* build: ensure all regional bedrock models have same supported values as base bedrock model
prevents drift
* test(base_llm_unit_tests.py): add testing for nested pydantic objects
* fix(test_utils.py): add test_get_potential_model_names
* fix(anthropic/chat/transformation.py): support nested pydantic objects
Fixes https://github.com/BerriAI/litellm/issues/7755
* test: initial commit enforcing testing on all anthropic pass through functions
prevents future regressions
* test(test_unit_test_anthropic_pass_through.py): add unit test for '_get_user_from_metadata' function
* test(test_unit_test_anthropic_passthrough.py): add unit test for handle_logging_anthropic_collected_chunks
* test(test_unit_test_anthropic_pass_through): add coverage for all anthropic pass through functions
* test: initial test to enforce all functions in user_api_key_auth.py have direct testing
* test(test_user_api_key_auth.py): add is_allowed_route unit test
* test(test_user_api_key_auth.py): add more tests
* test(test_user_api_key_auth.py): add complete testing coverage for all functions in `user_api_key_auth.py`
* test(test_db_schema_changes.py): add a unit test to ensure all db schema changes are backwards compatible
gives user an easy rollback path
* test: fix schema compatibility test filepath
* test: fix test
* feat(pass_through_endpoints.py): fix anthropic end user cost tracking
* fix(anthropic/chat/transformation.py): use returned provider model for anthropic
handles anthropic `-latest` tag in request body throwing cost calculation errors
ensures we can be accurate in our model cost tracking
* feat(model_prices_and_context_window.json): add gemini-2.0-flash-thinking-exp pricing
* test: update test to use assumption that user_api_key_dict can get anthropic user id
* test: fix test
* fix: fix test
* fix(anthropic_pass_through.py): uncomment previous anthropic end-user cost tracking code block
can't guarantee user api key dict always has end user id - too many code paths
* fix(user_api_key_auth.py): this allows end user id from request body to always be read and set in auth object
* fix(auth_check.py): fix linting error
* test: fix auth check
* fix(auth_utils.py): fix get end user id to handle metadata = None
* fix(gemini/): support gemini 'frequency_penalty' and 'presence_penalty'
Closes https://github.com/BerriAI/litellm/issues/7748
* feat(proxy_server.py): new env var to disable prisma health check on startup
* test: fix test
* fix base aws llm
* fix auth with aws role
* test aws base llm
* fix base aws llm init
* run ci/cd again
* fix get_credentials
* ci/cd run again
* _auth_with_aws_role
* fix(factory.py): fix bedrock document url check
Make check more generic - if starts with 'text' or 'application' assume it's a document and let it go through
Fixes https://github.com/BerriAI/litellm/issues/7746
* feat(key_management_endpoints.py): support writing new key alias to aws secret manager - on key rotation
adds rotation endpoint to aws key management hook - allows for rotated litellm virtual keys with new key alias to be written to it
* feat(key_management_event_hooks.py): support rotating keys and updating secret manager
* refactor(base_secret_manager.py): support rotate secret at the base level
since it's just an abstraction function, it's easy to implement at the base manager level
* style: cleanup unused imports
* fix(gpt_transformation.py): fix response_format translation check for 4o models
Fixes https://github.com/BerriAI/litellm/issues/7616
* feat(key_management_endpoints.py): support 'temp_budget_increase' and 'temp_budget_expiry' fields
Allow proxy admin to grant temporary budget increases to keys
* fix(proxy/_types.py): enforce temp_budget_increase and temp_budget_expiry are always passed together
* feat(user_api_key_auth.py): initial working temp budget increase logic
ensures key budget exceeded error checks for temp budget in key metadata
* feat(proxy_server.py): return the key max budget and key spend in the response headers
Allows clientside user to know their remaining limits
* test: add unit testing for new proxy utils
Ensures new key budget is correctly handled
* docs(temporary_budget_increase.md): add doc on temporary budget increase
* fix(utils.py): remove 3.5 from response_format check for now
not all azure 3.5 models support response_format
* fix(user_api_key_auth.py): return valid user api key auth object on all paths
* build(model_prices_and_context_window.json): add azure o1 pricing
Closes https://github.com/BerriAI/litellm/issues/7712
* refactor: replace regex with string method for whitespace check in stop-sequences handling (#7713)
* Allows overriding keep_alive time in ollama (#7079)
* Allows overriding keep_alive time in ollama
* Also adds to ollama_chat
* Adds some info on the docs about this parameter
* fix: together ai warning (#7688)
Co-authored-by: Carl Senze <carl.senze@aleph-alpha.com>
* fix(proxy_server.py): handle config containing thread locked objects when using get_config_state
* fix(proxy_server.py): add exception to debug
* build(model_prices_and_context_window.json): update 'supports_vision' for azure o1
