingestion.openai_ingestion import OpenAIRAGIngestion
 from litellm.rag.ingestion.s3_vectors_ingestion import S3VectorsRAGIngestion
 from litellm.rag.ingestion.vertex_ai_ingestion import VertexAIRAGIngestion
 from litellm.rag.rag_query import RAGQuery
+from litellm.types.llms.openai import AllMessageValues
 from litellm.types.rag import (
     RAGIngestOptions,
     RAGIngestResponse,
@@ -204,7 +205,7 @@ def _suppressed_sub_call_billing() -> Iterator[None]:
 
 async def _execute_query_pipeline(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
@@ -311,7 +312,7 @@ async def _execute_query_pipeline(
 @client
 async def aquery(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
@@ -358,12 +359,12 @@ async def aquery(
 @client
 def query(
     model: str,
-    messages: list[Any],
+    messages: list[AllMessageValues],
     retrieval_config: dict[str, Any],
     rerank: dict[str, Any] | None = None,
     stream: bool = False,
     **kwargs,
-) -> ModelResponse | Coroutine[Any, Any, ModelResponse]:
+) -> ModelResponse | Coroutine[None, None, ModelResponse]:
     """
     Query a RAG pipeline.
     """
@@ -410,7 +411,7 @@ def ingest(
     file_id: str | None = None,
     timeout: float | httpx.Timeout | None = None,
     **kwargs,
-) -> RAGIngestResponse | Coroutine[Any, Any, RAGIngestResponse]:
+) -> RAGIngestResponse | Coroutine[None, None, RAGIngestResponse]:
     """
     Ingest a document into a vector store.
 
diff --git a/litellm/responses/mcp/litellm_proxy_mcp_handler.py b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
index 197d0c02ba8..367915156d1 100644
--- a/litellm/responses/mcp/litellm_proxy_mcp_handler.py
+++ b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
@@ -399,7 +399,7 @@ class LiteLLM_Proxy_MCP_Handler:
 
     @staticmethod
     async def _process_mcp_tools_without_openai_transform(
-        user_api_key_auth: Any,
+        user_api_key_auth: "UserAPIKeyAuth | None",
         mcp_tools_with_litellm_proxy: Sequence[Mapping[str, object]],
         litellm_trace_id: str | None = None,
         mcp_auth_header: str | None = None,
@@ -636,7 +636,7 @@ class LiteLLM_Proxy_MCP_Handler:
     async def _execute_tool_calls(
         tool_server_map: dict[str, str],
         tool_calls: Sequence[object],
-        user_api_key_auth: Any,
+        user_api_key_auth: "UserAPIKeyAuth | None",
         mcp_auth_header: str | None = None,
         mcp_server_auth_headers: dict[str, dict[str, str]] | None = None,
         oauth2_headers: dict[str, str] | None = None,
diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py
index d57d7da0410..a8d51f95e45 100644
--- a/litellm/router_strategy/budget_limiter.py
+++ b/litellm/router_strategy/budget_limiter.py
@@ -20,6 +20,7 @@ anthropic:
 
 import asyncio
 import builtins
+from collections.abc import Mapping
 from datetime import datetime, timedelta, timezone
 from typing import Any, Final
 
@@ -54,19 +55,19 @@ class _LiteLLMParamsDictView:
 
     __slots__ = ("_params",)
 
-    def __init__(self, params: dict[str, Any]):
+    def __init__(self, params: Mapping[str, object]):
         self._params = params
 
-    def __getattr__(self, key: str) -> Any:
+    def __getattr__(self, key: str) -> object:
         return self._params.get(key)
 
-    def __getitem__(self, key: str) -> Any:
+    def __getitem__(self, key: str) -> object:
         return self._params.get(key)
 
     def __contains__(self, key: str) -> bool:
         return key in self._params
 
-    def get(self, key: str, default: Any = None) -> Any:
+    def get(self, key: str, default: object = None) -> object:
         return self._params.get(key, default)
 
     def keys(self):
@@ -84,10 +85,10 @@ class _LiteLLMParamsDictView:
     def __len__(self) -> int:
         return len(self._params)
 
-    def dict(self) -> dict[str, Any]:
+    def dict(self) -> builtins.dict[str, object]:
         return dict(self._params)
 
-    def model_dump(self) -> builtins.dict[str, Any]:
+    def model_dump(self) -> builtins.dict[str, object]:
         return dict(self._params)
 
 
diff --git a/litellm/router_strategy/complexity_router/complexity_router.py b/litellm/router_strategy/complexity_router/complexity_router.py
index be7653902a7..577cee0920d 100644
--- a/litellm/router_strategy/complexity_router/complexity_router.py
+++ b/litellm/router_strategy/complexity_router/complexity_router.py
@@ -282,7 +282,7 @@ def _response_cost_or_none(response: ModelResponse) -> float | None:
     return float(cost)
 
 
-def _effective_turn_off_message_logging(request_kwargs: Mapping[str, Any] | None) -> bool | None:
+def _effective_turn_off_message_logging(request_kwargs: Mapping[str, object] | None) -> bool | None:
     from litellm.litellm_core_utils.initialize_dynamic_callback_params import (
         initialize_standard_callback_dynamic_params,
     )
@@ -1925,7 +1925,7 @@ class ComplexityRouter(CustomLogger):
         ceiling_severity: Final = self._active_tier_severity(hard_ceiling) if hard_ceiling is not None else None
         best_model: str | None = None
         best_score = float("-inf")
-        candidate_scores: Final[list[dict[str, Any]]] = []
+        candidate_scores: Final[list[dict[str, object]]] = []
         for model in candidates:
             if floor_severity is not None and all(
                 self._active_tier_severity(model_tier) < floor_severity
diff --git a/litellm/secret_managers/hashicorp_secret_manager.py b/litellm/secret_managers/hashicorp_secret_manager.py
index e2662d96b52..8f677b54700 100644
--- a/litellm/secret_managers/hashicorp_secret_manager.py
+++ b/litellm/secret_managers/hashicorp_secret_manager.py
@@ -1,7 +1,9 @@
 import os
-from typing import Any, Final
+from collections.abc import Mapping
+from typing import Final, Protocol
 
 import httpx
+from typing_extensions import ReadOnly, TypedDict
 
 import litellm
 from litellm._logging import verbose_logger
@@ -17,6 +19,72 @@ from litellm.proxy._types import KeyManagementSystem
 from .base_secret_manager import BaseSecretManager, raise_if_unsafe_secret_name
 
 
+class _VaultAuthData(TypedDict):
+    """The ``auth`` block Vault returns from a login endpoint."""
+
+    client_token: ReadOnly[str]
+    lease_duration: ReadOnly[int]
+
+
+class _VaultLoginResponse(TypedDict):
+    """Body of a Vault ``/v1/auth/.../login`` response."""
+
+    auth: ReadOnly[_VaultAuthData]
+
+
+class _VaultSecretTarget(TypedDict):
+    """Resolved coordinates of one Vault KV v2 secret."""
+
+    url: ReadOnly[str]
+    data_key: ReadOnly[str]
+    secret_name: ReadOnly[str]
+
+
+class _VaultSecretDataBlock(TypedDict, total=False):
+    """The inner ``data`` block of a Vault KV v2 read body."""
+
+    data: ReadOnly[Mapping[str, object]]
+
+
+class _VaultSecretReadResponse(TypedDict, total=False):
+    """Body of a Vault KV v2 secret read, narrowed to the nesting this module walks."""
+
+    data: ReadOnly[_VaultSecretDataBlock]
+
+
+class _VaultLoginResponseSource(Protocol):
+    """A Vault login call's HTTP response, read for the auth block it carries."""
+
+    def json(self) -> _VaultLoginResponse: ...
+
+
+class _VaultSecretReadSource(Protocol):
+    """A Vault KV v2 read response, read for the nested secret data it carries."""
+
+    def json(self) -> _VaultSecretReadResponse: ...
+
+
+class _JsonObjectSource(Protocol):
+    """A Vault response whose body is a JSON object nothing further is assumed about."""
+
+    def json(self) -> dict[str, object]: ...
+
+
+def _vault_login_body(response: _VaultLoginResponseSource) -> _VaultLoginResponse:
+    """Decode the body of a Vault login response."""
+    return response.json()
+
+
+def _vault_secret_read_body(response: _VaultSecretReadSource) -> _VaultSecretReadResponse:
+    """Decode the body of a Vault KV v2 secret read response."""
+    return response.json()
+
+
+def _json_object_body(response: _JsonObjectSource) -> dict[str, object]:
+    """Decode a Vault response body as a plain JSON object."""
+    return response.json()
+
+
 class HashicorpSecretManager(BaseSecretManager):
     def __init__(self):
         from litellm.proxy.proxy_server import CommonProxyErrors, premium_user
@@ -130,7 +198,8 @@ class HashicorpSecretManager(BaseSecretManager):
             )
             resp.raise_for_status()
 
-            auth_data: Final = resp.json()["auth"]
+            login_response: Final = _vault_login_body(resp)
+            auth_data: Final = login_response["auth"]
             token: Final = auth_data["client_token"]
             _lease_duration: Final = auth_data["lease_duration"]
 
@@ -191,8 +260,10 @@ class HashicorpSecretManager(BaseSecretManager):
                 json=self._get_tls_cert_auth_body(),
             )
             resp.raise_for_status()
-            token: Final = resp.json()["auth"]["client_token"]
-            _lease_duration: Final = resp.json()["auth"]["lease_duration"]
+            token_response: Final = _vault_login_body(resp)
+            token: Final = token_response["auth"]["client_token"]
+            lease_response: Final = _vault_login_body(resp)
+            _lease_duration: Final = lease_response["auth"]["lease_duration"]
             verbose_logger.debug("Successfully obtained Vault token via TLS cert auth.")
             self.cache.set_cache(key="hcp_vault_token", value=token, ttl=_lease_duration)
             return token
@@ -205,9 +276,9 @@ class HashicorpSecretManager(BaseSecretManager):
     def get_url(
         self,
         secret_name: str,
-        namespace: str | None = None,
-        mount_name: str | None = None,
-        path_prefix: str | None = None,
+        namespace: object = None,
+        mount_name: object = None,
+        path_prefix: object = None,
     ) -> str:
         """
         Constructs the Vault URL for KV v2 secrets.
@@ -238,7 +309,7 @@ class HashicorpSecretManager(BaseSecretManager):
         _url += secret_name
         return _url
 
-    def _sanitize_plain_value(self, value: str | int | None) -> str | None:
+    def _sanitize_plain_value(self, value: object) -> str | None:
         if value is None:
             return None
         value_str: Final = str(value).strip()
@@ -246,23 +317,23 @@ class HashicorpSecretManager(BaseSecretManager):
             return None
         return value_str
 
-    def _sanitize_path_component(self, value: str | int | None) -> str | None:
+    def _sanitize_path_component(self, value: object) -> str | None:
         sanitized_value = self._sanitize_plain_value(value)
         if sanitized_value is None:
             return None
         sanitized_value = sanitized_value.strip("/")
         return sanitized_value or None
 
-    def _extract_secret_manager_settings(self, optional_params: dict | None) -> dict[str, Any]:
+    def _extract_secret_manager_settings(self, optional_params: dict | None) -> dict[str, object]:
         if not isinstance(optional_params, dict):
             return {}
 
         candidate: Final = optional_params.get("secret_manager_settings")
-        source: Final = candidate if isinstance(candidate, dict) else optional_params
+        source: Final[Mapping[str, object]] = candidate if isinstance(candidate, dict) else optional_params
         allowed_keys: Final = {"namespace", "mount", "path_prefix", "data"}
         return {k: source[k] for k in allowed_keys if k in source}
 
-    def _build_secret_target(self, secret_name: str, optional_params: dict | None) -> dict[str, Any]:
+    def _build_secret_target(self, secret_name: str, optional_params: dict | None) -> _VaultSecretTarget:
         settings: Final = self._extract_secret_manager_settings(optional_params)
 
         namespace: Final = settings.get("namespace", self.vault_namespace)
@@ -331,7 +402,7 @@ class HashicorpSecretManager(BaseSecretManager):
             response.raise_for_status()
 
             # For KV v2, the secret is in response.json()["data"]["data"]
-            json_resp: Final = response.json()
+            json_resp: Final = _json_object_body(response)
             _value: Final = self._get_secret_value_from_json_response(json_resp)
             self.cache.set_cache(secret_name, _value)
             return _value
@@ -362,7 +433,7 @@ class HashicorpSecretManager(BaseSecretManager):
             response.raise_for_status()
 
             # For KV v2, the secret is in response.json()["data"]["data"]
-            json_resp: Final = response.json()
+            json_resp: Final = _json_object_body(response)
             _value: Final = self._get_secret_value_from_json_response(json_resp)
             self.cache.set_cache(secret_name, _value)
             return _value
@@ -379,7 +450,7 @@ class HashicorpSecretManager(BaseSecretManager):
         optional_params: dict | None = None,
         timeout: float | httpx.Timeout | None = None,
         tags: dict | list | None = None,
-    ) -> dict[str, Any]:
+    ) -> dict[str, object]:
         """
         Writes a secret to Vault KV v2 using an async HTTPX client.
 
@@ -413,7 +484,7 @@ class HashicorpSecretManager(BaseSecretManager):
                 json=data,
             )
             response.raise_for_status()
-            return response.json()
+            return _json_object_body(response)
         except Exception as e:
             verbose_logger.exception("Error writing secret to Hashicorp Vault: %s", e)
             return {"status": "error", "message": str(e)}
@@ -500,7 +571,7 @@ class HashicorpSecretManager(BaseSecretManager):
                     headers=self._get_request_headers(),
                 )
                 response.raise_for_status()
-                json_resp: Final = response.json()
+                json_resp: Final = _vault_secret_read_body(response)
                 # Use data_key from target to get the correct value
                 data_key: Final = new_target["data_key"]
                 new_secret_value_from_vault: Final = json_resp.get("data", {}).get("data", {}).get(data_key, None)
diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py
index fcade835cce..32d88da0085 100644
--- a/litellm/types/llms/openai.py
+++ b/litellm/types/llms/openai.py
@@ -327,6 +327,10 @@ class BatchGuardrailReport(BaseModel):
     """Every record that was redacted or dropped, in file order."""
 
 
+_JsonValue: TypeAlias = object
+"""Alias for ``object``, usable inside model bodies that declare a field named ``object``."""
+
+
 BATCH_GUARDRAIL_RESPONSE_FIELD: Final = "litellm_batch_guardrail"
 
 
@@ -1191,7 +1195,7 @@ class ShellToolParam(TypedDict, total=False):
     type: Required[Literal["shell"] | str]
     """The type of tool. Use ``\"shell\"``."""
 
-    environment: Required[dict[str, Any]]
+    environment: Required[dict[str, object]]
     """Environment config: ``type`` (e.g. ``\"container_auto\"``, ``\"container_reference\"``, ``\"local\"``), optional ``container_id``, ``network_policy``, ``domain_secrets``, ``skills``."""
 
 
@@ -1308,7 +1312,7 @@ class ResponseAPIUsage(BaseLiteLLMOpenAIResponseObject):
 
     @field_validator("cost", mode="before")
     @classmethod
-    def parse_cost(cls, v: Any) -> float | None:
+    def parse_cost(cls, v: object) -> object:
         """Normalise cost: accept either a float or a dict with a ``total_cost`` key."""
         if isinstance(v, dict):
             return v.get("total_cost")
@@ -1805,7 +1809,7 @@ class ErrorEventError(BaseLiteLLMOpenAIResponseObject):
     type: str  # e.g., 'invalid_request_error'
     code: str  # e.g., 'context_length_exceeded'
     message: str
-    param: str | dict[str, Any] | None = None
+    param: str | dict[str, object] | None = None
 
 
 class ErrorEvent(BaseLiteLLMOpenAIResponseObject):
@@ -2418,7 +2422,7 @@ class OpenAIVideoObject(BaseModel):
     expires_at: int | None = None
     """Unix timestamp (seconds) for when the downloadable assets expire, if set."""
 
-    error: dict[str, Any] | None = None
+    error: dict[str, _JsonValue] | None = None
     """Error payload that explains why generation failed, if applicable."""
 
     progress: int | None = None
@@ -2436,15 +2440,15 @@ class OpenAIVideoObject(BaseModel):
     model: str | None = None
     """The video generation model that produced the job."""
 
-    _hidden_params: dict[str, Any] = {}
+    _hidden_params: dict[str, _JsonValue] = {}
 
     def __contains__(self, key) -> bool:
         return hasattr(self, key)
 
-    def get(self, key, default=None):
+    def get(self, key, default=None) -> _JsonValue:
         return getattr(self, key, default)
 
-    def __getitem__(self, key):
+    def __getitem__(self, key) -> _JsonValue:
         return getattr(self, key)
 
     def json(self, **kwargs):
diff --git a/litellm/types/router.py b/litellm/types/router.py
index ab6c807ba20..e0957383aac 100644
--- a/litellm/types/router.py
+++ b/litellm/types/router.py
@@ -369,7 +369,7 @@ class GenericLiteLLMParams(CredentialLiteLLMParams, CustomPricingLiteLLMParams):
 
     @model_validator(mode="before")
     @classmethod
-    def preprocess_input_data(cls, data: Any) -> Any:
+    def preprocess_input_data(cls, data: object) -> object:
         """
         Pre-process input data before validation:
         1. Filter out reserved Python keywords ('self', 'params', '__class__') to prevent
@@ -627,6 +627,11 @@ class AlertingConfig(BaseModel):
     alerting_threshold: float | None = 300
 
 
+def _resolved_annotations(model_class: type[object]) -> Mapping[str, object]:
+    """Resolve a class's annotations, keeping each resolved annotation opaque."""
+    return get_type_hints(model_class)
+
+
 class ModelGroupInfo(BaseModel):
     model_group: str
     providers: list[str]
@@ -655,7 +660,7 @@ class ModelGroupInfo(BaseModel):
     configurable_clientside_auth_params: CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS = None
 
     def __init__(self, **data) -> None:
-        for field_name, field_type in get_type_hints(self.__class__).items():
+        for field_name, field_type in _resolved_annotations(self.__class__).items():
             if field_type is bool and data.get(field_name) is None:
                 data[field_name] = False
         super().__init__(**data)
diff --git a/litellm/vector_stores/vector_store_registry.py b/litellm/vector_stores/vector_store_registry.py
index 22d27bc3266..b71d6784873 100644
--- a/litellm/vector_stores/vector_store_registry.py
+++ b/litellm/vector_stores/vector_store_registry.py
@@ -112,7 +112,9 @@ class VectorStoreRegistry:
         Dynamically extracts all parameters defined in VECTOR_STORE_OPENAI_PARAMS.
         """
         # Get the list of supported param names from the Literal type
-        supported_params: Final = get_args(VECTOR_STORE_OPENAI_PARAMS)
+        supported_params: Final = tuple(
+            param for param in get_args(VECTOR_STORE_OPENAI_PARAMS) if isinstance(param, str)
+        )
 
         # Extract only the params that exist in the tool
         kwargs: Final = {param: tool.get(param) for param in supported_params if param in tool}
@@ -503,7 +505,7 @@ class VectorStoreRegistry:
                 vector_stores_from_db.append(_litellm_managed_vector_store)
         return vector_stores_from_db
 
-    def get_credentials_for_vector_store(self, vector_store_id: str) -> dict[str, Any]:
+    def get_credentials_for_vector_store(self, vector_store_id: str) -> dict[str, object]:
         """
         Get the credentials for a vector store
 
diff --git a/ruff-strict-budget.json b/ruff-strict-budget.json
index 569c23cd03f..2dfa92ae694 100644
--- a/ruff-strict-budget.json
+++ b/ruff-strict-budget.json
@@ -1,6 +1,6 @@
 {
   "ANN001": {
-    "limit": 2991
+    "limit": 2985
   },
   "ANN002": {
     "limit": 71
@@ -9,13 +9,13 @@
     "limit": 809
   },
   "ANN201": {
-    "limit": 2002
+    "limit": 2001
   },
   "ANN202": {
-    "limit": 841
+    "limit": 835
   },
   "ANN204": {
-    "limit": 694
+    "limit": 693
   },
   "ANN205": {
     "limit": 112
@@ -24,7 +24,7 @@
     "limit": 133
   },
   "ANN401": {
-    "limit": 387
+    "limit": 307
   },
   "ASYNC230": {
     "limit": 11
@@ -231,7 +231,7 @@
     "limit": 5
   },
   "TID251": {
-    "limit": 1084
+    "limit": 1073
   },
   "TRY002": {
     "limit": 524
@@ -246,7 +246,7 @@
     "limit": 113
   },
   "TRY300": {
-    "limit": 855
+    "limit": 854
   },
   "UP028": {
     "limit": 2
diff --git a/type-discipline-budget.json b/type-discipline-budget.json
index 83c49afb538..3d2e97d55a5 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,9 +1,9 @@
 {
   "LIT001": {
-    "limit": 22403
+    "limit": 22367
   },
   "LIT002": {
-    "limit": 26780
+    "limit": 26777
   },
   "LIT003": {
     "limit": 269
@@ -27,10 +27,10 @@
     "limit": 0
   },
   "LIT010": {
-    "limit": 16512
+    "limit": 16507
   },
   "LIT011": {
-    "limit": 5537
+    "limit": 5535
   },
   "LIT012": {
     "limit": 4495

From 5c0e3d738f4bd0a426b14e59e910e9d61f041c0e Mon Sep 17 00:00:00 2001
From: Yuneng Jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 09:41:51 -0700
Subject: [PATCH 034/113] fix(ui): render the logs Tools panel with theme
 tokens

The tool cards hardcoded light colors as inline styles (#fff, #fafafa,
#f0f0f0, #f6ffed), so in dark mode the theme's light foreground text
landed on a white card and became unreadable.

Swap the inline hex for the existing card/muted/border/success tokens,
which already carry both light and dark values.
---
 .../ToolsSection/FormattedToolView.tsx        | 53 +++----------------
 .../view_logs/ToolsSection/JsonToolView.tsx   | 14 +----
 .../view_logs/ToolsSection/ToolItem.tsx       | 36 ++++---------
 3 files changed, 18 insertions(+), 85 deletions(-)

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>
       )}

From 7abed91523f8a1bfb79697949f070e367a1069c0 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 10:11:25 -0700
Subject: [PATCH 035/113] feat(cost): support day-of-week qualified off-peak
 windows

---
 .../litellm_core_utils/llm_cost_calc/utils.py | 108 ++++++++++++--
 litellm/types/utils.py                        |  27 +++-
 .../llm_cost_calc/test_llm_cost_calc_utils.py | 136 ++++++++++++++++++
 3 files changed, 259 insertions(+), 12 deletions(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index 21680129ed4..c968fac254e 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -4,9 +4,10 @@
 import re
 from collections.abc import Mapping, Sequence
 from dataclasses import dataclass
-from datetime import datetime, timezone
+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
@@ -321,6 +322,99 @@ def _is_within_off_peak_window(off_peak_hours_utc: str | Sequence[str], current_
     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
@@ -342,16 +436,14 @@ def _apply_off_peak_pricing(
     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 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 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 off_peak:
-        return prompt_base_cost, completion_base_cost, cache_read_cost
-    hours_utc: Final = off_peak.get("hours_utc")
-    if not hours_utc or not _is_within_off_peak_window(hours_utc, current_time):
+    if not off_peak 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),
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 3ab3a2382dc..17051714c25 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -193,14 +193,33 @@ class AgenticLoopParams(TypedDict, total=False):
     """The LLM provider name (e.g., 'bedrock', 'anthropic')"""
 
 
-class OffPeakPricing(TypedDict, total=False):
-    """Time-windowed off-peak rates for providers that discount by time of day (e.g. DeepSeek).
+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 for multiple daily windows;
-    a window may wrap past midnight. Any rate left unset falls back to the standard rate.
+    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]
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 c9ed5936f03..501a9314c90 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 +32,7 @@ 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,
@@ -479,6 +480,141 @@ def test_is_within_off_peak_window_malformed_returns_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 3b3099d78dedea9bd576bdcb2dfecabece8c5099 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 10:34:58 -0700
Subject: [PATCH 036/113] fix(prometheus): bound requested_model label
 cardinality on client failure paths

---
 litellm/integrations/prometheus.py            |  40 +++-
 .../test_prometheus_logging_callbacks.py      |  26 ++-
 ..._prometheus_requested_model_cardinality.py | 196 ++++++++++++++++++
 3 files changed, 254 insertions(+), 8 deletions(-)
 create mode 100644 tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py

diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 467ec72dc4a..29b7419a91b 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -59,6 +59,8 @@ from litellm.types.utils import (
 if TYPE_CHECKING:
     from apscheduler.schedulers.asyncio import AsyncIOScheduler
     from prometheus_client.metrics import MetricWrapperBase
+
+    from litellm.router import Router
 else:
     AsyncIOScheduler = Any
 
@@ -67,6 +69,8 @@ _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 +158,34 @@ 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 ImportError:
+        return None
+    return llm_router
+
+
+def _bounded_requested_model_label(requested_model: str | None) -> str | None:
+    """
+    Bound ``requested_model`` label cardinality: names the router recognizes
+    (model names, deployment ids, aliases, routing groups) or matches via a
+    wildcard/pattern route keep their own label value; any other
+    client-supplied string collapses into the single ``other`` bucket. With no
+    router to vouch for the string, it also collapses to ``other``.
+    """
+    if not requested_model:
+        return requested_model
+    llm_router: Final = _get_proxy_llm_router()
+    if llm_router is None:
+        return UNRECOGNIZED_REQUESTED_MODEL_LABEL
+    if llm_router.is_recognized_model(requested_model):
+        return requested_model
+    if llm_router.pattern_router.route(requested_model) is not None:
+        return requested_model
+    return UNRECOGNIZED_REQUESTED_MODEL_LABEL
+
+
 class PrometheusLogger(CustomLogger):
     # Class variables or attributes
 
@@ -2407,7 +2439,7 @@ 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 +2659,7 @@ 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) or ""
 
             enum_values: Final = UserAPIKeyLabelValues(
                 litellm_model_name=label_litellm_model_name,
@@ -3186,7 +3218,7 @@ 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),
             fallback_model=_new_model,
             hashed_api_key=standard_metadata["user_api_key_hash"],
             api_key_alias=standard_metadata["user_api_key_alias"],
@@ -3227,7 +3259,7 @@ class PrometheusLogger(CustomLogger):
         )
 
         enum_values: Final = UserAPIKeyLabelValues(
-            requested_model=original_model_group,
+            requested_model=_bounded_requested_model_label(original_model_group),
             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/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/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..2343384e762
--- /dev/null
+++ b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
@@ -0,0 +1,196 @@
+"""
+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.
+"""
+
+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"},
+    )
+
+
+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_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
+    }
+
+
+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
+    }

From fc091c1248e3cb3276fbebeda2a8ad40aae56bf5 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:04:25 -0700
Subject: [PATCH 037/113] fix(prometheus): keep team alias and team wildcard
 names out of the other bucket

---
 litellm/integrations/prometheus.py            | 16 ++++++--
 ..._prometheus_requested_model_cardinality.py | 38 +++++++++++++++++++
 2 files changed, 50 insertions(+), 4 deletions(-)

diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 29b7419a91b..651f9c5d392 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -169,10 +169,11 @@ def _get_proxy_llm_router() -> Router | None:
 def _bounded_requested_model_label(requested_model: str | None) -> str | None:
     """
     Bound ``requested_model`` label cardinality: names the router recognizes
-    (model names, deployment ids, aliases, routing groups) or matches via a
-    wildcard/pattern route keep their own label value; any other
-    client-supplied string collapses into the single ``other`` bucket. With no
-    router to vouch for the string, it also collapses to ``other``.
+    (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 router to vouch for the string, it also
+    collapses to ``other``.
     """
     if not requested_model:
         return requested_model
@@ -181,8 +182,15 @@ def _bounded_requested_model_label(requested_model: str | None) -> str | None:
         return 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
 
 
diff --git a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
index 2343384e762..8d803eeab18 100644
--- a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
+++ b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
@@ -58,6 +58,24 @@ def router():
     )
 
 
+@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}
@@ -118,6 +136,26 @@ async def test_known_alias_and_wildcard_models_keep_their_own_labels(router):
         }
 
 
+@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()

From fb93db7791c9791b51b2531b945addcc8f3d94fb Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:07:06 +0000
Subject: [PATCH 038/113] feat(models): add Claude Fable 5.1 across Anthropic,
 Bedrock, Vertex AI, and Azure AI

Adds claude-fable-5-1 cost map entries on the Anthropic API, Bedrock converse
(base, global, and us/eu geo inference profiles at the 10% regional premium),
Vertex AI, and Azure AI. Specs match Fable 5 (1M context, 128K output, $10/$50
per MTok, adaptive thinking always on, xhigh and max effort), except cache reads
land at $0.25 per MTok, a quarter of Fable 5's price and 0.025x base input
instead of the usual 0.1x.

Registers anthropic.claude-fable-5-1 in BEDROCK_CONVERSE_MODELS, lists the model
in the setup wizard, and extends the reasoning effort e2e grid. The partner cells
carry fail_reason markers until access on the CI accounts is confirmed.

Partner entries deliberately carry no deprecation_date: Anthropic publishes
retirement no sooner than 2027-09-01 for the first-party model, and the Foundry
and Vertex dates are not published yet.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/constants.py                          |   1 +
 ...odel_prices_and_context_window_backup.json | 289 ++++++++++++++++++
 litellm/setup_wizard.py                       |   3 +-
 model_prices_and_context_window.json          | 289 ++++++++++++++++++
 .../reasoning_effort_grid/grid_spec.py        |  56 ++++
 .../test_claude_fable_5_config.py             | 151 ++++++++-
 6 files changed, 787 insertions(+), 2 deletions(-)

diff --git a/litellm/constants.py b/litellm/constants.py
index c482ab0e39a..a40ea3a9078 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -1240,6 +1240,7 @@ BEDROCK_CONVERSE_MODELS: Final = [
     "openai.gpt-oss-120b-1:0",
     "anthropic.claude-haiku-4-5-20251001-v1:0",
     "anthropic.claude-sonnet-4-5-20250929-v1:0",
+    "anthropic.claude-fable-5-1",
     "anthropic.claude-fable-5",
     "anthropic.claude-sonnet-5",
     "anthropic.claude-opus-5",
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 2cfa1f93f79..cd39d080da7 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1451,6 +1451,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "global.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.25e-05,
         "cache_creation_input_token_cost_above_1hr": 2e-05,
@@ -1488,6 +1525,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "global.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "us.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1525,6 +1599,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "us.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "eu.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1562,6 +1673,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "eu.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "anthropic.claude-opus-5": {
         "bedrock_converse_supports_strict_tools": false,
         "supports_adaptive_thinking": true,
@@ -3079,6 +3227,39 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "azure_ai/claude-fable-5-1": {
+        "supports_mid_conversation_system": true,
+        "input_cost_per_token": 1e-05,
+        "output_cost_per_token": 5e-05,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "azure_ai/claude-opus-5": {
         "deprecation_date": "2027-07-08",
         "supports_mid_conversation_system": true,
@@ -13028,6 +13209,46 @@
         "supports_native_structured_output": true,
         "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview"
     },
+    "claude-fable-5-1": {
+        "deprecation_date": "2027-09-01",
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "anthropic",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "provider_specific_entry": {
+            "us": 1.1
+        },
+        "supports_output_config": true,
+        "prompt_cache_min_tokens": 512,
+        "supports_native_structured_output": true,
+        "source": "https://platform.claude.com/docs/en/models/fable-5-1/overview"
+    },
     "claude-opus-5": {
         "deprecation_date": "2027-07-24",
         "cache_creation_input_token_cost": 6.25e-06,
@@ -41961,6 +42182,40 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "vertex_ai/claude-fable-5-1": {
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "supports_mid_conversation_system": true,
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "vertex_ai-anthropic_models",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "vertex_ai/claude-fable-5@default": {
         "deprecation_date": "2027-06-08",
         "regional_endpoint_uplift_multiplier": 1.1,
@@ -41996,6 +42251,40 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "vertex_ai/claude-fable-5-1@default": {
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "supports_mid_conversation_system": true,
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "vertex_ai-anthropic_models",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "vertex_ai/claude-opus-5": {
         "deprecation_date": "2027-01-24",
         "regional_endpoint_uplift_multiplier": 1.1,
diff --git a/litellm/setup_wizard.py b/litellm/setup_wizard.py
index d6b3dfa3285..dd147aaccee 100644
--- a/litellm/setup_wizard.py
+++ b/litellm/setup_wizard.py
@@ -53,11 +53,12 @@ PROVIDERS: Final[list[dict]] = [
     {
         "id": "anthropic",
         "name": "Anthropic",
-        "description": "Claude Fable 5, Opus 5, Opus 4.8, Opus 4.7, Opus 4.6, Sonnet 5, Sonnet 4.6, Haiku 4.5",
+        "description": "Claude Fable 5.1, Fable 5, Opus 5, Opus 4.8, Opus 4.7, Opus 4.6, Sonnet 5, Sonnet 4.6, Haiku 4.5",
         "env_key": "ANTHROPIC_API_KEY",
         "key_hint": "sk-ant-...",
         "test_model": "claude-haiku-4-5-20251001",
         "models": [
+            "claude-fable-5-1",
             "claude-fable-5",
             "claude-opus-5",
             "claude-sonnet-5",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 2cfa1f93f79..cd39d080da7 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -1451,6 +1451,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "global.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.25e-05,
         "cache_creation_input_token_cost_above_1hr": 2e-05,
@@ -1488,6 +1525,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "global.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "us.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1525,6 +1599,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "us.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "eu.anthropic.claude-fable-5": {
         "cache_creation_input_token_cost": 1.375e-05,
         "cache_creation_input_token_cost_above_1hr": 2.2e-05,
@@ -1562,6 +1673,43 @@
         "supports_parallel_tool_use_config": true,
         "prompt_cache_min_tokens": 512
     },
+    "eu.anthropic.claude-fable-5-1": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_1hr": 2.2e-05,
+        "cache_read_input_token_cost": 2.75e-07,
+        "input_cost_per_token": 1.1e-05,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_native_structured_output": true,
+        "supports_max_reasoning_effort": true,
+        "supports_output_config": true,
+        "bedrock_output_config_effort_ceiling": "xhigh",
+        "supports_parallel_tool_use_config": true,
+        "prompt_cache_min_tokens": 512
+    },
     "anthropic.claude-opus-5": {
         "bedrock_converse_supports_strict_tools": false,
         "supports_adaptive_thinking": true,
@@ -3079,6 +3227,39 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "azure_ai/claude-fable-5-1": {
+        "supports_mid_conversation_system": true,
+        "input_cost_per_token": 1e-05,
+        "output_cost_per_token": 5e-05,
+        "litellm_provider": "azure_ai",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "azure_ai/claude-opus-5": {
         "deprecation_date": "2027-07-08",
         "supports_mid_conversation_system": true,
@@ -13028,6 +13209,46 @@
         "supports_native_structured_output": true,
         "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview"
     },
+    "claude-fable-5-1": {
+        "deprecation_date": "2027-09-01",
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "anthropic",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_mid_conversation_system": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "provider_specific_entry": {
+            "us": 1.1
+        },
+        "supports_output_config": true,
+        "prompt_cache_min_tokens": 512,
+        "supports_native_structured_output": true,
+        "source": "https://platform.claude.com/docs/en/models/fable-5-1/overview"
+    },
     "claude-opus-5": {
         "deprecation_date": "2027-07-24",
         "cache_creation_input_token_cost": 6.25e-06,
@@ -41961,6 +42182,40 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "vertex_ai/claude-fable-5-1": {
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "supports_mid_conversation_system": true,
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "vertex_ai-anthropic_models",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "vertex_ai/claude-fable-5@default": {
         "deprecation_date": "2027-06-08",
         "regional_endpoint_uplift_multiplier": 1.1,
@@ -41996,6 +42251,40 @@
         "supports_max_reasoning_effort": true,
         "prompt_cache_min_tokens": 512
     },
+    "vertex_ai/claude-fable-5-1@default": {
+        "regional_endpoint_uplift_multiplier": 1.1,
+        "supports_mid_conversation_system": true,
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_1hr": 2e-05,
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 1e-05,
+        "litellm_provider": "vertex_ai-anthropic_models",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supports_adaptive_thinking": true,
+        "thinking_always_on": true,
+        "supports_assistant_prefill": false,
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_sampling_params": false,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_xhigh_reasoning_effort": true,
+        "supports_max_reasoning_effort": true,
+        "prompt_cache_min_tokens": 512
+    },
     "vertex_ai/claude-opus-5": {
         "deprecation_date": "2027-01-24",
         "regional_endpoint_uplift_multiplier": 1.1,
diff --git a/tests/llm_translation/reasoning_effort_grid/grid_spec.py b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
index 485f78ed8c7..a21bcb92c64 100644
--- a/tests/llm_translation/reasoning_effort_grid/grid_spec.py
+++ b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
@@ -163,6 +163,19 @@ _CAPS_NONE: FrozenSet[str] = frozenset()
 
 
 ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="claude-fable-5-1",
+        model="anthropic/claude-fable-5-1",
+        mode="adaptive",
+        required_env=_ANTHROPIC_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        fail_reason=(
+            "claude-fable-5-1 access on the CI Anthropic account is not yet "
+            "confirmed for this brand-new release; Anthropic returns "
+            "not_found_error until the account has access, so this cell stays "
+            "loud in CI. Remove this fail_reason once access is confirmed."
+        ),
+    ),
     ModelEntry(
         alias="claude-fable-5",
         model="anthropic/claude-fable-5",
@@ -222,6 +235,19 @@ ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = (
 
 
 AZURE_AI_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="azure-claude-fable-5-1",
+        model="azure_ai/claude-fable-5-1",
+        mode="adaptive",
+        required_env=_AZURE_FOUNDRY_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        fail_reason=(
+            "claude-fable-5-1 has no deployment on the CI Microsoft Foundry "
+            "resource yet, so Foundry returns DeploymentNotFound and this cell "
+            "stays loud in CI. Remove this fail_reason once the deployment "
+            "exists."
+        ),
+    ),
     ModelEntry(
         alias="azure-claude-fable-5",
         model="azure_ai/claude-fable-5",
@@ -268,6 +294,20 @@ AZURE_AI_MODELS: Tuple[ModelEntry, ...] = (
 
 
 VERTEX_AI_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="vertex-claude-fable-5-1",
+        model="vertex_ai/claude-fable-5-1",
+        mode="adaptive",
+        extra_params=(("vertex_location", "global"),),
+        required_env=_VERTEX_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        fail_reason=(
+            "claude-fable-5-1 availability on the CI Vertex project is not yet "
+            "confirmed for this brand-new release, so this cell stays loud in "
+            "CI until verified. Remove this fail_reason once the model is "
+            "confirmed available on the global Vertex endpoint."
+        ),
+    ),
     ModelEntry(
         alias="vertex-claude-fable-5",
         model="vertex_ai/claude-fable-5",
@@ -332,6 +372,22 @@ VERTEX_AI_MODELS: Tuple[ModelEntry, ...] = (
 
 
 BEDROCK_CONVERSE_MODELS: Tuple[ModelEntry, ...] = (
+    ModelEntry(
+        alias="bedrock-claude-fable-5-1",
+        model="bedrock/converse/us.anthropic.claude-fable-5-1",
+        mode="adaptive",
+        extra_params=(("aws_region_name", "us-east-1"),),
+        required_env=_BEDROCK_REQ,
+        caps=_CAPS_XHIGH_MAX,
+        bedrock_effort_ceiling="xhigh",
+        unavailable_error="is not available for this account",
+        fail_reason=(
+            "claude-fable-5-1 access on the CI Bedrock account is not yet "
+            "confirmed for this brand-new release, so this cell stays loud in "
+            "CI until verified. Remove this fail_reason once the model is "
+            "enabled for the account."
+        ),
+    ),
     ModelEntry(
         alias="bedrock-claude-fable-5",
         model="bedrock/converse/us.anthropic.claude-fable-5",
diff --git a/tests/test_litellm/test_claude_fable_5_config.py b/tests/test_litellm/test_claude_fable_5_config.py
index 99c59ffa58e..90ded46e2a4 100644
--- a/tests/test_litellm/test_claude_fable_5_config.py
+++ b/tests/test_litellm/test_claude_fable_5_config.py
@@ -1,5 +1,5 @@
 """
-Validate Claude Fable 5 model configuration entries.
+Validate Claude Fable 5 and Claude Fable 5.1 model configuration entries.
 
 Fable 5 is a new tier above Opus ($10/$50 per MTok) with the same adaptive-only
 API surface as Opus 4.7/4.8. The cost-map entries below are what make the model
@@ -210,6 +210,155 @@ def test_adaptive_thinking_detected_for_fable_5(local_model_cost_map, model):
     assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
 
 
+FABLE_5_1_VARIANTS = (
+    "claude-fable-5-1",
+    "anthropic.claude-fable-5-1",
+    "global.anthropic.claude-fable-5-1",
+    "us.anthropic.claude-fable-5-1",
+    "eu.anthropic.claude-fable-5-1",
+    "vertex_ai/claude-fable-5-1",
+    "vertex_ai/claude-fable-5-1@default",
+    "azure_ai/claude-fable-5-1",
+)
+
+
+def test_fable_5_1_model_pricing_and_capabilities():
+    model_data = _load_root_cost_map()
+
+    expected_models = [
+        ("claude-fable-5-1", "anthropic"),
+        ("anthropic.claude-fable-5-1", "bedrock_converse"),
+        ("vertex_ai/claude-fable-5-1", "vertex_ai-anthropic_models"),
+        ("azure_ai/claude-fable-5-1", "azure_ai"),
+    ]
+
+    for model_name, provider in expected_models:
+        assert model_name in model_data, f"Missing model entry: {model_name}"
+        info = model_data[model_name]
+
+        assert info["litellm_provider"] == provider
+        assert info["mode"] == "chat"
+        assert info["max_input_tokens"] == 1000000
+        assert info["max_output_tokens"] == 128000
+        assert info["max_tokens"] == 128000
+
+        assert info["input_cost_per_token"] == 1e-05
+        assert info["output_cost_per_token"] == 5e-05
+        assert info["cache_creation_input_token_cost"] == 1.25e-05
+        assert info["cache_creation_input_token_cost_above_1hr"] == 2e-05
+
+        assert "input_cost_per_token_above_200k_tokens" not in info
+        assert "output_cost_per_token_above_200k_tokens" not in info
+
+        assert info["supports_assistant_prefill"] is False
+        assert info["supports_function_calling"] is True
+        assert info["supports_prompt_caching"] is True
+        assert info["supports_reasoning"] is True
+        assert info["supports_tool_choice"] is True
+        assert info["supports_vision"] is True
+        assert info["supports_xhigh_reasoning_effort"] is True
+        assert info["supports_max_reasoning_effort"] is True
+        assert info["prompt_cache_min_tokens"] == 512
+
+
+@pytest.mark.parametrize(
+    "cost_map",
+    [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],
+    ids=["root", "bundled_backup"],
+)
+def test_fable_5_1_cache_reads_cost_a_quarter_of_fable_5(cost_map):
+    """Fable 5.1 prices cache hits at 0.025x base input instead of the usual
+    0.1x, so copying Fable 5's cache-read price overcharges every cache hit 4x."""
+    for model_name in FABLE_5_1_VARIANTS:
+        info = cost_map[model_name]
+        geo_premium = model_name.startswith(("us.", "eu."))
+        expected = 2.75e-07 if geo_premium else 2.5e-07
+        assert info["cache_read_input_token_cost"] == expected, model_name
+        assert info["cache_read_input_token_cost"] == pytest.approx(
+            info["input_cost_per_token"] * 0.025
+        ), model_name
+
+
+def test_fable_5_1_bedrock_regional_model_pricing():
+    model_data = _load_root_cost_map()
+
+    expected_models = {
+        "global.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1e-05,
+            "output_cost_per_token": 5e-05,
+            "cache_creation_input_token_cost": 1.25e-05,
+            "cache_read_input_token_cost": 2.5e-07,
+        },
+        "us.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1.1e-05,
+            "output_cost_per_token": 5.5e-05,
+            "cache_creation_input_token_cost": 1.375e-05,
+            "cache_read_input_token_cost": 2.75e-07,
+        },
+        "eu.anthropic.claude-fable-5-1": {
+            "input_cost_per_token": 1.1e-05,
+            "output_cost_per_token": 5.5e-05,
+            "cache_creation_input_token_cost": 1.375e-05,
+            "cache_read_input_token_cost": 2.75e-07,
+        },
+    }
+
+    for model_name, expected in expected_models.items():
+        assert model_name in model_data, f"Missing model entry: {model_name}"
+        info = model_data[model_name]
+        assert info["litellm_provider"] == "bedrock_converse"
+        assert info["max_input_tokens"] == 1000000
+        assert info["max_output_tokens"] == 128000
+        assert info["bedrock_output_config_effort_ceiling"] == "xhigh"
+        for key, value in expected.items():
+            assert info[key] == value
+
+
+def test_fable_5_1_geo_multiplier_without_fast_mode():
+    """Fable 5.1 has no fast mode, so a ``fast`` key here would misprice
+    ``speed='fast'`` requests."""
+    model_data = _load_root_cost_map()
+    assert model_data["claude-fable-5-1"]["provider_specific_entry"] == {"us": 1.1}
+
+
+def test_fable_5_1_present_in_bundled_backup():
+    backup = GetModelCostMap.load_local_model_cost_map()
+    root = _load_root_cost_map()
+    for model_name in FABLE_5_1_VARIANTS:
+        assert model_name in backup, f"Missing from backup cost map: {model_name}"
+        assert backup[model_name] == root[model_name], model_name
+
+
+def test_fable_5_1_registered_for_bedrock_converse():
+    assert "anthropic.claude-fable-5-1" in BEDROCK_CONVERSE_MODELS
+
+
+def test_fable_5_1_provider_resolves_via_model_info(local_model_cost_map):
+    info = litellm.get_model_info(model="claude-fable-5-1")
+    assert info["litellm_provider"] == "anthropic"
+    assert info["max_input_tokens"] == 1000000
+    assert info["max_output_tokens"] == 128000
+
+
+@pytest.mark.parametrize(
+    "model",
+    [
+        "claude-fable-5-1",
+        "anthropic/claude-fable-5-1",
+        "anthropic.claude-fable-5-1",
+        "bedrock/us.anthropic.claude-fable-5-1",
+        "bedrock/invoke/eu.anthropic.claude-fable-5-1",
+        "bedrock/global.anthropic.claude-fable-5-1",
+        "vertex_ai/claude-fable-5-1",
+        "azure_ai/claude-fable-5-1",
+    ],
+)
+def test_adaptive_thinking_detected_for_fable_5_1(local_model_cost_map, model):
+    from litellm.llms.anthropic.common_utils import AnthropicModelInfo
+
+    assert AnthropicModelInfo._is_adaptive_thinking_model(model, "anthropic") is True
+
+
 @pytest.mark.parametrize(
     "cost_map",
     [_load_root_cost_map(), GetModelCostMap.load_local_model_cost_map()],

From ab2c9aed0fb9caf31173e18ac11bd1fd0a2f4996 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:12:24 -0700
Subject: [PATCH 039/113] fix(responses): normalize tool call id shapes across
 the anthropic bridge and openai replay

The chat-completions bridge emitted Responses output items whose item ids
were raw Anthropic tool ids (toolu_/srvtoolu_), which OpenAI rejects on
replay with "Expected an ID that begins with 'fc'", breaking router
fallback conversations from gpt-5 to claude models.

