Merge pull request #27906 from BerriAI/litellm_internal_staging
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[Infra] Promote internal staging to main
This commit is contained in:
shin-berri 2026-05-13 22:37:20 -07:00 committed by GitHub
commit e58a561caa
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453 changed files with 8150 additions and 1333 deletions

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@ -143,6 +143,7 @@ jobs:
tests/proxy_unit_tests/test_proxy_pass_user_config.py
tests/proxy_unit_tests/test_proxy_token_counter.py
tests/proxy_unit_tests/test_request_size_limit_middleware.py
tests/proxy_unit_tests/test_multipart_bypass_repro.py
workers: 4
dist: loadscope
timeout: 15

View file

@ -1,3 +1,3 @@
-- AlterTable
ALTER TABLE "LiteLLM_TeamMembership" ADD COLUMN "total_spend" DOUBLE PRECISION NOT NULL DEFAULT 0.0;
ALTER TABLE "LiteLLM_TeamMembership" ADD COLUMN IF NOT EXISTS "total_spend" DOUBLE PRECISION NOT NULL DEFAULT 0.0;

View file

@ -0,0 +1,2 @@
-- AlterTable
ALTER TABLE "LiteLLM_MCPServerTable" ADD COLUMN IF NOT EXISTS "delegate_auth_to_upstream" BOOLEAN NOT NULL DEFAULT false;

View file

@ -323,6 +323,7 @@ model LiteLLM_MCPServerTable {
registration_url String?
allow_all_keys Boolean @default(false)
available_on_public_internet Boolean @default(true)
delegate_auth_to_upstream Boolean @default(false)
is_byok Boolean @default(false)
byok_description String[] @default([])
byok_api_key_help_url String?

View file

@ -1,6 +1,6 @@
[project]
name = "litellm-proxy-extras"
version = "0.4.71"
version = "0.4.72"
description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
readme = "README.md"
requires-python = ">=3.9"
@ -26,7 +26,7 @@ required-version = ">=0.10.9"
module-root = ""
[tool.commitizen]
version = "0.4.71"
version = "0.4.72"
version_files = [
"pyproject.toml:^version",
"../pyproject.toml:litellm-proxy-extras==",

View file

@ -41,7 +41,7 @@ def _get_redis_kwargs():
"retry",
}
include_args = [
include_args = {
"url",
"redis_connect_func",
"gcp_service_account",
@ -50,9 +50,9 @@ def _get_redis_kwargs():
"azure_client_id",
"azure_tenant_id",
"azure_client_secret",
]
}
available_args = [x for x in arg_spec.args if x not in exclude_args] + include_args
available_args = {x for x in arg_spec.args if x not in exclude_args} | include_args
return available_args
@ -84,23 +84,23 @@ def _get_redis_cluster_kwargs(client=None):
# Only allow primitive arguments
exclude_args = {"self", "connection_pool", "retry", "host", "port", "startup_nodes"}
available_args = [x for x in arg_spec.args if x not in exclude_args]
available_args.append("password")
available_args.append("username")
available_args.append("ssl")
available_args.append("ssl_cert_reqs")
available_args.append("ssl_check_hostname")
available_args.append("ssl_ca_certs")
available_args.append(
"redis_connect_func"
) # Needed for sync clusters and IAM detection
available_args.append("gcp_service_account")
available_args.append("gcp_ssl_ca_certs")
available_args.append("azure_redis_ad_token")
available_args.append("azure_client_id")
available_args.append("azure_tenant_id")
available_args.append("azure_client_secret")
available_args.append("max_connections")
available_args = {x for x in arg_spec.args if x not in exclude_args}
available_args |= {
"password",
"username",
"ssl",
"ssl_cert_reqs",
"ssl_check_hostname",
"ssl_ca_certs",
"redis_connect_func", # Needed for sync clusters and IAM detection
"gcp_service_account",
"gcp_ssl_ca_certs",
"azure_redis_ad_token",
"azure_client_id",
"azure_tenant_id",
"azure_client_secret",
"max_connections",
}
return available_args
@ -479,10 +479,24 @@ def init_redis_cluster(redis_kwargs) -> redis.RedisCluster:
return redis.RedisCluster(startup_nodes=new_startup_nodes, **cluster_kwargs) # type: ignore
def _get_redis_sentinel_connection_kwargs(redis_kwargs: dict) -> dict:
connection_kwargs = {}
args = _get_redis_kwargs()
for arg in redis_kwargs:
if arg in args:
connection_kwargs[arg] = redis_kwargs[arg]
return connection_kwargs
def _init_redis_sentinel(redis_kwargs) -> redis.Redis:
sentinel_nodes = redis_kwargs.get("sentinel_nodes")
sentinel_password = redis_kwargs.get("sentinel_password")
service_name = redis_kwargs.get("service_name")
connection_kwargs = _get_redis_sentinel_connection_kwargs(redis_kwargs)
connection_kwargs.setdefault("socket_timeout", REDIS_SOCKET_TIMEOUT)
sentinel_kwargs = dict(connection_kwargs)
sentinel_kwargs["password"] = sentinel_password
if not sentinel_nodes or not service_name:
raise ValueError(
@ -494,19 +508,22 @@ def _init_redis_sentinel(redis_kwargs) -> redis.Redis:
# Set up the Sentinel client
sentinel = redis.Sentinel(
sentinel_nodes,
socket_timeout=REDIS_SOCKET_TIMEOUT,
password=sentinel_password,
sentinel_kwargs=sentinel_kwargs,
)
# Return the master instance for the given service
return sentinel.master_for(service_name)
return sentinel.master_for(service_name, **connection_kwargs)
def _init_async_redis_sentinel(redis_kwargs) -> async_redis.Redis:
sentinel_nodes = redis_kwargs.get("sentinel_nodes")
sentinel_password = redis_kwargs.get("sentinel_password")
service_name = redis_kwargs.get("service_name")
connection_kwargs = _get_redis_sentinel_connection_kwargs(redis_kwargs)
connection_kwargs.setdefault("socket_timeout", REDIS_SOCKET_TIMEOUT)
sentinel_kwargs = dict(connection_kwargs)
sentinel_kwargs["password"] = sentinel_password
if not sentinel_nodes or not service_name:
raise ValueError(
@ -518,13 +535,12 @@ def _init_async_redis_sentinel(redis_kwargs) -> async_redis.Redis:
# Set up the Sentinel client
sentinel = async_redis.Sentinel(
sentinel_nodes,
socket_timeout=REDIS_SOCKET_TIMEOUT,
password=sentinel_password,
sentinel_kwargs=sentinel_kwargs,
)
# Return the master instance for the given service
return sentinel.master_for(service_name)
return sentinel.master_for(service_name, **connection_kwargs)
def get_redis_client(**env_overrides):

