* fix(prometheus): emit remaining_tokens/requests gauges for bedrock + vertex (LIT-2719)
Bedrock and Vertex AI never return x-ratelimit-remaining-* response headers,
so litellm_remaining_tokens_metric / litellm_remaining_requests_metric only
fired for OpenAI / Azure / Anthropic deployments even when tpm/rpm was
configured on the router.
Add a provider-agnostic fallback in PrometheusLogger.async_log_success_event
that asks Router.get_remaining_model_group_usage() for the same model_group
and emits the gauges with configured_limit - current_usage when the upstream
provider didn't populate the headers itself. Existing OpenAI / Azure /
Anthropic flows are unchanged because the fallback short-circuits when both
header values are already present.
Tests: 8 new tests covering bedrock + vertex emission, header short-circuit,
partial-header fill, llm_router=None, missing model_group, empty router
result, and router exception swallowing.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(prometheus): narrow except to ImportError, log router lookup failures via verbose_logger.exception
Address greptile review:
- The optional 'from litellm.proxy.proxy_server import llm_router' should
guard against ImportError specifically, not all exceptions, so that
unexpected errors (e.g. AttributeError from partially-initialized state)
stay visible.
- get_remaining_model_group_usage failures are now logged via
verbose_logger.exception (with traceback) instead of debug, matching the
PR description's intent and avoiding silent loss of router-cache errors
in production.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(prometheus): subtract in-flight delta in router-remaining fallback
The router's TPM/RPM counter is incremented by
Router.deployment_callback_on_success, which fires alongside this
prometheus callback in the success-log fan-out. Prometheus wins the
race, so get_remaining_model_group_usage returns the pre-decrement
counter for the current request — while vendor headers
(OpenAI/Anthropic/Azure) are already post-decrement.
That broke parity between providers on the same gauge: dashboards
plotting litellm_remaining_requests_metric showed Bedrock/Vertex
perpetually one request behind Anthropic for the same throughput.
Replay the in-flight increment before emit: subtract total_tokens
from remaining_tokens and 1 from remaining_requests.
* Revert "fix(prometheus): subtract in-flight delta in router-remaining fallback"
This reverts commit 001ce95ecdd952b4b5a23dd2b1e62c4562c932bc.
* fix(router): post-decrement router-derived ratelimit headers
Router.set_response_headers injects x-ratelimit-remaining-{tokens,
requests} for providers that don't return them natively (Bedrock,
Vertex). The values come from get_remaining_model_group_usage, which
reads the router's TPM/RPM counter — incremented post-response by
deployment_callback_on_success. So the headers reflected the counter
state before the current request was counted: pre-decrement.
Vendor headers from OpenAI/Anthropic/Azure are post-decrement (the
vendor counted the request before responding). Same metric name, two
semantics — dashboards plotting litellm_remaining_requests_metric
showed Bedrock/Vertex perpetually one request behind for the same
throughput, and the HTTP response headers exposed the same skew to
clients.
Subtract the in-flight delta before writing: 1 from
remaining-requests, response.usage.total_tokens from remaining-tokens.
Fixes both the response headers and (transitively) the prometheus
gauges that read from standard_logging_payload.additional_headers.
---------
Co-authored-by: cursor <cursor@example.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(fireworks_ai): strip thinking_blocks from chat messages before API call
Fireworks OpenAI-compatible ChatMessage schema uses additionalProperties:false
and rejects Anthropic-style messages[].thinking_blocks (e.g. Claude Code replays),
returning invalid_request_error. Remove the field in _transform_messages_helper
alongside provider_specific_fields.
Adds unit test test_transform_messages_helper_strips_thinking_blocks.
Co-authored-by: Cursor <cursoragent@cursor.com>
* chore(fireworks_ai): drop inline comments from message sanitization
Co-authored-by: Cursor <cursoragent@cursor.com>
* docs(fireworks_ai): explain why provider_specific_fields and thinking_blocks are stripped
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix: strip Gemini thought-signature from tool_use.id in non-streaming path; example websearch config (#27873)
- adapters/transformation.py: mirror the streaming path and strip the
`__thought__<b64>` suffix off `tool_call.id` before building the
AnthropicResponseContentBlockToolUse. Base64's `+ / =` characters
violate Anthropic's `^[a-zA-Z0-9_-]+$` tool_use.id pattern, so when a
conversation that flowed through Gemini is later replayed to an
Anthropic-native provider (Bedrock or Anthropic API) the request 400s.
- example_config_yaml/websearch_interception_config.yaml: register the
interceptor under `callbacks:` not `success_callback:`. `success_callback`
does not run pre-request hooks, so the tool-conversion step never fires
on `/v1/messages` and the raw `web_search_20250305` tool is forwarded
to Bedrock, which 400s.
- adds a unit test pinning the non-streaming strip behavior and the
surviving `^[a-zA-Z0-9_-]+$` shape of the resulting id.
Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com>
* Fix/azure image edit auth header (#27863)
* fix(azure/image_edit): use api-key header instead of Authorization Bearer
Delegate `AzureImageEditConfig.validate_environment` to
`BaseAzureLLM._base_validate_azure_environment` so the image-edit route
follows the same auth resolution as every other Azure provider:
- prefer the Azure-native `api-key` header when an API key is available
- fall back to `Authorization: Bearer <azure_ad_token>` only for AAD auth
The previous implementation unconditionally set
`Authorization: Bearer <api_key>`, which is the OpenAI-direct convention
and is rejected by Azure OpenAI / APIM-fronted deployments with
`401 Access denied due to missing subscription key`.
Adds regression tests covering api_key kwarg, litellm_params.api_key, and
the AAD-token fallback path.
Co-authored-by: Cursor <cursoragent@cursor.com>
* docs(azure/image_edit): pin api-key precedence semantics + add regression test
Address review feedback that the move to
``BaseAzureLLM._base_validate_azure_environment`` changed the relative
priority of the positional ``api_key`` kwarg vs. ``litellm_params["api_key"]``.
The new behavior — ``litellm_params["api_key"]`` wins, positional only fills
in when ``litellm_params["api_key"]`` is empty — is intentional and matches
every other Azure ``validate_environment``: ``AzureVideosConfig`` uses the
exact same merge logic, while ``AzureVectorStoresConfig`` and
``AzureResponsesAPIConfig`` don't accept a positional ``api_key`` at all.