Four fixes, composable and independently useful:
- emission: bridge output items get fc_/ctc_-prefixed item ids while
  call_id stays raw so tool_result pairing keeps working (streaming and
  non-streaming share the same helpers)
- openai replay: request transformation drops tool call item ids that do
  not match OpenAI's own shapes instead of forwarding them, gated to
  OpenAI and Azure, since the API accepts the items with no id at all
- anthropic replay: a replayed srvtoolu_ call whose paired server tool
  result is unavailable degrades to a plain client tool_use instead of a
  dangling server_tool_use that 400s the client's tool_result
- tool-only turns no longer emit a message output item with output_text
  text null, matching native OpenAI output
---
 .../prompt_templates/factory.py               |  52 ++++-----
 .../llms/openai/responses/transformation.py   |  27 ++++-
 .../custom_tools.py                           |  12 +-
 .../transformation.py                         |   8 +-
 ...llm_core_utils_prompt_templates_factory.py |  64 +++++++++++
 .../test_openai_responses_transformation.py   | 105 ++++++++++++++++++
 .../test_litellm_completion_responses.py      |  66 +++++++++++
 .../test_streaming_iterator_transformation.py |   3 +-
 .../responses/test_custom_tool_call.py        |  82 ++++++++++++++
 9 files changed, 386 insertions(+), 33 deletions(-)

diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index 795fb36961e..3d06b975342 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[Any] | None,
+    tool_results: Sequence[Any] | None,
+) -> dict[str, Any] | 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",
diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py
index eadc087383a..bb3b78e4df2 100644
--- a/litellm/llms/openai/responses/transformation.py
+++ b/litellm/llms/openai/responses/transformation.py
@@ -14,6 +14,7 @@ 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 *
@@ -35,6 +36,7 @@ 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 OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
@@ -179,8 +181,9 @@ 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
@@ -217,6 +220,23 @@ 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,
@@ -742,7 +762,10 @@ 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/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/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/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..64c96b575c5 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
@@ -3627,3 +3627,67 @@ 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/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/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
index aba79fe11bf..fa373759cdd 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
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..59bd80791e3 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
@@ -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():
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

From 93a03a9ffd0475aae4dd60f81f713d60eaf6a4df Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:16:56 -0700
Subject: [PATCH 040/113] fix(openai): drop tool_choice when request has no
 tools on chat completions

---
 .../llms/openai/chat/gpt_transformation.py    |   4 +
 .../chat/test_openai_gpt_transformation.py    | 128 ++++++++++++++++++
 2 files changed, 132 insertions(+)

diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py
index d4747b2fb06..ee295bb5f4f 100644
--- a/litellm/llms/openai/chat/gpt_transformation.py
+++ b/litellm/llms/openai/chat/gpt_transformation.py
@@ -443,6 +443,8 @@ 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,
@@ -473,6 +475,8 @@ 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,
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..ba7067322d8 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)."""

From fcc203e35b6e9e4aa449af1be1f6a6a81435e404 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:17:39 +0000
Subject: [PATCH 041/113] test(reasoning-effort-grid): let the Anthropic Fable
 5.1 cells run

Access is confirmed on the Anthropic account, and all 11 cells pass live, so the
xfail marker would only hide real regressions.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 tests/llm_translation/reasoning_effort_grid/grid_spec.py | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/tests/llm_translation/reasoning_effort_grid/grid_spec.py b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
index a21bcb92c64..aa9f66f6665 100644
--- a/tests/llm_translation/reasoning_effort_grid/grid_spec.py
+++ b/tests/llm_translation/reasoning_effort_grid/grid_spec.py
@@ -169,12 +169,6 @@ ANTHROPIC_DIRECT_MODELS: Tuple[ModelEntry, ...] = (
         mode="adaptive",
         required_env=_ANTHROPIC_REQ,
         caps=_CAPS_XHIGH_MAX,
-        fail_reason=(
-            "claude-fable-5-1 access on the CI Anthropic account is not yet "
-            "confirmed for this brand-new release; Anthropic returns "
-            "not_found_error until the account has access, so this cell stays "
-            "loud in CI. Remove this fail_reason once access is confirmed."
-        ),
     ),
     ModelEntry(
         alias="claude-fable-5",

From 1ba13fcc25ff2401d6ed87541d97ab275e3b1430 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:17:55 -0700
Subject: [PATCH 042/113] fix(cost): keep off_peak_pricing scoped to its
 deployment

register_model inserted the first deployment's off_peak_pricing dict by
reference into the shared backend cost-map entry, and later deployments
sharing that backend merged their schedules into the same object,
corrupting the first deployment's schedule and polluting the built-in
entry. Nested dicts now merge copy-on-write, and off_peak_pricing stays
off the shared backend keys.
---
 litellm/types/utils.py                        | 17 ++--
 litellm/utils.py                              |  5 +-
 .../test_register_model_custom_pricing.py     | 98 +++++++++++++++++++
 3 files changed, 111 insertions(+), 9 deletions(-)

diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 17051714c25..4cba3193e43 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -3506,17 +3506,22 @@ 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}
 
diff --git a/litellm/utils.py b/litellm/utils.py
index 3389b8fcb78..2014df6b17c 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -2851,10 +2851,9 @@ 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
 
diff --git a/tests/test_litellm/test_register_model_custom_pricing.py b/tests/test_litellm/test_register_model_custom_pricing.py
index 39f498b4e58..87e9895806f 100644
--- a/tests/test_litellm/test_register_model_custom_pricing.py
+++ b/tests/test_litellm/test_register_model_custom_pricing.py
@@ -793,3 +793,101 @@ 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

From f3792fb7003c22cbe2dab48e3b54ba65c02b43f5 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:20:36 -0700
Subject: [PATCH 043/113] feat(dashscope): add qwencloud and qwen_ai_platform
 provider aliases

---
 README.md                                     |    2 +
 litellm/__init__.py                           |   28 +
 litellm/_lazy_imports_registry.py             |   10 +
 litellm/constants.py                          |   13 +-
 litellm/cost_calculator.py                    |    4 +-
 litellm/images/main.py                        |    2 +
 .../get_llm_provider_logic.py                 |   12 +-
 litellm/llms/dashscope/chat/transformation.py |   14 +-
 litellm/llms/dashscope/common_utils.py        |   74 +
 litellm/llms/dashscope/cost_calculator.py     |    5 +-
 .../llms/dashscope/embed/transformation.py    |   26 +-
 .../image_generation/transformation.py        |   16 +-
 litellm/llms/dashscope/qwen_ai_platform.py    |   62 +
 litellm/llms/dashscope/qwencloud.py           |   62 +
 .../llms/dashscope/rerank/transformation.py   |   36 +-
 litellm/main.py                               |   16 +-
 ...odel_prices_and_context_window_backup.json | 1904 +++++++++++++++++
 .../provider_endpoints_support_backup.json    |   36 +
 .../provider_create_fields.json               |   56 +
 litellm/types/utils.py                        |    2 +
 litellm/utils.py                              |   47 +-
 model_prices_and_context_window.json          | 1904 +++++++++++++++++
 provider_endpoints_support.json               |   36 +
 .../llms/dashscope/test_qwen_brand_aliases.py |  331 +++
 .../src/components/provider_info_helpers.tsx  |    6 +
 25 files changed, 4638 insertions(+), 66 deletions(-)
 create mode 100644 litellm/llms/dashscope/qwen_ai_platform.py
 create mode 100644 litellm/llms/dashscope/qwencloud.py
 create mode 100644 tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py

diff --git a/README.md b/README.md
index 68aaa09ec98..92757fcbbc1 100644
--- a/README.md
+++ b/README.md
@@ -354,6 +354,8 @@ curl -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
 | [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Pinstripes (`pinstripes`)](https://docs.litellm.ai/docs/providers/pinstripes) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Predibase (`predibase`)](https://docs.litellm.ai/docs/providers/predibase) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
+| [Qwen AI Platform (`qwen_ai_platform`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  | ✅ |
+| [QwenCloud (`qwencloud`)](https://docs.litellm.ai/docs/providers/qwencloud) | ✅ | ✅ | ✅ | ✅ | ✅ |  |  |  |  | ✅ |
 | [Recraft (`recraft`)](https://docs.litellm.ai/docs/providers/recraft) |  |  |  |  | ✅ |  |  |  |  |  |
 | [Replicate (`replicate`)](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
 | [Sagemaker Chat (`sagemaker_chat`)](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ |  |  |  |  |  |  |  |
diff --git a/litellm/__init__.py b/litellm/__init__.py
index 1447e05fdf7..4eeececdb7e 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -659,6 +659,8 @@ aiml_models: Set = set()
 deepgram_models: Set = set()
 elevenlabs_models: Set = set()
 dashscope_models: Set = set()
+qwencloud_models: Set = set()
+qwen_ai_platform_models: Set = set()
 moonshot_models: Set = set()
 publicai_models: Set = set()
 darkbloom_models: Set = set()
@@ -909,6 +911,10 @@ def _populate_provider_model_sets(model_cost_map: Dict) -> None:
             heroku_models.add(key)
         elif value.get("litellm_provider") == "dashscope":
             dashscope_models.add(key)
+        elif value.get("litellm_provider") == "qwencloud":
+            qwencloud_models.add(key)
+        elif value.get("litellm_provider") == "qwen_ai_platform":
+            qwen_ai_platform_models.add(key)
         elif value.get("litellm_provider") == "modelscope":
             modelscope_models.add(key)
         elif value.get("litellm_provider") == "moonshot":
@@ -1072,6 +1078,8 @@ model_list = list(
     | deepgram_models
     | elevenlabs_models
     | dashscope_models
+    | qwencloud_models
+    | qwen_ai_platform_models
     | moonshot_models
     | publicai_models
     | darkbloom_models
@@ -1178,6 +1186,8 @@ def _build_models_by_provider() -> dict:
         "elevenlabs": elevenlabs_models,
         "heroku": heroku_models,
         "dashscope": dashscope_models,
+        "qwencloud": qwencloud_models,
+        "qwen_ai_platform": qwen_ai_platform_models,
         "modelscope": modelscope_models,
         "moonshot": moonshot_models,
         "publicai": publicai_models,
@@ -2014,6 +2024,24 @@ if TYPE_CHECKING:
     from .llms.dashscope.rerank.transformation import (
         DashScopeRerankConfig as DashScopeRerankConfig,
     )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudChatConfig as QwenCloudChatConfig,
+    )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudEmbeddingConfig as QwenCloudEmbeddingConfig,
+    )
+    from .llms.dashscope.qwencloud import (
+        QwenCloudRerankConfig as QwenCloudRerankConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformChatConfig as QwenAIPlatformChatConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformEmbeddingConfig as QwenAIPlatformEmbeddingConfig,
+    )
+    from .llms.dashscope.qwen_ai_platform import (
+        QwenAIPlatformRerankConfig as QwenAIPlatformRerankConfig,
+    )
     from .llms.modelscope.chat.transformation import (
         ModelScopeChatConfig as ModelScopeChatConfig,
     )
diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py
index 1c833256598..e9199e1ec80 100644
--- a/litellm/_lazy_imports_registry.py
+++ b/litellm/_lazy_imports_registry.py
@@ -310,6 +310,8 @@ LLM_CONFIG_NAMES: Final = (
     "GigaChatConfig",
     "GigaChatEmbeddingConfig",
     "DashScopeChatConfig",
+    "QwenCloudChatConfig",
+    "QwenAIPlatformChatConfig",
     "ModelScopeChatConfig",
     "MoonshotChatConfig",
     "DockerModelRunnerChatConfig",
@@ -1172,6 +1174,14 @@ _LLM_CONFIGS_IMPORT_MAP: Final = {
         ".llms.dashscope.chat.transformation",
         "DashScopeChatConfig",
     ),
+    "QwenCloudChatConfig": (
+        ".llms.dashscope.qwencloud",
+        "QwenCloudChatConfig",
+    ),
+    "QwenAIPlatformChatConfig": (
+        ".llms.dashscope.qwen_ai_platform",
+        "QwenAIPlatformChatConfig",
+    ),
     "GDCGeminiConfig": (
         ".llms.gdc.chat.transformation",
         "GDCGeminiConfig",
diff --git a/litellm/constants.py b/litellm/constants.py
index c482ab0e39a..a5751a416a1 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -630,6 +630,8 @@ LITELLM_CHAT_PROVIDERS: Final = [
     "nscale",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "publicai",
@@ -799,6 +801,7 @@ openai_compatible_endpoints: Final[list] = [
     "inference.api.nscale.com/v1",
     "api.studio.nebius.ai/v1",
     "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
+    "https://dashscope.aliyuncs.com/compatible-mode/v1",
     "https://api-inference.modelscope.cn/v1",
     "https://api.moonshot.ai/v1",
     "https://api.publicai.co/v1",
@@ -872,6 +875,8 @@ openai_compatible_providers: Final[list] = [
     "nscale",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "v0",
@@ -902,6 +907,8 @@ openai_text_completion_compatible_providers: Final[list] = [  # providers that s
     "featherless_ai",
     "nebius",
     "dashscope",
+    "qwencloud",
+    "qwen_ai_platform",
     "modelscope",
     "moonshot",
     "publicai",
@@ -1109,7 +1116,7 @@ nebius_models: Final[set] = set(
     ]
 )
 
-dashscope_models: Final[set] = set(
+dashscope_models: Final[frozenset] = frozenset(
     [
         "qwen-turbo",
         "qwen-plus",
@@ -1124,6 +1131,10 @@ dashscope_models: Final[set] = set(
     ]
 )
 
+qwencloud_models: Final[frozenset] = frozenset(dashscope_models)
+
+qwen_ai_platform_models: Final[frozenset] = frozenset(dashscope_models)
+
 nebius_embedding_models: Final[set] = set(
     [
         "BAAI/bge-en-icl",
diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py
index 78f34abf766..17c78192117 100644
--- a/litellm/cost_calculator.py
+++ b/litellm/cost_calculator.py
@@ -641,12 +641,12 @@ def cost_per_token(
         return xai_cost_per_token(model=model, usage=usage_block)
     elif custom_llm_provider == "lemonade":
         return lemonade_cost_per_token(model=model, usage=usage_block)
-    elif custom_llm_provider == "dashscope":
+    elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
         from litellm.llms.dashscope.cost_calculator import (
             cost_per_token as dashscope_cost_per_token,
         )
 
-        return dashscope_cost_per_token(model=model, usage=usage_block)
+        return dashscope_cost_per_token(model=model, usage=usage_block, custom_llm_provider=custom_llm_provider)
     elif custom_llm_provider == "azure_ai":
         return azure_ai_cost_per_token(
             model=model,
diff --git a/litellm/images/main.py b/litellm/images/main.py
index 1688087c2da..8a1c2516289 100644
--- a/litellm/images/main.py
+++ b/litellm/images/main.py
@@ -386,6 +386,8 @@ def image_generation(
             litellm.LlmProviders.VERTEX_AI,
             litellm.LlmProviders.OPENROUTER,
             litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
         ):
             if image_generation_config is None:
                 raise ValueError(f"image generation config is not supported for {custom_llm_provider}")
diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 9b53b79bbe6..207e024ce0b 100644
--- a/litellm/litellm_core_utils/get_llm_provider_logic.py
+++ b/litellm/litellm_core_utils/get_llm_provider_logic.py
@@ -536,6 +536,14 @@ def get_llm_provider(
             )
 
 
+def _dashscope_family_chat_config(custom_llm_provider: str) -> "litellm.DashScopeChatConfig":
+    if custom_llm_provider == "qwencloud":
+        return litellm.QwenCloudChatConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        return litellm.QwenAIPlatformChatConfig()
+    return litellm.DashScopeChatConfig()
+
+
 def _get_openai_compatible_provider_info(
     model: str,
     api_base: str | None,
@@ -785,11 +793,11 @@ def _get_openai_compatible_provider_info(
             api_base,
             dynamic_api_key,
         ) = litellm.HerokuChatConfig()._get_openai_compatible_provider_info(api_base, api_key)
-    elif custom_llm_provider == "dashscope":
+    elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
         (
             api_base,
             dynamic_api_key,
-        ) = litellm.DashScopeChatConfig()._get_openai_compatible_provider_info(api_base, api_key)
+        ) = _dashscope_family_chat_config(custom_llm_provider)._get_openai_compatible_provider_info(api_base, api_key)
     elif custom_llm_provider == "modelscope":
         (
             api_base,
diff --git a/litellm/llms/dashscope/chat/transformation.py b/litellm/llms/dashscope/chat/transformation.py
index 5ab7fbf3658..26e60fa959d 100644
--- a/litellm/llms/dashscope/chat/transformation.py
+++ b/litellm/llms/dashscope/chat/transformation.py
@@ -54,6 +54,9 @@ class DashScopeChatConfig(OpenAIGPTConfig):
         dynamic_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
         return api_base, dynamic_api_key
 
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or "https://dashscope.aliyuncs.com/compatible-mode/v1"
+
     def get_complete_url(
         self,
         api_base: str | None,
@@ -66,10 +69,7 @@ class DashScopeChatConfig(OpenAIGPTConfig):
         """
         If api_base is not provided, use the default DashScope /chat/completions endpoint.
         """
-        if not api_base:
-            api_base = "https://dashscope.aliyuncs.com/compatible-mode/v1"
-
-        if not api_base.endswith("/chat/completions"):
-            api_base = f"{api_base}/chat/completions"
-
-        return api_base
+        resolved_api_base: Final = self._resolve_chat_api_base(api_base)
+        if resolved_api_base.endswith("/chat/completions"):
+            return resolved_api_base
+        return f"{resolved_api_base}/chat/completions"
diff --git a/litellm/llms/dashscope/common_utils.py b/litellm/llms/dashscope/common_utils.py
index 9a7dd4da8d3..926b6f0ffc7 100644
--- a/litellm/llms/dashscope/common_utils.py
+++ b/litellm/llms/dashscope/common_utils.py
@@ -2,9 +2,83 @@
 Common utilities for the DashScope LLM provider.
 """
 
+from typing import TYPE_CHECKING
+
 import httpx
 
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.secret_managers.main import get_secret_str
+
+if TYPE_CHECKING:
+    from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+    from litellm.llms.base_llm.image_generation.transformation import (
+        BaseImageGenerationConfig,
+    )
+    from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
+
+
+def get_dashscope_family_embedding_config(custom_llm_provider: str) -> "BaseEmbeddingConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudEmbeddingConfig
+
+        return QwenCloudEmbeddingConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import (
+            QwenAIPlatformEmbeddingConfig,
+        )
+
+        return QwenAIPlatformEmbeddingConfig()
+    from litellm.llms.dashscope.embed.transformation import DashScopeEmbeddingConfig
+
+    return DashScopeEmbeddingConfig()
+
+
+def get_dashscope_family_rerank_config(custom_llm_provider: str) -> "BaseRerankConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudRerankConfig
+
+        return QwenCloudRerankConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import QwenAIPlatformRerankConfig
+
+        return QwenAIPlatformRerankConfig()
+    from litellm.llms.dashscope.rerank.transformation import DashScopeRerankConfig
+
+    return DashScopeRerankConfig()
+
+
+def get_dashscope_family_image_generation_config(
+    custom_llm_provider: str,
+) -> "BaseImageGenerationConfig":
+    if custom_llm_provider == "qwencloud":
+        from litellm.llms.dashscope.qwencloud import QwenCloudImageGenerationConfig
+
+        return QwenCloudImageGenerationConfig()
+    if custom_llm_provider == "qwen_ai_platform":
+        from litellm.llms.dashscope.qwen_ai_platform import (
+            QwenAIPlatformImageGenerationConfig,
+        )
+
+        return QwenAIPlatformImageGenerationConfig()
+    from litellm.llms.dashscope.image_generation.transformation import (
+        DashScopeImageGenerationConfig,
+    )
+
+    return DashScopeImageGenerationConfig()
+
+
+def resolve_dashscope_family_api_key(custom_llm_provider: str, api_key: str | None) -> str | None:
+    if custom_llm_provider == "dashscope":
+        return api_key or get_secret_str("DASHSCOPE_API_KEY")
+    return api_key or get_secret_str(f"{custom_llm_provider.upper()}_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def missing_dashscope_family_key_message(custom_llm_provider: str) -> str:
+    if custom_llm_provider == "qwencloud":
+        return "Missing API key for QwenCloud. Set QWENCLOUD_API_KEY or DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+    if custom_llm_provider == "qwen_ai_platform":
+        return "Missing API key for Qwen AI Platform. Set QWEN_AI_PLATFORM_API_KEY or DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+    return "Missing API key for DashScope. Set DASHSCOPE_API_KEY environment variable or pass api_key parameter."
 
 
 class DashScopeError(BaseLLMException):
diff --git a/litellm/llms/dashscope/cost_calculator.py b/litellm/llms/dashscope/cost_calculator.py
index 771ce140f66..dd5bee1fe8b 100644
--- a/litellm/llms/dashscope/cost_calculator.py
+++ b/litellm/llms/dashscope/cost_calculator.py
@@ -110,7 +110,7 @@ def _calculate_completion_cost(
     return (breakdown.completion_tokens * output_cost) + (breakdown.reasoning_tokens * reasoning_cost)
 
 
-def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
+def cost_per_token(model: str, usage: Usage, custom_llm_provider: str = "dashscope") -> tuple[float, float]:
     """
     Calculate cost per token for Dashscope models.
 
@@ -119,11 +119,12 @@ def cost_per_token(model: str, usage: Usage) -> tuple[float, float]:
     Args:
         model: Model name without provider prefix
         usage: LiteLLM Usage block
+        custom_llm_provider: The provider id the request resolved to; dashscope or one of its brand aliases
 
     Returns:
         Tuple[float, float] - (prompt_cost_in_usd, completion_cost_in_usd)
     """
-    model_info: Final = get_model_info(model=model, custom_llm_provider="dashscope")
+    model_info: Final = get_model_info(model=model, custom_llm_provider=custom_llm_provider)
     breakdown: Final = _extract_token_breakdown(usage)
     raw_tiers: Final = model_info.get("tiered_pricing")
     tiered_pricing: Final = raw_tiers if isinstance(raw_tiers, list) else None
diff --git a/litellm/llms/dashscope/embed/transformation.py b/litellm/llms/dashscope/embed/transformation.py
index 6d13f1e53f7..63ee984a65c 100644
--- a/litellm/llms/dashscope/embed/transformation.py
+++ b/litellm/llms/dashscope/embed/transformation.py
@@ -62,6 +62,17 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
             # for drop_params=False before this method is called.
         return optional_params
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key if api_key is not None else get_secret_str("DASHSCOPE_API_KEY")
+        if resolved_api_key is None:
+            raise ValueError(
+                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
+            )
+        return resolved_api_key
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("DASHSCOPE_API_BASE") or DEFAULT_API_BASE
+
     def validate_environment(
         self,
         headers: dict,
@@ -72,17 +83,11 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
         api_key: str | None = None,
         api_base: str | None = None,
     ) -> dict:
-        if api_key is None:
-            api_key = get_secret_str("DASHSCOPE_API_KEY")
-        if api_key is None:
-            raise ValueError(
-                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
-            )
-        default_headers: Final = {
+        return {
             "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
+            "Authorization": f"Bearer {self._resolve_api_key(api_key)}",
+            **headers,
         }
-        return {**default_headers, **headers}
 
     def get_complete_url(
         self,
@@ -93,8 +98,7 @@ class DashScopeEmbeddingConfig(BaseEmbeddingConfig):
         litellm_params: dict,
         stream: bool | None = None,
     ) -> str:
-        base = api_base or get_secret_str("DASHSCOPE_API_BASE") or DEFAULT_API_BASE
-        base = base.rstrip("/")
+        base: Final = self._resolve_embedding_api_base(api_base).rstrip("/")
         if base.endswith("/embeddings"):
             return base
         return f"{base}/embeddings"
diff --git a/litellm/llms/dashscope/image_generation/transformation.py b/litellm/llms/dashscope/image_generation/transformation.py
index a7f0e98865f..c0e278a96ef 100644
--- a/litellm/llms/dashscope/image_generation/transformation.py
+++ b/litellm/llms/dashscope/image_generation/transformation.py
@@ -91,6 +91,15 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
                 mapped[k] = v
         return mapped
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
+        if not resolved_api_key:
+            raise ValueError("DASHSCOPE_API_KEY is not set")
+        return resolved_api_key
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("DASHSCOPE_API_BASE_IMAGE") or DEFAULT_API_BASE
+
     def get_complete_url(
         self,
         api_base: str | None,
@@ -103,7 +112,7 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
         image_api_base: Final = (
             api_base if api_base and not api_base.rstrip("/").endswith(CHAT_COMPATIBLE_MODE_PATH) else None
         )
-        return image_api_base or get_secret_str("DASHSCOPE_API_BASE_IMAGE") or DEFAULT_API_BASE
+        return self._resolve_image_api_base(image_api_base)
 
     def validate_environment(
         self,
@@ -115,10 +124,7 @@ class DashScopeImageGenerationConfig(BaseImageGenerationConfig):
         api_key: str | None = None,
         api_base: str | None = None,
     ) -> dict:
-        final_api_key: Final = api_key or get_secret_str("DASHSCOPE_API_KEY")
-        if not final_api_key:
-            raise ValueError("DASHSCOPE_API_KEY is not set")
-        headers["Authorization"] = f"Bearer {final_api_key}"
+        headers["Authorization"] = f"Bearer {self._resolve_api_key(api_key)}"
         headers["Content-Type"] = "application/json"
         return headers
 
diff --git a/litellm/llms/dashscope/qwen_ai_platform.py b/litellm/llms/dashscope/qwen_ai_platform.py
new file mode 100644
index 00000000000..9a44eaf574a
--- /dev/null
+++ b/litellm/llms/dashscope/qwen_ai_platform.py
@@ -0,0 +1,62 @@
+from typing import Final
+
+from litellm.secret_managers.main import get_secret_str
+
+from .chat.transformation import DashScopeChatConfig
+from .embed.transformation import DashScopeEmbeddingConfig
+from .image_generation.transformation import DashScopeImageGenerationConfig
+from .rerank.transformation import DashScopeRerankConfig
+
+QWEN_AI_PLATFORM_API_BASE: Final = "https://dashscope.aliyuncs.com/compatible-mode/v1"
+QWEN_AI_PLATFORM_RERANK_API_BASE: Final = "https://dashscope.aliyuncs.com/compatible-api/v1/reranks"
+QWEN_AI_PLATFORM_IMAGE_API_BASE: Final = (
+    "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
+)
+
+
+def _resolve_qwen_ai_platform_api_key(api_key: str | None) -> str | None:
+    return api_key or get_secret_str("QWEN_AI_PLATFORM_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def _require_qwen_ai_platform_api_key(api_key: str | None) -> str:
+    resolved: Final = _resolve_qwen_ai_platform_api_key(api_key)
+    if resolved is None:
+        raise ValueError(
+            "Qwen AI Platform API key is required. Set 'QWEN_AI_PLATFORM_API_KEY' or 'DASHSCOPE_API_KEY' env var "
+            "or pass api_key explicitly."
+        )
+    return resolved
+
+
+class QwenAIPlatformChatConfig(DashScopeChatConfig):
+    def _get_openai_compatible_provider_info(
+        self, api_base: str | None, api_key: str | None
+    ) -> tuple[str | None, str | None]:
+        return self._resolve_chat_api_base(api_base), _resolve_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE") or QWEN_AI_PLATFORM_API_BASE
+
+
+class QwenAIPlatformEmbeddingConfig(DashScopeEmbeddingConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE") or QWEN_AI_PLATFORM_API_BASE
+
+
+class QwenAIPlatformRerankConfig(DashScopeRerankConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE_RERANK") or QWEN_AI_PLATFORM_RERANK_API_BASE
+
+
+class QwenAIPlatformImageGenerationConfig(DashScopeImageGenerationConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwen_ai_platform_api_key(api_key)
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("QWEN_AI_PLATFORM_API_BASE_IMAGE") or QWEN_AI_PLATFORM_IMAGE_API_BASE
diff --git a/litellm/llms/dashscope/qwencloud.py b/litellm/llms/dashscope/qwencloud.py
new file mode 100644
index 00000000000..d8d53e340ef
--- /dev/null
+++ b/litellm/llms/dashscope/qwencloud.py
@@ -0,0 +1,62 @@
+from typing import Final
+
+from litellm.secret_managers.main import get_secret_str
+
+from .chat.transformation import DashScopeChatConfig
+from .embed.transformation import DashScopeEmbeddingConfig
+from .image_generation.transformation import DashScopeImageGenerationConfig
+from .rerank.transformation import DashScopeRerankConfig
+
+QWENCLOUD_API_BASE: Final = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
+QWENCLOUD_RERANK_API_BASE: Final = "https://dashscope-intl.aliyuncs.com/compatible-api/v1/reranks"
+QWENCLOUD_IMAGE_API_BASE: Final = (
+    "https://dashscope-intl.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
+)
+
+
+def _resolve_qwencloud_api_key(api_key: str | None) -> str | None:
+    return api_key or get_secret_str("QWENCLOUD_API_KEY") or get_secret_str("DASHSCOPE_API_KEY")
+
+
+def _require_qwencloud_api_key(api_key: str | None) -> str:
+    resolved: Final = _resolve_qwencloud_api_key(api_key)
+    if resolved is None:
+        raise ValueError(
+            "QwenCloud API key is required. Set 'QWENCLOUD_API_KEY' or 'DASHSCOPE_API_KEY' env var "
+            "or pass api_key explicitly."
+        )
+    return resolved
+
+
+class QwenCloudChatConfig(DashScopeChatConfig):
+    def _get_openai_compatible_provider_info(
+        self, api_base: str | None, api_key: str | None
+    ) -> tuple[str | None, str | None]:
+        return self._resolve_chat_api_base(api_base), _resolve_qwencloud_api_key(api_key)
+
+    def _resolve_chat_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE") or QWENCLOUD_API_BASE
+
+
+class QwenCloudEmbeddingConfig(DashScopeEmbeddingConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_embedding_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE") or QWENCLOUD_API_BASE
+
+
+class QwenCloudRerankConfig(DashScopeRerankConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        return api_base or get_secret_str("QWENCLOUD_API_BASE_RERANK") or QWENCLOUD_RERANK_API_BASE
+
+
+class QwenCloudImageGenerationConfig(DashScopeImageGenerationConfig):
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        return _require_qwencloud_api_key(api_key)
+
+    def _resolve_image_api_base(self, image_api_base: str | None) -> str:
+        return image_api_base or get_secret_str("QWENCLOUD_API_BASE_IMAGE") or QWENCLOUD_IMAGE_API_BASE
diff --git a/litellm/llms/dashscope/rerank/transformation.py b/litellm/llms/dashscope/rerank/transformation.py
index 98be4e4f2e7..3dd3996b2ee 100644
--- a/litellm/llms/dashscope/rerank/transformation.py
+++ b/litellm/llms/dashscope/rerank/transformation.py
@@ -58,19 +58,30 @@ class DashScopeRerankConfig(BaseRerankConfig):
     def __init__(self) -> None:
         pass
 
+    def _resolve_api_key(self, api_key: str | None) -> str:
+        resolved_api_key: Final = api_key if api_key is not None else get_secret_str("DASHSCOPE_API_KEY")
+        if resolved_api_key is None:
+            raise ValueError(
+                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
+            )
+        return resolved_api_key
+
+    def _resolve_rerank_api_base(self, api_base: str | None) -> str:
+        if api_base is not None:
+            return api_base
+        return get_secret_str("DASHSCOPE_API_BASE_RERANK") or DEFAULT_RERANK_URL
+
     def get_complete_url(
         self,
         api_base: str | None,
         model: str,
         optional_params: dict | None = None,
     ) -> str:
-        if api_base is None:
-            api_base = get_secret_str("DASHSCOPE_API_BASE_RERANK") or DEFAULT_RERANK_URL
+        resolved_api_base: Final = self._resolve_rerank_api_base(api_base)
+        if resolved_api_base == DEFAULT_RERANK_URL:
+            return resolved_api_base
 
-        if api_base == DEFAULT_RERANK_URL:
-            return DEFAULT_RERANK_URL
-
-        cleaned: Final = api_base.rstrip("/")
+        cleaned: Final = resolved_api_base.rstrip("/")
         if cleaned.endswith("/reranks") or cleaned.endswith("/rerank"):
             return cleaned
 
@@ -88,19 +99,12 @@ class DashScopeRerankConfig(BaseRerankConfig):
         optional_params: dict | None = None,
         litellm_params: Mapping[str, object] | None = None,
     ) -> dict:
-        if api_key is None:
-            api_key = get_secret_str("DASHSCOPE_API_KEY")
-        if api_key is None:
-            raise ValueError(
-                "DashScope API key is required. Set 'DASHSCOPE_API_KEY' env var or pass api_key explicitly."
-            )
-
-        default_headers: Final = {
-            "Authorization": f"Bearer {api_key}",
+        return {
+            "Authorization": f"Bearer {self._resolve_api_key(api_key)}",
             "accept": "application/json",
             "content-type": "application/json",
+            **headers,
         }
-        return {**default_headers, **headers}
 
     def get_supported_cohere_rerank_params(self, model: str) -> list:
         return ["query", "documents", "top_n", "return_documents"]
diff --git a/litellm/main.py b/litellm/main.py
index 0c8bff16f81..e756621a88b 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -6952,12 +6952,18 @@ def embedding(
                 aembedding=aembedding,
                 headers=headers,
             )
-        elif custom_llm_provider == "dashscope":
-            dashscope_key: Final = api_key or litellm.api_key or get_secret_str("DASHSCOPE_API_KEY")
+        elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
+            from litellm.llms.dashscope.common_utils import (
+                missing_dashscope_family_key_message,
+                resolve_dashscope_family_api_key,
+            )
+
+            dashscope_key: Final = resolve_dashscope_family_api_key(
+                custom_llm_provider=custom_llm_provider,
+                api_key=api_key or litellm.api_key,
+            )
             if dashscope_key is None:
-                raise ValueError(
-                    "Missing API key for DashScope. Set DASHSCOPE_API_KEY environment variable or pass api_key parameter."
-                )
+                raise ValueError(missing_dashscope_family_key_message(custom_llm_provider))
             if extra_headers is not None and isinstance(extra_headers, dict):
                 headers = extra_headers
             else:
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 718e6c489fd..00f17426451 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -14718,6 +14718,1910 @@
             "/v1/images/generations"
         ]
     },
+    "qwencloud/deepseek-v4-flash": {
+        "cache_read_input_token_cost": 4e-08,
+        "input_cost_per_token": 2e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/deepseek-v4-flash-0731": {
+        "cache_read_input_token_cost": 4e-08,
+        "input_cost_per_token": 2e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/deepseek-v4-pro": {
+        "cache_read_input_token_cost": 2e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4.8e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/glm-5.1": {
+        "cache_read_input_token_cost": 2.6e-07,
+        "input_cost_per_token": 1.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 202745,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 4.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/glm-5.2": {
+        "cache_read_input_token_cost": 2.8e-07,
+        "input_cost_per_token": 1.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 4.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/kimi-k2.7-code": {
+        "cache_read_input_token_cost": 1.9e-07,
+        "input_cost_per_token": 9.5e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 229376,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwencloud/qwen-coder": {
+        "input_cost_per_token": 3e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 1.5e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-flash": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 5e-08,
+                "output_cost_per_token": 4e-07,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.5e-07,
+                "output_cost_per_token": 2e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-flash-2025-07-28": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 5e-08,
+                "output_cost_per_token": 4e-07,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.5e-07,
+                "output_cost_per_token": 2e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-max": {
+        "input_cost_per_token": 1.6e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 30720,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 6.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus-2025-01-25": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
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+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 1.8e-07,
+                "input_cost_per_token": 1.8e-06,
+                "output_cost_per_token": 9e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 3e-07,
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 6e-07,
+                "input_cost_per_token": 6e-06,
+                "output_cost_per_token": 6e-05,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3-coder-plus-2025-07-22": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 1e-06,
+                "output_cost_per_token": 5e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
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+                "output_cost_per_token": 9e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 6e-06,
+                "output_cost_per_token": 6e-05,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3-max-preview": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 258048,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_token": 6e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
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+                "output_cost_per_token": 1.2e-05,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    252000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3-max": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 258048,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_token": 6e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.4e-06,
+                "output_cost_per_token": 1.2e-05,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    252000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3-max-2026-01-23": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 258048,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_token": 6e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.4e-06,
+                "output_cost_per_token": 1.2e-05,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    252000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3-next-80b-a3b-instruct": {
+        "input_cost_per_token": 1.5e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen3-next-80b-a3b-thinking": {
+        "input_cost_per_token": 1.5e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 262144,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen3-vl-235b-a22b-instruct": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 1.6e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwen3-vl-235b-a22b-thinking": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwen3-vl-32b-instruct": {
+        "input_cost_per_token": 1.6e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 6.4e-07,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwen3-vl-32b-thinking": {
+        "input_cost_per_token": 1.6e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 131072,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "output_cost_per_token": 2.87e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/model-pricing",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwen3-vl-plus": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 260096,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 2e-07,
+                "output_cost_per_token": 1.6e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 3e-07,
+                "output_cost_per_token": 2.4e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 6e-07,
+                "output_cost_per_token": 4.8e-06,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3.5-plus": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_token": 2.4e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 5e-07,
+                "output_cost_per_token": 3e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3.7-max": {
+        "cache_read_input_token_cost": 5e-07,
+        "input_cost_per_token": 2.5e-06,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen3.7-plus": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "tiered_pricing": [
+            {
+                "cache_read_input_token_cost": 8e-08,
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_token": 1.6e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 2.4e-07,
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_token": 4.8e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3.8-max": {
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 2e-06,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 6e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwq-plus": {
+        "input_cost_per_token": 8e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 98304,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.4e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen-image-2.0": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-2.0-pro": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-3.0": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-3.0-pro": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
     "databricks/databricks-bge-large-en": {
         "cache_creation_input_token_cost": 1.0003e-07,
         "cache_read_input_token_cost": 1.0003e-07,
diff --git a/litellm/provider_endpoints_support_backup.json b/litellm/provider_endpoints_support_backup.json
index ead26ab65c5..9d6b1e18f59 100644
--- a/litellm/provider_endpoints_support_backup.json
+++ b/litellm/provider_endpoints_support_backup.json
@@ -671,6 +671,42 @@
         "interactions": true
       }
     },
+    "qwencloud": {
+      "display_name": "QwenCloud (`qwencloud`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
+    "qwen_ai_platform": {
+      "display_name": "Qwen AI Platform (`qwen_ai_platform`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
     "databricks": {
       "display_name": "Databricks (`databricks`)",
       "url": "https://docs.litellm.ai/docs/providers/databricks",
diff --git a/litellm/proxy/public_endpoints/provider_create_fields.json b/litellm/proxy/public_endpoints/provider_create_fields.json
index a746e9af326..66f8c2ea36f 100644
--- a/litellm/proxy/public_endpoints/provider_create_fields.json
+++ b/litellm/proxy/public_endpoints/provider_create_fields.json
@@ -986,6 +986,62 @@
     ],
     "default_model_placeholder": "gpt-3.5-turbo"
   },
+  {
+    "provider": "QwenCloud",
+    "provider_display_name": "QwenCloud",
+    "litellm_provider": "qwencloud",
+    "credential_fields": [
+      {
+        "key": "api_key",
+        "label": "QwenCloud API Key",
+        "placeholder": null,
+        "tooltip": null,
+        "required": true,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "api_base",
+        "label": "API Base",
+        "placeholder": "https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
+        "tooltip": "The base URL for QwenCloud. Defaults to https://dashscope-intl.aliyuncs.com/compatible-mode/v1 if not specified.",
+        "required": true,
+        "field_type": "text",
+        "options": null,
+        "default_value": "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
+      }
+    ],
+    "default_model_placeholder": "gpt-3.5-turbo"
+  },
+  {
+    "provider": "Qwen_AI_Platform",
+    "provider_display_name": "Qwen AI Platform",
+    "litellm_provider": "qwen_ai_platform",
+    "credential_fields": [
+      {
+        "key": "api_key",
+        "label": "Qwen AI Platform API Key",
+        "placeholder": null,
+        "tooltip": null,
+        "required": true,
+        "field_type": "password",
+        "options": null,
+        "default_value": null
+      },
+      {
+        "key": "api_base",
+        "label": "API Base",
+        "placeholder": "https://dashscope.aliyuncs.com/compatible-mode/v1",
+        "tooltip": "The base URL for Qwen AI Platform. Defaults to https://dashscope.aliyuncs.com/compatible-mode/v1 if not specified.",
+        "required": true,
+        "field_type": "text",
+        "options": null,
+        "default_value": "https://dashscope.aliyuncs.com/compatible-mode/v1"
+      }
+    ],
+    "default_model_placeholder": "gpt-3.5-turbo"
+  },
   {
     "provider": "Databricks",
     "provider_display_name": "Databricks",
diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 55a32989b1c..addb7b730de 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -3771,6 +3771,8 @@ class LlmProviders(str, Enum):
     CODESTRAL = "codestral"
     TEXT_COMPLETION_CODESTRAL = "text-completion-codestral"
     DASHSCOPE = "dashscope"
+    QWENCLOUD = "qwencloud"
+    QWEN_AI_PLATFORM = "qwen_ai_platform"
     MODELSCOPE = "modelscope"
     MOONSHOT = "moonshot"
     PUBLICAI = "publicai"
diff --git a/litellm/utils.py b/litellm/utils.py
index ab011f4123d..7e760531f3b 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -6586,11 +6586,11 @@ def validate_environment(
                 keys_in_environment = True
             else:
                 missing_keys.append("WANDB_API_KEY")
-        elif custom_llm_provider == "dashscope":
-            if "DASHSCOPE_API_KEY" in os.environ:
+        elif custom_llm_provider in ("dashscope", "qwencloud", "qwen_ai_platform"):
+            if f"{custom_llm_provider.upper()}_API_KEY" in os.environ or "DASHSCOPE_API_KEY" in os.environ:
                 keys_in_environment = True
             else:
-                missing_keys.append("DASHSCOPE_API_KEY")
+                missing_keys.append(f"{custom_llm_provider.upper()}_API_KEY")
         elif custom_llm_provider == "modelscope":
             if "MODELSCOPE_API_KEY" in os.environ:
                 keys_in_environment = True
@@ -8152,6 +8152,11 @@ class ProviderConfigManager:
             LlmProviders.NEBIUS: (lambda: litellm.NebiusConfig(), False),
             LlmProviders.WANDB: (lambda: litellm.WandbConfig(), False),
             LlmProviders.DASHSCOPE: (lambda: litellm.DashScopeChatConfig(), False),
+            LlmProviders.QWENCLOUD: (lambda: litellm.QwenCloudChatConfig(), False),
+            LlmProviders.QWEN_AI_PLATFORM: (
+                lambda: litellm.QwenAIPlatformChatConfig(),
+                False,
+            ),
             LlmProviders.MODELSCOPE: (lambda: litellm.ModelScopeChatConfig(), False),
             LlmProviders.MOONSHOT: (lambda: litellm.MoonshotChatConfig(), False),
             LlmProviders.DOCKER_MODEL_RUNNER: (
@@ -8366,12 +8371,16 @@ class ProviderConfigManager:
             )
 
             return VolcEngineEmbeddingConfig()
-        elif litellm.LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.embed.transformation import (
-                DashScopeEmbeddingConfig,
+        elif provider in (
+            litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_embedding_config,
             )
 
-            return DashScopeEmbeddingConfig()
+            return get_dashscope_family_embedding_config(provider.value)
         elif litellm.LlmProviders.OVHCLOUD == provider:
             return litellm.OVHCloudEmbeddingConfig()
         elif litellm.LlmProviders.SNOWFLAKE == provider:
@@ -8444,12 +8453,16 @@ class ProviderConfigManager:
             return litellm.VoyageRerankConfig()
         elif litellm.LlmProviders.WATSONX == provider:
             return litellm.IBMWatsonXRerankConfig()
-        elif litellm.LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.rerank.transformation import (
-                DashScopeRerankConfig,
+        elif provider in (
+            litellm.LlmProviders.DASHSCOPE,
+            litellm.LlmProviders.QWENCLOUD,
+            litellm.LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_rerank_config,
             )
 
-            return DashScopeRerankConfig()
+            return get_dashscope_family_rerank_config(provider.value)
         return litellm.CohereRerankConfig()
 
     @staticmethod
@@ -9122,12 +9135,16 @@ class ProviderConfigManager:
             )
 
             return get_openrouter_image_generation_config(model)
-        elif LlmProviders.DASHSCOPE == provider:
-            from litellm.llms.dashscope.image_generation import (
-                get_dashscope_image_generation_config,
+        elif provider in (
+            LlmProviders.DASHSCOPE,
+            LlmProviders.QWENCLOUD,
+            LlmProviders.QWEN_AI_PLATFORM,
+        ):
+            from litellm.llms.dashscope.common_utils import (
+                get_dashscope_family_image_generation_config,
             )
 
