* feat(bedrock/converse/transformation.py): support claude-3-7-sonnet reasoning_Content transformation
Closes https://github.com/BerriAI/litellm/issues/8777
* fix(bedrock/): support returning `reasoning_content` on streaming for claude-3-7
Resolves https://github.com/BerriAI/litellm/issues/8777
* feat(bedrock/): unify converse reasoning content blocks for consistency across anthropic and bedrock
* fix(anthropic/chat/transformation.py): handle deepseek-style 'reasoning_content' extraction within transformation.py
simpler logic
* feat(bedrock/): fix streaming to return blocks in consistent format
* fix: fix linting error
* test: fix test
* feat(factory.py): fix bedrock thinking block translation on tool calling
allows passing the thinking blocks back to bedrock for tool calling
* fix(types/utils.py): don't exclude provider_specific_fields on model dump
ensures consistent responses
* fix: fix linting errors
* fix(convert_dict_to_response.py): pass reasoning_content on root
* fix: test
* fix(streaming_handler.py): add helper util for setting model id
* fix(streaming_handler.py): fix setting model id on model response stream chunk
* fix(streaming_handler.py): fix linting error
* fix(streaming_handler.py): fix linting error
* fix(types/utils.py): add provider_specific_fields to model stream response
* fix(streaming_handler.py): copy provider specific fields and add them to the root of the streaming response
* fix(streaming_handler.py): fix check
* fix: fix test
* fix(types/utils.py): ensure messages content is always openai compatible
* fix(types/utils.py): fix delta object to always be openai compatible
only introduce new params if variable exists
* test: fix bedrock nova tests
* test: skip flaky test
* test: skip flaky test in ci/cd
* fix(o_series_transformation.py): fix optional param check for o-series models
o3-mini and o-1 do not support parallel tool calling
* fix(utils.py): support 'drop_params' for 'thinking' param across models
allows switching to older claude versions (or non-anthropic models) and param to be safely dropped
* fix: fix passing thinking param in optional params
allows dropping thinking_param where not applicable
* test: update old model
* fix(utils.py): fix linting errors
* fix(main.py): add param to acompletion
* fix running litellm on windows
* fix importing litellm
* _init_hypercorn_server
* linting fix
* TestProxyInitializationHelpers
* ci/cd run again
* ci/cd run again
* Adding VertexAI Claude 3.7 Sonnet (#8774)
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
* build(model_prices_and_context_window.json): add anthropic 3-7 models on vertex ai and bedrock
* Support video_url (#8743)
* Support video_url
Support VLMs that works with video.
Example implemenation in vllm: https://github.com/vllm-project/vllm/pull/10020
* llms openai.py: Add ChatCompletionVideoObject
Add data structures to support `video_url` in chat completion
* test test_completion.py: add test for video_url
* Arize Phoenix - ensure correct endpoint/protocol are used; and default to phoenix cloud (#8750)
* minor fixes to default to http and to ensure that the correct endpoint is used
* Update test_arize_phoenix.py
* prioritize http over grpc
---------
Co-authored-by: Emerson Gomes <emerson.gomes@gmail.com>
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
Co-authored-by: Pang Wu <104795337+pang-wu@users.noreply.github.com>
Co-authored-by: Nate Mar <67926244+nate-mar@users.noreply.github.com>
* feat(bedrock/rerank): infer model region if model given as arn
* test: add unit testing to ensure bedrock region name inferred from arn on rerank
* feat(bedrock/rerank/transformation.py): include search units for bedrock rerank result
Resolves https://github.com/BerriAI/litellm/issues/7258#issuecomment-2671557137
* test(test_bedrock_completion.py): add testing for bedrock cohere rerank
* feat(cost_calculator.py): refactor rerank cost tracking to support bedrock cost tracking
* build(model_prices_and_context_window.json): add amazon.rerank model to model cost map
* fix(cost_calculator.py): bedrock/common_utils.py
get base model from model w/ arn -> handles rerank model
* build(model_prices_and_context_window.json): add bedrock cohere rerank pricing
* feat(bedrock/rerank): migrate bedrock config to basererank config
* Revert "feat(bedrock/rerank): migrate bedrock config to basererank config"
This reverts commit 84fae1f167.
* test: add testing to ensure large doc / queries are correctly counted
* Revert "test: add testing to ensure large doc / queries are correctly counted"
This reverts commit 4337f1657e.
