The deployment hook now converts stream=True→False in wrapper_async's
scope so the streaming early-return path is skipped and logging executes.
logging_obj.stream is synced after the hook, and the original stream
intent is recovered for the short-circuit path.
Made-with: Cursor
Adopt a React Query mutation for policy attachment deletion and add a pending-state test on the policies index panel. This removes local delete-loading state and keeps modal loading tied to mutation status.
Made-with: Cursor
Replace Tremor components in the regenerate key modal with Ant Design
equivalents and move the component to a new PascalCase file. The form
layout now uses Row/Col to place Max Budget, TPM Limit, and RPM Limit
on one row and Expire Key with Grace Period on another, reducing the
vertical footprint. The success view shows an Alert banner, the key
alias as secondary context, and the regenerated key in a monospace
block with an inline primary Copy button.
Also adds unit tests for the new component and updates the existing
Playwright spec to match the new banner and button text.
enable_tag_filtering: false (the default) passed the hasValues guard,
causing every team save to send router_settings even for teams that
never had them configured. This could silently overwrite backend-set
values. Now exclude false and empty arrays from the check.
Remove the silent try/catch from setSecureItem so OAuth hooks can
surface actionable "enable storage" guidance instead of a cryptic
"state lost" error after the round-trip. Add a local try/catch in
ChatUI where the storage write is non-critical.
Normalize JSON Schema type custom to object for Bedrock invoke and
_bedrock_tools_pt, ensure stable names for tools without name, and
avoid KeyError in the Anthropic messages adapter when translating
tools to OpenAI format for bedrock/converse.
Made-with: Cursor
Remove the onChange/value feedback loop between TeamInfo and
RouterSettingsAccordion. The parent passes initial value once and reads
current values at save time via ref.getValue(). This eliminates the
circular data flow that caused stale state and fallback tab resets.
When a fallback model was selected, the onChange effect fired, parent
re-rendered with new value prop, and the useEffect re-initialized the
groups with new IDs from fallbacksToGroups. This caused the active
fallback group tab to reset to Group 1. Now internal updates always
skip re-initialization regardless of value key changes.
The uncontrolled TabGroup reset to the first tab whenever the component
re-rendered due to onChange state updates. Using controlled index/onIndexChange
keeps the user on the current tab during fallback selection.
When a user clears a numeric field in the RouterSettingsAccordion, the empty
input should result in null, not fall through to the previous value from state.
The RouterSettingsAccordion uses uncontrolled DOM inputs for numeric fields.
The onChange effect only fires when formValue or fallbacks change, not when
the user types into uncontrolled inputs. Using the ref's getValue() method
at save time ensures we read fresh values from the DOM.
Add RouterSettingsAccordion to the team edit form and a read-only
display of router settings (routing strategy, retries, fallbacks,
cooldown, timeout, tag filtering) in the Settings tab.
Add Baseten Model API pricing entries for Nemotron, GLM, Kimi, GPT OSS, and DeepSeek models with validated model slugs. Include a focused regression test to assert provider and per-token pricing values.
Made-with: Cursor
* fix(vertex_ai): support pluggable (executable) credential_source for WIF auth (#24700)
The WIF credential dispatch in load_auth() only handled identity_pool and
aws credential types. When credential_source.executable was present (used
for Azure Managed Identity via Workload Identity Federation), it fell
through to identity_pool.Credentials which rejected it with MalformedError.
Add dispatch to google.auth.pluggable.Credentials for executable-type
credential sources, following the same pattern as the existing identity_pool
and aws helpers.
Fixes authentication for Azure Container Apps → GCP Vertex AI via WIF
with executable credential sources.
