* feat(internal_user_endpoints.py): allow passing team-specific details when creating new user with team
allows assigning users to teams on creation
* feat(internal_user_endpoints.py): support for setting team values in default internal user params
Ensures admin can assign all new users to a default team
* test(test_internal_user_endpoints.py): add unit tests
* feat(ui/): allow setting default team on admin UI
easier onboarding for users
* fix(internal_user_endpoints.py): fix exception check
* fix SCIM memberships Patch
* fixes for SCIM updates
* fixes for SCIM
* working provisioning for teams on SCIM
* working user patch / PUT ops SCIM
* fixes SCIM
* test_scim_v2_endpoints.py
* handle_existing_user_by_email
* fixes for provisioning SCIMUser
* fixes SCIM provisioning
* test scim v2
* fixes for linting
* fix _apply_patch_ops
* fixes code QA check for team membership checks
* use cost_per_request
* fix cost_per_request
* fixes cost_per_request
* fixes for cost per request for pass through
* ui fix param name
* fixes for _set_cost_per_request
* test cost per request pass through endpoints
* Update tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* tests pass through endpoints
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* feat: add summarize parameter to /spend/logs endpoint for individual transaction logs
- Introduced a new `summarize` parameter to control data format when querying spend logs.
- `summarize=true` (default) returns aggregated data, while `summarize=false` provides individual transaction logs.
- Updated documentation and added tests to validate the new functionality.
* fix: wrap boto3.Session() with tracer for observability - Add tracer.trace wrapper around boto3.Session() call in _get_aws_region_name method - Ensures all boto3 initializations in base_aws_llm.py are properly instrumented - Fixes test_boto3_init_tracer_wrapping test failure - Maintains consistency with other boto3 calls in the same file
* fix(litellm_pre_call_utils.py): add user agent tags to spend logs in standard logging payload logic
avoid clash when tag based routing is enabled
* test: remove redundant test
* test: rename oidc test to run earlier
quicker debuging
* fix(azure.py): return more detailed error message
* fix(azure/common_utils.py): use default scope, if scope is none
fixes oidc test
* fix: always default to cognitiveservices.azure.com
* test: update test
* feat: Add health check functionality and endpoints
- Introduced methods for saving health check results to the database, including validation and cleaning of data.
- Added new health check endpoints to retrieve health check history and latest health statuses for models.
- Updated model prices and context window configuration for new Azure transcription models.
* test: Add unit tests for health check functionality
- Introduced tests for PrismaClient health check methods, including saving results and retrieving health check history.
- Added tests for the _save_health_check_to_db function to ensure proper handling of healthy and unhealthy endpoints.
- Implemented mock objects to simulate database interactions and validate method behaviors.
* Refactor health endpoint model ID handling and improve logging
- Updated health endpoint to use `get_deployment` for retrieving model names based on model IDs, enhancing error handling for missing models.
- Changed health check result saving to the database to be non-blocking by using `asyncio.create_task`.
- Cleaned up code for better readability and maintainability.
* Refactor utility functions in proxy module for improved readability and error handling
- Removed unused imports and simplified exception handling in `_get_redoc_url` and `_get_docs_url` functions to manage circular imports.
- Cleaned up logging statements for consistency and clarity.
- Streamlined error message formatting in `handle_exception_on_proxy` function.
* Enhance type hinting and default values in ProxyUpdateSpend class for improved clarity and robustness
- Added type hints for `_end_user_list_transactions` to specify it as a dictionary mapping end user IDs to spend amounts.
- Updated default values for optional fields in `SpendLogsPayload` to ensure they are initialized properly, enhancing error handling.
- Refactored `_premium_user_check` function to improve model validation logic and error handling.
* Fix disable_spend_updates method to handle None return value gracefully
- Updated the disable_spend_updates method to return False if the environment variable DISABLE_SPEND_UPDATES is not set or is None, improving robustness in configuration handling.
* Refactor join_paths function in utils.py for improved path handling
- Enhanced the join_paths function to better manage leading and trailing slashes, ensuring correct path concatenation.
- Added logic to handle cases where either base_path or route is empty, improving robustness and usability.
* Enhance health check functionality and improve error handling
- Introduced a new method `_save_health_check_to_db` for saving health check results to the database, utilizing safe JSON functions for data integrity.
- Refactored existing health check methods to streamline the process and improve error logging.
- Updated email sending logic to ensure secure connections and better error handling.
- Improved spend update logic with batch processing and retry mechanisms for database operations.
- Added utility functions for projected spend calculations and enhanced validation for team configurations.