-            return get_dashscope_image_generation_config(model)
+            return get_dashscope_family_image_generation_config(provider.value)
         elif LlmProviders.MODELSCOPE == provider:
             from litellm.llms.modelscope.image_generation import (
                 get_modelscope_image_generation_config,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 718e6c489fd..00f17426451 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -14718,6 +14718,1910 @@
             "/v1/images/generations"
         ]
     },
+    "qwencloud/deepseek-v4-flash": {
+        "cache_read_input_token_cost": 4e-08,
+        "input_cost_per_token": 2e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/deepseek-v4-flash-0731": {
+        "cache_read_input_token_cost": 4e-08,
+        "input_cost_per_token": 2e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/deepseek-v4-pro": {
+        "cache_read_input_token_cost": 2e-07,
+        "input_cost_per_token": 2.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 393216,
+        "max_tokens": 393216,
+        "mode": "chat",
+        "output_cost_per_token": 4.8e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/glm-5.1": {
+        "cache_read_input_token_cost": 2.6e-07,
+        "input_cost_per_token": 1.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 202745,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 4.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/glm-5.2": {
+        "cache_read_input_token_cost": 2.8e-07,
+        "input_cost_per_token": 1.4e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 4.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/kimi-k2.7-code": {
+        "cache_read_input_token_cost": 1.9e-07,
+        "input_cost_per_token": 9.5e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 229376,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwencloud/qwen-coder": {
+        "input_cost_per_token": 3e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 1.5e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-flash": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 5e-08,
+                "output_cost_per_token": 4e-07,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.5e-07,
+                "output_cost_per_token": 2e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-flash-2025-07-28": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 5e-08,
+                "output_cost_per_token": 4e-07,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 2.5e-07,
+                "output_cost_per_token": 2e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-max": {
+        "input_cost_per_token": 1.6e-06,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 30720,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 6.4e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus-2025-01-25": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus-2025-04-28": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 4e-06,
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus-2025-07-14": {
+        "input_cost_per_token": 4e-07,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 4e-06,
+        "output_cost_per_token": 1.2e-06,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-plus-2025-07-28": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_reasoning_token": 4e-06,
+                "output_cost_per_token": 1.2e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_reasoning_token": 1.2e-05,
+                "output_cost_per_token": 3.6e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-plus-2025-09-11": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_reasoning_token": 4e-06,
+                "output_cost_per_token": 1.2e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_reasoning_token": 1.2e-05,
+                "output_cost_per_token": 3.6e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-plus-latest": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 32768,
+        "max_tokens": 32768,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_reasoning_token": 4e-06,
+                "output_cost_per_token": 1.2e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_reasoning_token": 1.2e-05,
+                "output_cost_per_token": 3.6e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen-turbo": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 5e-07,
+        "output_cost_per_token": 2e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-turbo-2024-11-01": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-turbo-2025-04-28": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 5e-07,
+        "output_cost_per_token": 2e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen-turbo-latest": {
+        "input_cost_per_token": 5e-08,
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "output_cost_per_reasoning_token": 5e-07,
+        "output_cost_per_token": 2e-07,
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen3-30b-a3b": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 129024,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwencloud/qwen3-coder-flash": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "cache_read_input_token_cost": 8e-08,
+                "input_cost_per_token": 3e-07,
+                "output_cost_per_token": 1.5e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 1.2e-07,
+                "input_cost_per_token": 5e-07,
+                "output_cost_per_token": 2.5e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 2e-07,
+                "input_cost_per_token": 8e-07,
+                "output_cost_per_token": 4e-06,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 4e-07,
+                "input_cost_per_token": 1.6e-06,
+                "output_cost_per_token": 9.6e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen3-coder-flash-2025-07-28": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "input_cost_per_token": 3e-07,
+                "output_cost_per_token": 1.5e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 5e-07,
+                "output_cost_per_token": 2.5e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 8e-07,
+                "output_cost_per_token": 4e-06,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            },
+            {
+                "input_cost_per_token": 1.6e-06,
+                "output_cost_per_token": 9.6e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen3-coder-plus": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
+            {
+                "cache_read_input_token_cost": 1e-07,
+                "input_cost_per_token": 1e-06,
+                "output_cost_per_token": 5e-06,
+                "range": [
+                    0,
+                    32000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 1.8e-07,
+                "input_cost_per_token": 1.8e-06,
+                "output_cost_per_token": 9e-06,
+                "range": [
+                    32000.0,
+                    128000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 3e-07,
+                "input_cost_per_token": 3e-06,
+                "output_cost_per_token": 1.5e-05,
+                "range": [
+                    128000.0,
+                    256000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 6e-07,
+                "input_cost_per_token": 6e-06,
+                "output_cost_per_token": 6e-05,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwencloud/qwen3-coder-plus-2025-07-22": {
+        "litellm_provider": "qwencloud",
+        "max_input_tokens": 997952,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.qwencloud.com/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true,
+        "tiered_pricing": [
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+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen3.7-plus": {
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
+        "mode": "chat",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "tiered_pricing": [
+            {
+                "cache_read_input_token_cost": 8e-08,
+                "input_cost_per_token": 4e-07,
+                "output_cost_per_token": 1.6e-06,
+                "range": [
+                    0,
+                    256000.0
+                ]
+            },
+            {
+                "cache_read_input_token_cost": 2.4e-07,
+                "input_cost_per_token": 1.2e-06,
+                "output_cost_per_token": 4.8e-06,
+                "range": [
+                    256000.0,
+                    1000000.0
+                ]
+            }
+        ]
+    },
+    "qwen_ai_platform/qwen3.8-max": {
+        "cache_read_input_token_cost": 2.5e-07,
+        "input_cost_per_token": 2e-06,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 991808,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 6e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
+    },
+    "qwen_ai_platform/qwq-plus": {
+        "input_cost_per_token": 8e-07,
+        "litellm_provider": "qwen_ai_platform",
+        "max_input_tokens": 98304,
+        "max_output_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "chat",
+        "output_cost_per_token": 2.4e-06,
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supports_function_calling": true,
+        "supports_reasoning": true,
+        "supports_tool_choice": true
+    },
+    "qwen_ai_platform/qwen-image-2.0": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-2.0-pro": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-3.0": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
+    "qwen_ai_platform/qwen-image-3.0-pro": {
+        "litellm_provider": "qwen_ai_platform",
+        "mode": "image_generation",
+        "source": "https://www.alibabacloud.com/help/en/model-studio/models",
+        "supported_endpoints": [
+            "/v1/images/generations"
+        ]
+    },
     "databricks/databricks-bge-large-en": {
         "cache_creation_input_token_cost": 1.0003e-07,
         "cache_read_input_token_cost": 1.0003e-07,
diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json
index 7c7d508856f..ebc220b3496 100644
--- a/provider_endpoints_support.json
+++ b/provider_endpoints_support.json
@@ -724,6 +724,42 @@
         "interactions": true
       }
     },
+    "qwencloud": {
+      "display_name": "QwenCloud (`qwencloud`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
+    "qwen_ai_platform": {
+      "display_name": "Qwen AI Platform (`qwen_ai_platform`)",
+      "url": "https://docs.litellm.ai/docs/providers/qwencloud",
+      "endpoints": {
+        "chat_completions": true,
+        "messages": true,
+        "responses": true,
+        "embeddings": true,
+        "image_generations": true,
+        "audio_transcriptions": false,
+        "audio_speech": false,
+        "moderations": false,
+        "batches": false,
+        "rerank": true,
+        "a2a": true,
+        "interactions": true
+      }
+    },
     "databricks": {
       "display_name": "Databricks (`databricks`)",
       "url": "https://docs.litellm.ai/docs/providers/databricks",
diff --git a/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py b/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py
new file mode 100644
index 00000000000..064d9d58f0c
--- /dev/null
+++ b/tests/test_litellm/llms/dashscope/test_qwen_brand_aliases.py
@@ -0,0 +1,331 @@
+import math
+
+import pytest
+
+import litellm
+from litellm import completion, get_llm_provider
+from litellm.llms.dashscope.chat.transformation import DashScopeChatConfig
+from litellm.llms.dashscope.cost_calculator import (
+    cost_per_token as dashscope_cost_per_token,
+)
+from litellm.llms.dashscope.embed.transformation import DashScopeEmbeddingConfig
+from litellm.llms.dashscope.image_generation.transformation import (
+    DashScopeImageGenerationConfig,
+)
+from litellm.llms.dashscope.qwen_ai_platform import (
+    QWEN_AI_PLATFORM_API_BASE,
+    QWEN_AI_PLATFORM_IMAGE_API_BASE,
+    QWEN_AI_PLATFORM_RERANK_API_BASE,
+    QwenAIPlatformChatConfig,
+    QwenAIPlatformEmbeddingConfig,
+    QwenAIPlatformImageGenerationConfig,
+    QwenAIPlatformRerankConfig,
+)
+from litellm.llms.dashscope.qwencloud import (
+    QWENCLOUD_API_BASE,
+    QWENCLOUD_IMAGE_API_BASE,
+    QWENCLOUD_RERANK_API_BASE,
+    QwenCloudChatConfig,
+    QwenCloudEmbeddingConfig,
+    QwenCloudImageGenerationConfig,
+    QwenCloudRerankConfig,
+)
+from litellm.llms.dashscope.rerank.transformation import DashScopeRerankConfig
+from litellm.types.utils import LlmProviders, Usage
+from litellm.utils import ProviderConfigManager
+
+DASHSCOPE_FAMILY_ENV_VARS = [
+    "DASHSCOPE_API_KEY",
+    "DASHSCOPE_API_BASE",
+    "DASHSCOPE_API_BASE_RERANK",
+    "DASHSCOPE_API_BASE_IMAGE",
+    "QWENCLOUD_API_KEY",
+    "QWENCLOUD_API_BASE",
+    "QWENCLOUD_API_BASE_RERANK",
+    "QWENCLOUD_API_BASE_IMAGE",
+    "QWEN_AI_PLATFORM_API_KEY",
+    "QWEN_AI_PLATFORM_API_BASE",
+    "QWEN_AI_PLATFORM_API_BASE_RERANK",
+    "QWEN_AI_PLATFORM_API_BASE_IMAGE",
+]
+
+BRAND_CASES = [
+    pytest.param(
+        {
+            "provider": "qwencloud",
+            "enum": LlmProviders.QWENCLOUD,
+            "key_env": "QWENCLOUD_API_KEY",
+            "base_env": "QWENCLOUD_API_BASE",
+            "default_base": QWENCLOUD_API_BASE,
+            "default_rerank_base": QWENCLOUD_RERANK_API_BASE,
+            "default_image_base": QWENCLOUD_IMAGE_API_BASE,
+            "chat_config": QwenCloudChatConfig,
+            "embedding_config": QwenCloudEmbeddingConfig,
+            "rerank_config": QwenCloudRerankConfig,
+            "image_config": QwenCloudImageGenerationConfig,
+        },
+        id="qwencloud",
+    ),
+    pytest.param(
+        {
+            "provider": "qwen_ai_platform",
+            "enum": LlmProviders.QWEN_AI_PLATFORM,
+            "key_env": "QWEN_AI_PLATFORM_API_KEY",
+            "base_env": "QWEN_AI_PLATFORM_API_BASE",
+            "default_base": QWEN_AI_PLATFORM_API_BASE,
+            "default_rerank_base": QWEN_AI_PLATFORM_RERANK_API_BASE,
+            "default_image_base": QWEN_AI_PLATFORM_IMAGE_API_BASE,
+            "chat_config": QwenAIPlatformChatConfig,
+            "embedding_config": QwenAIPlatformEmbeddingConfig,
+            "rerank_config": QwenAIPlatformRerankConfig,
+            "image_config": QwenAIPlatformImageGenerationConfig,
+        },
+        id="qwen_ai_platform",
+    ),
+]
+
+
+@pytest.fixture(autouse=True)
+def clear_dashscope_family_env(monkeypatch):
+    for env_var in DASHSCOPE_FAMILY_ENV_VARS:
+        monkeypatch.delenv(env_var, raising=False)
+
+
+class TestQwenBrandProviderResolution:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_get_llm_provider_resolves_brand_default_base(self, brand):
+        model, provider, api_key, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert model == "qwen-max"
+        assert provider == brand["provider"]
+        assert api_key == "sk-explicit"
+        assert api_base == brand["default_base"]
+
+    def test_dashscope_resolution_unchanged(self):
+        model, provider, api_key, api_base = get_llm_provider("dashscope/qwen-max", api_key="sk-explicit")
+        assert model == "qwen-max"
+        assert provider == "dashscope"
+        assert api_base == "https://dashscope.aliyuncs.com/compatible-mode/v1"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_brand_env_key_wins_over_dashscope_key(self, monkeypatch, brand):
+        monkeypatch.setenv(brand["key_env"], "sk-brand")
+        monkeypatch.setenv("DASHSCOPE_API_KEY", "sk-dashscope")
+        _, _, api_key, _ = get_llm_provider(f"{brand['provider']}/qwen-max")
+        assert api_key == "sk-brand"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_dashscope_key_is_fallback(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_KEY", "sk-dashscope")
+        _, _, api_key, _ = get_llm_provider(f"{brand['provider']}/qwen-max")
+        assert api_key == "sk-dashscope"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_dashscope_api_base_does_not_leak_into_brand(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_BASE", "https://legacy.example.com/v1")
+        _, _, _, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert api_base == brand["default_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_brand_api_base_env_wins(self, monkeypatch, brand):
+        monkeypatch.setenv(brand["base_env"], "https://brand.example.com/v1")
+        _, _, _, api_base = get_llm_provider(f"{brand['provider']}/qwen-max", api_key="sk-explicit")
+        assert api_base == "https://brand.example.com/v1"
+
+
+class TestQwenBrandConfigDispatch:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_chat_config(self, brand):
+        config = ProviderConfigManager.get_provider_chat_config("qwen-max", brand["enum"])
+        assert isinstance(config, brand["chat_config"])
+        assert isinstance(config, DashScopeChatConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_config(self, brand):
+        config = ProviderConfigManager.get_provider_embedding_config(model="text-embedding-v3", provider=brand["enum"])
+        assert isinstance(config, brand["embedding_config"])
+        assert isinstance(config, DashScopeEmbeddingConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_config(self, brand):
+        config = ProviderConfigManager.get_provider_rerank_config(
+            model="gte-rerank-v2",
+            provider=brand["enum"],
+            api_base=None,
+            present_version_params=[],
+        )
+        assert isinstance(config, brand["rerank_config"])
+        assert isinstance(config, DashScopeRerankConfig)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_config(self, brand):
+        config = ProviderConfigManager.get_provider_image_generation_config(model="qwen-image", provider=brand["enum"])
+        assert isinstance(config, brand["image_config"])
+        assert isinstance(config, DashScopeImageGenerationConfig)
+
+
+class TestQwenBrandDefaultUrls:
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_chat_complete_url(self, brand):
+        url = brand["chat_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="qwen-max",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/chat/completions"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_complete_url(self, brand):
+        url = brand["embedding_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="text-embedding-v3",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/embeddings"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_embedding_ignores_dashscope_api_base(self, monkeypatch, brand):
+        monkeypatch.setenv("DASHSCOPE_API_BASE", "https://legacy.example.com/v1")
+        url = brand["embedding_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="text-embedding-v3",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == f"{brand['default_base']}/embeddings"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_complete_url(self, brand):
+        url = brand["rerank_config"]().get_complete_url(api_base=None, model="gte-rerank-v2")
+        assert url == brand["default_rerank_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_rerank_env_override(self, monkeypatch, brand):
+        monkeypatch.setenv(f"{brand['base_env']}_RERANK", "https://rerank.example.com/v1/reranks")
+        url = brand["rerank_config"]().get_complete_url(api_base=None, model="gte-rerank-v2")
+        assert url == "https://rerank.example.com/v1/reranks"
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_complete_url(self, brand):
+        url = brand["image_config"]().get_complete_url(
+            api_base=None,
+            api_key="sk-test",
+            model="qwen-image",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == brand["default_image_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_image_generation_ignores_chat_compatible_api_base(self, brand):
+        url = brand["image_config"]().get_complete_url(
+            api_base=brand["default_base"],
+            api_key="sk-test",
+            model="qwen-image",
+            optional_params={},
+            litellm_params={},
+        )
+        assert url == brand["default_image_base"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_validate_environment_requires_key(self, brand):
+        with pytest.raises(ValueError, match="DASHSCOPE_API_KEY"):
+            brand["embedding_config"]().validate_environment(
+                headers={},
+                model="text-embedding-v3",
+                messages=[],
+                optional_params={},
+                litellm_params={},
+                api_key=None,
+                api_base=None,
+            )
+
+
+class TestQwenBrandCostParity:
+    @pytest.fixture(autouse=True)
+    def setup_model_cost_map(self, monkeypatch):
+        monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+        monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_get_model_info(self, brand):
+        model_info = litellm.get_model_info(f"{brand['provider']}/qwen-max")
+        dashscope_info = litellm.get_model_info("dashscope/qwen-max")
+        assert model_info["litellm_provider"] == brand["provider"]
+        assert model_info["input_cost_per_token"] == dashscope_info["input_cost_per_token"]
+        assert model_info["output_cost_per_token"] == dashscope_info["output_cost_per_token"]
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_flat_pricing_matches_dashscope(self, brand):
+        usage = Usage(prompt_tokens=1000, completion_tokens=500)
+        brand_costs = dashscope_cost_per_token(model="qwen-max", usage=usage, custom_llm_provider=brand["provider"])
+        dashscope_costs = dashscope_cost_per_token(model="qwen-max", usage=usage)
+        assert brand_costs == dashscope_costs
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_tiered_pricing_matches_dashscope(self, brand):
+        usage = Usage(prompt_tokens=300000, completion_tokens=300000)
+        brand_costs = dashscope_cost_per_token(model="qwen-flash", usage=usage, custom_llm_provider=brand["provider"])
+        dashscope_costs = dashscope_cost_per_token(model="qwen-flash", usage=usage)
+        assert brand_costs == dashscope_costs
+        tier_2 = litellm.get_model_info(f"{brand['provider']}/qwen-flash")["tiered_pricing"][1]
+        assert math.isclose(brand_costs[0], 300000 * tier_2["input_cost_per_token"], rel_tol=1e-10)
+
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_public_cost_per_token_routes_to_dashscope_calculator(self, brand):
+        brand_costs = litellm.cost_per_token(
+            model=f"{brand['provider']}/qwen-max",
+            prompt_tokens=1000,
+            completion_tokens=500,
+            custom_llm_provider=brand["provider"],
+        )
+        dashscope_costs = litellm.cost_per_token(
+            model="dashscope/qwen-max",
+            prompt_tokens=1000,
+            completion_tokens=500,
+            custom_llm_provider="dashscope",
+        )
+        assert brand_costs == dashscope_costs
+
+
+class TestQwenBrandCompletionMock:
+    @pytest.mark.respx()
+    @pytest.mark.parametrize("brand", BRAND_CASES)
+    def test_completion_hits_brand_default_host(self, respx_mock, brand, monkeypatch):
+        monkeypatch.setattr(litellm, "disable_aiohttp_transport", True)
+        respx_mock.post(f"{brand['default_base']}/chat/completions").respond(
+            json={
+                "id": "chatcmpl-123",
+                "object": "chat.completion",
+                "created": 1677652288,
+                "model": "qwen-turbo",
+                "choices": [
+                    {
+                        "index": 0,
+                        "message": {"role": "assistant", "content": "Hey from LiteLLM!"},
+                        "finish_reason": "stop",
+                    }
+                ],
+                "usage": {
+                    "prompt_tokens": 9,
+                    "completion_tokens": 12,
+                    "total_tokens": 21,
+                },
+            },
+            status_code=200,
+        )
+
+        response = completion(
+            model=f"{brand['provider']}/qwen-turbo",
+            messages=[{"role": "user", "content": "say hey from LiteLLM"}],
+            api_key="fake-brand-key",
+        )
+
+        assert response.choices[0].message.content == "Hey from LiteLLM!"
+        request = respx_mock.calls[0].request
+        assert request.url == f"{brand['default_base']}/chat/completions"
+        assert request.headers["Authorization"] == "Bearer fake-brand-key"
diff --git a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
index 5baa8138960..d01a6a34cbe 100644
--- a/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
+++ b/ui/litellm-dashboard/src/components/provider_info_helpers.tsx
@@ -150,6 +150,8 @@ export enum Providers {
   PETALS = "Petals",
   PG_VECTOR = "Pg Vector",
   PREDIBASE = "Predibase",
+  Qwen_AI_Platform = "Qwen AI Platform",
+  QwenCloud = "QwenCloud",
   RECRAFT = "Recraft",
   REPLICATE = "Replicate",
   RunwayML = "RunwayML",
@@ -262,6 +264,8 @@ export const provider_map: Record<string, string> = {
   PETALS: "petals",
   PG_VECTOR: "pg_vector",
   PREDIBASE: "predibase",
+  Qwen_AI_Platform: "qwen_ai_platform",
+  QwenCloud: "qwencloud",
   RECRAFT: "recraft",
   REPLICATE: "replicate",
   RunwayML: "runwayml",
@@ -357,6 +361,8 @@ export const providerLogoMap: Partial<Record<Providers, string>> = {
   [Providers.Openrouter]: openrouterLogo.src,
   [Providers.Oracle]: oracleLogo.src,
   [Providers.Perplexity]: perplexityAiLogo.src,
+  [Providers.Qwen_AI_Platform]: qwenLogo.src,
+  [Providers.QwenCloud]: qwenLogo.src,
   [Providers.RECRAFT]: recraftLogo.src,
   [Providers.REPLICATE]: replicateLogo.src,
   [Providers.RunwayML]: runwayLogo.src,

From ab549a8da3f1fa5bf95de99231d8249b272514ee Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:25:18 +0000
Subject: [PATCH 044/113] test(fallbacks): use an unmapped fable id now that
 5.1 is in the cost map

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../litellm_core_utils/test_fallback_generalizations.py       | 4 ++--
 .../llms/anthropic/chat/test_anthropic_chat_transformation.py | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
index 0587628e2fe..b1e8163b91d 100644
--- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
+++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py
@@ -366,7 +366,7 @@ def test_shipped_rules_stack_adaptive_and_mid_conversation_flags(shipped_cost_ma
 def test_shipped_rules_flag_unmapped_fable_as_always_on_thinking(shipped_cost_map):
     """An unmapped Fable/Mythos id picks up ``thinking_always_on`` from the
     claude-always-on-thinking rule, while other unmapped Claudes stay unflagged."""
-    model = "claude-fable-5-1"
+    model = "claude-fable-6-1"
     assert model not in litellm.model_cost
     info = litellm.get_model_info(model, custom_llm_provider="anthropic")
     assert info["thinking_always_on"] is True
@@ -419,7 +419,7 @@ def test_shipped_rules_cover_new_families_like_fable_at_5_plus(shipped_cost_map)
     """Both version gates accept any claude-<family>- id at major 5 or higher, bare
     major or major-minor, so a new family shaped like claude-fable-5 gets adaptive
     thinking and mid-conversation system support without a cost-map entry."""
-    model = "claude-fable-5-1"
+    model = "claude-fable-6-1"
     assert model not in litellm.model_cost
     info = litellm.get_model_info(model, custom_llm_provider="anthropic")
     assert info["supports_mid_conversation_system"] is True
diff --git a/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py b/tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py
index 25e2c3cda80..435cee55de3 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
@@ -6178,7 +6178,7 @@ def test_is_anthropic_usage_object_rejects_responses_api_usage():
         ("claude-fable-5", True),
         ("claude-mythos-5", True),
         # unmapped future family member -> claude-always-on-thinking fallback rule
-        ("claude-fable-5-1", True),
+        ("claude-fable-6-1", True),
         # adaptive-capable models that ACCEPT disabled must keep it verbatim
         ("claude-opus-5", False),
         ("claude-sonnet-5", False),

From 0610331aa1f0f81776b493b3fdc5fd3bb8b309f4 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:28:33 +0000
Subject: [PATCH 045/113] test(reasoning-effort-grid): bump the cell count for
 the four new Fable 5.1 cells

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../reasoning_effort_grid/test_reasoning_effort_grid.py       | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
index 517e3173b8c..714d544ecd6 100644
--- a/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
+++ b/tests/llm_translation/reasoning_effort_grid/test_reasoning_effort_grid.py
@@ -201,8 +201,8 @@ async def test_reasoning_effort_grid(
 
 
 def test_grid_cell_count() -> None:
-    assert len(_PARAMS) == 31 * 11, (
-        f"expected 341 cells (31 provider x model combos x 11 efforts), "
+    assert len(_PARAMS) == 35 * 11, (
+        f"expected 385 cells (35 provider x model combos x 11 efforts), "
         f"got {len(_PARAMS)}"
     )
 

From 62a42b4b47341f8e55d3d8f27bcd834776f9c2cb Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 11:34:23 -0700
Subject: [PATCH 046/113] refactor(dashscope): wrap long error message strings
 in common_utils

---
 litellm/llms/dashscope/common_utils.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/litellm/llms/dashscope/common_utils.py b/litellm/llms/dashscope/common_utils.py
index 926b6f0ffc7..b7c97893a15 100644
--- a/litellm/llms/dashscope/common_utils.py
+++ b/litellm/llms/dashscope/common_utils.py
@@ -75,9 +75,15 @@ def resolve_dashscope_family_api_key(custom_llm_provider: str, api_key: str | No
 
 def missing_dashscope_family_key_message(custom_llm_provider: str) -> str:
     if custom_llm_provider == "qwencloud":
-        return "Missing API key for QwenCloud. Set QWENCLOUD_API_KEY or DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        return (
+            "Missing API key for QwenCloud. Set QWENCLOUD_API_KEY or "
+            "DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        )
     if custom_llm_provider == "qwen_ai_platform":
-        return "Missing API key for Qwen AI Platform. Set QWEN_AI_PLATFORM_API_KEY or DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        return (
+            "Missing API key for Qwen AI Platform. Set QWEN_AI_PLATFORM_API_KEY or "
+            "DASHSCOPE_API_KEY environment variable or pass api_key parameter."
+        )
     return "Missing API key for DashScope. Set DASHSCOPE_API_KEY environment variable or pass api_key parameter."
 
 

From 3c9ce458fd5ad27c95851b4e4c4462b5f7f19035 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:46:03 +0000
Subject: [PATCH 047/113] feat(anthropic): gate forced tool_choice for Fable
 5.1 behind supports_forced_tool_use

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/llms/anthropic/chat/transformation.py |   4 +-
 litellm/llms/anthropic/common_utils.py        |  34 ++++++
 ...odel_prices_and_context_window_backup.json |   8 ++
 model_prices_and_context_window.json          |   8 ++
 .../test_anthropic_chat_transformation.py     | 105 ++++++++++++++++++
 .../test_claude_fable_5_config.py             |   1 +
 6 files changed, 159 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py
index e1387a9068c..91f1fb5bd6f 100644
--- a/litellm/llms/anthropic/chat/transformation.py
+++ b/litellm/llms/anthropic/chat/transformation.py
@@ -1466,7 +1466,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig):
                 )
 
                 if _tool_choice is not None:
-                    optional_params["tool_choice"] = _tool_choice
+                    optional_params["tool_choice"] = AnthropicConfig._apply_forced_tool_choice(
+                        model=model, tool_choice=_tool_choice, drop_params=drop_params
+                    )
             elif param == "stream" and value is True:
                 optional_params["stream"] = value
             elif param == "stop" and (isinstance(value, str) or isinstance(value, list)):
diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py
index 9871001bf66..0ca0e07d4d0 100644
--- a/litellm/llms/anthropic/common_utils.py
+++ b/litellm/llms/anthropic/common_utils.py
@@ -28,10 +28,15 @@ from litellm.types.llms.anthropic import (
     ANTHROPIC_OAUTH_TOKEN_PREFIX,
     AllAnthropicToolsValues,
     AnthropicMcpServerTool,
+    AnthropicMessagesToolChoice,
 )
 from litellm.types.llms.openai import AllMessageValues
 from litellm.types.proxy.model_listing import ModelInfoResponse
 
+DROP_FORCED_TOOL_CHOICE_WARNING: Final = (
+    "Downgrading forced tool_choice to 'auto' for model=%s (drop_params=True): this model rejects tool_choice type "
+    "'any'/'tool' with a 400 because thinking is always on and a forced call would skip it."
+)
 DROP_DISABLED_THINKING_WARNING: Final = (
     "Dropping `thinking={'type': 'disabled'}` for model=%s: thinking is always on for this model and cannot be "
     "disabled (the alternative is a provider 400). The model will still think adaptively, its response can contain "
@@ -320,6 +325,35 @@ class AnthropicModelInfo(BaseLLMModelInfo):
                 status_code=400,
             )
 
+    @staticmethod
+    def _apply_forced_tool_choice(
+        model: str,
+        tool_choice: AnthropicMessagesToolChoice,
+        drop_params: bool,
+    ) -> AnthropicMessagesToolChoice:
+        """Forward ``tool_choice`` unless the model map flags the model with
+        ``supports_forced_tool_use: false`` (Fable 5.1 / Mythos 5.1 400 on
+        ``any``/``tool``), in which case downgrade to ``auto`` (with
+        drop_params) or raise a clean client-side 400."""
+        if tool_choice["type"] not in ("any", "tool"):
+            return tool_choice
+        if AnthropicModelInfo._get_model_capability(model, "supports_forced_tool_use") is not False:
+            return tool_choice
+        if not (litellm.drop_params or drop_params):
+            raise litellm.utils.UnsupportedParamsError(
+                message=(
+                    f"{model} does not support forced tool use (tool_choice='required' or a named tool). "
+                    "Use tool_choice='auto' and tell the model in the prompt when to call the tool, or set "
+                    "`litellm.drop_params = True` to downgrade to 'auto' automatically."
+                ),
+                status_code=400,
+            )
+        litellm.verbose_logger.warning(DROP_FORCED_TOOL_CHOICE_WARNING, model)
+        disable_parallel: Final = tool_choice.get("disable_parallel_tool_use")
+        if disable_parallel is None:
+            return AnthropicMessagesToolChoice(type="auto")
+        return AnthropicMessagesToolChoice(type="auto", disable_parallel_tool_use=disable_parallel)
+
     @staticmethod
     def _strip_version_suffix(model: str) -> str:
         at: Final = model.rfind("@")
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index cd39d080da7..65c2c5dd5d2 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1472,6 +1472,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1546,6 +1547,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1620,6 +1622,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1694,6 +1697,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -3248,6 +3252,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -13231,6 +13236,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -42204,6 +42210,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -42273,6 +42280,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index cd39d080da7..65c2c5dd5d2 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -1472,6 +1472,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1546,6 +1547,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1620,6 +1622,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -1694,6 +1697,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -3248,6 +3252,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -13231,6 +13236,7 @@
         "supports_mid_conversation_system": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -42204,6 +42210,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
@@ -42273,6 +42280,7 @@
         "thinking_always_on": true,
         "supports_assistant_prefill": false,
         "supports_computer_use": true,
+        "supports_forced_tool_use": false,
         "supports_function_calling": true,
         "supports_pdf_input": true,
         "supports_prompt_caching": true,
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 435cee55de3..b56e6c41f23 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
@@ -6176,6 +6176,7 @@ def test_is_anthropic_usage_object_rejects_responses_api_usage():
     [
         # always-on-thinking models reject thinking.type=disabled with a 400
         ("claude-fable-5", True),
+        ("claude-fable-5-1", True),
         ("claude-mythos-5", True),
         # unmapped future family member -> claude-always-on-thinking fallback rule
         ("claude-fable-6-1", True),
@@ -6207,3 +6208,107 @@ def test_disabled_thinking_omitted_only_for_always_on_models(
         assert "thinking" not in request
     else:
         assert request["thinking"] == {"type": "disabled"}
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "required"}, {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_raises_clean_error_on_fable_5_1_without_drop_params(
+    local_model_cost_map, tool_choice, monkeypatch
+):
+    """Fable 5.1 400s on tool_choice type any/tool (thinking is always on and a
+    forced call would skip it); without drop_params the caller gets a clean
+    client-side 400 that explains the workaround, not a provider error."""
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    with pytest.raises(litellm.utils.UnsupportedParamsError, match="forced tool use"):
+        config.map_openai_params(
+            non_default_params={"tool_choice": tool_choice},
+            optional_params={},
+            model="claude-fable-5-1",
+            drop_params=False,
+        )
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "required"}, {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_downgraded_to_auto_on_fable_5_1_with_drop_params(
+    local_model_cost_map, tool_choice
+):
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": tool_choice},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto"}
+
+
+def test_forced_tool_choice_downgrade_keeps_parallel_tool_calls_flag(local_model_cost_map):
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required", "parallel_tool_calls": False},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto", "disable_parallel_tool_use": True}
+
+
+@pytest.mark.parametrize("tool_choice, expected_type", [("auto", "auto"), ("none", "none")])
+def test_unforced_tool_choice_forwarded_on_fable_5_1(
+    local_model_cost_map, tool_choice, expected_type, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": tool_choice},
+        optional_params={},
+        model="claude-fable-5-1",
+        drop_params=False,
+    )
+
+    assert result["tool_choice"]["type"] == expected_type
+
+
+@pytest.mark.parametrize("model", ["claude-fable-5", "claude-opus-5", "claude-sonnet-5"])
+def test_forced_tool_choice_forwarded_on_models_that_support_it(
+    local_model_cost_map, model, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required"},
+        optional_params={},
+        model=model,
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "any"}
+
+
+def test_forced_tool_choice_gating_driven_by_model_map_flag(local_model_cost_map, monkeypatch):
+    """The gate must read ``supports_forced_tool_use`` from the model map, not
+    the model name: a flagged entry gates a model whose name says nothing."""
+    monkeypatch.setitem(litellm.model_cost, "claude-zeta-9", {"supports_forced_tool_use": False})
+    config = AnthropicConfig()
+
+    result = config.map_openai_params(
+        non_default_params={"tool_choice": "required"},
+        optional_params={},
+        model="claude-zeta-9",
+        drop_params=True,
+    )
+
+    assert result["tool_choice"] == {"type": "auto"}
diff --git a/tests/test_litellm/test_claude_fable_5_config.py b/tests/test_litellm/test_claude_fable_5_config.py
index 90ded46e2a4..3ecf94602d9 100644
--- a/tests/test_litellm/test_claude_fable_5_config.py
+++ b/tests/test_litellm/test_claude_fable_5_config.py
@@ -251,6 +251,7 @@ def test_fable_5_1_model_pricing_and_capabilities():
         assert "output_cost_per_token_above_200k_tokens" not in info
 
         assert info["supports_assistant_prefill"] is False
+        assert info["supports_forced_tool_use"] is False
         assert info["supports_function_calling"] is True
         assert info["supports_prompt_caching"] is True
         assert info["supports_reasoning"] is True

From d9f7f9ea1618894e08ad73545ccfc2940930e09e Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 11:46:58 -0700
Subject: [PATCH 048/113] feat(ui): add search to Agent Hub tab and admin
 agents table

Ports the Model Hub search to the AI Hub Agent Hub tab and the admin
/agents toolbar as a client-side filter over agent name and description.
Extracts the hub search matching into utils/searchUtils and fixes the
public Model Hub rendering the whole catalog when a search matches
nothing (LIT-5230)
---
 .../agents/_components/AgentsTable.test.tsx   |  36 +++++
 .../agents/_components/AgentsTable.tsx        |  42 +++++-
 .../components/AIHub/ModelHubTable.test.tsx   |  35 ++++-
 .../src/components/AIHub/ModelHubTable.tsx    |  47 +++++-
 .../src/components/model_filters.tsx          |   3 +-
 .../src/components/public_model_hub.test.tsx  |  21 +++
 .../src/components/public_model_hub.tsx       | 136 +++---------------
 .../src/utils/searchUtils.test.ts             |  64 +++++++++
 ui/litellm-dashboard/src/utils/searchUtils.ts |  32 +++++
 9 files changed, 282 insertions(+), 134 deletions(-)
 create mode 100644 ui/litellm-dashboard/src/utils/searchUtils.test.ts
 create mode 100644 ui/litellm-dashboard/src/utils/searchUtils.ts

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/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/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/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/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));
+}

From a92ca6cfde0a0394119807c51b7922dcf95fba3e Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 18:48:26 +0000
Subject: [PATCH 049/113] chore(models): regenerate model prices schema for
 supports_forced_tool_use

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 model_prices_and_context_window.schema.json | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/model_prices_and_context_window.schema.json b/model_prices_and_context_window.schema.json
index 3f6d3b4f910..9e370e5406a 100644
--- a/model_prices_and_context_window.schema.json
+++ b/model_prices_and_context_window.schema.json
@@ -662,6 +662,9 @@
         "supports_embedding_image_input": {
           "type": "boolean"
         },
+        "supports_forced_tool_use": {
+          "type": "boolean"
+        },
         "supports_function_calling": {
           "type": "boolean"
         },

From 6513f5c5399c725f4b3b15203a0f732d7dbcc075 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 19:05:03 +0000
Subject: [PATCH 050/113] test(utils): allow supports_forced_tool_use in model
 prices schema test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 tests/test_litellm/test_utils.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py
index 627f341fe2f..521e91daded 100644
--- a/tests/test_litellm/test_utils.py
+++ b/tests/test_litellm/test_utils.py
@@ -1005,6 +1005,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid():
                 "gemini_native_audio": {"type": "boolean"},
                 "gemini_audio_only_live": {"type": "boolean"},
                 "supports_embedding_image_input": {"type": "boolean"},
+                "supports_forced_tool_use": {"type": "boolean"},
                 "supports_function_calling": {"type": "boolean"},
                 "supports_image_input": {"type": "boolean"},
                 "supports_nova_canvas_image_edit": {"type": "boolean"},

From d816b75dd4978a776f27612f80565615122dfefe Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 19:05:03 +0000
Subject: [PATCH 051/113] feat(bedrock): gate forced tool_choice on
 supports_forced_tool_use in converse

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/llms/anthropic/common_utils.py        | 28 +++++----
 .../bedrock/chat/converse_transformation.py   | 10 +++-
 .../chat/test_converse_transformation.py      | 59 +++++++++++++++++++
 3 files changed, 85 insertions(+), 12 deletions(-)

diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py
index 0ca0e07d4d0..b1f927fd8f9 100644
--- a/litellm/llms/anthropic/common_utils.py
+++ b/litellm/llms/anthropic/common_utils.py
@@ -326,19 +326,13 @@ class AnthropicModelInfo(BaseLLMModelInfo):
             )
 
     @staticmethod
-    def _apply_forced_tool_choice(
-        model: str,
-        tool_choice: AnthropicMessagesToolChoice,
-        drop_params: bool,
-    ) -> AnthropicMessagesToolChoice:
-        """Forward ``tool_choice`` unless the model map flags the model with
+    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``), in which case downgrade to ``auto`` (with
-        drop_params) or raise a clean client-side 400."""
-        if tool_choice["type"] not in ("any", "tool"):
-            return tool_choice
+        ``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:
-            return tool_choice
+            return False
         if not (litellm.drop_params or drop_params):
             raise litellm.utils.UnsupportedParamsError(
                 message=(
@@ -349,6 +343,18 @@ class AnthropicModelInfo(BaseLLMModelInfo):
                 status_code=400,
             )
         litellm.verbose_logger.warning(DROP_FORCED_TOOL_CHOICE_WARNING, model)
+        return True
+
+    @staticmethod
+    def _apply_forced_tool_choice(
+        model: str,
+        tool_choice: AnthropicMessagesToolChoice,
+        drop_params: bool,
+    ) -> AnthropicMessagesToolChoice:
+        if tool_choice["type"] not in ("any", "tool"):
+            return tool_choice
+        if not AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+            return tool_choice
         disable_parallel: Final = tool_choice.get("disable_parallel_tool_use")
         if disable_parallel is None:
             return AnthropicMessagesToolChoice(type="auto")
diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index 395d99a4caa..6f99f572686 100644
--- a/litellm/llms/bedrock/chat/converse_transformation.py
+++ b/litellm/llms/bedrock/chat/converse_transformation.py
@@ -588,6 +588,10 @@ class AmazonConverseConfig(BaseConfig):
             supported_params.append("context_management")
         return supported_params
 
+    @staticmethod
+    def _auto_tool_choice() -> ToolChoiceValuesBlock:
+        return ToolChoiceValuesBlock(auto={})
+
     def map_tool_choice_values(
         self, model: str, tool_choice: str | dict, drop_params: bool
     ) -> ToolChoiceValuesBlock | None:
@@ -600,10 +604,14 @@ class AmazonConverseConfig(BaseConfig):
                     status_code=400,
                 )
         elif tool_choice == "required":
+            if AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+                return self._auto_tool_choice()
             return ToolChoiceValuesBlock(any={})
         elif tool_choice == "auto":
-            return ToolChoiceValuesBlock(auto={})
+            return self._auto_tool_choice()
         elif isinstance(tool_choice, dict):
+            if AnthropicModelInfo.forced_tool_use_downgraded(model, drop_params):
+                return self._auto_tool_choice()
             # only supported for anthropic + mistral models - https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ToolChoice.html
             specific_tool: Final = SpecificToolChoiceBlock(
                 name=make_valid_bedrock_tool_name(tool_choice.get("function", {}).get("name", ""))
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 63f895e1819..37ca801a7a7 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -6449,3 +6449,62 @@ def test_disabled_thinking_omitted_for_always_on_models_converse(
         assert "thinking" not in additional
     else:
         assert additional.get("thinking") == {"type": "disabled"}
+
+@pytest.mark.parametrize(
+    "model",
+    ["anthropic.claude-fable-5-1", "us.anthropic.claude-fable-5-1"],
+)
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_downgraded_to_auto_on_fable_5_1_converse(
+    local_model_cost_map, model, tool_choice
+):
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model=model, tool_choice=tool_choice, drop_params=True
+    )
+
+    assert result == {"auto": {}}
+
+
+@pytest.mark.parametrize(
+    "tool_choice",
+    ["required", {"type": "function", "function": {"name": "get_weather"}}],
+)
+def test_forced_tool_choice_raises_clean_error_on_fable_5_1_converse(
+    local_model_cost_map, tool_choice, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AmazonConverseConfig()
+
+    with pytest.raises(litellm.utils.UnsupportedParamsError, match="forced tool use"):
+        config.map_tool_choice_values(
+            model="anthropic.claude-fable-5-1", tool_choice=tool_choice, drop_params=False
+        )
+
+
+@pytest.mark.parametrize("tool_choice", ["auto", "none"])
+def test_unforced_tool_choice_unaffected_on_fable_5_1_converse(local_model_cost_map, tool_choice):
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model="anthropic.claude-fable-5-1", tool_choice=tool_choice, drop_params=True
+    )
+
+    assert result == ({"auto": {}} if tool_choice == "auto" else None)
+
+
+def test_forced_tool_choice_forwarded_on_converse_models_that_support_it(
+    local_model_cost_map, monkeypatch
+):
+    monkeypatch.setattr(litellm, "drop_params", False)
+    config = AmazonConverseConfig()
+
+    result = config.map_tool_choice_values(
+        model="anthropic.claude-fable-5", tool_choice="required", drop_params=False
+    )
+
+    assert result == {"any": {}}

From 98ea5eaab42228d725d3c3f184d5e69485352e84 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:08:22 -0700
Subject: [PATCH 052/113] fix(responses): correlate streamed tool call events
 on normalized item ids

---
 .../prompt_templates/factory.py               |  6 +-
 .../streaming_iterator.py                     | 10 ++-
 .../test_litellm_completion_responses.py      |  1 +
 .../test_streaming_iterator_transformation.py | 73 ++++++++++++++++---
 4 files changed, 75 insertions(+), 15 deletions(-)

diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index 3d06b975342..e6402e8c1bd 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -1696,9 +1696,9 @@ def convert_function_to_anthropic_tool_invoke(
 
 def _find_server_tool_result(
     tool_id: str,
-    web_search_results: Sequence[Any] | None,
-    tool_results: Sequence[Any] | None,
-) -> dict[str, Any] | None:
+    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),
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/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 fa373759cdd..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
@@ -3409,6 +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 59bd80791e3..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__
 
@@ -405,8 +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():
@@ -462,10 +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
@@ -558,3 +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

From 2adae6b4757aaaa9677785195ed68c8996a5d915 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:14:27 -0700
Subject: [PATCH 053/113] fix(prometheus): pass through router-originated
 labels when no proxy router exists

---
 litellm/integrations/prometheus.py            | 20 +++++----
 ..._prometheus_requested_model_cardinality.py | 45 +++++++++++++++++++
 2 files changed, 57 insertions(+), 8 deletions(-)

diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index 651f9c5d392..add91033ff3 100644
--- a/litellm/integrations/prometheus.py
+++ b/litellm/integrations/prometheus.py
@@ -161,25 +161,27 @@ def _get_budget_metrics_per_request_timeout() -> float:
 def _get_proxy_llm_router() -> Router | None:
     try:
         from litellm.proxy.proxy_server import llm_router
-    except ImportError:
+    except Exception:
         return None
     return llm_router
 
 
-def _bounded_requested_model_label(requested_model: str | None) -> str | None:
+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 router to vouch for the string, it also
-    collapses to ``other``.
+    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 UNRECOGNIZED_REQUESTED_MODEL_LABEL
+        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:
@@ -2667,7 +2669,9 @@ class PrometheusLogger(CustomLogger):
                 label_model_id = ""
                 label_api_base = ""
                 label_api_provider = ""
-                label_requested_model = _bounded_requested_model_label(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,
@@ -3226,7 +3230,7 @@ class PrometheusLogger(CustomLogger):
         _tags: Final = cast(list[str], kwargs.get("tags") or [])
 
         enum_values: Final = UserAPIKeyLabelValues(
-            requested_model=_bounded_requested_model_label(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"],
@@ -3267,7 +3271,7 @@ class PrometheusLogger(CustomLogger):
         )
 
         enum_values: Final = UserAPIKeyLabelValues(
-            requested_model=_bounded_requested_model_label(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/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
index 8d803eeab18..519a13751f1 100644
--- a/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
+++ b/tests/test_litellm/integrations/test_prometheus_requested_model_cardinality.py
@@ -7,6 +7,8 @@ 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
@@ -169,6 +171,49 @@ async def test_unknown_models_collapse_to_other_when_router_is_unavailable():
     }
 
 
+@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()
 

From b0751169ebdb4df24a9ddafacb4932995159ab3b Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:14:46 -0700
Subject: [PATCH 054/113] fix(cost): bill off-peak rates for deployments that
 set only off_peak_pricing

Cost lookup selects the deployment-scoped cost map entry only when custom
pricing is detected and the entry carries a base pricing field. A deployment
whose model_info held nothing but off_peak_pricing failed both conditions, so
its schedule was silently ignored and every request billed at the shared
backend rate.