View file

@ -178,6 +178,18 @@ class BudgetManager:
return list(self.user_dict.keys())
def reset_cost(self, user):
"""
Reset the tracked spend for a user back to zero.
Clears both the aggregate ``current_cost`` and the per-model
``model_cost`` breakdown stored for the given user.
Args:
user: The user identifier whose cost should be reset.
Returns:
dict: ``{"user": <updated user record>}`` reflecting the reset state.
"""
self.user_dict[user]["current_cost"] = 0
self.user_dict[user]["model_cost"] = {}
return {"user": self.user_dict[user]}

View file

@ -1569,6 +1569,15 @@ DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL = int(
os.getenv("DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL", 60)
)
DEFAULT_ACCESS_GROUP_CACHE_TTL = int(os.getenv("DEFAULT_ACCESS_GROUP_CACHE_TTL", 600))
# Short TTL for negative MCP access-group existence lookups. Keeps unauthenticated
# callers from forcing a DB query per request for unknown names, while bounding
# staleness so a transient DB error (which surfaces as an empty list) cannot
# hide a real group for long.
DEFAULT_MCP_ACCESS_GROUP_NEGATIVE_CACHE_TTL = 10
# Maximum number of comma-separated MCP server / access-group tokens accepted
# in a single ``/{name1,name2,...}/mcp`` URL. Bounds the per-request DB / cache
# fan-out an authenticated caller can trigger by stuffing the path with tokens.
DEFAULT_MCP_NAMESPACE_CSV_MAX_TOKENS = 16
# Sentry Scrubbing Configuration
SENTRY_DENYLIST = [

View file

@ -1226,6 +1226,17 @@ class PrometheusLogger(CustomLogger):
label_context=label_context,
)
# Provider-agnostic fallback: providers like Bedrock and Vertex don't return
# x-ratelimit-remaining-* headers, so the gauges above only fire for OpenAI /
# Anthropic / Azure. When the proxy router has tpm/rpm configured for the
# model_group, derive remaining from configured-limit minus current usage so
# the same metric is populated for any provider.
await self._async_set_router_remaining_metrics(
standard_logging_payload=standard_logging_payload, # type: ignore
enum_values=enum_values,
label_context=label_context,
)
# cache metrics
self._increment_cache_metrics(
standard_logging_payload=standard_logging_payload, # type: ignore
@ -2199,6 +2210,99 @@ class PrometheusLogger(CustomLogger):
)
self.litellm_deployment_rpm_limit.labels(**_labels).set(rpm)
async def _async_set_router_remaining_metrics(
self,
standard_logging_payload: StandardLoggingPayload,
enum_values: UserAPIKeyLabelValues,
label_context: Optional[PrometheusLabelFactoryContext] = None,
) -> None:
"""
Populate ``litellm_remaining_tokens_metric`` /
``litellm_remaining_requests_metric`` from the router's internal usage
counters when the upstream provider did not return
``x-ratelimit-remaining-*`` response headers.
OpenAI / Anthropic / Azure return remaining tokens/requests in response
headers, but Bedrock and Vertex AI do not. This fallback computes
``configured_limit - current_usage`` via
``Router.get_remaining_model_group_usage`` so the same gauges are
emitted for every provider when tpm/rpm is configured on the
deployment.
"""
try:
additional_headers = (
standard_logging_payload.get("hidden_params", {}) or {}
).get("additional_headers") or {}
already_have_tokens = (
additional_headers.get("x_ratelimit_remaining_tokens") is not None
)
already_have_requests = (
additional_headers.get("x_ratelimit_remaining_requests") is not None
)
if already_have_tokens and already_have_requests:
return
model_group = standard_logging_payload.get("model_group")
if not model_group:
return
try:
from litellm.proxy.proxy_server import llm_router
except ImportError:
llm_router = None
if llm_router is None:
return
try:
remaining_usage = await llm_router.get_remaining_model_group_usage(
model_group
)
except Exception as e:
verbose_logger.exception(
"Prometheus: get_remaining_model_group_usage failed for "
"model_group=%s: %s",
model_group,
e,
)
return
if not remaining_usage:
return
remaining_tokens = remaining_usage.get("x-ratelimit-remaining-tokens")
remaining_requests = remaining_usage.get("x-ratelimit-remaining-requests")
if not already_have_tokens and remaining_tokens is not None:
_labels = prometheus_label_factory(
supported_enum_labels=self.get_labels_for_metric(
metric_name="litellm_remaining_tokens_metric"
),
enum_values=enum_values,
label_context=label_context,
)
self.litellm_remaining_tokens_metric.labels(**_labels).set(
remaining_tokens
)
if not already_have_requests and remaining_requests is not None:
_labels = prometheus_label_factory(
supported_enum_labels=self.get_labels_for_metric(
metric_name="litellm_remaining_requests_metric"
),
enum_values=enum_values,
label_context=label_context,
)
self.litellm_remaining_requests_metric.labels(**_labels).set(
remaining_requests
)
except Exception as e:
verbose_logger.exception(
"Prometheus Error: _async_set_router_remaining_metrics. "
"Exception occured - {}".format(str(e))
)
def set_llm_deployment_success_metrics(
self,
request_kwargs: dict,