The old ``or`` chain (positional wins) was the outlier and was part of the
same OpenAI-vs-Azure convention drift that produced the original
``Authorization: Bearer`` bug.
The only production caller (``llm_http_handler.image_edit``) sources both
values from the same ``litellm_params.api_key``, so this change is
behaviorally a no-op there. Document the precedence in the docstring and
lock it in with an explicit test so future refactors can't quietly
re-invert it.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: Adam Kirstein <adam.kirstein@disney.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(azure/image_edit): expect api-key header instead of Authorization Bearer
PR #27863 fixed Azure image edit to use the Azure-native api-key header
instead of OpenAI's Authorization: Bearer convention, but did not update
test_azure_image_edit_litellm_sdk to match. The test still asserted
'Authorization' in headers, which now fails since the new code routes
through BaseAzureLLM._base_validate_azure_environment and emits
api-key when an api_key is provided.
Update the assertion to pin the correct Azure behavior: api-key header
present with the resolved key, and no Authorization header.
---------
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: oss-agent-shin <279349115+oss-agent-shin@users.noreply.github.com>
Co-authored-by: Adam Kirstein <107421694+justalittleadam@users.noreply.github.com>
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: Adam Kirstein <adam.kirstein@disney.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* fix(ollama): Include provider in model list for ollama (#26135)
* Include provider in model names for ollama
* Fix unit tests
* fix(ollama): process both thinking and content in same streaming chunk (#26098)
* fix(health_check): skip max_tokens for image_generation mode (#26417)
* fix(health_check): skip max_tokens for image_generation mode
`_update_litellm_params_for_health_check` injected `max_tokens` for
every deployment. OpenAI `/v1/images/generations` strictly rejects
unknown fields, so health checks for dall-e-* and gpt-image-1 always
failed with `400 "Unknown parameter: 'max_tokens'"` even though the
actual image endpoint calls succeed. Skip the `max_tokens` injection
when `model_info.mode == "image_generation"`. `messages` still gets
injected (downstream `_filter_model_params` already strips it for
non-chat handlers).
* Switch to allow-list with per-deployment override
Per @krrishdholakia review: deny-listing image_generation only re-introduces
the same bug for every other non-chat mode (embedding, audio_*, rerank,
video_generation, ocr, search, moderation, ...).
Replace the single image_generation skip with `_MAX_TOKEN_SUPPORT_MODES =
{chat, completion, responses}`. Missing `mode` is treated as chat for
backward compatibility. New modes are safe by default.
Add `model_info.health_check_supports_max_tokens` as an operator escape
hatch — True forces injection on a non-listed deployment (operator wants
to bound probe tokens), False suppresses it on a chat-style deployment
behind a strict-schema provider.
Tests: parametrize over 3 chat-style + 10 non-chat modes, plus override
on/off and the no-mode legacy path.
* fix(http_handler): handle RequestNotRead in MaskedHTTPStatusError for multipart uploads (#26718)
Squash-merged by litellm-agent from dawidkulpa's PR.
* fix(ollama): guard against double 'ollama/' prefix in live model listing
Greptile flagged that Ollama servers can return names that already start
with 'ollama/'. Check the prefix before prepending so we don't produce
'ollama/ollama/...'. Adds a regression test.
* Fix Ollama empty reasoning stream chunks
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: James Myatt <james@jamesmyatt.co.uk>
Co-authored-by: VHash <225398745+vhash0@users.noreply.github.com>
Co-authored-by: hayden <sewhan.kim+@a-bly.com>
Co-authored-by: dawidkulpa <84176950+dawidkulpa@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude <claude@anthropic.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix: Fix Redis Sentinel client handling to solve authentication error with password protected sentinel (#25625)
* fix Redis Sentinel authentication handling
* test: cover Redis Sentinel auth routing
* refactor: align Redis Sentinel kwargs threading
* fix: avoid duplicate Redis Sentinel socket timeouts
* Address review comments
* refactor(_redis): return set from _get_redis_kwargs for O(1) lookup
Align _get_redis_kwargs() with the cluster helper by returning a set
instead of a list, so the sentinel connection-kwargs filter uses O(1)
membership tests. Addresses Greptile review feedback on PR #26302.
* fix(_redis): restore Azure-specific kwargs in cluster kwargs set
The set-literal refactor of _get_redis_cluster_kwargs dropped four
LiteLLM-custom Azure keys (azure_redis_ad_token, azure_client_id,
azure_tenant_id, azure_client_secret) that the prior list form had
explicitly appended. Because they are not in RedisCluster's argspec,
they were silently stripped, breaking Azure IAM auth on cluster
clients. Re-add them to the explicit include set.
---------
Co-authored-by: Kristin Cowalcijk <kristincowalcijk@gmail.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: krrish-berri-2 <krrish-berri-2@users.noreply.github.com>
Co-authored-by: claude <claude@anthropic.com>
External readiness probes consumed the legacy detailed payload's `db`
field to drive alerting and pod-rotation decisions. Stripping the body
to `{"status": "healthy"}` broke those probes silently — the HTTP code
still flipped to 503, but probes checking `body.db == "connected"`
treated the response as healthy.
Add `db` back to the unauthenticated payload. Keep the rest of the
diagnostic fields (litellm_version, callbacks, cache, log_level) gated
behind /health/readiness/details so the recon-leak gate from #26912
holds. Values match the legacy contract: "connected", "disconnected",
"Not connected".
* fix(responses): preserve cache_control in Responses API -> Chat Completion transformation
cache_control injected by AnthropicCacheControlHook was silently dropped when
_transform_responses_api_content_to_chat_completion_content rebuilt content blocks
with only {type, text}. Now copies cache_control through so Anthropic prompt caching
works correctly when using client.responses.create with cache_control_injection_points.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(responses): preserve cache_control for input_image and input_file blocks
Extends the cache_control fix to image and file content blocks, which were
also silently dropping cache_control during the Responses API -> Chat Completion
transformation. Adds tests for all three content block types.
Co-authored-by: Cursor <cursoragent@cursor.com>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude Babysitter <claude@anthropic.com>
* feat(mcp): add delegate_auth_to_upstream flag for PKCE passthrough
Adds an opt-in per-server flag that lets clients (e.g. VS Code) complete
PKCE directly with an upstream OAuth2 MCP server, instead of LiteLLM
double-gating with its own API-key/SSO check. Only honored when
auth_type=oauth2 and the operator explicitly sets the flag; mixed-target
or non-oauth2 requests fail closed.