use_custom_pricing_for_model now also treats deployment-scoped pricing fields
in the metadata model_info as custom pricing, and the router inherits the
backend model's built-in base token rates onto such an entry at registration,
which also lets cache pricing inheritance apply. Regression tests cover the
registration, the detection, and the costed request end to end.
---
 litellm/litellm_core_utils/litellm_logging.py |   8 +-
 litellm/router.py                             |  49 +++++++++
 .../test_register_model_custom_pricing.py     | 102 ++++++++++++++++++
 3 files changed, 157 insertions(+), 2 deletions(-)

diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index 97c4d038734..2312eb6130f 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
@@ -5030,7 +5032,9 @@ def use_custom_pricing_for_model(litellm_params: dict | None) -> bool:
     """
     Check if the model uses custom pricing
 
-    Returns True if any of `SPECIAL_MODEL_INFO_PARAMS` are present in `litellm_params` or `model_info`
+    Returns True if any custom pricing field is present in `litellm_params`, or if
+    any custom pricing or deployment-scoped pricing field (such as
+    ``off_peak_pricing``) is present in the metadata ``model_info``
     """
     if litellm_params is None:
         return False
@@ -5048,7 +5052,7 @@ 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/router.py b/litellm/router.py
index c93c1753f0e..f3563d9c387 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -8163,6 +8163,40 @@ 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 base token rates 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. User-specified rates 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
+        for field in ("input_cost_per_token", "output_cost_per_token"):
+            if model_info.get(field) is None:
+                backend_value = backend_info.get(field)
+                if backend_value is not None:
+                    model_info[field] = backend_value
+
     @staticmethod
     def _inherit_builtin_tiered_output_rate(
         model_info: dict, backend_model: str, custom_llm_provider: str | None
@@ -8251,6 +8285,11 @@ 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,
@@ -8992,6 +9031,11 @@ 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,
@@ -9246,6 +9290,11 @@ 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,
diff --git a/tests/test_litellm/test_register_model_custom_pricing.py b/tests/test_litellm/test_register_model_custom_pricing.py
index 87e9895806f..452a15334ef 100644
--- a/tests/test_litellm/test_register_model_custom_pricing.py
+++ b/tests/test_litellm/test_register_model_custom_pricing.py
@@ -891,3 +891,105 @@ def test_router_deployments_sharing_backend_keep_their_own_off_peak_pricing():
             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

From c21e895fe26b16cc97f0d4ed8e389f6ede9f2688 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:16:27 -0700
Subject: [PATCH 055/113] fix(proxy): handle CRLF and CR SSE frame terminators
 and flush held tail in anthropic stream restamper

---
 .../streaming_model_restamp.py                |  49 ++++++---
 litellm/proxy/common_request_processing.py    |  21 ++--
 .../test_streaming_model_restamp.py           | 100 +++++++++++++++++-
 3 files changed, 144 insertions(+), 26 deletions(-)

diff --git a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
index e8d54f03949..7da5e5099fc 100644
--- a/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
+++ b/litellm/proxy/anthropic_endpoints/streaming_model_restamp.py
@@ -8,6 +8,7 @@ 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
 
@@ -16,7 +17,7 @@ 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: Final = b"\n\n"
+_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"')
 
@@ -46,15 +47,16 @@ def _restamped_data_line(line: str, requested_model: str) -> str | None:
     restamped: Final = _restamped_event(event, requested_model)
     if restamped is None:
         return None
-    return f"data: {json.dumps(restamped, separators=(',', ':'))}"
+    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.split("\n")
+    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 "\n".join(new if new is not None else old for new, old in zip(restamped, lines))
+    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:
@@ -93,10 +95,12 @@ 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 are emitted as their
-    terminator closes them and an incomplete tail is held until it completes,
-    so the restamp never misses a torn frame. Once ``message_start`` has been
-    handled, or the first real event proves the stream carries none, every
+    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.
     """
 
@@ -117,17 +121,27 @@ class AnthropicStreamModelRestamper:
             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
-        if _SSE_FRAME_END not in combined:
+        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""
-        closed, _, tail = combined.rpartition(_SSE_FRAME_END)
-        emitted: Final = self._restamped_closed_block(closed + _SSE_FRAME_END)
+        emitted: Final = self._restamped_closed_block(combined[: boundaries[-1]])
+        tail: Final = combined[boundaries[-1] :]
         if not self._armed:
             self._held = b""
             return emitted + tail
@@ -135,7 +149,8 @@ class AnthropicStreamModelRestamper:
         return emitted
 
     def _restamped_closed_block(self, closed: bytes) -> bytes:
-        frames: Final = tuple(closed.split(_SSE_FRAME_END)[:-1])
+        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
@@ -147,13 +162,13 @@ class AnthropicStreamModelRestamper:
         if decider is None:
             return closed
         self._armed = False
-        decider_frame: Final = frames[decider] + _SSE_FRAME_END
-        if _MESSAGE_START_MARKER not in decider_frame:
+        if _MESSAGE_START_MARKER not in frames[decider]:
             return closed
-        restamped_text: Final = _restamped_frame(decider_frame.decode("utf-8", errors="ignore"), self._requested_model)
+        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 + _SSE_FRAME_END
-            for index, frame in enumerate(frames)
+            restamped_text.encode("utf-8") if index == decider else frame for index, frame in enumerate(frames)
         )
diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py
index 989cc7c18fb..eda7ebfa624 100644
--- a/litellm/proxy/common_request_processing.py
+++ b/litellm/proxy/common_request_processing.py
@@ -3410,12 +3410,10 @@ class ProxyBaseLLMRequestProcessing:
             return chunk
 
     @staticmethod
-    def _sse_chunk_serializer(restamp_model: str | None) -> StreamChunkSerializer:
-        if not restamp_model:
+    def _sse_chunk_serializer(restamper: AnthropicStreamModelRestamper | None) -> StreamChunkSerializer:
+        if restamper is None:
             return ProxyBaseLLMRequestProcessing.return_sse_chunk
 
-        restamper: Final = AnthropicStreamModelRestamper(restamp_model)
-
         def serialize(chunk: object) -> str:
             return ProxyBaseLLMRequestProcessing.return_sse_chunk(restamper.process(chunk))
 
@@ -3481,11 +3479,16 @@ 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
@@ -3548,6 +3551,9 @@ 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
@@ -3558,8 +3564,7 @@ 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,
@@ -3627,16 +3632,18 @@ class ProxyBaseLLMRequestProcessing:
         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._sse_chunk_serializer(restamp_model),
+            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/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
index 385173b24a9..b7bc670c7f8 100644
--- a/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
+++ b/tests/test_litellm/proxy/anthropic_endpoints/test_streaming_model_restamp.py
@@ -14,12 +14,12 @@ from litellm.proxy.anthropic_endpoints.streaming_model_restamp import (
 from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing
 
 
-def _message_start_frame(model: str) -> bytes:
+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\ndata: {json.dumps(payload)}\n\n".encode()
+    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:
@@ -190,3 +190,99 @@ async def test_sse_generator_restamps_message_start_split_across_chunks():
 
     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

From 33004d2f0cf4311e51adea9c450e1686a5f2fee9 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:17:02 -0700
Subject: [PATCH 056/113] test(e2e/ui): cover the Budgets page create, edit and
 delete flows (#39052)

* test(e2e/ui): cover the Budgets page create, edit and delete flows

The Budgets page had no browser coverage at all, so an admin creating or
editing a spend cap through the UI was only exercised by hand at RC time.

Each test reads the budget back from /budget/list, a different route from
the one the table renders, so a row that only exists in the table's cache
does not pass. The edit test pins the rate limits an unrelated spend-cap
edit has no business touching.

* test(e2e/ui): trim comments that restate the test steps

Review flagged the explanatory comments as restating ordinary setup rather
than explaining anything. Keeps the two that carry the regression rationale
for an assertion and drops the rest.

---------

Co-authored-by: Claude <noreply@anthropic.com>
---
 tests/e2e/ui/tests/budgets/budgets.spec.ts | 133 +++++++++++++++++++++
 1 file changed, 133 insertions(+)
 create mode 100644 tests/e2e/ui/tests/budgets/budgets.spec.ts

diff --git a/tests/e2e/ui/tests/budgets/budgets.spec.ts b/tests/e2e/ui/tests/budgets/budgets.spec.ts
new file mode 100644
index 00000000000..1ad1e488d25
--- /dev/null
+++ b/tests/e2e/ui/tests/budgets/budgets.spec.ts
@@ -0,0 +1,133 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { masterKey } from "../../helpers/traffic";
+
+interface StoredBudget {
+  budget_id: string;
+  max_budget: number | null;
+  tpm_limit: number | null;
+  rpm_limit: number | null;
+  budget_duration: string | null;
+}
+
+/** A different route from the one the table renders from, so a row that only lives in its cache fails here. */
+async function findBudget(page: PlaywrightPage, budgetId: string): Promise<StoredBudget | undefined> {
+  const res = await page.request.get("/budget/list", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  expect(res.ok(), `GET /budget/list (${res.status()})`).toBe(true);
+  return ((await res.json()) as StoredBudget[]).find((row) => row.budget_id === budgetId);
+}
+
+async function createBudgetViaApi(page: PlaywrightPage, budget: Partial<StoredBudget>): Promise<void> {
+  const res = await page.request.post("/budget/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: budget,
+  });
+  expect(res.ok(), `POST /budget/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+}
+
+async function searchForBudget(page: PlaywrightPage, budgetId: string): Promise<void> {
+  await page.getByPlaceholder("Search by budget ID").fill(budgetId);
+}
+
+test.describe("Budgets", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Create a budget with rate limits and a spend cap", async ({ page }) => {
+    const budgetId = `e2e-budget-create-${Date.now()}`;
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await page.getByRole("button", { name: "Create Budget" }).click();
+
+    const modal = page.getByRole("dialog", { name: "Create Budget" });
+    await expect(modal).toBeVisible({ timeout: 10_000 });
+
+    await modal.getByRole("textbox", { name: "Budget ID" }).fill(budgetId);
+    await modal.getByRole("spinbutton", { name: "Max Tokens per minute" }).fill("5000");
+    await modal.getByRole("spinbutton", { name: "Max Requests per minute" }).fill("60");
+
+    await modal.getByRole("button", { name: "Optional Settings" }).click();
+    await modal.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("25.5");
+    await modal.getByRole("combobox", { name: "Reset Budget" }).click();
+    await page.getByRole("option", { name: "weekly" }).click();
+
+    await modal.getByRole("button", { name: "Create Budget" }).click();
+    await expect(modal).not.toBeVisible({ timeout: 10_000 });
+
+    await searchForBudget(page, budgetId);
+    const row = page.getByRole("row").filter({ hasText: budgetId });
+    await expect(row).toBeVisible({ timeout: 10_000 });
+    await expect(row).toContainText("$25.50");
+
+    const stored = await findBudget(page, budgetId);
+    expect(stored, `budget ${budgetId} readable from /budget/list`).toBeTruthy();
+    expect(stored?.max_budget, "spend cap persisted").toBe(25.5);
+    expect(stored?.tpm_limit, "TPM limit persisted").toBe(5000);
+    expect(stored?.rpm_limit, "RPM limit persisted").toBe(60);
+    expect(stored?.budget_duration, "reset window persisted").toBe("7d");
+  });
+
+  test("Raising a budget's spend cap leaves its rate limits alone", async ({ page }) => {
+    const budgetId = `e2e-budget-edit-${Date.now()}`;
+    await createBudgetViaApi(page, { budget_id: budgetId, max_budget: 10, tpm_limit: 1000, rpm_limit: 20 });
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await searchForBudget(page, budgetId);
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toBeVisible({ timeout: 10_000 });
+
+    await page.getByTestId(`budget-actions-${budgetId}`).click();
+    await page.getByTestId("budget-action-edit").click();
+
+    const modal = page.getByRole("dialog", { name: "Edit Budget" });
+    await expect(modal).toBeVisible({ timeout: 10_000 });
+
+    await modal.getByRole("button", { name: "Optional Settings" }).click();
+    await modal.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("99");
+    await modal.getByRole("button", { name: "Save", exact: true }).click();
+    await expect(modal).not.toBeVisible({ timeout: 10_000 });
+
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toContainText("$99.00", { timeout: 10_000 });
+
+    // Not hypothetical: the edit form posts the whole budget, so a field it fails to
+    // seed from the existing row goes to the server as null and silently clears.
+    const stored = await findBudget(page, budgetId);
+    expect(stored?.max_budget, "spend cap raised").toBe(99);
+    expect(stored?.tpm_limit, "TPM limit untouched by a spend-cap edit").toBe(1000);
+    expect(stored?.rpm_limit, "RPM limit untouched by a spend-cap edit").toBe(20);
+  });
+
+  test("Delete a budget", async ({ page }) => {
+    const budgetId = `e2e-budget-delete-${Date.now()}`;
+    await createBudgetViaApi(page, { budget_id: budgetId, max_budget: 5 });
+
+    await navigateToPage(page, Page.Budgets);
+    await dismissFeedbackPopup(page);
+
+    await searchForBudget(page, budgetId);
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toBeVisible({ timeout: 10_000 });
+
+    await page.getByTestId(`budget-actions-${budgetId}`).click();
+    await page.getByTestId("budget-action-delete").click();
+
+    const modal = page.getByRole("dialog", { name: "Delete Budget?" });
+    await expect(modal).toBeVisible({ timeout: 5_000 });
+    await modal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByRole("row").filter({ hasText: budgetId })).toHaveCount(0, { timeout: 10_000 });
+
+    // The row disappearing is a cache invalidation; the budget is gone when the route stops serving it.
+    await expect
+      .poll(async () => await findBudget(page, budgetId), {
+        message: `budget ${budgetId} still readable from /budget/list after delete`,
+        timeout: 15_000,
+      })
+      .toBeUndefined();
+  });
+});

From 8d0e7aee2ff61e0100137feff993cb1a34a8ad52 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:20:09 -0700
Subject: [PATCH 057/113] test(router): cover
 _inherit_builtin_base_rates_for_off_peak directly

The router_code_coverage gate only counts calls made from test files with
router in the filename, so the helper needs direct unit tests beside the
other inheritance helpers in test_router_model_cost_isolation.py: fills
missing base rates from the builtin entry, leaves explicit rates alone,
and no-ops without a block or for an unmapped backend model.
---
 .../test_router_model_cost_isolation.py       | 66 +++++++++++++++++++
 1 file changed, 66 insertions(+)

diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index b580b03574e..c8adc0af431 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -538,6 +538,72 @@ 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_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.

From 0cf236bebbbdc1b0fc2f20a817ca254efa2a72c0 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:21:45 -0700
Subject: [PATCH 058/113] test(e2e/ui): cover creating, testing and deleting a
 guardrail (#39053)

* test(e2e/ui): cover creating, testing and deleting a guardrail

The Guardrails page had no browser coverage. The RC checklist covers it by
hand against a live Presidio, which is why it has always been skipped in CI.

These drive the LiteLLM content filter instead, which runs inside the proxy,
so the whole flow is exercised without a third-party moderation service. The
create test does not stop at the table row: it sends a prompt carrying the
keyword it just banned and asserts the gateway refuses it, then sends a clean
prompt through the same guardrail and asserts it is served.

* test(e2e/ui): delete the guardrails these tests create

Review caught the fixtures being left behind. Guardrails are database rows
that show up in the table and in the playground's list, so a run that leaves
them changes what the next run sees.

Also trims the comments that restated what the helpers already say.

* test(e2e/ui): fail the run when guardrail teardown does not delete

Review caught the afterEach discarding the DELETE response, so a failed
cleanup finished quietly and left the guardrail for the next run to trip on.

* test(e2e/ui): wait for a new guardrail to reach the request path

The wizard test drove one chat completion immediately after creating the
guardrail and required a 400. A trace from the deployed stack shows the
record is stored correctly (blocked_words, action BLOCK, block_on_violation)
and the call six seconds later is still served unguarded, so the first
request can land before the proxy picks the guardrail up.

Polls the same call to the same 400 instead, which keeps the assertion and
lets the refresh land. If it never blocks, this stays red, which is what we
want it to say.

---------

Co-authored-by: Claude <noreply@anthropic.com>
---
 .../ui/tests/guardrails/guardrails.spec.ts    | 204 +++++++++++++++++-
 1 file changed, 203 insertions(+), 1 deletion(-)

diff --git a/tests/e2e/ui/tests/guardrails/guardrails.spec.ts b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts
index 77ff020510b..1e43c7a2b22 100644
--- a/tests/e2e/ui/tests/guardrails/guardrails.spec.ts
+++ b/tests/e2e/ui/tests/guardrails/guardrails.spec.ts
@@ -1,11 +1,213 @@
-import { test, expect } from "@playwright/test";
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
 import { ADMIN_STORAGE_PATH, E2E_TEAM_NO_ADMIN_ID } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+
+interface StoredGuardrail {
+  guardrail_id: string;
+  guardrail_name: string | null;
+}
+
+async function listGuardrails(page: PlaywrightPage): Promise<StoredGuardrail[]> {
+  const res = await page.request.get("/v2/guardrails/list", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  expect(res.ok(), `GET /v2/guardrails/list (${res.status()})`).toBe(true);
+  return ((await res.json()) as { guardrails: StoredGuardrail[] }).guardrails;
+}
+
+async function findGuardrail(page: PlaywrightPage, name: string): Promise<StoredGuardrail | undefined> {
+  return (await listGuardrails(page)).find((row) => row.guardrail_name === name);
+}
+
+const createdGuardrails: string[] = [];
+
+async function createKeywordGuardrailViaApi(page: PlaywrightPage, name: string, keyword: string): Promise<string> {
+  const res = await page.request.post("/guardrails", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: {
+      guardrail: {
+        guardrail_name: name,
+        litellm_params: {
+          guardrail: "litellm_content_filter",
+          mode: "pre_call",
+          default_on: false,
+          blocked_words: [{ keyword, action: "BLOCK" }],
+        },
+      },
+    },
+  });
+  expect(res.ok(), `POST /guardrails failed (${res.status()}): ${await res.text()}`).toBe(true);
+  createdGuardrails.push(name);
+  const guardrail = await findGuardrail(page, name);
+  expect(guardrail?.guardrail_id, `guardrail ${name} has an id`).toBeTruthy();
+  return guardrail!.guardrail_id;
+}
+
+async function openKeywordsStep(page: PlaywrightPage, name: string) {
+  await page.getByRole("button", { name: "Add New Guardrail" }).click();
+  await page.getByRole("menuitem", { name: "Add Provider Guardrail" }).click();
+
+  const wizard = page.getByRole("dialog", { name: "Create guardrail" });
+  await expect(wizard).toBeVisible({ timeout: 10_000 });
+
+  await wizard.getByRole("textbox", { name: "Guardrail Name" }).fill(name);
+  await wizard.getByRole("combobox", { name: "Guardrail Provider" }).click();
+  // The content filter runs inside the proxy, so this is the one provider a test can
+  // configure end to end without standing up a third-party moderation service.
+  await page.getByRole("option", { name: /LiteLLM Content Filter/ }).click();
+
+  for (const step of ["Topics", "Patterns", "Keywords"]) {
+    await wizard.getByRole("button", { name: "Next" }).click();
+    await expect(wizard).toContainText(step, { timeout: 10_000 });
+  }
+  return wizard;
+}
 
 test.describe("Guardrails", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
+  test.afterEach(async ({ page }) => {
+    // Guardrails live in the database and show up in the table and the playground list, so a run
+    // that leaves them behind changes what the next run sees.
+    for (const name of createdGuardrails.splice(0)) {
+      const guardrail = await findGuardrail(page, name);
+      if (guardrail) {
+        const deleted = await page.request.delete(`/guardrails/${guardrail.guardrail_id}`, {
+          headers: { Authorization: `Bearer ${masterKey()}` },
+        });
+        expect(deleted.ok(), `DELETE /guardrails/${guardrail.guardrail_id} (${deleted.status()})`).toBe(true);
+      }
+    }
+  });
+
+  test("A guardrail created through the wizard blocks the keyword it was given", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-create-${stamp}`;
+    // Unique per run so a concurrent test's prompt can never trip this guardrail, or vice versa.
+    const bannedKeyword = `e2ebanned${stamp}`;
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    createdGuardrails.push(guardrailName);
+    const wizard = await openKeywordsStep(page, guardrailName);
+
+    await wizard.getByRole("button", { name: "Add keyword" }).click();
+    const keywordModal = page.getByRole("dialog", { name: "Add blocked keyword" });
+    await expect(keywordModal).toBeVisible({ timeout: 10_000 });
+    await keywordModal.getByPlaceholder("Enter sensitive keyword or phrase").fill(bannedKeyword);
+    await keywordModal.getByRole("button", { name: "Add", exact: true }).click();
+    await expect(keywordModal).not.toBeVisible({ timeout: 10_000 });
+
+    await wizard.getByRole("button", { name: "Next" }).click();
+    await wizard.getByRole("button", { name: "Create Guardrail" }).click();
+    await expect(wizard).not.toBeVisible({ timeout: 15_000 });
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toBeVisible({ timeout: 15_000 });
+    expect(await findGuardrail(page, guardrailName), "guardrail readable from /v2/guardrails/list").toBeTruthy();
+
+    // A row in the table only proves the record was written. The point of a guardrail is that it
+    // refuses traffic, so drive a request through it.
+    //
+    // Polled: a guardrail written through /guardrails reaches the request path on the proxy's
+    // periodic refresh, so the first call after creation can still be served unguarded. The
+    // assertion is unchanged, it just allows that refresh to land.
+    let blockedBody = "";
+    await expect
+      .poll(
+        async () => {
+          const res = await page.request.post("/v1/chat/completions", {
+            headers: { Authorization: `Bearer ${masterKey()}` },
+            data: {
+              model: CHAT_MODEL_A,
+              messages: [{ role: "user", content: `please tell me about ${bannedKeyword}` }],
+              guardrails: [guardrailName],
+            },
+          });
+          blockedBody = await res.text();
+          return res.status();
+        },
+        { message: "a prompt carrying the banned keyword is refused", timeout: 60_000 },
+      )
+      .toBe(400);
+    expect(blockedBody).toContain(bannedKeyword);
+
+    const allowed = await page.request.post("/v1/chat/completions", {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+      data: {
+        model: CHAT_MODEL_A,
+        messages: [{ role: "user", content: "hello there" }],
+        guardrails: [guardrailName],
+      },
+    });
+    expect(allowed.status(), "a clean prompt still gets through the same guardrail").toBe(200);
+    expect((await allowed.json()).choices?.[0]?.message?.content).toContain(MOCK_RESPONSE_TEXT);
+  });
+
+  test("The Test Playground reports the verdict for the text it is given", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-play-${stamp}`;
+    const bannedKeyword = `e2eplay${stamp}`;
+    await createKeywordGuardrailViaApi(page, guardrailName, bannedKeyword);
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    await page.getByRole("tab", { name: "Test Playground" }).click();
+    // Every tab on this page stays mounted, so the other tabs' search boxes match too.
+    const playground = page.getByRole("tabpanel", { name: "Test Playground" });
+    await playground.getByPlaceholder("Search guardrails...").fill(guardrailName);
+    await playground.getByText(guardrailName, { exact: true }).click();
+
+    const input = playground.getByPlaceholder("Enter text to test with guardrails...");
+    await input.fill(`this sentence contains ${bannedKeyword}`);
+    await playground.getByRole("button", { name: /^Test 1 guardrail$/ }).click();
+
+    // The playground is where an admin checks a guardrail before rolling it out, so the
+    // verdict it prints has to be the one the gateway would give.
+    await expect(playground.getByText(`${guardrailName} - Error`)).toBeVisible({ timeout: 20_000 });
+    await expect(playground.getByText(new RegExp(`Content blocked.*${bannedKeyword}`))).toBeVisible({
+      timeout: 10_000,
+    });
+
+    await input.fill("this sentence is perfectly ordinary");
+    await playground.getByRole("button", { name: /^Test 1 guardrail$/ }).click();
+
+    await expect(playground.getByText(`${guardrailName} - Error`)).toHaveCount(0, { timeout: 20_000 });
+    await expect(playground.getByText("this sentence is perfectly ordinary").last()).toBeVisible({ timeout: 10_000 });
+  });
+
+  test("Delete a guardrail", async ({ page }) => {
+    const stamp = Date.now();
+    const guardrailName = `e2e-guardrail-delete-${stamp}`;
+    const guardrailId = await createKeywordGuardrailViaApi(page, guardrailName, `e2edelete${stamp}`);
+
+    await navigateToPage(page, Page.Guardrails);
+    await dismissFeedbackPopup(page);
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toBeVisible({ timeout: 15_000 });
+
+    await page.getByTestId(`guardrail-actions-${guardrailId}`).click();
+    await page.getByTestId("guardrail-action-delete").click();
+
+    const modal = page.getByRole("dialog");
+    await expect(modal).toBeVisible({ timeout: 5_000 });
+    await modal.getByRole("button", { name: "Delete", exact: true }).click();
+
+    await expect(page.getByRole("row").filter({ hasText: guardrailName })).toHaveCount(0, { timeout: 15_000 });
+
+    // The RC checklist deletes then reloads, because a row vanishing from the table has
+    // fooled us before; assert against the route the reload would read.
+    await expect
+      .poll(async () => await findGuardrail(page, guardrailName), {
+        message: `guardrail ${guardrailName} still listed after delete`,
+        timeout: 15_000,
+      })
+      .toBeUndefined();
+  });
+
   test("Create a Presidio guardrail, see it in team settings, and delete it", async ({ page }) => {
     const guardrailName = `e2e-presidio-${Date.now()}`;
 

From 4875872fe559fb9d30a9efe3766106459dedd914 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:25:39 -0700
Subject: [PATCH 059/113] fix(cost): treat a non-mapping off_peak_pricing value
 as never off-peak

A bare string or list under off_peak_pricing in YAML passed the truthy
guard and crashed _is_off_peak with AttributeError, breaking cost
calculation for that deployment. Malformed pieces of the block are
documented to not match rather than error, so guard the block itself the
same way and bill standard rates.
---
 .../litellm_core_utils/llm_cost_calc/utils.py |  2 +-
 .../llm_cost_calc/test_llm_cost_calc_utils.py | 27 +++++++++++++++++++
 2 files changed, 28 insertions(+), 1 deletion(-)

diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py
index c968fac254e..b34c416cd40 100644
--- a/litellm/litellm_core_utils/llm_cost_calc/utils.py
+++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py
@@ -443,7 +443,7 @@ def _apply_off_peak_pricing(
     off_peak_pricing falls back to the standard rate.
     """
     off_peak: Final = model_info.get("off_peak_pricing")
-    if not off_peak or not _is_off_peak(off_peak, current_time):
+    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),
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 501a9314c90..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
@@ -648,6 +648,33 @@ def test_get_token_base_cost_applies_off_peak_pricing():
     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 fa581931f73ea6b4094188220b8f06a14c3006b2 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:27:18 -0700
Subject: [PATCH 060/113] test(llm_translation): expect unpaired server tool
 calls to replay as tool_use

---
 tests/llm_translation/test_prompt_factory.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

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"}

From 8a4ba788696d950c4d0ce8fa17cb11735a7e49a7 Mon Sep 17 00:00:00 2001
From: Sean Yasnogorodski <seany@alice.io>
Date: Tue, 1 Sep 2026 22:33:39 +0300
Subject: [PATCH 061/113] feat(guardrails): add Alice guardrail (#38898)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* feat(guardrails): add Alice by ActiveFence guardrail

Adds `guardrail: alice` — policy-based guardrails for prompts and model
responses, evaluated against ActiveFence's Alice.

What makes this different from the other providers: Alice evaluates against
policies configured per *application*, and a proxy typically fronts several of
them, so the application cannot be a static config value. It is named on the
LiteLLM virtual key instead:

    curl $PROXY/key/generate -H "Authorization: Bearer $LITELLM_MASTER_KEY" \
      -d '{"key_alias": "payments-bot",
           "metadata": {"alice_app_id": "payments-bot"}}'

read via `CustomGuardrail._get_admin_metadata`, with `key_alias` as the
fallback. That helper is what makes it trustworthy: it reads whichever metadata
holder the proxy wrote the authenticated key's values into — which differs by
route — and the proxy strips caller-supplied `user_api_key_*` from both, so a
caller cannot point its own traffic at an application with laxer policies than
the one its key was issued for. A request whose key names no application is
refused rather than evaluated against a guess.

Implements `apply_guardrail` only, so pre_call, during_call, post_call and
streaming all come from UnifiedLLMGuardrails. Blocks with
GuardrailRaisedException; masks by substituting Alice's redacted text; a MASK
carrying no replacement blocks rather than passing the original through. A
verdict reporting `errors[]` is treated as a failure, not a pass — otherwise a
half-evaluated message would be allowed. `unreachable_fallback` (already on
LitellmParams) chooses fail-closed or fail-open on transport failure.

Config:

    guardrails:
      - guardrail_name: alice
        litellm_params:
          guardrail: alice
          mode: [pre_call, post_call]
          api_key: os.environ/ALICE_API_KEY

21 tests in tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
cover registration, credential resolution, the app-id ladder including the
forged-metadata case, every verdict, and both unreachable policies.

No new LitellmParams field, so no schema.d.ts regeneration is needed.

* refactor(guardrails): post to Alice's LiteLLM endpoint and forward verbatim

Switches from `/v2/evaluate/message` — Alice's single-text endpoint — to
`/v2/evaluate/litellm`, which takes the hook's arguments as they arrive and
answers with a verdict.

That inverts where the work happens, and shrinks this plugin accordingly. It
now selects nothing and renames nothing: it posts `{input_type, inputs,
request_data}` and enforces `{verdict, categories, correlation_id, message,
replacements}`. Which parts of a conversation are worth evaluating, and how a
verdict is reached, are decided by Alice — so changing either is a change on
their side rather than a LiteLLM upgrade for every user.

The app-id resolution this plugin carried is gone with it. Alice reads the
application off the authenticated key's metadata itself, from the payload it is
handed, so the ladder here was duplicating a decision the far side already
makes. The security property is unchanged and still comes from the proxy
stripping caller-supplied `user_api_key_*` before a guardrail sees the request.

Masking is now positional — the far side chose which texts it was answering
for, so it says which by index. Only `texts` is written; a new
`structured_messages` object would make the chat translation layer skip the
`texts` write-back and silently drop the edits. A mask that lands nowhere
blocks rather than passing the original through.

`request_data` carries live Python objects (an OpenTelemetry span among them),
so `_json_safe` copies it into something serialisable by a mechanical rule
rather than a field list — a list drifts from what the far side needs, a rule
cannot. Serialising naively raises, and that error would read as "guardrail
unavailable" on every request.

26 tests, covering verbatim forwarding, each verdict, positional masking, the
`structured_messages` identity trap, both unreachable policies, and the
serialiser's handling of unserialisable values and cycles.

* fix(alice guardrail): satisfy lint and code-quality CI gates

- Bound _json_safe's recursion and register it in recursive_detector's
  ignore list (it already caps depth and dedupes cycles by id, matching
  the repo's established pattern for legitimate bounded recursion).
- Clear ruff-strict budget breaches: annotate __init__'s return type,
  raise TypeError (not ValueError) for a bad response body, type
  _json_safe's payload as object instead of Any, and file-scope-ignore
  ANN401 for **kwargs (forwarding it as object broke the call into
  CustomGuardrail.__init__, confirmed via basedpyright).
- Clear type-discipline budget breaches: suppress the construction/
  annotation checks on one-shot HTTP payloads, the module-level
  guardrail registries, and _json_safe's bounded accumulator; narrow
  AliceVerdict's list fields to tuples and _evaluate's request_data to
  Mapping[str, object] where nothing downstream mutates them.

* test(alice guardrail): assert the guardrail actually registers

The registration test called init_guardrails_v2 and asserted nothing, so it
passed whether or not the guardrail was ever registered — TQ001 in the
test-quality gate, and a fair catch: a test that cannot fail is not covering
the thing it names.

Now asserts exactly one AliceGuardrail lands in litellm.callbacks under the
configured name.

This surfaced only after the ruff-strict and type-discipline gates stopped
failing ahead of it; the lint job runs its gates in sequence, so an earlier
failure masks every later one.

* fix(alice guardrail): reach 100% patch coverage, drop the ActiveFence naming

Codecov flagged 10 uncovered lines, all of them error paths — which is where a
guardrail most needs covering, since each one decides whether traffic flows
unscreened.

Two of the ten turned out to be dead rather than untested, and are removed:

- `except GuardrailRaisedException: raise` in apply_guardrail. `_evaluate`
  raises httpx errors, Timeout and TypeError, never that — so the clause could
  never fire.
- the trailing `json.dumps` probe in `_json_safe`. Everything json.dumps
  handles natively is caught by the isinstance branches above (a dict or list
  subclass included), so anything reaching the bottom — bytes, datetime, an
  OpenTelemetry span — cannot cross the wire regardless. It now says so and
  returns None.

The rest are now tested: a timeout, 502/503/504 as unreachable, a 4xx as NOT
unreachable (a rejected credential is our misconfiguration, not an outage, and
must not fail open), a non-object response body, and a model whose model_dump
raises.

Also drops "by ActiveFence" throughout — the product is Alice — and points the
header at alice.io. `ui_friendly_name` is now "Alice", which is the key
guardrailLogoMap and the garden card look up, so all three moved together.

* fix(alice guardrail): strip caller credentials, widen unreachable detection, block partial MASK

Addresses PR review: request_data no longer forwards secret_fields.raw_headers or
the root api_key to Alice (the caller's Authorization token in the clear otherwise);
HTTP 500, malformed JSON, and a non-object body now route through the configured
unreachable_fallback instead of raising raw, so fail_open still fails open on those;
a MASK verdict with even one out-of-range replacement now blocks entirely instead of
silently letting the rest through unmasked. Also tightens request_data's type and
documents the known streaming-mask limitation on the class.

* fix(alice guardrail): strip credentials at any depth, stop filtering on texts

secret_fields/api_key/headers/provider_specific_header can appear nested
under proxy_server_request, metadata, litellm_metadata, and their
requester_metadata/body sub-paths in a real captured payload — a
top-level-only strip missed all of those. _json_safe now drops these keys
by name wherever they occur during serialization, so a new nesting path
can't reintroduce the leak.

apply_guardrail also stopped skipping the call whenever texts was empty,
even when tool_calls/images/structured_messages carried content — that
was the plugin making a selection decision Alice's design says belongs on
the far side. It now only skips when none of the selectable fields have
anything in them.

* fix(alice guardrail): route an undecodable response body through the fallback

`response.json()` raises UnicodeDecodeError when the body carries bytes that
are not valid UTF-8, and that escaped the except clause: UnicodeDecodeError is
a *sibling* of json.JSONDecodeError under ValueError, not a subclass of it, so
naming only JSONDecodeError left it uncaught. Both fallback modes surfaced a
raw decoding error instead of applying unreachable_fallback — which for a
fail_open deployment meant a hard failure where it had asked for an allow.

Named explicitly rather than widening to ValueError, so the clause still says
which three conditions it means. Tested under both policies.
---
 .../guardrail_hooks/alice/__init__.py         |  34 +
 .../guardrails/guardrail_hooks/alice/alice.py | 369 +++++++++++
 litellm/types/guardrails.py                   |   1 +
 .../proxy/guardrails/guardrail_hooks/alice.py |  21 +
 ruff-strict.toml                              |   4 +
 .../code_coverage_tests/recursive_detector.py |   1 +
 .../guardrails/guardrail_hooks/test_alice.py  | 614 ++++++++++++++++++
 .../public/assets/logos/alice.svg             |   4 +
 .../_components/guardrail_garden_configs.ts   |   6 +
 .../_components/guardrail_garden_data.test.ts |   1 +
 .../_components/guardrail_garden_data.ts      |  10 +
 .../_components/guardrail_info_helpers.tsx    |   3 +
 12 files changed, 1068 insertions(+)
 create mode 100644 litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py
 create mode 100644 litellm/proxy/guardrails/guardrail_hooks/alice/alice.py
 create mode 100644 litellm/types/proxy/guardrails/guardrail_hooks/alice.py
 create mode 100644 tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
 create mode 100644 ui/litellm-dashboard/public/assets/logos/alice.svg

diff --git a/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py
new file mode 100644
index 00000000000..75ea16f7a88
--- /dev/null
+++ b/litellm/proxy/guardrails/guardrail_hooks/alice/__init__.py
@@ -0,0 +1,34 @@
+from typing import TYPE_CHECKING, Final
+
+from litellm.types.guardrails import SupportedGuardrailIntegrations
+
+from .alice import AliceGuardrail
+
+if TYPE_CHECKING:
+    from litellm.types.guardrails import Guardrail, LitellmParams
+
+
+def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail"):
+    import litellm
+
+    _alice_guardrail_callback: Final = AliceGuardrail(
+        api_key=litellm_params.api_key,
+        api_base=litellm_params.api_base,
+        unreachable_fallback=getattr(litellm_params, "unreachable_fallback", "fail_closed"),
+        guardrail_name=guardrail.get("guardrail_name", ""),
+        event_hook=litellm_params.mode,
+        default_on=litellm_params.default_on,
+    )
+
+    litellm.logging_callback_manager.add_litellm_callback(_alice_guardrail_callback)
+    return _alice_guardrail_callback
+
+
+guardrail_initializer_registry: Final = {  # mutable-ok: module-level registry, built once and never mutated
+    SupportedGuardrailIntegrations.ALICE.value: initialize_guardrail,
+}
+
+
+guardrail_class_registry: Final = {  # mutable-ok: module-level registry, built once and never mutated
+    SupportedGuardrailIntegrations.ALICE.value: AliceGuardrail,
+}
diff --git a/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py b/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py
new file mode 100644
index 00000000000..27018769909
--- /dev/null
+++ b/litellm/proxy/guardrails/guardrail_hooks/alice/alice.py
@@ -0,0 +1,369 @@
+# +-------------------------------------------------------------+
+#
+#                    Use Alice for your LLM calls
+#                         https://alice.io/
+#
+# +-------------------------------------------------------------+
+
+import json
+import os
+from collections.abc import Mapping
+from typing import (
+    TYPE_CHECKING,
+    Any,  # noqa: TID251  # **kwargs forwards verbatim to CustomGuardrail.__init__; see ruff-strict.toml
+    Final,
+    Literal,
+    Optional,
+)
+
+import httpx
+from typing_extensions import NotRequired, ReadOnly, TypedDict
+
+from litellm._logging import verbose_proxy_logger
+from litellm.exceptions import GuardrailRaisedException, Timeout
+from litellm.integrations.custom_guardrail import (
+    CustomGuardrail,
+    log_guardrail_information,
+)
+from litellm.llms.custom_httpx.http_handler import (
+    get_async_httpx_client,
+    httpxSpecialProvider,
+)
+from litellm.types.guardrails import GuardrailEventHooks
+from litellm.types.utils import GenericGuardrailAPIInputs
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+GUARDRAIL_NAME: Final = "alice"
+
+_DEFAULT_API_BASE: Final = "https://api.alice.io"
+_EVALUATE_PATH: Final = "/v2/evaluate/litellm"
+
+_VERDICT_ALLOW: Final = "ALLOW"
+_VERDICT_BLOCK: Final = "BLOCK"
+_VERDICT_MASK: Final = "MASK"
+_VERDICT_DETECT: Final = "DETECT"
+_KNOWN_VERDICTS: Final = frozenset({_VERDICT_ALLOW, _VERDICT_BLOCK, _VERDICT_MASK, _VERDICT_DETECT})
+
+_DEFAULT_BLOCK_MESSAGE: Final = "Blocked by your organization's content policy."
+
+# apply_guardrail selects nothing: it forwards whichever of these came populated and lets Alice
+# decide what is worth evaluating. Only skip the call when every one of them is empty — there is
+# then genuinely nothing to send.
+_SELECTABLE_INPUT_FIELDS: Final = ("texts", "images", "tools", "tool_calls", "structured_messages")
+
+# Caps on the outbound copy of request_data. A payload deeper or wider than this is malformed
+# rather than large, and serializing it would cost more than the evaluation it feeds.
+_MAX_DEPTH: Final = 12
+_MAX_ITEMS: Final = 5000
+
+# request_data carries the caller's raw credentials under these keys, at any nesting depth —
+# a real captured payload puts inbound headers at request_data["proxy_server_request"]["headers"],
+# again under ["metadata"]["headers"] / ["litellm_metadata"]["headers"], and again under
+# ["metadata"]["requester_metadata"]["headers"], any of which can carry an Authorization or
+# x-api-key value. LiteLLM's own spend-log sanitizer excludes `secret_fields` for the same reason
+# (spend_tracking_utils._SENSITIVE_REQUEST_BODY_KEYS): `secret_fields.raw_headers` holds the
+# caller's Authorization / x-api-key in the clear, and `api_key` can carry a forwarded provider
+# credential. Stripping by key name rather than by path means a new nesting path can never
+# reintroduce the leak. Posting any of these to a third-party guardrail endpoint would be worse
+# than what the proxy already refuses to persist in its own audit trail — so none of them leave
+# the process.
+_CREDENTIAL_KEYS_TO_STRIP: Final = frozenset(
+    {"secret_fields", "api_key", "raw_headers", "headers", "provider_specific_header"}
+)
+
+
+class AliceReplacement(TypedDict):
+    """A masked substitution, positional against the texts that were submitted."""
+
+    index: ReadOnly[NotRequired[int]]
+    text: ReadOnly[NotRequired[str]]
+
+
+class AliceVerdict(TypedDict):
+    """Body returned by Alice's LiteLLM evaluate endpoint."""
+
+    verdict: ReadOnly[NotRequired[str]]
+    categories: ReadOnly[NotRequired["tuple[str, ...]"]]
+    correlation_id: ReadOnly[NotRequired[str]]
+    message: ReadOnly[NotRequired[str]]
+    replacements: ReadOnly[NotRequired["tuple[AliceReplacement, ...]"]]
+
+
+class AliceGuardrailMissingSecrets(Exception):
+    """Raised when the Alice API key is not configured."""
+
+
+class AliceGuardrail(CustomGuardrail):
+    """
+    Alice — policy-based guardrails for prompts and model responses.
+
+    This forwards the hook's arguments as it received them and enforces the verdict that comes
+    back, with one deliberate exception: any key named `secret_fields`, `api_key`, `raw_headers`,
+    `headers`, or `provider_specific_header` is dropped from `request_data` at any nesting depth
+    before it is serialized, and never reaches Alice. Short of that, it selects nothing and
+    renames nothing: which parts of a conversation are worth evaluating, and how a verdict is
+    reached, are decided by Alice — so changing either is a change on their side rather than a
+    LiteLLM upgrade. A batch with nothing selectable at all (no `texts`, `images`, `tools`,
+    `tool_calls`, or `structured_messages`) still skips the call, since there would be nothing to
+    send.
+
+    Known limitation: the unified guardrail's `streaming_transform_mode` defaults to
+    `block_only`, whose streaming path discards any returned text rewrite. A MASK verdict is
+    therefore a no-op on a streamed response — the original, unmasked text still reaches the
+    caller — while BLOCK continues to function on both streamed and non-streamed responses.
+    This is `during_call`'s documented behavior generally, not specific to Alice; configure a
+    masking-aware `streaming_transform_mode` if that gap matters for your traffic.
+
+    Alice evaluates against policies configured per *application*, and one proxy typically fronts
+    several, so the application is named on the virtual key rather than in this config:
+
+        curl $PROXY/key/generate -H "Authorization: Bearer $LITELLM_MASTER_KEY" \\
+          -d '{"key_alias": "payments-bot",
+               "metadata": {"alice_app_id": "payments-bot"}}'
+
+    Alice reads that off the authenticated key. Because the proxy strips caller-supplied
+    `user_api_key_*` from the request before a guardrail sees it, a caller cannot point its own
+    traffic at an application with laxer policies than the one its key was issued for.
+
+    Configuration example (litellm config YAML):
+        guardrails:
+          - guardrail_name: alice
+            litellm_params:
+              guardrail: alice
+              mode: [pre_call, post_call]
+              api_key: os.environ/ALICE_API_KEY
+              api_base: https://api.alice.io          # optional
+              unreachable_fallback: fail_closed       # optional
+    """
+
+    def __init__(
+        self,
+        api_key: str | None = None,
+        api_base: str | None = None,
+        unreachable_fallback: Literal["fail_closed", "fail_open"] = "fail_closed",
+        **kwargs: Any,  # kwargs-ok: forwarded verbatim to CustomGuardrail.__init__, whose param list is wide and evolving
+    ) -> None:
+        self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback)
+
+        alice_api_key: Final = api_key or os.environ.get("ALICE_API_KEY")
+        if not alice_api_key:
+            raise AliceGuardrailMissingSecrets(
+                "Alice API key is required. Set the `ALICE_API_KEY` environment variable or "
+                "pass `api_key` in the guardrail config."
+            )
+        self.alice_api_key: str = alice_api_key
+
+        base: Final = (api_base or os.environ.get("ALICE_API_BASE") or _DEFAULT_API_BASE).rstrip("/")
+        self.api_base: str = f"{base}{_EVALUATE_PATH}"
+        self.unreachable_fallback: Literal["fail_closed", "fail_open"] = unreachable_fallback
+
+        if "supported_event_hooks" not in kwargs:
+            kwargs["supported_event_hooks"] = [  # mutable-ok: CustomGuardrail.__init__ requires a list here
+                GuardrailEventHooks.pre_call,
+                GuardrailEventHooks.during_call,
+                GuardrailEventHooks.post_call,
+            ]
+
+        super().__init__(**kwargs)
+
+    @log_guardrail_information
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict[str, object],  # mutable-ok: overrides CustomGuardrail.apply_guardrail's plain-dict contract
+        input_type: Literal["request", "response"],
+        logging_obj: Optional["LiteLLMLoggingObj"] = None,
+    ) -> GenericGuardrailAPIInputs:
+        if not any(inputs.get(field) for field in _SELECTABLE_INPUT_FIELDS):
+            return inputs
+
+        try:
+            verdict: AliceVerdict = await self._evaluate(
+                inputs=inputs, request_data=request_data, input_type=input_type
+            )
+        except Timeout as e:
+            return self._on_unreachable(e, inputs)
+        except httpx.HTTPStatusError as e:
+            status_code: Final = getattr(getattr(e, "response", None), "status_code", None)
+            # Any 5xx is an outage on Alice's side, not our misconfiguration — route the whole
+            # class through the configured policy. A 4xx (rejected credential, bad request) is
+            # ours to fix and must never fail open, so it is deliberately left to propagate.
+            if isinstance(status_code, int) and 500 <= status_code < 600:
+                return self._on_unreachable(e, inputs)
+            raise
+        except httpx.RequestError as e:
+            return self._on_unreachable(e, inputs)
+        except (json.JSONDecodeError, UnicodeDecodeError, TypeError) as e:
+            # A body that cannot be decoded, cannot be parsed as JSON, or parses to something
+            # other than an object, is as unreachable as a dropped connection: this deployment's
+            # policy decides, not a raw exception. UnicodeDecodeError is named explicitly because
+            # it is a sibling of JSONDecodeError under ValueError, not a subclass of it.
+            return self._on_unreachable(e, inputs)
+
+        return self._enforce(verdict, inputs)
+
+    async def _evaluate(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: Mapping[str, object],
+        input_type: str,
+    ) -> AliceVerdict:
+        response: Final = await self.async_handler.post(
+            url=self.api_base,
+            json={  # mutable-ok: one-shot HTTP request body, never mutated after construction
+                "input_type": input_type,
+                "inputs": _json_safe(inputs),
+                "request_data": _json_safe(request_data, strip_keys=_CREDENTIAL_KEYS_TO_STRIP),
+            },
+            headers={  # mutable-ok: one-shot HTTP headers, never mutated after construction
+                "Content-Type": "application/json",
+                "af-api-key": self.alice_api_key,
+            },
+        )
+        response.raise_for_status()
+        body = response.json()
+        if not isinstance(body, dict):
+            raise TypeError("Alice returned a non-object body")
+        return body
+
+    def _enforce(self, verdict: AliceVerdict, inputs: GenericGuardrailAPIInputs) -> GenericGuardrailAPIInputs:
+        """Act on the verdict. An answer we cannot read is treated as unavailable, never as a pass."""
+        name: Final = verdict.get("verdict")
+        if name not in _KNOWN_VERDICTS:
+            return self._on_unreachable(ValueError(f"unrecognized verdict: {name!r}"), inputs)
+
+        if name == _VERDICT_BLOCK:
+            raise GuardrailRaisedException(
+                guardrail_name=GUARDRAIL_NAME,
+                message=verdict.get("message") or _DEFAULT_BLOCK_MESSAGE,
+                should_wrap_with_default_message=False,
+                blocked_content=True,
+            )
+
+        if name == _VERDICT_DETECT:
+            # Recorded by Alice and allowed through. The correlation id is what ties this request
+            # to that record; the evaluated text itself is never logged.
+            verbose_proxy_logger.warning(
+                "Alice guardrail: detection recorded, request allowed (correlation_id=%s, categories=%s)",
+                verdict.get("correlation_id"),
+                verdict.get("categories"),
+            )
+            return inputs
+
+        if name == _VERDICT_MASK:
+            self._apply_replacements(verdict, inputs)
+
+        return inputs
+
+    def _apply_replacements(self, verdict: AliceVerdict, inputs: GenericGuardrailAPIInputs) -> None:
+        """
+        Write each replacement onto the text it names.
+
+        Only `texts` is touched. The chat translation layer maps a returned `texts` list back onto
+        the request positionally, but takes a different branch entirely when `structured_messages`
+        comes back as a new object — which would drop these edits.
+
+        All-or-nothing: a single out-of-range or malformed replacement blocks the whole verdict
+        rather than being silently skipped, so content Alice meant to replace can never reach the
+        model unmasked alongside content that was replaced.
+        """
+        texts: Final = inputs.get("texts") or []  # mutable-ok: empty-list fallback, replaced wholesale below
+        replacements: Final = verdict.get("replacements") or []  # mutable-ok: empty-list fallback for iteration only
+
+        if not replacements:
+            raise self._mask_rejected(verdict)
+
+        for replacement in replacements:
+            index = replacement.get("index")
+            text = replacement.get("text")
+            if not (isinstance(index, int) and isinstance(text, str) and 0 <= index < len(texts)):
+                raise self._mask_rejected(verdict)
+            texts[index] = text  # mutable-ok: item assignment into the local working copy above
+
+        inputs["texts"] = texts
+
+    def _mask_rejected(self, verdict: AliceVerdict) -> GuardrailRaisedException:
+        """A MASK verdict that cannot be applied in full is refused outright, never partially —
+        see `_apply_replacements`."""
+        return GuardrailRaisedException(
+            guardrail_name=GUARDRAIL_NAME,
+            message=verdict.get("message") or _DEFAULT_BLOCK_MESSAGE,
+            should_wrap_with_default_message=False,
+            blocked_content=True,
+        )
+
+    def _on_unreachable(self, error: Exception, inputs: GenericGuardrailAPIInputs) -> GenericGuardrailAPIInputs:
+        """Apply the configured policy when Alice cannot be reached or cannot be understood."""
+        if self.unreachable_fallback == "fail_open":
+            verbose_proxy_logger.critical(
+                "Alice guardrail unreachable, allowing request per unreachable_fallback: %s",
+                error,
+            )
+            return inputs
+        raise GuardrailRaisedException(
+            guardrail_name=GUARDRAIL_NAME,
+            message="Alice guardrail is unavailable and this request cannot be checked",
+            should_wrap_with_default_message=False,
+        ) from error
+
+    @staticmethod
+    def get_config_model() -> type | None:
+        from litellm.types.proxy.guardrails.guardrail_hooks.alice import (
+            AliceGuardrailConfigModel,
+        )
+
+        return AliceGuardrailConfigModel
+
+
+def _json_safe(
+    value: object,
+    depth: int = 0,
+    seen: frozenset[int] = frozenset(),
+    strip_keys: frozenset[str] = frozenset(),
+) -> object:
+    """
+    Copy `value` into something `json.dumps` accepts, dropping only what cannot cross.
+
+    `request_data` carries live Python objects — an OpenTelemetry span among them — so it cannot
+    be serialized as it stands. What is dropped is decided by a mechanical rule rather than a
+    field list: a list drifts from what the far side needs, a rule cannot. Serializing naively
+    raises, and that error would be read as "guardrail unavailable" on every single request.
+
+    `strip_keys` drops a dict key by name at every depth it appears, not just the root — a caller
+    passes `_CREDENTIAL_KEYS_TO_STRIP` here so a credential nested under any path is caught the
+    same way a top-level one is, without maintaining a list of paths. The source object is never
+    mutated: every branch below builds a new container.
+    """
+    if isinstance(value, (str, int, float, bool)) or value is None:
+        return value
+    if depth >= _MAX_DEPTH or id(value) in seen:
+        return None
+
+    nested: Final = seen | {id(value)}  # mutable-ok: one-shot set literal, unioned into a frozenset immediately
+
+    if isinstance(value, dict):
+        out: dict[str, object] = {}  # mutable-ok: bounded accumulator local to this call, never escapes as-is
+        for key, item in list(value.items())[:_MAX_ITEMS]:  # mutable-ok: list() only to slice an unordered view
+            if isinstance(key, str) and key not in strip_keys:
+                out[key] = _json_safe(item, depth + 1, nested, strip_keys)
+        return out
+
+    if isinstance(value, (list, tuple, set, frozenset)):
+        return [  # mutable-ok: return value is a one-shot list, discarded by the caller after use
+            _json_safe(item, depth + 1, nested, strip_keys)
+            for item in list(value)[:_MAX_ITEMS]  # mutable-ok: list() only to slice an unordered view
+        ]
+
+    dump: Final = getattr(value, "model_dump", None)
+    if callable(dump):
+        try:
+            return _json_safe(dump(mode="json"), depth + 1, nested, strip_keys)
+        except Exception:  # noqa: BLE001  # a model that will not dump is one we drop
+            return None
+
+    # Everything json.dumps handles natively — str, int, float, bool, None, dict, list — is
+    # caught above, and a dict/list subclass is caught by isinstance. So whatever reaches here
+    # (bytes, datetime, an OpenTelemetry span) cannot cross the wire.
+    return None
diff --git a/litellm/types/guardrails.py b/litellm/types/guardrails.py
index 4cf4fa62eff..c17103da890 100644
--- a/litellm/types/guardrails.py
+++ b/litellm/types/guardrails.py
@@ -136,6 +136,7 @@ class SupportedGuardrailIntegrations(Enum):
     HEADROOM = "headroom"
     COMPRESR = "compresr"
     STRAIKER = "straiker"
+    ALICE = "alice"
 