* feat(logging): add component and logger fields to JSON logs for 3rd p… (#24447)
* feat(logging): add component and logger fields to JSON logs for 3rd party filtering
* Let user-supplied extra fields win over auto-generated component/logger, tighten test assertions
* Feat - Add organization into the metrics metadata for org_id & org_alias (#24440)
* Add org_id and org_alias label names to Prometheus metric definitions
* Add user_api_key_org_alias to StandardLoggingUserAPIKeyMetadata
* Populate user_api_key_org_alias in pre-call metadata
* Pass org_id and org_alias into per-request Prometheus metric labels
* Add test for org labels on per-request Prometheus metrics
* chore: resolve test mockdata
* Address review: populate org_alias from DB view, add feature flag, use .get() for org metadata
* Add org labels to failure path and verify flag behavior in test
* Fix test: build flag-off enum_values without org fields
* Gate org labels behind feature flag in get_labels() instead of static metric lists
* Scope org label injection to metrics that carry team context, remove orphaned budget label defs, add test teardown
* Use explicit metric allowlist for org label injection instead of team heuristic
* Fix duplicate org label guard, move _org_label_metrics to class constant
* Reset custom_prometheus_metadata_labels after duplicate label assertion
* fix: emit org labels by default, remove flag, fix missing org_alias in all metadata paths
* fix: emit org labels by default, no opt-in flag required
* fix: write org_alias to metadata unconditionally in proxy_server.py
* fix: 429s from batch creation being converted to 500 (#24703)
* add us gov models (#24660)
* add us gov models
* added max tokens
* Litellm dev 04 02 2026 p1 (#25052)
* fix: replace hardcoded url
* fix: Anthropic web search cost not tracked for Chat Completions
The ModelResponse branch in response_object_includes_web_search_call()
only checked url_citation annotations and prompt_tokens_details, missing
Anthropic's server_tool_use.web_search_requests field. This caused
_handle_web_search_cost() to never fire for Anthropic Claude models.
Also routes vertex_ai/claude-* models to the Anthropic cost calculator
instead of the Gemini one, since Claude on Vertex uses the same
server_tool_use billing structure as the direct Anthropic API.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix(anthropic): pass logging_obj to client.post for litellm_overhead_time_ms (#24071)
When LITELLM_DETAILED_TIMING=true, litellm_overhead_time_ms was null for
Anthropic because the handler did not pass logging_obj to client.post(),
so track_llm_api_timing could not set llm_api_duration_ms. Pass
logging_obj=logging_obj at all four post() call sites (make_call,
make_sync_call, acompletion, completion). Add test to ensure make_call
passes logging_obj to client.post.
Made-with: Cursor
* sap - add additional parameters for grounding
- additional parameter for grounding added for the sap provider
* sap - fix models
* (sap) add filtering, masking, translation SAP GEN AI Hub modules
* (sap) add tests and docs for new SAP modules
* (sap) add support of multiple modules config
* (sap) code refactoring
* (sap) rename file
* test(): add safeguard tests
* (sap) update tests
* (sap) update docs, solve merge conflict in transformation.py
* (sap) linter fix
* (sap) Align embedding request transformation with current API
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) mock commit
* (sap) run black formater
* (sap) add literals to models, add negative tests, fix test for tool transformation
* (sap) fix formating
* (sap) fix models
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) commit for rerun bot review
* (sap) minor improve
* (sap) fix after bot review
* (sap) lint fix
* docs(sap): update documentation
* fix(sap): change creds priority
* fix(sap): change creds priority
* fix(sap): fix sap creds unit test
* fix(sap): linter fix
* fix(sap): linter fix
* linter fix
* (sap) update logic of fetching creds, add additional tests
* (sap) clean up code
* (sap) fix after review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) add a possibility to put the service key by both variants
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) update test
* (sap) update service key resolve function
* (sap) run black formater
* (sap) fix validate credentials, add negative tests for credential fetching
* (sap) fix validate credentials, add negative tests for credential fetching
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) fix after bot review
* (sap) lint fix
* (sap) lint fix
* feat: support service_tier in gemini
* chore: add a service_tier field mapping from openai to gemini
* fix: use x-gemini-service-tier header in response
* docs: add service_tier to gemini docs
* chore: add defaut/standard mapping, and some tests
* chore: tidying up some case insensitivity
* chore: remove unnecessary guard
* fix: remove redundant test file
* fix: handle 'auto' case-insensitively
* fix: return service_tier on final steamed chunk
* chore: black
* feat: enable supports_service_tier to gemini models
* Fix get_standard_logging_metadata tests
* Fix test_get_model_info_bedrock_models
* Fix test_get_model_info_bedrock_models
* Fix remaining tests
* Fix mypy issues
* Fix tests
* Fix merge conflicts
* Fix code qa
* Fix code qa
* Fix code qa
* Fix greptile review
---------
Co-authored-by: michelligabriele <gabriele.michelli@icloud.com>
Co-authored-by: Josh <36064836+J-Byron@users.noreply.github.com>
Co-authored-by: mubashir1osmani <mubashir.osmani777@gmail.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: milan-berri <milan@berri.ai>
Co-authored-by: Alperen Kömürcü <alperen.koemuercue@sap.com>
Co-authored-by: Vasilisa Parshikova <vasilisa.parshikova@sap.com>
Co-authored-by: Lin Xu <lin.xu03@sap.com>
Co-authored-by: Mark McDonald <macd@google.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
* fix: expose reasoning effort fields in get_model_info and add together_ai/gpt-oss-120b
- litellm/utils.py: pass supports_none_reasoning_effort and
supports_xhigh_reasoning_effort through _get_model_info_helper so
get_model_info() returns them (previously silently dropped). Fixes#25096.
