Merge branch 'litellm_internal_staging' of https://github.com/BerriAI/litellm into litellm_techdebt_20260903

litellm/integrations/shadow_eval_logger.py

@@ -165,28 +165,91 @@ def _chat_request_from_responses(
     )
 
 
-def _chat_final_text(response_obj: object) -> str:
-    """The assistant's text, or empty when the turn carries tool calls: only text-final
-    turns produce a judgeable A/B comparison."""
+def _chat_choice(response_obj: object) -> object | None:
+    """The response's first choice, from a payload mapping or a duck-typed ModelResponse."""
     try:
-        message: Final = (
-            response_obj["choices"][0]["message"]
-            if isinstance(response_obj, Mapping)
-            else response_obj.choices[0].message  # pyright: ignore[reportAttributeAccessIssue]  # duck-typed ModelResponse
-        )
+        if isinstance(response_obj, Mapping):
+            return response_obj["choices"][0]
+        return response_obj.choices[0]  # pyright: ignore[reportAttributeAccessIssue]  # duck-typed ModelResponse
     except (AttributeError, KeyError, IndexError, TypeError):
+        return None
+
+
+def _field_reader(obj: object) -> Callable[[str], object]:
+    return obj.get if isinstance(obj, Mapping) else lambda key: getattr(obj, key, None)
+
+
+def _chat_message_reader(response_obj: object) -> Callable[[str], object] | None:
+    """Field access over the assistant message of a chat response, or None for a payload
+    with no readable message."""
+    choice: Final = _chat_choice(response_obj)
+    if choice is None:
+        return None
+    message: Final = _field_reader(choice)("message")
+    return _field_reader(message) if message is not None else None
+
+
+def _chat_final_text(response_obj: object) -> str:
+    """The turn's judgeable text: prose, or every tool call serialized alongside it as
+    `[tool call] name(arguments)` when the assistant chose to act instead of, or as well
+    as, answering directly. A tool call is a real turn, not a gap, so this is what both
+    the real arm's sampling decision and the shadow arm's reply compare against."""
+    read: Final = _chat_message_reader(response_obj)
+    if read is None:
         return ""
-    read: Final = message.get if isinstance(message, Mapping) else lambda key: getattr(message, key, None)
-    if read("tool_calls") or read("function_call"):
-        return ""
-    return extract_text_from_content(read("content"))
+    prose: Final = extract_text_from_content(read("content"))
+    if not (read("tool_calls") or read("function_call")):
+        return prose
+    serialized: Final = _serialize_tool_calls(read)
+    return f"{prose} {serialized}".strip() if prose else serialized
+
+
+def _chat_finish_reason(response_obj: object) -> str:
+    choice: Final = _chat_choice(response_obj)
+    raw: Final = _field_reader(choice)("finish_reason") if choice is not None else None
+    return str(raw) if raw else "unknown"
+
+
+_RESPONSES_TOOL_CALL_TYPES: Final = frozenset(("function_call", "custom_tool_call"))
+
+
+def _tool_calls_list(read: Callable[[str], object]) -> tuple[object, ...]:
+    calls: Final = read("tool_calls")
+    listed: Final = tuple(calls) if isinstance(calls, Sequence) and not isinstance(calls, str) else ()
+    single: Final = read("function_call")
+    return listed if listed else ((single,) if single is not None else ())
+
+
+def _tool_call_invocation(call: object) -> str:
+    """One tool call as `name(arguments)`. Custom tool calls name themselves and carry their
+    arguments under `custom` rather than `function`."""
+    read_call: Final = _field_reader(call)
+    payload: Final = read_call("function") or read_call("custom") or call
+    read_payload: Final = _field_reader(payload)
+    name: Final = read_payload("name")
+    arguments: Final = read_payload("arguments") or read_payload("input") or ""
+    return f"{name or 'unnamed'}({arguments})"
+
+
+def _serialize_tool_calls(read: Callable[[str], object]) -> str:
+    """Every tool call in a reply as text a judge built for prose can still read."""
+    return ", ".join(f"[tool call] {_tool_call_invocation(call)}" for call in _tool_calls_list(read))
+
+
+def _shadow_empty_reply_error(response_obj: object, routed_model: str) -> str:
+    """Why a shadow reply yielded no judgeable text at all: no prose, and no tool call to
+    serialize either. The stable sentence comes first and every varying part after the
+    semicolon, so grouping rows by error still yields one row per cause."""
+    detail: Final = f"finish_reason={_chat_finish_reason(response_obj)}, model={routed_model or 'unknown'}"
+    return f"shadow router returned an empty response; {detail}"
 
 
 def _responses_final_text(response_obj: object) -> str:
-    """The turn's aggregated output text, or empty when the turn carries tool calls. A
-    dict-shaped payload is validated into the owner type first, because ``output_text``
-    is a derived property rather than a serialized field, so it never exists on a dict;
-    a dict the owner type rejects is unjudgeable and skipped."""
+    """The turn's judgeable text: the aggregated output plus any tool call serialized
+    alongside it, the same way the chat surface renders one. A dict-shaped payload is
+    validated into the owner type first, because ``output_text`` is a derived property
+    rather than a serialized field, so it never exists on a dict; a dict the owner type
+    rejects is unjudgeable and skipped."""
     from litellm.types.llms.openai import ResponsesAPIResponse
 
     try:
@@ -199,11 +262,16 @@ def _responses_final_text(response_obj: object) -> str:
     if not isinstance(output, Sequence):
         return ""
     items: Final = tuple(item.model_dump() if isinstance(item, BaseModel) else item for item in output)
-    if any(
-        not isinstance(item, Mapping) or item.get("type") in ("function_call", "custom_tool_call") for item in items
-    ):
+    if any(not isinstance(item, Mapping) for item in items):
         return ""
-    return str(getattr(response, "output_text", "") or "")
+    calls: Final = tuple(
+        item for item in items if isinstance(item, Mapping) and item.get("type") in _RESPONSES_TOOL_CALL_TYPES
+    )
+    prose: Final = str(getattr(response, "output_text", "") or "")
+    if not calls:
+        return prose
+    serialized: Final = ", ".join(f"[tool call] {_tool_call_invocation(call)}" for call in calls)
+    return f"{prose} {serialized}".strip() if prose else serialized
 
 
 class _SurfaceOps:
@@ -273,8 +341,8 @@ def _judgeable_sample(
     response_obj: object,
 ) -> tuple[tuple[Mapping[str, object], ...], Mapping[str, object], str] | None:
     """The normalized chat conversation, the forwardable generation params, and the
-    judgeable final text; None when this request's shapes cannot be sampled (tool-final
-    turn, empty text, or a shape the owner transformations reject)."""
+    judgeable final text; None when this request's shapes cannot be sampled (no text and no
+    tool call to serialize, or a shape the owner transformations reject)."""
     try:
         request: Final = ops.chat_request(kwargs, model_parameters)
         items: Final = _MESSAGE_ITEMS_ADAPTER.validate_python(request.get("messages"))
@@ -307,6 +375,11 @@ PAIRWISE_JUDGE_SYSTEM_PROMPT: Final = """You are an impartial quality judge comp
 
 The responses are labeled A and B in random order. You do not know which system produced which.
 
+A response may be prose, or a tool call shown as `[tool call] name(arguments)` if the
+assistant chose to act instead of answering directly. A tool call is not a defect: judge
+whether calling that tool was the right response to the conversation, the same as you
+would judge prose.
+
 Criteria: correctness, completeness, clarity, conciseness.
 
 Return ONLY valid JSON in this exact format, no other text:
@@ -376,14 +449,37 @@ def _unmask_preference(raw_preference: str, real_is_a: bool) -> str:
     return "tie"
 
 
-def _judge_user_prompt(conversation: str, response_a: str, response_b: str) -> str:
+_MAX_JUDGE_TOOL_DEFS_CHARS: Final = 2_000
+
+
+def _tool_definitions_text(tools: object) -> str:
+    """The tools available to both arms, name and description only: enough for the judge
+    to tell whether the chosen tool, and not some other one, was the right call, without
+    forwarding parameter schemas it does not need to score that."""
+    if not isinstance(tools, Sequence) or isinstance(tools, str):
+        return ""
+    entries: Final = tuple(
+        _field_reader(t)("function") or _field_reader(t)("custom") or t for t in tools if not isinstance(t, str)
+    )
+    lines: Final = tuple(
+        f"- {_field_reader(e)('name') or 'unnamed'}: {_field_reader(e)('description') or 'no description'}"
+        for e in entries
+    )
+    if not lines:
+        return ""
+    return ("Tools available to both responses:\n" + "\n".join(lines))[:_MAX_JUDGE_TOOL_DEFS_CHARS]
+
+
+def _judge_user_prompt(conversation: str, response_a: str, response_b: str, tool_definitions: str = "") -> str:
     """The judge prompt under one total character budget: each response is capped, and
-    the conversation tail gets whatever budget the responses left over."""
+    the conversation tail gets whatever budget the responses and tool definitions left
+    over."""
     a: Final = response_a[:_MAX_JUDGE_RESPONSE_CHARS]
     b: Final = response_b[:_MAX_JUDGE_RESPONSE_CHARS]
-    conversation_budget: Final = _MAX_JUDGE_PROMPT_CHARS - len(a) - len(b)
+    prefix: Final = f"{tool_definitions}\n\n" if tool_definitions else ""
+    conversation_budget: Final = _MAX_JUDGE_PROMPT_CHARS - len(a) - len(b) - len(prefix)
     return (
-        f"Conversation:\n{conversation[-conversation_budget:]}\n\n"
+        f"{prefix}Conversation:\n{conversation[-conversation_budget:]}\n\n"
         f"Response A:\n{a}\n\n"
         f"Response B:\n{b}\n\n"
         "Which response is better?"
@@ -942,6 +1038,7 @@ class ShadowEvalLogger(CustomLogger):
                 messages=messages,
                 real_text=real_text,
                 shadow_text=shadow.text,
+                tools=shadow_params.get("tools"),
                 parent_metadata=parent_metadata,
             )
             if isinstance(verdict, _CallFailure):
@@ -1080,15 +1177,18 @@ class ShadowEvalLogger(CustomLogger):
                 classifier_cost=_decision_classifier_cost(shadow_metadata),
             )
         text: Final = _chat_final_text(response)
+        routed_model: Final = str(
+            getattr(response, "model", None) or _routing_decision(shadow_metadata).get("routed_model") or ""
+        )
         if not text:
             return _CallFailure(
-                "shadow router returned an empty response",
+                _shadow_empty_reply_error(response, routed_model),
                 cost=_call_cost(response),
                 classifier_cost=_decision_classifier_cost(shadow_metadata),
             )
         return _ShadowResponse(
             text=text,
-            model=str(getattr(response, "model", None) or _routing_decision(shadow_metadata).get("routed_model") or ""),
+            model=routed_model,
             tier=_routed_tier(shadow_metadata),
             cost=_call_cost(response),
             classifier_cost=_decision_classifier_cost(shadow_metadata),
@@ -1100,9 +1200,12 @@ class ShadowEvalLogger(CustomLogger):
         messages: Sequence[Mapping[str, object]],
         real_text: str,
         shadow_text: str,
+        tools: object,
         parent_metadata: Mapping[str, object],
     ) -> "_JudgeVerdict | _CallFailure":
-        """Blind pairwise judge with A/B labels randomized to cancel position bias."""
+        """Blind pairwise judge with A/B labels randomized to cancel position bias. Both
+        arms were offered the same tools, so the judge is shown their definitions too: a
+        tool call is only assessable against what else was available to call instead."""
         real_is_a: Final = random.random() < 0.5
         response_a: Final = real_text if real_is_a else shadow_text
         response_b: Final = shadow_text if real_is_a else real_text
@@ -1117,7 +1220,7 @@ class ShadowEvalLogger(CustomLogger):
             {"role": "system", "content": PAIRWISE_JUDGE_SYSTEM_PROMPT},  # mutable-ok: SDK message
             {
                 "role": "user",
-                "content": _judge_user_prompt(conversation, response_a, response_b),
+                "content": _judge_user_prompt(conversation, response_a, response_b, _tool_definitions_text(tools)),
             },  # mutable-ok: SDK message
         ]
         try:

litellm/litellm_core_utils/prompt_templates/common_utils.py

@@ -229,6 +229,45 @@ def _content_parts_contain_image(parts: Sequence[object]) -> bool:
     return False
 
 
+def anthropic_image_source_to_openai_url(image_source: Mapping[str, object]) -> str | None:
+    """Data or remote URL for an Anthropic ``source`` block, in the form chat completions expects."""
+    source_type: Final = image_source.get("type")
+    if source_type == "base64":
+        media_type: Final = image_source.get("media_type") or "image/jpeg"
+        image_data: Final = image_source.get("data") or ""
+        return f"data:{media_type};base64,{image_data}" if image_data else None
+    if source_type == "url":
+        url: Final = image_source.get("url")
+        return url if isinstance(url, str) else ""
+    return None
+
+
+def _image_part_url(part: Mapping[str, object]) -> str | None:
+    """The image URL carried by one content part, whichever of the three dialects wrote it."""
+    part_type: Final = part.get("type")
+    if part_type == "image_url":
+        image_url: Final = part.get("image_url")
+        if isinstance(image_url, str):
+            return image_url
+        return image_url.get("url") if isinstance(image_url, Mapping) else None
+    if part_type == "input_image":
+        responses_url: Final = part.get("image_url")
+        return responses_url if isinstance(responses_url, str) else None
+    if part_type == "image":
+        source: Final = part.get("source")
+        return anthropic_image_source_to_openai_url(source) if isinstance(source, Mapping) else None
+    return None
+
+
+def as_openai_image_part(part: Mapping[str, object]) -> ChatCompletionImageObject | None:
+    """One image content part rewritten into chat-completions dialect, or None when it is not one.
+
+    Rebuilt rather than forwarded so no caller-controlled key beyond the URL rides along.
+    """
+    url: Final = _image_part_url(part)
+    return {"type": "image_url", "image_url": {"url": url}} if url else None
+
+
 def request_contains_image_content(messages: Sequence[Mapping[str, object]]) -> bool:
     """Whether any message carries an image content part, across the dialects that reach
     pre-routing hooks untranslated: chat-completions ``image_url``, Responses ``input_image``,

litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py

@@ -99,6 +99,7 @@ def create_tool_name_mapping(
 from openai.types.chat.chat_completion_chunk import Choice as OpenAIStreamingChoice
 
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    anthropic_image_source_to_openai_url,
     parse_tool_call_arguments,
     reasoning_content_from_thinking_blocks,
     with_prompt_cache_breakpoint,
@@ -1225,20 +1226,7 @@ class LiteLLMAnthropicMessagesAdapter:
         """
         if not isinstance(image_source, dict):
             return None
-
-        source_type: Final = image_source.get("type")
-
-        if source_type == "base64":
-            # Base64 image format
-            media_type: Final = image_source.get("media_type", "image/jpeg")
-            image_data: Final = image_source.get("data", "")
-            if image_data:
-                return f"data:{media_type};base64,{image_data}"
-        elif source_type == "url":
-            # URL-referenced image format
-            return image_source.get("url", "")
-
-        return None
+        return anthropic_image_source_to_openai_url(image_source)
 
     def _tool_result_content(self, raw_content: object) -> ToolResultContent:
         if isinstance(raw_content, str):

litellm/llms/azure/responses/transformation.py

@@ -6,6 +6,7 @@ from openai.types.responses import ResponseReasoningItem
 
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.url_utils import encode_url_path_segment
+from litellm.llms.azure.chat.gpt_5_transformation import AzureOpenAIGPT5Config
 from litellm.llms.azure.common_utils import BaseAzureLLM
 from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
 from litellm.types.llms.openai import *
@@ -29,6 +30,14 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
     def custom_llm_provider(self) -> LlmProviders:
         return LlmProviders.AZURE
 
+    @staticmethod
+    def _supports_reasoning_effort_none(model: str) -> bool:
+        return AzureOpenAIGPT5Config._supports_reasoning_effort_level(model, "none")
+
+    @staticmethod
+    def _effort_resolves_to_none(model: str, effort: str | None) -> bool:
+        return AzureOpenAIGPT5Config.effort_resolves_to_none(model, effort)
+
     def get_supported_openai_params(self, model: str) -> list:
         """
         Azure Responses API does not support context_management (compaction).

litellm/llms/bedrock/passthrough/guardrail_translation/handler.py

@@ -89,11 +89,24 @@ def _extract_converse_texts(
     top-level ``text`` blocks this scans the arbitrary-JSON fields a caller can
     hide prompt content in -- ``toolUse.input`` and
     ``toolResult.content[].json`` (alongside ``toolResult.content[].text``) --
-    as well as the request-level fields still forwarded to Bedrock that a caller
-    can route blocked content through: ``toolConfig.tools`` (tool names,
-    descriptions and input schemas) and ``additionalModelRequestFields``. Tool
-    message blocks are skipped when tool messages are excluded, but tool
-    definitions are always scanned to match the chat-completions guardrail path.
+    as well as ``additionalModelRequestFields``, a free-form model-parameter bag
+    with no schema that a caller can route blocked content through.
+
+    ``toolConfig.tools`` is deliberately NOT scanned. Tool definitions are
+    app-authored config, so their names, descriptions and JSON-schema strings
+    ("object", property names, titles, type names, enum values) would each reach
+    the guardrail as a separate INPUT item, producing false positives and
+    inflating guardrail usage for a request whose only prompt is one user
+    message. No other guardrail translation handler puts tool definitions in
+    ``texts``; the chat and messages handlers carry them in the structured
+    ``tools`` input instead, which this handler does not populate because a
+    Bedrock ``toolSpec`` is not the OpenAI tool shape those consumers expect.
+
+    ``additionalModelRequestFields`` is treated differently on purpose. Bedrock
+    gives ``toolConfig.tools`` a fixed schema whose contents are tool metadata by
+    contract, while ``additionalModelRequestFields`` is free-form and defined by
+    the target model, so what it carries cannot be classified without knowing
+    that model. Scanning it stays the fail-closed default.
     """
     holders: Final[list[_StringHolder]] = []
 
@@ -121,10 +134,6 @@ def _extract_converse_texts(
                         _collect_block_text(inner, holders)
                         _collect_strings(inner.get("json"), holders)
 
-    tool_config: Final = body.get("toolConfig")
-    if isinstance(tool_config, dict):
-        _collect_strings(tool_config.get("tools"), holders)
-
     _collect_strings(body.get("additionalModelRequestFields"), holders)
 
     texts: Final = [container[key] for container, key in holders]

litellm/model_prices_and_context_window_backup.json

@@ -7157,6 +7157,53 @@
         "supports_xhigh_reasoning_effort": true,
         "supports_minimal_reasoning_effort": false
     },
+    "azure/gpt-6-astra": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05,
+        "cache_read_input_token_cost": 1e-06,
+        "cache_read_input_token_cost_above_272k_tokens": 2e-06,
+        "input_cost_per_token": 1e-05,
+        "input_cost_per_token_above_272k_tokens": 2e-05,
+        "litellm_provider": "azure",
+        "max_input_tokens": 922000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "output_cost_per_token_above_272k_tokens": 7.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_minimal_reasoning_effort": false,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "azure/us/gpt-5.6": {
         "cache_creation_input_token_cost": 6.875e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,
@@ -7376,6 +7423,53 @@
         "supports_xhigh_reasoning_effort": true,
         "supports_minimal_reasoning_effort": false
     },
+    "azure/us/gpt-6-astra": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_272k_tokens": 2.75e-05,
+        "cache_read_input_token_cost": 1.1e-06,
+        "cache_read_input_token_cost_above_272k_tokens": 2.2e-06,
+        "input_cost_per_token": 1.1e-05,
+        "input_cost_per_token_above_272k_tokens": 2.2e-05,
+        "litellm_provider": "azure",
+        "max_input_tokens": 922000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "output_cost_per_token_above_272k_tokens": 8.25e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_minimal_reasoning_effort": false,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "azure/eu/gpt-5.6": {
         "cache_creation_input_token_cost": 6.875e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,

litellm/proxy/_lazy_openapi_snapshot.json

@@ -741,6 +741,32 @@
           "title": "AccessGroupInfo",
           "type": "object"
         },
+        "AccessGroupResource": {
+          "description": "A resource referenced by an access group. `name` is null when the id no longer resolves or has no alias.",
+          "properties": {
+            "id": {
+              "title": "Id",
+              "type": "string"
+            },
+            "name": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "null"
+                }
+              ],
+              "title": "Name"
+            }
+          },
+          "required": [
+            "id",
+            "name"
+          ],
+          "title": "AccessGroupResource",
+          "type": "object"
+        },
         "AccessGroupResponse": {
           "properties": {
             "access_agent_ids": {
@@ -750,6 +776,13 @@
               "title": "Access Agent Ids",
               "type": "array"
             },
+            "access_agents": {
+              "items": {
+                "$ref": "#/components/schemas/AccessGroupResource"
+              },
+              "title": "Access Agents",
+              "type": "array"
+            },
             "access_group_id": {
               "title": "Access Group Id",
               "type": "string"
@@ -765,6 +798,13 @@
               "title": "Access Mcp Server Ids",
               "type": "array"
             },
+            "access_mcp_servers": {
+              "items": {
+                "$ref": "#/components/schemas/AccessGroupResource"
+              },
+              "title": "Access Mcp Servers",
+              "type": "array"
+            },
             "access_model_names": {
               "items": {
                 "type": "string"
@@ -779,6 +819,13 @@
               "title": "Assigned Key Ids",
               "type": "array"
             },
+            "assigned_keys": {
+              "items": {
+                "$ref": "#/components/schemas/AccessGroupResource"
+              },
+              "title": "Assigned Keys",
+              "type": "array"
+            },
             "assigned_team_ids": {
               "items": {
                 "type": "string"
@@ -786,6 +833,13 @@
               "title": "Assigned Team Ids",
               "type": "array"
             },
+            "assigned_teams": {
+              "items": {
+                "$ref": "#/components/schemas/AccessGroupResource"
+              },
+              "title": "Assigned Teams",
+              "type": "array"
+            },
             "created_at": {
               "format": "date-time",
               "title": "Created At",
@@ -838,6 +892,10 @@
             "access_agent_ids",
             "assigned_team_ids",
             "assigned_key_ids",
+            "access_mcp_servers",
+            "access_agents",
+            "assigned_teams",
+            "assigned_keys",
             "created_at",
             "updated_at"
           ],

litellm/proxy/common_utils/http_parsing_utils.py

@@ -2,11 +2,11 @@ import json
 import re
 from collections.abc import Collection, Mapping
 from types import MappingProxyType, UnionType
-from typing import Any, Final, Union, get_args, get_origin
+from typing import Annotated, Any, Final, Union, get_args, get_origin
 
 import orjson
 from fastapi import Request, UploadFile, status
-from typing_extensions import ReadOnly
+from typing_extensions import NotRequired, ReadOnly, Required
 
 from litellm._logging import verbose_proxy_logger
 from litellm.constants import MAX_REQUEST_BODY_SIZE_TO_REPAIR_MB
@@ -18,6 +18,8 @@ from litellm.types.router import Deployment
 
 _FORM_CONTENT_TYPES: Final[frozenset[str]] = frozenset({"application/x-www-form-urlencoded", "multipart/form-data"})
 
+_ANNOTATION_QUALIFIERS: Final[frozenset[object]] = frozenset({Annotated, NotRequired, ReadOnly, Required})
+
 
 def _normalize_media_type(content_type: str) -> str:
     """Return the bare media type per RFC 7231: strip params, trim, lowercase."""
@@ -42,9 +44,17 @@ def _is_json_content_type(content_type: str) -> bool:
     return _normalize_media_type(content_type) == "application/json"
 
 
+def _unqualified(annotation: object) -> object:
+    """Which qualifiers ``get_type_hints`` already stripped varies by interpreter version, so peel them all."""
+    if get_origin(annotation) not in _ANNOTATION_QUALIFIERS:
+        return annotation
+    qualified: Final[tuple[object, ...]] = get_args(annotation)
+    return _unqualified(qualified[0])
+
+
 def _numeric_form_type(annotation: object) -> type[int] | type[float] | None:
     """The scalar to parse an ``int``/``float``-typed field as, else ``None``."""
-    unwrapped: Final = get_args(annotation)[0] if get_origin(annotation) is ReadOnly else annotation
+    unwrapped: Final = _unqualified(annotation)
     candidates: Final = (
         tuple(arg for arg in get_args(unwrapped) if arg is not type(None))
         if get_origin(unwrapped) in (Union, UnionType)

litellm/proxy/common_utils/reset_budget_job.py

@@ -38,6 +38,7 @@ from litellm.proxy.common_utils.timezone_utils import (
     get_budget_reset_settings,
 )
 from litellm.proxy.common_utils.user_api_key_cache import (
+    end_user_cache_key,
     model_access_group_cache_key,
     model_access_group_spend_counter_key,
     tag_cache_key,
@@ -177,6 +178,21 @@ def _model_access_group_cache_keys(row: _ModelAccessGroupRow) -> tuple[str, ...]
     return (model_access_group_cache_key(row.access_group_name),)
 
 
+def _enduser_counter_key(row: _EndUserRow) -> str:
+    return f"spend:end_user:{row.user_id}"
+
+
+def _enduser_cache_keys(row: _EndUserRow) -> tuple[str, ...]:
+    return (end_user_cache_key(row.user_id),)
+
+
+def _enduser_carried_spend(row: _EndUserRow, caps: Mapping[str, float]) -> float:
+    if not caps:
+        return 0.0
+    effective_budget_id: Final[str | None] = row.budget_id or litellm.max_end_user_budget_id
+    return _carried_spend(row.spend, caps.get(effective_budget_id) if effective_budget_id is not None else None)
+
+
 def _budget_link_where(
     budget_ids: Sequence[str],
     extra: Mapping[str, object] = MappingProxyType({}),
@@ -650,6 +666,7 @@ class ResetBudgetJob:
             if _rollover_enabled()
             else {}  # mutable-ok: empty sentinel immediately frozen by MappingProxyType
         )
+        endusers: Final[tuple[_EndUserRow, ...]] = await self._collect_endusers_to_reset(budget_ids)
         return _BudgetCascade(
             budgets=tuple(budgets_to_reset),
             budget_ids=budget_ids,
@@ -661,7 +678,7 @@ class ResetBudgetJob:
                 for b in budgets_to_reset
                 if b.budget_id is not None and b.budget_duration is not None
             ),
-            endusers=await self._collect_endusers_to_reset(budget_ids),
+            endusers=endusers,
             counter_resets=(
                 *(
                     (_team_membership_counter_key(row), _row_carried_spend(row, rollover_caps))
@@ -674,6 +691,7 @@ class ResetBudgetJob:
                     (_model_access_group_counter_key(row), _row_carried_spend(row, rollover_caps))
                     for row in model_access_groups
                 ),
+                *((_enduser_counter_key(row), _enduser_carried_spend(row, rollover_caps)) for row in endusers),
             ),
             rollover_caps=rollover_caps,
             cache_keys=(
@@ -682,6 +700,7 @@ class ResetBudgetJob:
                 *(key for row in orgs for key in _org_cache_keys(row)),
                 *(key for row in tags for key in _tag_cache_keys(row)),
                 *(key for row in model_access_groups for key in _model_access_group_cache_keys(row)),
+                *(key for row in endusers for key in _enduser_cache_keys(row)),
             ),
         )
 

litellm/proxy/db/spend_counter_reseed.py

@@ -26,6 +26,7 @@ from litellm.proxy._types import Litellm_EntityType
 from litellm.repositories.organization_repository import OrganizationRepository
 from litellm.repositories.table_repositories import (
     BudgetWindowSpendRepository,
+    EndUserRepository,
     SpendLogsRepository,
     TeamMembershipRepository,
 )
@@ -36,6 +37,8 @@ from litellm.repositories.verification_token_repository import (
 )
 
 if TYPE_CHECKING:
+    from prisma.types import LiteLLM_EndUserTableWhereUniqueInput
+
     from litellm.caching.dual_cache import DualCache
     from litellm.proxy.utils import PrismaClient
 
@@ -47,6 +50,8 @@ _WINDOW_SPEND_ENTITY_TYPES: Final[Mapping[str, str]] = MappingProxyType(
     }
 )
 
+END_USER_COUNTER_PREFIX: Final = "spend:end_user:"
+
 _WINDOW_SPEND_LOG_FIELDS: Final[Mapping[str, str]] = MappingProxyType(
     {
         "Key": "api_key",
@@ -74,6 +79,10 @@ class SpendCounterReseed:
     End-user and tag spend counters intentionally do not reseed here. Their
     auth paths already load the corresponding objects via get_end_user_object()
     and get_tag_objects_batch(); callers pass those values as fallback_spend.
+    end_user_from_db is the one end-user read, used only as the budget floor when
+    a counter sits below that cached spend: a worker that did not run the budget
+    reset still caches the pre-reset end-user object, and LiteLLM_EndUserTable
+    is the row the reset zeroed.
     """
 
     _locks: ClassVar["OrderedDict[str, asyncio.Lock]"] = OrderedDict()
@@ -129,7 +138,7 @@ class SpendCounterReseed:
             elif counter_key.startswith("spend:user:"):
                 user_id = counter_key[len("spend:user:") :]
                 row = await UserRepository(prisma_client).table.find_unique(where={"user_id": user_id})
-            elif counter_key.startswith("spend:end_user:") or counter_key.startswith("spend:tag:"):
+            elif counter_key.startswith(END_USER_COUNTER_PREFIX) or counter_key.startswith("spend:tag:"):
                 return None
             elif counter_key.startswith("spend:org:"):
                 org_id: Final = counter_key[len("spend:org:") :]
@@ -143,6 +152,20 @@ class SpendCounterReseed:
             return None
         return float(getattr(row, "spend", 0.0) or 0.0)
 
+    @staticmethod
+    async def end_user_from_db(prisma_client: Optional["PrismaClient"], counter_key: str) -> float | None:
+        if prisma_client is None or not counter_key.startswith(END_USER_COUNTER_PREFIX):
+            return None
+        where: Final[LiteLLM_EndUserTableWhereUniqueInput] = {"user_id": counter_key[len(END_USER_COUNTER_PREFIX) :]}
+        try:
+            row: Final = await EndUserRepository(prisma_client).table.find_unique(where=where)
+        except Exception:  # noqa: BLE001  # a failed floor read falls back to the cached spend, like from_db
+            verbose_proxy_logger.exception("SpendCounterReseed.end_user_from_db: failed for %s", counter_key)
+            return None
+        if row is None:
+            return None
+        return float(row.spend or 0.0)
+
     @staticmethod
     def _is_key_or_team_window_counter(counter_key: str) -> bool:
         for prefix in ("spend:key:", "spend:team:"):

litellm/proxy/management_endpoints/access_group_endpoints.py

@@ -1,16 +1,20 @@
-from collections.abc import Mapping, Sequence
+import asyncio
+from collections.abc import Callable, Mapping, Sequence
+from dataclasses import dataclass
 from types import MappingProxyType
 from typing import Final, Protocol
 
 from fastapi import APIRouter, Depends, HTTPException, status
 
 from litellm._logging import verbose_proxy_logger
+from litellm.proxy._experimental.mcp_server.mcp_server_manager import global_mcp_server_manager
 from litellm.proxy._types import (
     CommonProxyErrors,
     LiteLLM_AccessGroupTable,
     LitellmUserRoles,
     UserAPIKeyAuth,
 )
+from litellm.proxy.agent_endpoints.agent_registry import global_agent_registry
 from litellm.proxy.auth.auth_checks import (
     _cache_access_object,
     _cache_key_object,
@@ -20,10 +24,16 @@ from litellm.proxy.auth.auth_checks import (
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
 from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler
 from litellm.proxy.management_helpers.access_group_team_sync import invalidate_access_group_cache
-from litellm.proxy.utils import get_prisma_client_or_throw
+from litellm.proxy.management_helpers.resource_display_names import (
+    agent_display_names,
+    key_display_names,
+    mcp_server_display_names,
+)
+from litellm.proxy.utils import PrismaClient, get_prisma_client_or_throw
 from litellm.repositories.table_repositories import AccessGroupRepository, TeamRepository
 from litellm.types.access_group import (
     AccessGroupCreateRequest,
+    AccessGroupResource,
     AccessGroupResponse,
     AccessGroupUpdateRequest,
 )
@@ -37,6 +47,12 @@ class _AccessGroupRecord(Protocol):
     @property
     def access_group_id(self) -> str: ...
 
