* litellm_fix_mapped_tests_core: fix test isolation and mock injection issues
## Problem
Four tests in litellm_mapped_tests_core were failing:
1. test_register_model_with_scientific_notation - KeyError due to test isolation issues
2. test_search_uses_registry_credentials - Mock not being called due to incorrect patch path
3. test_send_email_missing_api_key - Real API calls despite mocking
4. test_stream_transformation_error_sync - Mock not effective, real API called
## Solution
### test_register_model_with_scientific_notation
- Use unique model name to avoid conflicts with other tests
- Clear LRU caches before test to prevent stale data
- Clean up model_cost entry after test
### test_search_uses_registry_credentials
- Use patch.object() on the actual base_llm_http_handler instance
- String-based patching for instance methods can fail; direct object patching is more reliable
### test_send_email_missing_api_key
- Directly inject mock HTTP client into logger instance
- This bypasses any caching issues that could cause the fixture mock to be ineffective
### test_stream_transformation_error_sync
- Patch litellm.completion directly instead of the handler module's litellm reference
- This ensures the mock is effective regardless of import order
## Regression
These tests were affected by LRU caching added in #19606 and HTTP client caching.
* fix(test): use patch.object for container API tests to fix mock injection
## Problem
test_retrieve_container_basic tests were failing because mocks weren't
being applied correctly. The tests used string-based patching:
patch('litellm.containers.main.base_llm_http_handler')
But base_llm_http_handler is imported at module level, so the mock wasn't
intercepting the actual handler calls, resulting in real HTTP requests
to OpenAI API.
## Solution
Use patch.object() to directly mock methods on the imported handler
instance. Import base_llm_http_handler in the test file and patch like:
patch.object(base_llm_http_handler, 'container_retrieve_handler', ...)
This ensures the mock is applied to the actual object being used,
regardless of import order or caching.
* fix(test): add missing Prometheus metric labels to test_proxy_failure_metrics
Add client_ip, user_agent, model_id labels to expected metric patterns.
These labels were added in PRs #19717 and #19678 but test wasn't updated.
* fix(test_resend_email): use direct mock injection for all email tests
Extend the mock injection pattern used in test_send_email_missing_api_key
to all other tests in the file:
- test_send_email_success
- test_send_email_multiple_recipients
Instead of relying on fixture-based patching and respx mocks which can
fail due to import order and caching issues, directly inject the mock
HTTP client into the logger instance. This ensures mocks are always used
regardless of test execution order.
* fix(test): use patch.object for image_edit and vector_store tests
- test_image_edit_merges_headers_and_extra_headers: import base_llm_http_handler
and use patch.object instead of string path patching
- test_search_uses_registry_credentials: import module and patch via
module.base_llm_http_handler to ensure we patch the right instance
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Fixes#19225
Add prompt_cache_key and other missing OpenAI Chat Completions params
to DEFAULT_CHAT_COMPLETION_PARAM_VALUES so drop_params: true works.
Also fix additional_drop_params to filter extra params for all providers,
not just OpenAI/Azure.
* fix(anthropic): prevent dropping thinking when any message has thinking_blocks
When Claude returns multiple assistant messages in a conversation, some may
have thinking_blocks while others may not (Claude's behavior varies). The
previous logic only checked the LAST assistant message with tool_calls,
dropping the thinking param if it had no thinking_blocks.
This caused errors when earlier messages still contained thinking_blocks:
"When thinking is disabled, an assistant message cannot contain thinking"
The fix adds a new check: only drop thinking if NO assistant messages
have thinking_blocks. If any message has thinking_blocks, we keep
thinking enabled.
Fixes#18926
* chore: re-trigger CI
* fix: align max_tokens with max_output_tokens for consistency
Fixed inconsistent max_tokens definitions in model_prices_and_context_window.json.
According to LiteLLM convention, max_tokens should equal max_output_tokens when available.
Models fixed:
- deepseek-chat: 131072 → 8192 (now equals max_output_tokens)
- dashscope/qwen-flash: 1000000 → 32768 (now equals max_output_tokens)
- databricks/databricks-gemma-3-12b: 128000 → 32000 (now equals max_output_tokens)
This ensures consistency across all providers where max_tokens represents
the maximum number of tokens that can be generated in the output.
* fix: align max_tokens with max_output_tokens for 244 models
- Fix 244 models where max_tokens != max_output_tokens
- Add test to validate max_tokens consistency and prevent regressions
According to model_prices_and_context_window.json spec:
- max_tokens is a LEGACY parameter
- Should always equal max_output_tokens when both are present
This ensures consistency across all model definitions.
Claude models on Azure AI were incorrectly using AzureAIStudioConfig,
causing tool calls to fail with invalid_request_error because tools
remained in OpenAI format instead of being transformed to Anthropic format.
- Remove 20 deprecated/unavailable Groq models from registry
- Add groq/meta-llama/llama-guard-4-12b (new safety model)
- Add supports_vision to Llama 4 models (maverick, scout)
- Update Groq documentation with current model list
- Clean up test file references to deprecated models
Fixes#18043
Fixes#17821
The `is_cached_message` function crashed with TypeError when message
content was a string instead of a list of content blocks.