* fix(migrate-jina-ai-to-rerank-config): enables cost tracking
* refactor(jina_ai/): finish migrating jina ai to base rerank config
enables cost tracking
* fix(jina_ai/rerank): e2e jina ai rerank cost tracking
* fix: cleanup dead code
* fix: fix python3.8 compatibility error
* test: fix test
* test: add e2e testing for azure ai rerank
* fix: fix linting error
* test: mark cohere as flaky
* feat(create_key_button.tsx): initial commit using openapi.json to ensure all values via api are supported on ui for `/key/generate`
Closes https://github.com/BerriAI/litellm/issues/7763
* style(create_key_button.tsx): put openapi settings inside 'advanced setting' accordion
* fix(check_openapi_schema.tsx): style improvements for advanced settings
* style(create_key_button.tsx): add tooltip explaining what the settings mean
* fix(team_info.tsx): render metadata field on team update
allow updating a team's metadata
* fix(networking.tsx): add 'metadata' field to create team form
* refactor: cleanup dead codeblock
* fix(organization_endpoints.py): fix metadata param support on `/organization/new`
* feat(organization_endpoints.py): support updating metadata for organization on api + ui
* test: mark flaky test
* refactor get model info for team models
* allow adding a model to a team when creating team specific model
* ui update selected Team on Team Dropdown
* test_team_model_association
* testing for team specific models
* test_get_team_specific_model
* test: skip on internal server error
* remove model alias card on teams page
* linting fix _get_team_specific_model
* fix DeploymentTypedDict
* fix linting error
* fix code quality
* fix model info checks
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* fix(team_endpoints.py): cleanup user <-> team association on team delete
Fixes issue where user table still listed team membership post delete
* test(test_team.py): update e2e test - ensure user/team membership is deleted on team delete
* fix(base_invoke_transformation.py): fix deepseek r1 transformation
remove deepseek name from model url
* test(test_completion.py): assert model route not in url
* feat(base_invoke_transformation.py): infer region name from model arn
prevent errors due to different region name in env var vs. model arn, respect if explicitly set in call though
* test: fix test
* test: skip on internal server error
* fix(parallel_request_limiter.py): improve single instance rate limiting by updating in-memory cache instantly
Fixes issue where parallel request limiter had a leak
* fix(parallel_request_limiter.py): fix parallel request limiter to not decrement val on max limit being reached
* test(test_parallel_request_limiter.py): fix test
* test: fix test
* fix(parallel_request_limiter.py): move to using common enum
* test: fix test
* feat(litellm_pre_call_utils.py): support `x-litellm-tags` request header
allow tag based routing + spend tracking via request headers
* docs(request_headers.md): document new `x-litellm-tags` for tag based routing and spend tracking
* docs(tag_routing.md): add to docs
* fix(utils.py): only pass str values for openai metadata param
* fix(utils.py): drop non-str values for metadata param to openai
preview-feature, otel span was being sent in
* ui - use common team dropdown component
* re-use team component
* rename org field on add model
* handle add model submit
* working view model_id and team_id on root models page
* cleaner
* show all fields
* working model info view
* working team info selector
* clean up team id
* new component for model dashboard
* ui show table with dropdown
* make public model names like email
* revert changes to litellm model name
* fix litellm model name
* ui fix public model
* fix mappings
* fix conditional text input
* fix message
* ui fix bulk add models
* _add_team_model_to_db
* move model mgmt helper funcs
* test_add_team_model_to_db
* ui - display model team model name
* fix add model tab
* fix remove redundant info tab on models page
* dont pass model mappings all the way through
* fix jarring model name when adding team models
* fix edit model button
* delete button on model info
* ui fix model dashboard
* fix DeploymentTypedDict
* _is_model_access_group_for_wildcard_route
* test _get_public_model_name
* ui fix viewing public model name
* fix linting error
* fix linting errors
* fix selectedModel logic
* fix(azure/chat/gpt_transformation.py): add 'prediction' as a support azure param
Closes https://github.com/BerriAI/litellm/issues/8500
* build(model_prices_and_context_window.json): add new 'gemini-2.0-pro-exp-02-05' model
* style: cleanup invalid json trailing commma
* feat(utils.py): support passing 'tokenizer_config' to register_prompt_template
enables passing complete tokenizer config of model to litellm
