* fix(opentelemetry.py): fix issue where headers were not being split correctly
* feat(bedrock/image): Support bedrock titan image generation
Closes https://github.com/BerriAI/litellm/issues/361
* build(model_prices_and_context_window.json): track titan image gen pricing
enables cost tracking per request
* feat(amazon_titan_transformation.py): support titan image generation cost tracking
* docs: document new model
* docs: update docs to indicate cost tracking + refactor rerank into separate doc
* fix: fix mypy linting error
* fix: fix type ignore
* feat(responses_id_security.py): encrypt response.id - prevent user A from retrieving user B's response
additional security for retrievals on shared accounts
Closes LIT-1307
* feat(responses_id_security.py): allow admin to disable responses id security check
* test: add initial unit testing
* feat(responses_id_security.py): add streaming support
* docs: document new param
* docs: document new param
* feat(responses_id_security.py): add team id checks - ensure it works for service accounts
prevent service accounts keys from different teams from accessing each other's responses
more secure
* test: add unit testing
* fix: fix linting error
* fix(support-model-specific-tpm/rpm-limits): Allows setting rate limits by tpm/rpm for models by team
* fix(key_management_endpoints.py): enforce guaranteed throughput with key-level model tpm/rpm limits, when team-level tpm/rpm limits are set
* test: add unit testing
* feat(schema.prisma): add metadata to litellm budget table
* feat(proxy/utils.py): add org limits to user api key auth
allows org level tpm/rpm limiting to work
* feat: add org level tpm/rpm limits + inherit org id in key from team
enables org level tpm/rpm limits
* feat: validated working org tpm/rpm limits
* feat: support updating org level, model specific tpm/rpm limits
* fix: working key validation for org level tpm/rpm limits
* fix: working validation for orgs when giving tpm/rpm to teams
* fix(key_management_endpoints.py): fix tpm/rpm limits on orgs
* fix(key_management_endpoints.py): support limits
* refactor: remove duplicate var
* fix: refactor to avoid ruff errors
* fix: fix typign
* fix: fix linting error
* fix: fix testing
* fix(key_management_endpoints.py): document params
* fix(presidio.py): handle content as a list of texts
covers openai + anthropic messages api
* fix(presidio.py): safe get messages
* test: add unit testing for presidio guardrails
* fix(unified_guardrail.py): initial commit
* fix(enkryptai.py): implement apply_guardrail to enkrypt guardrail
* fix(unified_guardrail.py): support unified guardrail on input
* feat(unified_guardrail.py): add post call success hook implementation
allows us to just have 1 place to handle llm translation to guardrail api spec
* refactor: refactor initial unified guardrail component
* refactor: more refactoring
* feat(responses/): add guardrails to responses api
allows existing guardrails to work for new llm endpoints
* docs(adding_guardrail_support.md): document new guardrail endpoint support
* test: add unit tests
* feat(image_generation/): add guardrail support for image generation endpoint
* feat(openai/text_completion): support guardrails on `/v1/completions` API
* docs: document guardrails support on new endpoints
* docs: clarify when guardrails run
* feat(openai/speech): add guardrail support for input
* docs(rerank/): add guardrail support on input query
* fix: fix ruff check
* Addd v2/chat support for cohere
* fix streaming
* Use v2_transformation for logging passthrough:
* Use v2_transformation for logging passthrough:
* Add test for checking if document and citation_options is getting passed
* Update the cohere model
* Add cost tracking for vertex ai passthrough batch jobs
* Add full passthrough support
* refactor code according to the comments
* Add passthrough handler
* remove invalid params
* Updated documentation
* Updated documentation
* Updated documentation
* Correct the import
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix documentation for get batch req (#15742)
* Add grounding info to responses API (#15737)
* Add grounding info to responses API
* fix lint errors
* Use typed objects for annotations
* Use typed objects for annotations
* fix mypy error
* Litellm fix json serialize alreting 2 (#15741)
* fix json serializable error for alerts
* Add test
* fix mypt errors
* fix mypt errors
* Add Qwen3 imported model support for AWS Bedrock (#15783)
* Add qwen imported model support
* fix mypy errors
* fix empty user message error (#15784)
* fix typed dict for list
* Add azure supported videos endpoint
* fix mapped tests
* add azure sora models to model map
* Add OpenAI video generation and content retrieval support (#15745)
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix typed dict for list
* fix mypy errors
* move directory
* make v2 chat default
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Revert "Add Azure Video Generation Support with Sora Integration"
* refactor videos repo
* add test
* Add azure openai videos support
* Add azure openai videos support
* Add router endpoint support for videos
* fix mypy error
* add azure models
* fix mapped test