Changes:
- Add explicit `isinstance(content, list)` check before iteration
- Add `isinstance(content_item, dict)` check inside loop to skip non-dict items
- Use `.get()` for safer nested dict access
- Follow same pattern as `extract_ttl_from_cached_messages` (same module)
Tests:
- Add TestIsCachedMessage class with 9 test cases covering:
- String content (the reported bug)
- None content
- Missing content key
- Empty list content
- List with/without cache_control
- Mixed content types (strings + dicts)
- Wrong cache_control type
* Fix HostedVLLMRerankConfig will not be used
Signed-off-by: Jun-Fei Cherng <jfcherng@realtek.com>
* Fix no usage statistics in rerank with hosted_vllm
Signed-off-by: Jun-Fei Cherng <jfcherng@realtek.com>
* Revise typo in comment
Signed-off-by: Jun-Fei Cherng <jfcherng@realtek.com>
---------
Signed-off-by: Jun-Fei Cherng <jfcherng@realtek.com>
* Add v1 cut of container api
* fix lint errors
* Add proxy support to container apis & logging support (#16049)
* Add proxy support to container apis
* Add logging support
* Add cost tracking support for containers and documentation
* Add new constant documentation
* Add container cost in model map
* fix failing azure tests
* Update tests based on model map changes
* fix model map tests
* fix model map tests
* Container modeshould be container
* Container tests fix
* Merge branch 'main' into litellm_sameer_oct_staging_2
---------
Co-authored-by: Ishaan Jaffer <ishaanjaffer0324@gmail.com>
* Addd v2/chat support for cohere
* fix streaming
* Use v2_transformation for logging passthrough:
* Use v2_transformation for logging passthrough:
* Add test for checking if document and citation_options is getting passed
* Update the cohere model
* Add cost tracking for vertex ai passthrough batch jobs
* Add full passthrough support
* refactor code according to the comments
* Add passthrough handler
* remove invalid params
* Updated documentation
* Updated documentation
* Updated documentation
* Correct the import
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix documentation for get batch req (#15742)
* Add grounding info to responses API (#15737)
* Add grounding info to responses API
* fix lint errors
* Use typed objects for annotations
* Use typed objects for annotations
* fix mypy error
* Litellm fix json serialize alreting 2 (#15741)
* fix json serializable error for alerts
* Add test
* fix mypt errors
* fix mypt errors
* Add Qwen3 imported model support for AWS Bedrock (#15783)
* Add qwen imported model support
* fix mypy errors
* fix empty user message error (#15784)
* fix typed dict for list
* Add azure supported videos endpoint
* fix mapped tests
* add azure sora models to model map
* Add OpenAI video generation and content retrieval support (#15745)
* Add openai videos generation and retrieval support
* add retrieval endpoint
* Add docs
* Add imports
* remove orjson
* remove double import
* fix openai videos format
* remove mock code
* remove not required comments
* Add tests
* Add tests
* Add other video endpoints
* Fix cost calculation and transformation
* Fixed mypy tests
* remove not used imports
* fix typed dict for list
* fix mypy errors
* move directory
* make v2 chat default
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Fix mypy tests
* Revert "Add Azure Video Generation Support with Sora Integration"
* refactor videos repo
* add test
* Add azure openai videos support
* Add azure openai videos support
* Add router endpoint support for videos
* fix mypy error
* add azure models
* fix mapped test
* fix mypy error
* Add proxy router test
* Add proxy router test
* remove deprecated model name from tests
* fix import error
* fix import error
* Add gaurdrail integration in videos endpoint
* Add logging support for videos endpoint
* Add final documentation supporting videos integration
* fix model name and document input
* Update literals to avoid mypy errors
* Remove unused imports and print statements
* revert guardrail support for video generation and video remix
* revert guardrail support for video generation and video remix
* Fix failing mapped and llm translation tests
* fix: cli auth with SSO okta
* fix: add LITTELM_CLI_SERVICE_ACCOUNT_NAME
* fix: get_litellm_cli_user_api_key_auth
* use existing_key CLI
* fix: use existing key
* test auth commands
* test_cli_sso_callback_regenerate_vs_create_flow
* feat: add CLI Token Utilities
* fix: get_stored_api_key
* move file
* fix: get_valid_models
* fix config.yaml
* TestCLITokenUtils
* TestGetValidModelsWithCLI
* fix: tie user id to keys created through CLI
* fix: add teams interface to CLI
* add /keys/update to the list client commands
* fix /sso/cli/poll to return the user_id
* fix: working TeamsManagementClient
* fix CLI Login command
* fixes for auth
* Potential fix for code scanning alert no. 3400: Clear-text logging of sensitive information
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
* ruff fix
---------
Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>
- Implemented VolcEngineEmbeddingHandler for synchronous and asynchronous embedding requests.
- Created VolcEngineEmbeddingConfig for transforming requests and responses to/from Volcengine format.
- Added integration tests for embedding functionality, covering various scenarios including error handling and parameter validation.
- Established test structure for Volcengine embedding, ensuring compliance with LiteLLM testing patterns.
- Included comprehensive tests for parameter mapping, request transformation, and response handling.
Sameer Kankute