* 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
* 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
* 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
* fix(factory.py): ensure tool call converts image url
Fixes https://github.com/BerriAI/litellm/issues/6953
* fix(transformation.py): support mp4 + pdf url's for vertex ai
Fixes https://github.com/BerriAI/litellm/issues/6936
* fix(http_handler.py): mask gemini api key in error logs
Fixes https://github.com/BerriAI/litellm/issues/6963
* docs(prometheus.md): update prometheus FAQs
* feat(auth_checks.py): ensure specific model access > wildcard model access
if wildcard model is in access group, but specific model is not - deny access
* fix(auth_checks.py): handle auth checks for team based model access groups
handles scenario where model access group used for wildcard models
* fix(internal_user_endpoints.py): support adding guardrails on `/user/update`
Fixes https://github.com/BerriAI/litellm/issues/6942
* fix(key_management_endpoints.py): fix prepare_metadata_fields helper
* fix: fix tests
* build(requirements.txt): bump openai dep version
fixes proxies argument
* test: fix tests
* fix(http_handler.py): fix error message masking
* fix(bedrock_guardrails.py): pass in prepped data
* test: fix test
* test: fix nvidia nim test
* fix(http_handler.py): return original response headers
* fix: revert maskedhttpstatuserror
* test: update tests
* test: cleanup test
* fix(key_management_endpoints.py): fix metadata field update logic
* fix(key_management_endpoints.py): maintain initial order of guardrails in key update
* fix(key_management_endpoints.py): handle prepare metadata
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting errors
* fix: fix key management errors
* fix(key_management_endpoints.py): update metadata
* test: update test
* refactor: add more debug statements
* test: skip flaky test
* test: fix test
* fix: fix test
* fix: fix update metadata logic
* fix: fix test
* ci(config.yml): change db url for e2e ui testing
* 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>
* nvidia nim support embedding config
* add nvidia config in init
* nvidia nim embeddings
* docs nvidia nim embeddings
* docs embeddings on nvidia nim
* fix llm translation test
* add max_completion_tokens
* add max_completion_tokens
* add max_completion_tokens support for OpenAI models
* add max_completion_tokens param
* add max_completion_tokens for bedrock converse models
* add test for converse maxTokens
* fix openai o1 param mapping test
* move test optional params
* add max_completion_tokens for anthropic api
* fix conftest
* add max_completion tokens for vertex ai partner models
* add max_completion_tokens for fireworks ai
* add max_completion_tokens for hf rest api
* add test for param mapping
* add param mapping for vertex, gemini + testing
* predibase is the most unstable and unusable llm api in prod, can't handle our ci/cd
* add max_completion_tokens to openai supported params
* fix fireworks ai param mapping
