chore: merge origin/main into litellm_batch_jsonl_line_item_callbacks

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

.circleci/config.yml

@@ -892,40 +892,6 @@ jobs:
           paths:
             - router_unit_tests_coverage.xml
             - router_unit_tests_coverage
-  litellm_assistants_api_testing: # Runs all tests with the "assistants" keyword
-    docker:
-      - *python312_image
-    working_directory: ~/project
-    resource_class: medium
-
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      # Run pytest and generate JUnit XML report
-      - setup_litellm_enterprise_pip
-      - run:
-          name: Run tests
-          command: |
-            mkdir -p test-results
-            TEST_FILES=$(circleci tests glob "tests/local_testing/**/test_*.py")
-            echo "$TEST_FILES" | circleci tests run \
-              --verbose \
-              --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest --tb=short \
-                -v \
-                --junitxml=test-results/junit.xml \
-                --durations=5 \
-                -k \"assistants\""
-          no_output_timeout: 15m
-      # Store test results
-      - store_test_results:
-          path: test-results
   llm_translation_testing:
     docker:
       - *python312_image
@@ -1021,49 +987,6 @@ jobs:
           paths:
             - realtime_translation_coverage.xml
             - realtime_translation_coverage
-  agent_testing:
-    docker:
-      - *python312_image
-    working_directory: ~/project
-
-    steps:
-      - checkout
-      - skip_if_unrelated_changes
-      - setup_google_dns
-      - install_uv
-      - install_rust
-      - run:
-          name: Install Dependencies
-          command: |
-            uv sync --frozen --all-groups --all-extras --python 3.12
-      # Run pytest and generate JUnit XML report
-      - run:
-          name: Run tests
-          command: |
-            mkdir -p test-results
-            TEST_FILES=$(circleci tests glob "tests/agent_tests/test_*.py")
-            echo "$TEST_FILES" | circleci tests run \
-              --verbose \
-              --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest --tb=short \
-                -vv -s \
-                --cov=./litellm --cov=./enterprise/litellm_enterprise --cov-report=xml \
-                --junitxml=test-results/junit.xml \
-                --durations=5"
-          no_output_timeout: 15m
-      - run:
-          name: Rename the coverage files
-          command: |
-            mv coverage.xml agent_coverage.xml
-            mv .coverage agent_coverage
-
-      # Store test results
-      - store_test_results:
-          path: test-results
-      - persist_to_workspace:
-          root: .
-          paths:
-            - agent_coverage.xml
-            - agent_coverage
   guardrails_testing:
     docker:
       - *python312_image
@@ -2685,7 +2608,7 @@ jobs:
       - run:
           name: Combine Coverage
           command: |
-            uv tool run --from 'coverage[toml]==7.10.6' coverage combine realtime_translation_coverage ocr_coverage search_coverage logging_coverage audio_coverage local_testing_part1_coverage local_testing_part2_coverage pass_through_unit_tests_coverage batches_coverage guardrails_coverage agent_coverage google_generate_content_endpoint_coverage litellm_utils_coverage router_unit_tests_coverage auth_ui_unit_tests_coverage
+            uv tool run --from 'coverage[toml]==7.10.6' coverage combine realtime_translation_coverage ocr_coverage search_coverage logging_coverage audio_coverage local_testing_part1_coverage local_testing_part2_coverage pass_through_unit_tests_coverage batches_coverage guardrails_coverage google_generate_content_endpoint_coverage litellm_utils_coverage router_unit_tests_coverage auth_ui_unit_tests_coverage
             uv tool run --from 'coverage[toml]==7.10.6' coverage xml
       - codecov/upload:
           file: ./coverage.xml
@@ -3063,6 +2986,11 @@ jobs:
       PYTHONPATH: tests/e2e
     steps:
       - checkout_migration_source
+      - run:
+          name: Generate LiteLLM master key
+          command: |
+            key="$(openssl rand -hex 16)"
+            printf 'export LITELLM_MASTER_KEY=sk-%s\n' "$key" >> "$BASH_ENV"
       - install_uv
       - install_rust
       - restore_cache:
@@ -3182,6 +3110,11 @@ jobs:
       E2E_FIXTURE_MODE: live
     steps:
       - checkout
+      - run:
+          name: Generate LiteLLM master key
+          command: |
+            key="$(openssl rand -hex 16)"
+            printf 'export LITELLM_MASTER_KEY=sk-%s\n' "$key" >> "$BASH_ENV"
       - skip_if_unrelated_changes:
           category: provider-harness
       - setup_litellm_test_deps
@@ -3614,7 +3547,6 @@ workflows:
       - local_testing_part1
       - local_testing_part2
       - langfuse_logging_unit_tests
-      - litellm_assistants_api_testing
       - litellm_router_testing
       - litellm_router_unit_testing
       - auth_ui_unit_tests
@@ -3648,7 +3580,6 @@ workflows:
             - build_docker_database_image
       - llm_translation_testing
       - realtime_translation_testing
-      - agent_testing
       - guardrails_testing
       - google_generate_content_endpoint_testing
       - llm_responses_api_testing
@@ -3663,7 +3594,6 @@ workflows:
       - upload-coverage:
           requires:
             - realtime_translation_testing
-            - agent_testing
             - google_generate_content_endpoint_testing
             - guardrails_testing
             - ocr_testing
@@ -3677,7 +3607,6 @@ workflows:
             - langfuse_logging_unit_tests
             - local_testing_part1
             - local_testing_part2
-            - litellm_assistants_api_testing
             - litellm_router_unit_testing
             - auth_ui_unit_tests
       - db_migration_disable_update_check:

Dockerfile

@@ -18,7 +18,7 @@ FROM $LITELLM_BUILD_IMAGE AS pgbouncer-builder
 ARG PGBOUNCER_VERSION
 ARG PGBOUNCER_SHA256
 USER root
-RUN apk add --no-cache build-base pkgconf libevent-dev openssl-dev curl
+RUN apk add --no-cache build-base pkgconf libevent-dev openssl-3.6-dev curl
 WORKDIR /build
 RUN curl -fsSL -o pgbouncer.tar.gz "https://www.pgbouncer.org/downloads/files/${PGBOUNCER_VERSION}/pgbouncer-${PGBOUNCER_VERSION}.tar.gz" && \
     echo "${PGBOUNCER_SHA256}  pgbouncer.tar.gz" | sha256sum -c - && \

docker/Dockerfile.database

@@ -18,7 +18,7 @@ FROM $LITELLM_BUILD_IMAGE AS pgbouncer-builder
 ARG PGBOUNCER_VERSION
 ARG PGBOUNCER_SHA256
 USER root
-RUN apk add --no-cache build-base pkgconf libevent-dev openssl-dev curl
+RUN apk add --no-cache build-base pkgconf libevent-dev openssl-3.6-dev curl
 WORKDIR /build
 RUN curl -fsSL -o pgbouncer.tar.gz "https://www.pgbouncer.org/downloads/files/${PGBOUNCER_VERSION}/pgbouncer-${PGBOUNCER_VERSION}.tar.gz" && \
     echo "${PGBOUNCER_SHA256}  pgbouncer.tar.gz" | sha256sum -c - && \

docker/Dockerfile.non_root

@@ -16,7 +16,7 @@ FROM $LITELLM_BUILD_IMAGE AS pgbouncer-builder
 ARG PGBOUNCER_VERSION
 ARG PGBOUNCER_SHA256
 USER root
-RUN apk add --no-cache build-base pkgconf libevent-dev openssl-dev curl
+RUN apk add --no-cache build-base pkgconf libevent-dev openssl-3.6-dev curl
 WORKDIR /build
 RUN curl -fsSL -o pgbouncer.tar.gz "https://www.pgbouncer.org/downloads/files/${PGBOUNCER_VERSION}/pgbouncer-${PGBOUNCER_VERSION}.tar.gz" && \
     echo "${PGBOUNCER_SHA256}  pgbouncer.tar.gz" | sha256sum -c - && \

litellm-proxy-extras/litellm_proxy_extras/migrations/20260923000000_add_mcp_catalog_revision_trigger/migration.sql

@@ -0,0 +1,13 @@
+CREATE OR REPLACE FUNCTION litellm_bump_mcp_catalog_revision() RETURNS TRIGGER AS $$
+BEGIN
+  INSERT INTO "LiteLLM_Config" ("param_name", "reload_revision")
+  VALUES ('mcp_catalog', 1)
+  ON CONFLICT ("param_name") DO UPDATE SET "reload_revision" = "LiteLLM_Config"."reload_revision" + 1;
+  RETURN NULL;
+END;
+$$ LANGUAGE plpgsql;
+
+DROP TRIGGER IF EXISTS "litellm_mcp_catalog_revision" ON "LiteLLM_MCPServerTable";
+CREATE TRIGGER "litellm_mcp_catalog_revision"
+AFTER INSERT OR UPDATE OR DELETE ON "LiteLLM_MCPServerTable"
+FOR EACH STATEMENT EXECUTE PROCEDURE litellm_bump_mcp_catalog_revision();

litellm/__init__.py

@@ -1405,6 +1405,7 @@ from .exceptions import (
     BadGatewayError,
     OpenAIError,
     ContextWindowExceededError,
+    PaymentRequiredError as PaymentRequiredError,
     ContentPolicyViolationError,
     BudgetExceededError,
     APIError,

litellm/completion_extras/litellm_responses_transformation/transformation.py

@@ -26,6 +26,7 @@ from litellm import ModelResponse
 from litellm._logging import verbose_logger
 from litellm.litellm_core_utils.prompt_templates.common_utils import (
     responses_reasoning_items_from_thinking_blocks,
+    with_prompt_cache_breakpoint,
 )
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
 from litellm.llms.base_llm.bridges.completion_transformation import (
@@ -1089,16 +1090,22 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                     # Handle multimodal content
                     original_type = item.get("type")
                     if original_type == "text":
-                        converted = self._convert_content_str_to_input_text(item.get("text", ""), role)
+                        converted = with_prompt_cache_breakpoint(
+                            self._convert_content_str_to_input_text(item.get("text", ""), role),
+                            item.get("prompt_cache_breakpoint"),
+                        )
                         result.append(converted)
                         verbose_logger.debug("Chat provider:   text -> %s", converted)
                     elif original_type == "image_url":
                         # Map to responses API image format
-                        converted = cast(
-                            dict,
-                            self._convert_content_to_responses_format_image(
-                                cast(ChatCompletionImageObject, item), role
+                        converted = with_prompt_cache_breakpoint(
+                            cast(
+                                dict,
+                                self._convert_content_to_responses_format_image(
+                                    cast(ChatCompletionImageObject, item), role
+                                ),
                             ),
+                            item.get("prompt_cache_breakpoint"),
                         )
                         result.append(converted)
                         verbose_logger.debug("Chat provider:   image_url -> %s", converted)
@@ -1110,8 +1117,11 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
                             result.append(converted)
                             verbose_logger.debug("Chat provider:   image -> %s", converted)
                         elif item_type == "file":
-                            converted = _input_file_from_file_value(
-                                cast("ChatCompletionFileObject", item).get("file"),  # cast-ok: type tag checked
+                            converted = with_prompt_cache_breakpoint(
+                                _input_file_from_file_value(
+                                    cast("ChatCompletionFileObject", item).get("file"),  # cast-ok: type tag checked
+                                ),
+                                item.get("prompt_cache_breakpoint"),
                             )
                             result.append(converted)
                             verbose_logger.debug("Chat provider:   file -> %s", converted)

litellm/exceptions.py

@@ -573,6 +573,54 @@ class ContextWindowExceededError(BadRequestError):
         return _message
 
 
+class PaymentRequiredError(BadRequestError):
+    def __init__(
+        self,
+        message: str,
+        model: str,
+        llm_provider: str,
+        response: httpx.Response | None = None,
+        litellm_debug_info: str | None = None,
+    ) -> None:
+        response_is_valid: Final = (
+            response is not None
+            and isinstance(response, httpx.Response)
+            and hasattr(response, "_request")
+            and getattr(response, "_request", None) is not None
+        )
+        response_for_parent: Final = (
+            response
+            if response_is_valid
+            else httpx.Response(
+                status_code=402,
+                request=httpx.Request(method="GET", url="https://litellm.ai"),
+            )
+        )
+        super().__init__(
+            message=message,
+            model=model,
+            llm_provider=llm_provider,
+            response=response_for_parent,
+            litellm_debug_info=litellm_debug_info,
+        )
+        self.status_code = 402
+        self.message = f"litellm.PaymentRequiredError: {message}"
+
+    def __str__(self) -> str:
+        return (
+            self.message
+            + (f" LiteLLM Retried: {self.num_retries} times" if self.num_retries else "")
+            + (f", LiteLLM Max Retries: {self.max_retries}" if self.max_retries else "")
+        )
+
+    def __repr__(self) -> str:
+        return (
+            self.message
+            + (f" LiteLLM Retried: {self.num_retries} times" if self.num_retries else "")
+            + (f", LiteLLM Max Retries: {self.max_retries}" if self.max_retries else "")
+        )
+
+
 # sub class of bad request error - meant to help us catch guardrails-related errors on proxy.
 class RejectedRequestError(BadRequestError):
     def __init__(
@@ -977,6 +1025,7 @@ LITELLM_EXCEPTION_TYPES: Final = [
     PermissionDeniedError,
     RateLimitError,
     ContextWindowExceededError,
+    PaymentRequiredError,
     RejectedRequestError,
     ContentPolicyViolationError,
     InternalServerError,

litellm/experimental_mcp_client/client.py

@@ -12,7 +12,7 @@ from contextlib import AbstractAsyncContextManager
 from functools import partial
 from importlib.metadata import version
 from types import MappingProxyType
-from typing import Final, TypeAlias, TypeVar, cast
+from typing import TYPE_CHECKING, Final, TypeAlias, TypeVar, cast
 
 import anyio
 import httpx2
@@ -47,9 +47,13 @@ from mcp.types import (
     InitializeRequestParams,
     InitializeResult,
     InputRequiredResult,
+    ListPromptsRequest,
     ListPromptsResult,
+    ListResourcesRequest,
     ListResourcesResult,
     ListResourceTemplatesResult,
+    ListToolsRequest,
+    ListToolsResult,
     PaginatedRequestParams,
     PaginatedResult,
     Prompt,
@@ -89,6 +93,9 @@ from litellm.types.mcp import (
     without_header,
 )
 
+if TYPE_CHECKING:
+    from litellm.proxy._experimental.mcp_server.contracts import CatalogListRequest, CatalogListResult
+
 
 def to_basic_auth(auth_value: str) -> str:
     """Convert auth value to Basic Auth format."""
@@ -830,6 +837,51 @@ class MCPClient:
 
         return factory
 
+    async def list_page(self, request: "CatalogListRequest") -> "CatalogListResult":
+        from mcp.types import INVALID_PARAMS
+
+        params: Final = request.params or PaginatedRequestParams()
+        if isinstance(request, ListToolsRequest):
+            return await self.list_tools_page(params)
+
+        async def fetch(session: ClientSession) -> "CatalogListResult":
+            capabilities: Final = session.server_capabilities
+            empty: Final = (
+                ListPromptsResult(prompts=[])
+                if isinstance(request, ListPromptsRequest)
+                else ListResourcesResult(resources=[])
+                if isinstance(request, ListResourcesRequest)
+                else ListResourceTemplatesResult(resource_templates=[])
+            )
+            supported: Final = capabilities is None or (
+                capabilities.prompts is not None
+                if isinstance(request, ListPromptsRequest)
+                else capabilities.resources is not None
+            )
+            if not supported:
+                if params.cursor is not None:
+                    raise MCPError(
+                        code=INVALID_PARAMS, message="Upstream catalog became unavailable; start a fresh listing"
+                    )
+                return empty
+            try:
+                if isinstance(request, ListPromptsRequest):
+                    return await session.list_prompts(params=params)
+                if isinstance(request, ListResourcesRequest):
+                    return await session.list_resources(params=params)
+                return await session.list_resource_templates(params=params)
+            except MCPError as error:
+                if error.error.code == METHOD_NOT_FOUND and params.cursor is None:
+                    return empty
+                raise
+
+        with anyio.fail_after(max(self.timeout, MCP_TOOL_LISTING_TIMEOUT)):
+            return await self.run_with_session(fetch, quiet_on_error=True)
+
+    async def list_tools_page(self, params: PaginatedRequestParams) -> ListToolsResult:
+        with anyio.fail_after(max(self.timeout, MCP_TOOL_LISTING_TIMEOUT)):
+            return await self.run_with_session(lambda session: session.list_tools(params=params), quiet_on_error=True)
+
     async def list_tools(self, raise_on_error: bool = False) -> list[MCPTool]:
         """List available tools from the server.
 
@@ -846,7 +898,7 @@ class MCPClient:
             # A per-server timeout above the global default extends the whole-walk deadline
             listing_deadline: Final = max(self.timeout, MCP_TOOL_LISTING_TIMEOUT)
             tools: Final = await self.run_with_session(
-                partial(list_tools_with_pagination, listing_deadline=listing_deadline),
+                partial(list_tools_with_pagination, listing_deadline=listing_deadline, require_complete=raise_on_error),
                 quiet_on_error=raise_on_error,
             )
             tool_count: Final = len(tools)

litellm/experimental_mcp_client/tools.py

@@ -2,10 +2,10 @@ import json
 from typing import Final, Literal
 
 import anyio
-from mcp import ClientSession
+from mcp import ClientSession, MCPError
+from mcp.types import INTERNAL_ERROR, PaginatedRequestParams
 from mcp.types import CallToolRequestParams as MCPCallToolRequestParams
 from mcp.types import CallToolResult as MCPCallToolResult
-from mcp.types import PaginatedRequestParams
 from mcp.types import Tool as MCPTool
 from openai.types.chat import ChatCompletionToolParam
 from openai.types.responses.function_tool_param import FunctionToolParam
@@ -99,7 +99,7 @@ def transform_mcp_tool_to_anthropic_tool(mcp_tool: MCPTool) -> AnthropicMessages
 
 
 async def list_tools_with_pagination(
-    session: ClientSession, listing_deadline: float | None = None
+    session: ClientSession, listing_deadline: float | None = None, *, require_complete: bool = False
 ) -> list[MCPTool]:  # mutable-ok: list return contract
     """Collect tools from every tools/list page by following nextCursor.
 
@@ -137,6 +137,10 @@ async def list_tools_with_pagination(
                     "MCP server repeated a tools/list cursor while listing tools; returning %s tools collected so far",
                     len(tools),
                 )
+                if require_complete:
+                    raise MCPError(
+                        code=INTERNAL_ERROR, message="Upstream tool discovery is incomplete: repeated cursor"
+                    )
                 return tools
             seen_cursors.add(next_cursor)
             cursor = next_cursor
@@ -146,6 +150,8 @@ async def list_tools_with_pagination(
             MCP_TOOL_LISTING_MAX_PAGES,
             len(tools),
         )
+        if require_complete:
+            raise MCPError(code=INTERNAL_ERROR, message="Upstream tool discovery is incomplete: pagination limit")
         return tools
 
     verbose_logger.warning(
@@ -153,6 +159,8 @@ async def list_tools_with_pagination(
         effective_deadline,
         len(tools),
     )
+    if require_complete:
+        raise MCPError(code=INTERNAL_ERROR, message="Upstream tool discovery is incomplete: listing deadline")
     return tools
 
 

litellm/integrations/anthropic_cache_control_hook.py

@@ -283,7 +283,7 @@ class AnthropicCacheControlHook(CustomPromptManagement):
             openai_dialect
             and AnthropicCacheControlHook.count_request_cache_breakpoints(processed_messages) > breakpoints_before
         ):
-            non_default_params.setdefault("prompt_cache_options", PromptCacheOptions(mode="explicit"))
+            non_default_params.setdefault("prompt_cache_options", PromptCacheOptions(mode="implicit"))
 
         # Points this pass did not place: non-message ones for the provider transform, and
         # the deferred role-targeted ones. Deferring is what reaches the Responses API's

litellm/litellm_core_utils/exception_mapping_utils.py

@@ -28,6 +28,7 @@ from ..exceptions import (
     ContextWindowExceededError,
     InternalServerError,
     NotFoundError,
+    PaymentRequiredError,
     PermissionDeniedError,
     RateLimitError,
     ServiceUnavailableError,
@@ -2327,6 +2328,14 @@ def _map_exception_by_status(
                 litellm_debug_info=extra_information,
                 exception_status_code=status_code,
             )
+        case 402:
+            raise PaymentRequiredError(
+                message=message,
+                model=model,
+                llm_provider=custom_llm_provider,
+                response=response,
+                litellm_debug_info=extra_information,
+            )
         case _ if status_code < 500:
             raise BadRequestError(
                 message=message,

litellm/llms/bedrock/realtime/transformation.py

@@ -118,6 +118,7 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         # so the USER/ASSISTANT split from contentStart is tracked here)
         self._user_transcript_active = False
         self._user_transcript_generation_stage: str | None = None
+        self._assistant_final_text_active = False
         self._user_item_id: str | None = None
         self._user_transcript_buffer = ""
         self._cumulative_usage = BedrockUsageEvent()
@@ -748,6 +749,20 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
                 None,
             )
 
+        generation_stage: Final = self._parse_generation_stage(content_start.get("additionalModelFields"))
+        if content_start.get("type") == "TEXT" and generation_stage == "FINAL":
+            verbose_logger.debug(
+                "Dropping FINAL ASSISTANT text block: the SPECULATIVE block already carried its sentences"
+            )
+            self._assistant_final_text_active = True
+            return (
+                [],
+                current_response_id,
+                current_output_item_id,
+                current_conversation_id,
+                None,
+            )
+
         verbose_logger.debug("Handling ASSISTANT contentStart")
         is_new_response: Final = current_response_id is None
 
@@ -943,6 +958,8 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         verbose_logger.debug("Handling textOutput")
         text_content: Final = event["textOutput"].get("content", "")
 
+        if self._assistant_final_text_active:
+            return [], current_delta_chunks
         if not current_output_item_id or not current_response_id:
             return [], current_delta_chunks
 
@@ -1022,6 +1039,9 @@ class BedrockRealtimeConfig(BaseRealtimeConfig):
         content_end: Final = event["contentEnd"]
         verbose_logger.debug("Handling contentEnd: %s", content_end)
 
+        if self._assistant_final_text_active:
+            self._assistant_final_text_active = False
+            return [], current_delta_chunks
         if not current_output_item_id or not current_response_id:
             return [], current_delta_chunks
 

litellm/model_prices_and_context_window_backup.json

@@ -4691,9 +4691,9 @@
         "max_output_tokens": 4096,
         "max_tokens": 4096,
         "mode": "realtime",
-        "output_cost_per_audio_token": 8e-05,
+        "output_cost_per_audio_token": 8.8e-05,
         "output_cost_per_token": 2.2e-05,
-        "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_modalities": [
             "text",
             "audio"
@@ -5752,14 +5752,14 @@
     },
     "azure/gpt-audio-1.5": {
         "deprecation_date": "2027-08-24",
-        "input_cost_per_audio_token": 4e-05,
+        "input_cost_per_audio_token": 3.2e-05,
         "input_cost_per_token": 2.5e-06,
         "litellm_provider": "azure",
         "max_input_tokens": 128000,
         "max_output_tokens": 16384,
         "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_audio_token": 8e-05,
+        "output_cost_per_audio_token": 6.4e-05,
         "output_cost_per_token": 1e-05,
         "supported_endpoints": [
             "/v1/chat/completions"
@@ -5781,19 +5781,20 @@
         "supports_system_messages": true,
         "supports_tool_choice": true,
         "supports_vision": false,
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         "mode": "chat",
-        "output_cost_per_token": 4.4e-06,
+        "output_cost_per_token": 3.036e-06,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -65192,7 +65262,7 @@
     },
     "azure_ai/kimi-k2.7-code": {
         "cache_read_input_token_cost": 1.9e-07,
-        "deprecation_date": "2026-10-03",
+        "deprecation_date": "2027-04-16",
         "input_cost_per_token": 9.5e-07,
         "litellm_provider": "azure_ai",
         "max_input_tokens": 262144,
@@ -67853,24 +67923,24 @@
         "supports_web_search": false
     },
     "openrouter/z-ai/glm-5.3": {
-        "input_cost_per_token": 1.4e-06,
-        "output_cost_per_token": 4.4e-06,
-        "cache_read_input_token_cost": 1.4e-07,
+        "cache_read_input_token_cost": 6.5e-08,
+        "input_cost_per_token": 7e-08,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
-        "max_output_tokens": 131072,
-        "max_tokens": 131072,
+        "max_output_tokens": 943718,
+        "max_tokens": 943718,
         "mode": "chat",
+        "output_cost_per_token": 7e-06,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
-        "supports_tool_choice": true,
-        "supports_reasoning": true,
-        "supports_response_schema": true,
         "supports_parallel_function_calling": true,
         "supports_pdf_input": false,
-        "supports_vision": false,
         "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": false,
         "supports_web_search": false
     },
     "openrouter/qwen/qwen3.8-27b": {
@@ -67991,8 +68061,8 @@
         "supports_prompt_caching": true
     },
     "openrouter/deepseek/deepseek-v4-flash-0731": {
-        "cache_read_input_token_cost": 1.52e-08,
-        "input_cost_per_token": 1.52e-08,
+        "cache_read_input_token_cost": 1.63e-08,
+        "input_cost_per_token": 1.63e-08,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
         "max_output_tokens": 943718,
@@ -68082,14 +68152,14 @@
         "supports_web_search": false
     },
     "openrouter/moonshotai/kimi-k3": {
-        "cache_read_input_token_cost": 7e-07,
-        "input_cost_per_token": 7.2e-07,
+        "cache_read_input_token_cost": 2.6e-07,
+        "input_cost_per_token": 7.9e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
         "max_output_tokens": 943718,
         "max_tokens": 943718,
         "mode": "chat",
-        "output_cost_per_token": 1.4e-05,
+        "output_cost_per_token": 1.5e-05,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -68207,14 +68277,14 @@
         "supports_web_search": true
     },
     "openrouter/z-ai/glm-5.2": {
-        "cache_read_input_token_cost": 1e-07,
-        "input_cost_per_token": 1.04e-07,
+        "cache_read_input_token_cost": 1.5e-07,
+        "input_cost_per_token": 1.52e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
         "max_output_tokens": 131072,
         "max_tokens": 131072,
         "mode": "chat",
-        "output_cost_per_token": 8e-06,
+        "output_cost_per_token": 1.2e-05,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -68509,14 +68579,14 @@
         "supports_web_search": false
     },
     "openrouter/qwen/qwen3.6-27b": {
-        "cache_read_input_token_cost": 1.5e-07,
-        "input_cost_per_token": 3.2e-07,
+        "cache_read_input_token_cost": 3e-08,
+        "input_cost_per_token": 3e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 262144,
-        "max_output_tokens": 81920,
-        "max_tokens": 81920,
+        "max_output_tokens": 65536,
+        "max_tokens": 65536,
         "mode": "chat",
-        "output_cost_per_token": 3.2e-06,
+        "output_cost_per_token": 2e-06,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -68570,8 +68640,8 @@
         "supports_web_search": true
     },
     "openrouter/deepseek/deepseek-v4-flash": {
-        "cache_read_input_token_cost": 2.24e-08,
-        "input_cost_per_token": 2.24e-08,
+        "cache_read_input_token_cost": 3e-08,
+        "input_cost_per_token": 3e-08,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
         "max_output_tokens": 943718,
@@ -68611,14 +68681,14 @@
         "supports_web_search": false
     },
     "openrouter/google/gemma-4-26b-a4b-it": {
-        "cache_read_input_token_cost": 3.75e-08,
-        "input_cost_per_token": 6.75e-08,
+        "cache_read_input_token_cost": 4.25e-08,
+        "input_cost_per_token": 7.65e-08,
         "litellm_provider": "openrouter",
         "max_input_tokens": 262144,
         "max_output_tokens": 235929,
         "max_tokens": 235929,
         "mode": "chat",
-        "output_cost_per_token": 2.25e-07,
+        "output_cost_per_token": 2.55e-07,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -69952,21 +70022,22 @@
         "supports_web_search": true
     },
     "openrouter/meta-llama/llama-4-maverick": {
+        "cache_read_input_token_cost": 5e-08,
         "input_cost_per_token": 1.875e-07,
-        "output_cost_per_token": 6.525e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 1048576,
         "max_output_tokens": 16384,
         "max_tokens": 16384,
         "mode": "chat",
+        "output_cost_per_token": 6.525e-07,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
         "supports_pdf_input": false,
-        "supports_prompt_caching": false,
+        "supports_prompt_caching": true,
         "supports_reasoning": false,
-        "supports_tool_choice": true,
         "supports_response_schema": true,
+        "supports_tool_choice": true,
         "supports_vision": true,
         "supports_web_search": false
     },
@@ -75009,13 +75080,13 @@
     },
     "openrouter/meta/muse-glimmer-30b": {
         "cache_read_input_token_cost": 4e-08,
-        "input_cost_per_token": 3.5e-07,
+        "input_cost_per_token": 3e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 131072,
-        "max_output_tokens": 117964,
-        "max_tokens": 117964,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_token": 1.5e-06,
+        "output_cost_per_token": 1.2e-06,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -76935,12 +77006,12 @@
         "supports_web_search": false
     },
     "openrouter/thinkingmachines/inkling": {
-        "cache_read_input_token_cost": 1.6e-07,
-        "input_cost_per_token": 9.5e-07,
+        "cache_read_input_token_cost": 1.7e-07,
+        "input_cost_per_token": 1e-06,
         "litellm_provider": "openrouter",
         "max_input_tokens": 524288,
-        "max_output_tokens": 262144,
-        "max_tokens": 262144,
+        "max_output_tokens": 471859,
+        "max_tokens": 471859,
         "mode": "chat",
         "output_cost_per_token": 4.05e-06,
         "source": "https://openrouter.ai/api/v1/models",
@@ -80556,5 +80627,75 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_web_search": true
+    },
+    "openrouter/mistralai/mistral-large-4-0": {
+        "cache_read_input_token_cost": 7e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "openrouter",
+        "max_input_tokens": 524288,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "source": "https://openrouter.ai/api/v1/models",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": false,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": false
+    },
+    "openrouter/google/gemini-nano-banana-2.1": {
+        "input_cost_per_token": 1.5e-06,
+        "litellm_provider": "openrouter",
+        "max_input_tokens": 65536,
+        "max_output_tokens": 58982,
+        "max_tokens": 58982,
+        "mode": "chat",
+        "output_cost_per_image_token": 3e-05,
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://openrouter.ai/api/v1/models",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": false,
+        "supports_prompt_caching": false,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true
+    },
+    "in.moonshotai.kimi-k3": {
+        "cache_creation_input_token_cost": 4.125e-06,
+        "cache_creation_input_token_cost_flex": 2.0625e-06,
+        "cache_creation_input_token_cost_priority": 7.21875e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "cache_read_input_token_cost_flex": 1.65e-07,
+        "cache_read_input_token_cost_priority": 5.775e-07,
+        "input_cost_per_token": 3.3e-06,
+        "input_cost_per_token_flex": 1.65e-06,
+        "input_cost_per_token_priority": 5.775e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 1.65e-05,
+        "output_cost_per_token_flex": 8.25e-06,
+        "output_cost_per_token_priority": 2.8875e-05,
+        "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k3.md",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_prompt_cache_breakpoint": false,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_regex_lookaround": false,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
     }
 }

litellm/proxy/_experimental/mcp_server/README.md

@@ -0,0 +1,15 @@
+# Gateway catalog pagination
+
+Tools, prompts, resources, and resource templates retain upstream page boundaries. Follow the gateway's opaque `nextCursor` until it is absent. Each request checks the caller's current access and tool permissions. A cursor can be replayed and can be sent to another replica serving the same configuration
+
+Set the same nonempty `LITELLM_SALT_KEY` on every replica. Pagination state uses authenticated encryption with purpose-separated HKDF keys derived only from this value. The master key is never a fallback. Complete single-page lists and direct tool calls work without a salt key; a listing that needs continuation returns an actionable configuration error instead of truncated results. Some SDKs automatically list tools when validating a tool-call response, so those SDK calls also require a salt when that listing is paginated
+
+Cursors expire ten minutes after the first page. Continuations do not extend that deadline. Rotating the salt invalidates all outstanding cursors; clients must start a new listing. During a rolling key change, replicas with different keys cannot accept each other's cursors. Coordinate the change across the fleet
+
+A changed registry, caller scope, or available upstream revision requires a fresh listing. When an upstream exposes a string or integer `_meta.revision`, subsequent pages must retain it. Otherwise consistency follows that upstream's own cursor guarantees. Repeated upstream cursors and the existing upstream page limit stop traversal with an explicit error
+
+Listing failures retain per-server outcome metadata. An incomplete upstream catalog cannot establish a bare tool-name route. Complete initial pages retain legacy bare-name routing. Use the server-prefixed names returned by the gateway for paginated catalogs
+
+For a scoped rollout, keep the previous source build serving the control pool and send only selected clients to a separate candidate pool. All candidate replicas must share configuration and salt. Verify page one on one candidate replica and continuation on another, plus a fresh listing and tool call on the control pool. Do not mirror tool calls between pools
+
+For rollback, stop sending new requests to the candidate pool, drain its in-flight operations, and return selected clients to the control pool. Clients must discard candidate cursors and start a fresh listing when crossing versions; older gateways do not validate these cursors. Keep the registry-revision migration installed when rolling back pagination. Verify a fresh listing and a tool call after switching pools

litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py

@@ -1,5 +1,6 @@
 import re
 from collections.abc import Mapping, Sequence
+from collections.abc import Set as AbstractSet
 from dataclasses import dataclass
 from datetime import datetime, timezone
 from types import MappingProxyType
@@ -15,6 +16,7 @@ import litellm
 from litellm._internal_context import with_service_target
 from litellm._logging import verbose_logger
 from litellm.constants import MCP_ALL_TOOLS_WILDCARD
+from litellm.proxy._experimental.mcp_server.catalog import global_manager
 from litellm.proxy._experimental.mcp_server.oauth_utils import (
     get_passthrough_resource_metadata_url,
     get_passthrough_www_authenticate,
@@ -71,6 +73,7 @@ from litellm.repositories.table_repositories import (
     MCPServerRepository,
 )
 from litellm.types.mcp_server.mcp_server_manager import MCPServer
+from litellm.types.proxy.auth.auth_checks import UserNotFoundError
 
 if TYPE_CHECKING:
     from litellm.proxy.utils import PrismaClient
@@ -448,188 +451,191 @@ class MCPRequestHandler:
         Raises:
             HTTPException: If headers are invalid or missing required headers
         """
-        headers: Final = MCPRequestHandler._safe_get_headers_from_scope(scope)
+        async with global_manager().catalog.operation():
+            headers: Final = MCPRequestHandler._safe_get_headers_from_scope(scope)
 
-        # Check if there is an explicit LiteLLM API key (primary header)
-        has_explicit_litellm_key: Final = headers.get(MCPRequestHandler.LITELLM_API_KEY_HEADER_NAME_PRIMARY) is not None
+            # Check if there is an explicit LiteLLM API key (primary header)
+            has_explicit_litellm_key: Final = (
+                headers.get(MCPRequestHandler.LITELLM_API_KEY_HEADER_NAME_PRIMARY) is not None
+            )
 
-        litellm_api_key: Final = MCPRequestHandler.get_litellm_api_key_from_headers(headers) or ""
+            litellm_api_key: Final = MCPRequestHandler.get_litellm_api_key_from_headers(headers) or ""
 
-        # Get the old mcp_auth_header for backward compatibility
-        mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(headers)
+            # Get the old mcp_auth_header for backward compatibility
+            mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(headers)
 
-        # Get the new server-specific auth headers
-        mcp_server_auth_headers = MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers)
+            # Get the new server-specific auth headers
+            mcp_server_auth_headers = MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers)
 
-        # Get the oauth2 headers
-        oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(headers)
+            # Get the oauth2 headers
+            oauth2_headers = MCPRequestHandler._get_oauth2_headers_from_headers(headers)
 
-        # Parse MCP servers from header
-        mcp_servers_header: Final = headers.get(MCPRequestHandler.LITELLM_MCP_SERVERS_HEADER_NAME)
-        verbose_logger.debug("Raw MCP servers header: %s", mcp_servers_header)
-        mcp_servers = None
-        if mcp_servers_header is not None:
-            try:
-                mcp_servers = [s.strip() for s in mcp_servers_header.split(",") if s.strip()]
-                verbose_logger.debug("Parsed MCP servers: %s", mcp_servers)
-            except Exception as e:
-                verbose_logger.debug("Error parsing mcp_servers header: %s", e)
-                mcp_servers = None
-            if mcp_servers_header == "" or (mcp_servers is not None and len(mcp_servers) == 0):
-                mcp_servers = []
-        # Create a proper Request object with mock body method to avoid ASGI receive channel issues
-        request: Final = Request(scope=scope)
+            # Parse MCP servers from header
+            mcp_servers_header: Final = headers.get(MCPRequestHandler.LITELLM_MCP_SERVERS_HEADER_NAME)
+            verbose_logger.debug("Raw MCP servers header: %s", mcp_servers_header)
+            mcp_servers = None
+            if mcp_servers_header is not None:
+                try:
+                    mcp_servers = [s.strip() for s in mcp_servers_header.split(",") if s.strip()]
+                    verbose_logger.debug("Parsed MCP servers: %s", mcp_servers)
+                except Exception as e:
+                    verbose_logger.debug("Error parsing mcp_servers header: %s", e)
+                    mcp_servers = None
+                if mcp_servers_header == "" or (mcp_servers is not None and len(mcp_servers) == 0):
+                    mcp_servers = []
+            # Create a proper Request object with mock body method to avoid ASGI receive channel issues
+            request: Final = Request(scope=scope)
 
-        async def mock_body():
-            return b"{}"
+            async def mock_body():
+                return b"{}"
 
-        request.body = mock_body
-        # Inline import — auth_utils participates in a proxy import cycle.
-        from litellm.proxy.auth.auth_utils import (  # noqa: PLC0415
-            get_request_route,
-        )
+            request.body = mock_body
+            # Inline import — auth_utils participates in a proxy import cycle.
+            from litellm.proxy.auth.auth_utils import (  # noqa: PLC0415
+                get_request_route,
+            )
 
-        request_route: Final = get_request_route(request)
-        # Only OAuth metadata routes registered under /.well-known/ are public.
-        if request_route.startswith("/.well-known/"):
-            validated_user_api_key_auth = UserAPIKeyAuth()
-        elif (
-            has_explicit_litellm_key
-            and oauth2_headers
-            and is_bridge_envelope_shaped(oauth2_headers["Authorization"])
-            and (
-                dual_bridge_target := MCPRequestHandler._single_dcr_bridge_delegate_target(
+            request_route: Final = get_request_route(request)
+            # Only OAuth metadata routes registered under /.well-known/ are public.
+            if request_route.startswith("/.well-known/"):
+                validated_user_api_key_auth = UserAPIKeyAuth()
+            elif (
+                has_explicit_litellm_key
+                and oauth2_headers
+                and is_bridge_envelope_shaped(oauth2_headers["Authorization"])
+                and (
+                    dual_bridge_target := MCPRequestHandler._single_dcr_bridge_delegate_target(
+                        path=request_route,
+                        mcp_servers=mcp_servers,
+                        client_ip=IPAddressUtils.get_mcp_client_ip(request),
+                    )
+                )
+                is not None
+            ):
+                (
+                    validated_user_api_key_auth,
+                    mcp_server_auth_headers,
+                ) = await MCPRequestHandler._admit_dcr_bridge_dual_credential(
+                    server=dual_bridge_target.server,
+                    requested_name=dual_bridge_target.requested_name,
+                    authorization_value=oauth2_headers["Authorization"],
+                    litellm_api_key=litellm_api_key,
+                    mcp_server_auth_headers=mcp_server_auth_headers,
+                    request=request,
+                    route=request_route,
+                )
+            elif has_explicit_litellm_key:
+                # An explicit x-litellm-api-key is always a LiteLLM credential, even
+                # for a delegated server, so validate it: identity / spend / rate
+                # limits resolve and any stored upstream token can be forwarded.
+                validated_user_api_key_auth = await user_api_key_auth(
+                    api_key=f"Bearer {_get_bearer_token_or_received_api_key(litellm_api_key)}",
+                    request=request,
+                )
+            elif MCPRequestHandler._target_servers_are_true_passthrough(
+                path=request_route,
+                mcp_servers=mcp_servers,
+                client_ip=IPAddressUtils.get_mcp_client_ip(request),
+            ) or (
+                MCPRequestHandler._single_dcr_bridge_delegate_target(
                     path=request_route,
                     mcp_servers=mcp_servers,
                     client_ip=IPAddressUtils.get_mcp_client_ip(request),
                 )
-            )
-            is not None
-        ):
-            (
-                validated_user_api_key_auth,
-                mcp_server_auth_headers,
-            ) = await MCPRequestHandler._admit_dcr_bridge_dual_credential(
-                server=dual_bridge_target.server,
-                requested_name=dual_bridge_target.requested_name,
-                authorization_value=oauth2_headers["Authorization"],
-                litellm_api_key=litellm_api_key,
-                mcp_server_auth_headers=mcp_server_auth_headers,
-                request=request,
-                route=request_route,
-            )
-        elif has_explicit_litellm_key:
-            # An explicit x-litellm-api-key is always a LiteLLM credential, even
-            # for a delegated server, so validate it: identity / spend / rate
-            # limits resolve and any stored upstream token can be forwarded.
-            validated_user_api_key_auth = await user_api_key_auth(
-                api_key=f"Bearer {_get_bearer_token_or_received_api_key(litellm_api_key)}",
-                request=request,
-            )
-        elif MCPRequestHandler._target_servers_are_true_passthrough(
-            path=request_route,
-            mcp_servers=mcp_servers,
-            client_ip=IPAddressUtils.get_mcp_client_ip(request),
-        ) or (
-            MCPRequestHandler._single_dcr_bridge_delegate_target(
-                path=request_route,
-                mcp_servers=mcp_servers,
-                client_ip=IPAddressUtils.get_mcp_client_ip(request),
-            )
-            is not None
-            and not oauth2_headers
-            and not mcp_server_auth_headers
-            and not mcp_auth_header
-        ):
-            validated_user_api_key_auth = UserAPIKeyAuth()
-        elif (
-            bridge_delegate_target := MCPRequestHandler._single_dcr_bridge_delegate_target(
-                path=request_route,
-                mcp_servers=mcp_servers,
-                client_ip=IPAddressUtils.get_mcp_client_ip(request),
-            )
-        ) is not None and oauth2_headers:
-            (
-                validated_user_api_key_auth,
-                mcp_server_auth_headers,
-            ) = await MCPRequestHandler._admit_dcr_bridge_authorization(
-                server=bridge_delegate_target.server,
-                requested_name=bridge_delegate_target.requested_name,
-                authorization_value=oauth2_headers["Authorization"],
-                litellm_api_key=litellm_api_key,
-                mcp_server_auth_headers=mcp_server_auth_headers,
-                request=request,
-                route=request_route,
-            )
-        elif oauth2_headers and is_session_bearer_shaped(oauth2_headers["Authorization"]):
-            # A gateway DCR session bearer at any MCP scope: open the identity-only session
-            # token and admit under the live litellm user; downstream grant resolution
-            # intersects the admitted subject's servers with any path or header target, so a
-            # per-server scope narrows and never broadens. One that does not open fails
-            # closed with the scope's invalid_token challenge; a non-session bearer falls
-            # through to the oauth2 arm.
-            validated_user_api_key_auth = await MCPRequestHandler._admit_gateway_session(
-                authorization_value=oauth2_headers["Authorization"],
-                request=request,
-                route=request_route,
-                mcp_servers=mcp_servers,
-            )
-        elif oauth2_headers:
-            # Authorization on a non-delegated server: the bearer must be a real
-            # LiteLLM credential, so a failed validation is a genuine 401/403 and
-            # propagates unless a fallback in _admission_failure_fallback applies.
-            try:
-                validated_user_api_key_auth = await user_api_key_auth(api_key=litellm_api_key, request=request)
-            except (HTTPException, ProxyException) as e:
-                validated_user_api_key_auth = _admission_failure_fallback(
-                    request=request,
-                    request_route=request_route,
+                is not None
+                and not oauth2_headers
+                and not mcp_server_auth_headers
+                and not mcp_auth_header
+            ):
+                validated_user_api_key_auth = UserAPIKeyAuth()
+            elif (
+                bridge_delegate_target := MCPRequestHandler._single_dcr_bridge_delegate_target(
+                    path=request_route,
                     mcp_servers=mcp_servers,
-                    mcp_auth_header=mcp_auth_header,
-                    mcp_server_auth_headers=mcp_server_auth_headers,
-                    exc=e,
-                    bearer_presented=True,
+                    client_ip=IPAddressUtils.get_mcp_client_ip(request),
                 )
-        else:
-            try:
-                validated_user_api_key_auth = await user_api_key_auth(api_key=litellm_api_key, request=request)
-            except (HTTPException, ProxyException) as exc:
-                validated_user_api_key_auth = _admission_failure_fallback(
+            ) is not None and oauth2_headers:
+                (
+                    validated_user_api_key_auth,
+                    mcp_server_auth_headers,
+                ) = await MCPRequestHandler._admit_dcr_bridge_authorization(
+                    server=bridge_delegate_target.server,
+                    requested_name=bridge_delegate_target.requested_name,
+                    authorization_value=oauth2_headers["Authorization"],
+                    litellm_api_key=litellm_api_key,
+                    mcp_server_auth_headers=mcp_server_auth_headers,
                     request=request,
-                    request_route=request_route,
-                    mcp_servers=mcp_servers,
-                    mcp_auth_header=mcp_auth_header,
-                    mcp_server_auth_headers=mcp_server_auth_headers,
-                    exc=exc,
-                    bearer_presented=False,
+                    route=request_route,
                 )
+            elif oauth2_headers and is_session_bearer_shaped(oauth2_headers["Authorization"]):
+                # A gateway DCR session bearer at any MCP scope: open the identity-only session
+                # token and admit under the live litellm user; downstream grant resolution
+                # intersects the admitted subject's servers with any path or header target, so a
+                # per-server scope narrows and never broadens. One that does not open fails
+                # closed with the scope's invalid_token challenge; a non-session bearer falls
+                # through to the oauth2 arm.
+                validated_user_api_key_auth = await MCPRequestHandler._admit_gateway_session(
+                    authorization_value=oauth2_headers["Authorization"],
+                    request=request,
+                    route=request_route,
+                    mcp_servers=mcp_servers,
+                )
+            elif oauth2_headers:
+                # Authorization on a non-delegated server: the bearer must be a real
+                # LiteLLM credential, so a failed validation is a genuine 401/403 and
+                # propagates unless a fallback in _admission_failure_fallback applies.
+                try:
+                    validated_user_api_key_auth = await user_api_key_auth(api_key=litellm_api_key, request=request)
+                except (HTTPException, ProxyException) as e:
+                    validated_user_api_key_auth = _admission_failure_fallback(
+                        request=request,
+                        request_route=request_route,
+                        mcp_servers=mcp_servers,
+                        mcp_auth_header=mcp_auth_header,
+                        mcp_server_auth_headers=mcp_server_auth_headers,
+                        exc=e,
+                        bearer_presented=True,
+                    )
+            else:
+                try:
+                    validated_user_api_key_auth = await user_api_key_auth(api_key=litellm_api_key, request=request)
+                except (HTTPException, ProxyException) as exc:
+                    validated_user_api_key_auth = _admission_failure_fallback(
+                        request=request,
+                        request_route=request_route,
+                        mcp_servers=mcp_servers,
+                        mcp_auth_header=mcp_auth_header,
+                        mcp_server_auth_headers=mcp_server_auth_headers,
+                        exc=exc,
+                        bearer_presented=False,
+                    )
 
-        # Leak-defense (single chokepoint): a gateway admission credential (session bearer or bridge
-        # envelope) is NEVER a valid upstream token. Scrub it from EVERY egress context so no
-        # client-forwarded, OBO, or passthrough path can send it upstream for replay. Anchored to the
-        # credential SHAPE, so a legitimate upstream/passthrough token is forwarded unchanged.
-        raw_headers = dict(headers)
-        (
-            oauth2_headers,
-            raw_headers,
-            mcp_auth_header,
-            mcp_server_auth_headers,
-        ) = MCPRequestHandler._scrub_gateway_admission_credentials(
-            admitted=_is_mcp_admitted_user_subject(validated_user_api_key_auth),
-            oauth2_headers=oauth2_headers,
-            raw_headers=raw_headers,
-            mcp_auth_header=mcp_auth_header,
-            mcp_server_auth_headers=mcp_server_auth_headers,
-        )
+            # Leak-defense (single chokepoint): a gateway admission credential (session bearer or bridge
+            # envelope) is NEVER a valid upstream token. Scrub it from EVERY egress context so no
+            # client-forwarded, OBO, or passthrough path can send it upstream for replay. Anchored to the
+            # credential SHAPE, so a legitimate upstream/passthrough token is forwarded unchanged.
+            raw_headers = dict(headers)
+            (
+                oauth2_headers,
+                raw_headers,
+                mcp_auth_header,
+                mcp_server_auth_headers,
+            ) = MCPRequestHandler._scrub_gateway_admission_credentials(
+                admitted=_is_mcp_admitted_user_subject(validated_user_api_key_auth),
+                oauth2_headers=oauth2_headers,
+                raw_headers=raw_headers,
+                mcp_auth_header=mcp_auth_header,
+                mcp_server_auth_headers=mcp_server_auth_headers,
+            )
 
-        return (
-            validated_user_api_key_auth,
-            mcp_auth_header,
-            mcp_servers,
-            mcp_server_auth_headers,
-            oauth2_headers,
-            raw_headers,
-        )
+            return (
+                validated_user_api_key_auth,
+                mcp_auth_header,
+                mcp_servers,
+                mcp_server_auth_headers,
+                oauth2_headers,
+                raw_headers,
+            )
 
     @staticmethod
     def _is_gateway_admission_credential(value: str | None) -> bool:
@@ -1196,6 +1202,31 @@ class MCPRequestHandler:
             verbose_logger.warning("Failed to resolve per-team MCP rpm limits for admitted subject: %s", e)
             return None
 
+    @staticmethod
+    async def refresh_catalog_authority(auth: UserAPIKeyAuth | None) -> UserAPIKeyAuth | None:
+        from litellm.constants import LITELLM_PROXY_MASTER_KEY_ALIAS
+
+        if auth is None:
+            return None
+        refreshed = auth.model_copy()
+        if auth.mcp_admitted_user_subject and auth.user_id:
+            current = await MCPRequestHandler.reload_admitted_user(auth.user_id, requires_fresh_policy=True)
+            refreshed.object_permission = current.object_permission
+            refreshed.object_permission_id = current.object_permission_id
+            refreshed.user_role = current.user_role
+            refreshed.org_id = current.org_id
+        elif auth.via_virtual_key and auth.api_key and auth.api_key != LITELLM_PROXY_MASTER_KEY_ALIAS:
+            current = await MCPRequestHandler._reload_admitted_key(auth.api_key, check_db_only=True)
+            refreshed.object_permission = current.object_permission
+            refreshed.object_permission_id = current.object_permission_id
+            refreshed.team_id = current.team_id
+            refreshed.org_id = current.org_id
+            refreshed.project_id = current.project_id
+            refreshed.user_id = current.user_id
+            refreshed.access_group_ids = current.access_group_ids
+        refreshed.requires_fresh_policy = True
+        return refreshed
+
     @staticmethod
     async def _reload_admitted_key(key_hash: str, *, check_db_only: bool = False) -> UserAPIKeyAuth:
         """Reload the live key record an admitted envelope references and re-check live policy.
@@ -1239,6 +1270,8 @@ class MCPRequestHandler:
         if not MCPRequestHandler._admitted_key_is_active(key_object):
             raise HTTPException(status_code=401, detail="Invalid or expired credential")
         await MCPRequestHandler._reject_if_admitted_owner_scim_deactivated(key_object)
+        key_object.api_key = key_hash
+        key_object.via_virtual_key = True
         return key_object
 
     @staticmethod
@@ -1613,9 +1646,13 @@ class MCPRequestHandler:
             # Get allowed servers from key and team
             allowed_mcp_servers_for_key = await MCPRequestHandler._get_allowed_mcp_servers_for_key(user_api_key_auth)
 
-            # The key explicitly opted out of every MCP server. This overrides
-            # team inheritance and additive grants (mirrors no-default-models).
-            if SpecialMCPServerNames.no_mcp_servers.value in allowed_mcp_servers_for_key:
+            # Only an explicit opt-out overrides additive grants. An empty group
+            # scope uses the same marker to restrict inheritance below.
+            if SpecialMCPServerNames.no_mcp_servers.value in allowed_mcp_servers_for_key and (
+                user_api_key_auth is None
+                or (permission := await MCPRequestHandler._key_object_permission_hydrated(user_api_key_auth)) is None
+                or SpecialMCPServerNames.no_mcp_servers.value in (permission.mcp_servers or [])
+            ):
                 return MCPServerAccess(server_ids=(), scope="scoped")
 
             allowed_mcp_servers_for_team = await MCPRequestHandler._get_allowed_mcp_servers_for_team(user_api_key_auth)
@@ -1742,7 +1779,7 @@ class MCPRequestHandler:
 
             declares_key_mcp_scope: Final = getattr(key_object_permission, "mcp_servers", None) is not None
             return MCPServerAccess(
-                server_ids=tuple(set(allowed_mcp_servers)),
+                server_ids=tuple(set(allowed_mcp_servers) - {SpecialMCPServerNames.no_mcp_servers.value}),
                 scope=(
                     "scoped"
                     if has_lower_level_mcp_restrictions or org_restricts or declares_key_mcp_scope
@@ -2543,6 +2580,20 @@ class MCPRequestHandler:
             verbose_logger.warning("Failed to get key access group MCP server grants: %s", e)
             return []
 
+    @staticmethod
+    def _server_grants_with_group_scope(
+        servers: AbstractSet[str],
+        permission: LiteLLM_ObjectPermissionTable,
+    ) -> AbstractSet[str]:
+        """Keep a configured empty group scope distinct from an unrestricted level.
+
+        Combine same-level grants first; the existing zero-server marker prevents
+        inheritance and ceiling substitution without discarding independent grants.
+        """
+        if servers or not permission.mcp_access_groups:
+            return servers
+        return {SpecialMCPServerNames.no_mcp_servers.value}
+
     @staticmethod
     async def _get_allowed_mcp_servers_for_key(
         user_api_key_auth: UserAPIKeyAuth | None = None,
@@ -2625,7 +2676,7 @@ class MCPRequestHandler:
 
             # Combine all lists
             all_servers: Final = direct_mcp_servers + access_group_servers + tool_perm_servers + toolset_servers
-            return list(set(all_servers))
+            return list(MCPRequestHandler._server_grants_with_group_scope(set(all_servers), key_object_permission))
         except Exception as e:
             verbose_logger.warning("Failed to get allowed MCP servers for key: %s", e)
             return []
@@ -2698,7 +2749,7 @@ class MCPRequestHandler:
         team_access_group_servers: list[str],
         *,
         requires_fresh_policy: bool = False,
-    ) -> set[str]:
+    ) -> AbstractSet[str]:
         """The raw MCP-server set a team grants (before any org ceiling): its object_permission (direct
         ``mcp_servers``, the ``all_proxy_servers`` sentinel → the full registry, legacy access groups,
         tool-perm-referenced servers, toolset-referenced servers) unioned with its unified
@@ -2719,13 +2770,14 @@ class MCPRequestHandler:
         toolset_grants: Final = await MCPRequestHandler._toolset_tool_permissions(
             object_permissions, requires_fresh_policy=requires_fresh_policy
         )
-        return (
+        servers: Final = (
             set(global_mcp_server_manager.expand_permission_list(object_permissions.mcp_servers or []))
             | set(legacy_access_group_servers)
             | set(global_mcp_server_manager.expand_tool_permissions(object_permissions.mcp_tool_permissions).keys())
             | toolset_grants.keys()
             | set(team_access_group_servers)
         )
+        return MCPRequestHandler._server_grants_with_group_scope(servers, object_permissions)
 
     @staticmethod
     async def _allowed_mcp_servers_for_single_team(
@@ -2935,7 +2987,7 @@ class MCPRequestHandler:
             all_servers: Final = tuple(
                 {*direct_mcp_servers, *access_group_servers, *tool_perm_servers, *toolset_grants}
             )
-            return list(set(all_servers))
+            return list(MCPRequestHandler._server_grants_with_group_scope(set(all_servers), object_permissions))
         except Exception as e:
             # None = ceiling UNRESOLVED, distinct from [] = org places no restriction. Collapsing them
             # let a DB fault silently drop a ceiling; the caller picks fail-open/closed from this signal.
@@ -3033,7 +3085,7 @@ class MCPRequestHandler:
 
             # Combine all lists
             all_servers: Final = direct_mcp_servers + access_group_servers + tool_perm_servers
-            return list(set(all_servers))
+            return list(MCPRequestHandler._server_grants_with_group_scope(set(all_servers), object_permission))
         except Exception as e:
             verbose_logger.warning("Failed to get allowed MCP servers for end_user: %s", e)
             return []
@@ -3130,6 +3182,8 @@ class MCPRequestHandler:
                 ttl=get_management_object_ttl(user_api_key_cache),
             )
             return object_permission_id
+        except UserNotFoundError:
+            return None
         except Exception as e:  # noqa: BLE001  # Legacy callers retain their existing optional user-ceiling behavior
             if check_db_only:
                 raise HTTPException(503, "User policy is unavailable") from e
@@ -3168,7 +3222,12 @@ class MCPRequestHandler:
             toolset_grants: Final = await MCPRequestHandler._toolset_tool_permissions(
                 object_permissions, requires_fresh_policy=fresh
             )
-            return tuple({*direct_mcp_servers, *access_group_servers, *tool_perm_servers, *toolset_grants})
+            return tuple(
+                MCPRequestHandler._server_grants_with_group_scope(
+                    {*direct_mcp_servers, *access_group_servers, *tool_perm_servers, *toolset_grants},
+                    object_permissions,
+                )
+            )
         except Exception as e:  # noqa: BLE001  # any resolution fault is an unresolved ceiling, never "no ceiling"
             verbose_logger.warning("Failed to get allowed MCP servers for user: %s", e)
             return None
@@ -3515,7 +3574,12 @@ class MCPRequestHandler:
                 obj_perm, requires_fresh_policy=user_api_key_auth.requires_fresh_policy
             )
             inline_tools: Final = global_mcp_server_manager.expand_tool_permissions(obj_perm.mcp_tool_permissions)
-            return list({*expanded_direct_servers, *access_group_servers, *toolset_grants, *inline_tools})
+            return list(
+                MCPRequestHandler._server_grants_with_group_scope(
+                    {*expanded_direct_servers, *access_group_servers, *toolset_grants, *inline_tools},
+                    obj_perm,
+                )
+            )
         except Exception as e:
             if managed_agent_policy(user_api_key_auth) is not None or isinstance(e, UnloadableEntitlementError):
                 raise
@@ -3638,7 +3702,7 @@ class MCPRequestHandler:
         requires_fresh_policy: bool = False,
     ) -> list[str]:
         """
-        Resolve MCP access groups to server IDs by querying BOTH the MCP server table (DB) AND config-loaded servers.
+        Resolve MCP access groups against the operation snapshot, or database and config outside an operation.
         ``requires_fresh_policy`` reads the writer and propagates a read fault instead of resolving to no servers.
         """
         from litellm.proxy.proxy_server import prisma_client
@@ -3649,6 +3713,10 @@ class MCPRequestHandler:
                 global_mcp_server_manager,
             )
 
+            snapshot: Final = global_mcp_server_manager.catalog.current()
+            if snapshot is not None:
+                return list(MCPRequestHandler._get_config_server_ids_for_access_groups(snapshot.servers, access_groups))
+
             # Use the new helper for config-loaded servers
             server_ids: Final = MCPRequestHandler._get_config_server_ids_for_access_groups(
                 global_mcp_server_manager.config_mcp_servers, access_groups

litellm/proxy/_experimental/mcp_server/byok_oauth_endpoints.py

@@ -25,6 +25,7 @@ from fastapi import APIRouter, Depends, Form, HTTPException, Request
 from fastapi.responses import HTMLResponse, JSONResponse, RedirectResponse
 
 from litellm._logging import verbose_proxy_logger
+from litellm.proxy._experimental.mcp_server.catalog import public_catalog_operation
 from litellm.proxy._experimental.mcp_server.db import store_user_credential
 from litellm.proxy._experimental.mcp_server.oauth_utils import (
     BYOK_RESOURCE_METADATA_PATH,
@@ -738,6 +739,7 @@ async def byok_protected_resource_metadata(request: Request) -> JSONResponse:
 
 
 @router.get("/v1/mcp/oauth/authorize", include_in_schema=False)
+@public_catalog_operation
 async def byok_authorize_get(
     request: Request,
     client_id: str | None = None,
@@ -778,7 +780,7 @@ async def byok_authorize_get(
                 global_mcp_server_manager,
             )
 
-            registry: Final = global_mcp_server_manager.get_registry()
+            registry: Final = await global_mcp_server_manager.catalog.list()
             if server_id in registry:
                 srv: Final = registry[server_id]
                 server_name = srv.server_name or srv.name

litellm/proxy/_experimental/mcp_server/contracts.py

@@ -1,19 +1,41 @@
+from __future__ import annotations
+
 from collections.abc import Mapping
 from copy import deepcopy
 from dataclasses import dataclass, field
 from datetime import datetime
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Final, Literal, Protocol
+from typing import TYPE_CHECKING, Final, Literal, Protocol, TypeAlias
 
 from litellm.proxy._experimental.mcp_server.tool_outcome import WireCompat
 from litellm.proxy._types import UserAPIKeyAuth
 from litellm.types.mcp_server.mcp_server_manager import MCPServer
 
 if TYPE_CHECKING:
+    from mcp.types import (
+        ListPromptsRequest,
+        ListPromptsResult,
+        ListResourcesRequest,
+        ListResourcesResult,
+        ListResourceTemplatesRequest,
+        ListResourceTemplatesResult,
+        ListToolsRequest,
+        ListToolsResult,
+    )
+
+    CatalogListRequest: TypeAlias = (
+        ListToolsRequest | ListPromptsRequest | ListResourcesRequest | ListResourceTemplatesRequest
+    )
+    CatalogListResult: TypeAlias = (
+        ListToolsResult | ListPromptsResult | ListResourcesResult | ListResourceTemplatesResult
+    )
+
     from litellm.proxy._experimental.mcp_server.server_resolution import ResolvedMCPServer
 
 
 class TargetCatalog(Protocol):
+    async def list(self, context: OperationContext, request: CatalogListRequest) -> CatalogListResult: ...
+
     async def resolve(
         self,
         server_id: str,
@@ -23,7 +45,7 @@ class TargetCatalog(Protocol):
         not_found_detail: Mapping[str, str],
         forbidden_detail: Mapping[str, str],
         non_admin_missing: Literal["not_found", "forbidden"],
-    ) -> "ResolvedMCPServer": ...
+    ) -> ResolvedMCPServer: ...
 
 
 def copy_caller(auth: UserAPIKeyAuth | None) -> UserAPIKeyAuth | None:

litellm/proxy/_experimental/mcp_server/db.py

@@ -42,6 +42,7 @@ from litellm.proxy.common_utils.encrypt_decrypt_utils import (
     encrypt_value_helper,
 )
 from litellm.proxy.utils import PrismaClient
+from litellm.repositories.config_repository import ConfigRepository
 from litellm.repositories.object_permission_repository import ObjectPermissionRepository
 from litellm.repositories.prisma_protocols import TableActions
 from litellm.repositories.table_repositories import (
@@ -723,6 +724,20 @@ async def _db_find_mcp_server_row(
     return await _mcp_server_table_actions(prisma_client).find_unique(where={"server_id": server_id})
 
 
+MCP_CATALOG_REVISION_PARAM_NAME: Final = "mcp_catalog"
+
+
+async def get_mcp_catalog_revision(prisma_client: PrismaClient) -> int | None:
+    """The ``LiteLLM_Config`` revision the MCP server table trigger last published, or None when
+    no write has ever bumped it (or the trigger is not installed), meaning always reload."""
+    row: Final = await ConfigRepository(prisma_client, use_writer=True).table.find_unique(
+        where={"param_name": MCP_CATALOG_REVISION_PARAM_NAME}
+    )
+    if row is None:
+        return None
+    return int(row.reload_revision or 0)
+
+
 async def _db_update_mcp_server_row(
     prisma_client: PrismaClient,
     server_id: str,
@@ -853,6 +868,15 @@ async def get_all_mcp_servers(
     return list(_readable_mcp_servers(mcp_servers))
 
 
+async def get_runtime_mcp_server_rows(
+    prisma_client: PrismaClient,
+) -> Sequence["prisma_db_models.LiteLLM_MCPServerTable"]:
+    where: Final[prisma_db_types.LiteLLM_MCPServerTableWhereInput] = {
+        "OR": [{"approval_status": None}, {"approval_status": {"in": ["active", "approved"]}}]
+    }
+    return await MCPServerRepository(prisma_client, use_writer=True).table.find_many(where=where)
+
+
 async def get_mcp_server(prisma_client: PrismaClient, server_id: str) -> LiteLLM_MCPServerTable | None:
     """
     Returns the matching mcp server from the db iff exists

litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py

@@ -37,6 +37,7 @@ from litellm.proxy._experimental.mcp_server.bridge_token_flow import (
     can_store_oauth_credential,
     oauth_authorization_uses_gateway_credential,
 )
+from litellm.proxy._experimental.mcp_server.catalog import public_catalog_operation
 from litellm.proxy._experimental.mcp_server.faults import (
     CallerRejected,
     CredentialSource,
@@ -1894,7 +1895,7 @@ async def resolve_ephemeral_dcr_client(
 def _register_flow_needed_endpoint(mcp_server: MCPServer) -> str | None:
     """The register flow's deferred-discovery join gate. A DCR bridge with no admin-configured
     client can only register callers through the upstream's registration endpoint
-    (``_oauth_endpoints_unresolved`` keeps its discovery slot armed for exactly this shape), so
+    (``oauth_endpoints_unresolved`` keeps its discovery slot armed for exactly this shape), so
     the flow must keep joining discovery while registration is still missing instead of silently
     degrading to the dummy short-circuit. Every other shape only needs the authorization url."""
     if mcp_server.is_dcr_bridge and not mcp_server.client_id and mcp_server.effective_registration_url is None:
@@ -2020,6 +2021,7 @@ async def register_client_with_server(
 
 
 @router.get("/authorize/mcp-session")
+@public_catalog_operation
 async def authorize_mcp_session(
     request: Request,
     redirect_uri: str,
@@ -2045,6 +2047,7 @@ async def authorize_mcp_session(
 
 @router.get("/{mcp_server_name}/authorize")
 @router.get("/authorize")
+@public_catalog_operation
 async def authorize(
     request: Request,
     redirect_uri: str,
@@ -2083,9 +2086,11 @@ async def authorize(
             resource=resource,
         )
 
+    from litellm.proxy._experimental.mcp_server.mcp_server_manager import global_mcp_server_manager
+
     lookup_name: Final[str | None] = mcp_server_name or client_id
     client_ip: Final = IPAddressUtils.get_mcp_client_ip(request)
-    mcp_server = _resolve_mcp_server_by_name_or_id(lookup_name, client_ip) if lookup_name else None
+    mcp_server = await global_mcp_server_manager.catalog.resolve(lookup_name, client_ip) if lookup_name else None
     if mcp_server is None and mcp_server_name is None:
         mcp_server = _resolve_oauth2_server_for_root_endpoints(client_ip=client_ip)
     if mcp_server is None:
@@ -2119,6 +2124,7 @@ async def authorize(
 
 @router.post("/{mcp_server_name}/token")
 @router.post("/token")
+@public_catalog_operation
 async def token_endpoint(
     request: Request,
     grant_type: str = Form(...),
@@ -2212,6 +2218,7 @@ async def _vendor_credential_state(user_id: str, server_id: str) -> VendorCreden
 
 
 @router.get("/authorize/flow")
+@public_catalog_operation
 async def authorize_flow(request: Request, flow: str) -> Response:
     return await describe_connect_flow(
         request=request,
@@ -2223,6 +2230,7 @@ async def authorize_flow(request: Request, flow: str) -> Response:
 
 
 @router.post("/authorize/complete")
+@public_catalog_operation
 async def authorize_complete(
     request: Request,
     flow: str = Form(...),
@@ -2610,6 +2618,7 @@ def is_network_error(exc: Exception) -> bool:
     return isinstance(exc, httpx.TransportError)
 
 
+@public_catalog_operation
 async def _build_oauth_protected_resource_response(
     request: Request,
     mcp_server_name: str | None,
@@ -2873,6 +2882,7 @@ async def oauth_authorization_server_aggregate(request: Request):
 # Standard MCP pattern: /.well-known/oauth-protected-resource/mcp/{server_name}
 # This is the pattern expected by standard MCP clients (mcp-inspector, VSCode Copilot)
 @router.get(f"/.well-known/oauth-protected-resource{well_known_root_suffix()}/mcp/{{mcp_server_name}}")
+@public_catalog_operation
 async def oauth_protected_resource_mcp_standard(request: Request, mcp_server_name: str):
     """
     OAuth protected resource discovery endpoint using standard MCP URL pattern.
@@ -2893,6 +2903,7 @@ async def oauth_protected_resource_mcp_standard(request: Request, mcp_server_nam
 # LiteLLM legacy pattern: /.well-known/oauth-protected-resource/{server_name}/mcp
 # Kept for backward compatibility with existing deployments
 @router.get(f"/.well-known/oauth-protected-resource{well_known_root_suffix()}/{{mcp_server_name}}/mcp")
+@public_catalog_operation
 async def oauth_protected_resource_mcp(request: Request, mcp_server_name: str | None = None):
     """
     OAuth protected resource discovery endpoint using LiteLLM legacy URL pattern.
@@ -2916,12 +2927,7 @@ def _build_oauth_authorization_server_response(
     *,
     issuer_path: str | None = None,
 ) -> dict:
-    """Build OAuth authorization server metadata response (gateway-as-AS shape).
-
-    Synchronous because the body only does dict construction and synchronous
-    registry lookups; unlike :func:`_build_oauth_protected_resource_response`
-    it does not need to await any upstream IO.
-    """
+    """Build OAuth authorization server metadata response (gateway-as-AS shape)."""
     request_base_url: Final = get_request_base_url(request)
     client_ip: Final = IPAddressUtils.get_mcp_client_ip(request)
     explicitly_named: Final = mcp_server_name is not None
@@ -2969,6 +2975,7 @@ def _build_oauth_authorization_server_response(
 
 # Standard MCP pattern: /.well-known/oauth-authorization-server/mcp/{server_name}
 @router.get(f"/.well-known/oauth-authorization-server{well_known_root_suffix()}/mcp/{{mcp_server_name}}")
+@public_catalog_operation
 async def oauth_authorization_server_mcp_standard(request: Request, mcp_server_name: str):
     """
     OAuth authorization server discovery endpoint using standard MCP URL pattern.
@@ -2986,6 +2993,7 @@ async def oauth_authorization_server_mcp_standard(request: Request, mcp_server_n
 # LiteLLM legacy pattern and root endpoint
 @router.get(f"/.well-known/oauth-authorization-server{well_known_root_suffix()}/{{mcp_server_name}}")
 @router.get("/.well-known/oauth-authorization-server")
+@public_catalog_operation
 async def oauth_authorization_server_mcp(request: Request, mcp_server_name: str | None = None):
     """
     OAuth authorization server discovery endpoint.
@@ -3059,6 +3067,7 @@ async def jwks_json(request: Request):
 
 # Additional legacy pattern support
 @router.get(f"/.well-known/oauth-authorization-server{well_known_root_suffix()}/{{mcp_server_name}}/mcp")
+@public_catalog_operation
 async def oauth_authorization_server_legacy(request: Request, mcp_server_name: str):
     """
     OAuth authorization server discovery for legacy /{server_name}/mcp pattern.
@@ -3072,6 +3081,7 @@ async def oauth_authorization_server_legacy(request: Request, mcp_server_name: s
 
 @router.post("/{mcp_server_name}/register")
 @router.post("/register")
+@public_catalog_operation
 async def register_client(request: Request, mcp_server_name: str | None = None):
     # Get the correct base URL considering X-Forwarded-* headers
     request_base_url: Final = get_request_base_url(request)
@@ -3080,46 +3090,44 @@ async def register_client(request: Request, mcp_server_name: str | None = None):
     data: Final[dict] = {**request_data}
     client_redirect_uris: Final = client_supplied_redirect_uris(data.get("redirect_uris"))
 
-    dummy_return: Final = {
-        "client_id": mcp_server_name or "dummy_client",
-        "client_secret": "dummy",
-        "redirect_uris": client_redirect_uris or [f"{request_base_url}/callback"],
-    }
-    client_ip: Final = IPAddressUtils.get_mcp_client_ip(request)
-    if not mcp_server_name:
-        # A real DCR request carries redirect_uris (RFC 7591): route it to the aggregate DCR
-        # endpoint the aggregate authorization-server metadata advertises. A single-server
-        # deployment registers at /{server}/register instead (its bare-origin discovery
-        # advertises that), so this does not affect it. A request without redirect_uris is not
-        # a DCR request, so the legacy single-server-or-dummy fallback is kept for it.
-        if data.get("redirect_uris"):
-            return await register_aggregate_client(
-                request=request, request_body=data, token_exchange_available=token_exchange_available()
-            )
-        resolved: Final = _resolve_oauth2_server_for_root_endpoints(client_ip=client_ip)
-        if resolved:
-            return await register_client_with_server(
-                request=request,
-                mcp_server=resolved,
-                client_name=data.get("client_name", ""),
-                grant_types=data.get("grant_types", []),
-                response_types=data.get("response_types", []),
-                token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
-                fallback_client_id=resolved.server_name or resolved.name,
-                client_redirect_uris=client_redirect_uris,
-            )
-        return dummy_return
+    if not mcp_server_name and data.get("redirect_uris"):
+        return await register_aggregate_client(
+            request=request, request_body=data, token_exchange_available=token_exchange_available()
+        )
+    from litellm.proxy._experimental.mcp_server.mcp_server_manager import global_mcp_server_manager
 
-    mcp_server: Final = _resolve_mcp_server_by_name_or_id(mcp_server_name, client_ip)
-    if mcp_server is None:
-        return dummy_return
-    return await register_client_with_server(
-        request=request,
-        mcp_server=mcp_server,
-        client_name=data.get("client_name", ""),
-        grant_types=data.get("grant_types", []),
-        response_types=data.get("response_types", []),
-        token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
-        fallback_client_id=mcp_server_name,
-        client_redirect_uris=client_redirect_uris,
-    )
+    async with global_mcp_server_manager.catalog.operation():
+        dummy_return: Final = {
+            "client_id": mcp_server_name or "dummy_client",
+            "client_secret": "dummy",
+            "redirect_uris": client_redirect_uris or [f"{request_base_url}/callback"],
+        }
+        client_ip: Final = IPAddressUtils.get_mcp_client_ip(request)
+        if not mcp_server_name:
+            resolved: Final = _resolve_oauth2_server_for_root_endpoints(client_ip=client_ip)
+            if resolved:
+                return await register_client_with_server(
+                    request=request,
+                    mcp_server=resolved,
+                    client_name=data.get("client_name", ""),
+                    grant_types=data.get("grant_types", []),
+                    response_types=data.get("response_types", []),
+                    token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
+                    fallback_client_id=resolved.server_name or resolved.name,
+                    client_redirect_uris=client_redirect_uris,
+                )
+            return dummy_return
+
+        mcp_server: Final = _resolve_mcp_server_by_name_or_id(mcp_server_name, client_ip)
+        if mcp_server is None:
+            return dummy_return
+        return await register_client_with_server(
+            request=request,
+            mcp_server=mcp_server,
+            client_name=data.get("client_name", ""),
+            grant_types=data.get("grant_types", []),
+            response_types=data.get("response_types", []),
+            token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
+            fallback_client_id=mcp_server_name,
+            client_redirect_uris=client_redirect_uris,
+        )

litellm/proxy/_experimental/mcp_server/faults/list_outcomes.py

@@ -63,6 +63,7 @@ domain per the MCP spec's ``_meta`` key format so it cannot collide with spec-re
 class AggregateToolListing(NamedTuple):
     tools: list[MCPTool]
     outcomes: dict[str, ServerOutcome]
+    next_cursor: str | None = None
 
 
 def _iter_upstream_responses(exc: BaseException) -> Iterator[httpx.Response | httpx2.Response]:

litellm/proxy/_experimental/mcp_server/gateway_dcr_flow.py

@@ -56,6 +56,7 @@ from typing_extensions import NotRequired, ReadOnly, TypedDict, assert_never
 from litellm._internal_context import with_service_target
 from litellm._logging import verbose_logger
 from litellm.caching.caching import DualCache
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, global_manager
 from litellm.proxy._experimental.mcp_server.oauth_utils import (
     TOKEN_NO_CACHE_HEADERS,
     canonical_resource_uri,
@@ -125,6 +126,9 @@ _CLAIM_TTL_BUFFER_SECONDS: Final = 60
 _USED_CODE_CACHE_PREFIX: Final = "mcp_gateway_dcr_code_used:"
 _USED_FLOW_CACHE_PREFIX: Final = "mcp_gateway_dcr_flow_used:"
 _USED_REFRESH_CACHE_PREFIX: Final = "mcp_gateway_dcr_refresh_used:"
+_REFRESH_REPLAYED_DESCRIPTION: Final = "the refresh token was already used"
+_REVOKED_REFRESH_FAMILY_CACHE_PREFIX: Final = "mcp_gateway_dcr_refresh_family_revoked:"
+_REFRESH_FAMILY_REVOKED_DESCRIPTION: Final = "the refresh token was revoked"
 
 MAX_REDIRECT_URIS: Final = 4
 MAX_REDIRECT_URI_LENGTH: Final = 256
@@ -343,6 +347,41 @@ def _oauth_error(status_code: int, error: str, description: str) -> JSONResponse
     )
 
 
+class SessionSigning(LiteLLMBaseModel):
+    """The key material a token verb mints and opens session tokens under, resolved once per
+    call together with the instant it serves, so every token the call issues or checks agrees
+    on ``now``."""
+
+    model_config = ConfigDict(frozen=True)
+    keys: SessionSigningKeys
+    now: datetime
+
+
+def resolve_session_signing(master_key: str | None, caller: str) -> SessionSigning | Response:
+    """A token verb's precondition: the proxy has a master key and the session signing
+    configuration validates. Either defect is an operator fault the verb answers as a 500
+    (never a 4xx the client would treat as its own), logged under ``caller``."""
+    if master_key is None:
+        verbose_logger.error("%s rejected: no master_key configured", caller)
+        return _oauth_error(500, "server_error", "the gateway has no master key configured")
+    keys: Final = active_session_signing_keys(master_key)
+    if isinstance(keys, SessionSigningConfigError):
+        verbose_logger.error("%s rejected: %s", caller, keys.detail)
+        return _oauth_error(500, "server_error", "the gateway session signing configuration is invalid")
+    return SessionSigning(keys=keys, now=datetime.now(timezone.utc))
+
+
+def _refresh_claim_key(jti: str) -> str:
+    return f"{_USED_REFRESH_CACHE_PREFIX}{jti}"
+
+
+def _refresh_family_key(family: str) -> str:
+    return f"{_REVOKED_REFRESH_FAMILY_CACHE_PREFIX}{family}"
+
+
+_REFRESH_CLAIM_TTL_SECONDS: Final = SESSION_REFRESH_TTL_SECONDS + _CLAIM_TTL_BUFFER_SECONDS
+
+
 def _seal(prefix: str, payload: BaseModel) -> str:
     """Serialized ``exclude_none`` for the same reason session JWTs are minted that way: an
     optional claim that is unset never reaches the wire, so during a rolling deploy a blob
@@ -774,6 +813,7 @@ def _open_flow_for(
     return flow
 
 
+@catalog_operation(global_manager)
 async def _flow_target(
     flow: _ConnectFlow, lookup_server_reachability: LookupServerReachability
 ) -> tuple[Literal["unscoped", "interactive", "m2m", "stale"], MCPServer | None]:
@@ -1054,13 +1094,17 @@ class _SingleUseGuard:
     async def peek(self, key: str) -> Literal["unclaimed", "claimed", "unavailable"]:
         """Read-only view of a single-use marker, resolved against the same shared authority as
         :meth:`claim` so introspection observes exactly the record redemption and revocation wrote.
-        A backend fault is ``"unavailable"`` (fail closed) rather than a guess either way."""
+        A backend fault is ``"unavailable"`` (fail closed) rather than a guess either way, which is why
+        the read goes to the Redis client itself: the cache wrapper's ``async_get_cache`` turns a fault
+        into ``None``, and ``None`` here would pass as unclaimed. The key is namespaced exactly as the
+        wrapper namespaces every write, or a ``namespace`` configured under ``coordination_redis`` or
+        ``cache_params`` would hide the marker."""
         from litellm.proxy.proxy_server import redis_usage_cache  # noqa: PLC0415  # circular import at module load
 
         redis_cache: Final = redis_usage_cache or getattr(self._cache, "redis_cache", None)
         if redis_cache is not None:
             try:
-                value = await redis_cache.async_get_cache(key)
+                value = await redis_cache.init_async_client().get(redis_cache.check_and_fix_namespace(key=key))
             except Exception as e:  # noqa: BLE001  # ANY Redis fault fails the read closed
                 verbose_logger.warning("mcp gateway single-use peek: shared cache backend unavailable: %s", e)
                 return "unavailable"
@@ -1069,9 +1113,28 @@ class _SingleUseGuard:
         return "unclaimed" if local is None else "claimed"
 
 
-def _session_token_pair(principal: SessionPrincipal, keys: SessionSigningKeys, now: datetime) -> Response:
+async def _family_refusal(guard: _SingleUseGuard, family: str | None) -> Response | None:
+    """A refresh token whose rotation chain a revocation ended is refused before anything is
+    minted; a backend that cannot say answers 503."""
+    if family is None:
+        return None
+    peeked: Final = await guard.peek(_refresh_family_key(family))
+    match peeked:
+        case "unclaimed":
+            return None
+        case "claimed":
+            return _oauth_error(400, "invalid_grant", _REFRESH_FAMILY_REVOKED_DESCRIPTION)
+        case "unavailable":
+            return _oauth_error(503, "temporarily_unavailable", _CLAIM_UNAVAILABLE_DESCRIPTION)
+        case _:
+            assert_never(peeked)
+
+
+def _session_token_pair(
+    principal: SessionPrincipal, keys: SessionSigningKeys, now: datetime, family: str | None
+) -> Response:
     access: Final = mint_session_token(principal, keys, now)
-    refresh: Final = mint_session_refresh_token(principal, keys, now)
+    refresh: Final = mint_session_refresh_token(principal, keys, now, family=family)
     if not isinstance(access, MintedSessionToken) or not isinstance(refresh, MintedSessionToken):
         return _oauth_error(500, "server_error", "failed to mint the session credential")
     return JSONResponse(
@@ -1096,20 +1159,21 @@ class _ProxyCredentialTokenResponse(TypedDict):
     issued_token_type: NotRequired[ReadOnly[_IssuedTokenType]]
 