- Adds the field to Pydantic models, Prisma schema, and a migration
- New MCPRequestHandler._target_servers_delegate_auth_to_upstream gate
that runs only when no x-litellm-api-key is present, so authenticated
users still get user_id resolution + stored-credential lookup
- Anonymous callers now see delegate servers in get_allowed_mcp_servers
(scoped to delegate servers only; the upstream still enforces auth)
- mcp_management_endpoints: allow anonymous /authorize and /token for
delegate servers so VS Code can complete PKCE without a LiteLLM session
- UI toggle (shown only for oauth2) + payload/view wiring
- Tests covering: oauth2 on/off, non-oauth2 with flag, mixed targets,
no resolvable target, explicit key precedence, and 401 emission
Co-authored-by: Cursor <cursoragent@cursor.com>
* Enforce oauth2 for delegated MCP auth bypass
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): close secondary Authorization bypass for delegate servers
The delegate-auth bypass gated only on the primary `x-litellm-api-key`
header, so a LiteLLM key sent via `Authorization: Bearer sk-...` (the
secondary header) was silently dropped — skipping spend tracking and
rate limiting. Gate on the resolved litellm_api_key (which considers
both headers) so the bypass fires only when neither is present.
Also update the existing "Authorization header present" test to reflect
that an upstream OAuth token now flows through the existing oauth2
fallback (LiteLLM auth attempt → fail → anonymous), not via the
delegate branch.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Avoid duplicate MCP OAuth credential lookup
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): block delegate bypass for M2M and internal-only servers
Two security issues flagged in code review:
1. High – client_credentials (M2M) servers must not be delegatable:
LiteLLM auto-fetches the upstream token using stored credentials, so
allowing anonymous bypass would let any external caller invoke tools
authenticated as LiteLLM's service account.
Fix: check `server.has_client_credentials` in
`_target_servers_delegate_auth_to_upstream`, the anonymous
allow-list in `get_allowed_mcp_servers`, and `_mcp_oauth_user_api_key_auth`.
2. Medium – internal-only servers exposed to public internet:
The anonymous delegate allow-list was not filtering by
`available_on_public_internet`, so external callers with an upstream
OAuth token could invoke tools on servers marked internal-only.
Fix: add `available_on_public_internet` guard to the anonymous
delegate server list in `get_allowed_mcp_servers`.
Tests added for both cases.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Require public MCP delegate auth servers
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): align delegate auth path parsing with downstream routing
`_extract_target_server_names_from_path` used a naive segments-based
split while `server.py::_get_mcp_servers_in_path` uses a regex that
allows server names with one embedded slash and comma-separated lists.
With the old parser, a request to `/mcp/<delegated>/<garbage>` was
parsed as targeting `<delegated>` by the auth gate (bypassing LiteLLM
auth) while the routing layer parsed it as `<delegated>/<garbage>` —
when that name did not resolve, the request fell back to the anonymous
allow-list, which can include `allow_all_keys` servers that normally
require a LiteLLM key.
Replace the parser with the same regex logic as
`_get_mcp_servers_in_path` so auth gating sees the exact target name(s)
downstream routing sees. Add regression tests covering parser parity
and the specific extra-path-segment bypass attempt.
https://claude.ai/code/session_01SjyPmwfmrq8fveFgw9iHW9
* fix(mcp): close header/path TOCTOU in MCP delegate auth gate
`_target_servers_delegate_auth_to_upstream` and
`_target_servers_use_oauth2` trusted the `x-mcp-servers` header when
present, but `server.py::extract_mcp_auth_context` overrides that
header with the path-derived list for `/mcp/...` routes. An attacker
could set `x-mcp-servers: <delegated>` while pointing the URL path at
a non-delegate server, flipping the auth gate without changing the
target downstream routing actually uses.
Extract a shared `_resolve_target_server_names` helper that mirrors
the downstream override (path-derived names for `/mcp/...` routes,
header value otherwise). Add regression tests covering the TOCTOU
attempt and the helper's path-vs-header precedence.
https://claude.ai/code/session_01SjyPmwfmrq8fveFgw9iHW9
* Fix delegated MCP OAuth test mock
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): drop unreachable /{server}/mcp branch in auth path parser
`_extract_target_server_names_from_path` also matched the
``/{server_name}/mcp`` form, but the downstream parser
``_get_mcp_servers_in_path`` only handles ``/mcp/...`` — and
``dynamic_mcp_route`` in ``proxy_server`` rewrites ``/{name}/mcp``
to ``/mcp/{name}`` on the scope before the MCP handler runs. Parsing
the un-rewritten form on the auth side was therefore unreachable in
production, and contradicted the docstring's claim of mirroring the
downstream parser — exactly the kind of mismatch that risks a future
header/path TOCTOU if any new entry point skips the rewrite.
Drop the branch; the canonical ``/mcp/...`` path matches both
parsers. Update the regression test to assert the new behavior.
https://claude.ai/code/session_01SjyPmwfmrq8fveFgw9iHW9
* Fix MCP path auth target resolution
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): require auth for refresh_token grants on delegate-auth servers
`_mcp_oauth_user_api_key_auth` gates the unauthenticated PKCE flow for
``delegate_auth_to_upstream`` servers, but the bypass applied to BOTH
``/authorize`` and ``/token`` regardless of grant type. ``mcp_token``
accepts ``grant_type=refresh_token`` as well as ``authorization_code``,
and ``exchange_token_with_server`` attaches the server's stored
``client_secret`` to whatever is forwarded upstream. An unauthenticated
caller holding a refresh token issued to that OAuth client could mint
fresh upstream access tokens through LiteLLM.
Limit the anonymous bypass on ``/token`` to ``grant_type=authorization_code``
(the only grant PKCE actually protects via ``code_verifier``); fall
through to normal LiteLLM auth for ``refresh_token`` and any other grant.