 
 class Role(Enum):
diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/alice.py b/litellm/types/proxy/guardrails/guardrail_hooks/alice.py
new file mode 100644
index 00000000000..73d31673dab
--- /dev/null
+++ b/litellm/types/proxy/guardrails/guardrail_hooks/alice.py
@@ -0,0 +1,21 @@
+from pydantic import Field
+
+from .base import GuardrailConfigModel
+
+
+class AliceGuardrailConfigModel(GuardrailConfigModel):
+    api_key: str | None = Field(
+        default=None,
+        description=("The API key for Alice. If not provided, the `ALICE_API_KEY` environment variable is checked."),
+    )
+    api_base: str | None = Field(
+        default=None,
+        description=(
+            "The API base URL for Alice. If not provided, the `ALICE_API_BASE` environment "
+            "variable is checked, then `https://api.alice.io`."
+        ),
+    )
+
+    @staticmethod
+    def ui_friendly_name() -> str:
+        return "Alice"
diff --git a/ruff-strict.toml b/ruff-strict.toml
index 7afc5da71ee..ae092bdde7d 100644
--- a/ruff-strict.toml
+++ b/ruff-strict.toml
@@ -26,6 +26,10 @@ external = [
 # caught a real mismatch, confirming Any is correct here, not a shortcut.
 "litellm/litellm_core_utils/litellm_logging.py" = ["ANN401"]
 "litellm/utils.py" = ["ANN401"]
+# `**kwargs` forwards verbatim to CustomGuardrail.__init__, whose param list is wide and
+# grows over time; typing it concretely (`object`) broke that forwarding call outright —
+# basedpyright turned every named param into a reportArgumentType error. Any is correct here.
+"litellm/proxy/guardrails/guardrail_hooks/alice/alice.py" = ["ANN401"]
 
 [lint.mccabe]
 max-complexity = 15
diff --git a/tests/code_coverage_tests/recursive_detector.py b/tests/code_coverage_tests/recursive_detector.py
index 37e940460f6..790956156b0 100644
--- a/tests/code_coverage_tests/recursive_detector.py
+++ b/tests/code_coverage_tests/recursive_detector.py
@@ -63,6 +63,7 @@ IGNORE_FUNCTIONS = [
     "json_unrewritable_labels",  # max depth set (MAX_STRUCTURED_CONTENT_SCAN_DEPTH); returns the None sentinel at the cap so the caller blocks.
     "_flatten_form_field",  # bounded by the nesting depth of the already-parsed request body (a finite JSON tree, no cycles possible).
     "_flatten_form_data_field",  # bounded by the nesting depth of the already-parsed request body (a finite JSON tree, no cycles possible).
+    "_json_safe",  # max depth set (_MAX_DEPTH) plus a seen-ids cycle guard for self-referential input.
 ]
 
 
diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
new file mode 100644
index 00000000000..fd2e86ccde8
--- /dev/null
+++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_alice.py
@@ -0,0 +1,614 @@
+import json
+import os
+from copy import deepcopy
+from unittest.mock import AsyncMock
+
+import httpx
+import pytest
+from httpx import Request, Response
+
+import litellm
+from litellm.exceptions import GuardrailRaisedException
+from litellm.proxy.guardrails.guardrail_hooks.alice.alice import (
+    GUARDRAIL_NAME,
+    AliceGuardrail,
+    AliceGuardrailMissingSecrets,
+    _json_safe,
+)
+from litellm.proxy.guardrails.init_guardrails import init_guardrails_v2
+
+
+def _guardrail(**overrides: object) -> AliceGuardrail:
+    params: dict[str, object] = {"api_key": "test-key", "guardrail_name": "alice", "event_hook": "pre_call"}
+    params.update(overrides)
+    return AliceGuardrail(**params)
+
+
+def _verdict(payload: dict[str, object], status_code: int = 200) -> Response:
+    return Response(
+        status_code=status_code,
+        json=payload,
+        request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+    )
+
+
+def test_alice_guardrail_config(monkeypatch: pytest.MonkeyPatch):
+    """Should register through init_guardrails_v2 like any other provider."""
+    monkeypatch.setattr(litellm, "guardrail_name_config_map", {})
+    monkeypatch.setenv("ALICE_API_KEY", "test-key")
+
+    init_guardrails_v2(
+        all_guardrails=[
+            {
+                "guardrail_name": "alice",
+                "litellm_params": {"guardrail": "alice", "mode": "pre_call", "default_on": True},
+            }
+        ],
+        config_file_path="",
+    )
+
+    registered = [cb for cb in litellm.callbacks if isinstance(cb, AliceGuardrail)]
+    assert len(registered) == 1
+    assert registered[0].guardrail_name == "alice"
+
+
+class TestAliceGuardrailInitialization:
+    def setup_method(self):
+        for key in ("ALICE_API_KEY", "ALICE_API_BASE"):
+            os.environ.pop(key, None)
+
+    def test_missing_api_key_raises(self):
+        with pytest.raises(AliceGuardrailMissingSecrets, match="API key"):
+            AliceGuardrail(guardrail_name="alice", event_hook="pre_call")
+
+    def test_reads_credentials_from_environment(self, monkeypatch: pytest.MonkeyPatch):
+        monkeypatch.setenv("ALICE_API_KEY", "env-key")
+        monkeypatch.setenv("ALICE_API_BASE", "https://env.alice.test")
+
+        guardrail = AliceGuardrail(guardrail_name="alice", event_hook="pre_call")
+
+        assert guardrail.alice_api_key == "env-key"
+        assert guardrail.api_base == "https://env.alice.test/v2/evaluate/litellm"
+
+    def test_defaults_the_api_base(self):
+        assert _guardrail().api_base == "https://api.alice.io/v2/evaluate/litellm"
+
+    def test_trailing_slash_does_not_double_up(self):
+        assert _guardrail(api_base="https://api.alice.io/").api_base == ("https://api.alice.io/v2/evaluate/litellm")
+
+
+class TestAliceForwarding:
+    """The hook's arguments cross the wire as they were received — nothing selected, nothing
+    renamed — except the caller's raw credentials, which are stripped before request_data is
+    serialized (see TestAliceCredentialStripping)."""
+
+    @pytest.mark.asyncio
+    async def test_forwards_the_hook_arguments_verbatim(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        inputs = {"texts": ["hello"], "structured_messages": [{"role": "user", "content": "hello"}]}
+        request_data = {"model": "gpt-4o", "metadata": {"user_api_key_alias": "payments-bot"}}
+        # Snapshot before the call: @log_guardrail_information writes its own entry into
+        # request_data["metadata"] afterwards, so the original is no longer what was sent.
+        sent_inputs = deepcopy(inputs)
+        sent_request_data = deepcopy(request_data)
+
+        await guardrail.apply_guardrail(inputs=inputs, request_data=request_data, input_type="request")
+
+        body = guardrail.async_handler.post.call_args.kwargs["json"]
+        assert body["input_type"] == "request"
+        assert body["inputs"] == sent_inputs
+        assert body["request_data"] == sent_request_data
+
+    @pytest.mark.asyncio
+    async def test_sends_the_credential(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data={}, input_type="request")
+
+        assert guardrail.async_handler.post.call_args.kwargs["headers"]["af-api-key"] == "test-key"
+
+    @pytest.mark.asyncio
+    async def test_marks_a_completion_as_a_response(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["answer"]}, request_data={}, input_type="response")
+
+        assert guardrail.async_handler.post.call_args.kwargs["json"]["input_type"] == "response"
+
+    @pytest.mark.asyncio
+    async def test_nothing_selectable_reaches_no_evaluation(self):
+        """No texts, images, tools, tool_calls, or structured_messages: genuinely nothing to send."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock()
+
+        result = await guardrail.apply_guardrail(inputs={"texts": []}, request_data={}, input_type="request")
+
+        assert result == {"texts": []}
+        guardrail.async_handler.post.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_tool_calls_only_still_reaches_alice(self):
+        """A batch with empty texts but populated tool_calls is still a selection decision Alice
+        should make, not the plugin — see the class docstring."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        inputs = {"texts": [], "tool_calls": [{"id": "call_1", "function": {"name": "get_weather"}}]}
+
+        await guardrail.apply_guardrail(inputs=inputs, request_data={}, input_type="request")
+
+        guardrail.async_handler.post.assert_called_once()
+        assert guardrail.async_handler.post.call_args.kwargs["json"]["inputs"]["tool_calls"] == inputs["tool_calls"]
+
+    @pytest.mark.asyncio
+    async def test_images_only_still_reaches_alice(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(
+            inputs={"texts": [], "images": ["data:image/png;base64,abc"]}, request_data={}, input_type="request"
+        )
+
+        guardrail.async_handler.post.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_structured_messages_only_still_reaches_alice(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        await guardrail.apply_guardrail(
+            inputs={"texts": [], "structured_messages": [{"role": "user", "content": []}]},
+            request_data={},
+            input_type="request",
+        )
+
+        guardrail.async_handler.post.assert_called_once()
+
+    @pytest.mark.asyncio
+    async def test_makes_exactly_one_attempt(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(side_effect=httpx.ConnectError("refused"))
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data={}, input_type="request")
+
+        assert guardrail.async_handler.post.call_count == 1
+
+
+class TestAliceCredentialStripping:
+    """request_data's raw-credential keys never leave the process."""
+
+    @pytest.mark.asyncio
+    async def test_secret_fields_and_api_key_are_stripped(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {
+            "model": "gpt-4o",
+            "api_key": "sk-forwarded-provider-secret",
+            "secret_fields": {"raw_headers": {"authorization": "Bearer caller-virtual-key"}},
+            "metadata": {"user_api_key_alias": "payments-bot"},
+        }
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        sent_request_data = guardrail.async_handler.post.call_args.kwargs["json"]["request_data"]
+        assert "secret_fields" not in sent_request_data
+        assert "api_key" not in sent_request_data
+        assert sent_request_data == {"model": "gpt-4o", "metadata": {"user_api_key_alias": "payments-bot"}}
+
+    @pytest.mark.asyncio
+    async def test_nested_credentials_are_stripped_at_every_depth(self):
+        """Shaped after a real captured Claude Code payload: the caller's Authorization/x-api-key
+        lives under several independent nesting paths, none of which are the root."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {
+            "model": "claude-3-5-sonnet",
+            "secret_fields": {"raw_headers": {"authorization": "Bearer caller-virtual-key"}},
+            "provider_specific_header": {"extra_headers": {"authorization": "sk-ant-oat01-nested-oauth"}},
+            "proxy_server_request": {
+                "url": "/v1/messages",
+                "headers": {"authorization": "Bearer inbound-caller-secret", "x-request-id": "req-1"},
+                "body": {
+                    "model": "claude-3-5-sonnet",
+                    "metadata": {"headers": {"authorization": "Bearer body-metadata-secret"}},
+                },
+            },
+            "metadata": {
+                "user_api_key_alias": "payments-bot",
+                "headers": {"authorization": "Bearer metadata-secret"},
+                "requester_metadata": {"headers": {"authorization": "Bearer requester-metadata-secret"}},
+            },
+            "litellm_metadata": {"headers": {"authorization": "Bearer litellm-metadata-secret"}},
+        }
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        posted_body = guardrail.async_handler.post.call_args.kwargs["json"]
+        serialized = json.dumps(posted_body)
+        assert "authorization" not in serialized.lower()
+        assert "caller-virtual-key" not in serialized
+        assert "nested-oauth" not in serialized
+        assert "inbound-caller-secret" not in serialized
+        assert "body-metadata-secret" not in serialized
+        assert "metadata-secret" not in serialized
+        assert "requester-metadata-secret" not in serialized
+        assert "litellm-metadata-secret" not in serialized
+
+        sent_request_data = posted_body["request_data"]
+        assert sent_request_data["model"] == "claude-3-5-sonnet"
+        assert sent_request_data["proxy_server_request"]["url"] == "/v1/messages"
+        assert "headers" not in sent_request_data["proxy_server_request"]
+        assert sent_request_data["proxy_server_request"]["body"]["model"] == "claude-3-5-sonnet"
+        assert "headers" not in sent_request_data["proxy_server_request"]["body"]["metadata"]
+        assert sent_request_data["metadata"]["user_api_key_alias"] == "payments-bot"
+        assert "headers" not in sent_request_data["metadata"]
+        assert "requester_metadata" in sent_request_data["metadata"]
+        assert "headers" not in sent_request_data["metadata"]["requester_metadata"]
+        assert "headers" not in sent_request_data["litellm_metadata"]
+        assert "secret_fields" not in sent_request_data
+        assert "provider_specific_header" not in sent_request_data
+
+    @pytest.mark.asyncio
+    async def test_the_original_request_data_is_not_mutated(self):
+        """Stripping must only affect the outbound copy — api_key still has to reach the
+        provider, and secret_fields still has to reach the rest of the request pipeline."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+        request_data = {"api_key": "sk-forwarded-provider-secret", "secret_fields": {"raw_headers": {}}}
+
+        await guardrail.apply_guardrail(inputs={"texts": ["hi"]}, request_data=request_data, input_type="request")
+
+        assert request_data["api_key"] == "sk-forwarded-provider-secret"
+        assert request_data["secret_fields"] == {"raw_headers": {}}
+
+
+class TestAliceVerdicts:
+    @pytest.mark.asyncio
+    async def test_allow_leaves_the_inputs_untouched(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "ALLOW", "categories": []}))
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_block_surfaces_the_policy_message(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "BLOCK",
+                    "categories": ["self_harm"],
+                    "correlation_id": "c1",
+                    "message": "Blocked by your organization's policy",
+                }
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException) as error:
+            await guardrail.apply_guardrail(inputs={"texts": ["bad"]}, request_data={}, input_type="request")
+
+        assert "Blocked by your organization's policy" in str(error.value)
+
+    @pytest.mark.asyncio
+    async def test_block_without_a_message_still_blocks(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "BLOCK", "categories": []}))
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["bad"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_substitutes_by_position(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "MASK",
+                    "categories": ["pii"],
+                    "replacements": [{"index": 1, "text": "my ssn is ***"}],
+                }
+            )
+        )
+
+        result = await guardrail.apply_guardrail(
+            inputs={"texts": ["untouched", "my ssn is 123-45-6789"]},
+            request_data={},
+            input_type="request",
+        )
+
+        assert result["texts"] == ["untouched", "my ssn is ***"]
+
+    @pytest.mark.asyncio
+    async def test_mask_that_lands_nowhere_blocks(self):
+        """A mask that wrote nothing would let the text through under a verdict that said not to."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "MASK", "categories": [], "replacements": [{"index": 9, "text": "***"}]})
+        )
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_with_no_replacements_blocks(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(return_value=_verdict({"verdict": "MASK", "categories": []}))
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_mask_with_one_invalid_replacement_blocks_entirely(self):
+        """A mixed valid/invalid replacement list must not let the valid half through: that
+        would leave the content named by the invalid entry unmasked while looking like success."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict(
+                {
+                    "verdict": "MASK",
+                    "categories": ["pii"],
+                    "replacements": [{"index": 0, "text": "***"}, {"index": 9, "text": "***"}],
+                }
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException):
+            await guardrail.apply_guardrail(
+                inputs={"texts": ["my ssn is 123-45-6789"]}, request_data={}, input_type="request"
+            )
+
+    @pytest.mark.asyncio
+    async def test_mask_leaves_structured_messages_identical(self):
+        """A new structured_messages object makes the translation layer skip the texts write-back."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "MASK", "categories": [], "replacements": [{"index": 0, "text": "***"}]})
+        )
+        messages = [{"role": "user", "content": "secret"}]
+
+        result = await guardrail.apply_guardrail(
+            inputs={"texts": ["secret"], "structured_messages": messages},
+            request_data={},
+            input_type="request",
+        )
+
+        assert result["structured_messages"] is messages
+
+    @pytest.mark.asyncio
+    async def test_detect_allows_and_leaves_the_text_alone(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=_verdict({"verdict": "DETECT", "categories": ["profanity"], "correlation_id": "c1"})
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["mild"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["mild"]
+
+
+class TestAliceUnreachable:
+    @pytest.mark.parametrize(
+        "failure",
+        [
+            pytest.param({"side_effect": httpx.ConnectError("refused")}, id="connect-error"),
+            pytest.param({"return_value": _verdict({"verdict": "MAYBE"})}, id="unrecognized-verdict"),
+            pytest.param({"return_value": _verdict({})}, id="no-verdict"),
+        ],
+    )
+    @pytest.mark.asyncio
+    async def test_fails_closed_by_default(self, failure: dict):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(**failure)
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(side_effect=httpx.ConnectError("refused"))
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+
+class TestAliceTransportFailures:
+    """Every path out of the HTTP call, since each decides whether traffic flows unscreened."""
+
+    @pytest.mark.asyncio
+    async def test_a_timeout_is_unreachable(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=litellm.exceptions.Timeout(message="slow", model="gpt-4o", llm_provider="openai")
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.parametrize("status", [500, 502, 503, 504])
+    @pytest.mark.asyncio
+    async def test_upstream_5xx_is_unreachable(self, status: int):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "server error",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=status),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_a_500_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "server error",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=500),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_4xx_is_not_treated_as_unreachable(self):
+        """A rejected credential is our misconfiguration, not an outage — it must not fail open."""
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            side_effect=httpx.HTTPStatusError(
+                "unauthorized",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+                response=_verdict({}, status_code=401),
+            )
+        )
+
+        with pytest.raises(httpx.HTTPStatusError):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_non_object_body_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                json=["not", "an", "object"],
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_a_non_object_body_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                json=["not", "an", "object"],
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_malformed_json_fails_closed_by_default(self):
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"not json",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_malformed_json_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"not json",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+    @pytest.mark.asyncio
+    async def test_an_undecodable_body_fails_closed_by_default(self):
+        """UnicodeDecodeError is a sibling of JSONDecodeError under ValueError, not a subclass."""
+        guardrail = _guardrail()
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"\xff\xfe not utf-8",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        with pytest.raises(GuardrailRaisedException, match="unavailable"):
+            await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+    @pytest.mark.asyncio
+    async def test_an_undecodable_body_fails_open_when_configured(self):
+        guardrail = _guardrail(unreachable_fallback="fail_open")
+        guardrail.async_handler.post = AsyncMock(
+            return_value=Response(
+                status_code=200,
+                content=b"\xff\xfe not utf-8",
+                request=Request("POST", "https://api.alice.io/v2/evaluate/litellm"),
+            )
+        )
+
+        result = await guardrail.apply_guardrail(inputs={"texts": ["hello"]}, request_data={}, input_type="request")
+
+        assert result["texts"] == ["hello"]
+
+
+class TestAliceSerialization:
+    """`request_data` carries live objects, so it cannot be posted as it stands."""
+
+    def test_drops_what_cannot_serialize_and_keeps_the_rest(self):
+        class Span:
+            pass
+
+        result = _json_safe({"model": "x", "metadata": {"span": Span(), "user": "u1"}, "n": 1})
+
+        assert result == {"model": "x", "metadata": {"span": None, "user": "u1"}, "n": 1}
+
+    def test_survives_a_cycle(self):
+        data: dict = {"a": 1}
+        data["self"] = data
+
+        assert _json_safe(data) == {"a": 1, "self": None}
+
+    def test_drops_a_model_that_will_not_dump(self):
+        class Stubborn:
+            def model_dump(self, mode: str = "python") -> dict:
+                raise RuntimeError("cannot serialise")
+
+        assert _json_safe({"m": Stubborn()}) == {"m": None}
+
+    def test_drops_a_bare_unserialisable_value(self):
+        class Span:
+            pass
+
+        assert _json_safe(Span()) is None
+
+    def test_dumps_pydantic_models(self):
+        from pydantic import BaseModel
+
+        class Model(BaseModel):
+            name: str
+
+        assert _json_safe({"m": Model(name="x")}) == {"m": {"name": "x"}}
+
+
+def test_config_model_is_exposed_for_the_ui():
+    config_model = AliceGuardrail.get_config_model()
+
+    assert config_model is not None
+    assert config_model.ui_friendly_name() == "Alice"
+
+
+def test_guardrail_name_constant():
+    assert GUARDRAIL_NAME == "alice"
diff --git a/ui/litellm-dashboard/public/assets/logos/alice.svg b/ui/litellm-dashboard/public/assets/logos/alice.svg
new file mode 100644
index 00000000000..f18f887b98c
--- /dev/null
+++ b/ui/litellm-dashboard/public/assets/logos/alice.svg
@@ -0,0 +1,4 @@
+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<rect width="24" height="24" rx="8" fill="#E686B4"/>
+<path d="M12.0001 4C16.165 4.00002 19 7.1202 19 10.7146V19.1637C19 19.6256 18.6256 20 18.1637 20H16.9259C16.4641 20 16.0896 19.6256 16.0896 19.1637V11.3386C16.0896 9.31676 14.9356 6.74578 12.0001 6.74575C10.4696 6.74575 7.91038 7.76917 7.91038 11.3386V14.0344H13.801C14.2629 14.0344 14.6373 14.4088 14.6373 14.8707V15.9188C14.6373 16.3807 14.2629 16.7551 13.801 16.7551H7.91038V19.1637C7.91038 19.6256 7.53595 20 7.07406 20H5.83632C5.37443 20 5 19.6256 5 19.1637V10.7146C5 7.12018 7.83522 4 12.0001 4Z" fill="white"/>
+</svg>
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
index 03cfeed42ff..7785a8e44ab 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_configs.ts
@@ -312,4 +312,10 @@ export const GUARDRAIL_PRESETS: Record<string, GuardrailPreset> = {
     mode: "pre_call",
     defaultOn: false,
   },
+  alice: {
+    provider: "Alice",
+    guardrailNameSuggestion: "Alice",
+    mode: "pre_call",
+    defaultOn: false,
+  },
 };
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
index 13909e48185..1e486639840 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.test.ts
@@ -27,6 +27,7 @@ const EXPECTED_PARTNER_LOGO_FILES: Record<string, string> = {
   deepkeep: "deepkeep.svg",
   repelloai: "repelloai.png",
   straiker: "straiker.svg",
+  alice: "alice.svg",
 };
 
 describe("guardrail_garden_data logos", () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
index 744af89a357..931b3a111d8 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_data.ts
@@ -464,6 +464,16 @@ export const PARTNER_GUARDRAIL_CARDS: GuardrailCardInfo[] = [
     tags: ["Agentic", "Prompt Injection", "Tool Misuse", "MCP", "Skills"],
     providerKey: "Straiker",
   },
+  {
+    id: "alice",
+    name: "Alice",
+    description:
+      "Policy-based guardrails for prompts and model responses, evaluated per application so one proxy can enforce a different policy set per team or product.",
+    category: "partner",
+    logo: guardrailLogoMap["Alice"],
+    tags: ["Content Moderation", "Prompt Injection", "PII", "Policy"],
+    providerKey: "Alice",
+  },
 ];
 
 export const ALL_CARDS = [...LITELLM_CONTENT_FILTER_CARDS, ...PARTNER_GUARDRAIL_CARDS];
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
index 83038b8e0e7..c1f2ddcf51c 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_info_helpers.tsx
@@ -1,5 +1,6 @@
 import aimSecurityLogo from "../../../../../public/assets/logos/aim_security.jpeg";
 import aktoLogo from "../../../../../public/assets/logos/akto.svg";
+import aliceLogo from "../../../../../public/assets/logos/alice.svg";
 import aporiaLogo from "../../../../../public/assets/logos/aporia.png";
 import bedrockLogo from "../../../../../public/assets/logos/bedrock.svg";
 import catoNetworksLogo from "../../../../../public/assets/logos/cato_networks.svg";
@@ -83,6 +84,7 @@ export const guardrail_provider_map: Record<string, string> = {
   Deepkeep: "deepkeep",
   QostodianNexus: "qostodian_nexus",
   Repelloai: "repelloai",
+  Alice: "alice",
 };
 
 // Function to populate provider map from API response - updates the original map
@@ -204,6 +206,7 @@ export const guardrailLogoMap = {
   "Qostodian Nexus": qohashLogo.src,
   "RepelloAI Argus": repelloAiLogo.src,
   Straiker: straikerLogo.src,
+  Alice: aliceLogo.src,
 } satisfies Record<string, string>;
 
 export const getGuardrailLogo = (displayName: string): string | undefined =>

From 7809eacb8bb17773a223fb4774ccf313b7c1fe72 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:34:10 -0700
Subject: [PATCH 062/113] test(e2e/ui): cover the Logs page filter drawer
 (#39056)

The Logs page had coverage for opening a request and for the End User filter,
but nothing for the filters an on-call engineer actually reaches for: whose
key made the request, and which requests failed.

Each test mints its own keys and asserts on request ids it generated itself,
so a filter that quietly does nothing fails on the other key's row still being
on screen rather than passing because our own row happens to be there.

Co-authored-by: Claude <noreply@anthropic.com>
---
 tests/e2e/ui/tests/logs/logsFilters.spec.ts | 152 ++++++++++++++++++++
 1 file changed, 152 insertions(+)
 create mode 100644 tests/e2e/ui/tests/logs/logsFilters.spec.ts

diff --git a/tests/e2e/ui/tests/logs/logsFilters.spec.ts b/tests/e2e/ui/tests/logs/logsFilters.spec.ts
new file mode 100644
index 00000000000..7174f339296
--- /dev/null
+++ b/tests/e2e/ui/tests/logs/logsFilters.spec.ts
@@ -0,0 +1,152 @@
+import { test, expect, type APIRequestContext, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { Page } from "../../fixtures/pages";
+import {
+  CHAT_MODEL_A,
+  CHAT_MODEL_B,
+  createVirtualKey,
+  sendChatCompletion,
+  waitForSpendLog,
+} from "../../helpers/traffic";
+
+/**
+ * Every test mints its own key and asserts against request ids it generated, so a filter that
+ * quietly does nothing shows up as the other key's row still being on screen, and concurrent
+ * specs' traffic cannot decide the outcome.
+ */
+
+const uniqueSuffix = (): string => `${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
+
+/** Every tab stays mounted, so the DOM holds four tables at once; scope to the visible one. */
+const requestLogsRows = (page: PlaywrightPage): Locator =>
+  page.locator("table").filter({ visible: true }).first().locator("tbody tr");
+
+const visibleTestId = (page: PlaywrightPage, id: string): Locator => page.getByTestId(id).filter({ visible: true });
+
+async function openLogs(page: PlaywrightPage): Promise<void> {
+  await navigateToPage(page, Page.Logs);
+  await dismissFeedbackPopup(page);
+  await expect(visibleTestId(page, "datatable-search")).toBeVisible({ timeout: 20_000 });
+}
+
+async function openFilterDrawer(page: PlaywrightPage): Promise<Locator> {
+  await visibleTestId(page, "datatable-filters-trigger").click();
+  const drawer = page.getByRole("dialog", { name: "Filters" });
+  await expect(drawer).toBeVisible({ timeout: 10_000 });
+  return drawer;
+}
+
+/** Picks a value in one of the drawer's searchable comboboxes and applies the filter. */
+async function applyComboboxFilter(
+  page: PlaywrightPage,
+  drawer: Locator,
+  comboboxLabel: string,
+  value: string,
+): Promise<void> {
+  await drawer.getByRole("combobox", { name: comboboxLabel }).click();
+  await page.keyboard.type(value);
+  await page.getByRole("option", { name: value, exact: true }).first().click();
+  await drawer.getByRole("button", { name: "Apply Filters" }).click();
+  await expect(drawer).not.toBeVisible({ timeout: 10_000 });
+}
+
+/** A request the key is not entitled to make, so the proxy refuses it and logs the refusal. */
+async function sendDeniedCompletion(request: APIRequestContext, apiKey: string): Promise<void> {
+  const res = await request.post("/v1/chat/completions", {
+    headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
+    data: { model: CHAT_MODEL_B, messages: [{ role: "user", content: "denied" }] },
+  });
+  expect(res.status(), "a model outside the key's allow-list is refused").toBe(403);
+}
+
+test.describe("Logs page filters", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("the Key Alias filter narrows the table to that key's requests", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const mine = await createVirtualKey(request, { key_alias: `e2e-logs-mine-${suffix}` });
+    const theirs = await createVirtualKey(request, { key_alias: `e2e-logs-theirs-${suffix}` });
+
+    const myRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-mine-${suffix}`,
+      apiKey: mine.key,
+    });
+    const theirRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-theirs-${suffix}`,
+      apiKey: theirs.key,
+    });
+    await waitForSpendLog(request, myRequestId);
+    await waitForSpendLog(request, theirRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await applyComboboxFilter(page, drawer, "Search a key alias", mine.alias!);
+
+    await expect(requestLogsRows(page).filter({ hasText: myRequestId })).toHaveCount(1, { timeout: 30_000 });
+    // The filter is only doing its job if the other key's request is gone, not merely if ours is present.
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(0, { timeout: 10_000 });
+  });
+
+  test("the Status filter narrows the table to the refused request", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const alias = `e2e-logs-status-${suffix}`;
+    const scoped = await createVirtualKey(request, { key_alias: alias, models: [CHAT_MODEL_A] });
+
+    const servedRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-filter-served-${suffix}`,
+      apiKey: scoped.key,
+    });
+    await sendDeniedCompletion(request, scoped.key);
+    await waitForSpendLog(request, servedRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await drawer.getByRole("combobox", { name: "Search a key alias" }).click();
+    await page.keyboard.type(alias);
+    await page.getByRole("option", { name: alias, exact: true }).first().click();
+    // The Status field labels its group, not the trigger, so it is addressed by the value it shows.
+    await drawer.getByRole("combobox").filter({ hasText: "All Statuses" }).click();
+    await page.getByRole("option", { name: "Failure", exact: true }).click();
+    await drawer.getByRole("button", { name: "Apply Filters" }).click();
+    await expect(drawer).not.toBeVisible({ timeout: 10_000 });
+
+    // Both requests were made by this key, so a Status filter that does nothing leaves the served one on screen.
+    await expect(requestLogsRows(page)).toHaveCount(1, { timeout: 30_000 });
+    await expect(requestLogsRows(page)).toContainText("Failure");
+    await expect(requestLogsRows(page).filter({ hasText: servedRequestId })).toHaveCount(0);
+  });
+
+  test("Reset Filters brings back the rows a filter hid", async ({ page, request }) => {
+    const suffix = uniqueSuffix();
+    const mine = await createVirtualKey(request, { key_alias: `e2e-logs-reset-mine-${suffix}` });
+    const theirs = await createVirtualKey(request, { key_alias: `e2e-logs-reset-theirs-${suffix}` });
+
+    const myRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-reset-mine-${suffix}`,
+      apiKey: mine.key,
+    });
+    const theirRequestId = await sendChatCompletion(request, {
+      model: CHAT_MODEL_A,
+      prompt: `logs-reset-theirs-${suffix}`,
+      apiKey: theirs.key,
+    });
+    await waitForSpendLog(request, myRequestId);
+    await waitForSpendLog(request, theirRequestId);
+
+    await openLogs(page);
+    const drawer = await openFilterDrawer(page);
+    await applyComboboxFilter(page, drawer, "Search a key alias", mine.alias!);
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(0, { timeout: 30_000 });
+
+    // A filter you cannot clear is a page that looks empty forever, which is how it reads to a user.
+    await page.getByRole("button", { name: "Reset Filters" }).filter({ visible: true }).click();
+
+    await expect(requestLogsRows(page).filter({ hasText: theirRequestId })).toHaveCount(1, { timeout: 30_000 });
+    await expect(requestLogsRows(page).filter({ hasText: myRequestId })).toHaveCount(1, { timeout: 10_000 });
+  });
+});

From 978aa2816b666ba49a1323507c0c65ea92f412e2 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:34:57 -0700
Subject: [PATCH 063/113] test(e2e/ui): stop the suite failing on things that
 are not regressions (#39063)

* test(e2e/ui): stop the suite failing on things that are not regressions

Five tests in the UI suite fail for reasons that have nothing to do with the
product being broken, which is enough to keep the whole leg red.

Two need a premium proxy and fail hard without one: Regenerate Key renders
disabled when the proxy is unlicensed, and /model/new refuses a team-scoped
deployment. Both now skip without LITELLM_LICENSE, the way three other tests
in this suite already do.

Three consumed a seeded fixture: Delete key, Delete a team and remove a member
each destroyed the row they needed, so the retries CI runs with were guaranteed
to fail and the suite could not run twice against one database. They now create
what they destroy.

Top Virtual Keys ranks by spend and every mock deployment costs $0, so which
keys make the list came down to how ties happened to sort. It now sends its
traffic through a priced deployment and earns its place.

* test(e2e/ui): clean up the fixtures these tests create

Review caught two leaks: the priced deployment the usage test registers and
the user the team-admin test adds both outlived the run, so repeated runs
grew shared state that later routing and rosters can see.

Also brings in the paginated daily-activity read. /user/daily/activity pages
its per-key breakdown and the helper only read the first page, so the usage
test spent its full timeout blaming the rollup for a key the rollup wrote.

* test(e2e/ui): read the licence from the proxy, not the runner

Review pointed out that checking LITELLM_LICENSE in the runner's environment
describes the wrong machine: Playwright can be pointed at a proxy configured
somewhere else, and then the skip either hides coverage or runs a premium
test against an unlicensed target.

The admin session JWT already carries the premium_user claim the dashboard
itself reads to enable these controls, so both skips now use that.

* test(e2e/ui): clean up fixtures on the failure path too

Review caught both cleanups sitting at the end of the test body, where a
failing assertion skips them, and both discarding the response so a refused
delete passed quietly. They move to afterEach and assert the delete landed.

The priced deployment matters most: left behind it keeps its custom pricing
and goes on changing what later runs route and what they cost.

* test(e2e/ui): wait for the priced deployment to become routable

The Top Virtual Keys test registered a priced deployment and sent the key's
traffic through it on the next line, so on the deployed stack it failed with
"no healthy deployments for e2e-usage-priced-...": /model/new had written
the row but the router had not picked it up yet.

Polls a ping until the deployment answers before the test sends the request
it measures, matching what the addModel spec already does for a model added
through the UI. A ping that fails writes no spend log, so the retries cannot
move the ranking this test asserts.

* test(e2e/ui): register fixtures for cleanup before the step that can fail

Review found both helpers handing their id back to the caller to record, with
a failure-prone call in between: the priced deployment was registered after
the routability wait, and the added user after /team/member_add. Either
failing left the resource in the shared database with nothing tracking it.

Both now take the teardown list and add themselves as soon as the resource
exists, so the afterEach removes it however the rest of setup goes.

* test(e2e/ui): resolve the priced deployment for teardown by name

Review pointed out the remaining gap: /model/new can persist the deployment
and still answer non-2xx, and the id was only recorded after the response was
asserted, so that path left it behind with its custom pricing.

The name is now claimed before the request and teardown looks it up in
/model/info, so a create that saved without answering 2xx is still removed and
one that never saved is simply not there.

* test(e2e/ui): claim the member id before creating the user

/user/new can persist the user and still answer non-2xx, and the id is chosen
by the test rather than returned by the proxy, so registering it before the
call is what closes the last create-failure path.

Teardown now skips an id whose user is not there, so claiming it up front
cannot fail a run where the create never landed.

* test(e2e/ui): wait out the router reload when resolving a deployment to delete

/model/info answers from the router, not from the database, and /model/new
catches and logs a failed in-request reload while still answering 2xx. A
deployment can therefore be persisted and absent from the listing until the
next reload, which is where teardown was giving up and leaking it.

Teardown now retries the lookup for a little over one
PROXY_CONFIG_RELOAD_INTERVAL_SECONDS before treating the name as never
persisted, so the only names it skips are the ones that really are not there.

* test(e2e/ui): prove a stored credential survives a config reload before using it

The Test Connect assertion has been failing intermittently on the full-suite
runs. Artifacts from litellm-e2e-ui build 165 show the UI sending
litellm_credential_name and the proxy answering with the credential unapplied:
raw_request_api_base was https://api.openai.com/v1/ rather than the mock base
the credential carries, and the call died on an upstream 404 for the model. The
same credential had resolved on three probes eight seconds earlier.

The proxy's periodic credential refresh takes a database snapshot, prunes any
in-memory credential missing from it, then re-adds the snapshot. A credential
created while that is in flight gets pruned and stays gone until the next tick,
and load_credentials_from_list fails open onto the ambient key, so nothing in
the error names the credential.

The existing pre-check asked for three consecutive probe successes, but they
completed in under a second, so they could not span a refresh. Space them so
the run covers a whole interval, which is what proves the credential survived a
refresh and is therefore stable.

* test(e2e/ui): find a database-only deployment through the search listing

/model/info answers from the router, so a deployment that reached the database
while /model/new's in-request reload failed is invisible there, and waiting on
the next reload only helps if reconciliation eventually picks it up.

/v2/model/info?search= runs a bounded query against the model table and
deliberately returns rows the router does not hold, so it resolves those
deployments to the id /model/delete needs. Falling back to it removes the wait
as well: absent from both listings now means the deployment never persisted.

* test(e2e/ui): delete the temporary member without a lookup that can skip it

Teardown asked /user/info first and treated any non-2xx as absence, so a
transient failure on the lookup silently skipped the delete and left the user
behind, which is the leak the claimed id was meant to close.

/user/delete answers 404 for an id that is not there, so it can carry both
cases on its own: 404 means the create never persisted, and anything else that
is not 2xx now fails the teardown instead of passing quietly.

* test(e2e/ui): reach the database fallback when the router listing fails

Asserting on /model/info threw before the fallback could run, so a failure on
the router-backed listing aborted teardown and left the deployment persisted,
which is the leak the fallback was added to close.

The router listing is best-effort now: an unreadable response just falls
through to the search-backed one. That listing is the authoritative answer to
whether the deployment exists, so it is the one that has to be readable, and a
name missing from it is a create that never persisted.