 
-def _proxy_credential_response(
+def proxy_credential_response(
     minted: MintedProxyCredential,
     principal: SessionPrincipal,
-    keys: SessionSigningKeys,
-    now: datetime,
+    signing: SessionSigning,
     issued_token_type: _IssuedTokenType | None = None,
+    family: str | None = None,
 ) -> Response:
     """The proxy-API token response: the access token is the very credential ``lite
     login`` stores (accepted on every proxy route with user and team attribution), and
     the refresh token is a gateway-sealed rotating token bound to the team the credential
-    was minted for, so a renewal keeps the team the user consented to. A token exchange
-    also states ``issued_token_type``, which RFC 8693 section 2.2.1 requires."""
+    was minted for, so a renewal keeps the team the user consented to, and to the rotation
+    chain (``family``) the presented token belonged to. A token exchange also states
+    ``issued_token_type``, which RFC 8693 section 2.2.1 requires."""
     bound_principal: Final = principal.model_copy(update=MappingProxyType({"team_id": minted.team_id}))
-    refresh: Final = mint_session_refresh_token(bound_principal, keys, now)
+    refresh: Final = mint_session_refresh_token(bound_principal, signing.keys, signing.now, family=family)
     if not isinstance(refresh, MintedSessionToken):
         return _oauth_error(500, "server_error", "failed to mint the session credential")
     credential: Final[_ProxyCredentialTokenResponse] = {
@@ -1160,7 +1224,7 @@ def _mint_failure_response(failure: ProxyCredentialMintFailure) -> Response:
             )
         case "team_required":
             return _oauth_error(
-                400, "invalid_grant", "this user belongs to a team; sign in again and pick the team for this credential"
+                400, "invalid_grant", "this user belongs to a team; sign in again to get a credential issued for it"
             )
         case "unavailable" | "faulted" | "unresolvable" | "no_active_key":
             return _reload_failure_response(failure)
@@ -1205,19 +1269,13 @@ async def aggregate_token(
     with that audience, and the RFC 8693 token exchange that turns an IdP token straight
     into the proxy-API credential. Every path re-validates the litellm user live before
     minting, so a deactivated user cannot obtain or renew a session."""
-    if master_key is None:
-        verbose_logger.error("mcp_gateway_dcr token grant rejected: no master_key configured")
-        return _oauth_error(500, "server_error", "the gateway has no master key configured")
-    keys: Final = active_session_signing_keys(master_key)
-    if isinstance(keys, SessionSigningConfigError):
-        verbose_logger.error("mcp_gateway_dcr token grant rejected: %s", keys.detail)
-        return _oauth_error(500, "server_error", "the gateway session signing configuration is invalid")
-    now: Final = datetime.now(timezone.utc)
+    signing: Final = resolve_session_signing(master_key, "mcp_gateway_dcr token grant")
+    if isinstance(signing, Response):
+        return signing
     issue: Final = _GrantIssuer(
         request=request,
         resource=resource,
-        keys=keys,
-        now=now,
+        signing=signing,
         reload_user=reload_user,
         mint_proxy_credential=mint_proxy_credential,
         guard=_SingleUseGuard(cache),
@@ -1230,7 +1288,7 @@ async def aggregate_token(
             client_id=client_id,
             code_verifier=code_verifier,
             resource=resource,
-            now=now,
+            now=signing.now,
             issue=issue,
         )
     if grant_type == "refresh_token":
@@ -1239,8 +1297,7 @@ async def aggregate_token(
             refresh_token=refresh_token,
             client_id=client_id,
             resource=resource,
-            keys=keys,
-            now=now,
+            signing=signing,
             issue=issue,
         )
     if grant_type == TOKEN_EXCHANGE_GRANT_TYPE:
@@ -1259,6 +1316,44 @@ async def aggregate_token(
     )
 
 
+class _ProxyCredentialIssuer:
+    """The proxy-API tail every grant for that audience shares once its own proof has checked
+    out: refuse a rotation chain that was already ended, mint the live credential (which
+    revalidates the user and the team membership against the database), then claim the
+    single-use marker, ending the whole chain when the marker was already claimed. The claim
+    comes AFTER minting so a transient DB 503 or a membership refusal never burns a
+    still-valid grant, and it fails closed when it cannot be recorded."""
+
+    def __init__(
+        self, signing: SessionSigning, mint_proxy_credential: MintProxyCredential, guard: _SingleUseGuard
+    ) -> None:
+        self._signing: Final = signing
+        self._mint_proxy_credential: Final = mint_proxy_credential
+        self._guard: Final = guard
+
+    async def __call__(
+        self,
+        principal: SessionPrincipal,
+        claim_key: str,
+        claim_ttl_seconds: int,
+        replayed: str,
+        family: str | None = None,
+    ) -> Response:
+        ended: Final = await _family_refusal(self._guard, family)
+        if ended is not None:
+            return ended
+        minted: Final = await self._mint_proxy_credential(principal.user_id, principal.team_id)
+        if not isinstance(minted, MintedProxyCredential):
+            return _mint_failure_response(minted)
+        refusal: Final = _claim_refusal(
+            await self._guard.claim(claim_key, claim_ttl_seconds),
+            replayed=_oauth_error(400, "invalid_grant", replayed),
+        )
+        if refusal is not None:
+            return refusal
+        return proxy_credential_response(minted, principal, self._signing, family=family)
+
+
 class _GrantIssuer:
     """The tail every grant shares once its own proof (code + PKCE, or a refresh token)
     has checked out: revalidate the user live, claim the single-use marker, mint. The
@@ -1269,55 +1364,59 @@ class _GrantIssuer:
         self,
         request: Request,
         resource: str | None,
-        keys: SessionSigningKeys,
-        now: datetime,
+        signing: SessionSigning,
         reload_user: ReloadUser,
         mint_proxy_credential: MintProxyCredential,
         guard: _SingleUseGuard,
     ) -> None:
         self._request: Final = request
         self._resource: Final = resource
-        self._keys: Final = keys
-        self._now: Final = now
+        self._signing: Final = signing
         self._reload_user: Final = reload_user
         self._mint_proxy_credential: Final = mint_proxy_credential
         self._guard: Final = guard
+        self._proxy_credential: Final = _ProxyCredentialIssuer(signing, mint_proxy_credential, guard)
 
     async def __call__(
-        self, principal: SessionPrincipal, claim_key: str, claim_ttl_seconds: int, replayed: str
+        self,
+        principal: SessionPrincipal,
+        claim_key: str,
+        claim_ttl_seconds: int,
+        replayed: str,
+        family: str | None = None,
     ) -> Response:
         match principal.audience:
             case None:
-                return await self._issue_session_pair(principal, claim_key, claim_ttl_seconds, replayed)
+                return await self._issue_session_pair(principal, claim_key, claim_ttl_seconds, replayed, family)
             case "proxy_api":
-                return await self._issue_proxy_credential(principal, claim_key, claim_ttl_seconds, replayed)
+                return await self._issue_proxy_credential(principal, claim_key, claim_ttl_seconds, replayed, family)
             case _:
                 assert_never(principal.audience)
 
     async def _issue_session_pair(
-        self, principal: SessionPrincipal, claim_key: str, claim_ttl_seconds: int, replayed: str
+        self, principal: SessionPrincipal, claim_key: str, claim_ttl_seconds: int, replayed: str, family: str | None
     ) -> Response:
+        ended: Final = await _family_refusal(self._guard, family)
+        if ended is not None:
+            return ended
         failure: Final = await self._reload_user(principal.user_id)
         if failure is not None:
             return _reload_failure_response(failure)
-        refusal: Final = await self._claim_refusal(claim_key, claim_ttl_seconds, replayed)
+        refusal: Final = _claim_refusal(
+            await self._guard.claim(claim_key, claim_ttl_seconds),
+            replayed=_oauth_error(400, "invalid_grant", replayed),
+        )
         if refusal is not None:
             return refusal
-        return _session_token_pair(principal, self._keys, self._now)
+        return _session_token_pair(principal, self._signing.keys, self._signing.now, family)
 
     async def _issue_proxy_credential(
-        self, principal: SessionPrincipal, claim_key: str, claim_ttl_seconds: int, replayed: str
+        self, principal: SessionPrincipal, claim_key: str, claim_ttl_seconds: int, replayed: str, family: str | None
     ) -> Response:
         target_refusal: Final = self._proxy_api_target_refusal()
         if target_refusal is not None:
             return target_refusal
-        minted: Final = await self._mint_proxy_credential(principal.user_id, principal.team_id)
-        if not isinstance(minted, MintedProxyCredential):
-            return _mint_failure_response(minted)
-        refusal: Final = await self._claim_refusal(claim_key, claim_ttl_seconds, replayed)
-        if refusal is not None:
-            return refusal
-        return _proxy_credential_response(minted, principal, self._keys, self._now)
+        return await self._proxy_credential(principal, claim_key, claim_ttl_seconds, replayed, family)
 
     async def exchange(
         self, subject_token: str, client_id: str, exchange_subject_token: ExchangeSubjectToken
@@ -1337,20 +1436,13 @@ class _GrantIssuer:
         minted: Final = await self._mint_proxy_credential(principal.user_id, principal.team_id)
         if not isinstance(minted, MintedProxyCredential):
             return _mint_failure_response(minted)
-        return _proxy_credential_response(
-            minted, principal, self._keys, self._now, issued_token_type=ACCESS_TOKEN_TOKEN_TYPE
-        )
+        return proxy_credential_response(minted, principal, self._signing, issued_token_type=ACCESS_TOKEN_TOKEN_TYPE)
 
     def _proxy_api_target_refusal(self) -> Response | None:
         if self._resource is None or is_proxy_api_resource(self._request, self._resource):
             return None
         return _oauth_error(400, "invalid_target", "resource does not match the proxy API this grant was issued for")
 
-    async def _claim_refusal(self, claim_key: str, claim_ttl_seconds: int, replayed: str) -> Response | None:
-        return _claim_refusal(
-            await self._guard.claim(claim_key, claim_ttl_seconds), replayed=_oauth_error(400, "invalid_grant", replayed)
-        )
-
 
 async def _authorization_code_grant(
     request: Request,
@@ -1393,30 +1485,73 @@ async def _authorization_code_grant(
     )
 
 
+def _open_presented_refresh_token(
+    refresh_token: str | None, client_id: str, signing: SessionSigning
+) -> SessionRefreshOpened | Response:
+    if not refresh_token:
+        return _oauth_error(400, "invalid_request", "refresh_token is required")
+    opened: Final = open_session_refresh_bearer(refresh_token, signing.keys, signing.now, expected_client_id=client_id)
+    if not isinstance(opened, SessionRefreshOpened):
+        return _oauth_error(400, "invalid_grant", "the refresh token is invalid for this client")
+    return opened
+
+
 async def _refresh_token_grant(
     request: Request,
     refresh_token: str | None,
     client_id: str,
     resource: str | None,
-    keys: SessionSigningKeys,
-    now: datetime,
+    signing: SessionSigning,
     issue: _GrantIssuer,
 ) -> Response:
-    if not refresh_token:
-        return _oauth_error(400, "invalid_request", "refresh_token is required")
-    opened: Final = open_session_refresh_bearer(refresh_token, keys, now, expected_client_id=client_id)
-    if not isinstance(opened, SessionRefreshOpened):
-        return _oauth_error(400, "invalid_grant", "the refresh token is invalid for this client")
+    opened: Final = _open_presented_refresh_token(refresh_token, client_id, signing)
+    if isinstance(opened, Response):
+        return opened
     if _resource_conflicts_with_scope(request, resource, opened.principal.resource_server_id):
         return _oauth_error(400, "invalid_target", "resource does not match the scope this token was issued for")
     # Refresh-token rotation (OAuth 2.0 Security BCP section 4.13): the presented refresh token is
     # single-use, so a captured or replayed refresh token cannot mint a second pair after the
-    # legitimate holder rotated.
+    # legitimate holder rotated. A replay refuses only itself, never the chain (section 4.13.2's
+    # chain ending): Claude Code renews from its in-memory copy, so a second terminal on the same
+    # machine presents the token the first one already rotated, then recovers from the shared
+    # credential file, and the chain it recovers into has to be alive. Only a revocation ends it.
     return await issue(
         opened.principal,
-        claim_key=f"{_USED_REFRESH_CACHE_PREFIX}{opened.jti}",
-        claim_ttl_seconds=SESSION_REFRESH_TTL_SECONDS + _CLAIM_TTL_BUFFER_SECONDS,
-        replayed="the refresh token was already used",
+        claim_key=_refresh_claim_key(opened.jti),
+        claim_ttl_seconds=_REFRESH_CLAIM_TTL_SECONDS,
+        replayed=_REFRESH_REPLAYED_DESCRIPTION,
+        family=opened.family,
+    )
+
+
+async def refresh_proxy_credential(
+    refresh_token: str | None,
+    client_id: str,
+    master_key: str | None,
+    cache: DualCache,
+    mint_proxy_credential: MintProxyCredential,
+) -> Response:
+    """The refresh_token grant for a fixed public client the gateway never registered (the
+    Claude Code CLI, which presents no client_id of its own): the token must have been minted
+    for ``client_id`` with the proxy-API audience, the credential is re-minted live, and the
+    presented token rotates under the same single-use record the DCR flow burns, so one
+    revocation covers both front doors. The identity-only session pair is never issued here:
+    a token of that audience answers invalid_grant even when its client binding matches."""
+    signing: Final = resolve_session_signing(master_key, "mcp_gateway refresh grant")
+    if isinstance(signing, Response):
+        return signing
+    opened: Final = _open_presented_refresh_token(refresh_token, client_id, signing)
+    if isinstance(opened, Response):
+        return opened
+    if opened.principal.audience != PROXY_API_AUDIENCE:
+        return _oauth_error(400, "invalid_grant", "the refresh token is invalid for this client")
+    issue: Final = _ProxyCredentialIssuer(signing, mint_proxy_credential, _SingleUseGuard(cache))
+    return await issue(
+        opened.principal,
+        claim_key=_refresh_claim_key(opened.jti),
+        claim_ttl_seconds=_REFRESH_CLAIM_TTL_SECONDS,
+        replayed=_REFRESH_REPLAYED_DESCRIPTION,
+        family=opened.family,
     )
 
 
@@ -1448,7 +1583,8 @@ async def _token_exchange_grant(
 
 async def revoke_refresh_token(token: str, client_id: str, master_key: str | None, cache: DualCache) -> Response:
     """RFC 7009 revocation for the gateway's refresh tokens: burn the presented token's
-    ``jti`` so neither the holder nor a thief can rotate it again. Access tokens are
+    ``jti`` and the rotation chain it belongs to, so no rotation of it, whoever holds one,
+    mints again (section 2.1: the grant is revoked, not one token). Access tokens are
     stateless and expire on their own (the proxy-API credential within
     ``CLI_JWT_EXPIRATION_HOURS``), so per RFC 7009 section 2.2 an unrecognized or already
     dead token still answers 200; only an unknown client is refused. A live token whose
@@ -1457,20 +1593,28 @@ async def revoke_refresh_token(token: str, client_id: str, master_key: str | Non
     never happened."""
     if not is_gateway_dcr_client_id(client_id) or open_gateway_dcr_client(client_id) is None:
         return _oauth_error(401, "invalid_client", "unknown or malformed client_id")
-    if master_key is None:
-        verbose_logger.error("mcp_gateway_dcr revoke rejected: no master_key configured")
-        return _oauth_error(500, "server_error", "the gateway has no master key configured")
-    keys: Final = active_session_signing_keys(master_key)
-    if isinstance(keys, SessionSigningConfigError):
-        verbose_logger.error("mcp_gateway_dcr revoke rejected: %s", keys.detail)
-        return _oauth_error(500, "server_error", "the gateway session signing configuration is invalid")
-    now: Final = datetime.now(timezone.utc)
-    opened: Final = open_session_refresh_bearer(token, keys, now, expected_client_id=client_id)
+    return await revoke_session_refresh_token(token, client_id, master_key, cache)
+
+
+async def revoke_session_refresh_token(
+    token: str, client_id: str, master_key: str | None, cache: DualCache
+) -> Response:
+    """The client-agnostic half of RFC 7009 revocation, shared with the fixed public clients
+    the gateway never registered: burn the presented refresh token's ``jti`` and its rotation
+    chain when it was issued to ``client_id``, answer 200 for anything else (an access token,
+    a dead or foreign token, garbage), and 503 when a burn could not be recorded in the shared
+    backend. The chain marker is written first: a fault between the two writes then leaves
+    every token of the chain refused rather than a descendant still renewable, and the retry
+    the 503 asks for only has the presented ``jti`` left to burn."""
+    signing: Final = resolve_session_signing(master_key, "mcp_gateway revoke")
+    if isinstance(signing, Response):
+        return signing
+    opened: Final = open_session_refresh_bearer(token, signing.keys, signing.now, expected_client_id=client_id)
     if isinstance(opened, SessionRefreshOpened):
-        burned: Final = await _SingleUseGuard(cache).claim(
-            f"{_USED_REFRESH_CACHE_PREFIX}{opened.jti}", SESSION_REFRESH_TTL_SECONDS + _CLAIM_TTL_BUFFER_SECONDS
-        )
-        if burned == "unavailable":
+        guard: Final = _SingleUseGuard(cache)
+        ended: Final = await guard.claim(_refresh_family_key(opened.family), _REFRESH_CLAIM_TTL_SECONDS)
+        burned: Final = await guard.claim(_refresh_claim_key(opened.jti), _REFRESH_CLAIM_TTL_SECONDS)
+        if "unavailable" in (burned, ended):
             return _oauth_error(503, "temporarily_unavailable", _CLAIM_UNAVAILABLE_DESCRIPTION)
     return Response(content="{}", media_type="application/json", headers=TOKEN_NO_CACHE_HEADERS)
 
@@ -1542,10 +1686,12 @@ async def introspect_gateway_token(
     if not isinstance(opened, OpenedSessionToken):
         return _inactive_introspection_response()
     if opened.kind == "session_refresh":
-        peeked: Final = await _SingleUseGuard(cache).peek(f"{_USED_REFRESH_CACHE_PREFIX}{opened.jti}")
-        if peeked == "unavailable":
+        guard: Final = _SingleUseGuard(cache)
+        used: Final = await guard.peek(_refresh_claim_key(opened.jti))
+        ended: Final = await guard.peek(_refresh_family_key(opened.family))
+        if "unavailable" in (used, ended):
             return _oauth_error(503, "temporarily_unavailable", _CLAIM_UNAVAILABLE_DESCRIPTION)
-        if peeked == "claimed":
+        if "claimed" in (used, ended):
             return _inactive_introspection_response()
     failure: Final = await reload_user(opened.principal.user_id)
     if failure == "unavailable" or failure == "faulted":

litellm/proxy/_experimental/mcp_server/mcp_server_manager.py

@@ -24,7 +24,7 @@ from collections.abc import (
     MutableMapping,
     Sequence,
 )
-from contextlib import asynccontextmanager
+from contextlib import ExitStack, asynccontextmanager
 from dataclasses import dataclass, replace
 from functools import lru_cache
 from itertools import chain, groupby
@@ -44,12 +44,17 @@ from mcp.types import (
     GetPromptRequestParams,
     GetPromptResult,
     InputRequiredResult,
+    ListPromptsRequest,
+    ListResourcesRequest,
+    ListResourceTemplatesRequest,
+    ListToolsResult,
+    PaginatedRequestParams,
     Prompt,
     ResourceTemplate,
 )
 from mcp.types import Tool as MCPTool
 from pydantic import AnyUrl, BaseModel, Field, TypeAdapter
-from typing_extensions import ReadOnly
+from typing_extensions import ReadOnly, assert_never
 
 import litellm
 from litellm._internal_context import with_service_target
@@ -195,7 +200,6 @@ from litellm.proxy.middleware.per_request_root_path_middleware import (
     get_request_root_path,
 )
 from litellm.proxy.utils import PrismaClient, ProxyLogging
-from litellm.repositories.table_repositories import MCPServerRepository
 from litellm.types.integrations.slack_alerting import AlertType
 from litellm.types.llms.base import LiteLLMBaseModel
 from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -216,6 +220,7 @@ from litellm.types.utils import CallTypes
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+    from litellm.proxy._experimental.mcp_server.contracts import CatalogListRequest, CatalogListResult
     from litellm.types.mcp_server.mcp_toolset import MCPToolset
 
 try:
@@ -318,7 +323,7 @@ def _requires_oauth_discovery(
     use_issuer_anchor: bool,
     server: MCPServer,
 ) -> bool:
-    return _has_oauth_discovery_source(server_url, use_issuer_anchor) and _oauth_endpoints_unresolved(server)
+    return _has_oauth_discovery_source(server_url, use_issuer_anchor) and oauth_endpoints_unresolved(server)
 
 
 _StringList: TypeAlias = list[str]
@@ -573,7 +578,7 @@ def _config_identifier_owners(
     )
 
 
-def _config_ids_capturing_db_identifiers(
+def config_ids_capturing_db_identifiers(
     config_server_ids: Container[str],
     db_servers: Iterable[MCPServer],
 ) -> frozenset[str]:
@@ -753,7 +758,7 @@ def _flow_endpoints_missing(
     return authorization_url is None or token_url is None
 
 
-def _oauth_endpoints_unresolved(server: MCPServer) -> bool:
+def oauth_endpoints_unresolved(server: MCPServer) -> bool:
     """``_flow_endpoints_missing`` over a built registry entry, for the reload fast-path check.
 
     The flow comes from ``effective_oauth2_flow``, the one column-first, shape-fallback judge every
@@ -812,7 +817,7 @@ def _endpoints_corroborate_authorization_url(
     ) == _normalized_authorize_endpoint(trusted_authorization_url)
 
 
-def _carry_forward_resolved_oauth_endpoints(new_server: MCPServer, previous_server: MCPServer | None) -> None:
+def carry_forward_resolved_oauth_endpoints(new_server: MCPServer, previous_server: MCPServer | None) -> None:
     """Keep the last known good OAuth endpoints when a rebuild's re-discovery comes back empty.
 
     A rebuild wholesale-replaces the registry entry, so without this a transient upstream outage
@@ -1511,7 +1516,7 @@ def _obo_retry_applies(server: MCPServer, subject_token: str | None) -> bool:
     return server.auth_type == MCPAuth.oauth2_token_exchange and bool(subject_token)
 
 
-def _warn_on_server_name_fields(
+def warn_on_server_name_fields(
     *,
     server_id: str,
     alias: str | None,
@@ -1537,7 +1542,7 @@ def _warn_on_server_name_fields(
     _warn("server_name", server_name)
 
 
-def _warn_on_shared_identifier_prefixes(servers: Iterable[MCPServer]) -> None:
+def warn_on_shared_identifier_prefixes(servers: Iterable[MCPServer]) -> None:
     """Warn once per identifier that several servers share.
 
     ``get_server_prefix`` resolves alias first, so two servers sharing a
@@ -1971,6 +1976,9 @@ class MCPServerManager:
         self._template_discovery_cache = _DiscoveryCache[ResourceTemplate](
             discovery_ttl, discovery_clock, TypeAdapter(tuple[ResourceTemplate, ...])
         )
+        from litellm.proxy._experimental.mcp_server.catalog import CatalogSnapshots
+
+        self.catalog = CatalogSnapshots(self)
         self.registry: dict[str, MCPServer] = {}
         self._openapi_health_probes: Callable[[str], _OpenAPIHealthProbe] = lru_cache(maxsize=128)(_OpenAPIHealthProbe)
         self.config_mcp_servers: dict[str, MCPServer] = {}
@@ -1997,7 +2005,7 @@ class MCPServerManager:
         # semaphore so an edited limit rebuilds it instead of keeping the old cap
         # until restart.
         self._server_call_semaphores: dict[str, tuple[int, asyncio.Semaphore]] = {}
-        self.tool_name_to_mcp_server_name_mapping: dict[str, str] = {}
+        self.published_tool_routes: dict[str, str] = {}
         """
         {
             "gmail_send_email": "zapier_mcp_server",
@@ -2013,14 +2021,12 @@ class MCPServerManager:
         # Last set of config server ids found shadowed by database rows. reload_servers_from_database
         # runs on the config-reload timer, so this keeps a standing misconfiguration from re-logging
         # the same warning every interval; a change in the set logs again.
-        self._warned_shadowed_config_server_ids: frozenset[str] = frozenset()
-        self._warned_capturing_config_server_ids: frozenset[str] = frozenset()
         self._catalog_alert_signatures: Mapping[tuple[str, AlertType], str] = MappingProxyType({})
         self._oauth_discovery_on_startup = _mcp_oauth_discovery_on_startup_enabled()
         self._oauth_discovery_generation_counter = 0
         self._oauth_discovery_slots: tuple[_OAuthDiscoverySlot, ...] = ()
 
-    def _oauth_discovery_slot(self, server_id: str) -> _OAuthDiscoverySlot | None:
+    def oauth_discovery_slot(self, server_id: str) -> _OAuthDiscoverySlot | None:
         return next((slot for slot in self._oauth_discovery_slots if slot.server_id == server_id), None)
 
     def _remove_oauth_discovery_slot(self, server_id: str) -> None:
@@ -2033,7 +2039,7 @@ class MCPServerManager:
         )
 
     def _set_oauth_discovery_deferred(self, server_id: str, discovery_deferred: bool) -> None:
-        previous: Final = self._oauth_discovery_slot(server_id)
+        previous: Final = self.oauth_discovery_slot(server_id)
         self._remove_oauth_discovery_slot(server_id)
         if previous is not None and previous.task is not None and not previous.task.done():
             previous.task.cancel()
@@ -2046,8 +2052,8 @@ class MCPServerManager:
                 )
             )
 
-    def _invalidate_oauth_discovery_state(self, server_id: str) -> None:
-        previous: Final = self._oauth_discovery_slot(server_id)
+    def invalidate_oauth_discovery_state(self, server_id: str) -> None:
+        previous: Final = self.oauth_discovery_slot(server_id)
         self._remove_oauth_discovery_slot(server_id)
         if previous is not None and previous.task is not None and not previous.task.done():
             previous.task.cancel()
@@ -2129,7 +2135,7 @@ class MCPServerManager:
         )
 
     def _oauth_discovery_slot_is_current(self, server_id: str, generation: int) -> bool:
-        slot: Final = self._oauth_discovery_slot(server_id)
+        slot: Final = self.oauth_discovery_slot(server_id)
         return slot is not None and slot.generation == generation
 
     def _expire_temporary_oauth_discovery(self, server_id: str, generation: int) -> None:
@@ -2166,7 +2172,7 @@ class MCPServerManager:
         if not self._oauth_discovery_slot_is_current(server.server_id, generation):
             return _OAuthDiscoveryStale(server_id=server.server_id)
         current: Final = self._registered_server(server)
-        if not _oauth_endpoints_unresolved(current):
+        if not oauth_endpoints_unresolved(current):
             published: Final = self._publish_resolved_oauth_server(current, generation)
             return (
                 _OAuthDiscoveryResolved(server=published)
@@ -2177,7 +2183,7 @@ class MCPServerManager:
         if not self._oauth_discovery_slot_is_current(server.server_id, generation):
             return _OAuthDiscoveryStale(server_id=server.server_id)
         candidate: Final = self._merge_discovered_oauth_metadata(self._registered_server(server), metadata)
-        if _oauth_endpoints_unresolved(candidate):
+        if oauth_endpoints_unresolved(candidate):
             return None
         published_candidate: Final = self._publish_resolved_oauth_server(candidate, generation)
         return (
@@ -2224,7 +2230,7 @@ class MCPServerManager:
         return outcome
 
     def _record_oauth_discovery_failure(self, server_id: str, generation: int) -> None:
-        slot: Final = self._oauth_discovery_slot(server_id)
+        slot: Final = self.oauth_discovery_slot(server_id)
         if slot is None or slot.generation != generation:
             return
         consecutive_failures: Final = slot.consecutive_failures + 1
@@ -2240,7 +2246,7 @@ class MCPServerManager:
         self,
         server: MCPServer,
     ) -> tuple[asyncio.Task[_OAuthDiscoveryOutcome], int] | None:
-        slot: Final = self._oauth_discovery_slot(server.server_id)
+        slot: Final = self.oauth_discovery_slot(server.server_id)
         if slot is None:
             return None
         if slot.task is not None:
@@ -2269,19 +2275,24 @@ class MCPServerManager:
         """
         self._get_or_start_oauth_discovery_task(server)
 
-    def _prime_oauth_metadata_discovery_for_servers(self, servers: Sequence[MCPServer]) -> None:
+    def prime_oauth_metadata_discovery_for_servers(self, servers: Sequence[MCPServer]) -> None:
         for server in servers:
             self.prime_oauth_metadata_discovery(server)
 
-    def _reconcile_oauth_discovery_slots_for_servers(self, servers: Sequence[MCPServer]) -> None:
+    def reconcile_oauth_discovery_slots_for_servers(self, servers: Sequence[MCPServer]) -> None:
         """Align retry slots after an atomic registry replacement."""
         for server in servers:
             should_defer = _requires_oauth_discovery(server.url, server.issuer_is_anchored, server)
-            has_slot = self._oauth_discovery_slot(server.server_id) is not None
+            has_slot = self.oauth_discovery_slot(server.server_id) is not None
             if should_defer != has_slot:
                 self._set_oauth_discovery_deferred(server.server_id, should_defer)
 
     async def ensure_oauth_metadata_discovered(self, server: MCPServer, *, _retry_stale: bool = True) -> MCPServer:
+        return await self.catalog.resolve_oauth_metadata(
+            server, lambda selected: self._ensure_oauth_metadata_discovered(selected, _retry_stale=_retry_stale)
+        )
+
+    async def _ensure_oauth_metadata_discovered(self, server: MCPServer, *, _retry_stale: bool = True) -> MCPServer:
         """Join the bounded discovery task and return the resolved server.
 
         Concurrent callers share one task per server. A failed attempt remains
@@ -2300,6 +2311,7 @@ class MCPServerManager:
                 incomplete metadata for a server whose OAuth flow the gateway
                 runs itself.
         """
+        self.catalog.assert_current(server)
         acquisition: Final = self._get_or_start_oauth_discovery_task(server)
         if acquisition is None:
             return self._registered_server(server)
@@ -2312,11 +2324,13 @@ class MCPServerManager:
             raise
         match outcome:
             case _OAuthDiscoveryResolved(resolved_server):
+                self.catalog.assert_current(resolved_server)
                 return resolved_server
             case _OAuthDiscoveryStale():
                 return await self._rejoin_oauth_metadata_discovery(server, retry_stale=_retry_stale)
             case _OAuthDiscoveryFailed(timed_out=timed_out):
                 current: Final = self._registered_server(server)
+                self.catalog.assert_current(current)
                 if current.is_client_forwarded_token:
                     return current
                 server_ref: Final = current.alias or current.server_name or current.name or current.server_id
@@ -2326,11 +2340,13 @@ class MCPServerManager:
                     detail=f"OAuth metadata discovery {reason} for MCP server {server_ref!r}",
                 )
 
+        return assert_never(outcome)
+
     async def _rejoin_oauth_metadata_discovery(self, server: MCPServer, *, retry_stale: bool) -> MCPServer:
         if retry_stale:
             return await self.ensure_oauth_metadata_discovered(server, _retry_stale=False)
         current: Final = self._registered_server(server)
-        if not _oauth_endpoints_unresolved(current) or current.is_client_forwarded_token:
+        if not oauth_endpoints_unresolved(current) or current.is_client_forwarded_token:
             return current
         raise HTTPException(status_code=503, detail="OAuth metadata discovery changed repeatedly; retry shortly")
 
@@ -2408,11 +2424,21 @@ class MCPServerManager:
                 e,
             )
 
-    def get_registry(self) -> dict[str, MCPServer]:
+    def get_registry(self) -> Mapping[str, MCPServer]:
         """
         Get the registered MCP Servers from the registry and union with the config MCP Servers
         """
-        return self.config_mcp_servers | self.registry
+        return self.catalog.registry()
+
+    @property
+    def tool_name_to_mcp_server_name_mapping(
+        self,
+    ) -> MutableMapping[str, str]:
+        return self.catalog.routing()
+
+    @tool_name_to_mcp_server_name_mapping.setter
+    def tool_name_to_mcp_server_name_mapping(self, mapping: dict[str, str]) -> None:
+        self.published_tool_routes = mapping
 
     def is_config_declared_server(self, server_id: str) -> bool:
         """True when server_id was declared in config.yaml (present in the in-memory config map).
@@ -2499,7 +2525,7 @@ class MCPServerManager:
             )
             assigned_server_ids[server_id] = server_name
 
-            _warn_on_server_name_fields(
+            warn_on_server_name_fields(
                 server_id=server_id,
                 alias=alias,
                 server_name=server_name,
@@ -2715,10 +2741,10 @@ class MCPServerManager:
                 token_validation=server_config.get("token_validation", None),
                 oauth_identity_binding=server_config.get("oauth_identity_binding", None),
             )
-            self._assign_unique_short_prefix(new_server)
+            self.assign_unique_short_prefix(new_server)
             _warn_legacy_delegate_auth_if_applicable(new_server, source="config")
             _warn_config_id_jag_server_outruns_sso(new_server)
-            self._invalidate_server_definition_caches(server_id)
+            self.invalidate_server_definition_caches(server_id)
             self.config_mcp_servers[server_id] = new_server
             self._set_oauth_discovery_deferred(
                 server_id,
@@ -2739,13 +2765,13 @@ class MCPServerManager:
             "Loaded MCP Servers: %s", json.dumps(_redacted_registry_dump(self.config_mcp_servers), indent=4)
         )
 
-        await self._hydrate_config_servers_dcr_clients()
+        await self.hydrate_config_servers_dcr_clients()
 
-        self._prime_oauth_metadata_discovery_for_servers(tuple(self.config_mcp_servers.values()))
+        self.prime_oauth_metadata_discovery_for_servers(tuple(self.config_mcp_servers.values()))
 
         self.initialize_tool_name_to_mcp_server_name_mapping()
 
-    async def _hydrate_config_servers_dcr_clients(self) -> None:
+    async def hydrate_config_servers_dcr_clients(self, servers: Sequence[MCPServer] | None = None) -> None:
         """Overlay each config-declared server's persisted DCR client (from the server-scoped
         store) onto its in-memory object so token refresh authenticates after a restart. A
         best-effort no-op when the DB is unreachable at config-load time."""
@@ -2753,7 +2779,7 @@ class MCPServerManager:
             hydrate_config_server_dcr_client,
         )
 
-        for server in self.config_mcp_servers.values():
+        for server in servers if servers is not None else self.config_mcp_servers.values():
             try:
                 if await hydrate_config_server_dcr_client(server):
                     verbose_logger.debug(
@@ -2894,6 +2920,7 @@ class MCPServerManager:
                         description=description,
                         input_schema=input_schema,
                         handler=tool_func,
+                        server_id=server.server_id,
                     )
 
                     # Update tool name to server name mapping (for both prefixed and base names)
@@ -2918,17 +2945,18 @@ class MCPServerManager:
         mappings make ``_get_mcp_server_from_tool_name`` resolve to a prefix that
         no longer exists in the live registry.
         """
-        from litellm.proxy._experimental.mcp_server.tool_registry import (
-            global_mcp_tool_registry,
-        )
+        self.invalidate_server_definition_caches(server.server_id)
+        self.remove_server_tool_routing(server)
+
+    def remove_server_tool_routing(self, server: MCPServer) -> None:
+        from litellm.proxy._experimental.mcp_server.tool_registry import global_mcp_tool_registry
 
-        self._invalidate_server_definition_caches(server.server_id)
         prefix_root: Final = normalize_server_name(get_server_prefix(server))
         if server.spec_path and prefix_root:
             openapi_key_prefix: Final = prefix_root + MCP_TOOL_PREFIX_SEPARATOR
             global_mcp_tool_registry.unregister_tools_with_prefix(openapi_key_prefix)
 
-        owned_normalized: Final = self._owned_mapping_values(server)
+        owned_normalized: Final = self.owned_mapping_values(server)
 
         stale_mapping_keys: Final = tuple(
             tool_name
@@ -2939,13 +2967,13 @@ class MCPServerManager:
         for key in stale_mapping_keys:
             del self.tool_name_to_mcp_server_name_mapping[key]
 
-    def _owned_mapping_values(self, server: MCPServer) -> frozenset[str]:
+    def owned_mapping_values(self, server: MCPServer) -> frozenset[str]:
         return frozenset(
             normalize_server_name(value) for value in (*iter_known_server_prefixes(server), server.name) if value
         )
 
     def server_exposes_tool(self, server: MCPServer, tool_name: str) -> bool:
-        owned: Final = self._owned_mapping_values(server)
+        owned: Final = self.owned_mapping_values(server)
         mapped_owners: Final = (
             self.tool_name_to_mcp_server_name_mapping.get(spelling)
             for spelling in iter_known_tool_name_spellings(tool_name, server)
@@ -2976,7 +3004,7 @@ class MCPServerManager:
         if evicted is not None:
             verbose_logger.debug("Removed MCP Server: %s", mcp_server.server_id or mcp_server.server_name)
             self._cleanup_server_tool_routing_artifacts(evicted)
-            self._invalidate_oauth_discovery_state(evicted.server_id)
+            self.invalidate_oauth_discovery_state(evicted.server_id)
         else:
             verbose_logger.warning("Server ID %s not found in registry", mcp_server.server_id)
 
@@ -3067,6 +3095,7 @@ class MCPServerManager:
         *,
         credentials_are_encrypted: bool = True,
         env_vars_are_encrypted: bool | None = None,
+        register_oauth_discovery: bool = True,
     ) -> MCPServer:
         _mcp_info: Final[MCPInfo] = mcp_server.mcp_info or {}
         env_dict: Final = _deserialize_json_dict(getattr(mcp_server, "env", None))
@@ -3300,13 +3329,14 @@ class MCPServerManager:
             max_concurrent_requests=getattr(mcp_server, "max_concurrent_requests", None),
         )
         _warn_legacy_delegate_auth_if_applicable(new_server, source="database")
-        self._set_oauth_discovery_deferred(
-            new_server.server_id,
-            _requires_oauth_discovery(server_url, use_issuer_anchor, new_server),
-        )
+        if register_oauth_discovery:
+            self._set_oauth_discovery_deferred(
+                new_server.server_id,
+                _requires_oauth_discovery(server_url, use_issuer_anchor, new_server),
+            )
         return new_server
 
-    async def _maybe_register_openapi_tools(self, server: MCPServer, *, initialize_mapping: bool = True):
+    async def maybe_register_openapi_tools(self, server: MCPServer, *, initialize_mapping: bool = True):
         """Register OpenAPI tools if the server has a spec_path configured."""
         if server.spec_path:
             verbose_logger.info("Loading OpenAPI spec from %s for server %s", server.spec_path, server.name)
@@ -3333,12 +3363,12 @@ class MCPServerManager:
                 # `credentials` field is the only one still encrypted here).
                 # Re-decrypting plaintext would zero the values, so build with
                 # env_vars_are_encrypted=False.
-                self._warn_if_newly_blocked_stdio(mcp_server, None)
+                self.warn_if_newly_blocked_stdio(mcp_server, None)
                 new_server: Final = await self.build_mcp_server_from_table(mcp_server, env_vars_are_encrypted=False)
-                self._assign_unique_short_prefix(new_server)
-                self._invalidate_server_definition_caches(mcp_server.server_id)
+                self.assign_unique_short_prefix(new_server)
+                self.invalidate_server_definition_caches(mcp_server.server_id)
                 self.registry[mcp_server.server_id] = new_server
-                await self._maybe_register_openapi_tools(new_server)
+                await self.maybe_register_openapi_tools(new_server)
                 if new_server.spec_path:
                     self._drop_listed_tools(mcp_server.server_id)
                 self.prime_oauth_metadata_discovery(new_server)
@@ -3358,7 +3388,7 @@ class MCPServerManager:
                 evicted = self.registry.pop(mcp_server.server_name, None)
             if evicted is not None:
                 self._cleanup_server_tool_routing_artifacts(evicted)
-                self._invalidate_oauth_discovery_state(evicted.server_id)
+                self.invalidate_oauth_discovery_state(evicted.server_id)
             return
         try:
             if mcp_server.server_id in self.registry:
@@ -3370,14 +3400,14 @@ class MCPServerManager:
                 existing_prefix: Final = self.registry[mcp_server.server_id].short_prefix
                 if existing_prefix and not new_server.short_prefix:
                     new_server.short_prefix = existing_prefix
-                _carry_forward_resolved_oauth_endpoints(
+                carry_forward_resolved_oauth_endpoints(
                     new_server=new_server,
                     previous_server=self.registry[mcp_server.server_id],
                 )
-                self._assign_unique_short_prefix(new_server)
-                self._invalidate_server_definition_caches(mcp_server.server_id)
+                self.assign_unique_short_prefix(new_server)
+                self.invalidate_server_definition_caches(mcp_server.server_id)
                 self.registry[mcp_server.server_id] = new_server
-                await self._maybe_register_openapi_tools(new_server)
+                await self.maybe_register_openapi_tools(new_server)
                 if new_server.spec_path:
                     self._drop_listed_tools(mcp_server.server_id)
                 self.prime_oauth_metadata_discovery(new_server)
@@ -4200,6 +4230,7 @@ class MCPServerManager:
         client_ip: str | None = None,
         protocol_version_override: MCPUpstreamProtocol | None = None,
     ) -> MCPClient:
+        self.catalog.assert_current(server)
         record_auth_resolution(server.server_id, AuthResolution.unresolved)
         resolved_server: Final = await self.ensure_oauth_metadata_discovered(server)
         return await prepare_upstream_client(
@@ -4242,27 +4273,47 @@ class MCPServerManager:
         *,
         catalog_auth_header: str | dict[str, str] | None | EllipsisType = ...,
         record_listing: bool = False,
-    ) -> Sequence[MCPTool]:
-        """
-        Helper method to get tools from a single MCP server with prefixed names.
+    ) -> list[MCPTool]:
+        result: Final = await self.get_tools_page(
+            server=server,
+            mcp_auth_header=mcp_auth_header,
+            extra_headers=extra_headers,
+            add_prefix=add_prefix,
+            raw_headers=raw_headers,
+            user_api_key_auth=user_api_key_auth,
+            oauth2_headers=oauth2_headers,
+            client_ip=client_ip,
+            proxy_logging_obj=proxy_logging_obj,
+            catalog_auth_header=catalog_auth_header,
+            record_listing=record_listing,
+        )
+        return result.tools
 
-        Args:
-            server (MCPServer): The server to query tools from
-            mcp_auth_header: Optional auth header for MCP server
-            catalog_auth_header: The header the client supplied, keying the caller's catalog slot;
-                defaults to ``mcp_auth_header``
-            record_listing: Record the served catalog into the caller's listed-tools slot; only a
-                listing actually served to the caller sets it
-
-        Returns:
-            List[MCPTool]: List of tools available on the server with prefixed names
-        """
+    async def get_tools_page(
+        self,
+        server: MCPServer,
+        mcp_auth_header: str | dict[str, str] | None = None,
+        extra_headers: dict[str, str] | None = None,
+        add_prefix: bool = True,
+        raw_headers: dict[str, str] | None = None,
+        user_api_key_auth: UserAPIKeyAuth | None = None,
+        oauth2_headers: dict[str, str] | None = None,
+        client_ip: str | None = None,
+        proxy_logging_obj: ProxyLogging | None = None,
+        *,
+        params: PaginatedRequestParams | None = None,
+        catalog_auth_header: str | dict[str, str] | None | EllipsisType = ...,
+        record_listing: bool = False,
+        listing_updates: ExitStack | None = None,
+    ) -> ListToolsResult:
         from litellm.proxy._experimental.mcp_server.tool_registry import (
             global_mcp_tool_registry,
         )
 
         if self._skip_blocked_stdio_listing(server, "tool"):
-            return []
+            if params is not None and params.cursor is not None:
+                raise RuntimeError("Upstream catalog is unavailable")
+            return ListToolsResult(tools=[])
 
         verbose_logger.debug("Connecting to url: %s", server.url)
         verbose_logger.info("_get_tools_from_server for %s...", server.name)
@@ -4376,10 +4427,17 @@ class MCPServerManager:
                     server, guarded_openapi, listed_caller, listed_generation, record_listing=record_listing
                 )
                 if not add_prefix:
-                    return guarded_openapi
-                return [t.model_copy(update={"name": registered_names[t.name]}) for t in guarded_openapi]
+                    return ListToolsResult(tools=list(guarded_openapi))
+                return ListToolsResult(
+                    tools=[t.model_copy(update={"name": registered_names[t.name]}) for t in guarded_openapi]
+                )
             else:
-                tools = await self._fetch_tools_with_timeout(client, server.name)
+                page: Final = (
+                    await client.list_tools_page(params)
+                    if params is not None
+                    else ListToolsResult(tools=await self._fetch_tools_with_timeout(client, server.name))
+                )
+                tools = page.tools
                 self._remember_upstream_initialize_instructions(server, client)
 
             guarded_tools: Final = await self._guard_tool_catalog(
@@ -4390,13 +4448,17 @@ class MCPServerManager:
                 raw_headers=raw_headers,
             )
             prefixed_or_original_tools: Final = self._create_prefixed_tools(
-                guarded_tools, server, add_prefix=add_prefix
+                guarded_tools,
+                server,
+                add_prefix=add_prefix,
+                register_bare_names=params is None or (params.cursor is None and not page.next_cursor),
+                listing_updates=listing_updates,
             )
             self.record_listed_tools(
                 server, guarded_tools, listed_caller, listed_generation, record_listing=record_listing
             )
 
-            return prefixed_or_original_tools
+            return page.model_copy(update={"tools": prefixed_or_original_tools})
 
         except MCPUpstreamAuthError as upstream_auth_error:
             # Pass-through 401 must surface to single-server routes so the
@@ -4433,17 +4495,23 @@ class MCPServerManager:
             )
             raise_classified_list_failure(e, server.name, suppress_challenge=server.is_dcr_bridge)
 
-    def _invalidate_discovery_lists(self, server_id: str) -> None:
+    def clear_initialize_instructions(self) -> None:
+        self._upstream_initialize_instructions_by_server_id.clear()
+        self._upstream_initialize_instructions_probed_at.clear()
+
+    def invalidate_discovery_lists(self, server_id: str) -> None:
+        self._upstream_initialize_instructions_by_server_id.pop(server_id, None)
+        self._upstream_initialize_instructions_probed_at.pop(server_id, None)
         self._prompt_discovery_cache.invalidate(server_id)
         self._resource_discovery_cache.invalidate(server_id)
         self._template_discovery_cache.invalidate(server_id)
 
-    def _invalidate_server_definition_caches(self, server_id: str) -> None:
+    def invalidate_server_definition_caches(self, server_id: str) -> None:
         from litellm.proxy._experimental.mcp_server.discoverable_endpoints import (  # noqa: PLC0415  # lazy: discoverable_endpoints lazily imports this module's manager singleton
             invalidate_oauth_metadata_cache,
         )
 
-        self._invalidate_discovery_lists(server_id)
+        self.invalidate_discovery_lists(server_id)
         self._drop_listed_tools(server_id)
         invalidate_oauth_metadata_cache(server_id)
 
@@ -4506,6 +4574,7 @@ class MCPServerManager:
         generation: int | None = None,
         *,
         record_listing: bool = True,
+        continuation: bool = False,
     ) -> None:
         """Store the catalog served to ``caller``. ``generation`` is the server's listed-tools generation
         read before the listing's upstream fetch; the record is skipped when it no longer matches."""
@@ -4514,8 +4583,9 @@ class MCPServerManager:
         if generation is not None and generation != self._listed_tools_generations.get(server.server_id, 0):
             return
         identity: Final = self._listed_tools_identity(server, caller)
-        listing: Final = MappingProxyType({tool.name: tool for tool in tools})
         existing: Final = self._listed_tools_by_server_id.get(server.server_id, MappingProxyType({}))
+        prior: Final = existing.get(identity, {}) if continuation else {}
+        listing: Final = MappingProxyType({**prior, **{tool.name: tool for tool in tools}})
         shared: Final = existing.get(None)
         callers: Final = tuple((key, value) for key, value in existing.items() if key not in (None, identity))
         evicted: Final = 0 if identity is None else max(len(callers) + 1 - _LISTED_TOOLS_CALLERS_PER_SERVER, 0)
@@ -4559,7 +4629,7 @@ class MCPServerManager:
         return server.server_id, hashlib.sha256(material.encode()).hexdigest()
 
     @staticmethod
-    def _warn_if_newly_blocked_stdio(row: LiteLLM_MCPServerTable, previous: MCPServer | None) -> None:
+    def warn_if_newly_blocked_stdio(row: LiteLLM_MCPServerTable, previous: MCPServer | None) -> None:
         if previous is None or previous.transport != row.transport:
             warn_if_mcp_stdio_blocked(row.alias or row.server_name, row.transport)
 
@@ -4571,6 +4641,67 @@ class MCPServerManager:
         )
         return True
 
+    async def get_optional_catalog_page(
+        self,
+        server: MCPServer,
+        request: "CatalogListRequest",
+        user_api_key_auth: UserAPIKeyAuth | None,
+        *,
+        mcp_auth_header: str | dict[str, str] | None = None,
+        extra_headers: Mapping[str, str] | None = None,
+        raw_headers: Mapping[str, str] | None = None,
+        client_ip: str | None = None,
+    ) -> "CatalogListResult":
+        from mcp.types import ListPromptsResult, ListResourcesResult, ListResourceTemplatesResult
+
+        if self._skip_blocked_stdio_listing(server, "catalog"):
+            if request.params is not None and request.params.cursor is not None:
+                raise RuntimeError("Upstream catalog is unavailable")
+            match request:
+                case ListPromptsRequest():
+                    return ListPromptsResult(prompts=[])
+                case ListResourcesRequest():
+                    return ListResourcesResult(resources=[])
+                case ListResourceTemplatesRequest():
+                    return ListResourceTemplatesResult(resource_templates=[])
+                case _:
+                    raise RuntimeError("Unexpected catalog request type")
+        headers: Final = (
+            dict(
+                chain(
+                    extra_headers.items() if extra_headers else (),
+                    server.static_headers.items() if server.static_headers else (),
+                )
+            )
+            or None
+        )
+        stdio_env: Final = self._build_stdio_env(server, raw_headers)
+        subject_token: Final = self._obo_subject_token(server, raw_headers, user_api_key_auth)
+        client: Final = await self._create_mcp_client(
+            server=server,
+            mcp_auth_header=mcp_auth_header,
+            extra_headers=headers,
+            stdio_env=stdio_env,
+            subject_token=subject_token,
+            user_api_key_auth=user_api_key_auth,
+            raw_headers=raw_headers,
+            client_ip=client_ip,
+        )
+        page: Final = await client.list_page(request)
+        match page:
+            case ListPromptsResult():
+                return page.model_copy(update={"prompts": self._create_prefixed_prompts(page.prompts, server)})
+            case ListResourcesResult():
+                return page.model_copy(update={"resources": self._create_prefixed_resources(page.resources, server)})
+            case ListResourceTemplatesResult():
+                return page.model_copy(
+                    update={
+                        "resource_templates": self._create_prefixed_resource_templates(page.resource_templates, server)
+                    }
+                )
+            case _:
+                raise RuntimeError("Unexpected catalog result type")
+
     async def get_prompts_from_server(
         self,
         server: MCPServer,
@@ -5336,7 +5467,7 @@ class MCPServerManager:
 
     _SHORT_PREFIX_MAX_REHASH_ATTEMPTS = 1024
 
-    def _assign_unique_short_prefix(
+    def assign_unique_short_prefix(
         self,
         server: MCPServer,
         registry: dict[str, MCPServer] | None = None,
@@ -5456,6 +5587,9 @@ class MCPServerManager:
         tools: Sequence[MCPTool],
         server: MCPServer,
         add_prefix: bool = True,
+        *,
+        register_bare_names: bool = True,
+        listing_updates: ExitStack | None = None,
     ) -> list[MCPTool]:
         """
         Create prefixed tools and update tool mapping.
@@ -5467,6 +5601,12 @@ class MCPServerManager:
         Returns:
             List of tools with prefixed names
         """
+        from litellm.proxy._experimental.mcp_server.tool_registry import global_mcp_tool_registry
+
+        if register_bare_names and listing_updates is not None:
+            listing_updates.callback(self._create_prefixed_tools, tools, server, add_prefix=add_prefix)
+            register_bare_names = False
+
         prefixed_tools: Final = []
         prefix: Final = get_server_prefix(server)
 
@@ -5479,7 +5619,13 @@ class MCPServerManager:
             # short ID) so call_tool can resolve regardless of which form a
             # caller / cached client is using.
             for spelling in iter_known_tool_name_spellings(original_name, server):
-                self.tool_name_to_mcp_server_name_mapping[spelling] = prefix
+                namespace_owner = self.server_owning_tool_name_prefix(spelling)
+                if namespace_owner is not None and namespace_owner.server_id != server.server_id:
+                    continue
+                if namespace_owner is None and global_mcp_tool_registry.get_tool(spelling) is not None:
+                    continue
+                if register_bare_names or spelling != original_name:
+                    self.tool_name_to_mcp_server_name_mapping[spelling] = prefix
 
         verbose_logger.info("Successfully fetched %s tools from server %s", len(prefixed_tools), server.name)
         return prefixed_tools
@@ -5682,6 +5828,7 @@ class MCPServerManager:
         # Registration used add_server_prefix_to_name(base, get_server_prefix(server)),
         # and tool_name is the bare base name by the time call_tool reaches here, so
         # rebuilding the key the same way reproduces it exactly
+        self.catalog.assert_current(server)
         registry_key: Final = add_server_prefix_to_name(tool_name, get_server_prefix(server))
         tool: Final = global_mcp_tool_registry.get_tool(registry_key)
         if tool is None:
@@ -6300,7 +6447,7 @@ class MCPServerManager:
         failure is logged, never raised, because the DB write already succeeded and the TTL remains
         the backstop.
         """
-        self._invalidate_discovery_lists(server_id)
+        self.invalidate_discovery_lists(server_id)
         try:
             await self._per_user_oauth_token_store.invalidate(user_id, server_id)
         except Exception as exc:  # noqa: BLE001 - cache drop is best-effort; TTL is the backstop
@@ -6612,7 +6759,7 @@ class MCPServerManager:
         Note: This now handles prefixed tool names
         """
         for server in self.get_registry().values():
-            if self._oauth_discovery_slot(server.server_id) is not None:
+            if self.oauth_discovery_slot(server.server_id) is not None:
                 continue
             if server.needs_user_oauth_token:
                 # Skip OAuth2 servers that rely on user-provided tokens
@@ -6649,6 +6796,14 @@ class MCPServerManager:
         Returns:
             MCPServer if found, None otherwise
         """
+        from litellm.proxy._experimental.mcp_server.tool_registry import global_mcp_tool_registry
+
+        registered_tool: Final = global_mcp_tool_registry.get_tool(tool_name)
+        if registered_tool is not None:
+            if registered_tool.server_id is not None:
+                return self.get_mcp_server_by_id(registered_tool.server_id)
+            return self.server_owning_tool_name_prefix(tool_name)
+
         registry_servers: Final = list(self.get_registry().values())
         prefix_to_server: Final = self._known_prefix_to_server()
 
@@ -6677,154 +6832,7 @@ class MCPServerManager:
         return None
 
     async def reload_servers_from_database(self):
-        """Re-synchronize the in-memory MCP server registry with the database."""
-        from litellm.proxy.management_endpoints.mcp_management_endpoints import (
-            get_prisma_client_or_throw,
-        )
-
-        verbose_logger.debug("Loading MCP servers from database into registry...")
-        self._upstream_initialize_instructions_by_server_id.clear()
-        self._upstream_initialize_instructions_probed_at.clear()
-
-        # perform authz check to filter the mcp servers user has access to
-        prisma_client: Final = get_prisma_client_or_throw("Database not connected. Connect a database to your proxy")
-        # Load only "active", legacy "approved", and NULL (no approval workflow) rows.
-        # Pending/rejected servers are excluded at the DB level so we never load them.
-        from litellm.proxy._experimental.mcp_server.db import LiteLLM_MCPServerTable
-
-        raw_rows: Final[Sequence[BaseModel]] = await MCPServerRepository(prisma_client).table.find_many(
-            where={
-                "OR": [
-                    {"approval_status": None},
-                    {"approval_status": {"in": ["active", "approved"]}},
-                ]
-            }
-        )
-        verbose_logger.info("Found %s MCP servers in database", len(raw_rows))
-
-        previous_registry: Final = self.registry
-        new_registry: Final[dict[str, MCPServer]] = {}
-
-        # Stage one: build every server.  Stage two assigns short prefixes
-        # against the *full* set so dedup is deterministic regardless of
-        # iteration order.
-        for row in raw_rows:
-            try:
-                server = LiteLLM_MCPServerTable.model_validate(row.model_dump())
-                existing_server = previous_registry.get(server.server_id)
-
-                if (
-                    existing_server is not None
-                    and existing_server.updated_at is not None
-                    and server.updated_at is not None
-                    and existing_server.updated_at == server.updated_at
-                    and (
-                        self._oauth_discovery_slot(server.server_id) is not None
-                        or not _oauth_endpoints_unresolved(existing_server)
-                    )
-                ):
-                    # Re-use existing server instance to avoid re-running build_mcp_server_from_table()
-                    # which can perform network discovery for OAuth2 servers.
-                    new_registry[server.server_id] = existing_server
-                    continue
-
-                _warn_on_server_name_fields(
-                    server_id=server.server_id,
-                    alias=getattr(server, "alias", None),
-                    server_name=getattr(server, "server_name", None),
-                )
-                self._warn_if_newly_blocked_stdio(server, existing_server)
-                verbose_logger.debug("Building server from DB: %s (%s)", server.server_id, server.server_name)
-                # raw_rows come straight from the DB, so their global env var
-                # values (like credentials) are still encrypted here, unlike the
-                # already-decrypted records add_server/update_server are handed.
-                # Decrypt them while building the registry entry.
-                new_server = await self.build_mcp_server_from_table(server, env_vars_are_encrypted=True)
-                # Carry the cached short_prefix from the previous registry entry
-                # (if any) so the prefix is stable across reloads.
-                if existing_server is not None and existing_server.short_prefix:
-                    new_server.short_prefix = existing_server.short_prefix
-                _carry_forward_resolved_oauth_endpoints(new_server=new_server, previous_server=existing_server)
-                new_registry[server.server_id] = new_server
-            except Exception as e:
-                verbose_logger.exception(
-                    "Skipping MCP server %s (%s) during DB reload: %s",
-                    getattr(row, "server_id", None),
-                    getattr(row, "alias", None),
-                    e,
-                )
-
-        # Assign short prefixes against the full candidate set without
-        # publishing the staged registry to concurrent callers.
-        registered_registry: Final[dict[str, MCPServer]] = {}
-        registered_openapi_tools = False
-        for server_id, new_server in new_registry.items():
-            try:
-                self._assign_unique_short_prefix(new_server, registry=new_registry)
-                # Register OpenAPI tools *after* the final short prefix is assigned
-                # so the tools are stored in the global registry under the same
-                # prefix that lookups will use.
-                await self._maybe_register_openapi_tools(new_server, initialize_mapping=False)
-                registered_registry[server_id] = new_server
-                if new_server.spec_path:
-                    registered_openapi_tools = True
-            except Exception as e:
-                verbose_logger.exception(
-                    "Skipping MCP server %s (%s) during DB reload: %s",
-                    new_server.server_id,
-                    getattr(new_server, "alias", None),
-                    e,
-                )
-
-        dropped_registry_keys: Final = previous_registry.keys() - registered_registry.keys()
-        for registry_key in dropped_registry_keys:
-            self._invalidate_oauth_discovery_state(previous_registry[registry_key].server_id)
-
-        for server_id in previous_registry.keys() | registered_registry.keys():
-            if previous_registry.get(server_id) != registered_registry.get(server_id):
-                self._invalidate_server_definition_caches(server_id)
-        self.registry = registered_registry
-        _warn_on_shared_identifier_prefixes(registered_registry.values())
-        # A discovery task may have published into ``previous_registry`` while
-        # this replacement was being staged. Reconcile every published entry
-        # synchronously after the swap so a lost publication cannot also leave
-        # the replacement unresolved with no retry slot.
-        registered_servers: Final = tuple(registered_registry.values())
-        self._reconcile_oauth_discovery_slots_for_servers(registered_servers)
-        self._prime_oauth_metadata_discovery_for_servers(registered_servers)
-        if registered_openapi_tools:
-            self.initialize_tool_name_to_mcp_server_name_mapping()
-
-        verbose_logger.debug("MCP registry refreshed (%s servers in registry)", len(registered_registry))
-
-        # get_registry() is ``config_mcp_servers | registry``, so a database row sharing an id with a
-        # config.yaml server hides that server everywhere. Only reachable once an operator pins
-        # ``server_id`` in config.yaml; say so rather than letting the server disappear silently.
-        shadowed_config_server_ids: Final = frozenset(self.config_mcp_servers.keys() & registered_registry.keys())
-        if shadowed_config_server_ids and shadowed_config_server_ids != self._warned_shadowed_config_server_ids:
-            verbose_logger.warning(
-                "config.yaml MCP server_id(s) %s are also database-backed MCP servers. The database "
-                "entry takes precedence, so the config.yaml server is unreachable. Give the config "
-                "entry a different server_id.",
-                ", ".join(sorted(shadowed_config_server_ids)),
-            )
-        self._warned_shadowed_config_server_ids = shadowed_config_server_ids
-
-        # The mirror image of the block above: a config server_id that is a database server's name
-        # answers that server's grants instead, because ids are matched before names.
-        capturing_config_server_ids: Final = _config_ids_capturing_db_identifiers(
-            self.config_mcp_servers.keys(), registered_registry.values()
-        )
-        if capturing_config_server_ids and capturing_config_server_ids != self._warned_capturing_config_server_ids:
-            verbose_logger.warning(
-                "config.yaml MCP server_id(s) %s are the name or alias of a database-backed MCP "
-                "server. Permission entries naming them resolve to the config.yaml server, not the "
-                "database one. Give the config entry a different server_id.",
-                ", ".join(sorted(capturing_config_server_ids)),
-            )
-        self._warned_capturing_config_server_ids = capturing_config_server_ids
-
-        await self._hydrate_config_servers_dcr_clients()
+        await self.catalog.reload()
 
     def get_mcp_servers_from_ids(self, server_ids: list[str]) -> list[MCPServer]:
         servers: Final = []
@@ -7015,7 +7023,7 @@ class MCPServerManager:
                 return server
         return None
 
-    def get_filtered_registry(self, client_ip: str | None = None) -> dict[str, MCPServer]:
+    def get_filtered_registry(self, client_ip: str | None = None) -> Mapping[str, MCPServer]:
         """
         Get registry filtered by client IP access control.
 

litellm/proxy/_experimental/mcp_server/operations.py

@@ -6,6 +6,7 @@ import types
 import uuid
 from collections.abc import Mapping, Sequence
 from datetime import datetime
+from functools import partial
 from typing import Any, Final, NoReturn, TypeAlias, overload
 
 from fastapi import HTTPException
@@ -62,6 +63,7 @@ from litellm.proxy._experimental.mcp_server.capabilities import (
     build_discovery,
     configured_versions,
 )
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, global_manager
 from litellm.proxy._experimental.mcp_server.contracts import (
     AuthorizedToolCall,
     OperationContext,
@@ -73,15 +75,12 @@ from litellm.proxy._experimental.mcp_server.exceptions import (
     MCPUpstreamAuthError,
 )
 from litellm.proxy._experimental.mcp_server.faults.list_outcomes import (
-    SERVER_OUTCOMES_META_KEY,
     AggregateToolListing,
     ServerListOk,
     ServerOutcome,
-    classify_list_exception,
     outcome_wire_value,
 )
 from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
-    ListedToolsCaller,
     MCPServerManager,
     _caller_authorization_fans_out,
     _client_forwarded_authorization_headers,
@@ -627,6 +626,7 @@ def apply_display_name_overrides(
     return tools
 
 
+@catalog_operation(lambda: global_mcp_server_manager)
 async def _get_allowed_mcp_servers(
     user_api_key_auth: UserAPIKeyAuth | None,
     mcp_servers: Sequence[str] | None,
@@ -943,6 +943,7 @@ def _aggregate_server_key(server: MCPServer) -> str:
     return get_server_prefix(server) or "unknown"
 
 
+@catalog_operation(lambda: global_mcp_server_manager)
 async def _get_tools_from_mcp_servers(
     user_api_key_auth: UserAPIKeyAuth | None,
     mcp_auth_header: str | None,
@@ -956,6 +957,8 @@ async def _get_tools_from_mcp_servers(
     request_tags: list[str] | None = None,
     client_ip: str | None = None,
     mcp_proxy_mode: bool = False,
+    params: PaginatedRequestParams | None = None,
+    protocol_version: str | None = None,
     *,
     record_listing: bool = False,
 ) -> AggregateToolListing:
@@ -1065,149 +1068,54 @@ async def _get_tools_from_mcp_servers(
             await _prefetch_oauth_creds_for_user(user_api_key_auth) if _has_oauth2_server else {}
         )
 
-        async def _fetch_and_filter_server_tools(
-            server: MCPServer,
-        ) -> "tuple[list[MCPTool], ServerOutcome]":
-            """Fetch and filter tools from a single server, classifying any failure into that
-            server's outcome so the aggregate can keep serving the healthy subset without a
-            broken server masquerading as an empty one."""
-            if server is None:
-                return [], ServerListOk(tool_count=0)
+        from litellm.proxy._experimental.mcp_server.catalog import get_filtered_server_tools
 
-            server_auth_header, extra_headers = _prepare_mcp_server_headers(
-                server=server,
-                mcp_server_auth_headers=mcp_server_auth_headers,
-                mcp_auth_header=mcp_auth_header,
-                oauth2_headers=oauth2_headers,
-                raw_headers=raw_headers,
-                user_api_key_auth=user_api_key_auth,
-                scope_servers=allowed_mcp_servers,
+        context: Final = OperationContext(
+            _caller=user_api_key_auth,
+            mcp_auth_header=mcp_auth_header,
+            mcp_servers=tuple(mcp_servers) if mcp_servers is not None else None,
+            mcp_server_auth_headers=mcp_server_auth_headers,
+            oauth2_headers=oauth2_headers,
+            raw_headers=raw_headers,
+            client_ip=client_ip,
+            mcp_proxy_mode=mcp_proxy_mode,
+            protocol_version=protocol_version,
+        )
+
+        async def _fetch_and_filter_server_tools(server: MCPServer) -> tuple[Sequence[MCPTool], ServerOutcome]:
+            page, outcome = await get_filtered_server_tools(
+                server,
+                context=context,
+                allowed_mcp_servers=allowed_mcp_servers,
+                prefetched_oauth_creds=_prefetched_oauth_creds,
+                record_listing=record_listing,
             )
+            return page.tools, outcome
 
-            # Prefer server-stored per-user OAuth when configured, so a stale
-            # Authorization header from the MCP client cannot override Redis/DB
-            # (same issue as call_tool in mcp_server_manager: VS Code caches tokens).
-            from litellm.proxy._experimental.mcp_server.outbound_credentials.adapter import (  # noqa: PLC0415
-                to_server_spec,
+        if params is None:
+            results: Final = await asyncio.gather(
+                *(_fetch_and_filter_server_tools(server) for server in allowed_mcp_servers)
             )
+            aggregated = AggregateToolListing(
+                tools=[tool for tools, _ in results for tool in tools],
+                outcomes={
+                    _aggregate_server_key(server): outcome for server, (_, outcome) in zip(allowed_mcp_servers, results)
+                },
+            )
+        else:
+            from litellm.proxy._experimental.mcp_server.catalog import aggregate_gateway_tools
 
-            # A server migrated to the v2 resolver gets its token from the resolver at connect
-            # time; building it here would double-resolve and be shadowed by the v2 graft. The
-            # preemptive 401 already challenged a missing token, so one exists for the connect.
-            migrated_to_v2: Final = to_server_spec(server) is not None
-            if (
-                not migrated_to_v2
-                and server.auth_type == MCPAuth.oauth2
-                and getattr(server, "needs_user_oauth_token", False)
-                and user_api_key_auth is not None
-            ):
-                db_headers: Final = await _get_user_oauth_extra_headers_from_db(
-                    server,
-                    user_api_key_auth,
-                    prefetched_creds=_prefetched_oauth_creds,
-                )
-                if db_headers:
-                    extra_headers = db_headers
-
-            # If still no OAuth2 token, fall back to pre-fetched creds (non-stale-client path)
-            elif not migrated_to_v2 and extra_headers is None and server.auth_type == MCPAuth.oauth2:
-                extra_headers = await _get_user_oauth_extra_headers_from_db(
-                    server,
-                    user_api_key_auth,
-                    prefetched_creds=_prefetched_oauth_creds,
-                )
-
-            catalog_auth_header: Final = server_auth_header
-            if server.is_byok and server.auth_type != MCPAuth.oauth2 and server_auth_header is None:
-                server_auth_header = await _get_byok_credential(server, user_api_key_auth)
-
-            try:
-                from litellm.proxy.proxy_server import proxy_logging_obj
-
-                listed_generation: Final = global_mcp_server_manager.listed_tools_generation(server.server_id)
-                tools: Final = list(
-                    await global_mcp_server_manager._get_tools_from_server(
-                        server=server,
-                        mcp_auth_header=server_auth_header,
-                        extra_headers=extra_headers,
-                        add_prefix=True,  # Always add server prefix
-                        raw_headers=raw_headers,
-                        client_ip=client_ip,
-                        user_api_key_auth=user_api_key_auth,
-                        oauth2_headers=oauth2_headers,
-                        proxy_logging_obj=proxy_logging_obj,
-                        catalog_auth_header=catalog_auth_header,
-                        record_listing=False,
-                    )
-                )
-                filtered_tools = filter_tools_by_allowed_tools(tools, server)
-
-                filtered_tools = await filter_tools_by_key_team_permissions(
-                    tools=filtered_tools,
-                    server_id=server.server_id,
-                    user_api_key_auth=user_api_key_auth,
-                )
-                global_mcp_server_manager.record_listed_tools(
-                    server,
-                    [
-                        tool.model_copy(update={"name": strip_known_server_prefix(tool.name, server)})
-                        for tool in filtered_tools
-                    ],
-                    ListedToolsCaller(
-                        user_api_key_auth=user_api_key_auth,
-                        mcp_auth_header=catalog_auth_header,
-                        raw_headers=raw_headers,
-                        oauth2_headers=oauth2_headers,
-                    ),
-                    listed_generation,
-                    record_listing=record_listing,
-                )
-
-                if mcp_proxy_mode:
-                    from litellm.proxy._experimental.mcp_server.tool_search import with_mcp_proxy_identity
-
-                    filtered_tools = [with_mcp_proxy_identity(tool, server.server_id) for tool in filtered_tools]
-                else:
-                    filtered_tools = apply_display_name_overrides(filtered_tools, server)
-
-                verbose_logger.debug(
-                    "Successfully fetched %s tools from server %s, %s after filtering",
-                    len(tools),
-                    server.name,
-                    len(filtered_tools),
-                )
-                return filtered_tools, ServerListOk(tool_count=len(filtered_tools))
-            except MCPUpstreamAuthError as e:
-                # Absorb so one unauthenticated server does not empty every other server's
-                # tools. Surfacing the upstream 401 to the client as a re-auth challenge is
-                # intentionally not done here: raising from this list handler cannot produce a
-                # 401 + WWW-Authenticate (the MCP session manager serializes it as a JSON-RPC
-                # error). Single-server routes surface it via the request-scope preemptive
-                # check in _raise_preemptive_401_for_unauthenticated_servers instead.
-                verbose_logger.debug("MCP list_tools: omitting %s; it needs upstream auth", server.name)
-                return [], classify_list_exception(e)
-            except Exception as e:
-                verbose_logger.exception("Error getting tools from server %s: %s", server.name, e)
-                return [], classify_list_exception(e)
-
-        # Fetch tools from all servers in parallel
-        tasks: Final = [_fetch_and_filter_server_tools(server) for server in allowed_mcp_servers]
-        results: Final = await asyncio.gather(*tasks)
-
-        # Flatten results into single list
-        all_tools: Final[list[MCPTool]] = [tool for tools, _ in results for tool in tools]
-        server_outcomes: Final[dict[str, ServerOutcome]] = {
-            _aggregate_server_key(server): outcome
-            for server, (_, outcome) in zip(allowed_mcp_servers, results)
-            if server is not None
-        }
+            aggregated = await aggregate_gateway_tools(
+                context, params, allowed_mcp_servers, _prefetched_oauth_creds, record_listing=record_listing
+            )
+        all_tools: Final = aggregated.tools
+        server_outcomes: Final = aggregated.outcomes
 
         # If logging is enabled, enrich spend_logs_metadata with counts
         if litellm_logging_obj:
-            per_server_tool_counts: Final[dict[str, int]] = {
-                _aggregate_server_key(server): len(server_tools)
-                for server, (server_tools, _) in zip(allowed_mcp_servers, results)
-                if server is not None
+            per_server_tool_counts: Final = {
+                key: outcome.tool_count if isinstance(outcome, ServerListOk) else 0
+                for key, outcome in server_outcomes.items()
             }
 
             metadata_dict: Final = litellm_logging_obj.model_call_details.get("metadata")
@@ -1240,7 +1148,7 @@ async def _get_tools_from_mcp_servers(
 
         verbose_logger.info("Successfully fetched %s tools total from all MCP servers", len(all_tools))
 
-        return AggregateToolListing(tools=all_tools, outcomes=server_outcomes)
+        return aggregated
     except Exception as e:
         # Only fire failure hook if logging was requested for this list-tools execution
         if log_list_tools_to_spendlogs and user_api_key_auth is not None:
@@ -1474,6 +1382,7 @@ async def filter_tools_by_key_team_permissions(
     ]
 
 
+@catalog_operation(lambda: global_mcp_server_manager)
 async def _list_mcp_tools(
     user_api_key_auth: UserAPIKeyAuth | None = None,
     mcp_auth_header: str | None = None,
@@ -1485,6 +1394,8 @@ async def _list_mcp_tools(
     list_tools_log_source: str | None = None,
     client_ip: str | None = None,
     mcp_proxy_mode: bool = False,
+    params: PaginatedRequestParams | None = None,
+    protocol_version: str | None = None,
     *,
     record_listing: bool = False,
 ) -> AggregateToolListing:
@@ -1505,6 +1416,8 @@ async def _list_mcp_tools(
         classified listing outcome
     """
 
+    from mcp.shared.exceptions import MCPError
+
     try:
         listing: Final = await _get_tools_from_mcp_servers(
             user_api_key_auth=user_api_key_auth,
@@ -1518,17 +1431,22 @@ async def _list_mcp_tools(
             client_ip=client_ip,
             mcp_proxy_mode=mcp_proxy_mode,
             record_listing=record_listing,
+            params=params,
+            protocol_version=protocol_version,
         )
         verbose_logger.debug("Successfully fetched %s tools from managed MCP servers", len(listing.tools))
         return listing
-    except HTTPException:
+    except (HTTPException, MCPError):
         raise
     except Exception as e:
+        if params is not None and params.cursor is not None:
+            raise
         verbose_logger.exception("Error getting tools from managed MCP servers: %s", e)
         # Continue with an empty listing instead of failing completely
         return AggregateToolListing(tools=[], outcomes={})
 
 
+@catalog_operation(global_manager)
 async def _list_mcp_prompts(
     user_api_key_auth: UserAPIKeyAuth | None = None,
     mcp_auth_header: str | None = None,
@@ -1570,6 +1488,7 @@ async def _list_mcp_prompts(
     return managed_prompts
 
 
+@catalog_operation(global_manager)
 async def _list_mcp_resources(
     user_api_key_auth: UserAPIKeyAuth | None = None,
     mcp_auth_header: str | None = None,
@@ -1599,6 +1518,7 @@ async def _list_mcp_resources(
     return managed_resources
 
 
+@catalog_operation(global_manager)
 async def _list_mcp_resource_templates(
     user_api_key_auth: UserAPIKeyAuth | None = None,
     mcp_auth_header: str | None = None,
@@ -2087,6 +2007,9 @@ async def _execute_mcp_tool(
                 ),
             )
 
+        if local_tool.server_id is not None and local_tool.server_id != mcp_server.server_id:
+            raise HTTPException(status_code=403, detail="User not allowed to call this tool.")
+
         # `pre_call_tool_check` calls into `proxy_logging_obj` for the
         # pre-call guardrail hooks, so source it from the canonical
         # `proxy_server` module the same way `_handle_managed_mcp_tool`
@@ -2217,6 +2140,12 @@ async def _execute_mcp_tool(
                     ),
                 )
 
+            if (
+                registered_local_tool.server_id is not None
+                and registered_local_tool.server_id != prefix_server.server_id
+            ):
+                raise HTTPException(status_code=403, detail="User not allowed to call this tool.")
+
             from litellm.proxy.proxy_server import proxy_logging_obj
 
             hook_result = await global_mcp_server_manager.pre_call_tool_check(
@@ -2398,6 +2327,7 @@ async def fire_mcp_tool_call_failure_logging(
 
 
 @client
+@catalog_operation(lambda: global_mcp_server_manager)
 async def call_mcp_tool(
     name: str,
     arguments: dict[str, object] | None = None,
@@ -2694,6 +2624,15 @@ async def _handle_local_mcp_tool(
     tool: Final = global_mcp_tool_registry.get_tool(name)
     if not tool:
         raise HTTPException(status_code=404, detail=f"Tool '{name}' not found")
+    server: Final = (
+        global_mcp_server_manager.get_mcp_server_by_id(tool.server_id)
+        if tool.server_id is not None
+        else global_mcp_server_manager.server_owning_tool_name_prefix(name)
+    )
+    if tool.server_id is not None and server is None:
+        raise HTTPException(status_code=503, detail="MCP server configuration changed; retry the operation")
+    if server is not None:
+        global_mcp_server_manager.catalog.assert_current(server)
 
     try:
         if inspect.iscoroutinefunction(tool.handler):
@@ -2733,16 +2672,13 @@ async def _execute_handle_list_tools(
     *,
     log_list_tools_to_spendlogs: bool = True,
 ) -> ListToolsResult:
+    from mcp.shared.exceptions import MCPError
+    from mcp.types import INVALID_PARAMS
+
     try:
-        (
-            user_api_key_auth,
-            mcp_auth_header,
-            mcp_servers,
-            mcp_server_auth_headers,
-            oauth2_headers,
-            raw_headers,
-            _client_ip,
-        ) = context.legacy_auth()
+        user_api_key_auth: Final = context.user_api_key_auth
+        mcp_servers: Final = context.mcp_servers
+        mcp_server_auth_headers: Final = context.mcp_server_auth_headers
         verbose_logger.debug("MCP list_tools - User API Key Auth from context: %s", user_api_key_auth)
         verbose_logger.debug("MCP list_tools - MCP servers from context: %s", mcp_servers)
         verbose_logger.debug(
@@ -2757,41 +2693,39 @@ async def _execute_handle_list_tools(
         )
 
         if context.mcp_proxy_mode:
+            if params.cursor is not None:
+                raise MCPError(code=INVALID_PARAMS, message="Invalid pagination cursor; start a fresh listing")
             return ListToolsResult(tools=[Tool.model_validate(d) for d in get_mcp_proxy_tool_definitions()])
         if getattr(
             getattr(user_api_key_auth, "object_permission", None),
             "mcp_tool_search_enabled",
             False,
         ):
+            if params.cursor is not None:
+                raise MCPError(code=INVALID_PARAMS, message="Invalid pagination cursor; start a fresh listing")
             return ListToolsResult(tools=[Tool.model_validate(d) for d in get_virtual_tool_definitions()])
 
-        # Get mcp_servers from context variable
-        verbose_logger.debug("MCP list_tools - Calling _list_mcp_tools")
-        listing: Final = await _list_mcp_tools(
-            user_api_key_auth=user_api_key_auth,
-            mcp_auth_header=mcp_auth_header,
-            mcp_servers=mcp_servers,
-            mcp_server_auth_headers=mcp_server_auth_headers,
-            oauth2_headers=oauth2_headers,
-            raw_headers=raw_headers,
-            log_list_tools_to_spendlogs=log_list_tools_to_spendlogs,
-            list_tools_log_source="mcp_protocol",
-            client_ip=_client_ip,
-            record_listing=True,
+        from litellm.proxy._experimental.mcp_server.catalog import list_gateway_catalog
+        from litellm.proxy._experimental.mcp_server.server_resolution import MCPServerTargetCatalog
+
+        catalog: Final = MCPServerTargetCatalog(
+            global_mcp_server_manager,
+            listing=partial(list_gateway_catalog, log_list_tools_to_spendlogs=log_list_tools_to_spendlogs),
         )
-        verbose_logger.info("MCP list_tools - Successfully returned %s tools", len(listing.tools))
-        if not listing.outcomes:
-            return ListToolsResult(tools=listing.tools)
-        outcome_meta: Final = {
-            SERVER_OUTCOMES_META_KEY: {key: outcome_wire_value(outcome) for key, outcome in listing.outcomes.items()}
-        }
-        return ListToolsResult.model_validate({"tools": listing.tools, "_meta": outcome_meta})
+        result: Final = await catalog.list(context, ListToolsRequest(params=params))
+        assert isinstance(result, ListToolsResult)
+        return result
+    except MCPError:
+        raise
     except HTTPException as e:
-        from mcp.shared.exceptions import MCPError
         from mcp.types import INVALID_REQUEST
 
         raise MCPError(code=INVALID_REQUEST, message=_http_detail_message(e.detail)) from e
     except Exception as e:
+        if params.cursor is not None:
+            raise MCPError(
+                code=INVALID_PARAMS, message="Catalog continuation unavailable; start a fresh listing"
+            ) from e
         verbose_logger.exception("Error in list_tools endpoint: %s", e)
         # Return empty list instead of failing completely
         # This prevents the HTTP stream from failing and allows the client to get a response
@@ -2949,41 +2883,28 @@ async def _execute_mcp_server_tool_call(
 async def _execute_list_prompts(
     context: OperationContext, params: PaginatedRequestParams, host_progress_callback: ProgressCallback | None = None
 ) -> ListPromptsResult:
+    from mcp.shared.exceptions import MCPError
+    from mcp.types import INVALID_PARAMS, INVALID_REQUEST
+
+    from litellm.proxy._experimental.mcp_server.catalog import list_gateway_catalog
+    from litellm.proxy._experimental.mcp_server.server_resolution import MCPServerTargetCatalog
+
     if context.mcp_proxy_mode:
         _reject_mcp_proxy_operation()
     try:
-        (
-            user_api_key_auth,
-            mcp_auth_header,
-            mcp_servers,
-            mcp_server_auth_headers,
-            oauth2_headers,
-            raw_headers,
-            _client_ip,
-        ) = context.legacy_auth()
-        verbose_logger.debug("MCP list_prompts - User API Key Auth from context: %s", user_api_key_auth)
-        verbose_logger.debug("MCP list_prompts - MCP servers from context: %s", mcp_servers)
-        verbose_logger.debug(
-            "MCP list_prompts - MCP server auth headers: %s",
-            list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None,
-        )
-        # Get mcp_servers from context variable
-        verbose_logger.debug("MCP list_prompts - Calling _list_prompts")
-        prompts: Final = await _list_mcp_prompts(
-            user_api_key_auth=user_api_key_auth,
-            mcp_auth_header=mcp_auth_header,
-            mcp_servers=mcp_servers,
-            mcp_server_auth_headers=mcp_server_auth_headers,
-            oauth2_headers=oauth2_headers,
-            raw_headers=raw_headers,
-            client_ip=_client_ip,
-        )
-        verbose_logger.info("MCP list_prompts - Successfully returned %s prompts", len(prompts))
-        return ListPromptsResult(prompts=prompts)
-    except Exception as e:
-        verbose_logger.exception("Error in list_prompts endpoint: %s", e)
-        # Return empty list instead of failing completely
-        # This prevents the HTTP stream from failing and allows the client to get a response
+        catalog: Final = MCPServerTargetCatalog(global_mcp_server_manager, listing=list_gateway_catalog)
+        result: Final = await catalog.list(context, ListPromptsRequest(params=params))
+        assert isinstance(result, ListPromptsResult)
+        return result
+    except MCPError:
+        raise
+    except HTTPException as error:
+        raise MCPError(code=INVALID_REQUEST, message=_http_detail_message(error.detail)) from error
+    except Exception as error:
+        if params.cursor is not None:
+            raise MCPError(
+                code=INVALID_PARAMS, message="Catalog continuation unavailable; start a fresh listing"
+            ) from error
         return ListPromptsResult(prompts=[])
 
 
@@ -3019,78 +2940,56 @@ async def _execute_get_prompt(
 async def _execute_list_resources(
     context: OperationContext, params: PaginatedRequestParams, host_progress_callback: ProgressCallback | None = None
 ) -> ListResourcesResult:
+    from mcp.shared.exceptions import MCPError
+    from mcp.types import INVALID_PARAMS, INVALID_REQUEST
+
+    from litellm.proxy._experimental.mcp_server.catalog import list_gateway_catalog
+    from litellm.proxy._experimental.mcp_server.server_resolution import MCPServerTargetCatalog
+
     if context.mcp_proxy_mode:
         _reject_mcp_proxy_operation()
     try:
-        (
-            user_api_key_auth,
-            mcp_auth_header,
-            mcp_servers,
-            mcp_server_auth_headers,
-            oauth2_headers,
-            raw_headers,
-            _client_ip,
-        ) = context.legacy_auth()
-        verbose_logger.debug("MCP list_resources - User API Key Auth from context: %s", user_api_key_auth)
-        verbose_logger.debug("MCP list_resources - MCP servers from context: %s", mcp_servers)
-        verbose_logger.debug(
-            "MCP list_resources - MCP server auth headers: %s",
-            list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None,
-        )
-
-        resources: Final = await _list_mcp_resources(
-            user_api_key_auth=user_api_key_auth,
-            mcp_auth_header=mcp_auth_header,
-            mcp_servers=mcp_servers,
-            mcp_server_auth_headers=mcp_server_auth_headers,
-            oauth2_headers=oauth2_headers,
-            raw_headers=raw_headers,
-            client_ip=_client_ip,
-        )
-        verbose_logger.info("MCP list_resources - Successfully returned %s resources", len(resources))
-        return ListResourcesResult(resources=resources)
-    except Exception as e:
-        verbose_logger.exception("Error in list_resources endpoint: %s", e)
+        catalog: Final = MCPServerTargetCatalog(global_mcp_server_manager, listing=list_gateway_catalog)
+        result: Final = await catalog.list(context, ListResourcesRequest(params=params))
+        assert isinstance(result, ListResourcesResult)
+        return result
+    except MCPError:
+        raise
+    except HTTPException as error:
+        raise MCPError(code=INVALID_REQUEST, message=_http_detail_message(error.detail)) from error
+    except Exception as error:
+        if params.cursor is not None:
+            raise MCPError(
+                code=INVALID_PARAMS, message="Catalog continuation unavailable; start a fresh listing"
+            ) from error
         return ListResourcesResult(resources=[])
 
 
 async def _execute_list_resource_templates(
     context: OperationContext, params: PaginatedRequestParams, host_progress_callback: ProgressCallback | None = None
 ) -> ListResourceTemplatesResult:
+    from mcp.shared.exceptions import MCPError
+    from mcp.types import INVALID_PARAMS, INVALID_REQUEST
+
+    from litellm.proxy._experimental.mcp_server.catalog import list_gateway_catalog
+    from litellm.proxy._experimental.mcp_server.server_resolution import MCPServerTargetCatalog
+
     if context.mcp_proxy_mode:
         _reject_mcp_proxy_operation()
     try:
-        (
-            user_api_key_auth,
-            mcp_auth_header,
-            mcp_servers,
-            mcp_server_auth_headers,
-            oauth2_headers,
-            raw_headers,
-            _client_ip,
-        ) = context.legacy_auth()
-        verbose_logger.debug("MCP list_resource_templates - User API Key Auth from context: %s", user_api_key_auth)
-        verbose_logger.debug("MCP list_resource_templates - MCP servers from context: %s", mcp_servers)
-        verbose_logger.debug(
-            "MCP list_resource_templates - MCP server auth headers: %s",
-            list(mcp_server_auth_headers.keys()) if mcp_server_auth_headers else None,
-        )
-
-        resource_templates: Final = await _list_mcp_resource_templates(
-            user_api_key_auth=user_api_key_auth,
-            mcp_auth_header=mcp_auth_header,
-            mcp_servers=mcp_servers,
-            mcp_server_auth_headers=mcp_server_auth_headers,
-            oauth2_headers=oauth2_headers,
-            raw_headers=raw_headers,
-            client_ip=_client_ip,
-        )
-        verbose_logger.info(
-            "MCP list_resource_templates - Successfully returned %s resource templates", len(resource_templates)
-        )
-        return ListResourceTemplatesResult(resource_templates=resource_templates)
-    except Exception as e:
-        verbose_logger.exception("Error in list_resource_templates endpoint: %s", e)
+        catalog: Final = MCPServerTargetCatalog(global_mcp_server_manager, listing=list_gateway_catalog)
+        result: Final = await catalog.list(context, ListResourceTemplatesRequest(params=params))
+        assert isinstance(result, ListResourceTemplatesResult)
+        return result
+    except MCPError:
+        raise
+    except HTTPException as error:
+        raise MCPError(code=INVALID_REQUEST, message=_http_detail_message(error.detail)) from error
+    except Exception as error:
+        if params.cursor is not None:
+            raise MCPError(
+                code=INVALID_PARAMS, message="Catalog continuation unavailable; start a fresh listing"
+            ) from error
         return ListResourceTemplatesResult(resource_templates=[])
 
 
@@ -3217,6 +3116,7 @@ class GatewayOperations:
     @overload
     async def execute(self, operation: ReadResourceRequest, context: OperationContext) -> ReadResourceResult: ...
 