``/authorize`` continues to allow anonymous PKCE redirects.
https://claude.ai/code/session_01SjyPmwfmrq8fveFgw9iHW9
* fix(ui): clear delegate_auth_to_upstream when switching off oauth2
The ``delegate_auth_to_upstream`` form field is rendered inside an
``isOAuth2 && (...)`` conditional, so the Form.Item unmounts when the
user changes ``auth_type`` away from ``oauth2``. The follow-up
``form.setFieldValue("delegate_auth_to_upstream", false)`` runs after
the field has already deregistered, so ``onFinish`` receives
``undefined`` and the fallback ``?? mcpServer.delegate_auth_to_upstream``
preserved the old ``true``. The flag then persisted in the database for
a non-oauth2 server and silently re-activated if ``auth_type`` was later
switched back to ``oauth2``.
In the edit payload, force the flag to ``false`` whenever
``auth_type !== oauth2``; only trust the form value (and the existing
DB fallback) when the server is actually oauth2. Backend defense-in-depth
already ignores the flag for non-oauth2 servers, but the DB state should
stay clean too.
https://claude.ai/code/session_01SjyPmwfmrq8fveFgw9iHW9
* Fix MCP delegate auth reset on edit
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: Claude <claude@anthropic.com>
* fix(cost): align vertex_ai/gemini-embedding-2-preview with Vertex multimodal pricing
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(cost): align vertex_ai/gemini-embedding-2 GA source URL with preview
Per Greptile review on #27848: GA entry referenced ai.google.dev while
the preview entry was updated to the canonical Vertex AI pricing page.
Both share identical pricing values; sync the source URL for consistency.
https://claude.ai/code/session_01W8jRwstnmduadGw8Z8egxe
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Claude <noreply@anthropic.com>
* fix(mcp): surface upstream 401 for token-forwarding MCP servers
For MCP servers configured with extra_headers: [Authorization], the gateway
forwards the client token directly to the upstream. When that token is rejected
(expired or invalid) the upstream returns 401, but the MCP SDK starts the SSE
stream with 200 OK before calling handlers, so the 401 can't be returned
mid-stream.
Fix: add a pre-flight httpx probe in handle_streamable_http_mcp — before the
SDK opens the session — so the gateway can still return HTTP 401 with
WWW-Authenticate: Bearer authorization_uri=<gateway-discovery-url> when the
upstream rejects the token. The probe fails-open (returns 200) on network
errors so a transient hiccup does not block valid requests.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): parallelize pre-flight auth probes and use HEAD to avoid side effects
- Extract forwarded_auth outside the pass-through server loop (was called N times for the same scope value)
- Gather all upstream auth probes concurrently with asyncio.gather instead of sequentially; eliminates N×5 s worst-case latency
- Switch probe from POST+initialize JSON-RPC body to HEAD request; HEAD carries the Authorization header so the upstream rejects invalid tokens with 401 but never allocates a session or writes an audit entry
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): use get_async_httpx_client in _probe_upstream_auth
Replaces bare httpx.AsyncClient with the project-standard
get_async_httpx_client(httpxSpecialProvider.MCP) to satisfy the
ensure_async_clients_test code coverage check and avoid the +500 ms
per-request overhead of creating a new client on every probe call.
Co-authored-by: Cursor <cursoragent@cursor.com>
* refactor(mcp): extract pre-flight probe into _check_passthrough_upstream_auth
Moves the parallel upstream auth probe logic out of
handle_streamable_http_mcp into a dedicated helper to satisfy
Ruff PLR0915 (Too many statements > 50).
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): gate pre-flight probes on authorized server set to prevent bypass
_check_passthrough_upstream_auth was resolving user-supplied server names
directly before authorization ran, letting any permitted LiteLLM key
trigger an upstream HEAD probe to a server it was not allowed to use.
Changes:
- Call _get_allowed_mcp_servers inside the helper so only servers the
caller's key is authorized for are probed.
- Move the call site to after toolset scoping so the auth context is
fully resolved before the probe list is built.
- Thread user_api_key_auth into the helper signature (replaces the raw
mcp_servers name list).
Co-authored-by: Cursor <cursoragent@cursor.com>
* Add async HTTP HEAD support
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): use Scope type annotation in _get_forwarded_auth_from_scope
Co-authored-by: Cursor <cursoragent@cursor.com>
* Fix MCP upstream auth probe method
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* Remove unused AsyncHTTPHandler head method
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): exclude has_client_credentials servers from pre-flight auth probe
_prepare_mcp_server_headers skips caller Authorization when the server
uses OAuth client-credentials (M2M), but the pre-flight probe was still
selecting those servers and forwarding the caller's raw token in the HEAD
request. Exclude servers with has_client_credentials from the probe list
to match the actual downstream header-preparation logic.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): propagate upstream 403 as 403, not 401 with WWW-Authenticate
Per RFC 9110, 401 means "go get new credentials." Mapping an upstream 403
to a gateway 401 causes OAuth clients to restart the authorization flow,
obtain a fresh token with identical scopes, hit 403 again, and loop
indefinitely.
401 from upstream → gateway 401 + WWW-Authenticate (re-authorize)
403 from upstream → gateway 403 (no WWW-Authenticate hint)
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): skip auth probe when Authorization may be the LiteLLM proxy key
The pre-flight upstream probe must not forward the caller's Authorization
header when it could itself be the LiteLLM proxy API key. Restrict the
probe to requests that supply x-litellm-api-key explicitly — only then is
the Authorization header unambiguously the upstream OAuth token the
caller wants forwarded.
* Fix MCP ASGI HTTPException propagation
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* fix(mcp): use public AsyncHTTPHandler.post() in auth probe
Use AsyncHTTPHandler.post() and catch httpx.HTTPStatusError explicitly so
the 401/403 we want to surface is not silently swallowed by the broad
fail-open except Exception block. Avoids reaching into the handler's
private client attribute, which would silently regress to fail-open if
AsyncHTTPHandler is ever refactored.
* Fix MCP auth probe tests
Co-authored-by: Yassin Kortam <yassin@berri.ai>
* test(mcp): add coverage for httpx.HTTPStatusError path in auth probe
AsyncHTTPHandler.post() calls raise_for_status() internally, so a real
upstream 401/403 lands as httpx.HTTPStatusError. Add a test that exercises
that specific exception path so a regression that swallows the error in
the broad fail-open except Exception would be caught.