Allows calling deepseek on bedrock with the correct prompt template
* fix(utils.py): fix register_prompt_template for custom model names
* test(test_prompt_factory.py): fix test
* test(test_completion.py): add e2e test for bedrock invoke deepseek ft model
* feat(base_invoke_transformation.py): support hf_model_name param for bedrock invoke calls
enables proxy admin to set base model for ft bedrock deepseek model
* feat(bedrock/invoke): support deepseek_r1 route for bedrock
makes it easy to apply the right chat template to that call
* feat(constants.py): store deepseek r1 chat template - allow user to get correct response from deepseek r1 without extra work
* test(test_completion.py): add e2e mock test for bedrock deepseek
* docs(bedrock.md): document new deepseek_r1 route for bedrock
allows us to use the right config
* fix(exception_mapping_utils.py): catch read operation timeout
* fix(router.py): add more deployment timeout debug information for timeout errors
help understand why some calls in high-traffic don't respect their model-specific timeouts
* test(test_convert_dict_to_response.py): unit test ensuring empty str is not converted to None
Addresses https://github.com/BerriAI/litellm/issues/8507
* fix(convert_dict_to_response.py): handle empty message str - don't return back as 'None'
Fixes https://github.com/BerriAI/litellm/issues/8507
* test(test_completion.py): add e2e test
* fix(client_initialization_utils.py): handle custom llm provider set with valid value not from model name
* fix(handle_jwt.py): handle groups not existing in jwt token
if user not in group, this won't exist
* fix(handle_jwt.py): add new `enforce_team_based_model_access` flag to jwt auth
allows proxy admin to enforce user can only call model if team has access
* feat(navbar.tsx): expose new dropdown in navbar - allow org admin to create teams within org context
* fix(navbar.tsx): remove non-functional cogicon
* fix(proxy/utils.py): include user-org memberships in `/user/info` response
return orgs user is a member of and the user role within org
* feat(organization_endpoints.py): allow internal user to query `/organizations/list` and get all orgs they belong to
enables org admin to select org they belong to, to create teams
* fix(navbar.tsx): show change in ui when org switcher clicked
* feat(page.tsx): update user role based on org they're in
allows org admin to create teams in the org context
* feat(teams.tsx): working e2e flow for allowing org admin to add new teams
* style(navbar.tsx): clarify switching orgs on UI is in BETA
* fix(organization_endpoints.py): handle getting but not setting members
* test: fix test
* fix(client_initialization_utils.py): revert custom llm provider handling fix - causing unintended issues
* docs(token_auth.md): cleanup docs
* fix(parallel_request_limiter.py): add back parallel request information to max parallel request limiter
Resolves https://github.com/BerriAI/litellm/issues/8392
* test: mark flaky test to handle time based tracking issues
* feat(model_management_endpoints.py): expose new patch `/model/{model_id}/update` endpoint
Allows updating specific values of a model in db - makes it easy for admin to know this by calling it a PA
TCH
* feat(edit_model_modal.tsx): allow user to update llm provider + api key on the ui
* fix: fix linting error
* fix(utils.py): handle key error in msg validation
* Support running Aim Guard during LLM call (#7918)
* support running Aim Guard during LLM call
* Rename header
* adjust docs and fix type annotations
* fix(timeout.md): doc fix for openai example on dynamic timeouts
---------
Co-authored-by: Tomer Bin <117278227+hxtomer@users.noreply.github.com>
* initial transform for invoke
* invoke transform_response
* working - able to make request
* working get_complete_url
* working - invoke now runs on llm_http_handler
* fix unused imports
* track litellm overhead ms
* working stream request
* sign_request transform
* sign_request update
* use has_async_custom_stream_wrapper property
* use get_async_custom_stream_wrapper in base llm http handler
* fix make_call in invoke handler
* fix invoke with streaming get_async_custom_stream_wrapper
* working bedrock async streaming with invoke
* fix make call handler for bedrock
* test_all_model_configs
* fix test_bedrock_custom_prompt_template
* sync streaming for bedrock invoke
* fix _add_stream_param_to_request_body
* test_async_text_completion_bedrock
* fix transform_request
* fix get_supported_openai_params
* fix test supports tool choice
* fix test_supports_tool_choice
* add unit test coverage for bedrock invoke transform
* fix location of transformation files
* update import loc
* fix bedrock invoke unit tests
* fix import for max completion tokens