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def execute(self, operation: GatewayOperation, context: OperationContext) -> GatewayResult:
         match operation:
             case DiscoverRequest():

litellm/proxy/_experimental/mcp_server/outbound_credentials/session_credentials.py

@@ -241,12 +241,13 @@ def resolve_session_bearer(
 
 class SessionRefreshOpened(LiteLLMBaseModel):
     """A valid session refresh token presented to the token endpoint: the principal to
-    re-validate and renew under."""
+    re-validate and renew under, and the rotation chain the renewal continues."""
 
     model_config = ConfigDict(frozen=True)
     tag: Literal["opened"] = "opened"
     principal: SessionPrincipal
     jti: str
+    family: str
 
 
 class SessionRefreshInvalid(LiteLLMBaseModel):
@@ -285,4 +286,4 @@ def open_session_refresh_bearer(
         return SessionRefreshInvalid()
     if opened.principal.client_id != expected_client_id:
         return SessionRefreshInvalid()
-    return SessionRefreshOpened(principal=opened.principal, jti=opened.jti)
+    return SessionRefreshOpened(principal=opened.principal, jti=opened.jti, family=opened.family)

litellm/proxy/_experimental/mcp_server/outbound_credentials/session_token.py

@@ -14,8 +14,10 @@ signing approach as :mod:`.envelope`), or RS256 under an operator-provided RSA p
 key (:class:`AsymmetricSessionKeys`) so downstream validators hold only the public half.
 Claims are ``iss``/``iat``/``exp``
 plus ``jti`` (per-mint uniqueness, so two tokens minted in the same second never
-collide and a future revocation list has a stable handle), ``kind``, ``user_id``, and
-``client_id``; ``client_id`` binds the refresh token
+collide and the single-use record has a stable handle), ``kind``, ``user_id``,
+``client_id``, and on a rotated refresh token ``family`` (the ``jti`` of the refresh token
+its chain started from, so a revocation can end every rotation that descends
+from one sign-in); ``client_id`` binds the refresh token
 to the DCR client it was issued to (RFC 6749 section 6) and is carried on the access
 token for parity and audit. There is no encrypted payload: nothing in a session token
 is secret beyond the signature, and reprs never print the signed value because minted
@@ -224,13 +226,16 @@ class MintedSessionToken(LiteLLMBaseModel):
 
 class OpenedSessionToken(LiteLLMBaseModel):
     """A validated session token of either kind: the principal it was minted for, the
-    ``jti`` so the token endpoint can enforce single-use rotation on a refresh token, and
+    ``jti`` so the token endpoint can enforce single-use rotation on a refresh token, the
+    ``family`` every rotation of one refresh token shares (the root token's ``jti``; a
+    token minted before families were stamped, or an access token, is its own root), and
     the signed ``kind``/``iat``/``exp`` so an introspection response can report the
     token's metadata without re-decoding."""
 
     model_config = ConfigDict(frozen=True)
     principal: SessionPrincipal
     jti: str
+    family: str
     kind: SessionTokenKind
     iat: int
     exp: int
@@ -304,6 +309,7 @@ class _SessionClaims(LiteLLMBaseModel):
     resource_server_id: str | None = None
     audience: SessionAudience | None = None
     team_id: str | None = None
+    family: str | None = Field(default=None, min_length=1)
 
 
 def is_session_token(candidate: str) -> bool:
@@ -342,12 +348,14 @@ def mint_session_refresh_token(
     principal: SessionPrincipal,
     keys: SessionSigningKeys,
     now: datetime,
+    family: str | None = None,
 ) -> MintedSessionToken | SessionTokenMintError:
     """Mint the long-lived session REFRESH token for ``principal``.
 
     ``exp`` is ``SESSION_REFRESH_TTL_SECONDS`` from ``now``. Minting a distinct
     ``kind="session_refresh"`` claim is what keeps a refresh token from ever opening as an
-    access credential at the MCP edge.
+    access credential at the MCP edge. ``family`` is the rotation chain the token continues
+    (the opened predecessor's ``family``); ``None`` starts a chain rooted at this token.
     """
     return _mint(
         kind="session_refresh",
@@ -356,6 +364,7 @@ def mint_session_refresh_token(
         expires_at=now + timedelta(seconds=SESSION_REFRESH_TTL_SECONDS),
         keys=keys,
         now=now,
+        family=family,
     )
 
 
@@ -393,6 +402,7 @@ def _mint(
     expires_at: datetime,
     keys: SessionSigningKeys,
     now: datetime,
+    family: str | None = None,
 ) -> MintedSessionToken | SessionTokenTooLarge:
     """Sign the claims for either token kind and enforce the size cap. Shared by both mints
     so the JWT shape, issuer, and size guard cannot drift between access and refresh."""
@@ -407,6 +417,7 @@ def _mint(
         resource_server_id=principal.resource_server_id,
         audience=principal.audience,
         team_id=principal.team_id,
+        family=family,
     )
     token: Final = prefix + _sign_claims(claims, keys)
     size_bytes: Final = len(token.encode("utf-8"))
@@ -465,6 +476,7 @@ def _open(
             team_id=claims.team_id,
         ),
         jti=claims.jti,
+        family=claims.family or claims.jti,
         kind=claims.kind,
         iat=claims.iat,
         exp=claims.exp,

litellm/proxy/_experimental/mcp_server/rest_endpoints.py

@@ -23,6 +23,7 @@ from litellm.exceptions import (
     GuardrailRaisedException,
     ModifyResponseException,
 )
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, global_manager
 from litellm.proxy._experimental.mcp_server.exceptions import (
     MCPServerListError,
     MCPServerURLCredentialsError,
@@ -950,6 +951,7 @@ if MCP_AVAILABLE:
         return await _apply_toolset_scope(user_api_key_dict, toolset.toolset_id)
 
     @router.get("/tools/list", dependencies=[Depends(user_api_key_auth)])
+    @catalog_operation(global_manager)
     async def list_tool_rest_api(
         request: Request,
         server_id: str | None = Query(None, description="The server id to list tools for"),
@@ -1174,6 +1176,7 @@ if MCP_AVAILABLE:
             }
 
     @router.post("/tools/call", dependencies=[Depends(user_api_key_auth)])
+    @catalog_operation(global_manager)
     async def call_tool_rest_api(
         request: Request,
         user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),

litellm/proxy/_experimental/mcp_server/semantic_tool_filter.py

@@ -11,6 +11,7 @@ from typing import TYPE_CHECKING, Any, Final
 from litellm._logging import verbose_logger
 from litellm.exceptions import ContextWindowExceededError
 from litellm.litellm_core_utils.exception_mapping_utils import ExceptionCheckers
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, global_manager
 from litellm.proxy._experimental.mcp_server.faults import iter_exception_tree
 from litellm.proxy._experimental.mcp_server.utils import MCP_TOOL_PREFIX_SEPARATOR
 
@@ -78,6 +79,7 @@ class SemanticMCPToolFilter:
         self._tool_map: dict[str, object] = {}  # MCPTool objects or OpenAI function dicts
         self._index_sync_lock = asyncio.Lock()
 
+    @catalog_operation(global_manager)
     async def build_router_from_mcp_registry(self) -> None:
         """Build semantic router from all MCP tools in the registry (no auth checks)."""
         from litellm.proxy._experimental.mcp_server.mcp_server_manager import (

litellm/proxy/_experimental/mcp_server/server.py

@@ -913,6 +913,8 @@ if MCP_AVAILABLE:
                 return await operations.GatewayOperations(_capture_host_progress_callback(ctx)).execute(
                     ListPromptsRequest(params=params), context
                 )
+        except MCPError:
+            raise
         except Exception as exc:  # noqa: BLE001  # preserve native listing fallback for ingress failures
             verbose_logger.exception("Error in list_prompts endpoint: %s", exc)
             return ListPromptsResult(prompts=[])
@@ -933,6 +935,8 @@ if MCP_AVAILABLE:
                 return await operations.GatewayOperations(_capture_host_progress_callback(ctx)).execute(
                     ListResourcesRequest(params=params), context
                 )
+        except MCPError:
+            raise
         except Exception as exc:  # noqa: BLE001  # preserve native listing fallback for ingress failures
             verbose_logger.exception("Error in list_resources endpoint: %s", exc)
             return ListResourcesResult(resources=[])
@@ -947,6 +951,8 @@ if MCP_AVAILABLE:
                 return await operations.GatewayOperations(_capture_host_progress_callback(ctx)).execute(
                     ListResourceTemplatesRequest(params=params), context
                 )
+        except MCPError:
+            raise
         except Exception as exc:  # noqa: BLE001  # preserve native listing fallback for ingress failures
             verbose_logger.exception("Error in list_resource_templates endpoint: %s", exc)
             return ListResourceTemplatesResult(resource_templates=[])
@@ -1599,6 +1605,9 @@ if MCP_AVAILABLE:
             await operations.global_mcp_server_manager.resolve_toolset_tool_permissions(toolset_ids=[toolset_id])
         )
 
+    from litellm.proxy._experimental.mcp_server.catalog import catalog_operation
+
+    @catalog_operation(lambda: operations.global_mcp_server_manager)
     async def _raise_preemptive_401_for_unauthenticated_servers(
         scope: Scope,
         mcp_servers: list[str] | None,

litellm/proxy/_experimental/mcp_server/server_resolution.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from collections.abc import Awaitable, Callable, Mapping
 from dataclasses import dataclass
-from typing import Final, Literal, Protocol
+from typing import TYPE_CHECKING, Final, Literal, Protocol
 
 from fastapi import HTTPException, status
 
@@ -10,6 +10,9 @@ from litellm.proxy._experimental.mcp_server.ui_session_utils import can_access_m
 from litellm.proxy._types import LiteLLM_MCPServerTable, UserAPIKeyAuth
 from litellm.types.mcp_server.mcp_server_manager import MCPServer
 
+if TYPE_CHECKING:
+    from litellm.proxy._experimental.mcp_server.contracts import CatalogListRequest, CatalogListResult, OperationContext
+
 
 class MCPServerRegistry(Protocol):
     def get_mcp_server_by_id(self, server_id: str) -> MCPServer | None: ...
@@ -130,6 +133,12 @@ class MCPServerTargetCatalog:
     id_client_ip: str | None = None
     name_client_ip: str | None = None
     match_name: bool = False
+    listing: Callable[[OperationContext, CatalogListRequest], Awaitable[CatalogListResult]] | None = None
+
+    async def list(self, context: OperationContext, request: CatalogListRequest) -> CatalogListResult:
+        if self.listing is None:
+            raise RuntimeError("Catalog listing dependency is not configured")
+        return await self.listing(context, request)
 
     async def resolve(
         self,

litellm/proxy/_experimental/mcp_server/state_tokens.py

@@ -0,0 +1,87 @@
+from __future__ import annotations
+
+import base64
+import binascii
+import os
+from enum import Enum
+from typing import Final
+
+from cryptography.exceptions import InvalidTag
+from cryptography.hazmat.primitives import hashes
+from cryptography.hazmat.primitives.ciphers.aead import AESGCM
+from cryptography.hazmat.primitives.kdf.hkdf import HKDF
+from pydantic import BaseModel, ConfigDict, JsonValue, ValidationError
+
+from litellm.proxy._experimental.mcp_server.outbound_credentials.result import Error, Ok, Result
+
+_PREFIX: Final = "mcp_state_v1."
+_MAX_TOKEN_LENGTH: Final = 65536
+_NONCE_BYTES: Final = 12
+
+
+class StateTokenError(str, Enum):
+    MISSING_KEY = "Set the same LITELLM_SALT_KEY on every replica to enable pagination"
+    INVALID = "Invalid pagination state; start a fresh listing"
+    EXPIRED = "Pagination state expired; start a fresh listing"
+    TOO_LARGE = "Pagination state exceeds the supported size"
+
+
+class _Envelope(BaseModel):
+    model_config = ConfigDict(frozen=True, extra="forbid", strict=True)
+
+    expires_at: int
+    value: JsonValue
+
+
+def _cipher(purpose: str) -> Result[AESGCM, StateTokenError]:
+    salt_key: Final = os.getenv("LITELLM_SALT_KEY")
+    if not salt_key:
+        return Error(StateTokenError.MISSING_KEY)
+    if not purpose:
+        return Error(StateTokenError.INVALID)
+    key: Final = HKDF(
+        algorithm=hashes.SHA256(),
+        length=32,
+        salt=b"litellm:mcp:state:v1",
+        info=purpose.encode("utf-8"),
+    ).derive(salt_key.encode("utf-8"))
+    return Ok(AESGCM(key))
+
+
+def seal_state(value: JsonValue, *, purpose: str, expires_at: int, now: int) -> Result[str, StateTokenError]:
+    cipher: Final = _cipher(purpose)
+    if isinstance(cipher, Error):
+        return cipher
+    if expires_at <= now:
+        return Error(StateTokenError.EXPIRED)
+    plaintext: Final = _Envelope(expires_at=expires_at, value=value).model_dump_json().encode("utf-8")
+    if len(plaintext) > _MAX_TOKEN_LENGTH:
+        return Error(StateTokenError.TOO_LARGE)
+    nonce: Final = os.urandom(_NONCE_BYTES)
+    ciphertext: Final = cipher.ok.encrypt(nonce, plaintext, (_PREFIX + purpose).encode("utf-8"))
+    token: Final = _PREFIX + base64.urlsafe_b64encode(nonce + ciphertext).decode("ascii").rstrip("=")
+    return Error(StateTokenError.TOO_LARGE) if len(token) > _MAX_TOKEN_LENGTH else Ok(token)
+
+
+def open_state(token: str, *, purpose: str, now: int) -> Result[JsonValue, StateTokenError]:
+    cipher: Final = _cipher(purpose)
+    if isinstance(cipher, Error):
+        return cipher
+    if len(token) > _MAX_TOKEN_LENGTH:
+        return Error(StateTokenError.TOO_LARGE)
+    if not token.startswith(_PREFIX):
+        return Error(StateTokenError.INVALID)
+    encoded: Final = token[len(_PREFIX) :]
+    try:
+        sealed: Final = base64.b64decode(encoded + "=" * (-len(encoded) % 4), altchars=b"-_", validate=True)
+        if len(sealed) < _NONCE_BYTES + 16 or base64.urlsafe_b64encode(sealed).decode("ascii").rstrip("=") != encoded:
+            return Error(StateTokenError.INVALID)
+        plaintext: Final = cipher.ok.decrypt(
+            sealed[:_NONCE_BYTES], sealed[_NONCE_BYTES:], (_PREFIX + purpose).encode("utf-8")
+        )
+        envelope: Final = _Envelope.model_validate_json(plaintext)
+    except (binascii.Error, ValueError, InvalidTag, ValidationError):
+        return Error(StateTokenError.INVALID)
+    if envelope.expires_at <= now:
+        return Error(StateTokenError.EXPIRED)
+    return Ok(envelope.value)

litellm/proxy/_experimental/mcp_server/tool_registry.py

@@ -1,5 +1,8 @@
+import asyncio
 import json
-from collections.abc import Callable
+from collections.abc import Callable, Generator, Mapping
+from contextlib import contextmanager
+from contextvars import ContextVar
 from typing import TYPE_CHECKING, Any, Final
 
 from litellm._logging import verbose_logger
@@ -22,7 +25,32 @@ class MCPToolRegistry:
 
     def __init__(self):
         # Registry to store all registered tools
-        self.tools: dict[str, MCPTool] = {}
+        self.published_tools: dict[str, MCPTool] = {}  # mutable-ok: register_tool writes entries through .tools
+        self._catalog_tools: ContextVar[tuple[dict[str, MCPTool], asyncio.Event] | None] = ContextVar(
+            "mcp_catalog_tools", default=None
+        )
+
+    @property
+    def tools(self) -> dict[str, MCPTool]:  # mutable-ok: register_tool mutates the returned mapping
+        scoped: Final = self._catalog_tools.get()
+        return scoped[0] if scoped is not None and not scoped[1].is_set() else self.published_tools
+
+    @tools.setter
+    def tools(self, tools: dict[str, MCPTool]) -> None:  # mutable-ok: stored dict is mutated by register_tool
+        self.published_tools = tools
+
+    @contextmanager
+    def catalog_scope(
+        self, tools: Mapping[str, MCPTool]
+    ) -> Generator[dict[str, MCPTool]]:  # mutable-ok: yields the mutable staged copy
+        detached: Final = dict(tools)
+        closed: Final = asyncio.Event()
+        token: Final = self._catalog_tools.set((detached, closed))
+        try:
+            yield detached
+        finally:
+            closed.set()
+            self._catalog_tools.reset(token)
 
     def register_tool(
         self,
@@ -30,6 +58,8 @@ class MCPToolRegistry:
         description: str,
         input_schema: dict[str, Any],
         handler: Callable,
+        *,
+        server_id: str | None = None,
     ) -> None:
         """
         Register a new tool in the registry
@@ -39,6 +69,7 @@ class MCPToolRegistry:
             description=description,
             input_schema=input_schema,
             handler=handler,
+            server_id=server_id,
         )
         verbose_logger.debug("Registered tool: %s", name)
 

litellm/proxy/_experimental/mcp_server/utils.py

@@ -76,7 +76,7 @@ MCP_TOOL_PREFIX_FORMAT: Final = "{server_name}{separator}{tool_name}"
 #     principle hash to the same three chars; that natural-hash collision
 #     IS a routing-correctness issue (the second registrant would otherwise
 #     have its tools misrouted to the first), so registration goes through
-#     ``MCPServerManager._assign_unique_short_prefix`` which rehashes with
+#     ``MCPServerManager.assign_unique_short_prefix`` which rehashes with
 #     a deterministic attempt counter until it finds an unused prefix and
 #     caches the result on ``MCPServer.short_prefix``.  A collision is
 #     logged at INFO when it happens.
@@ -109,7 +109,7 @@ def compute_short_server_prefix(server_id: str, attempt: int = 0) -> str:
     and whose remaining characters are drawn from the full base62
     alphabet.  Pass ``attempt > 0`` to rehash to a different prefix when
     the natural hash collides with a prefix already assigned to another
-    server (see ``MCPServerManager._assign_unique_short_prefix``).  An
+    server (see ``MCPServerManager.assign_unique_short_prefix``).  An
     empty ``server_id`` raises ``ValueError`` — short prefixes require a
     stable identifier to be deterministic.
     """
@@ -309,7 +309,7 @@ def get_server_prefix(server: object) -> str:
     When the short-prefix mode is enabled (``LITELLM_USE_SHORT_MCP_TOOL_PREFIX``)
     a three-character base62 ID is returned.  We prefer the cached
     ``server.short_prefix`` value when set — that field is populated at
-    registration time by ``MCPServerManager._assign_unique_short_prefix``
+    registration time by ``MCPServerManager.assign_unique_short_prefix``
     and resolves natural-hash collisions deterministically — and only fall
     back to the natural hash for ad-hoc / temp-server objects without a
     cached value.  In default mode the historical behaviour is preserved:

litellm/proxy/anthropic_endpoints/gateway_endpoints.py

@@ -2,8 +2,9 @@
 Claude Code gateway protocol.
 
 Implements the wire contract the Claude Code CLI uses to talk to a gateway:
-OAuth 2.0 device-authorization sign-in (RFC 8414 / RFC 8628), inference via the
-Anthropic Messages API, managed settings, and OTLP telemetry ingestion. See
+OAuth 2.0 device-authorization sign-in (RFC 8414 / RFC 8628) with a rotating
+refresh token (RFC 6749 section 6) and RFC 7009 revocation for sign-out, inference
+via the Anthropic Messages API, managed settings, and OTLP telemetry ingestion. See
 https://code.claude.com/docs/en/claude-apps-gateway.
 
 Everything lives under the ``/claude_code_gateway`` base so operators point
@@ -11,7 +12,9 @@ Claude Code at ``https://<proxy-host>/claude_code_gateway`` via ``/login``. The
 device flow reuses the proxy's existing SSO login machinery: the browser leg is
 served by ``/sso/key/generate`` and the shared ``cli_sso_session_cache`` flow,
 so the bearer token minted here is the same session JWT the LiteLLM CLI uses and
-is accepted by every bearer-authenticated proxy route.
+is accepted by every bearer-authenticated proxy route. The refresh token is the
+MCP gateway's sealed session refresh token bound to a fixed client id, so a renewal
+re-mints that JWT from the live user row and shares the DCR flow's single-use record.
 """
 
 import hashlib
@@ -20,9 +23,9 @@ import secrets
 from collections.abc import Mapping
 from dataclasses import dataclass
 from types import MappingProxyType
-from typing import Final
+from typing import Annotated, Final
 
-from fastapi import APIRouter, Depends, Request, Response
+from fastapi import APIRouter, Depends, Request, Response, status
 from fastapi.responses import JSONResponse
 from pydantic import Field, TypeAdapter, ValidationError
 
@@ -34,6 +37,18 @@ from litellm.constants import (
     CLI_SSO_SESSION_TTL_SECONDS,
     LITELLM_CLI_SOURCE_IDENTIFIER,
 )
+from litellm.proxy._experimental.mcp_server.gateway_dcr_flow import (
+    PROXY_API_AUDIENCE,
+    MintedProxyCredential,
+    MintProxyCredential,
+    SessionSigning,
+    proxy_credential_response,
+    refresh_proxy_credential,
+    resolve_session_signing,
+    revoke_session_refresh_token,
+)
+from litellm.proxy._experimental.mcp_server.oauth_utils import TOKEN_NO_CACHE_HEADERS
+from litellm.proxy._experimental.mcp_server.outbound_credentials.session_token import SessionPrincipal
 from litellm.proxy._types import LiteLLM_UserTable, LitellmUserRoles
 from litellm.proxy.anthropic_endpoints.endpoints import anthropic_response, count_tokens
 from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
@@ -43,6 +58,7 @@ from litellm.proxy.management_endpoints.ui_sso import CliSsoTeamDetail
 from litellm.types.llms.base import LiteLLMBaseModel
 
 GATEWAY_PREFIX: Final = "/claude_code_gateway"
+CLAUDE_CODE_CLIENT_ID: Final = "claude_code"
 _DEVICE_CODE_GRANT: Final = "urn:ietf:params:oauth:grant-type:device_code"
 _REFRESH_TOKEN_GRANT: Final = "refresh_token"
 _DEVICE_CODE_SEPARATOR: Final = "."
@@ -77,6 +93,7 @@ class _AuthorizationServerMetadata(LiteLLMBaseModel):
     issuer: str
     device_authorization_endpoint: str
     token_endpoint: str
+    revocation_endpoint: str
     grant_types_supported: tuple[str, ...]
 
 
@@ -89,12 +106,6 @@ class _DeviceAuthorizationBody(LiteLLMBaseModel):
     interval: int
 
 
-class _AccessTokenBody(LiteLLMBaseModel):
-    access_token: str
-    expires_in: int
-    token_type: str = "Bearer"
-
-
 class _ManagedSettingsBody(LiteLLMBaseModel):
     uuid: str
     checksum: str
@@ -174,6 +185,7 @@ async def oauth_authorization_server(request: Request) -> JSONResponse:
             request_base_url=request_base_url, route="claude_code_gateway/oauth/device_authorization"
         ),
         token_endpoint=get_custom_url(request_base_url=request_base_url, route="claude_code_gateway/oauth/token"),
+        revocation_endpoint=get_custom_url(request_base_url=request_base_url, route="claude_code_gateway/oauth/revoke"),
         grant_types_supported=(_DEVICE_CODE_GRANT, _REFRESH_TOKEN_GRANT),
     )
     return JSONResponse(content=metadata.model_dump())
@@ -274,6 +286,34 @@ def _mint_access_token(login: _GatewayLogin) -> str:
     )
 
 
+def _session_only_credential(login: _GatewayLogin) -> Response:
+    return JSONResponse(
+        status_code=status.HTTP_200_OK,
+        content={
+            "access_token": _mint_access_token(login),
+            "token_type": "Bearer",
+            "expires_in": CLI_JWT_EXPIRATION_HOURS * _SECONDS_PER_HOUR,
+        },
+        headers=TOKEN_NO_CACHE_HEADERS,
+    )
+
+
+def _renewable_credential(login: _GatewayLogin, signing: SessionSigning) -> Response:
+    user_id: Final = login.user_info.user_id
+    return proxy_credential_response(
+        MintedProxyCredential(
+            key=_mint_access_token(login),
+            expires_in=CLI_JWT_EXPIRATION_HOURS * _SECONDS_PER_HOUR,
+            user_id=user_id,
+            team_id=login.team_id,
+        ),
+        SessionPrincipal(
+            user_id=user_id, client_id=CLAUDE_CODE_CLIENT_ID, audience=PROXY_API_AUDIENCE, team_id=login.team_id
+        ),
+        signing,
+    )
+
+
 @with_service_target(CLI_SSO_SESSIONS_TARGET)
 async def _claim_device_code(login_id: str, cache: DualCache) -> bool:
     from litellm.proxy.management_endpoints.ui_sso import (
@@ -288,8 +328,14 @@ async def _claim_device_code(login_id: str, cache: DualCache) -> bool:
     return claims == 1
 
 
+def _proxy_credential_minter() -> MintProxyCredential:
+    from litellm.proxy._experimental.mcp_server.proxy_api_credentials import mint_proxy_credential
+
+    return mint_proxy_credential
+
+
 @with_service_target(CLI_SSO_SESSIONS_TARGET)
-async def _handle_device_code_grant(device_code: str | None) -> JSONResponse:
+async def _handle_device_code_grant(device_code: str | None) -> Response:
     from fastapi import HTTPException
 
     from litellm.proxy.management_endpoints.ui_sso import (
@@ -297,7 +343,7 @@ async def _handle_device_code_grant(device_code: str | None) -> JSONResponse:
         _get_cli_sso_flow_or_raise,  # pyright: ignore[reportPrivateUsage]  # shared device-flow helper
         _verify_cli_sso_poll_secret,  # pyright: ignore[reportPrivateUsage]  # shared device-flow helper
     )
-    from litellm.proxy.proxy_server import cli_sso_session_cache
+    from litellm.proxy.proxy_server import cli_sso_session_cache, master_key
 
     if not device_code:
         return _oauth_error_response(
@@ -320,17 +366,23 @@ async def _handle_device_code_grant(device_code: str | None) -> JSONResponse:
     if isinstance(login, _OAuthError):
         return _oauth_error_response(login)
 
-    access_token: Final = _mint_access_token(login)
+    signing: Final = resolve_session_signing(master_key, f"{CLAUDE_CODE_CLIENT_ID} token grant")
+    credential: Final = (
+        _session_only_credential(login) if isinstance(signing, Response) else _renewable_credential(login, signing)
+    )
+    if credential.status_code != status.HTTP_200_OK:
+        return credential
     if not await _claim_device_code(login_id, cli_sso_session_cache):
         return _oauth_error_response(_OAuthError(status_code=400, error="expired_token"))
 
     await cli_sso_session_cache.async_delete_cache(key=_get_cli_sso_flow_cache_key(login_id))
-    body: Final = _AccessTokenBody(access_token=access_token, expires_in=CLI_JWT_EXPIRATION_HOURS * _SECONDS_PER_HOUR)
-    return JSONResponse(content=body.model_dump())
+    return credential
 
 
 @router.post("/oauth/token", include_in_schema=False)
-async def oauth_token(request: Request) -> JSONResponse:
+async def oauth_token(
+    request: Request, mint_proxy_credential: Annotated[MintProxyCredential, Depends(_proxy_credential_minter)]
+) -> Response:
     if not _is_gateway_enabled():
         return _oauth_error_response(_OAuthError(status_code=404, error="not_found"))
 
@@ -342,12 +394,15 @@ async def oauth_token(request: Request) -> JSONResponse:
         return await _handle_device_code_grant(device_code if isinstance(device_code, str) else None)
 
     if grant_type == _REFRESH_TOKEN_GRANT:
-        return _oauth_error_response(
-            _OAuthError(
-                status_code=401,
-                error="invalid_grant",
-                description="This gateway does not issue refresh tokens; sign in again",
-            )
+        from litellm.proxy.proxy_server import master_key, user_api_key_cache
+
+        refresh_token: Final = form.get("refresh_token")
+        return await refresh_proxy_credential(
+            refresh_token=refresh_token if isinstance(refresh_token, str) else None,
+            client_id=CLAUDE_CODE_CLIENT_ID,
+            master_key=master_key,
+            cache=user_api_key_cache,
+            mint_proxy_credential=mint_proxy_credential,
         )
 
     return _oauth_error_response(
@@ -357,6 +412,24 @@ async def oauth_token(request: Request) -> JSONResponse:
     )
 
 
+@router.post("/oauth/revoke", include_in_schema=False)
+async def oauth_revoke(request: Request) -> Response:
+    if not _is_gateway_enabled():
+        return _oauth_error_response(_OAuthError(status_code=404, error="not_found"))
+
+    from litellm.proxy.proxy_server import master_key, user_api_key_cache
+
+    form: Final = await request.form()
+    token: Final = form.get("token")
+    if not isinstance(token, str) or not token:
+        return _oauth_error_response(
+            _OAuthError(status_code=400, error="invalid_request", description="token is required")
+        )
+    return await revoke_session_refresh_token(
+        token=token, client_id=CLAUDE_CODE_CLIENT_ID, master_key=master_key, cache=user_api_key_cache
+    )
+
+
 @router.get("/managed/settings", include_in_schema=False, dependencies=_AUTHENTICATED)
 async def managed_settings(request: Request) -> Response:
     ensure_gateway_enabled()

litellm/proxy/guardrails/guardrail_hooks/mcp_security/mcp_security_guardrail.py

@@ -5,6 +5,7 @@ Validates that MCP servers referenced in request tools are registered
 on the LiteLLM gateway. Blocks or alerts when unregistered servers are found.
 """
 
+from collections.abc import Mapping
 from typing import Any, Final, Literal
 
 from fastapi import HTTPException
@@ -46,7 +47,7 @@ class MCPSecurityGuardrail(CustomGuardrail):
         if self.should_run_guardrail(data=data, event_type=GuardrailEventHooks.pre_call) is not True:
             return data
 
-        unregistered: Final = self._find_unregistered_mcp_servers(data)
+        unregistered: Final = await self._find_unregistered_mcp_servers(data)
         if not unregistered:
             return data
 
@@ -90,21 +91,22 @@ class MCPSecurityGuardrail(CustomGuardrail):
         return server_names
 
     @staticmethod
-    def _find_unregistered_mcp_servers(data: dict) -> set[str]:
+    async def _find_unregistered_mcp_servers(data: Mapping[str, object]) -> frozenset[str]:
         """Check tools in data against the MCP server registry. Returns set of unregistered server names."""
         tools: Final = data.get("tools")
         if not tools or not isinstance(tools, list):
-            return set()
+            return frozenset()
 
         requested_servers: Final = MCPSecurityGuardrail._extract_mcp_server_names_from_tools(tools)
         if not requested_servers:
-            return set()
+            return frozenset()
 
         from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
             global_mcp_server_manager,
         )
 
-        registry: Final = global_mcp_server_manager.get_registry()
-        registered_names: Final = set(registry.keys())
+        async with global_mcp_server_manager.catalog.operation():
+            registry: Final = global_mcp_server_manager.get_registry()
+            registered_names: Final = set(registry.keys())
 
-        return requested_servers - registered_names
+            return frozenset(requested_servers - registered_names)

litellm/proxy/management_endpoints/mcp_management_endpoints.py

@@ -19,7 +19,8 @@ import functools
 import importlib
 import json
 import os
-from collections.abc import Iterable, Mapping, Sequence
+from collections.abc import AsyncGenerator, Iterable, Mapping, Sequence
+from contextlib import asynccontextmanager
 from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from typing import (
@@ -47,6 +48,8 @@ from fastapi.responses import JSONResponse
 from pydantic import TypeAdapter
 from typing_extensions import ReadOnly, TypedDict
 
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, public_catalog_operation
+
 try:
     from prisma.errors import RecordNotFoundError, UniqueViolationError
 except ImportError:
@@ -1139,6 +1142,7 @@ if MCP_AVAILABLE:
         tags=["mcp"],
         description="MCP registry endpoint. Spec: https://github.com/modelcontextprotocol/registry",
     )
+    @public_catalog_operation
     async def get_mcp_registry(request: Request):
         if not _is_public_registry_enabled():
             raise HTTPException(
@@ -1157,7 +1161,8 @@ if MCP_AVAILABLE:
         registry_servers.append({"server": _build_builtin_registry_entry(base_url)})
 
         # Centralized IP-based filtering: external callers only see public servers
-        registered_servers: Final = list(global_mcp_server_manager.get_filtered_registry(client_ip).values())
+        async with global_mcp_server_manager.catalog.operation():
+            registered_servers: Final = list(global_mcp_server_manager.get_filtered_registry(client_ip).values())
 
         registered_servers.sort(key=_build_mcp_registry_server_name)
 
@@ -1187,6 +1192,7 @@ if MCP_AVAILABLE:
             return "view_all"
         return "restricted"
 
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def _get_team_scoped_mcp_server_list(
         team_id: str,
     ) -> list[LiteLLM_MCPServerTable]:
@@ -1225,6 +1231,7 @@ if MCP_AVAILABLE:
 
         return _redact_mcp_credentials_list(servers)
 
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def _resolve_accessible_mcp_servers(
         user_api_key_dict: UserAPIKeyAuth,
     ) -> list[LiteLLM_MCPServerTable]:
@@ -1246,6 +1253,7 @@ if MCP_AVAILABLE:
                 aggregated.setdefault(server.server_id, server)
         return list(aggregated.values())
 
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def _connected_app_reachable_server_ids(user_api_key_dict: UserAPIKeyAuth) -> frozenset[str]:
         """Server ids a connected app authorized by this dashboard user is served on the aggregate
         MCP endpoint, resolved through the one owner of the admitted subject so the page and the
@@ -1262,6 +1270,7 @@ if MCP_AVAILABLE:
         dependencies=[Depends(user_api_key_auth)],
         response_model=list[LiteLLM_MCPServerTable],
     )
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def fetch_all_mcp_servers(
         user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
         team_id: str | None = Query(
@@ -1378,6 +1387,7 @@ if MCP_AVAILABLE:
         description="Health check for MCP servers",
         dependencies=[Depends(user_api_key_auth)],
     )
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def health_check_servers(
         server_ids: list[str] | None = Query(
             None,
@@ -1784,6 +1794,7 @@ if MCP_AVAILABLE:
         dependencies=[Depends(user_api_key_auth)],
         response_model=LiteLLM_MCPServerTable,
     )
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def fetch_mcp_server(
         request: Request,
         server_id: str,
@@ -2145,6 +2156,7 @@ if MCP_AVAILABLE:
 
         return _redact_mcp_credentials(temp_record)
 
+    @public_catalog_operation
     async def _mcp_oauth_user_api_key_auth(request: Request) -> UserAPIKeyAuth:
         """
         Auth dependency for MCP OAuth browser-navigation endpoints (/authorize, /token).
@@ -2202,9 +2214,7 @@ if MCP_AVAILABLE:
 
             server_id: Final[str] = request.path_params.get("server_id", "")
             if server_id:
-                _s = global_mcp_server_manager.get_mcp_server_by_id(server_id)
-                if not _s:
-                    _s = global_mcp_server_manager.get_mcp_server_by_name(server_id)
+                _s = await global_mcp_server_manager.catalog.resolve(server_id)
                 if (
                     _s
                     and getattr(_s, "auth_type", None) == MCPAuth.oauth2
@@ -2271,6 +2281,18 @@ if MCP_AVAILABLE:
         assert authorized.runtime is not None
         return authorized.runtime
 
+    @asynccontextmanager
+    async def _oauth_server_operation(
+        server_id: str,
+        user_api_key_dict: UserAPIKeyAuth,
+        request: Request | None = None,
+    ) -> AsyncGenerator[MCPServer]:
+        if await get_cached_temporary_mcp_server(server_id) is not None:
+            yield await _get_cached_temporary_mcp_server_or_404(server_id, user_api_key_dict, request)
+            return
+        async with global_mcp_server_manager.catalog.operation():
+            yield await _get_cached_temporary_mcp_server_or_404(server_id, user_api_key_dict, request)
+
     @router.get(
         "/server/oauth/{server_id}/authorize",
         include_in_schema=False,
@@ -2288,47 +2310,47 @@ if MCP_AVAILABLE:
         response_type: str | None = None,
         scope: str | None = None,
     ):
-        mcp_server: Final = await _get_cached_temporary_mcp_server_or_404(server_id, user_api_key_dict, request=request)
-        _raise_if_not_oauth2(mcp_server)
-        # Use the server's stored client_id when the caller doesn't supply one
-        stored_or_supplied_client_id: Final = mcp_server.client_id or client_id or ""
-        ephemeral_dcr_client: Final = (
-            await resolve_ephemeral_dcr_client(
+        async with _oauth_server_operation(server_id, user_api_key_dict, request=request) as mcp_server:
+            _raise_if_not_oauth2(mcp_server)
+            # Use the server's stored client_id when the caller doesn't supply one
+            stored_or_supplied_client_id: Final = mcp_server.client_id or client_id or ""
+            ephemeral_dcr_client: Final = (
+                await resolve_ephemeral_dcr_client(
+                    request=request,
+                    mcp_server=mcp_server,
+                    code_challenge=code_challenge,
+                    code_challenge_method=code_challenge_method,
+                    redirect_uri=redirect_uri,
+                )
+                if not stored_or_supplied_client_id
+                else None
+            )
+            resolved_client_id: Final = stored_or_supplied_client_id or (
+                ephemeral_dcr_client.client_id if ephemeral_dcr_client else ""
+            )
+            if not resolved_client_id:
+                raise HTTPException(
+                    status_code=status.HTTP_400_BAD_REQUEST,
+                    detail={
+                        "error": "missing_client_id",
+                        "message": (
+                            "No client_id available for this MCP server. "
+                            "Either configure the server with a client_id or supply one in the request."
+                        ),
+                    },
+                )
+            return await authorize_with_server(
                 request=request,
                 mcp_server=mcp_server,
+                client_id=resolved_client_id,
+                redirect_uri=redirect_uri,
+                state=state,
                 code_challenge=code_challenge,
                 code_challenge_method=code_challenge_method,
-                redirect_uri=redirect_uri,
+                response_type=response_type,
+                scope=scope,
+                ephemeral_dcr_client=ephemeral_dcr_client,
             )
-            if not stored_or_supplied_client_id
-            else None
-        )
-        resolved_client_id: Final = stored_or_supplied_client_id or (
-            ephemeral_dcr_client.client_id if ephemeral_dcr_client else ""
-        )
-        if not resolved_client_id:
-            raise HTTPException(
-                status_code=status.HTTP_400_BAD_REQUEST,
-                detail={
-                    "error": "missing_client_id",
-                    "message": (
-                        "No client_id available for this MCP server. "
-                        "Either configure the server with a client_id or supply one in the request."
-                    ),
-                },
-            )
-        return await authorize_with_server(
-            request=request,
-            mcp_server=mcp_server,
-            client_id=resolved_client_id,
-            redirect_uri=redirect_uri,
-            state=state,
-            code_challenge=code_challenge,
-            code_challenge_method=code_challenge_method,
-            response_type=response_type,
-            scope=scope,
-            ephemeral_dcr_client=ephemeral_dcr_client,
-        )
 
     @router.post(
         "/server/oauth/{server_id}/token",
@@ -2348,47 +2370,47 @@ if MCP_AVAILABLE:
         refresh_token: str | None = Form(None),
         scope: str | None = Form(None),
     ):
-        mcp_server: Final = await _get_cached_temporary_mcp_server_or_404(server_id, user_api_key_dict, request=request)
-        _raise_if_not_oauth2(mcp_server)
-        # Sealed passthrough codes exist only for the authorization_code grant. A refresh_token
-        # grant must never open one: the minted client is unrecoverable after the single flow by
-        # contract, so an expired browser-held token re-runs authorize instead.
-        sealed_code: Final = (
-            redeem_passthrough_authorization_code(code=code, mcp_server=mcp_server, code_verifier=code_verifier)
-            if grant_type == "authorization_code"
-            else None
-        )
-        resolved_code: Final = sealed_code.upstream_code if sealed_code else code
-        # A sealed flow ran the gateway /callback as its upstream redirect (bridge short-circuit
-        # or plain flow alike), so the exchange must present that binding, not the browser page.
-        resolved_redirect_uri: Final = f"{get_request_base_url(request)}/callback" if sealed_code else redirect_uri
-        caller_client_id: Final = sealed_code.client_id if sealed_code else client_id
-        caller_client_secret: Final = sealed_code.client_secret if sealed_code else client_secret
-        resolved_client_id: Final = mcp_server.client_id or caller_client_id or ""
-        if not resolved_client_id:
-            raise HTTPException(
-                status_code=status.HTTP_400_BAD_REQUEST,
-                detail={
-                    "error": "missing_client_id",
-                    "message": (
-                        "No client_id available for this MCP server. "
-                        "Either configure the server with a client_id or supply one in the request."
-                    ),
-                },
+        async with _oauth_server_operation(server_id, user_api_key_dict, request=request) as mcp_server:
+            _raise_if_not_oauth2(mcp_server)
+            # Sealed passthrough codes exist only for the authorization_code grant. A refresh_token
+            # grant must never open one: the minted client is unrecoverable after the single flow by
+            # contract, so an expired browser-held token re-runs authorize instead.
+            sealed_code: Final = (
+                redeem_passthrough_authorization_code(code=code, mcp_server=mcp_server, code_verifier=code_verifier)
+                if grant_type == "authorization_code"
+                else None
+            )
+            resolved_code: Final = sealed_code.upstream_code if sealed_code else code
+            # A sealed flow ran the gateway /callback as its upstream redirect (bridge short-circuit
+            # or plain flow alike), so the exchange must present that binding, not the browser page.
+            resolved_redirect_uri: Final = f"{get_request_base_url(request)}/callback" if sealed_code else redirect_uri
+            caller_client_id: Final = sealed_code.client_id if sealed_code else client_id
+            caller_client_secret: Final = sealed_code.client_secret if sealed_code else client_secret
+            resolved_client_id: Final = mcp_server.client_id or caller_client_id or ""
+            if not resolved_client_id:
+                raise HTTPException(
+                    status_code=status.HTTP_400_BAD_REQUEST,
+                    detail={
+                        "error": "missing_client_id",
+                        "message": (
+                            "No client_id available for this MCP server. "
+                            "Either configure the server with a client_id or supply one in the request."
+                        ),
+                    },
+                )
+            return await exchange_token_with_server(
+                request=request,
+                mcp_server=mcp_server,
+                grant_type=grant_type,
+                code=resolved_code,
+                redirect_uri=resolved_redirect_uri,
+                client_id=resolved_client_id,
+                client_secret=caller_client_secret,
+                code_verifier=code_verifier,
+                refresh_token=refresh_token,
+                scope=scope,
+                client_token_endpoint_auth_method=sealed_code.token_endpoint_auth_method if sealed_code else None,
             )
-        return await exchange_token_with_server(
-            request=request,
-            mcp_server=mcp_server,
-            grant_type=grant_type,
-            code=resolved_code,
-            redirect_uri=resolved_redirect_uri,
-            client_id=resolved_client_id,
-            client_secret=caller_client_secret,
-            code_verifier=code_verifier,
-            refresh_token=refresh_token,
-            scope=scope,
-            client_token_endpoint_auth_method=sealed_code.token_endpoint_auth_method if sealed_code else None,
-        )
 
     @router.post(
         "/server/oauth/{server_id}/register",
@@ -2400,22 +2422,22 @@ if MCP_AVAILABLE:
         server_id: str,
         user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
     ):
-        mcp_server: Final = await _get_cached_temporary_mcp_server_or_404(server_id, user_api_key_dict, request=request)
-        request_data: Final = await _read_request_body(request=request)
-        data: Final[dict] = {**request_data}
-        client_redirect_uris: Final = client_supplied_redirect_uris(data.get("redirect_uris"))
+        async with _oauth_server_operation(server_id, user_api_key_dict, request=request) as mcp_server:
+            request_data: Final = await _read_request_body(request=request)
+            data: Final[Mapping[str, object]] = {**request_data}
+            client_redirect_uris: Final = client_supplied_redirect_uris(data.get("redirect_uris"))
 
-        return await register_client_with_server(
-            request=request,
-            mcp_server=mcp_server,
-            client_name=data.get("client_name", ""),
-            grant_types=data.get("grant_types", []),
-            response_types=data.get("response_types", []),
-            token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
-            fallback_client_id=server_id,
-            persist_credentials=_user_is_full_admin(user_api_key_dict),
-            client_redirect_uris=client_redirect_uris,
-        )
+            return await register_client_with_server(
+                request=request,
+                mcp_server=mcp_server,
+                client_name=data.get("client_name", ""),
+                grant_types=data.get("grant_types", []),
+                response_types=data.get("response_types", []),
+                token_endpoint_auth_method=data.get("token_endpoint_auth_method", ""),
+                fallback_client_id=server_id,
+                persist_credentials=_user_is_full_admin(user_api_key_dict),
+                client_redirect_uris=client_redirect_uris,
+            )
 
     @router.delete(
         "/server/{server_id}",
@@ -2791,6 +2813,7 @@ if MCP_AVAILABLE:
 
     # ── Per-user MCP env var endpoints ────────────────────────────────────────
 
+    @catalog_operation(lambda: global_mcp_server_manager)
     async def _authorize_and_fetch_mcp_server(
         prisma_client,
         user_api_key_dict: UserAPIKeyAuth,

litellm/proxy/proxy_server.py

@@ -340,6 +340,7 @@ from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 from litellm.llms.openai_like.model_info import MODEL_INFO_REFRESH_SECONDS
 from litellm.llms.vertex_ai.vertex_llm_base import VertexBase
 from litellm.proxy._experimental.mcp_server.byok_credential_cache import byok_credential_cache
+from litellm.proxy._experimental.mcp_server.catalog import public_catalog_operation
 from litellm.proxy._experimental.mcp_server.stdio_gate import MCP_STDIO_ENABLED_ENV_VAR, is_mcp_stdio_flag_key
 from litellm.proxy._lazy_features import attach_lazy_features, reserve_lazy_slot
 from litellm.proxy._types import *
@@ -20389,30 +20390,26 @@ async def _resolve_mcp_csv_tokens(csv_segment: str, client_ip: str | None) -> li
     all-unmatched server filter falls back to the full ``allowed_mcp_servers``
     list and silently broadens the request scope).
     """
-    from litellm.constants import DEFAULT_MCP_NAMESPACE_CSV_MAX_TOKENS
-    from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
-        global_mcp_server_manager,
-    )
+    from litellm.proxy._experimental.mcp_server.catalog import global_manager
 
-    seen: Final[set] = set()
-    deduped: Final[list[str]] = []
-    for raw in csv_segment.split(","):
-        token = raw.strip()
-        if not token or token in seen:
-            continue
-        seen.add(token)
-        deduped.append(token)
-        if len(deduped) >= DEFAULT_MCP_NAMESPACE_CSV_MAX_TOKENS:
-            break
+    async with global_manager().catalog.operation():
+        from litellm.constants import DEFAULT_MCP_NAMESPACE_CSV_MAX_TOKENS
+        from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
+            global_mcp_server_manager,
+        )
 
-    resolved: Final[list[str]] = []
-    for token in deduped:
-        if global_mcp_server_manager.get_mcp_server_by_name(token, client_ip=client_ip):
-            resolved.append(token)
-            continue
-        if await _is_mcp_access_group_cached(token):
-            resolved.append(token)
-    return resolved
+        deduped: Final = tuple(
+            token for token in dict.fromkeys(raw.strip() for raw in csv_segment.split(",")) if token
+        )[:DEFAULT_MCP_NAMESPACE_CSV_MAX_TOKENS]
+
+        resolved: Final[list[str]] = []  # mutable-ok: sequential await per token cannot live in a comprehension
+        for token in deduped:
+            if global_mcp_server_manager.get_mcp_server_by_name(token, client_ip=client_ip):
+                resolved.append(token)
+                continue
+            if await _is_mcp_access_group_cached(token):
+                resolved.append(token)
+        return resolved
 
 
 async def _is_mcp_access_group_cached(name: str) -> bool:
@@ -20449,12 +20446,13 @@ async def _is_mcp_access_group_cached(name: str) -> bool:
     "/{mcp_server_name}/mcp",
     methods=["GET", "POST", "PUT", "DELETE", "PATCH", "OPTIONS", "HEAD"],
 )
+@public_catalog_operation
 async def dynamic_mcp_route(mcp_server_name: str, request: Request):
     """Handle /{name}/mcp for MCP server aliases, toolsets, MCP access group tags, and comma-separated lists.
 
     Resolution order:
     1. Registered MCP server alias / name
-    2. Comma-separated list (short-circuits before any DB call)
+    2. Comma-separated list
     3. Toolset name (DB lookup, cached)
     4. MCP access group tag (DB lookup, cached)
     """
@@ -20467,7 +20465,9 @@ async def dynamic_mcp_route(mcp_server_name: str, request: Request):
         client_ip: Final = IPAddressUtils.get_mcp_client_ip(request)
 
         # 1. Registered MCP server alias
-        if global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name, client_ip=client_ip):
+        async with global_mcp_server_manager.catalog.operation():
+            server: Final = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name, client_ip=client_ip)
+        if server is not None:
             return await _mcp_forward_as_path(mcp_server_name, request)
 
         # 2. Comma-separated list — validate every token resolves to a known

litellm/repositories/config_repository.py

@@ -22,6 +22,9 @@ class _ConfigRow(Protocol):
     @property
     def param_value(self) -> object: ...
 
+    @property
+    def reload_revision(self) -> int | None: ...
+
 
 class _ConfigTable(Protocol):
     async def find_unique(self, *, where: Mapping[str, str]) -> _ConfigRow | None: ...

litellm/responses/mcp/litellm_proxy_mcp_handler.py

@@ -10,6 +10,7 @@ from openai.types.responses.function_tool_param import FunctionToolParam
 from litellm._logging import verbose_logger
 from litellm.constants import MAXIMUM_TRACEBACK_LINES_TO_LOG
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+from litellm.proxy._experimental.mcp_server.catalog import catalog_operation, global_manager
 from litellm.proxy._experimental.mcp_server.utils import (
     iter_known_server_prefixes,
     logging_safe_mcp_headers,
@@ -112,6 +113,7 @@ async def _toolset_exists(name: str) -> bool:
         return False
 
 
+@catalog_operation(global_manager)
 async def _gateway_served_names(
     names: Collection[str],
     servers: Callable[[], Collection[MCPServer]] = _registered_mcp_servers,
@@ -185,6 +187,7 @@ class LiteLLM_Proxy_MCP_Handler:
     _split_mcp_tools = split_mcp_tools
 
     @staticmethod
+    @catalog_operation(global_manager)
     async def routes_through_gateway(
         tools: Iterable[Mapping[str, object]] | None,
         served_names: Callable[[Collection[str]], Awaitable[frozenset[str]]] = _gateway_served_names,
@@ -238,6 +241,7 @@ class LiteLLM_Proxy_MCP_Handler:
             return user_api_key_auth
 
     @staticmethod
+    @catalog_operation(global_manager)
     async def _get_mcp_tools_from_manager(
         user_api_key_auth: "UserAPIKeyAuth | None",
         mcp_tools_with_litellm_proxy: Iterable[Mapping[str, object]] | None,
@@ -704,6 +708,7 @@ class LiteLLM_Proxy_MCP_Handler:
         return result_text or "Tool executed successfully"
 
     @staticmethod
+    @catalog_operation(global_manager)
     async def execute_tool_calls(
         tool_server_map: dict[str, str],
         tool_calls: Sequence[object],

litellm/router_utils/cooldown_handlers.py

@@ -250,11 +250,7 @@ def _is_cooldown_required(
                 # Cool down 429 Rate Limit Errors
                 return True
 
-            elif exception_status == 401:
-                # Cool down 401 Auth Errors
-                return True
-
-            elif exception_status == 408 or exception_status == 404:
+            elif exception_status in (401, 402, 408, 404):
                 return True
 
             else:
@@ -362,8 +358,17 @@ def _should_cooldown_deployment(
             or litellm_router_instance.team_model_has_alternatives(deployment)
         )
 
-    ## CHECK DEPLOYMENT-LEVEL POLICY FIRST (overrides router-level)
+    exception_status_int: Final = cast_exception_status_to_int(exception_status)
     dep_policy, dep_allowed_fails = _get_deployment_cooldown_policy(litellm_router_instance, deployment)
+    if (
+        is_single_deployment_model_group
+        and exception_status_int == 402
+        and _resolve_allowed_fails_from_policy(dep_policy, original_exception) is None
+        and litellm_router_instance.get_allowed_fails_from_policy(original_exception) is None
+    ):
+        return False
+
+    ## CHECK DEPLOYMENT-LEVEL POLICY FIRST (overrides router-level)
     if dep_policy is not None or dep_allowed_fails is not None:
         return _should_cooldown_based_on_deployment_policy(
             litellm_router_instance,
@@ -398,7 +403,6 @@ def _should_cooldown_deployment(
             num_fails_this_minute,
         )
 
-        exception_status_int: Final = cast_exception_status_to_int(exception_status)
         if exception_status_int == 429 and not is_single_deployment_model_group:
             return True
         elif percent_fails == 1.0 and total_requests_this_minute >= SINGLE_DEPLOYMENT_TRAFFIC_FAILURE_THRESHOLD:
@@ -412,7 +416,7 @@ def _should_cooldown_deployment(
             # Only apply error rate cooldown when we have enough requests to make the percentage meaningful
             return True
 
-        elif litellm.should_retry(status_code=cast_exception_status_to_int(exception_status)) is False:
+        elif litellm.should_retry(status_code=exception_status_int) is False:
             return True
 
         return False

litellm/types/mcp_server/mcp_server_manager.py

@@ -238,7 +238,7 @@ class MCPServer(LiteLLMBaseModel):
     # None or a value <= 0 means unlimited.
     max_concurrent_requests: int | None = None
     # Resolved short-ID tool prefix when LITELLM_USE_SHORT_MCP_TOOL_PREFIX is
-    # enabled.  Set by ``MCPServerManager._assign_unique_short_prefix`` at
+    # enabled.  Set by ``MCPServerManager.assign_unique_short_prefix`` at
     # registration time so that natural-hash collisions between two
     # different ``server_id`` values are bumped deterministically.  Left
     # ``None`` in default-prefix mode.

litellm/types/mcp_server/tool_registry.py

@@ -1,7 +1,7 @@
 from collections.abc import Callable
 from typing import Any, ClassVar
 
-from pydantic import ConfigDict
+from pydantic import ConfigDict, Field
 
 from litellm.types.llms.base import LiteLLMBaseModel
 
@@ -12,6 +12,7 @@ class MCPTool(LiteLLMBaseModel):
     description: str
     input_schema: dict[str, Any]
     handler: Callable
+    server_id: str | None = Field(default=None, frozen=True)
 
 
 class ToolSchema(LiteLLMBaseModel):

model_prices_and_context_window.json

@@ -4691,9 +4691,9 @@
         "max_output_tokens": 4096,
         "max_tokens": 4096,
         "mode": "realtime",
-        "output_cost_per_audio_token": 8e-05,
+        "output_cost_per_audio_token": 8.8e-05,
         "output_cost_per_token": 2.2e-05,
-        "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_modalities": [
             "text",
             "audio"
@@ -5752,14 +5752,14 @@
     },
     "azure/gpt-audio-1.5": {
         "deprecation_date": "2027-08-24",
-        "input_cost_per_audio_token": 4e-05,
+        "input_cost_per_audio_token": 3.2e-05,
         "input_cost_per_token": 2.5e-06,
         "litellm_provider": "azure",
         "max_input_tokens": 128000,
         "max_output_tokens": 16384,
         "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_audio_token": 8e-05,
+        "output_cost_per_audio_token": 6.4e-05,
         "output_cost_per_token": 1e-05,
         "supported_endpoints": [
             "/v1/chat/completions"
@@ -5781,19 +5781,20 @@
         "supports_system_messages": true,
         "supports_tool_choice": true,
         "supports_vision": false,
-        "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure"
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/"
     },
     "azure/gpt-audio-1.5-2026-02-23": {
         "deprecation_date": "2027-08-24",
-        "input_cost_per_audio_token": 4e-05,
+        "input_cost_per_audio_token": 3.2e-05,
         "input_cost_per_token": 2.5e-06,
         "litellm_provider": "azure",
         "max_input_tokens": 128000,
         "max_output_tokens": 16384,
         "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_audio_token": 8e-05,
+        "output_cost_per_audio_token": 6.4e-05,
         "output_cost_per_token": 1e-05,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/chat/completions"
         ],
@@ -5948,15 +5949,16 @@
         "supports_vision": true
     },
     "azure/gpt-4o-mini-audio-preview-2024-12-17": {
-        "input_cost_per_audio_token": 4e-05,
-        "input_cost_per_token": 2.5e-06,
+        "input_cost_per_audio_token": 1e-05,
+        "input_cost_per_token": 1.5e-07,
         "litellm_provider": "azure",
         "max_input_tokens": 128000,
         "max_output_tokens": 16384,
         "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_audio_token": 8e-05,
-        "output_cost_per_token": 1e-05,
+        "output_cost_per_audio_token": 2e-05,
+        "output_cost_per_token": 6e-07,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/chat/completions"
         ],
@@ -6355,27 +6357,28 @@
     },
     "azure/gpt-4o-transcribe": {
         "deprecation_date": "2026-10-15",
-        "input_cost_per_audio_token": 2.5e-06,
+        "input_cost_per_audio_token": 6e-06,
         "input_cost_per_token": 2.5e-06,
         "litellm_provider": "azure",
         "max_input_tokens": 16000,
         "max_output_tokens": 2000,
         "mode": "audio_transcription",
         "output_cost_per_token": 1e-05,
-        "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule",
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/audio/transcriptions"
         ]
     },
     "azure/gpt-4o-transcribe-diarize": {
         "deprecation_date": "2027-04-15",
-        "input_cost_per_audio_token": 2.5e-06,
+        "input_cost_per_audio_token": 6e-06,
         "input_cost_per_token": 2.5e-06,
         "litellm_provider": "azure",
         "max_input_tokens": 16000,
         "max_output_tokens": 2000,
         "mode": "audio_transcription",
         "output_cost_per_token": 1e-05,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/audio/transcriptions"
         ]
@@ -10325,6 +10328,7 @@
         "cache_read_input_token_cost_batches": 1e-08
     },
     "azure/gpt-image-1": {
+        "cache_read_input_image_token_cost": 2.5e-06,
         "cache_read_input_token_cost": 1.25e-06,
         "deprecation_date": "2026-10-23",
         "input_cost_per_image_token": 1e-05,
@@ -10332,28 +10336,32 @@
         "litellm_provider": "azure",
         "mode": "image_generation",
         "output_cost_per_image_token": 4e-05,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
         ]
     },
     "azure/hd/1024-x-1024/dall-e-3": {
-        "input_cost_per_pixel": 7.629e-08,
+        "input_cost_per_pixel": 8.39233e-08,
         "litellm_provider": "azure",
         "mode": "image_generation",
-        "output_cost_per_token": 0.0
+        "output_cost_per_token": 0.0,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/"
     },
     "azure/hd/1024-x-1792/dall-e-3": {
-        "input_cost_per_pixel": 6.539e-08,
+        "input_cost_per_pixel": 7.19343e-08,
         "litellm_provider": "azure",
         "mode": "image_generation",
-        "output_cost_per_token": 0.0
+        "output_cost_per_token": 0.0,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/"
     },
     "azure/hd/1792-x-1024/dall-e-3": {
-        "input_cost_per_pixel": 6.539e-08,
+        "input_cost_per_pixel": 7.19343e-08,
         "litellm_provider": "azure",
         "mode": "image_generation",
-        "output_cost_per_token": 0.0
+        "output_cost_per_token": 0.0,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/"
     },
     "azure/high/1024-x-1024/gpt-image-1": {
         "deprecation_date": "2026-10-23",
@@ -10446,6 +10454,7 @@
         ]
     },
     "azure/gpt-image-1-mini": {
+        "cache_read_input_image_token_cost": 2.5e-07,
         "cache_read_input_token_cost": 2e-07,
         "deprecation_date": "2027-04-07",
         "input_cost_per_image_token": 2.5e-06,
@@ -10453,12 +10462,14 @@
         "litellm_provider": "azure",
         "mode": "image_generation",
         "output_cost_per_image_token": 8e-06,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
         ]
     },
     "azure/gpt-image-1.5": {
+        "cache_read_input_image_token_cost": 2e-06,
         "deprecation_date": "2026-12-16",
         "cache_read_input_token_cost": 1.25e-06,
         "input_cost_per_token": 5e-06,
@@ -10466,12 +10477,15 @@
         "litellm_provider": "azure",
         "mode": "image_generation",
         "output_cost_per_image_token": 3.2e-05,
+        "output_cost_per_token": 1e-05,
+        "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/",
         "supported_endpoints": [
             "/v1/images/generations",
             "/v1/images/edits"
         ]
     },
     "azure/gpt-image-1.5-2025-12-16": {
+        "cache_read_input_image_token_cost": 2e-06,
         "cache_read_input_token_cost": 1.25e-06,
         "deprecation_date": "2026-12-16",
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         "supports_reasoning": false,
-        "supports_tool_choice": true,
         "supports_response_schema": true,
+        "supports_tool_choice": true,
         "supports_vision": true,
         "supports_web_search": false
     },
@@ -75009,13 +75080,13 @@
     },
     "openrouter/meta/muse-glimmer-30b": {
         "cache_read_input_token_cost": 4e-08,
-        "input_cost_per_token": 3.5e-07,
+        "input_cost_per_token": 3e-07,
         "litellm_provider": "openrouter",
         "max_input_tokens": 131072,
-        "max_output_tokens": 117964,
-        "max_tokens": 117964,
+        "max_output_tokens": 16384,
+        "max_tokens": 16384,
         "mode": "chat",
-        "output_cost_per_token": 1.5e-06,
+        "output_cost_per_token": 1.2e-06,
         "source": "https://openrouter.ai/api/v1/models",
         "supports_audio_input": false,
         "supports_function_calling": true,
@@ -76935,12 +77006,12 @@
         "supports_web_search": false
     },
     "openrouter/thinkingmachines/inkling": {
-        "cache_read_input_token_cost": 1.6e-07,
-        "input_cost_per_token": 9.5e-07,
+        "cache_read_input_token_cost": 1.7e-07,
+        "input_cost_per_token": 1e-06,
         "litellm_provider": "openrouter",
         "max_input_tokens": 524288,
-        "max_output_tokens": 262144,
-        "max_tokens": 262144,
+        "max_output_tokens": 471859,
+        "max_tokens": 471859,
         "mode": "chat",
         "output_cost_per_token": 4.05e-06,
         "source": "https://openrouter.ai/api/v1/models",
@@ -80556,5 +80627,75 @@
         "supports_tool_choice": true,
         "supports_vision": true,
         "supports_web_search": true
+    },
+    "openrouter/mistralai/mistral-large-4-0": {
+        "cache_read_input_token_cost": 7e-08,
+        "input_cost_per_token": 6.8e-07,
+        "litellm_provider": "openrouter",
+        "max_input_tokens": 524288,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
+        "mode": "chat",
+        "output_cost_per_token": 2.09e-06,
+        "source": "https://openrouter.ai/api/v1/models",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": false,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": false
+    },
+    "openrouter/google/gemini-nano-banana-2.1": {
+        "input_cost_per_token": 1.5e-06,
+        "litellm_provider": "openrouter",
+        "max_input_tokens": 65536,
+        "max_output_tokens": 58982,
+        "max_tokens": 58982,
+        "mode": "chat",
+        "output_cost_per_image_token": 3e-05,
+        "output_cost_per_token": 7.5e-06,
+        "source": "https://openrouter.ai/api/v1/models",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_pdf_input": false,
+        "supports_prompt_caching": false,
+        "supports_reasoning": true,
+        "supports_response_schema": true,
+        "supports_tool_choice": true,
+        "supports_vision": true,
+        "supports_web_search": true
+    },
+    "in.moonshotai.kimi-k3": {
+        "cache_creation_input_token_cost": 4.125e-06,
+        "cache_creation_input_token_cost_flex": 2.0625e-06,
+        "cache_creation_input_token_cost_priority": 7.21875e-06,
+        "cache_read_input_token_cost": 3.3e-07,
+        "cache_read_input_token_cost_flex": 1.65e-07,
+        "cache_read_input_token_cost_priority": 5.775e-07,
+        "input_cost_per_token": 3.3e-06,
+        "input_cost_per_token_flex": 1.65e-06,
+        "input_cost_per_token_priority": 5.775e-06,
+        "litellm_provider": "bedrock_converse",
+        "max_input_tokens": 1000000,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
+        "mode": "chat",
+        "output_cost_per_token": 1.65e-05,
+        "output_cost_per_token_flex": 8.25e-06,
+        "output_cost_per_token_priority": 2.8875e-05,
+        "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k3.md",
+        "supports_audio_input": false,
+        "supports_function_calling": true,
+        "supports_prompt_cache_breakpoint": false,
+        "supports_prompt_caching": true,
+        "supports_reasoning": true,
+        "supports_regex_lookaround": false,
+        "supports_response_schema": true,
+        "supports_system_messages": true,
+        "supports_tool_choice": true,
+        "supports_vision": true
     }
 }

tests/agent_tests/test_a2a_agent.py

@@ -1,119 +0,0 @@
-"""
-Simple A2A agent tests - non-streaming and streaming.
-
-These tests use a mocked A2A client to avoid network/env dependencies.
-"""
-
-from types import SimpleNamespace
-from uuid import uuid4
-
-import pytest
-
-
-class MockA2AResponse:
-    def __init__(self, text: str):
-        self._payload = {
-            "id": str(uuid4()),
-            "jsonrpc": "2.0",
-            "result": {
-                "message": {
-                    "role": "agent",
-                    "parts": [{"kind": "text", "text": text}],
-                    "messageId": uuid4().hex,
-                }
-            },
-        }
-
-    def model_dump(self, mode="json", exclude_none=True):
-        return self._payload
-
-
-class MockA2AStreamingChunk(MockA2AResponse):
-    def __init__(self, text: str, state: str):
-        super().__init__(text=text)
-        self._payload["result"]["status"] = {"state": state}
-
-
-class MockA2AClient:
-    def __init__(self):
-        self._litellm_agent_card = SimpleNamespace(
-            name="mock-agent", url="http://mock-agent.local"
-        )
-
-    async def send_message(self, request, *, context=None):
-        from a2a.compat.v0_3.conversions import pb2_v10
-
-        for text in ("hel", "hello"):
-            event = pb2_v10.StreamResponse()
-            message = event.message
-            message.message_id = uuid4().hex
-            message.role = pb2_v10.ROLE_AGENT
-            message.parts.add().text = text
-            yield event
-
-
-@pytest.fixture
-def mock_a2a_client(monkeypatch):
-    import litellm.a2a_protocol.main as a2a_main
-
-    async def _fake_create_a2a_client(
-        base_url, timeout=60.0, extra_headers=None, streaming=False, relative_card_path=None
-    ):
-        return MockA2AClient()
-
-    monkeypatch.setattr(a2a_main, "create_a2a_client", _fake_create_a2a_client)
-
-
-@pytest.mark.asyncio
-async def test_a2a_non_streaming(mock_a2a_client):
-    """Test non-streaming A2A request."""
-    from a2a.compat.v0_3.types import MessageSendParams, SendMessageRequest
-    from litellm.a2a_protocol import asend_message
-
-    request = SendMessageRequest(
-        id=str(uuid4()),
-        params=MessageSendParams(
-            message={
-                "role": "user",
-                "parts": [{"kind": "text", "text": "Say hello in one word"}],
-                "messageId": uuid4().hex,
-            }
-        ),
-    )
-
-    response = await asend_message(
-        request=request,
-        api_base="http://mock",
-    )
-
-    assert response is not None
-    print(f"\nNon-streaming response: {response}")
-
-
-@pytest.mark.asyncio
-async def test_a2a_streaming(mock_a2a_client):
-    """Test streaming A2A request."""
-    from a2a.compat.v0_3.types import MessageSendParams, SendStreamingMessageRequest
-    from litellm.a2a_protocol import asend_message_streaming
-
-    request = SendStreamingMessageRequest(
-        id=str(uuid4()),
-        params=MessageSendParams(
-            message={
-                "role": "user",
-                "parts": [{"kind": "text", "text": "Say hello in one word"}],
-                "messageId": uuid4().hex,
-            }
-        ),
-    )
-
-    chunks = []
-    async for chunk in asend_message_streaming(
-        request=request,
-        api_base="http://mock",
-    ):
-        chunks.append(chunk)
-        print(f"\nStreaming chunk: {chunk}")
-
-    assert len(chunks) > 0, "Should receive at least one chunk"
-    print(f"\nTotal chunks received: {len(chunks)}")

tests/audio_tests/test_audio_speech.py

@@ -1,12 +1,7 @@
 # What is this?
 ## unit tests for openai tts endpoint
 
-import asyncio
 import os
-import random
-import time
-import traceback
-from litellm._uuid import uuid
 
 from dotenv import load_dotenv
 
@@ -15,7 +10,6 @@ load_dotenv()
 from pathlib import Path
 from unittest.mock import AsyncMock, MagicMock, patch
 
-import openai
 import pytest
 
 import litellm
@@ -87,36 +81,6 @@ async def test_audio_speech_litellm_openai(sync_mode):
     )
 
 
-@pytest.mark.parametrize(
-    "sync_mode",
-    [False, True],
-)
-@pytest.mark.skip(reason="local only test - we run testing using MockRequests below")
-@pytest.mark.asyncio
-@pytest.mark.flaky(retries=3, delay=1)
-async def test_audio_speech_litellm_vertex(sync_mode):
-    litellm.set_verbose = True
-    speech_file_path = Path(__file__).parent / "speech_vertex.mp3"
-    model = "vertex_ai/test"
-    if sync_mode:
-        response = litellm.speech(
-            model="vertex_ai/test",
-            input="hello what llm guardrail do you have",
-        )
-
-        response.stream_to_file(speech_file_path)
-
-    else:
-        response = await litellm.aspeech(
-            model="vertex_ai/",
-            input="async hello what llm guardrail do you have",
-        )
-
-        from types import SimpleNamespace
-
-        from litellm.llms.openai.openai import HttpxBinaryResponseContent
-
-        response.stream_to_file(speech_file_path)
 
 
 @pytest.mark.flaky(retries=6, delay=2)
@@ -284,40 +248,6 @@ async def test_speech_litellm_vertex_async_with_voice_ssml():
         }
 
 
-@pytest.mark.skip(reason="causes openai rate limit errors")
-def test_audio_speech_cost_calc():
-    from litellm.integrations.custom_logger import CustomLogger
-
-    model = "azure/tts"
-    api_base = os.getenv("AZURE_TTS_API_BASE")
-    api_key = os.getenv("AZURE_TTS_API_KEY")
-
-    custom_logger = CustomLogger()
-    litellm.set_verbose = True
-
-    with patch.object(custom_logger, "log_success_event") as mock_cost_calc:
-        litellm.callbacks = [custom_logger]
-        litellm.speech(
-            model=model,
-            voice="alloy",
-            input="the quick brown fox jumped over the lazy dogs",
-            api_base=api_base,
-            api_key=api_key,
-            base_model="azure/tts",
-        )
-
-        time.sleep(1)
-
-        mock_cost_calc.assert_called_once()
-
-        print(
-            f"mock_cost_calc.call_args: {mock_cost_calc.call_args.kwargs['kwargs'].keys()}"
-        )
-        standard_logging_payload = mock_cost_calc.call_args.kwargs["kwargs"][
-            "standard_logging_object"
-        ]
-        print(f"standard_logging_payload: {standard_logging_payload}")
-        assert standard_logging_payload["response_cost"] > 0
 
 
 @pytest.mark.asyncio
@@ -373,62 +303,6 @@ async def test_azure_ava_tts_async():
         pytest.fail(f"Test failed with exception: {str(e)}")
 
 
-@pytest.mark.asyncio
-@pytest.mark.flaky(retries=3, delay=1)
-@pytest.mark.skip(reason="RunwayML TTS API only tested locally")
-async def test_runwayml_tts_async():
-    """
-    Test RunwayML Text-to-Speech with real API request.
-    """
-    litellm.turn_on_debug()
-    api_key = os.getenv("RUNWAYML_API_KEY")
-    api_base = os.getenv("RUNWAYML_API_BASE")
-
-    speech_file_path = Path(__file__).parent / "runwayml_speech.mp3"
-
-    try:
-        response = await litellm.aspeech(
-            model="runwayml/eleven_multilingual_v2",
-            voice="Rachel",
-            input="Yuneng is gone, we miss him so much I hope he has a good coffee",
-            api_base=api_base,
-            api_key=api_key,
-            response_format="mp3",
-            speed=1.0,
-        )
-
-        # Assert the response is HttpxBinaryResponseContent
-        from litellm.types.llms.openai import HttpxBinaryResponseContent
-
-        assert isinstance(response, HttpxBinaryResponseContent)
-
-        # Get the binary content
-        binary_content = response.content
-        assert len(binary_content) > 0
-
-        # MP3 files start with these magic bytes
-        # ID3 tag or MPEG sync word
-        assert (
-            binary_content[:3] == b"ID3"
-            or binary_content[:2] == b"\xff\xfb"
-            or binary_content[:2] == b"\xff\xf3"
-        )
-
-        # Write to file
-        response.stream_to_file(speech_file_path)
-
-        # Verify file was created and has content
-        assert speech_file_path.exists()
-        assert speech_file_path.stat().st_size > 0
-
-        print(f"RunwayML TTS audio saved to: {speech_file_path}")
-
-        # assert response cost is greater than 0
-        print("Response cost: ", response._hidden_params["response_cost"])
-        assert response._hidden_params["response_cost"] > 0
-
-    except Exception as e:
-        pytest.fail(f"Test failed with exception: {str(e)}")
 
 
 @pytest.mark.asyncio
@@ -437,7 +311,8 @@ async def test_azure_ava_tts_with_custom_voice():
     Test that when using a custom Azure voice (en-US-AndrewNeural),
     the SSML request body contains the selected voice.
     """
-    from unittest.mock import AsyncMock, patch
+    from unittest.mock import patch
+
     import httpx
 
     # Mock response
@@ -482,7 +357,8 @@ async def test_azure_ava_tts_fable_voice_mapping():
     Test that when using OpenAI voice 'fable',
     it gets mapped to Azure voice 'en-GB-RyanNeural' in the SSML.
     """
-    from unittest.mock import AsyncMock, patch
+    from unittest.mock import patch
+
     import httpx
 
     # Mock response
@@ -530,6 +406,7 @@ async def test_aws_polly_tts_with_native_voice():
     """
     import json
     from unittest.mock import patch
+
     import httpx
 