View file

@ -4977,8 +4977,9 @@ class BedrockConverseMessagesProcessor:
)
if reasoning_text and not reasoning_text.get("signature"):
reasoning_text_text = reasoning_text["text"]
assistants_part = BedrockContentBlock(text=reasoning_text_text)
assistant_parts.append(assistants_part)
if reasoning_text_text.strip():
assistants_part = BedrockContentBlock(text=reasoning_text_text)
assistant_parts.append(assistants_part)
else:
filtered_thinking_blocks.append(block)
if len(filtered_thinking_blocks) > 0:

View file

@ -1299,9 +1299,18 @@ class LiteLLMAnthropicMessagesAdapter:
else truncated_name
)
# Strip Gemini thought-signature suffix from id (mirrors streaming
# path below); base64 chars (+ / =) violate Anthropic's
# `^[a-zA-Z0-9_-]+$` tool_use.id pattern when replayed.
raw_id = tool_call.id or ""
base_id = (
raw_id.split(THOUGHT_SIGNATURE_SEPARATOR, 1)[0]
if THOUGHT_SIGNATURE_SEPARATOR in raw_id
else raw_id
)
tool_use_block = AnthropicResponseContentBlockToolUse(
type="tool_use",
id=tool_call.id,
id=base_id,
name=original_name,
input=parse_tool_call_arguments(
tool_call.function.arguments,

View file

@ -3,8 +3,10 @@ from typing import Optional, cast
import httpx
import litellm
from litellm.llms.azure.common_utils import BaseAzureLLM
from litellm.llms.openai.image_edit.transformation import OpenAIImageEditConfig
from litellm.secret_managers.main import get_secret_str
from litellm.types.router import GenericLiteLLMParams
from litellm.utils import _add_path_to_api_base
@ -30,20 +32,42 @@ class AzureImageEditConfig(OpenAIImageEditConfig):
litellm_params: Optional[dict] = None,
api_base: Optional[str] = None,
) -> dict:
api_key = (
api_key
or litellm.api_key
or litellm.azure_key
or get_secret_str("AZURE_OPENAI_API_KEY")
or get_secret_str("AZURE_API_KEY")
)
"""
Validate Azure environment and set up authentication headers.
headers.update(
{
"Authorization": f"Bearer {api_key}",
}
Delegates to ``BaseAzureLLM._base_validate_azure_environment`` so the
Azure image-edit route uses the same auth resolution as every other
Azure provider (videos, vector_stores, responses, containers, ...):
- prefers the Azure-style ``api-key`` header when an API key is available
- falls back to ``Authorization: Bearer <azure_ad_token>`` only when AAD
auth is configured
The previous implementation unconditionally set
``Authorization: Bearer <api_key>``, which is correct for OpenAI direct
but not for Azure OpenAI / API Management gateways that expect the
``api-key`` header. Subscription-key-based deployments (e.g., behind
Azure APIM) responded with ``401 "Access denied due to missing
subscription key"``.
API-key precedence (matches ``AzureVideosConfig``):
- ``litellm_params["api_key"]`` is the source of truth.
- The positional ``api_key`` kwarg only fills in when
``litellm_params["api_key"]`` is empty.
- This is a deliberate change from the old ``or`` chain (where the
positional ``api_key`` argument won) so behavior matches every other
Azure ``validate_environment`` implementation. In production the only
caller (``llm_http_handler.image_edit``) sources both values from
the same ``litellm_params.api_key``, so the precedence only matters
for direct callers of this method.
"""
params = GenericLiteLLMParams(**(litellm_params or {}))
if api_key is not None and params.api_key is None:
params.api_key = api_key
return BaseAzureLLM._base_validate_azure_environment(
headers=headers, litellm_params=params
)
return headers
def get_complete_url(
self,

View file

@ -485,11 +485,16 @@ class MaskedHTTPStatusError(httpx.HTTPStatusError):
if k.lower() not in ("content-encoding", "content-length")
}
try:
request_content = original_error.request.content
except httpx.RequestNotRead:
request_content = b""
masked_request = httpx.Request(
method=original_error.request.method,
url=masked_url,
headers=original_error.request.headers,
content=original_error.request.content,
content=request_content,
)
super().__init__(