+    @property
+    def access_mcp_server_ids(self) -> Sequence[str] | None: ...
+
+    @property
+    def access_agent_ids(self) -> Sequence[str] | None: ...
+
     @property
     def assigned_team_ids(self) -> Sequence[str] | None: ...
 
@@ -50,6 +66,9 @@ class _TeamRecord(Protocol):
     @property
     def team_id(self) -> str: ...
 
+    @property
+    def team_alias(self) -> str | None: ...
+
     @property
     def access_group_ids(self) -> Sequence[str] | None: ...
 
@@ -120,16 +139,75 @@ def _require_admin_view(user_api_key_dict: UserAPIKeyAuth) -> None:
         )
 
 
+@dataclass(frozen=True, slots=True)
+class _ResourceNames:
+    mcp_servers: Mapping[str, str]
+    agents: Mapping[str, str]
+    teams: Mapping[str, str | None]
+    keys: Mapping[str, str]
+
+
+def _label(ids: Sequence[str], names: Mapping[str, str | None]) -> tuple[AccessGroupResource, ...]:
+    return tuple(AccessGroupResource(id=resource_id, name=names.get(resource_id)) for resource_id in ids)
+
+
 def _record_to_response(
-    record: _AccessGroupRecord, *, assigned_team_ids: Sequence[str] | None = None
+    record: _AccessGroupRecord, *, assigned_team_ids: Sequence[str], names: _ResourceNames
 ) -> AccessGroupResponse:
-    stored: Final = record.dict()
-    payload: Final = (
-        stored if assigned_team_ids is None else MappingProxyType({**stored, "assigned_team_ids": assigned_team_ids})
+    payload: Final = MappingProxyType(
+        {
+            **record.dict(),
+            "assigned_team_ids": assigned_team_ids,
+            "access_mcp_servers": _label(record.access_mcp_server_ids or (), names.mcp_servers),
+            "access_agents": _label(record.access_agent_ids or (), names.agents),
+            "assigned_teams": _label(assigned_team_ids, names.teams),
+            "assigned_keys": _label(record.assigned_key_ids or (), names.keys),
+        }
     )
     return AccessGroupResponse.model_validate(payload)
 
 
+def _ids_across(
+    records: Sequence[_AccessGroupRecord], pick: Callable[[_AccessGroupRecord], Sequence[str] | None]
+) -> tuple[str, ...]:
+    return tuple(dict.fromkeys(resource_id for record in records for resource_id in (pick(record) or ())))
+
+
+async def _responses_for(
+    prisma_client: PrismaClient, records: Sequence[_AccessGroupRecord]
+) -> tuple[AccessGroupResponse, ...]:
+    if not records:
+        return ()
+    teams: Final = await _teams_touching(TeamRepository(prisma_client).table, records)
+    mcp_servers, agents, keys = await asyncio.gather(
+        mcp_server_display_names(
+            prisma_client,
+            _ids_across(records, lambda record: record.access_mcp_server_ids),
+            global_mcp_server_manager.config_mcp_servers,
+        ),
+        agent_display_names(
+            prisma_client, _ids_across(records, lambda record: record.access_agent_ids), global_agent_registry
+        ),
+        key_display_names(prisma_client, _ids_across(records, lambda record: record.assigned_key_ids)),
+    )
+    names: Final = _ResourceNames(
+        mcp_servers=mcp_servers,
+        agents=agents,
+        teams=MappingProxyType({team.team_id: team.team_alias for team in teams}),
+        keys=keys,
+    )
+    attached: Final = _attached_team_ids_by_group(records, teams)
+    return tuple(
+        _record_to_response(record, assigned_team_ids=attached[record.access_group_id], names=names)
+        for record in records
+    )
+
+
+async def _response_for(prisma_client: PrismaClient, record: _AccessGroupRecord) -> AccessGroupResponse:
+    (response,) = await _responses_for(prisma_client, (record,))
+    return response
+
+
 def _attached_team_ids_by_group(
     records: Sequence[_AccessGroupRecord], teams: Sequence[_TeamRecord]
 ) -> Mapping[str, tuple[str, ...]]:
@@ -144,19 +222,21 @@ def _attached_team_ids_by_group(
     return MappingProxyType({record.access_group_id: attached(record) for record in records})
 
 
+async def _teams_touching(team_table: _TeamTable, records: Sequence[_AccessGroupRecord]) -> Sequence[_TeamRecord]:
+    """Team rows listed on any of the groups or carrying any of them in access_group_ids."""
+    group_ids: Final = tuple(record.access_group_id for record in records)
+    stored_team_ids: Final = _ids_across(records, lambda record: record.assigned_team_ids)
+    carrying: Final = {"access_group_ids": {"hasSome": group_ids}}  # mutable-ok: prisma where is a dict
+    listed: Final = {"team_id": {"in": stored_team_ids}}  # mutable-ok: prisma where is a dict
+    return await team_table.find_many(where={"OR": (carrying, listed)})  # mutable-ok: prisma where is a dict
+
+
 async def _attached_team_ids_for(
     team_table: _TeamTable, records: Sequence[_AccessGroupRecord]
 ) -> Mapping[str, tuple[str, ...]]:
     if not records:
         return MappingProxyType({})
-    group_ids: Final = tuple(record.access_group_id for record in records)
-    stored_team_ids: Final = tuple(
-        dict.fromkeys(team_id for record in records for team_id in (record.assigned_team_ids or ()))
-    )
-    carrying: Final = {"access_group_ids": {"hasSome": group_ids}}  # mutable-ok: prisma where is a dict
-    listed: Final = {"team_id": {"in": stored_team_ids}}  # mutable-ok: prisma where is a dict
-    teams: Final = await team_table.find_many(where={"OR": (carrying, listed)})  # mutable-ok: prisma where is a dict
-    return _attached_team_ids_by_group(records, teams)
+    return _attached_team_ids_by_group(records, await _teams_touching(team_table, records))
 
 
 async def _require_teams_exist(tx: _AccessGroupTx, team_ids: Sequence[str]) -> None:
@@ -425,7 +505,7 @@ async def create_access_group(
         proxy_logging_obj,
     )
 
-    return _record_to_response(record)
+    return await _response_for(prisma_client, record)
 
 
 @router.get(
@@ -434,14 +514,13 @@ async def create_access_group(
 )
 async def list_access_groups(
     user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
-) -> list[AccessGroupResponse]:
+) -> Sequence[AccessGroupResponse]:
     _require_admin_view(user_api_key_dict)
     prisma_client: Final = get_prisma_client_or_throw(CommonProxyErrors.db_not_connected_error.value)
 
     table: Final = AccessGroupRepository(prisma_client).table
     records: Final = await table.find_many(order={"created_at": "desc"})
-    attached: Final = await _attached_team_ids_for(TeamRepository(prisma_client).table, records)
-    return [_record_to_response(r, assigned_team_ids=attached[r.access_group_id]) for r in records]
+    return await _responses_for(prisma_client, records)
 
 
 @router.get(
@@ -462,8 +541,7 @@ async def get_access_group(
             status_code=status.HTTP_404_NOT_FOUND,
             detail=f"Access group '{access_group_id}' not found",
         )
-    attached: Final = await _attached_team_ids_for(TeamRepository(prisma_client).table, (record,))
-    return _record_to_response(record, assigned_team_ids=attached[record.access_group_id])
+    return await _response_for(prisma_client, record)
 
 
 @router.put(
@@ -560,7 +638,7 @@ async def update_access_group(
     await _patch_key_caches_add_access_group(keys_to_add, access_group_id, user_api_key_cache, proxy_logging_obj)
     await _patch_key_caches_remove_access_group(keys_to_remove, access_group_id, user_api_key_cache, proxy_logging_obj)
 
-    return _record_to_response(record)
+    return await _response_for(prisma_client, record)
 
 
 @router.delete(

litellm/proxy/management_endpoints/team_endpoints.py

@@ -3326,9 +3326,6 @@ async def team_member_delete(
             data=data,
         )
 
-        if not removed_team_members:
-            raise HTTPException(status_code=400, detail={"error": "User not found in team"})
-
         existing_team_row.members_with_roles = new_team_members
 
         _db_new_team_members: Final[list[dict]] = [m.model_dump() for m in new_team_members]
@@ -3336,17 +3333,27 @@ async def team_member_delete(
         ## DELETE TEAM ID from USER ROW, IF EXISTS ##
         # get user row
         removed_user_ids: Final = frozenset(m.user_id for m in removed_team_members if m.user_id is not None)
+        addressed_user_ids: Final = (
+            removed_user_ids if removed_team_members else frozenset((data.user_id,) if data.user_id is not None else ())
+        )
         key_val: Final[Mapping[str, object]] = (
-            {"user_id": {"in": sorted(removed_user_ids)}} if removed_user_ids else {"user_email": data.user_email}
+            {"user_id": {"in": sorted(addressed_user_ids)}} if addressed_user_ids else {"user_email": data.user_email}
         )
         member_tx: Final[_MemberDeleteTx] = tx
         existing_user_rows: Final = await member_tx.litellm_usertable.find_many(where=key_val)
 
-        # Also clean up any existing team membership rows for this user and team
-        user_ids_to_delete: Final = removed_user_ids.union(
-            (data.user_id,) if data.user_id is not None else (),
-            (user.user_id for user in existing_user_rows if user.user_id),
-        )
+        # A user row can outlive its roster entry, and until the team is off user.teams the user
+        # still sees it and still fails key creation against it, so removal has to clear it too
+        stale_user_rows: Final = tuple(user for user in existing_user_rows if data.team_id in user.teams)
+
+        # Also clean up any existing team membership rows for this user and team. An email can
+        # match several user rows, so with no roster entry to name the member, only the rows
+        # actually carrying the team are the ones this request is allowed to touch
+        cleanup_user_rows: Final = existing_user_rows if removed_team_members else stale_user_rows
+        user_ids_to_delete: Final = addressed_user_ids.union(user.user_id for user in cleanup_user_rows if user.user_id)
+
+        if not removed_team_members and not stale_user_rows:
+            raise HTTPException(status_code=400, detail={"error": "User not found in team"})
 
         ## DELETE KEYS CREATED BY USER FOR THIS TEAM
         # Fetch keys before deletion so their audit records can be persisted alongside the delete.
@@ -3358,17 +3365,17 @@ async def team_member_delete(
             }
         )
 
-        await _team_tx_db(tx).update(
-            where={"team_id": data.team_id},
-            data={"members_with_roles": json.dumps(_db_new_team_members)},
-        )
+        if removed_team_members:
+            await _team_tx_db(tx).update(
+                where={"team_id": data.team_id},
+                data={"members_with_roles": json.dumps(_db_new_team_members)},
+            )
 
-        for existing_user in existing_user_rows:
-            if data.team_id in existing_user.teams:
-                await tx.litellm_usertable.update(
-                    where={"user_id": existing_user.user_id},
-                    data={"teams": {"set": [team for team in existing_user.teams if team != data.team_id]}},
-                )
+        for existing_user in stale_user_rows:
+            await tx.litellm_usertable.update(
+                where={"user_id": existing_user.user_id},
+                data={"teams": {"set": [team for team in existing_user.teams if team != data.team_id]}},
+            )
 
         for _uid in sorted(user_ids_to_delete):
             await tx.litellm_teammembership.delete_many(where={"team_id": data.team_id, "user_id": _uid})

litellm/proxy/management_helpers/resource_display_names.py

@@ -0,0 +1,61 @@
+"""Display names for ids stored on management objects. DB rows win; config-declared servers and agents fill the gaps."""
+
+from collections.abc import Mapping, Sequence
+from types import MappingProxyType
+from typing import Final
+
+from litellm.proxy.agent_endpoints.agent_registry import AgentRegistry
+from litellm.proxy.utils import PrismaClient
+from litellm.repositories.table_repositories import AgentsRepository, MCPServerRepository
+from litellm.repositories.verification_token_repository import VerificationTokenRepository
+from litellm.types.mcp_server.mcp_server_manager import MCPServer
+
+
+async def mcp_server_display_names(
+    prisma_client: PrismaClient,
+    server_ids: Sequence[str],
+    config_servers: Mapping[str, MCPServer],
+) -> Mapping[str, str]:
+    """server_id -> alias, falling back to server_name; config-only servers also fall back to their registry name."""
+    if not server_ids:
+        return MappingProxyType({})
+    wanted: Final = frozenset(server_ids)
+    where: Final = {"server_id": {"in": tuple(wanted)}}  # mutable-ok: prisma where is a dict
+    rows: Final = await MCPServerRepository(prisma_client).table.find_many(where=where)
+    from_config: Final = {
+        server_id: server.alias or server.server_name or server.name
+        for server_id, server in config_servers.items()
+        if server_id in wanted
+    }
+    from_db: Final = {row.server_id: name for row in rows if (name := row.alias or row.server_name)}
+    return MappingProxyType({**from_config, **from_db})
+
+
+async def agent_display_names(
+    prisma_client: PrismaClient,
+    agent_ids: Sequence[str],
+    registry: AgentRegistry,
+) -> Mapping[str, str]:
+    """agent_id -> agent_name. The registry covers config-declared agents and their legacy ids."""
+    if not agent_ids:
+        return MappingProxyType({})
+    wanted: Final = frozenset(agent_ids)
+    where: Final = {"agent_id": {"in": tuple(wanted)}}  # mutable-ok: prisma where is a dict
+    rows: Final = await AgentsRepository(prisma_client).table.find_many(where=where)
+    from_registry: Final = {
+        alias_id: agent.agent_name
+        for agent in registry.get_agent_list()
+        for alias_id in registry.ids_for_agent(agent.agent_id)
+        if alias_id in wanted
+    }
+    from_db: Final = {row.agent_id: row.agent_name for row in rows}
+    return MappingProxyType({**from_registry, **from_db})
+
+
+async def key_display_names(prisma_client: PrismaClient, tokens: Sequence[str]) -> Mapping[str, str]:
+    """token hash -> key_alias for the keys that have one."""
+    if not tokens:
+        return MappingProxyType({})
+    where: Final = {"token": {"in": tuple(frozenset(tokens))}}  # mutable-ok: prisma where is a dict
+    rows: Final = await VerificationTokenRepository(prisma_client).table.find_many(where=where)
+    return MappingProxyType({row.token: row.key_alias for row in rows if row.key_alias})

litellm/proxy/proxy_server.py

@@ -423,7 +423,7 @@ from litellm.proxy.db.proxy_worker_heartbeat import (
     PROXY_WORKER_HEARTBEAT_INTERVAL_SECONDS,
     ProxyWorkerHeartbeat,
 )
-from litellm.proxy.db.spend_counter_reseed import SpendCounterReseed
+from litellm.proxy.db.spend_counter_reseed import END_USER_COUNTER_PREFIX, SpendCounterReseed
 from litellm.proxy.discovery_endpoints import ui_discovery_endpoints_router
 from litellm.proxy.fine_tuning_endpoints.endpoints import router as fine_tuning_router
 from litellm.proxy.fine_tuning_endpoints.endpoints import set_fine_tuning_config
@@ -2477,7 +2477,8 @@ async def get_current_spend(
     authoritative source depends on the counter: primary key/team/user/org
     counters read the DB row; per-window counters (``window_start`` supplied)
     read the maintained window-spend row and only aggregate spend logs when
-    that row is missing or stale; end-user/tag counters have no DB row, so the caller's
+    that row is missing or stale; end-user counters read ``LiteLLM_EndUserTable``, the
+    row the budget reset zeroes; tag counters have no DB row, so the caller's
     ``fallback_spend`` (loaded fresh in auth) is authoritative. The DB read is
     skipped for healthy primary counters (counter at or above recorded spend)
     and cached in-process for a few seconds, so a persistently stale counter
@@ -2511,8 +2512,8 @@ async def get_current_spend(
                 await _repair_stale_spend_counter(counter_key=counter_key, db_spend=authoritative)
                 return authoritative
         elif fallback_spend > current:
-            # end-user / tag counters have no DB row; fallback_spend is the
-            # authoritative recorded value loaded in auth.
+            # nothing to read (tag counters, an end user without a row or a DB client, a
+            # failed read); fallback_spend is the authoritative recorded value loaded in auth.
             return fallback_spend
 
     # Opt-in hard guarantee: when the spend backing this admit decision came
@@ -2580,6 +2581,29 @@ async def reseed_spend_counter_from_db(counter_key: str) -> None:
     await _repair_stale_spend_counter(counter_key=counter_key, db_spend=db_spend)
 
 
+async def _floor_spend_from_db(
+    counter_key: str,
+    window_entity_type: str | None,
+    window_entity_id: str | None,
+    window_duration: str | None,
+    window_start: datetime | None,
+) -> float | None:
+    if counter_key.startswith(END_USER_COUNTER_PREFIX):
+        return await SpendCounterReseed.end_user_from_db(prisma_client=prisma_client, counter_key=counter_key)
+    entity_spend: Final = await SpendCounterReseed.from_db(prisma_client=prisma_client, counter_key=counter_key)
+    if entity_spend is not None:
+        return entity_spend
+    if window_entity_type is None or window_entity_id is None or window_start is None:
+        return None
+    return await SpendCounterReseed.window_from_db(
+        prisma_client=prisma_client,
+        entity_type=window_entity_type,
+        entity_id=window_entity_id,
+        window_duration=window_duration,
+        window_start=window_start,
+    )
+
+
 async def _authoritative_floor_spend(
     counter_key: str,
     window_entity_type: str | None = None,
@@ -2592,20 +2616,13 @@ async def _authoritative_floor_spend(
     if cached is not None:
         return float(cached)
 
-    db_spend = await SpendCounterReseed.from_db(prisma_client=prisma_client, counter_key=counter_key)
-    if (
-        db_spend is None
-        and window_entity_type is not None
-        and window_entity_id is not None
-        and window_start is not None
-    ):
-        db_spend = await SpendCounterReseed.window_from_db(
-            prisma_client=prisma_client,
-            entity_type=window_entity_type,
-            entity_id=window_entity_id,
-            window_duration=window_duration,
-            window_start=window_start,
-        )
+    db_spend: Final = await _floor_spend_from_db(
+        counter_key=counter_key,
+        window_entity_type=window_entity_type,
+        window_entity_id=window_entity_id,
+        window_duration=window_duration,
+        window_start=window_start,
+    )
     if db_spend is None:
         return None
 

litellm/router_strategy/complexity_router/README.md

@@ -247,6 +247,58 @@ unless `modality_routing` is also on.
 
 `session_affinity_ttl_seconds` is the idle window for both the model pin selected by session affinity and the deployment pin. Every request that reuses a pin refreshes its TTL, so a session actively sending requests stays pinned. After the window passes with no pin reuse, the next request classifies again and creates a fresh pin. Omit the setting to track the default of 3600 seconds.
 
+### Mid-task stall escalation
+
+A weak model working an agentic task can get stuck: it keeps calling the same tool with the
+same arguments, or the same call keeps erroring, when a stronger model would have broken the
+loop. `stall_escalation_enabled: true` catches this and bumps the request one tier higher, the
+automatic counterpart to a user typing an escalation keyword:
+
+```yaml
+model_list:
+  - model_name: smart-router
+    litellm_params:
+      model: auto_router/complexity_router
+      complexity_router_config:
+        stall_escalation_enabled: true
+        stall_escalation_window: 6
+        stall_escalation_repeat_threshold: 3
+        tiers:
+          SIMPLE: gpt-4o-mini
+          MEDIUM: gpt-4o
+          COMPLEX: claude-sonnet-4
+          REASONING: o1-preview
+```
+
+Detection looks at the assistant's own tool calls, not the human's messages. The task counts as
+stalled when the NEWEST tool call is still part of a stuck pattern: it repeats, or it errored, at
+least `stall_escalation_repeat_threshold` times across the last `stall_escalation_window` calls.
+The tier is then bumped one step by the same `_escalate_tier` ladder `escalation_keywords` uses,
+capped at the highest configured tier. It reads both tool-call shapes: Anthropic Messages
+`tool_use`/`tool_result` blocks (including `is_error`) and chat-completions `tool_calls`/`tool`
+messages (which carry no standard error flag, so those calls are judged on repetition alone).
+
+Anchoring on the newest call is what keeps a recovered task from being escalated on stale
+evidence. A model that tried the same command three times and then moved on still has those
+three calls sitting in the window for a few turns, and counting whichever pattern is most common
+in the window would escalate a request that is already making progress again. Anchoring still
+leaves room between the matches, so a retry loop broken up by an unrelated lookup counts.
+
+There is no state to expire or leak: detection reruns on every classified turn from that
+request's own message list, so the bump lasts only as long as the recent tool calls still look
+stuck and lifts on its own the moment they don't. This also means it reads the whole
+conversation rather than only the turns since the newest human ask, so a plain follow-up like
+"try again" does not discard evidence from before it. Escalation records `stall_escalation` in
+`routing_decision.signals`; unlike `escalation_keywords`, it does not set the
+`escalated`/`escalation_keyword` pair, which is reserved for the keyword mechanism specifically.
+
+`stall_escalation_enabled` cannot be combined with `session_affinity` or
+`classification_mode: user_turn`: both replay a held routing decision on most turns instead of
+classifying, so detection would never see the tool calls it needs to look at. It is also
+rejected together with `tier_definitions`, for the same reason `escalation_keywords` is: both
+rely on the built-in tier severity order, which a custom tier set does not define. Off by
+default.
+
 ### Heuristic-first chaining
 
 `classifier_type: heuristic_first` runs the local scorer on every request and only calls the LLM

litellm/router_strategy/complexity_router/complexity_router.py

@@ -40,7 +40,10 @@ from litellm.litellm_core_utils.core_helpers import (
     get_metadata_variable_name_from_kwargs,
 )
 from litellm.litellm_core_utils.internal_call_metadata import forwarded_internal_call_metadata
-from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content
+from litellm.litellm_core_utils.prompt_templates.common_utils import (
+    as_openai_image_part,
+    request_contains_image_content,
+)
 from litellm.litellm_core_utils.sensitive_data_masker import mask_credentials_in_payload
 from litellm.llms.base_llm.base_utils import type_to_response_format_param
 from litellm.router_strategy.adaptive_router.classifier import classify_prompt
@@ -48,7 +51,11 @@ from litellm.router_strategy.complexity_router.tier_predictor import (
     TierSuccessPredictor,
     resolve_tier_artifact,
 )
-from litellm.types.llms.openai import AllMessageValues
+from litellm.types.llms.openai import (
+    AllMessageValues,
+    ChatCompletionImageObject,
+    ChatCompletionTextObject,
+)
 from litellm.types.utils import (
     AUTOROUTER_CLASSIFIER_CALL_ORIGIN,
     ModelResponse,
@@ -76,6 +83,7 @@ from .config import (
     ComplexityTier,
     TierDefinition,
 )
+from .stall_detector import detect_stalled_task
 
 if TYPE_CHECKING:
     from semantic_router.routers import SemanticRouter
@@ -434,6 +442,23 @@ def _strip_reminder_blocks(text: str, marker_pairs: tuple[tuple[str, str], ...]
     return " ".join(kept for a, b in zip(keep_from, keep_to) if (kept := text[a:b].strip()))
 
 
+def _inline_image_part(part: Mapping[str, object]) -> ChatCompletionImageObject | None:
+    """One image content part safe to hand the classifier, or None.
+
+    Inline data URIs only. A remote URL is caller-controlled and provider adapters do not uniformly
+    delegate fetching to the provider: gigachat's file handler downloads any non-data URL with
+    `client.get` from the proxy host, so forwarding one would let a key scoped to this router aim a
+    proxy-side request at an internal address, on a call the caller never asked for. The routed
+    model still receives the original URL exactly as before.
+    """
+    converted: Final = as_openai_image_part(part)
+    if converted is None:
+        return None
+    image_url: Final = converted["image_url"]
+    url: Final = image_url if isinstance(image_url, str) else image_url.get("url", "")
+    return converted if url.startswith("data:") else None
+
+
 def _human_text(content: object, marker_pairs: tuple[tuple[str, str], ...] = _DEFAULT_REMINDER_MARKERS) -> str:
     """Message content as the text a human wrote, with complete reminder blocks removed.
 
@@ -1591,6 +1616,10 @@ class ComplexityRouter(CustomLogger):
         threshold check alone would hand that traffic to the cheapest model without ever consulting
         the classifier. Scores also go negative when simple indicators fire, so a score threshold
         would reject exactly the trivial prompts this path exists to serve.
+
+        A turn carrying images the classifier would see is never decided cheaply: the scorer reads
+        text alone, so its confidence describes a request it has only partly seen, and a trivial
+        caption beside a screenshot is exactly the misrouting vision classification exists to stop.
         """
         tier, score, signals, cause = self._score_and_classify(prompt, system_prompt)
         scored: Final = ClassificationOutcome(tier=tier, score=score, signals=signals, cause=cause)
@@ -1598,6 +1627,7 @@ class ComplexityRouter(CustomLogger):
         decided_cheaply: Final = (
             threshold is not None
             and bool(signals)
+            and not self._classifier_image_parts(messages)
             and self._active_tier_severity(tier) <= self._active_tier_severity(threshold)
         )
         if decided_cheaply:
@@ -1622,11 +1652,43 @@ class ComplexityRouter(CustomLogger):
         tier, score, signals, cause = self._score_and_classify(prompt, system_prompt)
         scored: Final = ClassificationOutcome(tier=tier, score=score, signals=signals, cause=cause)
         margin: Final = self.config.hybrid_boundary_margin
-        decided: Final = margin is not None and bool(signals) and not self._is_near_tier_boundary(score, margin)
+        decided: Final = (
+            margin is not None
+            and bool(signals)
+            and not self._classifier_image_parts(messages)
+            and not self._is_near_tier_boundary(score, margin)
+        )
         if decided:
             return ClassificationOutcome(tier=tier, score=score, signals=signals, cause="hybrid_short_circuit")
         return await self._llm_classifier_outcome(prompt, system_prompt, request_kwargs, messages, scored=scored)
 
+    def _classifier_image_parts(
+        self, messages: Sequence[Mapping[str, object]] | None
+    ) -> tuple[ChatCompletionImageObject, ...]:
+        """Images from the newest user turn to hand the classifier, capped by max_images.
+
+        Empty unless the operator opted in AND the classifier model is declared vision-capable, so
+        every other deployment keeps today's text-only payload byte for byte. Only the newest user
+        turn is read: earlier turns are context the classifier already gets as quoted text, and an
+        image nested in a tool_result is tool output rather than the ask being classified.
+        Remote-URL images are left out entirely; `_inline_image_part` carries why.
+        """
+        llm_config: Final = self.config.classifier_llm_config
+        if llm_config is None or not llm_config.vision.enabled or not self.config.uses_llm_classifier or not messages:
+            return ()
+        if not self._model_declares_vision_support(llm_config.model):
+            return ()
+        newest_user_turn: Final = next((msg for msg in reversed(messages) if msg.get("role") == "user"), None)
+        content: Final = newest_user_turn.get("content") if newest_user_turn is not None else None
+        if not isinstance(content, list):
+            return ()
+        return tuple(
+            islice(
+                (part for raw in content if isinstance(raw, Mapping) and (part := _inline_image_part(raw)) is not None),
+                llm_config.vision.max_images,
+            )
+        )
+
     async def _llm_classifier_outcome(
         self,
         prompt: str,
@@ -1864,9 +1926,18 @@ class ComplexityRouter(CustomLogger):
         }
         turn_off_message_logging: Final = _effective_turn_off_message_logging(request_kwargs)
 
+        image_parts: Final = self._classifier_image_parts(messages)
+        user_content: Final[str | Sequence[ChatCompletionTextObject | ChatCompletionImageObject]] = (
+            [  # mutable-ok: SDK request payload content list is built once
+                {"type": "text", "text": user_payload},
+                *image_parts,
+            ]
+            if image_parts
+            else user_payload
+        )
         messages_for_call: Final[list[AllMessageValues]] = [  # mutable-ok: SDK request payload list is built once
             {"role": "system", "content": classifier_system_prompt},
-            {"role": "user", "content": user_payload},
+            {"role": "user", "content": user_content},
         ]
         response_format: Final = classifier_response_format
         classifier_call_params: Mapping[str, str] = EMPTY_MAPPING
@@ -2557,31 +2628,53 @@ class ComplexityRouter(CustomLogger):
             return pinned_model
         return self.get_model_for_tier(escalated_tier)
 
-    def _model_accepts_image_input(self, model_name: str) -> bool:
-        """Whether a routed model or pool entry can serve an image request.
+    def _vision_verdicts(self, model_name: str) -> tuple[bool | None, ...]:
+        """Declared vision support per deployment serving the name: True, False, or None when
+        nothing declares either way.
 