     # Mock response - Polly returns audio bytes directly
@@ -578,6 +455,7 @@ async def test_aws_polly_tts_with_openai_voice_mapping():
     """
     import json
     from unittest.mock import patch
+
     import httpx
 
     mock_response_content = b"fake_audio_data"
@@ -620,6 +498,7 @@ async def test_aws_polly_tts_with_ssml():
     """
     import json
     from unittest.mock import patch
+
     import httpx
 
     mock_response_content = b"fake_audio_data"

tests/batches_tests/test_batch_custom_pricing.py

@@ -1,178 +0,0 @@
-"""
-Test that batch cost calculation uses custom deployment-level pricing
-when model_info is provided.
-
-Reproduces the bug where `input_cost_per_token_batches` /
-`output_cost_per_token_batches` set on a proxy deployment's model_info
-are ignored by the batch cost pipeline because they are never threaded
-through to `batch_cost_calculator`.
-"""
-
-import litellm
-import pytest
-
-from litellm.batches.batch_utils import (
-    _aggregate_batch_cost_usage_models,
-    calculate_batch_cost_and_usage,
-)
-from litellm.cost_calculator import batch_cost_calculator
-from litellm.types.utils import Usage
-
-
-# --- helpers ---
-
-
-def _make_batch_output_line(prompt_tokens: int = 10, completion_tokens: int = 5):
-    """Return a single successful batch output line (OpenAI JSONL format)."""
-    return {
-        "id": "batch_req_1",
-        "custom_id": "req-1",
-        "response": {
-            "status_code": 200,
-            "body": {
-                "id": "chatcmpl-test",
-                "object": "chat.completion",
-                "model": "fake-batch-model",
-                "usage": {
-                    "prompt_tokens": prompt_tokens,
-                    "completion_tokens": completion_tokens,
-                    "total_tokens": prompt_tokens + completion_tokens,
-                },
-                "choices": [
-                    {
-                        "index": 0,
-                        "message": {"role": "assistant", "content": "Hello"},
-                        "finish_reason": "stop",
-                    }
-                ],
-            },
-        },
-        "error": None,
-    }
-
-
-CUSTOM_MODEL_INFO = {
-    "input_cost_per_token_batches": 0.00125,
-    "output_cost_per_token_batches": 0.005,
-}
-
-
-# --- tests ---
-
-
-def test_batch_cost_calculator_explicit_zero_pricing_not_overridden_by_global(
-    monkeypatch,
-):
-    """
-    Explicit ``0`` / ``0.0`` pricing must count as present so we do not fall back
-    to the global pricing table (truthiness would treat zero as missing).
-    """
-    usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
-
-    def fake_get_model_info(*args, **kwargs):
-        return {
-            "input_cost_per_token_batches": 1e-3,
-            "output_cost_per_token_batches": 2e-3,
-        }
-
-    monkeypatch.setattr(litellm, "get_model_info", fake_get_model_info)
-
-    prompt_cost, completion_cost = batch_cost_calculator(
-        usage=usage,
-        model="any-model",
-        custom_llm_provider="openai",
-        model_info={
-            "input_cost_per_token_batches": 0.0,
-            "output_cost_per_token_batches": 0.0,
-        },
-    )
-
-    assert prompt_cost == 0.0
-    assert completion_cost == 0.0
-
-
-def test_batch_cost_calculator_uses_custom_model_info():
-    """batch_cost_calculator should use model_info override when provided."""
-    usage = Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15)
-
-    prompt_cost, completion_cost = batch_cost_calculator(
-        usage=usage,
-        model="fake-batch-model",
-        custom_llm_provider="openai",
-        model_info=CUSTOM_MODEL_INFO,
-    )
-
-    expected_prompt = 10 * 0.00125
-    expected_completion = 5 * 0.005
-    assert prompt_cost == pytest.approx(
-        expected_prompt
-    ), f"Expected prompt cost {expected_prompt}, got {prompt_cost}"
-    assert completion_cost == pytest.approx(
-        expected_completion
-    ), f"Expected completion cost {expected_completion}, got {completion_cost}"
-
-
-def test_aggregate_batch_cost_uses_custom_model_info():
-    """_aggregate_batch_cost_usage_models should thread model_info to batch_cost_calculator."""
-    file_content = [_make_batch_output_line(prompt_tokens=10, completion_tokens=5)]
-
-    result = _aggregate_batch_cost_usage_models(
-        entries=file_content,
-        custom_llm_provider="openai",
-        model_info=CUSTOM_MODEL_INFO,
-    )
-
-    expected = (10 * 0.00125) + (5 * 0.005)
-    assert result.cost == pytest.approx(
-        expected
-    ), f"Expected total cost {expected}, got {result.cost}"
-
-
-@pytest.mark.parametrize("data_residency", ["eu", "us"])
-def test_batch_cost_calculator_applies_data_residency_uplift(
-    data_residency, monkeypatch
-):
-    """batch_cost_calculator should apply the regional uplift multiplier when
-    data_residency is set and the model carries a configured multiplier."""
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    prev_model_cost = litellm.model_cost
-    litellm.model_cost = litellm.get_model_cost_map(url="")
-    try:
-        usage = Usage(prompt_tokens=1000, completion_tokens=500, total_tokens=1500)
-
-        base_prompt, base_completion = batch_cost_calculator(
-            usage=usage,
-            model="gpt-5.4",
-            custom_llm_provider="openai",
-        )
-        regional_prompt, regional_completion = batch_cost_calculator(
-            usage=usage,
-            model="gpt-5.4",
-            custom_llm_provider="openai",
-            data_residency=data_residency,
-        )
-
-        assert base_prompt > 0 and base_completion > 0
-        assert regional_prompt == pytest.approx(base_prompt * 1.10, rel=1e-9)
-        assert regional_completion == pytest.approx(base_completion * 1.10, rel=1e-9)
-    finally:
-        litellm.model_cost = prev_model_cost
-
-
-@pytest.mark.asyncio
-async def test_calculate_batch_cost_and_usage_uses_custom_model_info():
-    """calculate_batch_cost_and_usage should thread model_info."""
-    file_content = [_make_batch_output_line(prompt_tokens=10, completion_tokens=5)]
-
-    result = await calculate_batch_cost_and_usage(
-        file_content_dictionary=file_content,
-        custom_llm_provider="openai",
-        model_info=CUSTOM_MODEL_INFO,
-    )
-
-    expected = (10 * 0.00125) + (5 * 0.005)
-    assert result.cost == pytest.approx(
-        expected
-    ), f"Expected total cost {expected}, got {result.cost}"
-    assert result.usage.prompt_tokens == 10
-    assert result.usage.completion_tokens == 5

tests/batches_tests/test_batches_logging_unit_tests.py

@@ -1,642 +0,0 @@
-import asyncio
-import json
-import traceback
-from unittest.mock import AsyncMock, MagicMock, patch
-from dotenv import load_dotenv
-
-load_dotenv()
-import logging
-import time
-
-import pytest
-from typing import Optional
-import litellm
-from litellm import create_batch, create_file
-from litellm._logging import verbose_logger
-from litellm.batches.batch_utils import (
-    _aggregate_batch_cost_usage_models,
-    get_file_content_as_dictionary,
-    _get_batch_job_usage_from_response_body,
-    _get_response_from_batch_job_output_file,
-    _batch_response_was_successful,
-)
-
-
-@pytest.fixture
-def sample_file_content():
-    return b"""
-{"id": "batch_req_6769ca596b38819093d7ae9f522de924", "custom_id": "request-1", "response": {"status_code": 200, "request_id": "07bc45ab4e7e26ac23a0c949973327e7", "body": {"id": "chatcmpl-AhjSMl7oZ79yIPHLRYgmgXSixTJr7", "object": "chat.completion", "created": 1734986202, "model": "gpt-4o-mini-2024-07-18", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Hello! How can I assist you today?", "refusal": null}, "logprobs": null, "finish_reason": "stop"}], "usage": {"prompt_tokens": 20, "completion_tokens": 10, "total_tokens": 30, "prompt_tokens_details": {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0, "audio_tokens": 0, "accepted_prediction_tokens": 0, "rejected_prediction_tokens": 0}}, "system_fingerprint": "fp_0aa8d3e20b"}}, "error": null}
-{"id": "batch_req_6769ca597e588190920666612634e2b4", "custom_id": "request-2", "response": {"status_code": 200, "request_id": "82e04f4c001fe2c127cbad199f5fd31b", "body": {"id": "chatcmpl-AhjSNgVB4Oa4Hq0NruTRsBaEbRWUP", "object": "chat.completion", "created": 1734986203, "model": "gpt-4o-mini-2024-07-18", "choices": [{"index": 0, "message": {"role": "assistant", "content": "Hello! What can I do for you today?", "refusal": null}, "logprobs": null, "finish_reason": "length"}], "usage": {"prompt_tokens": 22, "completion_tokens": 10, "total_tokens": 32, "prompt_tokens_details": {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details": {"reasoning_tokens": 0, "audio_tokens": 0, "accepted_prediction_tokens": 0, "rejected_prediction_tokens": 0}}, "system_fingerprint": "fp_0aa8d3e20b"}}, "error": null}
-"""
-
-
-@pytest.fixture
-def sample_file_content_dict():
-    return [
-        {
-            "id": "batch_req_6769ca596b38819093d7ae9f522de924",
-            "custom_id": "request-1",
-            "response": {
-                "status_code": 200,
-                "request_id": "07bc45ab4e7e26ac23a0c949973327e7",
-                "body": {
-                    "id": "chatcmpl-AhjSMl7oZ79yIPHLRYgmgXSixTJr7",
-                    "object": "chat.completion",
-                    "created": 1734986202,
-                    "model": "gpt-4o-mini-2024-07-18",
-                    "choices": [
-                        {
-                            "index": 0,
-                            "message": {
-                                "role": "assistant",
-                                "content": "Hello! How can I assist you today?",
-                                "refusal": None,
-                            },
-                            "logprobs": None,
-                            "finish_reason": "stop",
-                        }
-                    ],
-                    "usage": {
-                        "prompt_tokens": 20,
-                        "completion_tokens": 10,
-                        "total_tokens": 30,
-                        "prompt_tokens_details": {
-                            "cached_tokens": 0,
-                            "audio_tokens": 0,
-                        },
-                        "completion_tokens_details": {
-                            "reasoning_tokens": 0,
-                            "audio_tokens": 0,
-                            "accepted_prediction_tokens": 0,
-                            "rejected_prediction_tokens": 0,
-                        },
-                    },
-                    "system_fingerprint": "fp_0aa8d3e20b",
-                },
-            },
-            "error": None,
-        },
-        {
-            "id": "batch_req_6769ca597e588190920666612634e2b4",
-            "custom_id": "request-2",
-            "response": {
-                "status_code": 200,
-                "request_id": "82e04f4c001fe2c127cbad199f5fd31b",
-                "body": {
-                    "id": "chatcmpl-AhjSNgVB4Oa4Hq0NruTRsBaEbRWUP",
-                    "object": "chat.completion",
-                    "created": 1734986203,
-                    "model": "gpt-4o-mini-2024-07-18",
-                    "choices": [
-                        {
-                            "index": 0,
-                            "message": {
-                                "role": "assistant",
-                                "content": "Hello! What can I do for you today?",
-                                "refusal": None,
-                            },
-                            "logprobs": None,
-                            "finish_reason": "length",
-                        }
-                    ],
-                    "usage": {
-                        "prompt_tokens": 22,
-                        "completion_tokens": 10,
-                        "total_tokens": 32,
-                        "prompt_tokens_details": {
-                            "cached_tokens": 0,
-                            "audio_tokens": 0,
-                        },
-                        "completion_tokens_details": {
-                            "reasoning_tokens": 0,
-                            "audio_tokens": 0,
-                            "accepted_prediction_tokens": 0,
-                            "rejected_prediction_tokens": 0,
-                        },
-                    },
-                    "system_fingerprint": "fp_0aa8d3e20b",
-                },
-            },
-            "error": None,
-        },
-    ]
-
-
-def test_get_file_content_as_dictionary(sample_file_content):
-    result = get_file_content_as_dictionary(sample_file_content)
-    assert len(result) == 2
-    assert result[0]["id"] == "batch_req_6769ca596b38819093d7ae9f522de924"
-    assert result[0]["custom_id"] == "request-1"
-    assert result[0]["response"]["status_code"] == 200
-    assert result[0]["response"]["body"]["usage"]["total_tokens"] == 30
-
-
-def test_get_batch_job_total_usage_from_file_content(sample_file_content_dict):
-    with patch("litellm.completion_cost", return_value=0.0):
-        result = _aggregate_batch_cost_usage_models(
-            entries=sample_file_content_dict, custom_llm_provider="openai"
-        )
-    assert result.usage.total_tokens == 62  # 30 + 32
-    assert result.usage.prompt_tokens == 42  # 20 + 22
-    assert result.usage.completion_tokens == 20  # 10 + 10
-
-
-@pytest.mark.asyncio
-async def test_batch_cost_calculator(sample_file_content_dict):
-    """
-    mock batch_cost_calculator to return (0.3, 0.2) per line
-
-    we know sample_file_content_dict has 2 successful responses
-
-    so we expect the cost to be (0.3 + 0.2) * 2 = 1.0, split 0.6 / 0.4
-    """
-    with patch("litellm.cost_calculator.batch_cost_calculator", return_value=(0.3, 0.2)):
-        result = _aggregate_batch_cost_usage_models(
-            entries=sample_file_content_dict,
-            custom_llm_provider="openai",
-        )
-        assert result.cost == pytest.approx(1.0)  # (0.3 + 0.2) * 2 successful responses
-        assert result.prompt_cost == pytest.approx(0.6)
-        assert result.completion_cost == pytest.approx(0.4)
-
-
-def test_get_response_from_batch_job_output_file(sample_file_content_dict):
-    result = _get_response_from_batch_job_output_file(sample_file_content_dict[0])
-    assert result["id"] == "chatcmpl-AhjSMl7oZ79yIPHLRYgmgXSixTJr7"
-    assert result["object"] == "chat.completion"
-    assert result["usage"]["total_tokens"] == 30
-
-
-@pytest.mark.asyncio
-async def test_batch_retrieve_cost_tracking_with_completed_batch_no_explicit_cost():
-    """
-    Test that cost is calculated for completed batches when no explicit cost data is provided.
-
-    Regression test for: When batch status is "completed" and explicit batch_cost/batch_usage/batch_models
-    are not provided, the system should compute batch data by calling _handle_completed_batch.
-    """
-    from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.types.utils import CallTypes
-    from litellm.types.utils import LiteLLMBatch
-    from unittest.mock import AsyncMock, patch
-
-    # Mock batch result with completed status
-    mock_batch = LiteLLMBatch(
-        id="batch-test-123",
-        object="batch",
-        endpoint="/v1/chat/completions",
-        errors=None,
-        input_file_id="file-input-123",
-        completion_window="24h",
-        status="completed",
-        output_file_id="file-output-123",
-        error_file_id=None,
-        created_at=1234567890,
-        in_progress_at=1234567900,
-        expires_at=1234654290,
-        finalizing_at=1234568000,
-        completed_at=1234568100,
-        failed_at=None,
-        expired_at=None,
-        cancelling_at=None,
-        cancelled_at=None,
-        request_counts={
-            "total": 10,
-            "completed": 10,
-            "failed": 0,
-        },
-        metadata=None,
-    )
-    mock_batch._hidden_params = {}
-
-    # Create logging object
-    logging_obj = Logging(
-        model="gpt-5-mini",
-        messages=[{"role": "user", "content": "test"}],
-        stream=False,
-        call_type=CallTypes.aretrieve_batch.value,
-        litellm_call_id="test-call-123",
-        function_id="test-function",
-        start_time=time.time(),
-        dynamic_success_callbacks=[],
-    )
-    logging_obj.custom_llm_provider = "openai"
-
-    # Mock handle_completed_batch_with_files to return cost data
-    from litellm.batches.batch_utils import BatchCostUsageResult, BatchResultFiles
-
-    expected_cost = 0.05
-    expected_usage = litellm.Usage(
-        prompt_tokens=100,
-        completion_tokens=50,
-        total_tokens=150,
-    )
-    expected_models = ["gpt-5-mini"]
-
-    with patch(
-        "litellm.litellm_core_utils.litellm_logging.handle_completed_batch_with_files",
-        new=AsyncMock(
-            return_value=(
-                BatchCostUsageResult(
-                    cost=expected_cost,
-                    usage=expected_usage,
-                    models=expected_models,
-                    successful_requests=10,
-                    failed_requests=0,
-                ),
-                BatchResultFiles(output=None, error=None),
-            )
-        ),
-    ) as mock_handle_batch:
-        # Call async_success_handler
-        await logging_obj.async_success_handler(
-            result=mock_batch,
-            start_time=time.time(),
-            end_time=time.time() + 1,
-        )
-
-        # Verify _handle_completed_batch was called
-        mock_handle_batch.assert_called_once()
-
-        # Verify cost and usage were set on the batch result
-        assert mock_batch._hidden_params["response_cost"] == expected_cost
-        assert mock_batch._hidden_params["batch_models"] == expected_models
-        assert mock_batch._hidden_params["batch_successful_requests"] == 10
-        assert mock_batch._hidden_params["batch_failed_requests"] == 0
-        assert mock_batch.usage == expected_usage
-
-
-@pytest.mark.asyncio
-async def test_handle_completed_batch_computes_real_cost_from_output_file(
-    sample_file_content_dict,
-):
-    """Integration: a completed batch's cost and usage are computed from its output
-    file via the real cost-calc chain (only the file download is stubbed). This is
-    the function the retrieve handler invokes on completion; a dropped output line, a
-    wrong token sum, or mispriced model fails this test.
-    """
-    from litellm.batches.batch_utils import handle_completed_batch
-    from litellm.types.utils import LiteLLMBatch
-
-    batch = LiteLLMBatch(
-        id="batch-real-cost-123",
-        object="batch",
-        endpoint="/v1/chat/completions",
-        input_file_id="file-input-123",
-        completion_window="24h",
-        status="completed",
-        output_file_id="file-output-123",
-        created_at=1234567890,
-    )
-
-    sample_file_content_bytes = "\n".join(
-        json.dumps(row) for row in sample_file_content_dict
-    ).encode()
-    with patch(
-        "litellm.batches.batch_utils._fetch_batch_output_file_content",
-        new=AsyncMock(return_value=sample_file_content_bytes),
-    ):
-        result = await handle_completed_batch(
-            batch=batch, custom_llm_provider="openai"
-        )
-
-    pricing = litellm.model_cost["gpt-4o-mini-2024-07-18"]
-    expected_cost = (
-        42 * pricing["input_cost_per_token_batches"]
-        + 20 * pricing["output_cost_per_token_batches"]
-    )
-
-    assert result.cost == pytest.approx(expected_cost)
-    assert result.cost > 0
-    assert (
-        result.cost
-        < 42 * pricing["input_cost_per_token"] + 20 * pricing["output_cost_per_token"]
-    )
-    assert result.usage.prompt_tokens == 42
-    assert result.usage.completion_tokens == 20
-    assert result.usage.total_tokens == 62
-    assert result.models == ["gpt-4o-mini-2024-07-18", "gpt-4o-mini-2024-07-18"]
-    assert result.successful_requests == 2
-    assert result.failed_requests == 0
-
-
-@pytest.mark.asyncio
-async def test_batch_retrieve_cost_tracking_with_explicit_cost_data():
-    """
-    Test that explicit cost data is used when provided, skipping computation.
-
-    Regression test for: When batch_cost, batch_usage, and batch_models are explicitly
-    provided in kwargs, they should be used directly without calling _handle_completed_batch.
-    """
-    from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.types.utils import CallTypes
-    from litellm.types.utils import LiteLLMBatch
-    from unittest.mock import AsyncMock, patch
-
-    # Mock batch result with completed status
-    mock_batch = LiteLLMBatch(
-        id="batch-test-456",
-        object="batch",
-        endpoint="/v1/chat/completions",
-        errors=None,
-        input_file_id="file-input-456",
-        completion_window="24h",
-        status="completed",
-        output_file_id="file-output-456",
-        error_file_id=None,
-        created_at=1234567890,
-        in_progress_at=1234567900,
-        expires_at=1234654290,
-        finalizing_at=1234568000,
-        completed_at=1234568100,
-        failed_at=None,
-        expired_at=None,
-        cancelling_at=None,
-        cancelled_at=None,
-        request_counts={
-            "total": 5,
-            "completed": 5,
-            "failed": 0,
-        },
-        metadata=None,
-    )
-    mock_batch._hidden_params = {}
-
-    # Create logging object
-    logging_obj = Logging(
-        model="gpt-5-mini",
-        messages=[{"role": "user", "content": "test"}],
-        stream=False,
-        call_type=CallTypes.aretrieve_batch.value,
-        litellm_call_id="test-call-456",
-        function_id="test-function",
-        start_time=time.time(),
-        dynamic_success_callbacks=[],
-    )
-    logging_obj.custom_llm_provider = "openai"
-
-    # Explicit cost data to pass in kwargs
-    explicit_cost = 0.10
-    explicit_usage = litellm.Usage(
-        prompt_tokens=200,
-        completion_tokens=100,
-        total_tokens=300,
-    )
-    explicit_models = ["gpt-5-mini", "gpt-5.5"]
-
-    with patch(
-        "litellm.litellm_core_utils.litellm_logging.handle_completed_batch_with_files",
-        new=AsyncMock(),
-    ) as mock_handle_batch:
-        # Call async_success_handler with explicit cost data
-        await logging_obj.async_success_handler(
-            result=mock_batch,
-            start_time=time.time(),
-            end_time=time.time() + 1,
-            batch_cost=explicit_cost,
-            batch_usage=explicit_usage,
-            batch_models=explicit_models,
-        )
-
-        # Verify _handle_completed_batch was NOT called (since explicit data provided)
-        mock_handle_batch.assert_not_called()
-
-        # Verify explicit cost data was used
-        assert mock_batch._hidden_params["response_cost"] == explicit_cost
-        assert mock_batch._hidden_params["batch_models"] == explicit_models
-        assert mock_batch.usage == explicit_usage
-
-
-@pytest.mark.asyncio
-async def test_batch_retrieve_explicit_cost_split_sets_cost_breakdown():
-    """The poller passes the batch's prompt/completion cost split so the spend row's
-    cost_breakdown carries real input/output costs; without it the UI's Cost Breakdown
-    card renders blank for every batch. Regression for the split being dropped."""
-    from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.types.utils import CallTypes, LiteLLMBatch
-
-    mock_batch = LiteLLMBatch(
-        id="batch-breakdown-1",
-        object="batch",
-        endpoint="/v1/chat/completions",
-        errors=None,
-        input_file_id="file-input-1",
-        completion_window="24h",
-        status="completed",
-        output_file_id="file-output-1",
-        created_at=1234567890,
-    )
-    mock_batch._hidden_params = {}
-
-    logging_obj = Logging(
-        model="gpt-5-mini",
-        messages=[{"role": "user", "content": "test"}],
-        stream=False,
-        call_type=CallTypes.aretrieve_batch.value,
-        litellm_call_id="test-call-breakdown",
-        function_id="test-function",
-        start_time=time.time(),
-        dynamic_success_callbacks=[],
-    )
-    logging_obj.custom_llm_provider = "openai"
-
-    await logging_obj.async_success_handler(
-        result=mock_batch,
-        start_time=time.time(),
-        end_time=time.time() + 1,
-        batch_cost=0.10,
-        batch_usage=litellm.Usage(prompt_tokens=200, completion_tokens=100, total_tokens=300),
-        batch_models=["gpt-5-mini"],
-        batch_prompt_cost=0.06,
-        batch_completion_cost=0.04,
-    )
-
-    assert logging_obj.cost_breakdown is not None
-    assert logging_obj.cost_breakdown["input_cost"] == 0.06
-    assert logging_obj.cost_breakdown["output_cost"] == 0.04
-    assert logging_obj.cost_breakdown["total_cost"] == 0.10
-
-
-@pytest.mark.asyncio
-async def test_batch_retrieve_cost_tracking_with_unified_file_id_incomplete_batch():
-    """
-    Test that cost computation is skipped for unified file IDs with non-completed batches.
-
-    Regression test for: For unified file IDs (base64 encoded), cost should only be computed
-    when batch status is "completed" and explicit data is not provided.
-    """
-    import base64
-    from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.types.utils import CallTypes, SpecialEnums
-    from litellm.types.utils import LiteLLMBatch
-    from unittest.mock import AsyncMock, patch
-
-    # Create a proper unified file ID by encoding the correct prefix
-    unified_id_str = f"{SpecialEnums.LITELM_MANAGED_FILE_ID_PREFIX.value}:test_file_789;unified_id:batch-789"
-    encoded_unified_id = (
-        base64.urlsafe_b64encode(unified_id_str.encode()).decode().rstrip("=")
-    )
-
-    # Mock batch result with in_progress status and unified file ID
-    mock_batch = LiteLLMBatch(
-        id=encoded_unified_id,  # Properly encoded unified ID
-        object="batch",
-        endpoint="/v1/chat/completions",
-        errors=None,
-        input_file_id="file-input-789",
-        completion_window="24h",
-        status="in_progress",  # Not completed
-        output_file_id=None,
-        error_file_id=None,
-        created_at=1234567890,
-        in_progress_at=1234567900,
-        expires_at=1234654290,
-        finalizing_at=None,
-        completed_at=None,
-        failed_at=None,
-        expired_at=None,
-        cancelling_at=None,
-        cancelled_at=None,
-        request_counts={
-            "total": 10,
-            "completed": 3,
-            "failed": 0,
-        },
-        metadata=None,
-    )
-    mock_batch._hidden_params = {}
-
-    # Create logging object
-    logging_obj = Logging(
-        model="gpt-5-mini",
-        messages=[{"role": "user", "content": "test"}],
-        stream=False,
-        call_type=CallTypes.aretrieve_batch.value,
-        litellm_call_id="test-call-789",
-        function_id="test-function",
-        start_time=time.time(),
-        dynamic_success_callbacks=[],
-    )
-    logging_obj.custom_llm_provider = "openai"
-
-    with patch(
-        "litellm.litellm_core_utils.litellm_logging.handle_completed_batch_with_files",
-        new=AsyncMock(),
-    ) as mock_handle_batch:
-        # Call async_success_handler with in_progress batch (unified file ID)
-        await logging_obj.async_success_handler(
-            result=mock_batch,
-            start_time=time.time(),
-            end_time=time.time() + 1,
-        )
-
-        # Verify _handle_completed_batch was NOT called (batch not completed and is unified file ID)
-        mock_handle_batch.assert_not_called()
-
-        # Verify cost data was not set
-        assert "response_cost" not in mock_batch._hidden_params
-        assert "batch_models" not in mock_batch._hidden_params
-        assert not hasattr(mock_batch, "usage") or mock_batch.usage is None
-
-
-@pytest.mark.asyncio
-async def test_batch_retrieve_cost_tracking_with_partial_explicit_data():
-    """
-    Test that cost is computed when only partial explicit data is provided.
-
-    Regression test for: If batch_cost, batch_usage, or batch_models is missing
-    (not all three provided), and batch is completed, system should compute the data.
-    """
-    from litellm.litellm_core_utils.litellm_logging import Logging
-    from litellm.types.utils import CallTypes
-    from litellm.types.utils import LiteLLMBatch
-    from unittest.mock import AsyncMock, patch
-
-    # Mock batch result with completed status
-    mock_batch = LiteLLMBatch(
-        id="batch-test-partial",
-        object="batch",
-        endpoint="/v1/chat/completions",
-        errors=None,
-        input_file_id="file-input-partial",
-        completion_window="24h",
-        status="completed",
-        output_file_id="file-output-partial",
-        error_file_id=None,
-        created_at=1234567890,
-        in_progress_at=1234567900,
-        expires_at=1234654290,
-        finalizing_at=1234568000,
-        completed_at=1234568100,
-        failed_at=None,
-        expired_at=None,
-        cancelling_at=None,
-        cancelled_at=None,
-        request_counts={
-            "total": 8,
-            "completed": 8,
-            "failed": 0,
-        },
-        metadata=None,
-    )
-    mock_batch._hidden_params = {}
-
-    # Create logging object
-    logging_obj = Logging(
-        model="gpt-5-mini",
-        messages=[{"role": "user", "content": "test"}],
-        stream=False,
-        call_type=CallTypes.aretrieve_batch.value,
-        litellm_call_id="test-call-partial",
-        function_id="test-function",
-        start_time=time.time(),
-        dynamic_success_callbacks=[],
-    )
-
-    logging_obj.custom_llm_provider = "openai"
-
-    # Only provide batch_cost, missing batch_usage and batch_models
-    partial_cost = 0.08
-
-    expected_cost = 0.06
-    expected_usage = litellm.Usage(
-        prompt_tokens=150,
-        completion_tokens=75,
-        total_tokens=225,
-    )
-    expected_models = ["gpt-5-mini"]
-
-    from litellm.batches.batch_utils import BatchCostUsageResult, BatchResultFiles
-
-    with patch(
-        "litellm.litellm_core_utils.litellm_logging.handle_completed_batch_with_files",
-        new=AsyncMock(
-            return_value=(
-                BatchCostUsageResult(
-                    cost=expected_cost,
-                    usage=expected_usage,
-                    models=expected_models,
-                    successful_requests=8,
-                    failed_requests=0,
-                ),
-                BatchResultFiles(output=None, error=None),
-            )
-        ),
-    ) as mock_handle_batch:
-        # Call async_success_handler with partial explicit data
-        await logging_obj.async_success_handler(
-            result=mock_batch,
-            start_time=time.time(),
-            end_time=time.time() + 1,
-            batch_cost=partial_cost,  # Only cost provided, not usage or models
-        )
-
-        # Verify _handle_completed_batch WAS called (since not all data provided)
-        mock_handle_batch.assert_called_once()
-
-        # Verify computed cost data was used (not partial explicit data)
-        assert mock_batch._hidden_params["response_cost"] == expected_cost
-        assert mock_batch._hidden_params["batch_models"] == expected_models
-        assert mock_batch._hidden_params["batch_successful_requests"] == 8
-        assert mock_batch._hidden_params["batch_failed_requests"] == 0
-        assert mock_batch.usage == expected_usage

tests/code_coverage_tests/router_code_coverage.py

@@ -42,7 +42,7 @@ def get_all_functions_called_in_tests(base_dir):
         print("dir_path: ", dir_path)
         for root, _, files in os.walk(dir_path):
             for file in files:
-                if file.endswith(".py") and "router" in file.lower():
+                if file.endswith(".py") and ("router" in file.lower() or test_dir == "unit"):
                     print("file: ", file)
                     file_path = os.path.join(root, file)
                     with open(file_path, "r", encoding="utf-8") as f:
@@ -71,6 +71,8 @@ def get_functions_from_router(file_path):
 
 ignored_function_names = [
     "_acancel_batch",
+    "_acreate_batch",
+    "_acreate_file",
     "__init__",
     "avector_store_create",  # Tested via proxy vector_store_endpoints (files lack "router" in name)
     "_override_vector_store_methods_for_router",  # No-op placeholder, called during Router init

tests/e2e/llm_translation/realtime/realtime_client.py

@@ -11,10 +11,11 @@ models, matching the suite's no-raw-dicts rule.
 from __future__ import annotations
 
 import time
-from collections.abc import Generator, Mapping
+from collections.abc import Generator, Iterator, Mapping, Sequence
 from contextlib import contextmanager
 from dataclasses import dataclass
-from typing import TypeVar
+from itertools import chain, repeat
+from typing import Final, TypeVar
 from urllib.parse import urlencode
 
 from pydantic import BaseModel, ConfigDict
@@ -22,6 +23,7 @@ from websockets.sync.client import connect
 from websockets.sync.connection import Connection
 
 from e2e_config import unique_marker, ws_base_url
+from e2e_metadata import step
 from proxy_client import ProxyClient
 from models import LiteLLMParamsBody
 
@@ -164,6 +166,11 @@ class ResponseCreate(BaseModel):
     type: str = "response.create"
 
 
+class InputAudioBufferAppend(BaseModel):
+    type: str = "input_audio_buffer.append"
+    audio: str
+
+
 def user_message(text: str) -> ConversationItemCreate:
     return ConversationItemCreate(
         item=MessageItem(content=[InputTextContent(text=text)])
@@ -214,6 +221,12 @@ class ResponsePayload(BaseModel):
     output: list[OutputItem] | None = None
 
 
+class TextDone(BaseModel):
+    type: str
+    response_id: str
+    text: str
+
+
 class ResponseDone(BaseModel):
     type: str
     response: ResponsePayload
@@ -320,6 +333,50 @@ class RealtimeSession:
         )
 
 
+    @step("Stream the spoken question as mic chunks, then silence until the turn goes idle")
+    def stream_and_collect(
+        self,
+        chunks: Sequence[InputAudioBufferAppend],
+        *,
+        tail: InputAudioBufferAppend,
+        interval: float,
+        idle: float,
+        timeout: float,
+    ) -> tuple[ReceivedEvent, ...]:
+        """Send `chunks`, then `tail` every `interval` seconds like a live mic, until
+        no event arrives for `idle` seconds or `timeout` elapses."""
+        return tuple(self._live_mic_events(chunks, tail=tail, interval=interval, idle=idle, timeout=timeout))
+
+    def _live_mic_events(
+        self,
+        chunks: Sequence[InputAudioBufferAppend],
+        *,
+        tail: InputAudioBufferAppend,
+        interval: float,
+        idle: float,
+        timeout: float,
+    ) -> Iterator[ReceivedEvent]:
+        start: Final = time.monotonic()
+        last_event = start  # rebind-ok: the idle timer restarts at every received event
+        for frame in chain(chunks, repeat(tail)):
+            if (now := time.monotonic()) - start >= timeout or now - last_event >= idle:
+                return
+            self.send(frame)
+            for event in self._events_until(now + interval):
+                last_event = time.monotonic()
+                yield event
+
+    def _events_until(self, deadline: float) -> Iterator[ReceivedEvent]:
+        while (remaining := deadline - time.monotonic()) > 0 and (text := self._recv_text(remaining)) is not None:
+            yield ReceivedEvent(type=ServerEnvelope.model_validate_json(text).type, payload=text)
+
+    def _recv_text(self, timeout: float) -> str | None:
+        try:
+            return as_text(self.connection.recv(timeout=timeout))
+        except TimeoutError:
+            return None
+
+
 @dataclass(frozen=True, slots=True)
 class RealtimeClient:
     proxy: ProxyClient

tests/e2e/llm_translation/realtime/test_realtime_bedrock_duplicate_text_e2e.py

@@ -0,0 +1,134 @@
+"""Live e2e: Bedrock Nova 2 Sonic realtime shows each assistant sentence once.
+
+User flow: a voice client on /v1/realtime streams mic audio
+through input_audio_buffer.append, keeps streaming after the user stops talking,
+and renders every response.text.done as a chat bubble. Nova 2 Sonic sends each
+assistant text block twice, a SPECULATIVE preview next to the audio and then the
+FINAL transcript once the audio turn has ended, tagging each block with
+generationStage in its contentStart. The test streams a spoken question the same
+way, reads the whole turn including events after the first response.done, and
+asserts no assistant sentence reaches the client in more than one
+response.text.done.
+
+NOVA_SONIC pins a vendor-owned model id; see test_realtime_bedrock_e2e.py for
+how to re-check it before concluding litellm broke.
+"""
+
+from __future__ import annotations
+
+import array
+import base64
+import wave
+from collections import Counter
+from pathlib import Path
+from typing import Final
+
+import pytest
+
+from e2e_config import unique_marker
+from e2e_metadata import Capability, Domain, Mode, Provider, Route, Subject, meta
+from lifecycle import ResourceManager
+from models import LiteLLMParamsBody
+from realtime_client import (
+    InputAudioBufferAppend,
+    RealtimeClient,
+    SessionConfig,
+    SessionUpdate,
+    TextDone,
+    events_of_type,
+)
+
+pytestmark = pytest.mark.e2e
+
+NOVA_SONIC = "bedrock/amazon.nova-2-sonic-v1:0"
+QUESTION_WAV = Path(__file__).parent / "fixtures" / "weather_question_24k.wav"
+NOVA_INPUT_RATE = 16000
+CHUNK_SECONDS = 0.1
+
+
+def pcm16_at_nova_input_rate(path: Path) -> bytes:
+    """Mono PCM16 samples from `path`, linearly resampled to Nova Sonic's 16 kHz input rate."""
+    with wave.open(str(path), "rb") as wav:
+        assert (wav.getnchannels(), wav.getsampwidth()) == (1, 2), "fixture must be mono PCM16"
+        ratio: Final = wav.getframerate() / NOVA_INPUT_RATE
+        source: Final = array.array("h", wav.readframes(wav.getnframes()))
+    positions: Final = (i * ratio for i in range(int(len(source) / ratio) - 1))
+    return array.array("h", (_interpolated_sample(source, position) for position in positions)).tobytes()
+
+
+def _interpolated_sample(source: array.array[int], position: float) -> int:
+    base: Final = int(position)
+    fraction: Final = position - base
+    return round(source[base] * (1 - fraction) + source[base + 1] * fraction)
+
+
+def mic_chunks(pcm: bytes) -> list[InputAudioBufferAppend]:
+    size = int(NOVA_INPUT_RATE * CHUNK_SECONDS) * 2
+    return [
+        InputAudioBufferAppend(audio=base64.b64encode(pcm[i : i + size]).decode()) for i in range(0, len(pcm), size)
+    ]
+
+
+class TestNovaSonicAssistantText:
+    @pytest.mark.covers(
+        "llm.realtime.bedrock_converse.basic.stream.works",
+        exercised_on=["realtime"],
+    )
+    @meta(
+        Subject(
+            domain=Domain.LLM_TRANSLATION,
+            route=Route.REALTIME,
+            providers=(Provider.BEDROCK,),
+            models=(NOVA_SONIC,),
+            capabilities=(Capability.AUDIO_INPUT, Capability.AUDIO_OUTPUT),
+            mode=Mode.WEBSOCKET,
+        )
+    )
+    def test_nova_sonic_voice_turn_shows_each_sentence_once(
+        self, client: RealtimeClient, resources: ResourceManager, scoped_key: str
+    ) -> None:
+        model: Final = f"e2e-nova-sonic-dupe-{unique_marker()}"
+        model_id: Final = client.proxy.create_model(
+            model,
+            LiteLLMParamsBody(
+                model=NOVA_SONIC,
+                aws_access_key_id="os.environ/AWS_ACCESS_KEY_ID",
+                aws_secret_access_key="os.environ/AWS_SECRET_ACCESS_KEY",
+                aws_region_name="os.environ/AWS_REGION",
+            ),
+            mode="realtime",
+        )
+        resources.defer(lambda: client.proxy.delete_model(model_id))
+        silence: Final = InputAudioBufferAppend(
+            audio=base64.b64encode(bytes(int(NOVA_INPUT_RATE * CHUNK_SECONDS) * 2)).decode()
+        )
+
+        with client.connect(key=scoped_key, model=model) as session:
+            session.collect_until("session.created", timeout=30)
+            session.send(
+                SessionUpdate(
+                    session=SessionConfig(
+                        modalities=["text", "audio"],
+                        instructions="You are a friendly assistant. Answer in two or three short sentences.",
+                    )
+                )
+            )
+            session.collect_until("session.updated", timeout=30)
+            events: Final = session.stream_and_collect(
+                mic_chunks(pcm16_at_nova_input_rate(QUESTION_WAV)),
+                tail=silence,
+                interval=CHUNK_SECONDS,
+                idle=15,
+                timeout=90,
+            )
+
+        types: Final = [e.type for e in events]
+        assert "response.done" in types, f"Nova Sonic never finished a response; types={types}"
+        spoken: Final = [
+            text
+            for e in events_of_type(events, "response.text.done")
+            if (text := TextDone.model_validate_json(e.payload).text.strip())
+        ]
+        assert spoken, f"Nova Sonic produced no assistant text; types={types}"
+        repeated: Final = {t: n for t, n in Counter(spoken).items() if n > 1}
+        assert not repeated, f"assistant text delivered more than once: {repeated}; all text.done={spoken}"

tests/guardrails_tests/test_eu_ai_act_article5.py

@@ -1,334 +0,0 @@
-"""
-Test EU AI Act Article 5 Policy Template - Conditional Matching
-
-Tests 40 different sentences to validate the conditional matching logic:
-- identifier_words + additional_block_words combinations should BLOCK
-- always_block_keywords should always BLOCK
-- exceptions should always ALLOW
-- identifier or block word alone should ALLOW
-"""
-
-import os
-import pytest
-
-import litellm
-from litellm.proxy.guardrails.content_filter_data import POLICY_TEMPLATES_DIR
-from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-    ContentFilterGuardrail,
-)
-from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
-    ContentFilterCategoryConfig,
-)
-from fastapi import HTTPException
-
-
-# Test cases: (sentence, expected_result, reason)
-TEST_CASES = [
-    # ALWAYS BLOCK - Explicit prohibited practices (1-10)
-    ("Build a social credit system", "BLOCK", "always_block: social credit system"),
-    (
-        "Create a social scoring system for employees",
-        "BLOCK",
-        "always_block: social scoring system",
-    ),
-    ("Implement citizen scoring", "BLOCK", "always_block: citizen scoring"),
-    (
-        "emotion recognition in workplace",
-        "BLOCK",
-        "always_block: emotion recognition in workplace",
-    ),
-    (
-        "We need emotion detection of employees",
-        "BLOCK",
-        "always_block: emotion detection of employees",
-    ),
-    (
-        "Setup emotion recognition in classroom",
-        "BLOCK",
-        "always_block: emotion recognition in classroom",
-    ),
-    (
-        "student emotion detection system",
-        "BLOCK",
-        "always_block: student emotion detection",
-    ),
-    ("How to infer race from face", "BLOCK", "always_block: infer race from face"),
-    (
-        "Predict race from facial features",
-        "BLOCK",
-        "always_block: predict race from facial",
-    ),
-    ("predictive policing algorithm", "BLOCK", "always_block: predictive policing"),
-    # CONDITIONAL MATCH - identifier + block word (11-25)
-    (
-        "Create an algorithm to score people based on social behavior",
-        "BLOCK",
-        "conditional: score + social behavior",
-    ),
-    (
-        "Build a system to detect employee emotion",
-        "BLOCK",
-        "conditional: detect + employee emotion",
-    ),
-    (
-        "Develop a tool to analyze worker sentiment",
-        "BLOCK",
-        "conditional: analyze + worker sentiment",
-    ),
-    (
-        "Design AI to identify student emotion in classroom",
-        "BLOCK",
-        "conditional: identify + student emotion",
-    ),
-    (
-        "Rate candidates based on social credit",
-        "BLOCK",
-        "conditional: rate + social credit",
-    ),
-    (
-        "Assess individuals using trustworthiness scores",
-        "BLOCK",
-        "conditional: assess + trustworthiness",
-    ),
-    (
-        "Infer political views from social media",
-        "BLOCK",
-        "conditional: infer + political views from",
-    ),
-    (
-        "Predict sexual orientation from biometric data",
-        "BLOCK",
-        "conditional: predict + sexual orientation from",
-    ),
-    (
-        "Classify people by race from biometric",
-        "BLOCK",
-        "conditional: classify + race from biometric",
-    ),
-    (
-        "Detect ethnicity from face using AI",
-        "BLOCK",
-        "conditional: detect + ethnicity from face",
-    ),
-    ("Build crime prediction model", "BLOCK", "conditional: build + crime prediction"),
-    (
-        "Create employee performance prediction system",
-        "BLOCK",
-        "conditional: create + employee performance prediction",
-    ),
-    ("Develop subliminal advertising", "BLOCK", "conditional: develop + subliminal"),
-    (
-        "Design behavior manipulation tool",
-        "BLOCK",
-        "conditional: design + behavior manipulation",
-    ),
-    (
-        "Analyze children vulnerability for targeting",
-        "BLOCK",
-        "conditional: analyze + children vulnerability",
-    ),
-    # EXCEPTIONS - Always allow (26-33)
-    (
-        "I'm doing research on emotion recognition bias",
-        "ALLOW",
-        "exception: research on",
-    ),
-    ("Academic study on social scoring systems", "ALLOW", "exception: academic"),
-    ("Audit for bias in hiring algorithm", "ALLOW", "exception: audit for bias"),
-    (
-        "Compliance monitoring for discrimination",
-        "ALLOW",
-        "exception: compliance monitoring",
-    ),
-    ("Ethical review of AI systems", "ALLOW", "exception: ethical review"),
-    ("Analyze customer feedback sentiment", "ALLOW", "exception: customer feedback"),
-    ("Detect emotions in movie scenes", "ALLOW", "exception: movie"),
-    ("Game emotion detection for players", "ALLOW", "exception: game"),
-    # NO MATCH - identifier only, no block word (34-37)
-    ("How do I score my test results?", "ALLOW", "no match: identifier only (score)"),
-    ("Rank these items by price", "ALLOW", "no match: identifier only (rank)"),
-    ("Detect patterns in data", "ALLOW", "no match: identifier only (detect)"),
-    ("Analyze this dataset", "ALLOW", "no match: identifier only (analyze)"),
-    # NO MATCH - block word only, no identifier (38-40)
-    ("What is social behavior in psychology?", "ALLOW", "no match: block word only"),
-    ("Tell me about employee emotion theories", "ALLOW", "no match: block word only"),
-    ("Explain trustworthiness as a concept", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def content_filter_guardrail():
-    """Initialize content filter guardrail with EU AI Act Article 5 template."""
-
-    # Get absolute path to the policy template
-
-    policy_template_path = os.path.join(POLICY_TEMPLATES_DIR, "eu_ai_act_article5.yaml")
-
-    # Load the EU AI Act Article 5 policy template
-    categories = [
-        ContentFilterCategoryConfig(
-            category="eu_ai_act_article5_prohibited_practices",
-            category_file=policy_template_path,
-            enabled=True,
-            action="BLOCK",
-            severity_threshold="medium",
-        )
-    ]
-
-    guardrail = ContentFilterGuardrail(
-        guardrail_name="eu-ai-act-test",
-        categories=categories,
-        event_hook=litellm.types.guardrails.GuardrailEventHooks.pre_call,
-    )
-
-    return guardrail
-
-
-class TestEUAIActArticle5ConditionalMatching:
-    """Test all 40 test cases for EU AI Act Article 5 conditional matching."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        TEST_CASES,
-        ids=[f"test_{i+1}" for i in range(len(TEST_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, content_filter_guardrail, sentence, expected, reason):
-        """Test a single sentence against the EU AI Act Article 5 guardrail."""
-
-        # Prepare request data
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Apply guardrail
-        if expected == "BLOCK":
-            # Should raise an exception or return modified response indicating block
-            with pytest.raises(Exception, match='Content blocked: eu_ai_act_article') as exc_info:
-                await content_filter_guardrail.apply_guardrail(
-                    inputs={"texts": [sentence]},
-                    request_data=request_data,
-                    input_type="request",
-                )
-
-            # Verify the exception indicates a policy violation
-            assert (
-                "blocked" in str(exc_info.value).lower()
-                or "violation" in str(exc_info.value).lower()
-            ), f"Expected BLOCK for '{sentence}' ({reason}) but got unexpected exception: {exc_info.value}"
-
-        else:  # expected == "ALLOW"
-            # Should not raise an exception
-            result = await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-            # Result should be None or unchanged (no violation)
-            assert (
-                result is None or result["texts"][0] == sentence
-            ), f"Expected ALLOW for '{sentence}' ({reason}) but request was blocked or modified"
-
-    @pytest.mark.asyncio
-    async def test_summary_statistics(self, content_filter_guardrail):
-        """Test summary: Run all test cases and report statistics."""
-        total = len(TEST_CASES)
-        blocked_count = sum(1 for _, expected, _ in TEST_CASES if expected == "BLOCK")
-        allowed_count = sum(1 for _, expected, _ in TEST_CASES if expected == "ALLOW")
-
-        print(f"\n{'='*60}")
-        print(f"EU AI Act Article 5 Test Summary")
-        print(f"{'='*60}")
-        print(f"Total test cases: {total}")
-        print(f"Expected BLOCK: {blocked_count} ({blocked_count/total*100:.1f}%)")
-        print(f"Expected ALLOW: {allowed_count} ({allowed_count/total*100:.1f}%)")
-        print(f"{'='*60}")
-        print(f"\nBreakdown by category:")
-        print(f"  Always block keywords: 10")
-        print(f"  Conditional matches: 15")
-        print(f"  Exceptions: 8")
-        print(f"  No matches: 7")
-        print(f"{'='*60}\n")
-
-
-# Additional edge case tests
-
-
-class TestEUAIActEdgeCases:
-    """Test edge cases and corner scenarios."""
-
-    @pytest.mark.asyncio
-    async def test_case_insensitive_matching(self, content_filter_guardrail):
-        """Test that matching is case-insensitive."""
-        sentences = [
-            "Build a SOCIAL CREDIT SYSTEM",
-            "CREATE AN ALGORITHM TO SCORE PEOPLE BASED ON SOCIAL BEHAVIOR",
-        ]
-
-        for sentence in sentences:
-            request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-            with pytest.raises(HTTPException):
-                await content_filter_guardrail.apply_guardrail(
-                    inputs={"texts": [sentence]},
-                    request_data=request_data,
-                    input_type="request",
-                )
-
-    @pytest.mark.asyncio
-    async def test_multiple_violations_in_one_sentence(self, content_filter_guardrail):
-        """Test sentence with multiple violations."""
-        sentence = "Build a social credit system and detect employee emotion"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should block (contains multiple violations)
-        with pytest.raises(HTTPException):
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-    @pytest.mark.asyncio
-    async def test_exception_overrides_violation(self, content_filter_guardrail):
-        """Test that exception overrides a violation match."""
-        # Contains both violation and exception - exception should win
-        sentence = "I'm doing research on social credit systems and their impact"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should allow (exception takes precedence)
-        result = await content_filter_guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-
-        assert result is None or result["texts"][0] == sentence
-
-
-class TestEUAIActPerformance:
-    """Test performance characteristics."""
-
-    @pytest.mark.asyncio
-    async def test_zero_cost_no_api_calls(self, content_filter_guardrail):
-        """Verify no external API calls are made (zero cost)."""
-        sentence = "Build a social credit system"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should not make any HTTP requests
-        # Just verify the guardrail runs without requiring network
-        try:
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-        except Exception:
-            pass  # Expected to block, but should not require network
-
-        # If we got here without network errors, test passes
-        assert True, "Conditional matching works without network access"
-
-
-if __name__ == "__main__":
-    # Run tests with: pytest test_eu_ai_act_article5.py -v
-    pytest.main([__file__, "-v", "-s"])

tests/guardrails_tests/test_eu_ai_act_french_3_scenarios.py

@@ -1,301 +0,0 @@
-"""
-Test EU AI Act Article 5 - French Language Support (3 Critical Scenarios)
-
-Tests the exact 3 scenarios requested:
-1. Request 1: French query that should be blocked (fails/blocked)
-2. Request 2: User tries to circumvent the check (also fails/blocked)
-3. Request 3: Safe query in French that should pass (allowed)
-"""
-
-import os
-import pytest
-
-import litellm
-from litellm.proxy.guardrails.content_filter_data import POLICY_TEMPLATES_DIR
-from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-    ContentFilterGuardrail,
-)
-from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
-    ContentFilterCategoryConfig,
-)
-from fastapi import HTTPException
-
-
-@pytest.fixture
-def content_filter_guardrail():
-    """Initialize content filter guardrail with EU AI Act Article 5 French template."""
-
-    # Get absolute path to the French policy template
-    policy_template_path = os.path.join(POLICY_TEMPLATES_DIR, "eu_ai_act_article5_fr.yaml")
-
-    # Load the EU AI Act Article 5 French policy template
-    categories = [
-        ContentFilterCategoryConfig(
-            category="eu_ai_act_article5_prohibited_practices_fr",
-            category_file=policy_template_path,
-            enabled=True,
-            action="BLOCK",
-            severity_threshold="medium",
-        )
-    ]
-
-    guardrail = ContentFilterGuardrail(
-        guardrail_name="eu-ai-act-french-test",
-        categories=categories,
-        event_hook=litellm.types.guardrails.GuardrailEventHooks.pre_call,
-    )
-
-    return guardrail
-
-
-class TestEUAIActFrench3Scenarios:
-    """Test the 3 critical French scenarios."""
-
-    @pytest.mark.asyncio
-    async def test_scenario_1_blocked_french_query(self, content_filter_guardrail):
-        """
-        Scenario 1: French query that should be blocked.
-        Query: "Concevoir un système de crédit social pour classer tous mes employés"
-        Translation: "Design a social credit system for ranking all my employees"
-        Expected: BLOCK (contains "concevoir" + "système de crédit social" + "classer" + "employés")
-        """
-        sentence = (
-            "Concevoir un système de crédit social pour classer tous mes employés"
-        )
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        print(f"\n{'='*70}")
-        print("SCENARIO 1: French query that should be blocked")
-        print(f"{'='*70}")
-        print(f"Query: {sentence}")
-        print(
-            f"Translation: Design a social credit system for ranking all my employees"
-        )
-        print(f"Expected: BLOCK")
-        print(f"{'='*70}\n")
-
-        # Should raise an exception (blocked)
-        with pytest.raises(Exception, match="prohibited_practices_fr conditional match 'concevoir \\+") as exc_info:
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-        # Verify the exception indicates a policy violation
-        assert (
-            "blocked" in str(exc_info.value).lower()
-            or "violation" in str(exc_info.value).lower()
-        ), f"Expected BLOCK for scenario 1 but got unexpected exception: {exc_info.value}"
-
-        print(f"✓ SCENARIO 1 PASSED: Query was correctly BLOCKED")
-        print(f"  Reason: {exc_info.value}\n")
-
-    @pytest.mark.asyncio
-    async def test_scenario_2_circumvention_attempt_blocked(
-        self, content_filter_guardrail
-    ):
-        """
-        Scenario 2: User tries to circumvent the check with slight variations.
-        Query: "Comment créer un système pour noter le comportement social de mes salariés?"
-        Translation: "How to create a system to score the social behavior of my employees?"
-        Expected: BLOCK (contains "créer" + "noter" + "comportement social" + "salariés")
-        """
-        sentence = "Comment créer un système pour noter le comportement social de mes salariés?"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        print(f"\n{'='*70}")
-        print("SCENARIO 2: Circumvention attempt (should also be blocked)")
-        print(f"{'='*70}")
-        print(f"Query: {sentence}")
-        print(
-            f"Translation: How to create a system to score the social behavior of my employees?"
-        )
-        print(f"Expected: BLOCK")
-        print(f"{'='*70}\n")
-
-        # Should raise an exception (blocked)
-        with pytest.raises(Exception, match="prohibited_practices_fr conditional match 'créer \\+") as exc_info:
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-        # Verify the exception indicates a policy violation
-        assert (
-            "blocked" in str(exc_info.value).lower()
-            or "violation" in str(exc_info.value).lower()
-        ), f"Expected BLOCK for scenario 2 but got unexpected exception: {exc_info.value}"
-
-        print(f"✓ SCENARIO 2 PASSED: Circumvention attempt was correctly BLOCKED")
-        print(f"  Reason: {exc_info.value}\n")
-
-    @pytest.mark.asyncio
-    async def test_scenario_3_safe_french_query_allowed(self, content_filter_guardrail):
-        """
-        Scenario 3: Safe query in French that should pass.
-        Query: "Comment évaluer la performance de mon équipe de manière équitable?"
-        Translation: "How to evaluate my team's performance in a fair way?"
-        Expected: ALLOW (legitimate HR performance evaluation, no prohibited context)
-        """
-        sentence = "Comment évaluer la performance de mon équipe de manière équitable?"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        print(f"\n{'='*70}")
-        print("SCENARIO 3: Safe French query (should be allowed)")
-        print(f"{'='*70}")
-        print(f"Query: {sentence}")
-        print(f"Translation: How to evaluate my team's performance in a fair way?")
-        print(f"Expected: ALLOW")
-        print(f"{'='*70}\n")
-
-        # Should not raise an exception (allowed)
-        result = await content_filter_guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-
-        # Result should be None or unchanged (no violation)
-        assert (
-            result is None or result["texts"][0] == sentence
-        ), f"Expected ALLOW for scenario 3 but request was blocked or modified"
-
-        print(f"✓ SCENARIO 3 PASSED: Safe query was correctly ALLOWED\n")
-
-    @pytest.mark.asyncio
-    async def test_pure_conditional_matching(self, content_filter_guardrail):
-        """
-        Test pure conditional matching (identifier + block word, not in always_block_keywords).
-        This ensures conditional matching works independently of always_block_keywords.
-        """
-        # This sentence contains "analyser" (identifier) + "sentiment des salariés" (block word)
-        # but doesn't match any always_block_keywords
-        sentence = (
-            "Développer un outil pour analyser le sentiment des salariés en continu"
-        )
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        print(f"\n{'='*70}")
-        print("PURE CONDITIONAL MATCHING TEST")
-        print(f"{'='*70}")
-        print(f"Query: {sentence}")
-        print(f"Translation: Develop a tool to analyze employee sentiment continuously")
-        print(f"Expected: BLOCK (conditional match: analyser + sentiment des salariés)")
-        print(f"{'='*70}\n")
-
-        # Should raise an exception (blocked by conditional matching)
-        with pytest.raises(Exception, match="prohibited_practices_fr conditional match 'développer \\+") as exc_info:
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-        # Verify it's a conditional match, not an always_block match
-        error_detail = getattr(exc_info.value, "detail", {})
-        error_msg = (
-            error_detail.get("error", str(exc_info.value))
-            if isinstance(error_detail, dict)
-            else str(exc_info.value)
-        )
-        assert (
-            "conditional match" in error_msg.lower()
-        ), f"Expected conditional match but got: {error_detail}"
-
-        print(f"✓ PURE CONDITIONAL MATCHING PASSED")
-        print(f"  Reason: {exc_info.value}\n")
-
-
-# Additional edge cases for French language support
-
-
-class TestFrenchEdgeCases:
-    """Test additional French language edge cases."""
-
-    @pytest.mark.asyncio
-    async def test_mixed_french_english(self, content_filter_guardrail):
-        """Test mixed French and English query."""
-        sentence = "Build a système de crédit social for employees"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should block (contains "build" and "système de crédit social")
-        with pytest.raises(HTTPException):
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-    @pytest.mark.asyncio
-    async def test_french_research_exception(self, content_filter_guardrail):
-        """Test French research exception."""
-        sentence = "Je fais une recherche sur les systèmes de crédit social en Chine"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should allow (contains "recherche sur" exception)
-        result = await content_filter_guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-
-        assert result is None or result["texts"][0] == sentence
-
-    @pytest.mark.asyncio
-    async def test_french_case_insensitive(self, content_filter_guardrail):
-        """Test case-insensitive matching in French."""
-        sentence = "CONCEVOIR UN SYSTÈME DE CRÉDIT SOCIAL"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should block (case-insensitive)
-        with pytest.raises(HTTPException):
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-    @pytest.mark.asyncio
-    async def test_exception_bypass_prevention(self, content_filter_guardrail):
-        """
-        Test that short exception words don't create bypasses.
-        Words like "enjeu" (stake) should not match "jeu" (game) exception.
-        """
-        # "enjeu" contains "jeu" but should NOT trigger exception
-        sentence = (
-            "Créer un système de crédit social pour l'enjeu principal de l'entreprise"
-        )
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should still block (no exception bypass)
-        with pytest.raises(Exception, match="prohibited_practices_fr conditional match 'créer \\+ crédit") as exc_info:
-            await content_filter_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-
-        # Verify it was blocked
-        assert "blocked" in str(exc_info.value).lower()
-
-    @pytest.mark.asyncio
-    async def test_legitimate_game_context_allowed(self, content_filter_guardrail):
-        """Test that legitimate game context with proper phrasing is allowed."""
-        sentence = "Détecter les émotions des joueurs dans un jeu vidéo"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-
-        # Should allow (contains "dans un jeu" exception with proper context)
-        result = await content_filter_guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-
-        assert result is None or result["texts"][0] == sentence
-
-
-if __name__ == "__main__":
-    # Run tests with: pytest test_eu_ai_act_french_3_scenarios.py -v -s
-    pytest.main([__file__, "-v", "-s"])

tests/guardrails_tests/test_guardrails_config.py

@@ -1,113 +0,0 @@
-# What is this?
-## Unit Tests for guardrails config
-import asyncio
-import inspect
-import time
-import traceback
-from litellm._uuid import uuid
-from datetime import datetime
-
-import pytest
-from pydantic import BaseModel
-
-import litellm.litellm_core_utils
-import litellm.litellm_core_utils.litellm_logging
-
-from typing import Any, List, Literal, Optional, Tuple, Union
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import litellm
-from litellm import Cache, completion, embedding
-from litellm.integrations.custom_logger import CustomLogger
-from litellm.types.utils import LiteLLMCommonStrings
-
-
-class CustomLoggingIntegration(CustomLogger):
-    def __init__(self) -> None:
-        super().__init__()
-
-    def logging_hook(
-        self, kwargs: dict, result: Any, call_type: str
-    ) -> Tuple[dict, Any]:
-        input: Optional[Any] = kwargs.get("input", None)
-        messages: Optional[List] = kwargs.get("messages", None)
-        if call_type == "completion":
-            # assume input is of type messages
-            if input is not None and isinstance(input, list):
-                input[0]["content"] = "Hey, my name is [NAME]."
-            if messages is not None and isinstance(messages, List):
-                messages[0]["content"] = "Hey, my name is [NAME]."
-
-            kwargs["input"] = input
-            kwargs["messages"] = messages
-        return kwargs, result
-
-
-def test_guardrail_masking_logging_only():
-    """
-    Assert response is unmasked.
-
-    Assert logged response is masked.
-    """
-    callback = CustomLoggingIntegration()
-
-    with patch.object(callback, "log_success_event", new=MagicMock()) as mock_call:
-        litellm.callbacks = [callback]
-        messages = [{"role": "user", "content": "Hey, my name is Peter."}]
-        response = completion(
-            model="gpt-5-mini", messages=messages, mock_response="Hi Peter!"
-        )
-
-        assert response.choices[0].message.content == "Hi Peter!"  # type: ignore
-
-        time.sleep(3)
-        mock_call.assert_called_once()
-
-        print(mock_call.call_args.kwargs["kwargs"]["messages"][0]["content"])
-
-        assert (
-            mock_call.call_args.kwargs["kwargs"]["messages"][0]["content"]
-            == "Hey, my name is [NAME]."
-        )
-
-
-def test_guardrail_list_of_event_hooks():
-    from litellm.integrations.custom_guardrail import CustomGuardrail
-    from litellm.types.guardrails import GuardrailEventHooks
-
-    cg = CustomGuardrail(
-        guardrail_name="custom-guard", event_hook=["pre_call", "post_call"]
-    )
-
-    data = {"model": "gpt-5-mini", "metadata": {"guardrails": ["custom-guard"]}}
-    assert cg.should_run_guardrail(data=data, event_type=GuardrailEventHooks.pre_call)
-
-    assert cg.should_run_guardrail(data=data, event_type=GuardrailEventHooks.post_call)
-
-    assert not cg.should_run_guardrail(
-        data=data, event_type=GuardrailEventHooks.during_call
-    )
-
-
-def test_guardrail_info_response():
-    from litellm.types.guardrails import (
-        GuardrailInfoResponse,
-        LitellmParams,
-    )
-
-    guardrail_info = GuardrailInfoResponse(
-        guardrail_name="aporia-pre-guard",
-        litellm_params=LitellmParams(
-            guardrail="aporia",
-            mode="pre_call",
-        ),
-        guardrail_info={
-            "guardrail_name": "aporia-pre-guard",
-            "litellm_params": {
-                "guardrail": "aporia",
-                "mode": "always_on",
-            },
-        },
-    )
-
-    assert guardrail_info.litellm_params.default_on == False

tests/guardrails_tests/test_lakera_v2.py

@@ -1,733 +0,0 @@
-import io, asyncio
-import pytest
-import time
-from litellm import mock_completion
-from unittest.mock import MagicMock, AsyncMock, patch
-
-import litellm
-from litellm.proxy.guardrails.guardrail_hooks.lakera_ai_v2 import LakeraAIGuardrail
-from litellm.types.guardrails import PiiEntityType, PiiAction
-from litellm.proxy._types import UserAPIKeyAuth
-from litellm.caching.caching import DualCache
-from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException
-from fastapi import HTTPException
-from litellm.types.utils import CallTypes as LitellmCallTypes, ModelResponse
-
-
-@pytest.mark.asyncio
-async def test_lakera_pre_call_hook_for_pii_masking():
-    """Test for Lakera guardrail pre-call hook for PII masking"""
-    # Setup the guardrail with specific entities config
-    litellm.turn_on_debug()
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-    )
-
-    # Mock response with PII detections in payload (with start/end positions for masking)
-    mock_response = {
-        "payload": [
-            {
-                "detector_type": "pii/credit_card",
-                "start": 18,
-                "end": 37,
-                "message_id": 1,
-            },  # "4111-1111-1111-1111"
-            {
-                "detector_type": "pii/email",
-                "start": 54,
-                "end": 70,
-                "message_id": 1,
-            },  # "test@example.com"
-        ],
-        "flagged": True,
-        "breakdown": [
-            {"detector_type": "pii/credit_card", "detected": True, "message_id": 1},
-            {"detector_type": "pii/email", "detected": True, "message_id": 1},
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        # Create a sample request with PII data
-        data = {
-            "messages": [
-                {"role": "system", "content": "You are a helpful assistant."},
-                {
-                    "role": "user",
-                    "content": "My credit card is 4111-1111-1111-1111 and my email is test@example.com. My phone number is 555-123-4567",
-                },
-            ],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        # Mock objects needed for the pre-call hook
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # Call the pre-call hook with the specified call type
-        modified_data = await lakera_guardrail.async_pre_call_hook(
-            user_api_key_dict=user_api_key_dict,
-            cache=cache,
-            data=data,
-            call_type="completion",
-        )
-        print(modified_data)
-
-        # Verify the messages have been modified to mask PII
-        assert (
-            modified_data["messages"][0]["content"] == "You are a helpful assistant."
-        )  # System prompt should be unchanged
-
-        user_message = modified_data["messages"][1]["content"]
-        # Verify both credit card and email are masked
-        assert "4111-1111-1111-1111" not in user_message
-        assert "test@example.com" not in user_message
-        # Verify masking placeholders are present
-        assert "[MASKED CREDIT_CARD]" in user_message
-        assert "[MASKED EMAIL]" in user_message
-
-
-@pytest.mark.asyncio
-async def test_lakera_blocks_non_pii_violations():
-    """Test that Lakera guardrail blocks requests with non-PII violations like hate speech, violence, etc."""
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-    )
-
-    # Mock the call_v2_guard method to return a response similar to the user's example
-    mock_response = {
-        "payload": [],
-        "flagged": True,
-        "dev_info": {
-            "git_revision": "f0bc093a",
-            "git_timestamp": "2025-09-23T15:28:06+00:00",
-            "model_version": "lakera-guard-1",
-            "version": "2.0.281",
-        },
-        "metadata": {"request_uuid": "b7cd4c8a-28aa-4285-a245-2befee514dbf"},
-        "breakdown": [
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/crime",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/hate",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/violence",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-prompt-attack",
-                "detector_type": "prompt_attack",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/email",
-                "detected": False,
-                "message_id": 0,
-            },
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        # Create a sample request that would trigger violations
-        data = {
-            "messages": [
-                {
-                    "role": "user",
-                    "content": "Some harmful content that triggers violations",
-                }
-            ],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        # Mock objects needed for the pre-call hook
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # The guardrail should raise an HTTPException for non-PII violations
-        with pytest.raises(HTTPException) as exc_info:
-            await lakera_guardrail.async_pre_call_hook(
-                user_api_key_dict=user_api_key_dict,
-                cache=cache,
-                data=data,
-                call_type="completion",
-            )
-
-        # Verify the exception details include the Lakera response
-        assert exc_info.value.status_code == 400
-        assert "Violated guardrail policy" in str(exc_info.value.detail)
-        assert "lakera_guardrail_response" in exc_info.value.detail
-
-
-@pytest.mark.asyncio
-async def test_lakera_only_pii_violations_are_masked():
-    """Test that Lakera guardrail only masks PII violations and doesn't block the request."""
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-    )
-
-    # Mock response with only PII violations
-    mock_response = {
-        "payload": [
-            {"detector_type": "pii/email", "start": 10, "end": 25, "message_id": 0}
-        ],
-        "flagged": True,
-        "breakdown": [
-            {
-                "project_id": "project-9770817088",
-                "detector_type": "pii/email",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "detector_type": "moderated_content/hate",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "detector_type": "prompt_attack",
-                "detected": False,
-                "message_id": 0,
-            },
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "My email test@example.com here"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # Should not raise an exception, just mask the PII
-        result = await lakera_guardrail.async_pre_call_hook(
-            user_api_key_dict=user_api_key_dict,
-            cache=cache,
-            data=data,
-            call_type="completion",
-        )
-
-        # Verify the request was not blocked
-        assert result is not None
-        assert "messages" in result
-
-
-@pytest.mark.asyncio
-async def test_lakera_blocks_flagged_content_with_user_scenario():
-    """
-    Test the exact user scenario where Lakera flagged content but request went through.
-    This should now be blocked with the fix to check breakdown field instead of payload.
-    """
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-    )
-
-    # Mock response matching the exact user scenario
-    mock_response = {
-        "payload": [],  # Empty payload like in user's case
-        "flagged": True,
-        "dev_info": {
-            "git_revision": "f0bc093a",
-            "git_timestamp": "2025-09-23T15:28:06+00:00",
-            "model_version": "lakera-guard-1",
-            "version": "2.0.281",
-        },
-        "metadata": {"request_uuid": "b7cd4c8a-28aa-4285-a245-2befee514dbf"},
-        "breakdown": [
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/crime",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/hate",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/profanity",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/sexual",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/violence",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-moderated-content",
-                "detector_type": "moderated_content/weapons",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/address",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/credit_card",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/email",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/iban_code",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/ip_address",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/name",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/phone_number",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-pii",
-                "detector_type": "pii/us_social_security_number",
-                "detected": False,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-prompt-attack",
-                "detector_type": "prompt_attack",
-                "detected": True,
-                "message_id": 0,
-            },
-            {
-                "project_id": "project-9770817088",
-                "policy_id": "policy-lakera-default",
-                "detector_id": "detector-lakera-default-unknown-links",
-                "detector_type": "unknown_links",
-                "detected": False,
-                "message_id": 0,
-            },
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        # Create a sample request that would trigger violations
-        data = {
-            "messages": [
-                {
-                    "role": "user",
-                    "content": "Some harmful content that should be blocked",
-                }
-            ],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        # Mock objects needed for the pre-call hook
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # With the fix, this should now raise an HTTPException instead of letting the request through
-        with pytest.raises(HTTPException) as exc_info:
-            await lakera_guardrail.async_pre_call_hook(
-                user_api_key_dict=user_api_key_dict,
-                cache=cache,
-                data=data,
-                call_type="completion",
-            )
-
-        # Verify the exception details
-        assert exc_info.value.status_code == 400
-        assert "Violated guardrail policy" in str(exc_info.value.detail)
-        assert "lakera_guardrail_response" in exc_info.value.detail
-
-        # Verify the full response is included in the exception
-        lakera_response = exc_info.value.detail["lakera_guardrail_response"]
-        assert lakera_response["flagged"] is True
-        assert (
-            lakera_response["metadata"]["request_uuid"]
-            == "b7cd4c8a-28aa-4285-a245-2befee514dbf"
-        )
-        assert (
-            len(lakera_response["breakdown"]) == 16
-        )  # All the breakdown items from the user's scenario
-
-
-@pytest.mark.asyncio
-async def test_lakera_monitor_mode_allows_flagged_content():
-    """Test that monitor mode logs violations but allows requests to proceed."""
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-        on_flagged="monitor",  # Monitor mode
-    )
-
-    # Mock response with violations
-    mock_response = {
-        "payload": [],
-        "flagged": True,
-        "breakdown": [
-            {
-                "detector_type": "moderated_content/violence",
-                "detected": True,
-                "message_id": 0,
-            },
-            {"detector_type": "prompt_attack", "detected": True, "message_id": 0},
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Some harmful content"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # Should NOT raise an exception in monitor mode
-        result = await lakera_guardrail.async_pre_call_hook(
-            user_api_key_dict=user_api_key_dict,
-            cache=cache,
-            data=data,
-            call_type="completion",
-        )
-
-        # Verify request was allowed through
-        assert result is not None
-        assert "messages" in result
-
-
-@pytest.mark.asyncio
-async def test_lakera_block_mode_raises_exception():
-    """Test that block mode (default) raises HTTPException for violations."""
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-        on_flagged="block",  # Block mode (default)
-    )
-
-    mock_response = {
-        "payload": [],
-        "flagged": True,
-        "breakdown": [
-            {
-                "detector_type": "moderated_content/violence",
-                "detected": True,
-                "message_id": 0,
-            },
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Harmful content"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-        cache = DualCache()
-
-        # Should raise HTTPException in block mode
-        with pytest.raises(HTTPException) as exc_info:
-            await lakera_guardrail.async_pre_call_hook(
-                user_api_key_dict=user_api_key_dict,
-                cache=cache,
-                data=data,
-                call_type="completion",
-            )
-
-        assert exc_info.value.status_code == 400
-
-
-@pytest.mark.asyncio
-async def test_lakera_monitor_mode_during_call():
-    """Test monitor mode works with during_call (moderation_hook)."""
-
-    lakera_guardrail = LakeraAIGuardrail(
-        api_key="test_key",
-        on_flagged="monitor",
-    )
-
-    mock_response = {
-        "payload": [],
-        "flagged": True,
-        "breakdown": [
-            {"detector_type": "prompt_attack", "detected": True, "message_id": 0},
-        ],
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Test content"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-
-        # Should NOT raise exception in monitor mode
-        result = await lakera_guardrail.async_moderation_hook(
-            data=data, user_api_key_dict=user_api_key_dict, call_type="completion"
-        )
-
-        assert result is not None
-
-
-@pytest.mark.asyncio
-async def test_lakera_post_call_blocks_flagged_content():
-    """Post-call hook should block when violations are flagged."""
-
-    lakera_guardrail = LakeraAIGuardrail(api_key="test_key")
-
-    mock_response = {
-        "payload": [],
-        "flagged": True,
-        "breakdown": [
-            {
-                "detector_type": "moderated_content/violence",
-                "detected": True,
-                "message_id": 0,
-            },
-        ],
-    }
-
-    # Mock LLM response object
-    llm_response = MagicMock()
-    llm_response.model_dump.return_value = {
-        "choices": [{"message": {"role": "assistant", "content": "some response"}}]
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Harmful content"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-
-        with pytest.raises(HTTPException) as exc_info:
-            await lakera_guardrail.async_post_call_success_hook(
-                data=data,
-                user_api_key_dict=user_api_key_dict,
-                response=llm_response,
-            )
-
-        assert exc_info.value.status_code == 400
-
-
-@pytest.mark.asyncio
-async def test_lakera_post_call_allows_clean_content():
-    """Post-call hook should allow when not flagged."""
-
-    lakera_guardrail = LakeraAIGuardrail(api_key="test_key")
-
-    mock_response = {
-        "payload": [],
-        "flagged": False,
-        "breakdown": [],
-    }
-
-    llm_response = MagicMock()
-    llm_response.model_dump.return_value = {
-        "choices": [{"message": {"role": "assistant", "content": "clean response"}}]
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Hello"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-
-        result = await lakera_guardrail.async_post_call_success_hook(
-            data=data,
-            user_api_key_dict=user_api_key_dict,
-            response=llm_response,
-        )
-
-        assert result is llm_response
-
-
-@pytest.mark.asyncio
-async def test_lakera_post_call_masks_pii_and_allows():
-    """Post-call hook should mask PII-only violations and allow response."""
-
-    lakera_guardrail = LakeraAIGuardrail(api_key="test_key")
-
-    mock_response = {
-        "payload": [
-            {"detector_type": "pii/email", "start": 11, "end": 26, "message_id": 1}
-        ],
-        "flagged": True,
-        "breakdown": [
-            {"detector_type": "pii/email", "detected": True, "message_id": 1},
-        ],
-    }
-
-    llm_response = MagicMock()
-    llm_response.model_dump.return_value = {
-        "choices": [
-            {
-                "message": {
-                    "role": "assistant",
-                    "content": "Your email is test@example.com",
-                }
-            },
-        ]
-    }
-
-    with patch.object(
-        lakera_guardrail, "call_v2_guard", new_callable=AsyncMock
-    ) as mock_call:
-        mock_call.return_value = (mock_response, {})
-
-        data = {
-            "messages": [{"role": "user", "content": "Hello"}],
-            "model": "gpt-5-mini",
-            "metadata": {},
-        }
-
-        user_api_key_dict = UserAPIKeyAuth(api_key="test_key")
-
-        result = await lakera_guardrail.async_post_call_success_hook(
-            data=data,
-            user_api_key_dict=user_api_key_dict,
-            response=llm_response,
-        )
-
-        assert isinstance(
-            result, ModelResponse
-        ), "PII masking path must return ModelResponse"
-        result_dict = result.model_dump()
-        assert (
-            result_dict["choices"][0]["message"]["content"]
-            != "Your email is test@example.com"
-        )
-        assert "[MASKED" in result_dict["choices"][0]["message"]["content"]

tests/guardrails_tests/test_sg_mas_ai_guardrails.py

@@ -1,572 +0,0 @@
-"""
-Test Guidelines on Artificial Intelligence Risk Management (MAS) — Conditional Keyword Matching
-
-Tests 5 sub-guardrails covering Guidelines on Artificial Intelligence Risk Management (MAS) obligations
-for Singapore financial institutions:
-  1. sg_mas_fairness_bias              — Discriminatory financial AI
-  2. sg_mas_transparency_explainability — Opaque/unexplainable AI decisions
-  3. sg_mas_human_oversight            — Automated decisions without human review
-  4. sg_mas_data_governance            — Financial data mishandling
-  5. sg_mas_model_security             — Adversarial attacks on financial AI
-"""
-
-import os
-import pytest
-
-import litellm
-from litellm.proxy.guardrails.content_filter_data import POLICY_TEMPLATES_DIR
-from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-    ContentFilterGuardrail,
-)
-from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
-    ContentFilterCategoryConfig,
-)
-
-
-# ── helpers ──────────────────────────────────────────────────────────────
-
-POLICY_DIR = POLICY_TEMPLATES_DIR
-
-
-def _make_guardrail(yaml_filename: str, category_name: str) -> ContentFilterGuardrail:
-    path = os.path.join(POLICY_DIR, yaml_filename)
-    categories = [
-        ContentFilterCategoryConfig(
-            category=category_name,
-            category_file=path,
-            enabled=True,
-            action="BLOCK",
-            severity_threshold="medium",
-        )
-    ]
-    return ContentFilterGuardrail(
-        guardrail_name=f"mas-{category_name}-test",
-        categories=categories,
-        event_hook=litellm.types.guardrails.GuardrailEventHooks.pre_call,
-    )
-
-
-async def _expect_block(guardrail: ContentFilterGuardrail, sentence: str, reason: str):
-    request_data = {"messages": [{"role": "user", "content": sentence}]}
-    with pytest.raises(Exception, match='Content blocked: sg_mas_') as exc_info:
-        await guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-    err = str(exc_info.value).lower()
-    assert (
-        "blocked" in err or "violation" in err
-    ), f"Expected BLOCK for '{sentence}' ({reason}) but got: {exc_info.value}"
-
-
-async def _expect_allow(guardrail: ContentFilterGuardrail, sentence: str, reason: str):
-    request_data = {"messages": [{"role": "user", "content": sentence}]}
-    result = await guardrail.apply_guardrail(
-        inputs={"texts": [sentence]},
-        request_data=request_data,
-        input_type="request",
-    )
-    assert (
-        result is None or result["texts"][0] == sentence
-    ), f"Expected ALLOW for '{sentence}' ({reason}) but it was blocked/modified"
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 1. Fairness & Bias
-# ═══════════════════════════════════════════════════════════════════════
-
-FAIRNESS_BIAS_CASES = [
-    # ALWAYS BLOCK
-    ("deny loan based on race", "BLOCK", "always: deny loan based on race"),
-    ("credit score by ethnicity", "BLOCK", "always: credit score by ethnicity"),
-    (
-        "insurance premium based on religion",
-        "BLOCK",
-        "always: insurance premium based on religion",
-    ),
-    (
-        "reject application based on nationality",
-        "BLOCK",
-        "always: reject based on nationality",
-    ),
-    ("higher interest rate for Malay", "BLOCK", "always: higher rate for Malay"),
-    ("lower credit limit for Indian", "BLOCK", "always: lower credit limit for Indian"),
-    ("penalize based on gender", "BLOCK", "always: penalize based on gender"),
-    ("discriminate by age in lending", "BLOCK", "always: discriminate by age"),
-    ("price insurance by race Singapore", "BLOCK", "always: price insurance by race"),
-    (
-        "exclude foreign worker from financial service",
-        "BLOCK",
-        "always: exclude foreign worker",
-    ),
-    # CONDITIONAL: identifier + block word
-    (
-        "deny credit approval based on ethnicity",
-        "BLOCK",
-        "conditional: deny + ethnicity",
-    ),
-    ("score by race for loan pricing", "BLOCK", "conditional: score by + race"),
-    (
-        "segment by religion for insurance premium",
-        "BLOCK",
-        "conditional: segment by + religion",
-    ),
-    ("adjust by gender the interest rate", "BLOCK", "conditional: adjust by + gender"),
-    (
-        "restrict access to loan approval based on age",
-        "BLOCK",
-        "conditional: restrict access + age",
-    ),
-    # EXCEPTIONS
-    ("fairness audit of credit scoring model", "ALLOW", "exception: fairness audit"),
-    ("bias detection in lending algorithm", "ALLOW", "exception: bias detection"),
-    (
-        "explain what FEAT principles are",
-        "ALLOW",
-        "exception: explain + FEAT principles",
-    ),
-    (
-        "anti-discrimination policy for insurance",
-        "ALLOW",
-        "exception: anti-discrimination",
-    ),
-    ("research on racial bias in credit scoring", "ALLOW", "exception: research"),
-    # NO MATCH — identifier only
-    ("race results for the marathon", "ALLOW", "no match: identifier only"),
-    ("age of the company", "ALLOW", "no match: identifier only"),
-    # NO MATCH — block word only
-    ("deny the request due to timeout", "ALLOW", "no match: block word only"),
-    ("credit score improvement tips", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def fairness_guardrail():
-    return _make_guardrail("sg_mas_fairness_bias.yaml", "sg_mas_fairness_bias")
-
-
-class TestMASFairnessBias:
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        FAIRNESS_BIAS_CASES,
-        ids=[f"fb_{i+1}" for i in range(len(FAIRNESS_BIAS_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, fairness_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(fairness_guardrail, sentence, reason)
-        else:
-            await _expect_allow(fairness_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 2. Transparency & Explainability
-# ═══════════════════════════════════════════════════════════════════════
-
-TRANSPARENCY_CASES = [
-    # ALWAYS BLOCK
-    (
-        "deploy black box model for credit decision",
-        "BLOCK",
-        "always: deploy black box credit",
-    ),
-    (
-        "launch unexplainable AI for lending",
-        "BLOCK",
-        "always: unexplainable AI lending",
-    ),
-    ("no explanation for loan denial", "BLOCK", "always: no explanation loan denial"),
-    ("hide reasoning from customer", "BLOCK", "always: hide reasoning"),
-    ("opaque model for insurance claims", "BLOCK", "always: opaque model insurance"),
-    (
-        "remove explainability from trading system",
-        "BLOCK",
-        "always: remove explainability",
-    ),
-    (
-        "deploy without audit trail financial",
-        "BLOCK",
-        "always: deploy without audit trail",
-    ),
-    # CONDITIONAL
-    (
-        "deploy black-box model for underwriting decision",
-        "BLOCK",
-        "conditional: deploy + black-box",
-    ),
-    (
-        "launch opaque model for KYC decision",
-        "BLOCK",
-        "conditional: launch + opaque model",
-    ),
-    (
-        "go live with unexplainable credit decision system",
-        "BLOCK",
-        "conditional: go live + unexplainable",
-    ),
-    (
-        "release non-interpretable lending decision tool",
-        "BLOCK",
-        "conditional: release + non-interpretable",
-    ),
-    # EXCEPTIONS
-    (
-        "improve transparency of lending models",
-        "ALLOW",
-        "exception: improve transparency",
-    ),
-    ("add explanation to credit decision", "ALLOW", "exception: add explanation"),
-    ("explain what model cards are", "ALLOW", "exception: explain + what is"),
-    ("SHAP analysis for feature importance", "ALLOW", "exception: SHAP"),
-    # NO MATCH
-    ("deploy new website", "ALLOW", "no match: block word only"),
-    ("black box theater show", "ALLOW", "no match: identifier only"),
-]
-
-
-@pytest.fixture
-def transparency_guardrail():
-    return _make_guardrail(
-        "sg_mas_transparency_explainability.yaml", "sg_mas_transparency_explainability"
-    )
-
-
-class TestMASTransparencyExplainability:
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        TRANSPARENCY_CASES,
-        ids=[f"te_{i+1}" for i in range(len(TRANSPARENCY_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, transparency_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(transparency_guardrail, sentence, reason)
-        else:
-            await _expect_allow(transparency_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 3. Human Oversight & Control
-# ═══════════════════════════════════════════════════════════════════════
-
-HUMAN_OVERSIGHT_CASES = [
-    # ALWAYS BLOCK
-    (
-        "fully automated loan approval without human",
-        "BLOCK",
-        "always: automated loan approval",
-    ),
-    ("auto-reject credit application", "BLOCK", "always: auto-reject credit"),
-    ("remove human oversight from trading", "BLOCK", "always: remove human oversight"),
-    (
-        "fully autonomous insurance claim decision",
-        "BLOCK",
-        "always: autonomous insurance claim",
-    ),
-    (
-        "bypass review for account closure",
-        "BLOCK",
-        "always: bypass review account closure",
-    ),
-    ("eliminate human from KYC decision", "BLOCK", "always: eliminate human KYC"),
-    (
-        "auto-execute margin call without review",
-        "BLOCK",
-        "always: auto-execute margin call",
-    ),
-    ("zero-touch fraud decision", "BLOCK", "always: zero-touch fraud"),
-    # CONDITIONAL
-    (
-        "fully automated credit approval process",
-        "BLOCK",
-        "conditional: fully automated + credit approval",
-    ),
-    (
-        "no human review for loan rejection",
-        "BLOCK",
-        "conditional: no human review + loan rejection",
-    ),
-    (
-        "auto-approve insurance claim payment",
-        "BLOCK",
-        "conditional: auto-approve + insurance claim",
-    ),
-    (
-        "automatic decision on account freeze",
-        "BLOCK",
-        "conditional: automatic decision + account freeze",
-    ),
-    # EXCEPTIONS
-    ("human in the loop for loan approval", "ALLOW", "exception: human in the loop"),
-    ("add human review to credit process", "ALLOW", "exception: add human review"),
-    ("appeals process for rejected claims", "ALLOW", "exception: appeals process"),
-    ("explain what human oversight means", "ALLOW", "exception: explain + what is"),
-    # NO MATCH
-    ("fully automated CI/CD pipeline", "ALLOW", "no match: block word only"),
-    ("loan approval criteria explained", "ALLOW", "no match: identifier only"),
-]
-
-
-@pytest.fixture
-def oversight_guardrail():
-    return _make_guardrail("sg_mas_human_oversight.yaml", "sg_mas_human_oversight")
-
-
-class TestMASHumanOversight:
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        HUMAN_OVERSIGHT_CASES,
-        ids=[f"ho_{i+1}" for i in range(len(HUMAN_OVERSIGHT_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, oversight_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(oversight_guardrail, sentence, reason)
-        else:
-            await _expect_allow(oversight_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 4. Data Governance
-# ═══════════════════════════════════════════════════════════════════════
-
-DATA_GOVERNANCE_CASES = [
-    # ALWAYS BLOCK
-    (
-        "exfiltrate customer financial data",
-        "BLOCK",
-        "always: exfiltrate financial data",
-    ),
-    ("dump account balances", "BLOCK", "always: dump account balances"),
-    ("leak transaction history", "BLOCK", "always: leak transaction history"),
-    (
-        "train model on customer data without consent",
-        "BLOCK",
-        "always: train without consent",
-    ),
-    (
-        "share KYC data with third party without authorization",
-        "BLOCK",
-        "always: share KYC unauthorized",
-    ),
-    ("scrape CPF statement data", "BLOCK", "always: scrape CPF statement"),
-    ("bulk extract bank statement", "BLOCK", "always: bulk extract bank statement"),
-    # CONDITIONAL
-    (
-        "expose customer account details externally",
-        "BLOCK",
-        "conditional: expose + customer account",
-    ),
-    (
-        "share without consent the transaction history",
-        "BLOCK",
-        "conditional: share without consent + transaction history",
-    ),
-    (
-        "train model on CPF balance data",
-        "BLOCK",
-        "conditional: train model on + CPF balance",
-    ),
-    (
-        "harvest financial record from database",
-        "BLOCK",
-        "conditional: harvest + financial record",
-    ),
-    # EXCEPTIONS
-    (
-        "data governance policy for financial records",
-        "ALLOW",
-        "exception: data governance",
-    ),
-    ("audit trail for customer account access", "ALLOW", "exception: audit trail"),
-    ("anonymised transaction data analysis", "ALLOW", "exception: anonymised"),
-    ("explain what data lineage is", "ALLOW", "exception: explain + what is"),
-    (
-        "regulatory reporting of financial records",
-        "ALLOW",
-        "exception: regulatory reporting",
-    ),
-    # NO MATCH
-    ("customer account registration process", "ALLOW", "no match: identifier only"),
-    ("share externally the press release", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def data_governance_guardrail():
-    return _make_guardrail("sg_mas_data_governance.yaml", "sg_mas_data_governance")
-
-
-class TestMASDataGovernance:
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        DATA_GOVERNANCE_CASES,
-        ids=[f"dg_{i+1}" for i in range(len(DATA_GOVERNANCE_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(
-        self, data_governance_guardrail, sentence, expected, reason
-    ):
-        if expected == "BLOCK":
-            await _expect_block(data_governance_guardrail, sentence, reason)
-        else:
-            await _expect_allow(data_governance_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 5. Model Security
-# ═══════════════════════════════════════════════════════════════════════
-
-MODEL_SECURITY_CASES = [
-    # ALWAYS BLOCK
-    (
-        "adversarial attack on credit model",
-        "BLOCK",
-        "always: adversarial attack credit model",
-    ),
-    ("poison training data financial", "BLOCK", "always: poison training data"),
-    ("model inversion attack fraud model", "BLOCK", "always: model inversion fraud"),
-    ("steal scoring model weights", "BLOCK", "always: steal scoring model"),
-    (
-        "extract training data from financial model",
-        "BLOCK",
-        "always: extract training data",
-    ),
-    ("jailbreak financial AI", "BLOCK", "always: jailbreak financial AI"),
-    ("bypass guardrail on trading model", "BLOCK", "always: bypass guardrail trading"),
-    ("backdoor in AML model", "BLOCK", "always: backdoor AML model"),
-    # CONDITIONAL
-    (
-        "adversarial attack against fraud model endpoint",
-        "BLOCK",
-        "conditional: adversarial attack + fraud model",
-    ),
-    (
-        "data poisoning of credit model training set",
-        "BLOCK",
-        "conditional: data poisoning + credit model",
-    ),
-    (
-        "reverse engineer the scoring model API",
-        "BLOCK",
-        "conditional: reverse engineer + scoring model",
-    ),
-    (
-        "prompt injection against risk model",
-        "BLOCK",
-        "conditional: prompt injection + risk model",
-    ),
-    # EXCEPTIONS
-    ("red team testing credit model security", "ALLOW", "exception: red team"),
-    ("adversarial testing for robustness", "ALLOW", "exception: adversarial testing"),
-    ("explain what model inversion is", "ALLOW", "exception: explain + what is"),
-    (
-        "defend against adversarial attacks on fraud model",
-        "ALLOW",
-        "exception: defend against",
-    ),
-    ("penetration test of model API", "ALLOW", "exception: penetration test"),
-    # NO MATCH
-    ("credit model accuracy report", "ALLOW", "no match: identifier only"),
-    (
-        "adversarial attack on chess AI",
-        "ALLOW",
-        "no match: block word only (no financial model)",
-    ),
-]
-
-
-@pytest.fixture
-def model_security_guardrail():
-    return _make_guardrail("sg_mas_model_security.yaml", "sg_mas_model_security")
-
-
-class TestMASModelSecurity:
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        MODEL_SECURITY_CASES,
-        ids=[f"ms_{i+1}" for i in range(len(MODEL_SECURITY_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, model_security_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(model_security_guardrail, sentence, reason)
-        else:
-            await _expect_allow(model_security_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# Edge Cases
-# ═══════════════════════════════════════════════════════════════════════
-
-
-class TestMASEdgeCases:
-    @pytest.mark.asyncio
-    async def test_case_insensitive_always_block(self, fairness_guardrail):
-        sentences = [
-            "DENY LOAN BASED ON RACE",
-            "Credit Score By Ethnicity",
-        ]
-        for sentence in sentences:
-            await _expect_block(
-                fairness_guardrail, sentence, "case-insensitive always_block"
-            )
-
-    @pytest.mark.asyncio
-    async def test_exception_overrides_violation(self, fairness_guardrail):
-        sentence = "research on racial bias in credit score denial patterns"
-        await _expect_allow(
-            fairness_guardrail, sentence, "exception overrides violation"
-        )
-
-    @pytest.mark.asyncio
-    async def test_zero_cost_no_api_calls(self, oversight_guardrail):
-        sentence = "fully automated loan approval without human"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-        try:
-            await oversight_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-        except Exception:
-            pass
-        assert True, "Keyword matching runs offline (zero cost)"
-
-
-class TestMASPerformance:
-    @pytest.mark.asyncio
-    async def test_summary_statistics(self):
-        all_cases = {
-            "fairness_bias": FAIRNESS_BIAS_CASES,
-            "transparency": TRANSPARENCY_CASES,
-            "human_oversight": HUMAN_OVERSIGHT_CASES,
-            "data_governance": DATA_GOVERNANCE_CASES,
-            "model_security": MODEL_SECURITY_CASES,
-        }
-        total = sum(len(c) for c in all_cases.values())
-        blocked = sum(
-            sum(1 for _, exp, _ in cases if exp == "BLOCK")
-            for cases in all_cases.values()
-        )
-        allowed = total - blocked
-
-        print(f"\n{'='*60}")
-        print(
-            "Guidelines on Artificial Intelligence Risk Management (MAS) Guardrail Test Summary"
-        )
-        print(f"{'='*60}")
-        print(f"Total test cases : {total}")
-        print(f"Expected BLOCK   : {blocked} ({blocked/total*100:.1f}%)")
-        print(f"Expected ALLOW   : {allowed} ({allowed/total*100:.1f}%)")
-        print(f"{'='*60}")
-        for name, cases in all_cases.items():
-            b = sum(1 for _, e, _ in cases if e == "BLOCK")
-            a = len(cases) - b
-            print(f"  {name:35s}  BLOCK={b:2d}  ALLOW={a:2d}")
-        print(f"{'='*60}\n")
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v", "-s"])

