This update integrates mock user API key authentication into the tag management endpoint tests, ensuring accurate simulation of user roles for creating, updating, and deleting tags. The changes enhance the reliability of the tests by properly setting up user authentication before executing test cases.
This update introduces a helper function to create a mock user API key authentication object, which is utilized in the tag management endpoint tests. The mock authentication is integrated into the test cases for creating, updating, and deleting tags, enhancing the reliability of the tests by simulating user roles accurately.
* fix(volcengine): handle thinking disabled parameter properly
When thinking is set to {"type": "disabled"} in volcengine provider config,
skip adding the parameter to extra_body entirely instead of passing it through.
This prevents "thinking: undefined" from appearing in request logs.
Fixes#13039
* test(volcengine): fix and enhance thinking parameter tests
- Fixed existing test that expected broken behavior
- Added comprehensive test coverage for all thinking parameter scenarios:
* thinking disabled → omitted from extra_body
* thinking enabled → included in extra_body
* thinking None → included in extra_body as None
* custom thinking values → included in extra_body
* no thinking parameter → empty result
All tests passing, verifying the fix for issue #13039
- Renamed `AmazonAnthropicClaude3MessagesConfig` to `AmazonAnthropicClaudeMessagesConfig` in the test file to align with recent refactoring.
- Adjusted the instantiation of the configuration class in the test to reflect the new naming convention.
- Updated test cases to use the renamed `AmazonAnthropicClaudeConfig` instead of `AmazonAnthropicClaude3Config` for consistency with recent changes.
- Adjusted imports and assertions in test files to reflect the new configuration class name.
- Renamed `AmazonAnthropicClaude3Config` and `AmazonAnthropicClaude3MessagesConfig` to `AmazonAnthropicClaudeConfig` and `AmazonAnthropicClaudeMessagesConfig` respectively for consistency.
- Implemented `get_anthropic_beta_from_headers` function to extract and handle `anthropic-beta` headers across various transformations.
- Updated request transformations in `AmazonConverseConfig` and `AmazonInvokeConfig` to include `anthropic_beta` parameters based on user headers.
- Added tests to ensure proper handling of `anthropic_beta` headers in different scenarios.
* Remove litellm_params.client_secret from /model/info
Added pop of client_secret (Azure provider secret) from litellm_params in remove_sensitive_info_from_deployment used by /model/info endpoints
* Added test for litellm.proxy.common_utils.openai_endpoint_utils.remove_sensitive_info_from_deployment
* fix(litellm_proxy/chat/transformation.py): support 'user' and all other openai chat completion params
Fixes issue where 'user' was not being sent in request to litellm proxy via sdk
* fix(prisma_migration.py): remove 'use_prisma_migrate' flag, is now default
* docs: cleanup docs
* fix(proxy_cli.py): remove --use_prisma_migrate flag
* refactor: remove references to use_prisma_migrate env var
This is now the default flow for db migrations
* feat: add CometAPI support with config, error handling and tests
* fix: specify type for extra_body in CometAPIConfig
---------
Signed-off-by: NULL <129579691+TensorNull@users.noreply.github.com>
Updated the chunk_parser method to return a ModelResponseStream when handling 'thinking' field content, allowing UIs to render reasoning information. Adjusted tests to verify the new behavior, ensuring that reasoning content is correctly returned in the response.
* fix(router.py): support base model for model group usage
allows model group info to show accurate cost information for azure models
* fix(router.py): fix changes
* test: add unit tests
* build(pyproject.toml): bump openai version requirements
support custom tool from responses api
Closes https://github.com/BerriAI/litellm/issues/13391
* docs(responses_api.md): add verbosity + free-form function calling parameters
* docs(responses_api.md): add cfg + minimal reasoning to docs
Closes https://github.com/BerriAI/litellm/issues/13391
* docs(responses_api.md): add proxy examples to docs
* refactor: fix ruff error
* added mcp guardrails doc in mcp.md
* add button to reload models
* Added button changes
* added button for scheduling reload
* add multi pod support to reloading the model price json
* fix ruff
* feat(proxy/utils.py): track pre-call hooks in OTEL
some pre call hooks can cause latency in high traffic - make sure this is tracked
* fix(router.py): move redis call on deployment_callback_on_success to pipeline operation
reduces p99 latency by half when redis is enabled
* fix(parallel_request_limiter_v3.py): only run check if any item has rate limits set
Prevents unnecessary latency added by rate limit checks
* test: add unit tests
* Latency Improvements: only track tpm/rpm usage when set on deployment+ LLM Caching - use an in-memory cache to reduce redis calls + OTEL - track time spent on LLM caching (#13472)
* fix(router.py): only track usage for deployments with tpm/rpm set
ensures additional latency avoided for non-tpm/rpm models
* fix(caching_handler.py): log time spent on request get cache to OTEL
enables easy debugging of call latency
* fix(caching_handler.py): use dual cache object for in-memory caching + trace redis call within caching handler
* fix(caching_handler.py): working in-memory cache for redis calls
ensures dual cache works when redis cache setup for llm calls
makes calls quicker by only checking redis when in-memory cache missed for llm api call
* test: remove redundant test
* test: add unit tests
