* feat: add _fix_enum_types function to remove enums from non-string fields in schema
* test: add test for _fix_enum_types function to validate enum removal from non-string fields
* fix(gemini): exclude image models from automatic thinking_level parameter (#17013)
- gemini-3-pro-image-preview does not support thinking_level parameter
- Added check to skip adding thinkingConfig for models containing "image"
- Fixes BadRequestError: "Thinking level is not supported for this model"
- Only affects automatic default behavior, user can still pass reasoning_effort explicitly
Fixes#17013
* test: add tests for gemini-3 image models thinking_level exclusion
* update docs
* propagate model id on errors too
* make it work for messages and streaming
* fix
* cleanup
* cleanup
* final
* cleanup
* clean up method name and fix responses api streaming
* remove comment
* add prompt security guardrails provider
* cosmetic
* small
* add file sanitization and update context window
* add pdf and OOXML files support
* add system prompt support
* add tests and documentation
* remove print
* fix PLR0915 Too many statements (96 > 50)
* cosmetic
* fix mypy error
* Fix failed tests due to naming conflict of responses directory with same-named pip package
* Fix mypy error: use 'aembedding' instead of 'embeddings' for async embedding call type
* Fix: Install enterprise package into Poetry virtualenv for tests
The GitHub Actions workflow was installing litellm-enterprise to system Python
using 'python -m pip install -e .', but tests run in Poetry's virtualenv using
'poetry run pytest'. This caused ImportError for enterprise package types.
Changed to 'poetry run pip install -e .' so the package is available in the
same virtualenv where pytest executes.
Fixes enterprise test collection errors in GitHub Actions CI.
* Move Prompt Security guardrail tests to tests/test_litellm/
Per reviewer feedback, move test_prompt_security_guardrails.py from
tests/guardrails_tests/ to tests/test_litellm/proxy/guardrails/ so
it will be executed by GitHub Actions workflow test-litellm.yml.
This ensures the Prompt Security integration tests run in CI.
---------
Co-authored-by: Ori Tabac <oritabac@prompt.security>
Co-authored-by: Vitaly Neyman <vitaly@prompt.security>
* Add fallback in sort to prevent NoneType and str comparison
* Hide Default Team Settings from Proxy Admin Viewers
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* fix: prevent duplicate spend logs in Responses API for non-OpenAI providers
Fixes#15740
This fixes a logging duplication bug where using kwargs.pop() removed
the litellm_logging_obj before passing kwargs to internal acompletion()
calls, causing duplicate spend log entries for providers without native
Responses API support (Anthropic, Gemini, etc).
By changing from pop() to get(), the logging object is preserved and
reused across the internal completion call, preventing duplicate entries
and maintaining correct cost tracking.
* test: add test for logging object preservation in responses API
Verify that litellm_logging_obj is preserved in kwargs when calling
responses(), ensuring no duplicate spend log entries are created.
- Add conditional check for 'global' vertex_location
- Use aiplatform.googleapis.com (no prefix) for global endpoint
- Apply fix to both v1 and v1beta1 APIs
- Matches existing behavior in regular completion calls
Fixes context caching 404 errors when using global location.
Regular completion already handles global correctly, this brings
context caching in line with that behavior.
Related: #11190, #9234
Co-authored-by: prawaan-singh <prawaan.singh@thoughtspot.com>
* fix: fix getting mcp servers
* fix(litellm_logging.py): handle list objects for final response in standard logging payload
Fixes issue where mcp tool call response wouldn't show up
* fix(litellm_responses_transformation/): remove invalid item error for unmapped objects - breaks stream and there's no real value to this as outside of a few of them, not all can be mapped to chat completions
resolves error for web search calls via chat completions to responses api
* Litellm dev 11 22 2025 p1 (#16975)
* fix(model_armor.py): return response after applying changes
* fix: initial commit adding guardrail span logging to otel on post-call runs
sends it as a separate span right now, need to include in the same llm request/response span
* fix(opentelemetry.py): include guardrail in received request log + set input/ouput fields on parent otel span instead of nesting it
allows request/response to be seen easily on observability tools
* fix(model_armor.py): working model armor logging on post call events
* fix: fix exception message
* fix(opentelemetry.py): add backwards compatibility for litellm_request
allow users building on the spec change to use previous spec
* feat(teams.py): param for disabling guardrails by team
allows use-case where you don't run global guardrails for team - only run team-specific guardrails
* feat(custom_guardrail.py): add support for disabling global guardrails
only run guardrails requested for in the request/key/team
* feat: support adding disable_global_guardrails to metadata if present in key/team metadata
* feat(create_key_button.tsx): new disable global guardrails field
* feat(key_edit_view.tsx): support disabling global guardrails on key edit
* feat(teams.tsx): add disable global guardrails on create team on UI
* feat(team_info.tsx): allow disabling global guardrails on team update
* fix: prevent memory blowout in LoggingWorker
Tasks were being executed sequentially with each task awaited before
processing the next one. When the queue had 10k+ tasks, only one could
execute at a time. Since the request rate exceeded execution speed,
objects accumulated in memory (50k+), holding references to heavy
objects and causing memory blowout.
The new implementation uses a semaphore to allow up to 1000 concurrent
tasks while properly tracking and cleaning up each task, significantly
improving throughput and preventing queue buildup.
* fix: require semaphor before removing task from queue
* fix: make worker concurrency configurable
* fix: clean comments
* fix: clarify new env purpose
* fix: add missing lib
* make constants configurable instead of hardcoded
* add more aggressive cleaning when queue is full
* add helpers function for the aggressive cleaning functionality
* use envs instead of static constants
* import and document constants
* add unit test for new functionality
* fix default value on config_settings
* fix: remove unused variables and imports to resolve linter errors
- Remove unused time_since_last_clear variable in logging_worker.py
The variable was calculated but never used in _handle_queue_full()
method, causing F841 linter error.
- Remove unused TYPE_CHECKING import in mcp_server/server.py
The import was not used anywhere in the file, causing F401 linter error.
These changes improve code cleanliness and ensure the codebase passes
all linter checks without affecting functionality.
* add missing log expected by test_queue_full_handling
* fix: clean config_setting.md file
* fix: handle logging errors gracefully during shutdown in _flush_on_exit
During process shutdown, logging handlers may be closed while _flush_on_exit
tries to flush queued logging coroutines. This causes 'ValueError: I/O
operation on closed file' errors when coroutines attempt to log.
Changes:
- Add _safe_log helper method that wraps logging calls and suppresses
errors when logging handlers are closed (ValueError, OSError, AttributeError)
- Replace all verbose_logger calls in _flush_on_exit with _safe_log
- Remove logging from exception handler in coroutine execution loop
to prevent cascading errors during shutdown
This ensures graceful shutdown even when logging handlers are closed,
which is common during process termination.
* feat(anthropic/chat/transformations): for claude-4-5-sonnet and opus-4-1 support passing structured output to anthropic api
* docs: document new feature
* fix: fix output format
* fix: cleanup
* fix(transformation.py): conditionally pass in json tool call
* fix: support ARIZE_SPACE_ID instead of ARIZE_SPACE_KEY
* docs(arize_integration.md): cleanup arize docs
* feat(callback_info_helpers.tsx): allow setting arize space id via ui
* fix: fix linting error
* fix(opentelemetry.py): working arize phoenix root span tracing