View file

@ -241,10 +241,13 @@ class FireworksAIConfig(OpenAIGPTConfig):
disable_add_transform_inline_image_block=disable_add_transform_inline_image_block,
)
filter_value_from_dict(cast(dict, message), "cache_control")
# Remove fields not permitted by FireworksAI that may cause:
# "Not permitted, field: 'messages[n].provider_specific_fields'"
if isinstance(message, dict) and "provider_specific_fields" in message:
cast(dict, message).pop("provider_specific_fields", None)
# Remove fields not permitted by FireworksAI (additionalProperties: false
# on their ChatMessage schema) that may cause:
# "Extra inputs are not permitted, field: 'messages[n].<field>'"
if isinstance(message, dict):
m = cast(dict, message)
m.pop("provider_specific_fields", None)
m.pop("thinking_blocks", None)
return messages

View file

@ -2,6 +2,7 @@
Transformation for Calling Google models in their native format.
"""
from copy import deepcopy
from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Tuple, Union, cast
import httpx
@ -11,6 +12,10 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging
from litellm.llms.base_llm.google_genai.transformation import (
BaseGoogleGenAIGenerateContentConfig,
)
from litellm.llms.vertex_ai.common_utils import (
_build_vertex_schema,
supports_response_json_schema,
)
from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import VertexLLM
from litellm.types.router import GenericLiteLLMParams
@ -302,6 +307,52 @@ class GoogleGenAIConfig(BaseGoogleGenAIGenerateContentConfig, VertexLLM):
litellm_params=litellm_params,
)
@staticmethod
def _normalize_response_schema(
generate_content_config_dict: Dict, model: str
) -> None:
schema_key = next(
(
k
for k in ("responseSchema", "response_schema")
if k in generate_content_config_dict
),
None,
)
json_schema_key = next(
(
k
for k in ("responseJsonSchema", "response_json_schema")
if k in generate_content_config_dict
),
None,
)
if schema_key is None:
return
value = generate_content_config_dict[schema_key]
if not isinstance(value, dict):
return
if supports_response_json_schema(model):
if json_schema_key is not None:
generate_content_config_dict.pop(schema_key)
return
generate_content_config_dict.pop(schema_key)
new_json_schema_key = (
"response_json_schema"
if schema_key == "response_schema"
else "responseJsonSchema"
)
generate_content_config_dict[new_json_schema_key] = value
else:
if json_schema_key is not None:
generate_content_config_dict.pop(json_schema_key)
generate_content_config_dict[schema_key] = _build_vertex_schema(
parameters=deepcopy(value), add_property_ordering=True
)
def transform_generate_content_request(
self,
model: str,
@ -315,6 +366,8 @@ class GoogleGenAIConfig(BaseGoogleGenAIGenerateContentConfig, VertexLLM):
GenerateContentRequestDict,
)
self._normalize_response_schema(generate_content_config_dict, model)
typed_generate_content_request = GenerateContentRequestDict(
model=model,
contents=contents,

View file

@ -507,10 +507,10 @@ class OllamaChatCompletionResponseIterator(BaseModelResponseIterator):
# PROCESS REASONING CONTENT
reasoning_content: Optional[str] = None
content: Optional[str] = None
if chunk["message"].get("thinking") is not None:
if chunk["message"].get("thinking"):
reasoning_content = chunk["message"].get("thinking")
self.started_reasoning_content = True
elif chunk["message"].get("content") is not None:
if chunk["message"].get("content"):
if (
self.started_reasoning_content
and not self.finished_reasoning_content

View file

@ -108,7 +108,7 @@ class OllamaModelInfo(BaseLLMModelInfo):
continue
nm = entry.get("name") or entry.get("model")
if isinstance(nm, str):
names.add(nm)
names.add(nm if nm.startswith("ollama/") else f"ollama/{nm}")
except Exception as e:
verbose_logger.warning(f"Error retrieving ollama tag endpoint: {e}")
# If tags endpoint fails, fall back to static list

View file

@ -79,6 +79,9 @@ class VertexAIGoogleGenAIConfig(GoogleGenAIConfig):
Transform the generate content request for Vertex AI.
Since Vertex AI natively supports Google GenAI format, we can pass most fields directly.
"""
if generate_content_config_dict:
self._normalize_response_schema(generate_content_config_dict, model)
# Build the request in Google GenAI format that Vertex AI expects
result = {
"model": model,

