* 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