         Resolved through the deployments that would actually serve the name; a name with no
         deployment on the router is served by the SDK directly and is checked against the model
-        cost map itself. Only an explicit supports_vision false excludes, a deployment-level
-        model_info override first and the map otherwise, so unmapped custom names stay routable.
+        cost map itself. A deployment-level model_info override wins over the map.
+
+        One verdict set, two readings, because the two callers fail in opposite directions.
+        Routing a user's image asks whether anything RULES IT OUT, so an undeclared model stays
+        eligible and unmapped custom names keep routing. Handing an image to the classifier asks
+        whether something RULES IT IN: an undeclared model that turns out to be text-only rejects
+        every image request, and that rejection is swallowed by the classifier's own fallback, so
+        the router quietly serves all image traffic from the fallback tier and pays for the failed
+        call each time. An undeclared model instead keeps today's text-only payload, which is a
+        visible no-op the operator fixes by declaring supports_vision on the deployment.
+        """
+        from litellm.utils import is_vision_explicitly_disabled, supports_vision
+
+        def model_verdict(model: str) -> bool | None:
+            if supports_vision(model):
+                return True
+            return False if is_vision_explicitly_disabled(model) else None
+
+        def deployment_verdict(deployment: Mapping[str, Any]) -> bool | None:
+            declared: Final = (deployment.get("model_info") or EMPTY_MAPPING).get("supports_vision")
+            if declared is not None:
+                return declared is True
+            return model_verdict((deployment.get("litellm_params") or EMPTY_MAPPING).get("model") or model_name)
+
+        deployments: Final = self.litellm_router_instance.get_model_list(model_name=model_name)
+        if not deployments:
+            return (model_verdict(model_name),)
+        return tuple(deployment_verdict(deployment) for deployment in deployments)
+
+    def _model_accepts_image_input(self, model_name: str) -> bool:
+        """Whether a routed model or pool entry can serve an image request.
 
         A multi-deployment group must accept on EVERY deployment: the router picks a deployment
         inside the group after this gate runs, so a mixed group marked eligible could still hand
         the image to its text-only member and fail with the exact 400 the gate exists to prevent.
         """
-        from litellm.utils import is_vision_explicitly_disabled
+        return all(verdict is not False for verdict in self._vision_verdicts(model_name))
 
-        def deployment_accepts(deployment: Mapping[str, Any]) -> bool:
-            declared: Final = (deployment.get("model_info") or EMPTY_MAPPING).get("supports_vision")
-            if declared is not None:
-                return declared is True
-            litellm_model: Final = (deployment.get("litellm_params") or EMPTY_MAPPING).get("model") or model_name
-            return not is_vision_explicitly_disabled(litellm_model)
-
-        deployments: Final = self.litellm_router_instance.get_model_list(model_name=model_name)
-        if not deployments:
-            return not is_vision_explicitly_disabled(model_name)
-        return all(deployment_accepts(deployment) for deployment in deployments)
+    def _model_declares_vision_support(self, model_name: str) -> bool:
+        """Whether every deployment serving the name is declared vision-capable."""
+        return all(verdict is True for verdict in self._vision_verdicts(model_name))
 
     def _modality_eligible_models(self) -> frozenset[str]:
         """Every configured pool entry, plus default_model, that can serve an image request."""
@@ -3373,8 +3466,9 @@ class ComplexityRouter(CustomLogger):
         has_original_messages: Final = messages is not None and len(messages) > 0
 
         user_message, system_prompt = _extract_current_ask_and_system_prompt(resolved_messages, self._reminder_markers)
+        classifier_images: Final = self._classifier_image_parts(resolved_messages)
 
-        if user_message is None:
+        if user_message is None and not classifier_images:
             verbose_router_logger.debug("ComplexityRouter: No user message found, routing to default model")
             default_model_first: Final = not self.config.plugins and self.config.default_model
             if default_model_first:
@@ -3401,8 +3495,17 @@ class ComplexityRouter(CustomLogger):
                 ),
             )
 
+        ask: Final = user_message or ""
         newest_ask: Final = _newest_turn_ask(resolved_messages, self._reminder_markers)
         escalation_keyword: Final = self._matched_escalation_keyword(newest_ask) if newest_ask is not None else None
+        # Resolved here rather than beside the classifier because the keyword-override path below
+        # returns before any classification runs, and a forced tier gets stuck for the same reason
+        # a classified one does.
+        stalled: Final = self.config.stall_escalation_enabled and detect_stalled_task(
+            resolved_messages,
+            window=self.config.stall_escalation_window,
+            repeat_threshold=self.config.stall_escalation_repeat_threshold,
+        )
 
         plan_mode_sentinel: Final = self._matched_plan_mode_signal(request_kwargs, resolved_messages)
         plan_floor: Final = self._resolve_plan_mode_floor() if plan_mode_sentinel is not None else None
@@ -3430,12 +3533,13 @@ class ComplexityRouter(CustomLogger):
                 ),
             )
 
-        override: Final = await self._resolve_keyword_tier_override(user_message, request_kwargs)
+        override: Final = await self._resolve_keyword_tier_override(ask, request_kwargs)
         if override is not None:
-            escalated_tier: Final = (
+            keyword_bumped_tier: Final = (
                 self._escalate_tier(override.tier) if escalation_keyword is not None else override.tier
             )
-            keyword_escalated: Final = escalated_tier != override.tier
+            escalated_tier: Final = self._escalate_tier(keyword_bumped_tier) if stalled else keyword_bumped_tier
+            keyword_escalated: Final = keyword_bumped_tier != override.tier
             routed_tier: Final = (
                 self._apply_plan_mode_floor(escalated_tier) if plan_floor is not None else escalated_tier
             )
@@ -3463,6 +3567,7 @@ class ComplexityRouter(CustomLogger):
                     conversation_continuing=conversation_continuing,
                     cause=keyword_cause,
                     tier=routed_tier,
+                    signals=("stall_escalation",) if stalled else None,
                     matched_keyword=plan_mode_sentinel if keyword_plan_floored else override.matched_keyword,
                     escalation_keyword=escalation_keyword,
                     escalated=keyword_escalated,
@@ -3475,9 +3580,7 @@ class ComplexityRouter(CustomLogger):
         outcome: Final = (
             ClassificationOutcome(tier=housekeeping_tier, score=None, signals=("housekeeping",), cause="housekeeping")
             if housekeeping_tier is not None
-            else await self.aclassify(
-                user_message, system_prompt, request_kwargs, resolved_messages, raw_messages=messages
-            )
+            else await self.aclassify(ask, system_prompt, request_kwargs, resolved_messages, raw_messages=messages)
         )
         tier, score, signals = outcome.tier, outcome.score, outcome.signals
         classified_tier: Final = tier
@@ -3486,6 +3589,9 @@ class ComplexityRouter(CustomLogger):
         escalated: Final = tier != classified_tier
         if escalated:
             signals = (*signals, "escalation")
+        if stalled:
+            tier = self._escalate_tier(tier)
+            signals = (*signals, "stall_escalation")
         pre_floor_tier: Final = tier
         if plan_floor is not None:
             tier = self._apply_plan_mode_floor(tier)
@@ -3544,7 +3650,7 @@ class ComplexityRouter(CustomLogger):
             # under is not a floor.
             routed_model = self._soft_floor_pick(
                 tier,
-                user_message,
+                ask,
                 request_kwargs,
                 hard_floor=tier if context_original_tier is not None else plan_floor,
                 hard_ceiling=housekeeping_ceiling,

litellm/router_strategy/complexity_router/config.py

@@ -442,12 +442,47 @@ DEFAULT_TIER_MODELS: Final[dict[str, str]] = {
 }
 
 
+class ClassifierVisionConfig(BaseModel):
+    """Whether the LLM classifier sees the images on the request it is classifying.
+
+    Off by default because images cost far more than the text ask they arrive with, and the
+    classifier runs on every request. A turn whose complexity lives in the image ("what is wrong in
+    this stack trace screenshot") is invisible to a text-only classifier, which is what this buys.
+    """
+
+    enabled: bool = Field(
+        default=False,
+        description=(
+            "Forward image content to the classifier. Requires a classifier model declared "
+            "supports_vision, on the deployment's model_info or in the model cost map; images stay "
+            "stripped otherwise, so a classifier that cannot read them is never sent one. Declare "
+            "model_info.supports_vision on the deployment to enable a model the cost map does not "
+            "describe. Only inline data: URIs are forwarded. A request whose images are http(s) "
+            "URLs still classifies on its text alone, because some providers fetch such a URL from "
+            "the proxy rather than the provider, which would let a caller aim a proxy-side request "
+            "at an address of their choosing."
+        ),
+    )
+    max_images: int = Field(
+        default=1,
+        ge=1,
+        description=(
+            "How many images from the newest user turn to forward, in wire order. Bounds the added "
+            "cost of a turn that attaches many images. Images on earlier turns are never forwarded."
+        ),
+    )
+
+
 class ClassifierLLMConfig(BaseModel):
     """Configuration for the LLM-based complexity classifier."""
 
     model: str = Field(
         description="Model name (from the router's model_list) to call for classification",
     )
+    vision: ClassifierVisionConfig = Field(
+        default_factory=ClassifierVisionConfig,
+        description="Whether the classifier sees images on the request, and how many",
+    )
     reasoning_effort: REASONING_EFFORT | None = Field(
         default=None,
         description=(
@@ -852,6 +887,43 @@ class ComplexityRouterConfig(BaseModel):
         description="Rules that force a specific tier when their keywords match the prompt",
     )
 
+    stall_escalation_enabled: bool = Field(
+        default=False,
+        description=(
+            "Escalate mid-task to the next-higher configured tier when the assistant's own recent "
+            "tool calls look stuck: the newest tool call repeats, or errors, at least "
+            "stall_escalation_repeat_threshold times across the last stall_escalation_window "
+            "calls. Both tests are anchored on the newest call, so a task that tried the same "
+            "thing a few times and then moved on is not escalated on the strength of those older "
+            "calls alone, while a retry loop broken up by an unrelated lookup still counts. One "
+            "tier at most, on the same ladder escalation_keywords bumps along, and never above "
+            "the highest configured tier. Detection re-runs on every classified turn from the "
+            "tool calls visible in that request, so it needs no state and nothing survives past "
+            "the task. Mutually exclusive with session_affinity and classification_mode="
+            "'user_turn', which both replay a held routing decision instead of classifying most "
+            "turns, so this would never see the tool calls to look at. Off by default."
+        ),
+    )
+    stall_escalation_window: int = Field(
+        default=6,
+        gt=0,
+        description=(
+            "How many of the assistant's most recent tool calls stall detection looks at, oldest "
+            "ones dropped as new calls happen. Counted across the whole visible conversation "
+            "rather than reset at the newest human ask, so evidence from before a plain follow-up "
+            "message like 'try again' is still visible on the turn after it."
+        ),
+    )
+    stall_escalation_repeat_threshold: int = Field(
+        default=3,
+        ge=2,
+        description=(
+            "How many of the last stall_escalation_window tool calls must repeat the newest call, "
+            "or must have errored alongside it, before the task counts as stalled. Must not "
+            "exceed stall_escalation_window, or the condition could never be reached."
+        ),
+    )
+
     plan_mode_min_tier: str | None = Field(
         default=None,
         description=(
@@ -1323,6 +1395,7 @@ class ComplexityRouterConfig(BaseModel):
                 ("adaptive", self.adaptive),
                 ("session_affinity", self.session_affinity),
                 ("escalation_keywords", bool(self.escalation_keywords)),
+                ("stall_escalation_enabled", self.stall_escalation_enabled),
                 ("plugins", bool(self.plugins)),
             )
             if enabled
@@ -1490,6 +1563,25 @@ class ComplexityRouterConfig(BaseModel):
             )
         return self
 
+    @model_validator(mode="after")
+    def _validate_stall_escalation(self) -> "ComplexityRouterConfig":
+        if not self.stall_escalation_enabled:
+            return self
+        if self.session_affinity or self.classification_mode == "user_turn":
+            raise ValueError(
+                "stall_escalation_enabled cannot be combined with session_affinity or "
+                "classification_mode='user_turn': both replay a held routing decision on most "
+                "turns instead of classifying, so stall detection would never see the tool calls "
+                "of the turns it needs to look at. Disable one or the other."
+            )
+        if self.stall_escalation_repeat_threshold > self.stall_escalation_window:
+            raise ValueError(
+                "stall_escalation_repeat_threshold "
+                f"({self.stall_escalation_repeat_threshold}) cannot exceed stall_escalation_window "
+                f"({self.stall_escalation_window}); the condition could never be reached."
+            )
+        return self
+
     @model_validator(mode="after")
     def _validate_tier_param_placement(self) -> "ComplexityRouterConfig":
         """Reject a router setting written into a tier entry's request params.

litellm/router_strategy/complexity_router/stall_detector.py

@@ -0,0 +1,118 @@
+"""
+Mid-task stall detection for the Complexity Router.
+
+Reads the assistant's own recent tool calls, which every agentic client resends on each
+turn, and reports whether the task currently looks stuck. No LLM call and no stored state:
+the same window is rescanned per classified turn, so the verdict follows the conversation
+rather than latching.
+
+Tool calls arrive in two shapes and are read in place rather than translated:
+- Anthropic Messages: assistant `tool_use` content blocks, answered by a user-turn
+  `tool_result` block carrying `is_error`
+- Chat completions: assistant `tool_calls` entries, answered by a `role: "tool"` message,
+  which has no standard error flag, so those calls are judged on repetition alone
+"""
+
+from __future__ import annotations
+
+import json
+from collections.abc import Iterator, Mapping, Sequence
+from itertools import islice
+from typing import Final, NamedTuple
+
+_ARGUMENTS_PARSE_FAILED: Final = object()
+
+
+class _ToolCallEvent(NamedTuple):
+    signature: tuple[str, str]
+    is_error: bool | None
+    """None where the surface reports no error status, and never counted as an error."""
+
+
+def _json_arguments(raw: str) -> object:
+    try:
+        return json.loads(raw)
+    except (TypeError, ValueError):
+        return _ARGUMENTS_PARSE_FAILED
+
+
+def _tool_call_signature(name: str, raw_arguments: object) -> tuple[str, str]:
+    """Canonicalized so the same call compares equal across both surfaces, which carry
+    arguments as a dict and as a JSON string respectively."""
+    parsed: Final = _json_arguments(raw_arguments) if isinstance(raw_arguments, str) else raw_arguments
+    arguments: Final = raw_arguments if parsed is _ARGUMENTS_PARSE_FAILED else parsed
+    try:
+        return name, json.dumps(arguments, sort_keys=True, default=str)
+    except (TypeError, ValueError):
+        return name, str(arguments)
+
+
+def _iter_tool_result_error_pairs(messages: Sequence[Mapping[str, object]]) -> Iterator[tuple[str, bool]]:
+    for msg in messages:
+        content = msg.get("content")
+        if msg.get("role") != "user" or not isinstance(content, list):
+            continue
+        for part in content:
+            if isinstance(part, Mapping) and part.get("type") == "tool_result":
+                call_id = part.get("tool_use_id")
+                if isinstance(call_id, str):
+                    yield call_id, bool(part.get("is_error", False))
+
+
+def _iter_tool_call_events_newest_first(messages: Sequence[Mapping[str, object]]) -> Iterator[_ToolCallEvent]:
+    error_by_call_id: Final = dict(_iter_tool_result_error_pairs(messages))
+    for msg in reversed(messages):
+        if msg.get("role") != "assistant":
+            continue
+        content = msg.get("content")
+        if isinstance(content, list):
+            for part in reversed(content):
+                if not (isinstance(part, Mapping) and part.get("type") == "tool_use"):
+                    continue
+                name = part.get("name")
+                if isinstance(name, str):
+                    call_id = part.get("id")
+                    yield _ToolCallEvent(
+                        signature=_tool_call_signature(name, part.get("input")),
+                        is_error=error_by_call_id.get(call_id) if isinstance(call_id, str) else None,
+                    )
+        tool_calls = msg.get("tool_calls")
+        if not isinstance(tool_calls, list):
+            continue
+        for call in reversed(tool_calls):
+            function = call.get("function") if isinstance(call, Mapping) else None
+            name = function.get("name") if isinstance(function, Mapping) else None
+            if isinstance(name, str):
+                yield _ToolCallEvent(
+                    signature=_tool_call_signature(name, function.get("arguments") if function else None),
+                    is_error=None,
+                )
+
+
+def detect_stalled_task(
+    messages: Sequence[Mapping[str, object]] | None,
+    *,
+    window: int,
+    repeat_threshold: int,
+) -> bool:
+    """Whether the newest tool call is still part of a stuck pattern: it repeats, or it
+    errored, at least repeat_threshold times across the last `window` calls.
+
+    Both tests are anchored on the newest call rather than counting whichever pattern is
+    most common in the window. A task that tried the same thing three times and then moved
+    on has those three calls in the window for a while yet, and counting them alone would
+    escalate a request that already recovered. Anchoring also leaves room between the
+    matches, so a retry loop broken up by an unrelated lookup still reads as stuck.
+    """
+    if not messages or repeat_threshold <= 0:
+        return False
+    recent: Final = tuple(islice(_iter_tool_call_events_newest_first(messages), window))
+    if len(recent) < repeat_threshold:
+        return False
+    newest: Final = recent[0]
+    repeats: Final = sum(1 for event in recent if event.signature == newest.signature)
+    if repeats >= repeat_threshold:
+        return True
+    if not newest.is_error:
+        return False
+    return sum(1 for event in recent if event.is_error) >= repeat_threshold

litellm/types/access_group.py

@@ -23,6 +23,13 @@ class AccessGroupUpdateRequest(BaseModel):
     assigned_key_ids: list[str] | None = None
 
 
+class AccessGroupResource(BaseModel):
+    """A resource referenced by an access group. `name` is null when the id no longer resolves or has no alias."""
+
+    id: str
+    name: str | None
+
+
 class AccessGroupResponse(BaseModel):
     access_group_id: str
     access_group_name: str
@@ -32,6 +39,10 @@ class AccessGroupResponse(BaseModel):
     access_agent_ids: list[str]
     assigned_team_ids: list[str]
     assigned_key_ids: list[str]
+    access_mcp_servers: tuple[AccessGroupResource, ...]
+    access_agents: tuple[AccessGroupResource, ...]
+    assigned_teams: tuple[AccessGroupResource, ...]
+    assigned_keys: tuple[AccessGroupResource, ...]
     created_at: datetime
     created_by: str | None = None
     updated_at: datetime

litellm/types/utils.py

@@ -3096,7 +3096,7 @@ PROMPT_CARRYING_GUARDRAIL_FIELDS: Final[frozenset[str]] = frozenset(
 
 # The rest of the record: what the guardrail is, what it decided, how long it took and what it cost.
 # None of these reproduce the prompt, so a redacted record keeps them and stays explainable.
-# `test_every_guardrail_field_is_classified` fails if a field is added to the record without being
+# `test_a_redacted_span_carries_every_declared_guardrail_field` fails if a field is added to the record without being
 # placed in one set or the other, so a new field is dropped from redacted records rather than
 # shipped unexamined.
 AUDIT_GUARDRAIL_FIELDS: Final[frozenset[str]] = frozenset(
@@ -3120,6 +3120,7 @@ AUDIT_GUARDRAIL_FIELDS: Final[frozenset[str]] = frozenset(
         "guardrail_action",
         "guardrail_usage",
         "guardrail_cost",
+        "guardrail_cost_by_unit",
         "guardrail_cost_in_spend",
     }
 )

model_prices_and_context_window.json

@@ -7157,6 +7157,53 @@
         "supports_xhigh_reasoning_effort": true,
         "supports_minimal_reasoning_effort": false
     },
+    "azure/gpt-6-astra": {
+        "cache_creation_input_token_cost": 1.25e-05,
+        "cache_creation_input_token_cost_above_272k_tokens": 2.5e-05,
+        "cache_read_input_token_cost": 1e-06,
+        "cache_read_input_token_cost_above_272k_tokens": 2e-06,
+        "input_cost_per_token": 1e-05,
+        "input_cost_per_token_above_272k_tokens": 2e-05,
+        "litellm_provider": "azure",
+        "max_input_tokens": 922000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5e-05,
+        "output_cost_per_token_above_272k_tokens": 7.5e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_minimal_reasoning_effort": false,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "azure/us/gpt-5.6": {
         "cache_creation_input_token_cost": 6.875e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,
@@ -7376,6 +7423,53 @@
         "supports_xhigh_reasoning_effort": true,
         "supports_minimal_reasoning_effort": false
     },
+    "azure/us/gpt-6-astra": {
+        "cache_creation_input_token_cost": 1.375e-05,
+        "cache_creation_input_token_cost_above_272k_tokens": 2.75e-05,
+        "cache_read_input_token_cost": 1.1e-06,
+        "cache_read_input_token_cost_above_272k_tokens": 2.2e-06,
+        "input_cost_per_token": 1.1e-05,
+        "input_cost_per_token_above_272k_tokens": 2.2e-05,
+        "litellm_provider": "azure",
+        "max_input_tokens": 922000,
+        "max_output_tokens": 128000,
+        "max_tokens": 128000,
+        "mode": "chat",
+        "output_cost_per_token": 5.5e-05,
+        "output_cost_per_token_above_272k_tokens": 8.25e-05,
+        "search_context_cost_per_query": {
+            "search_context_size_high": 0.01,
+            "search_context_size_low": 0.01,
+            "search_context_size_medium": 0.01
+        },
+        "supported_endpoints": [
+            "/v1/chat/completions",
+            "/v1/responses"
+        ],
+        "supported_modalities": [
+            "text",
+            "image"
+        ],
+        "supported_output_modalities": [
+            "text"
+        ],
+        "supports_computer_use": true,
+        "supports_function_calling": true,
+        "supports_max_reasoning_effort": true,
+        "supports_minimal_reasoning_effort": false,
+        "supports_native_streaming": true,
+        "supports_none_reasoning_effort": true,
+        "supports_parallel_function_calling": true,
+        "supports_pdf_input": true,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true,
+        "supports_xhigh_reasoning_effort": true
+    },
     "azure/eu/gpt-5.6": {
         "cache_creation_input_token_cost": 6.875e-06,
         "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05,

tests/code_coverage_tests/recursive_detector.py

@@ -66,6 +66,7 @@ IGNORE_FUNCTIONS = [
     "_json_safe",  # max depth set (_MAX_DEPTH) plus a seen-ids cycle guard for self-referential input.
     "_redact_agent_params_tree",  # max depth set (default 10), same shape as _redact_sensitive_litellm_params.
     "_restore_redacted_nested_value",  # max depth set (default 10), mirrors _redact_agent_params_tree on the write side.
+    "_unqualified",  # bounded by the qualifier depth of a static TypedDict annotation (Annotated, Required/NotRequired, ReadOnly around one type, no cycles possible).
 ]
 
 

tests/test_litellm/integrations/test_shadow_eval_logger.py

@@ -24,7 +24,13 @@ from litellm.integrations.shadow_eval_logger import (
     _unmask_preference,
 )
 from litellm.types.guardrails import GuardrailEventHooks
-from litellm.types.utils import SHADOW_EVAL_JUDGE_CALL_ORIGIN, SHADOW_EVAL_ROUTER_CALL_ORIGIN, ModelResponse
+from litellm.types.utils import (
+    SHADOW_EVAL_JUDGE_CALL_ORIGIN,
+    SHADOW_EVAL_ROUTER_CALL_ORIGIN,
+    ChatCompletionCustomToolCallPayload,
+    ChatCompletionMessageCustomToolCall,
+    ModelResponse,
+)
 
 
 def _job(**overrides) -> ActiveShadowEvalJob:
@@ -120,6 +126,39 @@ def _router(
     return router
 
 
+def _shadow_reply_router(message, finish_reason="stop", routed_model="cheap-model"):
+    """A router whose shadow arm answers with a caller-supplied message, so a reply that
+    yields no judgeable text can be posed as the two different things it can be: an arm
+    that chose a tool, or an arm that returned nothing."""
+    router = MagicMock()
+    router.model_group_alias = {}
+    router.get_model_list = MagicMock(return_value=[{"litellm_params": {"model": "openai/gpt-4o-mini"}}])
+
+    async def acompletion(**kwargs):
+        if kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN:
+            return {"choices": [{"message": {"content": '{"preference": "A", "confidence": 0.9}'}}]}
+        kwargs["metadata"]["routing_decision"] = {"tier_label": "SIMPLE", "routed_model": routed_model}
+        return {"choices": [{"message": message, "finish_reason": finish_reason}]}
+
+    router.acompletion = MagicMock(side_effect=acompletion)
+    return router
+
+
+TOOL_CALL_MESSAGE = {
+    "content": None,
+    "tool_calls": [{"id": "c1", "type": "function", "function": {"name": "Read", "arguments": "{}"}}],
+}
+
+CUSTOM_TOOL_CALL_MESSAGE = {
+    "content": None,
+    "tool_calls": [
+        ChatCompletionMessageCustomToolCall(
+            id="c2", custom=ChatCompletionCustomToolCallPayload(name="exec_sql", input="select 1")
+        )
+    ],
+}
+
+
 def _spend_counter(store=None):
     """In-memory stand-in for the proxy's cross-pod spend counter: reads take the max of
     the counter and the caller's fallback, exactly like get_current_spend does for a key
@@ -368,7 +407,13 @@ class TestSurfaceNormalization:
         ],
         ids=["tool-final-chat-turn", "tool-final-responses-turn"],
     )
-    async def test_unjudgeable_turns_are_skipped_without_consuming_budget(self, response_mutation, kwargs_mutation):
+    async def test_a_tool_final_turn_is_sampled_and_serialized_for_the_judge(
+        self, response_mutation, kwargs_mutation
+    ):
+        """A turn where the real model called a tool used to be dropped before sampling, on
+        every surface. On agentic traffic that is most of the traffic, so a job set to
+        sample 10% was really sampling 10% of the prose-only slice and calling it 10% of
+        the key. The turn is sampled like any other and the call is serialized as text."""
         from litellm.types.llms.openai import ResponsesAPIResponse
 
         hook_kwargs = _success_kwargs(**({"call_type": "acompletion"} | kwargs_mutation))
@@ -406,6 +451,38 @@ class TestSurfaceNormalization:
 
         prisma, router = await self._drive(hook_kwargs, response)
 
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+        assert "[tool call] f({})" in judge_prompt
+        prisma.db.litellm_shadowevalattempt.create.assert_called_once()
+
+    @pytest.mark.parametrize(
+        "response_mutation,kwargs_mutation",
+        [
+            ("chat-no-content", {}),
+            ("responses-no-output", {"call_type": "aresponses"}),
+        ],
+        ids=["empty-chat-turn", "empty-responses-turn"],
+    )
+    async def test_turns_with_nothing_to_compare_are_skipped_without_consuming_budget(
+        self, response_mutation, kwargs_mutation
+    ):
+        """No prose and no tool call leaves the judge nothing to score, so the turn is
+        still skipped rather than billed."""
+        from litellm.types.llms.openai import ResponsesAPIResponse
+
+        hook_kwargs = _success_kwargs(**({"call_type": "acompletion"} | kwargs_mutation))
+        if response_mutation == "chat-no-content":
+            response = {"choices": [{"message": {"content": ""}}]}
+        else:
+            hook_kwargs["messages"] = "do the thing"
+            response = ResponsesAPIResponse.model_validate(RESPONSES_API_RESPONSE | {"output": []})
+
+        prisma, router = await self._drive(hook_kwargs, response)
+
         router.acompletion.assert_not_called()
         prisma.db.litellm_shadowevalattempt.create.assert_not_called()
 
@@ -1134,6 +1211,206 @@ class TestShadowPipeline:
         assert row["shadow_cost"] == 0.007
         assert logger._test_counter["spend:shadow_eval:job-1"] == 0.007
 