View file

@ -3521,7 +3521,7 @@
"supports_tool_choice": true
},
"azure/gpt-4o-mini-transcribe": {
"input_cost_per_audio_token": 3e-06,
"input_cost_per_audio_token": 1.25e-06,
"input_cost_per_token": 1.25e-06,
"litellm_provider": "azure",
"max_input_tokens": 16000,
@ -3596,7 +3596,7 @@
"supports_tool_choice": true
},
"azure/gpt-4o-transcribe": {
"input_cost_per_audio_token": 6e-06,
"input_cost_per_audio_token": 2.5e-06,
"input_cost_per_token": 2.5e-06,
"litellm_provider": "azure",
"max_input_tokens": 16000,
@ -3608,7 +3608,7 @@
]
},
"azure/gpt-4o-transcribe-diarize": {
"input_cost_per_audio_token": 6e-06,
"input_cost_per_audio_token": 2.5e-06,
"input_cost_per_token": 2.5e-06,
"litellm_provider": "azure",
"max_input_tokens": 16000,
@ -8974,7 +8974,7 @@
"supports_vision": true
},
"gpt-4o-transcribe-diarize": {
"input_cost_per_audio_token": 6e-06,
"input_cost_per_audio_token": 2.5e-06,
"input_cost_per_token": 2.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 16000,
@ -15551,14 +15551,17 @@
"uses_embed_content": true
},
"vertex_ai/gemini-embedding-2-preview": {
"input_cost_per_token": 1.5e-07,
"input_cost_per_audio_per_second": 0.00016,
"input_cost_per_image": 0.00012,
"input_cost_per_token": 2e-07,
"input_cost_per_video_per_second": 0.00079,
"litellm_provider": "vertex_ai",
"max_input_tokens": 8192,
"max_tokens": 8192,
"mode": "embedding",
"output_cost_per_token": 0,
"output_vector_size": 3072,
"source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
"source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
"supports_multimodal": true,
"uses_embed_content": true
},
@ -15573,7 +15576,7 @@
"mode": "embedding",
"output_cost_per_token": 0,
"output_vector_size": 3072,
"source": "https://ai.google.dev/gemini-api/docs/embeddings#multimodal",
"source": "https://cloud.google.com/vertex-ai/generative-ai/pricing",
"supports_multimodal": true,
"uses_embed_content": true
},
@ -18988,7 +18991,7 @@
"supports_vision": true
},
"gpt-4o-mini-transcribe": {
"input_cost_per_audio_token": 3e-06,
"input_cost_per_audio_token": 1.25e-06,
"input_cost_per_token": 1.25e-06,
"litellm_provider": "openai",
"max_input_tokens": 16000,
@ -19118,7 +19121,7 @@
"supports_vision": true
},
"gpt-4o-transcribe": {
"input_cost_per_audio_token": 6e-06,
"input_cost_per_audio_token": 2.5e-06,
"input_cost_per_token": 2.5e-06,
"litellm_provider": "openai",
"max_input_tokens": 16000,
@ -38930,7 +38933,7 @@
]
},
"gpt-4o-mini-transcribe-2025-03-20": {
"input_cost_per_audio_token": 3e-06,
"input_cost_per_audio_token": 1.25e-06,
"input_cost_per_token": 1.25e-06,
"litellm_provider": "openai",
"max_input_tokens": 16000,
@ -38942,7 +38945,7 @@
]
},
"gpt-4o-mini-transcribe-2025-12-15": {
"input_cost_per_audio_token": 3e-06,
"input_cost_per_audio_token": 1.25e-06,
"input_cost_per_token": 1.25e-06,
"litellm_provider": "openai",
"max_input_tokens": 16000,

