* fix: enforce team member budget check in common_checks
- Add missing team member budget validation in common_checks() function
- Checks team membership budget when team key is used
- Raises BudgetExceededError when team member spend exceeds max_budget_in_team
- Follows same pattern as other budget checks (team, user, end_user)
- Uses cached get_team_membership() for performance
- Fix AttributeError in lowest_tpm_rpm.py
- Add null check for model_info before accessing .get() method
- Prevents 'NoneType' object has no attribute 'get' error
- Add unit tests for team member budget enforcement
- Test budget exceeded scenario
- Test within budget scenario
- Test edge cases (no budget, no membership, personal keys)
- Tests run without requiring proxy server
Fixes failing test: test_users_in_team_budget
* fix: mock get_async_httpx_client in test_langsmith_key_based_logging
- Mock get_async_httpx_client to return a mock AsyncHTTPHandler instance
- Fixes test failure where mock_post was never called
- LangsmithLogger creates its own httpx client instance via get_async_httpx_client,
so we need to mock the factory function rather than the class method
- Use MagicMock for response.raise_for_status (sync method) instead of AsyncMock
* fix: resolve linting errors (PLR0915, F401)
- Remove unused imports (datetime, ServiceLoggerPayload) from arize_phoenix.py
- Extract health ping setup logic from RedisCache.__init__ to reduce statement count
- Extract team member budget check from common_checks to reduce statement count
* fix: resolve type errors in ChatCompletionToolCallChunk construction
- Cast type field to Literal['function'] to satisfy TypedDict requirements
- Ensure arguments field is explicitly str type to match TypedDict signature
- Fixes pyright errors for incompatible types in transformation.py
* Add monitor mode support to Lakera guardrail
- Add on_flagged parameter to LakeraV2GuardrailConfigModel (default: 'block')
- Support 'monitor' mode that logs violations without blocking requests
- Support 'block' mode (default) that raises HTTPException on violations
- Update async_pre_call_hook and async_moderation_hook to check on_flagged
- Update guardrail initializer to pass on_flagged from config
- Add documentation with monitor mode examples
This allows users to tune Lakera security policies by monitoring violations
without blocking legitimate requests, similar to Pillar's on_flagged_action.
* Add tests for Lakera guardrail monitor mode
- Test monitor mode allows flagged content through (pre_call hook)
- Test block mode raises HTTPException for violations (pre_call hook)
- Test monitor mode works with during_call (moderation_hook)
These tests verify the on_flagged parameter functionality for both
monitor and block modes across different guardrail hooks.
---------
Co-authored-by: Steve <steve.giguere@lakera.ai>
* feat(litellm_content_filter.py): add support for content filtering categories
make it easy for proxy admin to prevent messages about violence, self harm or illegal weapons going through litellm
* feat: initial commit adding bias detection
allows admin to block inappropriate content about sexual orientation, etc.
* refactor: simplify content_filter.py
use a more exhaustive set of keywords, instead of guessing at potential phrases user can use
* feat(content_filter.py): add new denied topics for in-built content filter guardrails
allow user to automatically block content relating to certain categories from being sent to the LLML
* refactor(content-filter): document new params to litellm content filter
* feat(ui/): litellm content filter - select content categories on ui
* docs: update documentation
* docs(litellm_content_filter.md): document new content filters
* feat: initial commit adding support for inappropriate images via litellm content filter
* feat(content_filter.py): support blocking images containing blocked content
prevent images which contain disallowed content from being sent to the llm api
* docs(litellm_content_filter.md): document new image capabilities of litellm_content_filter
* fix: fix expected error code
* feat(litellm_content_filter.py): add support for content filtering categories
make it easy for proxy admin to prevent messages about violence, self harm or illegal weapons going through litellm
* feat: initial commit adding bias detection
allows admin to block inappropriate content about sexual orientation, etc.
* refactor: simplify content_filter.py
use a more exhaustive set of keywords, instead of guessing at potential phrases user can use
* feat(content_filter.py): add new denied topics for in-built content filter guardrails
allow user to automatically block content relating to certain categories from being sent to the LLML
* refactor(content-filter): document new params to litellm content filter
* feat(ui/): litellm content filter - select content categories on ui
* docs: update documentation
* docs(litellm_content_filter.md): document new content filters
* docs: expand Responses API section and update endpoints in README
- Add full Responses API example with code and output format
- Clarify OpenAI Chat Completions vs Responses API formats
- Update supported endpoints list (completions, responses, embeddings, images, audio, batches)
- Fix consistent output description to be endpoint-agnostic
* update docs
* update README with latest models
The _add_tag_to_deployment function was directly modifying the
deployment's litellm_params in memory and writing it back to the
database, which caused encrypted API keys and other sensitive fields
to be lost. This fix retrieves the model from the database first,
preserves all existing fields including encrypted ones, adds only the
new tag to the tags array, and updates the database with the modified
params while keeping encrypted fields intact.
Added comprehensive unit tests covering preservation of encrypted
fields, handling of both string and dict litellm_params formats,
duplicate tag prevention, and error handling for missing models.
Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Claude <noreply@anthropic.com>