---------

Co-authored-by: Claude <noreply@anthropic.com>
---
 tests/e2e/ui/helpers/premium.ts               |  20 ++++
 tests/e2e/ui/helpers/traffic.ts               |  73 +++++++++---
 .../e2e/ui/tests/modelsPage/addModel.spec.ts  |  34 ++++--
 tests/e2e/ui/tests/proxy-admin/keys.spec.ts   |  32 +++++-
 tests/e2e/ui/tests/proxy-admin/teams.spec.ts  |  32 ++++--
 .../e2e/ui/tests/team-admin/teamAdmin.spec.ts |  51 ++++++++-
 tests/e2e/ui/tests/usage/usagePage.spec.ts    | 108 +++++++++++++++++-
 7 files changed, 296 insertions(+), 54 deletions(-)
 create mode 100644 tests/e2e/ui/helpers/premium.ts

diff --git a/tests/e2e/ui/helpers/premium.ts b/tests/e2e/ui/helpers/premium.ts
new file mode 100644
index 00000000000..28bc2e58bbc
--- /dev/null
+++ b/tests/e2e/ui/helpers/premium.ts
@@ -0,0 +1,20 @@
+import * as fs from "fs";
+import { ADMIN_STORAGE_PATH } from "../constants";
+
+/**
+ * Whether the proxy under test is licensed, read from the admin session JWT's `premium_user`
+ * claim. That is the same value the dashboard reads to enable premium-gated controls, so it
+ * describes the proxy Playwright is pointed at rather than the environment the runner happens
+ * to have, which are not the same machine when E2E_UI_BASE_URL points elsewhere.
+ */
+export function proxyIsPremium(): boolean {
+  const storage = JSON.parse(fs.readFileSync(ADMIN_STORAGE_PATH, "utf-8")) as {
+    cookies?: { name: string; value: string }[];
+  };
+  const token = storage.cookies?.find((cookie) => cookie.name === "token")?.value;
+  const payload = token?.split(".")[1];
+  if (!payload) {
+    return false;
+  }
+  return JSON.parse(Buffer.from(payload, "base64url").toString("utf-8")).premium_user === true;
+}
diff --git a/tests/e2e/ui/helpers/traffic.ts b/tests/e2e/ui/helpers/traffic.ts
index ebd3c9a417f..25eb671fd0e 100644
--- a/tests/e2e/ui/helpers/traffic.ts
+++ b/tests/e2e/ui/helpers/traffic.ts
@@ -4,12 +4,16 @@ import { APIRequestContext, expect } from "@playwright/test";
 export const CHAT_MODEL_A = "fake-openai-gpt-4";
 export const CHAT_MODEL_B = "fake-anthropic-claude";
 
+/** The deployment each of those models routes to, as spend logs and usage breakdowns name it. */
+export const DEPLOYMENT_MODEL_A = "openai/fake-gpt-4";
+export const DEPLOYMENT_MODEL_B = "openai/fake-claude";
+
 /** The only completion text fixtures/mock_llm_server/server.py ever returns. */
 export const MOCK_RESPONSE_TEXT = "This is a mock response.";
 
 export const masterKey = (): string => process.env.LITELLM_MASTER_KEY || "sk-1234";
 
-const rootPath = (): string => process.env.SERVER_ROOT_PATH ?? "";
+export const rootPath = (): string => process.env.SERVER_ROOT_PATH ?? "";
 
 interface ChatOptions {
   model: string;
@@ -114,13 +118,54 @@ export async function waitForSpendLogByPrompt(
 
 const isoDay = (d: Date): string => d.toISOString().slice(0, 10);
 
+interface DailyActivityKey {
+  metrics?: { api_requests?: number };
+}
+
+interface DailyActivityPage {
+  results?: { breakdown?: { api_keys?: Record<string, DailyActivityKey> } }[];
+  metadata?: { total_pages?: number };
+}
+
+const requestsOnPage = (body: DailyActivityPage, keyToken: string): number =>
+  (body.results ?? []).reduce((sum, day) => sum + (day.breakdown?.api_keys?.[keyToken]?.metrics?.api_requests ?? 0), 0);
+
+/**
+ * The route paginates its per-key breakdown. Reading only the first page finds a key while the
+ * database is small and stops finding it once a run has generated more keys than one page holds,
+ * which reads as "the rollup is not running" when the rollup is fine.
+ */
+async function keyRequestsInDailyActivity(
+  request: APIRequestContext,
+  query: string,
+  keyToken: string,
+  page = 1,
+  seen = 0,
+): Promise<number> {
+  const res = await request.get(`${rootPath()}/user/daily/activity?${query}&page=${page}`, {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+  });
+  if (!res.ok()) {
+    return seen;
+  }
+  const body = (await res.json()) as DailyActivityPage;
+  const total = seen + requestsOnPage(body, keyToken);
+  return page >= (body.metadata?.total_pages ?? 1)
+    ? total
+    : keyRequestsInDailyActivity(request, query, keyToken, page + 1, total);
+}
+
 /**
  * The Usage page reads /user/daily/activity, a rollup written by a background job, and fetches it once
  * on mount. Navigating before the rollup lands leaves a stale render that never refreshes.
+ *
+ * The rollup lands request by request, so waiting only for the key to appear leaves a caller that
+ * sent several requests reading a partial count. Pass `minRequests` to wait for all of them.
  */
 export async function waitForKeyInDailyActivity(
   request: APIRequestContext,
   keyToken: string,
+  minRequests = 1,
   timeoutMs = 120_000,
 ): Promise<void> {
   const now = new Date();
@@ -129,25 +174,17 @@ export async function waitForKeyInDailyActivity(
   const query = `start_date=${isoDay(start)}&end_date=${isoDay(now)}`;
 
   const deadline = Date.now() + timeoutMs;
-  let lastStatus = 0;
-  while (Date.now() < deadline) {
-    const res = await request.get(`${rootPath()}/user/daily/activity?${query}`, {
-      headers: { Authorization: `Bearer ${masterKey()}` },
-    });
-    lastStatus = res.status();
-    if (res.ok()) {
-      const body = await res.json();
-      const seen = (body?.results ?? []).some(
-        (day: { breakdown?: { api_keys?: Record<string, unknown> } }) => keyToken in (day.breakdown?.api_keys ?? {}),
+  for (;;) {
+    const seen = await keyRequestsInDailyActivity(request, query, keyToken);
+    if (seen >= minRequests) {
+      return;
+    }
+    if (Date.now() >= deadline) {
+      throw new Error(
+        `key ${keyToken} reached ${seen} of ${minRequests} requests in /user/daily/activity across every page; ` +
+          "the daily spend rollup may not be running",
       );
-      if (seen) {
-        return;
-      }
     }
     await new Promise((r) => setTimeout(r, 3_000));
   }
-  throw new Error(
-    `key ${keyToken} never appeared in /user/daily/activity (last status ${lastStatus}); ` +
-      "the daily spend rollup may not be running",
-  );
 }
diff --git a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
index 073d3c0b79c..de25ec1aac5 100644
--- a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
+++ b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts
@@ -5,6 +5,11 @@ import { navigateToPage } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
 import { captureRequestBody, readBack } from "../../helpers/roundTrip";
 import { sendChatCompletion } from "../../helpers/traffic";
+import { proxyIsPremium } from "../../helpers/premium";
+
+/** Four probes 13s apart span 39s, one PROXY_CONFIG_RELOAD_INTERVAL_SECONDS (30s) plus margin. */
+const CREDENTIAL_PROBE_SUCCESSES = 4;
+const CREDENTIAL_PROBE_SPACING_MS = 13_000;
 
 /** The mock LLM as the proxy reaches it: same host locally, a sidecar in the deployed stack. */
 const MOCK_LLM_BASE = `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`;
@@ -35,7 +40,10 @@ async function selectProvider(page: PlaywrightPage, providerName: string) {
   const providerDropdown = page.getByRole("combobox", { name: "Provider", exact: true });
   await providerDropdown.click();
   await providerDropdown.fill(providerName);
-  await page.getByRole("option").filter({ hasText: exactly(providerName) }).click();
+  await page
+    .getByRole("option")
+    .filter({ hasText: exactly(providerName) })
+    .click();
   await expect(providerDropdown).toHaveValue(providerName);
 }
 
@@ -78,6 +86,9 @@ test.describe("Add Model", () => {
   });
 
   test("Edit team model TPM and RPM limits", async ({ page }) => {
+    // /model/new refuses a team-scoped deployment on an unlicensed proxy, so there this fails in
+    // setup on a product gate rather than on a regression in the edit it covers.
+    test.skip(!proxyIsPremium(), "proxy under test is unlicensed — team-scoped models are premium");
     const masterKey = users[Role.ProxyAdmin].password;
     const modelName = `e2e-team-model-${Date.now()}`;
 
@@ -226,8 +237,11 @@ test.describe("Add Model", () => {
     });
     expect(createCred.ok(), `POST /credentials failed (${createCred.status()}): ${await createCred.text()}`).toBe(true);
 
-    // Multi-instance stacks propagate a new credential to the probe-serving instances on a periodic
-    // sync; consecutive successes guard against a load balancer alternating synced and stale replicas
+    // The proxy's periodic credential refresh prunes its in-memory list against a database snapshot
+    // it took before this credential landed, so a credential that resolves right after POST
+    // /credentials can stop resolving until the refresh after that. Successes spanning a whole
+    // PROXY_CONFIG_RELOAD_INTERVAL_SECONDS prove it survived a refresh, after which it stays.
+    // Resolution fails open onto the ambient key, so losing it reads as a confusing upstream 404.
     let consecutiveProbeSuccesses = 0;
     await expect
       .poll(
@@ -249,11 +263,12 @@ test.describe("Add Model", () => {
           return consecutiveProbeSuccesses;
         },
         {
-          message: `stored credential ${credentialName} never became usable for a connection test`,
-          timeout: 60_000,
+          message: `stored credential ${credentialName} never stayed usable across a config reload`,
+          intervals: [0, CREDENTIAL_PROBE_SPACING_MS],
+          timeout: 110_000,
         },
       )
-      .toBeGreaterThanOrEqual(3);
+      .toBeGreaterThanOrEqual(CREDENTIAL_PROBE_SUCCESSES);
 
     try {
       await navigateToPage(page, Page.Models);
@@ -458,7 +473,7 @@ test.describe("Add Model", () => {
       await page.waitForLoadState("networkidle");
 
       await page.getByPlaceholder("Search model names").fill("cohere");
-  
+
       // Clearer failure than timing out on a row assertion when the table is empty.
       await expect(page.getByTestId("pagination-range")).toHaveText(/Showing \d+-\d+ of \d+/, {
         timeout: 15_000,
@@ -466,10 +481,7 @@ test.describe("Add Model", () => {
 
       // Pin to one row carrying both the name and the team, so the sibling test's
       // team-less cohere row can't satisfy it.
-      const teamCohereRow = page
-        .getByRole("row")
-        .filter({ hasText: "cohere/" })
-        .filter({ hasText: E2E_TEAM_CRUD_ID });
+      const teamCohereRow = page.getByRole("row").filter({ hasText: "cohere/" }).filter({ hasText: E2E_TEAM_CRUD_ID });
       await expect(teamCohereRow).toHaveCount(1, { timeout: 15_000 });
     } finally {
       await deleteTeamScopedCohereModels();
diff --git a/tests/e2e/ui/tests/proxy-admin/keys.spec.ts b/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
index f5bee68f245..deb7ae70d07 100644
--- a/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
+++ b/tests/e2e/ui/tests/proxy-admin/keys.spec.ts
@@ -1,15 +1,17 @@
 import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
 import {
   ADMIN_STORAGE_PATH,
-  E2E_DELETE_KEY_ALIAS,
   E2E_REGENERATE_KEY_ALIAS,
   E2E_UPDATE_LIMITS_KEY_ALIAS,
   E2E_INTERNAL_USER_KEY_ALIAS,
   E2E_TEAM_CRUD_ALIAS,
+  E2E_TEAM_CRUD_ID,
 } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { captureRequestBody, readBack } from "../../helpers/roundTrip";
+import { masterKey } from "../../helpers/traffic";
+import { proxyIsPremium } from "../../helpers/premium";
 
 /**
  * Looks a key up by alias, undefined when none carries it. `return_full_object=true` is what makes
@@ -23,6 +25,17 @@ async function findKeyByAlias(page: PlaywrightPage, alias: string): Promise<Reco
   return body.keys.find((row) => row.key_alias === alias);
 }
 
+/** A key this test owns, so deleting it costs the suite nothing on a retry or a second run. */
+async function createDeletableKey(page: PlaywrightPage): Promise<string> {
+  const alias = `e2e-delete-key-${Date.now()}`;
+  const res = await page.request.post("/key/generate", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { key_alias: alias, team_id: E2E_TEAM_CRUD_ID },
+  });
+  expect(res.ok(), `POST /key/generate failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return alias;
+}
+
 test.describe("Proxy Admin - Keys", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
@@ -67,6 +80,9 @@ test.describe("Proxy Admin - Keys", () => {
   });
 
   test("Regenerate key", async ({ page }) => {
+    // The Regenerate Key button renders disabled when the proxy is unlicensed, so without one this
+    // fails on a product gate rather than on a regression.
+    test.skip(!proxyIsPremium(), "proxy under test is unlicensed — Regenerate Key is premium-gated");
     await navigateToPage(page, Page.ApiKeys);
     await dismissFeedbackPopup(page);
 
@@ -143,12 +159,16 @@ test.describe("Proxy Admin - Keys", () => {
   });
 
   test("Delete key", async ({ page }) => {
+    // Deleting the seeded key leaves nothing for the next attempt, so the retries CI runs with are
+    // guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const alias = await createDeletableKey(page);
+
     await navigateToPage(page, Page.ApiKeys);
     await dismissFeedbackPopup(page);
 
-    const keyRow = page.getByRole("row").filter({ hasText: E2E_DELETE_KEY_ALIAS });
+    const keyRow = page.getByRole("row").filter({ hasText: alias });
     await expect(keyRow).toBeVisible({ timeout: 10_000 });
-    await keyRow.getByRole("button", { name: E2E_DELETE_KEY_ALIAS }).click();
+    await keyRow.getByRole("button", { name: alias }).click();
 
     await expect(page.getByText("Back to Keys")).toBeVisible({ timeout: 10_000 });
 
@@ -157,7 +177,7 @@ test.describe("Proxy Admin - Keys", () => {
 
     const modal = page.getByRole("dialog", { name: "Delete Key" });
     await expect(modal).toBeVisible({ timeout: 5_000 });
-    await modal.locator("input").fill(E2E_DELETE_KEY_ALIAS);
+    await modal.locator("input").fill(alias);
 
     const deleteButton = modal.getByRole("button", { name: "Delete", exact: true });
     await expect(deleteButton).toBeEnabled();
@@ -167,8 +187,8 @@ test.describe("Proxy Admin - Keys", () => {
 
     // The key is gone when the management API stops returning it, not when the toast says so.
     await expect
-      .poll(async () => await findKeyByAlias(page, E2E_DELETE_KEY_ALIAS), {
-        message: `key ${E2E_DELETE_KEY_ALIAS} still readable from /key/list after delete`,
+      .poll(async () => await findKeyByAlias(page, alias), {
+        message: `key ${alias} still readable from /key/list after delete`,
         timeout: 15_000,
       })
       .toBeUndefined();
diff --git a/tests/e2e/ui/tests/proxy-admin/teams.spec.ts b/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
index 7383b452162..303e4488e09 100644
--- a/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
+++ b/tests/e2e/ui/tests/proxy-admin/teams.spec.ts
@@ -1,14 +1,9 @@
 import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
-import {
-  ADMIN_STORAGE_PATH,
-  E2E_TEAM_CRUD_ID,
-  E2E_TEAM_DELETE_ALIAS,
-  E2E_TEAM_NO_ADMIN_ID,
-  E2E_TEAM_ORG_ID,
-} from "../../constants";
+import { ADMIN_STORAGE_PATH, E2E_TEAM_CRUD_ID, E2E_TEAM_NO_ADMIN_ID, E2E_TEAM_ORG_ID } from "../../constants";
 import { Page } from "../../fixtures/pages";
 import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
 import { readBack } from "../../helpers/roundTrip";
+import { masterKey } from "../../helpers/traffic";
 
 /** GET /team/list returns a bare array of teams, each carrying team_alias/team_id. */
 async function findTeamByAlias(page: PlaywrightPage, alias: string): Promise<Record<string, any> | undefined> {
@@ -25,6 +20,17 @@ async function teamMemberEmails(page: PlaywrightPage, teamId: string): Promise<s
   return (info.team_info.members_with_roles ?? []).map((member) => member.user_email ?? "").filter(Boolean);
 }
 
+/** A team this test owns, so deleting it costs the suite nothing on a retry or a second run. */
+async function createDeletableTeam(page: PlaywrightPage): Promise<string> {
+  const alias = `e2e-delete-team-${Date.now()}`;
+  const res = await page.request.post("/team/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { team_alias: alias, models: ["fake-openai-gpt-4"] },
+  });
+  expect(res.ok(), `POST /team/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return alias;
+}
+
 test.describe("Proxy Admin - Teams", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
@@ -121,10 +127,14 @@ test.describe("Proxy Admin - Teams", () => {
   });
 
   test("Delete a team", async ({ page }) => {
+    // Deleting the seeded team leaves nothing for the next attempt, so the retries CI runs with are
+    // guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const alias = await createDeletableTeam(page);
+
     await navigateToPage(page, Page.Teams);
     await dismissFeedbackPopup(page);
 
-    const teamRow = page.locator("tr", { hasText: E2E_TEAM_DELETE_ALIAS }).first();
+    const teamRow = page.locator("tr", { hasText: alias }).first();
     await expect(teamRow).toBeVisible({ timeout: 10_000 });
     // Actions live in a kebab menu: open it, then click "Delete team".
     await teamRow.locator('[data-testid^="team-actions-"]').click();
@@ -132,15 +142,15 @@ test.describe("Proxy Admin - Teams", () => {
 
     const modal = page.getByRole("dialog", { name: "Delete Team?" });
     await expect(modal).toBeVisible({ timeout: 5_000 });
-    await modal.locator("input").fill(E2E_TEAM_DELETE_ALIAS);
+    await modal.locator("input").fill(alias);
     await modal.getByRole("button", { name: /Force Delete|Delete/i }).click();
 
     await expect(teamRow).not.toBeVisible({ timeout: 10_000 });
 
     // A row vanishing is local state, which happens whether or not the delete landed.
     await expect
-      .poll(async () => await findTeamByAlias(page, E2E_TEAM_DELETE_ALIAS), {
-        message: `team ${E2E_TEAM_DELETE_ALIAS} still readable from /team/list after delete`,
+      .poll(async () => await findTeamByAlias(page, alias), {
+        message: `team ${alias} still readable from /team/list after delete`,
         timeout: 15_000,
       })
       .toBeUndefined();
diff --git a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
index 26a6fa50b4b..f3c031f0172 100644
--- a/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
+++ b/tests/e2e/ui/tests/team-admin/teamAdmin.spec.ts
@@ -35,7 +35,44 @@ async function findKeyByAlias(page: PlaywrightPage, alias: string): Promise<Reco
   return body.keys.find((row) => row.key_alias === alias);
 }
 
+/** A member this test adds itself, so removing it costs the suite nothing on a retry or a re-run. */
+async function addRemovableMember(page: PlaywrightPage, registerForCleanup: string[]): Promise<string> {
+  const userId = `e2e-removable-${Date.now()}`;
+  // Claimed before the call: /user/new can persist the user and still answer non-2xx, and the id is
+  // ours either way, so registering it up front is what no failure path can skip.
+  registerForCleanup.push(userId);
+  const created = await page.request.post("/user/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { user_id: userId, user_role: "internal_user", auto_create_key: false },
+  });
+  expect(created.ok(), `POST /user/new failed (${created.status()}): ${await created.text()}`).toBe(true);
+
+  const added = await page.request.post("/team/member_add", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { team_id: E2E_TEAM_CRUD_ID, member: { user_id: userId, role: "user" } },
+  });
+  expect(added.ok(), `POST /team/member_add failed (${added.status()}): ${await added.text()}`).toBe(true);
+  return userId;
+}
+
 test.describe("Team Admin", () => {
+  const createdMembers: string[] = [];
+
+  test.afterEach(async ({ page }) => {
+    // Runs on the failure path too, which a call at the end of the test body would not. Ids are
+    // claimed before the user is created, so the delete is attempted unconditionally and only its
+    // own 404 counts as never persisted; any other answer is a cleanup failure worth reporting
+    // rather than a reason to leave the user behind.
+    for (const userId of createdMembers.splice(0)) {
+      const deleted = await page.request.post("/user/delete", {
+        headers: { Authorization: `Bearer ${masterKey()}` },
+        data: { user_ids: [userId] },
+      });
+      const settled = deleted.ok() || deleted.status() === 404;
+      expect(settled, `POST /user/delete for ${userId} (${deleted.status()}): ${await deleted.text()}`).toBe(true);
+    }
+  });
+
   test.use({ storageState: TEAM_ADMIN_STORAGE_PATH });
 
   test("Team admin can see all team keys including internal user keys", async ({ page }) => {
@@ -95,6 +132,10 @@ test.describe("Team Admin", () => {
   });
 
   test("Team admin can remove a member from their team", async ({ page }) => {
+    // Removing the seeded member leaves nothing for the next attempt, so the retries CI runs with
+    // are guaranteed to fail and the suite cannot run twice against one database. Bring our own.
+    const memberId = await addRemovableMember(page, createdMembers);
+
     await navigateToPage(page, Page.Teams);
     await dismissFeedbackPopup(page);
 
@@ -102,9 +143,9 @@ test.describe("Team Admin", () => {
 
     await page.getByRole("tab", { name: "Members" }).click();
 
-    // Seeded members appear in the roster by user_id (members_with_roles has no
-    // email), so match the row on the user_id rather than the email.
-    const row = page.locator("tr", { hasText: "e2e-removable-member" }).first();
+    // Members appear in the roster by user_id (members_with_roles has no email), so match
+    // the row on the user_id rather than the email.
+    const row = page.locator("tr", { hasText: memberId }).first();
     await expect(row).toBeVisible({ timeout: 10_000 });
     await row.getByTestId("delete-member").click();
 
@@ -117,7 +158,7 @@ test.describe("Team Admin", () => {
     // Removing the wrong member is exactly what a success toast hides, so pin both halves.
     expect(remove.team_id, "delete targets the team being viewed").toBe(E2E_TEAM_CRUD_ID);
     expect([remove.user_id, remove.user_email], "delete identifies the member whose row was clicked").toContain(
-      "e2e-removable-member",
+      memberId,
     );
 
     await expect(page.getByText("Team member removed successfully").first()).toBeVisible({ timeout: 10_000 });
@@ -128,7 +169,7 @@ test.describe("Team Admin", () => {
         message: "removed member is still on the team",
         timeout: 15_000,
       })
-      .not.toContain("e2e-removable-member");
+      .not.toContain(memberId);
   });
 
   test("Team admin sees all team models in the Playground model dropdown", async ({ page, request }) => {
diff --git a/tests/e2e/ui/tests/usage/usagePage.spec.ts b/tests/e2e/ui/tests/usage/usagePage.spec.ts
index f61ab018e1b..3d057cfa2c9 100644
--- a/tests/e2e/ui/tests/usage/usagePage.spec.ts
+++ b/tests/e2e/ui/tests/usage/usagePage.spec.ts
@@ -1,10 +1,11 @@
-import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { test, expect, type APIRequestContext, type Locator, type Page as PlaywrightPage } from "@playwright/test";
 import { ADMIN_STORAGE_PATH } from "../../constants";
 import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
 import { Page } from "../../fixtures/pages";
 import {
-  CHAT_MODEL_A,
   createVirtualKey,
+  masterKey,
+  rootPath,
   sendChatCompletion,
   waitForKeyInDailyActivity,
   waitForSpendLog,
@@ -27,9 +28,105 @@ async function openUsage(page: PlaywrightPage): Promise<Locator> {
   return card;
 }
 
+/** The upstream fixtures/config.yml points its models at, so the mock server answers this too. */
+const MOCK_DEPLOYMENT = "openai/fake-gpt-4";
+
+/** A deployment whose traffic costs real money, so the key that used it outranks the $0 crowd. */
+async function createPricedDeployment(
+  request: APIRequestContext,
+  label: string,
+  registerForCleanup: string[],
+): Promise<{ modelName: string }> {
+  const modelName = `e2e-usage-priced-${label}`;
+  // Claimed before the call: /model/new can persist the deployment and still answer non-2xx, so a
+  // name recorded up front is the only registration no response shape can skip.
+  registerForCleanup.push(modelName);
+  const res = await request.post("/model/new", {
+    headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+    data: {
+      model_name: modelName,
+      litellm_params: {
+        model: MOCK_DEPLOYMENT,
+        api_base: `http://127.0.0.1:${process.env.MOCK_LLM_PORT ?? "8090"}/v1`,
+        api_key: "fake-key",
+        input_cost_per_token: 0.01,
+        output_cost_per_token: 0.01,
+      },
+    },
+  });
+  expect(res.ok(), `POST /model/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+
+  // /model/new returns once the row is written, but the router only picks the deployment up on its
+  // next refresh, so sending traffic straight away can still get "no healthy deployments". A ping
+  // that fails writes no spend log, so retrying it costs the ranking this test asserts nothing.
+  await expect
+    .poll(
+      async () => {
+        const ping = await request.post(`${rootPath()}/v1/chat/completions`, {
+          headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+          data: { model: modelName, messages: [{ role: "user", content: "readiness ping" }] },
+        });
+        return ping.ok();
+      },
+      { message: `deployment ${modelName} never became routable`, timeout: 60_000 },
+    )
+    .toBe(true);
+
+  return { modelName };
+}
+
 test.describe("Usage page", () => {
   test.use({ storageState: ADMIN_STORAGE_PATH });
 
+  const pricedDeployments: string[] = [];
+
+  test.afterEach(async ({ request }) => {
+    // A deployment left behind keeps its custom pricing, so it goes on changing what later runs
+    // route and what they cost. Runs on the failure path too, which the test body would not.
+    // Resolved by name rather than by a returned id, so a create that persisted without answering
+    // 2xx is still cleaned up. /model/info serves the router, and /model/new answers 2xx even when
+    // its in-request router reload failed, so the search-backed listing is what covers a deployment
+    // that reached the database only. Absent from both means it never persisted.
+    const names = pricedDeployments.splice(0);
+    if (names.length === 0) return;
+    const auth = { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" };
+
+    type Lookup =
+      | { readonly listed: true; readonly id: string | undefined }
+      | { readonly listed: false; readonly status: number };
+
+    const idIn = async (path: string, name: string): Promise<Lookup> => {
+      const listed = await request.get(path, { headers: auth });
+      if (!listed.ok()) return { listed: false, status: listed.status() };
+      const deployments = ((await listed.json()).data ?? []) as {
+        model_name?: string;
+        model_info?: { id?: string };
+      }[];
+      return { listed: true, id: deployments.find((d) => d.model_name === name)?.model_info?.id };
+    };
+
+    const remove = async (name: string, id: string) => {
+      const deleted = await request.post(`${rootPath()}/model/delete`, { headers: auth, data: { id } });
+      expect(deleted.ok(), `POST /model/delete for ${name} (${deleted.status()})`).toBe(true);
+    };
+
+    for (const name of names) {
+      const fromRouter = await idIn(`${rootPath()}/model/info`, name);
+      if (fromRouter.listed && fromRouter.id !== undefined) {
+        await remove(name, fromRouter.id);
+        continue;
+      }
+      const search = encodeURIComponent(name);
+      const fromDb = await idIn(`${rootPath()}/v2/model/info?search=${search}`, name);
+      expect(
+        fromDb.listed,
+        `GET /v2/model/info?search=${search} (${fromDb.listed ? 200 : fromDb.status}), so ${name} could not be checked`,
+      ).toBe(true);
+      if (!fromDb.listed || fromDb.id === undefined) continue;
+      await remove(name, fromDb.id);
+    }
+  });
+
   test("Top Virtual Keys lists a key that served traffic, toggles views, and opens key info", async ({
     page,
     request,
@@ -39,8 +136,13 @@ test.describe("Usage page", () => {
       key_alias: alias,
     });
 
+    // Top Virtual Keys ranks by spend, and every mock deployment costs $0, so once a run has more
+    // keys than the list shows, whether this one makes the cut is down to how ties happen to sort.
+    // Give it a priced deployment of its own so it earns its place.
+    const { modelName } = await createPricedDeployment(request, alias, pricedDeployments);
+
     const requestId = await sendChatCompletion(request, {
-      model: CHAT_MODEL_A,
+      model: modelName,
       prompt: `usage ping for ${alias}`,
       apiKey: key,
     });

From 284e96cfe76b0a8ec6339c63782b8a6a8b1eb2e3 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:35:45 -0700
Subject: [PATCH 064/113] test(e2e/ui): cover the team Settings tab (#39058)

The Teams tests covered creating, deleting and membership, but nothing on the
Settings tab, which is the form that posts the whole team back. That is the
shape behind the reports of a team losing its metadata or its model aliases
after an unrelated edit.

Each test creates its own team rather than editing a seeded one. The limits
test pins the models and members the edit had no business touching, and the
alias test calls the new alias with a team key instead of trusting the
readback, since an alias the router never resolves reads the same either way.

Co-authored-by: Claude <noreply@anthropic.com>
---
 .../ui/tests/proxy-admin/teamSettings.spec.ts | 162 ++++++++++++++++++
 1 file changed, 162 insertions(+)
 create mode 100644 tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts

diff --git a/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts b/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts
new file mode 100644
index 00000000000..e71945a4ccd
--- /dev/null
+++ b/tests/e2e/ui/tests/proxy-admin/teamSettings.spec.ts
@@ -0,0 +1,162 @@
+import { test, expect, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { Page } from "../../fixtures/pages";
+import { navigateToPage, dismissFeedbackPopup, clickTeamId } from "../../helpers/navigation";
+import { readBack } from "../../helpers/roundTrip";
+import { CHAT_MODEL_A, MOCK_RESPONSE_TEXT, masterKey } from "../../helpers/traffic";
+
+interface TeamInfo {
+  team_id: string;
+  team_alias: string;
+  models: string[];
+  max_budget: number | null;
+  tpm_limit: number | null;
+  rpm_limit: number | null;
+  metadata: Record<string, unknown> | null;
+  members_with_roles: { user_id?: string; role?: string }[];
+}
+
+/**
+ * Each test owns a team it created, rather than editing a seeded one, so a save that clobbers a
+ * field cannot take another spec's fixture down with it.
+ */
+async function createTeam(page: PlaywrightPage, alias: string, members: string[] = []): Promise<string> {
+  const res = await page.request.post("/team/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: {
+      team_alias: alias,
+      models: [CHAT_MODEL_A],
+      members_with_roles: members.map((user_id) => ({ user_id, role: "user" })),
+    },
+  });
+  expect(res.ok(), `POST /team/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return (await res.json()).team_id as string;
+}
+
+/**
+ * A member of this test's own, not one of the seeded users. Putting a seeded user on an extra team
+ * changes what every spec that asserts on their memberships sees.
+ */
+async function createMember(page: PlaywrightPage, userId: string): Promise<string> {
+  const res = await page.request.post("/user/new", {
+    headers: { Authorization: `Bearer ${masterKey()}` },
+    data: { user_id: userId, user_role: "internal_user", auto_create_key: false },
+  });
+  expect(res.ok(), `POST /user/new failed (${res.status()}): ${await res.text()}`).toBe(true);
+  return userId;
+}
+
+async function teamInfo(page: PlaywrightPage, teamId: string): Promise<TeamInfo> {
+  const body = await readBack<{ team_info: TeamInfo }>(page, `/team/info?team_id=${encodeURIComponent(teamId)}`);
+  return body.team_info;
+}
+
+async function openTeamSettings(page: PlaywrightPage, teamId: string): Promise<void> {
+  await navigateToPage(page, Page.Teams);
+  await dismissFeedbackPopup(page);
+  await clickTeamId(page, teamId);
+  await page.getByRole("tab", { name: "Settings" }).click();
+  await page.getByRole("button", { name: "Edit Settings" }).click();
+  await expect(page.getByRole("button", { name: "Save Changes" })).toBeVisible({ timeout: 10_000 });
+}
+
+test.describe("Proxy Admin - Team settings", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Setting a team's spend cap and rate limits leaves its models and members alone", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-limits-${stamp}`;
+    const member = await createMember(page, `e2e-team-limits-member-${stamp}`);
+    const teamId = await createTeam(page, alias, [member]);
+    const before = await teamInfo(page, teamId);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("spinbutton", { name: "Max Budget (USD)" }).fill("42.5");
+    await page.getByRole("spinbutton", { name: "Tokens per minute Limit (TPM)" }).fill("7000");
+    await page.getByRole("spinbutton", { name: "Requests per minute Limit (RPM)" }).fill("70");
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(
+        async () => {
+          const team = await teamInfo(page, teamId);
+          return [team.max_budget, team.tpm_limit, team.rpm_limit];
+        },
+        { message: "team limits did not persist", timeout: 20_000 },
+      )
+      .toEqual([42.5, 7000, 70]);
+
+    // The Settings form posts the whole team. A field it fails to seed goes back as null, and
+    // the toast still says success, so pin the fields this edit had no business touching.
+    const after = await teamInfo(page, teamId);
+    expect(after.models, "model access untouched by a limits edit").toEqual(before.models);
+    expect(
+      after.members_with_roles.map((member) => member.user_id).sort(),
+      "membership untouched by a limits edit",
+    ).toEqual(before.members_with_roles.map((member) => member.user_id).sort());
+  });
+
+  test("A model alias added on the Settings tab serves traffic under the alias name", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-alias-${stamp}`;
+    const modelAlias = `e2e-alias-${stamp}`;
+    const teamId = await createTeam(page, alias);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("textbox", { name: "Alias Name" }).fill(modelAlias);
+    await page.getByRole("combobox", { name: "Select target model" }).click();
+    await page.getByRole("option", { name: CHAT_MODEL_A, exact: true }).first().click();
+    await page.getByRole("button", { name: "Add Alias" }).click();
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(async () => (await teamInfo(page, teamId)).models, { message: "team lost its models", timeout: 20_000 })
+      .toEqual([CHAT_MODEL_A]);
+
+    const keyRes = await page.request.post("/key/generate", {
+      headers: { Authorization: `Bearer ${masterKey()}` },
+      data: { team_id: teamId, key_alias: `e2e-alias-key-${stamp}` },
+    });
+    expect(keyRes.ok(), `POST /key/generate failed (${keyRes.status()})`).toBe(true);
+    const teamKey = (await keyRes.json()).key as string;
+
+    // An alias the team can see but cannot call is the actual complaint; the readback alone
+    // would pass for an alias the router never resolves.
+    const served = await page.request.post("/v1/chat/completions", {
+      headers: { Authorization: `Bearer ${teamKey}`, "Content-Type": "application/json" },
+      data: { model: modelAlias, messages: [{ role: "user", content: "ping" }] },
+    });
+    expect(served.status(), `a team key calling ${modelAlias} is served`).toBe(200);
+    expect((await served.json()).choices?.[0]?.message?.content).toContain(MOCK_RESPONSE_TEXT);
+  });
+
+  test("Team metadata added as key-value pairs survives a reload", async ({ page }) => {
+    const stamp = Date.now();
+    const alias = `e2e-team-metadata-${stamp}`;
+    const metadataValue = `cost-center-${stamp}`;
+    const teamId = await createTeam(page, alias);
+
+    await openTeamSettings(page, teamId);
+
+    await page.getByRole("button", { name: "Add Key-Value Pair" }).click();
+    await page.getByPlaceholder("Key", { exact: true }).last().fill("owner");
+    await page.getByPlaceholder("Value", { exact: true }).last().fill(metadataValue);
+    await page.getByRole("button", { name: "Save Changes" }).click();
+
+    await expect
+      .poll(async () => (await teamInfo(page, teamId)).metadata?.owner, {
+        message: "team metadata did not persist",
+        timeout: 20_000,
+      })
+      .toBe(metadataValue);
+
+    // Reopening the form is the step that catches metadata the page writes but cannot read back.
+    await page.reload();
+    await page.getByRole("tab", { name: "Settings" }).click();
+    await page.getByRole("button", { name: "Edit Settings" }).click();
+    await expect(page.getByPlaceholder("Key", { exact: true })).toHaveValue("owner", { timeout: 15_000 });
+    await expect(page.getByPlaceholder("Value", { exact: true })).toHaveValue(metadataValue);
+  });
+});

From 4c86b1d58cb2d9a201daba7f7d1471b8f6da01e6 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:36:17 -0700
Subject: [PATCH 065/113] test(e2e/ui): cover the Usage page activity tabs
 (#39061)

* test(e2e/ui): cover the Usage page activity tabs

Usage had one test, on Top Virtual Keys. The Key, Model and Endpoint Activity
tabs are the ones an admin reads to answer where the spend went, and none of
them was covered.

Also fixes waitForKeyInDailyActivity, which only read the first page of
/user/daily/activity. The route paginates, so once a run generates more keys
than one page holds, the helper spins for its full 120 seconds and then blames
the rollup for a key the rollup wrote correctly. The Usage page itself already
walks every page; the helper now matches it.

* test(e2e/ui): route the user-creation call through SERVER_ROOT_PATH

Review caught /user/new posting to the server root, which misses the proxy
when it is mounted under a prefix. traffic.ts already had the helper for
this; it is now exported so specs making their own management calls can use
it too.

Also drops the mutable accumulators from the daily-activity paging, which
the repo conventions ask for.

---------

Co-authored-by: Claude <noreply@anthropic.com>
---
 .../ui/tests/usage/usageActivityTabs.spec.ts  | 135 ++++++++++++++++++
 1 file changed, 135 insertions(+)
 create mode 100644 tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts

diff --git a/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts b/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts
new file mode 100644
index 00000000000..2ee5ae3e392
--- /dev/null
+++ b/tests/e2e/ui/tests/usage/usageActivityTabs.spec.ts
@@ -0,0 +1,135 @@
+import { test, expect, type Locator, type Page as PlaywrightPage } from "@playwright/test";
+import { ADMIN_STORAGE_PATH } from "../../constants";
+import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation";
+import { Page } from "../../fixtures/pages";
+import {
+  CHAT_MODEL_A,
+  CHAT_MODEL_B,
+  DEPLOYMENT_MODEL_A,
+  DEPLOYMENT_MODEL_B,
+  createVirtualKey,
+  masterKey,
+  rootPath,
+  sendChatCompletion,
+  waitForKeyInDailyActivity,
+  waitForSpendLog,
+} from "../../helpers/traffic";
+
+/**
+ * Covers the per-entity breakdowns on /ui/usage. The page-level totals move with every other spec's
+ * traffic, so each assertion is scoped to a key this test minted and to the requests it sent.
+ */
+
+/** Each breakdown renders one expandable card per entity, named "<entity> $x.xx N requests". */
+const entityCard = (page: PlaywrightPage, tab: string, name: string): Locator =>
+  page.getByRole("tabpanel", { name: tab }).getByRole("button", { name: new RegExp(`^${name}\\s`) });
+
+async function openUsageTab(page: PlaywrightPage, tab: string): Promise<Locator> {
+  await navigateToPage(page, Page.NewUsage);
+  await dismissFeedbackPopup(page);
+  await page.getByRole("tab", { name: tab }).click();
+  const panel = page.getByRole("tabpanel", { name: tab });
+  await expect(panel).toBeVisible({ timeout: 30_000 });
+  return panel;
+}
+
+/** Sends `count` completions on one model and waits for each to reach the spend log. */
+async function sendTraffic(
+  request: Parameters<typeof sendChatCompletion>[0],
+  apiKey: string,
+  model: string,
+  count: number,
+  label: string,
+): Promise<void> {
+  for (let i = 0; i < count; i++) {
+    const requestId = await sendChatCompletion(request, { model, prompt: `${label} ${i}`, apiKey });
+    await waitForSpendLog(request, requestId);
+  }
+}
+
+test.describe("Usage page activity tabs", () => {
+  test.use({ storageState: ADMIN_STORAGE_PATH });
+
+  test("Key Activity breaks a key's traffic down by model", async ({ page, request }) => {
+    const alias = `e2e-usage-keyact-${Date.now()}`;
+    const { key, token } = await createVirtualKey(request, { key_alias: alias });
+
+    // An uneven split, so a breakdown that lumps everything into one row or attributes to the
+    // wrong model cannot land on these numbers by accident.
+    await sendTraffic(request, key, CHAT_MODEL_A, 2, alias);
+    await sendTraffic(request, key, CHAT_MODEL_B, 1, alias);
+    await waitForKeyInDailyActivity(request, token, 3);
+
+    await openUsageTab(page, "Key Activity");
+
+    const card = entityCard(page, "Key Activity", alias);
+    await expect(card, `${alias} missing from Key Activity`).toBeVisible({ timeout: 30_000 });
+    await expect(card).toContainText("3 requests");
+
+    // Every key gets a card, and the page opens the first one. Scope to this key's own section,
+    // which the collapsible renders as the trigger's next sibling.
+    await card.click();
+    const details = card.locator("xpath=following-sibling::*[1]");
+    const successfulFor = (model: string) =>
+      details.getByRole("row").filter({ hasText: model }).getByRole("cell").nth(2); // Model | Spend | Successful | Failed | Tokens
+
+    await expect(successfulFor(DEPLOYMENT_MODEL_A)).toHaveText("2", { timeout: 20_000 });
+    await expect(successfulFor(DEPLOYMENT_MODEL_B)).toHaveText("1");
+  });
+
+  test("Model Activity can name its models by deployment instead of by public name", async ({ page, request }) => {
+    const alias = `e2e-usage-modelact-${Date.now()}`;
+    const { key, token } = await createVirtualKey(request, { key_alias: alias });
+    await sendTraffic(request, key, CHAT_MODEL_A, 1, alias);
+    await waitForKeyInDailyActivity(request, token);
+
+    const panel = await openUsageTab(page, "Model Activity");
+
+    await expect(entityCard(page, "Model Activity", CHAT_MODEL_A), `${CHAT_MODEL_A} missing`).toBeVisible({
+      timeout: 30_000,
+    });
+    // Nothing is published under the deployment's name, so its absence here is what makes the
+    // toggle below a real change of key rather than a relabelled button.
+    await expect(entityCard(page, "Model Activity", DEPLOYMENT_MODEL_A)).toHaveCount(0);
+
+    // Admins reconcile provider bills against the deployment, not the name their users call.
+    await panel.getByRole("button", { name: "Litellm Model Name" }).click();
+    await expect(entityCard(page, "Model Activity", DEPLOYMENT_MODEL_A)).toBeVisible({ timeout: 20_000 });
+  });
+
+  test("Filter by user narrows Key Activity to that user's keys", async ({ page, request }) => {
+    const stamp = Date.now();
+    const email = `e2e-usage-owner-${stamp}@test.local`;
+    const ownedAlias = `e2e-usage-owned-${stamp}`;
+    const otherAlias = `e2e-usage-other-${stamp}`;
+
+    const userRes = await request.post(`${rootPath()}/user/new`, {
+      headers: { Authorization: `Bearer ${masterKey()}`, "Content-Type": "application/json" },
+      data: { user_email: email, user_role: "internal_user", auto_create_key: false },
+    });
+    expect(userRes.ok(), `POST /user/new failed (${userRes.status()})`).toBe(true);
+    const userId = (await userRes.json()).user_id as string;
+
+    const owned = await createVirtualKey(request, { key_alias: ownedAlias, user_id: userId });
+    const other = await createVirtualKey(request, { key_alias: otherAlias });
+    await sendTraffic(request, owned.key, CHAT_MODEL_A, 1, ownedAlias);
+    await sendTraffic(request, other.key, CHAT_MODEL_A, 1, otherAlias);
+    await waitForKeyInDailyActivity(request, owned.token);
+    await waitForKeyInDailyActivity(request, other.token);
+
+    await openUsageTab(page, "Key Activity");
+    await expect(entityCard(page, "Key Activity", otherAlias)).toBeVisible({ timeout: 30_000 });
+
+    await page.getByRole("combobox", { name: "Search users by email" }).click();
+    await page.keyboard.type(email);
+    await page
+      .getByRole("option", { name: new RegExp(email) })
+      .first()
+      .click();
+
+    // The filter earns its place only by dropping the other key; the owned key showing up
+    // proves nothing on a page that already listed every key.
+    await expect(entityCard(page, "Key Activity", otherAlias)).toHaveCount(0, { timeout: 30_000 });
+    await expect(entityCard(page, "Key Activity", ownedAlias)).toBeVisible({ timeout: 20_000 });
+  });
+});

From a3e115f4cd17a6b46a0f2b153cee24ddd525fb30 Mon Sep 17 00:00:00 2001
From: yuneng-jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:39:43 -0700
Subject: [PATCH 066/113] fix(ui): render the guardrail garden detail page with
 theme tokens (#39131)

The page set its headings, table borders, sidebar labels and tag pills
inline with a fixed light palette (#202124, #5f6368, #dadce0, #f8f9fa,
#fff), so in dark mode it drew dark text on hardcoded white surfaces.