View file

@ -1,3 +1,4 @@
import re
from typing import Dict, List, Optional, Set, Tuple, cast
from fastapi import HTTPException
@ -122,6 +123,24 @@ class MCPRequestHandler:
# cannot be smuggled via query string, hostname, or a deeper URL segment.
if request.url.path.startswith("/.well-known/"):
validated_user_api_key_auth = UserAPIKeyAuth()
elif (
not litellm_api_key
and MCPRequestHandler._target_servers_delegate_auth_to_upstream( # noqa: E501
path=request.url.path, mcp_servers=mcp_servers
)
):
# Operator opted this oauth2 server into upstream-delegated auth
# (PKCE passthrough): skip LiteLLM API-key/SSO entirely so the
# client authenticates directly with the upstream MCP server.
# Fires ONLY when neither x-litellm-api-key nor Authorization is
# present. If any LiteLLM key is supplied (primary or secondary
# header), we fall through so user_id is resolved, spend/rate
# limiting apply, and any stored OAuth token can be retrieved
# and forwarded upstream. Gated by
# _target_servers_delegate_auth_to_upstream, which only returns
# True when EVERY target is auth_type=oauth2 AND has the
# delegate_auth_to_upstream flag set — fails closed otherwise.
validated_user_api_key_auth = UserAPIKeyAuth()
elif has_explicit_litellm_key:
# Explicit x-litellm-api-key provided - always validate normally
validated_user_api_key_auth = await user_api_key_auth(
@ -181,23 +200,62 @@ class MCPRequestHandler:
@staticmethod
def _extract_target_server_names_from_path(path: str) -> List[str]:
"""
Extract the target MCP server name from the standard MCP transport
URL patterns: ``/mcp/{server_name}[/...]`` and
Extract the target MCP server name(s) from the standard MCP transport
URL patterns: ``/mcp/{server_name_or_csv}[/...]`` and
``/{server_name}/mcp[/...]``. Returns ``[]`` for any other path so
callers fail closed when the target cannot be resolved.
Mirrors the regex-based parser in ``server.py::_get_mcp_servers_in_path``
so the names used for auth gating match the names used for downstream
filtering. Without this alignment, an attacker could craft
``/mcp/<delegated_server>/<garbage>`` so that auth treats the request
as targeting the delegate server (bypassing LiteLLM auth) while
downstream filtering sees a different (non-existent) target and falls
back to the caller's full allowed-server set.
REST/admin endpoints, OAuth2 server endpoints
(``/{server_name}/authorize``, ``/token`` etc.), and ``.well-known``
discovery routes intentionally fall through those flows do not need
OAuth2 token passthrough. Clients aggregating multiple servers should
use ``x-mcp-servers``, which takes precedence over path parsing.
use ``x-mcp-servers`` on a path that does not encode a target.
"""
# ``/{server_name}/mcp[/...]`` form — single server. The literal
# ``mcp`` must be the second segment (not the first, which would be
# the ``/mcp/...`` form handled below). This branch must stay in sync
# with ``server.py::_get_mcp_servers_in_path``, which also accepts the
# un-rewritten form (some entry points may skip the
# ``dynamic_mcp_route`` rewrite).
segments = [s for s in path.split("/") if s]
if len(segments) >= 2 and segments[0] == "mcp":
return [segments[1]]
if len(segments) >= 2 and segments[1] == "mcp":
if len(segments) >= 2 and segments[1] == "mcp" and segments[0] != "mcp":
return [segments[0]]
return []
# ``/mcp/...`` form — server name(s) may contain a slash (e.g.
# ``custom_solutions/user_123``) and may be a comma-separated list.
# Use the same parsing logic as ``_get_mcp_servers_in_path`` so the
# parsed names match downstream routing.
mcp_path_match = re.match(r"^/mcp/([^?#]+)(?:\?.*)?(?:#.*)?$", path)
if not mcp_path_match:
return []
servers_and_path = mcp_path_match.group(1)
if not servers_and_path:
return []
if "," in servers_and_path:
# Comma-separated servers, possibly followed by a trailing path.
path_match = re.search(r"/([^/,]+(?:/[^/,]+)*)$", servers_and_path)
if path_match:
servers_part = servers_and_path[: -(len(path_match.group(1)) + 1)]
else:
servers_part = servers_and_path
return [s.strip() for s in servers_part.split(",") if s.strip()]
# Single-server case — server name may contain at most one slash.
single_server_match = re.match(
r"^([^/]+(?:/[^/]+)?)(?:/.*)?$", servers_and_path
)
if single_server_match:
return [single_server_match.group(1)]
return [servers_and_path]
@staticmethod
def _target_servers_use_oauth2(path: str, mcp_servers: Optional[List[str]]) -> bool:
@ -217,13 +275,13 @@ class MCPRequestHandler:
)
from litellm.types.mcp import MCPAuth
# Use the x-mcp-servers header verbatim when present (including the
# explicitly-empty list, which means "no targets" → fail closed).
# Only fall back to path parsing when the header was absent entirely.
target_names = (
mcp_servers
if mcp_servers is not None
else MCPRequestHandler._extract_target_server_names_from_path(path)
# Resolve the same target list downstream routing will use. For
# ``/mcp/...`` routes, ``extract_mcp_auth_context`` overrides the
# ``x-mcp-servers`` header with path-derived names, so we must mirror
# that here — otherwise a caller could set the header to a permissive
# server while the path targets a stricter one (header/path TOCTOU).
target_names = MCPRequestHandler._resolve_target_server_names(
path=path, mcp_servers_header=mcp_servers
)
if not target_names:
return False
@ -234,6 +292,78 @@ class MCPRequestHandler:
return False
return True
@staticmethod
def _target_servers_delegate_auth_to_upstream(
path: str, mcp_servers: Optional[List[str]]
) -> bool:
"""
True only when EVERY MCP server the request targets is configured for
``auth_type == oauth2`` AND has ``delegate_auth_to_upstream=True``.
Fails closed when any target does not opt in or cannot be resolved.
Used by :meth:`process_mcp_request` to skip LiteLLM API-key/SSO auth
entirely (PKCE passthrough) so the client authenticates directly with
the upstream MCP server. Mixed-target requests (e.g. one delegated +
one non-delegated server) fall back to normal LiteLLM auth.
"""
# Inline imports avoid a circular dependency: mcp_server_manager imports
# from this module.
from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
global_mcp_server_manager,
)
from litellm.types.mcp import MCPAuth
# See _target_servers_use_oauth2: must mirror the downstream
# header-vs-path override or an attacker could set
# ``x-mcp-servers`` to a delegate-enabled server while the URL path
# targets a non-delegate server, skipping LiteLLM auth for it.
target_names = MCPRequestHandler._resolve_target_server_names(
path=path, mcp_servers_header=mcp_servers
)
if not target_names:
return False
for name in target_names:
server = global_mcp_server_manager.get_mcp_server_by_name(name)
if server is None or server.auth_type != MCPAuth.oauth2:
return False
# `is True` is intentional: opt-in must be an explicit boolean
# True. A MagicMock attribute (in tests) or any other truthy
# non-bool must not silently enable the bypass.
if getattr(server, "delegate_auth_to_upstream", False) is not True:
return False
if not getattr(server, "available_on_public_internet", True):
return False
# Never delegate for M2M (client_credentials) servers: LiteLLM
# fetches the upstream token automatically using stored credentials,
# so allowing anonymous bypass would let any external caller invoke
# tools authenticated as LiteLLM's service account.
if server.has_client_credentials:
return False
return True
@staticmethod
def _resolve_target_server_names(
path: str, mcp_servers_header: Optional[List[str]]
) -> List[str]:
"""
Resolve the target MCP server names exactly as downstream routing
does (``server.py::extract_mcp_auth_context``).
For ``/mcp/...`` paths, downstream routing **overrides** any
``x-mcp-servers`` header value with the path-derived names. Mirror
that here so an attacker cannot use a permissive header value to
flip an auth gate while the path targets a stricter server
(header/path TOCTOU). For non-``/mcp/...`` paths (where the path
does not encode targets), fall back to the header.
"""
path_targets = MCPRequestHandler._extract_target_server_names_from_path(path)
if path_targets:
return path_targets
# Path did not resolve to /mcp/... targets — trust the header
# (including an explicitly empty list, which means "no targets").
return mcp_servers_header if mcp_servers_header is not None else []
@staticmethod
def _get_mcp_auth_header_from_headers(headers: Headers) -> Optional[str]:
"""

