Added a new "Configuration with Environment Variables" section demonstrating:
- Using os.getenv() to dynamically retrieve OpenRouter configuration
- Explicitly passing base_url parameter with environment variables
- Benefits of this approach for managing configs across environments
This helps users implement production-ready configuration patterns.
* 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(lasso): Upgrade to Lasso API v3 and fix ULID generation
- Update Lasso API endpoints from v2 to v3 (/gateway/v3/classify)
- Update masking endpoints from v1 to v3 (/gateway/v3/classifix)
- Fix ULID generation: use ulid.new() instead of ULID() constructor
- Resolve MemoryView error that occurred with incorrect ULID usage
Tested with real proxy server and verified:
- Malicious content (jailbreak) properly blocked
- Safe content passes through guardrail
- PII detection and masking works correctly
- No ULID generation errors
* docs(lasso): Add ulid-py>=1.1.0 dependency prerequisite
Add Prerequisites section documenting the required ulid-py package
(version 1.1.0 or higher) for Lasso guardrail conversation tracking.
* update docs with the right api_key format
* 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(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
* feat(vector_stores/): initial commit adding Vertex AI Search API support for litellm
new vector store provider
* feat(vector_store/): use vector store id for vertex ai search api
* fix: transformation.py
cleanup
* fix: implement abstract function
* fix: fix linting error
* fix: main.py
fix check
* feat: initial commit with working passthrough support for vertex ai search api through litellm
* feat(llm_passthrough_endpoints.py): fix passing correct project on datastore passthrough
* feat(vertex_ai/): support passthrough call for vertex ai search vector store
* docs(vertex_ai_search_datastore.md): document new vertex ai passthrough endpoint
* docs(sidebars.js): document new endpoint
* feat: initial commit adding logging for vertex ai passthrough api
allows vertex ai vector search api to work with cost calculation
* feat(vertex_ai/): search vector store cost tracking
* fix(vertex_passthrough_logging_handler.py): log the cost
* fix: improve logged response
* fix(vertex_passthrough_logging_handler.py): logging
* feat(litellm_logging): main.py
add cost tracking for vertex ai search api via unified api
* refactor: fix ruff checks
* fix(llm_passthrough_endpoints.py): fix linting
* fix(managed_files.py): don't raise error if managed object is not found
* feat(vector_stores): add azure ai search vector store support
Enables direct querying a vector store on azure
* fix(azure/vector_stores): working azure ai search api vector stores
allows azure direct querying on vector stores
* test: update env vars
* docs(docs/): document new azure ai vector store search
* docs(azure_ai_vector_stores.md): add table
* docs: clarify support for 'create' vector stores
* fix(vector_stores/endpoints.py): Fixes https://github.com/BerriAI/litellm/issues/14606
* fix: fix linting errors
* fix(oldteams.tsx): allow org admin to create team on ui
* fix(oldteams.tsx): show org admin a dropdown of allowed orgs for team creation
* docs(access_control.md): cleanup doc
* feat(ibm_guardrails/): initial commit adding support for ibm guardrails on litellm
allows user to use self-hosted ibm guardrails
* feat(ibm_detector.py): working detector
* docs(ibm_guardrails.md): document new ibm guardrails
* fix: fix linting errors
* 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] 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
* 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