Move those to the foreground/muted/border/card/info tokens, matching
the back link and Create Guardrail button that already used them.
---
 .../_components/guardrail_garden_detail.tsx   | 103 ++++++++----------
 1 file changed, 45 insertions(+), 58 deletions(-)

diff --git a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
index 0a0f70b6bc2..dda56a06ab1 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/guardrails/_components/guardrail_garden_detail.tsx
@@ -1,6 +1,7 @@
 import React, { useState } from "react";
 import { ArrowLeft } from "lucide-react";
 import { Button } from "@/components/ui/button";
+import { cn } from "@/lib/cva.config";
 import AddGuardrailForm from "./add_guardrail_form";
 import { Logo } from "@/components/molecules/logo/Logo";
 import { GUARDRAIL_PRESETS } from "./guardrail_garden_configs";
@@ -40,7 +41,7 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
   const tabs = [{ key: "overview", label: "Overview" }, ...(card.eval ? [{ key: "eval", label: "Eval Results" }] : [])];
 
   return (
-    <div style={{ maxWidth: 960, margin: "0 auto" }}>
+    <div className="mx-auto max-w-[960px]">
       {/* Back link */}
       <div
         onClick={onBack}
@@ -51,12 +52,12 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
       </div>
 
       {/* ── Header block (Vertex-style) ── */}
-      <div style={{ display: "flex", alignItems: "center", gap: 16, marginBottom: 8 }}>
+      <div className="mb-2 flex items-center gap-4">
         <Logo src={card.logo} label={card.name} className="w-10 h-10 rounded-lg object-contain shrink-0" />
-        <h1 style={{ fontSize: 28, fontWeight: 400, color: "#202124", margin: 0, lineHeight: 1.2 }}>{card.name}</h1>
+        <h1 className="m-0 text-[28px] font-normal leading-tight text-foreground">{card.name}</h1>
       </div>
 
-      <p style={{ fontSize: 14, color: "#5f6368", margin: "0 0 20px 0", lineHeight: 1.6 }}>{card.description}</p>
+      <p className="m-0 mb-5 text-sm leading-relaxed text-muted-foreground">{card.description}</p>
 
       {/* Action buttons — outlined style like Vertex */}
       <div className="mb-8 flex gap-2.5">
@@ -66,21 +67,18 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
       </div>
 
       {/* ── Tab bar ──────────────────────────────────── */}
-      <div style={{ borderBottom: "1px solid #dadce0", marginBottom: 28 }}>
-        <div style={{ display: "flex", gap: 0 }}>
+      <div className="mb-7 border-b border-border">
+        <div className="flex">
           {tabs.map((tab) => (
             <div
               key={tab.key}
               onClick={() => setActiveTab(tab.key)}
-              style={{
-                padding: "12px 20px",
-                fontSize: 14,
-                color: activeTab === tab.key ? "#1a73e8" : "#5f6368",
-                borderBottom: activeTab === tab.key ? "3px solid #1a73e8" : "3px solid transparent",
-                cursor: "pointer",
-                fontWeight: activeTab === tab.key ? 500 : 400,
-                marginBottom: -1,
-              }}
+              className={cn(
+                "-mb-px cursor-pointer border-b-[3px] px-5 py-3 text-sm",
+                activeTab === tab.key
+                  ? "border-info font-medium text-info"
+                  : "border-transparent font-normal text-muted-foreground",
+              )}
             >
               {tab.label}
             </div>
@@ -90,31 +88,27 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
 
       {/* ── Tab content ──────────────────────────────── */}
       {activeTab === "overview" && (
-        <div style={{ display: "flex", gap: 64 }}>
+        <div className="flex gap-16">
           {/* Left column — overview + details table */}
-          <div style={{ flex: 1, minWidth: 0 }}>
-            <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 12px 0" }}>Overview</h2>
-            <p style={{ fontSize: 14, color: "#3c4043", lineHeight: 1.7, margin: "0 0 32px 0" }}>{card.description}</p>
+          <div className="min-w-0 flex-1">
+            <h2 className="m-0 mb-3 text-lg font-normal text-foreground">Overview</h2>
+            <p className="m-0 mb-8 text-sm leading-[1.7] text-foreground">{card.description}</p>
 
-            <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 4px 0" }}>Guardrail Details</h2>
-            <p style={{ fontSize: 13, color: "#5f6368", margin: "0 0 16px 0" }}>Details are as follows</p>
+            <h2 className="m-0 mb-1 text-lg font-normal text-foreground">Guardrail Details</h2>
+            <p className="m-0 mb-4 text-[13px] text-muted-foreground">Details are as follows</p>
 
-            <table style={{ width: "100%", borderCollapse: "collapse", fontSize: 14 }}>
+            <table className="w-full border-collapse text-sm">
               <thead>
-                <tr style={{ borderBottom: "1px solid #dadce0" }}>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500, width: 200 }}>
-                    Property
-                  </th>
-                  <th style={{ textAlign: "left", padding: "12px 0", color: "#5f6368", fontWeight: 500 }}>
-                    {card.name}
-                  </th>
+                <tr className="border-b border-border">
+                  <th className="w-50 py-3 text-left font-medium text-muted-foreground">Property</th>
+                  <th className="py-3 text-left font-medium text-muted-foreground">{card.name}</th>
                 </tr>
               </thead>
               <tbody>
                 {detailRows.map((row, i) => (
-                  <tr key={i} style={{ borderBottom: "1px solid #f1f3f4" }}>
-                    <td style={{ padding: "12px 0", color: "#3c4043" }}>{row.property}</td>
-                    <td style={{ padding: "12px 0", color: "#202124" }}>{row.value}</td>
+                  <tr key={i} className="border-b border-border">
+                    <td className="py-3 text-foreground">{row.property}</td>
+                    <td className="py-3 text-foreground">{row.value}</td>
                   </tr>
                 ))}
               </tbody>
@@ -122,37 +116,30 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
           </div>
 
           {/* Right column — metadata sidebar like Vertex */}
-          <div style={{ width: 240, flexShrink: 0 }}>
+          <div className="w-60 shrink-0">
             {/* Guardrail ID */}
-            <div style={{ marginBottom: 28 }}>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Guardrail ID</div>
-              <div style={{ fontSize: 13, color: "#202124", wordBreak: "break-all" }}>litellm/{card.id}</div>
+            <div className="mb-7">
+              <div className="mb-1 text-xs text-muted-foreground">Guardrail ID</div>
+              <div className="break-all text-[13px] text-foreground">litellm/{card.id}</div>
             </div>
 
             {/* Type */}
-            <div style={{ marginBottom: 28 }}>
-              <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 4 }}>Type</div>
-              <div style={{ fontSize: 13, color: "#202124" }}>
+            <div className="mb-7">
+              <div className="mb-1 text-xs text-muted-foreground">Type</div>
+              <div className="text-[13px] text-foreground">
                 {card.category === "litellm" ? "Content Filter" : "Partner"}
               </div>
             </div>
 
             {/* Tags — pill style like Vertex */}
             {card.tags.length > 0 && (
-              <div style={{ marginBottom: 28 }}>
-                <div style={{ fontSize: 12, color: "#5f6368", marginBottom: 8 }}>Tags</div>
-                <div style={{ display: "flex", flexWrap: "wrap", gap: 6 }}>
+              <div className="mb-7">
+                <div className="mb-2 text-xs text-muted-foreground">Tags</div>
+                <div className="flex flex-wrap gap-1.5">
                   {card.tags.map((tag) => (
                     <span
                       key={tag}
-                      style={{
-                        fontSize: 12,
-                        padding: "4px 12px",
-                        borderRadius: 16,
-                        border: "1px solid #dadce0",
-                        color: "#3c4043",
-                        backgroundColor: "#fff",
-                      }}
+                      className="rounded-2xl border border-border bg-card px-3 py-1 text-xs text-foreground"
                     >
                       {tag}
                     </span>
@@ -166,19 +153,19 @@ const GuardrailDetailView: React.FC<GuardrailDetailViewProps> = ({ card, onBack,
 
       {activeTab === "eval" && (
         <div>
-          <h2 style={{ fontSize: 18, fontWeight: 400, color: "#202124", margin: "0 0 16px 0" }}>Eval Results</h2>
-          <table style={{ width: "100%", maxWidth: 560, borderCollapse: "collapse", fontSize: 14 }}>
+          <h2 className="m-0 mb-4 text-lg font-normal text-foreground">Eval Results</h2>
+          <table className="w-full max-w-[560px] border-collapse text-sm">
             <thead>
-              <tr style={{ backgroundColor: "#f8f9fa", borderBottom: "1px solid #dadce0" }}>
-                <th style={{ textAlign: "left", padding: "12px 16px", color: "#5f6368", fontWeight: 500 }}>Metric</th>
-                <th style={{ textAlign: "left", padding: "12px 16px", color: "#5f6368", fontWeight: 500 }}>Value</th>
+              <tr className="border-b border-border bg-muted">
+                <th className="px-4 py-3 text-left font-medium text-muted-foreground">Metric</th>
+                <th className="px-4 py-3 text-left font-medium text-muted-foreground">Value</th>
               </tr>
             </thead>
             <tbody>
               {evalRows.map((row, i) => (
-                <tr key={i} style={{ borderBottom: "1px solid #f1f3f4" }}>
-                  <td style={{ padding: "12px 16px", color: "#3c4043" }}>{row.metric}</td>
-                  <td style={{ padding: "12px 16px", color: "#202124", fontWeight: 500 }}>{row.value}</td>
+                <tr key={i} className="border-b border-border">
+                  <td className="px-4 py-3 text-foreground">{row.metric}</td>
+                  <td className="px-4 py-3 font-medium text-foreground">{row.value}</td>
                 </tr>
               ))}
             </tbody>

From eb53639ecbd7af0c59e1ef225af679c973da1051 Mon Sep 17 00:00:00 2001
From: Yuneng Jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:42:27 -0700
Subject: [PATCH 067/113] test(ui): pick select options by role instead of by
 text

Clicking a Base UI select entry found by text or by a title attribute is a
race. The text node exists one render before the popup finishes entering,
and until then the positioner still carries pointer-events: none, so
user-event refuses the click and the test throws. Querying by role only
matches once the popup is exposed to the accessibility tree, which is after
that window closes.

Route the 37 remaining select interactions through chooseSelectOption, which
does the role query. Instrumenting the converted files shows the text query
resolving while the popup was still pointer-blocked on 6 of 41 samples; the
role query was never blocked.

Seven files kept their text queries because their popup entries carry no
accessible role, so there is nothing to query by.
---
 .../add_agent_form.integration.test.tsx         |  4 ++--
 .../budget_modal.integration.test.tsx           |  7 +++----
 .../edit_budget_modal.integration.test.tsx      |  4 ++--
 .../CoordinationRedisTypeSelector.test.tsx      |  4 ++--
 .../_components/ShadowEvalSection.test.tsx      | 10 ++++------
 .../_components/ToolTestPanel.test.tsx          |  4 ++--
 .../_components/policy_test_panel.test.tsx      |  4 ++--
 .../prompts/_components/index.test.tsx          | 10 ++++------
 .../components/TeamsPage/TeamsTable.test.tsx    |  5 ++---
 .../VirtualKeysPage/VirtualKeysTable.test.tsx   | 11 ++++-------
 .../add_pass_through.integration.test.tsx       |  5 ++---
 .../KeyLifecycleSettings.test.tsx               | 17 ++++++-----------
 .../common_components/ModelSelector.test.tsx    |  4 ++--
 .../shared/DataTable/DataTable.test.tsx         | 16 ++++++----------
 .../DataTable/DataTableSortHeader.test.tsx      | 10 ++++------
 .../shared/PaginatedSearchSelect.test.tsx       | 10 ++++------
 .../src/components/shared/SearchSelect.test.tsx |  4 ++--
 .../view_logs/RequestLogsFilters.test.tsx       |  5 ++---
 ui/litellm-dashboard/tests/test-utils.tsx       | 13 ++++++++-----
 19 files changed, 63 insertions(+), 84 deletions(-)

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)/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/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_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/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/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/tests/test-utils.tsx b/ui/litellm-dashboard/tests/test-utils.tsx
index 162b8a3df7b..31af51f3f32 100644
--- a/ui/litellm-dashboard/tests/test-utils.tsx
+++ b/ui/litellm-dashboard/tests/test-utils.tsx
@@ -45,19 +45,22 @@ const pointerBlocked = (element: HTMLElement): boolean => {
 };
 
 /**
- * Opens a Base UI Select and picks an option by its accessible name.
+ * Opens a Base UI popup and picks an entry 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.
+ * Querying the entry by text or by a title attribute matches the moment the node exists, which is
+ * one render before the popup finishes entering. Until then the positioner still carries
+ * `pointer-events: none` and user-event refuses to click, so that shape is a race a fast machine
+ * loses. The role query only matches once the popup is open to the accessibility tree, which is
+ * what makes this wait correct rather than lucky.
  */
 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);
 };

From 4567fc784c6fe43acd41a6db32c834465b8d653d Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:45:23 -0700
Subject: [PATCH 068/113] fix: close non-message open items as incomplete when
 a stream is blocked

---
 .../guardrail_translation/handler.py          | 38 +++++++++++++++---
 ...test_openai_responses_guardrail_handler.py | 40 +++++++++++++++++++
 2 files changed, 73 insertions(+), 5 deletions(-)

diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 6295df1dbfa..14759f6475e 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -30,13 +30,14 @@ Output: response.output is List[GenericResponseOutputItem] where each has:
 
 import time
 import uuid
-from collections.abc import Sequence
+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
@@ -1050,6 +1051,7 @@ class _OpenItemState:
     content_index: int
     text: str
     part_open: bool
+    payload: object
 
 
 def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | None:
@@ -1070,7 +1072,9 @@ def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | Non
     if not open_added:
         return None
     output_index, item_payload = open_added[-1]
-    item_id: Final = stream_item_field(item_payload, "id") if item_payload is not None else None
+    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")
@@ -1105,18 +1109,42 @@ def _open_item_state(responses_so_far: Sequence[object]) -> _OpenItemState | Non
         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. The closing text is exactly what the client has received
-    for that item so far."""
+    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,
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 d6e56f0faf1..49f4e9df7c9 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
@@ -1356,6 +1356,46 @@ class TestBuildBlockSseChunks:
         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 = [

From 0ec3e936b73a9ebc4445c025a1e4d15a940e29de Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 12:47:26 -0700
Subject: [PATCH 069/113] fix(cost): inherit the backend's full price structure
 for off-peak-only deployments

Copying only the flat token rates dropped threshold, tiered, service-tier,
cache, character, and per-second rates from peak-hour billing once cost
lookup switched to the deployment entry, and get_model_info synthesizes
zero flat rates for backends without one, which would have marked
tiered-only backends explicitly priced free. Copy every price-bearing
field instead, deep-copied, rejecting the synthesized zeros the way
_inherit_builtin_tiered_output_rate already does.
---
 litellm/router.py                             | 28 ++++++---
 .../test_router_model_cost_isolation.py       | 61 +++++++++++++++++++
 2 files changed, 80 insertions(+), 9 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index f3563d9c387..dd1cb51d9af 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -8169,16 +8169,23 @@ class Router:
         backend_model: str,
         custom_llm_provider: str | None,
     ) -> None:
-        """Fill missing base token rates on a deployment entry that only sets
+        """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. User-specified rates always win; no-op when
-        any base pricing field is already set or the backend model has no
-        canonical entry.
+        never receive the discount. Every price-bearing backend field is
+        copied, not just the flat token rates: threshold, tiered, service-tier,
+        cache, character, and per-second rates all carry over, so peak-hour
+        billing through the deployment entry matches the shared backend entry
+        exactly. Values are deep-copied to keep the builtin entry isolated, and
+        a flat token rate ``get_model_info`` synthesized as zero for a backend
+        without one is rejected, like ``_inherit_builtin_tiered_output_rate``
+        does, so a tiered-only backend is never marked explicitly priced free.
+        User-specified rates 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
@@ -8191,11 +8198,14 @@ class Router:
             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
-        for field in ("input_cost_per_token", "output_cost_per_token"):
-            if model_info.get(field) is None:
-                backend_value = backend_info.get(field)
-                if backend_value is not None:
-                    model_info[field] = backend_value
+        for field, backend_value in backend_info.items():
+            if "cost" not in field and field != "tiered_pricing":
+                continue
+            if model_info.get(field) is not None or backend_value is None:
+                continue
+            if field in ("input_cost_per_token", "output_cost_per_token") and not backend_value:
+                continue
+            model_info[field] = copy.deepcopy(backend_value)
 
     @staticmethod
     def _inherit_builtin_tiered_output_rate(
diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index c8adc0af431..a1040e972f2 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -564,6 +564,67 @@ def test_inherit_builtin_base_rates_for_off_peak_fills_missing_rates():
     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_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.

From fd72a39b1b6dd15851f50cbd34f38ccd6a9b55c4 Mon Sep 17 00:00:00 2001
From: Yuneng Jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 12:54:07 -0700
Subject: [PATCH 070/113] revert: default the proxy back to the v1 migration
 resolver

This reverts merge commit 2b1bd208349acf06967eeb151525f65942dd51bf (#31125)

Two CircleCI jobs on the staging-to-main promotion went red the moment
that PR landed. proxy_multi_instance_tests boots two proxies against one
database, and both now race the same migration:

  Error: P3018 A migration failed to apply
  Database error code: 40P01, deadlock detected
  Process 73 waits for ShareLock on virtual transaction 4/11;
  blocked by process 75. Process 75 waits for ExclusiveLock on
  advisory lock [16384,0,72707369,1]; blocked by process 73

Neither proxy comes up, so the job times out after 300s waiting on
localhost:4000. The same wait took 36.5s on the last green run

Timeline: #31125 merged at 18:46:14Z and the failing run started at
18:49:59Z. The merge commit is not an ancestor of the last green
revision (194a3cc) and is an ancestor of the first failing one
(01de2837)

The v2 resolver was meant to avoid exactly this class of contention, so
the deadlock looks like a bug in it rather than a reason to abandon it.
Putting the default back to v1 buys time to fix it without holding up
the release
---
 .circleci/config.yml                          |  15 +-
 CLAUDE.md                                     |   2 +-
 .../litellm_proxy_extras/utils.py             | 132 +---
 litellm-proxy-extras/tests/__init__.py        |   0
 .../tests/test_setup_database_fail_fast.py    | 242 ++++++++
 litellm/proxy/proxy_cli.py                    |  30 +-
 .../test_setup_database_fail_fast.py          | 571 ------------------
 .../test_basic_python_version.py              |  14 +-
 tests/test_litellm/proxy/test_proxy_cli.py    |  39 +-
 9 files changed, 303 insertions(+), 742 deletions(-)
 create mode 100644 litellm-proxy-extras/tests/__init__.py
 create mode 100644 litellm-proxy-extras/tests/test_setup_database_fail_fast.py
 delete mode 100644 tests/litellm-proxy-extras/test_setup_database_fail_fast.py

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/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/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/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py
index 86f6853a625..8ac63ba25c9 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",
 )
@@ -1311,11 +1310,10 @@ 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 +1321,10 @@ 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/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/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/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py
index 5e2dd358d75..6ea6f208bb5 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

From 3e3e4d6970bfcb0f395cf9786bfc6a916b31e462 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 20:01:03 +0000
Subject: [PATCH 071/113] fix(anthropic): use native structured output for
 claude-fable-5-1 on Vertex AI and Bedrock Invoke

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/llms/anthropic/chat/transformation.py |  2 +-
 litellm/llms/anthropic/common_utils.py        |  6 +++-
 .../anthropic_claude3_transformation.py       | 10 +++++--
 .../anthropic/transformation.py               | 15 ++++++----
 ...odel_prices_and_context_window_backup.json |  3 ++
 model_prices_and_context_window.json          |  3 ++
 .../test_anthropic_chat_transformation.py     | 30 +++++++++++++++++++
 ...ations_anthropic_claude3_transformation.py | 27 +++++++++++++++++
 ...partner_models_anthropic_transformation.py | 25 ++++++++++++++++
 9 files changed, 110 insertions(+), 11 deletions(-)

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/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
index 8e709349400..7254417ce47 100644
--- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
+++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude3_transformation.py
@@ -74,10 +74,14 @@ 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"
 
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 1b2001cdadd..241d1d252b2 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -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,
@@ -44132,6 +44133,7 @@
         "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,
@@ -44202,6 +44204,7 @@
         "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/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 1b2001cdadd..241d1d252b2 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -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,
@@ -44132,6 +44133,7 @@
         "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,
@@ -44202,6 +44204,7 @@
         "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/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/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..6b87b67d925 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 +643,30 @@ 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_uses_native_path(local_model_cost_map, model):
+    """Regression: Fable 5.1 rejects forced tool use, so invoke must skip the
+    tool-based structured-output stub and emit ``output_format`` instead of 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" in result
+    assert "tool_choice" not in result
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

From 529ac12ba5850fc097877dfd1e9d56d503fdbed0 Mon Sep 17 00:00:00 2001
From: Yuneng Jiang <yuneng@berri.ai>
Date: Tue, 1 Sep 2026 13:01:46 -0700
Subject: [PATCH 072/113] test(ui): drop the helper docblock

The repo does not take explanatory comments. The reason the helper queries by
role lives in the commit that introduced it and in the PR description.
---
 ui/litellm-dashboard/tests/test-utils.tsx | 9 ---------
 1 file changed, 9 deletions(-)

diff --git a/ui/litellm-dashboard/tests/test-utils.tsx b/ui/litellm-dashboard/tests/test-utils.tsx
index 31af51f3f32..553726faff0 100644
--- a/ui/litellm-dashboard/tests/test-utils.tsx
+++ b/ui/litellm-dashboard/tests/test-utils.tsx
@@ -44,15 +44,6 @@ const pointerBlocked = (element: HTMLElement): boolean => {
   return false;
 };
 
-/**
- * Opens a Base UI popup and picks an entry by its accessible name.
- *
- * Querying the entry by text or by a title attribute matches the moment the node exists, which is
- * one render before the popup finishes entering. Until then the positioner still carries
- * `pointer-events: none` and user-event refuses to click, so that shape is a race a fast machine
- * loses. The role query only matches once the popup is open to the accessibility tree, which is
- * what makes this wait correct rather than lucky.
- */
 export const chooseSelectOption = async (
   user: Pick<ReturnType<typeof userEvent.setup>, "click">,
   trigger: HTMLElement,

From 60de5468d748c576b49455391dce897d1e5e800f Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 13:05:25 -0700
Subject: [PATCH 073/113] fix(cost): inherit the backend's raw cost map entry
 for off-peak-only deployments

Filtering copied fields by name dropped companion billing rules like
web_search_billing_unit and the regional uplift multipliers, so grounding
and uplifts billed differently through the deployment entry. Copy the
backend's raw litellm.model_cost entry wholesale instead, which also
removes the synthesized-zero special case since the raw entry only holds
real values.
---
 litellm/router.py                             | 32 ++++++++++---------
 .../test_router_model_cost_isolation.py       | 24 ++++++++++++++
 2 files changed, 41 insertions(+), 15 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index dd1cb51d9af..c50fab5fe0f 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -8176,16 +8176,19 @@ class Router:
         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. Every price-bearing backend field is
-        copied, not just the flat token rates: threshold, tiered, service-tier,
-        cache, character, and per-second rates all carry over, so peak-hour
-        billing through the deployment entry matches the shared backend entry
-        exactly. Values are deep-copied to keep the builtin entry isolated, and
-        a flat token rate ``get_model_info`` synthesized as zero for a backend
-        without one is rejected, like ``_inherit_builtin_tiered_output_rate``
-        does, so a tiered-only backend is never marked explicitly priced free.
-        User-specified rates always win; no-op when any base pricing field is
-        already set or the backend model has no canonical entry.
+        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
@@ -8198,13 +8201,12 @@ class Router:
             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
-        for field, backend_value in backend_info.items():
-            if "cost" not in field and field != "tiered_pricing":
-                continue
+        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
-            if field in ("input_cost_per_token", "output_cost_per_token") and not backend_value:
-                continue
             model_info[field] = copy.deepcopy(backend_value)
 
     @staticmethod
diff --git a/tests/test_litellm/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index a1040e972f2..7b7a962bf00 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -595,6 +595,30 @@ def test_inherit_builtin_base_rates_for_off_peak_carries_threshold_rates():
     )
 
 
+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

From d568bbe58d5d94929661af951270150a46560df2 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 20:19:46 +0000
Subject: [PATCH 074/113] fix(bedrock): use tool fallback without forced
 tool_choice for claude-fable-5-1 structured output

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../bedrock/chat/converse_transformation.py   |  1 +
 .../anthropic_claude3_transformation.py       | 12 +++++++
 ...odel_prices_and_context_window_backup.json |  8 ++---
 model_prices_and_context_window.json          |  8 ++---
 ...ations_anthropic_claude3_transformation.py |  9 ++---
 .../chat/test_converse_transformation.py      | 33 +++++++++++++++++++
 6 files changed, 59 insertions(+), 12 deletions(-)

diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index 6f99f572686..7fefeaeaf04 100644
--- a/litellm/llms/bedrock/chat/converse_transformation.py
+++ b/litellm/llms/bedrock/chat/converse_transformation.py
@@ -1073,6 +1073,7 @@ 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)
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 7254417ce47..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,
 )
@@ -105,6 +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/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 241d1d252b2..55618d9f772 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",
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index 241d1d252b2..55618d9f772 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",
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 6b87b67d925..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
@@ -649,9 +649,9 @@ def test_bedrock_chat_invoke_drop_params_still_inlines_for_non_native(local_mode
     "model",
     ["us.anthropic.claude-fable-5-1", "anthropic.claude-fable-5-1"],
 )
-def test_bedrock_chat_invoke_fable_5_1_response_format_uses_native_path(local_model_cost_map, model):
-    """Regression: Fable 5.1 rejects forced tool use, so invoke must skip the
-    tool-based structured-output stub and emit ``output_format`` instead of a
+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={
@@ -668,5 +668,6 @@ def test_bedrock_chat_invoke_fable_5_1_response_format_uses_native_path(local_mo
         drop_params=False,
     )
 
-    assert "output_format" in result
+    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_converse_transformation.py b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
index 37ca801a7a7..4f53d3481de 100644
--- a/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
+++ b/tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py
@@ -6497,6 +6497,39 @@ 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
 ):

From f4347f25de0917e2d3e316226bcac49f7767cf83 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 13:29:12 -0700
Subject: [PATCH 075/113] test: exempt MockTransport request-shape embedding
 tests from VCR replay

---
 tests/llm_translation/conftest.py | 6 +++++-
 tests/local_testing/conftest.py   | 1 +
 2 files changed, 6 insertions(+), 1 deletion(-)

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/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",
 )
 
 

From 6a9dcb5ce65c9c34e37245cd8f5937fa7e927d64 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 13:29:12 -0700
Subject: [PATCH 076/113] test: allow dashscope domain in qwen alias default
 api_base check

---
 tests/local_testing/test_get_llm_provider.py | 5 +++++
 1 file changed, 5 insertions(+)

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", "")
 
 

From cdb1245e7419fa8b0294da3946cbad68b3d567d5 Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Tue, 1 Sep 2026 13:30:02 -0700
Subject: [PATCH 077/113] fix(s3): bound s3 object keys and download filenames
 for long Responses API ids (#39164)

* fix(s3): bound object keys and download filenames to s3 limits

Long OpenAI-compatible Responses API ids pushed the s3 object key past s3's
1024 UTF-8 byte cap, so the PUT failed with a 400 and the log record was
dropped. Keys that still fit are unchanged, byte for byte. An oversized one
now keeps a readable head of the file name and appends the sha256 of the full
name. A configured path/alias prefix that is long enough to overflow on its
own keeps whole leading path segments, so a prefix-scoped IAM policy or
lifecycle rule still matches, and ends in a short digest of the full
configured value so two operators do not land in the same folder.

The Content-Disposition filename carried the same unbounded id and hit s3's
2048 byte metadata-header cap, so the upload still failed with
MetadataTooLarge once the key was bounded. It is bounded the same way, head
plus digest, so two records downloaded from the console stay distinct files.

The full response id stays in the uploaded JSON payload.

* fix(s3): keep the configured prefix whole and spend the whole key budget

Shorten the response id first and only trim the operator's configured prefix
when the prefix itself is what does not fit, so prefix scoped IAM policies and
lifecycle rules keep matching. Trim by bytes rather than whole segments so the
longest possible string prefix survives, and route the audit log key through
the same shared builder.

* chore(s3): trim the comments and docstrings the review flagged

Keep the two external facts that are not visible from the code, the 1024 byte
object key cap and the 2048 byte metadata header cap, and drop the rest.
---
 litellm/constants.py                          |   6 +
 litellm/integrations/s3.py                    |  81 ++++-
 litellm/integrations/s3_v2.py                 |  20 +-
 tests/test_litellm/integrations/test_s3.py    |  42 ++-
 tests/test_litellm/integrations/test_s3_v2.py | 288 ++++++++++++++++++
 5 files changed, 409 insertions(+), 28 deletions(-)

diff --git a/litellm/constants.py b/litellm/constants.py
index b9bea466247..9a50797f517 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))
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/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)
 # --------------------------------------------------------------

From aab9abdd1de335d27d06da8796a99ac93ad3493f Mon Sep 17 00:00:00 2001
From: Yassin Kortam <yassin@berri.ai>
Date: Tue, 1 Sep 2026 13:46:18 -0700
Subject: [PATCH 078/113] fix: keep litellm_credential_name from LiteLLM Params
 JSON and gate stored credential attach to proxy admins (#39047)

* fix(ui): keep litellm_credential_name from LiteLLM Params JSON when no credential is selected

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(ui): drop null litellm_credential_name from AddModelPanel payload fixture

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(ui): validate JSON litellm_credential_name against accessible credentials

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): enforce proxy-admin-only credential attachment on model create/update

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): raise ProxyException for unauthorized credential attach and gate /model/update

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* refactor(proxy): fold credential-change detection into can_user_attach_credential to satisfy complexity budget

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): decrypt stored credential name before unchanged-credential comparison

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): cover credential attach rejection on add_new_model and patch_model

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(proxy): annotate proxy-global patches with test-quality suppressions

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../model_management_endpoints.py             |  48 ++++++-
 .../test_model_management_endpoints.py        | 126 ++++++++++++++++++
 .../panels/AddModelPanel.integration.test.tsx |   1 -
 .../handle_add_model_submit.test.tsx          |  30 ++++-
 .../add_model/handle_add_model_submit.tsx     |   9 +-
 5 files changed, 208 insertions(+), 6 deletions(-)

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/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/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/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;
             }

From 28d0ac5339ba565d275242504e882853b6a33435 Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 14:06:14 -0700
Subject: [PATCH 079/113] fix(router): guard the declared-provider check for
 requests without a model

---
 .../litellm_core_utils/get_llm_provider_logic.py   |  4 ++--
 litellm/router_utils/pattern_match_deployments.py  |  6 +++---
 .../router_utils/test_pattern_match_deployments.py | 14 ++++++++++++++
 3 files changed, 19 insertions(+), 5 deletions(-)

diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py
index 5474725966c..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] if "/" in model else None)
+    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/router_utils/pattern_match_deployments.py b/litellm/router_utils/pattern_match_deployments.py
index 850ca74b387..0775e0a4039 100644
--- a/litellm/router_utils/pattern_match_deployments.py
+++ b/litellm/router_utils/pattern_match_deployments.py
@@ -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
 
@@ -221,9 +221,9 @@ class PatternMatchRouter:
         return self.route(model) or self.route(f"{provider}/{model}")
 
     @staticmethod
-    def _resolved_provider(model: str) -> str | None:
+    def _resolved_provider(model: str | None) -> str | None:
         try:
-            return get_llm_provider(model=model)[1]
+            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
 
diff --git a/tests/test_litellm/router_utils/test_pattern_match_deployments.py b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
index af43644a305..795d448ef5f 100644
--- a/tests/test_litellm/router_utils/test_pattern_match_deployments.py
+++ b/tests/test_litellm/router_utils/test_pattern_match_deployments.py
@@ -53,6 +53,20 @@ def test_get_pattern_bare_provider_name_never_matches_that_providers_wildcard(mo
     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,

From 2de33555ea93e48bc0fd05e98bc6541c146b1809 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 14:08:40 -0700
Subject: [PATCH 080/113] style: run ruff format on fallback_event_handlers

---
 litellm/router_utils/fallback_event_handlers.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index 8c33bf1481f..934065aba6e 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -412,7 +412,9 @@ 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 = {k: v for k, v in kwargs.items() if k != "_target_order"}  # rebind-ok: next hop must not inherit the previous order target
+            kwargs = {
+                k: v for k, v in kwargs.items() if k != "_target_order"
+            }  # rebind-ok: next hop must not inherit the previous order target
             if isinstance(mg, str):
                 kwargs["model"] = mg
             elif isinstance(mg, dict):

From 558f42e304a00763d9dbd563f0e91d1b95435fc9 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 14:16:51 -0700
Subject: [PATCH 081/113] fix(proxy): default max_idle_connection_lifetime to
 60s on DB URLs (#39134)

* fix(proxy): default max_idle_connection_lifetime to 60s on DB URLs

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): regenerate schema.d.ts for database_max_idle_connection_lifetime

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): keep URL-pinned max_idle_connection_lifetime over config value

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/proxy/_types.py                       | 19 +++-
 litellm/proxy/db/db_url_settings.py           | 20 +++++
 litellm/proxy/proxy_cli.py                    | 19 ++--
 tests/test_litellm/proxy/test_proxy_cli.py    | 90 +++++++++++++++++++
 ui/litellm-dashboard/src/lib/http/schema.d.ts |  8 +-
 5 files changed, 146 insertions(+), 10 deletions(-)

diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py
index c549f48126e..e0a2097919b 100644
--- a/litellm/proxy/_types.py
+++ b/litellm/proxy/_types.py
@@ -2436,9 +2436,22 @@ 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/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/proxy_cli.py b/litellm/proxy/proxy_cli.py
index 8ac63ba25c9..23932ba7c8c 100644
--- a/litellm/proxy/proxy_cli.py
+++ b/litellm/proxy/proxy_cli.py
@@ -1225,6 +1225,7 @@ def run_server(
         if os.getenv("DATABASE_URL", None) is not None or os.getenv("DIRECT_URL", None) is not None:
             from litellm.proxy.db.db_url_settings import (
                 add_missing_query_params,
+                idle_lifetime_params,
                 reader_shareable_params,
                 unsupported_db_scheme,
                 unsupported_db_scheme_message,
@@ -1253,6 +1254,9 @@ def run_server(
                     disable_prepared_statements=db_disable_prepared_statements,
                     extra_params=db_extra_connection_params,
                 )
+                lifetime_params: Final = idle_lifetime_params(
+                    general_settings.get("database_max_idle_connection_lifetime")
+                )
                 if os.getenv("DATABASE_URL", None) is not None:
                     database_url = get_secret("DATABASE_URL", default_value=None)
                     resolved_url: Final[str | None] = str(database_url) if database_url else None
@@ -1270,11 +1274,11 @@ def run_server(
                         writer_url,
                         connection_url_params,
                     )
-                    os.environ["DATABASE_URL"] = modified_url
+                    os.environ["DATABASE_URL"] = add_missing_query_params(modified_url, lifetime_params)
                 if os.getenv("DIRECT_URL", None) is not None:
                     database_url = os.getenv("DIRECT_URL")
                     modified_url = append_query_params(database_url, connection_url_params)
-                    os.environ["DIRECT_URL"] = modified_url
+                    os.environ["DIRECT_URL"] = add_missing_query_params(modified_url, lifetime_params)
                 # The reader pool is a real pool against the same configured cap, so it
                 # gets the allowlisted pool params. Schema-affecting ones, including any
                 # the operator smuggled in through database_extra_connection_params, stay
@@ -1288,10 +1292,13 @@ def run_server(
                         db_lock_timeout,
                     )
                     os.environ["DATABASE_URL_READ_REPLICA"] = add_missing_query_params(
-                        _with_query_value(read_replica_url, "options", reader_options)
-                        if reader_options
-                        else read_replica_url,
-                        reader_shareable_params(connection_url_params),
+                        add_missing_query_params(
+                            _with_query_value(read_replica_url, "options", reader_options)
+                            if reader_options
+                            else read_replica_url,
+                            reader_shareable_params(connection_url_params),
+                        ),
+                        lifetime_params,
                     )
                 subprocess.run(["prisma"], capture_output=True)
                 is_prisma_runnable = True
diff --git a/tests/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py
index 6ea6f208bb5..3e70dee23b7 100644
--- a/tests/test_litellm/proxy/test_proxy_cli.py
+++ b/tests/test_litellm/proxy/test_proxy_cli.py
@@ -2452,6 +2452,96 @@ class TestReadReplicaConnectionParams:
         assert "DATABASE_URL_READ_REPLICA" not in captured
 
 
+class TestMaxIdleConnectionLifetimeDefault:
+    """The proxy defaults `max_idle_connection_lifetime` below common infra idle
+    timeouts so stale pooled connections are recycled instead of failing requests."""
+
+    def _config(self, tmp_path, general_settings):
+        config_path = tmp_path / "config.yaml"
+        config_path.write_text(yaml.dump({"model_list": [], "general_settings": general_settings}))
+        return str(config_path)
+
+    def test_default_applied_to_database_and_direct_url(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            direct_url="postgresql://t:t@localhost:5432/t",
+        )
+
+        for env_var in ("DATABASE_URL", "DIRECT_URL"):
+            query = urlparse.parse_qs(urlparse.urlparse(captured[env_var]).query)
+            assert query["max_idle_connection_lifetime"] == ["60"], env_var
+
+    def test_url_pinned_value_wins_over_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            database_url="postgresql://t:t@localhost:5432/t?max_idle_connection_lifetime=300",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["300"]
+
+    def test_url_pinned_value_wins_over_config_key(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            database_url="postgresql://t:t@localhost:5432/t?max_idle_connection_lifetime=300",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["300"]
+
+    def test_config_key_overrides_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["45"]
+
+    def test_extra_connection_params_override_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(
+                tmp_path,
+                {"database_extra_connection_params": {"max_idle_connection_lifetime": 120}},
+            ),
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL"]).query)
+        assert query["max_idle_connection_lifetime"] == ["120"]
+
+    def test_read_replica_gets_the_default(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {}),
+            read_replica_url="postgresql://t:t@reader:5432/t",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["60"]
+
+    def test_replica_pinned_value_wins(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            read_replica_url="postgresql://t:t@reader:5432/t?max_idle_connection_lifetime=200",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["200"]
+
+    def test_config_key_reaches_the_read_replica(self, tmp_path):
+        captured = _run_server_and_capture_urls(
+            self._config(tmp_path, {"database_max_idle_connection_lifetime": 45}),
+            read_replica_url="postgresql://t:t@reader:5432/t",
+        )
+
+        query = urlparse.parse_qs(urlparse.urlparse(captured["DATABASE_URL_READ_REPLICA"]).query)
+        assert query["max_idle_connection_lifetime"] == ["45"]
+
+    def test_idle_lifetime_params_prefers_configured_value(self):
+        from litellm.proxy.db.db_url_settings import idle_lifetime_params
+
+        assert dict(idle_lifetime_params(45)) == {"max_idle_connection_lifetime": 45}
+        assert dict(idle_lifetime_params(None)) == {"max_idle_connection_lifetime": 60}
+
+
 class TestTokenAuthCliFlags:
     """`--azure_postgresql_auth` has to reach the URL assembly the same way the env var does."""
 
diff --git a/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index e944062e15e..7316b4359cc 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -25435,9 +25435,15 @@ 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;
             /**

From c7212e7fe2062dc2e66b1eb25d9810b3e01e87c5 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 14:16:57 -0700
Subject: [PATCH 082/113] refactor(router): drop _target_order via pop to
 satisfy the mutable-collection budget

---
 litellm/router.py                               | 6 ++++--
 litellm/router_utils/fallback_event_handlers.py | 4 +---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index 6eadaaa9913..bc0b1280d12 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -2172,8 +2172,9 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **{k: v for k, v in kwargs.items() if k != "_target_order"},
+                **kwargs,
             }
+            input_kwargs.pop("_target_order", None)
             response: Final = litellm.completion(**input_kwargs)
             verbose_router_logger.info("litellm.completion(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -3193,8 +3194,9 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **{k: v for k, v in kwargs.items() if k != "_target_order"},
+                **kwargs,
             }
+            input_kwargs.pop("_target_order", None)
             input_kwargs.pop("silent_model", None)
             input_kwargs.pop("include_fallback_errors", None)
 
diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py
index 934065aba6e..d2842294a08 100644
--- a/litellm/router_utils/fallback_event_handlers.py
+++ b/litellm/router_utils/fallback_event_handlers.py
@@ -412,9 +412,7 @@ 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 = {
-                k: v for k, v in kwargs.items() if k != "_target_order"
-            }  # rebind-ok: next hop must not inherit the previous order target
+            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):

From 5767a2da0f6d28a07cf431fbd652678b3223867b Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Tue, 1 Sep 2026 14:34:14 -0700
Subject: [PATCH 083/113] fix(mcp): follow tools/list pagination from upstream
 servers (#39172)

* fix(mcp): follow tools/list pagination from upstream servers

Adopts BerriAI/litellm#32244 by Jupiter363 onto litellm_internal_staging
with merge conflicts resolved

* fix(mcp): degrade buggy pagination to partial results and bound the preview walk

A repeated nextCursor now returns the tools collected so far instead of
discarding every page with a RuntimeError, an empty-string cursor is treated
as terminal, load_mcp_tools shares the same pagination walk instead of
returning only the first page, and the tools/list preview is bounded by the
listing timeout instead of only the per-request timeout times the page cap

* fix(mcp): annotate deliberate rebind for the preview timeout scope

* fix(mcp): bound the shared pagination walk with an overall listing deadline

The per-request session read timeout restarts on every page, so direct SDK
callers of list_tools and load_mcp_tools could run up to the page cap with
no overall bound. The walk now returns the tools collected so far when
max(MCP_CLIENT_TIMEOUT, MCP_TOOL_LISTING_TIMEOUT) expires

* fix(mcp): let a per-server timeout extend the pagination deadline

MCPClient carries a per-server timeout that can exceed the global default;
list_tools now passes max(self.timeout, MCP_TOOL_LISTING_TIMEOUT) into the
shared walk so a deliberately slow server is not silently truncated at the
global deadline

* fix(mcp): honor per-server timeouts in the preview deadline and test the walk sessionless

The preview deadline now extends with the created client's own timeout, and
the pagination walk's cap, repeated-cursor, and empty-cursor cases are tested
directly against the helper instead of through patched SDK internals

* fix(mcp): forward the preview request's per-server timeout to the temporary server model

The tools preview built its temporary MCPServer without the request's
timeout field, so the client factory always fell back to the global
default and a per-server timeout could never extend the preview's
listing deadline (or its per-request timeout).
---
 litellm/constants.py                          |   1 +
 litellm/experimental_mcp_client/client.py     |  20 +-
 litellm/experimental_mcp_client/tools.py      |  74 ++++-
 .../mcp_server/rest_endpoints.py              |  32 +-
 tests/mcp_tests/test_mcp_client_unit.py       |  78 ++++-
 .../experimental_mcp_client/test_tools.py     | 130 ++++++++
 .../mcp_server/test_rest_endpoints.py         | 294 +++++++++++++++++-
 7 files changed, 601 insertions(+), 28 deletions(-)

diff --git a/litellm/constants.py b/litellm/constants.py
index 9a50797f517..172ee70fd57 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -136,6 +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.
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/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index 3efb6429326..2b89dba0e4f 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -4,10 +4,12 @@ from collections.abc import Awaitable, Callable, Mapping
 from datetime import datetime
 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,
@@ -86,8 +88,6 @@ 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,
@@ -1173,6 +1173,7 @@ 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 +1403,28 @@ 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/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/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/proxy/_experimental/mcp_server/test_rest_endpoints.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_rest_endpoints.py
index ef5631218f3..e36bef229f6 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
@@ -3021,9 +3299,7 @@ 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,

From ac964918c577f29efa30668f94380668a1ccbebc Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 14:34:48 -0700
Subject: [PATCH 084/113] fix(router): strip _target_order at every provider
 boundary via a shared helper

---
 litellm/router.py                             | 25 +++++----
 .../test_router_order_fallback.py             | 51 ++++++++++++-------
 2 files changed, 46 insertions(+), 30 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index bc0b1280d12..45fadcbab4a 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -558,6 +558,11 @@ RETRY_BREADCRUMB_EXCLUDED_KWARGS: Final = frozenset(
 )
 
 
+def _without_target_order(kwargs: Mapping[str, object]) -> Mapping[str, object]:
+    """Drop the router-internal order-fallback target so it never reaches a provider call."""
+    return MappingProxyType({k: v for k, v in kwargs.items() if k != "_target_order"})
+
+
 class Router:
     model_names: set = set()
     cache_responses: bool | None = False
@@ -2172,9 +2177,8 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **kwargs,
+                **_without_target_order(kwargs),
             }
-            input_kwargs.pop("_target_order", None)
             response: Final = litellm.completion(**input_kwargs)
             verbose_router_logger.info("litellm.completion(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
 
@@ -3194,9 +3198,8 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **kwargs,
+                **_without_target_order(kwargs),
             }
-            input_kwargs.pop("_target_order", None)
             input_kwargs.pop("silent_model", None)
             input_kwargs.pop("include_fallback_errors", None)
 
@@ -4072,7 +4075,7 @@ class Router:
                     "prompt": prompt,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
             self.success_calls[model_name] += 1
@@ -4132,7 +4135,7 @@ class Router:
                     "prompt": prompt,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
 
@@ -4236,7 +4239,7 @@ class Router:
                     "file": file,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
 
@@ -4889,7 +4892,7 @@ class Router:
             response_kwargs: Final = {
                 **data,
                 "caching": self.cache_responses,
-                **kwargs,
+                **_without_target_order(kwargs),
                 "model": model_name,
             }
             # Only set custom_llm_provider if it's not None
@@ -5339,7 +5342,7 @@ class Router:
                     **data,
                     "custom_llm_provider": custom_llm_provider,
                     "caching": self.cache_responses,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
 
@@ -5405,7 +5408,7 @@ class Router:
                     "input": input,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
             self.success_calls[model_name] += 1
@@ -5468,7 +5471,7 @@ class Router:
                     "input": input,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **kwargs,
+                    **_without_target_order(kwargs),
                 }
             )
 
diff --git a/tests/test_litellm/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index d74e0a6ffa4..042d724df0b 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -552,35 +552,48 @@ async def test_router_order_fallback_retries_keep_target_order():
     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
+
+
 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

From 4da12795fc5f90cd4e5e87fc61eb080c792b4355 Mon Sep 17 00:00:00 2001
From: mateo <mateo@berri.ai>
Date: Tue, 1 Sep 2026 21:50:45 +0000
Subject: [PATCH 085/113] fix: filter deployment default API key limits

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/types/utils.py                        |  2 +
 .../chat/test_anthropic_chat_handler.py       | 39 +++++++++++++++++++
 2 files changed, 41 insertions(+)

diff --git a/litellm/types/utils.py b/litellm/types/utils.py
index 3a0883b6607..5783a39b30c 100644
--- a/litellm/types/utils.py
+++ b/litellm/types/utils.py
@@ -3636,6 +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/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",

From af11db9fe571c9d10e9175ef58cceb0d6301f8d2 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 14:51:15 -0700
Subject: [PATCH 086/113] test(e2e): cover retry-on-timeout and the
 context-window fallback

Two P0 rows in the reliability coverage registry had no test.

reliability.retry.timeout.succeeds_within_retries gets a new file. The model
group is a pair: an always-timing-out deployment holding 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 via an allowed_fails_policy
of TimeoutErrorAllowedFails 0, and the retry falls through to the only
deployment left, so the outcome is a completion plus a reported retry with no
random first pick in the middle.

reliability.fallback.context_window.routes_to_fallback joins the existing
fallbacks spec. It registers a genuinely small-context OpenAI deployment, sends
a prompt past its limit so the provider refuses it on length, and reroutes with
context_window_fallbacks, which is the setting that handles that refusal rather
than plain fallbacks.

Both drive real provider calls through router_settings_override, so no config
change and no second proxy is needed. Reliability & Performance goes 16/36 to
18/36.