View file

@ -402,6 +402,9 @@ class MCPServerManager:
available_on_public_internet=bool(
server_config.get("available_on_public_internet", True)
),
delegate_auth_to_upstream=bool(
server_config.get("delegate_auth_to_upstream", False)
),
# AWS SigV4 fields
aws_access_key_id=server_config.get("aws_access_key_id", None),
aws_secret_access_key=server_config.get("aws_secret_access_key", None),
@ -796,6 +799,9 @@ class MCPServerManager:
available_on_public_internet=bool(
getattr(mcp_server, "available_on_public_internet", True)
),
delegate_auth_to_upstream=bool(
getattr(mcp_server, "delegate_auth_to_upstream", False)
),
created_at=getattr(mcp_server, "created_at", None),
updated_at=getattr(mcp_server, "updated_at", None),
tool_name_to_display_name=_deserialize_json_dict(
@ -967,6 +973,34 @@ class MCPServerManager:
if not in_toolset_scope:
combined_servers.update(allow_all_server_ids)
# For anonymous callers (no user_id, no role), also surface any
# servers the operator has opted into upstream-delegated auth.
# These servers handle their own auth at the upstream level, so
# LiteLLM granting access here does not bypass any security gate.
is_anonymous = not (
user_api_key_auth
and (
getattr(user_api_key_auth, "user_id", None)
or getattr(user_api_key_auth, "user_role", None)
or getattr(user_api_key_auth, "api_key", None)
)
)
if is_anonymous:
delegate_server_ids = [
server.server_id
for server in self.get_registry().values()
if getattr(server, "auth_type", None) == MCPAuth.oauth2
and getattr(server, "delegate_auth_to_upstream", False) is True
# M2M servers must not be exposed anonymously: an
# unauthenticated caller would get LiteLLM to proxy tool
# calls using its stored client_credentials.
and not server.has_client_credentials
# Internal-only servers must not be reachable from public
# internet callers who happen to carry an upstream token.
and getattr(server, "available_on_public_internet", True)
]
combined_servers.update(delegate_server_ids)
if len(combined_servers) == 0:
verbose_logger.debug(
"No allowed MCP Servers found for user api key auth."