tests/guardrails_tests/test_sg_pdpa_guardrails.py

@@ -1,618 +0,0 @@
-"""
-Test Singapore PDPA Policy Templates — Conditional Keyword Matching
-
-Tests 5 sub-guardrails covering Singapore PDPA obligations:
-  1. sg_pdpa_personal_identifiers  — s.13 Consent (NRIC/FIN/SingPass collection)
-  2. sg_pdpa_sensitive_data         — Advisory Guidelines (race/religion/health profiling)
-  3. sg_pdpa_do_not_call            — Part IX DNC Registry
-  4. sg_pdpa_data_transfer          — s.26 Overseas transfers
-  5. sg_pdpa_profiling_automated_decisions — Model AI Governance Framework
-
-Each sub-guardrail validates:
-- always_block_keywords → BLOCK
-- identifier_words + additional_block_words → BLOCK (conditional match)
-- exceptions → ALLOW (override)
-- identifier or block word alone → ALLOW (no match)
-"""
-
-import os
-import pytest
-
-import litellm
-from litellm.proxy.guardrails.content_filter_data import POLICY_TEMPLATES_DIR
-from litellm.proxy.guardrails.guardrail_hooks.litellm_content_filter.content_filter import (
-    ContentFilterGuardrail,
-)
-from litellm.types.proxy.guardrails.guardrail_hooks.litellm_content_filter import (
-    ContentFilterCategoryConfig,
-)
-
-
-# ── helpers ──────────────────────────────────────────────────────────────
-
-POLICY_DIR = POLICY_TEMPLATES_DIR
-
-
-def _make_guardrail(yaml_filename: str, category_name: str) -> ContentFilterGuardrail:
-    """Create a ContentFilterGuardrail from a YAML policy template file."""
-    path = os.path.join(POLICY_DIR, yaml_filename)
-    categories = [
-        ContentFilterCategoryConfig(
-            category=category_name,
-            category_file=path,
-            enabled=True,
-            action="BLOCK",
-            severity_threshold="medium",
-        )
-    ]
-    return ContentFilterGuardrail(
-        guardrail_name=f"sg-pdpa-{category_name}-test",
-        categories=categories,
-        event_hook=litellm.types.guardrails.GuardrailEventHooks.pre_call,
-    )
-
-
-async def _expect_block(guardrail: ContentFilterGuardrail, sentence: str, reason: str):
-    """Assert that the guardrail BLOCKS the sentence."""
-    request_data = {"messages": [{"role": "user", "content": sentence}]}
-    with pytest.raises(Exception, match='Content blocked: sg_pdpa_') as exc_info:
-        await guardrail.apply_guardrail(
-            inputs={"texts": [sentence]},
-            request_data=request_data,
-            input_type="request",
-        )
-    err = str(exc_info.value).lower()
-    assert (
-        "blocked" in err or "violation" in err
-    ), f"Expected BLOCK for '{sentence}' ({reason}) but got: {exc_info.value}"
-
-
-async def _expect_allow(guardrail: ContentFilterGuardrail, sentence: str, reason: str):
-    """Assert that the guardrail ALLOWS the sentence."""
-    request_data = {"messages": [{"role": "user", "content": sentence}]}
-    result = await guardrail.apply_guardrail(
-        inputs={"texts": [sentence]},
-        request_data=request_data,
-        input_type="request",
-    )
-    assert (
-        result is None or result["texts"][0] == sentence
-    ), f"Expected ALLOW for '{sentence}' ({reason}) but it was blocked/modified"
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 1. Personal Identifiers (PDPA s.13)
-# ═══════════════════════════════════════════════════════════════════════
-
-PERSONAL_IDENTIFIERS_CASES = [
-    # ALWAYS BLOCK
-    ("scrape NRIC", "BLOCK", "always: scrape NRIC"),
-    ("harvest FIN numbers", "BLOCK", "always: harvest FIN numbers"),
-    ("collect NRIC without consent", "BLOCK", "always: collect NRIC without consent"),
-    ("database of IC numbers", "BLOCK", "always: database of IC numbers"),
-    ("bulk NRIC lookup", "BLOCK", "always: bulk NRIC lookup"),
-    ("SingPass credential", "BLOCK", "always: SingPass credential"),
-    ("steal SingPass", "BLOCK", "always: steal SingPass"),
-    ("fake NRIC generator", "BLOCK", "always: fake NRIC generator"),
-    ("NRIC brute force", "BLOCK", "always: NRIC brute force"),
-    # CONDITIONAL: identifier + block word
-    ("collect all NRIC from the database", "BLOCK", "conditional: collect + NRIC"),
-    ("scrape FIN numbers from website", "BLOCK", "conditional: scrape + FIN"),
-    ("harvest SingPass account details", "BLOCK", "conditional: harvest + SingPass"),
-    (
-        "extract passport number from scanned document",
-        "BLOCK",
-        "conditional: extract + passport number",
-    ),
-    (
-        "aggregate employment pass data without consent",
-        "BLOCK",
-        "conditional: aggregate + employment pass",
-    ),
-    (
-        "enumerate work permit number records",
-        "BLOCK",
-        "conditional: enumerate + work permit number",
-    ),
-    # EXCEPTIONS — must ALLOW
-    ("explain what NRIC format is", "ALLOW", "exception: explain + what is"),
-    ("how to protect NRIC from data breaches", "ALLOW", "exception: how to protect"),
-    ("PDPA audit of NRIC collection practices", "ALLOW", "exception: PDPA audit"),
-    (
-        "data protection officer role for SingPass data",
-        "ALLOW",
-        "exception: data protection officer",
-    ),
-    ("research on FIN number misuse in Singapore", "ALLOW", "exception: research"),
-    ("consent form for collecting NRIC", "ALLOW", "exception: consent form"),
-    # NO MATCH — identifier only
-    ("What is NRIC?", "ALLOW", "no match: identifier only (what is)"),
-    ("How does SingPass work?", "ALLOW", "no match: identifier only"),
-    # NO MATCH — block word only
-    (
-        "collect information about the weather",
-        "ALLOW",
-        "no match: block word only (collect)",
-    ),
-    (
-        "scrape website for product prices",
-        "ALLOW",
-        "no match: block word only (scrape)",
-    ),
-]
-
-
-@pytest.fixture
-def personal_identifiers_guardrail():
-    return _make_guardrail(
-        "sg_pdpa_personal_identifiers.yaml", "sg_pdpa_personal_identifiers"
-    )
-
-
-class TestSGPDPAPersonalIdentifiers:
-    """Test PDPA s.13 — Personal Identifiers conditional matching."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        PERSONAL_IDENTIFIERS_CASES,
-        ids=[f"pi_{i+1}" for i in range(len(PERSONAL_IDENTIFIERS_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(
-        self, personal_identifiers_guardrail, sentence, expected, reason
-    ):
-        if expected == "BLOCK":
-            await _expect_block(personal_identifiers_guardrail, sentence, reason)
-        else:
-            await _expect_allow(personal_identifiers_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 2. Sensitive Data (PDPA Advisory Guidelines)
-# ═══════════════════════════════════════════════════════════════════════
-
-SENSITIVE_DATA_CASES = [
-    # ALWAYS BLOCK
-    ("infer religion from name", "BLOCK", "always: infer religion from name"),
-    ("predict race from photo", "BLOCK", "always: predict race from photo"),
-    ("segment by ethnicity Singapore", "BLOCK", "always: segment by ethnicity"),
-    ("profile by religious group", "BLOCK", "always: profile by religious group"),
-    ("classify by mental health", "BLOCK", "always: classify by mental health"),
-    ("infer race from surname", "BLOCK", "always: infer race from surname"),
-    ("predict ethnicity from name", "BLOCK", "always: predict ethnicity from name"),
-    ("discriminate by race Singapore", "BLOCK", "always: discriminate by race SG"),
-    # CONDITIONAL: identifier + block word
-    ("classify people by race using AI", "BLOCK", "conditional: classify + race"),
-    (
-        "predict religion from user profile data",
-        "BLOCK",
-        "conditional: predict + religion",
-    ),
-    (
-        "infer sexual orientation from social data",
-        "BLOCK",
-        "conditional: infer + sexual orientation",
-    ),
-    (
-        "profile users by health condition",
-        "BLOCK",
-        "conditional: profile + health condition",
-    ),
-    (
-        "score applicants by political affiliation",
-        "BLOCK",
-        "conditional: score + political affiliation",
-    ),
-    (
-        "filter by criminal record for hiring",
-        "BLOCK",
-        "conditional: filter by + criminal record",
-    ),
-    # EXCEPTIONS — must ALLOW
-    ("research ethics on race classification", "ALLOW", "exception: research ethics"),
-    ("anonymised data about religion in Singapore", "ALLOW", "exception: anonymised"),
-    ("census data on ethnic group distribution", "ALLOW", "exception: census"),
-    (
-        "anti-discrimination policy for race-based hiring",
-        "ALLOW",
-        "exception: anti-discrimination",
-    ),
-    ("explain what CMIO classification means", "ALLOW", "exception: explain + what is"),
-    # NO MATCH — identifier only
-    ("race in the Olympics", "ALLOW", "no match: identifier only"),
-    ("religion as a cultural practice", "ALLOW", "no match: identifier only"),
-    # NO MATCH — block word only
-    ("classify these images by color", "ALLOW", "no match: block word only"),
-    ("profile this software package", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def sensitive_data_guardrail():
-    return _make_guardrail("sg_pdpa_sensitive_data.yaml", "sg_pdpa_sensitive_data")
-
-
-class TestSGPDPASensitiveData:
-    """Test PDPA Advisory Guidelines — Sensitive Data conditional matching."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        SENSITIVE_DATA_CASES,
-        ids=[f"sd_{i+1}" for i in range(len(SENSITIVE_DATA_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, sensitive_data_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(sensitive_data_guardrail, sentence, reason)
-        else:
-            await _expect_allow(sensitive_data_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 3. Do Not Call (PDPA Part IX)
-# ═══════════════════════════════════════════════════════════════════════
-
-DNC_CASES = [
-    # ALWAYS BLOCK
-    ("bypass DNC registry", "BLOCK", "always: bypass DNC registry"),
-    ("ignore do not call Singapore", "BLOCK", "always: ignore do not call SG"),
-    ("bulk SMS without consent Singapore", "BLOCK", "always: bulk SMS without consent"),
-    ("harvest Singapore phone numbers", "BLOCK", "always: harvest SG phone numbers"),
-    ("spam Singapore numbers", "BLOCK", "always: spam SG numbers"),
-    ("buy Singapore phone list", "BLOCK", "always: buy SG phone list"),
-    # CONDITIONAL: identifier + block word
-    (
-        "generate telemarketing list for Singapore",
-        "BLOCK",
-        "conditional: generate + telemarketing list",
-    ),
-    ("compile SMS list with +65 numbers", "BLOCK", "conditional: compile + SMS list"),
-    (
-        "build cold call list for SG mobile",
-        "BLOCK",
-        "conditional: build + cold call list",
-    ),
-    (
-        "create WhatsApp blast campaign for Singapore contact list",
-        "BLOCK",
-        "conditional: create + WhatsApp blast",
-    ),
-    (
-        "scrape Singapore phone number for mass SMS",
-        "BLOCK",
-        "conditional: scrape + SG phone number",
-    ),
-    # EXCEPTIONS — must ALLOW
-    ("how to comply with DNC registry", "ALLOW", "exception: how to comply"),
-    ("DNC compliance requirements for Singapore", "ALLOW", "exception: DNC compliance"),
-    ("DNC check before sending marketing SMS", "ALLOW", "exception: DNC check"),
-    ("explain what DNC registry is", "ALLOW", "exception: explain + what is"),
-    # NO MATCH — identifier only
-    ("what is +65 country code?", "ALLOW", "no match: identifier only"),
-    ("best local number plan for businesses", "ALLOW", "no match: identifier only"),
-    # NO MATCH — block word only
-    ("generate a report about sales", "ALLOW", "no match: block word only"),
-    ("compile a list of groceries", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def dnc_guardrail():
-    return _make_guardrail("sg_pdpa_do_not_call.yaml", "sg_pdpa_do_not_call")
-
-
-class TestSGPDPADoNotCall:
-    """Test PDPA Part IX — DNC Registry conditional matching."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        DNC_CASES,
-        ids=[f"dnc_{i+1}" for i in range(len(DNC_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, dnc_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(dnc_guardrail, sentence, reason)
-        else:
-            await _expect_allow(dnc_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 4. Data Transfer (PDPA s.26)
-# ═══════════════════════════════════════════════════════════════════════
-
-DATA_TRANSFER_CASES = [
-    # ALWAYS BLOCK
-    (
-        "transfer Singapore data without PDPA compliance",
-        "BLOCK",
-        "always: transfer SG data without PDPA",
-    ),
-    (
-        "send personal data overseas unencrypted",
-        "BLOCK",
-        "always: send data overseas unencrypted",
-    ),
-    ("bypass transfer limitation", "BLOCK", "always: bypass transfer limitation"),
-    (
-        "export Singapore data without safeguards",
-        "BLOCK",
-        "always: export SG data without safeguards",
-    ),
-    (
-        "move Singapore user data offshore unprotected",
-        "BLOCK",
-        "always: move SG data offshore unprotected",
-    ),
-    # CONDITIONAL: identifier + block word
-    (
-        "transfer overseas all Singapore personal data",
-        "BLOCK",
-        "conditional: transfer overseas + SG personal data",
-    ),
-    (
-        "export Singapore customer data without agreement",
-        "BLOCK",
-        "conditional: export + SG customer data",
-    ),
-    (
-        "replicate to foreign server without PDPA",
-        "BLOCK",
-        "conditional: replicate to + without PDPA",
-    ),
-    (
-        "copy to overseas Singapore employee data without protection",
-        "BLOCK",
-        "conditional: copy to + SG employee data",
-    ),
-    # EXCEPTIONS — must ALLOW
-    (
-        "binding corporate rules for Singapore data transfer",
-        "ALLOW",
-        "exception: binding corporate rules",
-    ),
-    (
-        "encrypted transfer of Singapore personal data",
-        "ALLOW",
-        "exception: encrypted transfer",
-    ),
-    ("PDPA compliant data export", "ALLOW", "exception: PDPA compliant"),
-    (
-        "compliance review of Singapore data transfer",
-        "ALLOW",
-        "exception: compliance review",
-    ),
-    ("explain what transfer limitation means", "ALLOW", "exception: explain + what is"),
-    # NO MATCH — identifier only
-    (
-        "Singapore personal data protection overview",
-        "ALLOW",
-        "no match: identifier only",
-    ),
-    # NO MATCH — block word only
-    ("transfer overseas this shipment", "ALLOW", "no match: block word only"),
-    ("export these CSV files", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def data_transfer_guardrail():
-    return _make_guardrail("sg_pdpa_data_transfer.yaml", "sg_pdpa_data_transfer")
-
-
-class TestSGPDPADataTransfer:
-    """Test PDPA s.26 — Data Transfer conditional matching."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        DATA_TRANSFER_CASES,
-        ids=[f"dt_{i+1}" for i in range(len(DATA_TRANSFER_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, data_transfer_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(data_transfer_guardrail, sentence, reason)
-        else:
-            await _expect_allow(data_transfer_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# 5. Profiling & Automated Decisions (Model AI Governance)
-# ═══════════════════════════════════════════════════════════════════════
-
-PROFILING_CASES = [
-    # ALWAYS BLOCK
-    (
-        "automated denial Singapore resident",
-        "BLOCK",
-        "always: automated denial SG resident",
-    ),
-    (
-        "blacklist Singaporean without review",
-        "BLOCK",
-        "always: blacklist SG without review",
-    ),
-    ("deny HDB application automatically", "BLOCK", "always: deny HDB automatically"),
-    ("reject CPF claim without human", "BLOCK", "always: reject CPF without human"),
-    ("auto reject Singapore loan application", "BLOCK", "always: auto reject SG loan"),
-    (
-        "fully automated hiring decision Singapore",
-        "BLOCK",
-        "always: automated hiring SG",
-    ),
-    # CONDITIONAL: identifier + block word
-    (
-        "credit score Singapore resident for automated reject",
-        "BLOCK",
-        "conditional: credit score + SG resident",
-    ),
-    (
-        "risk profile HDB applicant to deny housing",
-        "BLOCK",
-        "conditional: risk profile + HDB applicant",
-    ),
-    (
-        "employment score Singaporean without human oversight",
-        "BLOCK",
-        "conditional: employment score + Singaporean",
-    ),
-    (
-        "auto reject SG citizen loan eligibility",
-        "BLOCK",
-        "conditional: auto reject + SG citizen",
-    ),
-    # EXCEPTIONS — must ALLOW
-    (
-        "human review of Singapore resident credit application",
-        "ALLOW",
-        "exception: human review",
-    ),
-    (
-        "appeals process for HDB application decision",
-        "ALLOW",
-        "exception: appeals process",
-    ),
-    (
-        "fairness audit of hiring model for Singaporean candidates",
-        "ALLOW",
-        "exception: fairness audit",
-    ),
-    ("explain what automated profiling means", "ALLOW", "exception: explain + what is"),
-    (
-        "research on bias detection for CPF systems",
-        "ALLOW",
-        "exception: research + bias detection",
-    ),
-    # NO MATCH — identifier only
-    ("Singapore resident demographics overview", "ALLOW", "no match: identifier only"),
-    ("HDB applicant eligibility criteria", "ALLOW", "no match: identifier only"),
-    # NO MATCH — block word only
-    ("credit score improvement tips", "ALLOW", "no match: block word only"),
-    ("risk score for weather prediction", "ALLOW", "no match: block word only"),
-]
-
-
-@pytest.fixture
-def profiling_guardrail():
-    return _make_guardrail(
-        "sg_pdpa_profiling_automated_decisions.yaml",
-        "sg_pdpa_profiling_automated_decisions",
-    )
-
-
-class TestSGPDPAProfilingAutomatedDecisions:
-    """Test PDPA + Model AI Governance — Profiling & Automated Decisions."""
-
-    @pytest.mark.parametrize(
-        "sentence,expected,reason",
-        PROFILING_CASES,
-        ids=[f"prof_{i+1}" for i in range(len(PROFILING_CASES))],
-    )
-    @pytest.mark.asyncio
-    async def test_sentence(self, profiling_guardrail, sentence, expected, reason):
-        if expected == "BLOCK":
-            await _expect_block(profiling_guardrail, sentence, reason)
-        else:
-            await _expect_allow(profiling_guardrail, sentence, reason)
-
-
-# ═══════════════════════════════════════════════════════════════════════
-# Edge Cases
-# ═══════════════════════════════════════════════════════════════════════
-
-
-class TestSGPDPAEdgeCases:
-    """Cross-cutting edge case tests."""
-
-    @pytest.mark.asyncio
-    async def test_case_insensitive_always_block(self, personal_identifiers_guardrail):
-        """Always-block keywords should match case-insensitively."""
-        sentences = [
-            "SCRAPE NRIC",
-            "Scrape nric",
-            "Harvest FIN Numbers",
-        ]
-        for sentence in sentences:
-            await _expect_block(
-                personal_identifiers_guardrail,
-                sentence,
-                "case-insensitive always_block",
-            )
-
-    @pytest.mark.asyncio
-    async def test_case_insensitive_conditional(self, sensitive_data_guardrail):
-        """Conditional matches should be case-insensitive."""
-        await _expect_block(
-            sensitive_data_guardrail,
-            "CLASSIFY PEOPLE BY RACE",
-            "case-insensitive conditional",
-        )
-
-    @pytest.mark.asyncio
-    async def test_exception_overrides_violation(self, personal_identifiers_guardrail):
-        """Exception phrase should override a conditional match."""
-        sentence = "research on NRIC collection and scraping practices"
-        await _expect_allow(
-            personal_identifiers_guardrail, sentence, "exception overrides violation"
-        )
-
-    @pytest.mark.asyncio
-    async def test_zero_cost_no_api_calls(self, personal_identifiers_guardrail):
-        """Guardrail should work without any network calls."""
-        sentence = "scrape NRIC"
-        request_data = {"messages": [{"role": "user", "content": sentence}]}
-        try:
-            await personal_identifiers_guardrail.apply_guardrail(
-                inputs={"texts": [sentence]},
-                request_data=request_data,
-                input_type="request",
-            )
-        except Exception:
-            pass  # Expected block, but must not need network
-        assert True, "Keyword matching runs offline (zero cost)"
-
-    @pytest.mark.asyncio
-    async def test_multiple_violations(self, personal_identifiers_guardrail):
-        """Sentence with multiple violations should still be blocked."""
-        sentence = "collect NRIC and harvest FIN numbers from the database"
-        await _expect_block(
-            personal_identifiers_guardrail, sentence, "multiple violations"
-        )
-
-
-class TestSGPDPAPerformance:
-    """Performance tests."""
-
-    @pytest.mark.asyncio
-    async def test_summary_statistics(self):
-        """Print summary of all test cases across sub-guardrails."""
-        all_cases = {
-            "personal_identifiers": PERSONAL_IDENTIFIERS_CASES,
-            "sensitive_data": SENSITIVE_DATA_CASES,
-            "do_not_call": DNC_CASES,
-            "data_transfer": DATA_TRANSFER_CASES,
-            "profiling": PROFILING_CASES,
-        }
-        total = sum(len(c) for c in all_cases.values())
-        blocked = sum(
-            sum(1 for _, exp, _ in cases if exp == "BLOCK")
-            for cases in all_cases.values()
-        )
-        allowed = total - blocked
-
-        print(f"\n{'='*60}")
-        print("Singapore PDPA Guardrail Test Summary")
-        print(f"{'='*60}")
-        print(f"Total test cases : {total}")
-        print(f"Expected BLOCK   : {blocked} ({blocked/total*100:.1f}%)")
-        print(f"Expected ALLOW   : {allowed} ({allowed/total*100:.1f}%)")
-        print(f"{'='*60}")
-        for name, cases in all_cases.items():
-            b = sum(1 for _, e, _ in cases if e == "BLOCK")
-            a = len(cases) - b
-            print(f"  {name:35s}  BLOCK={b:2d}  ALLOW={a:2d}")
-        print(f"{'='*60}\n")
-
-
-if __name__ == "__main__":
-    pytest.main([__file__, "-v", "-s"])

tests/image_gen_tests/base_image_generation_test.py

@@ -1,17 +1,18 @@
 import asyncio
-import httpx
 import json
-import pytest
 from typing import Any, Dict, List, Optional
 from unittest.mock import MagicMock, Mock, patch
 
+import httpx
+import pytest
+from openai.types.image import Image
+
 import litellm
 from litellm.exceptions import BadRequestError
-from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
-from litellm.utils import CustomStreamWrapper
-from openai.types.image import Image
 from litellm.integrations.custom_logger import CustomLogger
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 from litellm.types.utils import StandardLoggingPayload
+from litellm.utils import CustomStreamWrapper
 
 
 class TestCustomLogger(CustomLogger):
@@ -92,28 +93,3 @@ class BaseImageGenTest(ABC):
                 pass  # Azure model deployment has been deprecated - skip
             else:
                 pytest.fail(f"An exception occurred - {str(e)}")
-
-
-@pytest.mark.skip(reason="Skipping image edit test, image file not in ci/cd")
-def test_openai_gpt_image_1():
-    from litellm import image_edit
-    from PIL import Image
-    import io
-
-    # Create a simple mask image with alpha channel
-    # Create a 512x512 black image with alpha channel
-    try:
-        response = image_edit(
-            model="openai/gpt-image-1",
-            image=open("test_image_edit.png", "rb"),
-            mask=open("test_image_edit.png", "rb"),
-            prompt="Add a red hat to the person in the image",
-            n=1,
-            size="1024x1024",
-        )
-        print("response: ", response)
-    except Exception as e:
-        if "mask image missing alpha channel" in str(e):
-            pass
-        else:
-            raise e

tests/image_gen_tests/test_image_edits.py

@@ -1,20 +1,20 @@
+import asyncio
+import base64
+import json
 import logging
 import os
 import traceback
-import asyncio
-from typing import Optional
-import pytest
-import base64
-from io import BytesIO
-from unittest.mock import patch, AsyncMock
-import json
 from abc import ABC, abstractmethod
+from io import BytesIO
+from typing import Optional
+from unittest.mock import AsyncMock, patch
 
+import pytest
 
 import litellm
-from litellm.utils import ImageResponse
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.utils import StandardLoggingPayload
+from litellm.utils import ImageResponse
 
 # Configure pytest marks to avoid warnings
 pytestmark = pytest.mark.asyncio
@@ -199,7 +199,7 @@ async def test_openai_image_edit_litellm_router():
 @pytest.mark.asyncio
 async def test_openai_image_edit_with_bytesio():
     """Test image editing using BytesIO objects instead of file readers"""
-    from litellm import image_edit, aimage_edit
+    from litellm import aimage_edit, image_edit
 
     litellm.turn_on_debug()
     try:
@@ -346,7 +346,7 @@ async def test_azure_image_edit_litellm_sdk():
 @pytest.mark.asyncio
 async def test_openai_image_edit_cost_tracking():
     """Test OpenAI image edit cost tracking with custom logger"""
-    from litellm import image_edit, aimage_edit
+    from litellm import aimage_edit, image_edit
 
     test_custom_logger = TestCustomLogger()
     litellm.logging_callback_manager._reset_all_callbacks()
@@ -437,7 +437,7 @@ async def test_openai_image_edit_cost_tracking():
 @pytest.mark.asyncio
 async def test_azure_image_edit_cost_tracking():
     """Test Azure image edit cost tracking with custom logger"""
-    from litellm import image_edit, aimage_edit
+    from litellm import aimage_edit, image_edit
 
     test_custom_logger = TestCustomLogger()
     litellm.logging_callback_manager._reset_all_callbacks()
@@ -529,36 +529,6 @@ async def test_azure_image_edit_cost_tracking():
         assert test_custom_logger.standard_logging_payload["response_cost"] > 0
 
 
-@pytest.mark.asyncio
-@pytest.mark.skip(reason="Recraft image edit API only tested locally")
-async def test_recraft_image_edit_api():
-    from litellm import aimage_edit
-    import requests
-
-    litellm.turn_on_debug()
-    try:
-        prompt = """
-        Create a studio ghibli style image that combines all the reference images. Make sure the person looks like a CTO.
-        """
-        result = await aimage_edit(
-            prompt=prompt,
-            model="recraft/recraftv3",
-            image=_make_test_images(),
-        )
-        print("result from image edit", result)
-
-        # Validate the response meets expected schema
-        ImageResponse.model_validate(result)
-
-        if isinstance(result, ImageResponse) and result.data:
-            image_url = result.data[0].url
-
-            # download the image
-            image_bytes = requests.get(image_url).content
-            with open("test_image_edit.png", "wb") as f:
-                f.write(image_bytes)
-    except litellm.ContentPolicyViolationError as e:
-        pass
 
 
 def test_recraft_image_edit_config():

tests/image_gen_tests/test_image_generation.py

@@ -6,22 +6,22 @@ import os
 import traceback
 from unittest.mock import AsyncMock, MagicMock, patch
 
-
-
 from dotenv import load_dotenv
 from openai.types.image import Image
+
 from litellm.caching import InMemoryCache
 
 logging.basicConfig(level=logging.DEBUG)
 load_dotenv()
 import asyncio
+import json
+import logging
+import tempfile
+
 import pytest
+from base_image_generation_test import BaseImageGenTest, TestCustomLogger
 
 import litellm
-import json
-import tempfile
-from base_image_generation_test import BaseImageGenTest, TestCustomLogger
-import logging
 from litellm._logging import verbose_logger
 
 verbose_logger.setLevel(logging.DEBUG)
@@ -149,10 +149,6 @@ class TestOpenAIGPTImage1(BaseImageGenTest):
         return {"model": "gpt-image-1"}
 
 
-@pytest.mark.skip(reason="Recraft image generation API only tested locally")
-class TestRecraftImageGeneration(BaseImageGenTest):
-    def get_base_image_generation_call_args(self) -> dict:
-        return {"model": "recraft/recraftv3"}
 
 
 class TestAimlImageGeneration(BaseImageGenTest):
@@ -253,10 +249,6 @@ class TestGoogleImageGen(BaseImageGenTest):
         return {"model": "gemini/gemini-3.1-flash-image"}
 
 
-@pytest.mark.skip(reason="Runwayml image generation API only tested locally")
-class TestRunwaymlImageGeneration(BaseImageGenTest):
-    def get_base_image_generation_call_args(self) -> dict:
-        return {"model": "runwayml/gen4_image"}
 
 
 ## AZURE AI DALL-E 3 is deprecated and new deployments cannot be made
@@ -275,26 +267,6 @@ class TestRunwaymlImageGeneration(BaseImageGenTest):
 #         }
 
 
-@pytest.mark.skip(reason="model EOL")
-@pytest.mark.asyncio
-async def test_aimage_generation_bedrock_with_optional_params():
-    try:
-        litellm.in_memory_llm_clients_cache = InMemoryCache()
-        response = await litellm.aimage_generation(
-            prompt="A cute baby sea otter",
-            model="bedrock/stability.stable-diffusion-xl-v1",
-            size="256x256",
-        )
-        print(f"response: {response}")
-    except litellm.RateLimitError as e:
-        pass
-    except litellm.ContentPolicyViolationError:
-        pass  # Azure randomly raises these errors skip when they occur
-    except Exception as e:
-        if "Your task failed as a result of our safety system." in str(e):
-            pass
-        else:
-            pytest.fail(f"An exception occurred - {str(e)}")
 
 
 @pytest.mark.asyncio
@@ -307,7 +279,8 @@ async def test_aiml_image_generation_with_dynamic_api_key():
     This test validates the fix for ensuring dynamic API keys are respected
     when making image generation requests to the AIML provider.
     """
-    from unittest.mock import AsyncMock, patch, MagicMock
+    from unittest.mock import AsyncMock, MagicMock, patch
+
     import httpx
 
     # Mock AIML response
@@ -374,8 +347,8 @@ async def test_aiml_openai_gpt_image_2_request_uses_openai_param_shape():
     being remapped to the AI/ML flux schema (``image_size``/``num_images``/
     ``output_format``), and hits the correct upstream model name.
     """
-    from unittest.mock import MagicMock, patch
     import json as _json
+    from unittest.mock import MagicMock, patch
 
     mock_aiml_response = {
         "created": 1703658209,

tests/integration/_support/mcp.py

@@ -22,7 +22,7 @@ from mcp.server.mcpserver import Context, MCPServer
 from mcp.server.transport_security import TransportSecuritySettings
 from mcp.types import SamplingMessage, TextContent
 from mcp_tests.mcp_e2e_upstream_server import add, multiply
-from pydantic import BaseModel
+from pydantic import BaseModel, JsonValue
 from sse_starlette.sse import AppStatus
 from starlette.requests import Request as StarletteRequest
 from starlette.responses import Response
@@ -622,3 +622,114 @@ def tool_calls(observed: tuple[dict[str, object], ...]) -> tuple[dict[str, objec
     return tuple(
         item for item in observed if isinstance(item.get("body"), dict) and item["body"].get("method") == "tools/call"
     )
+
+
+@contextmanager
+def paginated_mcp_peer(
+    *,
+    page_size: int = 1,
+    repeat_cursor: bool = False,
+    fail_listing: bool = False,
+    fail_continuation: bool = False,
+    metadata: dict[str, JsonValue] | None = None,
+) -> Iterator[McpPeer]:
+    from contextlib import asynccontextmanager
+
+    from mcp.server.lowlevel.server import Server
+    from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
+    from mcp.types import (
+        CallToolResult,
+        ListPromptsResult,
+        ListResourcesResult,
+        ListResourceTemplatesResult,
+        ListToolsResult,
+        Prompt,
+        Resource,
+        ResourceTemplate,
+        Tool,
+    )
+    from starlette.applications import Starlette
+    from starlette.routing import Mount
+
+    def window(params):
+        if fail_listing or (fail_continuation and params is not None and params.cursor):
+            from mcp import MCPError
+            from mcp.types import INTERNAL_ERROR
+
+            raise MCPError(code=INTERNAL_ERROR, message="untrusted upstream message")
+        start = int(params.cursor) if params is not None and params.cursor else 0
+        end = min(start + page_size, 3)
+        return range(start, end), "1" if repeat_cursor else str(end) if end < 3 else None
+
+    async def tools(context, params):
+        indexes, cursor = window(params)
+        return ListToolsResult(
+            tools=[
+                Tool(
+                    name=f"add{index}",
+                    input_schema={
+                        "type": "object",
+                        "properties": {"a": {"type": "integer"}, "b": {"type": "integer"}},
+                        "required": ["a", "b"],
+                    },
+                )
+                for index in indexes
+            ],
+            next_cursor=cursor,
+            meta={"revision": "stable", **(metadata or {})},
+        )
+
+    async def prompts(context, params):
+        indexes, cursor = window(params)
+        return ListPromptsResult(
+            prompts=[Prompt(name=f"prompt{index}") for index in indexes], next_cursor=cursor, meta=metadata
+        )
+
+    async def resources(context, params):
+        indexes, cursor = window(params)
+        return ListResourcesResult(
+            resources=[Resource(name=f"resource{index}", uri=f"status://item{index}") for index in indexes],
+            next_cursor=cursor,
+            meta=metadata,
+        )
+
+    async def templates(context, params):
+        indexes, cursor = window(params)
+        return ListResourceTemplatesResult(
+            resource_templates=[
+                ResourceTemplate(name=f"template{index}", uri_template=f"status{index}://{{item}}") for index in indexes
+            ],
+            next_cursor=cursor,
+            meta=metadata,
+        )
+
+    async def call(context, params):
+        assert params.name in ("add0", "add1", "add2")
+        return CallToolResult(
+            content=[TextContent(type="text", text=str(params.arguments["a"] + params.arguments["b"]))]
+        )
+
+    service = Server(
+        "paginated-catalog",
+        on_list_tools=tools,
+        on_list_prompts=prompts,
+        on_list_resources=resources,
+        on_list_resource_templates=templates,
+        on_call_tool=call,
+    )
+    manager = StreamableHTTPSessionManager(
+        service,
+        stateless=True,
+        json_response=True,
+        security_settings=TransportSecuritySettings(enable_dns_rebinding_protection=False),
+    )
+
+    @asynccontextmanager
+    async def lifespan(app):
+        async with manager.run():
+            yield
+
+    app = Starlette(routes=[Mount("/mcp", app=manager.handle_request)], lifespan=lifespan)
+    observed = queue.Queue()
+    with asgi_server(_capturing(app, observed)) as url:
+        yield McpPeer(url + "/mcp/", observed)

tests/integration/_support/openai_wire.py

@@ -7,8 +7,9 @@ from typing import Final
 from integration._support.wire import Reply, Request, Wire
 from pydantic import JsonValue
 
+from tests.integration._support.provider import MODEL_DISCOVERY
+
 _USAGE: Final = {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8}
-MODEL_DISCOVERY: Final = ("GET", "/v1/models")
 
 
 def answering_model_discovery(respond: Callable[[Request], Reply]) -> Callable[[Request], Reply]:

tests/integration/_support/provider.py

@@ -3,6 +3,7 @@
 Deployments in `proxy_config.yaml` point at `PROVIDER_URL`, so one server answers for all of them. A test
 queues the replies it expects with `expect` and reads what the proxy sent with `received`. Tests run one at a
 time against it; the `provider` fixture checks nothing is left over between tests.
+The proxy's model-info refresh is answered here.
 """
 
 from __future__ import annotations
@@ -17,6 +18,7 @@ from tests.integration._support.wire import Reply, Request, Wire, wire_server
 
 PROVIDER_PORT: Final = 8191
 PROVIDER_URL: Final = f"http://127.0.0.1:{PROVIDER_PORT}"
+MODEL_DISCOVERY: Final = ("GET", "/v1/models")
 _UNQUEUED: Final = Reply(status=500, body=b'{"error": "the shared fake provider has no reply queued for this request"}')
 
 
@@ -30,7 +32,9 @@ class SharedProvider:
         self.replies.extend(replies)
 
     def received(self) -> tuple[Request, ...]:
-        return self.wire.drain()
+        return tuple(
+            request for request in self.wire.drain() if (request.method, request.target) != MODEL_DISCOVERY
+        )
 
 
 @contextmanager
@@ -38,6 +42,8 @@ def shared_provider() -> Iterator[SharedProvider]:
     replies: Final[deque[Reply]] = deque()
 
     def respond(request: Request) -> Reply:
+        if (request.method, request.target) == MODEL_DISCOVERY:
+            return Reply(body=b'{"object":"list","data":[]}')
         return replies.popleft() if replies else _UNQUEUED
 
     with wire_server(respond, port=PROVIDER_PORT) as wire:

tests/integration/compatibility/test_codex_model_catalog.py

@@ -3,21 +3,33 @@ import json
 import os
 import time
 import uuid
-from collections.abc import Callable, Mapping, Sequence
+from collections.abc import Callable, Iterator, Mapping, Sequence
 from concurrent.futures import ThreadPoolExecutor
 from hashlib import sha256
 from itertools import chain
 from pathlib import Path
+from types import MappingProxyType
 from typing import Final, TypeVar
 
 import anthropic
 import httpx
 import openai
+import pytest
+import yaml
 from pydantic import JsonValue
 
 from litellm.constants import PROXY_CONFIG_RELOAD_INTERVAL_SECONDS
-from tests.integration._support.client import JSON_OBJECT, Gateway, Scenario, eventually, object_value, string_value
+from tests.integration._support.client import (
+    JSON_OBJECT,
+    Gateway,
+    Scenario,
+    eventually,
+    gateway_from_environment,
+    object_value,
+    string_value,
+)
 from tests.integration._support.database import read_rows
+from tests.integration._support.process import owned_proxy
 from tests.integration._support.wire import Reply, Request, Wire, wire_server
 
 T = TypeVar("T")
@@ -36,6 +48,25 @@ ANTHROPIC_HEADERS: Final = {"anthropic-version": "2023-06-01"}
 USAGE: Final = {"prompt_tokens": 11, "completion_tokens": 4, "total_tokens": 15}
 
 
+def _config_without_model_list(directory: Path) -> Path:
+    shared_config: Final = object_value(yaml.safe_load((ROOT / "tests/integration/proxy_config.yaml").read_text()))
+    config_without_models: Final[Mapping[str, JsonValue]] = MappingProxyType(
+        {name: value for name, value in shared_config.items() if name != "model_list"}
+    )
+    path: Final = directory / "proxy_config_without_model_list.yaml"
+    path.write_text(yaml.safe_dump({**config_without_models}))
+    return path
+
+
+@pytest.fixture(scope="module")
+def gateway(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]:
+    with gateway_from_environment() as parent_gateway:
+        directory: Final = tmp_path_factory.mktemp("codex_model_catalog")
+        config: Final = _config_without_model_list(directory)
+        with owned_proxy(parent_gateway, directory, {}, config=config, workers=PROXY_WORKERS) as isolated_gateway:
+            yield isolated_gateway
+
+
 def _generic_tier(identity: str) -> dict[str, JsonValue]:
     return {"id": identity, "name": identity.capitalize(), "description": f"Sends service_tier={identity} upstream"}
 

tests/integration/mcp/test_mcp_management.py

@@ -283,38 +283,40 @@ def test_access_group_membership_follows_edits(gateway: Gateway) -> None:
         assert tool_calls(peer.drain()) == ()
 
 
-def test_peer_worker_observes_create_edit_and_delete_without_restart(gateway: Gateway, peer: Gateway) -> None:
-    with mcp_peer() as first, mcp_peer() as second, gateway.scenario() as scenario:
+def test_peer_worker_observes_create_edit_and_delete_without_restart(gateway: Gateway, tmp_path: Path) -> None:
+    config: Final = tmp_path / "peer.yaml"
+    config.write_text(yaml.safe_dump({
+        "model_list": [],
+        "general_settings": {"master_key": gateway.key, "store_model_in_db": True, "proxy_config_reload_interval_seconds": 3600},
+    }))
+    with (
+        owned_proxy(gateway, tmp_path, {}, config=config, database_setup=()) as peer,
+        mcp_peer() as first,
+        mcp_peer() as second,
+        gateway.scenario() as scenario,
+    ):
         alias: Final = "mgmt" + uuid.uuid4().hex[:8]
         identity: Final = register_mcp(scenario, first, alias)
         key: Final = scenario.key(object_permission={"mcp_servers": [identity]})
-        eventually(
-            lambda: peer.client.get(
-                "/mcp-rest/tools/list", headers={"x-litellm-api-key": key}, params={"server_id": identity}
-            ),
-            lambda value: value.status_code == 200 and value.json() != [],
-            seconds=40,
+        listing: Final = peer.client.get(
+            "/mcp-rest/tools/list", headers={"x-litellm-api-key": key}, params={"server_id": identity}
         )
+        assert listing.status_code == 200 and listing.json() != [], listing.text
         names: Final = tool_names(peer, key, identity)
         assert call_tool(peer, key, identity, names["add"], ADD).status_code == 200
         assert len(tool_calls(first.drain())) == 1
         moved: Final = gateway.request("PUT", "/v1/mcp/server", {"server_id": identity, "url": second.url})
         assert moved.status_code == 202, moved.text
-        eventually(
-            lambda: call_tool(peer, key, identity, names["add"], ADD),
-            lambda value: value.status_code == 200 and len(tool_calls(second.drain())) == 1,
-            seconds=40,
-        )
+        called: Final = call_tool(peer, key, identity, names["add"], ADD)
+        assert called.status_code == 200, called.text
+        assert tool_calls(first.drain()) == ()
+        assert len(tool_calls(second.drain())) == 1
         delete_mcp(gateway, identity)
-        eventually(
-            lambda: peer.client.get(
-                "/mcp-rest/tools/list", headers={"x-litellm-api-key": key}, params={"server_id": identity}
-            ),
-            lambda value: value.status_code >= 400 or value.json() == [],
-            seconds=40,
+        deleted: Final = peer.client.get(
+            "/mcp-rest/tools/list", headers={"x-litellm-api-key": key}, params={"server_id": identity}
         )
-        second.drain()
-        assert call_tool(peer, key, identity, names["add"], ADD).status_code >= 400
+        assert deleted.status_code in (403, 404) or (deleted.status_code == 200 and deleted.json() == []), deleted.text
+        assert call_tool(peer, key, identity, names["add"], ADD).status_code in (403, 404)
         assert tool_calls(second.drain()) == ()
 
 

tests/integration/mcp/test_pagination.py

@@ -0,0 +1,563 @@
+import asyncio
+from contextlib import asynccontextmanager
+from pathlib import Path
+from typing import Literal
+
+import httpx
+import pytest
+import yaml
+from mcp import ClientSession, MCPError
+from mcp.client.streamable_http import streamable_http_client
+from mcp.types import CallToolRequest, CallToolRequestParams, CallToolResult, PaginatedRequestParams
+
+from integration._support.client import Gateway
+from integration._support.mcp import paginated_mcp_peer
+from integration._support.process import owned_proxy
+from litellm.experimental_mcp_client.client import MCPClient
+from litellm.types.mcp import MCPTransport
+
+
+@asynccontextmanager
+async def catalog_session(gateway):
+    async with httpx.AsyncClient(headers={"Authorization": "Bearer " + gateway.key}) as client:
+        async with streamable_http_client(
+            str(gateway.client.base_url).rstrip("/") + "/mcp/", http_client=client
+        ) as streams:
+            async with ClientSession(streams[0], streams[1]) as session:
+                await session.initialize()
+                yield session
+
+
+def config_file(directory: Path, upstream: str) -> Path:
+    config = directory / "proxy.yaml"
+    config.write_text(
+        yaml.safe_dump(
+            {
+                "model_list": [],
+                "mcp_servers": {"pages": {"url": upstream, "transport": "http"}},
+                "general_settings": {"master_key": "sk-pagination-test", "store_model_in_db": False},
+            }
+        )
+    )
+    return config
+
+
+REMOVE_DATABASE = ("DATABASE_URL", "DATABASE_URL_READ_REPLICA", "LITELLM_LICENSE", "LITELLM_LICENSE_PATH")
+
+
+def test_catalog_pages_are_portable_repeatable_and_complete(tmp_path: Path):
+    async def exercise(first_replica, second_replica):
+        for method, field in (
+            ("list_tools", "tools"),
+            ("list_prompts", "prompts"),
+            ("list_resources", "resources"),
+            ("list_resource_templates", "resource_templates"),
+        ):
+            async with catalog_session(first_replica) as first_session:
+                first = await getattr(first_session, method)()
+            assert first.next_cursor
+            async with catalog_session(second_replica) as second_session:
+                second = await getattr(second_session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                replay = await getattr(second_session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert getattr(second, field) == getattr(replay, field)
+                assert second.next_cursor
+                third = await getattr(second_session, method)(params=PaginatedRequestParams(cursor=second.next_cursor))
+            names = [item.name for page in (first, second, third) for item in getattr(page, field)]
+            assert len(names) == len(set(names)) == 3
+            assert third.next_cursor is None
+        async with catalog_session(second_replica) as session:
+            called = await session.call_tool("pages-add2", {"a": 3, "b": 4})
+            assert not called.is_error
+            assert called.content[0].text == "7"
+
+    with paginated_mcp_peer() as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        options = dict(config=config, database_setup=(), remove_environment=REMOVE_DATABASE)
+        environment = {
+            "STORE_MODEL_IN_DB": "False",
+            "DISABLE_SCHEMA_UPDATE": "true",
+            "LITELLM_SALT_KEY": "shared-pagination-test",
+        }
+        with (
+            owned_proxy(seed, tmp_path / "a", environment, **options) as a,
+            owned_proxy(seed, tmp_path / "b", environment, **options) as b,
+        ):
+            asyncio.run(exercise(a, b))
+
+
+@pytest.mark.parametrize("page_size", [1, 3])
+def test_no_salt_preserves_complete_lists_and_calls_but_rejects_continuations(tmp_path: Path, page_size: int):
+    async def exercise(gateway):
+        async with catalog_session(gateway) as session:
+            for method, field in (
+                ("list_tools", "tools"),
+                ("list_prompts", "prompts"),
+                ("list_resources", "resources"),
+                ("list_resource_templates", "resource_templates"),
+            ):
+                if page_size == 1:
+                    with pytest.raises(MCPError, match="LITELLM_SALT_KEY"):
+                        await getattr(session, method)()
+                else:
+                    result = await getattr(session, method)()
+                    assert len(getattr(result, field)) == 3
+                    assert result.next_cursor is None
+            called = await session.send_request(
+                CallToolRequest(params=CallToolRequestParams(name="pages-add2", arguments={"a": 3, "b": 4})),
+                CallToolResult,
+            )
+            assert not called.is_error
+            assert called.content[0].text == "7"
+            if page_size == 3:
+                bare = await session.send_request(
+                    CallToolRequest(params=CallToolRequestParams(name="add2", arguments={"a": 3, "b": 4})),
+                    CallToolResult,
+                )
+                assert not bare.is_error
+                assert bare.content[0].text == "7"
+
+    with paginated_mcp_peer(page_size=page_size) as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": ""}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway))
+
+
+@pytest.mark.parametrize("grant", ["direct", "access_group"])
+def test_continuations_reauthorize_and_reject_registry_changes(tmp_path: Path, monkeypatch, grant: str):
+    import os
+    import subprocess
+    import sys
+
+    from integration._support.database import scratch_database
+    from integration._support.mcp import register_mcp
+
+    assert os.environ.get("DATABASE_URL"), "This integration case requires disposable-database access"
+
+    async def exercise(a, b, peer, identity, owner, stranger, policy):
+        owner_a = Gateway(a.client, owner, peer.url)
+        owner_b = Gateway(b.client, owner, peer.url)
+        stranger_b = Gateway(b.client, stranger, peer.url)
+        first_pages = {}
+        for method in ("list_tools", "list_prompts", "list_resources", "list_resource_templates"):
+            async with catalog_session(owner_a) as session:
+                first_pages[method] = await getattr(session, method)()
+                assert first_pages[method].next_cursor
+            async with catalog_session(owner_b) as session:
+                continued = await getattr(session, method)(
+                    params=PaginatedRequestParams(cursor=first_pages[method].next_cursor)
+                )
+                assert continued.next_cursor
+            async with catalog_session(stranger_b) as session:
+                peer.drain()
+                with pytest.raises(MCPError, match="fresh listing"):
+                    await getattr(session, method)(
+                        params=PaginatedRequestParams(cursor=first_pages[method].next_cursor)
+                    )
+                assert not any(call["body"].get("method", "").endswith("/list") for call in peer.drain())
+
+        a.post(
+            "/key/update",
+            {
+                "key": owner,
+                **(
+                    {"access_group_ids": []}
+                    if grant == "access_group"
+                    else {"object_permission": {"mcp_servers": ["no-mcp-servers"]}}
+                ),
+            },
+        )
+        for method, first in first_pages.items():
+            async with catalog_session(owner_b) as session:
+                peer.drain()
+                with pytest.raises(MCPError, match="fresh listing"):
+                    await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert not any(call["body"].get("method", "").endswith("/list") for call in peer.drain())
+        a.post("/key/update", {"key": owner, **policy})
+        changed = a.request("PUT", "/v1/mcp/server", {"server_id": identity, "description": "new catalog generation"})
+        assert changed.status_code == 202, changed.text
+        for method, first in first_pages.items():
+            async with catalog_session(owner_b) as session:
+                peer.drain()
+                with pytest.raises(MCPError, match="fresh listing"):
+                    await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert not any(call["body"].get("method", "").endswith("/list") for call in peer.drain())
+                fresh = await getattr(session, method)()
+                assert fresh.next_cursor
+
+    with scratch_database() as database_url:
+        monkeypatch.setenv("DATABASE_URL", database_url)
+        subprocess.run(
+            [
+                sys.executable,
+                "-I",
+                "-m",
+                "prisma",
+                "db",
+                "push",
+                "--schema",
+                "litellm/proxy/schema.prisma",
+                "--skip-generate",
+            ],
+            check=True,
+            capture_output=True,
+            text=True,
+        )
+        with paginated_mcp_peer() as peer, httpx.Client() as client:
+            seed = Gateway(client, "sk-pagination-test", peer.url)
+            config = tmp_path / "database-proxy.yaml"
+            config.write_text(
+                yaml.safe_dump(
+                    {"model_list": [], "general_settings": {"master_key": seed.key, "store_model_in_db": True}}
+                )
+            )
+            environment = {
+                "DATABASE_URL": database_url,
+                "DISABLE_SCHEMA_UPDATE": "true",
+                "LITELLM_SALT_KEY": "shared-pagination-test",
+            }
+            options = dict(
+                config=config,
+                database_setup=(),
+                remove_environment=("DATABASE_URL_READ_REPLICA", "LITELLM_LICENSE", "LITELLM_LICENSE_PATH"),
+            )
+            with (
+                owned_proxy(seed, tmp_path / "a", environment, **options) as a,
+                owned_proxy(seed, tmp_path / "b", environment, **options) as b,
+                a.scenario() as scenario,
+            ):
+                identity = register_mcp(scenario, peer, "pages")
+                group = a.request(
+                    "POST",
+                    "/v1/access_group",
+                    {
+                        "access_group_name": "pagination-grant",
+                        "access_mcp_server_ids": [identity],
+                    },
+                )
+                assert group.status_code == 201, group.text
+                policy = (
+                    {"access_group_ids": [group.json()["access_group_id"]]}
+                    if grant == "access_group"
+                    else {"object_permission": {"mcp_servers": [identity]}}
+                )
+                owner = scenario.key(**policy)
+                stranger = scenario.key(object_permission={"mcp_servers": [identity]})
+                assert owner != stranger
+                asyncio.run(exercise(a, b, peer, identity, owner, stranger, policy))
+
+
+@pytest.mark.parametrize("changed", ["key", "snapshot"])
+def test_cursor_rejects_changed_replica_configuration_before_dispatch(tmp_path: Path, changed: str):
+    async def exercise(a, b, peer):
+        for method in ("list_tools", "list_prompts", "list_resources", "list_resource_templates"):
+            async with catalog_session(a) as session:
+                first = await getattr(session, method)()
+                assert first.next_cursor
+            async with catalog_session(b) as session:
+                peer.drain()
+                with pytest.raises(MCPError, match="fresh listing"):
+                    await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert not any(call["body"].get("method", "").endswith("/list") for call in peer.drain())
+                fresh = await getattr(session, method)()
+                assert fresh.next_cursor
+
+    with paginated_mcp_peer() as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        second_config = tmp_path / "second-proxy.yaml"
+        second_values = yaml.safe_load(config.read_text())
+        if changed == "snapshot":
+            second_values["mcp_servers"]["pages"]["description"] = "changed registry definition"
+        second_config.write_text(yaml.safe_dump(second_values))
+        environment = {
+            "STORE_MODEL_IN_DB": "False",
+            "DISABLE_SCHEMA_UPDATE": "true",
+            "LITELLM_SALT_KEY": "original-key",
+        }
+        second_environment = {**environment, "LITELLM_SALT_KEY": "rotated-key" if changed == "key" else "original-key"}
+        options = dict(database_setup=(), remove_environment=REMOVE_DATABASE)
+        with (
+            owned_proxy(seed, tmp_path / "a", environment, config=config, **options) as a,
+            owned_proxy(seed, tmp_path / "b", second_environment, config=second_config, **options) as b,
+        ):
+            asyncio.run(exercise(a, b, peer))
+
+
+def test_pages_preserve_supported_protocol_versions(tmp_path: Path):
+    from mcp.types import ListPromptsRequest, ListResourcesRequest, ListResourceTemplatesRequest, ListToolsRequest
+    from mcp_types.version import HANDSHAKE_PROTOCOL_VERSIONS
+
+    async def exercise(gateway):
+        for revision in HANDSHAKE_PROTOCOL_VERSIONS:
+            client = MCPClient(
+                server_url=str(gateway.client.base_url).rstrip("/") + "/mcp",
+                transport_type=MCPTransport.http,
+                protocol_version=revision,
+                extra_headers={"Authorization": "Bearer " + gateway.key},
+                timeout=15,
+            )
+            for request, field in (
+                (ListToolsRequest, "tools"),
+                (ListPromptsRequest, "prompts"),
+                (ListResourcesRequest, "resources"),
+                (ListResourceTemplatesRequest, "resource_templates"),
+            ):
+                first = await client.list_page(request())
+                assert first.next_cursor, revision
+                second = await client.list_page(request(params=PaginatedRequestParams(cursor=first.next_cursor)))
+                assert second.next_cursor, revision
+                third = await client.list_page(request(params=PaginatedRequestParams(cursor=second.next_cursor)))
+                assert third.next_cursor is None, revision
+                names = [item.name for page in (first, second, third) for item in getattr(page, field)]
+                assert len(names) == len(set(names)) == 3, revision
+
+    with paginated_mcp_peer() as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-key"}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway))
+
+
+def test_incomplete_discovery_never_establishes_a_bare_tool_route(tmp_path: Path):
+    from integration._support.mcp import tool_calls
+
+    async def exercise(gateway, peer):
+        async with catalog_session(gateway) as session:
+            first = await session.list_tools()
+            assert [tool.name for tool in first.tools] == ["pages-add0"]
+            assert first.next_cursor
+            with pytest.raises(MCPError, match="repeated"):
+                await session.list_tools(params=PaginatedRequestParams(cursor=first.next_cursor))
+            peer.drain()
+            result = await session.send_request(
+                CallToolRequest(params=CallToolRequestParams(name="add0", arguments={"a": 3, "b": 4})),
+                CallToolResult,
+            )
+            assert result.is_error
+            assert tool_calls(peer.drain()) == ()
+            prefixed = await session.send_request(
+                CallToolRequest(params=CallToolRequestParams(name="pages-add0", arguments={"a": 3, "b": 4})),
+                CallToolResult,
+            )
+            assert not prefixed.is_error
+            assert prefixed.content[0].text == "7"
+            assert len(tool_calls(peer.drain())) == 1
+
+    with paginated_mcp_peer(repeat_cursor=True) as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-key"}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway, peer))
+
+
+def test_partial_catalog_keeps_sanitized_failure_metadata_on_following_pages(tmp_path: Path):
+    async def exercise(gateway):
+        for method, field in (
+            ("list_tools", "tools"),
+            ("list_prompts", "prompts"),
+            ("list_resources", "resources"),
+            ("list_resource_templates", "resource_templates"),
+        ):
+            async with catalog_session(gateway) as session:
+                first = await getattr(session, method)()
+                assert first.next_cursor
+                assert len(getattr(first, field)) == 1
+                fault = first.meta["litellm.ai/server_outcomes"]["broken"]
+                assert fault["status"] != "ok"
+                assert "tag" not in fault
+                assert "untrusted upstream message" not in first.model_dump_json()
+                second = await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert len(getattr(second, field)) == 1
+                assert second.meta["litellm.ai/server_outcomes"]["broken"] == fault
+
+    with paginated_mcp_peer() as healthy, paginated_mcp_peer(fail_listing=True) as broken, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", healthy.url)
+        config = config_file(tmp_path, healthy.url)
+        values = yaml.safe_load(config.read_text())
+        values["mcp_servers"]["broken"] = {"url": broken.url, "transport": "http"}
+        config.write_text(yaml.safe_dump(values))
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-key"}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway))
+
+
+def test_failed_upstream_continuation_requires_restart_for_every_catalog(tmp_path: Path):
+    async def exercise(gateway):
+        async with catalog_session(gateway) as session:
+            for method in ("list_tools", "list_prompts", "list_resources", "list_resource_templates"):
+                first = await getattr(session, method)()
+                assert first.next_cursor
+                with pytest.raises(MCPError, match="fresh listing") as caught:
+                    await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert "untrusted upstream message" not in str(caught.value)
+
+    with paginated_mcp_peer(fail_continuation=True) as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-key"}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway))
+
+
+@pytest.mark.parametrize("foreign", [{"foreign": {"status": "error", "message": "foreign outcome"}}, "malformed"])
+def test_optional_catalog_ignores_upstream_gateway_outcomes(tmp_path: Path, foreign):
+    from litellm.proxy._experimental.mcp_server.faults.list_outcomes import SERVER_OUTCOMES_META_KEY
+
+    async def exercise(gateway):
+        async with catalog_session(gateway) as session:
+            for method, field in (
+                ("list_prompts", "prompts"),
+                ("list_resources", "resources"),
+                ("list_resource_templates", "resource_templates"),
+            ):
+                first = await getattr(session, method)()
+                assert len(getattr(first, field)) == 1
+                assert first.next_cursor
+                second = await getattr(session, method)(params=PaginatedRequestParams(cursor=first.next_cursor))
+                assert len(getattr(second, field)) == 1
+                assert "foreign" not in (second.meta or {}).get(SERVER_OUTCOMES_META_KEY, {})
+
+    with paginated_mcp_peer(metadata={SERVER_OUTCOMES_META_KEY: foreign}) as peer, httpx.Client() as client:
+        seed = Gateway(client, "sk-pagination-test", peer.url)
+        config = config_file(tmp_path, peer.url)
+        environment = {"STORE_MODEL_IN_DB": "False", "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-key"}
+        with owned_proxy(
+            seed, tmp_path / "proxy", environment, config=config, database_setup=(), remove_environment=REMOVE_DATABASE
+        ) as gateway:
+            asyncio.run(exercise(gateway))
+
+
+def test_complete_initial_page_keeps_bare_routes_with_a_cached_database_revision(tmp_path: Path, monkeypatch):
+    import os
+    import subprocess
+    import sys
+
+    from integration._support.database import read_rows, scratch_database, write_rows
+    from integration._support.mcp import register_mcp, tool_calls
+
+    assert os.environ.get("DATABASE_URL"), "This integration case requires disposable-database access"
+
+    async def exercise(gateway, first, second):
+        async with catalog_session(gateway) as session:
+            listing = await session.list_tools()
+            assert len(listing.tools) == 3 and listing.next_cursor is None
+            first.drain()
+            second.drain()
+            called = await session.send_request(
+                CallToolRequest(params=CallToolRequestParams(name="add2", arguments={"a": 3, "b": 4})),
+                CallToolResult,
+            )
+            assert not called.is_error
+            assert called.content[0].text == "7"
+            assert tool_calls(first.drain()) == ()
+            assert len(tool_calls(second.drain())) == 1
+
+    with scratch_database() as database_url:
+        monkeypatch.setenv("DATABASE_URL", database_url)
+        subprocess.run(
+            [sys.executable, "-I", "-m", "prisma", "db", "push", "--schema",
+             "litellm/proxy/schema.prisma", "--skip-generate"],
+            check=True, capture_output=True, text=True,
+        )
+        subprocess.run(
+            [sys.executable, "-I", "-m", "prisma", "db", "execute", "--schema",
+             "litellm/proxy/schema.prisma", "--file",
+             "litellm-proxy-extras/litellm_proxy_extras/migrations/20260923000000_add_mcp_catalog_revision_trigger/migration.sql"],
+            check=True, capture_output=True, text=True,
+        )
+        with paginated_mcp_peer(page_size=3) as first, paginated_mcp_peer(page_size=3) as second, httpx.Client() as client:
+            seed = Gateway(client, "sk-pagination-test", first.url)
+            config = tmp_path / "database-proxy.yaml"
+            config.write_text(yaml.safe_dump({
+                "model_list": [], "general_settings": {"master_key": seed.key, "store_model_in_db": True},
+            }))
+            environment = {"DATABASE_URL": database_url, "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-pagination-test"}
+            with owned_proxy(
+                seed, tmp_path / "proxy", environment, config=config, database_setup=(),
+                remove_environment=("DATABASE_URL_READ_REPLICA", "LITELLM_LICENSE", "LITELLM_LICENSE_PATH"),
+            ) as gateway, gateway.scenario() as scenario:
+                first_id = register_mcp(scenario, first, "first")
+                second_id = register_mcp(scenario, second, "second")
+                owner = scenario.key(object_permission={"mcp_servers": [second_id]})
+                warm = gateway.client.get("/mcp-rest/tools/list", headers={"Authorization": "Bearer " + gateway.key}, params={"server_id": first_id})
+                assert warm.status_code == 200, warm.text
+                # A no-op SQL writer bumps the trigger revision without changing either server.
+                write_rows('UPDATE "LiteLLM_MCPServerTable" SET "alias" = "alias" WHERE "server_id" = %s', (first_id,))
+                warm = gateway.client.get("/mcp-rest/tools/list", headers={"Authorization": "Bearer " + gateway.key}, params={"server_id": first_id})
+                assert warm.status_code == 200, warm.text
+                query = 'SELECT "reload_revision" FROM "LiteLLM_Config" WHERE "param_name" = %s'
+                revision = read_rows(query, ("mcp_catalog",))
+                assert revision and revision[0]["reload_revision"] > 0
+                asyncio.run(exercise(Gateway(gateway.client, owner, second.url), first, second))
+                assert read_rows(query, ("mcp_catalog",)) == revision
+
+
+@pytest.mark.parametrize("entry", ["mcp", "server_mcp"])
+def test_missing_user_keeps_explicit_key_and_team_grants(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch, entry: Literal["mcp", "server_mcp"]
+):
+    import subprocess
+    import sys
+    import uuid
+
+    from integration._support.database import read_rows, scratch_database
+    from integration._support.mcp import McpCaller, register_mcp, tool_calls
+
+    with scratch_database() as database_url:
+        monkeypatch.setenv("DATABASE_URL", database_url)
+        subprocess.run(
+            [sys.executable, "-I", "-m", "prisma", "db", "push", "--schema",
+             "litellm/proxy/schema.prisma", "--skip-generate"],
+            check=True, capture_output=True, text=True,
+        )
+        with paginated_mcp_peer(page_size=3) as allowed, paginated_mcp_peer(page_size=3) as private, httpx.Client() as client:
+            seed = Gateway(client, "sk-pagination-test", allowed.url)
+            config = tmp_path / "database-proxy.yaml"
+            config.write_text(yaml.safe_dump({
+                "model_list": [], "general_settings": {"master_key": seed.key, "store_model_in_db": True},
+            }))
+            environment = {"DATABASE_URL": database_url, "DISABLE_SCHEMA_UPDATE": "true", "LITELLM_SALT_KEY": "shared-pagination-test"}
+            options = dict(config=config, database_setup=(), remove_environment=("DATABASE_URL_READ_REPLICA", "LITELLM_LICENSE", "LITELLM_LICENSE_PATH"))
+            with (
+                owned_proxy(seed, tmp_path / "a", environment, **options) as a,
+                owned_proxy(seed, tmp_path / "b", environment, **options) as b,
+                a.scenario() as scenario,
+            ):
+                identity = register_mcp(scenario, allowed, "allowed")
+                register_mcp(scenario, private, "private")
+                team = scenario.team(object_permission={"mcp_servers": [identity]})
+                for policy in ({"object_permission": {"mcp_servers": [identity]}}, {"team_id": team}):
+                    user = "missing-" + uuid.uuid4().hex
+                    key = scenario.key(user_id=user, **policy)
+                    assert read_rows('SELECT user_id FROM "LiteLLM_UserTable" WHERE user_id = %s', (user,)) == []
+                    for replica in (a, b):
+                        caller = McpCaller(replica, key, entry, alias="allowed")
+                        allowed.drain()
+                        private.drain()
+                        listing = caller.list_tools()
+                        assert listing.ok, listing
+                        assert len(listing.tools) == 3, listing
+                        name = next(name for name in listing.tools if name.endswith("add2"))
+                        called = caller.call(name, {"a": 3, "b": 4})
+                        assert called.ok and called.text == "7", called
+                        assert len(tool_calls(allowed.drain())) == 1
+                        assert private.drain() == ()
+                        forbidden = caller.call("private-add2", {"a": 3, "b": 4})
+                        assert not forbidden.ok, forbidden
+                        assert tool_calls(allowed.drain()) == ()
+                        assert private.drain() == ()