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Co-authored-by: claude-bot <claude-bot@anthropic.com>
* fix(bedrock-converse): drop blank-text fallback for empty thinking blocks
Claude Code with extended thinking replays prior assistant turns that
include an empty thinking block (`thinking=""`, `signature=""`) alongside
tool_use blocks. The unsigned-reasoning fallback in
`add_thinking_blocks_to_assistant_content` was emitting
`BedrockContentBlock(text="")`, which Bedrock Converse rejects with:
"The text field in the ContentBlock object at messages.X.content.0
is blank."
Guard the fallback with a strip() check, matching the existing
empty-text guards elsewhere in `_bedrock_converse_messages_pt`.
* style: remove unneeded comments
* feat(proxy): skip disable_background_health_check models on GET /health when flag set
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix comment
* fix greptile comments
* Fix health check fallback kwargs
* Format health endpoint
* Harden direct health check kwargs compatibility for monkeypatched perform_health_check
Replace substring-based TypeError detection with unexpected-keyword checks
and a short retry chain (full kwargs, instrumentation only, filter only,
minimal) so partial stubs work regardless of which optional kwarg fails first.
Add proxy unit tests for legacy three-arg stubs and single-kwarg variants.
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix black
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: Sameer Kankute <Sameerlite@users.noreply.github.com>
* fix(gemini): normalize response_schema on native generateContent
The /v1beta/models/{model}:generateContent passthrough forwarded
generationConfig.response_schema verbatim, so schemas containing $defs,
$ref, anyOf-with-null, default, or title were rejected by Gemini even
though /chat/completions already handles them.
GoogleGenAIConfig.transform_generate_content_request now calls a new
_normalize_response_schema helper that mirrors the chat/completions
path: Gemini 2.0+ models get the schema promoted to responseJsonSchema
via _build_json_schema (preserving $defs/$ref natively), older models
keep responseSchema but the schema is flattened with
_build_vertex_schema. VertexAIGoogleGenAIConfig (which overrides the
transform entirely) calls the same helper before building the request.
* fix(gemini): preserve caller-supplied responseJsonSchema when responseSchema co-present
Previously, when both responseJsonSchema and responseSchema were present
on Gemini 2.0+, _normalize_response_schema processed responseJsonSchema
first (no-op normalization) then unconditionally promoted responseSchema
to responseJsonSchema, clobbering the caller-supplied value.
Now skip the promotion (and drop the redundant responseSchema) when the
caller already supplied responseJsonSchema.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* chore: strip restating comments from response-schema normalize
Drop the docstring on _normalize_response_schema and the two inline
comments that just restated what the surrounding code/asserts already
say. Function name + variable names carry the intent; PR description
covers the why-it-exists context.
* perf(gemini): drop redundant deepcopy on responseJsonSchema normalize
_build_json_schema is a no-op (returns its argument unchanged), so the
deepcopy + round-trip on the responseJsonSchema branch allocated a full
schema copy on every request with no observable effect. Forward the
caller's value as-is, and just move the popped responseSchema value when
promoting on Gemini 2.0+.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* style: remove unneeded comment
* fix(gemini): drop unsupported responseJsonSchema for older models
* test(gemini): add parity test between native and chat schema normalization
Per @Sameerlite review: lock the two Gemini schema-normalization paths
together. If either GoogleGenAIConfig._normalize_response_schema (native
generateContent) or VertexGeminiConfig.apply_response_schema_transformation
(/chat/completions) drifts, the parity test fails — forcing both to be
updated together.
* fix(google_genai): preserve key naming convention in _normalize_response_schema
When the input schema key is snake_case (response_schema), the promoted
JSON schema key should also be snake_case (response_json_schema) instead
of mixing in camelCase (responseJsonSchema). This matters for the Vertex
AI google_genai path which converts all keys to snake_case before
calling _normalize_response_schema.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
OpenAI returns 'The model dall-e-3 does not exist' for the test account,
breaking test_openai_img_gen_health_check and test_image_generation.
Switch to gpt-image-1, matching the existing TestOpenAIGPTImage1 pattern.
LazyFeatureMiddleware compared the raw scope path against registered
prefixes (e.g. /policies), so requests under a server root path like
/api/v1/policies/... never matched, the feature never loaded, and the
endpoint returned 404. Strip the configured root path before matching,
normalizing trailing slashes and enforcing a component boundary so
/api does not falsely match /apiv2.
1. Missing litellm_request child span when proxy parent in metadata:
_get_span_context now returns (ctx, None) for the metadata-injected
proxy parent so the primary span is always emitted as a child of ctx.
Proxy span lifecycle managed by new _end_proxy_span_from_kwargs.
2. open_telemetry_logger overwrite by later handlers:
_init_otel_logger_on_litellm_proxy now uses first-registered-wins —
only assigns proxy_server.open_telemetry_logger when currently None.
3. Duplicate litellm_request success spans in streaming paths:
Added _mark_success_span_once with per-handler dedupe key stored in
kwargs metadata, suppressing the second span when both sync and async
success callbacks fire for the same request.
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
`apply_client_tag_policy_pre_auth` overwrote string-typed metadata
with `{}` before merging header tags, dropping any tags inside. A
caller could send `metadata='{"tags":["over-budget"]}'` plus
`x-litellm-tags: within-budget` and bypass `_tag_max_budget_check`
on the body tag. Parse the string via `safe_json_loads` first so
existing tags survive the merge.
Also drop the empty `tests/test_litellm/proxy/credential_endpoints/`
directory — the cascade-rename tests it held imported a function
that was never implemented (out of scope for this PR).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
``model_dump(exclude_unset=True)`` in ``prepare_key_update_data``
includes any field the caller explicitly set, even when the value is
``None``. The previous guard short-circuited on ``getattr(data,
'user_id', None) is None``, which conflated "field omitted" (safe)
with "field explicitly set to null" (writes NULL to the token row,
detaching the key from its user and bypassing user-row role
checks).
Switch the omitted-vs-set distinction to ``data.model_fields_set``;
treat explicit-null and explicit-empty-string identically as a
removal attempt, both 403-rejected for non-admin callers.
Parametrized regression adds ``explicit_null_blocked`` alongside the
existing ``rebind_blocked`` / ``empty_blocked`` / ``same_user_id_allowed``
cases.
