The Gemini REST API documents the embedding task type parameter as
camelCase `taskType`. The existing transformation functions convert
`dimensions` to `outputDimensionality` but miss the parallel
`task_type` to `taskType` conversion. This adds that conversion to
both `transform_openai_input_gemini_content` (batchEmbedContents path)
and `transform_openai_input_gemini_embed_content` (embedContent path).
Fixes#24190
Non-streaming paths call _process_hidden_params_and_response_cost; streaming
assembles the full response later and skipped that, so litellm_params.metadata
lacked hidden_params (e.g. response_cost for OTEL/OpenSearch).
- Add _merge_hidden_params_from_response_into_metadata and call it from
success_handler and async_success_handler after cost is set, before
_build_standard_logging_payload.
- Unit tests for merge helper.
Tests: pytest tests/test_litellm/litellm_core_utils/test_litellm_logging.py
Made-with: Cursor
The /v1/messages/count_tokens endpoint was hardcoding the Bedrock runtime
URL, ignoring api_base and aws_bedrock_runtime_endpoint settings. This
aligns it with invoke/converse handlers by using the existing
get_runtime_endpoint() method for consistent endpoint resolution.
Signed-off-by: stias <seokjun.yang@mycraft.kr>
* fix: resolve recursion in OVHCloud get_supported_openai_params (#24111)
Root cause: OVHCloudChatConfig.get_supported_openai_params() called
get_model_info() which called back into get_supported_openai_params(),
causing infinite recursion and falling back to no tools support.
Made-with: Cursor
* fix: use .get() for TypedDict + don't hardcode function_calling support
Made-with: Cursor
---------
Co-authored-by: themavik <themavik@users.noreply.github.com>
Added a new section to the config.yaml documentation explaining how to
set the LITELLM_LICENSE environment variable for enterprise features.
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
- Skip short-circuit for providers that have a BaseAnthropicMessagesConfig
(bedrock, vertex_ai, azure_ai, anthropic) — they use the agentic loop
which includes a follow-up LLM synthesis step. Short-circuiting would
return raw search text instead of an LLM-synthesized answer.
- Add fallback to litellm.get_llm_provider() for custom_llm_provider
derivation when litellm_params is overwritten by kwargs.
- Add test for bedrock guard.
Addresses Greptile review comments #3 and #4.
Tests were outdated after _get_and_validate_existing_key was refactored
to use prisma_client.db.litellm_verificationtoken.find_unique() and
ProxyException. Also add ProxyException handling in bulk_update_keys
error extractor so error messages aren't empty.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Tests were outdated after _get_and_validate_existing_key was refactored
to use prisma_client.db.litellm_verificationtoken.find_unique() instead
of prisma_client.get_data(), and to raise ProxyException instead of
HTTPException. Also fix bulk_update_keys error handler to extract
ProxyException.message (str(ProxyException) returns empty string).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