- model_prices_and_context_window.json: add together_ai/openai/gpt-oss-120b
with supports_reasoning: true so reasoning_effort is accepted for this
model without requiring drop_params. Fixes#25132.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: consolidate duplicate together_ai/openai/gpt-oss-120b entry and sync backup file
* fix: link commit to GitHub account for CLA verification
---------
Co-authored-by: Austin Varga <austin@knowmi.ai>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
DashScope inherits OpenAIGPTConfig which strips cache_control from
messages and tools by default. Override remove_cache_control_flag_from_messages_and_tools()
to preserve cache_control, following the same pattern used by ZAI, MiniMax, and Databricks.
Verified through 10-round multi-turn conversation tests:
- Explicit caching works correctly: cached_tokens grows each round from R4 onwards,
with cache_creation_tokens reported on first cache build.
- Implicit caching is not affected: models that rely on implicit prefix-matching caching
produce identical cached_tokens with and without this change, confirmed by comparing
results against both the reverted codebase and direct API calls bypassing litellm.
- No errors or regressions observed on any model, including those that do not support
explicit caching — the DashScope API silently ignores unrecognized cache_control fields.
Fixes#25330
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: remove leading space from license public_key.pem
PEM must begin with -----BEGIN; a leading ASCII space breaks
cryptography.load_pem_public_key on older cryptography (e.g. 41.x),
causing OpenSSL no start line / deserialize errors.
Made-with: Cursor
* test: assert license public_key.pem loads as valid PEM
Regression guard for leading whitespace before -----BEGIN, which breaks
load_pem_public_key on older cryptography (e.g. 41.x).
Made-with: Cursor
Fixes 'LLM Provider NOT provided' errors when models are configured with
custom_llm_provider but model names lack provider prefix (e.g., 'gpt-4.1-mini'
instead of 'azure/gpt-4.1-mini').
Changes:
- Router now passes deployment's custom_llm_provider to get_llm_provider()
- Fixes 6 code paths: file creation, file content, batch operations, vector store
- Adds regression tests for file creation and file content operations
Made-with: Cursor
* fix(vertex_ai): normalize Gemini finish_reason enum through map_finish_reason in streaming handler
In the legacy vertex_ai SDK streaming path, the raw Gemini finish_reason enum name (e.g. "STOP", "MAX_TOKENS") was stored directly into self.received_finish_reason without being mapped to OpenAI-compatible values. The finish_reason_handler then compared against lowercase "stop", causing the case mismatch to prevent the tool_call override from ever firing. This fix applies map_finish_reason() so all Gemini enum names are normalized before storage.Refactor finish reason handling to use map_finish_reason function.
* refactor: use module-level map_finish_reason import; drop redundant inline import
map_finish_reason is already imported at module scope (line 49) via `from .core_helpers import map_finish_reason, process_response_headers`. The inline import added in the previous commit was redundant. Addressed Greptile review feedback.Removed unnecessary import of map_finish_reason from core_helpers.
* test: add unit tests for Gemini legacy vertex finish_reason normalisation
Added tests to ensure finish_reason normalization for Gemini legacy vertex tool calls and stop reasons.
