* fix(utils.py): default custom_llm_provider=None for 'supports_response_schema'
Closes https://github.com/BerriAI/litellm/issues/7397
* refactor(langfuse/): call langfuse logger inside customlogger compatible langfuse class, refactor langfuse logger to use verbose_logger.debug instead of print_verbose
* refactor(litellm_pre_call_utils.py): move config based team callbacks inside dynamic team callback logic
enables simpler unit testing for config-based team callbacks
* fix(proxy/_types.py): handle teamcallbackmetadata - none values
drop none values if present. if all none, use default dict to avoid downstream errors
* test(test_proxy_utils.py): add unit test preventing future issues - asserts team_id in config state not popped off across calls
Fixes https://github.com/BerriAI/litellm/issues/6787
* fix(langfuse_prompt_management.py): add success + failure logging event support
* fix: fix linting error
* test: fix test
* test: fix test
* test: override o1 prompt caching - openai currently not working
* test: fix test
* run azure testing on ci/cd
* update docs on azure batches endpoints
* add input azure.jsonl
* refactor - use separate file for batches endpoints
* fixes for passing custom llm provider to /batch endpoints
* pass custom llm provider to files endpoints
* update azure batches doc
* add info for azure batches api
* update batches endpoints
* use simple helper for raising proxy exception
* update config.yml
* fix imports
* add type hints to get_litellm_params
* update get_litellm_params
* update get_litellm_params
* update get slp
* QOL - stop double logging a create batch operations on custom loggers
* re use slp from og event
* _create_standard_logging_object_for_completed_batch
* fix linting errors
* reduce num changes in PR
* update BATCH_STATUS_POLL_MAX_ATTEMPTS
* fix(prometheus.py): support streaming end user litellm_proxy_total_requests_metric tracking
* fix(prometheus.py): add 'requested_model' and 'end_user_id' to 'litellm_request_total_latency_metric_bucket'
enables latency tracking by end user + requested model
* fix(prometheus.py): add end user, user and requested model metrics to 'litellm_llm_api_latency_metric'
* test: update prometheus unit tests
* test(test_prometheus.py): update tests
* test(test_prometheus.py): fix test
* test: reorder test
* build(model_prices_and_context_window.json): add gemini-1.5-flash context caching
* fix(context_caching/transformation.py): just use last identified cache point
Fixes https://github.com/BerriAI/litellm/issues/6738
* fix(context_caching/transformation.py): pick first contiguous block - handles system message error from google
Fixes https://github.com/BerriAI/litellm/issues/6738
* fix(vertex_ai/gemini/): track context caching tokens
* refactor(gemini/): place transformation.py inside `chat/` folder
make it easy for user to know we support the equivalent endpoint
* fix: fix import
* refactor(vertex_ai/): move vertex_ai cost calc inside vertex_ai/ folder
make it easier to see cost calculation logic
* fix: fix linting errors
* fix: fix circular import
* feat(gemini/cost_calculator.py): support gemini context caching cost calculation
generifies anthropic's cost calculation function and uses it across anthropic + gemini
* build(model_prices_and_context_window.json): add cost tracking for gemini-1.5-flash-002 w/ context caching
Closes https://github.com/BerriAI/litellm/issues/6891
* docs(gemini.md): add gemini context caching architecture diagram
make it easier for user to understand how context caching works
* docs(gemini.md): link to relevant gemini context caching code
* docs(gemini/context_caching): add readme in github, make it easy for dev to know context caching is supported + where to go for code
* fix(llm_cost_calc/utils.py): handle gemini 128k token diff cost calc scenario
* fix(deepseek/cost_calculator.py): support deepseek context caching cost calculation
* test: fix test
* feat(guardrails_endpoint.py): new `/guardrails/list` endpoint
Allow users to view what the available guardrails are
* docs: document new `/guardrails/list` endpoint
* docs(enterprise.md): update docs
* fix(openai/transcription/handler.py): support cost tracking on vtt + srt formats
* fix(openai/transcriptions/handler.py): default to 'verbose_json' response format if 'text' or 'json' response_format received. ensures 'duration' param is received for all audio transcription requests
* fix: fix linting errors
* fix: remove unused import
* fix(proxy_track_cost_callback.py): log to db if only end user param given
* fix: allows for jwt-auth based end user id spend tracking to work