Removes the allow_client_tags metadata check from apply_client_tag_policy_pre_auth so
x-litellm-tags headers are always merged into request metadata, matching the post-auth
behavior in add_litellm_data_to_request. Updates pre-call tests accordingly and adds a
new test suite covering cascading credential renames into model rows.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Previous wording read "User=<new_owner> is not allowed to update the
key to belong to user=<current_owner>" — easy to misread as "caller
wants to keep the key on its current owner". Reframe as
"Non-admin caller is not allowed to rebind the key from
user=<existing> to user=<incoming>" so the direction of the failed
operation is unambiguous.
Same shape preserved (HTTPException 403); only the ``detail`` string
changes. Regression test substring updated.
A non-admin caller could rebind their own key's ``user_id`` via
``/key/regenerate``. ``_execute_virtual_key_regeneration`` had org/team
guards but no ``user_id`` guard, and ``prepare_key_update_data`` did not
strip the field — it survived ``model_dump(exclude_unset=True)`` into
the Prisma update. On the next request,
``_return_user_api_key_auth_obj`` resolved the rebound ``user_id``
against ``litellm_usertable`` and returned ``PROXY_ADMIN`` whenever
the target row's ``user_role`` was admin (e.g. the default
``user_id="default_user_id"`` created on first password-UI login).
``/key/update`` had the equivalent guard inline at
``_validate_update_key_data``; extract it to a shared helper
``_validate_caller_can_change_key_ownership`` and call from both
``/key/update`` and ``_execute_virtual_key_regeneration``. Future
regenerate-style endpoints inherit the guard for free.
Also tighten the premium gate that allowed the master-key rotation
branch to skip the enterprise check. The previous predicate was
``data.new_master_key is not None`` — a field-presence test, not an
identity check. Any non-premium caller could send any value in that
field and the premium check would no-op. Verify the caller actually
holds the master key via ``_is_master_key`` before allowing the
non-premium path.
Tests:
- ``test_regenerate_user_id_rebind_guard`` — parametrized table over
cross-user rebind (blocked), empty-string removal (blocked), and
same-user no-op rebind (allowed).
- ``test_regenerate_premium_gate_requires_actual_master_key`` /
``test_regenerate_premium_gate_allows_actual_master_key_holder`` —
ensure the premium check requires the caller actually present the
master key, and that legitimate master-key rotation still works.
* fix(proxy): resolve cache handling issues in _lookup_deprecated_key
- Updated the in-memory cache for deprecated key lookups to store a 3-tuple (active_token_id, cache_expires_at_ts, revoke_at_ts) instead of a 2-tuple, ensuring proper unpacking and backward compatibility.
- Removed duplicate cache reads and added logic to handle legacy cache entries gracefully.
- Enhanced unit tests to cover scenarios for cache hits, DB misses, and respect for revoke_at timestamps, ensuring robust handling of the grace-period key-rotation feature.
* refactor(proxy): streamline cache handling in _lookup_deprecated_key
- Simplified the cache retrieval logic by directly unpacking the 3-tuple cache entries, removing the need for backward compatibility checks for 2-tuple entries.
- Updated unit tests to ensure that pre-warmed 3-tuple cache entries are served correctly without unnecessary database lookups.
* chore(ci): add new unit test for deprecated key grace period
- Included `test_deprecated_key_grace_period.py` in the CI workflow to enhance coverage for deprecated key handling scenarios.
* fix(proxy): remove unnecessary check for revoke_at in _lookup_deprecated_key
- Eliminated the redundant check for None on revoke_at, streamlining the logic for handling deprecated keys in the cache. This change enhances the efficiency of the key lookup process.
* test(proxy): add end-to-end tests for deprecated key lookup behavior
- Introduced a new test class `TestDeprecatedKeyLookupDbE2E` to validate the behavior of deprecated key lookups against a real Prisma-backed database.
- The test ensures that old key hashes resolve correctly and that repeated lookups utilize the in-memory cache without errors.
- Cleaned up the `_lookup_deprecated_key` function by removing an unnecessary check for `revoke_at`, enhancing the efficiency of the key lookup process.
Caller-supplied tags (`x-litellm-tags` header, body `tags`, `metadata.tags`)
were silently dropped unless the key/team had
`metadata.allow_client_tags: true` set. Restore the documented behavior:
tags from the request always flow into `metadata.tags` and union with any
admin-configured static tags from key/team/project metadata.
Removes the `allow_client_tags` opt-in flag from the pre-call pipeline.
The flag was only ever read here; it has no schema or endpoint footprint,
so leftover values in existing key metadata are inert.
Test cleanup mirrors the simplification: drop the three tests that
verified the strip-when-not-opted-in path, drop the `allow_client_tags`
fixture lines from the merge/union tests.
Second wave of failures from the 2026-05-12 DALL-E shutdown:
- tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditDallE2
and tests/image_gen_tests/test_image_generation.py::TestOpenAIDalle3
are explicitly named for the deprecated models and can't pass; remove.
gpt-image-1 coverage already exists in sibling classes.
- tests/local_testing/test_router.py image gen tests use dall-e-3 only
as a routing example; swap to gpt-image-1.
- tests/local_testing/test_custom_callback_input.py image_generation
success/failure paths swapped to gpt-image-1.
DALL-E 2 and DALL-E 3 were removed from the OpenAI API on 2026-05-12,
causing e2e image-generation tests to fail with "model does not exist".
Swap all live-API DALL-E references in proxy-backed tests to gpt-image-1
and update the dall-e-2 alias in proxy_server_config.yaml to point at
openai/gpt-image-1 (preserves any historical dall-e-2 callers).
* chore: reject bare str at file-input sinks to prevent local-file read (#27667)
Squash-merged by litellm-agent from stuxf's PR.
* fix: use os.PathLike in ocr sink and check truthy reasoningSummary for bridge
- ocr/main.py: widen Path check to os.PathLike for consistency with other sinks
- main.py: bridge condition checks truthiness of reasoning_summary, not just None
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix: remove unused pathlib.Path import in ocr/main.py
---------
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Second wave of failures from the 2026-05-12 DALL-E shutdown:
- tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditDallE2
and tests/image_gen_tests/test_image_generation.py::TestOpenAIDalle3
are explicitly named for the deprecated models and can't pass; remove.
gpt-image-1 coverage already exists in sibling classes.
- tests/local_testing/test_router.py image gen tests use dall-e-3 only
as a routing example; swap to gpt-image-1.
- tests/local_testing/test_custom_callback_input.py image_generation
success/failure paths swapped to gpt-image-1.