+    async def _no_text_error(self, router) -> str:
+        prisma = _prisma()
+        await _logger(router=router, prisma=prisma)._run_shadow_eval(
+            job=_job(),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.0,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params={},
+            parent_metadata={},
+        )
+        row = prisma.db.litellm_shadowevalattempt.create.call_args.kwargs["data"]
+        assert row["outcome"] == "error"
+        return row["error"]
+
+    async def _judged_shadow_row(self, router: MagicMock, shadow_params: dict | None = None) -> dict:
+        prisma = _prisma()
+        await _logger(router=router, prisma=prisma)._run_shadow_eval(
+            job=_job(),
+            request_id="req-1",
+            messages=({"role": "user", "content": "hi"},),
+            real_text="real answer",
+            real_model="claude-opus",
+            real_cost=0.0,
+            real_classifier_cost=0.0,
+            real_cache_hit=False,
+            control_tier=None,
+            shadow_params=shadow_params or {},
+            parent_metadata={},
+        )
+        return prisma.db.litellm_shadowevalattempt.create.call_args.kwargs["data"]
+
+    async def test_a_tool_call_shadow_reply_is_judged_rather_than_discarded(self):
+        """An arm that calls a tool where the real model wrote prose has answered, it just
+        answered by acting. Dropping that turn threw away the comparison the job exists to
+        make, and on agentic traffic it threw away most of them, so the tool call is
+        serialized into text and judged like any other response."""
+        row = await self._judged_shadow_row(_shadow_reply_router(TOOL_CALL_MESSAGE, finish_reason="tool_calls"))
+
+        assert row["outcome"] != "error"
+        assert row["error"] is None
+        assert row["confidence"] == 0.9
+
+    async def test_a_tool_call_reaches_the_judge_as_readable_text(self):
+        """The judge only ever sees strings, so a tool call has to arrive as its name and
+        arguments. A serialization that dropped either would ask the judge to score a
+        response it cannot tell apart from any other tool call."""
+        router = _shadow_reply_router(TOOL_CALL_MESSAGE, finish_reason="tool_calls")
+        await self._judged_shadow_row(router)
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "[tool call] Read({})" in judge_prompt
+
+    async def test_the_judge_sees_what_tools_were_available(self):
+        """Scoring whether a tool call was the right response needs to know what else the
+        arm could have called instead. Without the tool list, the judge can score the
+        arguments but not whether Read, specifically, was the correct choice."""
+        router = _shadow_reply_router(TOOL_CALL_MESSAGE, finish_reason="tool_calls")
+        tools = [
+            {"type": "function", "function": {"name": "Read", "description": "read a file from disk"}},
+            {"type": "function", "function": {"name": "Bash", "description": "run a shell command"}},
+        ]
+        await self._judged_shadow_row(router, shadow_params={"tools": tools})
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "Read: read a file from disk" in judge_prompt
+        assert "Bash: run a shell command" in judge_prompt
+
+    async def test_a_custom_tool_definition_is_named_for_the_judge(self):
+        """A custom tool definition nests name and description under `custom`, not
+        `function`, so reading only `function` renders every one of them as unnamed and
+        tells the judge nothing about what the arm could have called."""
+        from openai.types.chat import ChatCompletionCustomToolParam
+
+        router = _shadow_reply_router(TOOL_CALL_MESSAGE, finish_reason="tool_calls")
+        tools = [
+            ChatCompletionCustomToolParam(
+                type="custom",
+                custom={"name": "exec_sql", "description": "run a read-only sql query"},
+            )
+        ]
+        await self._judged_shadow_row(router, shadow_params={"tools": tools})
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "exec_sql: run a read-only sql query" in judge_prompt
+        assert "unnamed" not in judge_prompt
+
+    @pytest.mark.parametrize("shadow_params", [{}, {"tools": []}], ids=["omitted", "empty-list"])
+    async def test_no_tool_definitions_section_when_the_turn_offered_no_tools(self, shadow_params):
+        """Padding every judge prompt with an empty tools section wastes budget on the
+        turns, still the majority, that never offered one, whether tools was left out of
+        the request entirely or sent as an empty list."""
+        router = _shadow_reply_router({"content": "hello"}, finish_reason="stop")
+        await self._judged_shadow_row(router, shadow_params=shadow_params)
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "Tools available" not in judge_prompt
+
+    async def test_a_custom_tool_call_serializes_its_name_and_input(self):
+        """Custom tool calls carry no `function` key: name and arguments live under
+        `custom`, so reading only `function` serializes every one of them as unnamed."""
+        router = _shadow_reply_router(CUSTOM_TOOL_CALL_MESSAGE, finish_reason="tool_calls")
+        await self._judged_shadow_row(router)
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "[tool call] exec_sql(select 1)" in judge_prompt
+
+    async def test_the_judge_is_told_a_tool_call_is_not_a_defect(self):
+        """The judge scores on completeness and clarity. Handed a tool call with no
+        instruction, it marks it down for not reading like an answer, which would bias
+        every verdict against a tool-calling arm on exactly the traffic that calls tools."""
+        router = _shadow_reply_router(TOOL_CALL_MESSAGE, finish_reason="tool_calls")
+        await self._judged_shadow_row(router)
+
+        system_prompt = next(
+            call.kwargs["messages"][0]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "tool call" in system_prompt
+        assert "not a defect" in system_prompt
+
+    async def test_prose_written_alongside_a_tool_call_survives_into_the_verdict(self):
+        """Some providers write a sentence before acting. Serializing only the call would
+        hide half of what the arm actually said from the judge."""
+        router = _shadow_reply_router(
+            {"content": "Let me look that up.", "tool_calls": TOOL_CALL_MESSAGE["tool_calls"]},
+            finish_reason="tool_calls",
+        )
+        await self._judged_shadow_row(router)
+
+        judge_prompt = next(
+            call.kwargs["messages"][-1]["content"]
+            for call in router.acompletion.call_args_list
+            if call.kwargs["metadata"].get(INTERNAL_CALL_ORIGIN_METADATA_KEY) != SHADOW_EVAL_ROUTER_CALL_ORIGIN
+        )
+
+        assert "Let me look that up. [tool call] Read({})" in judge_prompt
+
+    async def test_an_empty_shadow_reply_names_the_finish_reason_and_the_routed_model(self):
+        """A reply that really carried no text is diagnosable only if the row says what
+        the arm was doing when it produced none: a truncated turn and a model that answers
+        with nothing are different faults with different fixes."""
+        error = await self._no_text_error(
+            _shadow_reply_router({"content": ""}, finish_reason="length", routed_model="some-model")
+        )
+
+        assert "empty response" in error
+        assert "finish_reason=length" in error
+        assert "model=some-model" in error
+
+    async def test_no_text_errors_stay_groupable_across_models_and_finish_reasons(self):
+        """Operators read these rows by grouping on the error text, which is how a job's
+        failures collapse to a handful of causes. Every varying part therefore has to sit
+        behind the first semicolon, or each row becomes its own group and the count that
+        made the problem visible stops existing."""
+        first = await self._no_text_error(
+            _shadow_reply_router({"content": None}, finish_reason="length", routed_model="model-a")
+        )
+        second = await self._no_text_error(
+            _shadow_reply_router(
+                {"content": ""},
+                finish_reason="stop",
+                routed_model="model-b",
+            )
+        )
+
+        assert first != second
+        assert first.split(";")[0] == second.split(";")[0]
+
     async def test_a_pipeline_error_after_the_shadow_call_keeps_its_billed_cost(self, monkeypatch: pytest.MonkeyPatch):
         """An unexpected error between the billed shadow call and the attempt write must
         still record the shadow cost, or the per-key dollar gate undercounts forever."""
@@ -1691,11 +1968,13 @@ class TestSamplingFunnel:
         prisma.db.litellm_shadowevalattempt.create.assert_not_awaited()
 
     async def test_an_unjudgeable_sampled_request_counts_unjudgeable(self):
+        """A tool call still serializes into judgeable text; a turn with neither prose nor
+        a tool call to serialize is the one case left with nothing to compare."""
         prisma = _prisma()
         logger = _logger(router=_router(), prisma=prisma, jobs=(_job(),))
-        tool_final = {"choices": [{"message": {"content": None, "tool_calls": [{"type": "function", "function": {}}]}}]}
+        empty = {"choices": [{"message": {"content": None}}]}
 
-        await logger.async_log_success_event(_success_kwargs(), tool_final, None, None)
+        await logger.async_log_success_event(_success_kwargs(), empty, None, None)
         await _drain(logger)
 
         assert logger._test_funnel == [("job-1", "unjudgeable")]

tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py

@@ -2008,6 +2008,49 @@ def test_generic_cost_per_token_azure_gpt56(_local_model_cost_map,
     assert round(completion_cost, 10) == round(output_cost * completion_tokens, 10)
 
 
+@pytest.mark.parametrize("model,zone_multiplier", [("azure/gpt-6-astra", 1.0), ("azure/us/gpt-6-astra", 1.1)])
+@pytest.mark.parametrize(
+    "prompt_tokens,input_side_multiplier,output_multiplier",
+    [(100000, 1.0, 1.0), (300000, 2.0, 1.5)],
+)
+def test_generic_cost_per_token_azure_gpt_6_astra_foundry_price_sheet(
+    _local_model_cost_map,
+    model,
+    zone_multiplier,
+    prompt_tokens,
+    input_side_multiplier,
+    output_multiplier,
+):
+    """Microsoft Foundry sells gpt-6-astra at the OpenAI rates: $10 input, $1 cache read, $12.50 cache write,
+    $50 output per 1M tokens on Standard Global, with the input side doubling and output 1.5x above 272K
+    prompt tokens. Standard US Data Zone carries the usual 10% uplift on every rate.
+    """
+    cached_tokens = 50000
+    cache_write_tokens = 40000
+    text_tokens = prompt_tokens - cached_tokens - cache_write_tokens
+    completion_tokens = 1000
+    usage = Usage(
+        prompt_tokens=prompt_tokens,
+        completion_tokens=completion_tokens,
+        total_tokens=prompt_tokens + completion_tokens,
+        prompt_tokens_details=PromptTokensDetailsWrapper(
+            cached_tokens=cached_tokens, cache_write_tokens=cache_write_tokens
+        ),
+    )
+
+    prompt_cost, completion_cost = generic_cost_per_token(
+        model=model,
+        usage=usage,
+        custom_llm_provider="azure",
+    )
+
+    input_side = zone_multiplier * input_side_multiplier
+    assert prompt_cost == pytest.approx(
+        input_side * (text_tokens * 1e-5 + cached_tokens * 1e-6 + cache_write_tokens * 1.25e-5)
+    )
+    assert completion_cost == pytest.approx(zone_multiplier * output_multiplier * completion_tokens * 5e-5)
+
+
 @pytest.mark.parametrize(
     "model,expected_none,expected_xhigh,expected_minimal",
     [

tests/test_litellm/llms/azure/chat/test_azure_gpt5_transformation.py

@@ -348,3 +348,31 @@ def test_azure_gpt_6_astra_takes_the_reasoning_series_request_shape():
     assert params["max_completion_tokens"] == 100
     assert "max_tokens" not in params
     assert params["reasoning_effort"] == "max"
+
+
+@pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
+def test_azure_gpt6_astra_reasoning_effort_none_unlocks_temperature(config: AzureOpenAIGPT5Config, model: str):
+    """Foundry's gpt-6-astra accepts reasoning_effort='none' and, only then, a non-default
+    temperature (verified live against a Foundry deployment), unlike OpenAI's gpt-6-astra."""
+    params = config.map_openai_params(
+        non_default_params={"temperature": 0.2, "reasoning_effort": "none"},
+        optional_params={},
+        model=model,
+        drop_params=False,
+        api_version="2025-04-01-preview",
+    )
+    assert params["temperature"] == 0.2
+    assert params["reasoning_effort"] == "none"
+
+
+@pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
+def test_azure_gpt6_astra_rejects_reasoning_effort_minimal(config: AzureOpenAIGPT5Config, model: str):
+    """Foundry's gpt-6-astra lists none, low, medium, high, xhigh and max but not minimal."""
+    with pytest.raises(litellm.utils.UnsupportedParamsError):
+        config.map_openai_params(
+            non_default_params={"reasoning_effort": "minimal"},
+            optional_params={},
+            model=model,
+            drop_params=False,
+            api_version="2025-04-01-preview",
+        )

tests/test_litellm/llms/azure/response/test_azure_transformation.py

@@ -1,11 +1,10 @@
 from copy import deepcopy
-from unittest.mock import patch
+from unittest.mock import MagicMock, patch
 
 import pytest
 
-
-from unittest.mock import MagicMock
-
+import litellm
+from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map
 from litellm.llms.azure.responses.o_series_transformation import (
     AzureOpenAIOSeriesResponsesAPIConfig,
 )
@@ -613,3 +612,39 @@ class TestAzureResponsesAPIConfig:
 
         assert result["tools"][0] is tool
         assert "anyOf" in result["tools"][0]["parameters"]
+
+
+@pytest.fixture()
+def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Pin the bundled cost map: the published map lags a key added in this repo."""
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", get_model_cost_map(url=litellm.model_cost_map_url))
+    litellm.add_known_models(model_cost_map=litellm.model_cost)
+
+
+def test_azure_responses_gpt6_astra_reasoning_effort_none_unlocks_temperature(local_model_cost_map: None):
+    """Foundry's gpt-6-astra accepts reasoning.effort='none' with a non-default temperature
+    while OpenAI's gpt-6-astra does not, so the gate must read the azure/ cost-map entry
+    for the bare deployment name rather than OpenAI's."""
+    params = AzureOpenAIResponsesAPIConfig().map_openai_params(
+        response_api_optional_params=ResponsesAPIOptionalRequestParams(
+            temperature=0.2,
+            reasoning={"effort": "none"},
+        ),
+        model="gpt-6-astra",
+        drop_params=False,
+    )
+    assert params["temperature"] == 0.2
+    assert params["reasoning"] == {"effort": "none"}
+
+
+def test_azure_responses_gpt6_astra_rejects_temperature_while_reasoning(local_model_cost_map: None):
+    with pytest.raises(litellm.UnsupportedParamsError):
+        AzureOpenAIResponsesAPIConfig().map_openai_params(
+            response_api_optional_params=ResponsesAPIOptionalRequestParams(
+                temperature=0.2,
+                reasoning={"effort": "low"},
+            ),
+            model="gpt-6-astra",
+            drop_params=False,
+        )

tests/test_litellm/llms/bedrock/passthrough/guardrail_translation/test_handler.py

@@ -170,22 +170,27 @@ class TestExtractConverseTexts:
         texts, _ = _extract_converse_texts(body, skip_system=False, skip_tool=False)
         assert texts == []
 
-    def test_extracts_tool_config_description_and_schema(self):
+    def test_tool_config_definitions_not_extracted(self):
+        """Tool definitions are app-authored config, so nothing under
+        toolConfig.tools reaches the guardrail as input content."""
         body = {
-            "messages": [{"role": "user", "content": [{"text": "hi"}]}],
+            "messages": [
+                {"role": "user", "content": [{"text": "How much lag is there in my data?"}]}
+            ],
             "toolConfig": {
                 "tools": [
                     {
                         "toolSpec": {
                             "name": "lookup",
-                            "description": "blocked tool description",
+                            "description": "tool description",
                             "inputSchema": {
                                 "json": {
                                     "type": "object",
                                     "properties": {
-                                        "q": {
+                                        "agent_name": {
                                             "type": "string",
-                                            "description": "blocked schema description",
+                                            "title": "Agent Name",
+                                            "enum": ["alpha", "beta", "gamma"],
                                         }
                                     },
                                 }
@@ -196,20 +201,56 @@ class TestExtractConverseTexts:
             },
         }
         texts, _ = _extract_converse_texts(body, skip_system=False, skip_tool=False)
-        assert "blocked tool description" in texts
-        assert "blocked schema description" in texts
+        assert texts == ["How much lag is there in my data?"]
 
-    def test_tool_config_scanned_even_when_tool_messages_skipped(self):
+    def test_every_tool_definition_excluded_not_just_the_first(self):
+        """A per-tool scan that only skipped tools[0] would still leak the rest."""
         body = {
             "messages": [{"role": "user", "content": [{"text": "hi"}]}],
             "toolConfig": {
                 "tools": [
-                    {"toolSpec": {"name": "fn", "description": "blocked description"}}
+                    {"toolSpec": {"name": "first", "description": "first description"}},
+                    {"toolSpec": {"name": "second", "description": "second description"}},
+                    {"toolSpec": {"name": "third", "description": "third description"}},
+                ]
+            },
+        }
+        texts, _ = _extract_converse_texts(body, skip_system=False, skip_tool=False)
+        assert texts == ["hi"]
+
+    def test_tool_config_definitions_not_extracted_when_tool_messages_skipped(self):
+        body = {
+            "messages": [{"role": "user", "content": [{"text": "hi"}]}],
+            "toolConfig": {
+                "tools": [
+                    {"toolSpec": {"name": "fn", "description": "tool description"}}
                 ]
             },
         }
         texts, _ = _extract_converse_texts(body, skip_system=False, skip_tool=True)
-        assert "blocked description" in texts
+        assert texts == ["hi"]
+
+    def test_tool_use_input_still_extracted_alongside_tool_config(self):
+        """Only tool DEFINITIONS are excluded; caller content inside a toolUse
+        block is still scanned."""
+        body = {
+            "messages": [
+                {
+                    "role": "user",
+                    "content": [
+                        {"text": "hi"},
+                        {"toolUse": {"toolUseId": "t1", "name": "fn", "input": {"q": "user secret"}}},
+                    ],
+                }
+            ],
+            "toolConfig": {
+                "tools": [
+                    {"toolSpec": {"name": "fn", "description": "tool description"}}
+                ]
+            },
+        }
+        texts, _ = _extract_converse_texts(body, skip_system=False, skip_tool=False)
+        assert texts == ["hi", "user secret"]
 
     def test_extracts_additional_model_request_fields(self):
         body = {
@@ -437,9 +478,9 @@ class TestBedrockPassthroughGuardrailHandlerInput:
         assert "blocked content" in sent_texts
 
     @pytest.mark.asyncio
-    async def test_tool_config_description_scanned_and_masked(self):
-        """Blocked text hidden in toolConfig.tools[].toolSpec.description is still
-        forwarded to Bedrock, so the guardrail must see it and mask it in place."""
+    async def test_tool_config_definitions_not_sent_and_left_untouched(self):
+        """Tool definitions never reach the guardrail, and the body forwarded to
+        Bedrock keeps them byte for byte."""
         handler = BedrockPassthroughGuardrailHandler()
         data = _converse_data()
         data["data"]["toolConfig"] = {
@@ -453,36 +494,42 @@ class TestBedrockPassthroughGuardrailHandlerInput:
                 }
             ]
         }
-        guardrail = _make_guardrail(
-            {"texts": ["You are helpful.", "Hello world", "lookup", "[REDACTED]", "object"]}
-        )
+        original_tool_config = copy.deepcopy(data["data"]["toolConfig"])
+        guardrail = _make_guardrail({"texts": ["[REDACTED]", "[REDACTED]"]})
 
         result = await handler.process_input_messages(data=data, guardrail_to_apply=guardrail)
 
         sent_texts = guardrail.apply_guardrail.call_args.kwargs["inputs"]["texts"]
-        assert "email john@example.com" in sent_texts
-        tool_spec = result["data"]["toolConfig"]["tools"][0]["toolSpec"]
-        assert tool_spec["description"] == "[REDACTED]"
+        assert sent_texts == ["You are helpful.", "Hello world"]
+        assert result["data"]["toolConfig"] == original_tool_config
 
     @pytest.mark.asyncio
-    async def test_tool_config_description_blocking_propagates(self):
-        """A blocking guardrail must reject content hidden in a tool description."""
+    async def test_blocking_guardrail_not_triggered_by_tool_description(self):
+        """LIT-5797: a request whose only prompt is a benign user message must not
+        be blocked because a denied term appears in a tool definition."""
         handler = BedrockPassthroughGuardrailHandler()
         data = _converse_data()
         data["data"]["toolConfig"] = {
             "tools": [{"toolSpec": {"name": "fn", "description": "blocked content"}}]
         }
+
+        async def _block_on_denied_term(**kwargs):
+            texts = kwargs["inputs"]["texts"]
+            if any("blocked content" in text for text in texts):
+                raise GuardrailBlocked("Blocked")
+            return {"texts": texts}
+
         guardrail = MagicMock()
         guardrail.guardrail_name = "block-guard"
         guardrail.skip_system_message_in_guardrail = False
         guardrail.skip_tool_message_in_guardrail = False
-        guardrail.apply_guardrail = AsyncMock(side_effect=GuardrailBlocked("Blocked"))
+        guardrail.apply_guardrail = AsyncMock(side_effect=_block_on_denied_term)
 
-        with pytest.raises(GuardrailBlocked):
-            await handler.process_input_messages(data=data, guardrail_to_apply=guardrail)
+        result = await handler.process_input_messages(data=data, guardrail_to_apply=guardrail)
 
         sent_texts = guardrail.apply_guardrail.call_args.kwargs["inputs"]["texts"]
-        assert "blocked content" in sent_texts
+        assert "blocked content" not in sent_texts
+        assert result["data"]["toolConfig"]["tools"][0]["toolSpec"]["description"] == "blocked content"
 
     @pytest.mark.asyncio
     async def test_additional_model_request_fields_scanned_and_masked(self):

tests/test_litellm/proxy/common_utils/test_http_parsing_utils.py

@@ -1053,6 +1053,8 @@ class TestNumericFormFields:
             read_only: ReadOnly[int | None]
             not_required: NotRequired[ReadOnly[int]]
             required: Required[ReadOnly[Annotated[float, "meta"]]]
+            read_only_not_required: ReadOnly[NotRequired[int]]
+            read_only_required: ReadOnly[Required[float]]
 
         assert dict(numeric_form_fields(get_type_hints(Schema))) == {
             "plain": int,
@@ -1061,6 +1063,22 @@ class TestNumericFormFields:
             "read_only": int,
             "not_required": int,
             "required": float,
+            "read_only_not_required": int,
+            "read_only_required": float,
+        }
+
+    def test_qualifiers_are_unwrapped_when_get_type_hints_keeps_extras(self):
+        from typing_extensions import Annotated, NotRequired, ReadOnly, Required, TypedDict
+
+        class Schema(TypedDict, total=False):
+            annotated: ReadOnly[Annotated[int, "meta"]]
+            not_required: NotRequired[ReadOnly[int]]
+            required: Required[ReadOnly[Annotated[float, "meta"]]]
+
+        assert dict(numeric_form_fields(get_type_hints(Schema, include_extras=True))) == {
+            "annotated": int,
+            "not_required": int,
+            "required": float,
         }
 
     def test_non_scalar_and_bool_fields_are_skipped(self):

tests/test_litellm/proxy/common_utils/test_reset_budget_job.py

@@ -4,7 +4,7 @@ import sys
 import types
 from datetime import datetime, timedelta, timezone
 from datetime import time as dt_time
-from typing import Any, Dict, List
+from typing import Any, Dict, Final, List
 from unittest.mock import AsyncMock, MagicMock
 
 import httpx
@@ -1495,6 +1495,32 @@ def test_budget_table_reset_invalidates_every_tag_not_just_the_first(reset_budge
     assert deleted == {"tag:tenant-a", "tag:tenant-b", "tag:tenant-c"}
 
 
+def test_budget_table_reset_invalidates_enduser_counter_and_cache(reset_budget_job, mock_prisma_client, monkeypatch):
+    """When an end user's budget resets, its Redis spend counter is zeroed and its management cache is evicted."""
+    counter_cache: Final = _make_counter_invalidation_job(monkeypatch)
+    budget: Final = _budget_row(budget_id="budget-1")
+    mock_prisma_client.data["budget"] = [budget]
+    test_enduser: Final = type(
+        "LiteLLM_EndUserTable",
+        (),
+        {
+            "spend": 20.0,
+            "litellm_budget_table": budget,
+            "budget_id": "budget-1",
+            "user_id": "customer-42",
+        },
+    )
+    mock_prisma_client.data["enduser"] = [test_enduser]
+
+    asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table())
+
+    counter_cache.in_memory_cache.set_cache.assert_any_call(key="spend:end_user:customer-42", value=0.0, ttl=60)
+    counter_cache.redis_cache.async_set_cache.assert_any_await(key="spend:end_user:customer-42", value=0.0, ttl=60)
+    deleted: Final = {call.kwargs.get("key") for call in counter_cache.user_api_key_cache.async_delete_cache.await_args_list}
+    assert "end_user_id:customer-42" in deleted
+
+
+
 def test_budget_table_reset_commits_even_when_cache_eviction_fails(reset_budget_job, mock_prisma_client, monkeypatch):
     """Eviction runs after the commit, so a broken cache cannot undo the write."""
     counter_cache = _make_counter_invalidation_job(monkeypatch)
@@ -3028,6 +3054,38 @@ def test_budget_cascade_carries_enduser_overage_when_rollover_enabled(
     } in enduser_writes
 
 
+def test_budget_cascade_carries_default_tier_enduser_counter_when_rollover_enabled(
+    rollover_enabled, reset_budget_job, mock_prisma_client, monkeypatch
+):
+    """An end user on the default budget (no budget_id on its row) 5 over the cap
+    keeps a counter of 5 in the next window and loses its cached object."""
+    import litellm
+
+    counter_cache: Final = _make_counter_invalidation_job(monkeypatch)
+    monkeypatch.setattr(litellm, "max_end_user_budget_id", "default-enduser-budget")
+    mock_prisma_client.data["budget"] = [
+        _budget_row(budget_id="default-enduser-budget", budget_duration="1d", max_budget=10.0)
+    ]
+    implicit_enduser: Final = type(
+        "EndUserRow",
+        (),
+        {
+            "spend": 15.0,
+            "user_id": "enduser-implicit",
+            "budget_id": None,
+            "model_dump": lambda self=None: {"spend": 15.0, "user_id": "enduser-implicit", "budget_id": None, "blocked": False},
+        },
+    )
+    mock_prisma_client.db.litellm_endusertable.set_find_many_results([implicit_enduser])
+
+    asyncio.run(reset_budget_job.reset_budget_for_litellm_budget_table())
+
+    counter_cache.in_memory_cache.set_cache.assert_any_call(key="spend:end_user:enduser-implicit", value=5.0, ttl=60)
+    counter_cache.redis_cache.async_set_cache.assert_any_await(key="spend:end_user:enduser-implicit", value=5.0, ttl=60)
+    deleted: Final = {call.kwargs.get("key") for call in counter_cache.user_api_key_cache.async_delete_cache.await_args_list}
+    assert "end_user_id:enduser-implicit" in deleted
+
+
 def _replay_spend_writes(writes, spend):
     """Apply the queued update_many statements in order, the way the DB
     transaction executes them, and return the row's final spend."""

tests/test_litellm/proxy/db/test_spend_counter_reseed.py

@@ -9,6 +9,7 @@ from __future__ import annotations
 
 from datetime import datetime, timedelta, timezone
 from types import SimpleNamespace
+from typing import Final
 
 import pytest
 
@@ -18,7 +19,7 @@ from litellm.proxy.db.spend_counter_reseed import SpendCounterReseed
 WINDOW_START = datetime(2026, 8, 1, tzinfo=timezone.utc)
 
 
-class _FakeWindowSpendTable:
+class _FakeFindUniqueTable:
     def __init__(self, row: SimpleNamespace | None, error: Exception | None = None) -> None:
         self._row = row
         self._error = error
@@ -47,10 +48,13 @@ class _FakePrismaClient:
         row: SimpleNamespace | None = None,
         spend_logs_total: float = 0.0,
         error: Exception | None = None,
+        end_user_row: SimpleNamespace | None = None,
+        end_user_error: Exception | None = None,
     ) -> None:
         self.db = SimpleNamespace(
-            litellm_budgetwindowspend=_FakeWindowSpendTable(row=row, error=error),
+            litellm_budgetwindowspend=_FakeFindUniqueTable(row=row, error=error),
             litellm_spendlogs=_FakeSpendLogsTable(total=spend_logs_total),
+            litellm_endusertable=_FakeFindUniqueTable(row=end_user_row, error=end_user_error),
         )
 
 
@@ -248,3 +252,65 @@ async def test_coalesced_window_seeds_a_cold_counter_from_the_row():
     assert result == 4.5
     assert cache.in_memory_cache.get_cache(key=counter_key) == 4.5
     assert prisma.db.litellm_spendlogs.call_count == 0
+
+
+@pytest.mark.asyncio
+async def test_end_user_from_db_reads_the_end_user_row_by_user_id():
+    prisma: Final = _FakePrismaClient(end_user_row=SimpleNamespace(user_id="customer-42", spend=0.0))
+
+    result: Final = await SpendCounterReseed.end_user_from_db(
+        prisma_client=prisma, counter_key="spend:end_user:customer-42"
+    )
+
+    assert result == 0.0
+    assert prisma.db.litellm_endusertable.where_clauses == [{"user_id": "customer-42"}]
+
+
+@pytest.mark.asyncio
+async def test_end_user_from_db_returns_the_recorded_spend():
+    prisma: Final = _FakePrismaClient(end_user_row=SimpleNamespace(user_id="customer-42", spend=12.5))
+
+    assert (
+        await SpendCounterReseed.end_user_from_db(prisma_client=prisma, counter_key="spend:end_user:customer-42")
+        == 12.5
+    )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("counter_key", ["spend:key:hashed", "spend:team:t1", "spend:tag:t1"])
+async def test_end_user_from_db_ignores_other_counter_kinds_without_touching_the_db(counter_key):
+    prisma: Final = _FakePrismaClient(end_user_row=SimpleNamespace(user_id="x", spend=5.0))
+
+    assert await SpendCounterReseed.end_user_from_db(prisma_client=prisma, counter_key=counter_key) is None
+    assert prisma.db.litellm_endusertable.where_clauses == []
+
+
+@pytest.mark.asyncio
+async def test_end_user_from_db_returns_none_without_a_row_a_client_or_on_db_error():
+    assert (
+        await SpendCounterReseed.end_user_from_db(prisma_client=None, counter_key="spend:end_user:customer-42")
+        is None
+    )
+    assert (
+        await SpendCounterReseed.end_user_from_db(
+            prisma_client=_FakePrismaClient(end_user_row=None), counter_key="spend:end_user:customer-42"
+        )
+        is None
+    )
+    assert (
+        await SpendCounterReseed.end_user_from_db(
+            prisma_client=_FakePrismaClient(end_user_error=RuntimeError("db down")),
+            counter_key="spend:end_user:customer-42",
+        )
+        is None
+    )
+
+
+@pytest.mark.asyncio
+async def test_from_db_still_never_reads_the_end_user_row():
+    """A cold end-user counter keeps seeding from the cached end-user object the auth
+    path already loaded; the row is read only as the budget floor."""
+    prisma: Final = _FakePrismaClient(end_user_row=SimpleNamespace(user_id="customer-42", spend=5.0))
+
+    assert await SpendCounterReseed.from_db(prisma_client=prisma, counter_key="spend:end_user:customer-42") is None
+    assert prisma.db.litellm_endusertable.where_clauses == []

tests/test_litellm/proxy/management_endpoints/test_access_group_endpoints.py

@@ -57,8 +57,20 @@ def _make_access_group_record(
     return record
 
 
-def _make_team_record(team_id: str, access_group_ids: list[str] | None = None):
-    return types.SimpleNamespace(team_id=team_id, access_group_ids=access_group_ids or [])
+def _make_team_record(team_id: str, access_group_ids: list[str] | None = None, team_alias: str | None = None):
+    return types.SimpleNamespace(team_id=team_id, access_group_ids=access_group_ids or [], team_alias=team_alias)
+
+
+def _make_mcp_server_record(server_id: str, alias: str | None = None, server_name: str | None = None):
+    return types.SimpleNamespace(server_id=server_id, alias=alias, server_name=server_name)
+
+
+def _make_agent_record(agent_id: str, agent_name: str):
+    return types.SimpleNamespace(agent_id=agent_id, agent_name=agent_name)
+
+
+def _make_key_record(token: str, key_alias: str | None = None):
+    return types.SimpleNamespace(token=token, key_alias=key_alias)
 
 
 @pytest.fixture
@@ -109,6 +121,12 @@ def client_and_mocks(monkeypatch):
     mock_key_table.find_unique = AsyncMock(return_value=None)
     mock_key_table.update = AsyncMock(return_value=None)
 