* fix(utils.py): fix 'get_end_user_id_for_cost_tracking' to use 'user_api_key_end_user_id'
more stable - works with jwt-auth based end user tracking as well
* test(test_jwt.py): add e2e unit test to confirm end user cost tracking works for spend logs
* test: update test to use end_user api key hash param
* fix(langfuse.py): support end user cost tracking via jwt auth + langfuse
logs end user to langfuse if decoded from jwt token
* fix: fix linting errors
* test: fix test
* test: fix test
* fix: fix end user id extraction
* fix: run test earlier
* fix(openai.py): fix returning o1 non-streaming requests
fixes issue where fake stream always true for o1
* build(model_prices_and_context_window.json): add 'supports_vision' for o1 models
* fix: add internal server error exception mapping
* fix(base_llm_unit_tests.py): drop temperature from test
* test: mark prompt caching as a flaky test
* fix(health.md): add rerank model health check information
* build(model_prices_and_context_window.json): add gemini 2.0 for google ai studio - pricing + commercial rate limits
* build(model_prices_and_context_window.json): add gemini-2.0 supports audio output = true
* docs(team_model_add.md): clarify allowing teams to add models is an enterprise feature
* fix(o1_transformation.py): add support for 'n', 'response_format' and 'stop' params for o1 and 'stream_options' param for o1-mini
* build(model_prices_and_context_window.json): add 'supports_system_message' to supporting openai models
needed as o1-preview, and o1-mini models don't support 'system message
* fix(o1_transformation.py): translate system message based on if o1 model supports it
* fix(o1_transformation.py): return 'stream' param support if o1-mini/o1-preview
o1 currently doesn't support streaming, but the other model versions do
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix(o1_transformation.py): return tool calling/response_format in supported params if model map says so
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix: fix linting errors
* fix: update '_transform_messages'
* fix(o1_transformation.py): fix provider passed for supported param checks
* test(base_llm_unit_tests.py): skip test if api takes >5s to respond
* fix(utils.py): return false in 'supports_factory' if can't find value
* fix(o1_transformation.py): always return stream + stream_options as supported params + handle stream options being passed in for azure o1
* feat(openai.py): support stream faking natively in openai handler
Allows o1 calls to be faked for just the "o1" model, allows native streaming for o1-mini, o1-preview
Fixes https://github.com/BerriAI/litellm/issues/7292
* fix(openai.py): use inference param instead of original optional param
* fix(factory.py): skip empty text blocks for bedrock user messages
Fixes https://github.com/BerriAI/litellm/issues/7169
* Add support for Gemini 2.0 GoogleSearch tool (#7257)
* Add support for google_search tool in gemini 2.0
* Add/modify tests
* Fix grounding check
* Remove 2.0 grounding test; exclude experimental model in VERTEX_MODELS_TO_NOT_TEST
* Swap order of tools
* DFix formatting
* fix(get_api_base.py): return api base in streaming response
Fixes https://github.com/BerriAI/litellm/issues/7249
Closes https://github.com/BerriAI/litellm/pull/7250
* fix(cost_calculator.py): only set base model to model if not none
Fixes https://github.com/BerriAI/litellm/issues/7223
* fix(cost_calculator.py): enforce stricter order when picking model for cost calculation
* fix(cost_calculator.py): fix '_select_model_name_for_cost_calc' to return model name with region name prefix if provided
* fix(utils.py): fix 'get_model_info()' to handle edge case where model name starts with custom llm provider AND custom llm provider is given
* fix(cost_calculator.py): handle `custom_llm_provider-` scenario
* fix(cost_calculator.py): e2e working tts cost tracking
ensures initial message is passed in, to cost calculator
* fix(factory.py): suppress linting errors
* fix(cost_calculator.py): strip llm provider from model name after selecting cost calc model
* fix(litellm_logging.py): store initial request in 'input' field + accept base_model to be passed in litellm_params directly
* test: handle none env var value in flaky test
* fix(litellm_logging.py): fix linting errors
---------
Co-authored-by: Sam B <samlingx@gmail.com>
* fix(litellm_logging.py): pass user metadata to langsmith on sdk calls
* fix(litellm_logging.py): pass nested user metadata to logging integration - e.g. langsmith
* fix(exception_mapping_utils.py): catch and clarify watsonx `/text/chat` endpoint not supported error message.