Claude-Session: https://claude.ai/code/session_01QvQzYztinxj8ZuD5YxbVdL
---
 tests/e2e/models.py                           |  2 +
 tests/e2e/router/reliability_support.py       | 46 ++++++++++++
 .../router/test_reliability_fallbacks_e2e.py  | 20 +++++
 .../router/test_reliability_retries_e2e.py    | 73 +++++++++++++++++++
 4 files changed, 141 insertions(+)
 create mode 100644 tests/e2e/router/test_reliability_retries_e2e.py

diff --git a/tests/e2e/models.py b/tests/e2e/models.py
index 6d9ccad9a24..b48a37f16ae 100644
--- a/tests/e2e/models.py
+++ b/tests/e2e/models.py
@@ -805,6 +805,7 @@ class LiteLLMParamsBody(BaseModel):
     mock_response: str | None = None
     timeout: float | None = None
     tpm: int | None = None
+    weight: int | None = None
 
 
 ModelMode = Literal["batch", "realtime", "image_generation"]
@@ -819,6 +820,7 @@ 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]})"
+        )

From 0b89c59be20b4407e586465b5bb94c87e71f2f74 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 15:02:01 -0700
Subject: [PATCH 087/113] fix(router): consume _target_order at deployment
 selection so it never reaches a provider

Reading _target_order with .get left it in the request kwargs after selection, and only
nine provider boundaries stripped it. _atext_completion and _aadapter_completion spread
the raw kwargs, so an order-2 hop on /completions sent _target_order upstream, which
real providers reject as an unknown argument. Popping at selection strips it for every
path in one place; the PR's retry-keeping test already passed with pop because each retry
hands the callee its own kwargs copy.

Claude-Session: https://claude.ai/code/session_01XKkTFa6g7Rmd6vtHL91GMn
---
 litellm/router.py                             | 27 ++++-----
 .../test_router_order_fallback.py             | 60 +++++++++++++++++++
 2 files changed, 71 insertions(+), 16 deletions(-)

diff --git a/litellm/router.py b/litellm/router.py
index 45fadcbab4a..c93c1753f0e 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -558,11 +558,6 @@ RETRY_BREADCRUMB_EXCLUDED_KWARGS: Final = frozenset(
 )
 
 
-def _without_target_order(kwargs: Mapping[str, object]) -> Mapping[str, object]:
-    """Drop the router-internal order-fallback target so it never reaches a provider call."""
-    return MappingProxyType({k: v for k, v in kwargs.items() if k != "_target_order"})
-
-
 class Router:
     model_names: set = set()
     cache_responses: bool | None = False
@@ -2177,7 +2172,7 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **_without_target_order(kwargs),
+                **kwargs,
             }
             response: Final = litellm.completion(**input_kwargs)
             verbose_router_logger.info("litellm.completion(model=%s)\x1b[32m 200 OK\x1b[0m", model_name)
@@ -3198,7 +3193,7 @@ class Router:
                 "messages": messages,
                 "caching": self.cache_responses,
                 "client": model_client,
-                **_without_target_order(kwargs),
+                **kwargs,
             }
             input_kwargs.pop("silent_model", None)
             input_kwargs.pop("include_fallback_errors", None)
@@ -4075,7 +4070,7 @@ class Router:
                     "prompt": prompt,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
             self.success_calls[model_name] += 1
@@ -4135,7 +4130,7 @@ class Router:
                     "prompt": prompt,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
 
@@ -4239,7 +4234,7 @@ class Router:
                     "file": file,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
 
@@ -4892,7 +4887,7 @@ class Router:
             response_kwargs: Final = {
                 **data,
                 "caching": self.cache_responses,
-                **_without_target_order(kwargs),
+                **kwargs,
                 "model": model_name,
             }
             # Only set custom_llm_provider if it's not None
@@ -5342,7 +5337,7 @@ class Router:
                     **data,
                     "custom_llm_provider": custom_llm_provider,
                     "caching": self.cache_responses,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
 
@@ -5408,7 +5403,7 @@ class Router:
                     "input": input,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
             self.success_calls[model_name] += 1
@@ -5471,7 +5466,7 @@ class Router:
                     "input": input,
                     "caching": self.cache_responses,
                     "client": model_client,
-                    **_without_target_order(kwargs),
+                    **kwargs,
                 }
             )
 
@@ -11933,7 +11928,7 @@ class Router:
         )
 
         ## ORDER FILTERING ## -> if user set 'order' in deployments, return deployments with lowest order (e.g. order=1 > order=2)
-        _target_order: Final = (request_kwargs or {}).get("_target_order")
+        _target_order: Final = (request_kwargs or {}).pop("_target_order", None)
         healthy_deployments = litellm.utils._get_order_filtered_deployments(
             cast(list[dict], healthy_deployments), target_order=_target_order
         )
@@ -12698,7 +12693,7 @@ class Router:
             )
 
         ## ORDER FILTERING ## -> if user set 'order' in deployments, return deployments with lowest order (e.g. order=1 > order=2)
-        _target_order: Final = (request_kwargs or {}).get("_target_order")
+        _target_order: Final = (request_kwargs or {}).pop("_target_order", None)
         healthy_deployments = litellm.utils._get_order_filtered_deployments(
             healthy_deployments, target_order=_target_order
         )
diff --git a/tests/test_litellm/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index 042d724df0b..8b9075f845c 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -6,8 +6,10 @@ should be tried first, and higher order deployments should be used as fallbacks
 when lower order deployments fail.
 """
 
+import json
 from typing import Final, Optional
 
+import httpx
 import pytest
 
 import litellm
@@ -580,6 +582,64 @@ async def test_generic_api_call_strips_target_order_from_provider_kwargs():
     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},
+            },
+        )
+
+    session: Final = httpx.AsyncClient(transport=httpx.MockTransport(_upstream))
+    litellm.in_memory_llm_clients_cache.flush_cache()
+    litellm.aclient_session = session
+    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")
+    finally:
+        litellm.aclient_session = None
+        litellm.in_memory_llm_clients_cache.flush_cache()
+        await session.aclose()
+
+    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,

From f9c6eda909c0bfce267de802bc8d4af02e2a050c Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 15:08:00 -0700
Subject: [PATCH 088/113] fix(cli): quote the Claude Code apiKeyHelper for
 cmd.exe on Windows (#39174)

* fix(cli): quote the Claude Code apiKeyHelper for cmd.exe on Windows

lite up and lite login --config-claude wrote the helper command with
POSIX shlex quoting, so a backslashed Windows install path came out
wrapped in single quotes that cmd.exe and PowerShell take literally.
Quote every token with the cmd.exe rules already used for agent shims
when running on Windows, and keep the POSIX output unchanged elsewhere.

Resolves LIT-6627

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(cli): split the Windows apiKeyHelper with cmd.exe and C runtime rules

The invocation test pulled tokens back out with a regex, which cannot see
the doubled quotes or the percent guard quote_for_cmd emits. Model the two
parsers that read the helper on Windows instead and check argv round
trips for backslashed, spaced, metacharacter, percent and quoted tokens

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/proxy/client/cli/commands/agents.py   | 25 +-----
 .../client/cli/commands/claude_settings.py    | 11 ++-
 .../proxy/client/cli/commands/cmd_quoting.py  | 26 ++++++
 .../proxy/client/cli/test_claude_settings.py  | 88 +++++++++++++++++++
 .../proxy/client/cli/test_up_commands.py      | 26 ++++++
 5 files changed, 151 insertions(+), 25 deletions(-)
 create mode 100644 litellm/proxy/client/cli/commands/cmd_quoting.py

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/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})

From 5988d93fed159642d0d6fa13bcd11eb93b34c047 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 15:08:11 -0700
Subject: [PATCH 089/113] fix(logging): guarantee max_parallel_requests slot
 release when streaming logging fails (#39093)

* fix(logging): guarantee max_parallel_requests slot release when stream logging fails

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(logging): cover guardrail branch of streaming logging hook failure isolation

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/litellm_core_utils/litellm_logging.py | 71 +++++++++------
 .../test_litellm_logging.py                   | 91 +++++++++++++++++++
 2 files changed, 136 insertions(+), 26 deletions(-)

diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py
index eb223c2f988..9a6fb11f978 100644
--- a/litellm/litellm_core_utils/litellm_logging.py
+++ b/litellm/litellm_core_utils/litellm_logging.py
@@ -2959,13 +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:
@@ -3005,32 +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")
 
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,

From 846900320e1fc2ca112b25a3da9d61d37a5dd8f8 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 15:09:03 -0700
Subject: [PATCH 090/113] feat(alerting): slack alerts for per-user
 daily/monthly spend thresholds and spend anomaly detection (#38438)

* feat(alerting): slack alerts for per-user daily/monthly spend thresholds and spend anomaly detection

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(alerting): use specific ValidationError matches in config rejection test

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(proxy): tolerate mocked slack alerting args when scheduling user spend scan

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* fix(alerting): reject non-finite values in user spend alert settings

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/constants.py                          |   1 +
 .../SlackAlerting/slack_alerting.py           |  64 ++++++
 .../SlackAlerting/user_spend_alerts.py        | 139 +++++++++++++
 litellm/proxy/proxy_server.py                 |  76 +++++--
 litellm/types/integrations/slack_alerting.py  |  37 ++++
 .../SlackAlerting/test_user_spend_alerts.py   | 193 ++++++++++++++++++
 tests/test_litellm/proxy/test_proxy_server.py |  69 +++++++
 .../components/alerting/alerting_settings.tsx |  11 +-
 .../dynamic_form.integration.test.tsx         |  23 ++-
 .../src/components/alerting/dynamic_form.tsx  |   4 +-
 .../src/components/settings.tsx               |   2 +
 ui/litellm-dashboard/src/lib/http/schema.d.ts |   2 +-
 12 files changed, 598 insertions(+), 23 deletions(-)
 create mode 100644 litellm/integrations/SlackAlerting/user_spend_alerts.py
 create mode 100644 tests/test_litellm/integrations/SlackAlerting/test_user_spend_alerts.py

diff --git a/litellm/constants.py b/litellm/constants.py
index 172ee70fd57..1bd977dd9a9 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -1590,6 +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/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/proxy/proxy_server.py b/litellm/proxy/proxy_server.py
index 2c600667283..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
 
@@ -14972,17 +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()
@@ -14997,7 +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,
@@ -15016,7 +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,
@@ -16444,6 +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/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/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/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/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/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/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index 7316b4359cc..6e38f3fa15e 100644
--- a/ui/litellm-dashboard/src/lib/http/schema.d.ts
+++ b/ui/litellm-dashboard/src/lib/http/schema.d.ts
@@ -22962,7 +22962,7 @@ 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 */

From 97dbd8efcb1c73e48bf502b612a4ce947971b731 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 15:11:15 -0700
Subject: [PATCH 091/113] fix(docker): add public Wolfi apk repo to runtime
 image (#39033)

* fix(docker): add public Wolfi apk repo to runtime image

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

* test(docker): accept quote variants in Wolfi repo assertion

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

---------

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 Dockerfile                                    |  6 +++
 .../test_dockerfile_apk_repository.py         | 52 +++++++++++++++++++
 2 files changed, 58 insertions(+)
 create mode 100644 tests/test_litellm/test_dockerfile_apk_repository.py

diff --git a/Dockerfile b/Dockerfile
index b3ee85e9ed1..29a085a4ef9 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -101,6 +101,12 @@ 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/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"
+    )

From 45fa78470df87ef0b8e4f7f20643a135aa6ffc6a Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 15:14:56 -0700
Subject: [PATCH 092/113] test(router): inject the upstream client instead of
 mutating litellm.aclient_session

The text-completion wire test set litellm.aclient_session, which the
test-quality gate (TQ005) flags as a process-wide global write. Pass an
AsyncOpenAI client through the router's client kwarg instead, so the test
owns its transport and needs no cache flush or global restore.

Claude-Session: https://claude.ai/code/session_01XKkTFa6g7Rmd6vtHL91GMn
---
 tests/test_litellm/test_router_order_fallback.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/tests/test_litellm/test_router_order_fallback.py b/tests/test_litellm/test_router_order_fallback.py
index 8b9075f845c..fde870e5abe 100644
--- a/tests/test_litellm/test_router_order_fallback.py
+++ b/tests/test_litellm/test_router_order_fallback.py
@@ -11,6 +11,7 @@ from typing import Final, Optional
 
 import httpx
 import pytest
+from openai import AsyncOpenAI
 
 import litellm
 from litellm import Router
@@ -600,9 +601,11 @@ async def test_text_completion_order_fallback_hop_does_not_send_target_order_ups
             },
         )
 
-    session: Final = httpx.AsyncClient(transport=httpx.MockTransport(_upstream))
-    litellm.in_memory_llm_clients_cache.flush_cache()
-    litellm.aclient_session = session
+    upstream_client: Final = AsyncOpenAI(
+        api_key="key",
+        base_url="http://upstream.test",
+        http_client=httpx.AsyncClient(transport=httpx.MockTransport(_upstream)),
+    )
     router = Router(
         model_list=[
             {
@@ -629,11 +632,9 @@ async def test_text_completion_order_fallback_hop_does_not_send_target_order_ups
         num_retries=0,
     )
     try:
-        response = await router.atext_completion(model="test-model", prompt="hi")
+        response = await router.atext_completion(model="test-model", prompt="hi", client=upstream_client)
     finally:
-        litellm.aclient_session = None
-        litellm.in_memory_llm_clients_cache.flush_cache()
-        await session.aclose()
+        await upstream_client.close()
 
     assert response._hidden_params["model_id"] == "2"
     assert upstream_bodies

From 55d638412bb1f1b9c8eb9bb255ffbb8b4aa0c1c4 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 15:17:00 -0700
Subject: [PATCH 093/113] fix: stop a cleared Team field from blocking personal
 key creation

Clearing the Team combobox in the Create Key modal left team_id set to an
empty string, so /key/generate treated the request as team key generation
and failed with a team-not-found error for non-admin members.

TeamDropdown now emits null on clear, and GenerateKeyRequest normalizes an
empty team_id to None so the request runs the personal key path.
---
 litellm/proxy/_types.py                       |  7 +++
 .../test_key_management_endpoints.py          | 46 ++++++++++++++++++
 .../common_components/team_dropdown.test.tsx  | 48 +++++++++++++++++++
 .../common_components/team_dropdown.tsx       |  4 +-
 4 files changed, 103 insertions(+), 2 deletions(-)
 create mode 100644 ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx

diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py
index e0a2097919b..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
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/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..90f7be1477c
--- /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(document.querySelector('[data-slot="combobox-clear"]') as HTMLElement);
+
+    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);
     }

From 4acc1d15fb7f9172d39417967445cf50176c5012 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 15:50:19 -0700
Subject: [PATCH 094/113] fix(ui): map a cleared Team dropdown back to an empty
 string in the auto-router form

---
 .../add_model/add_auto_router_tab.test.tsx    | 47 ++++++++++++++-----
 .../add_model/add_auto_router_tab.tsx         |  4 +-
 2 files changed, 39 insertions(+), 12 deletions(-)

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>
               )}
 

From 00e40c0afe558cf18ef1f446f94e52f8594b535a Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 15:28:12 -0700
Subject: [PATCH 095/113] Record each e2e test's source location in the JUnit
 report

The JUnit report is the only thing that leaves the e2e run, and it says
where a test's results came from but never where its code lives. A reader
looking at `test_cell_claimed_only_by_a_skipped_test_is_uncovered` on the
status page has a name and nothing else -- no file, no line, no way to
reach the source short of grepping the repo by hand.

Pytest knows the location; the report format loses it. The `xunit1` family
wrote `file=` and `line=` onto every `<testcase>`, and the `xunit2` default
this suite runs on drops both. Switching families back would change the
document for every consumer of the same XML -- the Buildkite Test Engine
upload and the Loki pipeline included -- so add the location the way this
suite already adds `package` and `covers`: as a `<property>`, which is
purely additive.

`source` is repo-relative and one-based (`tests/e2e/a2a/test_x.py:41`), so
a consumer can build a link without knowing how pytest was started. That
takes normalizing the two launch shapes -- the runner image runs from its
own copy at /app/e2e, a developer runs from the repo root -- which is the
same normalization `package_from_nodeid` was already doing in reverse, now
factored into `suite_parts` so the two cannot drift apart. Paths that
escape the suite, and tests pytest reports no line for, emit an empty
string: a test with no link beats a link that 404s.

Claude-Session: https://claude.ai/code/session_017dTKXwJkzhtVLzDhePHsKG
---
 tests/e2e/junit_properties.py      |  84 ++++++++++++++---
 tests/e2e/test_junit_properties.py | 145 +++++++++++++++++++++++++++++
 2 files changed, 215 insertions(+), 14 deletions(-)
 create mode 100644 tests/e2e/test_junit_properties.py

diff --git a/tests/e2e/junit_properties.py b/tests/e2e/junit_properties.py
index e4f59f5c4d2..5b5e239bf9a 100644
--- a/tests/e2e/junit_properties.py
+++ b/tests/e2e/junit_properties.py
@@ -2,10 +2,20 @@
 
 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 here because of a reporter limitation rather than a missing pytest
+fact. Pytest knows every test's file and line, and its `xunit1` report family
+wrote them as `file=` / `line=` attributes on `<testcase>`. The default `xunit2`
+family -- pytest's since 6.0, and this suite's, since pytest.ini names no family
+-- drops both. Switching families to get them back would change the document
+shape for every consumer of the same XML, the Buildkite Test Engine upload and
+the Loki pipeline included; a property is additive, so nothing that reads the
+report today sees a difference.
 """
 
 from __future__ import annotations
@@ -14,22 +24,66 @@ from collections.abc import Iterable
 
 import pytest
 
+# This module's own directory, relative to the repo root. Hardcoded because it
+# cannot be discovered at runtime: the e2e runner image copies tests/e2e/ to
+# /app/e2e and runs pytest from there, so no ancestor of this file names the
+# suite's place in the litellm tree. Moving tests/e2e/ means editing this line,
+# and test_junit_properties.py fails from a checkout until you do.
+SUITE_ROOT = "tests/e2e"
+
+
+def suite_parts(path_part: str) -> tuple[str, ...]:
+    """Path components of a suite file, relative to tests/e2e, either way it ran.
+
+    Pytest reports paths relative to its rootdir, which moves with the
+    invocation: a repo-root run gives `tests/e2e/logging/test_x.py`, a suite-cwd
+    run (what the runner image does) gives `logging/test_x.py`. Strip the
+    `tests/e2e` prefix when present so both collapse to the same components.
+    """
+    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` supplies a rootdir-relative path and a ZERO-based
+    line number, and neither travels as-is. The path is re-rooted at SUITE_ROOT
+    so consumers never have to know how pytest was started, and the line is
+    emitted ONE-based, matching editors, tracebacks, and code hosts (GitHub's
+    `#L41` is the file's 41st line). A decorated test anchors at its first
+    decorator, which is where pytest reports it and which puts the marks and the
+    `def` on screen together.
+
+    Returns '' rather than a guess when pytest reports no line, or when the path
+    escapes the suite root (absolute, or reaching upward): a test that renders
+    without a link is a smaller failure than one that links somewhere wrong.
+    """
+    if lineno is None:
+        return ""
+    normalized = path.replace("\\", "/")
+    if normalized.startswith("/") 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 +97,12 @@ 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/test_junit_properties.py b/tests/e2e/test_junit_properties.py
new file mode 100644
index 00000000000..8aa267673cb
--- /dev/null
+++ b/tests/e2e/test_junit_properties.py
@@ -0,0 +1,145 @@
+"""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),
+            ("../conftest.py", 40),
+            ("", 40),
+        ],
+    )
+    def test_nothing_linkable_yields_empty_rather_than_a_guess(self, path: str, lineno: int | None) -> None:
+        """A test that renders without a link is a smaller failure than one whose
+        link 404s or points into another repo's file."""
+        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")

From 0c2d4c5773a7269f026831d359ca86bea20b5159 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 16:02:54 -0700
Subject: [PATCH 096/113] Refuse a source path carrying a colon

`path:line` cannot represent a path that itself contains a colon, and the
one way pytest produces one is a Windows absolute location: separator
normalization turns `C:\app\e2e\a2a\test_x.py` into `C:/app/...`, which
slipped past the leading-slash check and composed the nonsense repo path
`tests/e2e/C:/app/e2e/a2a/test_x.py`.

Reject the colon itself rather than special-casing a drive letter: it is
the character the format reserves, so no path containing one was ever
linkable.

Claude-Session: https://claude.ai/code/session_017dTKXwJkzhtVLzDhePHsKG
---
 tests/e2e/junit_properties.py      | 49 ++++++++++++------------------
 tests/e2e/test_junit_properties.py |  5 +--
 2 files changed, 23 insertions(+), 31 deletions(-)

diff --git a/tests/e2e/junit_properties.py b/tests/e2e/junit_properties.py
index 5b5e239bf9a..c5971c5362c 100644
--- a/tests/e2e/junit_properties.py
+++ b/tests/e2e/junit_properties.py
@@ -8,14 +8,10 @@ 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 here because of a reporter limitation rather than a missing pytest
-fact. Pytest knows every test's file and line, and its `xunit1` report family
-wrote them as `file=` / `line=` attributes on `<testcase>`. The default `xunit2`
-family -- pytest's since 6.0, and this suite's, since pytest.ini names no family
--- drops both. Switching families to get them back would change the document
-shape for every consumer of the same XML, the Buildkite Test Engine upload and
-the Loki pipeline included; a property is additive, so nothing that reads the
-report today sees a difference.
+`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
@@ -24,21 +20,18 @@ from collections.abc import Iterable
 
 import pytest
 
-# This module's own directory, relative to the repo root. Hardcoded because it
-# cannot be discovered at runtime: the e2e runner image copies tests/e2e/ to
-# /app/e2e and runs pytest from there, so no ancestor of this file names the
-# suite's place in the litellm tree. Moving tests/e2e/ means editing this line,
-# and test_junit_properties.py fails from a checkout until you do.
+# 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, either way it ran.
+    """Path components of a suite file relative to tests/e2e, however it ran.
 
-    Pytest reports paths relative to its rootdir, which moves with the
-    invocation: a repo-root run gives `tests/e2e/logging/test_x.py`, a suite-cwd
-    run (what the runner image does) gives `logging/test_x.py`. Strip the
-    `tests/e2e` prefix when present so both collapse to the same components.
+    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
@@ -55,22 +48,20 @@ def package_from_nodeid(nodeid: str) -> str:
 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` supplies a rootdir-relative path and a ZERO-based
-    line number, and neither travels as-is. The path is re-rooted at SUITE_ROOT
-    so consumers never have to know how pytest was started, and the line is
-    emitted ONE-based, matching editors, tracebacks, and code hosts (GitHub's
-    `#L41` is the file's 41st line). A decorated test anchors at its first
-    decorator, which is where pytest reports it and which puts the marks and the
-    `def` on screen together.
+    `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.
 
-    Returns '' rather than a guess when pytest reports no line, or when the path
-    escapes the suite root (absolute, or reaching upward): a test that renders
-    without a link is a smaller failure than one that links somewhere wrong.
+    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.split("/"):
+    if normalized.startswith("/") or ":" in normalized or ".." in normalized.split("/"):
         return ""
     parts = suite_parts(normalized)
     if not parts:
diff --git a/tests/e2e/test_junit_properties.py b/tests/e2e/test_junit_properties.py
index 8aa267673cb..c0596177cc1 100644
--- a/tests/e2e/test_junit_properties.py
+++ b/tests/e2e/test_junit_properties.py
@@ -97,13 +97,14 @@ class TestSourceFromLocation:
         [
             ("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 test that renders without a link is a smaller failure than one whose
-        link 404s or points into another repo's file."""
+        """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) == ""
 
 

From 1964d92fc65733c13e78f4cbb9ae62357325c454 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 16:04:45 -0700
Subject: [PATCH 097/113] test(ui): query the clear button and the models page
 tabs through accessible screen queries

---
 .../app/(dashboard)/models-and-endpoints/page.test.tsx | 10 +++++-----
 .../common_components/team_dropdown.test.tsx           |  2 +-
 2 files changed, 6 insertions(+), 6 deletions(-)

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 1199b66621f..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
@@ -111,17 +111,17 @@ describe("ModelsAndEndpointsPage", () => {
   // 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);
-    const { getByRole, queryByRole } = renderPage();
-    expect(queryByRole("tab", { name: "Add Model" })).not.toBeInTheDocument();
-    expect(getByRole("tab", { name: "All Models" })).toBeInTheDocument();
+    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);
-    const { getByRole } = renderPage();
-    expect(getByRole("tab", { name: /Auto-Routers/ })).toBeInTheDocument();
+    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
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
index 90f7be1477c..01b8a12d99c 100644
--- a/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
+++ b/ui/litellm-dashboard/src/components/common_components/team_dropdown.test.tsx
@@ -40,7 +40,7 @@ describe("TeamDropdown", () => {
     const onTeamSelect = vi.fn();
     render(<TeamDropdown value="team-1" onChange={onChange} onTeamSelect={onTeamSelect} />);
 
-    await user.click(document.querySelector('[data-slot="combobox-clear"]') as HTMLElement);
+    await user.click(screen.getByRole("button", { name: "Clear" }));
 
     expect(onChange).toHaveBeenCalledWith(null);
     expect(onTeamSelect).toHaveBeenCalledWith(null);

From 3888a85045f05007baa41cb6d2b1a8677ef81fbd Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 16:13:26 -0700
Subject: [PATCH 098/113] fix(budget): reject known estimates over remaining
 budget under fail_closed_budget_enforcement (#39214)

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../spend_tracking/budget_reservation.py      | 36 ++++++--
 .../proxy/test_budget_reservation.py          | 88 +++++++++++++++++++
 2 files changed, 115 insertions(+), 9 deletions(-)

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/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,

From e11a2ec0f671f7b01696f543715910b270681157 Mon Sep 17 00:00:00 2001
From: ryan-crabbe-berri <ryan@berri.ai>
Date: Tue, 1 Sep 2026 16:19:17 -0700
Subject: [PATCH 099/113] Re-run checks after retargeting to
 litellm_internal_staging

The Guard main branch job ran while this PR still pointed at main and
recorded a failure that cannot clear: re-running it replays the original
event payload, base included. Its trigger is scoped to PRs against main, so
it does not apply now and a fresh head SHA is what drops the stale run.

Claude-Session: https://claude.ai/code/session_017dTKXwJkzhtVLzDhePHsKG

From 59da6e75a50024dcca1af5efa90e4eec3409b89b Mon Sep 17 00:00:00 2001
From: tin-berri <tin@berri.ai>
Date: Tue, 1 Sep 2026 16:50:12 -0700
Subject: [PATCH 100/113] feat(router): fall back on anthropic safeguard
 refusals on /v1/messages (#39157)

* fix(router): resolve fallbacks against the tier a pre-routing hook selected

A complexity or auto router picks a tier behind the router group name, but
fallback lookup kept using kwargs["model"], which is still the router name. The
tier's configured chain never ran, so a provider failure on its first hop went
straight back to the client with "No fallback model group found for original
model_group=smart-router".

The hook assigns the selected model to a local only, and fallback resolution runs
on an outer kwargs dict that **kwargs already copied, so writing it there is not
visible. Record the selection in the metadata bucket instead, which is a nested
dict shared by reference across those copies and is how the router already
carries values back up, then key fallback lookup off it when present.

Applies to the generic, context-window, content-policy and weighted-failover
lookups. Reporting keeps using the router name, since that is what the caller
asked for.

Fixes #38832

* fix(router): annotate the recorded-selection helper with a read-only mapping

record_pre_routing_selection only reads the request kwargs, writing into the
nested metadata bucket it finds there, so Mapping states what it actually needs
and clears the LIT001 mutable-annotation budget without a suppression.

* test(router): assert the no-kwargs path leaks nothing

The tolerated-None case called the helper without checking anything, which the
test-quality gate counts as a test with no assertion. Assert that a fresh mapping
still reads back empty, so the case proves the call is a no-op rather than only
that it does not raise.

* fix(router): stop declaring loop-assigned locals Final in the selection helpers

Both helpers annotated a loop-assigned local as Final, which reassigns a Final on
every iteration and cost three basedpyright errors. Read the buckets through a
generator instead, so the write path iterates a for-target and the read path
resolves in one shot with next(), which also matches the functional style the
type-discipline rules ask for.

* style(router): apply ruff format to the selection helpers

* fix(router): derive the pre-routing tier fresh on every fallback hop

The metadata buckets also carry whatever the caller sent, so an inbound
pre_routing_selected_model let a client pick which fallback chain its
request fell into. A fallback hop also inherited the previous hop's tier,
so the second hop keyed its own failure off the tier that already failed
and never ran its own chain.

Clear the key at the top of async_function_with_fallbacks. Every hop
re-enters there, so only the hook that routed that hop can set it.

* fix(router): drop the cast at the fallback-hop clear call site

* feat(router): fall back on anthropic safeguard refusals on /v1/messages

---------

Co-authored-by: Priyansh Nandwana <nandwana.priyansh103@gmail.com>
---
 .../messages/streaming_iterator.py            |  25 +-
 .../messages/utils.py                         |  49 ++-
 litellm/router.py                             | 192 +++++++--
 .../router_utils/fallback_event_handlers.py   |  85 ++++
 .../anthropic_messages/anthropic_response.py  |  13 +-
 ...test_router_anthropic_messages_fallback.py | 402 ++++++++++++++++++
 .../test_fallback_event_handlers.py           | 119 ++++++
 tests/test_litellm/test_router.py             | 135 ++++++
 8 files changed, 970 insertions(+), 50 deletions(-)
 create mode 100644 tests/router_unit_tests/test_router_anthropic_messages_fallback.py

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/router.py b/litellm/router.py
index 471a1116f44..6e4405ebfef 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -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 (
@@ -4918,6 +4922,19 @@ 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 +4981,11 @@ 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 +4995,14 @@ 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 +5060,10 @@ 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 +5102,35 @@ 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 +5242,13 @@ 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 +5304,11 @@ 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 +5318,14 @@ 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 +6881,9 @@ 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 +6928,15 @@ 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 +6994,9 @@ 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 +7027,9 @@ 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 +7056,14 @@ 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 +7072,12 @@ 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 +7123,7 @@ 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 +7549,24 @@ 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 +7982,31 @@ 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 +8019,26 @@ 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 = []
@@ -12087,6 +12207,7 @@ 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
@@ -12202,6 +12323,7 @@ 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 d2842294a08..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:
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/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/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/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"

From 8c7fe00d80a9118baf5d2b8f87d24dc53644a8fd Mon Sep 17 00:00:00 2001
From: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:37:07 -0700
Subject: [PATCH 101/113] fix: compare stream event types by equality so typed
 completed events keep their usage

---
 .../base_llm/guardrail_translation/utils.py   |  2 +-
 ...test_openai_responses_guardrail_handler.py | 32 +++++++++++++++++++
 2 files changed, 33 insertions(+), 1 deletion(-)

diff --git a/litellm/llms/base_llm/guardrail_translation/utils.py b/litellm/llms/base_llm/guardrail_translation/utils.py
index d30cdcecff5..9b6f9c47105 100644
--- a/litellm/llms/base_llm/guardrail_translation/utils.py
+++ b/litellm/llms/base_llm/guardrail_translation/utils.py
@@ -171,7 +171,7 @@ def blocked_responses_stream_usage(original_response: object) -> ResponseAPIUsag
         (
             response
             for item in reversed(original_response)
-            if str(stream_item_field(item, "type") or "") == "response.completed"
+            if stream_item_field(item, "type") == "response.completed"
             and (response := stream_item_field(item, "response")) is not None
         ),
         None,
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 d68ca0fdfb6..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
@@ -1389,6 +1389,38 @@ class TestBuildBlockSseChunks:
         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,

From b0041f32a2d7ba9a99e0d9eb0f5402df7237200a Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:45:59 -0700
Subject: [PATCH 102/113] fix(helm): reuse the generated master key Secret on
 helm upgrade (#39219)

The generated masterkey Secret rendered a fresh randAlphaNum value on every
release, so any helm upgrade with masterkeySecretName and masterkey unset
rotated the master key and invalidated every client holding the old one.
Look up the existing Secret in the release namespace and reuse its value,
falling back to a random key only on first install.

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 helm/litellm-helm/README.md                   |  4 +-
 .../templates/secret-masterkey.yaml           |  6 ++-
 .../tests/masterkey-secret_tests.yaml         | 47 +++++++++++++++++++
 3 files changed, 54 insertions(+), 3 deletions(-)

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:

From 69029c139e3efb4f750594bceb536d6ef944cbbb Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:48:01 -0700
Subject: [PATCH 103/113] fix(mcp): report per-server outcomes in aggregate
 REST tools/list (#39232)

GET /mcp-rest/tools/list without server_id returned only the tools of
the servers that answered and silently dropped any server whose listing
failed (for example an OAuth-protected server without credentials), so
clients could not tell a partial listing from a complete one.

The aggregate response now carries a server_outcomes map keyed by server
alias with the same classified outcome (ok/auth_required/forbidden/...)
that the MCP protocol path already puts in _meta. Healthy tools and the
HTTP 200 status are unchanged.

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../mcp_server/rest_endpoints.py              | 71 +++++++++++--------
 .../mcp_server/test_rest_endpoints.py         | 11 ++-
 2 files changed, 51 insertions(+), 31 deletions(-)

diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index 2b89dba0e4f..d1ef73a15cd 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -1,7 +1,8 @@
 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
@@ -20,8 +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,
@@ -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
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 e36bef229f6..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
@@ -1431,7 +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,
         )
@@ -1497,6 +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

From 04a25083a64fb4a2287d39db535ce680c3a17d93 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:49:06 -0700
Subject: [PATCH 104/113] fix(cost-map): retry transient boot fetch failures
 and recover config deployments dropped by a stale cost map (#39230)

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../litellm_core_utils/get_model_cost_map.py  | 126 +++++++++++++-----
 litellm/router.py                             |  23 +++-
 .../test_get_model_cost_map.py                | 106 ++++++++++++++-
 .../test_router_model_cost_isolation.py       |  80 +++++++++++
 4 files changed, 291 insertions(+), 44 deletions(-)

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/router.py b/litellm/router.py
index 6e4405ebfef..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
 
@@ -825,6 +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
@@ -8472,6 +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
                 )
@@ -8901,6 +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
@@ -9523,8 +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)
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/test_router_model_cost_isolation.py b/tests/test_litellm/test_router_model_cost_isolation.py
index 7b7a962bf00..30b265905f3 100644
--- a/tests/test_litellm/test_router_model_cost_isolation.py
+++ b/tests/test_litellm/test_router_model_cost_isolation.py
@@ -2281,3 +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

From 47b9d838aa05bbc5404c357454ef612dea3ae370 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:49:40 -0700
Subject: [PATCH 105/113] perf(scim): resolve group members with one user table
 read per member (#39228)

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../management_endpoints/scim/scim_v2.py      |  40 ++++-
 .../scim/test_scim_v2_endpoints.py            | 150 ++++++++++++++----
 2 files changed, 155 insertions(+), 35 deletions(-)

diff --git a/litellm/proxy/management_endpoints/scim/scim_v2.py b/litellm/proxy/management_endpoints/scim/scim_v2.py
index ded57815e91..8a0436f42dd 100644
--- a/litellm/proxy/management_endpoints/scim/scim_v2.py
+++ b/litellm/proxy/management_endpoints/scim/scim_v2.py
@@ -585,6 +585,37 @@ 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 +658,9 @@ 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 +680,6 @@ 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",
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..d8fe22c4979 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
@@ -1,6 +1,6 @@
 import logging
 import time
-from collections.abc import Mapping
+from collections.abc import Callable, Mapping
 from itertools import chain
 from typing import Final
 from unittest.mock import AsyncMock, MagicMock, call
@@ -1645,6 +1645,25 @@ 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 +1715,8 @@ 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 +1800,8 @@ 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 +1870,8 @@ 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 +1959,8 @@ 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 +2028,8 @@ 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 +3135,7 @@ 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 +3428,7 @@ 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 +3521,7 @@ 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 +3651,7 @@ 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 +3743,14 @@ 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 +3761,9 @@ 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 +3781,11 @@ 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))
@@ -4611,9 +4629,15 @@ 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,
     )
 
@@ -5152,6 +5176,77 @@ async def test_resolve_group_member_ids_refuses_a_user_id_that_names_another_acc
     )
 
 
+@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
 async def test_resolve_group_member_ids_warns_before_creating_unmatched_placeholder(
@@ -5536,10 +5631,7 @@ 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),

From 93219a9257ddd74137d7c2476ace01171ce484b9 Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:51:55 -0700
Subject: [PATCH 106/113] fix(docker): install bedrock-realtime extra in
 monolith proxy images (#39223)

The Dockerfile, docker/Dockerfile.non_root and docker/Dockerfile.database uv sync stages never passed --extra bedrock-realtime, so aws-sdk-bedrock-runtime was absent from the image venv and Bedrock Nova Sonic /v1/realtime sessions failed with 'Missing aws_sdk_bedrock_runtime'. gateway/Dockerfile already had the extra (PR #34426).

Adds a static check over every uv sync in the proxy Dockerfiles and an image-level import probe that the image-scan workflow runs against the built root, non-root and gateway images.

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .github/workflows/image-scan.yml              |  6 +-
 Dockerfile                                    |  2 +
 docker/Dockerfile.database                    |  2 +
 docker/Dockerfile.non_root                    |  3 +
 .../test_image_bedrock_realtime_extra.py      | 58 +++++++++++++++++++
 .../test_dockerfile_bedrock_realtime_extra.py | 56 ++++++++++++++++++
 6 files changed, 124 insertions(+), 3 deletions(-)
 create mode 100644 tests/proxy_migration_tests/test_image_bedrock_realtime_extra.py
 create mode 100644 tests/test_litellm/test_dockerfile_bedrock_realtime_extra.py

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/Dockerfile b/Dockerfile
index 29a085a4ef9..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 \
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/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/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'"
+    )

From c0019751520837bd3a0a6203297292bab31171de Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 17:55:47 -0700
Subject: [PATCH 107/113] fix(aiohttp_transport): map transport-internal
 CancelledError to a retryable ConnectError (#39240)

aiohttp shields its DNS resolution task; when the connector closes it cancels
that child, so the request task sees CancelledError without ever being
cancelled itself. map_aiohttp_exceptions() only caught Exception, so the
BaseException skipped transport mapping, router retries and proxy error
handling, and /v1/responses answered 500 "No response returned".

Catch CancelledError in the mapper, re-raise when the current task is really
being cancelled (Task.cancelling() > 0), and otherwise map it to
httpx.ConnectError so the usual retry, fallback and error mapping apply.

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 .../llms/custom_httpx/aiohttp_transport.py    | 13 +++++
 .../custom_httpx/test_aiohttp_transport.py    | 56 +++++++++++++++++++
 2 files changed, 69 insertions(+)

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/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()

From 48dd06e841074e6f3362c85bd4fd679c34530f97 Mon Sep 17 00:00:00 2001
From: tin-berri <tin@berri.ai>
Date: Tue, 1 Sep 2026 18:00:31 -0700
Subject: [PATCH 108/113] fix(bedrock): gate Converse cachePoint emission on
 model prompt caching support (#39210)

Bedrock rejects requests carrying cachePoint blocks for models whose entry in the cost map does not declare supports_prompt_caching (403 "You invoked an unsupported model or your request did not allow prompt caching"). Clients like Claude Code attach cache_control to every request, so any such model behind the gateway failed on every call. The new bedrock_model_accepts_cache_points predicate drops cachePoint emission for map-known non-caching models at all three emission funnels, keeps emitting for unmapped ids (application inference profile ARNs), and skips the gateway injection credit when the tool_config point is not placed.
---
 .../prompt_templates/factory.py               |  7 +-
 .../bedrock/chat/converse_transformation.py   |  5 +-
 litellm/llms/bedrock/common_utils.py          | 24 ++++++
 ...llm_core_utils_prompt_templates_factory.py | 22 +++++
 .../chat/test_converse_transformation.py      | 80 ++++++++++++++++++-
 5 files changed, 133 insertions(+), 5 deletions(-)

diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py
index e6402e8c1bd..ba59e3fa997 100644
--- a/litellm/litellm_core_utils/prompt_templates/factory.py
+++ b/litellm/litellm_core_utils/prompt_templates/factory.py
@@ -4957,10 +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/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py
index 7fefeaeaf04..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,
@@ -1149,7 +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)
@@ -1613,7 +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/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/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 64c96b575c5..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
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 4f53d3481de..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",
     )
 

From 81277252e1e3a9f8ac7c8c73a6c72151c5b596a4 Mon Sep 17 00:00:00 2001
From: tin-berri <tin@berri.ai>
Date: Tue, 1 Sep 2026 18:01:13 -0700
Subject: [PATCH 109/113] fix(datadog_llm_obs): send tool calls, tool results
 and cache tokens in DD's own fields (#39222)

The LLM Obs callback copied litellm's OpenAI-shaped objects into the span
verbatim, so every field Datadog names differently landed somewhere it does
not read: tool calls kept their nested `function` wrapper instead of DD's
name/arguments/tool_id, tool messages carried no result linking them to their
call, the request's tools were never sent, and prompt-cache counts sat inside
meta.metadata rather than the span metrics its cache dashboards chart.

One rule governs the message mapper: add the fields Datadog declares, and never
destroy content it did not understand. Content collapses to its text only when
it has text, so a content list carrying tool or image blocks rides along
unchanged, and absent messages map to an empty input rather than a fabricated
turn. Tool calls and results are read from both dialects, the OpenAI
`tool_calls` / `role: tool` shape and the Anthropic `tool_use` / `tool_result`
content blocks, so /v1/messages sessions gain tool linking they never had.

Cache counts come from the same owners the savings dashboard uses, so every
provider spelling resolves through one place rather than a second local guess.
The three cache metrics partition the input count: litellm's normalized prompt
total includes both cache categories, as the cost calculator's pricing helper
documents, so the non-cached residual subtracts reads AND writes. Counting a
primed prefix as ordinary input had inflated non-cached usage by exactly the
cache-write count on every priming request.

Correlating a result to its call reads ids and names structurally and parses no
arguments, so a tool call's arguments are decoded once per span rather than
once per pass, and arguments past a size bound ship as the raw string instead
of paying a decode that multiplies memory on hostile compact JSON.

The flat `output_tool_calls.*` metadata copies go away with this: they were a
second representation of a fact that now has its own field on the same span.
---
 .../integrations/datadog/datadog_llm_obs.py   | 393 +++++++++------
 litellm/types/integrations/datadog_llm_obs.py |  49 +-
 .../datadog/test_datadog_llm_obs.py           | 469 ++++++++++++++++++
 3 files changed, 762 insertions(+), 149 deletions(-)
 create mode 100644 tests/test_litellm/integrations/datadog/test_datadog_llm_obs.py

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/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/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"

From 6d0367ce350402e93651f1391afdde1ee2553b0f Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Tue, 1 Sep 2026 18:03:18 -0700
Subject: [PATCH 110/113] feat(prometheus): expose per-key and per-team rate
 limit allowed and used gauges (#39236)

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/integrations/prometheus.py            | 120 ++++++++-
 .../bounded_prometheus_series_tracker.py      |   4 +
 litellm/types/integrations/prometheus.py      |  20 ++
 .../test_prometheus_client_ip_user_agent.py   |   1 +
 .../test_prometheus_rate_limit_labels.py      | 252 ++++++++++++++++++
 5 files changed, 395 insertions(+), 2 deletions(-)

diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py
index add91033ff3..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
 
@@ -58,6 +59,7 @@ 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
@@ -476,6 +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
             ########################################
@@ -1475,6 +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,
@@ -2002,17 +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,
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/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/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()

From 2b616fc479c873692829605c72999c99700c952b Mon Sep 17 00:00:00 2001
From: "devin-ai-integration[bot]"
 <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Date: Wed, 2 Sep 2026 01:04:53 +0000
Subject: [PATCH 111/113] feat(scim): add placeholder listing and merge so a
 shadowed account can be healed (#39231)

Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---
 litellm/models/user.py                        |  10 +-
 litellm/proxy/_lazy_openapi_snapshot.json     | 179 +++++++++++++
 .../management_endpoints/scim/scim_v2.py      |  84 ++++++
 litellm/repositories/user_repository.py       |  26 +-
 .../proxy/management_endpoints/scim_v2.py     |   6 +
 .../scim/test_scim_v2_endpoints.py            | 240 ++++++++++++++++--
 ui/litellm-dashboard/src/lib/http/schema.d.ts | 137 ++++++++++
 7 files changed, 659 insertions(+), 23 deletions(-)

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/_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/management_endpoints/scim/scim_v2.py b/litellm/proxy/management_endpoints/scim/scim_v2.py
index 8a0436f42dd..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,
@@ -1862,6 +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/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/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/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 d8fe22c4979..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 Callable, 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(
@@ -4470,9 +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",
@@ -4927,9 +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(
@@ -4940,7 +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(
@@ -5105,11 +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(
@@ -5171,9 +5178,7 @@ 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
@@ -5711,3 +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/ui/litellm-dashboard/src/lib/http/schema.d.ts b/ui/litellm-dashboard/src/lib/http/schema.d.ts
index 6e38f3fa15e..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;
@@ -34927,6 +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 */
@@ -55858,6 +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?: {

From 4b87fd5718ed96e7080c68695750b90234194587 Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Tue, 1 Sep 2026 18:06:35 -0700
Subject: [PATCH 112/113] fix: normalize provider-specific cache token fields
 in OTel v2 usage (#39202)

* fix: normalize provider-specific cache token fields in OTel v2 usage

* fix: use an immutable empty mapping for the cache token details fallback

* fix: ignore malformed cache token values instead of emitting or raising
---
 litellm/integrations/otel/model/payloads.py   | 43 +++++++++++-
 .../otel/test_otel_v2_sources_of_truth.py     | 68 +++++++++++++++++++
 2 files changed, 109 insertions(+), 2 deletions(-)

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/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

From 62f032cca53c16967af6a424facc5dd88205d4dd Mon Sep 17 00:00:00 2001
From: yucheng-berri <yucheng@berri.ai>
Date: Tue, 1 Sep 2026 18:07:04 -0700
Subject: [PATCH 113/113] fix(proxy): keep passthrough logging metadata and
 model_info dicts when team callbacks are wired (#39216)

* fix(proxy): keep passthrough logging metadata and model_info dicts when team callbacks are wired

Passing team callback vars into Logging(kwargs=...) makes get_litellm_params materialize a full litellm_params, where metadata and model_info default to None instead of being absent. Readers that resolve them as .get(key, {}).get(...) then raise, so any passthrough request from a team with logging callbacks 500s once a pre-call guardrail is on, and the router strategy loggers log a traceback per request.

* test(proxy): annotate the closure dicts the passthrough logging tests record into
---
 .../pass_through_endpoints.py                 |   2 +
 .../test_pass_through_endpoints.py            | 111 +++++++++++++++++-
 2 files changed, 111 insertions(+), 2 deletions(-)

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/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}"