+    mock_mcp_server_table = MagicMock()
+    mock_mcp_server_table.find_many = AsyncMock(return_value=[])
+
+    mock_agents_table = MagicMock()
+    mock_agents_table.find_many = AsyncMock(return_value=[])
+
     @asynccontextmanager
     async def mock_tx():
         tx = types.SimpleNamespace(
@@ -122,6 +140,8 @@ def client_and_mocks(monkeypatch):
         litellm_accessgrouptable=mock_access_group_table,
         litellm_teamtable=mock_team_table,
         litellm_verificationtoken=mock_key_table,
+        litellm_mcpservertable=mock_mcp_server_table,
+        litellm_agentstable=mock_agents_table,
         tx=mock_tx,
     )
     mock_prisma.db = mock_db
@@ -1447,3 +1467,169 @@ def test_update_access_group_null_assigned_ids_treated_as_empty(client_and_mocks
     update_call_kwargs = mock_table.update.call_args.kwargs
     assert update_call_kwargs["data"]["assigned_team_ids"] == []
     assert update_call_kwargs["data"]["assigned_key_ids"] == []
+
+
+# ---------------------------------------------------------------------------
+# Resolved resource names (LIT-6594)
+# ---------------------------------------------------------------------------
+
+
+def _mock_resource_tables(mock_prisma, *, mcp_servers=(), agents=(), teams=(), keys=()):
+    mock_prisma.db.litellm_mcpservertable.find_many = AsyncMock(return_value=list(mcp_servers))
+    mock_prisma.db.litellm_agentstable.find_many = AsyncMock(return_value=list(agents))
+    mock_prisma.db.litellm_teamtable.find_many = AsyncMock(return_value=list(teams))
+    mock_prisma.db.litellm_verificationtoken.find_many = AsyncMock(return_value=list(keys))
+
+
+@pytest.mark.parametrize("base_path", ACCESS_GROUP_PATHS)
+def test_get_access_group_resolves_resource_names(client_and_mocks, base_path):
+    """Every id list gets a sibling list of {id, name}; name is null when the id has no alias or no longer resolves."""
+    client, mock_prisma, mock_table, *_ = client_and_mocks
+    mock_table.find_unique = AsyncMock(
+        return_value=_make_access_group_record(
+            access_group_id="ag-123",
+            access_mcp_server_ids=["mcp-a", "mcp-b", "mcp-ghost"],
+            access_agent_ids=["agent-a", "agent-ghost"],
+            assigned_team_ids=["team-a", "team-b"],
+            assigned_key_ids=["key-a", "key-b"],
+        )
+    )
+    _mock_resource_tables(
+        mock_prisma,
+        mcp_servers=[
+            _make_mcp_server_record("mcp-a", alias="GitHub"),
+            _make_mcp_server_record("mcp-b", server_name="jira_tools"),
+        ],
+        agents=[_make_agent_record("agent-a", "support-bot")],
+        teams=[
+            _make_team_record("team-a", ["ag-123"], team_alias="Platform"),
+            _make_team_record("team-b", ["ag-123"]),
+        ],
+        keys=[_make_key_record("key-a", key_alias="ci-key"), _make_key_record("key-b")],
+    )
+
+    resp = client.get(f"{base_path}/ag-123")
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["access_mcp_servers"] == [
+        {"id": "mcp-a", "name": "GitHub"},
+        {"id": "mcp-b", "name": "jira_tools"},
+        {"id": "mcp-ghost", "name": None},
+    ]
+    assert body["access_agents"] == [{"id": "agent-a", "name": "support-bot"}, {"id": "agent-ghost", "name": None}]
+    assert body["assigned_teams"] == [{"id": "team-a", "name": "Platform"}, {"id": "team-b", "name": None}]
+    assert body["assigned_keys"] == [{"id": "key-a", "name": "ci-key"}, {"id": "key-b", "name": None}]
+    assert body["access_mcp_server_ids"] == ["mcp-a", "mcp-b", "mcp-ghost"]
+    assert body["assigned_team_ids"] == ["team-a", "team-b"]
+
+    mcp_where = mock_prisma.db.litellm_mcpservertable.find_many.call_args.kwargs["where"]
+    assert sorted(mcp_where["server_id"]["in"]) == ["mcp-a", "mcp-b", "mcp-ghost"]
+    agent_where = mock_prisma.db.litellm_agentstable.find_many.call_args.kwargs["where"]
+    assert sorted(agent_where["agent_id"]["in"]) == ["agent-a", "agent-ghost"]
+    key_where = mock_prisma.db.litellm_verificationtoken.find_many.call_args.kwargs["where"]
+    assert sorted(key_where["token"]["in"]) == ["key-a", "key-b"]
+
+
+def test_list_access_groups_resolves_names_with_one_query_per_table(client_and_mocks):
+    """List batches every group's ids into one lookup per table and attributes names back to the right group."""
+    client, mock_prisma, mock_table, *_ = client_and_mocks
+    mock_table.find_many = AsyncMock(
+        return_value=[
+            _make_access_group_record(
+                access_group_id="ag-1", access_mcp_server_ids=["mcp-a"], access_agent_ids=["agent-a"], assigned_key_ids=["key-a"]
+            ),
+            _make_access_group_record(
+                access_group_id="ag-2", access_mcp_server_ids=["mcp-b"], access_agent_ids=["agent-b"], assigned_key_ids=["key-b"]
+            ),
+        ]
+    )
+    _mock_resource_tables(
+        mock_prisma,
+        mcp_servers=[_make_mcp_server_record("mcp-a", alias="A"), _make_mcp_server_record("mcp-b", alias="B")],
+        agents=[_make_agent_record("agent-a", "Agent A"), _make_agent_record("agent-b", "Agent B")],
+        keys=[_make_key_record("key-a", key_alias="Key A"), _make_key_record("key-b", key_alias="Key B")],
+    )
+
+    resp = client.get("/v1/access_group")
+    assert resp.status_code == 200
+    first, second = resp.json()
+    assert first["access_mcp_servers"] == [{"id": "mcp-a", "name": "A"}]
+    assert first["access_agents"] == [{"id": "agent-a", "name": "Agent A"}]
+    assert first["assigned_keys"] == [{"id": "key-a", "name": "Key A"}]
+    assert second["access_mcp_servers"] == [{"id": "mcp-b", "name": "B"}]
+    assert second["access_agents"] == [{"id": "agent-b", "name": "Agent B"}]
+    assert second["assigned_keys"] == [{"id": "key-b", "name": "Key B"}]
+
+    for table, column in (
+        (mock_prisma.db.litellm_mcpservertable, "server_id"),
+        (mock_prisma.db.litellm_agentstable, "agent_id"),
+        (mock_prisma.db.litellm_verificationtoken, "token"),
+    ):
+        table.find_many.assert_awaited_once()
+        assert len(table.find_many.call_args.kwargs["where"][column]["in"]) == 2
+
+
+def test_list_access_groups_skips_lookups_when_nothing_to_resolve(client_and_mocks):
+    """Groups with no MCP servers, agents or keys must not trigger an empty IN () query per table."""
+    client, mock_prisma, mock_table, *_ = client_and_mocks
+    mock_table.find_many = AsyncMock(
+        return_value=[_make_access_group_record(access_group_id="ag-1"), _make_access_group_record(access_group_id="ag-2")]
+    )
+
+    resp = client.get("/v1/access_group")
+    assert resp.status_code == 200
+    assert all(group["access_mcp_servers"] == [] and group["assigned_keys"] == [] for group in resp.json())
+
+    mock_prisma.db.litellm_mcpservertable.find_many.assert_not_awaited()
+    mock_prisma.db.litellm_agentstable.find_many.assert_not_awaited()
+    mock_prisma.db.litellm_verificationtoken.find_many.assert_not_awaited()
+
+
+def test_create_access_group_response_carries_resolved_names(client_and_mocks):
+    """The create response already shows names so the UI never has to refetch to label what it just saved."""
+    client, mock_prisma, *_ = client_and_mocks
+    team_record = _make_team_record("team-1", team_alias="Platform")
+    mock_prisma.db.litellm_teamtable.find_unique = AsyncMock(return_value=team_record)
+    _mock_resource_tables(
+        mock_prisma,
+        mcp_servers=[_make_mcp_server_record("mcp-a", alias="GitHub")],
+        agents=[_make_agent_record("agent-a", "support-bot")],
+        teams=[team_record],
+    )
+
+    resp = client.post(
+        "/v1/access_group",
+        json={
+            "access_group_name": "new-group",
+            "access_mcp_server_ids": ["mcp-a"],
+            "access_agent_ids": ["agent-a"],
+            "assigned_team_ids": ["team-1"],
+        },
+    )
+    assert resp.status_code == 201
+    body = resp.json()
+    assert body["access_mcp_servers"] == [{"id": "mcp-a", "name": "GitHub"}]
+    assert body["access_agents"] == [{"id": "agent-a", "name": "support-bot"}]
+    assert body["assigned_teams"] == [{"id": "team-1", "name": "Platform"}]
+
+
+def test_update_access_group_response_carries_resolved_names(client_and_mocks):
+    """The update response reflects the new ids with their names, not the pre-update state."""
+    client, mock_prisma, mock_table, *_ = client_and_mocks
+    mock_table.find_unique = AsyncMock(
+        return_value=_make_access_group_record(access_group_id="ag-update", access_mcp_server_ids=["mcp-old"])
+    )
+    _mock_resource_tables(
+        mock_prisma,
+        mcp_servers=[_make_mcp_server_record("mcp-new", alias="Linear")],
+        agents=[_make_agent_record("agent-a", "support-bot")],
+    )
+
+    resp = client.put(
+        "/v1/access_group/ag-update", json={"access_mcp_server_ids": ["mcp-new"], "access_agent_ids": ["agent-a"]}
+    )
+    assert resp.status_code == 200
+    body = resp.json()
+    assert body["access_mcp_servers"] == [{"id": "mcp-new", "name": "Linear"}]
+    assert body["access_agents"] == [{"id": "agent-a", "name": "support-bot"}]
+    assert body["access_mcp_server_ids"] == ["mcp-new"]

tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py

@@ -4863,6 +4863,302 @@ async def test_team_member_delete_by_email_the_user_row_does_not_carry(
     )
 
 
+@pytest.mark.asyncio
+async def test_team_member_delete_clears_team_left_on_the_user_row_without_a_roster_entry(
+    mock_db_client, mock_admin_auth
+):
+    """
+    A user row can keep a team (several times over, from older duplicate-prone adds) after the
+    roster entry is gone, which leaves the team listed on the user, offered in the key creation
+    dropdown, and rejected by key creation itself. Reporting "User not found in team" left that
+    residue unremovable, so the delete now cleans every copy of the team off the user row.
+    """
+    from litellm.proxy._types import TeamMemberDeleteRequest
+    from litellm.proxy.management_endpoints.team_endpoints import team_member_delete
+
+    test_team_id = "team-del-orphan-123"
+    test_user_id = "user-del-orphan-123"
+
+    mock_team_row = MagicMock()
+    mock_team_row.model_dump.return_value = {
+        "team_id": test_team_id,
+        "members_with_roles": [],
+        "team_member_permissions": [],
+        "metadata": {},
+        "models": [],
+        "spend": 0.0,
+    }
+    mock_db_client.db.litellm_teamtable.find_unique = AsyncMock(
+        return_value=mock_team_row
+    )
+    mock_db_client.db.litellm_teamtable.update = AsyncMock(return_value=mock_team_row)
+
+    mock_user_row = MagicMock()
+    mock_user_row.user_id = test_user_id
+    mock_user_row.user_email = None
+    mock_user_row.teams = [test_team_id, "other-team", test_team_id]
+    mock_db_client.db.litellm_usertable.find_many = AsyncMock(
+        return_value=[mock_user_row]
+    )
+    mock_db_client.db.litellm_usertable.update = AsyncMock(return_value=MagicMock())
+
+    mock_db_client.db.litellm_teammembership = MagicMock()
+    mock_db_client.db.litellm_teammembership.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    mock_db_client.db.litellm_verificationtoken = MagicMock()
+    mock_db_client.db.litellm_verificationtoken.find_many = AsyncMock(return_value=[])
+    mock_db_client.db.litellm_verificationtoken.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    _wire_member_delete_tx(mock_db_client)
+
+    await team_member_delete(
+        data=TeamMemberDeleteRequest(team_id=test_team_id, user_id=test_user_id),
+        user_api_key_dict=mock_admin_auth,
+    )
+
+    mock_db_client.db.litellm_usertable.update.assert_awaited_once_with(
+        where={"user_id": test_user_id},
+        data={"teams": {"set": ["other-team"]}},
+    )
+    mock_db_client.db.litellm_teammembership.delete_many.assert_awaited_once_with(
+        where={"team_id": test_team_id, "user_id": test_user_id}
+    )
+
+
+@pytest.mark.asyncio
+async def test_team_member_delete_still_rejects_a_user_the_team_has_no_trace_of(
+    mock_db_client, mock_admin_auth
+):
+    from litellm.proxy._types import TeamMemberDeleteRequest
+    from litellm.proxy.management_endpoints.team_endpoints import team_member_delete
+
+    test_team_id = "team-del-absent-123"
+    test_user_id = "user-del-absent-123"
+
+    mock_team_row = MagicMock()
+    mock_team_row.model_dump.return_value = {
+        "team_id": test_team_id,
+        "members_with_roles": [],
+        "team_member_permissions": [],
+        "metadata": {},
+        "models": [],
+        "spend": 0.0,
+    }
+    mock_db_client.db.litellm_teamtable.find_unique = AsyncMock(
+        return_value=mock_team_row
+    )
+    mock_db_client.db.litellm_teamtable.update = AsyncMock(return_value=mock_team_row)
+
+    mock_user_row = MagicMock()
+    mock_user_row.user_id = test_user_id
+    mock_user_row.user_email = None
+    mock_user_row.teams = ["other-team"]
+    mock_db_client.db.litellm_usertable.find_many = AsyncMock(
+        return_value=[mock_user_row]
+    )
+    mock_db_client.db.litellm_usertable.update = AsyncMock(return_value=MagicMock())
+
+    mock_db_client.db.litellm_teammembership = MagicMock()
+    mock_db_client.db.litellm_teammembership.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    _wire_member_delete_tx(mock_db_client)
+
+    with pytest.raises(HTTPException) as exc_info:
+        await team_member_delete(
+            data=TeamMemberDeleteRequest(team_id=test_team_id, user_id=test_user_id),
+            user_api_key_dict=mock_admin_auth,
+        )
+
+    assert exc_info.value.status_code == 400
+    assert exc_info.value.detail == {"error": "User not found in team"}
+    mock_db_client.db.litellm_usertable.update.assert_not_awaited()
+    mock_db_client.db.litellm_teammembership.delete_many.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_team_member_delete_leaves_a_bystander_named_by_a_conflicting_user_id_alone(
+    mock_db_client, mock_admin_auth
+):
+    """
+    A request can carry a user_id and a user_email that point at two different people, and only the
+    email matches a roster entry. Cleaning up both ids would strip the team, the membership row and
+    the keys off the bystander the roster never listed, so the user_id only widens the cleanup when
+    the roster came back empty.
+    """
+    from litellm.proxy._types import TeamMemberDeleteRequest
+    from litellm.proxy.management_endpoints.team_endpoints import team_member_delete
+
+    test_team_id = "team-del-conflict-123"
+    roster_user_id = "user-del-conflict-roster"
+    bystander_user_id = "user-del-conflict-bystander"
+    roster_email = "roster@example.com"
+
+    mock_team_row = MagicMock()
+    mock_team_row.model_dump.return_value = {
+        "team_id": test_team_id,
+        "members_with_roles": [
+            {"user_id": roster_user_id, "user_email": roster_email, "role": "user"}
+        ],
+        "team_member_permissions": [],
+        "metadata": {},
+        "models": [],
+        "spend": 0.0,
+    }
+    mock_db_client.db.litellm_teamtable.find_unique = AsyncMock(
+        return_value=mock_team_row
+    )
+    mock_db_client.db.litellm_teamtable.update = AsyncMock(return_value=mock_team_row)
+
+    roster_user_row = MagicMock()
+    roster_user_row.user_id = roster_user_id
+    roster_user_row.user_email = roster_email
+    roster_user_row.teams = [test_team_id]
+
+    bystander_user_row = MagicMock()
+    bystander_user_row.user_id = bystander_user_id
+    bystander_user_row.user_email = "bystander@example.com"
+    bystander_user_row.teams = [test_team_id]
+
+    rows_by_user_id = {
+        roster_user_id: roster_user_row,
+        bystander_user_id: bystander_user_row,
+    }
+
+    async def find_user_rows(where):
+        user_id_filter = where.get("user_id")
+        if isinstance(user_id_filter, dict):
+            return [
+                rows_by_user_id[uid]
+                for uid in user_id_filter.get("in", [])
+                if uid in rows_by_user_id
+            ]
+        return [
+            row
+            for row in rows_by_user_id.values()
+            if row.user_email == where.get("user_email")
+        ]
+
+    mock_db_client.db.litellm_usertable.find_many = AsyncMock(
+        side_effect=find_user_rows
+    )
+    mock_db_client.db.litellm_usertable.update = AsyncMock(return_value=MagicMock())
+
+    mock_db_client.db.litellm_teammembership = MagicMock()
+    mock_db_client.db.litellm_teammembership.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    mock_db_client.db.litellm_verificationtoken = MagicMock()
+    mock_db_client.db.litellm_verificationtoken.find_many = AsyncMock(return_value=[])
+    mock_db_client.db.litellm_verificationtoken.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    _wire_member_delete_tx(mock_db_client)
+
+    await team_member_delete(
+        data=TeamMemberDeleteRequest(
+            team_id=test_team_id,
+            user_id=bystander_user_id,
+            user_email=roster_email,
+        ),
+        user_api_key_dict=mock_admin_auth,
+    )
+
+    mock_db_client.db.litellm_usertable.update.assert_awaited_once_with(
+        where={"user_id": roster_user_id},
+        data={"teams": {"set": []}},
+    )
+    mock_db_client.db.litellm_teammembership.delete_many.assert_awaited_once_with(
+        where={"team_id": test_team_id, "user_id": roster_user_id}
+    )
+    mock_db_client.db.litellm_verificationtoken.delete_many.assert_awaited_once_with(
+        where={"user_id": {"in": [roster_user_id]}, "team_id": test_team_id}
+    )
+
+
+@pytest.mark.asyncio
+async def test_team_member_delete_by_email_only_touches_the_row_carrying_the_stale_team(
+    mock_db_client, mock_admin_auth
+):
+    """
+    user_email is not unique, so an email delete against an empty roster can match several user
+    rows. Only the row that actually carries the team is stale; the namesake keeps its team, its
+    membership row and its keys.
+    """
+    from litellm.proxy._types import TeamMemberDeleteRequest
+    from litellm.proxy.management_endpoints.team_endpoints import team_member_delete
+
+    test_team_id = "team-del-shared-email-123"
+    stale_user_id = "user-del-shared-email-stale"
+    namesake_user_id = "user-del-shared-email-namesake"
+    shared_email = "shared@example.com"
+
+    mock_team_row = MagicMock()
+    mock_team_row.model_dump.return_value = {
+        "team_id": test_team_id,
+        "members_with_roles": [],
+        "team_member_permissions": [],
+        "metadata": {},
+        "models": [],
+        "spend": 0.0,
+    }
+    mock_db_client.db.litellm_teamtable.find_unique = AsyncMock(
+        return_value=mock_team_row
+    )
+    mock_db_client.db.litellm_teamtable.update = AsyncMock(return_value=mock_team_row)
+
+    stale_user_row = MagicMock()
+    stale_user_row.user_id = stale_user_id
+    stale_user_row.user_email = shared_email
+    stale_user_row.teams = [test_team_id]
+
+    namesake_user_row = MagicMock()
+    namesake_user_row.user_id = namesake_user_id
+    namesake_user_row.user_email = shared_email
+    namesake_user_row.teams = ["other-team"]
+
+    mock_db_client.db.litellm_usertable.find_many = AsyncMock(
+        return_value=[stale_user_row, namesake_user_row]
+    )
+    mock_db_client.db.litellm_usertable.update = AsyncMock(return_value=MagicMock())
+
+    mock_db_client.db.litellm_teammembership = MagicMock()
+    mock_db_client.db.litellm_teammembership.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    mock_db_client.db.litellm_verificationtoken = MagicMock()
+    mock_db_client.db.litellm_verificationtoken.find_many = AsyncMock(return_value=[])
+    mock_db_client.db.litellm_verificationtoken.delete_many = AsyncMock(
+        return_value=MagicMock()
+    )
+
+    _wire_member_delete_tx(mock_db_client)
+
+    await team_member_delete(
+        data=TeamMemberDeleteRequest(team_id=test_team_id, user_email=shared_email),
+        user_api_key_dict=mock_admin_auth,
+    )
+
+    mock_db_client.db.litellm_usertable.update.assert_awaited_once_with(
+        where={"user_id": stale_user_id},
+        data={"teams": {"set": []}},
+    )
+    mock_db_client.db.litellm_teammembership.delete_many.assert_awaited_once_with(
+        where={"team_id": test_team_id, "user_id": stale_user_id}
+    )
+    mock_db_client.db.litellm_verificationtoken.delete_many.assert_awaited_once_with(
+        where={"user_id": {"in": [stale_user_id]}, "team_id": test_team_id}
+    )
+
+
 class _InjectedMemberDeleteFailure(Exception):
     pass
 

tests/test_litellm/proxy/management_helpers/test_resource_display_names.py

@@ -0,0 +1,130 @@
+import types
+from types import MappingProxyType
+from unittest.mock import AsyncMock
+
+import pytest
+
+from litellm.proxy.agent_endpoints.agent_registry import AgentRegistry
+from litellm.proxy.management_helpers.resource_display_names import (
+    agent_display_names,
+    key_display_names,
+    mcp_server_display_names,
+)
+from litellm.types.agents import AgentResponse
+from litellm.types.mcp_server.mcp_server_manager import MCPServer
+
+
+def _table(rows=()):
+    return types.SimpleNamespace(find_many=AsyncMock(return_value=list(rows)))
+
+
+def _prisma(**tables):
+    return types.SimpleNamespace(db=types.SimpleNamespace(**tables))
+
+
+def _config_server(server_id: str, name: str, alias: str | None = None, server_name: str | None = None) -> MCPServer:
+    return MCPServer(server_id=server_id, name=name, alias=alias, server_name=server_name, transport="http")
+
+
+def _registry_with(*agents: AgentResponse, legacy_ids: dict[str, str] | None = None) -> AgentRegistry:
+    registry = AgentRegistry()
+    for agent in agents:
+        registry.register_agent(agent)
+    registry.config_agent_legacy_ids = MappingProxyType(legacy_ids or {})
+    return registry
+
+
+def _agent(agent_id: str, agent_name: str) -> AgentResponse:
+    return AgentResponse(agent_id=agent_id, agent_name=agent_name, agent_card_params={})
+
+
+@pytest.mark.asyncio
+async def test_mcp_db_row_beats_config_entry_for_the_same_server():
+    """The DB is authoritative when both sources know a server; the registry may lag behind a rename on another pod."""
+    prisma = _prisma(
+        litellm_mcpservertable=_table([types.SimpleNamespace(server_id="s1", alias="db-alias", server_name=None)])
+    )
+    names = await mcp_server_display_names(prisma, ("s1",), {"s1": _config_server("s1", "config-name")})
+    assert dict(names) == {"s1": "db-alias"}
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    ("alias", "server_name", "expected"),
+    [("Alias", "server_name", "Alias"), (None, "server_name", "server_name"), (None, None, "config-name")],
+)
+async def test_mcp_config_only_server_falls_back_alias_then_server_name_then_name(alias, server_name, expected):
+    """Config-declared servers have no DB row, so their registry entry supplies the label."""
+    prisma = _prisma(litellm_mcpservertable=_table())
+    config = {"s1": _config_server("s1", "config-name", alias=alias, server_name=server_name)}
+    names = await mcp_server_display_names(prisma, ("s1",), config)
+    assert dict(names) == {"s1": expected}
+
+
+@pytest.mark.asyncio
+async def test_mcp_db_row_without_alias_or_server_name_yields_no_label():
+    """A bare DB row must not produce an empty string label; the caller falls back to the id."""
+    prisma = _prisma(
+        litellm_mcpservertable=_table([types.SimpleNamespace(server_id="s1", alias=None, server_name=None)])
+    )
+    assert dict(await mcp_server_display_names(prisma, ("s1",), {})) == {}
+
+
+@pytest.mark.asyncio
+async def test_mcp_only_requested_ids_are_returned_and_the_query_is_deduped():
+    """Unrequested config servers stay out of the result and repeated ids collapse to one IN filter entry."""
+    table = _table([types.SimpleNamespace(server_id="s1", alias="A", server_name=None)])
+    prisma = _prisma(litellm_mcpservertable=table)
+    config = {"other": _config_server("other", "not-requested")}
+    names = await mcp_server_display_names(prisma, ("s1", "s1", "missing"), config)
+    assert dict(names) == {"s1": "A"}
+    assert sorted(table.find_many.call_args.kwargs["where"]["server_id"]["in"]) == ["missing", "s1"]
+
+
+@pytest.mark.asyncio
+async def test_mcp_empty_ids_skip_the_db():
+    table = _table()
+    names = await mcp_server_display_names(_prisma(litellm_mcpservertable=table), (), {})
+    assert dict(names) == {}
+    table.find_many.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_agent_db_name_beats_registry_name():
+    prisma = _prisma(litellm_agentstable=_table([types.SimpleNamespace(agent_id="a1", agent_name="from-db")]))
+    registry = _registry_with(_agent("a1", "from-registry"))
+    assert dict(await agent_display_names(prisma, ("a1",), registry)) == {"a1": "from-db"}
+
+
+@pytest.mark.asyncio
+async def test_agent_legacy_config_id_resolves_to_the_stable_agent_name():
+    """Access groups saved before agent ids were stabilised still carry the legacy hash; it must still get a name."""
+    prisma = _prisma(litellm_agentstable=_table())
+    registry = _registry_with(_agent("stable-id", "config-agent"), legacy_ids={"legacy-id": "stable-id"})
+    names = await agent_display_names(prisma, ("legacy-id", "stable-id", "unknown"), registry)
+    assert dict(names) == {"legacy-id": "config-agent", "stable-id": "config-agent"}
+
+
+@pytest.mark.asyncio
+async def test_agent_empty_ids_skip_the_db():
+    table = _table()
+    names = await agent_display_names(_prisma(litellm_agentstable=table), (), _registry_with())
+    assert dict(names) == {}
+    table.find_many.assert_not_awaited()
+
+
+@pytest.mark.asyncio
+async def test_key_alias_only_for_keys_that_have_one():
+    table = _table(
+        [types.SimpleNamespace(token="k1", key_alias="ci-key"), types.SimpleNamespace(token="k2", key_alias=None)]
+    )
+    names = await key_display_names(_prisma(litellm_verificationtoken=table), ("k1", "k2", "k1"))
+    assert dict(names) == {"k1": "ci-key"}
+    assert sorted(table.find_many.call_args.kwargs["where"]["token"]["in"]) == ["k1", "k2"]
+
+
+@pytest.mark.asyncio
+async def test_key_empty_ids_skip_the_db():
+    table = _table()
+    assert dict(await key_display_names(_prisma(litellm_verificationtoken=table), ())) == {}
+    table.find_many.assert_not_awaited()

tests/test_litellm/proxy/proxy_server/test_spend_counters.py

@@ -22,6 +22,7 @@ from __future__ import annotations
 
 import asyncio
 from datetime import datetime
+from typing import Final
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -222,16 +223,19 @@ async def test_get_current_spend_floor_caches_db_read(monkeypatch):
 
 
 @pytest.mark.asyncio
-async def test_get_current_spend_floors_end_user_tag_against_fallback(monkeypatch):
-    """End-user and tag counters have no DB row (from_db returns None). When the
-    counter is stale-low, enforcement falls back to the caller's recorded spend
-    (loaded fresh in auth) instead of trusting the stale counter."""
-    fake_cache = _make_spend_counter_cache(redis_get_value=2.0)
+@pytest.mark.parametrize("counter_key", ("spend:end_user:e1", "spend:tag:t1"))
+async def test_get_current_spend_floors_end_user_tag_against_fallback(monkeypatch, counter_key):
+    """Tag counters have no DB row (from_db returns None), and an end-user counter has
+    none to read without a DB client. When such a counter is stale-low, enforcement
+    falls back to the caller's recorded spend (loaded fresh in auth) instead of
+    trusting the stale counter."""
+    fake_cache: Final = _make_spend_counter_cache(redis_get_value=2.0)
     monkeypatch.setattr(ps, "spend_counter_cache", fake_cache)
+    monkeypatch.setattr(ps, "prisma_client", None)
     monkeypatch.setattr(ps.SpendCounterReseed, "from_db", AsyncMock(return_value=None))
 
-    result = await ps.get_current_spend(
-        counter_key="spend:end_user:e1",
+    result: Final = await ps.get_current_spend(
+        counter_key=counter_key,
         fallback_spend=20.0,
         max_budget=10.0,
     )
@@ -241,6 +245,72 @@ async def test_get_current_spend_floors_end_user_tag_against_fallback(monkeypatc
     fake_cache.redis_cache.async_set_max.assert_not_called()
 