* fix mypy error
* Add proxy router test
* Add proxy router test
* remove deprecated model name from tests
* fix import error
* fix import error
* Add gaurdrail integration in videos endpoint
* Add logging support for videos endpoint
* Add final documentation supporting videos integration
* fix model name and document input
* Update literals to avoid mypy errors
* Remove unused imports and print statements
* revert guardrail support for video generation and video remix
* revert guardrail support for video generation and video remix
* Fix failing mapped and llm translation tests
* 1. add v3 classify
2. add new classifix for masking
3. support same id for the conversation for pre and post
working with duplicates
* clean code, remove some debug and run tests
* update liter errors
* improvment for Code Organization, httpx Error Handling Specificity, Logging Improvements and Type
* transfer test test_lasso_guard_config to the new location
* Fix type hints and linting errors in lasso.py
- Add type: ignore for httpx module when None
- Fix return type issues in _handle_classification and _handle_masking
- Ensure masked_messages is not None before passing to _apply_masking_to_model_response
- Convert LassoResponse to dict for _log_masking_applied call
* feat(cohere): Enhance embedding transformation to support Bedrock's embeddings by type
* test(cohere): Add unit tests for embedding transformation responses
* fix: Apply max_connections configuration to Redis async client
- Add max_connections to available Redis cluster kwargs
- Add connection_pool parameter to get_redis_async_client()
- Pass connection_pool to Redis client if provided
- Prevents Redis connection exhaustion under high load
* test: Add tests for Redis max_connections feature
- Test max_connections is included in cluster kwargs
- Test connection_pool parameter is properly passed to async client
- Test async client works without connection_pool parameter
All 3 tests pass successfully
- Change variable name in litellm/__init__.py from configured_cold_storage_logger to cold_storage_custom_logger
- Update all references across the codebase to use the new variable name
- This fixes silent failure of cold storage logging due to variable name mismatch
- Configuration files use cold_storage_custom_logger, code should match
Files updated:
- litellm/__init__.py
- litellm/litellm_core_utils/litellm_logging.py
- litellm/proxy/spend_tracking/cold_storage_handler.py
- litellm/responses/litellm_completion_transformation/session_handler.py
- tests/test_litellm/litellm_core_utils/test_litellm_logging.py
- tests/test_litellm/responses/litellm_completion_transformation/test_session_handler.py
* [Feat] Add SENTRY_ENVIRONMENT configuration for Sentry integration and corresponding tests
* [Refactor] Enhance test_sentry_environment by mocking sentry_sdk and improving environment handling
* [Fix] Update default SENTRY_ENVIRONMENT to 'production' and enhance test for Sentry integration
* [Fix] Update test_sentry_environment to verify correct handling of SENTRY_ENVIRONMENT values
* [Fix] Update test_sentry_environment to assert correct handling of production environment
* fix: Add response_type parameter to OAuth authorization endpoint
Fixes#15684
OAuth providers like Google require the response_type parameter during
the authorization flow. This commit adds response_type=code to the
authorization redirect parameters, which is required by the OAuth 2.0
specification (RFC 6749 Section 4.1.1).
Changes:
- Added response_type=code to authorization params in discoverable_endpoints.py
- Added test coverage for the response_type parameter
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix oauth flow by forwarding code_challenge and forwarding code_verifier
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(guardrails): Add content masking and streaming support to PANW Prisma AIRS
- Add mask_request_content and mask_response_content parameters
- Implement content masking for prompts and responses
- Add streaming support with real-time masking
- Add comprehensive test coverage (28 tests)
- Update documentation with masking examples and security notes
* fix(guardrails): Fix PANW Prisma AIRS env var fallback and text completion support
* fix(support-model-specific-tpm/rpm-limits): Allows setting rate limits by tpm/rpm for models by team
* fix(key_management_endpoints.py): enforce guaranteed throughput with key-level model tpm/rpm limits, when team-level tpm/rpm limits are set
* test: add unit testing
* fix: fix minor linting errors
* fix: refactor
* fix: minor fixes to mcp streaming with bedrock
* fix(bedrock/): working bedrock with mcp tools
handle empty description
* test: add unit test
* test: test fixes
* fix(vector_store_registry.py): load vector store with litellm params from config.yaml
fixes minor issue where litellm params weren't being loaded in from config.yaml
* docs(knowledgebase.md): document azure vector store current limitation
* fix(opentelemetry.py): add hidden params to otel logs
Fixes LIT-1274
* fix: fix test
* Implement fix for thinking_blocks and converse API calls
This fixes Claude's models via the Converse API, which should also fix
Claude Code.