* Add health check methods for database interaction
- Introduced `save_health_check_result` method to save health check results with detailed logging and validation.
- Added `get_health_check_history` method for retrieving health check records with optional filtering.
- Implemented `get_all_latest_health_checks` method to fetch the latest health checks for each model.
- Enhanced error handling and logging for all new methods to improve reliability and traceability.
* Refactor health check result saving to use typed arguments
- Updated the `_save_health_check_to_db` function to call `save_health_check_result` with explicitly typed arguments instead of a dictionary spread, enhancing code clarity and type safety.
- Removed unused method bindings in the mock Prisma client tests to streamline the test setup.
* Remove unused `_save_health_check_to_db` function from utils.py to streamline code and improve maintainability.
* Implement response time validation and details cleaning in health check result saving
- Added `_validate_response_time` method to ensure response time values are valid and handle exceptions gracefully.
- Introduced `_clean_details` method to validate and clean details JSON, improving data integrity.
- Refactored `save_health_check_result` to utilize these new methods for optional fields, enhancing code clarity and maintainability.
- Updated tests to bind new methods to the mock Prisma client for comprehensive testing.
* Add health check utility functions and refactor existing endpoints
- Introduced `_convert_health_check_to_dict` to standardize health check record conversion to dictionary format for JSON responses.
- Added `_check_prisma_client` helper function to streamline database availability checks and improve error handling.
- Refactored health check endpoints to utilize the new utility functions, enhancing code clarity and maintainability.
* Refactor health check tests for improved clarity and coverage
- Simplified the mock PrismaClient setup by consolidating method bindings.
- Updated health check result saving tests to use parameterized scenarios for better coverage.
- Added tests for health check history retrieval and graceful handling when no database client is provided.
- Removed redundant mock functions to streamline the test suite.
* Implement helper function for health check and database saving
- Added `_perform_health_check_and_save` to encapsulate health check execution and optional database saving.
- Refactored health endpoint logic to utilize the new helper function, improving code clarity and reducing redundancy.
- Enhanced error handling and streamlined the process of saving health check results to the database.
* refactor: rename target_model parameter to model in health check function
* fix(handle_jwt.py): check user object, if jwt user is proxy admin
correctly return user role - if jwt user has role updated in UI
* test(test_handle_jwt.py): add unit test for passing correct user role
* feat(model_info_view.tsx): separate UI component for updating edit model component
* feat(model_info_view.tsx): allow updating model access group on UI
show all available access groups in ui component
* docs: minor fixes
* feat(ui_sso.py): allow admin to specify additional headers for sso provider
some sso providers require special headers to return a json response
* test(test_ui_sso.py): add unit tests to ensure custom headers are respect3ed
* docs(config_settings.md): document new header param
* fix(litellm_pre_call_utils.py): add spend tag tracking by user agent
allows checking spend for cli tools like claude code
* feat(litellm_pre_call_utils.py): track spend by user agent part if user agent contains "/"
allows tracking spend across user agent versions
Better cost tracking for claude cod
* test(test_litellm_pre_call_utils.py): add testing for pre call utils, user agent parsing
* fix: fix linting check
* feat: Add health check functionality and endpoints
- Introduced methods for saving health check results to the database, including validation and cleaning of data.
- Added new health check endpoints to retrieve health check history and latest health statuses for models.
- Updated model prices and context window configuration for new Azure transcription models.
* test: Add unit tests for health check functionality
- Introduced tests for PrismaClient health check methods, including saving results and retrieving health check history.
- Added tests for the _save_health_check_to_db function to ensure proper handling of healthy and unhealthy endpoints.
- Implemented mock objects to simulate database interactions and validate method behaviors.
* Refactor health endpoint model ID handling and improve logging
- Updated health endpoint to use `get_deployment` for retrieving model names based on model IDs, enhancing error handling for missing models.
- Changed health check result saving to the database to be non-blocking by using `asyncio.create_task`.
- Cleaned up code for better readability and maintainability.
* Refactor utility functions in proxy module for improved readability and error handling
- Removed unused imports and simplified exception handling in `_get_redoc_url` and `_get_docs_url` functions to manage circular imports.
- Cleaned up logging statements for consistency and clarity.
- Streamlined error message formatting in `handle_exception_on_proxy` function.
* Enhance type hinting and default values in ProxyUpdateSpend class for improved clarity and robustness
- Added type hints for `_end_user_list_transactions` to specify it as a dictionary mapping end user IDs to spend amounts.
- Updated default values for optional fields in `SpendLogsPayload` to ensure they are initialized properly, enhancing error handling.