 
+def _make_prisma_with_end_user_row(spend: float | None):
+    prisma: Final = MagicMock()
+    prisma.db.litellm_endusertable.find_unique = AsyncMock(
+        return_value=None if spend is None else MagicMock(spend=spend)
+    )
+    return prisma
+
+
+@pytest.mark.asyncio
+async def test_get_current_spend_end_user_floor_admits_after_a_reset_on_a_stale_worker(monkeypatch):
+    """The reset job zeroes LiteLLM_EndUserTable.spend and the shared counter, but it
+    evicts the cached end-user object only on the worker that ran the reset. Every
+    other worker still passes the pre-reset spend as fallback_spend, and that stale
+    copy must not out-vote the reset row."""
+    fake_cache: Final = _make_spend_counter_cache(redis_get_value=0.0)
+    monkeypatch.setattr(ps, "spend_counter_cache", fake_cache)
+    prisma: Final = _make_prisma_with_end_user_row(spend=0.0)
+    monkeypatch.setattr(ps, "prisma_client", prisma)
+
+    result = await ps.get_current_spend(
+        counter_key="spend:end_user:customer-42",
+        fallback_spend=0.000032,
+        max_budget=0.00003,
+        fallback_authoritative=True,
+    )
+
+    assert result == 0.0
+    prisma.db.litellm_endusertable.find_unique.assert_awaited_once_with(where={"user_id": "customer-42"})
+    fake_cache.redis_cache.async_set_max.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_get_current_spend_end_user_floor_repairs_a_stale_low_counter(monkeypatch):
+    """After a Redis restart the end-user counter can sit below the recorded spend;
+    the row wins and the shared counter is raised so other workers stop admitting on
+    the stale value."""
+    fake_cache: Final = _make_spend_counter_cache(redis_get_value=2.0)
+    monkeypatch.setattr(ps, "spend_counter_cache", fake_cache)
+    monkeypatch.setattr(ps, "prisma_client", _make_prisma_with_end_user_row(spend=12.0))
+
+    result: Final = await ps.get_current_spend(
+        counter_key="spend:end_user:customer-42",
+        fallback_spend=12.0,
+        max_budget=10.0,
+    )
+
+    assert result == 12.0
+    fake_cache.redis_cache.async_set_max.assert_awaited_once_with(key="spend:end_user:customer-42", value=12.0)
+
+
+@pytest.mark.asyncio
+async def test_get_current_spend_end_user_without_a_row_keeps_the_cached_spend(monkeypatch):
+    fake_cache: Final = _make_spend_counter_cache(redis_get_value=0.0)
+    monkeypatch.setattr(ps, "spend_counter_cache", fake_cache)
+    monkeypatch.setattr(ps, "prisma_client", _make_prisma_with_end_user_row(spend=None))
+
+    result: Final = await ps.get_current_spend(
+        counter_key="spend:end_user:customer-42",
+        fallback_spend=20.0,
+        max_budget=10.0,
+    )
+
+    assert result == 20.0
+    fake_cache.redis_cache.async_set_max.assert_not_called()
+
+
 @pytest.mark.asyncio
 async def test_get_current_spend_floors_window_against_spend_logs(monkeypatch):
     """Per-window counters have no DB row but aggregate from spend logs. A

tests/test_litellm/router_strategy/test_complexity_router.py

@@ -2897,9 +2897,7 @@ class TestRouterPreRoutingAliasOverrides:
         import time
 
         monkeypatch.setenv("GITHUB_COPILOT_TOKEN_DIR", str(tmp_path))
-        (tmp_path / "api-key.json").write_text(
-            json.dumps({"token": "tid=test", "expires_at": int(time.time()) + 3600})
-        )
+        (tmp_path / "api-key.json").write_text(json.dumps({"token": "tid=test", "expires_at": int(time.time()) + 3600}))
         router = Router(
             model_list=[
                 {
@@ -2924,7 +2922,9 @@ class TestRouterPreRoutingAliasOverrides:
         copilot_resolutions: List = []
 
         def _guarded(*args, **kwargs):
-            target = str(kwargs.get("model") or (args[0] if args else "")) + str(kwargs.get("custom_llm_provider") or "")
+            target = str(kwargs.get("model") or (args[0] if args else "")) + str(
+                kwargs.get("custom_llm_provider") or ""
+            )
             if "github_copilot" in target:
                 copilot_resolutions.append(target)
                 raise RuntimeError("routing must not resolve an authenticating provider")
@@ -6133,6 +6133,150 @@ class TestEscalationKeywords:
         assert result.model == "o1-b"  # unchanged: no random hop to o1-a / o1-c
 
 
+def _stalled_tool_history(repeats: int = 3) -> List[Dict]:
+    """`repeats` identical bash tool calls in a row, the automatic counterpart to a user
+    typing an escalation keyword: the assistant, not the human, is the one stuck."""
+    return [
+        turn
+        for i in range(repeats)
+        for turn in (
+            {
+                "role": "assistant",
+                "content": [{"type": "tool_use", "id": f"call-{i}", "name": "bash", "input": {"cmd": "pytest"}}],
+            },
+            {
+                "role": "user",
+                "content": [{"type": "tool_result", "tool_use_id": f"call-{i}", "is_error": True, "content": "fail"}],
+            },
+        )
+    ]
+
+
+class TestStallEscalation:
+    """Mid-task auto-escalation when the assistant's own recent tool calls look stuck: the
+    automatic counterpart to escalation_keywords, gated by stall_escalation_enabled and off
+    by default."""
+
+    @pytest.mark.asyncio
+    async def test_repeated_tool_calls_escalate_the_classified_tier(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [*_stalled_tool_history(), {"role": "user", "content": "Hello there!"}]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "gpt-4o"  # SIMPLE bumped to MEDIUM
+
+    @pytest.mark.asyncio
+    async def test_varied_tool_calls_do_not_escalate(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [
+            {
+                "role": "assistant",
+                "content": [{"type": "tool_use", "id": "c1", "name": "bash", "input": {"cmd": "ls"}}],
+            },
+            {
+                "role": "user",
+                "content": [{"type": "tool_result", "tool_use_id": "c1", "is_error": False, "content": "ok"}],
+            },
+            {"role": "user", "content": "Hello there!"},
+        ]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "gpt-4o-mini"  # not escalated
+
+    @pytest.mark.asyncio
+    async def test_disabled_by_default_ignores_repeated_tool_calls(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config=basic_config,
+        )
+        messages = [*_stalled_tool_history(), {"role": "user", "content": "Hello there!"}]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "gpt-4o-mini"  # stall_escalation_enabled defaults False
+
+    @pytest.mark.asyncio
+    async def test_signals_record_stall_escalation(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [*_stalled_tool_history(), {"role": "user", "content": "Hello there!"}]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert "stall_escalation" in result.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    async def test_stall_escalation_caps_at_highest_tier(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [
+            *_stalled_tool_history(),
+            {"role": "user", "content": "Let's think step by step and reason through this carefully."},
+        ]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "o1-preview"  # already REASONING, stays there
+
+    @pytest.mark.asyncio
+    async def test_stall_escalation_stacks_with_keyword_escalation(self, mock_router_instance, basic_config):
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [*_stalled_tool_history(), {"role": "user", "content": "LITELLM ESCALATE Hello there!"}]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "claude-sonnet-4-20250514"  # SIMPLE -> MEDIUM (keyword) -> COMPLEX (stall)
+
+    @pytest.mark.asyncio
+    async def test_a_keyword_forced_tier_still_escalates_when_stalled(self, mock_router_instance, basic_config):
+        """A keyword rule forces its tier and returns before any classification runs, so
+        without its own bump the one path that can pin a weak model to a whole conversation
+        would be the one path a stall could never lift."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={
+                **basic_config,
+                "stall_escalation_enabled": True,
+                "keyword_tier_rules": [{"keywords": ["billing"], "tier": "SIMPLE"}],
+            },
+        )
+        healthy = await router.async_pre_routing_hook(
+            model="test-model", request_kwargs={}, messages=[{"role": "user", "content": "a billing question"}]
+        )
+        assert healthy.model == "gpt-4o-mini"  # forced SIMPLE, nothing stuck
+
+        stalled = await router.async_pre_routing_hook(
+            model="test-model",
+            request_kwargs={},
+            messages=[*_stalled_tool_history(), {"role": "user", "content": "a billing question"}],
+        )
+        assert stalled.model == "gpt-4o"  # forced SIMPLE bumped to MEDIUM
+        assert "stall_escalation" in stalled.routing_decision["signals"]
+
+    @pytest.mark.asyncio
+    async def test_evidence_survives_a_new_human_ask(self, mock_router_instance, basic_config):
+        """A plain follow-up like 'try again' must not erase the stall evidence that came
+        before it: escalation still fires on the turn carrying that follow-up."""
+        router = ComplexityRouter(
+            model_name="test-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={**basic_config, "stall_escalation_enabled": True},
+        )
+        messages = [*_stalled_tool_history(), {"role": "user", "content": "try again"}]
+        result = await router.async_pre_routing_hook(model="test-model", request_kwargs={}, messages=messages)
+        assert result.model == "gpt-4o"  # SIMPLE ("try again" carries no signal) bumped to MEDIUM
+
+
 class TestRoutingDecisionContents:
     """Every routing path must return a PreRoutingHookResponse carrying a routing_decision
     that names the mechanism that actually decided, with the facts of that path only."""
@@ -8027,7 +8171,6 @@ class TestClientHousekeepingCalls:
         assert result is not None
         assert result.model == "claude-sonnet-4-20250514"
 
-
     @pytest.mark.asyncio
     async def test_a_classifier_plugin_still_decides_its_own_routers(self, mock_router_instance):
         """A plugin is where an operator encodes policy the tier ladder cannot express.
@@ -8062,9 +8205,7 @@ class TestClientHousekeepingCalls:
         assert result.model == "o1-preview"
         assert result.routing_decision["cause"] == "classifier_plugin"
 
-    def _adaptive_router(
-        self, tier_distance_penalty: float, plan_mode_min_tier: str | None = None
-    ) -> ComplexityRouter:
+    def _adaptive_router(self, tier_distance_penalty: float, plan_mode_min_tier: str | None = None) -> ComplexityRouter:
         adaptive_instance = MagicMock()
         adaptive_instance.model_list = [
             {
@@ -8101,9 +8242,7 @@ class TestClientHousekeepingCalls:
         return router
 
     @pytest.mark.asyncio
-    async def test_the_bandit_cannot_route_a_housekeeping_call_above_the_cheapest_tier(
-        self, mock_router_instance
-    ):
+    async def test_the_bandit_cannot_route_a_housekeeping_call_above_the_cheapest_tier(self, mock_router_instance):
         """The tier here is what the request IS, not how hard it is, so the bandit has nothing to win.
 
         Without a ceiling the tier distance penalty is the only thing holding the tier, so a
@@ -8136,7 +8275,6 @@ class TestClientHousekeepingCalls:
         assert result is not None
         assert result.model == "premium"
 
-
     @pytest.mark.asyncio
     async def test_a_housekeeping_call_never_becomes_the_session_pin(self, mock_router_instance):
         """Pinning this is the most expensive mistake of the transient causes.
@@ -8178,9 +8316,7 @@ class TestClientHousekeepingCalls:
         assert work_turn.routing_decision["cause"] == "llm_classifier"
 
     @pytest.mark.asyncio
-    async def test_the_decision_records_which_sentinel_matched(
-        self, mock_router_instance, llm_classifier_config
-    ):
+    async def test_the_decision_records_which_sentinel_matched(self, mock_router_instance, llm_classifier_config):
         """The cause's contract says the sentinel rides in matched_keyword, so it has to be there.
 
         Without it an operator reading the logs can see that a call was treated as housekeeping but
@@ -8201,7 +8337,6 @@ class TestClientHousekeepingCalls:
             "Write the title in the predominant language of the session"
         )
 
-
     @pytest.mark.asyncio
     async def test_the_plan_mode_floor_raises_a_housekeeping_call_under_adaptive(self, mock_router_instance):
         """Floor and ceiling must not contradict each other on the same request.
@@ -9428,6 +9563,7 @@ class TestTierDefinitions:
             ({"adaptive": True}, "severity order"),
             ({"session_affinity": True}, "severity order"),
             ({"escalation_keywords": ["GO UP"]}, "severity order"),
+            ({"stall_escalation_enabled": True}, "severity order"),
             (
                 {"classifier_llm_config": {"model": "haiku-classifier", "system_prompt": "grade it"}},
                 "system_prompt",
@@ -10735,9 +10871,7 @@ class TestHeuristicFirst:
 
 # Scores 0.175 with one signal, so it sits 0.025 from simple_medium: the pair of tiers either side of
 # that boundary are different model pools, and a hair's difference in score picks the other one.
-NEAR_BOUNDARY_PROMPT = (
-    "design a distributed cache with consistent hashing, then explain the failure modes step by step"
-)
+NEAR_BOUNDARY_PROMPT = "design a distributed cache with consistent hashing, then explain the failure modes step by step"
 
 # Scores 0.075 with signals, the far side of any margin under 0.075: the scorer is decided here.
 CLEAR_OF_BOUNDARY_PROMPT = "explain step by step how consistent hashing rebalances keys"
@@ -11179,6 +11313,7 @@ class TestContextWindowEscalation:
             litellm_router_instance=_windowed_router(_SMALL, _BIG),
             complexity_router_config=_tier_config(session_affinity=True),
         )
+
         def session_kwargs() -> dict[str, object]:
             return {"metadata": {"session_id": "s-1", "user_api_key_hash": "k-1"}}
 
@@ -11203,6 +11338,7 @@ class TestContextWindowEscalation:
             litellm_router_instance=_windowed_router(_SMALL, _BIG),
             complexity_router_config=_tier_config(session_affinity=True),
         )
+
         def session_kwargs() -> dict[str, object]:
             return {"metadata": {"session_id": "s-2", "user_api_key_hash": "k-2"}}
 
@@ -11280,7 +11416,9 @@ class TestContextWindowEscalation:
         copilot_resolutions: List = []
 
         def _guarded(*args, **kwargs):
-            target = str(kwargs.get("model") or (args[0] if args else "")) + str(kwargs.get("custom_llm_provider") or "")
+            target = str(kwargs.get("model") or (args[0] if args else "")) + str(
+                kwargs.get("custom_llm_provider") or ""
+            )
             if "github_copilot" in target:
                 copilot_resolutions.append(target)
                 raise RuntimeError("the gate must not resolve an authenticating provider")
@@ -12291,3 +12429,277 @@ class TestTierHealthFailover:
             for _ in range(20)
         ]
         assert {r.model for r in results} == {"live-c"}
+
+
+ANTHROPIC_IMG_PART = {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": "aGk="}}
+RESPONSES_IMG_PART = {"type": "input_image", "image_url": "data:image/png;base64,aGk="}
+
+
+class TestClassifierVision:
+    """classifier_llm_config.vision: what the LLM classifier is shown for an image-bearing turn."""
+
+    TIERS = {"SIMPLE": "t-simple", "MEDIUM": "t-medium", "COMPLEX": "t-complex", "REASONING": "t-reasoning"}
+
+    @staticmethod
+    def _router(mock_router_instance, *, vision, classifier_declares_vision=True, classifier_type="llm", **extra):
+        def get_model_list(model_name=None):
+            if model_name != "clf":
+                return [{"model_name": model_name, "litellm_params": {"model": "openai/gpt-4o"}}]
+            declared = classifier_declares_vision
+            return [
+                {
+                    "model_name": "clf",
+                    "litellm_params": {"model": "openai/unmapped-classifier"},
+                    "model_info": {} if declared is None else {"supports_vision": declared},
+                }
+            ]
+
+        mock_router_instance.get_model_list = get_model_list
+        classifier_llm_config = {"model": "clf", "circuit_breaker_enabled": False}
+        return ComplexityRouter(
+            model_name="vision-classifier-router",
+            litellm_router_instance=mock_router_instance,
+            complexity_router_config={
+                "classifier_type": classifier_type,
+                "classifier_llm_config": (
+                    classifier_llm_config if vision is None else {**classifier_llm_config, "vision": vision}
+                ),
+                "tiers": dict(TestClassifierVision.TIERS),
+                **extra,
+            },
+        )
+
+    @staticmethod
+    def _classifier_user_content(mock_router_instance):
+        return mock_router_instance.acompletion.call_args.kwargs["messages"][-1]["content"]
+
+    @staticmethod
+    def _turn(*parts):
+        return [{"role": "user", "content": list(parts)}]
+
+    @pytest.fixture(autouse=True)
+    def _classifier_answers_complex(self, mock_router_instance):
+        mock_router_instance.acompletion = AsyncMock(return_value=_llm_response('{"tier": "COMPLEX"}'))
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "vision, classifier_declares_vision",
+        [
+            (None, True),
+            ({"enabled": False}, True),
+            ({"enabled": True}, False),
+            ({"enabled": True}, None),
+        ],
+        ids=["vision_unset", "vision_disabled", "classifier_declared_text_only", "classifier_undeclared"],
+    )
+    async def test_payload_stays_text_only(self, mock_router_instance, vision, classifier_declares_vision):
+        """Off, or a classifier not declared vision-capable, keeps the plain-string payload.
+
+        The undeclared case is the polarity. A text-only classifier handed an image rejects the
+        call, the rejection is swallowed by the classifier's own fallback, and every image request
+        then serves from the fallback tier while still paying for the failed call. Staying text-only
+        is instead a visible no-op the operator fixes by declaring supports_vision.
+        """
+        router = self._router(
+            mock_router_instance, vision=vision, classifier_declares_vision=classifier_declares_vision
+        )
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, IMG_PART)
+        )
+        content = self._classifier_user_content(mock_router_instance)
+        assert isinstance(content, str)
+        assert "what is this" in content
+
+    @pytest.mark.asyncio
+    async def test_deployment_model_info_enables_a_classifier_the_cost_map_does_not_describe(
+        self, mock_router_instance
+    ):
+        """The escape hatch for an unmapped classifier name, and the reason undeclared can stay off.
+
+        `_router` gives every deployment an `openai/unmapped-*` litellm_params model, so nothing in
+        the cost map declares it and the verdict comes only from model_info.
+        """
+        router = self._router(mock_router_instance, vision={"enabled": True}, classifier_declares_vision=True)
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, IMG_PART)
+        )
+        assert [b["type"] for b in self._classifier_user_content(mock_router_instance)] == ["text", "image_url"]
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "part",
+        [IMG_PART, ANTHROPIC_IMG_PART, RESPONSES_IMG_PART],
+        ids=["chat_completions", "anthropic_messages", "responses"],
+    )
+    async def test_image_reaches_the_classifier_in_chat_completions_dialect(self, mock_router_instance, part):
+        """Every surface's dialect arrives as a chat-completions image_url on the classifier call.
+
+        /v1/messages hands the hook an Anthropic image block untranslated, so forwarding verbatim
+        would send the classifier a content part its own request dialect has no meaning for.
+        """
+        router = self._router(mock_router_instance, vision={"enabled": True})
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, part)
+        )
+        content = self._classifier_user_content(mock_router_instance)
+        assert [block["type"] for block in content] == ["text", "image_url"]
+        assert content[1]["image_url"] == {"url": "data:image/png;base64,aGk="}
+        assert "what is this" in content[0]["text"]
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "part",
+        [
+            {"type": "image_url", "image_url": {"url": "http://169.254.169.254/latest/meta-data/"}},
+            {"type": "image_url", "image_url": {"url": "https://example.internal/secret.png"}},
+            {"type": "input_image", "image_url": "https://example.internal/secret.png"},
+            {"type": "image", "source": {"type": "url", "url": "https://example.internal/secret.png"}},
+        ],
+        ids=["metadata_service", "chat_completions", "responses", "anthropic"],
+    )
+    async def test_remote_url_images_are_never_forwarded(self, mock_router_instance, part):
+        """A caller-supplied URL must not reach an internal call the caller did not ask for.
+
+        Provider adapters do not uniformly delegate fetching: gigachat downloads any non-data URL
+        from the proxy host, so forwarding one would turn a router-scoped key into a proxy-side GET
+        at an address of the caller's choosing.
+        """
+        router = self._router(mock_router_instance, vision={"enabled": True})
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, part)
+        )
+        assert isinstance(self._classifier_user_content(mock_router_instance), str)
+
+    @pytest.mark.asyncio
+    async def test_remote_url_image_only_turn_does_not_reach_the_classifier(self, mock_router_instance):
+        """With nothing forwardable left, the turn stays unclassifiable rather than sending the URL."""
+        router = self._router(mock_router_instance, vision={"enabled": True})
+        response = await router.async_pre_routing_hook(
+            model="m",
+            request_kwargs={},
+            messages=self._turn({"type": "image_url", "image_url": {"url": "https://example.internal/x.png"}}),
+        )
+        assert response.routing_decision["cause"] == "default_fallback"
+        mock_router_instance.acompletion.assert_not_awaited()
+
+    @pytest.mark.asyncio
+    async def test_image_only_turn_is_classified_instead_of_falling_back(self, mock_router_instance):
+        """A turn carrying only an image reaches the classifier rather than the default model.
+
+        It flattens to empty text, so before this it never reached the classifier at all and was
+        routed as default_fallback on text the request never contained.
+        """
+        router = self._router(mock_router_instance, vision={"enabled": True})
+        response = await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn(IMG_PART)
+        )
+        assert response.routing_decision["cause"] == "llm_classifier"
+        assert response.model == "t-complex"
+        assert [block["type"] for block in self._classifier_user_content(mock_router_instance)] == [
+            "text",
+            "image_url",
+        ]
+
+    @pytest.mark.asyncio
+    async def test_image_only_turn_still_falls_back_when_vision_is_off(self, mock_router_instance):
+        router = self._router(mock_router_instance, vision={"enabled": False})
+        response = await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn(IMG_PART)
+        )
+        assert response.routing_decision["cause"] == "default_fallback"
+        mock_router_instance.acompletion.assert_not_awaited()
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize("max_images, expected", [(1, 1), (2, 2), (5, 3)])
+    async def test_max_images_caps_what_is_forwarded(self, mock_router_instance, max_images, expected):
+        router = self._router(mock_router_instance, vision={"enabled": True, "max_images": max_images})
+        images = [dict(IMG_PART, image_url={"url": f"data:image/png;base64,{n}"}) for n in ("a", "b", "c")]
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "look"}, *images)
+        )
+        content = self._classifier_user_content(mock_router_instance)
+        forwarded = [block for block in content if block["type"] == "image_url"]
+        assert len(forwarded) == expected
+        assert [block["image_url"]["url"] for block in forwarded] == [
+            f"data:image/png;base64,{n}" for n in ("a", "b", "c")[:expected]
+        ]
+
+    @pytest.mark.asyncio
+    async def test_earlier_turn_images_are_not_forwarded(self, mock_router_instance):
+        """Only the newest user turn's images ride along, so history cannot inflate every call.
+
+        The two turns carry different images on purpose: identical ones would pass this assertion
+        whichever turn the helper read.
+        """
+        older = dict(IMG_PART, image_url={"url": "data:image/png;base64,OLDER"})
+        newer = dict(IMG_PART, image_url={"url": "data:image/png;base64,NEWER"})
+        router = self._router(mock_router_instance, vision={"enabled": True, "max_images": 5})
+        await router.async_pre_routing_hook(
+            model="m",
+            request_kwargs={},
+            messages=[
+                {"role": "user", "content": [{"type": "text", "text": "first"}, older]},
+                {"role": "assistant", "content": "ok"},
+                {"role": "user", "content": [{"type": "text", "text": "second"}, newer]},
+            ],
+        )
+        content = self._classifier_user_content(mock_router_instance)
+        forwarded = [block for block in content if block["type"] == "image_url"]
+        assert [block["image_url"]["url"] for block in forwarded] == ["data:image/png;base64,NEWER"]
+
+    @pytest.mark.asyncio
+    async def test_logged_request_body_matches_what_was_sent(self, mock_router_instance):
+        """proxy_server_request is the logged copy of the classifier call and must not drift."""
+        router = self._router(mock_router_instance, vision={"enabled": True})
+        await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, IMG_PART)
+        )
+        call_kwargs = mock_router_instance.acompletion.call_args.kwargs
+        assert call_kwargs["proxy_server_request"]["body"]["messages"] == call_kwargs["messages"]
+
+    SHORT_CIRCUIT_ARMS = [
+        ("heuristic_first", {"heuristic_first_max_tier": "SIMPLE"}, "heuristic_first_short_circuit"),
+        ("hybrid", {"hybrid_boundary_margin": 0.05}, "hybrid_short_circuit"),
+    ]
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "classifier_type, extra, short_circuit_cause", SHORT_CIRCUIT_ARMS, ids=["heuristic_first", "hybrid"]
+    )
+    async def test_local_scorer_cannot_short_circuit_a_turn_it_cannot_see(
+        self, mock_router_instance, classifier_type, extra, short_circuit_cause
+    ):
+        """The scorer reads text alone, so its confidence is not a verdict on an image turn.
+
+        Both arms are tuned so the scorer WOULD short-circuit on this exact text, which is what
+        makes the image the only variable; a margin loose enough to leave the score undecided
+        would pass whether or not the guard exists.
+        """
+        router = self._router(
+            mock_router_instance, vision={"enabled": True}, classifier_type=classifier_type, **extra
+        )
+        response = await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=self._turn({"type": "text", "text": "what is this"}, IMG_PART)
+        )
+        assert response.routing_decision["cause"] == "llm_classifier"
+
+    @pytest.mark.asyncio
+    @pytest.mark.parametrize(
+        "classifier_type, extra, short_circuit_cause", SHORT_CIRCUIT_ARMS, ids=["heuristic_first", "hybrid"]
+    )
+    async def test_local_scorer_still_short_circuits_without_images(
+        self, mock_router_instance, classifier_type, extra, short_circuit_cause
+    ):
+        """The negative class: same router, same text, no image, and the scorer still decides."""
+        router = self._router(
+            mock_router_instance, vision={"enabled": True}, classifier_type=classifier_type, **extra
+        )
+        response = await router.async_pre_routing_hook(
+            model="m", request_kwargs={}, messages=[{"role": "user", "content": "what is this"}]
+        )
+        assert response.routing_decision["cause"] == short_circuit_cause
+        mock_router_instance.acompletion.assert_not_awaited()
+
+    def test_max_images_must_be_positive(self):
+        with pytest.raises(ValidationError):
+            ClassifierLLMConfig(model="clf", vision={"enabled": True, "max_images": 0})

tests/test_litellm/router_strategy/test_stall_detector.py

@@ -0,0 +1,154 @@
+"""
+Tests for mid-task stall detection: repeated identical tool calls or repeated tool
+errors, read from both Anthropic Messages and chat-completions tool-call shapes.
+"""
+
+from litellm.router_strategy.complexity_router.stall_detector import detect_stalled_task
+
+
+def _anthropic_call(call_id: str, name: str, arguments: dict, *, is_error: bool) -> list[dict]:
+    return [
+        {"role": "assistant", "content": [{"type": "tool_use", "id": call_id, "name": name, "input": arguments}]},
+        {
+            "role": "user",
+            "content": [{"type": "tool_result", "tool_use_id": call_id, "is_error": is_error, "content": "result"}],
+        },
+    ]
+
+
+def _chat_completions_call(call_id: str, name: str, arguments_json: str) -> list[dict]:
+    return [
+        {
+            "role": "assistant",
+            "tool_calls": [
+                {"id": call_id, "type": "function", "function": {"name": name, "arguments": arguments_json}}
+            ],
+        },
+        {"role": "tool", "tool_call_id": call_id, "content": "result"},
+    ]
+
+
+class TestDetectStalledTask:
+    def test_repeated_identical_anthropic_calls_are_stalled(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_repeated_errors_are_stalled_even_with_varied_arguments(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest tests/a.py"}, is_error=True),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest tests/b.py"}, is_error=True),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest tests/c.py"}, is_error=True),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_varied_successful_calls_are_not_stalled(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "ls"}, is_error=False),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t3", "grep", {"pattern": "x"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is False
+
+    def test_chat_completions_repeats_are_stalled(self):
+        messages = [
+            *_chat_completions_call("c1", "bash", '{"cmd": "pytest"}'),
+            *_chat_completions_call("c2", "bash", '{"cmd": "pytest"}'),
+            *_chat_completions_call("c3", "bash", '{"cmd": "pytest"}'),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_chat_completions_has_no_structured_error_signal(self):
+        """A chat-completions tool message carries no standard error flag, so varied calls
+        whose content happens to read like failures still aren't flagged on error alone."""
+        messages = [
+            *_chat_completions_call("c1", "bash", '{"cmd": "a"}'),
+            *_chat_completions_call("c2", "bash", '{"cmd": "b"}'),
+            *_chat_completions_call("c3", "bash", '{"cmd": "c"}'),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is False
+
+    def test_dict_and_json_string_arguments_compare_equal_across_surfaces(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=False),
+            *_chat_completions_call("c2", "bash", '{"cmd": "pytest"}'),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_below_repeat_threshold_is_not_stalled(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is False
+
+    def test_evidence_older_than_the_window_does_not_count(self):
+        """Only the most recent `window` tool calls are considered, so a stall the model
+        already recovered from does not keep re-triggering forever."""
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t4", "grep", {"pattern": "a"}, is_error=False),
+            *_anthropic_call("t5", "grep", {"pattern": "b"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=2, repeat_threshold=2) is False
+
+    def test_evidence_survives_a_new_human_ask(self):
+        """A follow-up like 'try again' must not erase evidence from before it: detection
+        reads the whole message list, not just the turns since the newest human ask."""
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=False),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=False),
+            {"role": "user", "content": [{"type": "text", "text": "try again"}]},
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_a_recovered_task_is_not_stalled_while_its_old_failures_sit_in_the_window(self):
+        """The three identical failures stay in the window for a few turns after the model
+        breaks out of them, and counting them on their own would escalate a request that is
+        already making progress again."""
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t4", "read_file", {"path": "conftest.py"}, is_error=False),
+            *_anthropic_call("t5", "edit_file", {"path": "conftest.py"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is False
+
+    def test_a_retry_loop_broken_up_by_an_unrelated_call_still_counts(self):
+        """Anchoring on the newest call must not require the repeats to be adjacent: a model
+        re-running the same failing command around a lookup in between is still stuck."""
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t2", "read_file", {"path": "conftest.py"}, is_error=False),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t4", "bash", {"cmd": "pytest"}, is_error=True),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is True
+
+    def test_errors_only_count_while_the_newest_call_is_still_failing(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest a"}, is_error=True),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest b"}, is_error=True),
+            *_anthropic_call("t3", "bash", {"cmd": "pytest c"}, is_error=True),
+            *_anthropic_call("t4", "bash", {"cmd": "pytest d"}, is_error=False),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=3) is False
+
+    def test_no_messages_is_not_stalled(self):
+        assert detect_stalled_task(None, window=6, repeat_threshold=3) is False
+        assert detect_stalled_task([], window=6, repeat_threshold=3) is False
+
+    def test_zero_threshold_never_flags_stalled(self):
+        messages = [
+            *_anthropic_call("t1", "bash", {"cmd": "pytest"}, is_error=True),
+            *_anthropic_call("t2", "bash", {"cmd": "pytest"}, is_error=True),
+        ]
+        assert detect_stalled_task(messages, window=6, repeat_threshold=0) is False

tests/test_litellm/router_utils/test_reasoning_effort_capability.py

@@ -388,3 +388,21 @@ class TestGpt6AstraAdvertisesItsDocumentedLevels:
             "xhigh",
             "max",
         )
+
+    @pytest.mark.parametrize("model", ["azure/gpt-6-astra", "azure/us/gpt-6-astra"])
+    def test_a_foundry_deployment_also_advertises_none(self, local_model_cost_map, model):
+        """Microsoft Foundry serves the same model but its API accepts reasoning_effort none
+        (verified live: 200 with zero reasoning tokens, and it unlocks temperature), which
+        OpenAI's rejects, so an Azure deployment offers none on top of low through max."""
+        from litellm.utils import _get_model_info_helper
+
+        model_info = dict(_get_model_info_helper(model=model, custom_llm_provider="azure"))
+
+        assert resolve_supported_reasoning_efforts(model_info, deployment_is_mapped=True) == (
+            "none",
+            "low",
+            "medium",
+            "high",
+            "xhigh",
+            "max",
+        )

ui/litellm-dashboard/src/app/(dashboard)/access-groups/_components/AccessGroupsDetailsPage.test.tsx

