* Fix duplicate imports in SAP embedding transformation
* fix: add missing prompt_spec parameter to HumanloopLogger.get_chat_completion_prompt
- Add prompt_spec: Optional[PromptSpec] = None parameter to match base class signature
- Import PromptSpec from litellm.types.prompts.init_prompts
- Pass prompt_spec to super().get_chat_completion_prompt() call
- Fixes mypy type error: Signature incompatible with supertype CustomLogger
* fix: add missing parameters to AnthropicCacheControlHook.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Change litellm_logging_obj type from Any to LiteLLMLoggingObj using TYPE_CHECKING pattern
- Pass all parameters including prompt_spec to get_chat_completion_prompt call
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: add missing parameters to DotpromptManager.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Change litellm_logging_obj type from Any to LiteLLMLoggingObj using TYPE_CHECKING pattern
- Pass all parameters including ignore flags to PromptManagementBase.async_get_chat_completion_prompt
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: document envs
* fix: add missing parameters to LangfusePromptManagement.async_get_chat_completion_prompt
- Add ignore_prompt_manager_model and ignore_prompt_manager_optional_params parameters
- Pass all parameters including prompt_spec and ignore flags to get_chat_completion_prompt
- Fixes mypy type errors: Signature incompatible with supertype CustomLogger and PromptManagementBase
* fix: add missing parameters to prompt management async methods (Category 1)
- vector_store_pre_call_hook: add ignore_prompt_manager_model, ignore_prompt_manager_optional_params, prompt_spec
- gitlab_prompt_manager: add ignore parameters, fix litellm_logging_obj type
- bitbucket_prompt_manager: add ignore parameters, fix litellm_logging_obj type
- proxy/custom_prompt_management: add prompt_spec parameter
- Fixes mypy type errors: Signature incompatible with supertype
* fix: fix arize_phoenix_prompt_manager and custom_prompt_management (Category 2)
- arize_phoenix_prompt_manager: add prompt_spec to all methods, fix prompt_id types, implement async_compile_prompt_helper
- custom_prompt_management: implement async_compile_prompt_helper abstract method
- Fixes mypy type errors: Signature incompatible with supertype and abstract method errors
* fix: fix obvious type errors (Category 3 - Quick Wins)
- langfuse: change 'callable' to 'Callable' type annotation
- presidio: add type narrowing check for Choices vs StreamingChoices
- StreamingChoices doesn't have .message attribute, only Choices does
- Add hasattr check before accessing choice.message
- Fixes mypy type errors: callable? not callable and union-attr errors
* fix: handle expires_after None in Azure files handler (Todo 14)
- Extract logic to _prepare_create_file_data helper method
- Remove expires_after from dict if None to match SDK's Omit pattern
- Add type ignore for FileExpiresAfter -> file_create_params.ExpiresAfter mismatch
- Fixes mypy error: Argument expires_after has incompatible type
* fix: change purpose parameter type to OpenAIFilesPurpose (Todo 18)
- Import OpenAIFilesPurpose in storage_backend_service.py
- Change upload_file_to_storage_backend purpose parameter from str to OpenAIFilesPurpose
- Change _create_file_object_with_storage_metadata purpose parameter from str to OpenAIFilesPurpose
- Fixes mypy error: Argument purpose has incompatible type str; expected Literal type
- Purpose is already validated in files_endpoints.py before reaching these functions
* fix: handle UploadFile | str type for expires_after form fields (Todo 19)
- Validate expires_after[anchor] and expires_after[seconds] are strings, not UploadFiles
- Validate anchor equals 'created_at' before using literal in TypedDict
- Use literal 'created_at' (not variable) in FileExpiresAfter to satisfy Literal type
- Add proper error handling for invalid anchor values and int conversion
- Fixes mypy errors: Incompatible types for anchor and seconds in FileExpiresAfter
* fix: add type narrowing for expires_after_seconds_str to fix mypy error
- Add assert statement after UploadFile validation to help mypy narrow type
- Use validated variable with explicit str type annotation
- Fixes: Argument of type 'UploadFile | str' cannot be assigned to int()
* fix: trigger async_success_handler for MCP tool calls to enable cost tracking and logging
- Set call_type to CallTypes.call_mcp_tool.value before calling async_success_handler
- Update mcp_tool_call_metadata with cost info when server is found
- Call async_success_handler to build standard_logging_object and trigger callbacks
- Fixes test_mcp_cost_tracking by ensuring standard_logging_payload is populated
* refactor: use positive isinstance check for safer type narrowing
- Replace assert with positive isinstance(..., str) check
- Matches codebase pattern (see pass_through_endpoints.py)
- Safer than assert: assertions can be disabled with -O flag
- Mypy properly narrows type after positive isinstance check
- More explicit and readable than assert statement
* fix: add missing REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE to ServiceTypes enum (Todo 17)
- Add REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE enum value following the pattern of other daily spend queues
- Add corresponding entry to DEFAULT_SERVICE_CONFIGS with GAUGE metrics
- Fixes mypy error: 'type[ServiceTypes]' has no attribute 'REDIS_DAILY_AGENT_SPEND_UPDATE_QUEUE'
- This enum value is already used in redis_update_buffer.py for agent spend tracking
Add support for the 'xhigh' reasoning effort level on all gpt-5.2 model
variants, not just gpt-5.2-pro. This enables deeper reasoning capabilities
for the base gpt-5.2 model.