- Refactored `_premium_user_check` function to improve model validation logic and error handling.
* Fix disable_spend_updates method to handle None return value gracefully
- Updated the disable_spend_updates method to return False if the environment variable DISABLE_SPEND_UPDATES is not set or is None, improving robustness in configuration handling.
* Refactor join_paths function in utils.py for improved path handling
- Enhanced the join_paths function to better manage leading and trailing slashes, ensuring correct path concatenation.
- Added logic to handle cases where either base_path or route is empty, improving robustness and usability.
* Enhance health check functionality and improve error handling
- Introduced a new method `_save_health_check_to_db` for saving health check results to the database, utilizing safe JSON functions for data integrity.
- Refactored existing health check methods to streamline the process and improve error logging.
- Updated email sending logic to ensure secure connections and better error handling.
- Improved spend update logic with batch processing and retry mechanisms for database operations.
- Added utility functions for projected spend calculations and enhanced validation for team configurations.
* Add health check methods for database interaction
- Introduced `save_health_check_result` method to save health check results with detailed logging and validation.
- Added `get_health_check_history` method for retrieving health check records with optional filtering.
- Implemented `get_all_latest_health_checks` method to fetch the latest health checks for each model.
- Enhanced error handling and logging for all new methods to improve reliability and traceability.
* Refactor health check result saving to use typed arguments
- Updated the `_save_health_check_to_db` function to call `save_health_check_result` with explicitly typed arguments instead of a dictionary spread, enhancing code clarity and type safety.
- Removed unused method bindings in the mock Prisma client tests to streamline the test setup.
* Remove unused `_save_health_check_to_db` function from utils.py to streamline code and improve maintainability.
* Implement response time validation and details cleaning in health check result saving
- Added `_validate_response_time` method to ensure response time values are valid and handle exceptions gracefully.
- Introduced `_clean_details` method to validate and clean details JSON, improving data integrity.
- Refactored `save_health_check_result` to utilize these new methods for optional fields, enhancing code clarity and maintainability.
- Updated tests to bind new methods to the mock Prisma client for comprehensive testing.
* Add health check utility functions and refactor existing endpoints
- Introduced `_convert_health_check_to_dict` to standardize health check record conversion to dictionary format for JSON responses.
- Added `_check_prisma_client` helper function to streamline database availability checks and improve error handling.
- Refactored health check endpoints to utilize the new utility functions, enhancing code clarity and maintainability.
* Refactor health check tests for improved clarity and coverage
- Simplified the mock PrismaClient setup by consolidating method bindings.
- Updated health check result saving tests to use parameterized scenarios for better coverage.
- Added tests for health check history retrieval and graceful handling when no database client is provided.
- Removed redundant mock functions to streamline the test suite.
* Implement helper function for health check and database saving
- Added `_perform_health_check_and_save` to encapsulate health check execution and optional database saving.
- Refactored health endpoint logic to utilize the new helper function, improving code clarity and reducing redundancy.
- Enhanced error handling and streamlined the process of saving health check results to the database.
* feat(parallel_request_limiter_v3.py): allows admin to enforce token rate limit based on just output tokens
Useful when trying to rate limit for primarily self hosted model use-cases
* test(test_parallel_request_limiter_v3.py): add unit test for token rate limit type
* feat(parallel_request_limiter_v3.py): return remaining token limits in header
* feat: return rate limit headers in response
* feat(parallel_request_limiter_v3.py): working rate limit response headers
* feat(parallel_request_limiter_v3.py): fix rate limit tracking for tpm when rpm also set
* feat(parallel_request_limiter_v3.py): show headers for key/user/team
* feat(parallel_request_limiter_v3.py): decrement max parallel request limiter on failure event
* feat(parallel_request_limiter_v3.py): add in-memory cache implementation of parallel request rate limiter
allows rate limiter to work even without redis cache setup
Work for GA of parallel request limiter v3
* refactor(proxy/hooks/__init__.py): replace with new parallel request handler
* test: update testing
* fix: fix ruff check
* fix: revert ga of multi instance rate limiting - needs more work to pass testing
* fix(internal_user_endpoints.py): support user with `+` in email on user info
ensures user is correctly parsed from input
* fix(factory.py): support vertex function call args as None
handles empty string in args for vertex gemini calls
* docs(langfuse_integration.md): pin langfuse sdk version on docs