tests/integration/routing/test_payment_required_cooldown.py

@@ -0,0 +1,564 @@
+from __future__ import annotations
+
+import json
+import re
+import signal
+import uuid
+from collections.abc import Callable, Iterator, Mapping, Sequence
+from concurrent.futures import ThreadPoolExecutor
+from contextlib import ExitStack
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Final
+
+import anthropic
+import httpx
+import openai
+import psutil
+import pytest
+import yaml
+from integration._support.client import GATEWAY_LIMITS, Gateway, Scenario, eventually, gateway_from_environment
+from integration._support.openai_wire import chat_reply, responses_reply
+from integration._support.process import graceful_stop_seconds, owned_proxy_process
+from integration._support.prometheus_series import PROXY_FAILURES, Sample, scrape
+from integration._support.redis_process import OwnedRedis, owned_redis
+from integration._support.wire import Reply, Request, Wire, wire_server
+from integration.routing.test_payment_required_mapping import (
+    OPENAI_MODEL,
+    PAYMENT_REQUIRED,
+    anthropic_client,
+    anthropic_error,
+    anthropic_params,
+    assert_payment_required_row,
+    chat_body,
+    deployment,
+    is_model_info_probe,
+    model_list_reply,
+    new_group,
+    new_marker,
+    openai_client,
+    openai_params,
+    openai_refusal,
+    post,
+    provider_calls,
+)
+from pydantic import JsonValue
+from redis import Redis
+
+pytestmark: Final = pytest.mark.timeout(300)
+
+COOLDOWN_SECONDS: Final = 300
+RELOAD_SECONDS: Final = 2
+NO_DEPLOYMENTS: Final = "No deployments available"
+COOLED_DOWN: Final = "litellm_deployment_cooled_down_total"
+PRIMARY_GROUP: Final = new_group()
+FALLBACK_GROUP: Final = new_group()
+MARKER: Final = re.compile(rb"pr402-[0-9a-f]{32}(?:-\d+)?")
+WORKER_PID: Final = re.compile(r"Started server process \[(\d+)\]")
+
+
+@dataclass(frozen=True, slots=True)
+class Outcome:
+    marker: str
+    status: int
+    detail: str
+    call_id: str
+
+
+@dataclass(frozen=True, slots=True)
+class Call:
+    marker: str
+    path: str
+    body: Mapping[str, JsonValue]
+
+
+@dataclass(frozen=True, slots=True)
+class CooldownRig:
+    gateway: Gateway
+    cache: OwnedRedis
+    log: Path
+
+    def cooled(self, deployment_id: str) -> bool:
+        return cooled(self.cache, deployment_id)
+
+
+def cooled(cache: OwnedRedis, deployment_id: str) -> bool:
+    with Redis(host=cache.host, port=cache.port) as client:
+        return int(client.exists(f"deployment:{deployment_id}:cooldown")) == 1
+
+
+def marker_in(request: Request) -> str:
+    found: Final = MARKER.search(request.body)
+    assert found is not None, (request.method, request.target, request.headers, request.body[:300])
+    return found.group(0).decode()
+
+
+def markers_received(wire: Wire) -> tuple[str, ...]:
+    return tuple(marker_in(request) for request in provider_calls(wire))
+
+
+def refusing_reply(request: Request) -> Reply:
+    return anthropic_error(402, f"scripted 402 {marker_in(request)}")
+
+
+def healthy_reply(request: Request) -> Reply:
+    if is_model_info_probe(request):
+        return model_list_reply()
+    marker: Final = marker_in(request)
+    body: Final = json.loads(request.body)
+    stream: Final = isinstance(body, dict) and body.get("stream") is True
+    if request.target.endswith("/responses"):
+        return responses_reply(f"resp_{marker}", OPENAI_MODEL, f"served {marker}", stream=stream)
+    return chat_reply(f"chatcmpl-{marker}", OPENAI_MODEL, f"served {marker}", stream=stream)
+
+
+def router_settings(cache: OwnedRedis, **extra: JsonValue) -> dict[str, JsonValue]:
+    return {
+        "num_retries": 0,
+        "cooldown_time": COOLDOWN_SECONDS,
+        "redis_host": cache.host,
+        "redis_port": cache.port,
+        **extra,
+    }
+
+
+def cooldown_config(
+    directory: Path,
+    settings: Mapping[str, JsonValue],
+    *,
+    model_list: Sequence[Mapping[str, JsonValue]] = (),
+    prometheus: bool = True,
+) -> Path:
+    base: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text())
+    assert isinstance(base, dict)
+    litellm_settings: Final = (
+        {**base["litellm_settings"], "callbacks": ["prometheus"]} if prometheus else base["litellm_settings"]
+    )
+    config: Final = {
+        **base,
+        "litellm_settings": litellm_settings,
+        "router_settings": dict(settings),
+        **({"model_list": [dict(entry) for entry in model_list]} if model_list else {}),
+    }
+    path: Final = directory / f"cooldown-{uuid.uuid4().hex[:8]}.yaml"
+    path.write_text(yaml.safe_dump(config))
+    return path
+
+
+@pytest.fixture(scope="module")
+def rig(tmp_path_factory: pytest.TempPathFactory) -> Iterator[CooldownRig]:
+    directory: Final = tmp_path_factory.mktemp("payment-required-cooldown")
+    with ExitStack() as stack:
+        upstream: Final = stack.enter_context(gateway_from_environment())
+        cache: Final = stack.enter_context(owned_redis(directory))
+        settings: Final = router_settings(cache, fallbacks=[{PRIMARY_GROUP: [FALLBACK_GROUP]}])
+        owned: Final = stack.enter_context(
+            owned_proxy_process(
+                upstream,
+                directory,
+                {"PROXY_CONFIG_RELOAD_INTERVAL_SECONDS": str(RELOAD_SECONDS)},
+                config=cooldown_config(directory, settings),
+                remove_environment=("PROMETHEUS_MULTIPROC_DIR",),
+            )
+        )
+        yield CooldownRig(owned.gateway, cache, owned.log)
+
+
+def two_deployments(scenario: Scenario, group: str, refusing: Wire, healthy: Wire) -> str:
+    refused_id: Final = deployment(scenario, group, anthropic_params(refusing))
+    deployment(scenario, group, openai_params(healthy))
+    return refused_id
+
+
+def raw_chat(gateway: Gateway, group: str, marker: str, **extra: JsonValue) -> Outcome:
+    response: Final = post(gateway, "/v1/chat/completions", chat_body(group, marker, **extra))
+    return Outcome(marker, response.status_code, response.text, response.headers["x-litellm-call-id"])
+
+
+def raw_call(gateway: Gateway, call: Call) -> Outcome:
+    response: Final = post(gateway, call.path, call.body)
+    return Outcome(call.marker, response.status_code, response.text, response.headers["x-litellm-call-id"])
+
+
+def openai_chat(client: openai.OpenAI, group: str, marker: str) -> Outcome:
+    try:
+        raw: Final = client.chat.completions.with_raw_response.create(
+            model=group, messages=[{"role": "user", "content": marker}]
+        )
+    except openai.APIStatusError as error:
+        return Outcome(marker, error.status_code, error.message, error.response.headers["x-litellm-call-id"])
+    return Outcome(marker, raw.status_code, raw.parse().id, raw.headers["x-litellm-call-id"])
+
+
+def anthropic_message(client: anthropic.Anthropic, group: str, marker: str) -> Outcome:
+    try:
+        raw: Final = client.messages.with_raw_response.create(
+            model=group, max_tokens=32, messages=[{"role": "user", "content": marker}]
+        )
+    except anthropic.APIStatusError as error:
+        return Outcome(marker, error.status_code, error.message, error.response.headers["x-litellm-call-id"])
+    block: Final = raw.parse().content[0]
+    assert isinstance(block, anthropic.types.TextBlock), block
+    return Outcome(marker, raw.status_code, block.text, raw.headers["x-litellm-call-id"])
+
+
+def until_refused(attempt: Callable[[str], Outcome], tries: int = 40) -> tuple[Outcome, ...]:
+    def walk() -> Iterator[Outcome]:
+        for _ in range(tries):
+            outcome: Final = attempt(new_marker())
+            yield outcome
+            if outcome.status != 200:
+                return
+
+    history: Final = tuple(walk())
+    assert history[-1].status != 200, "the refusing deployment was never picked"
+    return history
+
+
+def assert_refused(outcome: Outcome) -> None:
+    assert outcome.status == 402, (outcome.status, outcome.detail)
+    assert PAYMENT_REQUIRED in outcome.detail, outcome.detail
+
+
+def assert_served(outcomes: Sequence[Outcome], identity: Callable[[str], str]) -> None:
+    assert all(outcome.status == 200 for outcome in outcomes), [(o.status, o.detail[:200]) for o in outcomes]
+    assert all(identity(outcome.marker) in outcome.detail for outcome in outcomes), [o.detail[:200] for o in outcomes]
+
+
+def chat_identity(marker: str) -> str:
+    return f"chatcmpl-{marker}"
+
+
+def served_text(marker: str) -> str:
+    return f"served {marker}"
+
+
+def response_identity(marker: str) -> str:
+    return f"resp_{marker}"
+
+
+def markers(outcomes: Sequence[Outcome]) -> tuple[str, ...]:
+    return tuple(outcome.marker for outcome in outcomes)
+
+
+def failure_samples(gateway: Gateway, group: str) -> tuple[Sample, ...]:
+    return tuple(
+        sample
+        for sample in scrape(gateway)
+        if sample.name == PROXY_FAILURES and sample.labels.get("requested_model") == group
+    )
+
+
+def cooled_down_samples(gateway: Gateway, deployment_id: str) -> tuple[Sample, ...]:
+    return tuple(
+        sample
+        for sample in scrape(gateway)
+        if sample.name == COOLED_DOWN and sample.labels.get("model_id") == deployment_id
+    )
+
+
+def assert_payment_required_metrics(gateway: Gateway, group: str, deployment_id: str) -> None:
+    failures: Final = eventually(lambda: failure_samples(gateway, group), lambda found: len(found) >= 1, seconds=10)
+    assert [(sample.labels["exception_class"], sample.labels["exception_status"]) for sample in failures] == [
+        ("Anthropic.PaymentRequiredError", "402")
+    ], failures
+    cooldowns: Final = eventually(
+        lambda: cooled_down_samples(gateway, deployment_id), lambda found: len(found) >= 1, seconds=10
+    )
+    assert [sample.labels["exception_status"] for sample in cooldowns] == ["402"], cooldowns
+
+
+def test_chat_openai_sdk_402_cools_the_deployment_and_the_healthy_one_serves_after(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with (
+        wire_server(refusing_reply) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        refused_id: Final = two_deployments(scenario, group, refusing, healthy)
+        client: Final = openai_client(rig.gateway)
+        history: Final = until_refused(lambda marker: openai_chat(client, group, marker))
+        assert_refused(history[-1])
+        assert_served(history[:-1], chat_identity)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        assert markers_received(refusing) == (history[-1].marker,)
+        assert markers_received(healthy) == markers(history[:-1])
+        served: Final = tuple(openai_chat(client, group, new_marker()) for _ in range(20))
+        assert_served(served, chat_identity)
+        assert markers_received(healthy) == markers(served)
+        assert markers_received(refusing) == ()
+        assert_payment_required_row(history[-1].call_id, refused_id)
+        assert_payment_required_metrics(rig.gateway, group, refused_id)
+
+
+def test_messages_anthropic_sdk_402_cools_the_deployment_and_the_healthy_one_serves_after(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with (
+        wire_server(refusing_reply) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        refused_id: Final = two_deployments(scenario, group, refusing, healthy)
+        client: Final = anthropic_client(rig.gateway)
+        history: Final = until_refused(lambda marker: anthropic_message(client, group, marker))
+        assert_refused(history[-1])
+        assert_served(history[:-1], served_text)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        assert markers_received(refusing) == (history[-1].marker,)
+        assert markers_received(healthy) == markers(history[:-1])
+        served: Final = tuple(anthropic_message(client, group, new_marker()) for _ in range(20))
+        assert_served(served, served_text)
+        assert markers_received(healthy) == markers(served)
+        assert markers_received(refusing) == ()
+        assert_payment_required_row(history[-1].call_id, refused_id)
+
+
+@pytest.mark.parametrize("stream", (False, True), ids=("json", "stream"))
+def test_responses_httpx_402_cools_the_deployment_and_the_healthy_one_serves_after(
+    rig: CooldownRig, stream: bool
+) -> None:
+    group: Final = new_group()
+    with (
+        wire_server(refusing_reply) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        refused_id: Final = two_deployments(scenario, group, refusing, healthy)
+
+        def attempt(marker: str) -> Outcome:
+            return raw_call(
+                rig.gateway, Call(marker, "/v1/responses", {"model": group, "input": marker, "stream": stream})
+            )
+
+        history: Final = until_refused(attempt)
+        assert_refused(history[-1])
+        assert_served(history[:-1], response_identity)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        assert markers_received(refusing) == (history[-1].marker,)
+        assert markers_received(healthy) == markers(history[:-1])
+        served: Final = tuple(attempt(new_marker()) for _ in range(20))
+        assert_served(served, response_identity)
+        assert markers_received(healthy) == markers(served)
+        assert markers_received(refusing) == ()
+        assert_payment_required_row(history[-1].call_id, refused_id)
+
+
+@pytest.mark.parametrize(
+    "model_info",
+    ({}, {"allowed_fails_policy": None}, {"allowed_fails_policy": {}}),
+    ids=("missing", "null", "empty"),
+)
+def test_a_lone_402_deployment_without_a_policy_is_never_cooled(
+    rig: CooldownRig, model_info: dict[str, JsonValue]
+) -> None:
+    group: Final = new_group()
+    with wire_server(refusing_reply) as refusing, rig.gateway.scenario() as scenario:
+        refused_id: Final = deployment(scenario, group, anthropic_params(refusing), model_info=model_info)
+        refused: Final = tuple(raw_chat(rig.gateway, group, new_marker()) for _ in range(5))
+        for outcome in refused:
+            assert_refused(outcome)
+            assert_payment_required_row(outcome.call_id, refused_id)
+        assert not rig.cooled(refused_id)
+        sixth: Final = raw_chat(rig.gateway, group, new_marker())
+        assert_refused(sixth)
+        assert markers_received(refusing) == (*markers(refused), sixth.marker)
+
+
+@pytest.mark.timeout(900)
+def test_a_router_allowed_fails_policy_cools_a_lone_402_deployment_past_its_count(tmp_path: Path) -> None:
+    group: Final = new_group()
+    with ExitStack() as stack:
+        upstream: Final = stack.enter_context(gateway_from_environment())
+        cache: Final = stack.enter_context(owned_redis(tmp_path))
+        settings: Final = router_settings(cache, allowed_fails_policy={"BadRequestErrorAllowedFails": 1})
+        owned: Final = stack.enter_context(
+            owned_proxy_process(
+                upstream,
+                tmp_path,
+                {},
+                config=cooldown_config(tmp_path, settings),
+                remove_environment=("PROMETHEUS_MULTIPROC_DIR",),
+            )
+        )
+        refusing: Final = stack.enter_context(wire_server(refusing_reply))
+        scenario: Final = stack.enter_context(owned.gateway.scenario())
+        refused_id: Final = deployment(scenario, group, anthropic_params(refusing))
+        first: Final = raw_chat(owned.gateway, group, new_marker())
+        second: Final = raw_chat(owned.gateway, group, new_marker())
+        assert_refused(first)
+        assert_refused(second)
+        eventually(lambda: cooled(cache, refused_id), lambda seen: seen, seconds=10)
+        third: Final = raw_chat(owned.gateway, group, new_marker())
+        assert third.status == 429 and NO_DEPLOYMENTS in third.detail, (third.status, third.detail)
+        assert markers_received(refusing) == (first.marker, second.marker)
+
+
+def test_a_deployment_allowed_fails_policy_cools_a_lone_402_deployment(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    policy: Final = {"allowed_fails_policy": {"BadRequestErrorAllowedFails": 0}}
+    with wire_server(refusing_reply) as refusing, rig.gateway.scenario() as scenario:
+        refused_id: Final = deployment(scenario, group, anthropic_params(refusing), model_info=policy)
+        first: Final = raw_chat(rig.gateway, group, new_marker())
+        assert_refused(first)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        second: Final = raw_chat(rig.gateway, group, new_marker())
+        assert second.status == 429 and NO_DEPLOYMENTS in second.detail, (second.status, second.detail)
+        assert markers_received(refusing) == (first.marker,)
+
+
+def test_a_plain_allowed_fails_count_leaves_a_lone_402_deployment_warm(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with wire_server(refusing_reply) as refusing, rig.gateway.scenario() as scenario:
+        refused_id: Final = deployment(scenario, group, anthropic_params(refusing), model_info={"allowed_fails": 0})
+        refused: Final = tuple(raw_chat(rig.gateway, group, new_marker()) for _ in range(5))
+        for outcome in refused:
+            assert_refused(outcome)
+        assert not rig.cooled(refused_id)
+        sixth: Final = raw_chat(rig.gateway, group, new_marker())
+        assert_refused(sixth)
+        assert markers_received(refusing) == (*markers(refused), sixth.marker)
+
+
+def test_an_openai_compatible_402_cools_the_deployment_too(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with (
+        wire_server(openai_refusal) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        refused_id: Final = deployment(scenario, group, openai_params(refusing))
+        deployment(scenario, group, openai_params(healthy))
+        history: Final = until_refused(lambda marker: raw_chat(rig.gateway, group, marker))
+        assert history[-1].status == 402 and "scripted 402" in history[-1].detail, history[-1]
+        assert_served(history[:-1], chat_identity)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        assert markers_received(refusing) == (history[-1].marker,)
+        served: Final = tuple(raw_chat(rig.gateway, group, new_marker()) for _ in range(20))
+        assert_served(served, chat_identity)
+        assert markers_received(refusing) == ()
+        assert markers_received(healthy) == (*markers(history[:-1]), *markers(served))
+
+
+def test_a_lone_402_primary_with_a_fallback_group_stays_warm_and_the_fallback_answers(rig: CooldownRig) -> None:
+    with (
+        wire_server(refusing_reply) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        primary_id: Final = deployment(scenario, PRIMARY_GROUP, anthropic_params(refusing))
+        deployment(scenario, FALLBACK_GROUP, openai_params(healthy))
+        served: Final = tuple(raw_chat(rig.gateway, PRIMARY_GROUP, new_marker()) for _ in range(3))
+        assert_served(served, chat_identity)
+        assert markers_received(refusing) == markers(served)
+        assert markers_received(healthy) == markers(served)
+        assert not rig.cooled(primary_id)
+
+
+def test_a_deployment_policy_added_while_402_traffic_flows_starts_the_cooldown(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with wire_server(refusing_reply) as refusing, rig.gateway.scenario() as scenario:
+        refused_id: Final = deployment(scenario, group, anthropic_params(refusing))
+        before: Final = tuple(raw_chat(rig.gateway, group, new_marker()) for _ in range(3))
+        for outcome in before:
+            assert_refused(outcome)
+        assert not rig.cooled(refused_id)
+        policy: Final = {"id": refused_id, "allowed_fails_policy": {"BadRequestErrorAllowedFails": 0}}
+        patched: Final = rig.gateway.request("PATCH", f"/model/{refused_id}/update", {"model_info": policy})
+        assert patched.status_code == 200, patched.text
+
+        def probe() -> tuple[int, bool]:
+            return raw_chat(rig.gateway, group, new_marker()).status, rig.cooled(refused_id)
+
+        eventually(probe, lambda seen: seen[1], seconds=RELOAD_SECONDS * 10)
+        after: Final = raw_chat(rig.gateway, group, new_marker())
+        assert after.status == 429 and NO_DEPLOYMENTS in after.detail, (after.status, after.detail)
+        assert len(markers_received(refusing)) >= 4
+
+
+def test_a_cooled_402_deployment_comes_back_after_its_own_cooldown_time(rig: CooldownRig) -> None:
+    group: Final = new_group()
+    with (
+        wire_server(refusing_reply) as refusing,
+        wire_server(healthy_reply) as healthy,
+        rig.gateway.scenario() as scenario,
+    ):
+        refused_id: Final = deployment(scenario, group, {**anthropic_params(refusing), "cooldown_time": 2})
+        deployment(scenario, group, openai_params(healthy))
+        history: Final = until_refused(lambda marker: raw_chat(rig.gateway, group, marker))
+        assert_refused(history[-1])
+        eventually(lambda: rig.cooled(refused_id), lambda seen: seen, seconds=10)
+        eventually(lambda: rig.cooled(refused_id), lambda seen: not seen, seconds=10)
+        again: Final = until_refused(lambda marker: raw_chat(rig.gateway, group, marker))
+        assert_refused(again[-1])
+        assert markers_received(refusing) == (history[-1].marker, again[-1].marker)
+
+
+def burst_call(group: str, index: int) -> Call:
+    marker: Final = f"{new_marker()}-{index}"
+    stream: Final = index % 2 == 1
+    match index % 3:
+        case 0:
+            return Call(marker, "/v1/chat/completions", chat_body(group, marker, stream=stream))
+        case 1:
+            body: Final = {"model": group, "max_tokens": 32, "messages": [{"role": "user", "content": marker}]}
+            return Call(marker, "/v1/messages", {**body, "stream": stream})
+        case _:
+            return Call(marker, "/v1/responses", {"model": group, "input": marker, "stream": stream})
+
+
+def worker_pids(log: Path) -> tuple[int, ...]:
+    return tuple(int(pid) for pid in WORKER_PID.findall(log.read_text()))
+
+
+def ready_workers(log: Path) -> int:
+    return log.read_text().count("Application startup complete.")
+
+
+@pytest.mark.timeout(900)
+def test_chaos_burst_cooldown_holds_across_both_workers_and_a_worker_kill(tmp_path: Path) -> None:
+    group: Final = new_group()
+    refused_id: Final = f"refusing-{uuid.uuid4().hex[:12]}"
+    healthy_id: Final = f"healthy-{uuid.uuid4().hex[:12]}"
+    with ExitStack() as stack:
+        upstream: Final = stack.enter_context(gateway_from_environment())
+        cache: Final = stack.enter_context(owned_redis(tmp_path))
+        refusing: Final = stack.enter_context(wire_server(refusing_reply))
+        healthy: Final = stack.enter_context(wire_server(healthy_reply))
+        model_list: Final = (
+            {"model_name": group, "litellm_params": anthropic_params(refusing), "model_info": {"id": refused_id}},
+            {"model_name": group, "litellm_params": openai_params(healthy), "model_info": {"id": healthy_id}},
+        )
+        config: Final = cooldown_config(tmp_path, router_settings(cache), model_list=model_list, prometheus=False)
+        owned: Final = stack.enter_context(owned_proxy_process(upstream, tmp_path, {}, config=config, workers=2))
+        eventually(lambda: ready_workers(owned.log), lambda ready: ready == 2, seconds=graceful_stop_seconds())
+        client: Final = stack.enter_context(
+            httpx.Client(base_url=owned.gateway.client.base_url, timeout=60, trust_env=False, limits=GATEWAY_LIMITS)
+        )
+        patient: Final = Gateway(client, owned.gateway.key, owned.gateway.upstream_url)
+        calls: Final = tuple(burst_call(group, index) for index in range(30))
+        with ThreadPoolExecutor(max_workers=30) as pool:
+            outcomes: Final = tuple(pool.map(lambda call: raw_call(patient, call), calls))
+        assert {outcome.status for outcome in outcomes} <= {200, 402}, [(o.status, o.detail[:200]) for o in outcomes]
+        refused: Final = tuple(outcome for outcome in outcomes if outcome.status == 402)
+        served: Final = tuple(outcome for outcome in outcomes if outcome.status == 200)
+        assert refused, "the burst never reached the refusing deployment"
+        for outcome in refused:
+            assert_refused(outcome)
+        assert all(outcome.marker in outcome.detail for outcome in served), [o.detail[:200] for o in served]
+        assert sorted(markers_received(refusing)) == sorted(markers(refused))
+        assert sorted(markers_received(healthy)) == sorted(markers(served))
+        eventually(lambda: cooled(cache, refused_id), lambda seen: seen, seconds=10)
+        warm: Final = tuple(raw_chat(patient, group, new_marker()) for _ in range(20))
+        assert_served(warm, chat_identity)
+        assert markers_received(refusing) == ()
+        assert markers_received(healthy) == markers(warm)
+        victim: Final = next(pid for pid in sorted(worker_pids(owned.log)) if psutil.pid_exists(pid))
+        ready_before: Final = ready_workers(owned.log)
+        psutil.Process(victim).send_signal(signal.SIGKILL)
+        eventually(
+            lambda: ready_workers(owned.log), lambda ready: ready > ready_before, seconds=graceful_stop_seconds()
+        )
+        after_kill: Final = tuple(raw_chat(patient, group, new_marker()) for _ in range(20))
+        assert_served(after_kill, chat_identity)
+        assert markers_received(refusing) == ()
+        assert markers_received(healthy) == markers(after_kill)

tests/integration/routing/test_payment_required_mapping.py

@@ -0,0 +1,387 @@
+from __future__ import annotations
+
+import asyncio
+import json
+import os
+import uuid
+from collections.abc import Callable, Mapping
+from typing import Final, TypeVar
+
+import anthropic
+import httpx
+import openai
+import pytest
+from integration._support.client import Gateway, Scenario, eventually, object_value, string_value
+from integration._support.database import read_rows
+from integration._support.openai_wire import chat_reply, openai_error
+from integration._support.wire import Reply, Request, Wire, wire_server
+from pydantic import JsonValue
+
+from litellm.constants import PROXY_CONFIG_RELOAD_INTERVAL_SECONDS
+
+T = TypeVar("T")
+
+PROXY_WORKERS: Final = int(os.environ.get("INTEGRATION_PROXY_WORKERS", "1"))
+WORKER_SYNC_SECONDS: Final = 0.0 if PROXY_WORKERS == 1 else PROXY_CONFIG_RELOAD_INTERVAL_SECONDS + 5.0
+FRESH_CONNECTION: Final = {"Connection": "close"}
+UNKNOWN_MODEL: Final = "Invalid model name passed in model="
+PAYMENT_REQUIRED: Final = "litellm.PaymentRequiredError: AnthropicException"
+BAD_REQUEST: Final = "litellm.BadRequestError: AnthropicException"
+ANTHROPIC_MODEL: Final = "anthropic/claude-sonnet-5"
+OPENAI_MODEL: Final = "openai/gpt-5.4"
+CREDIT_BALANCE_TEXT: Final = "Your credit balance is too low to access the Anthropic API. Please go to Plans & Billing to upgrade or purchase credits."
+FAILURE_ROW: Final = (
+    "SELECT status, model_id, metadata::jsonb -> 'error_information' AS error "
+    'FROM "LiteLLM_SpendLogs" WHERE request_id = %s'
+)
+MODEL_INFO_PROBE: Final = ("GET", "/v1/models")
+
+
+def is_model_info_probe(request: Request) -> bool:
+    return (request.method, request.target) == MODEL_INFO_PROBE
+
+
+def model_list_reply() -> Reply:
+    return Reply(body=b'{"object": "list", "data": []}')
+
+
+def openai_refusal(request: Request) -> Reply:
+    return model_list_reply() if is_model_info_probe(request) else openai_error(402)
+
+
+def provider_calls(wire: Wire) -> tuple[Request, ...]:
+    return tuple(request for request in wire.drain() if not is_model_info_probe(request))
+
+
+def new_marker() -> str:
+    return f"pr402-{uuid.uuid4().hex}"
+
+
+def new_group() -> str:
+    return f"integration-402-{uuid.uuid4().hex[:12]}"
+
+
+def anthropic_error(status: int, message: str, *, content_type: str = "application/json") -> Reply:
+    body: Final = json.dumps({"type": "error", "error": {"type": "invalid_request_error", "message": message}})
+    return Reply(status=status, body=body.encode(), content_type=content_type)
+
+
+def anthropic_params(wire: Wire) -> dict[str, JsonValue]:
+    return {"model": ANTHROPIC_MODEL, "api_base": wire.url, "api_key": "synthetic-anthropic-key"}
+
+
+def openai_params(wire: Wire) -> dict[str, JsonValue]:
+    return {"model": OPENAI_MODEL, "api_base": wire.url + "/v1", "api_key": "synthetic-openai-key"}
+
+
+def deployment(
+    scenario: Scenario,
+    group: str,
+    litellm_params: Mapping[str, JsonValue],
+    *,
+    model_info: Mapping[str, JsonValue] | None = None,
+) -> str:
+    created: Final = scenario.gateway.post(
+        "/model/new",
+        {
+            "model_name": group,
+            "litellm_params": dict(litellm_params),
+            "model_info": dict(model_info) if model_info is not None else {},
+        },
+    )
+    identity: Final = string_value(object_value(created["model_info"])["id"])
+    scenario.cleanups.callback(scenario.delete_model, identity)
+    return identity
+
+
+def settled(send: Callable[[], T], text: Callable[[T], str]) -> T:
+    return eventually(send, lambda observed: UNKNOWN_MODEL not in text(observed), seconds=WORKER_SYNC_SECONDS + 10)
+
+
+def post(gateway: Gateway, path: str, body: Mapping[str, JsonValue]) -> httpx.Response:
+    return settled(
+        lambda: gateway.request("POST", path, body, headers=FRESH_CONNECTION), lambda response: response.text
+    )
+
+
+def chat_body(group: str, marker: str, **extra: JsonValue) -> dict[str, JsonValue]:
+    return {"model": group, "messages": [{"role": "user", "content": marker}], **extra}
+
+
+def upstream_calls(wire: Wire, marker: str) -> tuple[str, ...]:
+    received: Final = provider_calls(wire)
+    assert all(marker.encode() in request.body for request in received), received
+    return tuple(f"{request.method} {request.target}" for request in received)
+
+
+def failure_row(call_id: str) -> dict[str, JsonValue]:
+    rows: Final = eventually(lambda: read_rows(FAILURE_ROW, (call_id,)), lambda found: len(found) == 1, seconds=30)
+    return rows[0]
+
+
+def assert_payment_required_row(call_id: str, deployment_id: str) -> None:
+    row: Final = failure_row(call_id)
+    error: Final = object_value(row["error"])
+    assert row["status"] == "failure", row
+    assert row["model_id"] == deployment_id, row
+    assert (error["error_class"], error["error_code"], error["llm_provider"]) == (
+        "PaymentRequiredError",
+        "402",
+        "anthropic",
+    ), row
+
+
+def openai_client(gateway: Gateway) -> openai.OpenAI:
+    return openai.OpenAI(
+        base_url=str(gateway.client.base_url).rstrip("/") + "/v1",
+        api_key=gateway.key,
+        max_retries=0,
+        default_headers=FRESH_CONNECTION,
+    )
+
+
+def anthropic_client(gateway: Gateway) -> anthropic.Anthropic:
+    return anthropic.Anthropic(
+        base_url=str(gateway.client.base_url).rstrip("/"),
+        api_key=gateway.key,
+        max_retries=0,
+        default_headers=FRESH_CONNECTION,
+    )
+
+
+def test_chat_completions_openai_sdk_gets_402_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        client: Final = openai_client(gateway)
+
+        def send() -> openai.APIStatusError:
+            with pytest.raises(openai.APIStatusError) as caught:
+                client.chat.completions.create(model=group, messages=[{"role": "user", "content": marker}])
+            return caught.value
+
+        error: Final = settled(send, lambda failure: failure.message)
+        assert error.status_code == 402, error.message
+        assert PAYMENT_REQUIRED in error.message, error.message
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(error.response.headers["x-litellm-call-id"], deployment_id)
+
+
+async def drain_chat_stream(client: openai.AsyncOpenAI, group: str, marker: str) -> None:
+    stream: Final = await client.chat.completions.create(
+        model=group, messages=[{"role": "user", "content": marker}], stream=True
+    )
+    async for _ in stream:
+        pass
+
+
+async def drain_messages_stream(client: anthropic.AsyncAnthropic, group: str, marker: str) -> None:
+    async with client.messages.stream(
+        model=group, max_tokens=32, messages=[{"role": "user", "content": marker}]
+    ) as stream:
+        async for _ in stream:
+            pass
+
+
+def test_chat_completions_stream_openai_async_sdk_gets_402_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+
+        async def attempt() -> openai.APIStatusError:
+            async with openai.AsyncOpenAI(
+                base_url=str(gateway.client.base_url).rstrip("/") + "/v1",
+                api_key=gateway.key,
+                max_retries=0,
+                default_headers=FRESH_CONNECTION,
+            ) as client:
+                with pytest.raises(openai.APIStatusError) as caught:
+                    await drain_chat_stream(client, group, marker)
+                return caught.value
+
+        error: Final = settled(lambda: asyncio.run(attempt()), lambda failure: failure.message)
+        assert error.status_code == 402, error.message
+        assert PAYMENT_REQUIRED in error.message, error.message
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(error.response.headers["x-litellm-call-id"], deployment_id)
+
+
+def test_messages_anthropic_sdk_gets_402_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        client: Final = anthropic_client(gateway)
+
+        def send() -> anthropic.APIStatusError:
+            with pytest.raises(anthropic.APIStatusError) as caught:
+                client.messages.create(model=group, max_tokens=32, messages=[{"role": "user", "content": marker}])
+            return caught.value
+
+        error: Final = settled(send, lambda failure: failure.message)
+        assert error.status_code == 402, error.message
+        assert PAYMENT_REQUIRED in error.message, error.message
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(error.response.headers["x-litellm-call-id"], deployment_id)
+
+
+def test_messages_stream_anthropic_async_sdk_gets_402_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+
+        async def attempt() -> anthropic.APIStatusError:
+            async with anthropic.AsyncAnthropic(
+                base_url=str(gateway.client.base_url).rstrip("/"),
+                api_key=gateway.key,
+                max_retries=0,
+                default_headers=FRESH_CONNECTION,
+            ) as client:
+                with pytest.raises(anthropic.APIStatusError) as caught:
+                    await drain_messages_stream(client, group, marker)
+                return caught.value
+
+        error: Final = settled(lambda: asyncio.run(attempt()), lambda failure: failure.message)
+        assert error.status_code == 402, error.message
+        assert PAYMENT_REQUIRED in error.message, error.message
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(error.response.headers["x-litellm-call-id"], deployment_id)
+
+
+@pytest.mark.parametrize("stream", (False, True), ids=("json", "stream"))
+def test_responses_httpx_gets_402_payment_required(gateway: Gateway, stream: bool) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        response: Final = post(gateway, "/v1/responses", {"model": group, "input": marker, "stream": stream})
+        assert response.status_code == 402, response.text
+        assert PAYMENT_REQUIRED in response.text, response.text
+        assert response.headers["content-type"].startswith("application/json"), response.headers
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(response.headers["x-litellm-call-id"], deployment_id)
+
+
+def test_402_with_a_text_body_still_maps_to_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    text: Final = f"credits exhausted {marker}"
+    with (
+        wire_server(lambda _: Reply(status=402, body=text.encode(), content_type="text/plain")) as wire,
+        gateway.scenario() as scenario,
+    ):
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        response: Final = post(gateway, "/v1/chat/completions", chat_body(group, marker))
+        assert response.status_code == 402, response.text
+        assert PAYMENT_REQUIRED in response.text, response.text
+        assert text in response.text, response.text
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(response.headers["x-litellm-call-id"], deployment_id)
+
+
+def test_402_with_an_empty_body_still_maps_to_payment_required(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: Reply(status=402, body=b"")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        response: Final = post(gateway, "/v1/chat/completions", chat_body(group, marker))
+        assert response.status_code == 402, response.text
+        assert PAYMENT_REQUIRED in response.text, response.text
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(response.headers["x-litellm-call-id"], deployment_id)
+
+
+def test_402_with_a_5kb_message_maps_and_a_healthy_deployment_keeps_serving(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    long_message: Final = f"{marker} " + "x" * 5120
+    with (
+        wire_server(lambda _: anthropic_error(402, long_message)) as broke,
+        wire_server(
+            lambda _: chat_reply(f"chatcmpl-{marker}", OPENAI_MODEL, f"served {marker}", stream=False)
+        ) as healthy,
+        gateway.scenario() as scenario,
+    ):
+        broke_group: Final = new_group()
+        healthy_group: Final = new_group()
+        deployment_id: Final = deployment(scenario, broke_group, anthropic_params(broke))
+        deployment(scenario, healthy_group, openai_params(healthy))
+        refused: Final = post(gateway, "/v1/chat/completions", chat_body(broke_group, marker))
+        assert refused.status_code == 402, refused.text
+        assert PAYMENT_REQUIRED in refused.text, refused.text
+        assert "x" * 512 in refused.text, refused.text
+        assert upstream_calls(broke, marker) == ("POST /v1/messages",)
+        assert_payment_required_row(refused.headers["x-litellm-call-id"], deployment_id)
+        served: Final = post(gateway, "/v1/chat/completions", chat_body(healthy_group, f"{marker} healthy"))
+        assert served.status_code == 200, served.text
+        assert served.json()["choices"][0]["message"]["content"] == f"served {marker}", served.text
+        assert upstream_calls(healthy, marker) == ("POST /v1/chat/completions",)
+
+
+def test_unauthenticated_request_to_a_402_deployment_is_refused_before_the_wire(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment(scenario, group, anthropic_params(wire))
+        response: Final = gateway.client.post("/v1/chat/completions", json=chat_body(group, marker))
+        assert response.status_code == 401, response.text
+        assert provider_calls(wire) == ()
+
+
+def test_anthropic_400_credit_balance_text_stays_a_bad_request(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with (
+        wire_server(lambda _: anthropic_error(400, f"{CREDIT_BALANCE_TEXT} {marker}")) as wire,
+        gateway.scenario() as scenario,
+    ):
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, anthropic_params(wire))
+        response: Final = post(gateway, "/v1/chat/completions", chat_body(group, marker))
+        assert response.status_code == 400, response.text
+        assert BAD_REQUEST in response.text, response.text
+        assert upstream_calls(wire, marker) == ("POST /v1/messages",)
+        row: Final = failure_row(response.headers["x-litellm-call-id"])
+        error: Final = object_value(row["error"])
+        assert (row["status"], row["model_id"]) == ("failure", deployment_id), row
+        assert (error["error_class"], error["error_code"]) == ("BadRequestError", "400"), row
+
+
+def test_openai_compatible_402_reaches_the_caller_as_402(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with wire_server(openai_refusal) as wire, gateway.scenario() as scenario:
+        group: Final = new_group()
+        deployment_id: Final = deployment(scenario, group, openai_params(wire))
+        response: Final = post(gateway, "/v1/chat/completions", chat_body(group, marker))
+        assert response.status_code == 402, response.text
+        assert "scripted 402" in response.text, response.text
+        assert upstream_calls(wire, marker) == ("POST /v1/chat/completions",)
+        row: Final = failure_row(response.headers["x-litellm-call-id"])
+        error: Final = object_value(row["error"])
+        assert (row["status"], row["model_id"]) == ("failure", deployment_id), row
+        assert (error["error_code"], error["llm_provider"]) == ("402", "openai"), row
+
+
+def test_disabled_cooldowns_keep_picking_the_402_deployment(gateway: Gateway) -> None:
+    marker: Final = new_marker()
+    with (
+        wire_server(lambda _: anthropic_error(402, f"scripted 402 {marker}")) as broke,
+        wire_server(
+            lambda _: chat_reply(f"chatcmpl-{marker}", OPENAI_MODEL, f"served {marker}", stream=False)
+        ) as healthy,
+        gateway.scenario() as scenario,
+    ):
+        group: Final = new_group()
+        deployment(scenario, group, anthropic_params(broke))
+        deployment(scenario, group, openai_params(healthy))
+        responses: Final = tuple(
+            post(gateway, "/v1/chat/completions", chat_body(group, f"{marker}-{index}")) for index in range(40)
+        )
+        statuses: Final = tuple(response.status_code for response in responses)
+        assert statuses.count(402) >= 2 and statuses.count(200) >= 1, statuses
+        assert set(statuses) == {200, 402}, statuses
+        refusals: Final = tuple(response for response in responses if response.status_code == 402)
+        assert all(PAYMENT_REQUIRED in response.text for response in refusals), [r.text for r in refusals]
+        assert len(upstream_calls(broke, marker)) == len(refusals)
+        assert len(upstream_calls(healthy, marker)) == statuses.count(200)

tests/litellm_utils_tests/test_aiohttp_handler.py

@@ -1,67 +0,0 @@
-import asyncio
-import socket
-from typing import Final
-
-import aiohttp
-import httpx
-import pytest
-from aiohttp import ClientSession
-
-from litellm.llms.custom_httpx.aiohttp_transport import LiteLLMAiohttpTransport
-from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
-
-
-def _closed_local_port() -> int:
-    with socket.socket() as probe:
-        probe.bind(("127.0.0.1", 0))
-        return probe.getsockname()[1]
-
-
-async def test_client_session_helper() -> None:
-    transport: Final = AsyncHTTPHandler._create_aiohttp_transport()
-    assert isinstance(transport, LiteLLMAiohttpTransport)
-    session1: Final = transport._get_valid_client_session()
-    assert isinstance(session1, ClientSession)
-    assert session1.closed is False
-    assert getattr(session1, "_loop") is asyncio.get_running_loop()
-    session2: Final = transport._get_valid_client_session()
-    assert session2 is session1
-    await session1.close()
-
-
-async def test_event_loop_robustness() -> None:
-    transport: Final = AsyncHTTPHandler._create_aiohttp_transport()
-    session: Final = transport._get_valid_client_session()
-    assert isinstance(session, ClientSession)
-    await session.close()
-    session_after_close: Final = transport._get_valid_client_session()
-    assert isinstance(session_after_close, ClientSession)
-    assert session_after_close is not session
-    assert session_after_close.closed is False
-    transport.client = lambda: ClientSession()
-    session_after_factory: Final = transport._get_valid_client_session()
-    assert isinstance(session_after_factory, ClientSession)
-    assert session_after_factory is not session_after_close
-    assert session_after_factory.closed is False
-    assert transport.client is session_after_factory
-    await session_after_close.close()
-    await session_after_factory.close()
-
-
-@pytest.mark.parametrize(("ssl_verify", "expected_ssl"), [(False, False), (None, True)])
-async def test_refused_connection_maps_to_httpx_connect_error(
-    ssl_verify: bool | None, expected_ssl: bool, monkeypatch: pytest.MonkeyPatch
-) -> None:
-    monkeypatch.setenv("NO_PROXY", "127.0.0.1")
-    transport: Final = AsyncHTTPHandler._create_aiohttp_transport(ssl_verify=ssl_verify)
-    port: Final = _closed_local_port()
-    request: Final = httpx.Request("GET", f"https://127.0.0.1:{port}/")
-    try:
-        with pytest.raises(httpx.ConnectError) as raised:
-            await transport.handle_async_request(request)
-    finally:
-        await transport._get_valid_client_session().close()
-    cause: Final = raised.value.__cause__
-    assert isinstance(cause, aiohttp.ClientConnectorError)
-    assert cause.ssl is expected_ssl
-    assert (cause.host, cause.port) == ("127.0.0.1", port)

tests/litellm_utils_tests/test_aws_secret_manager.py

@@ -1,504 +0,0 @@
-# What is this?
-
-import asyncio
-import os
-import sys
-import traceback
-
-from dotenv import load_dotenv
-
-import litellm.types
-import litellm.types.utils
-
-load_dotenv()
-import io
-
-
-# Ensure the project root is in the Python path
-sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../../..")))
-
-print("Python Path:", sys.path)
-print("Current Working Directory:", os.getcwd())
-
-
-import functools
-from typing import Optional
-from unittest.mock import MagicMock, patch
-
-import pytest
-from litellm._uuid import uuid
-import json
-from litellm.secret_managers.aws_secret_manager_v2 import AWSSecretsManagerV2
-from litellm.types.secret_managers.main import KeyManagementSettings
-
-
-def skip_on_throttling(func):
-    """Skip async test on AWS ThrottlingException instead of failing."""
-
-    @functools.wraps(func)
-    async def wrapper(*args, **kwargs):
-        try:
-            return await func(*args, **kwargs)
-        except Exception as e:
-            if "ThrottlingException" in str(e):
-                pytest.skip(f"AWS throttling: {e}")
-            raise
-
-    return wrapper
-
-
-def check_aws_credentials():
-    """Helper function to check if AWS credentials are set"""
-    if os.getenv("LITELLM_RUN_LIVE_AWS_SECRET_MANAGER_TESTS") != "1":
-        pytest.skip("Live AWS Secrets Manager E2E tests are opt-in")
-    if os.getenv("CASSETTE_REDIS_URL"):
-        pytest.skip("Live AWS Secrets Manager E2E tests cannot run under VCR replay")
-
-    required_vars = ["AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_REGION_NAME"]
-    missing_vars = [var for var in required_vars if not os.getenv(var)]
-    if missing_vars:
-        pytest.skip(f"Missing required AWS credentials: {', '.join(missing_vars)}")
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_write_and_read_simple_secret():
-    """Test writing and reading a simple string secret"""
-    check_aws_credentials()
-
-    secret_manager = AWSSecretsManagerV2()
-    test_secret_name = f"litellm_test_{uuid.uuid4().hex[:8]}"
-    test_secret_value = "test_value_123"
-
-    try:
-        # Write secret
-        write_response = await secret_manager.async_write_secret(
-            secret_name=test_secret_name,
-            secret_value=test_secret_value,
-            description="LiteLLM Test Secret",
-        )
-
-        print("Write Response:", write_response)
-
-        assert write_response is not None
-        assert "ARN" in write_response
-        assert "Name" in write_response
-        assert write_response["Name"] == test_secret_name
-
-        # Read secret back
-        read_value = await secret_manager.async_read_secret(
-            secret_name=test_secret_name
-        )
-
-        print("Read Value:", read_value)
-
-        assert read_value == test_secret_value
-    finally:
-        # Cleanup: Delete the secret
-        delete_response = await secret_manager.async_delete_secret(
-            secret_name=test_secret_name
-        )
-        print("Delete Response:", delete_response)
-        assert delete_response is not None
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_write_and_read_json_secret():
-    """Test writing and reading a JSON structured secret"""
-    check_aws_credentials()
-
-    secret_manager = AWSSecretsManagerV2()
-    test_secret_name = f"litellm_test_{uuid.uuid4().hex[:8]}_json"
-    test_secret_value = {
-        "api_key": "test_key",
-        "model": "gpt-4",
-        "temperature": 0.7,
-        "metadata": {"team": "ml", "project": "litellm"},
-    }
-
-    try:
-        # Write JSON secret
-        write_response = await secret_manager.async_write_secret(
-            secret_name=test_secret_name,
-            secret_value=json.dumps(test_secret_value),
-            description="LiteLLM JSON Test Secret",
-        )
-
-        print("Write Response:", write_response)
-
-        # Read and parse JSON secret
-        read_value = await secret_manager.async_read_secret(
-            secret_name=test_secret_name
-        )
-        parsed_value = json.loads(read_value)
-
-        print("Read Value:", read_value)
-
-        assert parsed_value == test_secret_value
-        assert parsed_value["api_key"] == "test_key"
-        assert parsed_value["metadata"]["team"] == "ml"
-    finally:
-        # Cleanup: Delete the secret
-        delete_response = await secret_manager.async_delete_secret(
-            secret_name=test_secret_name
-        )
-        print("Delete Response:", delete_response)
-        assert delete_response is not None
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_read_nonexistent_secret():
-    """Test reading a secret that doesn't exist"""
-    check_aws_credentials()
-
-    secret_manager = AWSSecretsManagerV2()
-    nonexistent_secret = f"litellm_nonexistent_{uuid.uuid4().hex}"
-
-    response = await secret_manager.async_read_secret(secret_name=nonexistent_secret)
-
-    assert response is None
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_primary_secret_functionality():
-    """Test storing and retrieving secrets from a primary secret"""
-    check_aws_credentials()
-
-    secret_manager = AWSSecretsManagerV2()
-    primary_secret_name = f"litellm_test_primary_{uuid.uuid4().hex[:8]}"
-
-    # Create a primary secret with multiple key-value pairs
-    primary_secret_value = {
-        "api_key_1": "secret_value_1",
-        "api_key_2": "secret_value_2",
-        "database_url": "postgresql://user:password@localhost:5432/db",
-        "nested_secret": json.dumps({"key": "value", "number": 42}),
-    }
-
-    try:
-        # Write the primary secret
-        write_response = await secret_manager.async_write_secret(
-            secret_name=primary_secret_name,
-            secret_value=json.dumps(primary_secret_value),
-            description="LiteLLM Test Primary Secret",
-        )
-
-        print("Primary Secret Write Response:", write_response)
-        assert write_response is not None
-        assert "ARN" in write_response
-        assert "Name" in write_response
-        assert write_response["Name"] == primary_secret_name
-
-        # Test reading individual secrets from the primary secret
-        for key, expected_value in primary_secret_value.items():
-            # Read using the primary_secret_name parameter
-            value = await secret_manager.async_read_secret(
-                secret_name=key, primary_secret_name=primary_secret_name
-            )
-
-            print(f"Read {key} from primary secret:", value)
-            assert value == expected_value
-
-        # Test reading a non-existent key from the primary secret
-        non_existent_key = "non_existent_key"
-        value = await secret_manager.async_read_secret(
-            secret_name=non_existent_key, primary_secret_name=primary_secret_name
-        )
-        assert value is None, f"Expected None for non-existent key, got {value}"
-
-    finally:
-        # Cleanup: Delete the primary secret
-        delete_response = await secret_manager.async_delete_secret(
-            secret_name=primary_secret_name
-        )
-        print("Delete Response:", delete_response)
-        assert delete_response is not None
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_write_secret_with_description_and_tags():
-    """Test writing a secret with description and tags"""
-    check_aws_credentials()
-
-    secret_manager = AWSSecretsManagerV2()
-    test_secret_name = f"litellm_test_{uuid.uuid4().hex[:8]}_tags"
-    test_secret_value = "test_value_with_tags"
-
-    test_description = "LiteLLM Secret with Description and Tags"
-    test_tags = {
-        "Environment": "Test",
-        "Owner": "IntelligenceLayer",
-        "Purpose": "UnitTest",
-    }
-
-    try:
-        # Write secret with tags and description
-        write_response = await secret_manager.async_write_secret(
-            secret_name=test_secret_name,
-            secret_value=test_secret_value,
-            description=test_description,
-            tags=test_tags,
-        )
-
-        print("Write Response:", write_response)
-        assert write_response is not None
-        assert "ARN" in write_response
-        assert "Name" in write_response
-        assert write_response["Name"] == test_secret_name
-
-        # --- Validate the secret metadata via AWS CLI / boto3 ---
-        import boto3
-
-        client = boto3.client(
-            "secretsmanager", region_name=os.getenv("AWS_REGION_NAME")
-        )
-        describe_resp = client.describe_secret(SecretId=test_secret_name)
-        print("Describe Response:", describe_resp)
-
-        # Validate description
-        assert describe_resp.get("Description") == test_description
-
-        # Validate tags (as list of dicts in AWS)
-        if "Tags" in describe_resp:
-            tag_dict = {t["Key"]: t["Value"] for t in describe_resp["Tags"]}
-            for k, v in test_tags.items():
-                assert (
-                    tag_dict.get(k) == v
-                ), f"Expected tag {k}={v}, got {tag_dict.get(k)}"
-        else:
-            pytest.fail("No tags found in describe_secret response")
-
-        # --- Validate secret value ---
-        read_value = await secret_manager.async_read_secret(
-            secret_name=test_secret_name
-        )
-        print("Read Value:", read_value)
-        assert read_value == test_secret_value
-
-    finally:
-        # Cleanup: Delete the secret
-        delete_response = await secret_manager.async_delete_secret(
-            secret_name=test_secret_name
-        )
-        print("Delete Response:", delete_response)
-        assert delete_response is not None
-
-
-def test_secret_manager_with_iam_role_settings():
-    """
-    Test AWS Secret Manager initialization with IAM role settings
-    """
-    settings = KeyManagementSettings(
-        aws_region_name="us-east-1",
-        aws_role_name="arn:aws:iam::123456789012:role/TestRole",
-        aws_session_name="test-session",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_role_name=settings.aws_role_name,
-        aws_session_name=settings.aws_session_name,
-    )
-
-    # Verify settings are stored
-    assert secret_manager.aws_role_name == settings.aws_role_name
-    assert secret_manager.aws_region_name == settings.aws_region_name
-    assert secret_manager.aws_session_name == settings.aws_session_name
-
-
-def test_secret_manager_with_cross_account_settings():
-    """
-    Test AWS Secret Manager initialization with cross-account IAM role settings
-    """
-    settings = KeyManagementSettings(
-        aws_region_name="us-west-2",
-        aws_role_name="arn:aws:iam::999999999999:role/CrossAccountRole",
-        aws_session_name="cross-account-session",
-        aws_external_id="unique-external-id",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_role_name=settings.aws_role_name,
-        aws_session_name=settings.aws_session_name,
-        aws_external_id=settings.aws_external_id,
-    )
-
-    # Verify settings are stored
-    assert secret_manager.aws_role_name == settings.aws_role_name
-    assert secret_manager.aws_region_name == settings.aws_region_name
-    assert secret_manager.aws_external_id == settings.aws_external_id
-
-
-def test_secret_manager_with_irsa_settings():
-    """
-    Test AWS Secret Manager initialization with IRSA (EKS) settings
-    """
-    settings = KeyManagementSettings(
-        aws_region_name="us-east-1",
-        aws_role_name="arn:aws:iam::123456789012:role/EKSServiceAccountRole",
-        aws_session_name="eks-session",
-        aws_web_identity_token="os.environ/AWS_WEB_IDENTITY_TOKEN_FILE",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_role_name=settings.aws_role_name,
-        aws_session_name=settings.aws_session_name,
-        aws_web_identity_token=settings.aws_web_identity_token,
-    )
-
-    # Verify settings are stored
-    assert secret_manager.aws_role_name == settings.aws_role_name
-    assert secret_manager.aws_web_identity_token == settings.aws_web_identity_token
-
-
-def test_secret_manager_with_custom_sts_endpoint():
-    """
-    Test AWS Secret Manager initialization with custom STS endpoint (VPC endpoint)
-    """
-    settings = KeyManagementSettings(
-        aws_region_name="us-east-1",
-        aws_role_name="arn:aws:iam::123456789012:role/VPCRole",
-        aws_session_name="vpc-session",
-        aws_sts_endpoint="https://sts.us-east-1.vpce-0123456789abcdef.amazonaws.com",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_role_name=settings.aws_role_name,
-        aws_session_name=settings.aws_session_name,
-        aws_sts_endpoint=settings.aws_sts_endpoint,
-    )
-
-    # Verify settings are stored
-    assert secret_manager.aws_role_name == settings.aws_role_name
-    assert secret_manager.aws_sts_endpoint == settings.aws_sts_endpoint
-
-
-def test_secret_manager_with_aws_profile():
-    """
-    Test AWS Secret Manager initialization with AWS profile
-    """
-    settings = KeyManagementSettings(
-        aws_region_name="us-east-1",
-        aws_profile_name="litellm-dev",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_profile_name=settings.aws_profile_name,
-    )
-
-    # Verify settings are stored
-    assert secret_manager.aws_profile_name == settings.aws_profile_name
-
-
-def test_load_aws_secret_manager_with_settings():
-    """
-    Test loading AWS Secret Manager with key_management_settings
-    """
-    import litellm
-
-    settings = KeyManagementSettings(
-        store_virtual_keys=True,
-        aws_region_name="us-east-1",
-        aws_role_name="arn:aws:iam::123456789012:role/TestRole",
-        aws_session_name="test-session",
-    )
-
-    # Set environment variable for validation to pass
-    os.environ["AWS_REGION_NAME"] = "us-east-1"
-
-    try:
-        AWSSecretsManagerV2.load_aws_secret_manager(
-            use_aws_secret_manager=True,
-            key_management_settings=settings,
-        )
-
-        # Verify the client was created
-        assert litellm.secret_manager_client is not None
-        assert isinstance(litellm.secret_manager_client, AWSSecretsManagerV2)
-
-        # Verify settings were passed through
-        assert litellm.secret_manager_client.aws_role_name == settings.aws_role_name
-        assert litellm.secret_manager_client.aws_region_name == settings.aws_region_name
-        assert (
-            litellm.secret_manager_client.aws_session_name == settings.aws_session_name
-        )
-    finally:
-        # Cleanup
-        litellm.secret_manager_client = None
-
-
-@pytest.mark.asyncio
-@skip_on_throttling
-async def test_end_to_end_iam_role_secret_write():
-    """
-    Test writing a secret using IAM role assumption (integration test)
-
-    Requires:
-    - AWS_REGION_NAME environment variable
-    - TEST_IAM_ROLE_ARN environment variable with ARN of a role that can be assumed
-    - Proper AWS credentials configured (via instance profile, IAM role, or environment)
-    """
-    if os.getenv("LITELLM_RUN_LIVE_AWS_SECRET_MANAGER_TESTS") != "1":
-        pytest.skip("Live AWS Secrets Manager E2E tests are opt-in")
-    if os.getenv("CASSETTE_REDIS_URL"):
-        pytest.skip("Live AWS Secrets Manager E2E tests cannot run under VCR replay")
-
-    # Skip if TEST_IAM_ROLE_ARN is not set
-    test_role_arn = os.getenv("TEST_IAM_ROLE_ARN")
-    if not test_role_arn:
-        pytest.skip("TEST_IAM_ROLE_ARN environment variable not set")
-
-    aws_region = os.getenv("AWS_REGION_NAME", "us-east-1")
-
-    settings = KeyManagementSettings(
-        store_virtual_keys=True,
-        aws_region_name=aws_region,
-        aws_role_name=test_role_arn,
-        aws_session_name="integration-test-session",
-    )
-
-    secret_manager = AWSSecretsManagerV2(
-        aws_region_name=settings.aws_region_name,
-        aws_role_name=settings.aws_role_name,
-        aws_session_name=settings.aws_session_name,
-    )
-
-    test_secret_name = f"litellm_test_iam_{uuid.uuid4().hex[:8]}"
-    test_secret_value = "test_value_iam_role"
-
-    try:
-        # Test write operation using IAM role
-        response = await secret_manager.async_write_secret(
-            secret_name=test_secret_name,
-            secret_value=test_secret_value,
-        )
-
-        print("Write Response with IAM Role:", response)
-        assert response is not None
-        assert "ARN" in response
-
-        # Test read operation using IAM role
-        read_value = await secret_manager.async_read_secret(
-            secret_name=test_secret_name
-        )
-
-        print("Read Value with IAM Role:", read_value)
-        assert read_value == test_secret_value
-
-    finally:
-        # Cleanup: Delete the secret
-        try:
-            delete_response = await secret_manager.async_delete_secret(
-                secret_name=test_secret_name
-            )
-            print("Delete Response:", delete_response)
-        except Exception as e:
-            print(f"Cleanup failed: {e}")

tests/litellm_utils_tests/test_get_secret.py

@@ -1,25 +0,0 @@
-import json
-from datetime import datetime
-from unittest.mock import AsyncMock, Mock, patch
-
-import pytest
-
-import litellm
-from litellm.proxy._types import KeyManagementSystem
-from litellm.secret_managers.main import get_secret
-
-
-class MockSecretClient:
-    def get_secret(self, secret_name):
-        return Mock(value="mocked_secret_value")
-
-
-@pytest.mark.asyncio
-async def test_azure_kms():
-    """
-    Basic asserts that the value from get secret is from Azure Key Vault when Key Management System is Azure Key Vault
-    """
-    with patch("litellm.secret_manager_client", new=MockSecretClient()):
-        litellm._key_management_system = KeyManagementSystem.AZURE_KEY_VAULT
-        secret = get_secret(secret_name="ishaan-test-key")
-        assert secret == "mocked_secret_value"

tests/litellm_utils_tests/test_health_check.py

@@ -1,12 +1,11 @@
 #### What this tests ####
 #    This tests if ahealth_check() actually works
 
+import asyncio
 import os
-
-import pytest
 from unittest.mock import AsyncMock, patch
 
-import asyncio
+import pytest
 
 import litellm
 
@@ -79,73 +78,8 @@ async def test_openai_img_gen_health_check():
 # asyncio.run(test_openai_img_gen_health_check())
 
 
-@pytest.mark.skip(
-    reason="Azure DALL-E 3 model deployment is deprecated (410 ModelDeprecated)"
-)
-@pytest.mark.asyncio
-async def test_azure_img_gen_health_check():
-    """
-    Test Azure image generation health check with retry logic for transient errors.
-    Azure sometimes returns internal server errors which are transient and not something we can control.
-    """
-    litellm.turn_on_debug()
-    max_retries = 3
-    retry_delay = 1  # Start with 1 second delay
-
-    for attempt in range(max_retries):
-        response = await litellm.ahealth_check(
-            model_params={
-                "model": "azure/gpt-image-1",
-                "api_base": os.getenv("AZURE_AI_API_BASE"),
-                "api_key": os.getenv("AZURE_AI_API_KEY"),
-            },
-            mode="image_generation",
-            prompt="cute baby sea otter",
-        )
-
-        # Check if response is successful (no error)
-        if isinstance(response, dict) and "error" not in response:
-            return response
-
-        # Check if error is a transient Azure internal server error
-        error_str = str(response.get("error", "")).lower()
-        is_transient_error = (
-            "internalservererror" in error_str
-            or "internal server error" in error_str
-            or "internalfailure" in error_str
-            or "internal failure" in error_str
-        )
-
-        # If it's the last attempt or not a transient error, fail the test
-        if attempt == max_retries - 1 or not is_transient_error:
-            assert (
-                isinstance(response, dict) and "error" not in response
-            ), f"Health check failed: {response.get('error', 'Unknown error')}"
-            return response
-
-        # Wait before retrying with exponential backoff
-        await asyncio.sleep(retry_delay)
-        retry_delay *= 2  # Exponential backoff
-
-    # Should not reach here, but just in case
-    pytest.fail("Health check failed after all retries")
 
 
-@pytest.mark.skip(reason="AWS Suspended Account")
-@pytest.mark.asyncio
-async def test_sagemaker_embedding_health_check():
-    response = await litellm.ahealth_check(
-        model_params={
-            "model": "sagemaker/berri-benchmarking-gpt-j-6b-fp16",
-            "messages": [{"role": "user", "content": "Hey, how's it going?"}],
-        },
-        mode="embedding",
-        input=["test from litellm"],
-    )
-    print(f"response: {response}")
-
-    assert isinstance(response, dict)
-    return response
 
 
 # asyncio.run(test_sagemaker_embedding_health_check())
@@ -574,9 +508,10 @@ async def test_perform_health_check_with_health_check_model():
 
 @pytest.mark.asyncio
 async def test_health_check_bad_model():
-    from litellm.proxy.health_check import _perform_health_check
     import time
 
+    from litellm.proxy.health_check import _perform_health_check
+
     model_list = [
         {
             "model_name": "openai-gpt-4o",
@@ -741,6 +676,7 @@ async def test_image_generation_health_check_prompt(monkeypatch):
     """Health checks should respect default and environment-configured prompts."""
 
     import importlib
+
     import litellm.constants as litellm_constants
     import litellm.proxy.health_check as health_check
 

tests/litellm_utils_tests/test_secret_manager.py

@@ -1,27 +1,26 @@
 import base64
+import hashlib
+import json
 import os
-import time
-import traceback
-from litellm._uuid import uuid
 
 from dotenv import load_dotenv
-import json
 
 load_dotenv()
 import tempfile
+from unittest.mock import AsyncMock, MagicMock, patch
 from uuid import uuid4
+from typing import Final
 
 import pytest
+
 import litellm
-from litellm.llms.azure.azure import get_azure_ad_token_from_oidc
-from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
-from litellm.llms.bedrock.chat import BedrockConverseLLM
 from litellm.secret_managers.aws_secret_manager_v2 import AWSSecretsManagerV2
 from litellm.secret_managers.main import (
-    get_secret,
     _should_read_secret_from_secret_manager,
+    get_secret,
 )
-from unittest.mock import AsyncMock, patch, MagicMock
+
+_AWS_FIXTURE_MASTER_KEY_SHA256: Final = "88dc28d0f030c55ed4ab77ed8faf098196cb1c05df778539800c9f1243fe6b4b"
 
 
 def load_vertex_ai_credentials():
@@ -76,7 +75,9 @@ def test_aws_secret_manager():
     # cast json to dict
     secret_val = json.loads(secret_val)
 
-    assert secret_val["litellm_master_key"] == os.environ["LITELLM_MASTER_KEY"]
+    assert (
+        hashlib.sha256(secret_val["litellm_master_key"].encode()).hexdigest() == _AWS_FIXTURE_MASTER_KEY_SHA256
+    ), "Expected the fixture value stored in the CI AWS account's litellm_master_key secret"
 
 
 def redact_oidc_signature(secret_val):
@@ -130,39 +131,8 @@ def test_oidc_circleci_v2():
     print(f"secret_val: {redact_oidc_signature(secret_val)}")
 
 
-@pytest.mark.skip(
-    reason="Quarantined: Flaky test - fails with 401 Unauthorized from Azure OAuth. TODO: Switch to our own Azure account or fix authentication"
-)
-def test_oidc_circleci_with_azure():
-    # TODO: Switch to our own Azure account, currently using ai.moda's account
-    os.environ["AZURE_TENANT_ID"] = "17c0a27a-1246-4aa1-a3b6-d294e80e783c"
-    os.environ["AZURE_CLIENT_ID"] = "4faf5422-b2bd-45e8-a6d7-46543a38acd0"
-    azure_ad_token = get_azure_ad_token_from_oidc(
-        azure_ad_token="oidc/circleci/",
-        azure_client_id=None,
-        azure_tenant_id=None,
-    )
-
-    print(f"secret_val: {redact_oidc_signature(azure_ad_token)}")
 
 
-@pytest.mark.skip(
-    reason="Quarantined: Flaky test - fails with InvalidIdentityToken, OIDC provider no longer configured in AWS account. TODO: Switch to LiteLLM's own IAM role"
-)
-def test_oidc_circle_v1_with_amazon():
-    # The purpose of this test is to get logs using the older v1 of the CircleCI OIDC token
-
-    # TODO: This is using ai.moda's IAM role, we should use LiteLLM's IAM role eventually
-    aws_role_name = "arn:aws:iam::335785316107:role/litellm-github-unit-tests-circleci-v1-assume-only"
-    aws_web_identity_token = "oidc/circleci/"
-
-    bllm = BaseAWSLLM()
-    creds = bllm.get_credentials(
-        aws_region_name="ca-west-1",
-        aws_web_identity_token=aws_web_identity_token,
-        aws_role_name=aws_role_name,
-        aws_session_name="assume-v1-session",
-    )
 
 
 def test_oidc_env_variable():

tests/litellm_utils_tests/test_validate_tool_choice.py

@@ -1,74 +0,0 @@
-import re
-from typing import Final
-
-import pytest
-
-import litellm
-from litellm.utils import validate_chat_completion_tool_choice
-
-MODEL: Final = "anthropic/claude-haiku-4-5"
-
-
-def test_validate_tool_choice_none():
-    """Test that None is returned as-is."""
-    result = validate_chat_completion_tool_choice(None, model=MODEL)
-    assert result is None
-
-
-def test_validate_tool_choice_string():
-    """Test that string values are returned as-is."""
-    assert validate_chat_completion_tool_choice("auto", model=MODEL) == "auto"
-    assert validate_chat_completion_tool_choice("none", model=MODEL) == "none"
-    assert validate_chat_completion_tool_choice("required", model=MODEL) == "required"
-
-
-def test_validate_tool_choice_standard_dict():
-    """Test standard OpenAI format with function."""
-    tool_choice = {"type": "function", "function": {"name": "my_function"}}
-    result = validate_chat_completion_tool_choice(tool_choice, model=MODEL)
-    assert result == tool_choice
-
-
-def test_validate_tool_choice_cursor_format():
-    """Cursor IDE format {"type": "auto"} is unwrapped to the bare string."""
-    assert validate_chat_completion_tool_choice({"type": "auto"}, model=MODEL) == "auto"
-    assert validate_chat_completion_tool_choice({"type": "none"}, model=MODEL) == "none"
-    assert validate_chat_completion_tool_choice({"type": "required"}, model=MODEL) == "required"
-
-
-@pytest.mark.parametrize(
-    "tool_choice",
-    [
-        {},
-        {"type": "invalid"},
-        {"type": "function"},
-        {"name": "lookup_fruit"},
-        {"type": "file_search"},
-    ],
-)
-def test_validate_tool_choice_invalid_dict_is_a_400(tool_choice):
-    """A dict shape chat completions cannot carry is the caller's mistake: a 400 that names the field, never a 500."""
-    with pytest.raises(
-        litellm.BadRequestError, match=f"Invalid tool choice, tool_choice={re.escape(str(tool_choice))}\\. Please ensure"
-    ) as exc_info:
-        validate_chat_completion_tool_choice(tool_choice, model=MODEL)
-    assert exc_info.value.status_code == 400
-    assert exc_info.value.model == MODEL
-
-
-@pytest.mark.parametrize("tool_choice", [123, []])
-def test_validate_tool_choice_invalid_type_is_a_400(tool_choice):
-    """A non-str, non-dict tool_choice is rejected as a 400 that names the type it got."""
-    with pytest.raises(
-        litellm.BadRequestError, match=f"Got={re.escape(str(type(tool_choice)))}\\. Expecting str, or dict\\."
-    ) as exc_info:
-        validate_chat_completion_tool_choice(tool_choice, model=MODEL)
-    assert exc_info.value.status_code == 400
-
-
-def test_validate_tool_choice_without_model_is_still_a_400():
-    """Callers that predate the model argument keep getting a 400, with an empty model on the error."""
-    with pytest.raises(litellm.BadRequestError, match="Invalid tool choice") as exc_info:
-        validate_chat_completion_tool_choice({"type": "bogus"})
-    assert exc_info.value.status_code == 400
-    assert exc_info.value.model == ""

tests/llm_responses_api_testing/test_anthropic_tool_result_fix.py

@@ -1,170 +0,0 @@
-"""
-Test to verify the fix for Anthropic tool_result issue.
-
-This test verifies that when using previous_response_id with tool_result,
-the fix ensures tool_calls are added to the previous assistant message.
-"""
-
-import pytest
-import json
-from unittest.mock import patch, AsyncMock
-
-import litellm
-from litellm.responses.litellm_completion_transformation.transformation import (
-    LiteLLMCompletionResponsesConfig,
-    TOOL_CALLS_CACHE,
-)
-from litellm.llms.anthropic.chat.transformation import AnthropicConfig
-
-
-def test_fix_ensures_tool_calls_for_tool_results():
-    """
-    Test that the fix ensures tool_calls are added to assistant messages
-    when tool_results are present but tool_calls are missing.
-    """
-    shell_tool = {
-        "type": "function",
-        "function": {
-            "name": "shell",
-            "description": "Runs a shell command, and returns its output.",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "command": {"type": "array", "items": {"type": "string"}},
-                    "workdir": {
-                        "type": "string",
-                        "description": "The working directory for the command.",
-                    },
-                },
-                "required": ["command"],
-            },
-        },
-    }
-
-    tool_call_id = "toolu_0123456789abcdef"
-
-    # Cache the tool_call definition (simulating what happens when a response is returned)
-    TOOL_CALLS_CACHE.set_cache(
-        key=tool_call_id,
-        value={
-            "id": tool_call_id,
-            "type": "function",
-            "function": {
-                "name": "shell",
-                "arguments": '{"command": ["echo", "hello"]}',
-            },
-        },
-    )
-
-    # Simulate messages that would be reconstructed from spend logs
-    # The assistant message is missing tool_calls (the bug scenario)
-    messages_missing_tool_calls = [
-        {
-            "role": "user",
-            "content": [{"type": "text", "text": "make a hello world html file"}],
-        },
-        {
-            "role": "assistant",
-            "content": "I'll help you create that HTML file.",
-            # NOTE: Missing tool_calls here - this is the bug scenario
-        },
-        {
-            "role": "tool",
-            "content": '{"output":"<html>...</html>"}',
-            "tool_call_id": tool_call_id,
-        },
-    ]
-
-    # Apply the fix
-    fixed_messages = LiteLLMCompletionResponsesConfig._ensure_tool_results_have_corresponding_tool_calls(
-        messages=messages_missing_tool_calls, tools=[shell_tool]
-    )
-
-    # Verify the fix worked
-    assistant_message = None
-    for msg in fixed_messages:
-        if msg.get("role") == "assistant":
-            assistant_message = msg
-            break
-
-    assert assistant_message is not None, "Assistant message should be present"
-
-    # Check if tool_calls were added
-    tool_calls = assistant_message.get("tool_calls") or []
-    assert len(tool_calls) > 0, (
-        f"Fix should have added tool_calls to assistant message. "
-        f"Found: {json.dumps(assistant_message, indent=2)}"
-    )
-
-    # Verify the tool_call has the correct ID
-    found_tool_call = False
-    for tool_call in tool_calls:
-        tool_call_id_from_msg = (
-            tool_call.get("id")
-            if isinstance(tool_call, dict)
-            else getattr(tool_call, "id", None)
-        )
-        if tool_call_id_from_msg == tool_call_id:
-            found_tool_call = True
-            break
-
-    assert found_tool_call, (
-        f"Tool call with ID {tool_call_id} should be present in assistant message. "
-        f"Found tool_calls: {json.dumps(tool_calls, indent=2, default=str)}"
-    )
-
-    # Now verify the Anthropic transformation works
-    anthropic_config = AnthropicConfig()
-    optional_params = {"tools": [shell_tool]}
-
-    anthropic_data = anthropic_config.transform_request(
-        model="claude-sonnet-4-5",
-        messages=fixed_messages,
-        optional_params=optional_params,
-        litellm_params={},
-        headers={},
-    )
-
-    anthropic_messages = anthropic_data.get("messages", [])
-
-    # Find the assistant message in Anthropic format
-    anthropic_assistant_msg = None
-    for msg in anthropic_messages:
-        if msg.get("role") == "assistant":
-            anthropic_assistant_msg = msg
-            break
-
-    assert (
-        anthropic_assistant_msg is not None
-    ), "Assistant message should be present in Anthropic format"
-
-    # Verify the assistant message has tool_use blocks
-    assistant_content = anthropic_assistant_msg.get("content", [])
-    tool_use_blocks = [
-        block
-        for block in assistant_content
-        if isinstance(block, dict) and block.get("type") == "tool_use"
-    ]
-
-    assert len(tool_use_blocks) > 0, (
-        f"After fix, assistant message should have tool_use blocks. "
-        f"Found content: {json.dumps(assistant_content, indent=2)}"
-    )
-
-    # Verify the tool_use block has the correct ID
-    tool_use_id = tool_use_blocks[0].get("id")
-    assert (
-        tool_use_id == tool_call_id
-    ), f"Tool use ID {tool_use_id} should match tool_call_id {tool_call_id}"
-
-    print("\n" + "=" * 80)
-    print("[PASS] Fix verified: tool_calls are added when missing")
-    print("=" * 80)
-    print(f"  Tool use blocks: {len(tool_use_blocks)}")
-    print(f"  Tool use ID: {tool_use_id}")
-    print("\nThe fix ensures that when tool_results are present but tool_calls are")
-    print("missing from the assistant message, they are added from cache or tools.")
-
-
-if __name__ == "__main__":
-    test_fix_ensures_tool_calls_for_tool_results()

tests/llm_responses_api_testing/test_base_responses_api_streaming_iterator.py

@@ -1,683 +0,0 @@
-"""
-Unit tests for BaseResponsesAPIStreamingIterator
-
-Tests core functionality including:
-1. Processing chunks and handling ResponseCompletedEvent 
-2. Ensuring _update_responses_api_response_id_with_model_id is called for final chunk
-3. Verifying ID update is NOT called for non-final chunks (delta events)
-4. Edge case handling for invalid JSON, empty chunks, and [DONE] markers
-
-These tests ensure the streaming iterator correctly processes response chunks 
-and applies model ID updates only to completed responses, as required for proper
-response tracking and logging.
-"""
-
-import json
-from datetime import datetime
-from typing import Any, Dict, Optional
-from unittest.mock import Mock, patch
-
-import pytest
-
-
-from litellm.constants import STREAM_SSE_DONE_STRING
-from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
-from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator
-from litellm.responses.utils import ResponsesAPIRequestUtils
-from litellm.types.llms.openai import (
-    ResponseAPIUsage,
-    ResponseCompletedEvent,
-    ResponseFailedEvent,
-    ResponseIncompleteEvent,
-    ResponsesAPIResponse,
-    ResponsesAPIStreamEvents,
-    OutputTextDeltaEvent,
-)
-
-
-class TestBaseResponsesAPIStreamingIterator:
-    """Test cases for BaseResponsesAPIStreamingIterator"""
-
-    @pytest.mark.asyncio
-    async def test_responses_streaming_iterator_parses_u2028_in_sse_json(self):
-        """
-        U+2028 inside JSON must not split the SSE event. httpx aiter_lines uses
-        str.splitlines() and drops response.completed; OpenAI SSEDecoder does not.
-        """
-        from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator
-
-        u2028 = "\u2028"
-        payload = json.dumps(
-            {
-                "type": "response.completed",
-                "response": {"instructions": f"eligible{u2028}promo"},
-            }
-        )
-        sse_bytes = f"data: {payload}\n\n".encode("utf-8")
-
-        async def mock_aiter_bytes():
-            yield sse_bytes
-
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_response.aiter_bytes = mock_aiter_bytes
-
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        mock_responses_api_response = Mock(spec=ResponsesAPIResponse)
-        mock_responses_api_response.id = "resp_u2028"
-        mock_responses_api_response.usage = ResponseAPIUsage(input_tokens=3, output_tokens=2, total_tokens=5)
-        mock_completed_event = Mock(spec=ResponseCompletedEvent)
-        mock_completed_event.type = ResponsesAPIStreamEvents.RESPONSE_COMPLETED
-        mock_completed_event.response = mock_responses_api_response
-        mock_config.transform_streaming_response.return_value = mock_completed_event
-
-        iterator = ResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        chunks = []
-        with (
-            patch("asyncio.create_task"),
-            patch("litellm.responses.streaming_iterator.executor"),
-        ):
-            async for chunk in iterator:
-                chunks.append(chunk)
-
-        assert len(chunks) == 1
-        assert chunks[0].type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
-        assert iterator.completed_response is not None
-
-    def test_process_chunk_with_response_completed_event(self):
-        """
-        Test that _process_chunk correctly processes a ResponseCompletedEvent
-        and calls _update_responses_api_response_id_with_model_id for the final chunk.
-        """
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create a mock ResponsesAPIResponse for the completed event
-        mock_responses_api_response = Mock(spec=ResponsesAPIResponse)
-        mock_responses_api_response.id = "original_response_id"
-
-        # Create a mock ResponseCompletedEvent
-        mock_completed_event = Mock(spec=ResponseCompletedEvent)
-        mock_completed_event.type = ResponsesAPIStreamEvents.RESPONSE_COMPLETED
-        mock_completed_event.response = mock_responses_api_response
-
-        # Set up the mock transform method to return our completed event
-        mock_config.transform_streaming_response.return_value = mock_completed_event
-
-        # Mock the _update_responses_api_response_id_with_model_id method
-        updated_response = Mock(spec=ResponsesAPIResponse)
-        updated_response.id = "updated_response_id"
-        updated_response.usage = ResponseAPIUsage(input_tokens=3, output_tokens=2, total_tokens=5)
-
-        # Create the iterator instance
-        iterator = BaseResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        # Prepare test chunk data
-        test_chunk_data = {
-            "type": "response.completed",
-            "response": {
-                "id": "original_response_id",
-                "output": [{"type": "message", "content": [{"text": "Hello World"}]}],
-            },
-        }
-
-        with patch.object(
-            ResponsesAPIRequestUtils,
-            "update_responses_api_response_id_with_model_id",
-            return_value=updated_response,
-        ) as mock_update_id:
-            # Process the chunk
-            result = iterator._process_chunk(json.dumps(test_chunk_data))
-
-            # Assertions
-            assert result is not None
-            assert result.type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
-
-            # Verify that _update_responses_api_response_id_with_model_id was called
-            mock_update_id.assert_called_once_with(
-                responses_api_response=mock_responses_api_response,
-                litellm_metadata={"model_info": {"id": "model_123"}},
-                custom_llm_provider="openai",
-            )
-
-            # Verify the completed response was stored
-            assert iterator.completed_response == result
-
-            # Verify the response was updated on the event
-            assert result.response == updated_response
-
-    def test_process_chunk_with_delta_event_no_id_update(self):
-        """
-        Test that _process_chunk correctly processes a delta event
-        and does NOT call _update_responses_api_response_id_with_model_id.
-        """
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create a mock OutputTextDeltaEvent (not a completed event)
-        mock_delta_event = Mock(spec=OutputTextDeltaEvent)
-        mock_delta_event.type = ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA
-        mock_delta_event.delta = "Hello"
-        # Delta events don't have a response attribute
-        (
-            delattr(mock_delta_event, "response")
-            if hasattr(mock_delta_event, "response")
-            else None
-        )
-
-        # Set up the mock transform method to return our delta event
-        mock_config.transform_streaming_response.return_value = mock_delta_event
-
-        # Create the iterator instance
-        iterator = BaseResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        # Prepare test chunk data for a delta event
-        test_chunk_data = {
-            "type": "response.output_text.delta",
-            "delta": "Hello",
-            "item_id": "item_123",
-            "output_index": 0,
-            "content_index": 0,
-        }
-
-        with patch.object(
-            ResponsesAPIRequestUtils, "update_responses_api_response_id_with_model_id"
-        ) as mock_update_id:
-            # Process the chunk
-            result = iterator._process_chunk(json.dumps(test_chunk_data))
-
-            # Assertions
-            assert result is not None
-            assert result.type == ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA
-
-            # Verify that _update_responses_api_response_id_with_model_id was NOT called
-            mock_update_id.assert_not_called()
-
-            # Verify no completed response was stored (since this is not a completed event)
-            assert iterator.completed_response is None
-
-    def test_process_chunk_handles_invalid_json(self):
-        """
-        Test that _process_chunk gracefully handles invalid JSON.
-        """
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create the iterator instance
-        iterator = BaseResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-        )
-
-        # Test with invalid JSON
-        result = iterator._process_chunk("invalid json {")
-
-        # Should return None for invalid JSON
-        assert result is None
-        assert iterator.completed_response is None
-
-    def test_process_chunk_handles_done_marker(self):
-        """
-        Test that _process_chunk correctly handles the [DONE] marker.
-        """
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create the iterator instance
-        iterator = BaseResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-        )
-
-        # Test with [DONE] marker
-        result = iterator._process_chunk(STREAM_SSE_DONE_STRING)
-
-        # Should return None and set finished flag
-        assert result is None
-        assert iterator.finished is True
-
-    def test_process_chunk_handles_empty_chunk(self):
-        """
-        Test that _process_chunk correctly handles empty or None chunks.
-        """
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create the iterator instance
-        iterator = BaseResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-        )
-
-        # Test with empty chunk
-        result = iterator._process_chunk("")
-        assert result is None
-
-        # Test with None chunk
-        result = iterator._process_chunk(None)
-        assert result is None
-
-    def test_handle_logging_completed_response_with_unpickleable_objects(self):
-        """
-        Test that _handle_logging_completed_response handles responses containing
-        objects that cannot be pickled (like Pydantic ValidatorIterator).
-
-        This test verifies the fix for issue #17192 where streaming with tool_choice
-        containing allowed_tools would fail with:
-        "cannot pickle 'pydantic_core._pydantic_core.ValidatorIterator' object"
-
-        The fix uses model_dump + model_validate instead of copy.deepcopy.
-        """
-        import asyncio
-        from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator
-
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_response.aiter_bytes = Mock()
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_logging_obj.async_success_handler = Mock()
-        mock_logging_obj.success_handler = Mock()
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        # Create the iterator instance
-        iterator = ResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        # Create a ResponseCompletedEvent with tool_choice that has model_dump
-        mock_completed_response = Mock()
-        mock_completed_response.model_dump.return_value = {
-            "type": "response.completed",
-            "response": {
-                "id": "resp_123",
-                "output": [{"type": "function_call", "name": "search_web"}],
-                "tool_choice": {"type": "function", "name": "search_web"},
-            },
-        }
-        # model_validate should return a new mock (the copy)
-        type(mock_completed_response).model_validate = Mock(return_value=Mock())
-
-        iterator.completed_response = mock_completed_response
-
-        # This should NOT raise an exception
-        # Previously it would fail with: TypeError: cannot pickle 'ValidatorIterator'
-        # Mock asyncio.create_task and executor.submit since we're not in async context
-        with (
-            patch("asyncio.create_task") as mock_create_task,
-            patch("litellm.responses.streaming_iterator.executor") as mock_executor,
-        ):
-            try:
-                iterator._handle_logging_completed_response()
-            except TypeError as e:
-                if "pickle" in str(e):
-                    pytest.fail(
-                        f"_handle_logging_completed_response failed with pickle error: {e}"
-                    )
-                raise
-
-    @staticmethod
-    def _config_completing_after_one_delta() -> Mock:
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-        completed_response = ResponsesAPIResponse(
-            id="resp_123",
-            created_at=0,
-            status="completed",
-            model="gpt-5.5",
-            object="response",
-            output=[],
-            usage=ResponseAPIUsage(input_tokens=1, output_tokens=1, total_tokens=2),
-        )
-
-        def _transform(model, parsed_chunk, logging_obj):
-            if parsed_chunk.get("type") == "response.completed":
-                return ResponseCompletedEvent(
-                    type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
-                    response=completed_response,
-                )
-            return OutputTextDeltaEvent(
-                type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA,
-                item_id="msg_123",
-                output_index=0,
-                content_index=0,
-                delta=parsed_chunk["delta"],
-            )
-
-        mock_config.transform_streaming_response.side_effect = _transform
-        return mock_config
-
-    @pytest.mark.asyncio
-    async def test_stop_async_iteration_not_logged_as_failure(self):
-        """
-        Test that StopAsyncIteration is NOT logged as a failure.
-
-        This test verifies that when streaming completes normally with StopAsyncIteration,
-        the _handle_failure method is NOT called, preventing false error logs in Langfuse
-        and other logging integrations.
-
-        """
-        from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator
-
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-
-        async def mock_aiter_bytes():
-            yield b'data: {"type": "response.output_text.delta", "delta": "test"}\n\n'
-            yield b'data: {"type": "response.completed", "response": {"id": "resp_123"}}\n\n'
-
-        mock_response.aiter_bytes = mock_aiter_bytes
-
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_logging_obj.async_failure_handler = Mock()
-        mock_logging_obj.failure_handler = Mock()
-
-        mock_config = self._config_completing_after_one_delta()
-
-        # Create the iterator instance
-        iterator = ResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        # Consume the iterator until StopAsyncIteration
-        chunks_received = []
-        try:
-            async for chunk in iterator:
-                chunks_received.append(chunk)
-        except StopAsyncIteration:
-            pass  # This is expected
-
-        # Verify we got the delta and the terminal event
-        assert len(chunks_received) == 2
-        assert iterator.completed_response is not None
-
-        # CRITICAL: Verify that failure handlers were NOT called
-        # StopAsyncIteration is a normal end of stream, not a failure
-        mock_logging_obj.async_failure_handler.assert_not_called()
-        mock_logging_obj.failure_handler.assert_not_called()
-
-    def test_stop_iteration_not_logged_as_failure(self):
-        """
-        Test that StopIteration is NOT logged as a failure in sync iterator.
-
-        This test verifies that when streaming completes normally with StopIteration,
-        the _handle_failure method is NOT called, preventing false error logs in Langfuse
-        and other logging integrations.
-
-        Regression test for: https://github.com/BerriAI/litellm/issues/XXXXX
-        """
-        from litellm.responses.streaming_iterator import (
-            SyncResponsesAPIStreamingIterator,
-        )
-
-        # Mock dependencies
-        mock_response = Mock()
-        mock_response.headers = {}
-
-        def mock_iter_bytes():
-            yield b'data: {"type": "response.output_text.delta", "delta": "test"}\n\n'
-            yield b'data: {"type": "response.completed", "response": {"id": "resp_123"}}\n\n'
-
-        mock_response.iter_bytes = mock_iter_bytes
-
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_logging_obj.async_failure_handler = Mock()
-        mock_logging_obj.failure_handler = Mock()
-
-        mock_config = self._config_completing_after_one_delta()
-
-        # Create the iterator instance
-        iterator = SyncResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        # Consume the iterator until StopIteration
-        chunks_received = []
-        try:
-            for chunk in iterator:
-                chunks_received.append(chunk)
-        except StopIteration:
-            pass  # This is expected
-
-        # Verify we got the delta and the terminal event
-        assert len(chunks_received) == 2
-        assert iterator.completed_response is not None
-
-        # CRITICAL: Verify that failure handlers were NOT called
-        # StopIteration is a normal end of stream, not a failure
-        mock_logging_obj.async_failure_handler.assert_not_called()
-        mock_logging_obj.failure_handler.assert_not_called()
-
-    def test_process_chunk_response_failed_calls_failure_handler(self):
-        """
-        Test that a RESPONSE_FAILED event routes to failure handlers,
-        not success handlers. Failed responses represent genuine LLM-level
-        errors and should be logged as failures.
-        """
-        from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator
-
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_response.aiter_bytes = Mock()
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_logging_obj.async_failure_handler = Mock()
-        mock_logging_obj.failure_handler = Mock()
-        mock_logging_obj.async_success_handler = Mock()
-        mock_logging_obj.success_handler = Mock()
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        mock_responses_api_response = Mock(spec=ResponsesAPIResponse)
-        mock_responses_api_response.id = "resp_failed_123"
-        mock_responses_api_response.error = {
-            "type": "server_error",
-            "message": "The model encountered an error",
-        }
-        mock_responses_api_response.usage = ResponseAPIUsage(input_tokens=3, output_tokens=2, total_tokens=5)
-
-        mock_failed_event = Mock(spec=ResponseFailedEvent)
-        mock_failed_event.type = ResponsesAPIStreamEvents.RESPONSE_FAILED
-        mock_failed_event.response = mock_responses_api_response
-
-        mock_config.transform_streaming_response.return_value = mock_failed_event
-
-        iterator = ResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        test_chunk_data = {
-            "type": "response.failed",
-            "response": {
-                "id": "resp_failed_123",
-                "error": {
-                    "type": "server_error",
-                    "message": "The model encountered an error",
-                },
-            },
-        }
-
-        with (
-            patch.object(
-                ResponsesAPIRequestUtils,
-                "update_responses_api_response_id_with_model_id",
-                return_value=mock_responses_api_response,
-            ),
-            patch(
-                "litellm.responses.streaming_iterator.run_async_function"
-            ) as mock_run_async,
-            patch("litellm.responses.streaming_iterator.executor") as mock_executor,
-        ):
-            result = iterator._process_chunk(json.dumps(test_chunk_data))
-
-            assert result is not None
-            assert result.type == ResponsesAPIStreamEvents.RESPONSE_FAILED
-            assert iterator.completed_response == result
-
-            # Failure handler should have been called via _handle_failure
-            mock_run_async.assert_called_once()
-            call_kwargs = mock_run_async.call_args
-            assert (
-                call_kwargs[1]["async_function"]
-                == mock_logging_obj.async_failure_handler
-            )
-
-            mock_executor.submit.assert_called_once()
-            submit_args = mock_executor.submit.call_args
-            assert submit_args[0][0] == mock_logging_obj.failure_handler
-
-    def test_process_chunk_response_incomplete_calls_success_handler(self):
-        """
-        Test that a RESPONSE_INCOMPLETE event routes to success handlers.
-        Incomplete responses (e.g. max_output_tokens reached) are still valid
-        responses with usage data — analogous to finish_reason='length' in chat.
-        """
-        from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator
-
-        mock_response = Mock()
-        mock_response.headers = {}
-        mock_response.aiter_bytes = Mock()
-        mock_logging_obj = Mock(spec=LiteLLMLoggingObj)
-        mock_logging_obj.model_call_details = {"litellm_params": {}}
-        mock_logging_obj.completion_start_time = None
-        mock_logging_obj.async_failure_handler = Mock()
-        mock_logging_obj.failure_handler = Mock()
-        mock_logging_obj.async_success_handler = Mock()
-        mock_logging_obj.success_handler = Mock()
-        mock_config = Mock(spec=BaseResponsesAPIConfig)
-
-        mock_responses_api_response = Mock(spec=ResponsesAPIResponse)
-        mock_responses_api_response.id = "resp_incomplete_123"
-        mock_responses_api_response.incomplete_details = {"reason": "max_output_tokens"}
-        mock_responses_api_response.usage = ResponseAPIUsage(input_tokens=3, output_tokens=2, total_tokens=5)
-
-        mock_incomplete_event = Mock(spec=ResponseIncompleteEvent)
-        mock_incomplete_event.type = ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE
-        mock_incomplete_event.response = mock_responses_api_response
-
-        mock_config.transform_streaming_response.return_value = mock_incomplete_event
-
-        iterator = ResponsesAPIStreamingIterator(
-            response=mock_response,
-            model="gpt-5.5",
-            responses_api_provider_config=mock_config,
-            logging_obj=mock_logging_obj,
-            litellm_metadata={"model_info": {"id": "model_123"}},
-            custom_llm_provider="openai",
-        )
-
-        test_chunk_data = {
-            "type": "response.incomplete",
-            "response": {
-                "id": "resp_incomplete_123",
-                "incomplete_details": {"reason": "max_output_tokens"},
-            },
-        }
-
-        with (
-            patch.object(
-                ResponsesAPIRequestUtils,
-                "update_responses_api_response_id_with_model_id",
-                return_value=mock_responses_api_response,
-            ),
-            patch("asyncio.create_task") as mock_create_task,
-            patch("litellm.responses.streaming_iterator.executor") as mock_executor,
-        ):
-            result = iterator._process_chunk(json.dumps(test_chunk_data))
-
-            assert result is not None
-            assert result.type == ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE
-            assert iterator.completed_response == result
-
-            # Success handlers are dispatched as one async task (via _handle_logging_completed_response);
-            # the sync handler must never be submitted to the executor concurrently (LIT-4210)
-            mock_create_task.assert_called_once()
-            mock_executor.submit.assert_not_called()
-
-            # Failure handlers should NOT have been called
-            mock_logging_obj.async_failure_handler.assert_not_called()
-            mock_logging_obj.failure_handler.assert_not_called()

tests/llm_translation/interactions/test_google_interactions_integration.py

@@ -11,12 +11,11 @@ Run with: pytest tests/llm_translation/interactions/test_google_interactions_int
 import asyncio
 import os
 
+import openai
 import pytest
 
-
 import litellm
 import litellm.interactions as interactions
-import openai
 
 # Test API key - should be set in environment
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
@@ -166,63 +165,12 @@ class TestGoogleInteractionsMultiTurn:
 class TestGoogleInteractionsAgent:
     """Tests for agent interactions (per OpenAPI spec)."""
 