@@ -7,6 +7,7 @@ import { renderWithProviders } from "../../../../../tests/test-utils";
 import { AccessGroupDetail } from "./AccessGroupsDetailsPage";
 
 vi.mock("@/app/(dashboard)/hooks/accessGroups/useAccessGroupDetails");
+vi.mock("next/navigation", () => ({ useRouter: () => ({ push: vi.fn() }) }));
 vi.mock("./AccessGroupsModal/AccessGroupEditModal", () => ({
   AccessGroupEditModal: ({ visible, onCancel }: { visible: boolean; onCancel: () => void }) =>
     visible ? (
@@ -44,6 +45,8 @@ const baseMockReturnValue = {
   refetch: vi.fn(),
 } as unknown as ReturnType<typeof useAccessGroupDetails>;
 
+const unnamed = (ids: readonly string[]) => ids.map((id) => ({ id, name: null }));
+
 const createMockAccessGroup = (overrides: Partial<AccessGroupResponse> = {}): AccessGroupResponse => ({
   access_group_id: "ag-1",
   access_group_name: "Test Group",
@@ -53,6 +56,13 @@ const createMockAccessGroup = (overrides: Partial<AccessGroupResponse> = {}): Ac
   access_agent_ids: ["agent-1"],
   assigned_team_ids: ["team-1"],
   assigned_key_ids: ["key-1", "key-2"],
+  access_mcp_servers: [{ id: "mcp-1", name: "GitHub MCP" }],
+  access_agents: [{ id: "agent-1", name: "Support Agent" }],
+  assigned_teams: [{ id: "team-1", name: "Platform Team" }],
+  assigned_keys: [
+    { id: "key-1", name: "ci-key" },
+    { id: "key-2", name: null },
+  ],
   created_at: "2025-01-01T00:00:00Z",
   created_by: null,
   updated_at: "2025-01-02T00:00:00Z",
@@ -60,6 +70,14 @@ const createMockAccessGroup = (overrides: Partial<AccessGroupResponse> = {}): Ac
   ...overrides,
 });
 
+const renderWith = (overrides: Partial<AccessGroupResponse> = {}) => {
+  mockUseAccessGroupDetails.mockReturnValue({
+    ...baseMockReturnValue,
+    data: createMockAccessGroup(overrides),
+  } as ReturnType<typeof useAccessGroupDetails>);
+  return renderWithProviders(<AccessGroupDetail accessGroupId="ag-1" onBack={vi.fn()} />);
+};
+
 describe("AccessGroupDetail", () => {
   const mockOnBack = vi.fn();
   const accessGroupId = "ag-1";
@@ -106,9 +124,7 @@ describe("AccessGroupDetail", () => {
     const user = userEvent.setup();
     renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
-    const buttons = screen.getAllByRole("button");
-    const backButton = buttons.find((btn) => !btn.textContent?.includes("Edit"));
-    await user.click(backButton!);
+    await user.click(screen.getByRole("button", { name: "Back" }));
 
     expect(mockOnBack).toHaveBeenCalledTimes(1);
   });
@@ -128,12 +144,7 @@ describe("AccessGroupDetail", () => {
   });
 
   it("should display em dash when description is empty", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ description: null }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+    renderWith({ description: null });
 
     expect(screen.getByText("—")).toBeInTheDocument();
   });
@@ -144,8 +155,7 @@ describe("AccessGroupDetail", () => {
 
     expect(screen.queryByRole("dialog", { name: "Edit Access Group" })).not.toBeInTheDocument();
 
-    const editButton = screen.getByRole("button", { name: /Edit Access Group/i });
-    await user.click(editButton);
+    await user.click(screen.getByRole("button", { name: /Edit Access Group/i }));
 
     expect(screen.getByRole("dialog", { name: "Edit Access Group" })).toBeInTheDocument();
   });
@@ -161,88 +171,126 @@ describe("AccessGroupDetail", () => {
     expect(screen.queryByRole("dialog", { name: "Edit Access Group" })).not.toBeInTheDocument();
   });
 
-  it("should display attached keys", () => {
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+  describe("attached keys", () => {
+    it("should show the key alias and hide the token when the key has an alias", () => {
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
-    expect(screen.getByText("Attached Keys")).toBeInTheDocument();
-    expect(screen.getByText("key-1")).toBeInTheDocument();
-    expect(screen.getByText("key-2")).toBeInTheDocument();
+      expect(screen.getByText("Attached Keys")).toBeInTheDocument();
+      expect(screen.getByText("ci-key")).toBeInTheDocument();
+      expect(screen.queryByText("key-1")).not.toBeInTheDocument();
+    });
+
+    it("should fall back to the token when the key has no alias", () => {
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      expect(screen.getByText("key-2")).toBeInTheDocument();
+    });
+
+    it("should link each key to its detail page", () => {
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      expect(screen.getByRole("link", { name: "ci-key" })).toHaveAttribute(
+        "href",
+        expect.stringContaining("key=key-1"),
+      );
+      expect(screen.getByRole("link", { name: "key-2" })).toHaveAttribute("href", expect.stringContaining("key=key-2"));
+    });
+
+    it("should reveal the token in a tooltip when hovering an aliased key", async () => {
+      const user = userEvent.setup();
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      await user.hover(screen.getByText("ci-key"));
+
+      expect(await screen.findByText("key-1")).toBeInTheDocument();
+    });
+
+    it("should show View All button for keys when more than 5", () => {
+      renderWith({ assigned_keys: unnamed(["k1", "k2", "k3", "k4", "k5", "k6"]) });
+
+      expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
+      expect(screen.queryByText("k6")).not.toBeInTheDocument();
+    });
+
+    it("should toggle between View All and Show Less for keys", async () => {
+      const user = userEvent.setup();
+      renderWith({ assigned_keys: unnamed(["k1", "k2", "k3", "k4", "k5", "k6"]) });
+
+      await user.click(screen.getByRole("button", { name: "View All (6)" }));
+      expect(screen.getByRole("button", { name: "Show Less" })).toBeInTheDocument();
+      expect(screen.getByText("k6")).toBeInTheDocument();
+
+      await user.click(screen.getByRole("button", { name: "Show Less" }));
+      expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
+    });
+
+    it("should show empty state when no keys attached", () => {
+      renderWith({ assigned_keys: [] });
+
+      expect(screen.getByText("No keys attached")).toBeInTheDocument();
+    });
+
+    it("should truncate long unaliased tokens with ellipsis", () => {
+      renderWith({ assigned_keys: unnamed(["a".repeat(25)]) });
+
+      expect(screen.getByText(/^a{10}\.\.\.a{6}$/)).toBeInTheDocument();
+    });
+
+    it("should not truncate a long alias", () => {
+      const alias = "b".repeat(25);
+      renderWith({ assigned_keys: [{ id: "a".repeat(25), name: alias }] });
+
+      expect(screen.getByText(alias)).toBeInTheDocument();
+    });
   });
 
-  it("should display attached teams", () => {
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+  describe("attached teams", () => {
+    it("should show the team alias and hide the id when the team has an alias", () => {
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
-    expect(screen.getByText("Attached Teams")).toBeInTheDocument();
-    expect(screen.getByText("team-1")).toBeInTheDocument();
+      expect(screen.getByText("Attached Teams")).toBeInTheDocument();
+      expect(screen.getByText("Platform Team")).toBeInTheDocument();
+      expect(screen.queryByText("team-1")).not.toBeInTheDocument();
+    });
+
+    it("should link each team to its detail page", () => {
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      expect(screen.getByRole("link", { name: "Platform Team" })).toHaveAttribute(
+        "href",
+        expect.stringContaining("team=team-1"),
+      );
+    });
+
+    it("should reveal the team id in a tooltip when hovering an aliased team", async () => {
+      const user = userEvent.setup();
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      await user.hover(screen.getByText("Platform Team"));
+
+      expect(await screen.findByText("team-1")).toBeInTheDocument();
+    });
+
+    it("should fall back to the team id when the team has no alias", () => {
+      renderWith({ assigned_teams: unnamed(["team-ghost"]) });
+
+      expect(screen.getByText("team-ghost")).toBeInTheDocument();
+    });
+
+    it("should show View All button for teams when more than 5", () => {
+      renderWith({ assigned_teams: unnamed(["t1", "t2", "t3", "t4", "t5", "t6"]) });
+
+      expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
+    });
+
+    it("should show empty state when no teams attached", () => {
+      renderWith({ assigned_teams: [] });
+
+      expect(screen.getByText("No teams attached")).toBeInTheDocument();
+    });
   });
 
-  it("should show View All button for keys when more than 5", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({
-        assigned_key_ids: ["k1", "k2", "k3", "k4", "k5", "k6"],
-      }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
-  });
-
-  it("should toggle between View All and Show Less for keys", async () => {
-    const user = userEvent.setup();
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({
-        assigned_key_ids: ["k1", "k2", "k3", "k4", "k5", "k6"],
-      }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    await user.click(screen.getByRole("button", { name: "View All (6)" }));
-    expect(screen.getByRole("button", { name: "Show Less" })).toBeInTheDocument();
-
-    await user.click(screen.getByRole("button", { name: "Show Less" }));
-    expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
-  });
-
-  it("should show View All button for teams when more than 5", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({
-        assigned_team_ids: ["t1", "t2", "t3", "t4", "t5", "t6"],
-      }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    expect(screen.getByRole("button", { name: "View All (6)" })).toBeInTheDocument();
-  });
-
-  it("should show empty state when no keys attached", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ assigned_key_ids: [] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    expect(screen.getByText("No keys attached")).toBeInTheDocument();
-  });
-
-  it("should show empty state when no teams attached", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ assigned_team_ids: [] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    expect(screen.getByText("No teams attached")).toBeInTheDocument();
-  });
-
-  it("should display Models tab with model IDs", () => {
+  it("should display Models tab with model names", () => {
     renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
     expect(screen.getByRole("tab", { name: /Models/i })).toBeInTheDocument();
@@ -250,73 +298,90 @@ describe("AccessGroupDetail", () => {
     expect(screen.getByText("model-2")).toBeInTheDocument();
   });
 
-  it("should display MCP Servers tab with server IDs", async () => {
-    const user = userEvent.setup();
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+  describe("MCP Servers tab", () => {
+    it("should show server names instead of ids", async () => {
+      const user = userEvent.setup();
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
-    const mcpTab = screen.getByRole("tab", { name: /MCP Servers/i });
-    expect(mcpTab).toBeInTheDocument();
-    await user.click(mcpTab);
-    expect(screen.getByText("mcp-1")).toBeInTheDocument();
+      await user.click(screen.getByRole("tab", { name: /MCP Servers/i }));
+
+      expect(screen.getByText("GitHub MCP")).toBeInTheDocument();
+      expect(screen.queryByText("mcp-1")).not.toBeInTheDocument();
+    });
+
+    it("should reveal the server id in a tooltip when hovering the name", async () => {
+      const user = userEvent.setup();
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+
+      await user.click(screen.getByRole("tab", { name: /MCP Servers/i }));
+      await user.hover(screen.getByText("GitHub MCP"));
+
+      expect(await screen.findByText("mcp-1")).toBeInTheDocument();
+    });
+
+    it("should fall back to the id when the server has no name", async () => {
+      const user = userEvent.setup();
+      renderWith({ access_mcp_servers: unnamed(["mcp-deleted"]) });
+
+      await user.click(screen.getByRole("tab", { name: /MCP Servers/i }));
+
+      expect(screen.getByText("mcp-deleted")).toBeInTheDocument();
+    });
+
+    it("should show empty state when none assigned", async () => {
+      const user = userEvent.setup();
+      renderWith({ access_mcp_servers: [] });
+
+      await user.click(screen.getByRole("tab", { name: /MCP Servers/i }));
+
+      expect(screen.getByText("No MCP servers assigned to this group")).toBeInTheDocument();
+    });
   });
 
-  it("should display Agents tab with agent IDs", async () => {
-    const user = userEvent.setup();
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+  describe("Agents tab", () => {
+    it("should show agent names instead of ids", async () => {
+      const user = userEvent.setup();
+      renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
 
-    const agentsTab = screen.getByRole("tab", { name: /Agents/i });
-    expect(agentsTab).toBeInTheDocument();
-    await user.click(agentsTab);
-    expect(screen.getByText("agent-1")).toBeInTheDocument();
+      await user.click(screen.getByRole("tab", { name: /Agents/i }));
+
+      expect(screen.getByText("Support Agent")).toBeInTheDocument();
+      expect(screen.queryByText("agent-1")).not.toBeInTheDocument();
+    });
+
+    it("should fall back to the id when the agent has no name", async () => {
+      const user = userEvent.setup();
+      renderWith({ access_agents: unnamed(["agent-deleted"]) });
+
+      await user.click(screen.getByRole("tab", { name: /Agents/i }));
+
+      expect(screen.getByText("agent-deleted")).toBeInTheDocument();
+    });
+
+    it("should show empty state when none assigned", async () => {
+      const user = userEvent.setup();
+      renderWith({ access_agents: [] });
+
+      await user.click(screen.getByRole("tab", { name: /Agents/i }));
+
+      expect(screen.getByText("No agents assigned to this group")).toBeInTheDocument();
+    });
   });
 
   it("should show empty state in Models tab when no models assigned", () => {
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ access_model_names: [] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
+    renderWith({ access_model_names: [] });
 
     expect(screen.getByText("No models assigned to this group")).toBeInTheDocument();
   });
 
-  it("should show empty state in MCP Servers tab when none assigned", async () => {
-    const user = userEvent.setup();
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ access_mcp_server_ids: [] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
+  it("should count resources from the resolved lists in the tab badges", () => {
+    renderWith({
+      access_mcp_servers: unnamed(["m1", "m2", "m3"]),
+      access_agents: unnamed(["a1", "a2"]),
+    });
 
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    await user.click(screen.getByRole("tab", { name: /MCP Servers/i }));
-    expect(screen.getByText("No MCP servers assigned to this group")).toBeInTheDocument();
-  });
-
-  it("should show empty state in Agents tab when none assigned", async () => {
-    const user = userEvent.setup();
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ access_agent_ids: [] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    await user.click(screen.getByRole("tab", { name: /Agents/i }));
-    expect(screen.getByText("No agents assigned to this group")).toBeInTheDocument();
-  });
-
-  it("should truncate long key IDs with ellipsis", () => {
-    const longKeyId = "a".repeat(25);
-    mockUseAccessGroupDetails.mockReturnValue({
-      ...baseMockReturnValue,
-      data: createMockAccessGroup({ assigned_key_ids: [longKeyId] }),
-    } as ReturnType<typeof useAccessGroupDetails>);
-
-    renderWithProviders(<AccessGroupDetail accessGroupId={accessGroupId} onBack={mockOnBack} />);
-
-    expect(screen.getByText(/a{10}\.\.\.a{6}/)).toBeInTheDocument();
+    expect(screen.getByRole("tab", { name: /MCP Servers/i })).toHaveTextContent("3");
+    expect(screen.getByRole("tab", { name: /Agents/i })).toHaveTextContent("2");
   });
 
   it("should display created and last updated timestamps", () => {

ui/litellm-dashboard/src/app/(dashboard)/access-groups/_components/AccessGroupsDetailsPage.tsx

@@ -2,14 +2,20 @@ import { useAccessGroupDetails } from "@/app/(dashboard)/hooks/accessGroups/useA
 import { ArrowLeftIcon, BotIcon, EditIcon, KeyIcon, LayersIcon, ServerIcon, UsersIcon } from "lucide-react";
 import { useState } from "react";
 import DefaultProxyAdminTag from "@/components/common_components/DefaultProxyAdminTag";
+import { BadgeLink } from "@/components/shared/BadgeLink";
 import CopyButton from "@/components/shared/CopyButton";
 import { Badge } from "@/components/ui/badge";
 import { Button } from "@/components/ui/button";
 import { Card, CardAction, CardContent, CardHeader, CardTitle } from "@/components/ui/card";
 import { Tabs, TabsContent, TabsList, TabsTrigger } from "@/components/ui/tabs";
+import { SimpleTooltip } from "@/components/ui/tooltip";
 import { UiLoadingSpinner } from "@/components/ui/ui-loading-spinner";
+import type { components } from "@/lib/http/schema";
+import { keyDetailHref, teamDetailHref } from "@/utils/entityLinks";
 import { AccessGroupEditModal } from "./AccessGroupsModal/AccessGroupEditModal";
 
+type AccessGroupResource = components["schemas"]["AccessGroupResource"];
+
 interface AccessGroupDetailProps {
   accessGroupId: string;
   onBack: () => void;
@@ -17,16 +23,24 @@ interface AccessGroupDetailProps {
 
 const MAX_PREVIEW = 5;
 
-function ResourceList({ ids, emptyMessage }: { ids: string[]; emptyMessage: string }) {
-  if (ids.length === 0) {
+const shortId = (id: string) => (id.length > 20 ? `${id.slice(0, 10)}...${id.slice(-6)}` : id);
+
+function ResourceList({ items, emptyMessage }: { items: readonly AccessGroupResource[]; emptyMessage: string }) {
+  if (items.length === 0) {
     return <p className="py-8 text-center text-sm text-muted-foreground">{emptyMessage}</p>;
   }
   return (
     <div className="grid grid-cols-1 gap-4 sm:grid-cols-2 md:grid-cols-3 lg:grid-cols-4">
-      {ids.map((id) => (
+      {items.map(({ id, name }) => (
         <Card key={id} size="sm">
           <CardContent>
-            <code className="font-mono text-xs break-all text-foreground">{id}</code>
+            {name ? (
+              <SimpleTooltip content={id}>
+                <span className="text-sm font-medium break-all text-foreground">{name}</span>
+              </SimpleTooltip>
+            ) : (
+              <code className="font-mono text-xs break-all text-foreground">{id}</code>
+            )}
           </CardContent>
         </Card>
       ))}
@@ -34,6 +48,23 @@ function ResourceList({ ids, emptyMessage }: { ids: string[]; emptyMessage: stri
   );
 }
 
+function ResourceBadge({
+  resource: { id, name },
+  href,
+  fallback,
+}: {
+  resource: AccessGroupResource;
+  href: string;
+  fallback: (id: string) => string;
+}) {
+  const badge = (
+    <BadgeLink href={href} className={name ? undefined : "font-mono"}>
+      {name ?? fallback(id)}
+    </BadgeLink>
+  );
+  return name ? <SimpleTooltip content={id}>{badge}</SimpleTooltip> : badge;
+}
+
 export function AccessGroupDetail({ accessGroupId, onBack }: AccessGroupDetailProps) {
   const { data: accessGroup, isLoading } = useAccessGroupDetails(accessGroupId);
   const [isEditModalVisible, setIsEditModalVisible] = useState(false);
@@ -61,14 +92,14 @@ export function AccessGroupDetail({ accessGroupId, onBack }: AccessGroupDetailPr
     );
   }
 
-  const modelIds = accessGroup.access_model_names ?? [];
-  const mcpServerIds = accessGroup.access_mcp_server_ids ?? [];
-  const agentIds = accessGroup.access_agent_ids ?? [];
-  const keyIds = accessGroup.assigned_key_ids ?? [];
-  const teamIds = accessGroup.assigned_team_ids ?? [];
+  const models = accessGroup.access_model_names.map((id) => ({ id, name: null }));
+  const mcpServers = accessGroup.access_mcp_servers;
+  const agents = accessGroup.access_agents;
+  const keys = accessGroup.assigned_keys;
+  const teams = accessGroup.assigned_teams;
 
-  const displayedKeys = showAllKeys ? keyIds : keyIds.slice(0, MAX_PREVIEW);
-  const displayedTeams = showAllTeams ? teamIds : teamIds.slice(0, MAX_PREVIEW);
+  const displayedKeys = showAllKeys ? keys : keys.slice(0, MAX_PREVIEW);
+  const displayedTeams = showAllTeams ? teams : teams.slice(0, MAX_PREVIEW);
 
   return (
     <div className="p-6 px-12">
@@ -129,23 +160,21 @@ export function AccessGroupDetail({ accessGroupId, onBack }: AccessGroupDetailPr
             <CardTitle className="flex items-center gap-2">
               <KeyIcon className="size-4" />
               Attached Keys
-              <Badge variant="secondary">{keyIds.length}</Badge>
+              <Badge variant="secondary">{keys.length}</Badge>
             </CardTitle>
-            {keyIds.length > MAX_PREVIEW && (
+            {keys.length > MAX_PREVIEW && (
               <CardAction>
                 <Button variant="link" size="sm" onClick={() => setShowAllKeys(!showAllKeys)}>
-                  {showAllKeys ? "Show Less" : `View All (${keyIds.length})`}
+                  {showAllKeys ? "Show Less" : `View All (${keys.length})`}
                 </Button>
               </CardAction>
             )}
           </CardHeader>
           <CardContent>
-            {keyIds.length > 0 ? (
+            {keys.length > 0 ? (
               <div className="flex flex-wrap gap-2">
-                {displayedKeys.map((id) => (
-                  <Badge key={id} variant="secondary" className="font-mono">
-                    {id.length > 20 ? `${id.slice(0, 10)}...${id.slice(-6)}` : id}
-                  </Badge>
+                {displayedKeys.map((key) => (
+                  <ResourceBadge key={key.id} resource={key} href={keyDetailHref(key.id)} fallback={shortId} />
                 ))}
               </div>
             ) : (
@@ -159,23 +188,21 @@ export function AccessGroupDetail({ accessGroupId, onBack }: AccessGroupDetailPr
             <CardTitle className="flex items-center gap-2">
               <UsersIcon className="size-4" />
               Attached Teams
-              <Badge variant="secondary">{teamIds.length}</Badge>
+              <Badge variant="secondary">{teams.length}</Badge>
             </CardTitle>
-            {teamIds.length > MAX_PREVIEW && (
+            {teams.length > MAX_PREVIEW && (
               <CardAction>
                 <Button variant="link" size="sm" onClick={() => setShowAllTeams(!showAllTeams)}>
-                  {showAllTeams ? "Show Less" : `View All (${teamIds.length})`}
+                  {showAllTeams ? "Show Less" : `View All (${teams.length})`}
                 </Button>
               </CardAction>
             )}
           </CardHeader>
           <CardContent>
-            {teamIds.length > 0 ? (
+            {teams.length > 0 ? (
               <div className="flex flex-wrap gap-2">
-                {displayedTeams.map((id) => (
-                  <Badge key={id} variant="secondary" className="font-mono">
-                    {id}
-                  </Badge>
+                {displayedTeams.map((team) => (
+                  <ResourceBadge key={team.id} resource={team} href={teamDetailHref(team.id)} fallback={(id) => id} />
                 ))}
               </div>
             ) : (
@@ -192,27 +219,27 @@ export function AccessGroupDetail({ accessGroupId, onBack }: AccessGroupDetailPr
               <TabsTrigger value="models" className="flex-none gap-2 rounded-none px-4 py-2">
                 <LayersIcon className="size-4" />
                 Models
-                <Badge variant="secondary">{modelIds.length}</Badge>
+                <Badge variant="secondary">{models.length}</Badge>
               </TabsTrigger>
               <TabsTrigger value="mcp" className="flex-none gap-2 rounded-none px-4 py-2">
                 <ServerIcon className="size-4" />
                 MCP Servers
-                <Badge variant="secondary">{mcpServerIds.length}</Badge>
+                <Badge variant="secondary">{mcpServers.length}</Badge>
               </TabsTrigger>
               <TabsTrigger value="agents" className="flex-none gap-2 rounded-none px-4 py-2">
                 <BotIcon className="size-4" />
                 Agents
-                <Badge variant="secondary">{agentIds.length}</Badge>
+                <Badge variant="secondary">{agents.length}</Badge>
               </TabsTrigger>
             </TabsList>
             <TabsContent value="models" className="pt-4">
-              <ResourceList ids={modelIds} emptyMessage="No models assigned to this group" />
+              <ResourceList items={models} emptyMessage="No models assigned to this group" />
             </TabsContent>
             <TabsContent value="mcp" className="pt-4">
-              <ResourceList ids={mcpServerIds} emptyMessage="No MCP servers assigned to this group" />
+              <ResourceList items={mcpServers} emptyMessage="No MCP servers assigned to this group" />
             </TabsContent>
             <TabsContent value="agents" className="pt-4">
-              <ResourceList ids={agentIds} emptyMessage="No agents assigned to this group" />
+              <ResourceList items={agents} emptyMessage="No agents assigned to this group" />
             </TabsContent>
           </Tabs>
         </CardContent>

ui/litellm-dashboard/src/app/(dashboard)/access-groups/_components/AccessGroupsModal/AccessGroupEditModal.integration.test.tsx

@@ -42,6 +42,10 @@ const accessGroup: AccessGroupResponse = {
   access_agent_ids: ["agent-1"],
   assigned_team_ids: [],
   assigned_key_ids: [],
+  access_mcp_servers: [{ id: "srv-1", name: "Server One" }],
+  access_agents: [{ id: "agent-1", name: "Agent One" }],
+  assigned_teams: [],
+  assigned_keys: [],
   created_at: "2024-01-01T00:00:00Z",
   created_by: "user-1",
   updated_at: "2024-01-02T00:00:00Z",

ui/litellm-dashboard/src/app/(dashboard)/access-groups/_components/AccessGroupsPage.test.tsx

@@ -15,6 +15,10 @@ const mockAccessGroups: AccessGroupResponse[] = [
     access_agent_ids: ["a1"],
     assigned_team_ids: [],
     assigned_key_ids: [],
+    access_mcp_servers: [{ id: "s1", name: "Server One" }],
+    access_agents: [{ id: "a1", name: "Agent One" }],
+    assigned_teams: [],
+    assigned_keys: [],
     created_at: "2024-01-15T10:00:00Z",
     created_by: "user-1",
     updated_at: "2024-01-20T12:00:00Z",
@@ -29,6 +33,10 @@ const mockAccessGroups: AccessGroupResponse[] = [
     access_agent_ids: [],
     assigned_team_ids: [],
     assigned_key_ids: [],
+    access_mcp_servers: [],
+    access_agents: [],
+    assigned_teams: [],
+    assigned_keys: [],
     created_at: "2024-01-10T09:00:00Z",
     created_by: null,
     updated_at: "2024-01-12T11:00:00Z",

ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.test.ts

@@ -46,6 +46,10 @@ const mockAccessGroups: AccessGroupResponse[] = [
     access_agent_ids: [],
     assigned_team_ids: [],
     assigned_key_ids: [],
+    access_mcp_servers: [],
+    access_agents: [],
+    assigned_teams: [],
+    assigned_keys: [],
     created_at: "2025-01-01T00:00:00Z",
     created_by: "user-1",
     updated_at: "2025-01-01T00:00:00Z",

ui/litellm-dashboard/src/app/(dashboard)/hooks/accessGroups/useAccessGroups.ts

@@ -3,23 +3,11 @@ import { createQueryKeys } from "../common/queryKeysFactory";
 import { getProxyBaseUrl, getGlobalLitellmHeaderName, deriveErrorMessage, handleError } from "@/components/networking";
 import { all_admin_roles } from "@/utils/roles";
 import useAuthorized from "@/app/(dashboard)/hooks/useAuthorized";
+import type { components } from "@/lib/http/schema";
 
 // ── Types ────────────────────────────────────────────────────────────────────
 
-export interface AccessGroupResponse {
-  access_group_id: string;
-  access_group_name: string;
-  description: string | null;
-  access_model_names: string[];
-  access_mcp_server_ids: string[];
-  access_agent_ids: string[];
-  assigned_team_ids: string[];
-  assigned_key_ids: string[];
-  created_at: string;
-  created_by: string | null;
-  updated_at: string;
-  updated_by: string | null;
-}
+export type AccessGroupResponse = components["schemas"]["AccessGroupResponse"];
 
 // ── Query keys (shared across access-group hooks) ────────────────────────────
 

ui/litellm-dashboard/src/components/add_model/ComplexityRouterConfig.tsx

@@ -33,6 +33,8 @@ import { ModelGroup } from "@/components/llm_calls/fetch_models";
 import AdaptiveRoutingConfig from "./AdaptiveRoutingConfig";
 import ClassificationMethodConfig from "./ClassificationMethodConfig";
 import ContextWindowEscalationConfig from "./ContextWindowEscalationConfig";
+import ResponseFormatControls from "./ResponseFormatControls";
+import StallEscalationConfig from "./StallEscalationConfig";
 import { Restricted, restrictedBy } from "./TierRestrictions";
 import { type TierSetAction, applyTierSetAction, setFallbackTier } from "./tier_set_actions";
 import {
@@ -422,6 +424,14 @@ export interface ComplexityRouterConfigValue {
   deployment_affinity?: boolean;
   /** Plan-mode floor as a tier ROW ID, unset meaning off. The wire carries the row's name. */
   plan_mode_min_tier?: string;
+  /**
+   * Mid-task stall escalation. Undefined means off, which keeps all three keys out of the payload:
+   * the backend rejects them alongside session pinning, user-turn classification and a custom tier
+   * set, so an off router must stay silent about them rather than send an explicit false.
+   */
+  stall_escalation_enabled?: boolean;
+  stall_escalation_window?: number;
+  stall_escalation_repeat_threshold?: number;
   adaptive?: boolean;
   adaptive_weights?: AdaptiveRouterWeights;
   tier_distance_penalty?: number;
@@ -575,25 +585,6 @@ const PlanModeOverrideControls: React.FC<{
   </>
 );
 
