* Update Groq models on model_prices_and_context_window.json
Add support for 6 new models; add deprecations dates to 12 model; and update context-windows/max-tokens for 3 models
* Round model costs to 8 decimal places
* feat(cohere/embed): v2 embed api support
adds output_dimensions param support
* fix(cohere/embed): migrate to v2 embedding
Adds output dimension support
* fix: maintain /v1/embedding compatibility for bedrock cohere
Bedrock cohere is still using /v1 endpoints
* fix: fix linting error
* fix: fix passing extra headers
* test: update tests
* fix(litellm_logging.py): log custom headers in requester metadata
allows passing along custom headers from client to logging integration - e.g. `x-correlation-id`
* refactor: move enterprise code out of OSS package
work towards simplified CE version of docker image
* test: update test
* fix: fix linting error
* add test_function_calling_with_tool_response to base llm tests
* run test suite for nova
* update test_function_calling_with_tool_response
* allowed ToolJsonSchemaBlock keys
* fix ToolJsonSchemaBlock
* add back pytest fixture
* test: test_prompt_caching
* fix: bump: DEFAULT_MAX_RECURSE_DEPTH
* fix: bump: DEFAULT_MAX_RECURSE_DEPTH
* test: test_vertex_ai_complex_response_schema
* fix: allow all constants to be overriden
* fix: allow all numeric constants to be overriden with env vars
* fix: remove dup DEFAULT_MAX_TOKENS in constants.py
* document all constants env vars
* docs - DEFAULT_PROMPT_INJECTION_SIMILARITY_THRESHOLD
* fix(main.py): use base model instead of user model if given
Fixes https://github.com/BerriAI/litellm/issues/10760
* feat(azure/image_generation/__init__.py): make azure image gen check more robust
Fixes https://github.com/BerriAI/litellm/issues/10760
* fix(user_api_key_auth.py): support bearer token auth for `x-litellm-api-key` header
Fixes earlier regression on vertex ai passthrough auth
* fix(user_api_key_auth.py): refactor get api key into separate function
enables easier testing
* fix: cleanup
* fix: fix linting error
* fix: cleanup
* test: update tests
* Add new model provider Novita AI (#7582)
* feat: add new model provider Novita AI
* feat: use deepseek r1 model for examples in Novita AI docs
* fix: fix tests
* fix: fix tests for novita
* fix: fix novita transformation
* ci: fix ci yaml
* fix: fix novita transformation and test (#10056)
---------
Co-authored-by: Jason <ggbbddjm@gmail.com>
* Instead of listing models and pricing, we provide a link to our website. We also highlight our free credits.
* Add all models supported tip to top of NScale README
* add space
---------
Co-authored-by: Oscar Savolainen <oscar.savolainen@enscale.com>
* fix(factory.py): Add reasoning content handling for missing assistant content
* fix(factory.py): Improve handling of thinking blocks for assistant content
* test(factory.py): Add test for Bedrock processing of thinking blocks with None content
* Fixed Json.dumps in JSON Schema Validation Error
* Added Response Schema to Ollama chat for structured response
* Added Test cases
* refactor(ollama): remove redundant response_format check
The response_format parameter conversion is already handled in utils.py's
get_optional_params function, making the duplicate check in ollama_chat.py
unnecessary. This change removes the redundant code while maintaining the
same functionality.
