* KeyManagementSystem add cyberark
* add CyberArkSecretManager
* add CyberArkSecretManager
* add CyberArkSecretManager
* docs add CyberArkSecretManager
* docs
* refactor to use get_secret_from_manager
* Potential fix for code scanning alert no. 3645: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* Potential fix for code scanning alert no. 3650: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* Potential fix for code scanning alert no. 3649: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* Potential fix for code scanning alert no. 3646: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
---------
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* Add v1 cut of container api
* fix lint errors
* Add proxy support to container apis & logging support (#16049)
* Add proxy support to container apis
* Add logging support
* Add cost tracking support for containers and documentation
* Add new constant documentation
* Add container cost in model map
* fix failing azure tests
* Update tests based on model map changes
* fix model map tests
* fix model map tests
* Container modeshould be container
* Container tests fix
* Merge branch 'main' into litellm_sameer_oct_staging_2
---------
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* feat(vector_store_endpoints/endpoints.py): add new index_create endpoint
allows admin to create a virtual index, to do permission management for
* feat(key_management_endpoints.py): enable setting allowed_vector_store_indexes on keys
proxy admin can enable dev to create an index on a vector stor
* feat: initial commit adding vector store index passthrough logic to litellm
* feat: add vector store table
* fix(azure_ai/transformation.py): fix headers
* feat: track read/write endpoints by vector store integration
enables permissions by index to work
* fix: azure_ai/vector_stores/search
document the vector store endpoints correctly
ensures permission management works as expected
* fix(proxy/utils.py): improve error message
* docs(azure_ai_vector_stores_passthrough.md): document azure ai passthrough vector store support
* docs(create.md): document azure ai support via passthrough for vector store create
* fix: fix code qa errors
* fix: document new allowed_vector_store_indexes endpoint
* feat(milvus/): initial commit adding milvus vector store support to LiteLLM
allows querying milvus vector store through litellm
* feat(bedrock/vector_stores): support translating openai filters param to aws kb
adds filtering to aws kb
* feat(milvus/): add milvus vector store unified search support
allows calling milvus vector store in through chat completions
* docs(milvus_vector_stores.md): document new milvus vector search integration
* feat(pass_through_endpoints.py): support passing form data through to a passthrough endpoint
Closes LIT-1147
* fix: fix linting errors
* 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
* 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