---------
Co-authored-by: Wolfram Ravenwolf <52386626+WolframRavenwolf@users.noreply.github.com>
Co-authored-by: Regis David Souza Mesquita <github@rdsm.dev>
Co-authored-by: Carl <45709281+capsenz@users.noreply.github.com>
Co-authored-by: Carl Senze <carl.senze@aleph-alpha.com>
* 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(langfuse.py): log the used prompt when prompt management used
* test: fix test
* docs(self_serve.md): add doc on restricting personal key creation on ui
* feat(s3.py): support s3 logging with team alias prefixes (if available)
New preview feature
* fix(main.py): remove old if block - simplify to just await if coroutine returned
fixes lm_studio async embedding error
* fix(langfuse.py): handle get prompt check
* test(test_basic_python_version.py): assert all optional dependencies are marked as extras on poetry
Fixes https://github.com/BerriAI/litellm/issues/7677
* docs(secret.md): clarify 'read_and_write' secret manager usage on aws
* docs(secret.md): fix doc
* build(ui/teams.tsx): add edit/delete button for updating user / team membership on ui
allows updating user role to admin on ui
* build(ui/teams.tsx): display edit member component on ui, when edit button on member clicked
* feat(team_endpoints.py): support updating team member role to admin via api endpoints
allows team member to become admin post-add
* build(ui/user_dashboard.tsx): if team admin - show all team keys
Fixes https://github.com/BerriAI/litellm/issues/7650
* test(config.yml): add tomli to ci/cd
* test: don't call python_basic_testing in local testing (covered by python 3.13 testing)
* test(test_get_model_info.py): add unit test confirming router deployment updates global 'get_model_info'
* fix(get_supported_openai_params.py): fix custom llm provider 'get_supported_openai_params'
Fixes https://github.com/BerriAI/litellm/issues/7668
* docs(azure.md): clarify how azure ad token refresh on proxy works
Closes https://github.com/BerriAI/litellm/issues/7665
* fix(vertex_ai/gemini/transformation.py): handle 'http://' in gemini process url
* refactor(router.py): refactor '_prompt_management_factory' to use logging obj get_chat_completion logic
deduplicates code
* fix(litellm_logging.py): update 'get_chat_completion_prompt' to update logging object messages
* docs(prompt_management.md): update prompt management to be in beta
given feedback - this still needs to be revised (e.g. passing in user message, not ignoring)
* refactor(prompt_management_base.py): introduce base class for prompt management
allows consistent behaviour across prompt management integrations
* feat(prompt_management_base.py): support adding client message to template message + refactor langfuse prompt management to use prompt management base
* fix(litellm_logging.py): log prompt id + prompt variables to langfuse if set
allows tracking what prompt was used for what purpose
* feat(litellm_logging.py): log prompt management metadata in standard logging payload + use in langfuse
allows logging prompt id / prompt variables to langfuse
* test: fix test
* fix(router.py): cleanup unused imports
* fix: fix linting error
* fix: fix trace param typing
* fix: fix linting errors
* fix: fix code qa check
* fix(main.py): fix lm_studio/ embedding routing
adds the mapping + updates docs with example
* docs(self_serve.md): update doc to show how to auto-add sso users to teams
* fix(streaming_handler.py): simplify async iterator check, to just check if streaming response is an async iterable
* feat(ui_sso.py): support reading team ids from sso token
* feat(ui_sso.py): working upsert sso user teams membership in litellm - if team exists
Adds user to relevant teams, if user is part of teams and team exists on litellm
* fix(ui_sso.py): safely handle add team member task
* build(ui/): support setting team id when creating team on UI
* build(ui/): teams.tsx
allow setting team id on ui
* build(circle_ci/requirements.txt): add fastapi-sso to ci/cd testing
* fix: fix linting errors
* fix(streaming_chunk_builder_utils.py): add test for groq tool calling + streaming + combine chunks
Addresses https://github.com/BerriAI/litellm/issues/7621
* fix(streaming_utils.py): fix modelresponseiterator for openai like chunk parser
ensures chunk parser uses the correct tool call id when translating the chunk
Fixes https://github.com/BerriAI/litellm/issues/7621
* build(model_hub.tsx): display cost pricing on model hub
* build(model_hub.tsx): show cost per token pricing + complete model information
* fix(types/utils.py): fix usage object handling
* build(ui/): update ui
* fix: drop unsupported non-whitespace characters for real when calling… (#7484)
* fix: drop unsupported non-whitespace characters for real when calling anthropic with stop sequences
* test: add parameterized test for _map_stop_sequences method in AnthropicConfig
---------
Co-authored-by: Wolfram Ravenwolf <52386626+WolframRavenwolf@users.noreply.github.com>
* fix working build from pip
* add tests for proxy_build_from_pip_tests
* doc clean up for deployment
* docs cleanup
* docs build from pip
* fix cd docker/build_from_pip