Changes:
- Add is_model_gpt_5_2_model() method to detect gpt-5.2 variants
- Update xhigh validation to allow gpt-5.2 models
- Update documentation with gpt-5.2 reasoning_effort support
- Update tests to reflect new behavior
* feat(deepseek): add native support for thinking and reasoning_effort params
Add proper parameter mapping for DeepSeek thinking mode, allowing users
to use the unified LiteLLM interface instead of extra_body workarounds.
Supported formats:
- thinking={"type": "enabled"}
- thinking={"type": "enabled", "budget_tokens": X} (budget_tokens ignored)
- reasoning_effort="low|medium|high" (maps to thinking enabled)
DeepSeek only supports {"type": "enabled"} without budget_tokens,
so any budget_tokens are stripped and all reasoning_effort values
(except "none") map to enabled.
Reference: https://api-docs.deepseek.com/guides/thinking_mode
* docs(deepseek): add thinking and reasoning_effort parameter documentation
* fix: resolve mypy type errors in hiddenlayer guardrail and transformation
- Fix return type of apply_guardrail from str to GenericGuardrailAPIInputs
- Add None checks for logging_obj before accessing attributes
- Convert AllMessageValues to dict format for HiddenLayer API compatibility
- Fix payload type annotation in _call_hiddenlayer
- Ensure transformed_output always returns list[dict[str, Any]] in transformation.py
* fix: use litellm_call_id as trace_id fallback in langfuse logging
- Only use standard_logging_object.trace_id if explicitly set via litellm_session_id or litellm_trace_id params
- Fallback to litellm_call_id when no explicit trace_id is provided (matches test expectation)
- Return the trace_id we set instead of generation_client.trace_id for consistency
- Add warning if langfuse modifies the trace_id to help debug potential issues
Fixes test_logging_trace_id test failure where auto-generated UUID was used instead of litellm_call_id
* fix: document envs
* fix: handle None response in /spend/logs endpoint when no records found
- Return empty list [] instead of [None] when spend_log is None
- Prevents 500 errors when querying by request_id, api_key, or user_id with no matching records
- Fixes test_chat_completion_bad_model_with_spend_logs test failure
* fix: use standard_logging_object trace_id when available in langfuse logger
- Fix trace_id selection logic to use standard_logging_object.trace_id when available
- Previously only used standard_logging_object.trace_id if explicitly set via params
- Now uses standard_logging_object.trace_id whenever it's present, matching test expectations
- Falls back to litellm_call_id if no trace_id is found
- Fixes test_log_langfuse_v2_uses_standard_trace_id_when_available test failure
Add support for the Bedrock Converse API serviceTier parameter to allow
specifying processing tier (priority, default, or flex).
Changes:
- Add ServiceTierBlock type in litellm/types/llms/bedrock.py
- Add serviceTier to CommonRequestObject
- Add serviceTier to get_config_blocks() in AmazonConverseConfig
- Add comprehensive tests for serviceTier functionality
- Add documentation for serviceTier usage
This allows users to configure service tier via:
- litellm_params in proxy config
- optional_params in SDK calls
* docs(prompt_management.md): document how to onboard prompts to litellm
* feat(arize_phoenix_prompt_manager.py): support new prompt management integration
allows users to connect arize phoenix prompt manager to litellm
* fix(proxy/utils.py): remove prompt variables to avoid re-processing prompt
* docs(arize_phoenix_prompts.md): document new prompt management integration
The relative link was causing Docusaurus to incorrectly associate the
/supported_endpoints page with SDK Functions category instead of the
actual Supported Endpoints generated-index.
* Add community contribution guide for integration partners
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
* Update community docs to direct users to #integration-partners
Co-authored-by: krrishdholakia <krrishdholakia@gmail.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
* feat(voyage): add rerank API support
Add support for Voyage AI rerank models (rerank-2.5, rerank-2.5-lite,
rerank-2, rerank-2-lite) to the LiteLLM rerank API.
Changes:
- Add VoyageRerankConfig transformation class
- Register voyage provider in rerank_api/main.py
- Add voyage case in utils.py get_provider_rerank_config
- Add rerank-2.5 and rerank-2.5-lite models to pricing JSON
- Add unit tests for transformation logic
- Update documentation for voyage.md and rerank.md
Usage:
```python
from litellm import rerank
response = rerank(
model="voyage/rerank-2.5",
query="What is the capital of France?",
documents=["Paris is...", "London is..."],
top_n=3,
)
```
* refactor(voyage): simplify rerank transformation code
Remove verbose docstrings to align with other providers (jina_ai pattern).
No functional changes - 168 lines vs 169 for jina_ai.
* fix(voyage): remove incorrect input_cost_per_query from rerank models
Voyage AI charges per token, not per query. The input_cost_per_query
field was incorrectly set to the same value as input_cost_per_token
in the existing rerank-2 and rerank-2-lite models.
Removes input_cost_per_query from all Voyage rerank models:
- voyage/rerank-2
- voyage/rerank-2-lite
- voyage/rerank-2.5
- voyage/rerank-2.5-lite
Pricing source: https://docs.voyageai.com/docs/pricing
* attempt to implement the passthrough feature
* Formatting and small change
* Fix formatting
* feat: grayswan guardrail overwrite ModelResponse in passthrough mode
* fix missing exception error catching on certain
endpoints
* fix wrong call site
* fix: patch anthropic endpoint internal error on streaming obj
* fix grayswan testcase
* feat: update the violation response to more natural
* Formatting
* move passthrough exception definition to custom_guardrail.
* Enhancement: show whether the blocked at input or output
* update exception name
* fix a typo in testing unit.
---------
Co-authored-by: Xiaohan Fu <xiaohan@grayswan.ai>
Alexsander Hamir