Closes https://github.com/BerriAI/litellm/issues/7213
* fix(watsonx/common_utils.py): accept new 'WATSONX_IAM_URL' env var
allows user to use local watsonx
Fixes https://github.com/BerriAI/litellm/issues/4991
* fix(litellm_logging.py): cleanup unused function
* test: skip bad ibm test
* feat(bedrock/): add bedrock converse top k param
Closes https://github.com/BerriAI/litellm/issues/7087
* Fix bedrock empty content error (#7177)
* add resolver
* handle empty content on bedrock with default content
* use existing default message, tests
* Update tests/llm_translation/test_bedrock_completion.py
* fix tests
* Revert "add resolver"
This reverts commit c717e376ee.
* fallback to empty
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* fix(factory.py): handle empty content blocks in messages
Fixes https://github.com/BerriAI/litellm/issues/7169
* feat(router.py): add stripped model check to model fallback search
if model_name="openai/gpt-3.5-turbo" and fallback=[{"gpt-3.5-turbo"..}] the fallback should just work as expected
* fix: fix linting error
* fix(factory.py): fix linting error
* fix(factory.py): in base case still support skip empty text blocks
---------
Co-authored-by: Engel Nyst <enyst@users.noreply.github.com>
* fix(acompletion): support fallbacks on acompletion
allows health checks for wildcard routes to use fallback models
* test: update cohere generate api testing
* add max tokens to health check (#7000)
* fix: fix health check test
* test: update testing
---------
Co-authored-by: Cameron <561860+wallies@users.noreply.github.com>
* refactor(fireworks_ai/): inherit from openai like base config
refactors fireworks ai to use a common config
* test: fix import in test
* refactor(watsonx/): refactor watsonx to use llm base config
refactors chat + completion routes to base config path
* fix: fix linting error
* test: fix test
* fix: fix test
* fix use new format for Cohere config
* fix base llm http handler
* Litellm code qa common config (#7116)
* feat(base_llm): initial commit for common base config class
Addresses code qa critique https://github.com/andrewyng/aisuite/issues/113#issuecomment-2512369132
* feat(base_llm/): add transform request/response abstract methods to base config class
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* use base transform helpers
* use base_llm_http_handler for cohere
* working cohere using base llm handler
* add async cohere chat completion support on base handler
* fix completion code
* working sync cohere stream
* add async support cohere_chat
* fix types get_model_response_iterator
* async / sync tests cohere
* feat cohere using base llm class
* fix linting errors
* fix _abc error
* add cohere params to transformation
* remove old cohere file
* fix type error
* fix merge conflicts
* fix cohere merge conflicts
* fix linting error
* fix litellm.llms.custom_httpx.http_handler.HTTPHandler.post
* fix passing cohere specific params
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* feat(base_llm): initial commit for common base config class
Addresses code qa critique https://github.com/andrewyng/aisuite/issues/113#issuecomment-2512369132
* feat(base_llm/): add transform request/response abstract methods to base config class
* feat(cohere-+-clarifai): refactor integrations to use common base config class
* fix: fix linting errors
* refactor(anthropic/): move anthropic + vertex anthropic to use base config
* test: fix xai test
* test: fix tests
* fix: fix linting errors
* test: comment out WIP test
* fix(transformation.py): fix is pdf used check
* fix: fix linting error
* feat(langfuse/): support langfuse prompt management
Initial working commit for langfuse prompt management support
Closes https://github.com/BerriAI/litellm/issues/6269
* test: update test
* fix(litellm_logging.py): suppress linting error
* fix(edit_budget_modal.tsx): call `/budget/update` endpoint instead of `/budget/new`
allows updating existing budget on ui
* fix(user_api_key_auth.py): support cost tracking for end user via jwt field
* fix(presidio.py): support pii masking on sync logging callbacks
enables masking before logging to langfuse
* feat(utils.py): support retry policy logic inside '.completion()'
Fixes https://github.com/BerriAI/litellm/issues/6623
* fix(utils.py): support retry by retry policy on async logic as well
* fix(handle_jwt.py): set leeway default leeway value
* test: fix test to handle jwt audience claim
* fix(cost_calculator.py): move to using `.get_model_info()` for cost per token calculations
ensures cost tracking is reliable - handles edge cases of parsing model cost map