* Add thinking literal
* Fix mypy issues
* Type fix for redacted thinking
* Add voyage model integration in sagemaker
* Add config file logic
* Use already exiting voyage transformation
* refactor code as per comments
* fix merge error
* refactor code as per comments
* refactor code as per comments
* UI new build
* [Fix] router - regression when adding/removing models (#15451)
* fix(router): update model_name_to_deployment_indices on deployment removal
When a deployment is deleted, the model_name_to_deployment_indices map
was not being updated, causing stale index references. This could lead
to incorrect routing behavior when deployments with the same model_name
were dynamically removed.
Changes:
- Update _update_deployment_indices_after_removal to maintain
model_name_to_deployment_indices mapping
- Remove deleted indices and decrement indices greater than removed index
- Clean up empty entries when no deployments remain for a model name
- Update test to verify proper index shifting and cleanup behavior
* fix(router): remove redundant index building during initialization
Remove duplicate index building operations that were causing unnecessary
work during router initialization:
1. Removed redundant `_build_model_id_to_deployment_index_map` call in
__init__ - `set_model_list` already builds all indices from scratch
2. Removed redundant `_build_model_name_index` call at end of
`set_model_list` - the index is already built incrementally via
`_create_deployment` -> `_add_model_to_list_and_index_map`
Both indices (model_id_to_deployment_index_map and
model_name_to_deployment_indices) are properly maintained as lookup
indexes through existing helper methods. This change eliminates O(N)
duplicate work during initialization without any behavioral changes.
The indices continue to be correctly synchronized with model_list on
all operations (add/remove/upsert).
* fix(prometheus): Fix Prometheus metric collection in a multi-workers environment (#14929)
Co-authored-by: sotazhang <sotazhang@tencent.com>
* Add tiered pricing and cost calculation for xai
* Use generic cost calculator
* Resolve conflicts in generated HTML files
* Remove penalty params as supported params for gemini preview model (#15503)
* fix conversion of thinking block
* add application level encryption in SQS (#15512)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* build: bump version
* bump: version 1.78.0 → 1.78.1
* add application level encryption in SQS
* add application level encryption in SQS
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: deepanshu <deepanshu.lulla@hq.bill.com>
* [Feat] Bedrock Knowledgebase - return search_response when using /chat/completions API with LiteLLM (#15509)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* add AnthropicCitation
* fix async_post_call_success_deployment_hook
* fix add vector_store_custom_logger to global callbacks
* test_e2e_bedrock_knowledgebase_retrieval_with_llm_api_call
* async_post_call_success_deployment_hook
* add async_post_call_streaming_deployment_hook
* async def test_e2e_bedrock_knowledgebase_retrieval_with_llm_api_call_streaming(setup_vector_store_registry):
* fix _call_post_streaming_deployment_hook
* fix async_post_call_streaming_deployment_hook
* test update
* docs: Accessing Search Results
* docs KB
* fix chatUI
* fix searchResults
* fix onSearchResults
* fix kb
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* [Feat] Add dynamic rate limits on LiteLLM Gateway (#15518)
* docs: fix doc
* docs(index.md): bump rc
* [Fix] GEMINI - CLI - add google_routes to llm_api_routes (#15500)
* fix: add google_routes to llm_api_routes
* test: test_virtual_key_llm_api_routes_allows_google_routes
* build: bump version
* bump: version 1.78.0 → 1.78.1
* fix: KeyRequestBase
* fix rpm_limit_type
* fix dynamic rate limits
* fix use dynamic limits here
* fix _should_enforce_rate_limit
* fix _should_enforce_rate_limit
* fix counter
* test_dynamic_rate_limiting_v3
* use _create_rate_limit_descriptors
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* Add google rerank endpoint
* Add docs
* fix mypy error
* fix mypy and lint errors
* Add haiku 4.5 integration
* Add haiku 4.5 integration for other regions as well
* Handle citation field correctly
* Fix filtering headers for signature calcs
* Add haiku 4.5 integration (#15650)
---------
Co-authored-by: Leslie Cheng <leslie.cheng5@gmail.com>
Co-authored-by: Sameer Kankute <sameer@berri.ai>
Co-authored-by: Alexsander Hamir <alexsanderhamirgomesbaptista@gmail.com>
Co-authored-by: Lucas <10226902+LoadingZhang@users.noreply.github.com>
Co-authored-by: sotazhang <sotazhang@tencent.com>
Co-authored-by: Deepanshu Lulla <deepanshu.lulla@gmail.com>
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: deepanshu <deepanshu.lulla@hq.bill.com>
* chore: Consistency in install-test-deps using poetry run
* feat: update in-memory guardrails after database CRUD operations
* test: add parameterized tests for guardrail CRUD with memory sync