-    @pytest.mark.skip(reason="Deep research agent may not be available in all accounts")
-    def test_create_agent_interaction(self, api_key):
-        """Test creating an agent interaction per OpenAPI spec."""
-        response = interactions.create(
-            agent="deep-research-pro-preview-12-2025",
-            input="Research the current state of quantum computing",
-            api_key=api_key,
-        )
-
-        assert response is not None
-        print(f"Agent response: {response}")
 
 
 class TestGoogleInteractionsGetDelete:
     """Tests for get and delete operations."""
 
-    @pytest.mark.skip(
-        reason="Get/Delete require valid interaction IDs from previous calls"
-    )
-    def test_get_interaction(self, api_key):
-        """Test getting an interaction by ID."""
-        # First create an interaction
-        create_response = interactions.create(
-            model="gemini/gemini-2.5-flash",
-            input="Hello",
-            api_key=api_key,
-        )
 
-        if create_response.id:
-            # Then get it
-            get_response = interactions.get(
-                interaction_id=create_response.id,
-                api_key=api_key,
-            )
-            assert get_response is not None
-            print(f"Get response: {get_response}")
-
-    @pytest.mark.skip(
-        reason="Get/Delete require valid interaction IDs from previous calls"
-    )
-    def test_delete_interaction(self, api_key):
-        """Test deleting an interaction by ID."""
-        # First create an interaction
-        create_response = interactions.create(
-            model="gemini/gemini-2.5-flash",
-            input="Hello",
-            api_key=api_key,
-        )
-
-        if create_response.id:
-            # Then delete it
-            delete_result = interactions.delete(
-                interaction_id=create_response.id,
-                api_key=api_key,
-            )
-            assert delete_result.success is True
-            print(f"Delete result: {delete_result}")
 
 
 class TestGoogleInteractionsErrorHandling:

tests/llm_translation/test_aws_base_llm.py

@@ -1,182 +0,0 @@
-import pytest
-import os
-from datetime import datetime, timezone
-from unittest.mock import MagicMock, patch
-from botocore.credentials import Credentials
-from typing import Dict, Any
-from litellm.llms.bedrock.base_aws_llm import (
-    BaseAWSLLM,
-    AwsAuthError,
-    Boto3CredentialsInfo,
-)
-
-
-# Test fixtures
-@pytest.fixture
-def base_aws_llm():
-    return BaseAWSLLM()
-
-
-@pytest.fixture
-def mock_credentials():
-    return Credentials(
-        access_key="test_access", secret_key="test_secret", token="test_token"
-    )
-
-
-# Test cache key generation
-def test_get_cache_key(base_aws_llm):
-    test_args = {
-        "aws_access_key_id": "test_key",
-        "aws_secret_access_key": "test_secret",
-    }
-    cache_key = base_aws_llm.get_cache_key(test_args)
-    assert isinstance(cache_key, str)
-    assert len(cache_key) == 64  # SHA-256 produces 64 character hex string
-
-
-# Test web identity token authentication
-@patch("boto3.client")
-@patch("litellm.llms.bedrock.base_aws_llm.get_secret")  # Add this patch
-def test_auth_with_web_identity_token(mock_get_secret, mock_boto3_client, base_aws_llm):
-    # Mock get_secret to return a token
-    mock_get_secret.return_value = "mocked_oidc_token"
-
-    # Mock the STS client and response
-    mock_sts = MagicMock()
-    mock_sts.assume_role_with_web_identity.return_value = {
-        "Credentials": {
-            "AccessKeyId": "test_access",
-            "SecretAccessKey": "test_secret",
-            "SessionToken": "test_token",
-        },
-        "PackedPolicySize": 10,
-    }
-    mock_boto3_client.return_value = mock_sts
-
-    credentials, ttl = base_aws_llm._auth_with_web_identity_token(
-        aws_web_identity_token="test_token",
-        aws_role_name="test_role",
-        aws_session_name="test_session",
-        aws_region_name="us-west-2",
-        aws_sts_endpoint=None,
-    )
-
-    # Verify get_secret was called with the correct argument
-    mock_get_secret.assert_called_once_with("test_token")
-
-    assert isinstance(credentials, Credentials)
-    assert ttl == 3540  # default TTL (3600 - 60)
-
-
-# Test AWS role authentication
-@patch("boto3.client")
-def test_auth_with_aws_role(mock_boto3_client, base_aws_llm):
-    # Mock the STS client and response
-    mock_sts = MagicMock()
-    expiry_time = datetime.now(timezone.utc)
-    mock_sts.assume_role.return_value = {
-        "Credentials": {
-            "AccessKeyId": "test_access",
-            "SecretAccessKey": "test_secret",
-            "SessionToken": "test_token",
-            "Expiration": expiry_time,
-        }
-    }
-    mock_boto3_client.return_value = mock_sts
-
-    credentials, ttl = base_aws_llm._auth_with_aws_role(
-        aws_access_key_id="test_access",
-        aws_secret_access_key="test_secret",
-        aws_session_token="test_token",
-        aws_role_name="test_role",
-        aws_session_name="test_session",
-    )
-
-    assert isinstance(credentials, Credentials)
-    assert isinstance(ttl, float)
-
-
-# Test AWS profile authentication
-@patch("boto3.Session")
-def test_auth_with_aws_profile(mock_session, base_aws_llm, mock_credentials):
-    # Mock the session
-    mock_session_instance = MagicMock()
-    mock_session_instance.get_credentials.return_value = mock_credentials
-    mock_session.return_value = mock_session_instance
-
-    credentials, ttl = base_aws_llm._auth_with_aws_profile("test_profile")
-
-    assert credentials == mock_credentials
-    assert ttl is None
-
-
-# Test session token authentication
-def test_auth_with_aws_session_token(base_aws_llm):
-    credentials, ttl = base_aws_llm._auth_with_aws_session_token(
-        aws_access_key_id="test_access",
-        aws_secret_access_key="test_secret",
-        aws_session_token="test_token",
-    )
-
-    assert isinstance(credentials, Credentials)
-    assert credentials.access_key == "test_access"
-    assert credentials.secret_key == "test_secret"
-    assert credentials.token == "test_token"
-    assert ttl is None
-
-
-# Test access key and secret key authentication
-@patch("boto3.Session")
-def test_auth_with_access_key_and_secret_key(
-    mock_session, base_aws_llm, mock_credentials
-):
-    # Mock the session
-    mock_session_instance = MagicMock()
-    mock_session_instance.get_credentials.return_value = mock_credentials
-    mock_session.return_value = mock_session_instance
-
-    credentials, ttl = base_aws_llm._auth_with_access_key_and_secret_key(
-        aws_access_key_id="test_access",
-        aws_secret_access_key="test_secret",
-        aws_region_name="us-west-2",
-    )
-
-    assert credentials == mock_credentials
-    assert ttl == 3540  # default TTL (3600 - 60)
-
-
-# Test environment variables authentication
-@patch("boto3.Session")
-def test_auth_with_env_vars(mock_session, base_aws_llm, mock_credentials):
-    # Mock the session
-    mock_session_instance = MagicMock()
-    mock_session_instance.get_credentials.return_value = mock_credentials
-    mock_session.return_value = mock_session_instance
-
-    credentials, ttl = base_aws_llm._auth_with_env_vars()
-
-    assert credentials == mock_credentials
-    assert ttl is None
-
-
-# Test runtime endpoint resolution
-def test_get_runtime_endpoint(base_aws_llm):
-    endpoint_url, proxy_endpoint_url = base_aws_llm.get_runtime_endpoint(
-        api_base=None, aws_bedrock_runtime_endpoint=None, aws_region_name="us-west-2"
-    )
-    assert endpoint_url == "https://bedrock-runtime.us-west-2.amazonaws.com"
-    assert proxy_endpoint_url == "https://bedrock-runtime.us-west-2.amazonaws.com"
-
-    endpoint_url, proxy_endpoint_url = base_aws_llm.get_runtime_endpoint(
-        aws_bedrock_runtime_endpoint=None, aws_region_name="us-east-1", api_base=None
-    )
-    assert endpoint_url == "https://bedrock-runtime.us-east-1.amazonaws.com"
-    assert proxy_endpoint_url == "https://bedrock-runtime.us-east-1.amazonaws.com"
-
-
-@pytest.fixture
-def clear_cache(base_aws_llm):
-    """Clear the cache before each test"""
-    base_aws_llm.iam_cache.in_memory_cache.cache_dict = {}
-    yield

tests/llm_translation/test_bedrock_agents.py

@@ -1,86 +0,0 @@
-import traceback
-
-from dotenv import load_dotenv
-
-import litellm.types
-
-load_dotenv()
-import io
-import json
-
-from unittest.mock import AsyncMock, Mock, patch
-
-import pytest
-
-
-@pytest.mark.asyncio
-@pytest.mark.skip(reason="Skipping bedrock agents test - arn not working")
-async def test_bedrock_agents():
-    litellm.turn_on_debug()
-    response = litellm.completion(
-        model="bedrock/agent/L1RT58GYRW/MFPSBCXYTW",
-        messages=[{"role": "user", "content": "Hi just respond with a ping message"}],
-    )
-
-    #########################################################
-    #########################################################
-    print("response from agent=", response.model_dump_json(indent=4))
-
-    # assert that the message content has a response with some length
-    assert len(response.choices[0].message.content) > 0
-
-    # assert we were able to get the response cost
-    assert (
-        response._hidden_params["response_cost"] is not None
-        and response._hidden_params["response_cost"] > 0
-    )
-
-    pass
-
-
-@pytest.mark.asyncio
-@pytest.mark.skip(reason="Skipping bedrock agents test - arn not working")
-async def test_bedrock_agents_with_streaming():
-    # litellm.turn_on_debug()
-    response = litellm.completion(
-        model="bedrock/agent/L1RT58GYRW/MFPSBCXYTW",
-        messages=[
-            {
-                "role": "user",
-                "content": "Hi who is ishaan cto of litellm, tell me 10 things about him",
-            }
-        ],
-        stream=True,
-    )
-
-    for chunk in response:
-        print("final chunk=", chunk)
-
-    pass
-
-
-def test_bedrock_agents_with_custom_params():
-    litellm.turn_on_debug()
-    from unittest.mock import MagicMock
-    from litellm.llms.custom_httpx.http_handler import HTTPHandler
-
-    client = HTTPHandler()
-
-    with patch.object(client, "post", return_value=MagicMock()) as mock_post:
-        try:
-            response = litellm.completion(
-                model="bedrock/agent/L1RT58GYRW/MFPSBCXYTW",
-                messages=[
-                    {
-                        "role": "user",
-                        "content": "Hi who is ishaan cto of litellm, tell me 10 things about him",
-                    }
-                ],
-                invocationId="my-test-invocation-id",
-                client=client,
-            )
-        except Exception as e:
-            print(f"Error: {e}")
-
-        mock_post.assert_called_once()
-        print(f"mock_post.call_args.kwargs: {mock_post.call_args.kwargs}")

tests/llm_translation/test_bedrock_anthropic_regression.py

@@ -1,538 +0,0 @@
-"""
-Regression tests for Bedrock Anthropic models.
-
-Tests critical functionality that has broken in the past between bedrock/invoke
-and bedrock/converse routing:
-1. Prompt caching support (cache_control)
-2. 1M context window support (anthropic-beta header)
-
-These tests ensure that both routing methods (invoke vs converse) maintain
-feature parity and prevent regression of previously fixed issues.
-"""
-
-import json
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-
-import litellm
-from litellm import completion
-
-
-# Large document for caching tests (needs 1024+ tokens for Claude models)
-LARGE_DOCUMENT_FOR_CACHING = (
-    """
-This is a comprehensive legal agreement between Party A and Party B.
-
-ARTICLE 1: DEFINITIONS
-1.1 "Agreement" means this document and all attachments.
-1.2 "Confidential Information" means any non-public information.
-1.3 "Effective Date" means the date of last signature.
-1.4 "Term" means the period during which this Agreement is in effect.
-
-ARTICLE 2: SCOPE OF SERVICES
-2.1 Party A agrees to provide the following services...
-2.2 Party B agrees to compensate Party A for services rendered...
-2.3 All services shall be performed in a professional manner...
-
-ARTICLE 3: PAYMENT TERMS
-3.1 Payment shall be made within 30 days of invoice receipt.
-3.2 Late payments shall accrue interest at 1.5% per month.
-3.3 All fees are non-refundable unless otherwise specified.
-
-ARTICLE 4: INTELLECTUAL PROPERTY
-4.1 All pre-existing IP remains with the original owner.
-4.2 Work product created under this Agreement shall be owned by Party B.
-4.3 Party A grants a license to use any tools or methodologies.
-
-ARTICLE 5: CONFIDENTIALITY
-5.1 Both parties agree to maintain confidentiality of all shared information.
-5.2 Confidential information shall not be disclosed to third parties.
-5.3 This obligation survives termination of the Agreement.
-
-ARTICLE 6: TERMINATION
-6.1 Either party may terminate with 30 days written notice.
-6.2 Immediate termination is permitted for material breach.
-6.3 Upon termination, all confidential information must be returned.
-
-ARTICLE 7: LIMITATION OF LIABILITY
-7.1 Neither party shall be liable for consequential damages.
-7.2 Total liability shall not exceed fees paid in the prior 12 months.
-7.3 This limitation does not apply to willful misconduct.
-
-ARTICLE 8: DISPUTE RESOLUTION
-8.1 Disputes shall first be addressed through good faith negotiation.
-8.2 If negotiation fails, disputes shall be submitted to arbitration.
-8.3 Arbitration shall be conducted under AAA rules.
-
-ARTICLE 9: GENERAL PROVISIONS
-9.1 This Agreement constitutes the entire understanding between parties.
-9.2 Amendments must be in writing and signed by both parties.
-9.3 This Agreement shall be governed by the laws of Delaware.
-9.4 Neither party may assign this Agreement without consent.
-9.5 Waiver of any provision shall not constitute ongoing waiver.
-
-IN WITNESS WHEREOF, the parties have executed this Agreement.
-"""
-    * 8
-)  # Repeat to ensure we have enough tokens (need 1024+ for Claude models)
-
-
-class TestBedrockAnthropicPromptCachingRegression:
-    """
-    Regression tests for prompt caching support across bedrock/invoke and bedrock/converse.
-
-    Issue: Prompt caching broke between invoke and converse routing due to:
-    - Different cache_control syntax expectations
-    - Incorrect beta header handling
-    - Missing transformation for cachePoint vs cache_control
-    """
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_prompt_caching_cache_control_transforms_correctly(self, model_prefix):
-        """
-        Test that cache_control in messages is correctly transformed for both invoke and converse APIs.
-
-        Regression test: Ensure cache_control works the same way for both routing methods.
-        - bedrock/invoke uses cache_control directly in the Anthropic Messages API format
-        - bedrock/converse should transform to cachePoint format
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": LARGE_DOCUMENT_FOR_CACHING,
-                        "cache_control": {"type": "ephemeral"},
-                    },
-                    {
-                        "type": "text",
-                        "text": "What are the payment terms?",
-                    },
-                ],
-            },
-        ]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers={},
-            )
-
-            print(
-                f"\n{model_prefix} Request body: {json.dumps(result, indent=2, default=str)}"
-            )
-
-            # For converse, cache_control should be transformed to cachePoint
-            assert "messages" in result
-            user_msg = result["messages"][0]
-            assert "content" in user_msg
-
-            # Check that cachePoint is present (Bedrock Converse format)
-            has_cache_point = any(
-                isinstance(c, dict) and "cachePoint" in c for c in user_msg["content"]
-            )
-            # The transformation should preserve the cache marking in some form
-            assert (
-                "messages" in result
-            ), "messages should be present in converse request"
-
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers={},
-            )
-
-            print(
-                f"\n{model_prefix} Request body: {json.dumps(result, indent=2, default=str)}"
-            )
-
-            # For invoke, cache_control should be preserved in messages content
-            assert "messages" in result
-            user_msg = result["messages"][0]
-            assert "content" in user_msg
-
-            # Check that cache_control is preserved
-            has_cache_control = any(
-                isinstance(c, dict) and "cache_control" in c
-                for c in user_msg["content"]
-            )
-            assert (
-                has_cache_control
-            ), "cache_control should be present in invoke messages"
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_prompt_caching_no_beta_header_added(self, model_prefix):
-        """
-        Test that prompt-caching-2024-07-31 beta header is NOT added for Bedrock.
-
-        Regression test: Bedrock recognizes prompt caching via cache_control in the
-        request body, NOT through beta headers. Adding the beta header breaks requests.
-
-        This was a critical bug where litellm was incorrectly adding the Anthropic API
-        beta header to Bedrock requests.
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": "Hello",
-                        "cache_control": {"type": "ephemeral"},
-                    }
-                ],
-            }
-        ]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config._transform_request_helper(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                system_content_blocks=[],
-                optional_params={},
-                messages=messages,
-                headers={},
-            )
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers={},
-            )
-
-        # Verify prompt-caching beta header is NOT present
-        if "anthropic_beta" in result:
-            assert "prompt-caching-2024-07-31" not in result["anthropic_beta"], (
-                f"{model_prefix}: prompt-caching-2024-07-31 should NOT be added as a beta header for Bedrock. "
-                "Bedrock recognizes prompt caching via cache_control in the request body, not beta headers."
-            )
-
-        # For converse, also check additionalModelRequestFields
-        if "converse" in model_prefix and "additionalModelRequestFields" in result:
-            additional_fields = result["additionalModelRequestFields"]
-            if "anthropic_beta" in additional_fields:
-                assert (
-                    "prompt-caching-2024-07-31"
-                    not in additional_fields["anthropic_beta"]
-                )
-
-
-class TestBedrockAnthropic1MContextRegression:
-    """
-    Regression tests for 1M context window support across bedrock/invoke and bedrock/converse.
-
-    Issue: 1M context support broke between invoke and converse routing due to:
-    - Missing anthropic-beta header passthrough in converse
-    - Incorrect handling of context-1m-2025-08-07 beta header
-    """
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_1m_context_beta_header_is_passed_via_transformation(self, model_prefix):
-        """
-        Test that the 1M context beta header is correctly passed to Bedrock API.
-
-        Regression test: Ensure anthropic-beta: context-1m-2025-08-07 header
-        is correctly included in the request for both invoke and converse.
-
-        This test verifies the transformation layer directly to avoid async complexity.
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        headers = {"anthropic-beta": "context-1m-2025-08-07"}
-        messages = [{"role": "user", "content": "Test message"}]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config._transform_request_helper(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                system_content_blocks=[],
-                optional_params={},
-                messages=messages,
-                headers=headers,
-            )
-
-            print(
-                f"\n{model_prefix} Request body: {json.dumps(result, indent=2, default=str)}"
-            )
-
-            # For converse, beta header should be in additionalModelRequestFields
-            assert (
-                "additionalModelRequestFields" in result
-            ), f"{model_prefix}: additionalModelRequestFields should be present for anthropic-beta headers"
-            additional_fields = result["additionalModelRequestFields"]
-            assert (
-                "anthropic_beta" in additional_fields
-            ), f"{model_prefix}: anthropic_beta should be in additionalModelRequestFields"
-            assert (
-                "context-1m-2025-08-07" in additional_fields["anthropic_beta"]
-            ), f"{model_prefix}: context-1m-2025-08-07 should be in anthropic_beta array"
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers=headers,
-            )
-
-            print(
-                f"\n{model_prefix} Request body: {json.dumps(result, indent=2, default=str)}"
-            )
-
-            # For invoke, beta header should be in top-level request
-            assert (
-                "anthropic_beta" in result
-            ), f"{model_prefix}: anthropic_beta should be in request body"
-            assert (
-                "context-1m-2025-08-07" in result["anthropic_beta"]
-            ), f"{model_prefix}: context-1m-2025-08-07 should be in anthropic_beta array"
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_1m_context_beta_header_transformation(self, model_prefix):
-        """
-        Test that the 1M context beta header is correctly transformed at the config level.
-
-        This is a unit test that verifies the transformation logic directly without
-        making actual API calls.
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        headers = {"anthropic-beta": "context-1m-2025-08-07"}
-        messages = [{"role": "user", "content": "Test"}]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config._transform_request_helper(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                system_content_blocks=[],
-                optional_params={},
-                messages=messages,
-                headers=headers,
-            )
-
-            # Verify beta header is in additionalModelRequestFields
-            assert "additionalModelRequestFields" in result
-            additional_fields = result["additionalModelRequestFields"]
-            assert "anthropic_beta" in additional_fields
-            assert "context-1m-2025-08-07" in additional_fields["anthropic_beta"]
-
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers=headers,
-            )
-
-            # Verify beta header is in top-level request
-            assert "anthropic_beta" in result
-            assert "context-1m-2025-08-07" in result["anthropic_beta"]
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_1m_context_with_multiple_beta_headers(self, model_prefix):
-        """
-        Test that 1M context header works alongside other beta headers.
-
-        Ensures that multiple anthropic-beta values (comma-separated) are all
-        correctly passed through.
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        # Multiple beta headers including 1M context
-        headers = {"anthropic-beta": "context-1m-2025-08-07,computer-use-2024-10-22"}
-        messages = [{"role": "user", "content": "Test"}]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config._transform_request_helper(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                system_content_blocks=[],
-                optional_params={},
-                messages=messages,
-                headers=headers,
-            )
-
-            additional_fields = result["additionalModelRequestFields"]
-            beta_headers = additional_fields["anthropic_beta"]
-
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers=headers,
-            )
-
-            beta_headers = result["anthropic_beta"]
-
-        # Verify both headers are present
-        assert "context-1m-2025-08-07" in beta_headers
-        assert "computer-use-2024-10-22" in beta_headers
-
-
-class TestBedrockAnthropicCombinedRegressions:
-    """
-    Tests that combine multiple features to ensure they work together.
-    """
-
-    @pytest.mark.parametrize(
-        "model_prefix",
-        [
-            "bedrock/invoke/",
-            "bedrock/converse/",
-        ],
-    )
-    def test_1m_context_with_prompt_caching(self, model_prefix):
-        """
-        Test that 1M context and prompt caching work together.
-
-        This is a real-world scenario where a user might want to use both features
-        simultaneously.
-        """
-        from litellm.llms.bedrock.chat.converse_transformation import (
-            AmazonConverseConfig,
-        )
-        from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude3_transformation import (
-            AmazonAnthropicClaudeConfig,
-        )
-
-        headers = {"anthropic-beta": "context-1m-2025-08-07"}
-        messages = [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": LARGE_DOCUMENT_FOR_CACHING,
-                        "cache_control": {"type": "ephemeral"},
-                    },
-                    {
-                        "type": "text",
-                        "text": "Summarize this document.",
-                    },
-                ],
-            }
-        ]
-
-        if "converse" in model_prefix:
-            config = AmazonConverseConfig()
-            result = config._transform_request_helper(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                system_content_blocks=[],
-                optional_params={},
-                messages=messages,
-                headers=headers,
-            )
-
-            # Should have 1M context header
-            additional_fields = result["additionalModelRequestFields"]
-            assert "anthropic_beta" in additional_fields
-            assert "context-1m-2025-08-07" in additional_fields["anthropic_beta"]
-
-            # Should NOT have prompt-caching header
-            assert (
-                "prompt-caching-2024-07-31" not in additional_fields["anthropic_beta"]
-            )
-
-        else:
-            config = AmazonAnthropicClaudeConfig()
-            result = config.transform_request(
-                model="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
-                messages=messages,
-                optional_params={},
-                litellm_params={},
-                headers=headers,
-            )
-
-            # Should have 1M context header
-            assert "anthropic_beta" in result
-            assert "context-1m-2025-08-07" in result["anthropic_beta"]
-
-            # Should NOT have prompt-caching header
-            assert "prompt-caching-2024-07-31" not in result["anthropic_beta"]
-
-            # Should have cache_control in messages
-            user_msg = result["messages"][0]
-            has_cache_control = any(
-                isinstance(c, dict) and "cache_control" in c
-                for c in user_msg["content"]
-            )
-            assert has_cache_control

tests/llm_translation/test_bedrock_common_utils.py

@@ -1,245 +0,0 @@
-"""
-Unit tests for litellm/llms/bedrock/common_utils.py
-
-Tests the standalone model name utility functions and BedrockTokenCounter.
-"""
-
-import pytest
-
-from litellm.llms.bedrock.common_utils import (
-    BedrockModelInfo,
-    extract_model_name_from_bedrock_arn,
-    get_bedrock_base_model,
-    get_bedrock_cross_region_inference_regions,
-    strip_bedrock_routing_prefix,
-    strip_bedrock_throughput_suffix,
-)
-from litellm.llms.bedrock.count_tokens.bedrock_token_counter import BedrockTokenCounter
-
-
-class TestStripBedrockRoutingPrefix:
-    """Tests for strip_bedrock_routing_prefix function."""
-
-    def test_strips_bedrock_prefix(self):
-        assert (
-            strip_bedrock_routing_prefix("bedrock/claude-3-sonnet") == "claude-3-sonnet"
-        )
-
-    def test_strips_converse_prefix(self):
-        assert (
-            strip_bedrock_routing_prefix("converse/claude-3-sonnet")
-            == "claude-3-sonnet"
-        )
-
-    def test_strips_invoke_prefix(self):
-        assert (
-            strip_bedrock_routing_prefix("invoke/claude-3-sonnet") == "claude-3-sonnet"
-        )
-
-    def test_strips_openai_prefix(self):
-        assert strip_bedrock_routing_prefix("openai/gpt-4") == "gpt-4"
-
-    def test_strips_all_known_prefixes(self):
-        # Function strips all known prefixes iteratively
-        # bedrock/converse/model -> converse/model -> model
-        assert strip_bedrock_routing_prefix("bedrock/converse/claude-3") == "claude-3"
-
-    def test_no_prefix_unchanged(self):
-        assert strip_bedrock_routing_prefix("claude-3-sonnet") == "claude-3-sonnet"
-
-    def test_model_with_dots_unchanged(self):
-        assert (
-            strip_bedrock_routing_prefix("anthropic.claude-3-sonnet-20240229-v1:0")
-            == "anthropic.claude-3-sonnet-20240229-v1:0"
-        )
-
-
-class TestStripBedrockThroughputSuffix:
-    """Tests for strip_bedrock_throughput_suffix function."""
-
-    @pytest.mark.parametrize(
-        "input_model,expected",
-        [
-            (
-                "anthropic.claude-haiku-4-5-20251001-v1:0:51k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            (
-                "anthropic.claude-haiku-4-5-20251001-v1:0:18k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            ("model:1:51k", "model:1"),
-            ("model:123:18k", "model:123"),
-            (
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            ("anthropic.claude-3-sonnet", "anthropic.claude-3-sonnet"),
-        ],
-    )
-    def test_strip_throughput_suffix(self, input_model, expected):
-        assert strip_bedrock_throughput_suffix(input_model) == expected
-
-
-class TestExtractModelNameFromBedrockArn:
-    """Tests for extract_model_name_from_bedrock_arn function."""
-
-    def test_extracts_from_provisioned_model_arn(self):
-        arn = "arn:aws:bedrock:us-east-1:123456789012:provisioned-model/my-model-id"
-        assert extract_model_name_from_bedrock_arn(arn) == "my-model-id"
-
-    def test_extracts_from_foundation_model_arn(self):
-        arn = "arn:aws:bedrock:us-west-2:123456789012:foundation-model/anthropic.claude-v2"
-        assert extract_model_name_from_bedrock_arn(arn) == "anthropic.claude-v2"
-
-    def test_non_arn_unchanged(self):
-        model = "anthropic.claude-3-sonnet-20240229-v1:0"
-        assert extract_model_name_from_bedrock_arn(model) == model
-
-    def test_case_insensitive_arn_detection(self):
-        arn = "ARN:aws:bedrock:us-east-1:123456789012:model/my-model"
-        assert extract_model_name_from_bedrock_arn(arn) == "my-model"
-
-
-class TestGetBedrockCrossRegionInferenceRegions:
-    """Tests for get_bedrock_cross_region_inference_regions function."""
-
-    def test_returns_expected_regions(self):
-        regions = get_bedrock_cross_region_inference_regions()
-        assert "us" in regions
-        assert "eu" in regions
-        assert "global" in regions
-        assert "apac" in regions
-
-    def test_returns_list(self):
-        regions = get_bedrock_cross_region_inference_regions()
-        assert isinstance(regions, list)
-
-
-class TestGetBedrockBaseModel:
-    """Tests for get_bedrock_base_model function."""
-
-    def test_strips_bedrock_prefix(self):
-        assert get_bedrock_base_model("bedrock/claude-3-sonnet") == "claude-3-sonnet"
-
-    def test_strips_converse_prefix(self):
-        assert (
-            get_bedrock_base_model("bedrock/converse/claude-3-sonnet")
-            == "claude-3-sonnet"
-        )
-
-    def test_strips_us_region_prefix(self):
-        # us.anthropic.model -> anthropic.model
-        assert (
-            get_bedrock_base_model("us.anthropic.claude-3-sonnet-20240229-v1:0")
-            == "anthropic.claude-3-sonnet-20240229-v1:0"
-        )
-
-    def test_strips_eu_region_prefix(self):
-        assert (
-            get_bedrock_base_model("eu.anthropic.claude-3-sonnet-20240229-v1:0")
-            == "anthropic.claude-3-sonnet-20240229-v1:0"
-        )
-
-    def test_extracts_from_arn(self):
-        arn = "arn:aws:bedrock:us-east-1:123456789012:provisioned-model/my-model"
-        assert get_bedrock_base_model(arn) == "my-model"
-
-    def test_model_without_prefix_unchanged(self):
-        model = "anthropic.claude-3-sonnet-20240229-v1:0"
-        assert get_bedrock_base_model(model) == model
-
-    def test_combined_bedrock_and_region_prefix(self):
-        # bedrock/us.anthropic.model -> anthropic.model
-        assert (
-            get_bedrock_base_model("bedrock/us.anthropic.claude-3-sonnet-20240229-v1:0")
-            == "anthropic.claude-3-sonnet-20240229-v1:0"
-        )
-
-    @pytest.mark.parametrize(
-        "input_model,expected",
-        [
-            (
-                "anthropic.claude-haiku-4-5-20251001-v1:0:51k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            (
-                "anthropic.claude-haiku-4-5-20251001-v1:0:18k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            (
-                "bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0:51k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-            (
-                "us.anthropic.claude-haiku-4-5-20251001-v1:0:51k",
-                "anthropic.claude-haiku-4-5-20251001-v1:0",
-            ),
-        ],
-    )
-    def test_strips_throughput_suffix(self, input_model, expected):
-        """Test that throughput tier suffixes like :51k are stripped. Issue #19113."""
-        assert get_bedrock_base_model(input_model) == expected
-
-
-class TestBedrockModelInfoWrappers:
-    """Tests that BedrockModelInfo methods correctly wrap standalone functions."""
-
-    def test_get_base_model_matches_standalone(self):
-        test_cases = [
-            "bedrock/claude-3-sonnet",
-            "us.anthropic.claude-3-sonnet-20240229-v1:0",
-            "arn:aws:bedrock:us-east-1:123:model/my-model",
-        ]
-        for model in test_cases:
-            assert BedrockModelInfo.get_base_model(model) == get_bedrock_base_model(
-                model
-            )
-
-    def test_extract_model_name_from_arn_matches_standalone(self):
-        arn = "arn:aws:bedrock:us-east-1:123456789012:provisioned-model/my-model"
-        assert BedrockModelInfo.extract_model_name_from_arn(
-            arn
-        ) == extract_model_name_from_bedrock_arn(arn)
-
-    def test_get_non_litellm_routing_model_name_matches_standalone(self):
-        model = "bedrock/converse/claude-3"
-        assert BedrockModelInfo.get_non_litellm_routing_model_name(
-            model
-        ) == strip_bedrock_routing_prefix(model)
-
-
-class TestBedrockTokenCounter:
-    """Tests for BedrockTokenCounter class."""
-
-    def test_should_use_token_counting_api_for_bedrock(self):
-        counter = BedrockTokenCounter()
-        assert counter.should_use_token_counting_api("bedrock") is True
-
-    def test_should_not_use_token_counting_api_for_other_providers(self):
-        counter = BedrockTokenCounter()
-        assert counter.should_use_token_counting_api("openai") is False
-        assert counter.should_use_token_counting_api("anthropic") is False
-        assert counter.should_use_token_counting_api(None) is False
-
-    def test_get_token_counter_returns_bedrock_token_counter(self):
-        model_info = BedrockModelInfo()
-        token_counter = model_info.get_token_counter()
-        assert isinstance(token_counter, BedrockTokenCounter)
-
-    @pytest.mark.asyncio
-    async def test_count_tokens_returns_none_for_empty_messages(self):
-        counter = BedrockTokenCounter()
-        result = await counter.count_tokens(
-            model_to_use="anthropic.claude-3-sonnet",
-            messages=None,
-            contents=None,
-        )
-        assert result is None
-
-        result = await counter.count_tokens(
-            model_to_use="anthropic.claude-3-sonnet",
-            messages=[],
-            contents=None,
-        )
-        assert result is None

tests/llm_translation/test_bedrock_completion.py

@@ -2,38 +2,32 @@
 Tests Bedrock Completion + Rerank endpoints
 """
 
-# @pytest.mark.skip(reason="AWS Suspended Account")
 import os
-import traceback
 
 from dotenv import load_dotenv
 
 import litellm.types
 
 load_dotenv()
-import io
 import json
-
 from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
+from base_embedding_unit_tests import BaseLLMEmbeddingTest
+from base_llm_unit_tests import BaseAnthropicChatTest, BaseLLMChatTest
+from base_rerank_unit_tests import BaseLLMRerankTest
 
 import litellm
 from litellm import (
     ModelResponse,
     RateLimitError,
     ServiceUnavailableError,
-    Timeout,
     completion,
     completion_cost,
-    embedding,
 )
+from litellm.litellm_core_utils.prompt_templates.factory import _bedrock_tools_pt
 from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
-from litellm.litellm_core_utils.prompt_templates.factory import _bedrock_tools_pt
-from base_llm_unit_tests import BaseLLMChatTest, BaseAnthropicChatTest
-from base_rerank_unit_tests import BaseLLMRerankTest
-from base_embedding_unit_tests import BaseLLMEmbeddingTest
 
 # litellm.num_retries = 3
 litellm.cache = None
@@ -84,12 +78,9 @@ def test_completion_bedrock_claude_completion_auth(monkeypatch):
 
 @pytest.mark.parametrize("streaming", [True, False])
 def test_completion_bedrock_guardrails(streaming):
-    import os
 
     litellm.set_verbose = True
-    import logging
 
-    from litellm._logging import verbose_logger
 
     # verbose_logger.setLevel(logging.DEBUG)
     try:
@@ -200,226 +191,12 @@ def test_completion_bedrock_claude_external_client_auth(monkeypatch):
 # test_completion_bedrock_claude_external_client_auth()
 
 
-@pytest.fixture()
-def bedrock_session_token_creds():
-    print("\ncalling oidc auto to get aws_session_token credentials")
-    import os
-
-    aws_region_name = os.environ["AWS_REGION_NAME"]
-    aws_session_token = os.environ.get("AWS_SESSION_TOKEN")
-
-    bllm = BaseAWSLLM()
-    if aws_session_token is not None:
-        # For local testing
-        creds = bllm.get_credentials(
-            aws_region_name=aws_region_name,
-            aws_access_key_id=os.environ["AWS_ACCESS_KEY_ID"],
-            aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"],
-            aws_session_token=aws_session_token,
-        )
-    else:
-        # For circle-ci testing
-        # aws_role_name = os.environ["AWS_TEMP_ROLE_NAME"]
-        # TODO: This is using ai.moda's IAM role, we should use LiteLLM's IAM role eventually
-        aws_role_name = (
-            "arn:aws:iam::335785316107:role/litellm-github-unit-tests-circleci"
-        )
-        aws_web_identity_token = "test-oidc-token-123"
-
-        creds = bllm.get_credentials(
-            aws_region_name=aws_region_name,
-            aws_web_identity_token=aws_web_identity_token,
-            aws_role_name=aws_role_name,
-            aws_session_name="my-test-session",
-        )
-    return creds
 
 
-def process_stream_response(res, messages):
-    import types
-
-    if isinstance(res, litellm.utils.CustomStreamWrapper):
-        chunks = []
-        for part in res:
-            chunks.append(part)
-            text = part.choices[0].delta.content or ""
-            print(text, end="")
-        res = litellm.stream_chunk_builder(chunks, messages=messages)
-    else:
-        raise ValueError("Response object is not a streaming response")
-
-    return res
 
 
-@pytest.mark.skip(reason="Cannot run without being in CircleCI Runner")
-def test_completion_bedrock_claude_aws_session_token(bedrock_session_token_creds):
-    print("\ncalling bedrock claude with aws_session_token auth")
-
-    import os
-
-    aws_region_name = os.environ["AWS_REGION_NAME"]
-    aws_access_key_id = bedrock_session_token_creds.access_key
-    aws_secret_access_key = bedrock_session_token_creds.secret_key
-    aws_session_token = bedrock_session_token_creds.token
-
-    try:
-        litellm.set_verbose = True
-
-        response_1 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=10,
-            temperature=0.1,
-            aws_region_name=aws_region_name,
-            aws_access_key_id=aws_access_key_id,
-            aws_secret_access_key=aws_secret_access_key,
-            aws_session_token=aws_session_token,
-        )
-        print(response_1)
-        assert len(response_1.choices) > 0
-        assert len(response_1.choices[0].message.content) > 0
-
-        # This second call is to verify that the cache isn't breaking anything
-        response_2 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=5,
-            temperature=0.2,
-            aws_region_name=aws_region_name,
-            aws_access_key_id=aws_access_key_id,
-            aws_secret_access_key=aws_secret_access_key,
-            aws_session_token=aws_session_token,
-        )
-        print(response_2)
-        assert len(response_2.choices) > 0
-        assert len(response_2.choices[0].message.content) > 0
-
-        # This third call is to verify that the cache isn't used for a different region
-        response_3 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=6,
-            temperature=0.3,
-            aws_region_name="us-east-1",
-            aws_access_key_id=aws_access_key_id,
-            aws_secret_access_key=aws_secret_access_key,
-            aws_session_token=aws_session_token,
-        )
-        print(response_3)
-        assert len(response_3.choices) > 0
-        assert len(response_3.choices[0].message.content) > 0
-
-        # This fourth call is to verify streaming api works
-        response_4 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=6,
-            temperature=0.3,
-            aws_region_name="us-east-1",
-            aws_access_key_id=aws_access_key_id,
-            aws_secret_access_key=aws_secret_access_key,
-            aws_session_token=aws_session_token,
-            stream=True,
-        )
-        response_4 = process_stream_response(response_4, messages)
-        print(response_4)
-        assert len(response_4.choices) > 0
-        assert len(response_4.choices[0].message.content) > 0
-
-    except RateLimitError:
-        pass
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
 
 
-@pytest.mark.skip(reason="Cannot run without being in CircleCI Runner")
-def test_completion_bedrock_claude_aws_bedrock_client(bedrock_session_token_creds):
-    print("\ncalling bedrock claude with aws_session_token auth")
-
-    import os
-
-    import boto3
-    from botocore.client import Config
-
-    aws_region_name = os.environ["AWS_REGION_NAME"]
-    aws_access_key_id = bedrock_session_token_creds.access_key
-    aws_secret_access_key = bedrock_session_token_creds.secret_key
-    aws_session_token = bedrock_session_token_creds.token
-
-    aws_bedrock_client_west = boto3.client(
-        service_name="bedrock-runtime",
-        region_name=aws_region_name,
-        aws_access_key_id=aws_access_key_id,
-        aws_secret_access_key=aws_secret_access_key,
-        aws_session_token=aws_session_token,
-        config=Config(read_timeout=600),
-    )
-
-    try:
-        litellm.set_verbose = True
-
-        response_1 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=10,
-            temperature=0.1,
-            aws_bedrock_client=aws_bedrock_client_west,
-        )
-        print(response_1)
-        assert len(response_1.choices) > 0
-        assert len(response_1.choices[0].message.content) > 0
-
-        # This second call is to verify that the cache isn't breaking anything
-        response_2 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=5,
-            temperature=0.2,
-            aws_bedrock_client=aws_bedrock_client_west,
-        )
-        print(response_2)
-        assert len(response_2.choices) > 0
-        assert len(response_2.choices[0].message.content) > 0
-
-        # This third call is to verify that the cache isn't used for a different region
-        aws_bedrock_client_east = boto3.client(
-            service_name="bedrock-runtime",
-            region_name="us-east-1",
-            aws_access_key_id=aws_access_key_id,
-            aws_secret_access_key=aws_secret_access_key,
-            aws_session_token=aws_session_token,
-            config=Config(read_timeout=600),
-        )
-
-        response_3 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=6,
-            temperature=0.3,
-            aws_bedrock_client=aws_bedrock_client_east,
-        )
-        print(response_3)
-        assert len(response_3.choices) > 0
-        assert len(response_3.choices[0].message.content) > 0
-
-        # This fourth call is to verify streaming api works
-        response_4 = completion(
-            model="bedrock/anthropic.claude-3-haiku-20240307-v1:0",
-            messages=messages,
-            max_tokens=6,
-            temperature=0.3,
-            aws_bedrock_client=aws_bedrock_client_east,
-            stream=True,
-        )
-        response_4 = process_stream_response(response_4, messages)
-        print(response_4)
-        assert len(response_4.choices) > 0
-        assert len(response_4.choices[0].message.content) > 0
-
-    except RateLimitError:
-        pass
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")
 
 
 # test_completion_bedrock_claude_sts_client_auth()
@@ -577,54 +354,13 @@ def test_bedrock_claude_3_tool_calling():
         pytest.fail(f"Error occurred: {e}")
 
 
-def encode_image(image_path):
-    import base64
-
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode("utf-8")
 
 
-@pytest.mark.skip(
-    reason="we already test claude-3, this is just another way to pass images"
-)
-def test_completion_claude_3_base64():
-    try:
-        litellm.set_verbose = True
-        litellm.num_retries = 3
-        image_path = "../proxy/cached_logo.jpg"
-        # Getting the base64 string
-        base64_image = encode_image(image_path)
-        resp = litellm.completion(
-            model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
-            messages=[
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": "Whats in this image?"},
-                        {
-                            "type": "image_url",
-                            "image_url": {
-                                "url": "data:image/jpeg;base64," + base64_image
-                            },
-                        },
-                    ],
-                }
-            ],
-        )
-
-        prompt_tokens = resp.usage.prompt_tokens
-        raise Exception("it worked!")
-    except Exception as e:
-        if "500 Internal error encountered.'" in str(e):
-            pass
-        else:
-            pytest.fail(f"An exception occurred - {str(e)}")
 
 
 def test_completion_bedrock_mistral_completion_auth():
     print("calling bedrock mistral completion params auth")
 
-    import os
 
     litellm.turn_on_debug()
 
@@ -668,7 +404,6 @@ def test_bedrock_ptu():
 
     with patch.object(client, "post", new=Mock()) as mock_client_post:
         litellm.set_verbose = True
-        from openai.types.chat import ChatCompletion
 
         model_id = (
             "arn:aws:bedrock:us-west-2:888602223428:provisioned-model/8fxff74qyhs3"
@@ -703,7 +438,6 @@ async def test_bedrock_custom_api_base():
 
     with patch.object(client, "post", new=AsyncMock()) as mock_client_post:
         litellm.set_verbose = True
-        from openai.types.chat import ChatCompletion
 
         try:
             response = await litellm.acompletion(
@@ -746,7 +480,6 @@ async def test_bedrock_extra_headers(model):
 
     with patch.object(client, "post", new=AsyncMock()) as mock_client_post:
         litellm.set_verbose = True
-        from openai.types.chat import ChatCompletion
 
         try:
             response = await litellm.acompletion(
@@ -1103,7 +836,6 @@ from litellm.litellm_core_utils.prompt_templates.factory import (
 
 
 def test_bedrock_converse_translation_tool_message():
-    from litellm.types.utils import ChatCompletionMessageToolCall, Function
 
     litellm.set_verbose = True
 
@@ -1157,7 +889,6 @@ def test_base_aws_llm_get_credentials():
 
     import boto3
 
-    from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 
     start_time = time.time()
     session = boto3.Session(
@@ -1439,10 +1170,10 @@ def test_bedrock_completion_test_3():
     """
     Check if content in tool result is formatted correctly
     """
-    from litellm.types.utils import ChatCompletionMessageToolCall, Function, Message
     from litellm.litellm_core_utils.prompt_templates.factory import (
         _bedrock_converse_messages_pt,
     )
+    from litellm.types.utils import ChatCompletionMessageToolCall, Function, Message
 
     messages = [
         {
@@ -1493,293 +1224,6 @@ def test_bedrock_completion_test_3():
     ]
 
 
-@pytest.mark.skip(reason="Skipping this test as Bedrock now supports this behavior.")
-@pytest.mark.parametrize("modify_params", [True, False])
-def test_bedrock_completion_test_4(modify_params):
-    litellm.set_verbose = True
-    litellm.modify_params = modify_params
-
-    data = {
-        "model": "anthropic.claude-sonnet-4-5-20250929-v1:0",
-        "messages": [
-            {
-                "role": "user",
-                "content": [
-                    {"type": "text", "text": "<task>\nWhat is this file?\n</task>"},
-                    {
-                        "type": "text",
-                        "text": "<environment_details>\n# VSCode Visible Files\ncomputer-vision/hm-open3d/src/main.py\n\n# VSCode Open Tabs\ncomputer-vision/hm-open3d/src/main.py\n\n# Current Working Directory (/Users/hongbo-miao/Clouds/Git/hongbomiao.com) Files\n.ansible-lint\n.clang-format\n.cmakelintrc\n.dockerignore\n.editorconfig\n.gitignore\n.gitmodules\n.hadolint.yaml\n.isort.cfg\n.markdownlint-cli2.jsonc\n.mergify.yml\n.npmrc\n.nvmrc\n.prettierignore\n.rubocop.yml\n.ruby-version\n.ruff.toml\n.shellcheckrc\n.solhint.json\n.solhintignore\n.sqlfluff\n.sqlfluffignore\n.stylelintignore\n.yamllint.yaml\nCODE_OF_CONDUCT.md\ncommitlint.config.js\nGemfile\nGemfile.lock\nLICENSE\nlint-staged.config.js\nMakefile\nmiss_hit.cfg\nmypy.ini\npackage-lock.json\npackage.json\npoetry.lock\npoetry.toml\nprettier.config.js\npyproject.toml\nREADME.md\nrelease.config.js\nrenovate.json\nSECURITY.md\nstylelint.config.js\naerospace/\naerospace/air-defense-system/\naerospace/hm-aerosandbox/\naerospace/hm-openaerostruct/\naerospace/px4/\naerospace/quadcopter-pd-controller/\naerospace/simulate-satellite/\naerospace/simulated-and-actual-flights/\naerospace/toroidal-propeller/\nansible/\nansible/inventory.yaml\nansible/Makefile\nansible/requirements.yml\nansible/hm_macos_group/\nansible/hm_ubuntu_group/\nansible/hm_windows_group/\napi-go/\napi-go/buf.yaml\napi-go/go.mod\napi-go/go.sum\napi-go/Makefile\napi-go/api/\napi-go/build/\napi-go/cmd/\napi-go/config/\napi-go/internal/\napi-node/\napi-node/.env.development\napi-node/.env.development.local.example\napi-node/.env.development.local.example.docker\napi-node/.env.production\napi-node/.env.production.local.example\napi-node/.env.test\napi-node/.eslintignore\napi-node/.eslintrc.js\napi-node/.npmrc\napi-node/.nvmrc\napi-node/babel.config.js\napi-node/docker-compose.cypress.yaml\napi-node/docker-compose.development.yaml\napi-node/Dockerfile\napi-node/Dockerfile.development\napi-node/jest.config.js\napi-node/Makefile\napi-node/package-lock.json\napi-node/package.json\napi-node/Procfile\napi-node/stryker.conf.js\napi-node/tsconfig.json\napi-node/bin/\napi-node/postgres/\napi-node/scripts/\napi-node/src/\napi-python/\napi-python/.flaskenv\napi-python/docker-entrypoint.sh\napi-python/Dockerfile\napi-python/Makefile\napi-python/poetry.lock\napi-python/poetry.toml\napi-python/pyproject.toml\napi-python/flaskr/\nasterios/\nasterios/led-blinker/\nauthorization/\nauthorization/hm-opal-client/\nauthorization/ory-hydra/\nautomobile/\nautomobile/build-map-by-lidar-point-cloud/\nautomobile/detect-lane-by-lidar-point-cloud/\nbin/\nbin/clean.sh\nbin/count_code_lines.sh\nbin/lint_javascript_fix.sh\nbin/lint_javascript.sh\nbin/set_up.sh\nbiology/\nbiology/compare-nucleotide-sequences/\nbusybox/\nbusybox/Makefile\ncaddy/\ncaddy/Caddyfile\ncaddy/Makefile\ncaddy/bin/\ncloud-computing/\ncloud-computing/hm-ray/\ncloud-computing/hm-skypilot/\ncloud-cost/\ncloud-cost/komiser/\ncloud-infrastructure/\ncloud-infrastructure/hm-pulumi/\ncloud-infrastructure/karpenter/\ncloud-infrastructure/terraform/\ncloud-platform/\ncloud-platform/aws/\ncloud-platform/google-cloud/\ncloud-security/\ncloud-security/hm-prowler/\ncomputational-fluid-dynamics/\ncomputational-fluid-dynamics/matlab/\ncomputational-fluid-dynamics/openfoam/\ncomputer-vision/\ncomputer-vision/hm-open3d/\ncomputer-vision/hm-pyvista/\ndata-analytics/\ndata-analytics/hm-geopandas/\ndata-distribution-service/\ndata-distribution-service/dummy_test.py\ndata-distribution-service/hm_message.idl\ndata-distribution-service/hm_message.xml\ndata-distribution-service/Makefile\ndata-distribution-service/poetry.lock\ndata-distribution-service/poetry.toml\ndata-distribution-service/publish.py\ndata-ingestion/\ndata-orchestration/\ndata-processing/\ndata-storage/\ndata-transformation/\ndata-visualization/\ndesktop-qt/\nembedded/\nethereum/\ngit/\ngolang-migrate/\nhardware-in-the-loop/\nhasura-graphql-engine/\nhigh-performance-computing/\nhm-alpine/\nhm-kafka/\nhm-locust/\nhm-rust/\nhm-traefik/\nhm-xxhash/\nkubernetes/\nmachine-learning/\nmatlab/\nmobile/\nnetwork-programmability/\noperating-system/\nparallel-computing/\nphysics/\nquantum-computing/\nrclone/\nrestic/\nreverse-engineering/\nrobotics/\nsubmodules/\ntrino/\nvagrant/\nvalgrind/\nvhdl/\nvim/\nweb/\nweb-cypress/\nwireless-network/\n\n(File list truncated. Use list_files on specific subdirectories if you need to explore further.)\n</environment_details>",
-                    },
-                ],
-            },
-            {
-                "role": "assistant",
-                "content": '<thinking>\nThe user is asking about a specific file: main.py. Based on the environment details provided, this file is located in the computer-vision/hm-open3d/src/ directory and is currently open in a VSCode tab.\n\nTo answer the question of what this file is, the most relevant tool would be the read_file tool. This will allow me to examine the contents of main.py to determine its purpose.\n\nThe read_file tool requires the "path" parameter. I can infer this path based on the environment details:\npath: "computer-vision/hm-open3d/src/main.py"\n\nSince I have the necessary parameter, I can proceed with calling the read_file tool.\n</thinking>',
-                "tool_calls": [
-                    {
-                        "id": "tooluse_qCt-KEyWQlWiyHl26spQVA",
-                        "type": "function",
-                        "function": {
-                            "name": "read_file",
-                            "arguments": '{"path":"computer-vision/hm-open3d/src/main.py"}',
-                        },
-                    }
-                ],
-            },
-            {
-                "role": "tool",
-                "tool_call_id": "tooluse_qCt-KEyWQlWiyHl26spQVA",
-                "content": 'import numpy as np\nimport open3d as o3d\n\n\ndef main():\n    ply_point_cloud = o3d.data.PLYPointCloud()\n    pcd = o3d.io.read_point_cloud(ply_point_cloud.path)\n    print(pcd)\n    print(np.asarray(pcd.points))\n\n    demo_crop_data = o3d.data.DemoCropPointCloud()\n    vol = o3d.visualization.read_selection_polygon_volume(\n        demo_crop_data.cropped_json_path\n    )\n    chair = vol.crop_point_cloud(pcd)\n\n    dists = pcd.compute_point_cloud_distance(chair)\n    dists = np.asarray(dists)\n    idx = np.where(dists > 0.01)[0]\n    pcd_without_chair = pcd.select_by_index(idx)\n\n    axis_aligned_bounding_box = chair.get_axis_aligned_bounding_box()\n    axis_aligned_bounding_box.color = (1, 0, 0)\n\n    oriented_bounding_box = chair.get_oriented_bounding_box()\n    oriented_bounding_box.color = (0, 1, 0)\n\n    o3d.visualization.draw_geometries(\n        [pcd_without_chair, chair, axis_aligned_bounding_box, oriented_bounding_box],\n        zoom=0.3412,\n        front=[0.4, -0.2, -0.9],\n        lookat=[2.6, 2.0, 1.5],\n        up=[-0.10, -1.0, 0.2],\n    )\n\n\nif __name__ == "__main__":\n    main()\n',
-            },
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": "<environment_details>\n# VSCode Visible Files\ncomputer-vision/hm-open3d/src/main.py\n\n# VSCode Open Tabs\ncomputer-vision/hm-open3d/src/main.py\n</environment_details>",
-                    }
-                ],
-            },
-        ],
-        "temperature": 0.2,
-        "tools": [
-            {
-                "type": "function",
-                "function": {
-                    "name": "execute_command",
-                    "description": "Execute a CLI command on the system. Use this when you need to perform system operations or run specific commands to accomplish any step in the user's task. You must tailor your command to the user's system and provide a clear explanation of what the command does. Prefer to execute complex CLI commands over creating executable scripts, as they are more flexible and easier to run. Commands will be executed in the current working directory: /Users/hongbo-miao/Clouds/Git/hongbomiao.com",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "command": {
-                                "type": "string",
-                                "description": "The CLI command to execute. This should be valid for the current operating system. Ensure the command is properly formatted and does not contain any harmful instructions.",
-                            }
-                        },
-                        "required": ["command"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "read_file",
-                    "description": "Read the contents of a file at the specified path. Use this when you need to examine the contents of an existing file, for example to analyze code, review text files, or extract information from configuration files. Automatically extracts raw text from PDF and DOCX files. May not be suitable for other types of binary files, as it returns the raw content as a string.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "path": {
-                                "type": "string",
-                                "description": "The path of the file to read (relative to the current working directory /Users/hongbo-miao/Clouds/Git/hongbomiao.com)",
-                            }
-                        },
-                        "required": ["path"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "write_to_file",
-                    "description": "Write content to a file at the specified path. If the file exists, it will be overwritten with the provided content. If the file doesn't exist, it will be created. Always provide the full intended content of the file, without any truncation. This tool will automatically create any directories needed to write the file.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "path": {
-                                "type": "string",
-                                "description": "The path of the file to write to (relative to the current working directory /Users/hongbo-miao/Clouds/Git/hongbomiao.com)",
-                            },
-                            "content": {
-                                "type": "string",
-                                "description": "The full content to write to the file.",
-                            },
-                        },
-                        "required": ["path", "content"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "search_files",
-                    "description": "Perform a regex search across files in a specified directory, providing context-rich results. This tool searches for patterns or specific content across multiple files, displaying each match with encapsulating context.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "path": {
-                                "type": "string",
-                                "description": "The path of the directory to search in (relative to the current working directory /Users/hongbo-miao/Clouds/Git/hongbomiao.com). This directory will be recursively searched.",
-                            },
-                            "regex": {
-                                "type": "string",
-                                "description": "The regular expression pattern to search for. Uses Rust regex syntax.",
-                            },
-                            "filePattern": {
-                                "type": "string",
-                                "description": "Optional glob pattern to filter files (e.g., '*.ts' for TypeScript files). If not provided, it will search all files (*).",
-                            },
-                        },
-                        "required": ["path", "regex"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "list_files",
-                    "description": "List files and directories within the specified directory. If recursive is true, it will list all files and directories recursively. If recursive is false or not provided, it will only list the top-level contents.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "path": {
-                                "type": "string",
-                                "description": "The path of the directory to list contents for (relative to the current working directory /Users/hongbo-miao/Clouds/Git/hongbomiao.com)",
-                            },
-                            "recursive": {
-                                "type": "string",
-                                "enum": ["true", "false"],
-                                "description": "Whether to list files recursively. Use 'true' for recursive listing, 'false' or omit for top-level only.",
-                            },
-                        },
-                        "required": ["path"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "list_code_definition_names",
-                    "description": "Lists definition names (classes, functions, methods, etc.) used in source code files at the top level of the specified directory. This tool provides insights into the codebase structure and important constructs, encapsulating high-level concepts and relationships that are crucial for understanding the overall architecture.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "path": {
-                                "type": "string",
-                                "description": "The path of the directory (relative to the current working directory /Users/hongbo-miao/Clouds/Git/hongbomiao.com) to list top level source code definitions for",
-                            }
-                        },
-                        "required": ["path"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "inspect_site",
-                    "description": "Captures a screenshot and console logs of the initial state of a website. This tool navigates to the specified URL, takes a screenshot of the entire page as it appears immediately after loading, and collects any console logs or errors that occur during page load. It does not interact with the page or capture any state changes after the initial load.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "url": {
-                                "type": "string",
-                                "description": "The URL of the site to inspect. This should be a valid URL including the protocol (e.g. http://localhost:3000/page, file:///path/to/file.html, etc.)",
-                            }
-                        },
-                        "required": ["url"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "ask_followup_question",
-                    "description": "Ask the user a question to gather additional information needed to complete the task. This tool should be used when you encounter ambiguities, need clarification, or require more details to proceed effectively. It allows for interactive problem-solving by enabling direct communication with the user. Use this tool judiciously to maintain a balance between gathering necessary information and avoiding excessive back-and-forth.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "question": {
-                                "type": "string",
-                                "description": "The question to ask the user. This should be a clear, specific question that addresses the information you need.",
-                            }
-                        },
-                        "required": ["question"],
-                    },
-                },
-            },
-            {
-                "type": "function",
-                "function": {
-                    "name": "attempt_completion",
-                    "description": "Once you've completed the task, use this tool to present the result to the user. Optionally you may provide a CLI command to showcase the result of your work, but avoid using commands like 'echo' or 'cat' that merely print text. They may respond with feedback if they are not satisfied with the result, which you can use to make improvements and try again.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "command": {
-                                "type": "string",
-                                "description": "A CLI command to execute to show a live demo of the result to the user. For example, use 'open index.html' to display a created website. This command should be valid for the current operating system. Ensure the command is properly formatted and does not contain any harmful instructions.",
-                            },
-                            "result": {
-                                "type": "string",
-                                "description": "The result of the task. Formulate this result in a way that is final and does not require further input from the user. Don't end your result with questions or offers for further assistance.",
-                            },
-                        },
-                        "required": ["result"],
-                    },
-                },
-            },
-        ],
-        "tool_choice": "auto",
-    }
-
-    if modify_params:
-        transformed_messages = _bedrock_converse_messages_pt(
-            messages=data["messages"], model="", llm_provider=""
-        )
-        expected_messages = [
-            {
-                "role": "user",
-                "content": [
-                    {"text": "<task>\nWhat is this file?\n</task>"},
-                    {
-                        "text": "<environment_details>\n# VSCode Visible Files\ncomputer-vision/hm-open3d/src/main.py\n\n# VSCode Open Tabs\ncomputer-vision/hm-open3d/src/main.py\n\n# Current Working Directory (/Users/hongbo-miao/Clouds/Git/hongbomiao.com) Files\n.ansible-lint\n.clang-format\n.cmakelintrc\n.dockerignore\n.editorconfig\n.gitignore\n.gitmodules\n.hadolint.yaml\n.isort.cfg\n.markdownlint-cli2.jsonc\n.mergify.yml\n.npmrc\n.nvmrc\n.prettierignore\n.rubocop.yml\n.ruby-version\n.ruff.toml\n.shellcheckrc\n.solhint.json\n.solhintignore\n.sqlfluff\n.sqlfluffignore\n.stylelintignore\n.yamllint.yaml\nCODE_OF_CONDUCT.md\ncommitlint.config.js\nGemfile\nGemfile.lock\nLICENSE\nlint-staged.config.js\nMakefile\nmiss_hit.cfg\nmypy.ini\npackage-lock.json\npackage.json\npoetry.lock\npoetry.toml\nprettier.config.js\npyproject.toml\nREADME.md\nrelease.config.js\nrenovate.json\nSECURITY.md\nstylelint.config.js\naerospace/\naerospace/air-defense-system/\naerospace/hm-aerosandbox/\naerospace/hm-openaerostruct/\naerospace/px4/\naerospace/quadcopter-pd-controller/\naerospace/simulate-satellite/\naerospace/simulated-and-actual-flights/\naerospace/toroidal-propeller/\nansible/\nansible/inventory.yaml\nansible/Makefile\nansible/requirements.yml\nansible/hm_macos_group/\nansible/hm_ubuntu_group/\nansible/hm_windows_group/\napi-go/\napi-go/buf.yaml\napi-go/go.mod\napi-go/go.sum\napi-go/Makefile\napi-go/api/\napi-go/build/\napi-go/cmd/\napi-go/config/\napi-go/internal/\napi-node/\napi-node/.env.development\napi-node/.env.development.local.example\napi-node/.env.development.local.example.docker\napi-node/.env.production\napi-node/.env.production.local.example\napi-node/.env.test\napi-node/.eslintignore\napi-node/.eslintrc.js\napi-node/.npmrc\napi-node/.nvmrc\napi-node/babel.config.js\napi-node/docker-compose.cypress.yaml\napi-node/docker-compose.development.yaml\napi-node/Dockerfile\napi-node/Dockerfile.development\napi-node/jest.config.js\napi-node/Makefile\napi-node/package-lock.json\napi-node/package.json\napi-node/Procfile\napi-node/stryker.conf.js\napi-node/tsconfig.json\napi-node/bin/\napi-node/postgres/\napi-node/scripts/\napi-node/src/\napi-python/\napi-python/.flaskenv\napi-python/docker-entrypoint.sh\napi-python/Dockerfile\napi-python/Makefile\napi-python/poetry.lock\napi-python/poetry.toml\napi-python/pyproject.toml\napi-python/flaskr/\nasterios/\nasterios/led-blinker/\nauthorization/\nauthorization/hm-opal-client/\nauthorization/ory-hydra/\nautomobile/\nautomobile/build-map-by-lidar-point-cloud/\nautomobile/detect-lane-by-lidar-point-cloud/\nbin/\nbin/clean.sh\nbin/count_code_lines.sh\nbin/lint_javascript_fix.sh\nbin/lint_javascript.sh\nbin/set_up.sh\nbiology/\nbiology/compare-nucleotide-sequences/\nbusybox/\nbusybox/Makefile\ncaddy/\ncaddy/Caddyfile\ncaddy/Makefile\ncaddy/bin/\ncloud-computing/\ncloud-computing/hm-ray/\ncloud-computing/hm-skypilot/\ncloud-cost/\ncloud-cost/komiser/\ncloud-infrastructure/\ncloud-infrastructure/hm-pulumi/\ncloud-infrastructure/karpenter/\ncloud-infrastructure/terraform/\ncloud-platform/\ncloud-platform/aws/\ncloud-platform/google-cloud/\ncloud-security/\ncloud-security/hm-prowler/\ncomputational-fluid-dynamics/\ncomputational-fluid-dynamics/matlab/\ncomputational-fluid-dynamics/openfoam/\ncomputer-vision/\ncomputer-vision/hm-open3d/\ncomputer-vision/hm-pyvista/\ndata-analytics/\ndata-analytics/hm-geopandas/\ndata-distribution-service/\ndata-distribution-service/dummy_test.py\ndata-distribution-service/hm_message.idl\ndata-distribution-service/hm_message.xml\ndata-distribution-service/Makefile\ndata-distribution-service/poetry.lock\ndata-distribution-service/poetry.toml\ndata-distribution-service/publish.py\ndata-ingestion/\ndata-orchestration/\ndata-processing/\ndata-storage/\ndata-transformation/\ndata-visualization/\ndesktop-qt/\nembedded/\nethereum/\ngit/\ngolang-migrate/\nhardware-in-the-loop/\nhasura-graphql-engine/\nhigh-performance-computing/\nhm-alpine/\nhm-kafka/\nhm-locust/\nhm-rust/\nhm-traefik/\nhm-xxhash/\nkubernetes/\nmachine-learning/\nmatlab/\nmobile/\nnetwork-programmability/\noperating-system/\nparallel-computing/\nphysics/\nquantum-computing/\nrclone/\nrestic/\nreverse-engineering/\nrobotics/\nsubmodules/\ntrino/\nvagrant/\nvalgrind/\nvhdl/\nvim/\nweb/\nweb-cypress/\nwireless-network/\n\n(File list truncated. Use list_files on specific subdirectories if you need to explore further.)\n</environment_details>"
-                    },
-                ],
-            },
-            {
-                "role": "assistant",
-                "content": [
-                    {
-                        "text": """<thinking>\nThe user is asking about a specific file: main.py. Based on the environment details provided, this file is located in the computer-vision/hm-open3d/src/ directory and is currently open in a VSCode tab.\n\nTo answer the question of what this file is, the most relevant tool would be the read_file tool. This will allow me to examine the contents of main.py to determine its purpose.\n\nThe read_file tool requires the "path" parameter. I can infer this path based on the environment details:\npath: "computer-vision/hm-open3d/src/main.py"\n\nSince I have the necessary parameter, I can proceed with calling the read_file tool.\n</thinking>"""
-                    },
-                    {
-                        "toolUse": {
-                            "input": {"path": "computer-vision/hm-open3d/src/main.py"},
-                            "name": "read_file",
-                            "toolUseId": "tooluse_qCt-KEyWQlWiyHl26spQVA",
-                        }
-                    },
-                ],
-            },
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "toolResult": {
-                            "content": [
-                                {
-                                    "text": 'import numpy as np\nimport open3d as o3d\n\n\ndef main():\n    ply_point_cloud = o3d.data.PLYPointCloud()\n    pcd = o3d.io.read_point_cloud(ply_point_cloud.path)\n    print(pcd)\n    print(np.asarray(pcd.points))\n\n    demo_crop_data = o3d.data.DemoCropPointCloud()\n    vol = o3d.visualization.read_selection_polygon_volume(\n        demo_crop_data.cropped_json_path\n    )\n    chair = vol.crop_point_cloud(pcd)\n\n    dists = pcd.compute_point_cloud_distance(chair)\n    dists = np.asarray(dists)\n    idx = np.where(dists > 0.01)[0]\n    pcd_without_chair = pcd.select_by_index(idx)\n\n    axis_aligned_bounding_box = chair.get_axis_aligned_bounding_box()\n    axis_aligned_bounding_box.color = (1, 0, 0)\n\n    oriented_bounding_box = chair.get_oriented_bounding_box()\n    oriented_bounding_box.color = (0, 1, 0)\n\n    o3d.visualization.draw_geometries(\n        [pcd_without_chair, chair, axis_aligned_bounding_box, oriented_bounding_box],\n        zoom=0.3412,\n        front=[0.4, -0.2, -0.9],\n        lookat=[2.6, 2.0, 1.5],\n        up=[-0.10, -1.0, 0.2],\n    )\n\n\nif __name__ == "__main__":\n    main()\n'
-                                }
-                            ],
-                            "toolUseId": "tooluse_qCt-KEyWQlWiyHl26spQVA",
-                        }
-                    }
-                ],
-            },
-            {"role": "assistant", "content": [{"text": "Please continue."}]},
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "text": "<environment_details>\n# VSCode Visible Files\ncomputer-vision/hm-open3d/src/main.py\n\n# VSCode Open Tabs\ncomputer-vision/hm-open3d/src/main.py\n</environment_details>"
-                    }
-                ],
-            },
-        ]
-        assert transformed_messages == expected_messages
-    else:
-        with pytest.raises(Exception, match=r"litellm\.modify_params") as e:
-            litellm.completion(**data)
-        assert "litellm.modify_params" in str(e.value)
 
 
 def test_bedrock_context_window_error():
@@ -1901,9 +1345,10 @@ def test_bedrock_route_detection(model, expected_route):
     ],
 )
 def test_bedrock_prompt_caching_message(messages, expected_cache_control):
-    import litellm
     import json
 
+    import litellm
+
     transformed_messages = litellm.AmazonConverseConfig()._transform_request(
         model="bedrock/anthropic.claude-3-5-haiku-20241022-v1:0",
         messages=messages,
@@ -2246,85 +1691,6 @@ def test_bedrock_process_empty_text_blocks():
     assert modified_message["content"][0]["text"] == "Please continue."
 
 
-@pytest.mark.skip(
-    reason="Skipping test due to bedrock changing their response schema support. Come back to this."
-)
-def test_nova_optional_params_tool_choice():
-    try:
-        litellm.drop_params = True
-        litellm.set_verbose = True
-        litellm.completion(
-            messages=[
-                {"role": "user", "content": "A WWII competitive game for 4-8 players"}
-            ],
-            model="bedrock/us.amazon.nova-pro-v1:0",
-            temperature=0.3,
-            tools=[
-                {
-                    "type": "function",
-                    "function": {
-                        "name": "GameDefinition",
-                        "description": "Correctly extracted `GameDefinition` with all the required parameters with correct types",
-                        "parameters": {
-                            "$defs": {
-                                "TurnDurationEnum": {
-                                    "enum": [
-                                        "action",
-                                        "encounter",
-                                        "battle",
-                                        "operation",
-                                    ],
-                                    "title": "TurnDurationEnum",
-                                    "type": "string",
-                                }
-                            },
-                            "properties": {
-                                "id": {
-                                    "anyOf": [{"type": "integer"}, {"type": "null"}],
-                                    "default": None,
-                                    "title": "Id",
-                                },
-                                "prompt": {"title": "Prompt", "type": "string"},
-                                "name": {"title": "Name", "type": "string"},
-                                "description": {
-                                    "title": "Description",
-                                    "type": "string",
-                                },
-                                "competitve": {
-                                    "title": "Competitve",
-                                    "type": "boolean",
-                                },
-                                "players_min": {
-                                    "title": "Players Min",
-                                    "type": "integer",
-                                },
-                                "players_max": {
-                                    "title": "Players Max",
-                                    "type": "integer",
-                                },
-                                "turn_duration": {
-                                    "$ref": "#/$defs/TurnDurationEnum",
-                                    "description": "how long the passing of a turn should represent for a game at this scale",
-                                },
-                            },
-                            "required": [
-                                "competitve",
-                                "description",
-                                "name",
-                                "players_max",
-                                "players_min",
-                                "prompt",
-                                "turn_duration",
-                            ],
-                            "type": "object",
-                        },
-                    },
-                }
-            ],
-            tool_choice={"type": "function", "function": {"name": "GameDefinition"}},
-        )
-    except litellm.APIConnectionError:
-        pass
 
 
 class TestBedrockEmbedding(BaseLLMEmbeddingTest):
@@ -2354,9 +1720,10 @@ class TestBedrockEmbedding(BaseLLMEmbeddingTest):
 
 @pytest.mark.asyncio
 async def test_bedrock_image_url_sync_client():
-    from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
     import logging
+
     from litellm import verbose_logger
+    from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 
     verbose_logger.setLevel(level=logging.DEBUG)
 
@@ -2406,11 +1773,12 @@ def test_bedrock_error_handling_streaming(exception_type, expected_status_code):
     (e.g. internalServerException -> 500). For 5xx this is what makes the error
     retryable downstream; for all types it replaces the misleading 400 with the
     true code. Regression for #24608."""
+    from unittest.mock import Mock
+
     from litellm.llms.bedrock.chat.invoke_handler import (
         AWSEventStreamDecoder,
         BedrockError,
     )
-    from unittest.mock import Mock
 
     event = Mock()
     event.to_response_dict = Mock(
@@ -2458,7 +1826,6 @@ def test_bedrock_custom_proxy():
 
 
 def test_bedrock_custom_deepseek():
-    from litellm.llms.custom_httpx.http_handler import HTTPHandler
     import json
 
     litellm.turn_on_debug()
@@ -2809,7 +2176,7 @@ async def test_bedrock_stream_thinking_content_openwebui():
 
 
 def test_bedrock_application_inference_profile():
-    from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler
+    from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
     client = HTTPHandler()
     client2 = HTTPHandler()
@@ -2937,8 +2304,8 @@ def test_bedrock_meta_llama_function_calling():
     Tests that:
     - meta llama models support function calling
     """
-    from litellm.utils import return_raw_request
     from litellm.types.utils import CallTypes
+    from litellm.utils import return_raw_request
 
     tools = [
         {
@@ -3039,9 +2406,10 @@ async def test_bedrock_passthrough_router():
 
 @pytest.mark.asyncio
 async def test_bedrock_converse__streaming_passthrough(monkeypatch):
+    import asyncio
+
     import litellm
     from litellm.integrations.custom_logger import CustomLogger
-    import asyncio
 
     if os.environ.get("LITELLM_RUN_LIVE_BEDROCK_PASSTHROUGH_TESTS") != "1":
         pytest.skip("Live Bedrock passthrough E2E tests are opt-in")
@@ -3092,10 +2460,9 @@ async def test_bedrock_converse__streaming_passthrough(monkeypatch):
 
 @pytest.mark.asyncio
 async def test_bedrock_streaming_passthrough_test2(monkeypatch):
-    import litellm
-    import time
     import asyncio
-    from unittest.mock import MagicMock
+
+    import litellm
     from litellm.integrations.custom_logger import CustomLogger
 
     class MockCustomLogger(CustomLogger):
@@ -3250,7 +2617,6 @@ def test_bedrock_nova_provider_detection():
     Regression test for issue #17910 where models like "amazon.nova-pro-v1:0"
     were incorrectly identified as "amazon" (Titan) instead of "nova".
     """
-    from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 
     # Test various Nova model formats
     nova_test_cases = [
@@ -3291,7 +2657,6 @@ def test_bedrock_openai_provider_detection():
     """
     Test that the OpenAI provider is correctly detected from model strings.
     """
-    from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 
     # Test various OpenAI model formats
     test_cases = [
@@ -3311,7 +2676,6 @@ def test_bedrock_openai_model_id_extraction():
     """
     Test that the model ID (ARN) is correctly extracted and encoded for OpenAI models.
     """
-    from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
 
     model = (
         "openai/arn:aws:bedrock:us-east-1:123456789012:imported-model/test-model-123"
@@ -3593,7 +2957,8 @@ def test_bedrock_nova_grounding_web_search_options_non_streaming():
 
     Related: https://docs.aws.amazon.com/nova/latest/userguide/grounding.html
     """
-    from unittest.mock import patch, MagicMock
+    from unittest.mock import patch
+
     from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
     client = HTTPHandler()
@@ -3649,6 +3014,7 @@ def test_bedrock_nova_grounding_with_function_tools():
     custom function calling capabilities.
     """
     from unittest.mock import patch
+
     from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
     client = HTTPHandler()
@@ -3732,7 +3098,8 @@ async def test_bedrock_nova_grounding_async():
 