* build(model_prices_and_context_window.json): add 'supports_response_schema' for select tgai models
Fixes https://github.com/BerriAI/litellm/pull/7037#discussion_r1872157329
* build(model_prices_and_context_window.json): remove 'pdf input' and 'vision' support from nova micro in model map
Bedrock docs indicate no support for micro - https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-supported-models-features.html
* fix(converse_transformation.py): support amazon nova tool use
* fix(opentelemetry): Add missing LLM request type attribute to spans (#7041)
* feat(opentelemetry): add LLM request type attribute to spans
* lint
* fix: curl usage (#7038)
curl -d, --data <data> is lowercase d
curl -D, --dump-header <filename> is uppercase D
references:
https://curl.se/docs/manpage.html#-dhttps://curl.se/docs/manpage.html#-D
* fix(spend_tracking.py): handle empty 'id' in model response - when creating spend log
Fixes https://github.com/BerriAI/litellm/issues/7023
* fix(streaming_chunk_builder.py): handle initial id being empty string
Fixes https://github.com/BerriAI/litellm/issues/7023
* fix(anthropic_passthrough_logging_handler.py): add end user cost tracking for anthropic pass through endpoint
* docs(pass_through/): refactor docs location + add table on supported features for pass through endpoints
* feat(anthropic_passthrough_logging_handler.py): support end user cost tracking via anthropic sdk
* docs(anthropic_completion.md): add docs on passing end user param for cost tracking on anthropic sdk
* fix(litellm_logging.py): use standard logging payload if present in kwargs
prevent datadog logging error for pass through endpoints
* docs(bedrock.md): add rerank api usage example to docs
* bugfix/change dummy tool name format (#7053)
* fix viewing keys (#7042)
* ui new build
* build(model_prices_and_context_window.json): add bedrock region models to model cost map (#7044)
* bye (#6982)
* (fix) litellm router.aspeech (#6962)
* doc Migrating Databases
* fix aspeech on router
* test_audio_speech_router
* test_audio_speech_router
* docs show supported providers on batches api doc
* change dummy tool name format
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
Co-authored-by: yujonglee <yujonglee.dev@gmail.com>
* fix: fix linting errors
* test: update test
* fix(litellm_logging.py): fix pass through check
* fix(test_otel_logging.py): fix test
* fix(cost_calculator.py): update handling for cost per second
* fix(cost_calculator.py): fix cost check
* test: fix test
* (fix) adding public routes when using custom header (#7045)
* get_api_key_from_custom_header
* add test_get_api_key_from_custom_header
* fix testing use 1 file for test user api key auth
* fix test user api key auth
* test_custom_api_key_header_name
* build: update ui build
---------
Co-authored-by: Doron Kopit <83537683+doronkopit5@users.noreply.github.com>
Co-authored-by: lloydchang <lloydchang@gmail.com>
Co-authored-by: hgulersen <haymigulersen@gmail.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: yujonglee <yujonglee.dev@gmail.com>
* fix(key_management_endpoints.py): override metadata field value on update
allow user to override tags
* feat(__init__.py): expose new disable_end_user_cost_tracking_prometheus_only metric
allow disabling end user cost tracking on prometheus - fixes cardinality issue
* fix(litellm_pre_call_utils.py): add key/team level enforced params
Fixes https://github.com/BerriAI/litellm/issues/6652
* fix(key_management_endpoints.py): allow user to pass in `enforced_params` as a top level param on /key/generate and /key/update
* docs(enterprise.md): add docs on enforcing required params for llm requests
* Add support of Galadriel API (#7005)
* fix(router.py): robust retry after handling
set retry after time to 0 if >0 healthy deployments. handle base case = 1 deployment
* test(test_router.py): fix test
* feat(bedrock/): add support for 'nova' models
also adds explicit 'converse/' route for simpler routing
* fix: fix 'supports_pdf_input'
return if model supports pdf input on get_model_info
* feat(converse_transformation.py): support bedrock pdf input
* docs(document_understanding.md): add document understanding to docs
* fix(litellm_pre_call_utils.py): fix linting error
* fix(init.py): fix passing of bedrock converse models
* feat(bedrock/converse): support 'response_format={"type": "json_object"}'
* fix(converse_handler.py): fix linting error
* fix(base_llm_unit_tests.py): fix test
* fix: fix test
* test: fix test
* test: fix test
* test: remove duplicate test
---------
Co-authored-by: h4n0 <4738254+h4n0@users.noreply.github.com>