Anthropic/Claude Code use input_schema.type "custom"; Bedrock rejects it.
- Add normalize_json_schema_custom_types_to_object and use it for Invoke,
chat invoke, and _bedrock_tools_pt (Anthropic input_schema + OpenAI params).
- Coerce invalid root types to object for Converse toolSpec.
- Tests for invoke transform, converse _bedrock_tools_pt, and unit helper.
Made-with: Cursor
* feat(triton): add embedding usage estimation for self-hosted responses
Populate Triton embedding usage from request input using token counting with a safe fallback so cost/observability flows work even when provider usage is missing.
Made-with: Cursor
* fix(triton): sum per-input embedding token counts for batches
Joining batch strings with newlines before token_counter added spurious
tokens. Count each input separately and sum, matching OpenAI-style usage.
Made-with: Cursor
Using setdefault('litellm_metadata', {}) unconditionally created an empty
litellm_metadata key for chat completions and embeddings. This caused
_get_metadata_variable_name_from_kwargs to return 'litellm_metadata' instead
of 'metadata', so tag-based routing looked for tags in the wrong dict and
ignored all tag filters.
Fix: only set the encrypted_content_affinity_enabled flag when litellm_metadata
already exists (Responses API path). Chat completions and embeddings never have
this key, so nothing is created and tag routing works correctly.
- Dockerfile.health_check: HEALTHCHECK now verifies the script is intact
instead of unconditionally exiting 0
- secureStorage.ts: replace deprecated escape/unescape with
encodeURIComponent/decodeURIComponent; don't delete legacy values on
decode failure so in-flight flows can time out naturally
- OAuth callback: add same-origin check before redirecting to stored
return URL
Port security fixes from litellm_v1.82.3.dev.6:
- Use secureStorage (sessionStorage wrapper) instead of raw storage for tokens
- Add URL validation for stored worker URLs to prevent open redirects
- Add same-origin checks before redirecting to stored return URLs
- Harden Dockerfile.health_check with non-root user and exec-form HEALTHCHECK
Unit Tests: Proxy DB Operations / proxy-db (auth-checks, tests/proxy_unit_tests/test_auth_checks.py tests/proxy_unit_tests/test_user_api_key_auth.py, 20, 8) (push) Waiting to run
Unit Tests: Proxy DB Operations / proxy-db (remaining, tests/proxy_unit_tests --ignore=tests/proxy_unit_tests/test_key_generate_prisma.py --ignore=tests/proxy_unit_tests/test_auth_checks.py --ignore=tests/proxy_unit_tests/test_user_api_key_auth.py, 20, 8) (push) Waiting to run
- Add constants.ts with all required exports (key aliases, team IDs)
- Add fixtures/users.ts with all role definitions and storage paths
- Add fixtures/seed.sql for deterministic test database seeding
- Remove Firefox project from playwright config (only Chromium installed)
- Remove unused variable in teams.spec.ts
- Rename CircleCI job to e2e_ui_testing
Add Playwright E2E tests covering proxy admin team and key management
workflows, with a self-contained test runner and CircleCI integration.
Tests cover: create team, invite user, edit/delete team members, create
key in team, regenerate key, update TPM/RPM limits, delete key, and
verify internal user keys are visible.
Infrastructure: run_e2e.sh builds the UI from source before starting
the proxy, ensuring tests always run against the latest UI changes.
Added data-testid attributes to key UI components for reliable selectors.
- Add route_all_chat_openai_to_responses global flag docs under
'Getting Reasoning Content in /chat/completions' in openai.md
with SDK and proxy examples using gpt-5.4
- Remove the section from responses_api.md (wrong location)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Use .lower() == "true" for LITELLM_ROUTE_ALL_CHAT_OPENAI_TO_RESPONSES to avoid bool("False") == True bug
- Add clarifying comment on early return in responses_api_bridge_check
- Document route_all_chat_openai_to_responses flag in openai/responses_api.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds `litellm.route_all_chat_openai_to_responses` (env: `LITELLM_ROUTE_ALL_CHAT_OPENAI_TO_RESPONSES`) to route all OpenAI /chat/completions requests through the Responses API bridge. Also fixes reasoning param dict passthrough in completion transformation.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
