* 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>
- Added gpt-5-pro entry to model_prices_and_context_window.json with complete specifications
- Mode: responses (Responses API only)
- Pricing: $15.00 input / $120.00 output (Standard), $7.50 input / $60.00 output (Batch)
- Context: 400,000 input tokens, 272,000 output tokens
- Endpoints: /v1/batch, /v1/responses only
- Features: Web Search, Function Calling, Vision, PDF Input, Prompt Caching, Reasoning
- No streaming support, no Code Interpreter, no Computer Use
- Added gpt-5-pro to supported models list in docs/my-website/src/pages/completion/supported.md
- Added gpt-5-pro to OpenAI provider documentation in docs/my-website/docs/providers/openai.md
- Added comprehensive GPT-5 Pro Special Notes section with usage examples and limitations
Added comprehensive Watson X model support including:
- IBM Granite models (granite-4-h-small, granite-3-3-8b-instruct, granite-guardian variants, granite-vision, granite-ttm time series models)
- Meta Llama models (llama-3-2-1b/3b/11b-vision/90b-vision, llama-3-3-70b, llama-4-maverick-17b, llama-guard-3-11b-vision)
- Mistral models (mistral-medium-2505, mistral-small-2503, pixtral-12b-2409)
- Additional models (BigScience mt0-xxl-13b, Google flan-t5-xl-3b, OpenAI gpt-oss-120b, SDAIA allam-1-13b-instruct, Core42 jais-13b-chat)
All models include proper pricing, token limits, and capability flags (function calling, vision support, etc.) based on IBM Watson X documentation.