View file

@ -23,6 +23,7 @@ from typing import (
cast,
)
import httpx
from fastapi import FastAPI, HTTPException
from pydantic import AnyUrl, ConfigDict
from starlette.requests import Request as StarletteRequest
@ -51,13 +52,17 @@ from litellm.proxy._experimental.mcp_server.utils import (
get_server_prefix,
iter_known_server_prefixes,
)
from litellm.llms.custom_httpx.http_handler import (
get_async_httpx_client,
httpxSpecialProvider,
)
from litellm.proxy._types import UserAPIKeyAuth
from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.litellm_pre_call_utils import (
LiteLLMProxyRequestSetup,
get_chain_id_from_headers,
)
from litellm.types.mcp import MCPAuth
from litellm.types.mcp import MCPAuth, MCPSpecVersion
from litellm.types.mcp_server.mcp_server_manager import MCPInfo, MCPServer
from litellm.types.utils import CallTypes, StandardLoggingMCPToolCall
from litellm.utils import Rules, client, function_setup
@ -1332,8 +1337,24 @@ if MCP_AVAILABLE:
raw_headers=raw_headers,
)
# If no OAuth2 token came from request headers, fall back to pre-fetched creds
if extra_headers is None and server.auth_type == MCPAuth.oauth2:
# 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).
if (
server.auth_type == MCPAuth.oauth2
and getattr(server, "needs_user_oauth_token", False)
and user_api_key_auth is not None
):
db_headers = 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 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,
@ -2536,6 +2557,10 @@ if MCP_AVAILABLE:
import re
mcp_servers_from_path: Optional[List[str]] = None
segments = [s for s in path.split("/") if s]
if len(segments) >= 2 and segments[1] == "mcp" and segments[0] != "mcp":
return [segments[0]]
# Match /mcp/<servers_and_maybe_path>
# Where servers can be comma-separated list of server names
# Server names can contain slashes (e.g., "custom_solutions/user_123")
@ -2754,6 +2779,157 @@ if MCP_AVAILABLE:
)
return user_api_key_auth.model_copy(update={"object_permission": updated_op})
def _get_forwarded_auth_from_scope(scope: Scope) -> Optional[str]:
"""Return the upstream-bound ``Authorization`` header value, or None.
Only returns the ``Authorization`` header when ``x-litellm-api-key`` is
also present. In that case ``Authorization`` is unambiguously the
upstream token the caller wants forwarded to the MCP server. When
``x-litellm-api-key`` is absent the ``Authorization`` header may itself
be the LiteLLM proxy API key (backward-compat path in
``MCPRequestHandler.process_mcp_request``), and forwarding it upstream
would leak the proxy key to a third-party MCP server.
"""
authorization = None
has_litellm_key_header = False
for key, value in scope.get("headers", []):
key_lower = key.lower()
if key_lower == b"authorization":
authorization = value.decode("latin-1")
elif key_lower == b"x-litellm-api-key":
has_litellm_key_header = True
if not has_litellm_key_header:
return None
return authorization
async def _probe_upstream_auth(
url: str,
auth_header: str,
timeout: float = 5.0,
) -> tuple:
"""JSON-RPC initialize-probe the upstream URL to check whether the token is accepted.
Uses POST so StreamableHTTP MCP servers run the same auth path as a
real client request. Returns (status_code, www_authenticate).
Fails-open with (200, None) on network errors so a transient hiccup
does not block valid requests.
Uses the public ``AsyncHTTPHandler.post()`` interface and catches
``httpx.HTTPStatusError`` separately so the 401/403 we want to surface
is not swallowed by the broad fail-open ``except Exception`` below.
"""
client = get_async_httpx_client(
llm_provider=httpxSpecialProvider.MCP,
params={"timeout": timeout},
)
probe_payload = {
"jsonrpc": "2.0",
"id": "litellm-mcp-auth-probe",
"method": "initialize",
"params": {
"protocolVersion": MCPSpecVersion.jun_2025.value,
"capabilities": {},
"clientInfo": {
"name": "litellm-mcp-auth-probe",
"version": "1.0.0",
},
},
}
probe_headers = {
"Authorization": auth_header,
"Accept": "application/json, text/event-stream",
}
try:
resp = await client.post(
url=url,
headers=probe_headers,
json=probe_payload,
timeout=timeout,
)
return resp.status_code, resp.headers.get("www-authenticate")
except httpx.HTTPStatusError as exc:
# AsyncHTTPHandler.post() calls raise_for_status(); a 401/403 from
# upstream lands here. Return its status so the caller can map it
# to the appropriate response.
return exc.response.status_code, exc.response.headers.get(
"www-authenticate"
)
except Exception as exc:
verbose_logger.debug(
f"_probe_upstream_auth: probe to {url} failed ({exc}), allowing request through"
)
return 200, None
async def _check_passthrough_upstream_auth(
scope: Scope,
user_api_key_auth: Optional[UserAPIKeyAuth],
mcp_servers: Optional[List[str]],
client_ip: Optional[str],
) -> None:
"""Probe pass-through upstream servers in parallel before the MCP session starts.
Only servers the caller's key is already authorized to reach are probed —
the list is derived from _get_allowed_mcp_servers so that a user cannot
trigger an upstream probe against a server their key is not permitted for.
The MCP SDK commits HTTP 200 headers before invoking handlers, so a 401
can only be returned before that point. This function raises HTTPException(401)
with a WWW-Authenticate header if any upstream rejects the client token.
Fails-open: network errors are logged and the request is allowed through.
"""
forwarded_auth = _get_forwarded_auth_from_scope(scope)
if not forwarded_auth:
return
# Use the authorized server set, not the raw user-supplied names, so that
# a caller cannot force a probe to a server their key is not allowed to use.
allowed_servers = await _get_allowed_mcp_servers(
user_api_key_auth=user_api_key_auth,
mcp_servers=mcp_servers,
client_ip=client_ip,
)
passthrough_servers = [
srv
for srv in allowed_servers
if srv.extra_headers
and any(h.lower() == "authorization" for h in srv.extra_headers)
# Exclude M2M servers: _prepare_mcp_server_headers skips caller
# Authorization when has_client_credentials is set, so probing
# those with the caller's token would send the wrong credential.
and not srv.has_client_credentials
]
if not passthrough_servers:
return
probe_results = await asyncio.gather(
*[
_probe_upstream_auth(srv.url or "", forwarded_auth)
for srv in passthrough_servers
]
)
request = StarletteRequest(scope)
base_url = get_request_base_url(request)
for srv, (probe_status, _) in zip(passthrough_servers, probe_results):
if probe_status == 401:
# Token is missing or expired — direct the client to re-authorize.
authorization_uri = (
f"Bearer authorization_uri="
f"{base_url}/.well-known/oauth-authorization-server/{srv.name}"
)
raise HTTPException(
status_code=401,
detail="Unauthorized",
headers={"WWW-Authenticate": authorization_uri},
)
if probe_status == 403:
# Token is valid but the caller lacks permission — do not hint
# at re-authorization (RFC 9110: a fresh token with the same
# scopes would just hit 403 again and loop indefinitely).
raise HTTPException(
status_code=403,
detail="Forbidden",
)
async def handle_streamable_http_mcp(
scope: Scope, receive: Receive, send: Send
) -> None:
@ -2827,6 +3003,13 @@ if MCP_AVAILABLE:
user_api_key_auth, active_toolset_id
)
# Pre-flight auth check for pass-through servers. Must run after
# toolset scoping so the probe list is derived from the fully-authorized
# server set, not the raw user-supplied names.
await _check_passthrough_upstream_auth(
scope, user_api_key_auth, mcp_servers, _client_ip
)
# Inject masked debug headers when client sends x-litellm-mcp-debug: true
_debug_headers = MCPDebug.maybe_build_debug_headers(
raw_headers=raw_headers,

View file

@ -92,13 +92,20 @@ class MCPToolRegistry:
]
def load_tools_from_config(
self, mcp_tools_config: Optional[Dict[str, Any]] = None
self,
mcp_tools_config: Optional[Dict[str, Any]] = None,
config_file_path: Optional[str] = None,
) -> None:
"""
Load and register tools from the proxy config
Args:
mcp_tools_config: The mcp_tools config from the proxy config
config_file_path: Path to the operator's config.yaml. Threaded
through to ``get_instance_fn`` so an ``s3://``/``gcs://``
``handler`` declared in the YAML resolves; callers from a
non-YAML path must leave this ``None`` so the runtime gate
fires.
"""
if mcp_tools_config is None:
raise ValueError(
@ -121,7 +128,7 @@ class MCPToolRegistry:
# First check if it's a module path (e.g., "module.submodule.function")
if handler_name is None:
raise ValueError(f"handler is required for tool {name}")
handler = get_instance_fn(handler_name)
handler = get_instance_fn(handler_name, config_file_path)
if handler is None:
verbose_logger.warning(

File diff suppressed because one or more lines are too long

View file

@ -1,10 +1,10 @@
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