DALL-E 2 and DALL-E 3 were removed from the OpenAI API on 2026-05-12,
causing e2e image-generation tests to fail with "model does not exist".
Swap all live-API DALL-E references in proxy-backed tests to gpt-image-1
and update the dall-e-2 alias in proxy_server_config.yaml to point at
openai/gpt-image-1 (preserves any historical dall-e-2 callers).
Caller-supplied tags (`x-litellm-tags` header, body `tags`, `metadata.tags`)
were silently dropped unless the key/team had
`metadata.allow_client_tags: true` set. Restore the documented behavior:
tags from the request always flow into `metadata.tags` and union with any
admin-configured static tags from key/team/project metadata.
Removes the `allow_client_tags` opt-in flag from the pre-call pipeline.
The flag was only ever read here; it has no schema or endpoint footprint,
so leftover values in existing key metadata are inert.
Test cleanup mirrors the simplification: drop the three tests that
verified the strip-when-not-opted-in path, drop the `allow_client_tags`
fixture lines from the merge/union tests.
The enterprise package is installed as `litellm_enterprise` (per
enterprise/pyproject.toml), but several tests imported it as
`enterprise.litellm_enterprise.*` — a path that only resolves
because the repo root happens to sit on sys.path, letting Python's
implicit namespace package machinery discover `enterprise/` as a
directory.
This breaks any test runner that relocates source (e.g. the
mutation-testing workflow, which copies tests under `mutants/`) and
also caused two `patch()` strings to target a module path that does
not match what production code imports — meaning those mocks were
never actually patching the production module's attribute.
Replace `from enterprise.litellm_enterprise.` with the canonical
`from litellm_enterprise.` across 6 test files, and fix two
`patch()` target strings (and one `sys.modules` patch key in the
SSO test) to match.
* feat(ui): search teams by team ID alongside name
The Teams page search box only matched team_alias, so pasting a team UUID
returned zero results. Detect when the input is a full UUID and route it
to the team_id filter instead; otherwise keep the existing alias substring
search. Placeholder now reads "Search teams by name or ID...".
Resolves LIT-2648
* refactor: search teams via backend OR clause, drop client-side UUID detection
Adds a `search` query param to /v2/team/list that ORs across team_id
(exact) and team_alias (case-insensitive contains), so the search box
sends one param regardless of input format. Removes the isLikelyTeamId
helper and the client-side branching it fed.
* fix: invalidate cached tag object on tag budget reset (#27481) (#27572)
Squash-merged by litellm-agent from oss-agent-shin's PR.
* chore(mcp): tighten stdio server registration paths (#27570)
Squash-merged by litellm-agent from stuxf's PR.
* fix(proxy): clear MCP OpenAPI mappings on server eviction; widen budget cache invalidation
Evict OpenAPI tools from global_mcp_tool_registry and strip tool_name_to_mcp_server_name_mapping entries when a server leaves the runtime registry (remove_server and approval-status eviction). Invalidate user_api_key_cache for keys, orgs, and team members on budget-tier spend resets alongside tags.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): align update_server eviction with remove_server name fallback
Document budget-reset test assertion flip (cross-pod cache staleness).
Greptile: eviction now pops by server_id then server_name like remove_server;
test docstring explains assert_not_awaited -> assert_any_await change.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Fix org budget cache invalidation
---------
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Greptile flagged that the strict isinstance(dict) guard in
_encryption_boundary_key would silently return None for any non-dict input,
including a LiteLLM_Params Pydantic instance, which exposes a custom .get()
method and is intended to be used dict-style in some router paths. If such
an instance ever flowed into healthy_deployments, the guard would drop every
candidate from boundary matching and fall through to the full deployment
pool, i.e. trigger the exact invalid_encrypted_content failure this check
exists to prevent.
Loosen the guard to accept any object exposing a callable .get(): plain
dicts (the common case) and LiteLLM_Params-style Pydantic instances. The
function still returns None for non-dict-like values (None, lists, strings,
ints, bare objects).
Adds regression tests covering:
- LiteLLM_Params Pydantic instance resolves to the same boundary tuple as
an equivalent plain dict
- non-dict-like values and dicts missing required fields still return None
When a Responses API follow-up switches model_name (e.g. gpt-5.3-codex ->
gpt-5.4, or to a LiteLLM-side alias of the same Azure deployment), the
router has already filtered healthy_deployments to the new group, so the
originating model_id is no longer present. The encrypted_content_affinity
check would log "decoded deployment not found" and fall back to the full
deployment pool, where simple-shuffle could land on a different Azure
resource and trip a 400 invalid_encrypted_content.
Fall back to pinning by the originating deployment's encryption boundary
(api_base + api_key) when the model_id miss is across model groups. The
encrypted_content travels with the Azure resource, not the model_name,
so any deployment on the same resource accepts it.
LIT-2531
* fix(tests): drop deprecated OpenAI-Beta realtime header
OpenAI deprecated the 'OpenAI-Beta: realtime=v1' header; the live
service now returns code 4000 invalid_beta with
"Unknown beta requested: 'realtime'.". Two integration tests in
tests/llm_translation/realtime/test_realtime_guardrails_openai.py
hardcoded the header and started failing across all PRs.
Library code is unaffected: the OpenAI realtime handler only
forwards 'OpenAI-Beta: realtime=v1' upstream when the proxy *client*
sends it (litellm/llms/openai/realtime/handler.py). Default proxy
behavior uses the GA protocol.
Connect to OpenAI without the deprecated header, and accept the GA
event name 'response.output_audio_transcript.delta' alongside the
beta-protocol name 'response.audio_transcript.delta' for the
transcript-delta assertion.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(logging): post_call tolerates non-JSON-serializable values
post_call() did json.dumps(original_response) without default=str, so
any provider passing a dict containing datetime/Decimal/etc. would
raise TypeError. Bedrock batch retrieval hits this with
get_model_invocation_job() responses that include datetime fields
(submitTime, lastModifiedTime, endTime), failing
tests/batches_tests/test_bedrock_files_and_batches.py::test_async_file_and_batch
across all PRs.
Pass default=str so non-serializable values fall back to str().
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(tests): mock boto3 in bedrock retrieve batch test
The test patched AsyncHTTPHandler.get, but the bedrock retrieve
handler uses boto3.client('bedrock').get_model_invocation_job
directly, so the real AWS call was being made on every run, failing
with AccessDeniedException because the hardcoded test ARN belongs to
a different AWS account.