* fix(vertex_ai/): return empty dict, instead of none when empty string given
* refactor: reduce function size
* fix: fix linting errors
* fix: revert check
* fix(internal_user_endpoints.py): fix check
* test: update tests
* test: update tests
* docs(deploy.md): move docker recommendation to `main-stable`
* feat(enterprise/internal_user_endpoints.py): expose endpoint for checking available premium users
* feat(usage_indictor.tsx): add new element to help track remaining premium users
* feat(usage_indicator.tsx): show premium user remaining usage
allows users with user caps to know how much is left
* fix(vertex_and_google_ai_studio_gemini.py): bubble up stream is not finished, even if stop reason is given
prevents early completion of stream
Closes https://github.com/BerriAI/litellm/issues/11549
* fix(streaming_handler.py): respect is_finished = False in hidden params
internal logic for preventing ending stream early
* fix(litellm_license.py): add function to check if user is over limit
* fix(internal_user_endpoints.py): add function to check if user is over limit
* refactor: move test
* docs(customer_endpoints.py): document new param
* fix(onboarding_link.tsx): fix adding ui/invitation id
* fix(onboarding_link.tsx): update invitation link function to handle w/ and w/out custom server path cases
* fix(model_checks.py): ensure team only models returned when all proxy models set for team
* refactor: comment out circuit breaker
causes incorrect rate limiting in high traffic
* fix(base_routing_strategy.py): don't reset value if redis val is lower than current in-memory value
Fixes issue where redis might be trailing in-memory value
* fix(parallel_request_limiter_v2.py): if in-memory higher than redis, don't reset value; add previous slot keys to redis increment to correctly 'get' them
* fix(parallel_request_limiter_v3.py): v3 implementation of parallel request limiter
does not use background redis syncing - increments redis in call
simplify rate limiting logic, to improve accuracy
* fix: fix ruff errors
* fix(parallel_request_limiter_v3.py): don't decrement limit on post call success - causes double decrements
* fix(parallel_request_limiter_v3.py): working accurate multi-instance logic
ensured just 100 requests allowed on 100 users, 10 ramp up, 100 rpm limit key, 2 instances
* fix(parallel_request_limiter_v3.py): working accurate rate limiting with time window resets
allows rate limiting to work across multiple windows
* test: add unit tests for v3 rate limiter
* fix(parallel_request_limiter_v3.py): return window value into in-memory cache
allows in-memory cache checks to be used correctly
* refactor(parallel_request_limiter_v3.py): refactor rate limiting to work for multiple window/counter key pairs
enables using for user/team/model rate limiting
* feat(parallel_request_limiter_v3.py): working rate limiting, across key/user/team/end-user
* fix(parallel_request_limiter_v3.py): add model specific rate limiting
* fix(parallel_request_limiter_v3.py): ignore if no rate limits set
skip unecessary rate limit checks - if no limits set
* fix(parallel_request_limiter_v3.py): initial commit bringing token rate limits back
* fix(parallel_request_limiter_v3.py): increment by value in list + update assertions to handle tokens + max parallel requests
* test(parallel_request_limiter_v3.py): more testing
* fix(parallel_request_limiter.py): working in-memory cache limiter
* fix(redis_cache.py): ignore linting error - use safe hasattr
* fix(parallel_request_limiter_v3.py): fix linting error
* refactor: remove redundant parallel_Request_limiter_v2.py
old / inaccurate implementation
* test: update tests
* style: cleanup
* test: update test
* docs(config_settings.md): document new env var
* test(test_base_routing_strategy.py): update test
* Enhance proxy CLI with Rich formatting and improved user experience
- Integrated Rich library for better console output in `proxy_cli.py`, including version display, health check results, and test completion responses.
- Updated health check and test completion methods to provide progress indicators and formatted tables.
- Refactored feedback display in `proxy_server.py` to use Rich for a more visually appealing user interface.
- Adjusted tests in `test_proxy_cli.py` to mock console output instead of using print statements, ensuring compatibility with Rich formatting.
* fix linting error
* refactor(proxy_cli.py): simplify DB setup logging
- Removed progress indicators for IAM token generation and environment variable decryption to simplify the code.
- Consolidated the logic for generating the database URL and setting environment variables.
- Enhanced error handling for configuration loading and database setup, ensuring clearer feedback
* Update test-linting workflow to include proxy-dev dependencies in Poetry installation
* Enhance proxy server initialization with Rich console for improved model display. Added support for loading model parameters from environment variables and refined provider identification logic. Fallback to original print formatting if Rich is not available.
* Refactor feedback handling: Moved feedback message generation and custom warning display to utils.py. Enhanced feedback box with rich formatting and fallback to ASCII for environments without rich. Cleaned up proxy_server.py by removing obsolete code.
