- Pass request_model to Azure AI cost calculator to detect router requests
- Add router flat cost ($0.14/M input tokens) even when Azure returns actual model in response
- Add test for router flat cost with response containing actual model
- Update docs with cost calculation flow and configuration requirements
Made-with: Cursor
- Update translate_thinking_for_model (3rd code path) to inject
summary="detailed" by default, consistent with the other two paths
- Add disable_default_reasoning_summary flag check via shared helper
- Add tests for flag enabled/disabled and user-provided summary
- Document disable_default_reasoning_summary in reasoning_content.md
Documents exactly how every request and response field gets translated
when LiteLLM routes an Anthropic /v1/messages call through the OpenAI
Responses API path (for OpenAI/Azure targets). Covers messages content
block mapping, tools, tool_choice, thinking→reasoning, context_management,
and the reverse response translation. Wired into the /v1/messages sidebar.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds provider documentation for bedrock_mantle including:
- API key and region configuration
- Supported models with pricing table
- SDK, streaming, and async usage examples
- LiteLLM Proxy config and usage
- Added to Bedrock category in sidebar
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Document the `summary` optional field in the `thinking` object for the
Anthropic `/v1/messages` adapter, and add a section on summary preservation
when routing to non-Anthropic providers via the adapter.
- Fix F821: add BaseTokenCounter TYPE_CHECKING import in gpt_transformation.py
- Remove duplicate auth invocation in count_response_input_tokens endpoint
- Preserve `strict` field during chat→Responses API tool conversion
- Fix docs tools example to use chat completions format (not Responses API format)
- Return None early for system-only messages to avoid noisy error logs
- Add OpenAITokenCounter using POST /v1/responses/input_tokens endpoint
- Add litellm.acount_tokens() public async API that auto-routes to provider APIs
- Add proxy endpoint POST /v1/responses/input_tokens for OpenAI-compatible counting
- Transform chat tools format to Responses API format for correct token counting
- Fall back to local tiktoken when provider API unavailable
Fixes#22302
Add global media_resolution support for Gemini 2.x models (2.0, 2.5) when
using OpenAI's detail parameter on images. Previously, the detail parameter
was only working for Gemini 3+ models (per-part) and was silently ignored
for older Gemini models.
- Add _get_highest_media_resolution() and _extract_max_media_resolution_from_messages()
to extract highest detail from all images/files in a request
- Update _transform_request_body() to add mediaResolution to generationConfig
for Gemini 2.x models only (not 1.x which doesn't support it, not 3+ which
uses per-part)
- Add mediaResolution field to GenerationConfig TypedDict
- Support detail extraction from both image_url and file content types
- Add comprehensive unit tests and update documentation
Add Mistral to the supported providers list in audio_transcription.md
and add Audio Transcription section to the Mistral provider page with
SDK usage, optional params, diarize support, and proxy configuration.
* azure content enhancement...
* rafactored to increase confidence score
* improvements based on additional feedback
* removed unused import
* Force-split any word longer than max length allowed
* preserve whitespace in text splitting
* moving common initialization to base class
* consolidate enforcement into async_make_request as single point, remove redundant caller-side checks, extract shared init/HTTP logic into base, and fix stale log messages
* clean up
* clean up tests
1. Okta SSO docs (admin_ui_sso.md):
- Rewrite Step 3 to document both Org Auth Server (free) and
Custom Auth Server (paid SKU) as tabbed options
- Add Step 4 for GENERIC_CLIENT_STATE and PKCE configuration
(moved from troubleshooting into the main guide)
- Clarify no_matching_policy error only applies to Custom Auth Server
- Deduplicate troubleshooting section to reference Step 4
2. Custom SSO handler (custom_sso.py + custom_sso.md):
- Replace broken user_info() call with prisma_client.get_data()
- user_info() is a FastAPI route handler requiring Request and
UserAPIKeyAuth params, cannot be called directly
- Keep new_user/add_new_member as commented-out import references
in docs for customers who need them