-const ResponseFormatControls: React.FC<{
-  value: ComplexityRouterConfigValue;
-  onChange: (value: ComplexityRouterConfigValue) => void;
-}> = ({ value, onChange }) => (
-  <>
-    <div className="flex items-center gap-2 mb-2">
-      <Switch
-        checked={value.return_raw_model_name ?? false}
-        onCheckedChange={(returnRawModelName) => onChange({ ...value, return_raw_model_name: returnRawModelName })}
-        aria-label="Return raw model name"
-      />
-      <strong className="font-semibold">Return raw model name</strong>
-    </div>
-    <span className="block text-xs text-muted-foreground">
-      Return the resolved underlying model name in responses instead of the autorouter alias.
-    </span>
-  </>
-);
-
 const ComplexityRouterConfig: React.FC<ComplexityRouterConfigProps> = ({
   modelInfo,
   value,
@@ -859,6 +850,15 @@ const ComplexityRouterConfig: React.FC<ComplexityRouterConfigProps> = ({
             label: <strong className="text-foreground font-semibold">Advanced: Context Window Escalation</strong>,
             children: <ContextWindowEscalationConfig value={value} onChange={onChange} />,
           },
+          {
+            key: "stall-escalation",
+            label: <strong className="text-foreground font-semibold">Advanced: Stalled Task Escalation</strong>,
+            children: (
+              <Restricted by={restrictedBy(value, "stallEscalation")}>
+                <StallEscalationConfig value={value} onChange={onChange} />
+              </Restricted>
+            ),
+          },
           {
             key: "response",
             label: <strong className="text-foreground font-semibold">Advanced: Response Format</strong>,

ui/litellm-dashboard/src/components/add_model/ResponseFormatControls.tsx

@@ -0,0 +1,24 @@
+import { Switch } from "@/components/ui/switch";
+import React from "react";
+import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig";
+
+const ResponseFormatControls: React.FC<{
+  value: ComplexityRouterConfigValue;
+  onChange: (value: ComplexityRouterConfigValue) => void;
+}> = ({ value, onChange }) => (
+  <>
+    <div className="flex items-center gap-2 mb-2">
+      <Switch
+        checked={value.return_raw_model_name ?? false}
+        onCheckedChange={(returnRawModelName) => onChange({ ...value, return_raw_model_name: returnRawModelName })}
+        aria-label="Return raw model name"
+      />
+      <strong className="font-semibold">Return raw model name</strong>
+    </div>
+    <span className="block text-xs text-muted-foreground">
+      Return the resolved underlying model name in responses instead of the autorouter alias.
+    </span>
+  </>
+);
+
+export default ResponseFormatControls;

ui/litellm-dashboard/src/components/add_model/StallEscalationConfig.test.tsx

@@ -0,0 +1,115 @@
+import { fireEvent, renderWithProviders, screen } from "../../../tests/test-utils";
+import { vi } from "vitest";
+import type { ComplexityRouterConfigValue } from "./ComplexityRouterConfig";
+import StallEscalationConfig, { stallEscalationBlockedReason } from "./StallEscalationConfig";
+
+const tiers = { SIMPLE: "gpt-4o-mini", MEDIUM: "gpt-4o", COMPLEX: "claude-sonnet-4", REASONING: "o1-preview" };
+
+const baseValue: ComplexityRouterConfigValue = {
+  tiers,
+  classifier_type: "heuristic",
+};
+
+const renderConfig = (value: Partial<ComplexityRouterConfigValue> = {}) => {
+  const onChange = vi.fn();
+  renderWithProviders(<StallEscalationConfig value={{ ...baseValue, ...value }} onChange={onChange} />);
+  return onChange;
+};
+
+const toggle = () => screen.getByRole("switch", { name: "Escalate a stalled task to a stronger model" });
+
+describe("stallEscalationBlockedReason", () => {
+  it("blocks on session pinning, which replays a model instead of classifying", () => {
+    expect(stallEscalationBlockedReason({ ...baseValue, session_affinity: true })).toContain("Classification Method");
+  });
+
+  it("blocks on user-turn classification, which skips the agent-loop turns a stall shows up in", () => {
+    expect(stallEscalationBlockedReason({ ...baseValue, classification_mode: "user_turn" })).toContain("every request");
+  });
+
+  it("allows the default every-request router", () => {
+    expect(stallEscalationBlockedReason(baseValue)).toBeNull();
+  });
+});
+
+describe("StallEscalationConfig", () => {
+  it("hides the knobs until the feature is turned on", () => {
+    renderConfig();
+    expect(toggle()).not.toBeChecked();
+    expect(screen.queryByLabelText("Repeats before escalating")).not.toBeInTheDocument();
+  });
+
+  it("turning it on seeds both knobs so the saved config is explicit rather than half-set", () => {
+    const onChange = renderConfig();
+    fireEvent.click(toggle());
+    expect(onChange).toHaveBeenCalledWith(
+      expect.objectContaining({
+        stall_escalation_enabled: true,
+        stall_escalation_window: 6,
+        stall_escalation_repeat_threshold: 3,
+      }),
+    );
+  });
+
+  it("turning it off clears all three keys, since the backend rejects them next to session pinning", () => {
+    const onChange = renderConfig({
+      stall_escalation_enabled: true,
+      stall_escalation_window: 6,
+      stall_escalation_repeat_threshold: 3,
+    });
+    fireEvent.click(toggle());
+    expect(onChange).toHaveBeenCalledWith(
+      expect.objectContaining({
+        stall_escalation_enabled: undefined,
+        stall_escalation_window: undefined,
+        stall_escalation_repeat_threshold: undefined,
+      }),
+    );
+  });
+
+  it("raises the window to match a larger threshold, which could otherwise never be reached", () => {
+    const onChange = renderConfig({
+      stall_escalation_enabled: true,
+      stall_escalation_window: 4,
+      stall_escalation_repeat_threshold: 3,
+    });
+    fireEvent.change(screen.getByLabelText("Repeats before escalating"), { target: { value: "9" } });
+    expect(onChange).toHaveBeenCalledWith(
+      expect.objectContaining({ stall_escalation_repeat_threshold: 9, stall_escalation_window: 9 }),
+    );
+  });
+
+  it("holds the window at the threshold when someone types a smaller one", () => {
+    const onChange = renderConfig({
+      stall_escalation_enabled: true,
+      stall_escalation_window: 6,
+      stall_escalation_repeat_threshold: 3,
+    });
+    fireEvent.change(screen.getByLabelText("Recent calls examined"), { target: { value: "1" } });
+    expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ stall_escalation_window: 3 }));
+  });
+
+  it("floors the threshold at 2, below which a single ordinary retry would escalate", () => {
+    const onChange = renderConfig({ stall_escalation_enabled: true });
+    fireEvent.change(screen.getByLabelText("Repeats before escalating"), { target: { value: "1" } });
+    expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ stall_escalation_repeat_threshold: 2 }));
+  });
+
+  it("disables the toggle and says why when session pinning is on", () => {
+    renderConfig({ session_affinity: true });
+    expect(toggle()).toHaveAttribute("aria-disabled", "true");
+    expect(screen.getByText(/How often to classify/)).toBeInTheDocument();
+  });
+
+  it("hides the knobs when a blocker is switched on under an already-enabled router", () => {
+    renderConfig({ stall_escalation_enabled: true, session_affinity: true });
+    expect(screen.queryByLabelText("Repeats before escalating")).not.toBeInTheDocument();
+  });
+
+  it("still lets an already-on router turn it off once a blocker appears, which the save needs", () => {
+    const onChange = renderConfig({ stall_escalation_enabled: true, session_affinity: true });
+    expect(toggle()).not.toHaveAttribute("aria-disabled", "true");
+    fireEvent.click(toggle());
+    expect(onChange).toHaveBeenCalledWith(expect.objectContaining({ stall_escalation_enabled: undefined }));
+  });
+});

ui/litellm-dashboard/src/components/add_model/StallEscalationConfig.tsx

@@ -0,0 +1,119 @@
+import { Input } from "@/components/ui/input";
+import { Switch } from "@/components/ui/switch";
+import React from "react";
+import { type ComplexityRouterConfigValue, classificationFrequency } from "./ComplexityRouterConfig";
+
+export const DEFAULT_STALL_ESCALATION_WINDOW = 6;
+export const DEFAULT_STALL_ESCALATION_REPEAT_THRESHOLD = 3;
+
+/**
+ * Why the toggle is unavailable, or null when it can be turned on. Both blockers replay a held
+ * routing decision instead of classifying most turns, so detection would never see the tool
+ * calls it reads.
+ */
+export const stallEscalationBlockedReason = (value: ComplexityRouterConfigValue): string | null => {
+  const frequency = classificationFrequency(value);
+  if (frequency === "session")
+    return 'Set "How often to classify" to every request under Advanced: Classification Method to use this. Scoring once per session replays that model instead of classifying, so a stall never reaches the classifier.';
+  if (frequency === "user_turn")
+    return 'Set "How often to classify" to every request under Advanced: Classification Method to use this. Scoring only new user messages skips the tool-call turns a stall shows up in.';
+  return null;
+};
+
+const clampedInt = (raw: string, min: number, fallback: number): number => {
+  const parsed = Number(raw);
+  if (!Number.isFinite(parsed)) return fallback;
+  return Math.max(min, Math.trunc(parsed));
+};
+
+const StallEscalationConfig: React.FC<{
+  value: ComplexityRouterConfigValue;
+  onChange: (value: ComplexityRouterConfigValue) => void;
+}> = ({ value, onChange }) => {
+  const enabled = value.stall_escalation_enabled ?? false;
+  const blockedReason = stallEscalationBlockedReason(value);
+  const window = value.stall_escalation_window ?? DEFAULT_STALL_ESCALATION_WINDOW;
+  const threshold = value.stall_escalation_repeat_threshold ?? DEFAULT_STALL_ESCALATION_REPEAT_THRESHOLD;
+  // A threshold above the window can never be reached, and the backend rejects the pair, so the
+  // window rises with the threshold rather than letting the form save something inert.
+  const commitThreshold = (raw: string) => {
+    const nextThreshold = clampedInt(raw, 2, DEFAULT_STALL_ESCALATION_REPEAT_THRESHOLD);
+    onChange({
+      ...value,
+      stall_escalation_repeat_threshold: nextThreshold,
+      stall_escalation_window: Math.max(window, nextThreshold),
+    });
+  };
+  const commitWindow = (raw: string) => {
+    const nextWindow = clampedInt(raw, 1, DEFAULT_STALL_ESCALATION_WINDOW);
+    onChange({
+      ...value,
+      stall_escalation_window: Math.max(nextWindow, threshold),
+    });
+  };
+  const toggle = (next: boolean) => {
+    const enabledValue: ComplexityRouterConfigValue = {
+      ...value,
+      stall_escalation_enabled: next || undefined,
+      stall_escalation_window: next ? window : undefined,
+      stall_escalation_repeat_threshold: next ? threshold : undefined,
+    };
+    onChange(enabledValue);
+  };
+  return (
+    <>
+      <div className="flex items-center gap-2 mb-2">
+        <Switch
+          checked={enabled}
+          // Blocked only prevents turning it on: an already-on router that just became
+          // blocked (e.g. session pinning turned on afterward) still needs a way to turn
+          // this back off, since the backend rejects saving both together.
+          disabled={blockedReason !== null && !enabled}
+          onCheckedChange={toggle}
+          aria-label="Escalate a stalled task to a stronger model"
+        />
+        <strong className="font-semibold">Escalate a stalled task to a stronger model</strong>
+      </div>
+      <span className="block text-xs mb-3 text-muted-foreground">
+        When the model keeps repeating the same tool call, or the same call keeps erroring, bump the request one tier
+        higher for as long as it looks stuck. The automatic counterpart to an escalation keyword: nobody has to notice
+        the loop and ask. Off means a stuck task keeps the model it was classified onto.
+        {blockedReason !== null && ` ${blockedReason}`}
+      </span>
+      {enabled && blockedReason === null && (
+        <div className="flex flex-wrap gap-4">
+          <div style={{ maxWidth: 240 }}>
+            <label className="block text-sm font-medium mb-1" htmlFor="stall-escalation-repeat-threshold">
+              Repeats before escalating
+            </label>
+            <Input
+              id="stall-escalation-repeat-threshold"
+              inputMode="numeric"
+              value={threshold}
+              onChange={(event) => commitThreshold(event.target.value)}
+            />
+            <span className="block text-xs mt-1 text-muted-foreground">
+              How many identical or failing calls count as stuck. At least 2; lower reacts sooner and misfires more.
+            </span>
+          </div>
+          <div style={{ maxWidth: 240 }}>
+            <label className="block text-sm font-medium mb-1" htmlFor="stall-escalation-window">
+              Recent calls examined
+            </label>
+            <Input
+              id="stall-escalation-window"
+              inputMode="numeric"
+              value={window}
+              onChange={(event) => commitWindow(event.target.value)}
+            />
+            <span className="block text-xs mt-1 text-muted-foreground">
+              How far back to look, in tool calls. Never below the repeat count, since that could never be reached.
+            </span>
+          </div>
+        </div>
+      )}
+    </>
+  );
+};
+
+export default StallEscalationConfig;

ui/litellm-dashboard/src/components/add_model/add_auto_router_tab.tsx

@@ -395,6 +395,9 @@ const AddAutoRouterTab: React.FC<AddAutoRouterTabProps> = ({
     embeddingModel,
     matchThreshold,
     escalationKeywords,
+    stallEscalationEnabled: complexityRouterConfig.stall_escalation_enabled,
+    stallEscalationWindow: complexityRouterConfig.stall_escalation_window,
+    stallEscalationRepeatThreshold: complexityRouterConfig.stall_escalation_repeat_threshold,
     adaptive: complexityRouterConfig.adaptive ?? false,
     adaptiveWeights: complexityRouterConfig.adaptive_weights ?? DEFAULT_ADAPTIVE_WEIGHTS,
     tierDistancePenalty: complexityRouterConfig.tier_distance_penalty ?? DEFAULT_TIER_DISTANCE_PENALTY,

ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.test.ts

@@ -592,6 +592,12 @@ describe("classifier prompt and fallback", () => {
       timeout_ms: 1,
     });
   });
+
+  it.each([{}, { system_prompt: "x" }])("normalizeClassifierLlmConfig carries vision through %o", (extra) => {
+    const base = { model: "m", timeout_ms: 1, ...extra };
+    const vision = { enabled: true, max_images: 2 };
+    expect(normalizeClassifierLlmConfig({ ...base, vision })).toEqual({ ...base, vision });
+  });
 });
 
 describe("tier labels", () => {
@@ -1058,6 +1064,9 @@ describe("buildComplexityRouterConfig with an edited tier set", () => {
       heuristicFirstMaxTier: "SIMPLE",
       hybridBoundaryMargin: 0.03,
       customTechnicalKeywords: ["kubernetes"],
+      stallEscalationEnabled: true,
+      stallEscalationWindow: 6,
+      stallEscalationRepeatThreshold: 3,
     };
     const emittingType = key === "heuristic_first_max_tier" ? "heuristic_first" : "llm";
     const typeForKey = key === "hybrid_boundary_margin" ? "hybrid" : emittingType;
@@ -1152,6 +1161,34 @@ describe("hydrateCustomTierSet", () => {
   });
 });
 
+describe("buildComplexityRouterConfig stall escalation", () => {
+  it("omits all three keys when the toggle is off, since the backend rejects them next to session pinning", () => {
+    const config = buildComplexityRouterConfig({ ...baseParams, stallEscalationEnabled: false });
+    expect(config).not.toHaveProperty("stall_escalation_enabled");
+    expect(config).not.toHaveProperty("stall_escalation_window");
+    expect(config).not.toHaveProperty("stall_escalation_repeat_threshold");
+  });
+
+  it("emits the toggle and both knobs when it is on", () => {
+    const config = buildComplexityRouterConfig({
+      ...baseParams,
+      stallEscalationEnabled: true,
+      stallEscalationWindow: 8,
+      stallEscalationRepeatThreshold: 4,
+    });
+    expect(config.stall_escalation_enabled).toBe(true);
+    expect(config.stall_escalation_window).toBe(8);
+    expect(config.stall_escalation_repeat_threshold).toBe(4);
+  });
+
+  it("emits the toggle alone when neither knob was touched, so both track the backend defaults", () => {
+    const config = buildComplexityRouterConfig({ ...baseParams, stallEscalationEnabled: true });
+    expect(config.stall_escalation_enabled).toBe(true);
+    expect(config).not.toHaveProperty("stall_escalation_window");
+    expect(config).not.toHaveProperty("stall_escalation_repeat_threshold");
+  });
+});
+
 describe("dryRunRejection", () => {
   it("blocks the save on a rejection whose message is missing, which the write would return as a raw 400", () => {
     expect(dryRunRejection({ valid: false })).toBe("The proxy rejected this auto-router configuration");

ui/litellm-dashboard/src/components/add_model/build_complexity_router_config.ts

@@ -1,4 +1,7 @@
 import { KeywordTierRule } from "./KeywordTierRules";
+
+type ClassifierLLMConfigWire = ClassifierLLMConfig & { vision?: { enabled?: boolean; max_images?: number } };
+
 import type { ModelGroup } from "../llm_calls/fetch_models";
 import {
   type CustomTierSet,
@@ -61,7 +64,8 @@ export const normalizeClassifierLlmConfig = ({
   reasoning_effort,
   classification_rubric,
   system_prompt,
-}: ClassifierLLMConfig): ClassifierLLMConfig =>
+  vision,
+}: ClassifierLLMConfigWire): ClassifierLLMConfigWire =>
   system_prompt?.trim()
     ? {
         model,
@@ -69,6 +73,7 @@ export const normalizeClassifierLlmConfig = ({
         ...(circuit_breaker_enabled !== undefined && { circuit_breaker_enabled }),
         ...(circuit_breaker_cooldown_seconds !== undefined && { circuit_breaker_cooldown_seconds }),
         ...(reasoning_effort && { reasoning_effort }),
+        ...(vision && { vision }),
         system_prompt,
       }
     : {
@@ -78,6 +83,7 @@ export const normalizeClassifierLlmConfig = ({
         ...(circuit_breaker_cooldown_seconds !== undefined && { circuit_breaker_cooldown_seconds }),
         ...(reasoning_effort && { reasoning_effort }),
         ...(classification_rubric && { classification_rubric }),
+        ...(vision && { vision }),
       };
 
 interface ScorerKnobInputs {
@@ -138,6 +144,9 @@ export interface BuildComplexityRouterConfigParams {
   embeddingModel: string | undefined;
   matchThreshold: number;
   escalationKeywords: string[];
+  stallEscalationEnabled?: boolean;
+  stallEscalationWindow?: number;
+  stallEscalationRepeatThreshold?: number;
   adaptive: boolean;
   adaptiveWeights: AdaptiveRouterWeights;
   tierDistancePenalty: number;
@@ -199,6 +208,9 @@ export interface ComplexityRouterConfigPayload {
   embedding_model?: string;
   match_threshold?: number;
   escalation_keywords?: string[];
+  stall_escalation_enabled?: boolean;
+  stall_escalation_window?: number;
+  stall_escalation_repeat_threshold?: number;
   adaptive?: boolean;
   adaptive_weights?: AdaptiveRouterWeights;
   tier_distance_penalty?: number;
@@ -318,7 +330,7 @@ export const getSemanticConfigError = ({
 };
 
 interface CustomTierWireFieldInputs {
-  classifierLlmConfig: ClassifierLLMConfig | undefined;
+  classifierLlmConfig: ClassifierLLMConfigWire | undefined;
   planModeMinTierId: string | undefined;
   classificationPrompt: string | undefined;
   classificationExamples: string | undefined;
@@ -350,6 +362,7 @@ export const customTierWireFields = (
           circuit_breaker_cooldown_seconds: classifierLlmConfig.circuit_breaker_cooldown_seconds,
         }),
         ...(classifierLlmConfig.reasoning_effort && { reasoning_effort: classifierLlmConfig.reasoning_effort }),
+        ...(classifierLlmConfig.vision && { vision: classifierLlmConfig.vision }),
       },
     }),
     session_affinity: false,
@@ -472,6 +485,9 @@ export const buildComplexityRouterConfig = ({
   embeddingModel,
   matchThreshold,
   escalationKeywords,
+  stallEscalationEnabled,
+  stallEscalationWindow,
+  stallEscalationRepeatThreshold,
   adaptive,
   adaptiveWeights,
   tierDistancePenalty,
@@ -541,6 +557,15 @@ export const buildComplexityRouterConfig = ({
     ...(customTechnicalKeywords.length > 0 && { custom_technical_keywords: customTechnicalKeywords }),
     ...(cleanedKeywordTierRules.length > 0 && { keyword_tier_rules: cleanedKeywordTierRules }),
     escalation_keywords: cleanedEscalationKeywords,
+    // Only written when on: the backend rejects it alongside session_affinity, user_turn mode and
+    // a custom tier set, so an off router must not carry the key into any of those saves.
+    ...(stallEscalationEnabled && {
+      stall_escalation_enabled: true,
+      ...(stallEscalationWindow !== undefined && { stall_escalation_window: stallEscalationWindow }),
+      ...(stallEscalationRepeatThreshold !== undefined && {
+        stall_escalation_repeat_threshold: stallEscalationRepeatThreshold,
+      }),
+    }),
     ...(semanticMatchingEnabled && {
       semantic_keyword_matching: true,
       embedding_model: embeddingModel,

ui/litellm-dashboard/src/components/add_model/tier_rows.ts

@@ -113,6 +113,10 @@ export const CUSTOM_TIER_RESTRICTIONS = {
     omit: ["escalation_keywords"],
     reason: "Escalation bumps a request along the built-in tier ladder, which your tier set replaces",
   },
+  stallEscalation: {
+    omit: ["stall_escalation_enabled", "stall_escalation_window", "stall_escalation_repeat_threshold"],
+    reason: "Stall escalation bumps a request along the built-in tier ladder, which your tier set replaces",
+  },
   adaptive: {
     omit: ["adaptive", "adaptive_weights", "tier_distance_penalty", "adaptive_eligible"],
     reason: "Adaptive routing scores models along the built-in tier ladder, which your tier set replaces",

ui/litellm-dashboard/src/components/edit_auto_router/build_updated_complexity_router_config.test.ts

@@ -590,16 +590,54 @@ describe("managed keys survive an untouched open-and-save", () => {
   // hold every managed key. Each gets its own round trip below.
   const KEYS_ANOTHER_CLASSIFIER_TYPE_OWNS = new Set(["tier_definitions", "fallback_tier", "hybrid_boundary_margin"]);
 
+  // The stall keys are rejected beside the session pinning and user-turn classification this
+  // fixture sets, so they get their own round trip below rather than widening this one.
+  const KEYS_ANOTHER_CLASSIFICATION_FREQUENCY_OWNS = new Set([
+    "stall_escalation_enabled",
+    "stall_escalation_window",
+    "stall_escalation_repeat_threshold",
+  ]);
+
   it("carries every managed key a built-in router can hold through hydrate then save", () => {
     const hydrated = hydrateComplexityRouterConfig(STORED_ALL_MANAGED, undefined);
     const saved = buildUpdatedComplexityRouterConfig(STORED_ALL_MANAGED, hydrated);
 
     const dropped = [...MANAGED_COMPLEXITY_ROUTER_KEYS]
       .filter((key) => !KEYS_ANOTHER_CLASSIFIER_TYPE_OWNS.has(key))
+      .filter((key) => !KEYS_ANOTHER_CLASSIFICATION_FREQUENCY_OWNS.has(key))
       .filter((key) => saved[key] === undefined);
     expect(dropped).toEqual([]);
   });
 
+  it("carries the stall-escalation keys through their own round trip", () => {
+    const stored: Record<string, unknown> = {
+      ...STORED_ALL_MANAGED,
+      session_affinity: false,
+      classification_mode: "every_request",
+      stall_escalation_enabled: true,
+      stall_escalation_window: 8,
+      stall_escalation_repeat_threshold: 4,
+    };
+    const hydrated = hydrateComplexityRouterConfig(stored, undefined);
+    const saved = buildUpdatedComplexityRouterConfig(stored, hydrated);
+
+    expect(saved.stall_escalation_enabled).toBe(true);
+    expect(saved.stall_escalation_window).toBe(8);
+    expect(saved.stall_escalation_repeat_threshold).toBe(4);
+  });
+
+  it("leaves the stall keys out of a saved config that never had them on", () => {
+    const stored: Record<string, unknown> = {
+      ...STORED_ALL_MANAGED,
+      session_affinity: false,
+      classification_mode: "every_request",
+    };
+    const hydrated = hydrateComplexityRouterConfig(stored, undefined);
+    const saved = buildUpdatedComplexityRouterConfig(stored, hydrated);
+
+    expect(saved).not.toHaveProperty("stall_escalation_enabled");
+  });
+
   it("drops a stored local-scorer threshold when the operator converts the router to custom tiers", () => {
     const hydrated = hydrateComplexityRouterConfig(STORED_ALL_MANAGED, undefined);
     const converted = {

ui/litellm-dashboard/src/components/edit_auto_router/edit_auto_router_modal.tsx

@@ -116,6 +116,9 @@ export interface StoredComplexityRouterConfig {
   return_raw_model_name?: boolean;
   enable_context_window_escalation?: unknown;
   context_window_escalation_buffer?: unknown;
+  stall_escalation_enabled?: unknown;
+  stall_escalation_window?: unknown;
+  stall_escalation_repeat_threshold?: unknown;
 }
 
 /**
@@ -213,6 +216,13 @@ export const hydrateComplexityRouterConfig = (
       typeof parsedConfig.context_window_escalation_buffer === "number"
         ? parsedConfig.context_window_escalation_buffer
         : undefined,
+    stall_escalation_enabled: parsedConfig.stall_escalation_enabled === true || undefined,
+    stall_escalation_window:
+      typeof parsedConfig.stall_escalation_window === "number" ? parsedConfig.stall_escalation_window : undefined,
+    stall_escalation_repeat_threshold:
+      typeof parsedConfig.stall_escalation_repeat_threshold === "number"
+        ? parsedConfig.stall_escalation_repeat_threshold
+        : undefined,
   };
 };
 
@@ -251,6 +261,9 @@ export const MANAGED_COMPLEXITY_ROUTER_KEYS = new Set([
   "reasoning_override_min_score",
   "enable_context_window_escalation",
   "context_window_escalation_buffer",
+  "stall_escalation_enabled",
+  "stall_escalation_window",
+  "stall_escalation_repeat_threshold",
 ]);
 
 // Managed only when the caller passes the corresponding state. A caller that does not render
@@ -358,6 +371,9 @@ export const buildUpdatedComplexityRouterConfig = (
     tierModelParams: value.tier_model_params,
     enableContextWindowEscalation: value.enable_context_window_escalation,
     contextWindowEscalationBuffer: value.context_window_escalation_buffer,
+    stallEscalationEnabled: value.stall_escalation_enabled,
+    stallEscalationWindow: value.stall_escalation_window,
+    stallEscalationRepeatThreshold: value.stall_escalation_repeat_threshold,
   };
   const built = buildComplexityRouterConfig(builderParams);
 

ui/litellm-dashboard/src/lib/http/schema.d.ts

@@ -22764,22 +22764,40 @@ export interface components {
             /** Spend */
             spend?: number | null;
         };
+        /**
+         * AccessGroupResource
+         * @description A resource referenced by an access group. `name` is null when the id no longer resolves or has no alias.
+         */
+        AccessGroupResource: {
+            /** Id */
+            id: string;
+            /** Name */
+            name: string | null;
+        };
         /** AccessGroupResponse */
         AccessGroupResponse: {
             /** Access Agent Ids */
             access_agent_ids: string[];
+            /** Access Agents */
+            access_agents: components["schemas"]["AccessGroupResource"][];
             /** Access Group Id */
             access_group_id: string;
             /** Access Group Name */
             access_group_name: string;
             /** Access Mcp Server Ids */
             access_mcp_server_ids: string[];
+            /** Access Mcp Servers */
+            access_mcp_servers: components["schemas"]["AccessGroupResource"][];
             /** Access Model Names */
             access_model_names: string[];
             /** Assigned Key Ids */
             assigned_key_ids: string[];
+            /** Assigned Keys */
+            assigned_keys: components["schemas"]["AccessGroupResource"][];
             /** Assigned Team Ids */
             assigned_team_ids: string[];
+            /** Assigned Teams */
+            assigned_teams: components["schemas"]["AccessGroupResource"][];
             /**
              * Created At
              * Format: date-time
@@ -25305,6 +25323,30 @@ export interface components {
              * @default 3000
              */
             timeout_ms: number;
+            /** @description Whether the classifier sees images on the request, and how many */
+            vision?: components["schemas"]["ClassifierVisionConfig"];
+        };
+        /**
+         * ClassifierVisionConfig
+         * @description Whether the LLM classifier sees the images on the request it is classifying.
+         *
+         *     Off by default because images cost far more than the text ask they arrive with, and the
+         *     classifier runs on every request. A turn whose complexity lives in the image ("what is wrong in
+         *     this stack trace screenshot") is invisible to a text-only classifier, which is what this buys.
+         */
+        ClassifierVisionConfig: {
+            /**
+             * Enabled
+             * @description Forward image content to the classifier. Requires a classifier model declared supports_vision, on the deployment's model_info or in the model cost map; images stay stripped otherwise, so a classifier that cannot read them is never sent one. Declare model_info.supports_vision on the deployment to enable a model the cost map does not describe. Only inline data: URIs are forwarded. A request whose images are http(s) URLs still classifies on its text alone, because some providers fetch such a URL from the proxy rather than the provider, which would let a caller aim a proxy-side request at an address of their choosing.
+             * @default false
+             */
+            enabled: boolean;
+            /**
+             * Max Images
+             * @description How many images from the newest user turn to forward, in wire order. Bounds the added cost of a turn that attaches many images. Images on earlier turns are never forwarded.
+             * @default 1
+             */
+            max_images: number;
         };
         /**
          * CloudZeroExportRequest
@@ -34923,6 +34965,24 @@ export interface components {
              * @description Keywords indicating simple/basic queries
              */
             simple_keywords?: string[] | null;
+            /**
+             * Stall Escalation Enabled
+             * @description Escalate mid-task to the next-higher configured tier when the assistant's own recent tool calls look stuck: the newest tool call repeats, or errors, at least stall_escalation_repeat_threshold times across the last stall_escalation_window calls. Both tests are anchored on the newest call, so a task that tried the same thing a few times and then moved on is not escalated on the strength of those older calls alone, while a retry loop broken up by an unrelated lookup still counts. One tier at most, on the same ladder escalation_keywords bumps along, and never above the highest configured tier. Detection re-runs on every classified turn from the tool calls visible in that request, so it needs no state and nothing survives past the task. Mutually exclusive with session_affinity and classification_mode='user_turn', which both replay a held routing decision instead of classifying most turns, so this would never see the tool calls to look at. Off by default.
+             * @default false
+             */
+            stall_escalation_enabled: boolean;
+            /**
+             * Stall Escalation Repeat Threshold
+             * @description How many of the last stall_escalation_window tool calls must repeat the newest call, or must have errored alongside it, before the task counts as stalled. Must not exceed stall_escalation_window, or the condition could never be reached.
+             * @default 3
+             */
+            stall_escalation_repeat_threshold: number;
+            /**
+             * Stall Escalation Window
+             * @description How many of the assistant's most recent tool calls stall detection looks at, oldest ones dropped as new calls happen. Counted across the whole visible conversation rather than reset at the newest human ask, so evidence from before a plain follow-up message like 'try again' is still visible on the turn after it.
+             * @default 6
+             */
+            stall_escalation_window: number;
             /**
              * Technical Keywords
              * @description Keywords indicating technical content