- Mock boto3.client and BedrockBatchesConfig.get_credentials so the
test never touches AWS.
- Use status=Completed in the mock response so output_file_id is
populated (the handler intentionally leaves it None for
non-completed jobs).
- Assert the predicted per-job output object URI (matches what the
handler actually returns) instead of the bare output prefix.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* docs(tests): include GA event name in guardrail-block test docstring
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* feat(bedrock): support retrieve for model-invocation-job batch ARNs
`bedrock.retrieve_batch` previously only handled `:async-invoke/` ARNs
(Twelve Labs Marengo embeddings). The `:model-invocation-job/` ARNs
returned by `CreateModelInvocationJob` (the bulk batch inference API
behind `bedrock.create_batch`) fell through and returned a misleading
data-plane error, leaving created jobs unretrievable through the
LiteLLM batches API.
The two ARN families live on different AWS service endpoints
(`bedrock-runtime` data plane vs `bedrock` control plane), so they need
distinct handlers. This adds:
* `BedrockBatchesHandler._handle_model_invocation_job_status` — calls
the control plane via boto3 (`bedrock:GetModelInvocationJob`),
reusing `BaseAWSLLM.get_credentials` for credential resolution so
model_list / env / role-assumption configs continue to apply. The
response is reshaped into a `LiteLLMBatch` with the same status
mapping `transform_create_batch_response` already uses.
* Output-file-URI prediction. Bedrock surfaces the user-supplied
`s3OutputDataConfig.s3Uri` *prefix* in `GetModelInvocationJob`, but
results actually land at `<prefix>/<job-id>/<basename(input)>.out`.
We compute that single-file URI client-side and surface it as
`output_file_id`, so OpenAI-style `client.files.content(...)` works
without an extra `ListObjectsV2` round-trip. The bare prefix stays
in metadata for callers that want the manifest.
* Dispatch in `litellm/batches/main.py` for the new ARN family,
alongside the existing async-invoke branch.
* Unit tests covering ARN parsing, output-URI prediction (incl. edge
cases), the full status mapping, region resolution precedence, and
failure-message propagation.
Note: `request_counts` is intentionally `(0, 0, 0)` —
`GetModelInvocationJob` does not report per-record counts; getting
accurate numbers requires parsing `manifest.json.out` from the output
S3 prefix, which is left to callers.
Made-with: Cursor
* fix(bedrock): address PR feedback on model-invocation-job retrieve
Addresses Greptile P2 findings on #26834:
1. Use the bare job id (not the full ARN) when constructing the
`api_base` URL for `pre_call` logging. Passing the full ARN double-
counts the `model-invocation-job/` segment and embeds colons in the
path, producing misleading log lines.
2. Drop the `or output_prefix` fallback when `_predict_output_file_uri`
returns None. A bare prefix is not a downloadable object and surfacing
it as `output_file_id` re-creates the very NoSuchKey bug this handler
exists to fix. The bare prefix is still preserved in
`metadata["output_s3_uri"]` for callers that want to do their own S3
listing or read `manifest.json.out`.
`metadata["output_file_uri"]` uses "" rather than None to satisfy the
OpenAI Batch metadata schema (`dict[str, str]`); callers should branch
on the typed `output_file_id` field instead.
Also expands test coverage on the new code path:
- new "stay None" regression test for the prediction-fail case
- pre_call/post_call logging hook assertions (incl. the bare-id URL)
- explicit cancelled_at / expired_at coverage
- _to_epoch type-handling matrix and the boto3 ImportError branch
- defensive _extract_region_from_bedrock_arn exception path
- empty-basename case for _predict_output_file_uri
Patch coverage on the changed lines is now 100% (the only remaining
uncovered lines in the file belong to the pre-existing
`_handle_async_invoke_status` method, which this PR does not touch).
Made-with: Cursor
* test(bedrock): cover retrieve_batch dispatch for both ARN families
Codecov flagged 8 uncovered lines on `litellm/batches/main.py` after
this PR refactored the Bedrock dispatch into a single guard with two
sub-branches (`async-invoke` + `model-invocation-job`). Existing tests
exercised the handlers directly but not the dispatch in `main.py`.
Adds `tests/test_litellm/batches/test_retrieve_batch_bedrock_dispatch.py`
with 6 mocked tests that exercise `litellm.retrieve_batch` end-to-end
for the dispatch logic:
- async-invoke ARN routes to `_handle_async_invoke_status`
- async-invoke ARN with no region falls back to "us-east-1" (preserves
prior behavior on this branch)
- model-invocation-job ARN routes to the new
`_handle_model_invocation_job_status` handler
- model-invocation-job ARN with no region forwards None (so the new
handler can sniff region from the ARN itself, rather than getting
silently routed to us-east-1)
- unrelated bedrock ARN family falls through to the generic
provider-config retrieve path (neither special handler invoked)
- non-bedrock batch ids skip the bedrock dispatch entirely
Both handlers are mocked at the import site so the tests don't hit
AWS — the focus here is purely the new dispatch logic in main.py.
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(bedrock): move retrieve_batch dispatch test to tests/test_litellm/
The dispatch test landed under `tests/test_litellm/batches/`, a new
directory that no upstream `test-unit-*.yml` workflow's `test-path`
allow-list includes. As a result, the test was never executed in CI
and codecov reported `litellm/batches/main.py` patch coverage at
11.11% (8 lines uncovered) — the lines belonging to this PR's
dispatch refactor itself.
Move the file up one level so it matches the
`tests/test_litellm/test_*.py` glob that `test-unit-misc.yml`
already runs, and adjust `sys.path.insert` for the new depth.
The companion handler tests under
`tests/test_litellm/llms/bedrock/batches/test_handler.py` are
unaffected — they're picked up by the `llms` directory in
`test-unit-llm-providers.yml`.
Made-with: Cursor
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Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(responses): map chat tool_choice to Responses API when bridging from completions
OpenAI /v1/responses rejects tool_choice.function. Normalize forced-function
choice from chat shape to {type, name} in LiteLLMResponsesTransformationHandler.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(responses): strip tool_choice.function when top-level name is set
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Co-authored-by: Cursor <cursoragent@cursor.com>