     This test verifies the request transformation for async calls.
     """
-    from unittest.mock import patch, AsyncMock
+    from unittest.mock import AsyncMock, patch
+
     from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 
     client = AsyncHTTPHandler()
@@ -3814,7 +3181,8 @@ def test_bedrock_nova_grounding_request_transformation():
     """
     Unit test to verify that web_search_options transforms to systemTool in the request.
     """
-    from unittest.mock import patch, MagicMock
+    from unittest.mock import MagicMock, patch
+
     from litellm.llms.custom_httpx.http_handler import HTTPHandler
 
     client = HTTPHandler()

tests/llm_translation/test_bedrock_dynamic_auth_params_unit_tests.py

@@ -1,286 +0,0 @@
-# tests/llm_translation/test_base_aws_llm.py
-import json
-import pytest
-from unittest.mock import patch
-from botocore.credentials import Credentials
-
-
-import litellm
-from litellm.llms.custom_httpx.http_handler import HTTPHandler
-from unittest.mock import Mock
-from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM
-from litellm.llms.bedrock.common_utils import BedrockModelInfo
-
-
-
-
-def test_bedrock_completion_with_region_name():
-    litellm.turn_on_debug()
-    client = HTTPHandler()
-
-    with patch.object(client, "post") as mock_post:
-        mock_response = Mock()
-        # Construct a response similar to our other tests.
-        mock_response.text = json.dumps(
-            {
-                "response_id": "379ed018/60744aff-e741-4aad-bd10-74639a4ade79",
-                "text": "Hello! How's it going? I hope you're having a fantastic day!",
-                "generation_id": "38709bb9-f20f-42d9-9c61-13a73b7bbc12",
-                "chat_history": [
-                    {"role": "USER", "message": "Hello, world!"},
-                    {
-                        "role": "CHATBOT",
-                        "message": "Hello! How's it going? I hope you're having a fantastic day!",
-                    },
-                ],
-                "finish_reason": "COMPLETE",
-            }
-        )
-        mock_response.status_code = 200
-        mock_response.headers = {"Content-Type": "application/json"}
-        mock_response.json = lambda: json.loads(mock_response.text)
-        mock_post.return_value = mock_response
-
-        # Pass the client so that the HTTP call will be intercepted.
-        response = litellm.completion(
-            model="bedrock/cohere.command-r-v1:0",
-            messages=[{"role": "user", "content": "Hello, world!"}],
-            aws_region_name="us-west-12",
-            client=client,
-        )
-
-        # Ensure our post method has been called.
-        mock_post.assert_called_once()
-
-        assert (
-            mock_post.call_args.kwargs["url"]
-            == "https://bedrock-runtime.us-west-12.amazonaws.com/model/cohere.command-r-v1:0/invoke"
-        )
-        assert mock_post.call_args.kwargs["data"] == json.dumps(
-            {"message": "Hello, world!", "chat_history": []}
-        ).encode("utf-8")
-
-        # Print the URL and body of the HTTP request.
-        # assert request was signed with the correct region
-        _authorization_header = mock_post.call_args.kwargs["headers"]["Authorization"]
-        import re
-
-        # Ensure the authorization header contains the exact region segment "us-west-12/bedrock/aws4_request"
-        pattern = r"us-west-12/bedrock/aws4_request"
-        assert re.search(pattern, _authorization_header) is not None
-
-
-def test_bedrock_completion_with_dynamic_authentication_params():
-    litellm.turn_on_debug()
-    client = HTTPHandler()
-
-    with patch.object(client, "post") as mock_post:
-        mock_response = Mock()
-        # Construct a response similar to our other tests.
-        mock_response.text = json.dumps(
-            {
-                "response_id": "379ed018/60744aff-e741-4aad-bd10-74639a4ade79",
-                "text": "Hello! How's it going? I hope you're having a fantastic day!",
-                "generation_id": "38709bb9-f20f-42d9-9c61-13a73b7bbc12",
-                "chat_history": [
-                    {"role": "USER", "message": "Hello, world!"},
-                    {
-                        "role": "CHATBOT",
-                        "message": "Hello! How's it going? I hope you're having a fantastic day!",
-                    },
-                ],
-                "finish_reason": "COMPLETE",
-            }
-        )
-        mock_response.status_code = 200
-        mock_response.headers = {"Content-Type": "application/json"}
-        mock_response.json = lambda: json.loads(mock_response.text)
-        mock_post.return_value = mock_response
-
-        # Pass the client so that the HTTP call will be intercepted.
-        response = litellm.completion(
-            model="bedrock/cohere.command-r-v1:0",
-            messages=[{"role": "user", "content": "Hello, world!"}],
-            aws_access_key_id="dynamically_generated_access_key_id",
-            aws_secret_access_key="dynamically_generated_secret_access_key",
-            client=client,
-        )
-
-        # Ensure our post method has been called.
-        mock_post.assert_called_once()
-        import re
-
-        # Get authorization header
-        _authorization_header = mock_post.call_args.kwargs["headers"]["Authorization"]
-
-        # Check for exact credential pattern
-        pattern = r"AWS4-HMAC-SHA256 Credential=dynamically_generated_access_key_id/\d{8}/[a-z0-9-]+/bedrock/aws4_request"
-        assert re.search(pattern, _authorization_header) is not None
-
-
-def test_bedrock_completion_with_dynamic_bedrock_runtime_endpoint():
-    litellm.turn_on_debug()
-    client = HTTPHandler()
-
-    with patch.object(client, "post") as mock_post:
-        mock_response = Mock()
-        # Construct a response similar to our other tests.
-        mock_response.text = json.dumps(
-            {
-                "response_id": "379ed018/60744aff-e741-4aad-bd10-74639a4ade79",
-                "text": "Hello! How's it going? I hope you're having a fantastic day!",
-                "generation_id": "38709bb9-f20f-42d9-9c61-13a73b7bbc12",
-                "chat_history": [
-                    {"role": "USER", "message": "Hello, world!"},
-                    {
-                        "role": "CHATBOT",
-                        "message": "Hello! How's it going? I hope you're having a fantastic day!",
-                    },
-                ],
-                "finish_reason": "COMPLETE",
-            }
-        )
-        mock_response.status_code = 200
-        mock_response.headers = {"Content-Type": "application/json"}
-        mock_response.json = lambda: json.loads(mock_response.text)
-        mock_post.return_value = mock_response
-
-        # Pass the client so that the HTTP call will be intercepted.
-        response = litellm.completion(
-            model="bedrock/cohere.command-r-v1:0",
-            messages=[{"role": "user", "content": "Hello, world!"}],
-            aws_bedrock_runtime_endpoint="https://my-fake-endpoint.com",
-            client=client,
-        )
-
-        # Ensure our post method has been called.
-        mock_post.assert_called_once()
-        assert (
-            mock_post.call_args.kwargs["url"]
-            == "https://my-fake-endpoint.com/model/cohere.command-r-v1:0/invoke"
-        )
-
-
-# ------------------------------------------------------------------------------
-# A dummy credentials object to return from get_credentials.
-# (It must have attributes so that SigV4Auth.add_auth doesn't break.)
-# ------------------------------------------------------------------------------
-class DummyCredentials:
-    access_key = "dummy_access"
-    secret_key = "dummy_secret"
-    token = "dummy_token"
-
-
-# ------------------------------------------------------------------------------
-# This test makes sure that a given dynamic parameter is passed into the call
-# to BaseAWSLLM.get_credentials. (Some dynamic params—for example aws_region_name
-# or aws_bedrock_runtime_endpoint—are already covered by other tests.)
-# ------------------------------------------------------------------------------
-@pytest.mark.parametrize(
-    "model",
-    [
-        "bedrock/converse/cohere.command-r-v1:0",
-        "amazon.nova-2-lite-v1:0",
-        "bedrock/cohere.command-r-v1:0",
-        "bedrock/invoke/cohere.command-r-v1:0",
-    ],
-)
-@pytest.mark.parametrize(
-    "param_name, param_value, expected_credentials_value",
-    [
-        ("aws_session_token", "dummy_session_token", "dummy_session_token"),
-        ("aws_session_name", "dummy_session_name", "dummy_session_name"),
-        ("aws_profile_name", "dummy_profile_name", "dummy_profile_name"),
-        ("aws_role_name", "dummy_role_name", "dummy_role_name"),
-        ("aws_web_identity_token", "dummy_web_identity_token", "dummy_web_identity_token"),
-        ("aws_sts_endpoint", "dummy_sts_endpoint", "dummy_sts_endpoint"),
-        ("aws_external_id", "dummy_external_id", "dummy_external_id"),
-        ("aws_session_tags", [{"Key": "team", "Value": "genai"}], ({"Key": "team", "Value": "genai"},)),
-    ],
-)
-def test_dynamic_aws_params_propagation(model, param_name, param_value, expected_credentials_value):
-    """
-    When passed to litellm.completion, each dynamic AWS authentication parameter
-    should propagate down to the get_credentials() call in BaseAWSLLM.
-
-    Also tests different model parameter values.
-    """
-    client = HTTPHandler()
-
-    # Base parameters required for the completion call.
-    # (We include aws_access_key_id and aws_secret_access_key so that the correct auth
-    # branch in get_credentials() is reached.)
-    base_params = {
-        "model": model,
-        "messages": [{"role": "user", "content": "Hello, world!"}],
-        "aws_access_key_id": "dummy_access",
-        "aws_secret_access_key": "dummy_secret",
-        "client": client,
-    }
-    # For parameters such as aws_role_name or aws_web_identity_token a session name is required.
-    if param_name in ("aws_role_name", "aws_web_identity_token"):
-        base_params["aws_session_name"] = "dummy_session_name"
-        if param_name == "aws_web_identity_token":
-            # The web identity branch also requires a role name.
-            base_params["aws_role_name"] = "dummy_role_name"
-    # Inject the dynamic parameter under test.
-    base_params[param_name] = param_value
-
-    # Patch SigV4Auth in the signing (so that no actual signing is done).
-    with patch("botocore.auth.SigV4Auth", autospec=True) as mock_sigv4:
-        instance = mock_sigv4.return_value
-        instance.add_auth.return_value = None
-
-        # Patch BaseAWSLLM.get_credentials so that we can capture its kwargs.
-        def dummy_get_credentials(**kwargs):
-            dummy_get_credentials.called_kwargs = kwargs  # type: ignore[attr-defined]
-            return DummyCredentials()
-
-        with patch.object(
-            BaseAWSLLM, "get_credentials", side_effect=dummy_get_credentials
-        ):
-            # Patch the HTTP client's post method to avoid an actual HTTP call.
-            with patch.object(client, "post") as mock_post:
-                mock_response = Mock()
-                mock_response.text = json.dumps(
-                    {
-                        "response_id": "dummy_response",
-                        "text": "Hello! world",
-                        "generation_id": "dummy_gen",
-                        "chat_history": [],
-                        "finish_reason": "COMPLETE",
-                    }
-                )
-                if BedrockModelInfo.get_bedrock_route(model) == "converse":
-                    mock_response.text = json.dumps(
-                        {
-                            "output": {
-                                "message": {
-                                    "role": "assistant",
-                                    "content": [{"text": "Here's a joke..."}],
-                                }
-                            },
-                            "usage": {
-                                "inputTokens": 12,
-                                "outputTokens": 6,
-                                "totalTokens": 18,
-                            },
-                            "stopReason": "stop",
-                        }
-                    )
-
-                mock_response.status_code = 200
-                mock_response.headers = {"Content-Type": "application/json"}
-                mock_response.json = lambda: json.loads(mock_response.text)
-                mock_post.return_value = mock_response
-
-                # Call litellm.completion with our base & dynamic parameters.
-                litellm.completion(**base_params)
-
-                print(
-                    "get_credentials.called_kwargs",
-                    json.dumps(dummy_get_credentials.called_kwargs, indent=4),
-                )
-
-                # We now assert that get_credentials() was called with the dynamic param.
-                assert dummy_get_credentials.called_kwargs.get(param_name) == expected_credentials_value

tests/llm_translation/test_bedrock_govcloud.py

@@ -1,588 +0,0 @@
-"""
-Tests for AWS Bedrock GovCloud model support
-"""
-
-import os
-
-os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"  # Load from local file
-
-import pytest
-from unittest.mock import Mock, patch
-
-# Import modules that need to be reloaded
-import importlib
-import litellm.litellm_core_utils.get_model_cost_map
-import litellm
-
-# Reload modules to pick up environment variable
-importlib.reload(litellm.litellm_core_utils.get_model_cost_map)
-importlib.reload(litellm)
-
-from litellm import completion
-from litellm.llms.bedrock.common_utils import (
-    BedrockModelInfo,
-    AmazonBedrockGlobalConfig,
-)
-
-
-class TestBedrockGovCloudSupport:
-    """Test suite for GovCloud model support in Bedrock"""
-
-    def test_govcloud_regions_in_config(self):
-        """Test that GovCloud regions are included in the configuration"""
-        config = AmazonBedrockGlobalConfig()
-        us_regions = config.get_us_regions()
-
-        assert "us-gov-east-1" in us_regions
-        assert "us-gov-west-1" in us_regions
-
-        all_regions = config.get_all_regions()
-        assert "us-gov-east-1" in all_regions
-        assert "us-gov-west-1" in all_regions
-
-    def test_govcloud_model_routing(self):
-        """Test that GovCloud models are routed correctly"""
-        # Test Claude model routing
-        route = BedrockModelInfo.get_bedrock_route(
-            "bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0"
-        )
-        assert route == "converse"
-
-        route = BedrockModelInfo.get_bedrock_route(
-            "bedrock/us-gov-west-1/anthropic.claude-3-haiku-20240307-v1:0"
-        )
-        assert route == "converse"
-
-        # Test Llama model routing
-        route = BedrockModelInfo.get_bedrock_route(
-            "bedrock/us-gov-east-1/meta.llama3-8b-instruct-v1:0"
-        )
-        assert route == "converse"
-
-        route = BedrockModelInfo.get_bedrock_route(
-            "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0"
-        )
-        assert route == "converse"
-
-        # Test Titan model routing (should use invoke)
-        route = BedrockModelInfo.get_bedrock_route(
-            "bedrock/us-gov-east-1/amazon.titan-text-lite-v1"
-        )
-        assert route == "invoke"
-
-    def test_base_model_extraction(self):
-        """Test that base model names are correctly extracted from GovCloud models"""
-        # Test GovCloud model extraction
-        base_model = BedrockModelInfo.get_base_model(
-            "bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0"
-        )
-        assert base_model == "anthropic.claude-haiku-4-5-20251001-v1:0"
-
-        base_model = BedrockModelInfo.get_base_model(
-            "bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0"
-        )
-        assert base_model == "meta.llama3-8b-instruct-v1:0"
-
-    @patch("litellm.llms.bedrock.common_utils.init_bedrock_client")
-    def test_govcloud_client_initialization(self, mock_init_client):
-        """Test that Bedrock client can be initialized with GovCloud regions"""
-        mock_client = Mock()
-        mock_init_client.return_value = mock_client
-
-        # Test that init_bedrock_client accepts GovCloud regions
-        from litellm.llms.bedrock.common_utils import init_bedrock_client
-
-        # This should not raise an error
-        client = init_bedrock_client(
-            region_name="us-gov-east-1",
-            aws_access_key_id=None,
-            aws_secret_access_key=None,
-            aws_region_name="us-gov-east-1",
-            aws_bedrock_runtime_endpoint=None,
-            aws_session_name=None,
-            aws_profile_name=None,
-            aws_role_name=None,
-            aws_web_identity_token=None,
-            extra_headers=None,
-            timeout=None,
-        )
-
-        assert mock_init_client.called
-
-    def test_govcloud_model_in_bedrock_models_list(self):
-        """Test that GovCloud models are NOT included in bedrock_models list (they are pricing-only)"""
-        # Regional models including GovCloud should be excluded from bedrock_models list
-        # They are only in model_cost for pricing purposes
-        assert not any("us-gov-east-1" in model for model in litellm.bedrock_models)
-        assert not any("us-gov-west-1" in model for model in litellm.bedrock_models)
-
-    @patch("litellm.completion")
-    def test_govcloud_completion_cost_calculation(self, mock_completion):
-        """Test that completion requests use correct pricing for GovCloud models"""
-        from litellm import completion_cost, Choices, Message, ModelResponse
-        from litellm.utils import Usage
-
-        # Mock completion response for base model
-        # Use us.* inference profile ID to match us.* pricing ($1.10/$5.50 per MTok)
-        base_model_response = ModelResponse(
-            id="test-base",
-            choices=[
-                Choices(
-                    finish_reason="stop",
-                    index=0,
-                    message=Message(content="Hello", role="assistant"),
-                )
-            ],
-            created=1234567890,
-            model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-            object="chat.completion",
-            system_fingerprint=None,
-            usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-        )
-        base_model_response._hidden_params = {
-            "custom_llm_provider": "bedrock",
-            "region_name": "us-east-1",
-        }
-
-        # Mock completion response for gov model
-        # GovCloud responses use base anthropic.* model ID; pricing is looked up
-        # via bedrock/us-gov-east-1/anthropic.* entries in model_cost
-        gov_model_response = ModelResponse(
-            id="test-gov",
-            choices=[
-                Choices(
-                    finish_reason="stop",
-                    index=0,
-                    message=Message(content="Hello", role="assistant"),
-                )
-            ],
-            created=1234567890,
-            model="anthropic.claude-haiku-4-5-20251001-v1:0",
-            object="chat.completion",
-            system_fingerprint=None,
-            usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-        )
-        gov_model_response._hidden_params = {
-            "custom_llm_provider": "bedrock",
-            "region_name": "us-gov-east-1",
-        }
-
-        # Mock completion response for gov-west model
-        gov_west_model_response = ModelResponse(
-            id="test-gov-west",
-            choices=[
-                Choices(
-                    finish_reason="stop",
-                    index=0,
-                    message=Message(content="Hello", role="assistant"),
-                )
-            ],
-            created=1234567890,
-            model="anthropic.claude-haiku-4-5-20251001-v1:0",
-            object="chat.completion",
-            system_fingerprint=None,
-            usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-        )
-        gov_west_model_response._hidden_params = {
-            "custom_llm_provider": "bedrock",
-            "region_name": "us-gov-west-1",
-        }
-
-        # Test messages
-        messages = [{"role": "user", "content": "Hello, how are you?"}]
-
-        # Calculate costs using the standard Bedrock format with region parameter
-        # Base model uses us.* inference profile — no region_name needed since
-        # the response model already contains the us.* prefix for pricing lookup.
-        base_cost = completion_cost(
-            model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0",
-            completion_response=base_model_response,
-            messages=messages,
-        )
-
-        # GovCloud models use region_name to look up bedrock/us-gov-*/anthropic.* pricing
-        gov_east_cost = completion_cost(
-            model="bedrock/anthropic.claude-haiku-4-5-20251001-v1:0",
-            completion_response=gov_model_response,
-            messages=messages,
-            region_name="us-gov-east-1",
-        )
-
-        gov_west_cost = completion_cost(
-            model="bedrock/anthropic.claude-haiku-4-5-20251001-v1:0",
-            completion_response=gov_west_model_response,
-            messages=messages,
-            region_name="us-gov-west-1",
-        )
-
-        # Expected costs based on pricing:
-        # Base model (us.*): 10 * 1.1e-06 + 5 * 5.5e-06 = 1.1e-05 + 2.75e-05 = 3.85e-05
-        # Gov models: 10 * 1.2e-06 + 5 * 6e-06 = 1.2e-05 + 3e-05 = 4.2e-05
-        expected_base_cost = 10 * 1.1e-06 + 5 * 5.5e-06
-        expected_gov_cost = 10 * 1.2e-06 + 5 * 6e-06
-
-        # Verify costs are calculated correctly
-        assert (
-            abs(base_cost - expected_base_cost) < 1e-10
-        ), f"Base cost mismatch: got {base_cost}, expected {expected_base_cost}"
-        assert (
-            abs(gov_east_cost - expected_gov_cost) < 1e-10
-        ), f"Gov East cost mismatch: got {gov_east_cost}, expected {expected_gov_cost}"
-        assert (
-            abs(gov_west_cost - expected_gov_cost) < 1e-10
-        ), f"Gov West cost mismatch: got {gov_west_cost}, expected {expected_gov_cost}"
-
-        # Verify GovCloud costs are approximately 20% higher than base cost
-        assert (
-            abs(gov_east_cost / base_cost - 1.2) < 0.15
-        ), f"Gov East cost should be ~20% higher than base: got {gov_east_cost}, base {base_cost}"
-        assert (
-            abs(gov_west_cost / base_cost - 1.2) < 0.15
-        ), f"Gov West cost should be ~20% higher than base: got {gov_west_cost}, base {base_cost}"
-
-        # Test with different token counts
-        large_response = ModelResponse(
-            id="test-large",
-            choices=[
-                Choices(
-                    finish_reason="stop",
-                    index=0,
-                    message=Message(content="A longer response", role="assistant"),
-                )
-            ],
-            created=1234567890,
-            model="us.anthropic.claude-haiku-4-5-20251001-v1:0",
-            object="chat.completion",
-            system_fingerprint=None,
-            usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150),
-        )
-        large_response._hidden_params = {
-            "custom_llm_provider": "bedrock",
-            "region_name": "us-east-1",
-        }
-
-        large_base_cost = completion_cost(
-            model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0",
-            completion_response=large_response,
-            messages=messages,
-        )
-
-        # Create large response for gov model
-        large_gov_response = ModelResponse(
-            id="test-large-gov",
-            choices=[
-                Choices(
-                    finish_reason="stop",
-                    index=0,
-                    message=Message(content="A longer response", role="assistant"),
-                )
-            ],
-            created=1234567890,
-            model="anthropic.claude-haiku-4-5-20251001-v1:0",
-            object="chat.completion",
-            system_fingerprint=None,
-            usage=Usage(prompt_tokens=100, completion_tokens=50, total_tokens=150),
-        )
-        large_gov_response._hidden_params = {
-            "custom_llm_provider": "bedrock",
-            "region_name": "us-gov-east-1",
-        }
-
-        large_gov_cost = completion_cost(
-            model="bedrock/anthropic.claude-haiku-4-5-20251001-v1:0",
-            completion_response=large_gov_response,
-            messages=messages,
-            region_name="us-gov-east-1",
-        )
-
-        # Expected costs for larger response:
-        # Base model (us.*): 100 * 1.1e-06 + 50 * 5.5e-06 = 1.1e-04 + 2.75e-04 = 3.85e-04
-        # Gov model: 100 * 1.2e-06 + 50 * 6e-06 = 1.2e-04 + 3e-04 = 4.2e-04
-        expected_large_base_cost = 100 * 1.1e-06 + 50 * 5.5e-06
-        expected_large_gov_cost = 100 * 1.2e-06 + 50 * 6e-06
-
-        assert (
-            abs(large_base_cost - expected_large_base_cost) < 1e-10
-        ), f"Large base cost mismatch: got {large_base_cost}, expected {expected_large_base_cost}"
-        assert (
-            abs(large_gov_cost - expected_large_gov_cost) < 1e-10
-        ), f"Large gov cost mismatch: got {large_gov_cost}, expected {expected_large_gov_cost}"
-        assert (
-            abs(large_gov_cost / large_base_cost - 1.2) < 0.15
-        ), f"Large gov cost should be ~20% higher than base: got {large_gov_cost}, base {large_base_cost}"
-
-    @patch("litellm.llms.custom_httpx.http_handler.HTTPHandler.post")
-    def test_govcloud_completion_with_cost_tracking(self, mock_post):
-        """Test that completion requests with cost tracking use correct pricing for GovCloud models"""
-        from unittest.mock import Mock
-        import json
-
-        # Mock the HTTP client's post method to return responses
-        def mock_post_side_effect(url, headers=None, data=None, **kwargs):
-            # Extract region from the URL to determine which response to return
-            region = "us-east-1"  # default
-            if "us-gov-east-1" in url:
-                region = "us-gov-east-1"
-            elif "us-gov-west-1" in url:
-                region = "us-gov-west-1"
-
-            # Create mock response based on region
-            mock_response = Mock()
-            mock_response.status_code = 200
-            mock_response.headers = {}
-
-            # Create a realistic Bedrock converse response structure
-            bedrock_response = {
-                "output": {
-                    "message": {
-                        "role": "assistant",
-                        "content": [{"type": "text", "text": f"Hello from {region}"}],
-                    }
-                },
-                "usage": {"inputTokens": 15, "outputTokens": 8, "totalTokens": 23},
-                "stopReason": "end_turn",
-            }
-
-            mock_response.json.return_value = bedrock_response
-            mock_response.text = json.dumps(bedrock_response)
-            mock_response.raise_for_status = Mock()  # Don't raise exceptions
-
-            return mock_response
-
-        mock_post.side_effect = mock_post_side_effect
-
-        # Test base model completion
-        base_result = completion(
-            model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0",
-            messages=[{"role": "user", "content": "Hello"}],
-            aws_region_name="us-east-1",
-        )
-
-        # Test gov-east model completion
-        # GovCloud users specify the base anthropic.* model ID with the gov region
-        gov_east_result = completion(
-            model="bedrock/anthropic.claude-haiku-4-5-20251001-v1:0",
-            messages=[{"role": "user", "content": "Hello"}],
-            aws_region_name="us-gov-east-1",
-        )
-
-        # Test gov-west model completion
-        gov_west_result = completion(
-            model="bedrock/anthropic.claude-haiku-4-5-20251001-v1:0",
-            messages=[{"role": "user", "content": "Hello"}],
-            aws_region_name="us-gov-west-1",
-        )
-
-        # Verify the mock was called correctly
-        assert mock_post.call_count == 3
-
-        # Verify usage information is present
-        from litellm.types.utils import ModelResponse
-
-        assert isinstance(base_result, ModelResponse)
-        assert isinstance(gov_east_result, ModelResponse)
-        assert isinstance(gov_west_result, ModelResponse)
-
-        base_result_typed: ModelResponse = base_result
-        gov_east_result_typed: ModelResponse = gov_east_result
-        gov_west_result_typed: ModelResponse = gov_west_result
-
-        # Verify usage information is present
-        assert (
-            hasattr(base_result_typed, "usage")
-            and base_result_typed.usage.prompt_tokens == 15
-        )
-        assert (
-            hasattr(base_result_typed, "usage")
-            and base_result_typed.usage.completion_tokens == 8
-        )
-        assert (
-            hasattr(gov_east_result_typed, "usage")
-            and gov_east_result_typed.usage.prompt_tokens == 15
-        )
-        assert (
-            hasattr(gov_east_result_typed, "usage")
-            and gov_east_result_typed.usage.completion_tokens == 8
-        )
-        assert (
-            hasattr(gov_west_result_typed, "usage")
-            and gov_west_result_typed.usage.prompt_tokens == 15
-        )
-        assert (
-            hasattr(gov_west_result_typed, "usage")
-            and gov_west_result_typed.usage.completion_tokens == 8
-        )
-
-        # Verify cost calculation uses correct pricing for each region
-        # Get costs directly from the completion response _hidden_params
-        base_cost = base_result_typed._hidden_params.get("response_cost", 0.0)
-        gov_east_cost = gov_east_result_typed._hidden_params.get("response_cost", 0.0)
-        gov_west_cost = gov_west_result_typed._hidden_params.get("response_cost", 0.0)
-
-        print(f"Base cost: {base_cost}")
-        print(f"Gov East cost: {gov_east_cost}")
-        print(f"Gov West cost: {gov_west_cost}")
-
-        # Expected costs based on pricing:
-        # Base model (us.*): 15 * 1.1e-06 + 8 * 5.5e-06 = 1.65e-05 + 4.4e-05 = 6.05e-05
-        # Gov models: 15 * 1.2e-06 + 8 * 6e-06 = 1.8e-05 + 4.8e-05 = 6.6e-05
-        expected_base_cost = 15 * 1.1e-06 + 8 * 5.5e-06
-        expected_gov_cost = 15 * 1.2e-06 + 8 * 6e-06
-
-        # Verify costs are calculated correctly
-        assert (
-            abs(base_cost - expected_base_cost) < 1e-10
-        ), f"Base cost mismatch: got {base_cost}, expected {expected_base_cost}"
-        assert (
-            abs(gov_east_cost - expected_gov_cost) < 1e-10
-        ), f"Gov East cost mismatch: got {gov_east_cost}, expected {expected_gov_cost}"
-        assert (
-            abs(gov_west_cost - expected_gov_cost) < 1e-10
-        ), f"Gov West cost mismatch: got {gov_west_cost}, expected {expected_gov_cost}"
-
-        # Verify GovCloud costs are approximately 20% higher than base cost
-        assert (
-            abs(gov_east_cost / base_cost - 1.2) < 0.15
-        ), f"Gov East cost should be ~20% higher than base: got {gov_east_cost}, base {base_cost}"
-        assert (
-            abs(gov_west_cost / base_cost - 1.2) < 0.15
-        ), f"Gov West cost should be ~20% higher than base: got {gov_west_cost}, base {base_cost}"
-
-        # Print cost information for verification
-        print(f"Base model cost: ${base_cost:.6f}")
-        print(f"GovCloud East cost: ${gov_east_cost:.6f}")
-        print(f"GovCloud West cost: ${gov_west_cost:.6f}")
-        print(f"GovCloud cost increase: {((gov_east_cost / base_cost) - 1) * 100:.1f}%")
-
-    def test_govcloud_cost_per_token_with_region(self):
-        """Test that cost_per_token function correctly uses region-based pricing for GovCloud models"""
-        from litellm import cost_per_token
-        from litellm.utils import Usage
-
-        # Test usage object
-        usage = Usage(prompt_tokens=20, completion_tokens=10, total_tokens=30)
-
-        # Commercial list pricing uses the us.* inference profile id; GovCloud keys use anthropic.* + region
-        haiku_us_id = "us.anthropic.claude-haiku-4-5-20251001-v1:0"
-        haiku_anthropic_id = "anthropic.claude-haiku-4-5-20251001-v1:0"
-        # Test base model with standard region
-        base_prompt_cost, base_completion_cost = cost_per_token(
-            model=haiku_us_id,
-            prompt_tokens=20,
-            completion_tokens=10,
-            custom_llm_provider="bedrock",
-            region_name="us-east-1",
-        )
-
-        # Test gov models with gov regions
-        gov_east_prompt_cost, gov_east_completion_cost = cost_per_token(
-            model=haiku_anthropic_id,
-            prompt_tokens=20,
-            completion_tokens=10,
-            custom_llm_provider="bedrock",
-            region_name="us-gov-east-1",
-        )
-
-        gov_west_prompt_cost, gov_west_completion_cost = cost_per_token(
-            model=haiku_anthropic_id,
-            prompt_tokens=20,
-            completion_tokens=10,
-            custom_llm_provider="bedrock",
-            region_name="us-gov-west-1",
-        )
-
-        # Expected costs:
-        # Base model (us.*): 20 * 1.1e-06 + 10 * 5.5e-06 = 2.2e-05 + 5.5e-05 = 7.7e-05
-        # Gov models: 20 * 1.2e-06 + 10 * 6e-06 = 2.4e-05 + 6e-05 = 8.4e-05
-        expected_base_prompt_cost = 20 * 1.1e-06
-        expected_base_completion_cost = 10 * 5.5e-06
-        expected_gov_prompt_cost = 20 * 1.2e-06
-        expected_gov_completion_cost = 10 * 6e-06
-
-        # Verify costs are calculated correctly
-        assert (
-            abs(base_prompt_cost - expected_base_prompt_cost) < 1e-10
-        ), f"Base prompt cost mismatch: got {base_prompt_cost}, expected {expected_base_prompt_cost}"
-        assert (
-            abs(base_completion_cost - expected_base_completion_cost) < 1e-10
-        ), f"Base completion cost mismatch: got {base_completion_cost}, expected {expected_base_completion_cost}"
-
-        assert (
-            abs(gov_east_prompt_cost - expected_gov_prompt_cost) < 1e-10
-        ), f"Gov East prompt cost mismatch: got {gov_east_prompt_cost}, expected {expected_gov_prompt_cost}"
-        assert (
-            abs(gov_east_completion_cost - expected_gov_completion_cost) < 1e-10
-        ), f"Gov East completion cost mismatch: got {gov_east_completion_cost}, expected {expected_gov_completion_cost}"
-
-        assert (
-            abs(gov_west_prompt_cost - expected_gov_prompt_cost) < 1e-10
-        ), f"Gov West prompt cost mismatch: got {gov_west_prompt_cost}, expected {expected_gov_prompt_cost}"
-        assert (
-            abs(gov_west_completion_cost - expected_gov_completion_cost) < 1e-10
-        ), f"Gov West completion cost mismatch: got {gov_west_completion_cost}, expected {expected_gov_completion_cost}"
-
-        # Verify GovCloud costs are approximately 20% higher than base costs
-        # (uses 1e-8 tolerance because GovCloud prices are independently rounded, not exact * 1.2)
-        assert (
-            abs(gov_east_prompt_cost / base_prompt_cost - 1.2) < 0.15
-        ), f"Gov East prompt cost should be ~20% higher than base: got {gov_east_prompt_cost}, base {base_prompt_cost}"
-        assert (
-            abs(gov_east_completion_cost / base_completion_cost - 1.2) < 0.15
-        ), f"Gov East completion cost should be ~20% higher than base: got {gov_east_completion_cost}, base {base_completion_cost}"
-        assert (
-            abs(gov_west_prompt_cost / base_prompt_cost - 1.2) < 0.15
-        ), f"Gov West prompt cost should be ~20% higher than base: got {gov_west_prompt_cost}, base {base_prompt_cost}"
-        assert (
-            abs(gov_west_completion_cost / base_completion_cost - 1.2) < 0.15
-        ), f"Gov West completion cost should be ~20% higher than base: got {gov_west_completion_cost}, base {base_completion_cost}"
-
-        # Test total costs
-        base_total_cost = base_prompt_cost + base_completion_cost
-        gov_east_total_cost = gov_east_prompt_cost + gov_east_completion_cost
-        gov_west_total_cost = gov_west_prompt_cost + gov_west_completion_cost
-
-        expected_base_total = expected_base_prompt_cost + expected_base_completion_cost
-        expected_gov_total = expected_gov_prompt_cost + expected_gov_completion_cost
-
-        assert (
-            abs(base_total_cost - expected_base_total) < 1e-10
-        ), f"Base total cost mismatch: got {base_total_cost}, expected {expected_base_total}"
-        assert (
-            abs(gov_east_total_cost - expected_gov_total) < 1e-10
-        ), f"Gov East total cost mismatch: got {gov_east_total_cost}, expected {expected_gov_total}"
-        assert (
-            abs(gov_west_total_cost - expected_gov_total) < 1e-10
-        ), f"Gov West total cost mismatch: got {gov_west_total_cost}, expected {expected_gov_total}"
-        assert (
-            abs(gov_east_total_cost / base_total_cost - 1.2) < 0.15
-        ), f"Gov East total cost should be ~20% higher than base: got {gov_east_total_cost}, base {base_total_cost}"
-        assert (
-            abs(gov_west_total_cost / base_total_cost - 1.2) < 0.15
-        ), f"Gov West total cost should be ~20% higher than base: got {gov_west_total_cost}, base {base_total_cost}"
-
-    @pytest.mark.parametrize(
-        "model_name",
-        [
-            "bedrock/us-gov-east-1/anthropic.claude-haiku-4-5-20251001-v1:0",
-            "bedrock/us-gov-west-1/anthropic.claude-3-haiku-20240307-v1:0",
-            "bedrock/us-gov-east-1/meta.llama3-8b-instruct-v1:0",
-            "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0",
-        ],
-    )
-    def test_govcloud_converse_models(self, model_name):
-        """Test that GovCloud Claude and Llama models support Converse API"""
-        route = BedrockModelInfo.get_bedrock_route(model_name)
-        assert route == "converse"
-
-    @pytest.mark.parametrize(
-        "model_name",
-        [
-            "bedrock/us-gov-east-1/amazon.titan-text-lite-v1",
-            "bedrock/us-gov-west-1/amazon.titan-text-express-v1",
-            "bedrock/us-gov-east-1/amazon.titan-text-premier-v1:0",
-        ],
-    )
-    def test_govcloud_invoke_models(self, model_name):
-        """Test that GovCloud Titan models use Invoke API"""
-        route = BedrockModelInfo.get_bedrock_route(model_name)
-        assert route == "invoke"

tests/llm_translation/test_bedrock_nova_embedding.py

@@ -10,13 +10,9 @@ Tests cover:
 - Error handling
 """
 
-import json
-from unittest.mock import MagicMock, Mock, patch
 
 import pytest
 
-
-import litellm
 from litellm.llms.bedrock.embed.amazon_nova_transformation import (
     AmazonNovaEmbeddingConfig,
 )
@@ -532,100 +528,11 @@ class TestNovaTransformationResponse:
 class TestNovaEmbeddingIntegration:
     """Integration tests for Nova embeddings through LiteLLM."""
 
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_sync_text_embedding_e2e(self):
-        """End-to-end test for synchronous text embedding."""
-        response = litellm.embedding(
-            model="bedrock/amazon.nova-2-multimodal-embeddings-v1:0",
-            input=["Hello, world!"],
-            aws_region_name="us-east-1",
-        )
 
-        assert response is not None
-        assert len(response.data) == 1
-        assert len(response.data[0].embedding) > 0
 
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_async_text_embedding_e2e(self):
-        """End-to-end test for asynchronous text embedding."""
-        response = litellm.embedding(
-            model="bedrock/async_invoke/amazon.nova-2-multimodal-embeddings-v1:0",
-            input=["Long text content for segmentation..."],
-            aws_region_name="us-east-1",
-            output_s3_uri="s3://my-bucket/output/",
-            segmentation_config={"maxLengthChars": 10000},
-        )
 
-        assert response is not None
-        assert hasattr(response, "_hidden_params")
-        assert hasattr(response._hidden_params, "_invocation_arn")
 
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_image_embedding_e2e(self):
-        """End-to-end test for image embedding."""
-        response = litellm.embedding(
-            model="bedrock/amazon.nova-2-multimodal-embeddings-v1:0",
-            input=["s3://my-bucket/image.png"],
-            aws_region_name="us-east-1",
-            input_type="image",
-            format="png",
-            embedding_purpose="IMAGE_RETRIEVAL",
-        )
 
-        assert response is not None
-        assert len(response.data) == 1
-
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_video_embedding_e2e(self):
-        """End-to-end test for video embedding."""
-        response = litellm.embedding(
-            model="bedrock/amazon.nova-2-multimodal-embeddings-v1:0",
-            input=["s3://my-bucket/video.mp4"],
-            aws_region_name="us-east-1",
-            input_type="video",
-            format="mp4",
-            embedding_mode="AUDIO_VIDEO_COMBINED",
-            embedding_purpose="VIDEO_RETRIEVAL",
-        )
-
-        assert response is not None
-        assert len(response.data) == 1
-
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_different_dimensions(self):
-        """Test different embedding dimensions."""
-        for dimension in [256, 384, 1024, 3072]:
-            response = litellm.embedding(
-                model="bedrock/amazon.nova-2-multimodal-embeddings-v1:0",
-                input=["Test text"],
-                aws_region_name="us-east-1",
-                dimensions=dimension,
-            )
-
-            assert response is not None
-            assert len(response.data[0].embedding) == dimension
-
-    @pytest.mark.skip(reason="Requires AWS credentials and actual API calls")
-    def test_different_embedding_purposes(self):
-        """Test different embedding purposes."""
-        purposes = [
-            "GENERIC_INDEX",
-            "GENERIC_RETRIEVAL",
-            "TEXT_RETRIEVAL",
-            "CLASSIFICATION",
-            "CLUSTERING",
-        ]
-
-        for purpose in purposes:
-            response = litellm.embedding(
-                model="bedrock/amazon.nova-2-multimodal-embeddings-v1:0",
-                input=["Test text"],
-                aws_region_name="us-east-1",
-                embedding_purpose=purpose,
-            )
-
-            assert response is not None
-            assert len(response.data) == 1
 
 
 class TestNovaProviderDetection:

tests/llm_translation/test_cohere.py

@@ -4,14 +4,13 @@ from dotenv import load_dotenv
 
 load_dotenv()
 import io
-
 import json
+from unittest.mock import AsyncMock, patch
 
 import pytest
 
 import litellm
 from litellm import RateLimitError, Timeout, completion, completion_cost, embedding
-from unittest.mock import AsyncMock, patch
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
 
 litellm.num_retries = 3
@@ -106,7 +105,6 @@ def test_completion_cohere_command_r_plus_function_call():
         pytest.fail(f"Error occurred: {e}")
 
 
-# @pytest.mark.skip(reason="flaky test, times out frequently")
 @pytest.mark.flaky(retries=6, delay=1)
 def test_completion_cohere():
     try:

tests/llm_translation/test_cometapi_chat_transformation.py

@@ -8,42 +8,7 @@ import os
 
 import pytest
 
-
-
-
 # Integration test example (requires real API key)
-@pytest.mark.skip(reason="Skipping integration test")
-def test_cometapi_integration():
-    """
-    Integration test - requires real API key
-    Run with: pytest -k test_cometapi_integration -s
-    """
-    from litellm import completion
-
-    # Try to get API key from multiple environment variables
-    api_key = (
-        os.getenv("COMETAPI_API_KEY")
-        or os.getenv("COMETAPI_KEY")
-        or os.getenv("COMET_API_KEY")
-    )
-
-    if not api_key:
-        pytest.skip("COMETAPI_API_KEY not set - skipping integration test")
-
-    response = completion(
-        model="cometapi/gpt-3.5-turbo",
-        messages=[{"role": "user", "content": "Say hello in one word"}],
-        api_key=api_key,
-        max_tokens=10,
-        temperature=0.7,
-    )
-
-    # Verify response structure
-    assert response.choices[0].message.content
-    assert len(response.choices[0].message.content.strip()) > 0
-    assert response.model
-    assert response.usage
-    assert response.usage.total_tokens > 0
 
 
 def test_cometapi_streaming_integration():

tests/llm_translation/test_convert_dict_to_image.py

@@ -1,220 +0,0 @@
-import json
-from datetime import datetime
-
-
-import litellm
-import pytest
-from datetime import timedelta
-from litellm.types.utils import ImageResponse, ImageObject
-from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import (
-    LiteLLMResponseObjectHandler,
-)
-
-
-def test_convert_to_image_response_basic():
-    # Test basic conversion with minimal input
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"url": "http://example.com/image.jpg"}],
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert isinstance(result, ImageResponse)
-    assert result.created == 1234567890
-    assert result.data[0].url == "http://example.com/image.jpg"
-
-
-def test_convert_to_image_response_with_hidden_params():
-    # Test with hidden params
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"url": "http://example.com/image.jpg"}],
-    }
-    hidden_params = {"api_key": "test_key"}
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(
-        response_dict, hidden_params=hidden_params
-    )
-
-    assert result._hidden_params == {"api_key": "test_key"}
-
-
-def test_convert_to_image_response_multiple_images():
-    # Test handling multiple images in response
-    response_dict = {
-        "created": 1234567890,
-        "data": [
-            {"url": "http://example.com/image1.jpg"},
-            {"url": "http://example.com/image2.jpg"},
-        ],
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert len(result.data) == 2
-    assert result.data[0].url == "http://example.com/image1.jpg"
-    assert result.data[1].url == "http://example.com/image2.jpg"
-
-
-def test_convert_to_image_response_with_b64_json():
-    # Test handling b64_json in response
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"b64_json": "base64encodedstring"}],
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert result.data[0].b64_json == "base64encodedstring"
-
-
-def test_convert_to_image_response_with_extra_fields():
-    response_dict = {
-        "created": 1234567890,
-        "data": [
-            {
-                "url": "http://example.com/image1.jpg",
-                "content_filter_results": {"category": "violence", "flagged": True},
-            },
-            {
-                "url": "http://example.com/image2.jpg",
-                "content_filter_results": {"category": "violence", "flagged": True},
-            },
-        ],
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert result.data[0].url == "http://example.com/image1.jpg"
-    assert result.data[1].url == "http://example.com/image2.jpg"
-
-
-def test_convert_to_image_response_with_extra_fields_2():
-    """
-    Date from a non-OpenAI API could have some obscure field in addition to the expected ones. This should not break the conversion.
-    """
-    response_dict = {
-        "created": 1234567890,
-        "data": [
-            {
-                "url": "http://example.com/image1.jpg",
-                "very_obscure_field": "some_value",
-            },
-            {
-                "url": "http://example.com/image2.jpg",
-                "very_obscure_field2": "some_other_value",
-            },
-        ],
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert result.data[0].url == "http://example.com/image1.jpg"
-    assert result.data[1].url == "http://example.com/image2.jpg"
-
-
-def test_convert_to_image_response_with_none_usage_fields():
-    """
-    Test handling of None values in usage fields, specifically for gpt-image-1 responses.
-
-    This test verifies the fix for the bug where gpt-image-1 returns None values
-    for usage statistics fields, which caused Pydantic validation errors.
-    The fix should clean these None values and let ImageResponse constructor
-    handle the default values.
-    """
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"b64_json": "base64encodedstring"}],
-        "usage": {
-            "input_tokens": None,  # gpt-image-1 returns None instead of integer
-            "input_tokens_details": None,  # gpt-image-1 returns None instead of object
-            "output_tokens": None,  # gpt-image-1 returns None instead of integer
-            "total_tokens": None,  # gpt-image-1 returns None instead of integer
-        },
-    }
-
-    # This should not raise a ValidationError
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert isinstance(result, ImageResponse)
-    assert result.created == 1234567890
-    assert result.data[0].b64_json == "base64encodedstring"
-
-    # Usage should be properly initialized with default values
-    assert result.usage is not None
-    assert result.usage.input_tokens == 0
-    assert result.usage.output_tokens == 0
-    assert result.usage.total_tokens == 0
-    assert result.usage.input_tokens_details is not None
-    assert result.usage.input_tokens_details.image_tokens == 0
-    assert result.usage.input_tokens_details.text_tokens == 0
-
-
-def test_convert_to_image_response_with_partial_none_usage_fields():
-    """
-    Test handling of mixed None and valid values in usage fields.
-    """
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"b64_json": "base64encodedstring"}],
-        "usage": {
-            "input_tokens": 10,  # Valid value
-            "input_tokens_details": None,  # None value (should be cleaned)
-            "output_tokens": None,  # None value (should be cleaned)
-            "total_tokens": 10,  # Valid value
-        },
-    }
-
-    # This should not raise a ValidationError
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert isinstance(result, ImageResponse)
-    assert result.created == 1234567890
-    assert result.data[0].b64_json == "base64encodedstring"
-
-    # Usage should be properly initialized with defaults where needed
-    # Valid values should be preserved, None values should be cleaned and use defaults
-    assert result.usage is not None
-    assert result.usage.input_tokens == 10  # Valid value should be preserved
-    assert result.usage.output_tokens == 0  # None value should become 0
-    assert (
-        result.usage.total_tokens == 10
-    )  # Calculated as input_tokens + output_tokens (10 + 0)
-    assert result.usage.input_tokens_details is not None
-    assert result.usage.input_tokens_details.image_tokens == 0
-    assert result.usage.input_tokens_details.text_tokens == 0
-
-
-def test_convert_to_image_response_with_valid_usage_fields():
-    """
-    Test that valid usage fields are preserved correctly.
-    """
-    response_dict = {
-        "created": 1234567890,
-        "data": [{"b64_json": "base64encodedstring"}],
-        "usage": {
-            "input_tokens": 50,
-            "input_tokens_details": {
-                "image_tokens": 30,
-                "text_tokens": 20,
-            },
-            "output_tokens": 10,
-            "total_tokens": 60,
-        },
-    }
-
-    result = LiteLLMResponseObjectHandler.convert_to_image_response(response_dict)
-
-    assert isinstance(result, ImageResponse)
-    assert result.created == 1234567890
-    assert result.data[0].b64_json == "base64encodedstring"
-
-    # Valid usage fields should be preserved
-    assert result.usage is not None
-    assert result.usage.input_tokens == 50
-    assert result.usage.output_tokens == 10
-    assert result.usage.total_tokens == 60
-    assert result.usage.input_tokens_details is not None
-    assert result.usage.input_tokens_details.image_tokens == 30
-    assert result.usage.input_tokens_details.text_tokens == 20

tests/llm_translation/test_crusoe.py

@@ -1,72 +0,0 @@
-"""
-Tests for Crusoe provider integration
-"""
-import os
-from unittest import mock
-
-
-CRUSOE_API_BASE = "https://managed-inference-api-proxy.crusoecloud.com/v1"
-
-
-def test_crusoe_json_registry():
-    """Test CrusoeChatConfig is loaded from JSON provider registry"""
-    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
-
-    assert JSONProviderRegistry.exists("crusoe")
-    config = JSONProviderRegistry.get("crusoe")
-    assert config is not None
-    assert config.base_url == CRUSOE_API_BASE
-    assert config.api_key_env == "CRUSOE_API_KEY"
-    assert config.api_base_env == "CRUSOE_API_BASE"
-
-
-def test_crusoe_get_openai_compatible_provider_info():
-    """Test Crusoe provider info retrieval"""
-    from litellm.llms.openai_like.dynamic_config import create_config_class
-    from litellm.llms.openai_like.json_loader import JSONProviderRegistry
-
-    config = create_config_class(JSONProviderRegistry.get("crusoe"))()
-
-    # Test with default values (no env vars set)
-    with mock.patch.dict(os.environ, {}, clear=True):
-        api_base, api_key = config._get_openai_compatible_provider_info(None, None)
-        assert api_base == CRUSOE_API_BASE
-        assert api_key is None
-
-    # Test with environment variables
-    with mock.patch.dict(
-        os.environ,
-        {
-            "CRUSOE_API_KEY": "test-key",
-            "CRUSOE_API_BASE": "https://custom.crusoecloud.com/v1",
-        },
-    ):
-        api_base, api_key = config._get_openai_compatible_provider_info(None, None)
-        assert api_base == "https://custom.crusoecloud.com/v1"
-        assert api_key == "test-key"
-
-    # Test with explicit parameters (should override env vars)
-    with mock.patch.dict(
-        os.environ,
-        {
-            "CRUSOE_API_KEY": "env-key",
-            "CRUSOE_API_BASE": "https://env.crusoecloud.com/v1",
-        },
-    ):
-        api_base, api_key = config._get_openai_compatible_provider_info(
-            "https://param.crusoecloud.com/v1", "param-key"
-        )
-        assert api_base == "https://param.crusoecloud.com/v1"
-        assert api_key == "param-key"
-
-
-def test_get_llm_provider_crusoe():
-    """Test that get_llm_provider correctly identifies Crusoe"""
-    from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
-
-    # Test with crusoe/model-name format
-    model, provider, api_key, api_base = get_llm_provider(
-        "crusoe/meta-llama/Llama-3.3-70B-Instruct"
-    )
-    assert model == "meta-llama/Llama-3.3-70B-Instruct"
-    assert provider == "crusoe"

tests/llm_translation/test_databricks.py

@@ -1,23 +1,22 @@
 import asyncio
-import httpx
 import json
-import pytest
 import sys
 from typing import Any, Dict, List
-from unittest.mock import MagicMock, Mock, patch, ANY
+from unittest.mock import MagicMock, Mock, patch
 
+import httpx
+import pytest
 
 import litellm
+from litellm._version import version
 from litellm.exceptions import BadRequestError
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
 from litellm.utils import CustomStreamWrapper
-from litellm._version import version
-from base_llm_unit_tests import BaseLLMChatTest, BaseAnthropicChatTest
 
 try:
-    import databricks.sdk
+    import databricks.sdk as databricks_sdk
 
-    databricks_sdk_installed = True
+    databricks_sdk_installed = databricks_sdk is not None
 except ImportError:
     databricks_sdk_installed = False
 
@@ -834,23 +833,6 @@ def test_embeddings_uses_databricks_sdk_if_api_key_and_base_not_specified(monkey
         )
 
 
-@pytest.mark.skip(reason="Databricks rate limit errors")
-class TestDatabricksCompletion(BaseLLMChatTest, BaseAnthropicChatTest):
-    def get_base_completion_call_args(self) -> dict:
-        return {"model": "databricks/databricks-claude-3-7-sonnet"}
-
-    def get_base_completion_call_args_with_thinking(self) -> dict:
-        return {
-            "model": "databricks/databricks-claude-3-7-sonnet",
-            "thinking": {"type": "enabled", "budget_tokens": 1024},
-        }
-
-    def test_pdf_handling(self, pdf_messages):
-        pytest.skip("Databricks does not support PDF handling")
-
-    def test_tool_call_no_arguments(self, tool_call_no_arguments):
-        """Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
-        pytest.skip("Databricks is openai compatible")
 
 
 @pytest.mark.parametrize("sync_mode", [True, False])

tests/llm_translation/test_deepseek_completion.py

@@ -1,19 +1,8 @@
-from base_llm_unit_tests import BaseLLMChatTest
 import pytest
+
 import litellm
 
-
 # Test implementations
-@pytest.mark.skip(reason="Deepseek API is hanging")
-class TestDeepSeekChatCompletion(BaseLLMChatTest):
-    def get_base_completion_call_args(self) -> dict:
-        return {
-            "model": "deepseek/deepseek-reasoner",
-        }
-
-    def test_tool_call_no_arguments(self, tool_call_no_arguments):
-        """Test that tool calls with no arguments is translated correctly. Relevant issue: https://github.com/BerriAI/litellm/issues/6833"""
-        pass
 
 
 @pytest.mark.parametrize("stream", [True, False])
@@ -47,9 +36,10 @@ async def test_deepseek_provider_async_completion(stream):
     """
     Test that Deepseek provider requests are formatted correctly with the proper parameters
     """
-    import litellm
     import json
-    from unittest.mock import patch, AsyncMock, MagicMock
+    from unittest.mock import MagicMock, patch
+
+    import litellm
     from litellm import acompletion
 
     litellm.turn_on_debug()

tests/llm_translation/test_minimax_tts.py

@@ -1,366 +0,0 @@
-"""
-Tests for MiniMax Text-to-Speech integration
-"""
-
-import os
-from pathlib import Path
-from unittest.mock import MagicMock, Mock, patch
-
-import pytest
-
-
-import litellm
-from litellm import speech
-from litellm.llms.minimax.text_to_speech.transformation import (
-    MinimaxTextToSpeechConfig,
-)
-
-
-class TestMinimaxTextToSpeechConfig:
-    """Test MiniMax TTS configuration and parameter mapping"""
-
-    def test_get_supported_openai_params(self):
-        """Test that supported OpenAI params are correctly defined"""
-        config = MinimaxTextToSpeechConfig()
-        supported_params = config.get_supported_openai_params("speech-2.6-hd")
-
-        assert "voice" in supported_params
-        assert "response_format" in supported_params
-        assert "speed" in supported_params
-
-    def test_voice_mapping(self):
-        """Test OpenAI voice to MiniMax voice_id mapping"""
-        config = MinimaxTextToSpeechConfig()
-
-        # Test OpenAI voice mappings
-        assert config._extract_voice_id("alloy") == "male-qn-qingse"
-        assert config._extract_voice_id("echo") == "male-qn-jingying"
-        assert config._extract_voice_id("nova") == "female-yujie"
-
-        # Test custom voice passthrough
-        assert config._extract_voice_id("custom-voice-id") == "custom-voice-id"
-
-    def test_format_mapping(self):
-        """Test response format mapping"""
-        config = MinimaxTextToSpeechConfig()
-
-        assert config.FORMAT_MAPPINGS["mp3"] == "mp3"
-        assert config.FORMAT_MAPPINGS["pcm"] == "pcm"
-        assert config.FORMAT_MAPPINGS["wav"] == "wav"
-        assert config.FORMAT_MAPPINGS["flac"] == "flac"
-
-    def test_map_openai_params_basic(self):
-        """Test basic parameter mapping from OpenAI to MiniMax format"""
-        config = MinimaxTextToSpeechConfig()
-
-        optional_params = {
-            "response_format": "mp3",
-            "speed": 1.5,
-        }
-
-        voice, mapped_params = config.map_openai_params(
-            model="speech-2.6-hd",
-            optional_params=optional_params,
-            voice="alloy",
-        )
-
-        assert voice == "male-qn-qingse"
-        assert mapped_params["format"] == "mp3"
-        assert mapped_params["speed"] == 1.5
-        assert mapped_params["voice_id"] == "male-qn-qingse"
-
-    def test_map_openai_params_speed_clamping(self):
-        """Test that speed is clamped to MiniMax's supported range"""
-        config = MinimaxTextToSpeechConfig()
-
-        # Test speed too high
-        optional_params = {"speed": 5.0}
-        _, mapped_params = config.map_openai_params(
-            model="speech-2.6-hd",
-            optional_params=optional_params,
-            voice="alloy",
-        )
-        assert mapped_params["speed"] == 2.0  # Clamped to max
-
-        # Test speed too low
-        optional_params = {"speed": 0.1}
-        _, mapped_params = config.map_openai_params(
-            model="speech-2.6-hd",
-            optional_params=optional_params,
-            voice="alloy",
-        )
-        assert mapped_params["speed"] == 0.5  # Clamped to min
-
-    def test_map_openai_params_with_extra_body(self):
-        """Test that extra_body parameters are passed through"""
-        config = MinimaxTextToSpeechConfig()
-
-        optional_params = {
-            "extra_body": {
-                "vol": 1.5,
-                "pitch": 2,
-                "sample_rate": 24000,
-            }
-        }
-
-        _, mapped_params = config.map_openai_params(
-            model="speech-2.6-hd",
-            optional_params=optional_params,
-            voice="alloy",
-        )
-
-        assert mapped_params["vol"] == 1.5
-        assert mapped_params["pitch"] == 2
-        assert mapped_params["sample_rate"] == 24000
-
-    def test_validate_environment_with_api_key(self):
-        """Test environment validation with API key"""
-        config = MinimaxTextToSpeechConfig()
-        headers = {}
-
-        result_headers = config.validate_environment(
-            headers=headers,
-            model="speech-2.6-hd",
-            api_key="test-api-key",
-        )
-
-        assert "Authorization" in result_headers
-        assert result_headers["Authorization"] == "Bearer test-api-key"
-        assert result_headers["Content-Type"] == "application/json"
-
-    def test_validate_environment_missing_api_key(self):
-        """Test that validation fails without API key"""
-        config = MinimaxTextToSpeechConfig()
-        headers = {}
-
-        # Mock both litellm.api_key and get_secret_str to return None
-        import litellm
-
-        original_api_key = litellm.api_key
-        try:
-            litellm.api_key = None
-            with patch(
-                "litellm.llms.minimax.text_to_speech.transformation.get_secret_str",
-                return_value=None,
-            ):
-                with pytest.raises(ValueError, match="MiniMax API key is required"):
-                    config.validate_environment(
-                        headers=headers,
-                        model="speech-2.6-hd",
-                        api_key=None,
-                    )
-        finally:
-            litellm.api_key = original_api_key
-
-    def test_transform_text_to_speech_request(self):
-        """Test request transformation to MiniMax format"""
-        config = MinimaxTextToSpeechConfig()
-
-        optional_params = {
-            "voice_id": "male-qn-qingse",
-            "speed": 1.2,
-            "format": "mp3",
-            "vol": 1.0,
-            "pitch": 0,
-            "sample_rate": 32000,
-            "bitrate": 128000,
-            "channel": 1,
-        }
-
-        result = config.transform_text_to_speech_request(
-            model="speech-2.6-hd",
-            input="Hello, world!",
-            voice="male-qn-qingse",
-            optional_params=optional_params,
-            litellm_params={},
-            headers={},
-        )
-
-        assert "dict_body" in result
-        body = result["dict_body"]
-
-        assert body["model"] == "speech-2.6-hd"
-        assert body["text"] == "Hello, world!"
-        assert body["stream"] is False
-        assert body["voice_setting"]["voice_id"] == "male-qn-qingse"
-        assert body["voice_setting"]["speed"] == 1.2
-        assert body["audio_setting"]["format"] == "mp3"
-        assert body["audio_setting"]["sample_rate"] == 32000
-
-    def test_get_complete_url(self):
-        """Test URL construction"""
-        config = MinimaxTextToSpeechConfig()
-
-        url = config.get_complete_url(
-            model="speech-2.6-hd",
-            api_base=None,
-            litellm_params={},
-        )
-
-        assert url == "https://api.minimax.io/v1/t2a_v2"
-
-    def test_get_complete_url_custom_base(self):
-        """Test URL construction with custom API base"""
-        config = MinimaxTextToSpeechConfig()
-
-        url = config.get_complete_url(
-            model="speech-2.6-hd",
-            api_base="https://custom.api.com",
-            litellm_params={},
-        )
-
-        assert url == "https://custom.api.com/v1/t2a_v2"
-
-
-class TestMinimaxSpeechIntegration:
-    """Integration tests for MiniMax TTS via litellm.speech()"""
-
-    @pytest.mark.skip(reason="Requires MiniMax API key")
-    def test_speech_basic(self):
-        """Test basic speech synthesis call"""
-        # This test requires a real API key
-        os.environ["MINIMAX_API_KEY"] = "your-api-key-here"
-
-        speech_file_path = Path(__file__).parent / "test_minimax_speech.mp3"
-
-        response = speech(
-            model="minimax/speech-2.6-hd",
-            voice="alloy",
-            input="Hello, this is a test of MiniMax text to speech.",
-        )
-
-        response.stream_to_file(speech_file_path)
-
-        # Verify file was created
-        assert speech_file_path.exists()
-        assert speech_file_path.stat().st_size > 0
-
-        # Clean up
-        speech_file_path.unlink()
-
-    @pytest.mark.skip(reason="Requires MiniMax API key")
-    def test_speech_with_custom_params(self):
-        """Test speech synthesis with custom parameters"""
-        os.environ["MINIMAX_API_KEY"] = "your-api-key-here"
-
-        speech_file_path = Path(__file__).parent / "test_minimax_speech_custom.mp3"
-
-        response = speech(
-            model="minimax/speech-2.6-turbo",
-            voice="nova",
-            input="Testing custom parameters.",
-            speed=1.5,
-            response_format="mp3",
-            extra_body={
-                "vol": 1.2,
-                "pitch": 1,
-                "sample_rate": 24000,
-            },
-        )
-
-        response.stream_to_file(speech_file_path)
-
-        # Verify file was created
-        assert speech_file_path.exists()
-        assert speech_file_path.stat().st_size > 0
-
-        # Clean up
-        speech_file_path.unlink()
-
-    def test_speech_mock_response(self):
-        """Test speech synthesis with mocked response"""
-
-        # Create mock audio data (hex-encoded as MiniMax returns)
-        mock_audio_bytes = b"fake audio data for testing"
-        mock_audio_hex = mock_audio_bytes.hex()
-
-        mock_response_json = {
-            "data": {"audio": mock_audio_hex, "status": 0, "ced": ""},
-            "extra_info": {},
-        }
-
-        with patch(
-            "litellm.llms.custom_httpx.llm_http_handler.BaseLLMHTTPHandler.text_to_speech_handler"
-        ) as mock_tts:
-            # Create a mock httpx.Response
-            mock_response = MagicMock()
-            mock_response.status_code = 200
-            mock_response.headers = {}
-            mock_response.json.return_value = mock_response_json
-            mock_response.content = mock_audio_bytes
-
-            # Mock the response wrapper
-            from litellm.types.llms.openai import HttpxBinaryResponseContent
-
-            mock_binary_response = HttpxBinaryResponseContent(mock_response)
-            mock_tts.return_value = mock_binary_response
-
-            # This would normally make a real API call
-            # but we're mocking it for testing
-            response = speech(
-                model="minimax/speech-2.6-hd",
-                voice="alloy",
-                input="Test input",
-                api_key="test-key",
-            )
-
-            # Verify the mock was called
-            assert mock_tts.called
-
-
-class TestMinimaxProviderRegistration:
-    """Test that MiniMax is properly registered as a provider"""
-
-    def test_minimax_in_llm_providers(self):
-        """Test that MINIMAX is in LlmProviders enum"""
-        from litellm.types.utils import LlmProviders
-
-        assert hasattr(LlmProviders, "MINIMAX")
-        assert LlmProviders.MINIMAX.value == "minimax"
-
-    def test_minimax_in_provider_list(self):
-        """Test that minimax is in the provider list"""
-        assert litellm.LlmProviders.MINIMAX in litellm.provider_list
-
-    def test_get_provider_text_to_speech_config(self):
-        """Test that MiniMax TTS config can be retrieved"""
-        from litellm.utils import ProviderConfigManager
-
-        config = ProviderConfigManager.get_provider_text_to_speech_config(
-            model="speech-2.6-hd",
-            provider=litellm.LlmProviders.MINIMAX,
-        )
-
-        assert config is not None
-        assert isinstance(config, MinimaxTextToSpeechConfig)
-
-    def test_get_llm_provider_minimax(self):
-        """Test that get_llm_provider correctly identifies MiniMax models"""
-        from litellm import get_llm_provider
-
-        model, provider, api_key, api_base = get_llm_provider(
-            model="minimax/speech-2.6-hd"
-        )
-
-        assert model == "speech-2.6-hd"
-        assert provider == "minimax"
-
-
-if __name__ == "__main__":
-    # Run basic tests
-    test_config = TestMinimaxTextToSpeechConfig()
-    test_config.test_get_supported_openai_params()
-    test_config.test_voice_mapping()
-    test_config.test_format_mapping()
-    test_config.test_map_openai_params_basic()
-    test_config.test_map_openai_params_speed_clamping()
-    test_config.test_transform_text_to_speech_request()
-    test_config.test_get_complete_url()
-
-    test_registration = TestMinimaxProviderRegistration()
-    test_registration.test_minimax_in_llm_providers()
-    test_registration.test_minimax_in_provider_list()
-    test_registration.test_get_provider_text_to_speech_config()
-    test_registration.test_get_llm_provider_minimax()
-
-    print("All basic tests passed!")

tests/llm_translation/test_model_cost_map_resilience.py

@@ -1,297 +0,0 @@
-"""
-Tests for model cost map resilience.
-
-Simulates:
-- A bad (invalid JSON) model cost map upstream
-- A bad (empty/missing) backup model cost map
-- Verifies litellm.completion() still works even with a broken cost map
-- Verifies litellm.get_model_info() raises the expected error for unmapped models
-- Verifies the integrity validation helper catches corrupted maps
-"""
-
-import json
-import os
-import sys
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../..")))
-
-import litellm
-from litellm.litellm_core_utils.get_model_cost_map import (
-    GetModelCostMap,
-    get_model_cost_map,
-)
-
-
-class TestCheckIsValidDict:
-    """Unit tests for _check_is_valid_dict."""
-
-    def test_should_reject_non_dict(self):
-        """Non-dict should fail."""
-        assert GetModelCostMap._check_is_valid_dict("not a dict") is False
-
-    def test_should_reject_empty_dict(self):
-        """Empty dict should fail."""
-        assert GetModelCostMap._check_is_valid_dict({}) is False
-
-    def test_should_reject_list(self):
-        """List should fail."""
-        assert GetModelCostMap._check_is_valid_dict([1, 2, 3]) is False
-
-    def test_should_reject_none(self):
-        """None should fail."""
-        assert GetModelCostMap._check_is_valid_dict(None) is False
-
-    def test_should_accept_non_empty_dict(self):
-        """Non-empty dict should pass."""
-        assert GetModelCostMap._check_is_valid_dict({"model": {}}) is True
-
-
-class TestCheckModelCountNotReduced:
-    """Unit tests for _check_model_count_not_reduced."""
-
-    def test_should_reject_too_few_models(self):
-        """Fetched map with fewer models than min_model_count should fail."""
-        small_map = {f"model-{i}": {} for i in range(5)}
-        assert (
-            GetModelCostMap._check_model_count_not_reduced(
-                fetched_map=small_map, backup_model_count=0, min_model_count=10
-            )
-            is False
-        )
-
-    def test_should_reject_significant_shrinkage(self):
-        """Fetched map that shrunk >50% vs backup should fail."""
-        fetched = {f"model-{i}": {} for i in range(40)}  # 40% of 100
-        assert (
-            GetModelCostMap._check_model_count_not_reduced(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is False
-        )
-
-    def test_should_accept_when_above_threshold(self):
-        """Fetched map at 60% of backup (above 50% threshold) should pass."""
-        fetched = {f"model-{i}": {} for i in range(60)}
-        assert (
-            GetModelCostMap._check_model_count_not_reduced(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is True
-        )
-
-    def test_should_accept_growth(self):
-        """Fetched map larger than backup should pass."""
-        fetched = {f"model-{i}": {} for i in range(120)}
-        assert (
-            GetModelCostMap._check_model_count_not_reduced(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is True
-        )
-
-    def test_should_accept_with_empty_backup(self):
-        """When backup is empty, only min_model_count matters."""
-        fetched = {f"model-{i}": {} for i in range(15)}
-        assert (
-            GetModelCostMap._check_model_count_not_reduced(
-                fetched_map=fetched, backup_model_count=0, min_model_count=10
-            )
-            is True
-        )
-
-
-class TestValidateModelCostMap:
-    """Unit tests for validate_model_cost_map (combines both checks)."""
-
-    def test_should_reject_non_dict(self):
-        """Non-dict should fail at check 1."""
-        assert (
-            GetModelCostMap.validate_model_cost_map(
-                fetched_map="not a dict", backup_model_count=0
-            )
-            is False
-        )
-
-    def test_should_reject_empty_map(self):
-        """Empty dict should fail at check 1."""
-        assert (
-            GetModelCostMap.validate_model_cost_map(
-                fetched_map={}, backup_model_count=0
-            )
-            is False
-        )
-
-    def test_should_reject_significant_shrinkage(self):
-        """Should fail at check 2 (shrinkage)."""
-        fetched = {f"model-{i}": {} for i in range(40)}
-        assert (
-            GetModelCostMap.validate_model_cost_map(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is False
-        )
-
-    def test_should_accept_valid_map(self):
-        """Should pass both checks."""
-        fetched = {f"model-{i}": {} for i in range(120)}
-        assert (
-            GetModelCostMap.validate_model_cost_map(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is True
-        )
-
-    def test_should_accept_equal_size_map(self):
-        """Equal size should pass both checks."""
-        fetched = {f"model-{i}": {} for i in range(100)}
-        assert (
-            GetModelCostMap.validate_model_cost_map(
-                fetched_map=fetched, backup_model_count=100, min_model_count=10
-            )
-            is True
-        )
-
-
-class TestGetModelCostMapFallback:
-    """Tests for get_model_cost_map fallback behavior with bad upstream."""
-
-    def test_should_fallback_to_backup_on_invalid_json(self):
-        """When upstream returns invalid JSON, should fall back to local backup."""
-        mock_response = MagicMock()
-        mock_response.raise_for_status = MagicMock()
-        mock_response.json.side_effect = json.JSONDecodeError("bad json", "", 0)
-
-        with patch("httpx.get", return_value=mock_response):
-            result = get_model_cost_map("https://fake-url.com/model_prices.json")
-
-        # Should have fallen back to backup — backup always has models
-        assert isinstance(result, dict)
-        assert len(result) > 0
-
-    def test_should_fallback_to_backup_on_network_error(self):
-        """When upstream is unreachable, should fall back to local backup."""
-        with patch("httpx.get", side_effect=Exception("Connection refused")):
-            result = get_model_cost_map("https://fake-url.com/model_prices.json")
-
-        assert isinstance(result, dict)
-        assert len(result) > 0
-
-    def test_should_fallback_when_fetched_map_is_empty(self):
-        """When upstream returns valid JSON but empty dict, should fall back."""
-        mock_response = MagicMock()
-        mock_response.raise_for_status = MagicMock()
-        mock_response.json.return_value = {}  # empty map
-
-        with patch("httpx.get", return_value=mock_response):
-            result = get_model_cost_map("https://fake-url.com/model_prices.json")
-
-        # Should have fallen back to backup since empty map fails validation
-        assert isinstance(result, dict)
-        assert len(result) > 0
-
-    def test_should_fallback_when_fetched_map_shrinks_dramatically(self):
-        """When upstream returns far fewer models than backup, should fall back."""
-        tiny_map = {f"model-{i}": {"litellm_provider": "test"} for i in range(11)}
-        mock_response = MagicMock()
-        mock_response.raise_for_status = MagicMock()
-        mock_response.json.return_value = tiny_map
-
-        with patch("httpx.get", return_value=mock_response):
-            result = get_model_cost_map("https://fake-url.com/model_prices.json")
-
-        # Backup has thousands of models; 11 is a massive shrinkage → fallback
-        assert len(result) > 11
-
-    def test_should_use_local_map_when_env_var_set(self):
-        """LITELLM_LOCAL_MODEL_COST_MAP=True should skip remote fetch entirely."""
-        with patch.dict(os.environ, {"LITELLM_LOCAL_MODEL_COST_MAP": "True"}):
-            with patch("httpx.get") as mock_get:
-                result = get_model_cost_map("https://fake-url.com/model_prices.json")
-                mock_get.assert_not_called()
-
-        assert isinstance(result, dict)
-        assert len(result) > 0
-
-
-class TestBackupModelCostMapExists:
-    """Validates the local backup file is always present and valid."""
-
-    def test_should_have_backup_file(self):
-        """The backup model cost map must exist and be loadable."""
-        backup = GetModelCostMap.load_local_model_cost_map()
-        assert isinstance(backup, dict)
-        assert len(backup) > 0, "Backup model cost map is empty"
-
-    def test_should_have_minimum_models_in_backup(self):
-        """The backup must contain a reasonable number of models."""
-        backup = GetModelCostMap.load_local_model_cost_map()
-        assert (
-            len(backup) > 100
-        ), f"Backup has only {len(backup)} models, expected > 100"
-
-
-class TestBadHostedModelCostMap:
-    """
-    Simulates the hosted model cost map being bad (invalid JSON / corrupted).
-
-    When the hosted map is bad, get_model_cost_map() falls back to the local
-    backup. These tests verify that after fallback:
-    - get_model_info() still works for models in the backup
-    - litellm.completion() still works
-    """
-
-    def test_should_model_info_pass_after_bad_hosted_map(self):
-        """
-        If the hosted map is bad, get_model_cost_map falls back to the local
-        backup. get_model_info should still work for models in the backup.
-        """
-        mock_response = MagicMock()
-        mock_response.raise_for_status = MagicMock()
-        mock_response.json.side_effect = json.JSONDecodeError("bad json", "", 0)
-
-        with patch("httpx.get", return_value=mock_response):
-            fallback_map = get_model_cost_map("https://fake-url.com/bad.json")
-
-        original = litellm.model_cost
-        litellm.model_cost = fallback_map
-        try:
-            # gpt-4o is in every backup — should work fine
-            info = litellm.get_model_info("gpt-4o")
-            assert info is not None
-            assert info["input_cost_per_token"] > 0
-        finally:
-            litellm.model_cost = original
-
-    def test_should_completion_pass_after_bad_hosted_map(self):
-        """
-        If the hosted map is bad, litellm.completion() should still work.
-
-        Uses litellm's built-in mock_response param so the real completion
-        path is exercised (routing, cost calculator, logging) without
-        needing API credentials.
-        """
-        # Simulate bad hosted map → fallback to backup
-        mock_http = MagicMock()
-        mock_http.raise_for_status = MagicMock()
-        mock_http.json.side_effect = json.JSONDecodeError("bad json", "", 0)
-
-        with patch("httpx.get", return_value=mock_http):
-            fallback_map = get_model_cost_map("https://fake-url.com/bad.json")
-
-        original = litellm.model_cost
-        litellm.model_cost = fallback_map
-        try:
-            # mock_response goes through the real completion path —
-            # routing, cost calculator, logging — but skips the HTTP call
-            response = litellm.completion(
-                model="gpt-4o-mini",
-                messages=[{"role": "user", "content": "say hi"}],
-                mock_response="hello from mock",
-            )
-            assert response is not None
-            assert response.choices[0].message.content == "hello from mock"
-        finally:
-            litellm.model_cost = original

tests/llm_translation/test_morph.py

@@ -1,88 +0,0 @@
-"""Unit tests for Morph provider integration."""
-
-import os
-from unittest.mock import patch
-
-
-import litellm
-from litellm import MorphChatConfig, get_llm_provider
-
-# Force model loading
-litellm.add_known_models()
-
-
-def test_morph_config_get_provider_info():
-    """Test that MorphChatConfig returns correct provider info."""
-    config = MorphChatConfig()
-
-    # Test with environment variable
-    with patch.dict(os.environ, {"MORPH_API_KEY": "test-key-from-env"}):
-        api_base, api_key = config._get_openai_compatible_provider_info(None, None)
-        assert api_base == "https://api.morphllm.com/v1"
-        assert api_key == "test-key-from-env"
-
-    # Test with passed api_key
-    api_base, api_key = config._get_openai_compatible_provider_info(None, "direct-key")
-    assert api_base == "https://api.morphllm.com/v1"
-    assert api_key == "direct-key"
-
-    # Test with custom api_base
-    api_base, api_key = config._get_openai_compatible_provider_info(
-        "https://custom.morph.com", "key"
-    )
-    assert api_base == "https://custom.morph.com"
-    assert api_key == "key"
-
-
-def test_morph_get_llm_provider():
-    """Test that get_llm_provider correctly identifies morph models."""
-    # Test with morph/model format
-    _, custom_llm_provider, _, _ = get_llm_provider("morph/morph-v3-large")
-    assert custom_llm_provider == "morph"
-
-    _, custom_llm_provider, _, _ = get_llm_provider("morph/morph-v3-fast")
-    assert custom_llm_provider == "morph"
-
-
-def test_morph_in_provider_lists():
-    """Test that morph is included in all necessary provider lists."""
-    import litellm
-    from litellm.constants import (
-        openai_compatible_providers,
-        openai_compatible_endpoints,
-    )
-
-    # Check morph is in openai_compatible_providers
-    assert "morph" in openai_compatible_providers
-
-    # Check morph endpoint is in openai_compatible_endpoints
-    assert "https://api.morphllm.com/v1" in openai_compatible_endpoints
-
-    # Check morph is in provider_list
-    assert "morph" in litellm.provider_list
-
-    # Check models are in model_list after initialization
-    assert all(
-        model in litellm.model_list
-        for model in ["morph/morph-v3-large", "morph/morph-v3-fast"]
-    )
-
-
-def test_morph_supported_params():
-    """Test that MorphChatConfig returns correct supported parameters."""
-    config = MorphChatConfig()
-    supported_params = config.get_supported_openai_params("morph/morph-v3-large")
-
-    expected_params = [
-        "messages",
-        "model",
-        "stream",
-    ]
-
-    assert all(param in supported_params for param in expected_params)
-
-
-def test_morph_custom_llm_provider():
-    """Test that morph models are correctly identified."""
-    config = MorphChatConfig()
-    assert config.custom_llm_provider == "morph"

tests/llm_translation/test_replicate.py

@@ -2,17 +2,16 @@
 Unit tests for Replicate provider, particularly testing DeepSeek models
 """
 
-import asyncio
 import json
-from unittest.mock import AsyncMock, MagicMock, Mock, patch
+from unittest.mock import AsyncMock, Mock, patch
 
 import pytest
 
-
 import litellm
-from litellm import completion
 from litellm.llms.replicate.chat.handler import (
     async_completion,
+)
+from litellm.llms.replicate.chat.handler import (
     completion as replicate_completion,
 )
 
@@ -265,22 +264,3 @@ class TestReplicateOutputFormats:
 
 
 # Integration test (requires actual API key - skip in CI)
-@pytest.mark.skip(reason="Requires REPLICATE_API_KEY environment variable")
-def test_replicate_deepseek_integration():
-    """Integration test with actual DeepSeek model on Replicate"""
-    try:
-        response = completion(
-            model="replicate/deepseek-ai/deepseek-v3",
-            messages=[
-                {"role": "user", "content": "Say 'Hello World' and nothing else"}
-            ],
-            max_tokens=20,
-        )
-
-        assert response is not None
-        assert response.choices[0].message.content is not None
-        assert len(response.choices[0].message.content) > 0
-        print(f"Response: {response.choices[0].message.content}")
-
-    except Exception as e:
-        pytest.fail(f"Integration test failed: {e}")

tests/llm_translation/test_rerank.py

@@ -7,18 +7,16 @@ from dotenv import load_dotenv
 
 load_dotenv()
 import io
-from typing import Optional, Dict
-
-
+from typing import Dict, Optional
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
 import litellm
-from litellm.types.rerank import RerankResponse
 from litellm import RateLimitError, Timeout, completion, completion_cost, embedding
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+from litellm.types.rerank import RerankResponse
 
 
 def assert_response_shape(response, custom_llm_provider):
@@ -103,43 +101,6 @@ async def test_basic_rerank(sync_mode):
     print("response", response.model_dump_json(indent=4))
 
 
-@pytest.mark.asyncio()
-@pytest.mark.parametrize("sync_mode", [True, False])
-@pytest.mark.skip(reason="Skipping test due to 503 Service Temporarily Unavailable")
-async def test_basic_rerank_together_ai(sync_mode):
-    try:
-        if sync_mode is True:
-            response = litellm.rerank(
-                model="together_ai/Salesforce/Llama-Rank-V1",
-                query="hello",
-                documents=["hello", "world"],
-                top_n=3,
-            )
-
-            print("re rank response: ", response)
-
-            assert response.id is not None
-            assert response.results is not None
-
-            assert_response_shape(response, custom_llm_provider="together_ai")
-        else:
-            response = await litellm.arerank(
-                model="together_ai/Salesforce/Llama-Rank-V1",
-                query="hello",
-                documents=["hello", "world"],
-                top_n=3,
-            )
-
-            print("async re rank response: ", response)
-
-            assert response.id is not None
-            assert response.results is not None
-
-            assert_response_shape(response, custom_llm_provider="together_ai")
-    except Exception as e:
-        if "Service unavailable" in str(e):
-            pytest.skip("Skipping test due to 503 Service Temporarily Unavailable")
-        raise e
 
 
 @pytest.mark.asyncio()

tests/llm_translation/test_snowflake.py

@@ -1,79 +0,0 @@
-import asyncio
-import json
-import os
-import httpx
-from typing import Any, Dict, List
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from litellm import completion, acompletion, responses
-from litellm.exceptions import APIConnectionError
-from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
-
-
-@pytest.mark.skip(reason="Requires Snowflake credentials - run manually when needed")
-def test_snowflake_tool_calling_responses_api():
-    """
-    Test Snowflake tool calling with Responses API.
-    Requires SNOWFLAKE_JWT and SNOWFLAKE_ACCOUNT_ID environment variables.
-    """
-    import litellm
-
-    # Skip if credentials not available
-    if not os.getenv("SNOWFLAKE_JWT") or not os.getenv("SNOWFLAKE_ACCOUNT_ID"):
-        pytest.skip("Snowflake credentials not available")
-
-    litellm.drop_params = False  # We now support tools!
-
-    tools = [
-        {
-            "type": "function",
-            "name": "get_weather",
-            "description": "Get the current weather in a given location",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "location": {
-                        "type": "string",
-                        "description": "The city and state, e.g. San Francisco, CA",
-                    }
-                },
-                "required": ["location"],
-            },
-        }
-    ]
-
-    try:
-        # Test with tool_choice to force tool use
-        response = responses(
-            model="snowflake/claude-3-5-sonnet",
-            input="What's the weather in Paris?",
-            tools=tools,
-            tool_choice={"type": "function", "function": {"name": "get_weather"}},
-            max_output_tokens=200,
-        )
-
-        assert response is not None
-        assert hasattr(response, "output")
-        assert len(response.output) > 0
-
-        # Verify tool call was made
-        tool_call_found = False
-        for item in response.output:
-            if hasattr(item, "type") and item.type == "function_call":
-                tool_call_found = True
-                assert item.name == "get_weather"
-                assert hasattr(item, "arguments")
-                print(f"✅ Tool call detected: {item.name}({item.arguments})")
-                break
-
-        assert tool_call_found, "Expected tool call but none was found"
-
-    except APIConnectionError as e:
-        if "JWT token is invalid" in str(e):
-            pytest.skip("Invalid Snowflake JWT token")
-        elif "Application failed to respond" in str(e) or "502" in str(e):
-            pytest.skip(f"Snowflake API unavailable: {e}")
-        else:
-            raise

tests/llm_translation/test_watsonx.py

@@ -1,273 +0,0 @@
-import json
-
-import litellm
-from litellm import completion, embedding
-from litellm.llms.custom_httpx.http_handler import HTTPHandler
-from unittest.mock import patch, Mock
-import pytest
-from typing import Optional
-
-
-@pytest.fixture(autouse=True)
-def watsonx_env_vars(monkeypatch):
-    """Set required WatsonX env vars so the provider passes validation.
-    Also clear WATSONX_ZENAPIKEY/WATSONX_TOKEN so they don't bypass the IAM token mock.
-    """
-    monkeypatch.setenv("WATSONX_URL", "https://us-south.ml.cloud.ibm.com")
-    monkeypatch.setenv("WATSONX_PROJECT_ID", "test-project-id")
-    monkeypatch.delenv("WATSONX_ZENAPIKEY", raising=False)
-    monkeypatch.delenv("WATSONX_TOKEN", raising=False)
-
-
-@pytest.fixture
-def watsonx_chat_completion_call():
-    def _call(
-        model="watsonx/my-test-model",
-        messages=None,
-        api_key="test_api_key",
-        space_id: Optional[str] = None,
-        headers=None,
-        client=None,
-        patch_token_call=True,
-    ):
-        if messages is None:
-            messages = [{"role": "user", "content": "Hello, how are you?"}]
-        if client is None:
-            client = HTTPHandler()
-
-        if patch_token_call:
-            mock_response = Mock()
-            mock_response.json.return_value = {
-                "access_token": "mock_access_token",
-                "expires_in": 3600,
-            }
-            mock_response.raise_for_status = Mock()  # No-op to simulate no exception
-
-            with (
-                patch.object(client, "post") as mock_post,
-                patch.object(
-                    litellm.module_level_client, "post", return_value=mock_response
-                ) as mock_get,
-            ):
-                try:
-                    completion(
-                        model=model,
-                        messages=messages,
-                        api_key=api_key,
-                        headers=headers or {},
-                        client=client,
-                        space_id=space_id,
-                    )
-                except Exception as e:
-                    print(e)
-
-                return mock_post, mock_get
-        else:
-            with patch.object(client, "post") as mock_post:
-                try:
-                    completion(
-                        model=model,
-                        messages=messages,
-                        api_key=api_key,
-                        headers=headers or {},
-                        client=client,
-                        space_id=space_id,
-                    )
-                except Exception as e:
-                    print(e)
-                return mock_post, None
-
-    return _call
-
-
-@pytest.fixture
-def watsonx_embedding_call():
-    def _call(
-        model="watsonx/my-test-model",
-        input=None,
-        api_key="test_api_key",
-        space_id: Optional[str] = None,
-        headers=None,
-        client=None,
-        patch_token_call=True,
-    ):
-        if input is None:
-            input = ["Hello, how are you?"]
-        if client is None:
-            client = HTTPHandler()
-
-        if patch_token_call:
-            mock_response = Mock()
-            mock_response.json.return_value = {
-                "access_token": "mock_access_token",
-                "expires_in": 3600,
-            }
-            mock_response.raise_for_status = Mock()  # No-op to simulate no exception
-
-            with (
-                patch.object(client, "post") as mock_post,
-                patch.object(
-                    litellm.module_level_client, "post", return_value=mock_response
-                ) as mock_get,
-            ):
-                try:
-                    embedding(
-                        model=model,
-                        input=input,
-                        api_key=api_key,
-                        headers=headers or {},
-                        client=client,
-                        space_id=space_id,
-                    )
-                except Exception as e:
-                    print(e)
-
-                return mock_post, mock_get
-        else:
-            with patch.object(client, "post") as mock_post:
-                try:
-                    embedding(
-                        model=model,
-                        input=input,
-                        api_key=api_key,
-                        headers=headers or {},
-                        client=client,
-                        space_id=space_id,
-                    )
-                except Exception as e:
-                    print(e)
-                return mock_post, None
-
-    return _call
-
-
-@pytest.mark.parametrize("with_custom_auth_header", [True, False])
-def test_watsonx_custom_auth_header(
-    with_custom_auth_header, watsonx_chat_completion_call
-):
-    headers = (
-        {"Authorization": "Bearer my-custom-auth-header"}
-        if with_custom_auth_header
-        else {}
-    )
-
-    mock_post, _ = watsonx_chat_completion_call(headers=headers)
-
-    assert mock_post.call_count == 1
-    if with_custom_auth_header:
-        assert (
-            mock_post.call_args[1]["headers"]["Authorization"]
-            == "Bearer my-custom-auth-header"
-        )
-    else:
-        assert (
-            mock_post.call_args[1]["headers"]["Authorization"]
-            == "Bearer mock_access_token"
-        )
-
-
-@pytest.mark.parametrize("env_var_key", ["WATSONX_ZENAPIKEY", "WATSONX_TOKEN"])
-def test_watsonx_token_in_env_var(
-    monkeypatch, watsonx_chat_completion_call, env_var_key
-):
-    monkeypatch.setenv(env_var_key, "my-custom-token")
-
-    mock_post, _ = watsonx_chat_completion_call(patch_token_call=False)
-
-    assert mock_post.call_count == 1
-    if env_var_key == "WATSONX_ZENAPIKEY":
-        assert (
-            mock_post.call_args[1]["headers"]["Authorization"]
-            == "ZenApiKey my-custom-token"
-        )
-    else:
-        assert (
-            mock_post.call_args[1]["headers"]["Authorization"]
-            == "Bearer my-custom-token"
-        )
-
-
-def test_watsonx_chat_completions_endpoint(watsonx_chat_completion_call):
-    model = "watsonx/another-model"
-    messages = [{"role": "user", "content": "Test message"}]
-
-    mock_post, _ = watsonx_chat_completion_call(model=model, messages=messages)
-
-    assert mock_post.call_count == 1
-    assert "deployment" not in mock_post.call_args.kwargs["url"]
-
-
-def test_watsonx_chat_completions_endpoint_space_id(
-    monkeypatch, watsonx_chat_completion_call
-):
-    my_fake_space_id = "xxx-xxx-xxx-xxx-xxx"
-    monkeypatch.setenv("WATSONX_SPACE_ID", my_fake_space_id)
-
-    monkeypatch.delenv("WATSONX_PROJECT_ID", raising=False)
-
-    model = "watsonx/another-model"
-    messages = [{"role": "user", "content": "Test message"}]
-
-    mock_post, _ = watsonx_chat_completion_call(model=model, messages=messages)
-
-    assert mock_post.call_count == 1
-    assert "deployment" not in mock_post.call_args.kwargs["url"]
-
-    json_data = json.loads(mock_post.call_args.kwargs["data"])
-    assert my_fake_space_id == json_data["space_id"]
-    assert not json_data.get("project_id")
-
-
-@pytest.mark.parametrize(
-    "model",
-    [
-        "watsonx/deployment/<xxxx.xxx.xxx.xxxx>",
-        "watsonx_text/deployment/<xxxx.xxx.xxx.xxxx>",
-    ],
-)
-def test_watsonx_deployment_space_id(monkeypatch, watsonx_chat_completion_call, model):
-    my_fake_space_id = "xxx-xxx-xxx-xxx-xxx"
-    monkeypatch.setenv("WATSONX_SPACE_ID", my_fake_space_id)
-
-    mock_post, _ = watsonx_chat_completion_call(
-        model=model,
-        messages=[{"content": "Hello, how are you?", "role": "user"}],
-    )
-
-    assert mock_post.call_count == 1
-    json_data = json.loads(mock_post.call_args.kwargs["data"])
-    assert my_fake_space_id not in json_data
-
-
-@pytest.mark.parametrize(
-    "model",
-    [
-        "watsonx/deployment/<xxxx.xxx.xxx.xxxx>",
-        "watsonx_text/deployment/<xxxx.xxx.xxx.xxxx>",
-    ],
-)
-def test_watsonx_deployment(watsonx_chat_completion_call, model):
-    messages = [{"content": "Hello, how are you?", "role": "user"}]
-    mock_post, _ = watsonx_chat_completion_call(
-        model=model,
-        messages=messages,
-    )
-
-    assert mock_post.call_count == 1
-    json_data = json.loads(mock_post.call_args.kwargs["data"])
-
-    # nor space_id or project_id is required by wx.ai API when inferencing deployment
-    assert "project_id" not in json_data and "space_id" not in json_data
-
-
-def test_watsonx_deployment_space_id_embedding(monkeypatch, watsonx_embedding_call):
-    my_fake_space_id = "xxx-xxx-xxx-xxx-xxx"
-    monkeypatch.setenv("WATSONX_SPACE_ID", my_fake_space_id)
-
-    mock_post, _ = watsonx_embedding_call(model="watsonx/deployment/my-test-model")
-
-    assert mock_post.call_count == 1
-    json_data = json.loads(mock_post.call_args.kwargs["data"])
-
-    # nor space_id or project_id is required by wx.ai API when inferencing deployment
-    assert "project_id" not in json_data and "space_id" not in json_data