* 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
* docs: Corrected documentation updates from Sept 2025
This PR contains the actual intended documentation changes, properly synced with main:
✅ Real changes applied:
- Added AWS authentication link to bedrock guardrails documentation
- Updated Vertex AI with Gemini API alternative configuration
- Added async_post_call_success_hook code snippet to custom callback docs
- Added SSO free for up to 5 users information to enterprise and custom_sso docs
- Added SSO free information block to security.md
- Added cancel response API usage and curl example to response_api.md
- Added image for modifying default user budget via admin UI
- Re-ordered sidebars in documentation
❌ Sync issues resolved:
- Kept all upstream changes that were added to main after branch diverged
- Preserved Provider-Specific Metadata Parameters section that was added upstream
- Maintained proper curl parameter formatting (-d instead of -D)
This corrects the sync issues from the original PR #14769.
* docs: Restore missing files from original PR
Added back ~16 missing documentation files that were part of the original PR:
✅ Restored files:
- docs/my-website/docs/completion/usage.md
- docs/my-website/docs/fine_tuning.md
- docs/my-website/docs/getting_started.md
- docs/my-website/docs/image_edits.md
- docs/my-website/docs/image_generation.md
- docs/my-website/docs/index.md
- docs/my-website/docs/moderation.md
- docs/my-website/docs/observability/callbacks.md
- docs/my-website/docs/providers/bedrock.md
- docs/my-website/docs/proxy/caching.md
- docs/my-website/docs/proxy/config_settings.md
- docs/my-website/docs/proxy/db_deadlocks.md
- docs/my-website/docs/proxy/load_balancing.md
- docs/my-website/docs/proxy_api.md
- docs/my-website/docs/rerank.md
✅ Fixed context-caching issue:
- Restored provider_specific_params.md to main version (preserving Provider-Specific Metadata Parameters section)
- Your original PR didn't intend to modify this file - it was just a sync issue
Now includes all ~26 documentation files from the original PR #14769.
* docs: Remove files that were deleted in original PR
- Removed docs/my-website/docs/providers/azure_ai_img_edit.md (was deleted in original PR)
- sdk/headers.md was already not present
Now matches the complete intended changes from original PR #14769.
* docs: Restore azure_ai_img_edit.md from main
- Restored docs/my-website/docs/providers/azure_ai_img_edit.md from main branch
- This file should not have been deleted as it was a newer commit
- SDK headers file doesn't exist in main (was reverted) and wasn't part of your original changes
Fixes the file restoration issues.
* docs: Fix vertex.md - preserve context caching from newer commit
- Restored vertex.md to main version to preserve context caching content (lines 817-887)
- Added back only your intended change: alternative gemini config example
- Context caching content from newer commit is now preserved
Fixes the vertex.md sync issue where newer content was incorrectly deleted.
* docs: Fix providers/bedrock.md - restore deleted content from newer commit
- Restored providers/bedrock.md to main version
- Preserves 'Usage - Request Metadata' section that was added in newer commit
- Your actual intended change was to proxy/guardrails/bedrock.md (authentication tip) which is preserved
- Now only has additions, no subtractions as intended
Fixes the bedrock.md sync issue.
* docs: Restore missing IAM policy section in bedrock.md
Added back your intended IAM policy documentation that was lost when restoring main version:
✅ Added IAM AssumeRole Policy section:
- Explains requirement for sts:AssumeRole permission
- Shows error message example when permission missing
- Provides complete IAM policy JSON example
- Links to AWS AssumeRole documentation
- Clarifies trust policy requirements
Now bedrock.md has both:
- All newer content preserved (Request Metadata section)
- Your intended IAM policy addition restored
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Co-authored-by: Cursor Agent <cursoragent@cursor.com>