* fix linting error
* Refactor model initialization display: Moved model initialization logic to a new utility function `display_model_initialization` for improved readability and maintainability. Enhanced model provider extraction with a dedicated function. Fallback to basic logging if Rich console is unavailable.
* Refactor model provider extraction: Replace the `_extract_provider_from_model` function with a more robust approach using `get_llm_provider`. Implement fallback logic for provider identification and improve error handling. Ensure compatibility with Rich console for model initialization display.
* Refactor get_end_user_id_from_request_body to support user ID retrieval from custom headers and multiple request body formats. Enhance tests to cover various scenarios including header precedence and fallback mechanisms.
* Refactor get_end_user_id_from_request_body function to accept request_body as the first parameter, improving clarity and flexibility. Update tests for compatibility and add new cases to ensure correct functionality across various request body formats.
* Update _user_api_key_auth_builder and user_api_key_auth to pass request object to get_end_user_id_from_request_body, enhancing user ID retrieval from request data.
* refactor(auth_utils.py): update get_end_user_id_from_request_body to accept request_headers instead of request, and adjust related function calls in user_api_key_auth and tests
* refactor(tests): update mock request handling in LLM pass-through endpoint tests
- Replaced the Request object with a Mock for better flexibility in testing.
- Enhanced mock setup to include user API key handling and virtual key retrieval.
- Updated test calls to reflect changes in mock request structure and added necessary patches for new dependencies.
* refactor(vertex_and_google_ai_studio_gemini.py): remove redundant variable declaration for url_context_metadata, linting error
- Renamed SSOSettingsResponse to inherit from a new base class SettingsResponse for better structure.
- Introduced InternalUserSettingsResponse and DefaultTeamSettingsResponse models for internal user and default team settings.
- Updated endpoint responses to use field_schema instead of schema for consistency.
- Enhanced test cases to validate the new response structure and ensure proper functionality of SSO settings.
* fix(ui_sso.py): update user as proxy admin in db table, when checking for proxy_admin_id
Fixes issue where existing internal user, unable to make calls when set as proxy admin id
* fix(utils.py): fix custom base path
* Fixes issue with team_endpoints on member budget update
* refactored location of budget membership fix
* added test for _upsert_budget_membership func
* fix(proxy_server.py): working swagger on custom base
removes the swagger monkey patch - this seems to render the swagger on custom base paths
* fix(ui/): working custom auth uptil login success event
* fix(ui/): working custom server root path for login
* fix(proxy_server.py): create typed dict for ui returned token
allows better documentation of expected params
* refactor(proxy_server.py): refactor all ui login endpoints to use same returned ui token object
* feat(ui_sso.py): add server root path to ui token
* feat(ui_sso.py): allows ui to call correct endpoint
* fix(networking.tsx): update proxy base url with custom root path
* fix(networking.tsx): handle updating proxy base url for non-local instances
* refactor: remove uneccessary references to proxybaseurl in ui code - reduce potential for errors
* fix: fix linting error
* fix(onboarding_link.tsx): fix onboarding link when custom server path is set
* feat(ui_discovery_endpoints.py): add new public .well-known/ route for litellm ui config
returns the server root path and proxy base url for constructing api calls
* feat(_types.py): add litellm well known config as public route
allows ui to query it
* fix(/_types.py): add .well-known config to as public route
* fix(page.tsx): create pattern for loading in ui config before making network requests
ensures requests are formatted correctly
* fix(page.tsx): call credential endpoint once ui config is loaded
* fix(page.tsx): route correctly to litellm dashboard from new user login
* fix(page.tsx): remove hardcoded `/litellm` for /sso/key/generate request
* fix(proxy_server.py): re-add moderations endpoint
* fix(proxy_server.py): mount __next__ at / and /litellm
allows it to work when proxy is mounted on root
* docs(contributing.md): remove /ui on ui doc - it will now run on root
* docs(custom_root_ui.md): add docs on custom root path
* feat(parallel_request_limiter_v2.py): add sliding window logic
allows rate limiting to work across minutes
* fix(parallel_request_limiter_v2.py): decrement usage on rate limit error
* fix(base_routing_strategy.py): fix merge from redis - preserve values in in-memory cache during gap b/w push to redis and read from redis
* fix(base_routing_strategy.py): catch the delta change during redis sync
ensures values are kept in sync
* fix(parallel_request_limiter_v2.py): update tpm tracking to use slot key logic
* fix: fix linting error
* test: update testing
* test: update tests
* test: skip on rate limit or internal server errors
* test: use pytest fixture instead
* test: bump mistral model
Ishaan Jaff