* fix(__init__.py): fix init to exclude pricing-only model cost values from real model names
prevents bad health checks on wildcard routes
* fix(get_llm_provider.py): fix to handle calling bedrock_converse models
* feat(cost_calculator.py): add cost tracking ($0) for openai moderations endpoint
removes sentry cost tracking errors caused by this
* build(teams.tsx): allow assigning teams to orgs
* 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
* 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(utils.py): fix openai-like api response format parsing
Fixes issue passing structured output to litellm_proxy/ route
* fix(cost_calculator.py): fix whisper transcription cost calc to use file duration, not response time
'
* test: skip test if credentials not found
* fix(main.py): fix retries being multiplied when using openai sdk
Closes https://github.com/BerriAI/litellm/pull/7130
* docs(prompt_management.md): add langfuse prompt management doc
* feat(team_endpoints.py): allow teams to add their own models
Enables teams to call their own finetuned models via the proxy
* test: add better enforcement check testing for `/model/new` now that teams can add their own models
* docs(team_model_add.md): tutorial for allowing teams to add their own models
* test: fix test
* feat(customer_endpoints.py): support passing budget duration via `/customer/new` endpoint
Closes https://github.com/BerriAI/litellm/issues/5651
* docs: add missing params to swagger + api documentation test
* docs: add documentation for all key endpoints
documents all params on swagger
* docs(internal_user_endpoints.py): document all /user/new params
Ensures all params are documented
* docs(team_endpoints.py): add missing documentation for team endpoints
Ensures 100% param documentation on swagger
* docs(organization_endpoints.py): document all org params
Adds documentation for all params in org endpoint
* docs(customer_endpoints.py): add coverage for all params on /customer endpoints
ensures all /customer/* params are documented
* ci(config.yml): add endpoint doc testing to ci/cd
* fix: fix internal_user_endpoints.py
* fix(internal_user_endpoints.py): support 'duration' param
* fix(partner_models/main.py): fix anthropic re-raise exception on vertex
* fix: fix pydantic obj
* build(model_prices_and_context_window.json): add new vertex claude model names
vertex claude changed model names - causes cost tracking errors
* fix(utils.py): add 'disallowed_special' for token counting on .encode()
Fixes error when '<
endoftext
>' in string
* Revert "(fix) standard logging metadata + add unit testing (#6366)" (#6381)
This reverts commit 8359cb6fa9.
* add new 35 mode lcard (#6378)
* Add claude 3 5 sonnet 20241022 models for all provides (#6380)
* Add Claude 3.5 v2 on Amazon Bedrock and Vertex AI.
* added anthropic/claude-3-5-sonnet-20241022
* add new 35 mode lcard
---------
Co-authored-by: Paul Gauthier <paul@paulg.com>
Co-authored-by: lowjiansheng <15527690+lowjiansheng@users.noreply.github.com>
* test(skip-flaky-google-context-caching-test): google is not reliable. their sample code is also not working
* Fix metadata being overwritten in speech() (#6295)
* fix: adding missing redis cluster kwargs (#6318)
Co-authored-by: Ali Arian <ali.arian@breadfinancial.com>
* Add support for `max_completion_tokens` in Azure OpenAI (#6376)
Now that Azure supports `max_completion_tokens`, no need for special handling for this param and let it pass thru. More details: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models?tabs=python-secure#api-support
* build(model_prices_and_context_window.json): add voyage-finance-2 pricing
Closes https://github.com/BerriAI/litellm/issues/6371
* build(model_prices_and_context_window.json): fix llama3.1 pricing model name on map
Closes https://github.com/BerriAI/litellm/issues/6310
* feat(realtime_streaming.py): just log specific events
Closes https://github.com/BerriAI/litellm/issues/6267
* fix(utils.py): more robust checking if unmapped vertex anthropic model belongs to that family of models
Fixes https://github.com/BerriAI/litellm/issues/6383
* Fix Ollama stream handling for tool calls with None content (#6155)
* test(test_max_completions): update test now that azure supports 'max_completion_tokens'
* fix(handler.py): fix linting error
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Low Jian Sheng <15527690+lowjiansheng@users.noreply.github.com>
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
Co-authored-by: Paul Gauthier <paul@paulg.com>
Co-authored-by: John HU <hszqqq12@gmail.com>
Co-authored-by: Ali Arian <113945203+ali-arian@users.noreply.github.com>
Co-authored-by: Ali Arian <ali.arian@breadfinancial.com>
Co-authored-by: Anand Taralika <46954145+taralika@users.noreply.github.com>
Co-authored-by: Nolan Tremelling <34580718+NolanTrem@users.noreply.github.com>
